Browse Articles

Genetic diversity and recombination of begomoviruses associated with chilli leaf curl disease in northern and Central-East India

Scalable irradiance-adaptive electrochromic shading for photothermal regulation

Abstract Agricultural production in hot climates requires effective photothermal regulation under fluctuating solar conditions. Electrochromic devices offer a promising route for dynamic photothermal regulation, yet their deployment in real-world agricultural environments remains limited by challenges in scalability, durability, and system-level integration. Here, we show a scalable, solar-powered, irradiance-adaptive electrochromic shading system that autonomously regulates photosynthetically active radiation and suppresses ultraviolet and near-infrared radiation under fluctuating outdoor conditions without external energy input. The electrochromic devices exhibit large optical contrast and robust operational stability during tropical outdoor exposure. Field deployment in tropical agriculture reduces crop-surrounding temperature by up to 3.8 °C while maintaining optimal conditions for photosynthesis. Consequently, crops grown under electrochromic shading exhibit 23.7–64% increases in vitamin C, total sugar, and pigments, together with a 235% increase in biomass yield compared with a conventional shading system. Cultivation modeling further reveals substantial cooling-energy savings across diverse climate zones during hot seasons.

Early intraocular pressure dynamics after intravitreal aflibercept 8 mg versus 2 mg

FlyTomo: a streamlined software for on-the-fly cryo-ET data processing and diagnosis

Turkish nurses’ attitudes towards violence against women, level of recognition of signs, and intention to report violence against women: a cross-sectional study

Preparation method shapes the recovery and ecological interpretation of DNA and RNA soil viral communities

Abstract Deciphering viral ecology in soils is challenging due to soil’s high physicochemical and microbial community complexity. To enhance detection of DNA and RNA viruses, we applied different preparation methods to soils collected from a grassland field experiment. Analyses included metagenomics and metatranscriptomics of size-fractionated extracellular viruses, total soil metagenomics and metatranscriptomics, total soil metatranscriptomics with polyadenylation enrichment, and metagenomics of bacteria/archaea as well as eukaryote-enriched samples. DNA viromes outperformed total soil metagenomes in viral detection and quality. Contrastingly, RNA viromes and total soil metatranscriptomes performed similarly for viral recovery, though RNA viromes yielded higher-quality genomes. Together, our results highlight how different preparation methods can influence the recovery and quality of DNA and RNA vOTUs. Further, we demonstrate the power of different methods in identifying distinct viral communities with unique host predictions, which in turn can have significant implications for ecological investigations related to interkingdom interactions.

Factors associated with meconium stained amniotic fluid and birth outcomes among mothers at Woldia Comprehensive Specialized Hospital

Temporal drift of sleep-wake representations in hypothalamic neuronal ensembles

Abstract Correlative and causal evidence implicates distinct genetically-defined and evolutionary-conserved hypothalamic neurons in regulating wakefulness, non-rapid eye movement (NREM), and rapid eye movement (REM) sleep. The prevailing view is that these circuits govern sleep-wake states by recruiting stable, invariant neuronal substrates, yet, this remains unknown. Here, we show that inhibitory, excitatory, hypocretins/orexins-, and melanin concentrating hormone-expressing neurons in hypothalamus did not exhibit stable state-specific activities using longitudinal single cell calcium imaging in freely-moving, sleeping male mice. Instead, their activity patterns shift across sleep-wake states over time, while the distribution of active neurons in each sleep state remains stable. While sleep deprivation minimally affected the selectivity of these activity patterns, we found that the sleep-promoting drug diazepam recruited NREM sleep-active cells that were previously inactive or wake-active. These findings indicate that while individual neurons exhibit dynamic, state-dependent shifts of their activity, the overall organization of sleep-wake neural populations remains stable.

Levels and determinants of healthcare-seeking delay for pediatric pneumonia: a mixed-methods study

Dynamic remodeling of the pancreas immune landscape in obesity

Image-based multiphysics modelling of random metallic meshes

Abstract Bio-inspired conductive networks are increasingly exploited in transparent heaters and smart multifunctional structures due to their inherent scalability, robustness, and efficient transport properties, yet their intrinsic disorder poses major challenges for quantitative modelling. Here we introduce a computationally efficient, image-driven framework for the automated digitisation, reconstruction, and multiphysics analysis of random conductive meshes. High-resolution microscopy images are converted into graph-based network representations via skeletonization, branch tracking, and connectivity refinement, preserving local geometry while drastically reducing degrees of freedom. An analytical model is developed to predict sheet resistance directly from extracted network metrics, enabling rapid, non-destructive electrical characterisation. The digitised networks are further used to perform coupled electro-thermal and electro-thermo-mechanical finite-element simulations. Experimental validation using silver mesh heaters embedded in polymer laminates shows excellent agreement with predicted electrical resistance, temperature evolution, and stiffness modulation under electrical loading. The framework reduces analysis time and enables systematic assessment of structural features, such as dangling branches, on device performance. This approach provides a scalable route for predictive design and optimisation of fractal-based multifunctional electronic materials.

Restoration of anti-bacterial innate immune cell function lags behind nutritional recovery among children convalescing from complicated severe acute malnutrition

Abstract Children recovering from complicated severe acute malnutrition (SAM) have a high risk of infectious mortality and morbidity, which could reflect impaired anti-microbial defence. We used blood samples from a cross-sectional cohort of children under 5 years’ old admitted to hospital with SAM in Zambia and Zimbabwe (cases, n  = 125) and adequately nourished non-hospitalised children from the same communities (controls, n  = 73) to characterise anti-bacterial innate immune cell function. We did not find evidence that inpatient immune function differed between cases who experienced subsequent adverse clinical outcomes (death, readmission, SAM at 48 weeks) versus those who did not. However, pro-inflammatory cytokine (IL-6, IL-8 and TNF) responses to E. coli lipopolysaccharide and heat-killed Salmonella typhimurium were positively associated with subsequent gains in mid-upper arm circumference, an indicator of nutritional recovery. We then characterised how innate immune cell function changed during post-discharge rehabilitation in a longitudinal sub-cohort of cases who provided repeat blood samples at discharge, 12, 24 and/or 48 weeks post-discharge ( n  = 83). Relative to inpatient immune function, bacterial binding capacity declined whilst anti-bacterial pro-inflammatory cytokine secretion increased in the cases over the post-discharge follow-up period with both normalising towards control ranges. These changes were also evident in cases who had recovered to a healthy nutritional status (weight-for-height Z score ≥ −2). Collectively, our data suggest that restoration of anti-bacterial innate immune cell function following complicated SAM lags behind nutritional recovery. Thus, children who are no longer wasted may continue to have deficient anti-bacterial innate immunity months after hospital admission for SAM.

Enhancing the fertilizing properties of digestate’s solid fraction by Trichoderma-driven microbial activation: In-field application effects on tomato growth

Electrochemical upcycling of spent ITO via charge-induced deconstruction

Abstract Spent indium tin oxide (s-ITO, the mass ratio of In 2 O 3 to SnO 2 is approximately 9:1) represents the main secondary resource for the rare metal indium, possessing exceptionally potential for reutilization. However, traditional hydrometallurgical or pyrometallurgical recycling methods grapple with substantial challenges, including low product purity, lengthy processes, and environmental pollution. This paper presents an electrochemical upcycling strategy for spent ITO based on charge-induced deconstruction, effectively addressing the aforementioned issues. In this approach, spent ITO serves as the anode in an aqueous electrolysis system. The number of oxygen vacancies on the ITO surface increases drastically under charge excitation, leading to weakened metal-oxygen bonds and the subsequent release of indium and tin ions into the electrolyte. These ions then migrate to the cathode, where high-purity indium tin alloy is obtained by leveraging the differences in electrochemical properties between impurity ions and the target metal ions. Notably, the electrolyte employed in this process can be reused, which significantly reduces wastewater generation. Through systematic optimization of electrolysis parameters, a cathode current efficiency of 71.12% and an energy consumption of 4.87 kWh kg −1 are achieved in a hundred-ampere scale trial, fully demonstrating the industrial applicability of this method.

Exosomal PD-L1 level in plasma as a predictive marker for prognostic and clinical correlation in NSCLC

Fungal diagnostics and antifungal drug access in Latin America and the Caribbean: an ESCMID EFISG multinational survey

Abstract Invasive fungal diseases (IFD) pose a major health challenge in Latin America and the Caribbean (LAC), particularly in vulnerable populations. A cross-sectional, survey is distributed between April 2023 and May 2025 to institutions involved in IFD diagnosis or care across LAC. The questionnaire evaluates diagnostic tools, antifungal availability, and therapeutic drug monitoring (TDM). A total of 619 institutions from 23 countries across LAC participate. Candida spp. (92%) and Aspergillus spp. (54%) are most frequently reported as major fungal threats. Culture (90%) is widely available, whereas access to galactomannan (41%), β-D-glucan (29%), and molecular testing (23%) is considerably lower. Availability of antifungals, including liposomal amphotericin B (38%), echinocandins (51%), voriconazole (57%) or posaconazole (33%) is significantly higher in countries with GDP per capita >US$ 10,000, in transplant centres, and in institutions managing people living with HIV. Therapeutic drug monitoring is available in only 36% of centres. Major diagnostic and treatment gaps persist in low-income countries, particularly in access to tools for identifying endemic mycoses. Substantial disparities exist in IFD diagnostic and treatment capacity across LAC, primarily driven by national income and institutional complexity. Strengthening laboratory infrastructure, antifungal access, and integration of fungal disease management into public health systems is urgently needed.

A novel pray optimization algorithm for six degree of freedom robotic arm trajectory planning

Abstract This study introduces the Pray Optimization Algorithm (POA), a novel metaheuristic inspired by the procedural rituals of Islamic pray, designed to solve complex engineering and robotic manipulator problems. The mathematical model is structured into three distinct phases: Phase I simulates searching for a suitable mosque; Phase II models congregational alignment (lining up for pray); and Phase III implements a cumulative scoring system to drive convergence. The efficacy of the POA is initially validated on the CEC2017 benchmark suite through comparative analysis with six high-performing metaheuristic algorithms. The algorithm’s statistical superiority is subsequently confirmed using the Wilcoxon rank-sum and Friedman tests. To verify its practical applicability, the POA is deployed to solve three classical real-world engineering optimization problems. Ultimately, the algorithm demonstrates superior performance when compared against five state-of-the-art methods in optimizing the trajectory planning of a 6-DOF industrial robotic arm. These findings substantiate the effectiveness of the proposed POA in navigating constrained, real-world engineering search spaces.

Impact of currents on non-equilibrium coexistence in chemically driven mixtures

Virtually every biological function emerges through the organization of molecules in time and space. Consequently, a major challenge in statistical physics is to uncover the universal principles governing macromolecular self-organization within the crowded, non-equilibrium environment of the cell. Here, we investigate a class of models where molecules maintain a conserved total concentration but can switch “identities,” thereby modulating their intermolecular interactions. By enforcing thermodynamic consistency via the local detailed balance condition, we derive the steady-state criteria determining coexisting concentrations in a binary mixture. In particular, local detailed balance together with state-dependent kinetics impose a difference in chemical potentials across the interface, and we obtain jump conditions that generalize Gibbs’ equilibrium coexistence criteria of equal pressure and chemical potential to chemically driven steady states. Maintaining the chemical potential differences requires particle currents, which are confined to the interfacial region.

Table-top all-attosecond transient absorption spectroscopy

Abstract Attosecond transient absorption spectroscopy (ATAS) has emerged as a powerful technique within the field of attosecond science, combining extremely high temporal and excellent spectral resolution. So far, ATAS has been implemented in pump-probe experiments where an attosecond extreme-ultraviolet (XUV) pump or probe pulse was combined with a near-infrared (NIR) pulse in the femtosecond range, with the attosecond time resolution deriving from sub-cycle NIR-driven dynamics. Investigations of ultrafast electron dynamics in atoms, molecules and solids, with potential impact across physics, chemistry, and biology, would benefit significantly from the ability to perform all-attosecond transient absorption spectroscopy (AATAS). Here we demonstrate time-resolved AATAS using a table-top high-harmonic generation (HHG) source. The method is applied to investigate previously unresolved electronic coherences in Xe, revealing oscillatory valence hole motion with a 3-femtosecond period. In addition, systematic investigations of electron dynamics in Kr, Ar, and Ne are presented. Our work shows that, thanks to its broad bandwidth, high stability and easy accessibility, HHG is an ideal source for AATAS, offering the potential for replication in numerous laboratories.

RMSD: an interpretable framework for streaming-compatible multi-source data fusion and skill-gap diagnosis in vocational education

Abstract Vocational education often faces a mismatch between curriculum design and evolving enterprise skill demands. This paper proposes RMSD, an interpretable framework for streaming-compatible multi-source data fusion, student–job matching, and skill-gap diagnosis. RMSD integrates student records, behavioral logs, project and internship information, job descriptions, and enterprise feedback. It combines BERT-based semantic encoding, temporal self-attention, CFN-based multimodal fusion, and hierarchical skill-tree context to estimate matching scores and node-level skill gaps. Experiments on student–enterprise interaction data show that RMSD outperforms representative baselines, including DeepFM, NCF, BERT-Dual Encoder, Transformer-Seq, and Skill-KG Matching. Compared with DeepFM, RMSD improves HR@5 and MRR@10 by 5.7 and 4.7 percentage points, respectively. It also reduces the average skill-gap score from 0.42 to 0.30 during the observed curriculum-intervention period. System-level evaluation shows that RMSD supports near-real-time updates under the tested institutional workload. These results suggest that RMSD offers a practical and interpretable approach for data-driven vocational education analytics.