A Cross-Sectional Study on Empathy and its Association With Stress in Medical Students

Introduction: Empathy is the cornerstone of the doctor-patient relationship and a crucial quality associated with better patient compliance and clinical outcomes. This study aims to assess the level of empathy and its association with the level of stress in 3rd and 4th year medical students Methods: This cross-sectional study was conducted in Kathmandu Medical College after taking ethical approval from the Institutional Review Committee and informed written consent from all the participants. The respondents completed a structured questionnaire including demographic profile, Jefferson Scale of Empathy-Student Version, and Perceived Stress Scale. Data were entered and analyzed in Statistical Package for the Social Sciences version 20. Results: A total of 255 questionnaires were obtained with a response rate of 85.2%. The mean empathy score was 101.79 (SD  =  11.26) and the mean perceived stress score was 18.55(SD = 5.56). There was a statistically significant negative correlation between empathy and stress (p-value <0.01) and similar negative correlations were seen in sub-group analysis. Female students had higher empathy scores compared to their male counterparts (p-value <0.01). Fourth-year students reported lower empathy scores than third-year students (p-value <0.05).  Conclusion: Stress was found to be a significant determinant of empathy among medical students. Medical educators must be aware of this and should try to incorporate means to alleviate stress in medical education. Furthermore, effective stress management techniques to preserve empathy in medical students with a view to improve clinical competency and achieve optimum patient care needs to be studied

BCAA catabolism in brown fat controls energy homeostasis through SLC25A44.

Branched-chain amino acid (BCAA; valine, leucine and isoleucine) supplementation is often beneficial to energy expenditure; however, increased circulating levels of BCAA are linked to obesity and diabetes. The mechanisms of this paradox remain unclear. Here we report that, on cold exposure, brown adipose tissue (BAT) actively utilizes BCAA in the mitochondria for thermogenesis and promotes systemic BCAA clearance in mice and humans. In turn, a BAT-specific defect in BCAA catabolism attenuates systemic BCAA clearance, BAT fuel oxidation and thermogenesis, leading to diet-induced obesity and glucose intolerance. Mechanistically, active BCAA catabolism in BAT is mediated by SLC25A44, which transports BCAAs into mitochondria. Our results suggest that BAT serves as a key metabolic filter that controls BCAA clearance via SLC25A44, thereby contributing to the improvement of metabolic health

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Journal articleWheat (Tritium aestivum L.) is the major food crop of India contributing 12 per cent of the total food grain production, covering an area of 31.5 Mha with production and productivity of 86.5 Mt and 2.8 tha-1 respectively (http://eands.dacnet.nic.in/). In India, wheat is grown during November to March, as it requires cool and moist weather during the vegetative phase, and warm and dry weather during reproductive phase. Cardinal (minimum, maximum and optimum) temperature is one of the most critical parameter that decides fate of crop productivity in wheat. However, wheat sowing after rice is delayed because of late harvesting of rice, large turn around time and poor soil tilth of seed bed which forces delaying of wheat sowing to varying degrees. Wheat yield under such circumstances is mainly affected by terminal heat and water stress.Reproductive phase is the ultimate determinant of yield, if faces high temperature stress shows a significant impact on yield (Mitra and Bhatia, 2008). Different wheat cultivars take different time from germination to maturity under varied agro-climatic condition. Therefore, crop development phases alone cannot be considered as a good predictor for measuring abiotic stress. The more scientific way of characterizing abiotic stressis through meteorological indices like growing degreedays, heat use efficiency, etc. Considering all these, a study was undertaken to investigate the impact of sowing date on yield, heat and water use efficiency of three wheat cultivars in Indo-Gangetic Plains of India.Not Availabl

Reconstructed Hedgehog Pathway.

<p>Total 57 proteins included in this pathway figure. The green and red arrows are indicating Activation/Production and Inhibition process respectively. The black arrows indicate the nuclear translocation process. All the proteins of this network are allocated into four main regions with different color codes: Extracellular and Membrane (Blue); Cytoplasm (Red); Nucleus (Green); and Output (Yellow). The output proteins are linked with various cellular responses (cross talk with other pathways or phenotypic expressions) with black dotted arrow.</p

Comparison between Normal, Cancer and Perturbed scenarios for Glioma.

<p>TS: Treated Scenario; NS: Normal Scenario; GS: Glioma Scenario. The green arrow heads are indicating the minimal combination of proteins which was inhibited in the drug treated perturbation analysis. (A) Represents number of Upstream activator proteins (Y-axis) activating the proteins (X-axis) representing significant variations. Compared to the normal scenario, proteins, SHH, SMO, GLI1, GLI2, and output proteins BMI, SNAI1, BCL2 and Cyclins, are activated by maximum number of upstream activator proteins. On drug treated perturbation of SMO, GLI1 and GLI2, the number of activators of the output proteins become zero. (B) Represents number of Upstream inhibitory proteins (Y-axis) inhibiting the proteins (X-axis) representing significant variations. The numbers of upstream inhibitor proteins in normal versus Glioma scenario remain same. Similar perturbation results are observed as in (A). (C) Represents number of Downstream proteins (Y-axis) activated by the proteins (X-axis) representing significant variations. The number of downstream proteins activated in normal versus Glioma remains same. On perturbation of SMO, GLI1 and GLI2, the number of downstream proteins activated by these proteins is reduced to zero. (D) Represents number of Downstream proteins (Y-axis) inhibited by the proteins (X-axis) representing significant variations. The number of downstream proteins inhibited in normal versus Glioma remains the same.</p

Protein expression levels observed in SMO inhibition and Treatment Scenarios for different cancers.

<p>First columns of (A), (B) and (C) represent the expressions of the proteins found after inhibiting SMO in Glioma, Colon and Pancreatic cancer models, respectively. Second columns of (A) represents the expressions of the proteins observed in the treatment scenario by perturbing SMO, GLI1 and GLI2 in combination in the same Glioma model; (B) represents the expressions of the proteins in the treatment scenario by perturbing SMO, HFU, ULK3, and RAS in combination in the same Colon cancer model; (C) represents the expressions of the proteins in the treatment scenario by perturbing SMO, HFU, ULK3, ERK12, and RAS in combination in the same Pancreatic cancer model. (D), (E) and (F) represent the identified alternative pathways (shown by solid green arrows) that remain active even after the inhibition of SMO in membrane (pathway shown by broken red arrows) by its inhibitor molecule (i.e. Cyclopamine, Vismodegib etc. ) in Glioma, Colon and Pancreatic cancer scenarios, respectively.</p

Parameter values from Connectivity and Centrality Analysis.

<p>Heat map of the values of the parameters used in Connectivity and Centrality analysis. The names of the proteins or nodes are arranged row wise (Y-axis) according to the position of their corresponding region (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0069132#pone-0069132-g001" target="_blank">Figure 1</a>). The parameter values are arranged column wise (X-axis) in the heat map. (A) Heat map of the values of the parameters values used in connectivity analysis: IN-DEGREE, OUT-DEGREE and TOTAL DEGREE of each protein. High IN-DEGREE value of GLI1, PTCH1, HHIP and SHH indicates their higher number of up-regulation by the other proteins in the network. High OUT-DEGREE value of several nuclear proteins (e.g. DYRK1, NUMB, NUC_GLI1, NUC_SUFU, NUC_STK36 etc.) refers their ability to regulate other proteins in HH network. In case of total degree, GLI1, GLI2 and NUC_GLI1 have significant highest value. It refers that these two proteins are mostly connected to the other proteins in the network. (B) Heat map of the individual centrality score of each protein of Hedgehog map. The Centrality measurement parameters used in this analysis were Eigenvector (EC), Betweenness (BC) and Closeness (CC) centrality. It is observed that GLI1 has the highest value for each parameter score. Subsequently, PTCH1, PTCH2, HHIP, STK36, NUC_GLI1, NUC_GLI2 etc. are also showing significant value for each individual centrality score.</p

Significant proteins extracted from Connectivity analysis.

<p>Significant proteins extracted from Connectivity analysis.</p

Comparison between Normal, Cancer and Perturbed scenarios for Pancreatic Cancer.

<p>TS: Treated Scenario; NS: Normal Scenario; PC: Pancreatic Cancer Scenario. The green arrow heads are indicating the minimal combination of proteins which was inhibited in the drug treated perturbation analysis. (A) Represents number of Upstream activator proteins (Y-axis) activating the proteins (X-axis) representing significant variations. Compared to the normal scenario, proteins, SHH, IHH, SMO, GLI1, GLI2 and output proteins BMI, SNAI1, BCL2 and Cyclins are activated by maximum number of upstream activator proteins. On drug treated perturbation of SMO, HFU, ULK3, RAS and ERK12, the number of activators of the output proteins become zero. (B) Represents number of upstream inhibitory proteins (Y-axis) inhibiting the proteins (X-axis) representing significant variations. The numbers of upstream inhibitor proteins in normal versus Pancreatic cancer scenario remain same. Similar perturbation results are observed as in (A). (C) Represents number of downstream proteins (Y-axis) activated by the proteins (X-axis) representing significant variations. The numbers of downstream proteins activated in normal versus Pancreatic Cancer remain same. On perturbation of SMO, HFU, ULK3, RAS and ERK12, the number of downstream proteins activated by these proteins is reduced to zero. (D) Represents number of downstream proteins (Y-axis) inhibited by the proteins (X-axis) representing significant variations. The numbers of downstream proteins inhibited in normal versus Pancreatic cancer scenario remain same.</p