Immune digital twins for complex human pathologies: applications, limitations, and challenges.

Digital twins represent a key technology for precision health. Medical digital twins consist of computational models that represent the health state of individual patients over time, enabling optimal therapeutics and forecasting patient prognosis. Many health conditions involve the immune system, so it is crucial to include its key features when designing medical digital twins.

Profiling the bacterial microbiome diversity and assessing the potential to detect antimicrobial resistance bacteria in wastewater in Kimberley, South Africa.

Wastewater treatment plants (WWTPs) are hotspots for pathogens, and can facilitate horizontal gene transfer, potentially releasing harmful genetic material and antimicrobial resistance genes into the environment. Little information exists on the composition and behavior of microbes in WWTPs, especially in developing countries. This study used environmental DNA (eDNA) techniques to examine the microbiome load of wastewater from WWTPs.

Multiscale modelling of hepatitis B virus at cell level of organization.

Multiscale modelling is a promising quantitative approach for studying infectious disease dynamics. This approach garners attention from both individuals who model diseases and those who plan for public health because it has great potential to contribute in expanding the understanding necessary for managing, reducing, and potentially exterminating infectious diseases. In this article, we developed a nested multiscale model of hepatitis B virus (HBV) that integrates the within-cell scale and the between-cell scale at cell level of organization of this disease system.

Uncertainty quantification in multi-class image classification using chest X-ray images of COVID-19 and pneumonia.

This paper investigates uncertainty quantification (UQ) techniques in multi-class classification of chest X-ray images (COVID-19, Pneumonia, and Normal). We evaluate Bayesian Neural Networks (BNN) and the Deep Neural Network with UQ (DNN with UQ) techniques, including Monte Carlo dropout, Ensemble Bayesian Neural Network (EBNN), Ensemble Monte Carlo (EMC) dropout, across different evaluation metrics. Our analysis reveals that DNN with UQ, especially EBNN and EMC dropout, consistently outperform BNNs.

Investigation of red-emitting CaMoO: Eu phosphor by partitioning of substitutional PO ions via solid-state reaction method.

To investigate the impact of PO anionic groups, the trivalent europium ion-doped calcium molybdate (CaMoO-PO:xEu, where x = 0.5, 1.0, 1.

Increasing densities of Leucosidea sericea have minimal effects on grazing capacity and soil characteristics of a high-altitude communal rangeland at Vuvu, South Africa.

Increasing densities of woody plants, known as woody plant encroachment, is a phenomenon affecting savannas and grasslands in many parts of the world. Yet, these ecosystems sustain a significant proportion of the human population through the provision of ecosystem services, such as forage for livestock and wildlife production. While low to medium altitude rangelands are encroached by many species of woody plants, high altitude rangelands in southern Africa show increasing densities of Leucosidea sericea, a woody shrub or small to medium-sized tree.

Are earthworms the victim, facilitator or antidote of antibiotics and antibiotic resistance at the soil-animal-human interface? A One-Health perspective.

The transfer of antibiotics and antibiotic resistance (AR) to the soil systems poses ecological hazards to various organisms, including earthworms. Understanding the complex interactions between earthworms, antibiotics, and AR in the soil system requires a comprehensive assessment. Hence, the present review investigates the behaviour, fate, impacts, and mechanisms involved in the interaction of earthworms with antibiotics and AR.

An optimised and validated surrogate analyte A-TEEM-PARAFAC-PLS technique for detecting and quantifying the biological oxygen demand in surface water.

A 5-day test duration makes BOD measurement unsatisfactory and hinders the development of a quick technique. Protein-like fluorescence peaks show a strong correlation between the BOD characteristics and the fluorescence intensities. For identifying and measuring BOD in surface water, a simultaneous absorbance-transmittance and fluorescence excitation-emission matrices (A-TEEM) method combined with PARAFAC (parallel factor) and PLS (partial least squares) analyses was developed using a tyrosine and tryptophan (tyr-trpt) mix as a surrogate analyte for BOD.

Deep learning and content-based filtering techniques for improving plant disease identification and treatment recommendations: A comprehensive review.

The importance of identifying plant diseases has risen recently due to the adverse effect they have on agricultutal production. Plant diseases have been a big concern in agriculture, as they affect crop production, and constitute a major threat to global food security. In the domain of modern agriculture, effective plant disease management is vital to ensure healthy crop yields and sustainable practices.

Emerging organic contaminants in drinking water systems: Human intake, emerging health risks, and future research directions.

Few earlier reviews on emerging organic contaminants (EOCs) in drinking water systems (DWS) focused on their detection, behaviour, removal and fate. Reviews on multiple exposure pathways, human intake estimates, and health risks including toxicokinetics, and toxicodynamics of EOCs in DWS are scarce. This review presents recent advances in human intake and health risks of EOCs in DWS.

Evidence for Chiral Wobbler in Nuclei.

Three ΔI=1 bands with the πg_{9/2}⊗νg_{9/2} configuration have been identified in _{35}^{74}Br_{39}. Angular distribution, linear polarization, and lifetime measurements were performed to determine the multipolarity, type, mixing ratio, and absolute transition probability of the transitions. By comparing these experimental observations with the corresponding fingerprints and the quantum particle rotor model calculations, the second and third lowest bands are, respectively, suggested as the chiral partner and one-phonon wobbling excitation built on the yrast band.

Emerging organic contaminants in the soil-plant-receptor continuum: transport, fate, health risks, and removal mechanisms.

There is a lack of comprehensive reviews tracking emerging organic contaminants (EOCs) within the soil-plant continuum using the source-pathway-receptor-impact-mitigation (SPRIM) framework. Therefore, this review examines existing literature to gain insights into the occurrence, behaviour, fate, health hazards, and strategies for mitigating EOCs within the soil-plant system. EOCs identified in the soil-plant system encompass endocrine-disrupting chemicals, surfactants, pharmaceuticals, personal care products, plasticizers, gasoline additives, flame retardants, and per- and poly-fluoroalkyl substances (PFAS).

Exploring the cognitive development of children born to adolescent mothers in South Africa.

Unlabelled: This study explores the cognitive development of children born to adolescent mothers within South Africa compared to existing reference data, and explores development by child age bands to examine relative levels of development. Cross-sectional analyses present data from 954 adolescents (10-19 years) and their first-born children (0-68 months). All adolescents completed questionnaires relating to themselves and their children, and standardized child cognitive assessments (Mullen Scales of Early Learning) were undertaken.

The soil-microbe-plant resistome: A focus on the source-pathway-receptor continuum.

The One World, One Health concept implies that antibiotic resistance (AR) in the soil-microbe-plant resistome is intricately linked to the human resistome. However, the literature is mainly confined to sources and types of AR in soils or microbes, but comprehensive reviews tracking AR in the soil-microbe-plant resistome are limited. The present review applies the source-pathway-receptor concept to understand the sources, behaviour, and health hazards of the soil-microbe-plant resistome.

Oklo natural fission reactors and dynamical models of dark energy.

Bounds on the cosmological variation of the fine structure constant α inferred from Oklo neutron capture data are sometimes taken cum grano salis. It is possible to quantify uncertainties related to the treatment of excitation, deformation and the Coulomb interaction. On the basis of this analysis, it is concluded that Oklo data imply the relative change in α over the last 1.

Detection and Quantification of Bisphenol A in Surface Water Using Absorbance-Transmittance and Fluorescence Excitation-Emission Matrices (A-TEEM) Coupled with Multiway Techniques.

In the present protocol, we determined the presence and concentrations of bisphenol A (BPA) spiked in surface water samples using EEM fluorescence spectroscopy in conjunction with modelling using partial least squares (PLS) and parallel factor (PARAFAC). PARAFAC modelling of the EEM fluorescence data obtained from surface water samples contaminated with BPA unraveled four fluorophores including BPA. The best outcomes were obtained for BPA concentration (R = 0.

Air pollution particulate matter (PM2.5) prediction in South African cities using machine learning techniques.

Background: Air pollution contributes to the most severe environmental and health problems due to industrial emissions and atmosphere contamination, produced by climate and traffic factors, fossil fuel combustion, and industrial characteristics. Because this is a global issue, several nations have established control of air pollution stations in various cities to monitor pollutants like Nitrogen Dioxide (NO2), Ozone (O3), Sulfur Dioxide (SO2), Carbon Monoxide (CO), Particulate Matter (PM2.5, PM10), to notify inhabitants when pollution levels surpass the quality threshold.

Supervised machine learning models for depression sentiment analysis.

Introduction: Globally, the prevalence of mental health problems, especially depression, is at an all-time high. The objective of this study is to utilize machine learning models and sentiment analysis techniques to predict the level of depression earlier in social media users' posts.

Methods: The datasets used in this research were obtained from Twitter posts.

A clay-coal fly ash based dual hydraulic-reactive liner for controlling acid mine drainage.

Hydraulic liners are used to restrict hazardous leachates such as acid mine drainage (AMD) from entering the hydrogeological system. In this study, we hypothesized that: (1) a compacted mix ratio of natural clay and coal fly ash with a hydraulic conductivity of at most 1 × 10 ms can be achieved, and (2) mixing clay and coal fly ash in the right proportion can result in increased contaminant removal efficiency of a liner system. The effects of adding coal fly ash to clay on the mechanical behavior, contaminant removal efficiency, and saturated hydraulic conductivity of the liner were investigated.

The utilisation of domestic goats in rural and peri-urban areas of KwaZulu-Natal, South Africa.

Goats are a common ruminant in livestock husbandry systems in communal areas of southern Africa, but less so in peri-urban areas. While dynamics of goat farming in the former are relatively well-understood, little is known about it in peri-urban environments. We investigated the contribution of small-scale farming of goats to household livelihoods in rural and peri-urban areas in KwaZulu-Natal Province of South Africa.

Remote Sensing Application in Mountainous Environments: A Bibliographic Analysis.

Advancement in remote sensing platforms, sensors, and technology has significantly improved the assessment of hard-to-access areas, such as mountains. Despite these improvements, Africa lags in terms of research work published. This is of great concern as the continent needs more research to achieve sustainable development.