Improved DeTraC Binary Coyote Net-Based Multiple Instance Learning for Predicting Lymph Node Metastasis of Breast Cancer From Whole-Slide Pathological Images.

Background: Early detection of lymph node metastasis in breast cancer is vital for improving treatment outcomes and prognosis.

Methods: This study introduces an Improved Decompose, Transfer, and Compose Binary Coyote Net-based Multiple Instance Learning (ImDeTraC-BCNet-MIL) method for predicting lymph node metastasis from Whole Slide Images (WSIs) using multiple instance learning. The method involves segmenting WSIs into patches using Otsu and double-dimensional clustering techniques.

Unraveling the enigma: chronic kidney disease of unknown etiology and its causative factors with a specific focus on dissolved organic compounds in groundwater-reviews and future prospects.

Chronic kidney disease is globally recognized as a highly impactful non-communicable disease. The inability of early identification contributes to its high mortality rate and financial burden on affected individuals. Chronic kidney disease of uncertain etiology (CKDu) constitutes a significant global public health concern.

Exploring Pathogen Presence Prediction in Pastured Poultry Farms through Transformer-Based Models and Attention Mechanism Explainability.

In this study, we explore how transformer models, which are known for their attention mechanisms, can improve pathogen prediction in pastured poultry farming. By combining farm management practices with microbiome data, our model outperforms traditional prediction methods in terms of the F1 score-an evaluation metric for model performance-thus fulfilling an essential need in predictive microbiology. Additionally, the emphasis is on making our model's predictions explainable.

Experimental investigation of mechanical properties and multi-objective optimization of electronic, glass, and ceramic waste-mixed concrete.

The utilization of waste from various sources plays an important role in minimizing environmental pollution and civil construction costs. In this research, the mechanical properties of concrete were studied by mixing electronic waste (EW), glass powder (GW), and ceramic tile waste (CW). The effects of weight percentages of EW, GW, and CW are considered to investigate improvements in mechanical properties such as compressive strength (CS), split tensile strength (STS), and flexural strength (FS) of concrete.

Genome-wide identification and characterization of DIRIGENT gene family (CcDIR) in pigeonpea (Cajanus cajan L.) provide insights on their spatial expression pattern and relevance to stress response.

This study is a thorough characterization of pigeonpea dirigent gene (CcDIR) family, an important component of the lignin biosynthesis pathway. Genome-wide analysis identified 25 CcDIR genes followed by a range of analytical approaches employed to unravel their structural and functional characteristics. Structural examination revealed a classic single exon and no intron arrangement in CcDIRs contributing to our understanding on evolutionary dynamics.

Deep volcanic residual U-Net for nodal metastasis (Nmet) identification from lung cancer.

Lymph node metastasis detections are more clinically significant task associated with the presence and reappearance of lung cancer. The development of the computer-assisted diagnostic approach has greatly supported the diagnosis of human disorders in the field of medicine including lung cancer. Lung cancer treatment is possible if it is detected at the initial stage.

Predicting MIC and Deciphering Genomic Determinants of Antibiotic Resistance and Susceptibility.

spp., a leading cause of foodborne illness, is a formidable global menace due to escalating antimicrobial resistance (AMR). The evaluation of minimum inhibitory concentration (MIC) for antimicrobials is critical for characterizing AMR.

Spatio-temporal epidemiology and associated indicators of COVID-19 (wave-I and II) in India.

The spatio-temporal distribution of COVID-19 across India's states and union territories is not uniform, and the reasons for the heterogeneous spread are unclear. Identifying the space-time trends and underlying indicators influencing COVID-19 epidemiology at micro-administrative units (districts) will help guide public health strategies. The district-wise daily COVID-19 data of cases and deaths from February 2020 to August 2021 (COVID-19 waves-I and II) for the entire country were downloaded and curated from public databases.

Predicting foodborne pathogens and probiotics taxa within poultry-related microbiomes using a machine learning approach.

Background: Microbiomes that can serve as an indicator of gut, intestinal, and general health of humans and animals are largely influenced by food consumed and contaminant bioagents. Microbiome studies usually focus on estimating the alpha (within sample) and beta (similarity/dissimilarity among samples) diversities. This study took a combinatorial approach and applied machine learning to microbiome data to predict the presence of disease-causing pathogens and their association with known/potential probiotic taxa.

Identifying cancer risks using spectral subset feature selection based on multi-layer perception neural network for premature treatment.

Recently, human beings have been affected mainly by dreadful cancer diseases. Predicting cancer risk levels is a major challenge in biomedical research for feature selection and classification at the margins. To resolve this problem, we propose a Subset Clustering-Based Feature Selection using a Multi-Layer Perception Neural Network (SCFS-MLPNN).

Integration of miRNA dynamics and drought tolerant QTLs in rice reveals the role of miR2919 in drought stress response.

To combat drought stress in rice, a major threat to global food security, three major quantitative trait loci for 'yield under drought stress' (qDTYs) were successfully exploited in the last decade. However, their molecular basis still remains unknown. To understand the role of secondary regulation by miRNA in drought stress response and their relation, if any, with the three qDTYs, the miRNA dynamics under drought stress was studied at booting stage in two drought tolerant (Sahbaghi Dhan and Vandana) and one drought sensitive (IR 20) cultivars.

Geochemical fractionation, mobility of elements and environmental significance of surface sediments in a Tropical River, Borneo.

Miri River is a tropical river in Borneo that drains on flat terrain and urbanised area and debauches into the South China Sea. This paper documents the environmental status of this river, and provides an insight into the provenance using bulk chemistry of the sediments, and brings out the geochemical mobility, bioavailability, and potential toxicity of some critical elements based on BCR sequential extraction. The sediments are intense to moderately weathered and recycled products of Neogene sedimentary rocks.

Ensemble classifier fostered detection of arrhythmia using ECG data.

Electrocardiogram (ECG) is a non-invasive medical tool that divulges the rhythm and function of the human heart. This is broadly employed in heart disease detection including arrhythmia. Arrhythmia is a general term for abnormal heart rhythms that can be identified and classified into many categories.

Meta-Analysis of Microarray Data and Their Utility in Dissecting the Mapped QTLs for Heat Acclimation in Rice.

In the current global warming scenario, it is imperative to develop crops with improved heat tolerance or acclimation, for which knowledge of major heat stress-tolerant genes or genomic regions is a prerequisite. Though several quantitative trait loci (QTLs) for heat tolerance have been mapped in rice, candidate genes from these QTLs have not been reported yet. The meta-analysis of microarray datasets for heat stress in rice can give us a better genomic resource for the dissection of QTLs and the identification of major candidate genes for heat stress tolerance.

Development of an Atomic-Oxygen-Erosion-Resistant, Alumina-Fiber-Reinforced, Fluorinated Polybenzoxazine Composite for Low-Earth Orbital Applications.

An atomic-oxygen-erosion-resistant fluorinated benzoxazine resin and composite were developed. The benzoxazine resin, abbreviated as “BAF-oda-fu,” consists of four benzoxazine rings, and was synthesized from bisphenol AF (BAF), 4,4′-oxydianiline (oda), furfurylamine (fu), and paraformaldehyde. The resin was characterized by infrared spectroscopy (FT-IR), proton nuclear magnetic resonance spectroscopy (1H NMR), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA).

An ensemble learning approach to identify pastured poultry farm practice variables and soil constituents that promote prevalence.

Animal sourced foods including contaminated poultry meat and eggs contribute to human non-typhoidal salmonellosis, a foodborne zoonosis. Prevalence of in pastured poultry production systems can lead to contamination of the final product. Identification of farm practices that affect prevalence is critical for implementing control measures to ensure the safety of these products.

Artificial Intelligence Models for Zoonotic Pathogens: A Survey.

Zoonotic diseases or zoonoses are infections due to the natural transmission of pathogens between species (animals and humans). More than 70% of emerging infectious diseases are attributed to animal origin. Artificial Intelligence (AI) models have been used for studying zoonotic pathogens and the factors that contribute to their spread.

Preharvest Environmental and Management Drivers of Multidrug Resistance in Major Bacterial Zoonotic Pathogens in Pastured Poultry Flocks.

Due to nutritional benefits and perceived humane ways of treating the animals, the demand for antibiotic-free pastured poultry chicken has continued to be steadily rise. Despite the non-usage of antibiotics in pastured poultry broiler production, antibiotic resistance (AR) is reported in zoonotic poultry pathogens. However, factors that drive multidrug resistance (MDR) in pastured poultry are not well understood.

Identification of major candidate genes for multiple abiotic stress tolerance at seedling stage by network analysis and their validation by expression profiling in rice ( L.).

Unlabelled: A wealth of microarray and RNA-seq data for studying abiotic stress tolerance in rice exists but only limited studies have been carried out on multiple stress-tolerance responses and mechanisms. In this study, we identified 6657 abiotic stress-responsive genes pertaining to drought, salinity and heat stresses from the seedling stage microarray data of 83 samples and used them to perform unweighted network analysis and to identify key hub genes or master regulators for multiple abiotic stress tolerance. Of the total 55 modules identified from the analysis, the top 10 modules with 8-61 nodes comprised 239 genes.

Risk assessment in supply chains: a state-of-the-art review of methodologies and their applications.

The year 2020 can be earmarked as the year of global supply chain disruption owing to the outbreak of the coronavirus (COVID-19). It is however not only because of the pandemic that supply chain risk assessment (SCRA) has become more critical today than it has ever been. With the number of supply chain risks having increased significantly over the last decade, particularly during the last 5 years, there has been a flurry of literature on supply chain risk management (SCRM), illustrating the need for further classification so as to guide researchers to the most promising avenues and opportunities.

Healthcare Biclustering-Based Prediction on Gene Expression Dataset.

In this paper, we develop a healthcare biclustering model in the field of healthcare to reduce the inconveniences linked to the data clustering on gene expression. The present study uses two separate healthcare biclustering approaches to identify specific gene activity in certain environments and remove the duplication of broad gene information components. Moreover, because of its adequacy in the problem where populations of potential solutions allow exploration of a greater portion of the research area, machine learning or heuristic algorithm has become extensively used for healthcare biclustering in the field of healthcare.

A multi-echelon dynamic cold chain for managing vaccine distribution.

While cold chain management has been part of healthcare systems, enabling the efficient administration of vaccines in both urban and rural areas, the COVID-19 virus has created entirely new challenges for vaccine distributions. With virtually every individual worldwide being impacted, strategies are needed to devise best vaccine distribution scenarios, ensuring proper storage, transportation and cost considerations. Current models do not consider the magnitude of distribution efforts needed in our current pandemic, in particular the objective that entire populations need to be vaccinated.

Convalescent plasma bank facility location-allocation problem for COVID-19.

With convalescent plasma being recognized as an eminent treatment option for COVID-19, this paper addresses the location-allocation problem for convalescent plasma bank facilities. This is a critical topic, since limited supply and overtly increasing cases demand a well-established supply chain. We present a novel plasma supply chain model considering stochastic parameters affecting plasma demand and the unique features of the plasma supply chain.

Allele mining for a drought responsive gene determining root growth angle in donors of drought tolerance in rice ( L.).

Unlabelled: gene identified from a major QTL on chromosome 9 increases the root growth angle (RGA) and thus facilitates survival under drought and hence is an excellent candidate for rice improvement. Twenty-four major Indian upland and lowland genotypes including the 'yield under drought' (DTY) QTL donors were subjected to allele mining of (3058 bp) using four pairs of overlapping primers. A total of 216 and 52 SNPs were identified across all genotypes in the gene and coding region (756 bp) respectively with transversions 3.

Source of Post-Transplant Care and Mortality among Kidney Transplant Recipients Dually Enrolled in VA and Medicare.

Background And Objectives: Many kidney transplant recipients enrolled in the Veterans Health Administration are also enrolled in Medicare and eligible to receive both Veterans Health Administration and private sector care. Where these patients receive transplant care and its association with mortality are unknown.

Design, Setting, Participants, & Measurements: We conducted a retrospective cohort study of veterans who underwent kidney transplantation between 2008 and 2016 and were dually enrolled in Veterans Health Administration and Medicare at the time of surgery.