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Graph feature selection for enhancing radiomic stability and reproducibility across multiple institutions in head and neck cancer
Folate-based binuclear Mn(II) chelates with 2,2’-bipyridine/1,10-phenanthroline as targeted anticancer agents for colon cancer cells
Abstract Researchers have shown significant interest in the chemistry of mixed ligand transition metal chelates due to their diverse applications and bonding features. Herein, we have reported the synthesis of two new binuclear Mn(II) chelates with the composition of [Mn2(FA)(Bpy)2(H2O)2Cl2].7H2O (Chelate 1) and [Mn2(FA)(Phen)2(H2O)2Cl2].7H2O (Chelate 2) (where, FA = folate anion, Bpy = 2,2’-bipyridine, Phen = 1,10-phenanthroline). The folate anion acts as a bridging ligand to obtain the binuclear complexes with the suggested composition. The chelates have been characterized by using elemental analysis, spectroscopic (FTIR, UV-vis), EI-MS and TGA techniques. Further, the results from density functional theory (DFT) computations support well the suggested structures, which indicate the development of distorted octahedral geometries around each Mn(II) center for both binuclear complexes. The sulforhodamine B (SRB) assay was used to assess the cytotoxicity of the chelates against a series of folate receptor-positive and -negative cell lines. The prepared chelates exhibit significant cytotoxic effects against folate receptor-positive cell lines, with colon cancer HCT116 cells being the most affected. Furthermore, the anticancer mechanism of action on the HCT116 cell line was investigated by analyzing the wound healing, cell cycle profile, expression of pro-apoptotic and anti-apoptotic proteins, as well as examining the morphological changes in treated cells. The results provided compelling evidence of binuclear Mn(II) chelates-induced cellular and nuclear alterations.
Investigating the wave profiles to the linear quadratic model in mathematical biology
A large-scale case-control study on the association between dietary fat quality indices and risk of breast cancer
Significance of kidney and spleen volumes analyzed via three-dimensional computed tomography prior to allogeneic stem cell transplantation
Integrative network pharmacology and multi-omics reveal anisodamine hydrobromide’s multi-target mechanisms in sepsis
Effect of analgesic treatments on voluntary activity, mechanical sensitivity and muscle regeneration after cardiotoxin injection in mice
Mixture-of-experts graph transformers for interpretable particle collision detection
Physicists should revel in the diversity of ways to understand quantum mechanics
Higher glass transition temperatures reduce thermal stress cracking in aqueous solutions relevant to cryopreservation
Malaria infection prevalence and diagnostic performance of the Abbott Bioline Malaria Ag P.f/Pan rapid test in rural populations of Central Cameroon
Abstract In Cameroon, the management of uncomplicated malaria cases in the communities and in low-resource health facilities rely on the use of reliable rapid diagnostic tests (RDTs). This work was undertaken to determine the trend in human malaria infection in rural settings of Central Cameroon and assess the diagnostic performance of Abbott Bioline Malaria Ag P.f/Pan RDT recommended by the National Malaria Control Programme (NMCP). Cross-sectional surveys were conducted in March 2022 and May 2024. Plasmodium infection was detected using RDT and microscopy techniques, and with real-time PCR for validation of discordant results. Sensitivity (Se), specificity (Sp), positive and negative predictive values, positive and negative likelihood ratios (LR + and LR-), accuracy and agreement were calculated to assess the performance of the RDT. Plasmodium infection prevalence was 64.9% and 71.7% by microscopy and RDT, respectively, Plasmodium falciparum being the predominant species (microscopy:97.48%). With microscopy as reference, the RDT showed high sensitivity (Se:93.37%; CI:91.15%-95.77%) and low specificity (Sp: 68.50%; CI:62.40%-74.17%) for the detection of P. falciparum infection. The positive and negative predictive values were respectively 84.43% (CI:81.01%-87.46%) and 85.71% (CI:80.13%-90.22%). The RDT showed a small positive likelihood ratio (LR + = 2.96; CI:2.47-3.5734), a good negative likelihood ratio (LR-=0.09; CI:0.06–0.13) and moderate agreement (k = 0.652; CI:0.593–0.710; P < 0.001) with microscopy. The RDT showed higher sensitivity (81.48% vs. 48.14%), accuracy (0.75 and vs. 0.50), and agreement (AC1 = 0.715 vs. 0.371) than microscopy. The Abbott Bioline Malaria Ag P.f/Pan RDT demonstrated a high level of agreement with the most sensitive qPCR technique compared to microscopy. These findings further support its use as a reliable malaria diagnostic tool in the highly endemic setting of Central Cameroon.
The retina as a window into detecting subclinical cardiovascular disease in type 2 diabetes
Abstract Individuals with Type 2 Diabetes (T2D) are at high risk of subclinical cardiovascular disease (CVD), potentially detectable through retinal alterations. In this single-centre, prospective cohort study, 255 asymptomatic adults with T2D and no prior history of CVD underwent echocardiography, non-contrast coronary computed tomography and cardiovascular magnetic resonance. Retinal photographs were evaluated for diabetic retinopathy grade and microvascular geometric characteristics using deep learning (DL) tools. Associations with cardiac imaging markers of subclinical CVD were explored. Of the participants (aged 64 ± 7 years, 62% males); 200 (78%) had no diabetic retinopathy and 55 (22%) had mild background retinopathy. Groups were well-matched for age, sex, ethnicity, CV risk factors, urine microalbuminuria, and serum natriuretic peptide and high-sensitivity troponin levels. Presence of retinopathy was associated with a greater burden of coronary atherosclerosis (coronary artery calcium score ≥ 100; OR 2.63; 95% CI 1.29–5.36; P = 0.008), more concentric left ventricular remodelling (OR 3.11; 95% CI 1.50–6.45; P = 0.002), and worse global longitudinal strain (OR 2.32; 95% CI 1.18–4.59; P = 0.015), independent of key co-variables. Early diabetic retinopathy is associated with a high burden of coronary atherosclerosis and markers of early heart failure. Routine diabetic eye screening may serve as an effective alternative to currently advocated screening tests for detecting subclinical CVD in T2D, presenting opportunities for earlier detection and intervention.
The need for guardrails with large language models in pharmacovigilance and other medical safety critical settings
Efficacy of Stb resistance genes and pathotype diversity in Zymoseptoria tritici from Ethiopia
Abstract Zymoseptoria tritici, the causal agent of Septoria tritici blotch (STB) in bread wheat (Triticum aestivum), leads to significant global yield losses. Resistance breeding is vital for managing STB, but there is limited information on Z. tritici infection behaviour in Ethiopia. This study examined the virulence variability of Z. tritici isolates from Ethiopia’s Central Highlands and evaluated the effectiveness of known wheat STB-resistance genes. Eight wheat lines were tested against six Z. tritici isolates, showing significant differences (p < 0.0001) in necrotic leaf area (%NLA) and pycnidia coverage (%PC) among the tested Z. tritici isolates, wheat lines and their interactions. Wheat genotype TE9111 exhibited specific resistance to 50% of the isolates, while Taichung 29 showed no resistance. Isolate ZSE158 was the most aggressive, causing 61.4% PC and 54% NLA. The Ethiopian isolates displayed broad virulence against resistance genes, including Stb2 – Stb7. TE9111, carrying Stb11, showed resistance to 50% of isolates, making it a valuable source for resistance breeding against STB. This study identified highly virulent pathogen isolates useful for wheat germplasm screening for STB resistance and also key resistance source materials for use in wheat resistance breeding in Ethiopia.
Towards more effective nature-based climate solutions in global forests
A pilot study on the hemodynamic effects of negative pressure ventilation in patients after cardiac surgery focussing on right ventricular function
Reliability enhancement of EM-based tuning of microwave components using regularized operating band scanning
Abstract Numerical optimization is ubiquitous in contemporary microwave passive component design. Reliable quantification of electromagnetic (EM) cross-coupling, substrate losses, or environmental effects (e.g., connectors, housing) is impossible using analytical or equivalent network models. Consequently, the designs rendered using such tools must be further tuned at the EM simulation level. Although local algorithms are predominantly employed for this purpose, they are likely to fail if the starting point is of insufficient quality. On the other hand, global search techniques are associated with tremendous computational expenses. This study suggests an innovative technique for immunizing local algorithms against poor starting points, enabling their quasi-global search capability. The presented methodology reformulates the underlying optimization task by evaluating the circuit performance concerning the target operating bands scanned within the predefined ranges and by adding penalty factors proportional to the distance between the original and the scanned targets. The penalized objective is computed as the minimum of the above combination over the entire scanning range. As a result, the design specifications become attainable through local optimization over considerably broader frequency spectra at the expense of only a slight increase in the algorithm running costs. The presented approach is comprehensively verified using several microstrip components and the sensitivity-based routine as the search algorithm. The results unanimously showcase the ability of the procedure to allocate the optimum even under troublesome scenarios (poor initial points), which are unmanageable by conventional algorithms.
Genetic diversity and structure of Asian cowpea germplasm
Abstract Cowpea (Vigna unguiculata L. Walp., 2n = 2x = 22) is a vital dryland legume crop, renowned for its affordable dietary protein and essential nutrients for humans and animals. Cowpea originated in Africa and spread to various parts of the world through human migration, eventually reaching Asia. However, genetic diversity and structure in Asia cowpea remain poorly understood. This study utilized 6334 SilicoDArT and 14,482 single nucleotide polymorphism (SNP) markers to assess the genetic diversity and population structure of 405 cowpea accessions from 17 different countries, sourced from the National Agriculture and Food Research Organization (NARO) genebank in Japan. We used population structure, principal component analysis, discriminant analysis of principal components, and phylogenetic tree analysis to group the accessions into two main genetic populations. The accessions were further classified into six subgroups of African and Asian populations, corresponding to the geographical origins of the accessions. South Asian accessions showed the highest differentiation, with Nepalese accessions forming a distinct group along with Japanese accessions, highlighting that the rich genetic resources preserved within these regions may harbor valuable traits for breeding. In contrast, Southeast Asian and West African accessions exhibited low to moderate differentiation, suggesting recently shared genetic ancestry. AMOVA demonstrated that most genetic variation existed within accessions, while variation between populations was minimal. These findings highlight the rich genetic potential within the Asian cowpea germplasm, particularly in Nepalese and Japanese accessions. This study provides critical insights into breeding strategies aimed at enhancing the adaptability and productivity of cowpea in diverse environments.
A new band selection approach integrated with physical reflectance autoencoders and albedo recovery for hyperspectral image classification
Abstract Hyperspectral imaging has emerged as a powerful tool for remote sensing applications, offering rich spectral information across a broad electromagnetic spectrum. However, the high dimensionality of hyperspectral data poses significant challenges in analysis and interpretation. In this study, we propose a novel approach for hyperspectral image processing, focusing on dimensionality reduction, albedo recovery, and subsequent classification. Our method begins with a grouping strategy based on the electromagnetic spectrum that considers the images’ physical properties, facilitating the segmentation of hyperspectral data into meaningful spectral bands. This grouping reduces the dimensionality of the data and preserves crucial spectral information. Subsequently, we integrate autoencoders to incorporate non-linear transformations in the feature extraction phase, thereby improving the model’s capacity to learn intricate patterns within the data. A key goal of our methodology is to effectively embed spatial information into the representation. Albedo recovery is employed aimed at improving spatial resolution while retaining spectral fidelity. By leveraging the reduced-dimensional representation obtained through grouping and autoencoders, we reconstruct the hyperspectral image with enhanced spatial details, thereby facilitating more accurate interpretation and analysis. To assess the performance of the proposed approach, we perform experiments using three standard hyperspectral datasets: Indian Pines, University of Pavia, and Salinas.