Browse Articles

Comparison of DeepSeek-V3.2 and ChatGPT-5.2 in the outpatient diagnosis and treatment of prostate cancer: a multicenter evaluation of application value and multilingual adaptability

Enantioselective Total Syntheses of Bisleuconothine A and Bousigonine B

ABSTRACT Hetero‐oligomeric monoterpenoid indole alkaloids (MIAs), which possess unique three‐dimensional architectures and relatively high molecular weights, are intriguing targets in drug discovery owing to their potential to disrupt protein–protein interactions. Herein, we describe the first enantioselective total syntheses of bisleuconothine A, a dimeric MIA, and bousigonine B, a trimeric MIA. The central element of our strategy is the concise construction of a chiral 3‐ethylpiperidine scaffold, a common structural motif in MIAs. This key intermediate was prepared using a cascade sequence comprising an organocatalytic enantioselective Michael addition of a cyclic enamine to acrolein promoted by a chiral secondary amine catalyst, followed by hemiaminal cyclization and acetalization. Coupling of the aspidosperma‐ and eburnane‐type fragments, both derived from this common intermediate, was accomplished via a biomimetic Friedel–Crafts‐type reaction. The present total synthesis also revises the absolute stereochemistry of bousigonine B and constitutes the first total synthesis of a trimeric MIA.

Simulation of multi-mechanism deposition characteristics of dust particles on the cylindrical surface based on lattice Boltzmann method

Community-aware sparse topology design for efficient spiking neural networks

Prevalence, pattern and prognosis of lung lesions in pediatric Hodgkin lymphoma

Abstract Children and adolescents with classical Hodgkin lymphoma have a progression-free survival (PFS) rate of ≥ 90% with current treatments. The current challenge is to reduce adverse late-effects while maintaining high survival. Distinguishing lung involvement (Stage IV) from benign lung lesions remains a staging challenge in pediatric Hodgkin lymphoma (pHL). This study analyzed the prevalence, morphological patterns, and prognostic impact of lung lesions on progression-free survival (PFS) within the EuroNet-PHL-C1 trial. A retrospective analysis was conducted on chest CT scans from 1,298 pHL patients enrolled in the EuroNet-PHL-C1 trial. Patients were stratified by established treatment groups (TG-1, TG-2, TG-3). Lesions were classified by morphological pattern, and Kaplan-Meier analysis was used to compare 60-month PFS between groups with and without lung lesions. Lung lesions were identified in 60.2% (782/1298) of patients, with nodules being the predominant pattern (89%). In the combined TG-1 and TG-2 cohort (early/intermediate stages), the presence of any lung lesion correlated with significantly lower 5-year PFS (85.5% vs. 91.7%; p  = 0.0197). Importantly, this lower PFS was driven by non-nodule morphologies. In the TG-3 (advanced stage) cohort, neither the presence of lung lesions nor stage IV classification significantly affected PFS. Lung lesions are highly prevalent in pHL. However, the presence of pulmonary nodules does not confer an inferior prognosis. The prognostic impact of lung lesions is primarily limited to non-nodule patterns in early-stage disease. These findings suggest that incorporating morphological patterns may be beneficial for refining risk stratification in future pHL trials.

Effect of temperature on electrical resistivity and charge storage behavior of novel (Mn$$_{2/3}$$Ru$$_{1/3}$$)$$_2$$AC LAX phases for next-generation supercapacitor anodes: a first-principles study

Factors associated with non-steroidal anti-inflammatory drug continuation at discharge in patients with heart failure

The role of Zn2+ on structure, magnetic properties, and drug delivery performance of ZnxFe3–xO4/SiO2 nanocomposites

Optimized image preprocessing strategies for enhanced neural network-based defect detection in industrial automation

Abstract Machine vision and AI-based defect detection systems are increasingly deployed in manufacturing to support consistent product quality and high production efficiency. However, these automated inspection systems often suffer from sensitivity to imaging variability, dependence on large labeled datasets, and the need for manually engineered preprocessing pipelines–limitations that hinder accuracy and reliability in real industrial conditions. This study presents a novel approach for optimizing image preprocessing strategies for neural network–based defect detection using a genetic algorithm (GA)-driven evolutionary framework. The method systematically explores a set of 48 preprocessing operations and automatically evolves optimal filter sequences through multi-objective fitness evaluations incorporating classification accuracy, computational efficiency, and preprocessing robustness. The genetic algorithm generates diverse preprocessing sequences of varying lengths (3–6 filters) and evaluates a broad range of population sizes (20–100 individuals) and generation limits (20–150 generations) to identify configurations that maximize detection performance while reducing data requirements. Extensive experiments across three product categories show that GA-optimized preprocessing significantly outperforms raw-image baselines and manually designed preprocessing pipelines. Results demonstrate substantial gains in classification accuracy (up to 15%) and improved data efficiency, requiring 30–60% fewer training images to achieve target performance. The findings confirm that evolutionary optimization provides a robust and scalable solution for industrial defect detection, enabling more reliable and efficient machine vision systems for modern manufacturing environments.

Competing Tropical and Extra-tropical Processes drive Zonal Asymmetries in Hadley Circulation Expansion

Influence of thoracic paravertebral block on cardiac repolarization

Gas–Responsive Metal–Organic Frameworks for Adaptive Thermal Energy Storage with Tunable Charge–Discharge Temperatures

Nitrogen-oxygen plasma induces selective cancer cell death via apoptosis with lipid-peroxidation-associated mechanisms across multiple cancer cell models

Abstract Plasma-based approaches are attracting interest as potential anticancer strategies due to their ability to generate reactive species that damage tumor cells. However, clinical translation remains limited by challenges in biocompatibility, reproducibility, and chemical tunability. In this study, we utilized a nitrogen-oxygen gas mixture to generate a controllable spectrum of reactive species and evaluated its effects in endometrial (HEC1A), cervical (HeLa), melanoma (B16F10), and lung (H1299) cancer models. Nitrogen-oxygen plasma treatment preferentially reduced cancer cell viability compared to normal fibroblasts in vitro. Mechanistically, plasma exposure increased intracellular oxidative stress, and co-treatment with GSH attenuated cytotoxicity, indicating a central role for reactive species. Apoptosis was supported by Annexin V/PI staining, caspase-3 and PARP cleavage, mitochondrial depolarization, and increased γH2AX, phospho-p53, BiP, and CHOP. Transcriptomic profiling revealed activation of apoptotic pathways alongside modulation of ferroptosis-associated genes. Ferrostatin-1 partially rescued cell viability, linking cytotoxicity to lipid peroxidation, whereas iron chelation did not reduce lipid peroxidation. These findings indicate a contribution of lipid peroxidation without canonical iron-dependent ferroptosis. In vivo, treatment significantly suppressed tumor growth in a B16F10 melanoma allograft model following intratumoral administration. Together, these results demonstrate that nitrogen-oxygen plasma induces apoptosis with additional oxidative lipid damage, supporting its therapeutic potential.

Histopathological zonal patterns in ascending aortic aneurysm with bicuspid and tricuspid aortic valves

Abstract While medial degeneration is the recognized substrate of ascending thoracic aortic aneurysm (TAA), data on its regional heterogeneity are lacking, particularly regarding bicuspid (BAV) and tricuspid (TAV) aortic valves. This study performed level-by-level histological analysis of the ascending aorta in TAA. Surgical specimens from sinotubular junction (STJ), mid-ascending aorta (AscA), and proximal aortic arch (PrAA) were obtained from 66 TAA patients (25 BAV, 41 TAV). Histological assessment followed SCVP/AECVP criteria. Medial degeneration was universal (100%), with elastic fiber fragmentation most prevalent across all levels. TAV patients exhibited a more severe phenotype, with significantly higher prevalence of translamellar mucoid accumulation (T-MEMA) in STJ (54% vs. 24%, p  = 0.019) and AscA (45% vs. 13%, p  = 0.010), diffuse elastic fiber loss in STJ (29% vs. 8%, p  = 0.041), and smooth muscle cell nuclei loss in STJ (41% vs. 16%, p  = 0.032) and AscA (50% vs. 22%, p  = 0.028). Atherosclerosis was significantly more prevalent in TAV patients overall (65.9% vs. 28.0%, p  = 0.003) and specifically in PrAA (43% vs. 14%, p  = 0.021), with severe lesions exclusive to this group. This first systematic multi-level analysis reveals that TAA is characterized by regional and valve-dependent heterogeneity: in TAV patients, degenerative markers predominated proximally, whereas atherosclerotic involvement was more pronounced distally.

Data-driven causal networks for pork supply chain risk analysis in Sichuan Province

Molecular dynamics simulation of the atropine drug encapsulation inside protein origami icosahedral nanocages in physiological environment

Pre-post changes in agility, balance, and functional movement during short-term functional strength and balance training in national-level Kho-Kho players

Comparative radiosensitivity of soybean genotypes to electron beam and gamma ray irradiation for optimisation of GR50 and LD50 doses

Safety, tolerability and pharmacokinetic properties of intranasal artesunate in a first in human phase 1 trial

Abstract Malaria is responsible for more than half a million deaths each year. Parenteral artesunate is the recommended first-line treatment for severe malaria, but prompt treatment is often delayed affecting patient outcomes. Rectal artesunate is recommended as a pre-referral treatment but shows variable absorption and can be problematic when treating children with gastrointestinal disturbances. Nasal drug administration offers a non-invasive and user-friendly alternative that enables rapid drug absorption. A Phase I, first in human trial was conducted to evaluate the safety, tolerability and pharmacokinetic properties of increasing doses of a novel intranasal formulation of artesunate powder. Three dosing regimens were assessed in adult volunteers. Plasma samples were collected for up to 24 h post-dose for drug measurements of artesunate and dihydroartemisinin. Intranasal artesunate was safe and well tolerated. Only mild adverse events were reported shortly after drug administration. No severe adverse events were observed. Pharmacokinetic analysis confirmed rapid systemic absorption of artesunate but with high inter-individual variability. Dose-normalized exposures to dihydroartemisinin suggested a non-linear dose-exposure relationship. Further evaluation of this novel formulation of artesunate is needed to establish safety and efficacy in patients with malaria. This, first in human, phase 1 provides justification for subsequent phase 2 clinical trials.

Identifying high-risk patient clusters for falls using unsupervised machine learning on linked primary and secondary care electronic health record data

Abstract Falls risk is multifactorial, involving a combination of clinical and sociodemographic factors. Although guidelines acknowledge this complexity, most research has focused on individual risk factors, leaving the combined impact of comorbidities relatively understudied. This population-wide study used electronic health records (EHR) linked across primary and secondary care to identify falls risk profiles in the North West London (NWL) population and to stratify patients by their likelihood of requiring falls-related hospital care using unsupervised clustering. We conducted cluster analysis on patients from NWL General Practice records using coded falls risk factors. Cluster membership was compared against the risk of falls-related hospital encounters. Among four identified clusters, two groups of older, multimorbid patients were 11 times more likely to have a fall-related hospital encounter (RR 11.45, 95% CI 10.14–12.92 and RR 11.63, 95% CI 10.30–13.13) and had significantly longer mean length of stay compared with younger, fitter patients. Between two younger clusters, patients with higher deprivation levels were 29% more likely to have a fall-related hospital encounter (RR 1.29, 95% CI 1.12–1.49). These findings demonstrate that clustering routinely collected EHR data can identify population segments at highest risk of falls-related hospital use, supporting more targeted, multifactorial risk assessment and prevention strategies.