Correlation of clinical and radiological outcome of distal radius fractures treated with volar plating

Background: Distal radius fractures are one of the most common injuries treated by an orthopaedic surgeon, accounting for approximately one sixth of all fractures. Due to increase in incidence of high velocity trauma, the injury is seen occurring in young patients more often. A displaced fracture deranges the wrist anatomy causing deformity and loss of function at the wrist joint. Open reduction and internal fixation with plate using a volar approach allows anatomical reduction of the fracture, stable fixation aiding in early mobilization.Methods: Our study was a hospital-based study conducted during the period June 2016 to November 2018. A total of 30 patients with distal radius fracture were treated with ORIF with a volar plate. They were followed up for a year and clinical and radiological outcomes were evaluated.Results: Among the 30 patients studied 25 were males and 5 were females with mean age of 36.23 years. According to Gartland and Werley demerit scoring system, 15 of them had excellent result at the end of one year. 13 Of them had good and 2 of them had fair results. Radiological assessment was done by Sarmiento’s modification of the Lind storm criteria and 15 of them had excellent results. 15 patients had good radiological outcome.Conclusions: From this study we conclude that ORIF with volar plating can provide good clinical and functional outcome in distal radius fractures. Anatomical reduction of the fracture fragments is the key in achieving good results

A Grey Wolf Optimization-Based Clustering Approach for Energy Efficiency in Wireless Sensor Networks

In the realm of Wireless Sensor Networks, the longevity of a sensor node's battery is pivotal, especially since these nodes are often deployed in locations where battery replacement is not feasible. Heterogeneous networks introduce additional challenges due to varying buffer capacities among nodes, necessitating timely data transmission to prevent loss from buffer overflows. Despite numerous attempts to address these issues, previous solutions have been deficient in significant respects. Our innovative strategy employs Grey Wolf Optimization for Cluster Head selection within heterogeneous networks, aiming to concurrently optimise energy efficiency and buffer capacity. We conducted comprehensive simulations using Network Simulator 2, with results analysed in MATLAB, focusing on metrics such as energy depletion rates, remaining energy, node-to-node distance, node count, packet delivery, and average energy in the cluster head selection process. Our approach was benchmarked against leading protocols like LEACH and PEGASIS, considering five key performance indicators: energy usage, network lifespan, the survival rate of nodes over time, data throughput, and remaining network energy. The simulations demonstrate that our Grey Wolf Optimisation method outperforms conventional protocols, showing a 9% reduction in energy usage, a 12% increase in node longevity, a 9.8% improvement in data packet delivery, and a 12.2% boost in data throughput

A simple breath test for tuberculosis using ion mobility : a pilot study

Tuberculosis (TB) remains one of the world's major health burdens with 9.6 million new infections globally. Though considerable progress has been made in reduction of TB incidence and mortality, there is a continuous need for lower cost, simpler and more robust means of diagnosis. One method that may fulfil these requirements is in the area of breath analysis. In this study we analysed the breath of 21 patients with pulmonary or extra-pulmonary TB, recruited from a UK teaching hospital (University Hospital Coventry and Warwickshire) before or within 1 week of commencing treatment for TB. TB diagnosis was confirmed by reference tests (mycobacterial culture), histology or radiology. 19 controls were recruited to calculate specificity; these patients were all interferon-gamma release assay negative (T.SPOT®.TB, Oxford Immunotec Ltd.). Whole breath samples were collected with subsequent chemical analysis undertaken by Ion Mobility Spectrometry. Our results produced a sensitivity of 81% and a specificity of 79% for all cases of TB (pulmonary and extra-pulmonary). Though lower than other studies analysing pulmonary TB alone, we believe that this technique shows promise, and a higher sensitivity could be achieved by further improving our sample capture methodology

Implementing and sustaining a mobile medical clinic for prenatal care and sexually transmitted infection prevention in rural Mysore, India

Background In rural India, mobile medical clinics are useful models for delivering health promotion, education, and care. Mobile medical clinics use fewer providers for larger catchment areas compared to traditional clinic models in resource limited settings, which is especially useful in areas with shortages of healthcare providers and a wide geographical distribution of patients. Methods From 2008 to 2011, we built infrastructure to implement a mobile clinic system to educate rural communities about maternal child health, train community health workers in common safe birthing procedures, and provide comprehensive antenatal care, prevention of mother-to-child transmission (PMTCT) of human immunodeficiency virus (HIV), and testing for specific infections in a large rural catchment area of pregnant women in rural Mysore. This was done using two mobile clinics and one walk-in clinic. Women were tested for HIV, hepatitis B, syphilis, and bacterial vaginosis along with random blood sugar, urine albumin, and anemia. Sociodemographic information, medical, and obstetric history were collected using interviewer-administered questionnaires in the local language, Kannada. Data were entered in Microsoft Excel and analyzed using Stata SE 14.1. Results During the program period, nearly 700 community workers and 100 health care providers were trained; educational sessions were delivered to over 15,000 men and women and integrated antenatal care and HIV/sexually transmitted infection testing was offered to 3545 pregnant women. There were 22 (0.6%) cases of HIV, 19 (0.5%) cases of hepatitis B, 2 (0.1%) cases of syphilis, and 250 (7.1%) cases of BV, which were identified and treated. Additionally, 1755 (49.5%) cases of moderate to severe anemia and 154 (4.3%) cases of hypertension were identified and treated among the pregnant women tested. Conclusions Patient-centered mobile medical clinics are feasible, successful, and acceptable models that can be used to provide quality healthcare to pregnant women in rural and hard-to-reach settings. The high numbers of pregnant women attending mobile medical clinics show that integrated antenatal care with PMTCT services were acceptable and utilized. The program also developed and trained health professionals who continue to remain in those communities

HEAT TRANSFER ANALYSIS OF RECUPERATIVE AIR PREHEATER

Abstract: Steam generators are very complex class of pressure vessels. It contains many accessories for the generation of required steam quality. The prime motto of industrial steam generator is to generate steam at medium pressure (MP), low pressure (LP) steam at required pressure temperature and quantity for the process industry like sugar, paper, jute and chemical industries. LP and MP steam after expansion in the turbine from super saturation is utilized by process industry. In the present work Air Preheater, one of the accessories of the steam generator is analysed. Air preheaters make a considerable contribution to the improved overall efficiency of fossil-fuel-fired power plants. In this study, a theoretical design of Recuperative Primary Air preheater with In-line tube arrangement and a combination of fluid dynamics analysis with theoretical value. The model enables heat transfer of the flue-gas flow through the air preheater as well as the tubular heat transfer and the resulting temperature distribution in the matrix of the preheater. The present work is carried in Mysore Paper Mills (MPM) Bhadravathi, CFD (Computational Fluid Dynamics) analysis of recuperative air preheater is carried out using ANSYS CFX-12.1.The analysis of flue gas flow phenomenon and air flow phenomenon are discussed using Laminar model, k-ε model, k-ω model and SST model. The parameters like temperature distribution, heat flux, pressure drop, velocity, are also discussed. An increase of 2.7% in boiler efficiency was found out with incorporation of this design, their by an increase in the air inlet temperature of about 60℃ is been observed

FMRP Interacts with C/D Box snoRNA in the Nucleus and Regulates Ribosomal RNA Methylation

Summary: FMRP is an RNA-binding protein that is known to localize in the cytoplasm and in the nucleus. Here, we have identified an interaction of FMRP with a specific set of C/D box snoRNAs in the nucleus. C/D box snoRNAs guide 2’O methylations of ribosomal RNA (rRNA) on defined sites, and this modification regulates rRNA folding and assembly of ribosomes. 2’O methylation of rRNA is partial on several sites in human embryonic stem cells, which results in ribosomes with differential methylation patterns. FMRP-snoRNA interaction affects rRNA methylation on several of these sites, and in the absence of FMRP, differential methylation pattern of rRNA is significantly altered. We found that FMRP recognizes ribosomes carrying specific methylation patterns on rRNA and the recognition of methylation pattern by FMRP may potentially determine the translation status of its target mRNAs. Thus, FMRP integrates its function in the nucleus and in the cytoplasm. : Molecular Interaction; Stem Cells Research; Omics Subject Areas: Molecular Interaction, Stem Cells Research, Omic

QTL-seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut (Arachis hypogaea L.)

Rust and late leaf spot (LLS) are the two major foliar fungal diseases in groundnut, and their co-occurrence leads to significant yield loss in addition to the deterioration of fodder quality. To identify candidate genomic regions controlling resistance to rust and LLS, whole-genome resequencing (WGRS)-based approach referred as ‘QTL-seq’ was deployed. A total of 231.67 Gb raw and 192.10 Gb of clean sequence data were generated through WGRS of resistant parent and the resistant and susceptible bulks for rust and LLS. Sequence analysis of bulks for rust and LLS with reference-guided resistant parent assembly identified 3136 single-nucleotide polymorphisms (SNPs) for rust and 66 SNPs for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNPs affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNPs affecting nine candidate genes for LLS resistance. Subsequently, allele-specific diagnostic markers were identified for three SNPs for rust resistance and one SNP for LLS resistance. Genotyping of one RIL population (TAG 24 × GPBD 4) with these four diagnostic markers revealed higher phenotypic variation for these two diseases. These results suggest usefulness of QTL-seq approach in precise and rapid identification of candidate genomic regions and development of diagnostic markers for breeding applications

Identification of several small main-effect QTLs and a large number of epistatic QTLs for drought tolerance related traits in groundnut (Arachishypogaea L.)

Cultivated groundnut or peanut (Arachis hypogaea L.), an allotetraploid (2n = 4x = 40), is a self pollinated and widely grown crop in the semi-arid regions of the world. Improvement of drought tolerance is an important area of research for groundnut breeding programmes. Therefore, for the identification of candidate QTLs for drought tolerance, a comprehensive and refined genetic map containing 191 SSR loci based on a single mapping population (TAG 24 × ICGV 86031), segregating for drought and surrogate traits was developed. Genotyping data and phenotyping data collected for more than ten drought related traits in 2–3 seasons were analyzed in detail for identification of main effect QTLs (M-QTLs) and epistatic QTLs (E-QTLs) using QTL Cartographer, QTLNetwork and Genotype Matrix Mapping (GMM) programmes. A total of 105 M-QTLs with 3.48–33.36% phenotypic variation explained (PVE) were identified using QTL Cartographer, while only 65 M-QTLs with 1.3–15.01% PVE were identified using QTLNetwork. A total of 53 M-QTLs were such which were identified using both programmes. On the other hand, GMM identified 186 (8.54–44.72% PVE) and 63 (7.11–21.13% PVE), three and two loci interactions, whereas only 8 E-QTL interactions with 1.7–8.34% PVE were identified through QTLNetwork. Interestingly a number of co-localized QTLs controlling 2–9 traits were also identified. The identification of few major, many minor M-QTLs and QTL × QTL interactions during the present study confirmed the complex and quantitative nature of drought tolerance in groundnut. This study suggests deployment of modern approaches like marker-assisted recurrent selection or genomic selection instead of marker-assisted backcrossing approach for breeding for drought tolerance in groundnut

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages