Browse Articles

Tremelimumab with or without durvalumab in combination with paclitaxel in metastatic urothelial cancer: phase I/II ICRA trial

The future fate of Somali upwelling productivity and the implications for fisheries under climate change

Abstract The Somali upwelling is the strongest upwelling region globally during its seasonal peak. The intense productivity that occurs during the southwest monsoon (May-September) sustains artisanal and industrial fisheries. However, due to its complex structure and seasonality, and the typically coarse spatial resolution of global climate models, understanding its future fate remains a challenge. Using a high-resolution future climate projection and a size-spectrum model (in the absence of reliable fish catch data), we identify key climate stressors and projected changes in higher trophic levels to understand potential future impacts on Somali fisheries. Overall, the productivity generated by the Somali upwelling is projected to decline by the end of the century. Our results show that the inner coastal zone may experience elevated productivity, potentially due to changes in the prevailing winds and Somali Current. This may indicate potential climate refugia and minimal impacts to the artisanal fishing fleet. However, further offshore in the Great Whirl region dominated by small pelagic fish, there is a projected decline in productivity and biomass, which may impact the industrial fishing fleets that may target this area in future. To overcome challenges in understanding the fate of global upwelling systems, high-resolution models must be employed to more accurately simulate individual systems.

Phospholipid-independent biogenesis and function of the RP4 conjugation pilus

Abstract Bacterial conjugation, the process of horizontal gene transfer between bacteria, is initiated by mating pair formation (MPF) via a conjugative pilus. Conjugation of the IncP RP4 plasmid is mediated by short mating pili. Here, we report the cryo-EM structure of the RP4 pilus at 2.74 Å resolution. Uniquely, both the structural and quantitative mass spectral analyses revealed that the cyclic TrbC pilin subunit is not lipidated. Consistently, an E. coli pgsA mutant lacking phosphatidylglycerol (PG) can serve as a donor of RP4 but not of F- (pKpQIL), H- (R27) or W- (R388) pili, whose biogenesis and DNA transfer is PG-dependent. RP4 is the first example of a lipid-independent functional mating pilus. This discovery suggests that an amphipathic lipid moiety is not universally essential for the biogenesis of conjugative pili and MPF, providing an alternative model for their assembly and function. These data expand our understanding of the diverse bacterial mechanisms employ to transfer genetic material.

A multi-task learning-based fully connected neural network for personalized news recommendation

Integrative chemotaxonomic and micromorphological insights into Peucedanum (Apiaceae)

Quantum-inspired hybrid optimization framework for energy-efficient clustering and routing in wireless sensor networks

Mouse model of X-linked Alport syndrome with K229X mutation in the COL4A5 gene

Is the elimination of violence against women a realistic goal for the near future?

Sustainable intensive agriculture as key player in ensuring food security and mitigating atmospheric CO2 growth

PVC microplastics facilitate uropathogenic Escherichia coli pathogenicity by enhancing host cell invasion and mitochondrial-dependent pyroptosis

Highly Selective Methane Photooxidation to Formaldehyde by Constructing Symmetry-Breaking Sites

Fully automated CT-based quantitative body composition analysis for predicting survival in patients with HCC undergoing TACE: a dual-cohort study

Abstract Transarterial chemoembolization (TACE) is a standard treatment for patients with unresectable hepatocellular carcinoma (HCC), yet existing models provide limited individualized risk stratification. Automated CT-derived body composition analysis has emerged as an objective marker of patient physiological reserve, but its value in prognostication in TACE patients is insufficiently studied. Therefore, the aim of the study was to evaluate the prognostic value of a fully automated, open-source pipeline for CT-based body composition analysis in predicting overall survival (OS) in patients with HCC undergoing TACE. In this study, we used two independent cohorts of treatment-naive patients undergoing TACE: the WAW-TACE cohort (development; n  = 230, OS: 28.6 months) and the HCC-TACE-Seg cohort (validation; n  = 100, OS: 24.0 months). Skeletal muscle and fat metrics were extracted from pre-treatment CTs using a standardized deep learning pipeline and normalized by sex. Survival analyses were performed using Cox proportional hazards (CoxPH) models and random survival forests (RSF). Skeletal muscle density (SMD) at the L3 level was the strongest and independent predictor of OS across both cohorts (HR: development, 0.84; p  = 0.029; validation, 0.79; p  = 0.028). This association remained significant after adjustment for the best-performing clinical composite scores: mHAP-2 in the development (adjusted HR = 0.68; p  = 0.049) and CLIP in the validation cohort (adjusted HR = 0.43; p  = 0.003). In CoxPH, the addition of SMD metrics resulted in only modest improvements in discrimination (ΔC-index 0.011–0.037) that did not reach statistical significance. In contrast, RSF analysis demonstrated a statistically significant improvement in model discrimination when muscle-based variables were added to clinical features (ΔC-index = 0.023; p  < 0.001). In both cohorts, SMD showed a reproducible independent prognostic association with overall survival. While adding SMD to traditional clinical models resulted in only modest, and in Cox-based analyses not statistically significant, improvements in discrimination, SMD provided complementary prognostic information. This suggests that the primary value of these automated CT-derived body composition metrics lies not in their performance as standalone predictors, but in their ability to provide an additional layer of objective biological data that may contribute to risk stratification in a complementary and exploratory manner within multivariable frameworks. Notably, in internally cross-validated RSF analyses, statistically significant increases in model discrimination were observed when muscle-based features were integrated into the model, highlighting their potential complementary value within machine learning frameworks.

Targeting dopamine transporter for treating social transmission of depression-like behaviors in male mice

Effect of fulvic acid contamination on the shear strength and microstructural evolution of red clay

Hybrid integration of quantum dot single-photon sources with lithium tantalate photonics for on-chip routing

Abstract A promising pathway towards scalable quantum photonic processors involves the simultaneous integration of deterministic single-photon sources, low-loss photonic circuitry, and fast reconfigurability. Thin-film lithium tantalate on insulator (LTOI) offers an exceptional electro-optic response and low optical loss at 900 nm wavelength band, yet its lack of efficient quantum emitters has hindered progress toward fully integrated quantum technologies. Here, we demonstrate heterogeneous integration of indium arsenide quantum dots (QDs) with low-loss reconfigurable LTOI waveguides (0.30 ± 0.04 dB/cm) using micro-transfer printing. By directly butt-coupling tapered gallium arsenide waveguides with inversely tapered LTOI waveguides, we achieve robust and alignment-tolerant inter-waveguide coupling. The hybrid chip operates at cryogenic temperatures, enabling deterministic routing of successively emitted single photons from the QDs with a half-wave voltage-length product ( ~ 1.9 V·cm at 4 K), confirming the cryogenic stability of LTOI’s electro-optic coefficient. These results establish demonstration of high-speed on-chip routing of single photons with hybrid QD-LTOI circuits, providing a scalable pathway toward integrated quantum photonic processors.

Acoustic deep learning for defect detection in aluminium wheel rims

A preoperative Artificial Intelligence model to estimate cancer-specific mortality in nonmetastatic kidney cancer patients

Atomistic insights into the magnetic-field modulation of the $$\hbox {A}_{2A}$$ adenosine receptor

Interpretable graph-based models on multimodal biomedical data integration: a technical review and benchmarking

Abstract Integrating diverse biomedical modalities is essential for robust healthcare insights, and graph-based models are increasingly used to capture complex relational structures. Yet, their clinical translation hinges on interpretability. This review surveys interpretable graph-based models applied to multimodal biomedical data, highlighting dominant trends in disease classification, static graph construction, and post-hoc explainability. We categorize explainable artificial intelligence (XAI) techniques, benchmark SHAP, saliency, sensitivity, and graph masking on Alzheimer’s disease data, and reveal complementary strengths. A development flowchart and future directions, such as dynamic graphs, knowledge integration, and LLM-based explainability, position this work as a key reference for trustworthy biomedical AI.

Assessment of fermented vegetable wastes in Nile tilapia diets: impacts on fish performance, amino acids profile, health, and intestine histomorphology

Abstract This study assessed the effects of incorporating fermented vegetable wastes (FVW), with Bacillus subtilis and Saccharomyces cerevisiae , in Nile tilapia ( Oreochromis niloticus ) diets at 0, 10, 20, and 30% inclusion levels (FVW0, FVW1, FVW2, and FVW3, respectively) on fish growth, feed utility, amino acids profile, health, nutrient utilization and intestine histomorphology. The results indicated 100% survival rates for all experimental groups. Furthermore, based on WG and SGR recorded values, fish growth was insignificantly changed among all fish groups ( P  > 0.05). Feed intake was significantly higher in FVW3 and FVW2 compared to other groups, however, feed utilization efficiency was not varied among all experimental groups depending on FCR and PER values. Carcass biochemical analysis showed that only ash content was significantly different among dietary groups as it was higher in FVW1 and FVW2 compared with the other two groups. The results illustrated an increase in most of the essential amino acids (EAAs) percent in the experimental groups relative to the control. Complete blood count revealed that red blood cells count remained insignificantly different among all groups, however, FVW1 showed a significantly lower hemoglobin content compared to the control and other groups. White blood cells count was significantly the highest in FVW2. Aspartate aminotransferase (AST) concentration was significantly elevated in both FVW2 and FVW3 groups compared to control, however, alkaline phosphatase (ALP) concentration was significantly decreased in these two experimental groups. The highest alanine aminotransferase (ALT) concentration was recorded in FVW3. Total protein and globulin values were significantly increased in all tested groups relative to the control. Proteases activity was propositionally increased with increasing FVW inclusion level, however, both lipase and amylase activities were significantly decreased in the treated groups relative to the control. Histomorphological inspection of fish distal intestine revealed normal intestinal architecture with enhanced villi development and goblet cell density in FVW-fed fish, particularly at 20% inclusion. The present results indicate that FVW can be safely included in Nile tilapia diets up to 30%.