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Pan-cancer landscape of ITGAV and its potential role in gastric cancer
Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures
PEGylated liposomal metformin overcomes pharmacokinetic barriers to trigger potent mitochondrial disruption and cell cycle arrest in hepatocellular carcinoma
Abstract This study presents a comprehensive experimental and computational evaluation of PEGylated liposomal metformin as a nanocarrier-based therapeutic strategy for hepatocellular carcinoma (HCC). Liposomal formulations were prepared via thin-film hydration, yielding spherical, well-dispersed vesicles with high encapsulation efficiency (> 90%) and a mean hydrodynamic diameter of 177.2 ± 30.2 nm. PEGylation and metformin loading induced significant physicochemical alterations, as confirmed by differential scanning calorimetry and FTIR spectroscopy, reflecting increased bilayer fluidity and headgroup interactions. Cytotoxicity assays revealed a substantial enhancement in antitumor potency: PEGylated liposomal metformin reduced the IC₅₀ against HepG2 cells to 118.76 μg/mL compared to 2392.81 μg/mL for free metformin—representing a > 20-fold improvement. In Vero cells, IC₅₀ values were 137.13 μg/mL and 2113.86 μg/mL, respectively, yielding a selectivity index of 1.15. Apoptosis analysis demonstrated increased early and late apoptotic populations, with PEGylated formulations inducing total apoptosis rates of 20.67% in HepG2 cells. Cell cycle profiling revealed marked G₀/G₁ arrest, with 78.12% accumulation versus 58.21% in untreated controls. DNA fragmentation analysis via comet assay further supported elevated genotoxic effects in cancer cells. Molecular docking and 100 ns molecular dynamics simulations confirmed stable binding of metformin to mitochondrial Complex I and CDK4/cyclin D3, with a total MM-PBSA binding energy of − 27.33 kcal/mol in the CDK4 complex. These findings demonstrate that PEGylated liposomal encapsulation substantially enhances the cytotoxic profile of metformin, supporting its advancement as a targeted nanotherapeutic candidate for HCC.
Network-based approach identifies key genes associated with tumor heterogeneity in HPV positive and negative head and neck cancer patients
Abstract Head and Neck Squamous Cell Carcinoma (HNSCC) is the seventh most prevalent cancer worldwide and is classified as human papillomavirus (HPV) positive or negative. Substantial heterogeneity has been observed in the two groups, posing a significant clinical challenge. In the disease context, global transcriptional changes are likely driven by a few key genes that reflect the disease etiology more accurately compared to differentially expressed genes (DEGs). We implemented our network-based tool PathExt on 501 TCGA-HNSCC samples (64 HPV positive & 437 HPV negative) to characterize central genes in two subtypes, where in subtype 1, HPV-positive samples were considered as cases and negative as controls, and vice versa in subtype 2. We also identified DEGs and performed several analyses on multiple benchmarking datasets to compare the biology of central genes with DEGs. PathExt key genes performed better with respect to DEGs in both subtypes in recapitulating disease etiology. Gene ontology analysis using central genes revealed shared biological processes such as “epithelial cell proliferation” as well as subtype-specific processes (immune- and metabolic-related processes in subtype 1 and peptide-related processes in subtype 2). However, in the case of DEGs, no subtype-specific processes were seen. Additionally, PathExt central genes did better than DEGs on external validation datasets that were specific to HNSCC and included HNSCC-specific cancer driver genes, FDA-approved therapeutic targets, and pan-cancer tumor suppressor genes. Unlike DEGs, central genes exhibit significant expression in various cell types, enrichment for cancer hallmarks, and mutated protein systems. Central gene expression-based machine learning model shows better performance than DEGs in classifying responders/non-responders with 0.74 AUROC. Lastly, the top 10 potential therapeutic targets and drugs were proposed. Overall, we observed PathExt as a complementary approach to DEGs, characterizing common and HNSCC subtype-specific key genes associated with distinct HNSCC molecular subtypes.
Targeting de novo purine biosynthesis for tuberculosis treatment
BIM-driven digital twin for demolition waste management of existing residential buildings
Abstract With the accelerated development of urbanisation, the construction industry has significantly contributed to environmental degradation due to its substantial energy consumption and construction and demolition (C&D) waste generation. By assessing the ecological impact of the construction industry alongside existing demolition waste management practices, this article aims to develop a conceptual framework to optimise building demolition, transportation, and recycling processes. This study integrates a BIM-driven Digital Twin framework into C&D waste management, aiming to maximise economic benefits and advance the sustainable development of construction practices. Specifically, it simulates the demolition process of an existing townhouse in Washington, D.C., using BIM-Navisworks software and employs a digital twin to update demolition data in real-time. This approach optimises the classification and transportation of demolition waste, enhancing efficiency and sustainability. The study validates the proposed conceptual framework for building demolition waste management through case simulation. Additionally, it utilises BIM-Dynamo software to analyse the economic benefits of demolition waste recycling, demonstrating that a high recycling rate can significantly enhance economic outcomes. The proposed framework leverages BIM technology to optimise demolition and recycling processes, providing a valuable reference for selecting demolition waste management strategies for other buildings.
R9AP is a common receptor for EBV infection in epithelial cells and B cells
The ratio of serum glucose to potassium is associated with poor prognosis in patients with severe acute myocardial infarction
Major expansion in the human niche preceded out of Africa dispersal
Abstract All contemporary Eurasians trace most of their ancestry to a small population that dispersed out of Africa about 50,000 years ago (ka)1–9. By contrast, fossil evidence attests to earlier migrations out of Africa10–15. These lines of evidence can only be reconciled if early dispersals made little to no genetic contribution to the later, major wave. A key question therefore concerns what factors facilitated the successful later dispersal that led to long-term settlement beyond Africa. Here we show that a notable expansion in human niche breadth within Africa precedes this later dispersal. We assembled a pan-African database of chronometrically dated archaeological sites and used species distribution models (SDMs) to quantify changes in the bioclimatic niche over the past 120,000 years. We found that the human niche began to expand substantially from 70 ka and that this expansion was driven by humans increasing their use of diverse habitat types, from forests to arid deserts. Thus, humans dispersing out of Africa after 50 ka were equipped with a distinctive ecological flexibility among hominins as they encountered climatically challenging habitats, providing a key mechanism for their adaptive success.
Grid-connected PV inverter system control optimization using Grey Wolf optimized PID controller
Batch evaluation of collective owned commercialised construction land using machine learning
Powerful satellite will map changes on Earth in stunning detail — down to a centimetre
Retraction Note: Human fetal cerebellar cell atlas informs medulloblastoma origin and oncogenesis
LOMS.cz computational platform for high-throughput classical and combinatorial Judd-Ofelt analysis and rare-earth spectroscopy
Abstract We present LOMS.cz ( L uminescence, O ptical and M agneto-optical S oftware), an open-source computational platform that addresses the long-standing challenge of standardizing Judd-Ofelt (JO) calculations in rare-earth spectroscopy. Despite JO theory’s six-decade history as the fundamental framework for understanding $$4f\leftrightarrow 4f$$ transitions, the field lacks standardized computational methodologies for precise and reproducible parameter determination. LOMS integrates three key innovations: (1) automated computation of JO parameters, transition probabilities, branching ratios, and theoretical radiative lifetimes, (2) a dynamically expanding database of experimentally validated parameters enabling direct comparison between computed and empirical results, and (3) a novel Combinatorial JO (C-JO) analysis algorithm that systematically identifies optimal absorption band combinations to ensure reliable parameter extraction. As a proof-of-concept, we demonstrate how this computational framework enables rapid screening of spectroscopic parameters, allowing researchers to predict optical properties with enhanced reliability. By combining automated analysis with experimental validation through its integrated database, LOMS.cz establishes a standardized platform for accelerating the discovery and optimization of rare-earth-based photonic and optoelectronic materials.
Cell viability measured by cytotoxicity assay as a biomarker of chronic obstructive pulmonary disease exacerbation: a prospective cohort study
Abstract Acute severe exacerbation of chronic obstructive pulmonary disease (COPD) is related to high mortality; however, a robust blood biomarker for COPD exacerbation has not been established. Impaired clearance of apoptotic cells is a possible pathogenesis of COPD development. We evaluated the clinical utility of serum cell viability as a predictive biomarker for COPD exacerbation.Using serum from patients with stable COPD, cell viability was analyzed with a lactate dehydrogenase (LDH) assay. The patients were divided into low (optical density [OD] > 0.737) and high (OD ≤ 0.737) cell viability groups. Poisson regression analyses estimated the prognostic impact for COPD exacerbation, and a Cox proportional hazard model determined the impact on mortality. Among 162 patients, 47 were excluded due to follow-up loss within 1 year, asthma or combined interstitial lung disease diagnosis, and unsuitable cell viability measurements. The median follow-up duration was 6.3 years (range 0.7–11 years); 61 (53%) patients experienced at least one moderate or severe exacerbation, and 21 (19.7%) died. Patients in the low cell viability group were older, more likely to have poor quality of life and had a lower proportion of the non-exacerbator phenotype than those in the high cell viability group. The low cell viability group had a higher risk of moderate (incidence rate ratio [IRR], 1.58; p = 0.049) and severe (IRR, 2.69; p = 0.001) exacerbations and mortality (adjusted hazard ratio, 5.79; p = 0.016).We identified that low cell viability, measured with a serum LDH cytotoxicity assay, was associated with severe COPD exacerbation and higher mortality in patients with COPD.