Green Synthesized Chitosan Nanoparticles for Controlling Multidrug-Resistant mecA- and blaZ-Positive Staphylococcus aureus and aadA1-Positive Escherichia coli.

Antimicrobial resistance has recently been considered an emerging catastrophe globally. The public health and environmental threats were aggravated by the injudicious use of antibiotics in animal farming, aquaculture, and croup fields, etc. Consequently, failure of antibiotic therapies is common because of the emergence of multidrug-resistant (MDR) bacteria in the environment. Thus, the reduction in antibiotic spillage in the environment could be an important step for overcoming this situation. Bear in mind, this research was focused on the green synthesis of chitosan nanoparticles (ChiNPs) using Citrus lemon (Assam lemon) extract as a cross-linker and application in controlling MDR bacteria to reduce the antibiotic spillage in that sector. For evaluating antibacterial activity, Staphylococcus aureus and Escherichia coli were isolated from environmental specimens, and their multidrug-resistant pattern were identified both phenotypically by disk diffusion and genotypically by detecting methicillin- (mecA), penicillin- (blaZ), and streptomycin (aadA1)-resistance encoding genes. The inhibitory zone's diameter was employed as a parameter for determining the antibacterial effect against MDR bacteria revealing 30 ± 0.4 mm, 34 ± 0.2 mm, and 36 ± 0.8 mm zones of inhibition against methicillin- (mecA) and penicillin (blaZ)-resistant S. aureus, and streptomycin (aadA1)-resistant E. coli, respectively. The minimum inhibitory concentration at 0.31 mg/mL and minimum bactericidal concentration at 0.62 mg/mL of yielded ChiNPs were used as the broad-spectrum application against MDR bacteria. Finally, the biocompatibility of ChiNPs was confirmed by showing a negligible decrease in BHK-21 cell viability at doses less than 2 MIC, suggesting their potential for future application in antibiotic-free farming practices.

A cross-sectional study on anxiety due to COVID-19 and its predictors among undergraduate medical students in a tertiary care teaching hospital of Kolkata, West Bengal.

Background: Medical education is recognized as stressful globally. COVID-19 pandemic is an additional source of anxiety to the medical students. Objectives: This study was conducted to assess the prevalence and to identify the factors associated with anxiety due to COVID-19 among undergraduate medical students in a teaching hospital of Kolkata, West Bengal. . Methods: An observational cross-sectional study was conducted among 363 undergraduate medical students using the stratified random sampling of a medical college from June to July 2021. Data were collected using a predesigned, pretested, and structured online questionnaire, including "Coronavirus Anxiety Scale." Descriptive statistics were used to estimate the prevalence of anxiety. Pearson's Chi-square test was performed to find out the factors associated with anxiety due to COVID-19. Results: About 25.6% of the medical students were found to have anxiety due to COVID-19. About 28.9% of them reported COVID-19 infection in family in recent past and 11.0% had themselves tested positive. Nearly 20% reported loss of family members, relatives, and close friends due to COVID-19. The factors associated with anxiety due to pandemic were socioeconomic status, social stigma, sleep disturbances, history of COVID-19 in family, loss of job. and vaccination status of family members missing practical classes and exam-related anxiety. Conclusion: The study found that one-fourth of the medical students had anxiety due to COVID-19. Social stigma due to COVID-19 and loss of job of parents were the most significant predictors. It is recommended that targeted psychological and clinical interventions need to be taken to alleviate students' anxiety due to COVID.

Seasonal characteristics of boundary layer over a high-altitude rural site in Western India: implications on dispersal of particulate matter.

The temporal variability of the planetary boundary layer height (PBLH) over Mahabaleshwar was studied for a period of 1 year from 1 December 2015 to 30 November 2016 using microwave radiometer (MWR) observations. The PBLH over Mahabaleshwar was found to be the highest during the pre-monsoon (March-May) season and lowest during the winter (December-February) season. The seasonal mean of PBLH was estimated to be 339±88 m during winter, 485±70 m during pre-monsoon, 99±153 m during monsoon, and 438±24 m during post-monsoon season. Frequency distribution analysis of PBLH during pre-monsoon season revealed that the formation of turbulence internal boundary layer (TIBL) is evident. In contrast, cold and moist air mass during the monsoon season enhances the wind shear with lower buoyancy term which results in lowering of PBLH. The comparison of PBLH between MWR and radiosonde observations shows a good correlation (r2 = 0.66, p=0.001). The growth rate was observed to be 388 m/h during pre-monsoon, 206 m/h during winter, 57 m/h during monsoon, and 167 m/h during post-monsoon season. The seasonal mean concentration of PM2.5 was found to be 42.3±4.6 µg/m3during winter, 33.4±8.7 µg/m3 during pre-monsoon, 6.6±2.2 µg/m3 during monsoon, and 26.1±1.7 µg/m3during post-monsoon season. The effect of higher loading of scattering-type aerosol (dust particle) was also investigated as a case study. The analysis reveals the inverse relationship between the PBL height variability and the particulate loading indicating the importance of aerosol direct effect. Analysis of the ventilation coefficient (Vc) revealed that the dissipation potential was higher (1736 m2/s) during pre-monsoon season as compared to (1191 m2/s, 455m2/s, and 1580 m2/s) winter, monsoon, and post-monsoon seasons.

Study comparing the management decisions by IMNCI algorithm and pediatricians in a teaching hospital for the young infants between 0 to 2 months.

Integrated management of neonatal and childhood illness (IMNCI) was already operational in many states of India, but there were very few studies in Indian scenario comparing its validity and reliability with the decisions of pediatricians. The general objective of the study is to compare the IMNCI decisions with the decisions of pediatricians and the specific objectives are to assess the agreement between IMNCI decisions and the decisions of pediatricians, to assess the under diagnosis and over diagnosis in IMNCI algorithm in comparison to the decisions of pediatricians and to assess the significance of multiple presenting symptoms in IMNCI algorithm. The study was conducted among the sick young infants presenting in pediatric department from January to March 2009. The IMNCI decision was compared with pediatrician's decisions by percent agreement, Kappa and weighted Kappa with the aids of SPSS version 10. The overall diagnostic agreement between IMNCI algorithm and pediatrician's decisions was 55.56%, (Kappa 0.32 and weighted Kappa 0.41) with 33.33% over diagnosis, and 11.11% under diagnosis. 71.88% young infants with multiple symptoms and 40% with single symptom were classified as red by IMNCI algorithm, which is statistically significant (P=0.004) whereas 56.25% young infants with multiple and 31.76% with single symptom were considered admissible by pediatricians, which is not statistically significant (P=0.052).

A study on cognitive status of 50 years and above aged non-demented women in a rural area of West Bengal.

The prevalence of ageing population is increasing not only in developed countries but also in developing world like India. Epidemiological reports about cognitive impairment or dementia in elderly people from developing countries are scarce. To study the cognitive status of women more than 50 years of age and to study the relationship of sociodemographic factors with cognitive status of the study subjects a descriptive epidemiological, community based cross-sectional survey was done involving 179 old women of 50 years and above in the rural field practice area of All India Institute of Hygiene and Public Health, Kolkata. The data were analysed using Epi-info 6.04, software packages. The mean age of the sample was 64.0 +/- 7.6 years. In the total sample, 53 subjects (29.6%) were in 50-59 years, 83 (43.4%) in 60-69 years, 34 (19%) in 70-79 years and 9 (5%) in women who were more than 80 years old. The cognitive defect was found to be 42.4% in elderly women .The variables like age > 70 years, widowhood, low per capita income, economic dependence, non-support from children, not staying with own children and having no satisfaction with life, were found to be significantly associated with cognitive defect. On (stepwise) multiple regression analysis these factors together contributed to 37% of cognitive impairment among these women. Prevalence of cognitive defect of more than 40% in the elderly women of this study emphasises the need for more attention and more social security measures for this neglected group.