Browse Articles

Deep Actor–Critic Reinforcement Learning (DA-CRL) based multi-objective optimal control of solar PV integrated UPQC for power quality enhancement in smart distribution networks

One-pot green synthesis of a glutamine-modified calcium tartrate bio-metal-organic framework for pH-responsive delivery of palbociclib in skin cancer therapy

Low field magneto-tuneable photodetection in Dy3+ doped Co-Zn ferrite based heterojunctions

Aging with multiple sclerosis and associated prevalence, incidence, comorbidities and healthcare utilization patterns in a population based study

Computational discovery of emodin-based anthraquinones as PARP-1 inhibitors with relevance to ovarian and prostate cancer

Abstract Cancer is a disease characterized by genomic instability and aberrant DNA repair. Poly (ADP-ribose) polymerase-1 (PARP-1) represents a well-established therapeutic target, particularly in ovarian and prostate cancer. However, the currently approved PARP inhibitors face challenges such as resistance, toxicity, and reduced efficacy. The search for alternative scaffolds has therefore become increasingly urgent. In this study, we used an integrated approach combining computer-aided methods to search for potential lead compounds among emodin-based anthraquinone derivatives as PARP-1 inhibitors. Using a PASS-based QSAR approach, drug-likeness prediction, and in silico ADMET assessment, we pre-screened a large set of anthraquinones and identified several potential hits for interaction with PARP-1. These hits were studied using molecular docking with the PARP-1 catalytic domain (PDB ID: 7KK4). The most stable and compact complexes were further explored by 500 ns molecular dynamics (MD) simulations and various dynamic properties (RMSD, RMSF, Rg, SASA, MolSA, hydrogen bonds, PCA, DCCM). The key finding of this study is that several emodin-derived anthraquinones exhibited binding behavior and ADMET profiles comparable to, or better than, the reference PARP-1 inhibitor. Among them, CID-10425624 emerged as the most promising candidate, exhibiting stable binding, reduced conformational fluctuation, compact complex formation, persistent hydrogen-bond interactions, and enhanced dynamic residue correlations within the PARP-1 catalytic domain. These findings suggest that the anthraquinone scaffold can provide a valuable starting point for developing structurally distinct PARP-1 inhibitors. In summary, this study identified several emodin-derived anthraquinones, particularly CID-10425624, as computationally prioritized lead candidates for PARP-1 inhibition, providing a novel anthraquinone-based scaffold for further experimental validation and optimization.

An energy–trust balanced and attack-resilient cluster head election scheme for resource-constrained wireless sensor networks

3D perception algorithm of unstructured environment based on point cloud enhanced pixel fusion

Dynamic convolutional neural networks for altitude aware UAV object detection

Metaheuristic-optimized interaction-aware deep learning with large language model assistance for data-driven water quality prediction

Sleep quality and depressive symptoms among Korean older adults

Data-driven fault diagnosis framework of taper roller bearings using statistically ranked feature sets and machine learning algorithms

Anthropometrics, physical fitness, and sport-specific performance of young German canoe sprint athletes (U13-U17) to predict senior performance level: a machine-learning approach

Abstract The aim of this study was to evaluate whether machine learning models comprising anthropometric, physical fitness, and sport-specific performance data from young canoe sprint athletes can predict their senior performance level (SPL). Between 1992 and 2019, anthropometric (e.g. body mass/height), physical fitness (e.g. 800 m/1500 m run, 2 min bench press/pull), and sport-specific performance (e.g. 250 m/2000 m on-water canoe sprint) data as well as age (i.e. U13 to U16) and sport discipline were annually examined in young male and female canoe sprint athletes (n = 729, male: 495, female: 234). A benchmark experiment was conducted to evaluate and compare multiple classification models and to use the final model to predict SPL (national vs. international) on three validation datasets (n = 103, U13 to U17, 2021 to 2023) with ground-truth labels from 2025. Findings revealed that an XGBoost model achieved acceptable discrimination (AUC = 0.81) and balanced accuracy (BACC = 0.73) for predicting SPL in young canoe sprint athletes. However, precision for the international class was low (PRAUC = 0.35, PPV = 0.20), indicating many false-positive international predictions. The most important feature was 2000 m on-water canoe sprint test. Furthermore, predictions on the three external validation datasets showed limited temporal generalizability, with moderate discrimination (AUC: 0.68 to 0.73), modest but consistently above-chance balanced accuracy (BACC: 0.59 to 0.63), and moderate but variable sensitivity (0.20 to 0.67). However, precision for identifying international athletes was low across the external validation datasets, indicating a high false-positive rate. Therefore, the model should be interpreted as an acceptable screening tool. However, low precision and variable sensitivity limit its practical utility as a stand alone selection instrument. The present findings may help practitioners involved in talent selection and development in Olympic canoe sprinting and may inform the development of future prediction models for young canoeists based on anthropometric, physical fitness, and sport-specific performance data.

Temporal patterns of haemoglobin phenotypes among Nigerian university students based on ten years of surveillance data

Strain transfer efficiency model and finite element simulation experiment for end-bonded substrate-type FBG sensors

Rhodococcus folensis sp. nov., an orange-red-pigmented bacterium from mining soil

Abstract Mining-impacted environments represent chemically complex ecosystems that may harbor metabolically versatile and pigment-producing microorganisms. During a survey of pigment-producing bacteria from abandoned mining soil in Trabzon, Türkiye, a red-pigmented strain, designated FMA22 T , was isolated and characterized using a polyphasic taxonomic approach. 16 S rRNA gene sequence analysis placed the strain within the genus Rhodococcus , showing the highest similarity to R. corynebacterioides DSM 20,151 T (99.57%), R. kroppenstedtii DSM 44908ᵀ (99.06%) and R. trifolii T8 T (98.96%). The strain was Gram-stain-positive, aerobic and non-motile, and grew at 4–40 °C. Polar lipids included phosphatidylethanolamine, diphosphatidylglycerol, phosphatidylinositol, phosphatidylinositol mannoside, phosphatidylcholine, five unidentified glycolipids, four unidentified lipids, one unidentified phospholipid and one unidentified phosphoglycolipid; MK-8(H2) was the major respiratory quinone. Major fatty acids were C18:1 ω9c, summed feature 3 (C16:1 ω7c/C16:1 ω6c) and C16:0. ANI and dDDH values with the closest relatives were below 76.8% and 20.5%, respectively. The draft genome (4.23 Mb; 67.2 mol% G + C; 4,106 CDSs) harbors a terpene-associated carotenoid cluster containing crtB, crtI and crtY. The orange-red pigment (λmax = 475 nm) showed antioxidant activity (DPPH SC₅₀ = 5.38 mg mL⁻¹; FRAP = 4.34 µmol TE g⁻¹) and weak but measurable HIV-1 reverse transcriptase inhibition (IC₅₀ = 22 mg mL⁻¹). These data support the proposal of Rhodococcus folensis sp. nov., with FMA22ᵀ (= LMG 34144ᵀ = DSM 120048ᵀ) as the type strain.

USP Gene Network Modulation and Osmoprotection Define Salt Resilience in Chenopodium quinoa Genotypes

Sequestration of methyl blue dye from aqueous solution onto raw and modified Banana (Musa paradisiaca) flower wastes

Enhancing mechanical performance of sandwich structures via uniform and gradient auxetic cores

Abstract Auxetic metamaterials have attracted substantial attention as core materials for sandwich structures for advanced lightweight applications due to their unconventional deformation behavior. This investigation studies the nonlinear dynamic response of re-entrant auxetic sandwich panels with various core designs subjected to three-point bending. The examined core designs include pure auxetic and gradient variations of the unit cell wall thickness -vertically and horizontally- across the core. Acrylonitrile Butadiene Styrene (ABS) polymer is chosen as the overall material, due to its high toughness, impact resistance, good processability and suitability for additive manufacturing processes. Finite element simulations were conducted in Abaqus/CAE to evaluate the influence of auxetic core geometry on load distribution, failure behavior, and energy absorption capacity. The numerical models were validated using previously published experimental data from the literature. The results showed that the graded designs improved the distribution of loads and postponed localized failure, thus improving maximum load bearing capacity and energy absorption resulting in enhanced bending performance. The horizontal internal graded configuration exhibited the best mechanical response, achieving a 23.2% increase in maximum load capacity and a 32.8% increase in energy absorption relative to the uniform auxetic core. Furthermore, the gradient effect introduced a progressive deformation mechanism, which induced smoother force-displacement responses alongside decreased stress concentrations. These findings demonstrate that graded auxetic core architectures provide an effective approach for enhancing the mechanical performance of sandwich structures in lightweight engineering applications.

Cooperative UAV swarms for zero knowledge verification of edge generative AI using trust-aware multiagent learning

Biological motion is perceived as faster with shorter auditory time intervals