Predictors of Mortality in Scrub Typhus Infection Requiring Intensive Care Admission in Tertiary Healthcare Centre of Nepal

© 2018 Shital Adhikari et al. Introduction. This study aimed to explore the predictors of mortality from scrub typhus infection in patients requiring intensive care unit (ICU) admission. Materials and Methods. A retrospective study was conducted on 120 patients with serum ELISA IgM positive for scrub typhus (optical density ≥ 0.5) admitted at the medical ICU of Chitwan Medical College Teaching Hospital between April 2016 and September 2017. Data was extracted from patient medical records and electronic database of the hospital. The outcome measurement was mortality (Yes/No) due to the infection. A multivariate binary logistic regression analysis (p 100/minute (p 1.4 mg/dl (p<0.001), acute kidney injury requiring dialysis (p=0.029), acute respiratory distress syndrome (p<0.001), and shock requiring vasopressor (p<0.001). Regression analysis showed age (odds ratio [OR] = 1.063; 95% CI = 1.010-1.118; p=0.019) and serum creatinine (OR = 1.063; 95% CI = 1.010-1.118; p=0.019) as significant predictors of poor outcome. Conclusion. Older age and high serum creatinine were found to be independent predictors of poor outcome in patients with scrub typhus admitted in medical ICU

Dorsal anterior cingulate cortex encodes the integrated incentive motivational value of cognitive task performance

Humans can seamlessly combine value signals from diverse motivational incentives, yet it is not well understood how these signals are bundled in the brain to modulate cognitive control. The dorsal ACC (dACC) is theorized to integrate motivational value dimensions in the service of goal-directed action, although this hypothesis has yet to receive rigorous confirmation. In the present study, we examined the role of human dACC in motivational incentive integration. Healthy young adult men and women were scanned with fMRI while engaged in an experimental paradigm that quantifies the combined effects of liquid (e.g., juice, neutral, saltwater) and monetary incentives on cognitive task performance. Monetary incentives modulated trial-by-trial dACC activation, whereas block-related effects of liquid incentives on dACC activity were observed. When bundled together, incentive-related dACC modulation predicted fluctuations in both cognitive performance and self-report motivation ratings. Statistical mediation analyses suggest that dACC encoded the incentives in terms of their integrated subjective motivational value, and that this value signal was most proximally associated with task performance. Finally, we confirmed that these incentive integration effects were selectively present in dACC. Together, the results support an account in which dACC integrates motivational signals to compute the expected value of goal-directed cognitive control

Metabolic characterization of triple negative breast cancer

Background: The aims of this study were to characterize the metabolite profiles of triple negative breast cancer (TNBC) and to investigate the metabolite profiles associated with human epidermal growth factor receptor-2/neu (HER-2) overexpression using ex vivo high resolution magic angle spinning magnetic resonance spectroscopy (HR MAS MRS). Metabolic alterations caused by the different estrogen receptor (ER), progesterone receptor (PgR) and HER-2 receptor statuses were also examined. To investigate the metabolic differences between two distinct receptor groups, TNBC tumors were compared to tumors with ERpos/PgR(pos)/HER-2(pos) status which for the sake of simplicity is called triple positive breast cancer (TPBC).Methods: The study included 75 breast cancer patients without known distant metastases. HR MAS MRS was performed for identification and quantification of the metabolite content in the tumors. Multivariate partial least squares discriminant analysis (PLS-DA) modeling and relative metabolite quantification were used to analyze the MR data.Results: Choline levels were found to be higher in TNBC compared to TPBC tumors, possibly related to cell proliferation and oncogenic signaling. In addition, TNBC tumors contain a lower level of Glutamine and a higher level of Glutamate compared to TPBC tumors, which indicate an increase in glutaminolysis metabolism. The development of glutamine dependent cell growth or "Glutamine addiction" has been suggested as a new therapeutic target in cancer. Our results show that the metabolite profiles associated with HER-2 overexpression may affect the metabolic characterization of TNBC. High Glycine levels were found in HER-2(pos) tumors, which support Glycine as potential marker for tumor aggressiveness.Conclusions: Metabolic alterations caused by the individual and combined receptors involved in breast cancer progression can provide a better understanding of the biochemical changes underlying the different breast cancer subtypes. Studies are needed to validate the potential of metabolic markers as targets for personalized treatment of breast cancer subtypes

Examining delay of gratification in healthy aging

Delay of gratification (DofG) refers to the capacity to forego an immediate reward in order to receive a more desirable reward later. As a core executive function, it might be expected that DofG would follow the standard pattern of age-related decline observed in older adults for other executive tasks. However, there actually have been few studies of aging and DofG, and even these have shown mixed results, suggesting the need for further investigation and new approaches. The present study tested a novel reward-based decision-making paradigm enabling examination of age-related DofG effects in adult humans. Results showed that older adults earned fewer overall rewards than young adults, both before and after instruction regarding the optimal DofG strategy. Prior to instruction, learning this strategy was challenging for all participants, regardless of age. The finding of age-related impairments even after strategy instruction indicated that these impairments were not due to a failure to understand the task or follow the optimal strategy, but instead were related to self-reported difficulty in waiting for delayed rewards. These results suggest the presence of age-related changes in DofG capacity and highlight the advantages of this new experimental paradigm for use in future investigations, including both behavioral and neuroimaging studies

Soil analysis gis-based fertility assessment and mapping of agricultural research station, Pakhribas, Dhankuta, Nepal

Soil fertility evaluation has been considered as a most effective tool for sustainable planning of a particular region. This study was conducted to determine the soil fertility status of the Agricultural Research Station, Pakhribas, Dhankuta, Nepal. The total 60 soil samples were collected randomly at a depth of 0-20 cm by using the soil sampling auger. For identification of soil sampling points A GPS device was used. The collected samples were analyzed for their texture, pH, OM, N, P2O5, K2O, Ca, Mg, S, B, Fe, Zn, Cu and Mn status following standard methods in the laboratory of Soil Science Division, Khumaltar. The Arc-GIS 10.1 software was used for soil fertility maps preparation. The observed data revealed that soil was dark yellowish brown (10YR 4/4) and yellowish brown (10YR 5/6) in colour, and single grained, granular and sub-angular blocky in structure. The sand, silt and clay content were 56.61±0.97%, 27.62±0.56% and 15.77±0.58%, respectively and categorized as loam, sandy loam and sandy clay loam in texture. The soil was very acidic in pH (4.66±0.07) and very low in available sulphur (0.53±0.11mg/kg), available boron (0.24±0.07mg/kg). The organic matter (1.34±0.07%), total nitrogen (0.09±0.003mg/kg), available calcium (605.70±31.40mg/kg), available magnesium (55.96±4.67mg/kg) and available zinc (0.54±0.22mg/kg) were low in status. Similarly, available potassium (115.98±9.19 mg/kg) and available copper (1.13±0.09 mg/kg) were medium in status. Furthermore, available manganese (36.31±2.82mg/kg) was high, whereas available phosphorus (105.07±9.89 mg/kg) and available iron (55.80±8.89 mg/kg) were very high in status. The soil fertility management practice should be adopted based on the determined status in the field for the sustainable production of crops. The future research strategy should be built based on the soil fertility status of the research farm

Extrapulmonary Tuberculosis: A retrospective Study at a tertiary care hospital in Palpa, Nepal

Background: Extra-pulmonary tuberculosis (EPTB) is a significant global health problem. Related studies to it in different places and diff erent durations are indicated by many previous research findings. Findings of this study could be beneficial for its preventive and control strategies. Methodology: Retrospective analysis of clinical specimens submitted to Central laboratory of Lumbini Medical College and Teaching Hospital (LMCTH) for extrapulmonary tuberculosis was performed. Total 261 samples submitted from April 2011 to February 2013 were included for analysis in this study. Results: Total 20.7% (54/261) prevalence of EPTB was reported. Based on sites involved; lymph node 87.03%, pleural effusion7.40%, peritoneal5.55% were found. Genderwise equal prevalence was seen among male and females. Age-wise prevalence among patients between 21-40 years was reported. Conclusion: Our finding indicates great necessity for further large scale study on prevalence of EPTB in this location for its prevention and control

Machine learning analytics of resting-state functional connectivity predicts survival outcomes of glioblastoma multiforme patients

Glioblastoma multiforme (GBM) is the most frequently occurring brain malignancy. Due to its poor prognosis with currently available treatments, there is a pressing need for easily accessible, non-invasive techniques to help inform pre-treatment planning, patient counseling, and improve outcomes. In this study we determined the feasibility of resting-state functional connectivity (rsFC) to classify GBM patients into short-term and long-term survival groups with respect to reported median survival (14.6 months). We used a support vector machine with rsFC between regions of interest as predictive features. We employed a novel hybrid feature selection method whereby features were first filtered using correlations between rsFC and OS, and then using the established method of recursive feature elimination (RFE) to select the optimal feature subset. Leave-one-subject-out cross-validation evaluated the performance of models. Classification between short- and long-term survival accuracy was 71.9%. Sensitivity and specificity were 77.1 and 65.5%, respectively. The area under the receiver operating characteristic curve was 0.752 (95% CI, 0.62-0.88). These findings suggest that highly specific features of rsFC may predict GBM survival. Taken together, the findings of this study support that resting-state fMRI and machine learning analytics could enable a radiomic biomarker for GBM, augmenting care and planning for individual patients