Browse Articles

My diverse academic background is affecting my PhD studies — what do I do?

This World Cup could be the most high-tech yet — the innovations to watch for

HIV-1 signalling remodels nuclear pores to licence infection

Abstract HIV-1 is readily detected in resting CD4 + T cells in vivo 1–4 . However, resting T cells are highly refractory to cell-free virus infection in vitro 5–7 and require mitogenic activation to become permissive. This paradox raises the fundamental question of what makes a T cell permissive for HIV-1. Here we address this and show that HIV-1 capsid nuclear import at the nuclear pore complex (NPC) is a bottleneck to resting T cell infection, but that HIV-1 overcomes this by triggering receptor-mediated signalling during cell–cell spread to drive nuclear import and licence infection. Coupling viral and cellular assays with super-resolution imaging, we show that contact between HIV-1 infected and uninfected T cells triggers CD4–LCK signalling that activates CDK1, independent of cell-cycle entry, phosphorylating nucleoporins and priming the NPC to promote HIV-1 nuclear import. Critically, cell–cell contact also accelerates nuclear import in activated T cells, providing a paradigm for why cell–cell spread dominates infection. By contrast, HIV-1 virions do not trigger this response, explaining why resting T cells cannot be efficiently infected by cell-free virus. We propose that HIV-1 has evolved to selectively activate CD4 signalling during cell–cell spread to regulate infection at the step of the NPC, offering an explanation for how resting T cells can be infected in vivo.

A physiological investigation of rootstock effects on the water use of irrigated ‘Rosy Glow’ apple trees under water deficit conditions

Metabolic reprogramming in Oocystis borgei drives the biosynthesis of gold nanoparticles

Abstract Microalgae-mediated biosynthesis of gold nanoparticles (AuNPs) offers a sustainable alternative for nanomaterial synthesis; however the metabolic mechanisms underlying the reduction of HAuCl 4 and the formation of AuNPs remain unclear. In this study, the green microalga Oocystis borgei was employed to synthesize AuNPs, and associated cellular metabolic alterations were systematically examined using transmission electron microscopy (TEM) and untargeted LC-MS-based metabolomics. TEM revealed AuNP accumulation in the chloroplasts, accompanied by substructural disorganization. Metabolomic profiling identified 1,871 upregulated and 1,681 downregulated ions in positive ion mode, and 1,092 upregulated and 1,032 downregulated ions in negative ion mode. Among the significantly upregulated metabolites, fatty acyls, glycerophospholipids, and oxidanesulfonic acid were associated with lipid peroxidation and membrane remodeling. In contrast, downregulated metabolites, including carbohydrates, nucleic acids, and chlorophyll derivatives, indicated suppressed growth and metabolic activity. The differentially abundant metabolites(DAMs) were enriched in purine metabolism, porphyrin and chlorophyll biosynthesis, and plant hormone signaling pathway. Notably, porphyrin and chlorophyll degradation and amino acid/protein metabolism suppression correlated with growth inhibition, whereas oxidised lipids (19-hydroxy-nonadecanoic acid) and stress-responsive metabolites (brassinosteroids and carotenoids) facilitated AuNP synthesis. These findings elucidate the metabolic trade-offs in O. borgei during HAuCl 4 detoxification and AuNP biogenesis, enhancing our mechanistic understanding of algal-based nanomaterial synthesis.

The neural mechanisms supporting the rise and fall of maternal aggression

Melatonin modulates inflammation in human fetal membranes: an ex vivo approach

Selection of reference genes for studying blood-brain borders in the rat and the non-human primate using quantitative real-time PCR

A two-stage fuzzy flexible flow shop scheduling problem with no-wait and reentrant constraints using adaptive particle swarm optimization

Abstract To address increasing production and logistical challenges in the fresh livestock processing industry, this study investigates a two-stage multiprocessor flow shop scheduling problem with fuzzy processing times and time window constraints. Ensuring product freshness under urban congestion and limited storage capacity requires precise and flexible scheduling to minimize early and late completion penalties. This study proposes an adaptive particle swarm optimization algorithm that integrates fuzzy processing environments with time-constrained scheduling. The main contributions are threefold: (1) the formulation of a bi-objective mathematical model incorporating fuzzy processing times and time window constraints, (2) the development of an adaptive inertia weight mechanism to enhance the exploration–exploitation balance of particle swarm optimization (PSO), and (3) a comprehensive comparative analysis against benchmark algorithms, including hybrid genetic algorithm, the linearly decreasing inertia weight PSO, and the multi-objective evolutionary algorithm with heuristic decoding. Experimental results demonstrate that the proposed ADPSO significantly outperforms existing methods, achieving an average improvement of 18.10% in total penalty reduction and 19.93% in solution stability, thereby confirming its effectiveness and robustness in solving complex scheduling problems under uncertainty.

Predicting the strength of waste aggregate concrete blocks using novel hybrid machine learning models and graphical user interface deployment

Loudness changes as a function of the audiovisual scene

Abstract Understanding how listeners perceive speech in complex audiovisual (AV) environments is essential for characterizing communication in everyday settings. Here, we used loudness ratings to examine how AV scene characteristics shape the perceptual representation of a target talker in multitalker babble. Twenty-five normal-hearing adults rated the perceived loudness of a female talker presented in four-talker babble at four target-to-masker ratios (TMRs: − 21, − 9, − 6, − 3 dB). Audiovisual temporal coherence was manipulated by delaying the audio relative to the video at five stimulus onset asynchronies (SOAs: 0–500 ms), and three linguistic categories were tested: words, pseudowords, and reversed words. At synchronous presentations, loudness ratings scaled with TMR and were higher for words than pseudowords and reversed words, despite identical physical intensities. Increasing AV asynchrony reduced perceived loudness, with significant drops emerging beyond 150–300 ms SOA. Mapping loudness ratings onto perceived TMR change using individual loudness-growth slopes eliminated the main effect of the linguistic category, isolating a 2–3 dB perceived TMR drop at 500 ms SOA across all categories. These results demonstrate that both AV temporal synchrony and linguistic content shape loudness perception in noise, but their contributions are dissociable. This provides a novel view into how the perceptual construct of loudness changes with the AV scene, with implications for how loudness ratings can be used to study scene analysis and communication.

A 5.3-million-year-old deep-sea whale necropolis in the Diamantina Zone

Experimental and numerical study on the size effect of miniature penetration strength in fluidized solidified soils

Collagen promotes PD-L1 overexpression in fibroblasts through binding to CD44 and activating YAP1 signaling during keloid formation

Abstract Keloid is a skin collagen disease secondary to skin injury, characterized by excessive collagen deposition and a markedly high rate of recurrence. To date, there is still a lack of effective prevention and treatment methods for keloid. Thus, it is urgent to explore the main pathological mechanism of keloid formation, which requires to identify the biological mechanism of deposited collagen regulating the formation of fibroblast-mediated local immunosuppressive microenvironment. Collagen accumulation, CD4 + T, CD8 + T, CD86 + Macrophages, FOXP3 + Treg cells infiltration, CD44 expression, and α-smooth muscle actin (α-SMA), platelet-derived growth factor receptor (PDGFR) and programmed cell death 1 ligand 1 (PD-L1) levels in keloid and normal skin tissue samples were determined by tissue immunofluorescence assay. The effects of collagen I on the expression of PD-L1, YAP1 and phosphorylated YAP1 (p-YAP1) in primary keloid fibroblasts were examined by reverse transcription-quantitative PCR and western blot assays. The co-location of collagen I and CD44 or PD-L1 and α-SMA was determined by cell immunofluorescence assay. Collagen accumulated in keloid pathological tissues, and fibroblasts proliferated abnormally in keloid pathological tissues. The infiltration of CD4 + T, CD86 + Macrophages and FOXP3 + Treg cells in keloid tissues was significantly upregulated, while the infiltration of CD8 + T cells in keloid tissues was significantly reduced. PD-L1 was significantly overexpressed in the fibroblasts of keloid tissues. Further mechanistic exploration found that deposited collagen (induced by inflammation) could bind to CD44 on the surface of fibroblasts, activate the YAP1 signaling pathway and lead to PD-L1 overexpression to form a local immunosuppressive microenvironment, resulting in the inability to remove the deposited collagen and the continuous proliferation of fibroblasts, ultimately forming keloid. The present study revealed that collagen deposition induced an immunosuppressive microenvironment and promoted the formation of keloid, thus providing potential new targets and theoretical basis for the prevention and treatment of keloid.

Impact of ECRH on runaway electron generation during plasma disruptions in the HL-3 tokamak

Dietary patterns and pesticide exposure in rural Latvia: evidence from a human biomonitoring study

Abstract Dietary intake is the main route of pesticide exposure in the general population. While several European studies have linked food consumption to human biomonitoring data, evidence from smaller countries such as Latvia is scarce. This study is the first to systematically examine how dietary habits influence pesticide exposure in the Latvian rural population, addressing an important knowledge gap and providing evidence with direct relevance for public health and food safety policies. This study used data from the HBM4EU SPECIMEn study, including 101 adult–child pairs from rural Latvia. Morning spot urine samples were collected from all pairs. Urinary pesticide metabolites were measured using suspect screening with full scan liquid chromatography coupled to HRMS, resulting in annotated metabolites. Dietary information was collected through food diaries 24 h prior to urine collection, and associations between the consumption of specific fruits and vegetables and pesticide detection were assessed using descriptive frequency analysis and logistic mixed-effects regression models. Consumption of apples, bananas, eggplants/courgettes, grapes, pears, and processed potato products was consistently associated with higher detection frequencies and increased odds of pesticide detection. Acetamiprid was detected in 66.7% of grape consumer urine samples compared with 31.8% of non-consumers, and 73.6% of French fries/chips consumers had chlorpropham detected compared with 25.9% of non-consumers. Logistic regression confirmed these associations, showing strong links between apple consumption and acetamiprid (OR = 2.49, 95% CI 1.51–4.09, p  < 0.001) and between banana consumption and boscalid (OR = 2.66, 95% CI 1.34–5.28, p  = 0.005). No significant differences were observed between organic/homegrown and conventional food items. Higher pesticide detection frequencies and odds ratios were observed among participants reporting consumption of apples, bananas, grapes, pears, and processed potato products compared with non-consumers, with the strongest associations for acetamiprid in grapes, chlorpropham in French fries and chips, and multiple pesticides in apples. The detection of pesticides not registered in Latvia, such as acetamiprid, pyrimethanil, and imazalil, indicates that imported foods are an important source of exposure. These findings contribute to understanding dietary exposure pathways and may support future exposure monitoring and food safety communication strategies.

Assessment of modifications to a blind-sweep ultrasound protocol for improved lower-uterus imaging by novice operators

AutoLabs: cognitive multi-agent systems with self-correction for autonomous chemical experimentation

Abstract The automation of chemical research through self-driving laboratories (SDLs) promises to accelerate scientific discovery, yet the reliability and granular performance of the underlying AI agents remain critical, under-examined challenges. In this work, we introduce AutoLabs, a self-correcting, multi-agent architecture designed to autonomously translate natural-language instructions into executable protocols for a high-throughput liquid handler. The system engages users in dialogue, decomposes experimental goals into discrete tasks for specialized agents, performs tool-assisted stoichiometric calculations, and iteratively self-corrects its output before generating a hardware-ready file. We present a comprehensive evaluation framework featuring five benchmark experiments of increasing complexity, from simple sample preparation to multi-plate timed syntheses. Through a systematic ablation study of 20 agent configurations, we assess the impact of reasoning capacity, architectural design (single- vs. multi-agent), tool use, and self-correction mechanisms. Our results demonstrate that agent reasoning capacity is the most critical factor for success, reducing quantitative errors in chemical amounts (nRMSE) by over 85% in complex tasks. When combined with a multi-agent architecture and iterative self-correction, AutoLabs approaches expert-authored reference procedures on the benchmark (F1-score > 0.89) on challenging multi-plate syntheses. These findings establish a clear blueprint for developing robust and trustworthy AI partners for autonomous laboratories, highlighting the synergistic effects of modular design, advanced reasoning, and self-correction to ensure both performance and reliability in high-stakes scientific applications. Code: https://github.com/pnnl/autolabs

Clofibrate downregulates DNA damage response proteins via the MELK-AKT-mTOR axis in breast cancer

Pathways to resilient agricultural water management through contrasting governance systems in California and South Korea

Abstract Agricultural water systems are increasingly exposed to climate-driven extremes, aging infrastructure, and intensifying cross-sectoral competition, requiring a transition toward more adaptive and resilient management. Here, we present a comparative analysis of agricultural water management pathways in California, USA, and South Korea—two regions facing similar hydroclimatic pressures but operating under contrasting governance systems. We show that California prioritizes decentralized, data-driven, and adaptive management, whereas South Korea emphasizes centralized coordination, infrastructure-based solutions, and national-scale planning. Despite these differences, both regions exhibit converging systemic challenges, including increasing vulnerability to droughts, floods, and heatwaves, inefficiencies in conventional water use, labor constraints, and growing trade-offs between agricultural production and ecosystem sustainability. Building on these findings, we identify four key pathways for advancing sustainable agricultural water management: (1) enhancing water supply resilience through diversification and optimized storage, (2) improving water-use efficiency via digital technologies and advanced irrigation systems, (3) integrating ecosystem-based approaches to sustain environmental functions, and (4) strengthening collaborative governance for equitable and adaptive water allocation. Our results demonstrate that sustainable agricultural water management depends not only on technological innovation, but also on institutional adaptability and governance integration. These findings provide transferable insights for regions facing similar water stress and highlight the need for hybrid management approaches that combine flexibility, coordination, and resilience under accelerating climate change.