Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-524197EnglishN2017April11General SciencesAn Overview of Recent Developments of Fuzzy Divergence Measures and their Generalizations English0104Anshu OhlanEnglishAim: The aim of the paper is to present an overview of recent developments in fuzzy divergence measures. Methodology: We analysis some of well-known notions and the concepts associated with fuzzy set theory with an axiomatic definition of fuzzy divergence measure. Results: Fuzzy divergence measures and their generalizations existing in the literature are summarized briefly. Conclusion: The reviewed divergence measures and their generalizations are useful for further development of measures of divergence and appropriate to deal with different areas. EnglishFuzzy Sets, Fuzzy Measure of Information, Fuzzy Divergence MeasuresINTRODUCTION In 1965, as a generalization of classical (crisp) set theory, Zadeh [1] first proposed the concept of fuzzy set theory. It was found to be suitable in dealing with many fields like pattern recognition, image processing, speech recognition, bioinformatics, fuzzy aircraft control, feature selection, decision making, etc. Over the last six decades, the study on fuzzy set (FS) theory and its application to different area has been extended evenly by the researchers. Afterwards, in 1965, Zadeh [2] introduced the notion of fuzzy entropy as a measure of uncertainty. In 1972, De Luca and Termini [3] presented an axiomatic composition of fuzzy entropy corresponding to the probabilistic entropy measure of Shannon [4]. For determining  the difference between the two FSs divergence measure is a significant tool among the most exciting measures in FSs theory. The concept of fuzzy divergence measure is itself one of the generalization of fuzzy information measure. Analogous to Kullback and Leibler [5] measure of divergence, Bhandari and Pal [6] introduced the fuzzy divergence measure. Thereafter literature on fuzzy measures of information, divergence and their generalizations are considerably extended by the different researchers [7-25] in the past decades. Briefly motivated by the study of the literature on measures of fuzzy information and their generalization in the paper Methodology section introduce some well-known concepts, and the notation related to fuzzy set theory, axiomatic definitions of fuzzy information measure, fuzzy divergence measure etc. In the results section, we  provide an overview of recent developments in fuzzy divergence measures and their generalizations. An essential analysis of the existing  measures of divergence is presented in the discussion section. The final section concludes the paper. METHODOLOGY We now introduce some of well-known notions and the concepts associated with fuzzy set theory with an axiomatic definition of fuzzy divergence measure. Zadeh [1] defined a fuzzy set (FS) on a universe of discourse U having the membership function    as follows: The membership value  describes the degree of the belongingness of in X.  When is valued in {0, 1}, it is the characteristic function of a crisp (i.e., non-fuzzy) set. The measure of difference between two fuzzy sets is called the fuzzy divergence measure. Bhandari and Pal [6] initiated the measure of fuzzy divergence corresponding to divergence measure of Kullback and Leibler [5], as satisfying the conditions: is a convex function of Bhandari and Pal [6] also defined the fuzzy symmetric divergence measure: A general study of the axiomatic definition of a divergence measure for fuzzy sets was also presented in Bouchon-Meunier et al. [26]. As a significant content in fuzzy mathematics, the research on divergence measures between fuzzy sets has received more attention. In recent years, some definitions of generalized measures of fuzzy divergence have been proposed. Afterwards, Shang and Jiang [27] provided a modified version of the fuzzy divergence measure of Bhandari and Pal [6] with the novel idea of Lin [28] and defined as Fan and Xie [29] proposed the fuzzy information of discrimination of  against corresponding to the exponential fuzzy entropy of Pal and Pal [30] and is given by Thereafter Couso et al. [31] define that if X is a universe of discourse and F(X) is the set of all fuzzy subsets, a mapping D:F (X) x F (X) is a divergence measure between fuzzy subsets if and only if for each  the following axioms hold: Non-negativity of   is the natural assumption.  Montes et al. [32] studied the special classes of divergence measures and used the link between fuzzy and probabilistic uncertainty. It also studied widely the divergence measure for fuzzy sets as a particular case. Hooda [33] presented a fuzzy divergence measure corresponding to Havada-Charvat [34] measure of divergence which is given by Parkash et al. [35] proposed a fuzzy divergence measure corresponding to Ferreri [36] probabilistic measure of divergence given by   and another one given by Parkash et al. [35]  is Corresponding to Renyi [36] and Sharma and Mittal [37] generalized measure of divergence Bajaj and Hooda [38] provided the generalized fuzzy divergence measure which are given by DISCUSSION Singh and Tomar [39, 40,41,42] have defined and studied some of symmetric and non-symmetric fuzzy divergence measures analogous to probabilistic divergence measures and inequalities among them. Moreover, Singh and Tomar [43,44] presented a number of refinement of inequalities among fuzzy divergence measures. Bhatia and Singh [45] proposed three families of fuzzy divergence. Thereafter, Hooda and Jain [46] presented a generalized fuzzy divergence measure, its ambiguity and information improvement. Further, in the recent years, fuzzy measures of information, divergence and their generalizations are considerably extended by Tomar and Ohlan [17-20 ] and Ohlan and Ohlan [9-16] and Ohlan [7,8, 21-25] and find their applications emerging in various fields like decision making (e.g., multi-criteria decision making, multi-attribute decision making), pattern recognition, medical diagnosis and suitability in linguistic variables.   CONCLUSION In this paper we have presented a review of the fuzzy measures of divergence and their generalizations existing in the literature. It was noted that these measures of fuzzy divergence can be used for further development of generalized fuzzy divergence measures, appropriate to deal with different areas. ACKNOWLEDGEMENT Authors acknowledge the immense help received from the scholars whose article cited and included in references of this manuscript. The authors are also grateful to authors/editors/publishers of all those articles, journals and books from where the literature for this article has been reviewed and discussed. Conflict of interest: Nil Source of Funding: Nil Englishhttp://ijcrr.com/abstract.php?article_id=278http://ijcrr.com/article_html.php?did=278 L.A. Zadeh, Fuzzy sets, Information and Control 8(3) (1965), 338-353. L.A. Zadeh, Probability measures of fuzzy events, Journal of Mathematical Analysis and Applications 23(1968), 421-427. De Luca A. and Termini S.(1972), “A definition of non-probabilistic entropy in the setting of fuzzy set theory”, Information and Control, 20(4), 301-312. Shannon C.E.(1948), “The mathematical theory of communication”, The Bell System Technical Journal, 27(3), 379-423. Kullback S. and Leibler R.A.(1951), “On information and sufficiency”, The Annals of Mathematical Statistics, 22(1), 79-86. Bhandari D. and Pal N.R.(1993), “Some new information measures for fuzzy sets”, Information Sciences, 67(3), 209-228. Ohlan A.(2015),  “A new generalized fuzzy divergence measure and applications,” Fuzzy Information and Engineering, 7(4), 507-523. Ohlan A.(2016), “Intuitionistic fuzzy exponential divergence: application in multi-attribute decision making,” Journal of Intelligent and Fuzzy Systems, 30, 1519-1530. Ohlan A. and Ohlan R.(2016), “Generalizations of Fuzzy Information Measures,”  Switzerland: Springer International Publishing. Ohlan A. and Ohlan R.(2016), “Fundamentals of Fuzzy Information Measures,” in Ohlan A. and Ohlan R., Generalizations of Fuzzy Information Measures, Springer International Publishing Switzerland, 1-22. Ohlan A. and Ohlan R.(2016), “Parametric Generalized R-norm Fuzzy Information and Divergence Measures,” in Ohlan A. and Ohlan R., Generalizations of Fuzzy Information Measures, Springer International Publishing Switzerland, 23-52. Ohlan A. and Ohlan R.(2016), “Parametric Generalized Exponential Fuzzy Divergence Measure and Strategic Decision-Making,” in Ohlan A. and Ohlan R., Generalizations of Fuzzy Information Measures, Springer International Publishing Switzerland, 53-69. Ohlan A. and Ohlan R.(2016), “Sequence and Application of Inequalities Among Fuzzy Mean Difference Divergence Measures in Pattern Recognition” in Ohlan A. and Ohlan R., Generalizations of Fuzzy Information Measures, Springer International Publishing Switzerland, 71-92. Ohlan A. and Ohlan R.(2016), “Applications of Generalized Fuzzy Divergence Measure Multi-criteria Decision Making and Pattern Recognition” in Ohlan A. and Ohlan R., Generalizations of Fuzzy Information Measures, Springer International Publishing Switzerland, 93-105. Ohlan A. and Ohlan R.(2016), “Generalized Hellinger's Divergence Measure and Its Applications” in Ohlan A. and Ohlan R., Generalizations of Fuzzy Information Measures, Springer International Publishing Switzerland, 107-121. Ohlan A. and Ohlan R.(2016), “Intuitionistic  Fuzzy  Exponential  Divergence  and  Multi-attribute Decision-Making”,  in  Ohlan  A.  and  Ohlan  R.,  Generalizations  of  Fuzzy  Information Measures, Springer International Publishing Switzerland, 123-142.    Tomar V.P. and Ohlan A.(2014a), “Two new parametric generalized norm fuzzy information measures”, International Journal of Computer Applications 93(13), 22-27 Tomar V.P. and Ohlan A.(2014b), “Sequence of fuzzy divergence measures and inequalities”, AMO - Advanced Modeling and Optimization, 16(2), 439-452. Tomar V.P. and Ohlan A.(2014c), “Sequence of inequalities among fuzzy mean difference divergence measures and their applications”, SpringerPlus, 3, 623, 1-20. Tomar V.P. and Ohlan A.(2014d), “New parametric generalized exponential fuzzy divergence measure,” Journal of Uncertainty Analysis and Applications, 2(1), 1-14. Ohlan A.(2016a), “Some Recent Developments on Probabilistic Information Measures,” International Journal of Innovative Research in Science, Engineering and Technology, 5(12), 20455-20460. Ohlan A.(2016b), “Overview on Development of Fuzzy Information Measures,” International Journal of All Research Education and Scientific Methods (IJARESM), 4(12), 17-22. Ohlan A.(2016c), “An Overview On Intuitionistic Fuzzy Similarity Measures,” International Journal of Advanced Technology in Engineering and Science, 4(11), 192-198. Ohlan A.(2016d), “Generalized Exponential Fuzzy Information Measures,” International Journal of Advanced Technology in Engineering and Science, 4(12), 392-399. Ohlan A.(2016d), “Similarity Measures on Intuitionistic Fuzzy Sets,” International Journal of Science Technology and Management, 5(12), 463-468. Bouchon-Meunier B., Rifqi M. and Bothorel S.(1996), “Towards general measures of comparison of objects”, Fuzzy Sets and Systems, 84, 143-153. Shang X. and Jiang G.(1997), “A note on fuzzy information measures,” Pattern Recognition Letters, 18(5), 425-432. Lin J.(1991), “Divergence measure based on Shannon entropy,” IEEE Transactions on Information Theory, 37(1), 145-151. Fan J. and Xie W.(1999), “Distance measures and induced fuzzy entropy”, Fuzzy Sets and Systems, 104(2), 305-314. Pal N.R. and Pal S.K.(1989), “Object background segmentation using new definition of entropy”, IEE Proceedings - Computers and Digital Techniques, 136(4), 248-295. Couso I., Janis V. and Montes S.(2000), “Fuzzy divergence measures”, Acta Univ M Belii, 8, 21-26. Montes S., Couso I., Gil P. and Bertoluzza C.(2002), “Divergence measure between fuzzy sets”, International Journal of Approximate Reasoning, 30, 91-105. Hooda D.S.(2004), “On generalized measures of fuzzy entropy”, Mathematica Slovaca, 54, 315-325. Havrada J.H. and Charvat F.(1967), “Quantification methods of classification processes: concept of structural α-entropy”, Kybernetika, 3(1), 30-35. Parkash O., Sharma P.K. and Kumar S.(2006), “Two new measures of fuzzy divergence and their properties”, SQU Journal for Science, 11, 69-77. Ferreri C.(1980), “Hyperentropy and related heterogeneity divergence and information measures”, Statistica, 40(2), 155-168. Renyi A.(1961), “On measures of entropy and information”, In Proceeding of Fourth Berkeley Symposium on Mathematics, Statistics and Probability, 1, 547-561. Bajaj R.K. and Hooda D.S.(2010), “On some new generalized measures of fuzzy information”, World Academy of Science, Engineering and Technology, 62, 747-753. Singh R.P. and Tomar V.P.(2006), “Fuzzy information measures through generating functions”, Proceedings of Information Processing and Management of Uncertainty in Knowledge based System (IPMU), Paris, 21-28. Singh R.P. and Tomar V.P.(2008), “On fuzzy divergence measures and their inequalities”, Proceedings of 10th National Conference of ISITA, 41-43. Singh R.P. and Tomar V.P.(2012), “Generalized symmetric fuzzy divergence measures and their inequalities”, Presented in International Conference on History and Development of Mathematical Sciences and Symposium on Nonlinear Analysis(ICHDMS), Maharshi Dayanand University Rohtak, Haryana. Singh R.P. and Tomar V.P.(2014), “On fuzzy mean divergence measures and their inequalities”, 5th National Conference at MIT, Academy of Engineering, Alandi(D), Pune, Maharashtra. Singh R.P. and Tomar V.P.(2009), “Refinement of inequalities among fuzzy Means difference”, Advances in Fuzzy Mathematics, 4(2), 113-127. Singh R.P. and Tomar V.P.(2010), “Refinement of inequalities among fuzzy divergence measures”, Advances in Applied Research, 2(2), 142-156. Bhatia P.K. and Singh S.(2012), “Three families of generalized fuzzy directed divergence”, AMO-Advanced Modeling and Optimization, 14(3), 599-614. Hooda D.S. and Jain D.(2012), “The generalized fuzzy measures of directed divergence, total ambiguity and information improvement”, Investigations in Mathematical Sciences, 2, 239-260.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-524197EnglishN2017April11General SciencesChanges in Levels of Soil Carbon and Forest Floor Carbon Stocks in the different Temperate Forests of Garhwal Himalaya English0510Ram KrishanEnglish Om Prakash TiwariEnglish Yashwant Singh RanaEnglish Ashish K. MishraEnglish C. M. SharmaEnglishObjectives: Since soil carbon (C) is a principal source of energy for the nutrient-recycling activities of heterotrophic soil organisms, the maintenance of belowground C stocks is vital for sustaining forest productivity. Methods: The present study was conducted in temperate region of the Garhwal Himalaya during the year 2014-2016 to assess the belowground carbon flux in the forest ecosystem. In the study, we studied the component wise belowground carbon flux in trees, soil organic carbon (SOC) and litter carbon of six different forest types for measuring total belowground carbon allocation (TBCA). Results and Conclusion: The total belowground carbon of live trees varies 20.02 to 60.58 MgC/ha, whereas stock root carbon (14.01-38.27 MgC/ha), lateral roots carbon (5.24-17.57 MgC/ha) and fine root carbon (0.67-12.2 MgC/ha) in selected forest types were recorded. The maximum SOC was exhibited by Abies pindrow forest (110.83± 5.04 MgC/ha), followed by Pinus roxburghii forest (108.22±13.03MgC/ha), Quercus floribunda forest (97.37±7.64 MgC/ha), whereas minimum SOC was recorded in Cedrus deodara forest (56.94±5.13 MgC/ha). The maximum value of litter carbon was recorded for Abies pindrow forest (2.94±1.02 MgC/ha), followed by Quercus semecarpifolia forest (2.22±0.33 MgC/ha), Quercus floribunda forest (2.06±0.28 MgC/ha), Cedrus deodara forest (1.86±0.26 MgC/ha), Quercus leucotrichophora forest (1.44±0.27 MgC/ha), Pinus roxburghii forest (0.84±0.10 MgC/ha). Forest ecosystem in Garhwal Himalaya appears to be the most conducive soil–climatic environment for higher accumulation of SOC, thus helping in maintaining the soil quality. The study showed that belowground carbon stocks in Abies pindrow forests seems has maximum in carbon assimilatory capacity, whereas Cedrus deodara forest has minimum BGC stocks. There is a huge potential to increase SOC potential through the soil conservation and hence should be implemented. EnglishSoil organic carbon, Biomass, Garhwal himalaya, Climate changeIntroduction: Carbon sequestration through forestry has immense potential and plays a significant role in solving critical global environmental problems such as atmospheric accumulation of Green House gases (GHG) and climate change. Estimates of existing C stock pools, stored in various forest types can be helpful in making decisions about C management. Forest biomass constitutes the largest terrestrial carbon sink for CO2 removal from the atmosphere through the process of photosynthesis. Forests absorb CO2 from the surrounding atmosphere and store carbon in  their different components like wood, leaves, litter, roots and soil allocating as “carbon sinks” (Haripriya, 2003). The major carbon pools in forest ecosystem are plant biomass (above and below ground), coarse woody debris, litter and soil (Sharma et al., 2016a). In most forested ecosystems, the majority of the carbon is stored below ground as roots and decaying biomass or as dead organic matter (DOM). Forest floor contribute large amounts of organic material to the soil in the form of different components such as leaves, twigs, branches, reproductive parts, fruits, where their decomposition releases different nutrients into the soil (Tandel et al., 2009). However, belowground biomass (stock, lateral and fine roots components of trees) also plays an important role in carbon sequestration. Total Belowground Carbon (TBGC) is a large fraction of gross primary production (more than 30%) (Ryan et al., 1994; Gower et al., 1996). In some ecosystem, amount of TBGC can surpass the values of aboveground net primary production (Law et al., 1999) and provides the principal source of detritus C to mineral soil. Despite the significant role of TBGC in the C budget of terrestrial ecosystems, controls on TBGC are poorly understood. There is a large dissimilarities in the rate and the length of time that forest floor carbon may sequestered in soil that are related to the vegetation productivity, biological and physical conditions in the soil, the past history of soil organic carbon inputs and various disturbances including physical and anthropogenic (Post and Kwon, 2000). Forest ecosystem in Garhwal Himalaya appears to be the most conducive soil–climatic environment for higher accumulation of SOC, thus helping in maintaining the soil quality. It is essential to examine the changes in carbon fluxes derived from land-use change patterns to obtain basic information on the carbon contents associated with the various stocks of the natural forests. In earlier studies from Garhwal Himalaya, various researchers (Chaturvedi et al., 1982; Rawat and Singh, 1988; Adikari et al., 1995) from Kumoun Himalaya and (Sharma et al., 2010; Gairola et al., 2011; Sharma et al., 2016c) from Garhwal Himalaya attempted to predict biomass and carbon stocks. The present paper aimed at the assessment of the forest diversity, componentised contribution of belowground carbon accumulation of tree species, litter fall and soil organic carbon (SOC) stocks of the different forests of Garhwal Himalaya under temperate conditions. Method and methodology: Study area The Uttarakhand state is located in North-West part of the country. Its geographical area is 53,483 km2 which constitutes 1.63% of total area of the country (FSI, 2013). The present study was conducted in temperate region of the Garhwal Himalaya during the year 2014-2016 to assess the belowground carbon flux in the forest ecosystem. The study area is located in Uttarkashi and Tehri district of Garhwal Himalaya along the catchment area of Bhagirathi River (tributary of river Ganga). In this study, general survey of the area was carried out at selected sites of Tehri and Uttarkashi district of Garhwal Himalaya (Figure1). After the reconnaissance survey, we selected following six dominant forest types were named according to the classification given by Champion and Seth (1968) viz, (i) Pinus wallichiana forest (PF) - Pine Forest (9/C1b) (ii) Quercus leucotrichophora forest (QLF) - Ban Oak forest (12/C1a) (iii) Quercus floribunda forest (QFF) - Moru Oak Forest (12/C1b) (iv) Quercus semecarpifolia forest (QSF) - West Himalayan Upper Oak Forest (12/C2b) (v) Cedrus deodara forest (CF) - Dry Deodar Forest (13/C2b) (vi) Abies spectabilis forest (AF) - West Himalayan Sub-alpine Fir Forest (14/C1a) Methodology: To analyse the forest vegetation on different ridge tops, 10 sample plots of 0.1 ha each were laid out in 6 selected ridge tops of each forest types (10 plots × 06 forest types = total 60 sample plots). All individuals ≥ 10 cm diameter at breast height (DBH = 1.37 m from ground) were considered as tree in each sample plot. The DBH and height of all the trees falling within the sample plot were measured by tree Calliper and Ravi multimeter respectively. The tree height on different slope positions was measured following MacDicken et al. (1991). The slope correction was employed for the sample plots which are located on a slope > 10%, so that the adjustment can be made to the plot area at the time of analysis. The slope angle was measured by clinometer. The biomass of the tree species were calculated by regression equations. The tree components (bole, bole bark, branches, twigs, leaves, stump roots, lateral roots, fine roots) were calculated by various equations developed by Rawat and Singh (1988), Garkoti and Singh (1992) and Adhikari et al. (1995). Biomass equations by tree components were developed to relate oven dry weight to tree cbh. The form of the allometric function of the equation was: Ln Y= a + b Ln X Where, Y is weight of tree component in kilograms, and X is tree circumference in centimetres measured at breast height (CBH), a and b is the intercept and slope of the particular tree species respectively. The total Carbon density (TCD) was estimated by the following formula (Sharma et al., 2010): Carbon (C Mg/ha) = Biomass (Mg/ha) ×Carbon % Forest litter was collected by using 1×1m randomly placed quadrat at three places in 0.1ha sample plot. Litter was collected three times in a year consisted of basically fresh and partially decomposed leaves, bark and reproductive parts. Fresh weight was determined in the field. The collected litter was brought to the laboratory and oven dried at 800C up to the constant weights. The biomass hence obtained from the detritus was then multiplied by appropriate carbon fraction according to IPCC (2006) and extrapolated for a hectare. For organic C determination, the soil samples were sieved through a 2 mm sieve and then thoroughly mixed. Modified Walkley and Black’s rapid titration method (Walkley, 1947) was used to estimate the SOC content in the collected soil samples (Mehta et al., 2014). The contents of organic carbon in soil estimated in percentage were then converted to tonnes per hectare using bulk density, depth of soil and area. Results: The mean values of density, species richness and belowground carbon allocation in different forest types are shown in table 1. A total of 27 tree species were occurred in  all six studied forest types, out of which highest 12 species were recorded in QFF and least 8 species were found in CF. The highest stem density was seen AF (778 ± 89.97 trees/ha) followed by QFF and the lowest density seen in pine forest (560 ± 69.93 trees/ha). The different studied forests showed their distribution above 1500m asl. upto 3500 m asl. with QFF have showed narrow distributional range whereas, QLF and QSF distributed over broad elevational range. The  total  live tree carbon stocks in these studied forest types were seen in the range of 163.47 ± 14.08 Mg C ha-1 to 320.3 ± 29.7 Mg C ha-1, Out of which the variation in TBCA seen in the range of 20.02 ± 2.47 to 60.58 ± 5.93 Mg C ha-1. AF had the highest value of carbon stock followed by PF, CF had the lowest TBCA in case of conifer dominated forests. In case of broad-leaved forests, QSF forests has highest carbon stocks value, whereas QFF and QLF had  showed carbon stocks in the range of 49.96 ± 5.8 Mg C ha-1 and  47.07 ± 5.58 Mg C ha-1 respectively. In our study, the component wise distribution of carbon in burial parts of trees shows that stock roots (14.01-38.27 MgC/ha) stores more carbon than other roots followed by lateral roots carbon (5.24-17.57 MgC/ha) and fine root carbon (0.67-12.2 MgC/ha) in selected forest types were recorded.  In different forest types, QLF shows highest value of Stock roots Carbon, AF shows highest value of Lateral roots carbon and QFF shows highest carbon storage in lateral roots system. However, mean value of aboveground biomass and carbon stocks are seen in highest in AF (259.71 ± 23.87 MgC/ha) followed by QFF (215.23 ± 20.58 MgC/ha) and least value in PF (139.11 ± 11.44 MgC/ha). The soil organic carbon (SOC) in different forest types are shown in Table 1. The maximum value of litter carbon was recorded for Abies pindrow forest (2.94±1.02 MgC/ha), followed by Quercus semecarpifolia forest (2.22±0.33 MgC/ha), Quercus floribunda forest (2.06±0.28 MgC/ha), Cedrus deodara forest (1.86±0.26 MgC/ha), Quercus leucotrichophora forest (1.44±0.27 MgC/ha), Pinus roxburghii forest (0.84±0.10 MgC/ha). The maximum SOC was exhibited by Abies pindrow forest (110.83± 5.04 MgC/ha), followed by Pinus roxburghii forest (108.22±13 MgC/ha), Quercus floribunda forest (97.37±7.64 MgC/ha), whereas minimum SOC was recorded in Cedrus deodara forest (56.94±5.13 MgC/ha). The correlation between different carbon components and diversity indices are shown in table 2.  Total basal cover and species richness show negative correlation, however density shows positive correlation with AGC and TCD. The patterns of variations in different forest types across different ecological varibles are presented by mean of PCA diagram (Figure 2). The distance between ecological parameters (blue dots) approximates the dissimilarity of distribution of relative abundance of those species across these forests. The distance between forests (red dots) show which ecological parameter effects the forest composition within the forest and between the forests. Discussion: Along with the climatic variations, lower elevational QLF had comparatively higher number of species than lower number of species was found at higher elevational AF, which implies the climatic adaptation of plant species. There is also seen exponential decline in biomass and carbon increment with increasing DBH as observed in our study is primarily related to the age of trees (Figure 3). Elevation and temperature, rainfall are main physical factors for forest structure and carbon allocation in different in Garhwal Himalaya. Forests in studied area were mature with higher girth values as they were undisturbed. According to Saxena et al. (1979), trees with higher girths indicate the best representation of a species in the particular forest in specific environmental conditions whereas, lower girths either indicate the chance occurrence of the species in that area or show presence of the biotic disturbance in the past. Age-related declines in carbon stocks are widely documented (e.g., Pregitzer and Euskirchen, 2004; Bradford and Kastendick, 2010; D’Amato et al., 2011).             Tree biomass and carbon stocks in forest ecosystems vary with forest type, species composition, stand age, size class of trees, site conditions, rainfall pattern and altitude (Sharma et al., 2016a; 2016b; 2016c; Gairola et al., 2011; Zhao et al., 2014). The values of belowground biomass density in the present study ranged between of 20.02 ± 2.47 to 60.58 ± 5.93 Mg C ha-1. Negi et al. (2003) observed that the conifers have maximum C stored followed by mixed and broad leaved forests. The BGCA values obtained were lowered than Sheikh et al 2012 but followed the values reported by Sharma et al. (2010). These values are higher than earlier reported values from Garhwal Himalaya, comparative values of TBD and TCD from Uttarakhand and other parts of India. Type stratum AF in general exhibited higher values for higher SOC density (110.83± 5.04 MgC/ha) followed by in PF (108.22±13.03 MgC/ha) and lowest value of SOC were calculated in QSF (74.65±6.10 MgC/ha) which may be due to the presence of mature girth classes compared to other type strata and existence of coniferous leaves, which generally decompose slower than leaves of broadleaf species (Mendoza-Vega et al., 2003).  Lower temperatures may be also one of the reasons for highest carbon stocks at higher altitudes Schlesinger (1997). However, Liebens and VanMolle (2003) also reported the soils of coniferous forest might store more SOC per hectare than broadleaf forest soils. Litter fall carbon also shower highest value in AF (2.94 ± 1.02 MgC/ha) and lowest in PF (0.84 ± 0.1 MgC/ha).  Hobbie et al. (2006) also found that litter turnover rate was positively correlated with mean annual soil temperature. The study showed that belowground carbon stocks in Abies pindrow forests seems has maximum in carbon assimilatory capacity, whereas Cedrus deodara forest has minimum BGC stocks. These Forest floor thus play a key role in the global carbon budget in Garhwal Himalaya and can have large impact on carbon release under a climate change scenario (Lal, 2002). These forests have huge potential to increase SOC potential through the soil conservation and hence should be implemented. As the climate change issues became prominent on political and corporate agenda, it is duty of people of India and other countries to start recognizing their responsibility towards taking action against global warming. The prevention of deforestation and promotion of afforestation have often been cited as strategies to slow down global warming and climate change (Bala et al., 2007) and help in increase to sinks  more carbon from their present potential. Agro forestry practices are the agents that can enhance the ability of forest to sink more carbon (Ahmed et al., 2016). Alternate production of energy like Hydro power and solar energy can significantly reduce the pressure on forest in terms of fuel wood removal. Conclusion: The present study showed the AF, CF and oak forests and stored more biomass and carbon stocks than other forests; hence these forests have higher potential C sinks to tone down the global warming consequences as well as meet our future energy demands. Data obtained through regular assessments of these carbon stocks will yield knowledge on the impacts of particular conservation and management regimes on the forest resources that can assist the enhanced carbon management. Optimized forest management with regard to conservation should implement to secure a high productivity of the forest and avoid disturbances as much as possible. Sustainable use of the forest resources will enable us to conserve them for future generation. Acknowledgements: Authors acknowledge the immense help received from the scholars whose articles are cited and included in references of this manuscript. The authors are also grateful to authors / editors / publishers of all those articles, journals and books from where the literature for this article has been reviewed and discussed. Source of Funding: The authors are also thankful to Department of Science and Technology, Government of India, New Delhi, India for providing financial support (Project No. SERB/SR/SO/PS/14/2010) and also one of the author is thankful to University Grant Commission, India for providing fellowship under Rajiv Gandhi National fellowship for SC scheme. Conflict of interest: The authors declare that they have no conflict of interest. Englishhttp://ijcrr.com/abstract.php?article_id=279http://ijcrr.com/article_html.php?did=279Adhikari BS, Rawat YS, Singh SP. Structure and function of high altitude forests in Central Himalaya. II. Nutrient dynamics.  Annals of Botany 1995; 75:249–258. Ahmed A, Kurian J, Raghavan A. Biochar influences on agricultural soils, crop production, and the environment: A review. Environmental Reviews 2016; 24(4):495–502. Bala G, Caldeira K, Wickett M, Phillips TJ, Lobel DB, Delire C, Mirin A. Combined climate and carbon-cycle effects of large scale deforestation. Proceedings of National Academy of Science, USA.  2007; 104:6550–6555 Chaturvedi OP, Singh SP. Total biomass and biomass production of Pinus roxburgii trees growing in all-aged natural forests. Canadian Journal of Forest Research 1982; 12:632–640. FSI. State of Forest Report 2013, Dehradun, India: Forest Survey of India, Ministry of Environment and Forests, Government of India; 2013. p. 209–211 Gairola S, Sharma CM, Ghildiyal SK, Suyal S. Live tree biomass and carbon variation along an altitudinal gradient in moist temperate valley slopes of the Garhwal Himalaya (India).  Current Science 2011; 100(12):1862–1870. Garkoti SC, Singh SP. Biomass, productivity and nutrient cycling in alpine Rhododendron community of Central Himalaya.  Oecologia Montana 1992; 2:21–32. Gower ST, Pongracic S, Landsberg JJ. A global trend in belowground carbon allocation: can we use the relationship at smaller scales? Ecology 1996; 77:1750–1755. Haripriya GS. Carbon budget of the Indian forest ecosystem. Climatic Change 2003; 56 (3):291–319. IPPC. Climate Change 1995 Impacts, adaptations and mitigation of climate: scientific –technical analyses. In contribution of II to the second assessment report of the Intergovernmental Panel on Climate Change. U. K.: Cambridge University Press, Cambridge; 1996. Lal R. The potential of soils of the tropics to sequester carbon and mitigate the greenhouse effect. Advances in Agronomy 2002; 74:155–192. Law BE, Ryan MG, Anthoni PM. Seasonal and annual respiration of a ponderosa pine ecosystem. Global Change Biology 1999; 5:169–82. Liebens J, VanMolle M. Influence of estimation procedure on soil organic carbon stock assessment in Flanders, Belgium. Soil Use and Management 2003; 19(4):364–71. Mehta JP, Shreshthamani, Bhatt VP. Analysis of the physico-chemical properties of the soil and climatic attribute on vegetation in Central Himalaya. Nature and Science 2014; 12(11):46-54. Negi JDS, Chauhan PS, Negi M. Evidences of climate change and its impact on structure and function of forest ecosystems in and around Doon valley. Indian Forester 2003; 129:757–769. Post WM, Kwon KC. Soil carbon sequestration and land-use change: processes and potential. Global Change Biology. 2000; 6:317–327. Pregitzer KS, Euskirchen ES. Carbon cycling and storage in world forests, biome patterns related to forest age. Global Change Biology 2004; 10:2052–2077. Rawat YS, Singh JS. Structure and function of Oak forests in Central Himalaya. I. Dry matter dynamics. Annals of Botany 1988; 62(4):397–411. Ryan MG, Linder S, Vose JM, Hubbard RM. Dark respiration in pines. In: Gholz HL, Linder S, McMurtrie RE, editors. Ecological Bulletins 43, Environmental constraints on the structure and productivity of pine forest ecosystems: a comparative analysis. Uppsala, Sweden: Munksgaard; 1994. p 50–63. Saxena AK, Singh JS. A phytosociological analysis of woody species in forest communities of a part of Kumaun Himalaya. Vegetatio 1982; 5:03–22. Sharma CM, Baduni NP, Gairola S, Ghildiyal SK, Suyal S. Tree diversity and carbon stocks of some major forest types of Garhwal Himalaya, India. Forest Ecology and Management 2010; 260:2170–2179 Sharma CM, Mishra AK, Krishan R, Tiwari OP, Rana YS. Variation in vegetation composition, biomass production, and carbon storage in ridge top forests of high mountains of Garhwal Himalaya. Journal of Sustainable Forestry 2016a; 35 (2):119–132. Sharma CM, Mishra AK, Krishan R, Tiwari OP, Rana YS. Impact of climate on structure and composition of ridge top forests in Garhwal Himalaya. Taiwania 2016b; 61(2):61–69. Sharma CM, Tiwari OP, Rana YS, Krishan R, Mishra AK. Plant diversity, tree regeneration, biomass Production and carbon storage in different Oak forests on ridge tops of Garhwal Himalaya. Journal of Forest and Environmental Science. 2016c; 32(4):329–343. Tandel M B, Kukadia M U, Kulambe B N, Jadeja D B. Influence of tree cover on physical properties of soil. Indian Forester, 2009; 135(3):420–424 Walkley A. A critical examination of a rapid method for determining organic carbon in soils: effect of variations in digestion conditions and inorganic soil constituents. Soil Science 1947; 63:251–264. Zhao J, Kang F, Wang L, Yu X, Zhao W, Song X, Zhang Y, Chen F, Sun Y, He T, Han H. Patterns of biomass and carbon distribution across a chronosequence of Chinese pine Pinus tabulaeformis forests. PLoS One 2014; (4):e94966. Doi:10.1371/journal.pone.0094966.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-524197EnglishN2017April11General SciencesIntegrated Approach Towards Holistic Health: Current Trends and Future Scope English1114Mrunal R. ShenwaiEnglish Kirti N. TareEnglishModern medicine is evidence based system of medicine with its high end investigative tools, surgical procedures and continued research at molecular, genetic and pharmaceutical levels. Ayurveda is an intricate system of healing that originated in India thousands of years ago. It is designed to promote good health and longevity along with the treatment of disease. It would be more apt to call Ayurveda a completely natural way of life. But the fact is, there exists a wide gap between these two health care systems. Modern medicine has no replacement, but traditional healthcare providers still form the basis of rural healthcare in India. This review article stresses the importance and need for integrating modern medicine with the ayurvedic system of medicine. Although it will be a challenging job, but will definitely lead us towards better and holistic health. EnglishModern medicine, Ayurveda, Integrated approach, Holistic healthINTRODUCTION: All of us are aware that the present era is marked by the emergence of many health related challenges like Diabetes Mellitus, Hypertension, AIDS which are occurring like an epidemic throughout the world.1 Modern medicine is trying to the fullest of its strength to cope up with these challenges with the help of new drugs, newer forms of therapy and latest technologies. But the focus of modern medicine is more towards diagnosis, treatment and prevention of complications. Here, we would like to emphasize the role of our traditional healthcare system i.e. “Ayurveda” in expanding the definition of term “Health,” as not a mere ‘absence of disease’ to a ‘state of complete mental and physical wellbeing’. A time has come to build the bridges between traditional and modern healthcare systems through an integrated approach towards holistic health. PERSPECTIVE OF MODERN MEDICINE: Medicine is the applied science or practice of diagnosis, treatment, and prevention of disease. It encompasses a variety of health care practices evolved to maintain and restore health by the prevention and treatment of illness in human beings. Modern medicine applies health science, biomedical research, and medical technology to diagnose and treat injury and disease, typically through medication or surgery.2 Medical science has evolved over decades of experimentation which involved lots of hard work. Modern medicine is mainly evidence based. In contrast with the traditional healthcare provider, an allopathic practitioner is more scientific in approach. Whatever he is trying to cure is either visible under the microscope or can be made visible by biochemical reactions in test tubes. Modern medicine “makes it possible for us to draw precise picture of internal workings of the human body, measure tiny metabolic reactions, exchange organs from one person to another and even grow babies in test tubes”.3 Scientifically if one gets sick, it is because he has come in contact with the microbes present in the environment. The goal of modern medicine is to intervene with effective measures of eliminating the source of disease, thus promoting healing. Modern medicine with its continued on-going research in various fields, has led to remarkable achievements in understanding various disease processes, their causative agents and developing newer drugs and technologies to deal with them. It has successfully reduced the prevalence of infectious diseases and significantly improved the quality of life of patients with chronic ailments. So we cannot think of holistic health without the help of modern medicine.4   But the newly emerging diseases and health problems are still outnumbering the therapeutic efforts. Newer challenges in the form of Diabetes, Hypertension, AIDS, different malignancies, infertility etc. are still a constant cause of worry. E.g. in spite of the billions of dollars spent on cancer research and the availability of the best health care in the world, cancer is one of the leading causes of death in the US and around the world. Lifestyle has been named as one of the major contributors to the incidence of cancer. Although modern science has made some major strides in understanding cancer and its molecular basis, the knowledge about how to prevent or treat cancer is still lagging behind.5,6 Several chemotherapeutic, cytotoxic and immunomodulating agents which are available in Western medicine to treat cancer are enormously expensive and associated with serious side effects and morbidity. Though the biology of cancer is much better understood today still, the search continues for an ideal treatment that has minimal side effects and is cost-effective.7 Similarly, diabetes and hypertension have emerged like an epidemic in last few decades. These are labeled as lifestyle disorders and once you get them you have to live with them. So the question is; are we really heading towards ‘Health’? According to WHO “Health is a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity”.8 So, health can be defined as an outcome of multiple factors operating at various levels. Good health permits the optimal utilization of one’s physical and mental abilities for one’s own good as well as for society.9 But the current trend suggests that we are restricting the use of modern medicine to merely identifying physical problems and their treatment. Failure to diagnose correctly, increased awareness amongst patients about the investigations and treatment options, growing trend of using newer and costlier drugs ignoring their side effects, are all causing a sense of distrust between doctors and patients. Many such patients prefer alternative forms of therapies like Ayurveda. Over a period of years allopathic practitioners have shown a sense of discontent towards traditional healthcare providers. A time has come to fill the gap between these two healthcare systems and for that matter we must try to understand the fundamentals behind Ayurvedic practice. PERSPECTIVE OF AYURVEDIC SYSTEM OF HEALTH: Ayurveda which means, the science of long life, is an intricate system of healing that originated in India thousands of years ago (1500–1000 BC).5,10 It is designed to promote good health and longevity rather than to fight disease and was practiced by physicians and surgeons. The two different textbooks one by ‘‘Charaka’’ is called Charaka Samhita11 which deals with the etiology, symptomatology, pathology, prognosis, and medical management of disease, and the other by ‘‘Sushruta’’ is called Sushruta Samhita12 deals with various surgical instruments and procedures. Ayurveda is not only a science of medicine but it would be more apt to call it a completely natural way of life. This can be evident from the basic concepts of Ayurveda. Concept of complete life: According to Vedas, a human being should strive for four basic instincts in life i.e. Dharma(the code of conduct),  Artha(money, jewellery etc.), Kaama(desires), Moksha(spiritual end). Acquiring these instincts in a fair way means living a complete life. For this a person needs complete wellness which is provided with the help of Ayurveda. The two basic mottos of Ayurveda are: “Swasthasya swaasthyarakshanam” means to maintain the health of a healthy individual and “Aaturasya Vikaar prashamanam” is to cure the disease of a patient. Complete health refers to physical and mental health. Following the daily routine (Dinacharya) as well as seasonal routine (Rutucharya) helps to stay healthy physically. The concept of Sadvritta meaning personal and social code of conduct can help stay healthy mentally as well.   Composition of body from five natural elements: Our body is made up of Panchamahabhutas (five gross elements) viz. Ether/Space (Aakaash), Air (Vaayu), Energy/Fire (Tej), Water (Aapa) and Earth (Prithvi). Earth and Water combines to form Kapha, Fire is Pitta whereas Air and Ether form Vaat, together known as Tridoshas. Similarly the seven types of tissues (Dhatus) and three waste products (Mala) are the result of the combinations of these five elements.  Tridoshas, Dhatus and Mala with their respective properties maintain health and cause illness when get imbalanced. The status of these doshas in the body of father and mother at the time of fertilization determines the body type (Prakruti) of the baby which is unaltered till death. Ayurveda regards every individual as unique so the therapeutic approach is individualistic based on prakruti assessment. The Prakruti is determined on the basis of physical signs like complexion, stature, skin type, eyes color, voice, appetite, endurance, bowel habits, food habits etc. Pathological assessment of the disease comprises of causative factors in the form of food (aahaar) and daily activities (vihaar), the predisposing symptoms, present symptoms, relieving factors, and etiology of the disease. The treatment is advised in the form of medicines, the necessary dietary and lifestyle corrections after a complete Ayurvedic assessment of disease (Ayurved Nidan Paddhati). Recent research has tried to identify the inheritance possibilities of human Prakriti by observing positive correlations between specific alleles and Prakruti sub-types.13, 14 According to Ayurveda, the imbalance in the body metabolism or the digestive fire is the root cause of all the diseases. A detailed guide to maintain this balance is described in Ayurvedic dietetics which can prove a complete solution to present life style diseases like Obesity, Diabetes, Cardiac problems. A review article by Priti Garodia et al suggests the ayurvedic approach to cancer diagnosis and treatment and also attempts to reveal how these approaches can be employed in today’s world.5 DISCUSSION: CURRENT SCENARIO IN INDIA: In India like any other developing country, more than 90% of the population relies on Complementary and Alternative medicine for primary care, particularly Ayurvedic medicine and Yoga.15,16 Ayurveda colleges graduate around 20,000 physicians every year to meet this soaring demand.17 Many of them practice modern medicine as per the needs of the patients although Medical Council of India (MCI) has not included any of the ayurvedic aspects in the MBBS curriculum. This has created a major rift between practitioners of modern and ayurvedic medicines. Recently Government has also allowed ayurvedic physicians to practice modern medicine. This has again created debate and widened the gap between these two healthcare physicians. Keeping apart the ego clashes we cannot deny that physicians practicing traditional systems still form the backbone of rural healthcare in India. Even in urban areas ayurvedic treatments e.g. Panchkarma and various dietary and health care products are gaining popularity. So instead of just debating which healthcare system is better, a time has come to follow an integrative approach for the betterment of our patients. CHALLENGES: To make Ayurvedic key concepts like Prakruti and Panchkarma more scientific and evidence based. 2. Drug trials about the safety and efficacy of ayurvedic drugs. 3. Publication of ayurvedic studies in good quality peer reviewed journals. 4. Collaborative efforts in providing treatment by modern and ayurvedic physicians. We feel that to bridge the gap, the curriculum should be designed in such a way that it will incorporate the key concepts and treatment modalities of traditional system into modern medicine. Such integration is being done by China in an organized way as well as by US to some extent with their traditional systems.4,18 Even in India; such integration has been tried by Banaras Hindu University (BHU) in early 20th century. They have proposed a model where a student will be educated with both modern and Ayurvedic systems of medicine and it will be up to him/her to treat his/her patients depending upon his/her best judgment and nature of the disease.4 But due to lack of Gov. support the process has remained slow and unorganized. Thus on one hand we have modern system of medicine with all the glamour as well as attention from higher authorities but lacking holistic approach and on the other hand our thousands of years old traditional healthcare system having holistic approach but seems to be in a pathetic condition. We feel that this is the right time to build the bridges between these two healthcare systems to achieve the goal of complete health to all and lead globally in medical science. CONCLUSION: Every healthcare system has its own limitations and advantages. There are conditions where one system may work better than the other, depending upon the nature and course of illness. Aggressive efforts are needed by GOVT. bodies, AYUSH and MCI to follow an integrative approach which will be based upon needs assessment. Moreover extensive collaborative research using multispecialty network is also the need of time. Modern medicine with its advanced technology and ancient Ayurveda with its age-old techniques if go hand in hand then the day is no longer when India will become a global leader in complete health solutions. ACKNOWLEDGEMENT: Authors acknowledge the immense help received from the scholars whose articles are cited and included in references of this manuscript. The authors are also grateful to authors / editors / publishers of all those articles, journals and books from where the literature for this article has been reviewed and discussed. SOURCE OF FUNDING: Nil CONFLICT OF INTEREST: Nil Englishhttp://ijcrr.com/abstract.php?article_id=280http://ijcrr.com/article_html.php?did=280 Tabish SA. Is Diabetes Becoming the Biggest Epidemic of the Twenty-first Century? Int J Health Sci (Qassim) 2007;1(2):V–VIII. Medicine [Internet]. Wikipedia. Wikimedia Foundation; 2017 [cited 2017Feb16]. Available from: https://en.wikipedia.org/wiki/Medicine#cite_note-2 Xu H, Chen K-J. Integrating traditional medicine with biomedicine towards a patient-centered healthcare system. Chin J Integr Med. 2011;17(2):83–4. Manoj Kumar, Integrative medicine: India needs integrated efforts. J Res Educ Indian Med 2015; 21(1): 3-5 Garodia P, Ichikawa H, Malani N, Sethi G, Aggarwal B. From Ancient Medicine to Modern Medicine: Ayurvedic Concepts of Health and Their Role in Inflammation and Cancer. J Soc Integr Oncol 2007; 05(01):25. Pal SK. A review on an Ayurvedic approach for cancer treatment developed by Vaidya Balendu Prakash. IJIMS 2014; 1 (6): 1-11. M. P Shafi, M. Thambi “Rhizome Essential Oil Composition of Costus Speciosus and its Antimicrobial Properties” Int. j. pharm. res. allied sci. 2015;4(1):28-32 World Health Organization. Basic documents. 39th ed. Geneva: WHO, 1992. Rastogi S. Ayurveda for comprehensive healthcare. Indian J Med Ethics2009; 6(2):101.  Ayur.com. 2017 [cited 25 March 2017]. Available from: http://ayur.com/about.html Sharma PV. Charaka samhita. Varanasi: Choukhamba Orientalia; 1981. Murthy KRS. Sushruta samhita (700 BC). Varanasi: Choukhamba Orientalia; 2005. Patwardhan B, Joshi K, Chopra A. Classification of Human Population based on HLA gene polymorphism and the concept of Prakriti in Ayurveda. J Altern Complement Med.  2005; 11:349–53. Rastogi S. Building bridges between Ayurveda and modern science. Int J Ayurveda Res 2010 Jan; (1):41. Dr Rajashree R, Dr Jirge VVL, Dr Parineetha B, Dr Goudar S. A Survey Of Attitude Towards Complementary And Alternative Medicine Among First Year Undergraduate Medical Students In Belgaum. Natl J Integr Res Med 2016, 7(1): 83-87. WHO. New alternative medicine guide launched amidst increasing reports of adverse reactions. Bull World Health Org. 2004; 82(8):635-6. Thatte U, Valiathan M. Ayurveda: The time to experiment. Int  Ayurveda Res 2010;1(1):3. National Center for Complementary and Integrative Health (NCCIH) [Internet]. National Institutes of Health (NIH). 2017 [cited 20 February 2017]. Available from: https://www.nih.gov/about-nih/what-we-do/nih-almanac/national-center-complementary-integrative-health-nccih  

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-524197EnglishN2017April11HealthcareA Pilot Study on Vitamin D and Respiratory Diseases in Southern Part of India English1518Vijetha Shenoy BelleEnglish Priyanka DattaEnglish Krishnananda PrabhuEnglish Kriti SinghEnglishBackground: Over the past decade, interest has grown in the role of vitamin D in many nonskeletal medical conditions, such as cancer, diabetes mellitus, and cardiovascular diseases including respiratory infection. Emerging evidence indicates that vitamin D-mediated innate immunity is important in host defenses against respiratory tract pathogens. There are few researches linking vitamin D to various immune-related conditions, including asthma, allergic rhinitis, although the pattern of this relationship is still yet to establish. This study was done to understand the role of vitamin D levels in patients with respiratory tract infection in the southern part of India. Materials and Methods: After obtaining ethical clearance from the institutional ethics committee retrospective study was conducted. A total of 125 Patients with respiratory complaints like bronchial asthma, chronic obstructive pulmonary disease, and allergic rhinitis were included.100 healthy volunteers were included as a control. Total serum vitamin D assay was measured by ECLIA method. Serum IgE levels were measured using COBAS 6001 analyzer. Statistical analysis was done using SPSS 16.0 version. Results: Vitamin D level was highly significantly lower(p EnglishVitamin D, Respiratory tract infections, IgEIntroduction: The sunshine hormone, vitamin D is seco-steroid hormone, produced in the skin by sun exposure under the influence of UVB light. In the liver it is hydroxylated to 25-hydroxy vitamin D [25 (OH) D] by 25- hydroxylase enzyme. In kidney 1, 25-dihydroxyvitamin D, which is the final product, requires the enzyme 1-alpha-hydroxylase, also occurs in extra renal tissues, epithelial cells and immune cells. [1,2]Vitamin D insufficiency is increasingly seen in the general population due to dietary, lifestyle and behavioral changes. The active vitamin D is present only in minute concentrations in the circulation and it is crucial for vitamin D mediated effects on immune system at the site of local activation. The prevalence of vitamin D deficiency has been increasing in the general population in recent decades. Observational studies suggest that vitamin D deficiency increases risk of respiratory infections. Vitamin D was found to be modulating the regulatory T-cell function and interleukin-10 production. [3,4] It has long been thought that by inducing respiratory muscle weakness, vitamin D deficiency gives rise to difficulties in eliminating respiratory secretions and thus facilitates the development of infections. These concepts now need to be integrated with the role of vitamin D in the respiratory system. Children with rickets and asymptomatic vitamin D deficiency were more likely to develop pneumonia, and this was observed in children in India.[5] Respiratory tract infection (RTI) is widespread not only in the pediatric age group but also in adults. It is the major cause of mortality and morbidity. 2.8 million deaths were by RTI during 2010.A link between vitamin D and respiratory tract infection has been hypothesized. Recent evidence suggests that vitamin D causes suppression of inflammation and strengthening of immunity by the induction of antimicrobial peptides. Early studies of vitamin D in mice came to different conclusions, with one group reporting a link and the other no link between deficiency and infection. More recent studies in humans also had divergent results. Evidence indicates that vitamin D-mediated innate immunity is important in host defenses against respiratory tract pathogens. Vitamin D affects B lymphocytes functions and modulates the humoral immune response including secretion of IgE.[6,7] In addition, vitamin D modulates the adaptive immune system via direct effects on T-cell activation and on the phenotype and function of antigen-presenting cells. Cross-sectional data indicate that low vitamin D levels in patients with mild to moderate asthma are correlated with poor asthma control, decreased lung function, decreased glucocorticoid response, more frequent exacerbations, and consequent increased steroid use[8,9]. However, there is insufficient evidence to support a causal association between vitamin D status and asthma. Also, there are very limited data in adult asthma patients addressing the impact of vitamin D status on disease control and severity [10, 11]. Therefore, the aim of this study was to investigate the adult patients with respiratory infections and its potential relationship with vitamin D levels in the southern part of India. Materials and methods: Study subjects: Between March 2013 to July 2013, 125individuals of 30- 65years age group having A total of 125 Patients with respiratory complaints like bronchial asthma, chronic obstructive pulmonary disease, and allergic rhinitis visiting Kasturba Hospital, Manipal University, Manipal, India were enrolled in the study. 100 healthy volunteers were included as a control group. Study groups: Individuals were divided in three groups according to their disease group I = patients with asthma. Group II patients with rhinitis and group III with COPD Exclusion Criteria: Patients suffering from diabetes, mal-absorption, pregnant women, patients of significant cardiac, hepatic, renal, oncologic or psychiatric diseases and those on long term medications were excluded from the study. Ethical statement: Ethics clearance was obtained prior to data collection from the institutional ethics committee Kasturba Hospital, Manipal University, Manipal, India. Sample collection: Using aseptic precautions 4ml of venous blood samples were collected in red capped vaccutainer and were used for estimation of vitamin D. Method of estimation of vitamin D and IgE: Total serum vitamin D assay was measured by Electro Chemi-Luminiscence Immuno Assay (ECLIA) method in Elecsys 2010. Serum IgE levels were measured using COBAS 6001  analyser, Electro Chemi-Luminiscence Immuno Assay (ECLIA).  The instrument is calibrated to provide quantitative values for Serum IgE up to 2500 IU/ml. Statistical analysis: Data was compiled and statistical evaluation was done using Statistical Package for the Social Sciences (SPSS) 16.0. Data were expressed as mean± standard deviation. ANOVA was used for comparison between groups. P value Englishhttp://ijcrr.com/abstract.php?article_id=281http://ijcrr.com/article_html.php?did=281 Holick MF. Vitamin D deficiency. N Engl J Med. 2007;357:266–81. Holick MF, Chen TC. Vitamin D deficiency: a worldwide problem with health consequences. Am J Clin Nutr. 2008;87:1080–6. Black PN, Scragg R. Relationship between serum 25-hydroxyvitamin d and pulmonary function in the third national health and nutrition examinationsurvey. Chest. 2005;128:3792–8.  Searing DA, Leung DY. Vitamin D in atopic dermatitis, asthma and allergic diseases. Immunol Allergy Clin North Am. 2010;30:397–409. Wayse V, Yousafzai A, Mogale K, Filteau S. Association of subclinical vitamin D deficiency with severe acute lower respiratory infection in Indian children under 5 y. Eur J Clin Nutr 2004;58:563–567.  Searing DA, Leung DY. Vitamin D in atopic dermatitis, asthma and allergic diseases. Immunol Allergy Clin North Am. 2010;30:397–409. Sun J. Vitamin D and mucosal immune function. Curr Opin Gastroenterol 2010;26:591–595 Brehm JM, Celedon JC, Soto-Quiros ME, Avila L: Serum vitamin D levels and markers of severity of childhood asthma in Costa Rica. Am J Respir Crit Care Med 2009, 179:765–771. Chinellato I, Piazza M, Sandri M, Peroni D, Piacentini G, Boner AL: Vitamin D serum levels and markers of asthma control in Italian children. J Pediatr 2011, 158:437–441. Sutherland ER, Goleva E, Jackson LP, Stevens AD, Leung DY: Vitamin D levels, lung function, and steroid response in adult asthma. Am J Respir Crit Care Med 2010, 181:699–704.  Li F, Peng M, Jiang L, Sun Q, Zhang K, Lian F: Vitamin D deficiency is associated with decreased lung function in Chinese adults with asthma. Respiration 2011, 81:469–475. . Arshi S, Ghalehbaghi B, Kamrava SK, Aminlou M. Vitamin D serum levels in allergic rhinitis: Any difference from normal population? Asia Pac Allergy 2012;2:45?8 Moradzadeh K, Larijan B, Keshtkar AA, Hossein?Nezhad A, Rajabian R, Nabipour I, et al. Normative values of vitamin D among Iranian population: A population based study. Int J Osteoporos Metab Disord 2008; 1:8?15. Wjst M, Hyppönen E. Vitamin D serum levels and allergic rhinitis. Allergy 2007;62:1085?6. Thirunavukkarasu S, Mysore S, Chickballapur R, Srikantaiah C, Mohan R, Rage E et al. Evaluation of serum immunoglobulin E levels in bronchial asthma. Lung India 2010; 27:138–140. Adams JS, Hewison M. Unexpected actions of vitamin D: new perspectives on the regulation of innate and adaptive immunity. Nat Clin Pract Endocrinol Metab 2008;4:80–90.  Yim S, Dhawan P, Ragunath C, Christakos S, Diamond G. Induction of cathelicidin in normal and CF bronchial epithelial cells by 1,25-dihydroxyvitamin D(3). J Cyst Fibros 2007;6:403–410 Felicia M, Giovanni S, Allan R. Vitamin D insufficiency is associated with asthma severity. Allergy Asthma Immunol Res 2013;5:283–288 Eman Shebl R, SM Shehata, M Elgabry, SAI Ali, Elsaid HH. Vitamin D and phenotypes of bronchial asthma. Egypt J Chest Dis Tuberc 2013;62:201–205. Liu PT, Stenger S, Li H, Wenzel L, Tan BH, Krutzik SR et al . Toll-like receptor triggering of a vitamin D-mediated human antimicrobial response. Science. 2006 Mar 24;311(5768):1770-3  Berry MA, Hargadon B, Shelley M, Parker D et al. Evidence of a role of tumor necrosisfactor alpha in refractory asthma. N Engl J Med 2006, 354:697–708. Mora JR, Iwata M, von Andrian UH: Vitamin effects on the immunesystem: vitamins A and D take centre stage. Nat Rev Immunol 2008,8:685–698. F. Li, M. Peng, L. Jiang, Q. Sun, K. Zhang, F. Lian, et al.Vitamin D deficiency is associated with decreased lung function in Chinese adults with asthma. Respiration 2011, 81(6):  469–475.  S. Sharief, S. Jariwala, J. Kumar, P. Muntner, M.L. Melamed.Vitamin D levels and food and environmental allergies in the United States: results from the National Health and Nutrition Examination Survey 2005–2006 .J Allergy Clin Immunol, 2011;127(5): 1195–1202.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-524197EnglishN2017April11HealthcareA Comparative Study of Carrying Angle with Respect to Sex and Dominant Arm in Eastern Population of Nepal English1922Rakesh Kumar AdhikariEnglish Subodh Kumar YadavEnglish Abhishek KarnEnglishObjective: To find the gender and dominant handedness difference in the carrying angle of adolescent males and females of eastern population of Nepal. Methods: The carrying angle was measured by a goniometer in 100 healthy subjects without any anomaly, pathology or asymmetry in shoulder, elbow or wrist (50 males and 50 females) by extending, supinating and fixing each forearm and placing the fixed arm of the goniometer on the central longitudinal axis of the upper arm and the adjustable arm of the goniometer on the central longitudinal axis of the lower arm. The means were evaluated using the Student t-test where p < 0.05 was considered to be statistically significant. Results: The mean carrying angle of males on the dominant upper limb was 11.72±1.37 and the non-dominant upper limb was 10.02±1.5 and the mean carrying angle of females on the dominant upper limb was 13.7±2.09 and the non-dominant upper limb was 11.74±2.03. The carrying angle was significant greater in females (p < 0.00001) and in the dominant arm in both sexes (p < 0.00001). Conclusions: Our observation of carrying angle can be used to assess traumatic elbow injuries and as an adjunct to identification of skeletal remains in forensic practice in this population. EnglishCarrying angle, Gender, Dominant arm, AdolescentsIntroduction The arm and the forearm are not aligned in humans, which is most obvious when the elbow is straight and the forearm fully supinated. An acute angle at the elbow medially made by the long axis of the humerus and the long axis of the ulna in the anatomic position is recognized as the carrying angle.1 A little degree of cubitus valgus is fashioned by the axis of a radially swerved forearm and the axis of the humerus which assists the arms whilst walking to move to and fro without thumping the hips.2 The normal carrying angle in males is 5°-10° and slightly greater in females being 10°-15°. 3 If this angle is > 15°, it is called cubitus valgus whearas if it is < 5° it is called cubitus varus.3 The angulation is as a consequence of the configuration of the articulating surfaces of the humeral condyles that articulate with the radius and ulna. This angulation vanishes when the forearm is pronated and the elbow is in full extension and when the supinated forearm is flexed alongside the humerus in full elbow flexion.4 The angle differs noticeably between individuals and it is greater in females as compared to males and greater in adults as compared to children. Females have narrower shoulders and wider hips than males which may be a suitable cause for having a more acute carrying angle and is therefore deemed as one of the secondary sexual characters.5-9 Nevertheless, there is a wide overlap in this angle between males and females, and a gender difference has not been steadily scrutinized in scientific studies.2, 10 Therefore, this present study was carried out to estimate the gender dominant handedness difference in the carrying angle of pubescent males and females of eastern population of Nepal. Furthermore, our study might be helpful in monitoring of traumatic elbow injuries which frequently necessitate appraisal of the carrying angle. Additionally, the forensic experts may employ our study to determine the gender of an individual of this area from skeletal remains. Materials and Methods: A total of 200 elbows of 100 healthy young males and females belonging to the age group of 16 to 24 years with normal bony configuration in equal sex ratio were examined at the Department of Human Anatomy of Nobel Medical College Teaching Hospital, which is situated in eastern Nepal. Individuals with shoulder, elbow or wrist pathologies, asymmetry, congenital malformations, history of elbow surgery, and fracture of limbs were excluded from the study. They were placed in anatomical position and the bony landmarks (olecranon process of the ulna, head of the radius, medial and lateral epicondyles of humerus and head of ulna) were acknowledged by means of palpation. Then the carrying angle was measured by a goniometer by extending, supinating and fixing each forearm. The fixed arm of the goniometer was placed on the central longitudinal axis of the upper arm and the adjustable arm of the goniometer was placed on the central longitudinal axis of the lower arm.11 Figure 1 The angle thus measured was noted by two observers to evade interobserver disparity. The carrying angle of dominant and non-dominant hands was recorded separately. Statistical Method: The obtained data were statistically analyzed using the SPSS® for Windows, Version 17.0.  Continuous variables means were evaluated using the Student t-test where p < 0.05 was considered to be significant. Results  The mean carrying angle of males on the dominant upper limb was 11.72±1.37 and the non-dominant upper limb was 10.02±1.5 and the mean carrying angle of females on the dominant upper limb was 13.7±2.09 and the non-dominant upper limb was 11.74±2.03. In this study we observed that there was a significant difference (p< .00001) between the carrying angles of dominant and non-dominant hands in the same gender as well as in the carrying angles of dominant hands in between males and females as shown in the tables below. Table 1 Table 2 Table 3 Figure 2 Discussion In this present study, the mean carrying angle of males on the dominant upper limb was 11.72±1.37 and the mean carrying angle of females on the dominant upper limb was 13.7±2.09. The mean carrying angle of dominant hand in females was more compared to that of males which was found to be statistically significant. The first researcher to carry out a study on variation of carrying angle in between males and females was Potter H.P who observed the carrying angle to be greater in females as compared to males.5 Except few researchers who found no significant difference between the carrying angles of males and females 10-14 most of the study shows that the carrying angle of females was greater than males 2, 5- 9, 16-24 also observed by our study which shows that the carrying angle of dominant hand of females and males differ statistically. We also observed that the mean carrying angle of the dominant hand was more as compared to the non-dominant hand in either sexes (males:11.72±1.32 vs 10.02±1.50; females: 13.7±2.09 vs 11.74±2.03) and this too was statistically significant finding also observed in other studies.21,22,24  This significant difference between the carrying angles of the dominant and non-dominant sides may imply more laxity of the ligament at the medial elbow or bony remodeling to adapt more stress in the dominant hand. However, we did not analyze the influence of variables like height, age and race of the individual, length of the arm, length of the forearm, and width of the hip to the carrying angle. Conclusion Our subjects were adolescents and the carrying angle was significantly more in females as compare to males which may be due to laxity of articular ligaments and a wider pelvis, the outcome of which is a greater tangential divergence of the forearm on the arm. The carrying angle of dominant arm was observed to be greater than the non-dominant arm in both males and females which was statistically significant. This may be because of bony remodeling to adapt more and repeated stress in the dominant arm due to its more frequent use as compared to the non-dominant arm. Our observed values will be important in the management of traumatic elbow injuries and in the diagnosis of diseases of the lateral and medial epicondyles which frequently necessitate appraisal of the carrying angle. Our finding can also be used as an indicator of gender in this population and thus an adjuvant forensic parameter to aid in identification of human remains which is an important part of medicolegal practice. Acknowledgement Authors acknowledge the immense help received from the scholars whose articles are cited and included in references of this manuscript. The authors are also grateful to authors / editors / publishers of all those articles, journals and books from where the literature for this article has been reviewed and discussed. Ethical Clearance Ethical clearance was obtained from the Institutional Review Committee of Nobel Medical College and Teaching Hospital, Biratnagar-5, Morang. Source of Funding None declared. Conflict of interest None declared.     Englishhttp://ijcrr.com/abstract.php?article_id=282http://ijcrr.com/article_html.php?did=282 Williams PL, Bannister LH, Berry MM, Collins P, Dyson M, Dussek JE, Ferguson MW, Greys Anatomy, 38th Ed, Churchill Livingston, London, 1995. pp.642-643. Van RP, Baeyens JP, Fauvart D, Lanssiers R, Clarijs JP. Arthro-kinematics of the elbow: study of the carrying angle. Ergonomics 2005;48:1645–56. David J. Magee, Orthopedic Physical assessment, 6th edition (2014),: 392-393. Norkin, C.C,P.K. Levangie, The elbow complex. In Joint Structure and Function, 4th Ed, F.A. Davis, Philadelphia, 2005. pp.284 Potter HP. The obliquity of the arm of the females in extension. J Anat Physiol 1895;29:488-492.  Atkinson WD. Elftman H. The carrying angle of the human arm as a, secondary sex character. Anat Record 1945;91:49-53. Aebi H, Ellbogenwinkel DER, Geschlecht SB, Hüftbreite KU. Acta Anat 1947;3:228-264. Keats TE, Teeslink R, Diamong AE, Williams JH. Normal axial relationship of the major joints. Radiol 1966;87:904-908. Baugman FA, Higgins JV, Wads¬worth TG, Demaray MJ. The carrying angle in sex chromosome anomalies. JAMA 1974;230:718-720. Zampagni M, Casino D, Zaffagnini S, Visani AA, Marcacci M. Estimating the elbow carrying angle with an electrogoniometer: acquisition of data and reliability of measurements. Orthopedics 2008;31:370. Bari W, Alam M, Omar S. Goniometry of elbow carrying angle: a comparative clinical study on sexual dimorphism in young males and females Int J Res Med Sci. 2015;3(12):3482-3484. Steel FLD, Tomalinson JDW. The carrying angle in man. J Anat. 1958;92:315-317. Smith L. Deformity following supracondylar fractures of the humerus. J Bone joint surg. 1960;42-A:235-238. Maria LZ, Daniela C, Sandra M, Andrea V, Maurilio M. Estimating the elbow carrying angle with an electrogoniometer. J Shoulder elbow surg 2008;17(1):106-112. Zampagni ML, Casino D, Zaffagnini S, Visani AA, Marcacci M. Estimating the elbow carrying angle with an electrogoniometer: acquisition of data and reliability of measurements. Orthopedics. 2008;31(4):370. Purkait R. An Anthropometric investigation to the probable cause of formation carrying angle. A Sex indicator. JIAFM 2004;26:14?20. Balasubramanian P, Madhuri V, Muliyil J. Carrying angle in children: a normative study. J Pediatr Orthop B. 2006;15:37-40. Golden DW, Jhee JT, Gilpin SP, Sawyer JR. Elbow range of motion and clinical carrying angle in a healthy pediatric population. J Pediatr Orthop B. 2007;16:144-149. Tükenmez M, Demirel H, Perçin S, Tezeren G. [Measurement of the carrying angle of the elbow in 2,000 children at ages six and fourteen years]. Acta Orthop Traumatol Turc. 2004;38:274-276. Sharma K, Mansur DI, Khanal K, Haque MK. Variation of carrying angle with age, sex, height and special reference to side. Kathmandu Univ Med J (KUMJ). 2013;11(44):315-8. Paraskevas G, Papadopoulos A, Papaziogas B, Spanidou S, Argiriadou H, Gigis J. Study of the carrying angle of the human elbow joint in full extension: a morphometric analysis. Surg Radiol Anat. 2004;26:19–23. Yilmaz E, Karakurt L, Belhan O, Bulut M, Serin E, Avci M. Variation of carrying angle with age, sex, and special reference to side. Orthopedics. 2005;28(11):1360-1363. Chein-Wei Chang, Yi-Chian Wang, Chang-Hung Chu. Increased Carrying Angle is a Risk Factor for Nontraumatic Ulnar Neuropathy at the Elbow. Clin Orthop Relat Res. 2008; 466(9):2190–2195. Allouh MZ, Abu Ghaida JH, Jarrar AA, Khasawneh RR, Mustafa AG, Bashaireh KM. The carrying angle: racial differences and relevance to inter-epicondylar distance of the humerus. Folia Morphol (Warsz). 2016;75(3):388-392.        

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-524197EnglishN2017April11HealthcareCraniofacial Anthropometric Measurement of Normal Full Term Newborns in Lower Hills of Himachal Pradesh English2327Soni PankajEnglish K. PrabhakaranEnglish Kapoor KanchanEnglishIntroduction: Anthropometric measurements of infant body help us to predict their health and future growth. The objective of this study is to document anthropometric data of normal newborns in Himachal Pradesh. This work will definitely prove a contribution in the anthropometric study as hardly any research work is done on this subject in Himachal Pradesh. Methods: 100 normal full term newborns comprising 50 males 50 females delivered in labor ward of civil hospitals in Himachal Pradesh, measured within12-24 hours after birth. The mean and SD values for different cranio-facial dimensions were obtained by using Digital caliper and non-stretchable measuring tape. Result: All the parameters were significantly (pEnglishAnthropometric, New born, Himachal, Cranio-facial, Correlation, Full termINTRODUCTION All health personnel having responsibility for the care of children should be sufficiently familiar with normal patterns of growth and milestones so that they can recognize overt deviations from the normal range as early as possible, in order for underlying disorders to be identified and given appropriate attention (Alshemeri et al, 2008). The evaluation and measurement of human body dimensions is achieved by physical anthropometry. The human body dimensions are affected by ecological, biological, geographical, racial, gender and age factors (Golalipour et al, 2003). Man has an unending, and perpetual quest to acquire more and more knowledge about him and the nature around him. He endeavour’s to unfold, unravel various areas of human importance and always tries to extend the boundaries of his wisdom and knowledge. The geographical location, racial and environmental factors are responsible for the growth and body composition. As the geographical and environmental conditions of Himachal Pradesh are different from rest of the India In view of this we selected to undertake an anthropometric study of normal newborns in hills of Himachal Pradesh, which is known for its unique and uncanny socio-political and cultural traditions. Its unique composition, location, and character all makes it the bounder land. (Balokhara et al, 2014). The birth size is the result of fetal growth. The fetal growth which commences shortly after conception is largely determined genetically with the modification of this genetic process by the environment. In several studies, researchers have been used anthropometric measurements, such as weight length in order to evaluate growth of infants; some also used the head circumference. (Alshemeri et al, 2008). AIM AND OBJECTIVE Present study was performed with objective to find correlation between craniofacial anthropometric measurements of full term newborns and to conduct normograms for all the anthropometric measurements studied.  This provide base line data for indigenous population and can be gainfully employed for further studies to know whether anthropometric measurements other than birth weight will be useful to quantitate fetal growth and to identify at risk babies in rural community level. This study was also planned to contribute to the collection of newborn standard craniofacial parameters of Himachali. MATERIALS AND METHODS: The study was undertaken on 100 normal full term newborns comprising 50 males and 50 females of lower hills of Himachal Pradesh (Elevation 350-1500 meters from sea level) from the district of Kangra, Una, Hamirpur, Bilaspur, Mandi in the labor ward of civil hospitals as dimension of newborn’s can be basis for all changes in anthropometric indices which will be helpful for anatomists, forensic scientists, plastic surgeons, general surgeon, pediatrics, medical imaging and Physical anthropologists. All the newborns were evaluated in 12- 24 hours after birth. Ethical clearance is taken from Geetanjali University, Udaipur, Rajasthan, (India). Informed consent of mother /father /guardians was taken before measurements.  The anthropometric dimensions do not take into consideration the study of the Neonates of high risk or complicated pregnancies having medical illness such as hypertension, diabetes mellitus, infection, autoimmune disease, heart disease etc., neonate who had caput succedaneum and cephalheamatoma and Neonates delivered by caesarean section showing any craniofacial deformity. Parameters measured and their standard definitions are presented in the following table:1 and Figure:1 Observation and Result: The present study conducted to obtain a baseline standard criterion (Mean±SD) for craniofacial parameters of normal full term newborns of lower Himachal Pradesh and their inter-correlation. Independent sample t test were applied to find significant difference between different parameters among male and female. There is no significant difference in anthropometric measurements of male and female except nasal width which is highly significant (p=0.0042). (Table-2) All the parameters were significantly (pEnglishhttp://ijcrr.com/abstract.php?article_id=283http://ijcrr.com/article_html.php?did=2831. Agnihotri G and Singh D. Craniofacial Anthropometry in Newborns and Infants. Iran J Pediatr. 2007; 17 (4): 332-38. 2. Anupama MP and Dakshayani KR. The Study of Anthropometric Measurements of Newborn Babies in Relation to Maternal Illness. Anatomica Karnataka. 2013; 7(1): 67-71. 3. Anupama M P and Dakshayani K R. The Study of Anthropometricn Measurements of Newborn Babies in Relation to Ges-tational Age. International Journal of Recent Trends in Science and Technology. 2014; 10(1):133-35. 4. Balokhara JM. The Wonderland Himachal Pradesh. 1st ed. India. H.G publication. 2011. 5. Ghosh A, Manjari C and Mahapatra S. The craniofacial anthropometric measurement in a population of normal newborns of Kolkata. Nepal Journal of Medical sciences. 2013; 2(2):125-29. 6. Golalipour MJ, Haidari K, Jahanshahi M and Farahani R.M. The Shapes of Head and Face in Normal Male Newborns In South- East of Caspian Sea (Iran-Gorgan). J Anat. Soc. India. 2003; 52(1): 28-31. 7. Jaya DS, Kumar NS and Bai LS. Anthropometric indices, cord length and placental weight in newborns. Nutrition research centre directorate of health services, thiruvananthapuram. 1995; 32:1183-88. 8. Kataria SK and Gaur S. An Anthropometric Study of Normal Full Term Newborns at Birth in Western Rajasthan. International Journal of Advanced Research. 2014; 2(10): 671-75. 9. Kaur M, Singh Z, Kaur G and Goyal LD. Correlation of birth weight with other anthropometric measurements of newborns. Indian Journal of Basic and Applied Medical Research. 2013; 8(2): 870-79. 10. Mohanta KD, Panda TN and Praharaj KC. Anthropometric measurements of children of Western Orissa. Indian J. Pediat. 1972; 39(1):12-14. 11. Pachauri S and Marwah SM. An anthropometric study of the newborn in Varanasi. The Indian Journal of Pediatrics. 1970; 37(2):47-53. 12. Pachauri S and Marwah SM. An anthropometric study of the newborn in a New Delhi urban community. The Indian Journal of Pediatrics. 1971; 38(7): 291-97. 13. Jreal M. Tourism in Himachal Pradesh. Indus Publication. New Delhi. 2004 14. Taksande AM, Lakhkar B and Gadekar A. Anthropometric measurements of term neonates in tertiary care hospital of Wardha district. Al Ameen J Med Sci. 2015; 8(2):140-43.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-524197EnglishN2017April11HealthcareMicrobiota of Chronic Periodontitis and their Association with Severity of the Disease English2832Mohammad Mukhit KaziEnglish Renu BharadwajEnglishAim: To know the role of these microorganisms as etiological agents in chronic periodontitis and their role in the severity of the disease. Material and Method: A total of 300 patients with chronic periodontitis and 300 age and sex matched controls were enrolled with prior informed consent. Sub gingival plaque specimens was collected and processed for bacterial and yeast etiology. The data was analyzed by using SPSS software and Chi square test with p-value of EnglishChronic periodontitis, Microbiota, Anaerobes, Aerobes, Yeasts, SeverityIntroduction: Chronic periodontitis is the most common oral disease affecting worldwide especially in India which leads to tooth loss if kept untreated for long (1). It is initiated by plaque which consists of bacteria that are responsible for initiation and further progression of the disease(2). Aerobes, anaerobes and possibly yeasts could play a crucial role in the initiation of chronic periodontitis (3). The present study has evaluated the role of microorganisms in chronic periodontitis and in the severity of the disease. Material and Methods: The present study was a prospective case control study. The ethical approval was taken from Ethical Committee (D-1210169-71) and the study period was from June 2011 to December 2014. A total of 300 patients with chronic periodontitis (100 each from mild, moderate and severe) as per classification of American Association of Periodontologist(4) and 300 age and sex matched controls were enrolled with prior informed consent. An inclusion and exclusion criterion was applied before obtaining specimens from patients as well as healthy controls.Subgingival plaque specimen was collected and transferred to brain heart infusion (BHI) broth and Robertson cocker meat (RCM) medium and processed for cultivation of aerobes and anaerobes by standard methods (5). The data was analyzed with the help of SPSS software v17.0 and Chi square test with p-value of 0.05). The overall detection rate of aerobes, anaerobes and yeasts was 47.3, 78.3 and 4.6 % respectively (Table 1). The aerobes were significantly associated with mild while anaerobes were significantly associated with severe chronic periodontitis (Table 2). The common etiological agents include Peptostreptococcus anaerobius (37.3 %), Veillonella parvula (34.3 %), Enterococcus faecalis (33.0 %) and Porphyromonas gingivalis (25 %) (Table 3). Anaerobes (P. gingivalis, B. fragilis, F. nucleatum, V. parvula) were found to be associated significantly with increasing severity of the disease (Table 4). Discussion: In adult patients there is a complex interplay of the mixed polymicrobial infection and host response. The present study has evaluated the role of these microorganisms as etiological agents in chronic periodontitis and their association with severity of the disease.Anaerobic bacteria (78.3 %) were the commonest bacterial pathogen detected from patients with chronic periodontitis (Table 1). Various studies have reported anaerobes in periodontitis with isolation rates ranging from 57.0 % to 93.0 % (6-11). The anaerobic flora plays an important role in the progression of chronic periodontitis. This could be due to the fact that the more the pocket depth and attachment loss an anaerobic environment is created, which is ultimately favorable to the growth of anaerobic pathogens. They establish in the depth of the oral pockets and cause tissue destruction. The anaerobes were significantly associated with the severity (p Englishhttp://ijcrr.com/abstract.php?article_id=284http://ijcrr.com/article_html.php?did=284 Kumar TS, Dagli RJ, Mathur A, Jain M, Balasubramanyam G, Prabhu D, et al. Oral health status and practices of dentate Bhil adult tribes of southern Rajasthan, India. Int Dent J. 2009; 59(3):133-40. Page RC, Schroeder HE. Pathogenesis of inflammatory periodontal disease. A summary of current work. Lab Invest.1976; 34:235–49.  Aas JA, Barbuto SM, Alpagot T, Olsen I, Dewhirst FE, Paster BJ. Subgingival plaque microbiota in HIV positive patients. J Clin Periodontol. 2007; 34 (3): 189-95. The American Academy of Periodontology. Proceedings of the World Workshop in Clinical Periodontics. Chicago. The American Academy of Periodontology. 1989; 1-22. Summanen P, Baron EJ, Citron DM, Strong C, Wexler HM, and Finegold SM. Wadsworth Anaerobic Bacteriology Manual, 5th ed. Star Publishing Co., Belmont, Calif. 1993.  Saini A, Gupta N, Mahajan A, Arora DR. Microbial flora in orodental infections. Indian J of Medical Microbiology. 2003; 21(2):111-4. Mane AK, Karmarkar AP, Bharadwaj RS. Anaerobic Bacteria in Subjects with Chronic Periodontitis and in Periodontal Health. JOHCD. 2009; 3(3):49-51.  Benachinmardi KK, Nagamoti J, Kothiwale S, Metgud SC. Microbial flora in chronic periodontitis: Study at a tertiary health care center from North Karnataka. J Lab Physicians. 2015;7:49-54.  Daniluk T, Tokajuk G, Cylwik-Rokicka D, Rozkiewicz D, Zaremba ML, Stokowska W. Aerobic and anaerobic bacteria in subgingival and supragingival plaques of adult patients with periodontal disease. Advances in Medical Sciences. 2006;51 (supl 1):81-5. Boyanova L, Setchanova L, Gergova G, Kostyanev T, Yordanov D, Popova C, et  al. Microbiological diagnosis of the severe chronic periodontitis. Journal of IMAB – Annual proceedings (Scientific paper) 2009, book 2:89-94. Salari MH, Kadkhoda Z. Rate of cultivable subgingival periodontopathogenic bacteria in chronic periodontitis. Journal of Oral Science. 2004; 46(3):157-61. Edwardsson S, Bing M, Axtelius B, Lindberg B, SoÈderfeldt B, AttstroÈm R. The microbiota of periodontal pockets with different depths in therapy-resistant periodontitis. J Clin Periodontal. 1999; 26 (3): 143-52.  Farias BC, Souza PRE, Ferreira B, Melo RSA, Machado FB, Gusmão ES, et al. Occurrence of periodontal pathogens among patients with chronic periodontitis. Brazilian Journal of Microbiology. 2012; 43(3): 909-16.  Kamma JJ, Nakul M, Mant FA. Predominant microflora of severe, moderate and minimal lesions in young adults with rapidly progressive periodontitis. Periodontol Res. 1995; 30 (1): 66-72.  Younis HM, Al- Jebouri MM. Anaerobic Microbiological study of periodontitis in Salah Al – Deen City.  Tikrit Journal for Dental Sciences. 2016; 4:10-5.  Sixou JL, Magaud C, Jolivet-Gougeon A, Cormier M, Bonnaure-Mallet M. Microbiology of mandibular third molar pericoronitis: Incidence of beta-lactamase-producing bacteria. Oral Surg Oral Med Oral Pathol Oral Radiol Endod. 2003;95 (6):655–9.  Sixou JL, Magaud C, Jolivet-Gougeon A, Cormier M, Bonnaure-Mallet M. Evaluation of the mandibular third molar pericoronitis flora and its susceptibility to different antibiotics prescribed in France. J Clin Microbiol. 2003;41:5794–7.  Koll-Klais P, Mandar R, LeiburE and Mikelsaar M. Oral microbial ecology in chronic periodontitis and periodontal health. Microbial Ecology in Health and Disease. 2005; 17 (3): 146-55. Mane AK,Karmakar AP, Bharadwaj RS, Van Winkelhoff AJ, Loss BG, Van der Reijden WA, et al. Porphyromonas gingivalis, Bacteroids forsythus and other periodontal pathogens in subjects with and without periodontal destruction. J Clin Periodontal. 2002;29 (11):1023. Mashima I, Fujita M, NakatsukaY, Kado T, Furuichi Y, Herastuti S et al. The Distribution and Frequency of Oral Veillonella spp. Associated with Chronic Periodontitis. In J Curr Microbiol App Sci. 2015; 4(3): 150-60. Ardila CM, Granada MI, Guzma´n IC. Antibiotic resistance of subgingival species in chronic periodontitis patients. J Periodontal Res. 2010; 45 (4): 557–63. Rams TR, Degener JE and van Winkelhoff AJ. Antibiotic Resistance in Human Chronic Periodontitis Microbiota. J Periodontol. 2014; 85 (1):160-9. Van Winkelhoff AJ, Loss BG, Van der Reijden WA, Van der Velden U. Porphyromonas gingivalis, Bacteroides forsythus and other periodontal pathogens in subjects with and without periodontal destruction. J Clin Periodontol. 2002; 29 (11):1023-8. Kamma JJ, Nakou M and Manti FA. Predominant microflora of severe, moderate and minimal periodontal lesions in young adults with rapidly progressive periodontitis. Journal of Periodontal Research. 1995;3:66–72. Mombelli A, Gmur R, Frey J, Meyer J, Zee KY, Tam JO, et al. Actinobacillus actinomycetemcomitans and Porphyromonas gingivalis in young Chinese adults. Oral Microbiology and Immunology. 1998;13 (4): 231–7. Parekh M, Pammi V, Vardhana SB, Hinduja DM, Asnani MM, Ahmed A. Isolation and evaluation of microbial flora in patients with chronic periodontitis: A microbiological study. J Int Oral Health. 2016;8(5):619-622. Souto R. and Colombo APV. Prevalence of Enterococcus faecalis in subgingival biofilm and saliva of subjects with chronic periodontal infection. Archives of Oral Biology. 2008; 53 (2):155-60.  Balaei-Gajan E, Shirmohammadi A, Abashov R, Agazadeh M, Faramarzie M. Detection of enterococcus faecalis in subgingival biofilm of patients with chronic refractory periodontitis. Med Oral Patol Oral Cir Bucal. 2010;15 (4):e667-70. Loberto JCS, de Paiva Martins CA, Ferreira dos Santos SS, Cortelli JR. Staphylococcus spp. in the oral cavity and periodontal pockets of chronic periodontitis patients. Brazilian Journal of Microbiology. 2004;35 (1-2):64-68.  Dahlén G, Wikström M. Occurrence of enteric rods, staphylococci and Candida in subgingival samples. Oral Microbiol Immunol. 1995; 10 (1):42-6. Dr. Joshi PS, Dr. Joshi SG, Dr. Gedam R. Isolation of Candida Albicans from Subgingival Plaque in Patients with Chronic Periodontitis- A Microbiological Study. International J of Scientific Research. 2013;2(2):286-70. Jarvensivu A, Hietanen J, Rautemaa R, Sorsa T, Richardson M. Candida yeasts in chronic periodontitis tissues and subgingival microbial biofilms in vivo. Oral Diseases. 2004; 10 (2): 106–12. Arumugam M, Seshan H, Hemanth B. 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Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-524197EnglishN2017April11HealthcareAnthropometric Characteristics and Body Composition of the Rural and Urban Children English3338Kanwar Mandeep SinghEnglish Mandeep SinghEnglish Karanjit SinghEnglishAim: The purpose of the present study was to evaluate the anthropometric characteristics and body composition components of the rural and urban children from Punjab. Methodology: Total 360 children (180 rural and 180 urban) of age between 12 to 18 years were selected to participate in the study. Height of the subjects was measured with the stadiometer. Body mass was assessed by using the portable weighing machine. Widths and diameters of body parts were measured by using digital caliper. Girths and lengths were taken with the flexible steel tape. Skinfold thicknesses were measured with the help of Harpenden skinfold caliper. Results: The results revealed that the rural children were significantly taller (pEnglishAnthropometric Measurements, Rural, Urban, Children, Percent body FatINTRODUCTION Human settlements are categorized as rural or urban areas on the basis of the density of population and human formed structures in a particular area. Urban areas consist of towns and cities while rural areas contain villages and hamlets. Rural areas may develop randomly on the foundation of natural vegetation and fauna available in a region, whereas urban settlements are proper, suitable and planned settlements developed according to a process called urbanization. The urbanization process takes place in various countries under different circumstances in recent times (Valladares and Coelho, 1993). The differences in growth, body dimensions, body composition and fitness levels of children due to urban and rural environmental disparities have come into center of attention during the last few years. Nowadays studies are conducted to examine the evolutionary importance of differences in anthropometric characteristics, body proportions and body composition between populations whose ancestors lived in different environmental settings. Many research studies in the human biological literature investigated the differences in urban and rural populations and in different socio-economic strata with regard to anthropometric characteristics. Height, weight and other body dimensions are differed in rural and urban children and in children from different socio-economic groups in nearly all the developed and in developing countries. Many studies have reported that physical parameters related to growth and development in urban children was at higher level than in rural children (ICMR, 1972; Phadake, 1968; Sahoo et al, 2011). There are several studies from Europe in the past 100 years show that urban children have greater body dimensions and mature earlier compared to children living in rural areas and urban and rural differences are existed among adults in many countries (Bielicki, 1986). The greater anthropometric characteristics among urban children are attributed to advantageous transformations in health and diet and in wide-ranging living circumstances related to urbanization. The differences among urban and rural children are exaggerated by unending dietary problems in the rural areas and noticeable economic disparities in many African, Asian and Latin American countries. In the more developed countries of these continents, the greater anthropometric characteristics and earlier growth and development of children living in urban areas reveal the advantageous outcomes of urbanization related with enhanced economic status and access to facilities (Eveleth and Tanner, 1990). There is little agreement from published comparisons of urban and rural children with regard to anthropometric measurements. A study of children in Crete (Mamalakis et al, 2000) found higher skinfolds among urban children, while higher levels of body fat have been reported in rural Belgian (Guillaume et al, 1997) and North American (McMurray et al, 1999) youth. A Polish study (Wilczewski et al, 1996) reported lower skinfolds in rural boys compared with urban boys but no differences for girls. Booth et al (1999) found no differences between urban and rural children with regard to body mass index and skinfolds in New South Wales. Henneberg and Louw (1998) reported that urban South African children had greater height, weight and skinfold thickness than their rural counterparts. Arm muscle area and waist/hip ratio were higher among rural adolescents compared to urban adolescents in the Cameroon (Dapi et al, 2005). Aberle et al (2009) found no differences in anthropometric characteristics between rural and urban children in Croatia. Greater height and lower body mass index were reported among rural Vietnamese children compared to their urban counterparts (Dang et al, 2010). Mesa et al (1996) reported no significant differences in percent body fat, lean body mass and sum of skinfolds between rural and urban children in central Spain. In a study on Kenyan children, Adamo et al (2010) reported that none of rural children were overweight or obese and they had lower body mass index, waist circumference and triceps skinfold than urban children. Body mass index and skinfolds thickness were higher among urban children in Turkey (Ozdirenc et al, 2005; Tinazci and Emiroglu, 2008; Tinazci Emiroglu, 2009). Urban children in Oman had higher percentage of body fat and body mass index compared to their rural counterparts (Albarwani et al, 2009; Al-Shamli, 2010). Genetic endowments influence the growth and maturation process can better evident under better environmental conditions. In the growth studies, the effects of socioeconomic factors and rural and urban environment are related. In the present study, the attempt has been made to study the differences (if any) in anthropometric characteristics and body composition with regard to place of residence among children from Punjab, India. METHODOLOGY The subjects of the present study were selected from the camps organized under “Catch Them Young Programme” by Department of Physical Education (AT), Guru Nanak Dev University, Amritsar. A total 360 children, aged 12-17 years, from the various districts of Punjab viz. Amritsar, Jalandhar, Tarn-taran, Kapurthala, Nawashehar and Gurdaspur were purposively selected to participate in the study. Out of 360 male children, 180 children were from rural areas and 180 children were belonged to the urban areas. The meaning and definition of rural and urban residence is differing in different studies and countries according to their country norms. An area with a minimum population of 15,000, with 75 percent of the male population is engaged in non-agricultural works is considered as urban area tn the present study. Anthropometry Standing height of the subjects was measured using a Stadiometer, with the subject’s shoes off and head in the Frankfort horizontal plane. Body mass of the subjects was assessed by using the portable weighing machine. Diameters of body parts of the subjects were measured by using digital sliding caliper. Circumferences and length measurements of body parts of the subjects were taken with the flexible steel tape. Skinfold thicknesses of the subjects were measured with the help of Harpenden skinfold caliper. Body Mass Index Body mass index (BMI) was calculated by the following formulae BMI (Kg/m2) = (Body mass in Kg)/(Stature in Meters)2                                                                                                                              (Meltzer et al., 1988) Percent Body Fat        Percentage body fat as estimated from the sum of skinfolds was calculated using equations of Slaughter et al (1988). Percent Body Fat = 1.21(triceps+subscapular)x0.008(triceps+subscapular)x2-1.7 Total Body Fat (kg) = (%body fat/100) ´ body mass (kg) Lean body mass (LBM) was calculated using the % body fat value estimated from the sum of skinfolds. Lean Body Mass (kg) = body mass (kg) – total body fat (kg) Statistical Analysis Statistical analysis was performed using SPSS version 16.0 for windows (SPSS Inc, Chicago, IL, USA). All descriptive data pertaining to anthropometric measurements and body composition variables was reported as mean and standard deviation. An independent sample t-test was used to compare the mean values of anthropometric measurements and body composition variables between rural and urban boys. Significance levels were set at pEnglishhttp://ijcrr.com/abstract.php?article_id=285http://ijcrr.com/article_html.php?did=285 Aberle, N., Blekic, M., Ivanis, A. and Pavlovic, I. (2009). The comparison of anthropometrical parameters of the four-year-old children in the urban and rural Slavonia, Croatia, 1985 and 2005. Collegium Antropologicum, 32(2):447-451. Adak, D.K., Tiwari, M.K., Randhawa, M., Bharati, S. and Bharati, P. (2002). Pattern of adolescent growth among the brahmin girls: rural-urban variation. Collegium Antropologicum, 26(2): 501–507. Adamo, K.B., Sheel. A.W., Onywera, V., Waudo, J.,   Boit, M. and   Tremblay, M.S. (2010). Child obesity and fitness levels among Kenyan and Canadian children from urban and rural environments: A KIDS-CAN Research Alliance Study. International Journal of Pediatric Obesity, 1–8. 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Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-524197EnglishN2017April11HealthcarePrevalence and Risk Factors Associated with Coagulase-Negative Staphylococcus Infections in a Tertiary Care Center in North India English3943Lubna SamadEnglish Dalip K. KakruEnglish Bashir A. FomdaEnglish Shugufta RoohiEnglish Mohd Suhail LoneEnglish Junaid AhmadEnglish Saalim NazkiEnglish Nayeem-u-din WaniEnglishContext: Coagulase negative Staphylococci (CoNS) are Gram positive cocci that are widespread commensals among mammalia. CoNS are more resistant to antimicrobials, including ß-lactam antibiotics, some hospitals revealing oxacillin resistance rates approaching 90%. Aim: Determine the prevalence and antimicrobial susceptibility profile of CoNS in our hospital, and to observe various risk factors responsible for the isolation of clinically significant species. Setting and Design: This prospective study was done in the Department of Microbiology, SKIMS, JandK over a period of 1year Material and Methods: A total of 325 CoNS isolates were obtained from patients of all age groups and both the sexes. Antimicrobial susceptibility testing was done by Kirby-Bauer disc diffusion method. The minimum inhibitory concentration of vancomycin and teicoplanin for CSCoNS, was done by microbroth dilution method. Statistical Analysis: The Chi-square test was used to compare two groups. Results: Out of 325 CoNS recovered, 140 (43.1%) were found to be clinically significant. Maximum CSCoNS were isolated from the age group 0-9 years 27 (19.3%) and blood samples (n=48, 34.3%). Samples from the neonatal intensive care unit yielded the maximum number of CSCoNS, 29 (20.7%). Hospital stay of >1 week, prior use of β-lactam antibiotics and fluoroquinolones and intravenous line catheters were significant risk factors in patients from whom CSCoNS were recovered. Staphylococcus epidermidis was most common isolate. Methicillin resistance was seen in 79 (56.4%) of CSCoNS. Conclusion: The recovery of CoNS should be seriously regarded as they are resistant to multiple antibiotics and their prevalence not only limits the treatment options but also acts as a reservoir of drug-resistant genes. EnglishPrevalence, CSCoNS- clinically significant CoNS, NSCoNS- non significant CoNS, Glycopeptide, Risk factors, MIC-minimum inhibitory concentrationIntroduction Coagulase negative Staphylococci (CoNS) are a heterogenous group of Gram positive cocci that are widespread commensals among mammalia.1 Unlike their coagulase positive counterpart, Staphylococcus aureus, CoNS produce a few virulence patterns and normally refrain from invading tissue.2 Staphylococcal biofilm formation is quite common in CoNS infections and markedly increases the MIC for older antimicrobials.1 Since CoNS are widespread on the human body and are capable of producing very large populations, distinguishing the etiologic agents from contaminating flora is a serious challenge, with the former confirmed only if the same strain is repeatedly isolated from a series of specimens.3 Staphylococcus epidermidis and Staphylococcus saprophyticus are the most frequently isolated clinically significant CoNS (CSCoNS) in clinical laboratories working with specimens of human origin with S. epidermidis alone accounting for 50-80% of the isolates, which are maximally nosocomially acquired.4  S. saprophyticus is a well-documented pathogen, colonizing the rectum or urogenital tracts of approximately 5% to 10% of women5 and is the second most common cause of uncomplicated cystitis in young healthy, sexually active women after Escherchia coli.2 S. haemolyticus has demanded increased interest recently because of the emergence of glycopeptide resistance.4 S. lugdunensis  has been described to cause fulminant native valve endocarditis and prosthetic valve endocarditis.2,6,7 CoNS have historically been more resistant to antimicrobials, including ß-lactam antibiotics, than S. aureus and some hospitals reveal rates of oxacillin resistance in CoNS approaching 90%.1 The purpose of this study was to determine the prevalence and antimicrobial susceptibility profile of  CoNS in our hospital, and to observe various risk factors responsible for the isolation of clinically significant species. Materials and methods A total number of 325 CoNS isolates were obtained from patients of all age groups and both the sexes, who were either admitted at SKIMS or attending its OPD. The clinical samples like blood, sputum, pus and other body fluids, urine, catheter tips received for routine culture and sensitivity between December 2012 to December 2013, were processed as per standard microbiological techniques for the recovery of bacterial pathogens.4, 8 Gram positive cocci that were catalase positive, slide and tube coagulase negative were identified as CoNS4, 8 and taken up for speciation by Vitek 2 compact. In case of urinary isolates from sexually active women, an additional Novobiocin disc susceptibility test was performed.4 CSCoNS,9  based on the repeated isolation from a single patient, clinical condition of the patient and the recovery of Staphylococcus saprophyticus from urine samples of reproductive age group females, were preserved for testing of glycopeptide resistance by microbroth dilution method. Antimicrobial susceptibility testing Antimicrobial susceptibility testing for penicillin, erythromycin, clindamycin, vancomycin, cotrimoxazole, tetracycline, ciprofloxacin, linezolid and nitrofurantoin (in urinary isolates only) was done by Kirby-Bauer disc diffusion method on Mueller Hinton agar plates. Methicillin resistance was screened by cefoxitin discs (30 µg/disc). The results were interpreted as per CLSI guidelines. 10 Minimum inhibitory concentration (MIC) The minimum inhibitory concentration of vancomycin and teicoplanin for CSCoNS, was done by microbroth dilution method. Concentration of vancomycin and teicoplanin used was in the range of 0.125-64 µg/ml. Antimicrobial powders were obtained from HiMedia, Mumbai. MIC endpoint was read as the lowest concentration of the antibiotic at which there was no visible growth. 10 Ethical Clearance The ethical clearance was granted by the Institute’s Ethical Clearance Committee. Statistical analysis Data entry and analysis were done using SPSS Version SPSS 20.0. Percentages were calculated for categorical variables. The Chi-square test was used to compare two groups. Results     A total of 1968 isolates of gram positive bacteria were recovered from patients admitted or attending the OPD at SKIMS, during the study period. Out of these, 325 (16.5%) isolates were found to be CoNS. From the 325 CoNS recovered, 140 (43.1%) isolates of CoNS were included in the present study in view of repeated isolation (two or more cultures) and the clinical condition of the patient thus found to be significant pathogens. Maximum number of CSCoNS were isolated from patients in the age group of 0-9 years, 27 (19.3%) followed by the age group of ≥ 60 years, 24 (17.1%). Table 1 Maximum CSCoNS were isolated from blood, 48 (34.3%) followed by pus, 32 (22.9%); swab, 26 (18.6%); and ascitic fluid, 14 (10%). In addition to these 8 (5.7%) CSCoNS were recovered from catheter tips and from pleural fluid each. Least number of CSCoNS were recovered from urine 4 (2.9%). Samples received from patients in neonatology/NICU, yielded the maximum number of CSCoNS 29 (20.7%) followed by general medicine, 27 (19.3%); general surgery 25 (17.9%); the surgical intensive care unit, 18 (12.9%); urology, 11 (7.9%); medical oncology 8 (5.7%) and endocrinology 8 (5.7%). In addition 5 (3.6%) isolates were recovered form neurosurgery, 4 (2.9%) from cardiology, 3 (2.1%) from gastroenterology and 2 (1.4%) from out-patient department. All CSCoNS isolates were resistant to penicillin, 140 (100%). Methicillin resistance was seen in 79 (56.4%) isolates. Out of the 140 CSCoNS, 102 (72.9%) were resistant to Clindamycin, 121 (86.4%) were resistant to erythromycin and 118 (84.3%) were resistant to cotrimoxazole.  Also 95 (67.9%) CSCoNS isolates were resistant to tetracycline and 126 (90%) were resistant to ciprofloxacin. None of the recovered isolates was resistant to vancomycin. However 4 (2.86), of the isolates of CSCoNS recovered were resistant to linezolid.  Of all 4 CSCoNS recovered from urine, all (100%) were found to be resistant to nitrofurantoin. Majority of the patients from whom CSCoNS were isolated had septicemia, 98 (70%); followed by abscesses, 21 (15%) with the most common species isolated being S. epidermidis, 67 (47.9%). 109 (77.9%) patients from whom CSCoNS were recovered had the presence of intravenous line catheters, whereas only 63 (34.1%) from whom NSCoNS (non significant CoNS) were recovered had IV line catheters, (p < 0.001); table 2. In addition, 86 (61.4%) patients with CSCoNS recovered had prolonged hospital stay (>1 week). (p < 0.001) Table 2 106 (75.7%) and 119 (85%) patients from whom CSCoNS were isolated had history of prior use of β-lactam antibiotics, and fluoroquinolones respectively. Table 3 MIC by microbroth dilution for vancomycin and teicoplanin was done on all the 140 CSCoNS isolates, which was found to be within the susceptible range for all of them. Discussion CoNS, because of their prevalence on human skin, mucous membranes and their relatively low virulence, have in the past been regarded as culture contaminants; however, in recent years, seen to be assuming greater importance as true pathogens.11,12 CoNS is the most commonly encountered organism in catheter-related bloodstream infections (CRBSIs), causing between 11%- 45% of infections with an incidence of 15.8 per 10,000 hospital admissions.13 In addition, a large proportion of nosocomial isolates of CoNS are resistant to multiple antibiotics, including penicillinase -resistant penicillins.11 At present, glycopeptides are among the last available antibiotics, for treating multidrug-resistant, gram-positive nosocomial infections, which are mostly caused by methicillin-resistant staphylococci and enterococci.14, 15 The prevalence of CoNS in our study was found to be 16.5% (325/1968), which is lower than reported in some studies such as Khadri H et al.16 (30.2% ) and Al-Mazroea AH et al. 17 (44.8%). Mir BA et al.18 from his study reported a CoNS prevalence of 14.3% from their hospital. 19.3% of CSCoNS were isolated from patients in the age group of 0-9 years, followed by the age group of ≥60 years (17.1%). Cercenado E et al.11 ,found that 38.5% of CSCoNS were from age-group of ≥60 years and 50-59 years each followed by 0-9 year age group (23.07%). This is consistent with our study as the most of the patients in these age groups are vulnerable to many infections especially when admitted in acute care settings such as the ICU’s of the hospital. Amita J et al. 19 reported  CoNS to be the most common organisms associated with neonatal late-onset septicemia (>50%).  In this study, an increased rate of isolation of CoNS was seen in 0-9 year age group, most of the patients being admitted in ICU’s for long periods. Placement of intravenous lines and the administration of high end antibiotics like third generation cephalosporins and carbapenems and prolonged ICU stay could have been instrumental in infections (due to CoNS) in these patients. A significantly higher isolation of CSCoNS from blood (34.3%) was seen as majority of the patients had sepsis with bacteremia. Similar results were reported by Sharma V et al.20 and Begum SE et al.21 who in their studies isolated maximum number of CoNS from blood (46.33%, 48.6%, respectively). Also 4 (2.9%) S. saprophyticus were isolated from urine. All the 4 isolates belonged to women in the age group of 30-39 years. Two of the four females were pregnant (1st trimester) and had urinary tract infection. The other two had pyuria. Most of our CSCoNS were isolated from patients housed in high dependency areas; the neonatology/NICU (20.7%) of our hospital followed by the SICCU (12.9%). Tacconelli E et al.14 in their study found that admission to any ICU predisposes to infection with CoNS. Similarly Cimiotti JP et al.22 reported an increase in the rate of CoNS infection in NICU (34%) from their hospital. Penicillin resistance was demonstrated in 100% of the CSCoNS with 56.4% of the isolates being methicillin resistant. A resistance of 72.9% was seen to clindamycin, 86.4% to erythromycin and 84.3% to cotrimoxazole.  67.9% and 90% of the CSCoNS were resistant to tetracycline and ciprofloxacin respectively. None of the recovered isolates was resistant to vancomycin. However 2.86% of the isolates recovered were resistant to linezolid.  Out of the 4 isolates of CSCoNS recovered from urine, all (100%) were found to be resistant to nitrofurantoin. Similar results were seen by Al Mazroea et al.17 where the authors reported 99.24% resistance to penicillin in CoNS, followed by high resistance to erythromycin, cotrimoxazole and clindamycin. In agreement with our study, they found 100% vancomycin sensitivity in all CoNS isolates. Asangi SY et al.23 demonstrated a resistance of 16.7% to linezolid in their study. Antibiotic resistant CoNS has emerged as a major cause of morbidity and mortality in hospital setting in the last decade.24 The presence of intravenous line catheters was seen significantly higher in patients from whom CSCoNS were recovered (77.9%). In a study done among CRBSIs by Worthington T et al.,25 the authors found that 96% of the causative agents were CoNS. Our results are concordant with Al Mazroea AH et al.17 who documented that the prolonged use of intravascular catheters, in adult or neonatal ICUs predispose to bloodstream infection. In addition 61.4% of the patients from whom CSCoNS were recovered had prolonged hospital stay (>1 week) than those with NSCoNS (p < 0.001). These results are in agreement with many other studies conducted worldwide. 14, 17 Prior use of β-lactam antibiotics (75.7%) and fluoroquinolones (85%) was significantly higher in patients from whom CSCoNS were isolated. Tacconelli E et al.14 reported that patients with methicillin resistant CoNS (MRCoNS) bacteremia experienced significantly higher exposure to β-lactam antibiotics and cephalosporins. Mir BA et al.,18 reported that after exposure to multiple antibiotics due to their indiscriminate use, patients become colonized with multi-drug resistant CoNS strains which predisposes to infection. Majority of CSCoNS were isolated from patients who had septicemia (70%). CoNS have been implicated as a significant cause of late-onset neonatal septicaemia as stated by Cimiotti JP et al.22 This study identified a total of 10 species of CoNS, with Staphylococcus epidermidis (47.9%) being isolated as the most common species followed by Staphylococcus haemolyticus, 28.6%. In a study by De Paulis A et al.26 ,the authors revealed 51 % strains to be S. epidermidis, followed by S. haemolyticus (18%) and S. saprophyticus (16%). Many other studies have reported Staphylococcus epidermidis to be the most  common species of CoNS isolated.18, 20, 23, 27 MIC was done by microbroth method for vancomycin and teicoplanin on all the 140 CSCoNS isolates. However none of the isolates was found to be resistant to any of these antibiotics. The MIC for teicoplanin was slightly higher in our isolates as compared to vancomycin. In a study conducted by Center KJ et al.28 antimicrobial susceptibility testing of CoNS by microbroth dilution method revealed that 50 and 90% of the isolates were inhibited at a concentration of 1 and 2 µg/ml, respectively for vancomycin with the risk factors associated with higher vancomycin MIC being male gender, presence of a central venous catheter, prior exposure to any antibiotic including vancomycin and prolonged ICU stay. Conclusion Isolation of CoNS and their antibiotic susceptibility pattern should be regarded with all seriousness in clinical practice and clinical epidemiology because these are often missed as true sources of infection and their significance needs to be proved by repeated isolation from the samples. By being resistant to multiple antibiotics, (MRCoNS in particular), their prevalence in the hospitals not only limits the treatment options but also acts as a reservoir of drug-resistant genes. Acknowledgement Authors acknowledge the immense help received from the scholars whose articles are cited and included in references of this manuscript. The authors are also grateful to authors / editors / publishers of all those articles, journals and books from where the literature for this article has been reviewed and discussed. Source of funding:   None Conflict of interest:  None   Englishhttp://ijcrr.com/abstract.php?article_id=286http://ijcrr.com/article_html.php?did=286 John JF, Harvin AM. History and evolution of antibiotic resistance in coagulase-negative staphylococci: Susceptibility profiles of new anti-staphylococcal agents. Therapeutic and  Clinical  Risk Management. 2007; 3: 1143-52. Mandell GL, Bennett JE, Dolin R. Staphylococcus epidermidis and other coagulase-negative staphylococci. In: Principles and Practice of Infectious Diseases. 7th edn. Churchill Livingstone Elsevier; 2010: p. 2579-86. Sharma P, Lahiri KK, Kapila K. Conventional and molecular characterization of coagulase-negative staphylococcus in hospital isolates. IJPM; 54: 85-9. Koneman EW, Allen SD, Janda WM, Schreckenberger PC, Winn WC jr. Gram-positive cocci Part I: Staphylococci and related gram-positive cocci. In: Color Atlas and Textbook of Diagnostic Microbiology. 6th edn. Lippincott Williams and Wilkins. 2006; p. 624-651. Rupp ME, Soper DE, Archer GL. Colonization of the female genital tract with Staphylococcus saprophyticus. J Clin Microbiol. 1992; 30: 2975-9. Herchline TE, Ayers LW. Occurrence of Staphylococcus lugdunensis in consecutive clinical cultures and relationship of isolation to infection. J Clin Microbiol. 1991; 29: 419-21. Sharma P, Lahiri KK, Kapila K. Conventional and molecular characterization of coagulase-negative staphylococcus in hospital isolates. IJPM; 54: 85-9. Cunha MLRS, Sinzato YK, Silveira LVA. Comparison of methods for the identification of coagulase-negative staphylococci. Mem Inst Oswaldo Cruz. 2004; 99: 855-60. Horan TC, Andrus M, Dudeck. CDC/NHSN surveillance definition of health-care associated infection and criteria for specific types of infections in the acute care setting. Am J Infect Control. 2008; 36: 309-32. CLSI. Performance Standards for Antimicrobial Susceptibility Testing; Twenty-Third Informational Supplement. CLSI document M100-S23. Wayne, PA: Clinical and Laboratory Standards Institute; 2013. Cercenado E, Garcia-Leoni ME, Diaz MD, Sanchez-Carrillo C, Catalan P, Bernaldo JCL. Emergence of teicoplanin-resistant coagulase negative staphylococci. J Clin Microbiol. 1996; 34: 1765-8. Pfaller MA, Herwaldt LA. Laboratory, clinical, and epidemiological aspects of coagulase-negaive staphylococci. Clin Microbiol Rev. 1988; 1: 281-99. Rewa O, Muscedere J, Reynolds S, Jiang X, Heyland DK. Coagulase-negative Staphylococcus, catheter-related, bloodstream infections and their association with acute phase markers of inflammation in the intensive care unit: An observational study. Can J Infect Dis Med Microbiol. 2012; 23: 204-8. Tacconelli E, Tumbarello M, Donati KG, Bettio M, Spanu T, Leone F, Glycopeptide resistance among coagulase-negative staphylococci that cause bacteremia, Epidemiological and clinical findings from a case-control study. Clin Infect Dis. 2001 Nov 15; 33: 1628. Sieradzki K, Villari P, Tomasz A. Decreased susceptibilities to teicoplanin and vancomycin among coagulase-negative methicillin-resistant clinical isolates of staphylococci. Antimicrob. Agents Chemother. 1998; 42: 100–07. Khadri H, Alzohairy M. Prevalence and antibiotic susceptibility pattern of methicillin-resistant and coagulase-negative staphylococci in a tertiary care hospital in India. Int J Med Med Sci. 2010; 2: 116-20. Al-Mazroea AH. Incidence and clinical significance of coagulase negative staphylococci in blood. J T U Med Sci. 2009; 4: 137-47. Mir BA, Srikanth D. Prevalence and antimicrobial susceptibility of methicillin resistant Staphyloccus aureus and coagulase-negative staphylococci in a tertiary care hospital. Asian J Pharm Clin Res. 2013; 6: 231-34. Amita J, Agarwal J, Bansal S. Prevalence of methicillin-resistant, coagulase-negative staphylococci in neonatal intensive care units: findings from a tertiary care hospital in India. J Med Microbiol. 2004; 53: 941-44. Sharma V, Jindal N, Devi P. Prevalence of methicillin resistant coagulase negative staphylococci in a tertiary care hospital. Iran  J Microbiol. 2010; 2: 185-88. Begum ES, Dr. Anbumani N, Dr. Kalyani J, Dr. Mallika M. Prevalence and antimicrobial susceptibility pattern of coagulase-negative staphylococcus. Int J Med Public health. 2011; 1: 59-62. Cimiotti JP, Haas JP, Latta PD, Wu F, Salman L, Larson EL. Prevalence and clinical relevance of Staphylococcus warneri in neonatal intensive care unit. Infection Control Hosp Epidemiol. 2007; 28: 326-30. Asangi SY, Mariraj J, Satyanarayan MS, Nagabhushan, Rashmi. Speciation of clinically significant coagulase negative staphylococci and their antibiotic resistant patterns in a tertiary care hospital. Int J Biol Med Res. 2011; 2: 735-9. Mohan V, Jindal N, Aggarwal P. Species distribution and antibiotic sensitivity pattern of coagulase negative staphylococci isolated from various clinical specimens. Ind J Med Microbiol. 2002; 20: 45-46. Worthington T, Lambert PA, Elliot TS. Is hospital-acquired intravascular catheter-related sepsis associated with outbreak strains of coagulase negative staphylococci. J Hos Infect. 2000; 46: 130-34. De Paulis A, Predari S, Chazarreta C, Santoiani J. Five-test simple scheme for species level identification of clinically significant coagulase negative staphylococci. J Clin Microbiol. 2003; 41: 1219-24. Oliveira AD, Sanches P, Lyra JC, Bentlin MR, Rugolo LMSS, Cunha MLRS. Clinical Medicine Insights: Pediatrics. 2012; 6:1-9. Center KJ, Reboli AC, Hubler R, Rodgers GL, Long SL. Decreased vancomycin susceptibility of coagulase-negative staphylococci in a neonatal intensive care unit, evidence of spread of Staphylococcus warneri. J Clin Microbiol. 2003; 41: 4660-5.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-524197EnglishN2017April11HealthcareOccupational Exposure and Needlestick Injuries among Employees of a Tertiary Care Institute in Kashmir English4448Anjum B. FaziliEnglish Rohul J. ShahEnglish Qazi M. IqbalEnglish Feroz A. WaniEnglish Beenish M.EnglishBackground: Needlestick injuries are one of the important occupational hazards of health care workers which pose serious health consequences. The present study examines the prevalence of NSIs among the employees of a tertiary care institute. Methods: This cross-sectional study was carried out for a period of six months at Sher-i-Kashmir Institute of Medical Sciences, Soura. All categories of the workforce participated in the study. Results: Out of a total of 2763 employees studied the prevalence of NSIs was 39.19% NSIs were more common in males, doctors, nursing staff and employees belonging to high risk group and the differences were statistically significant. Conclusion: NSIs are a common public health problem in this tertiary care institute. Proper awareness with regard to adoption of standard precautions coupled with proper working conditions will help in ensuring control of potential blood borne infections due to occupational exposure in this tertiary care institute. EnglishNeedlestick injury, Occupational exposure, High risk, Blood and body fluidINTRODUCTION: Health care workers have increased risk of occupational exposure to blood and other body fluids. Needle stick injuries (NSIs) are major cause of blood borne infections transmitted among health care personnel. These preventable injuries expose workers to over different blood borne pathogens[1] and the most common being Hepatitis B, Hepatitis C and HIV.[2] Most exposures among HCWs are caused by percutaneous injuries with sharp objects contaminated with blood or body fluids which include needles, scalpels, lancets and broken glass. NSIs are therefore one of the potential occupational hazards for HCWs. Transmission of at least twenty different pathogens by injuries due to sharps instruments and needlesticks has been reported in the literature.[3,4] Globally, more than 35 million HCWs face the risk of sustaining a percutaneous injury with a contaminated object every year.[5] American health workers suffer 800,000 to 1 million NSIs annually excluding those that go unreported.[4,6,7] More than 100,000NSIs occur in UK hospitals each year.[7,8] In India, it is not known exactly how many occupation related injuries occur each year, and as data are scarce, it is not possible to estimate an annual incidence[9,10]. An HCWs chance of contracting HIV after an HIV infected accidental NSI is 1 in 250, while the chance of contracting HBV after an accidental NSI is 1 in 20while the chances of contracting HCV after exposure to an HCV contaminated needle stick is 3.5 in 100[11] Although lower transmission rate is found for HIV Englishhttp://ijcrr.com/abstract.php?article_id=287http://ijcrr.com/article_html.php?did=287 Elizabeth A, Bolyard R, Ofelia CT, Walter WW, Pearson ML, Craig N, et al. Guideline for infection control in health care personnel, 1998. Am J Infect Control. 1998;26(3):289–327. Hughes S. Annual Number of Occupational Percutaneous Injuries and Mucocutaneous Exposures to Blood or Potentially Infective Biological Substances. International Healthcare Worker Safety Center, University of Virginia. 1998 [cited 2013 Sep 7]. Available from: http://www.healthsystem.virginia.edu/pub/epinet/estimates.html Saleem T, Khalid U, Ishaque S, Zafar A. Knowledge, attitudes and practices of medical students regarding needle stick injuries. J Pak Med Assoc 2010;60:151?6. World Health Organization ICN on Preventing Needlestick Injuries. Facts and Issues. 2000. Wicker S, Jung J, Allwinn R, Gottschalk R, Rabenau HF. Prevalence and prevention of needlestick injuries among health care workers in a German University Hospital. Int Arch Occup Environ Health 2008;81:347?54 Hanafi MI, Mohamed AM, Kassem MS, Shawki M. Needlestick injuries among health care workers of University of Alexandria Hospitals. East Mediterr Health J 2011;17:26?35. Mokuolu OA. Needlestick Injuries in Nigerian Health Workers. Available from: http://www.thefreelibrary.com/Needle+stick+injuries+in+Nigeria+Health+Care+Worker. [Last accessed on 2015 Dec 27]. Adams D, Elliot TS. A comparative user evaluation of three needle protective devices. Br J Nurs 2003;12:470-4. Jayanth ST, Kirupakaran H, Brahmadatan KN, Gnanaraj L, Kang G. Needle stick injuries in a tertiary care hospital. Indian J Med Microbiol 2009; 27 : 44-7. Rele M, Mathur M, Turbadkar D. Risk of needle stick injuries in health care workers – a report. Indian J Med Microbiol 2002; 20: 206-7. Jahan S. Epidemiology of needlestick injuries among health care workers ina secondary care hospital in Saudi Arabia. Ann Saudi Med 2005;25:233-8. European Centre for Disease Prevention and Control. Rapid risk assessment of Ebola in West Africa. Stockholm. 2014. Available from: http: //www.ecdc.europa [Last accessed on 2014 Sep 15]. Asuzu MC, Adebiyi AO. Prevention of nosocomial outbreaks of Lassafever. Arch Ib Med 2007;9:42?5. Amini M, Behzadnia MJ, Saboori F, Bahadori MK, Ravangard R. Needle stick injuries among health care works in a Teaching Hospital. Trauma Monthly. 2015 Nov;20(4). Holla R, Unikrishnan B, Ram P, Thapar R, Mithra P, Kumar N et al. Occupational exposure to needle stick injuries among health care personnel in a tertiary care hospital: A cross sectional study. J. Community Med Health Education S2:004.doi:10.4172/2161-0711,S2-004. Jaybhaye D, Dahire P, Nagoankar A, Vedpathak V, Deo D, Kawalkar U. Needle stick injuries among health care workers in a tertiary care hospital in rural India. Int.journal of medical Science and Public Health.2014; 3 (1):49-52. Chen L, Zhang M, YanY, MiaoJ, Lin H, ZhangY, et al. Sharp object injuries among health care workers in a Chinese Province. AAOHN J.2009;57(1):13-16. Honda M, Chompikul J, Rattanapan C, Wood G, Klungboonkrong S. Sharps injuries among nurses in a Thai regional hospital: Prevalence and risk factors. Int J  Occup. Environ Med. 2011;2(4):215-23. Cleveland JL, Barker LK, Cuney EJ, Panlilio AL. National Surveillance System for health Care Workers. Preventing percutaneous injuries among dental health care personnel. J Am Dent Assoc.2007;138(2):169-78. Salelkar S, Motghare DD, Kulkarni MS, Vaz FS. Study of needle stick injuries among health care workers at a tertiary care hospital. Indian Journal of Public Health.2010;54(1):18-20. Sharma R, Rasania SK, Verma A and Singh S. Study of prevalence and response to needlestick injuries among health care workers in a tertiary care hospital in Delhi, India. Indian J Community Med 2010;35(1):74-77. Muralidhar S, Singh PK, Jain RK, Malhotra M and Bala M. Needle stick injuries among health care workers in a tertiary care hospital of India. Indian J Med Res 131, March 2010:405-410. Evans B, Duggan W, Baker J, Ramsay M, Abiteboul D. Exposure of health care workers in England Wales and the Northern Ireland to blood borne viruses between July 1997 and June 2000: Analysis of surveillance data. BMJ 2001;322:397-8.