Browse Articles

A manually driven centrifugal microfluidic LAMP platform for rapid visual detection of waterborne pathogens in aquatic sports

4D printing of trigger-free shape-memory hydrogels towards self-adaptive substrates for bioelectronics

Magnetic field sensing of 3D printed Halbach arrays

Abstract This paper investigates magnetic field amplification in Halbach arrays. A Halbach array, composed of permanent magnets, is arranged to produce a strong magnetic field on one side and a weak field on the other. This configuration has numerous scientific and engineering applications. The literature review surveys representative implementations. In this work, we propose and validate a cost-effective approach for designing and fabricating Halbach magnet arrays. Specifically, in our experiments, we employ a low-cost Hall-effect sensor to measure the Halbach array’s magnetic flux density. Hall-effect sensors are well suited for measuring magnetic fields owing to their accuracy, ease of integration, low cost, and simplicity. Thus, analytical expressions for the magnetic flux density are derived from the magnetic scalar potential using the magnetostatic approximation to Maxwell’s equations and a Fourier-series expansion. We then determine and compare the magnetic flux density through experimental measurements, numerical simulations, and analytical calculations. Numerical simulations are performed using the open-source Python package Magpylib , followed by an exponential regression analysis of both experimental and simulated data. These procedures can be implemented without resorting to costly full three-dimensional magnetostatic simulations or specialized laboratory equipment and may be suited for imperfect physical models by inclusion of experimentally-fitted adjustment proportionality factor $$\xi$$ . Notably, the maximum relative error between the simulation and experimental results is approximately 11% for the Halbach array with large size permanent magnets.

Widespread land surface cooling from paddy rice cultivation revealed by global satellite mapping

Photovoltaic power interval prediction with conditional error dependency using Bayesian optimized deep learning

Abstract Accurate photovoltaic (PV) power forecasting serves as a critical foundation for economic dispatch and reliable grid operation. To address the inherent uncertainty in PV power generation, this study proposes a short-term PV power interval prediction method based on Bayesian-optimized CNN-BiLSTM-attention (BO-CNN-BiLSTM-attention) that accounts for conditional dependencies in prediction errors. The methodology comprises three main stages: first, PV output data undergoes preprocessing and feature selection. Second, a Bayesian-optimized CNN-BiLSTM-attention model achieves high-precision point forecasting for target time periods. Finally, the K-shape time series clustering algorithm matches point predictions with temporally similar historical data, while adaptive bandwidth kernel density estimation models the probability distribution of prediction errors from similar patterns, thereby enabling interval prediction. Experimental validation on a photovoltaic plant in Xinjiang, China demonstrates that the proposed method achieves superior prediction accuracy compared to various single and ensemble forecasting models, while outperforming multiple interval construction approaches in terms of prediction effectiveness.

Noise-induced tipping of Atlantic Meridional Overturning Circulation under climate mitigation scenarios

Methodological guidance on implementing propensity score matching in observational studies of kidney transplantation

Biradical-mediated synergistic electrocatalysis using metal-free redox molecular catalysts

Solvent-induced photophysical properties and stability of clonazepam and Chlordiazepoxide

Impact and cost-effectiveness of the community-led AMETHIST intervention among female sex workers in Zimbabwe

Abstract Female sex workers (FSW) face high HIV risk of HIV transmission and acquisition. The AMETHIST (“Adapted Microplanning: Eliminating Transmissible HIV In Sex Transactions”) trial enhanced Zimbabwe’s Key Populations (KP) programme by providing targeted, community-based support for FSW. We used the HIV Synthesis Model to assess its long-term impact and cost-effectiveness. Given USAID’s major role in funding, we also evaluated the effects of ending US support on the KP programme. We modelled a KP programme from 2010. From 2024 we compared (i) continuation of KP programme to (ii) continuation of KP programme + ‘AMETHIST’ intervention. We assessed HIV outcomes in 2030 and conducted cost-effectiveness analysis over a 50 year time horizon. Similar analyses were undertaken comparing continuation of the current KP programme to discontinuation. Here we show that AMETHIST had greater positive impact than the KP programme alone; a higher proportion of FSW tested for HIV in the past year, were diagnosed, on ART and had undetectable viral loads compared to the KP programme alone. Disability adjusted life years were averted with AMETHIST and it was cost-saving within 15 years. Continuing the current KP programme was also cost-saving compared to discontinuation of the KP programme.

Comparative assessment of landslide susceptibility in Fugu town using machine learning models at multiple grid resolutions

Two- and many-body physics of ultracold molecules dressed by dual microwave fields

The nephroprotective potential of russelioside B isolated from Caralluma quadrangula in gentamicin-induced acute kidney injury via modulation of SIRT-1 pathway

Abstract Using nephrotoxic antibiotics such as gentamicin may result in acute renal damage. This study aimed to investigate the nephroprotective effect of russelioside B (RB) isolated from C ralluma quadrangula (Forssk.) N.E.Br against gentamicin-induced acute kidney injury. Twenty male rats were randomly distributed into four groups (five animals each). Normal, Gentamicin, Genta + 50RB, and Genta + 75RB groups. The RB was taken orally for 3 days at a dose of 50 and 75 mg/Kg B.wt) before injection with gentamicin, followed by the same dose along with gentamicin injection (I/P) for 7 consecutive days. At the end of the study, kidneys and blood samples were collected. The blood samples were tested for BUN and Creatinine. Tissue samples were tested for SOD, MDA, and NO. Genes expression of IGF-1, iNOS and Bcl2 by RT-PCR were tested. Histopathological evaluation was performed along with immunohistochemistry for SIRT1, NQO1, Nrf-2, TNF-α, and NF-қB. RB treated groups showed reduction in serum BUN and creatinine levels. Along with reduced MDA and nitric oxide while there was an elevation in SOD, SIRT1, NQO-1, Nrf2, and IGF-1 with a decrease in TNF-α, NF-қB and iNOS. Confirming the anti-oxidant and anti-inflammatory properties of RB. RB treatment resulted in elevation in the anti-apoptotic protein Bcl2 and reduction in BAX confirming the anti-apoptotic potential of RB. Gentamicin-induced histopathological alterations were also alleviated with RB treatment. The findings of the study proved the nephroprotective potential of RB.

Inhibiting translation elongation by reducing eIF5A activity induces feedback inhibition of initiation, limiting tumour cell proliferation

Abstract Cancer development is associated with dysregulation of the translatome, and targeting canonical eukaryotic initiation and elongation factors can offer treatment avenues for various neoplasms. Emerging evidence indicates that dysregulated mRNA elongation, involving alterations in eEF2 activity and eIF5A expression, also contributes to tumour cell growth. In this study, we investigate whether targeting eIF5A with the inhibitor GC7 is a viable strategy to curtail aberrant cell growth. Our findings demonstrate that inhibiting elongation by reducing eIF5A activity induces feedback inhibition of initiation through eIF2α phosphorylation, decreasing ternary complex formation and shutting down bulk protein synthesis. Employing dynamic SILAC, we identify proteins impacted by reduced eIF5A activity, and show their decreased translation results from feedback inhibition to initiation or other processes downstream of eIF5A. Decreased eIF5A activity impairs mitochondrial function, which activates signalling through HRI to eIF2α phosphorylation, reducing cancer cell proliferation. These effects are reversed by treatment with the integrated stress response inhibitor, implying that the impact of GC7 on cancer cell proliferation is mediated via translation initiation rather than elongation inhibition. These data suggest that eIF5A inhibition could be used to target cancer cells that depend on mitochondrial function for their proliferation and survival.

Dynamic behavior and micro–meso scale fracture mechanisms of sandstone under long-term water immersion

Deep-subwavelength ultra-low and ultra-broadband acoustic-black-hole metamaterials

Enhanced mechanical and thermal properties of polyester/glass/sheep wool fiber hybrid composites by successful replacement glass with wool

Evaluating transportability of in vitro cellular models to in vivo human phenotypes using gene perturbation data

Abstract Gene perturbation screens (e.g. CRISPR-Cas9) assess the impact of gene disruption on in-vitro cellular phenotypes (e.g., proliferation, anti-viral response). In-vitro experiments can be useful models for in-vivo (organismal) phenotypes (e.g., immune cell anti-viral response and infectious diseases). However, assessing whether an in-vitro cellular model effectively captures in-vivo biology is challenging. An in-vitro model is ‘transportable’ to an in-vivo phenotype if perturbations impacting the in-vitro phenotype also impact the in-vivo phenotype with mechanism-consistent directionality and effect sizes. We propose a framework; Gene Perturbation Analysis for Transportability (GPAT), to assess model transportability using gene perturbation effect estimates from perturbation screens (in-vitro) and loss-of-function burden tests (in-vivo). In hypothesis-driven analyses, GPAT provides evidence for model transportability of higher lysosomal cholesterol accumulation in-vitro to lower human plasma LDL-cholesterol (P = 0.0006), consistent with the known role of lysosomes in lipid biosynthesis. In contrast, there was limited evidence for other putative in-vitro models. In hypothesis-free analyses, we find evidence for transportability of cancer cell line proliferation to in-vivo human plasma cellular phenotypes (e.g. erythroleukemia proliferation and plasma lymphocyte percentage). Here we show that perturbation data can be used to evaluate transportability of in-vitro cellular models, informing assay prioritisation and supporting novel hypothesis generation.

Prediction of rapid chloride permeability using silica fume, fly ash, GGBS and micro fibers based geopolymer concrete

Environmental exposures associated with the gut microbiome and resistome of pregnant women and children in Northwest Ecuador

Abstract Inadequate water, sanitation, and hygiene (WASH) infrastructure may increase exposure to antimicrobial resistance (AMR). In addition, close human-animal interactions and unregulated antibiotic use in livestock facilitate the spread of resistant bacteria. We use metagenomic sequence data and multivariate models to assess how animal exposure and WASH conditions affect the gut resistome and microbiome in 53 pregnant women and 84 children in Ecuador. Here we show improving WASH infrastructure and managing animal exposure may be important in reducing AMR but could also reduce taxonomic diversity in the gut. Escherichia coli , Klebsiella pneumoniae , and clinically relevant antimicrobial resistance genes (ARGs) are detected across all age groups, but the highest abundance is found in children compared to mothers. In mothers, higher animal exposure trends towards a higher number of unique ARGs compared to low animal exposure and is significantly associated with greater taxonomic diversity. In addition, mothers with sewer systems or septic tanks and piped drinking water have fewer unique ARGs compared to those without, and mothers with longer duration of drinking water access have lower total ARG abundance. In contrast, few associations are observed in children, likely due to the dynamic nature of the gut microbiome during early childhood.