Browse Articles

Geographic spillover of antimicrobial resistance from mass distribution of azithromycin

Abstract Large-scale, placebo-controlled, cluster-randomized trials in high-mortality settings in sub-Saharan Africa demonstrated a 14–18% reduction in childhood mortality following twice-annual mass drug administration (MDA) of azithromycin among children aged 1–59 months. Azithromycin MDA also selected for antimicrobial resistance (AMR), particularly macrolide resistance. It is unknown whether the AMR from azithromycin MDA could spill over to neighboring untreated populations. If present, such geographic spillover effects could lead trials to underestimate AMR risks. We assess between-village geographic spillover effects of genotypic macrolide resistance using metagenomic deep sequencing in rectal swabs collected from 300 children in 30 monitoring villages in Niger after two years of MDA in 594 surrounding villages. Conditional permutation tests assess associations between proximal azithromycin treatment intensity and resistance gene abundance. We find no evidence of geographic spillover of macrolide resistance in untreated villages, as the genetic load of AMR remains at baseline levels in placebo-treated villages regardless of surrounding azithromycin treatment intensity (Spearman ρ = −0.05, P  = 0.83). Sensitivity analyses confirm robustness across metrics, and no spillover effects are detected for other antibiotic classes. Azithromycin MDA-induced macrolide resistance appears localized to treated villages, mitigating some concerns about geographic spillover of AMR to nearby untreated villages at 24 months.

Clinical features and inflammatory signatures of patients with persistent gastrointestinal long COVID two years after severe SARS-CoV-2 infection

Abstract Persistent gastrointestinal (GI) symptoms are increasingly recognized as part of long COVID, yet their underlying mechanisms remain poorly defined. We conducted an exploratory case-series study of 80 adults hospitalized with severe COVID-19 in March-May 2020 in Manaus, Brazil. Two years post-infection, participants underwent structured clinical interviews and longitudinal cytokine analysis (IL-1β, IL-6, IL-8, IL-10, IL-12, and TNF-α). Overall, 30 participants reported ongoing GI symptoms (GI group) predominantly gastroesophageal reflux (63%), abdominal pain (43%), and diarrhea (37%). Compared with participants without GI symptoms (nGI group, n  = 50), the GI group reported a higher burden of additional long COVID symptoms, including palpitations, headache, and arthralgia. They also exhibited distinct clinical and laboratory features, including lower baseline creatinine and ferritin levels and altered platelet indices. Although IL-6 levels were lower during the acute hospitalization phase, they became significantly elevated at four months post-infection (D120, p  = 0.005), suggesting delayed inflammatory response. Ascendent biomarker analysis identified TNF-α as highly expressed in a large proportion of GI group. The findings suggest GI problems can persist two years after severe COVID-19, and long-term inflammatory dysregulation may underlie the pathogenesis of these GI manifestations in long COVID. Prolonged gastrointestinal surveillance in COVID-19 survivors is necessary.

How ‘forest bathing’ keeps lungs healthy

Photothermal effects control ultrafast charge transport in titanium carbide MXenes

Abstract Titanium carbide MXene (Ti₃C₂T ₓ ) is an emerging metallic material with promise for (opto)electronics and thermal management. Yet how photoexcitation—particularly via photogenerated thermal energy—modifies its charge carrier dynamics remains poorly understood. By combining time-resolved terahertz spectroscopy and transient reflectance measurements, we reveal a long-lived, photo-induced suppression of conductivity, which we attribute to efficient lattice heating and slow heat dissipation in Ti₃C₂T x . A systematic variation of pump photon energy reveals that this ‘negative’ photoconductivity can equivalently be induced by lattice temperature increases, indicating a thermal origin. Repetition-rate-dependent transient reflectance measurements further show residual heat persisting over 100 ns, substantially longer than in conventional metals. Our work presents a unified understanding of photothermal effects in Ti₃C₂T ₓ and their influence on non-equilibrium charge transport, underscoring its potential for photothermal electronics and light-to-thermal energy storage applications.

Reliability-based assessment of road design features and crash risk using a socio-economic index for safety prioritization

Abstract This study investigates the relationship between road design features and crash risk on a 186 km segment of Highway No. 36 in Iran. A socio-economic risk index was developed by integrating Empirical Bayes crash predictions, severity-based social crash costs, and construction cost estimates. This index was incorporated into a reliability framework, where limit-state functions and Monte Carlo simulation were used to compute the exceedance probability of crash risk. Geometric data were collected through field surveys, and traffic and crash data were obtained from the Khorasan Razavi Road Maintenance and transportation organization’s database (2019–2023). The results show that horizontal curves have the highest crash risk, while segments longer than 4 km exhibit the lowest values. Crash risk also increases with wider lanes, gravel shoulders, greater shoulder widths, and embankment slopes steeper than 4%. Grades between 0 and 3% reduce risk, whereas steeper grades elevate it. Guardrails demonstrate mixed effects, reducing risk at lower levels but not consistently at higher ones. The reliability-based probabilistic framework integrates crash data, societal costs with severity, and construction costs to systematically prioritize safety interventions, offering a clear methodological advantage over deterministic approaches.

Funding cuts could put research into emerging threats to lung health at risk

Machine-learning-guided tungsten single atoms promote oxyhydroxides for noble-metal-free water electrolysis

Green zinc oxide nanoparticles improve zinc bioavailability and mitigate high temperature stress in rice

A flexible digital compute-in-memory chip for edge intelligence

Imaging multilevel exciton transport enabled by correlated electronic states

High levels of Interleukin − 13 in patients with scrub typhus correlate with disease severity

The complex role of nutrients in cancer spread

Spinal cord stimulation therapy for gait impairment in Parkinson’s disease: a double-blinded, randomised feasibility trial with an open extension

Mechanistic insights into the lipotropic and atheroprotective effects of rosuvastatin-loaded glycerosomes in dyslipidemic rats

Abstract Dyslipidemia is a major risk factor for the development of NAFLD, atherosclerosis and cardiovascular diseases. Rosuvastatin (ROS) is a lipid-lowering drug that protects against the development of NAFLD and atherosclerosis. However, the mechanism of this protection remains obscure. Therefore, the current study aims to explore the mechanism by which ROS-loaded glycerosomes (ROS-GLY) protect against NAFLD and atherosclerosis. Hence, for this purpose, hepatic lncRNA-H19/miR-130a/PPAR-γ and aortic PPAR-γ/LXRα/ABCA1 signaling pathways were assessed. In addition, these target pathways were predicted using molecular docking analysis. Thirty-five male Sprague Dawley rats were separated into control, dyslipidemic (poloxamer 407 (P 407)), P 407+ROS-GLY, P 407+NC, and P 407+ROS-GLY+NC groups. ROS-GLY improved lipid profile, hepatic MDA, SOD, catalase and total antioxidant capacity (TAC) in compared to P 407 group. In the dyslipidemic group, ROS-GLY downregulated hepatic lncRNA-H19 expression which leads to an upregulate of the miR-130a level and subsequent reduction of the PPAR-γ level. Consequently, the hepatic expression level of lipogenic genes such as, ACC-1, FASN and SCD-1 was significantly downregulated in the ROS-GLY group than the dyslipidemic one. Aortic PPAR-γ/LXRα/ABCA1 signaling pathway was significantly upregulated in the ROS-GLY group compared to the dyslipidemic group. Furthermore, ROS-GLY modulated IL-6 and IL-10 immunoprotein expression in hepatic and aortic tissues. Interestingly, ROS showed a substantial binding affinity with PPAR-γ, LXR-α, and FASN, according to a molecular docking study. The current study indicated that ROS-GLY protected against the progression of NAFLD and atherosclerosis in dyslipidemic rats via modulation of lipid profile, oxidative stress, pro-/anti-inflammatory cytokines, hepatic lncRNA-H19/miR-130a/PPAR-γ, and aortic PPAR-γ/LXRα/ABCA1 signaling pathways.

Limit of atomic-resolution-tomography reconstruction of amorphous nanoparticles

Expression of CD38+CD8+ T cells in hepatitis B-related acute-on-chronic liver failure and its prognostic value

A new method for predicting the shear strength of loess based on moisture content and large and medium pore volume

Synthesis and characterization of g-C3N5/CuS/AgNPs nanocomposite as a Z-scheme photocatalyst for efficient methyl parathion degradation

Abstract Water pollutants constitute a significant environmental concern today. Organophosphorus compounds, notably parathion, represent a critical category of water pollutants. Their extensive usage poses substantial risks to human health and the environment, necessitating their removal from water sources. This study focuses on the photocatalytic degradation of parathion, utilizing a g-C 3 N 5 /CuS/AgNPs nanocomposite synthesized through a combination of hydrothermal and ultrasonic methods. The nanocomposite was characterized using microscopic and spectroscopic techniques and demonstrated the capacity to degrade approximately 94.90% of parathion in the presence of visible light within one hour at pH 6. Parameters such as pH, initial pollutant concentration, and photocatalyst concentration were optimized. The study’s findings highlight that • O 2 − and • OH play a predominant role in the degradation process of this contaminant.

Advancing regulatory variant effect prediction with AlphaGenome

Abstract Deep learning models that predict functional genomic measurements from DNA sequences are powerful tools for deciphering the genetic regulatory code. Existing methods involve a trade-off between input sequence length and prediction resolution, thereby limiting their modality scope and performance 1–5 . We present AlphaGenome, a unified DNA sequence model, which takes as input 1 Mb of DNA sequence and predicts thousands of functional genomic tracks up to single-base-pair resolution across diverse modalities. The modalities include gene expression, transcription initiation, chromatin accessibility, histone modifications, transcription factor binding, chromatin contact maps, splice site usage and splice junction coordinates and strength. Trained on human and mouse genomes, AlphaGenome matches or exceeds the strongest available external models in 25 of 26 evaluations of variant effect prediction. The ability of AlphaGenome to simultaneously score variant effects across all modalities accurately recapitulates the mechanisms of clinically relevant variants near the TAL1 oncogene 6 . To facilitate broader use, we provide tools for making genome track and variant effect predictions from sequence.

A meta learning framework for few shot personalized gait cycle generation and reconstruction