Investigating dengue outbreak in Tamil Nadu, India

Dengue has been indigenous to India in last decade. There was a major outbreak in the state of Tamil Nadu in 2017. Here, we investigate the dengue outbreak in parts of Tamil Nadu, India. Dengue case data were obtained from the hospital records in the Chennai district of Tamil Nadu. The data were analyzed using statistical approaches such as correlation and regression. The result shows that the dengue outbreak in Tamil Nadu during 2017 was due to the population, water stagnation, and sewage, whereas the human activity weren’t the cause of the dengue outbreak which caused 65 deaths. Male constitutes 54.71% whereas female accounted for 45.29% of dengue incidence in Tamil Nadu, majority deaths were children aged less than 10 years due to the outbreak of Dengue Hemorrhagic Fever (DHF). This investigation was evaluated using mathematical regressions, Geographically Weighted Regression (GWR) regression outperformed Ordinary Least Square (OLS) regression model in detecting dengue incidence. This investigation can be strengthened by implementing a surveillance system in parts of Tamil Nadu before an outbreak

An ensemble multi-model technique for predicting chronic kidney disease

Chronic Kidney Disease (CKD) is a type of lifelong kidney disease that leads to the gradual loss of kidney function over time; the main function of the kidney is to filter the wastein the human body. When the kidney malfunctions, the wastes accumulate in our body leading to complete failure. Machine learning algorithms can be used in prediction of the kidney disease at early stages by analyzing the symptoms. The aim of this paper is to propose an ensemble learning technique for predicting Chronic Kidney Disease (CKD). We propose a new hybrid classifier called as ABC4.5, which is ensemble learning for predicting Chronic Kidney Disease (CKD). The proposed hybrid classifier is compared with the machine learning classifiers such as Support Vector Machine (SVM), Decision Tree (DT), C4.5, Particle Swarm Optimized Multi Layer Perceptron (PSO-MLP). The proposed classifier accurately predicts the occurrences of kidney disease by analysis various medical factors. The work comprises of two stages, the first stage consists of obtaining weak decision tree classifiers from C4.5 and in the second stage, the weak classifiers are added to the weighted sum to represent the final output for improved performance of the classifier

Breast cancer prediction model with decision tree and adaptive boosting

In this study, breast cancer prediction model is proposed with decision tree and adaptive boosting (Adboost). Furthermore, an extensive experimental evaluation of the predictive performance of the proposed model is conducted. The study is conducted on breast cancer dataset collected form the kaggle data repository. The dataset consists of 569 observations of which the 212 or 37.25% are benign or breast cancer negative and 62.74% are malignant or breast cancer positive. The class distribution shows that, the dataset is highly imbalanced and a learning algorithm such as decision tree is biased to the benign observation and results in poor performance on predicting the malignant observation. To improve the performance of the decision tree on the malignant observation, boosting algorithm namely, the adaptive boosting is employed. Finally, the predictive performance of the decision tree and adaptive boosting is analyzed. The analysis on predictive performance of the model on the kaggle breast cancer data repository shows that, adaptive boosting has 92.53% accuracy and the accuracy of decision tree is 88.80%, Overall, the adaboost algorithm performed better than decision tree

DNA Methylation and Transcription Patterns in Intestinal Epithelial Cells From Pediatric Patients With Inflammatory Bowel Diseases Differentiate Disease Subtypes and Associate With Outcome.

BACKGROUND & AIMS: We analyzed DNA methylation patterns and transcriptomes of primary intestinal epithelial cells (IEC) of children newly diagnosed with inflammatory bowel diseases (IBD) to learn more about pathogenesis. METHODS: We obtained mucosal biopsies (N = 236) collected from terminal ileum and ascending and sigmoid colons of children (median age 13 years) newly diagnosed with IBD (43 with Crohn's disease [CD], 23 with ulcerative colitis [UC]), and 30 children without IBD (controls). Patients were recruited and managed at a hospital in the United Kingdom from 2013 through 2016. We also obtained biopsies collected at later stages from a subset of patients. IECs were purified and analyzed for genome-wide DNA methylation patterns and gene expression profiles. Adjacent microbiota were isolated from biopsies and analyzed by 16S gene sequencing. We generated intestinal organoid cultures from a subset of samples and genome-wide DNA methylation analysis was performed. RESULTS: We found gut segment-specific differences in DNA methylation and transcription profiles of IECs from children with IBD vs controls; some were independent of mucosal inflammation. Changes in gut microbiota between IBD and control groups were not as large and were difficult to assess because of large amounts of intra-individual variation. Only IECs from patients with CD had changes in DNA methylation and transcription patterns in terminal ileum epithelium, compared with controls. Colon epithelium from patients with CD and from patients with ulcerative colitis had distinct changes in DNA methylation and transcription patterns, compared with controls. In IECs from patients with IBD, changes in DNA methylation, compared with controls, were stable over time and were partially retained in ex-vivo organoid cultures. Statistical analyses of epithelial cell profiles allowed us to distinguish children with CD or UC from controls; profiles correlated with disease outcome parameters, such as the requirement for treatment with biologic agents. CONCLUSIONS: We identified specific changes in DNA methylation and transcriptome patterns in IECs from pediatric patients with IBD compared with controls. These data indicate that IECs undergo changes during IBD development and could be involved in pathogenesis. Further analyses of primary IECs from patients with IBD could improve our understanding of the large variations in disease progression and outcomes

A guide to best practice in faculty development for health professions schools: a qualitative analysis

BACKGROUND: This is a practice guide for the evaluation tool specifically created to objectively evaluate longitudinal faculty development programs (FDP) using the “5×2 -D backward planning faculty development model”. It was necessary to create this tool as existing evaluation methods are designed to evaluate linear faculty development models with a specific endpoint. This backward planning approach is a cyclical model without an endpoint, consisting of 5 dynamic steps that are flexible and interchangeable, therefore can be a base for an evaluation tool that is objective and takes into account all the domains of the FDP in contrast to the existing, traditional, linear evaluation tools which focus on individual aspects of the program. The developed tool will target evaluation of longitudinal faculty development programs regardless of how they were planned. METHODOLOGY: Deductive qualitative grounded theory approach was used. Evaluation questions were generated and tailored based on the 5 × 2-D model followed by 2 Delphi rounds to finalize them. Based on the finalized evaluation questions from the results of the Delphi rounds, two online focus group discussions (FGDs) were conducted to deduce the indicators, data sources and data collection method. RESULTS: Based on the suggested additions, the authors added 1 new question to domains B, with a total of 42 modifications, such as wording changes or discarding or merging questions. Some domains received no comments, therefore, were not included in round 2. For each evaluation question, authors generated indicators, data sources and data collection methods during the FGD. CONCLUSION: The methodology used to develop this tool takes into account expert opinions. Comprehensiveness of this tool makes it an ideal evaluation tool during self-evaluation or external quality assurance for longitudinal FDP. After its validation and testing, this practice guide can be used worldwide, along with the provided indicators which can be quantified and used to suit the local context. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12909-022-03208-x

Safety and efficacy of primaquine in patients with Plasmodium vivax malaria from South Asia: a systematic review and individual patient data meta-analysis

Background The optimal dosing of primaquine to prevent relapsing Plasmodium vivax malaria in South Asia remains unclear. We investigated the efficacy and safety of different primaquine regimens to prevent P. vivax relapse. Methods A systematic review identified P. vivax efficacy studies from South Asia published between 1 January 2000 and 23 August 2021. In a one-stage meta-analysis of available individual patient data, the cumulative risks of P. vivax recurrence at day 42 and 180 were assessed by primaquine total mg/kg dose and duration. The risk of recurrence by day 180 was also determined in a two-stage meta-analysis. Patients with a >25% drop in haemoglobin to 50 g/L between days 1 and 14 were categorised by daily mg/kg primaquine dose. Results In 791 patients from 7 studies in the one-stage meta-analysis, the day 180 cumulative risk of recurrence was 61.1% (95% CI 42.2% to 80.4%; 201 patients; 25 recurrences) after treatment without primaquine, 28.8% (95% CI 8.2% to 74.1%; 398 patients; 4 recurrences) following low total (2 to 25% drop in haemoglobin to <70 g/L. Conclusions Primaquine treatment led to a marked decrease in P. vivax recurrences following low (~3.5 mg/kg) and high (~7 mg/kg) total doses, with no reported severe haemolytic events. PROSPERO registration number CRD42022313730

MHD activity induced coherent mode excitation in the edge plasma region of ADITYA-U Tokamak

In this paper, we report the excitation of coherent density and potential fluctuations induced by magnetohydrodynamic (MHD) activity in the edge plasma region of ADITYA-U Tokamak. When the amplitude of the MHD mode, mainly the m/n = 2/1, increases beyond a threshold value of 0.3-0.4 %, coherent oscillations in the density and potential fluctuations are observed having the same frequency as that of the MHD mode. The mode numbers of these MHD induced density and potential fluctuations are obtained by Langmuir probes placed at different radial, poloidal, and toroidal locations in the edge plasma region. Detailed analyses of these Langmuir probe measurements reveal that the coherent mode in edge potential fluctuation has a mode structure of m/n = 2/1 whereas the edge density fluctuation has an m/n = 1/1 structure. It is further observed that beyond the threshold, the coupled power fraction scales almost linearly with the magnitude of magnetic fluctuations. Furthermore, the rise rates of the coupled power fraction for coherent modes in density and potential fluctuations are also found to be dependent on the growth rate of magnetic fluctuations. The disparate mode structures of the excited modes in density and plasma potential fluctuations suggest that the underlying mechanism for their existence is most likely due to the excitation of the global high-frequency branch of zonal flows occurring through the coupling of even harmonics of potential to the odd harmonics of pressure due to 1/R dependence of the toroidal magnetic field

Perceptions about hemodialysis and transplantation among African American adults with end-stage renal disease: inferences from focus groups

BACKGROUND: Disparities in access to kidney transplantation (KT) remain inadequately understood and addressed. Detailed descriptions of patient attitudes may provide insight into mechanisms of disparity. The aims of this study were to explore perceptions of dialysis and KT among African American adults undergoing hemodialysis, with particular attention to age- and sex-specific concerns. METHODS: Qualitative data on experiences with hemodialysis and views about KT were collected through four age- and sex-stratified (males <65, males ≥65, females <65, and females ≥65 years) focus group discussions with 36 African American adults recruited from seven urban dialysis centers in Baltimore, Maryland. RESULTS: Four themes emerged from thematic content analysis: 1) current health and perceptions of dialysis, 2) support while undergoing dialysis, 3) interactions with medical professionals, and 4) concerns about KT. Females and older males tended to be more positive about dialysis experiences. Younger males expressed a lack of support from friends and family. All participants shared feelings of being treated poorly by medical professionals and lacking information about renal disease and treatment options. Common concerns about pursuing KT were increased medication burden, fear of surgery, fear of organ rejection, and older age (among older participants). CONCLUSIONS: These perceptions may contribute to disparities in access to KT, motivating granular studies based on the themes identified

Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017.

The Global Burden of Diseases, Injuries and Risk Factors 2017 includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. METHODS: We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting