Browse Articles

National Elimination of Hepatitis C — The Case for Starting in Prisons and Jails

Switchable Copula-guided Transformer diffusion model for detecting small sea-surface targets

Abstract Detecting low, slow and small maritime targets remains difficult because sea clutter is non-uniform, non-stationary, non-Gaussian and often observed at extremely low signal-to-clutter ratios. Here we present a switchable Copula-guided Transformer denoising diffusion probabilistic model (SCT-DDPM) for unsupervised radar target detection. The framework replaces the conventional i.i.d. Gaussian forward prior with Copula-structured noise, uses a copula-aware weighted MSE objective to align denoising with the observed dependence structure, and combines diffusion-based anomaly attention with Transformer encoding to score target-like deviations from normal clutter. Across 13 Copula families on the IPIX radar dataset, SCT-DDPM maintained high detection performance. These results show that dependence-aware diffusion priors can improve target-clutter separability and provide a statistically grounded route for configuring diffusion models in complex maritime environments.

Polyesterification-assisted interface engineering of carboxylate metal-organic frameworks membranes for selective gas separation

Daraxonrasib or Chemotherapy in Previously Treated Metastatic Pancreatic Cancer

Real-time ultrasonic monitoring of cement composites reinforced with recycled wind turbine blade fibers

Abstract Cement composites with the addition of fibers from wind turbine blades and polypropylene fibers are an innovative material, based, among other things, on the replacement of fibers produced in manufacturing processes with recycled fibers, in this case from wind turbines. Testing such materials to assess the potential of the proposed solution is important, but the full scope of destructive testing and long-term laboratory analysis would involve high costs and significant material consumption. For this reason, non-destructive methods are particularly useful. This article presents considerations and research on the continuous measurement of the velocity and acceleration of ultrasonic wave propagation in the tested material, conducted in real time. The work presents research in this area and points to the benefits of using the ultrasonic method, such as the ability to estimate strength, determine the dynamic Young’s modulus, analyse the homogeneity of the structure and monitor the course of hydration processes. This study proposes a sustainable material innovation that involves the replacement of traditional fibers with recycled ones.

cellGeometry: ultra-fast single-cell deconvolution of bulk RNA-Seq using a geometric solution

Abstract Single-cell analysis has rapidly expanded to produce cell atlases encompassing all human tissues. However, computational methods to deconvolute bulk samples using single-cell reference data have failed to keep pace with the increasing data size. Here we present cellGeometry, which uses non-negative geometric deconvolution (NGD), an intuitive vector projection method featuring non-negative matrix regularisation. Using matrix operations, cellGeometry scales to massive datasets and is ultrafast. Benchmarked using simulations from single-cell/nucleus RNA-Seq datasets with >3 million cells, cellGeometry is more accurate than existing methods and more robust against noise simulating different sequencing chemistries. It identifies outlying residual genes which may unveil pathogenic changes in gene expression and the presence of cell types absent from the reference. cellGeometry’s flexible architecture allows merging of single-cell reference signatures to expand the range of cell types being deconvoluted. Validated against real bulk RNA blood and tissue samples, cellGeometry produces more accurate and realistic results.

Klebsiella Brain Abscess and Evolution of Heterovirulence in the Urinary Tract

FedRAPT: federated representation-aligned prototypical contrastive learning

Characterization and evolutionary history of novel SARS-CoV-2-related viruses in bats from Cambodia

Abstract Circulating bat coronaviruses present a significant pandemic threat, yet our understanding of their genetic diversity and evolutionary dynamics remains limited. Over 3 years, we sampled 1,462 bats in Cambodia’s Steung Treng province, identifying extensive and diverse coronaviruses co-circulation. Using metatranscriptomic and amplicon sequencing, we generated 33 complete sarbecovirus genomes sequences, revealing novel lineages that cluster into four distinct groups, each associated with different Rhinolophus bat species. Our analysis highlights rapid migration and recombination of sarbecovirus lineages over short distances and timescales. Of note, the receptor-binding domains of two novel viral groups exhibit high similarity to SARS-CoV-2, and pseudovirus assays confirmed the ability of this spike protein to mediate entry into cells expressing human ACE2, suggesting a potential zoonotic risk. The observed genetic diversity underscores the urgent need for continuous surveillance to identify high-risk animal-to-human interfaces and inform pandemic preparedness.

A New Standard in Muscle-Invasive Bladder Cancer — The End of the Cisplatin Era?

Triglyceride-glucose index and mortality risk in patients undergoing PCI

Acute rapamycin treatment reveals distinct mechanisms of dysfunction in a maternal inflammation mouse model

Abstract Maternal inflammatory response (MIR) during early mouse gestation induces a cascade of physiological and behavioral changes associated with autism spectrum disorder (ASD). We have shown that mild MIR causes chronic systemic and brain inflammation, mTOR pathway activation, mild brain overgrowth with regionally specific volumetric changes, sensory processing dysregulation, and repetitive behavior abnormalities. Prior rapamycin studies in autism models focused on chronic treatments that alter or prevent physical brain changes. Here, we focus on acute rapamycin effects to uncover novel mTOR pathway-mediated mechanisms of dysfunction. Within 2 hours, rapamycin rescues neuronal hyperexcitability, seizure susceptibility, functional network connectivity, brain community structure, repetitive behaviors, and sensory over-responsivity in adult MIR offspring. These CNS-mediated effects coincide with altered expression of genes associated with ASD, ion channels, and epilepsy. Our findings demonstrate that mTOR dysregulation drives dysfunctional brain development in MIR offspring but the adult brain remains amenable to rapid functional normalization, rescuing core and comorbid ASD-associated brain and behavior phenotypes. Restoring excitatory/inhibitory imbalance and sensory functional network modularity may be important targets for therapeutically addressing multiple ASD phenotypes.

When Celebrities Prescribe — Regulating Drug Promotion on the Internet

Aerodynamic analysis of Savonius and 3-bladed Darrieus-type vertical axis wind turbine utilizing NACA0012 and NACA0015 airfoils

Abstract This study investigates the aerodynamic performance of vertical axis wind turbines (VAWTs) operating under low wind-speed conditions representative of inland and urban environments. A combined numerical-experimental approach was adopted, wherein the aerodynamic characteristics of a three-bladed Darrieus-type VAWT employing NACA0012 and NACA0015 airfoils were evaluated numerically, while complementary wind tunnel experiments were conducted on a geometrically accurate Savonius rotor to examine its low-speed performance. The numerical methodology for the Darrieus turbine was first validated against established benchmark studies and subsequently employed to perform transient Computational Fluid Dynamics (CFD) simulations using the sliding-mesh technique in ANSYS Fluent. Simulations covered Reynolds numbers ( Re ) ranging from 5.3 × 10 4 to 2.67 × 10 5 , with a near-wall grid resolution of 10 −5 m, convergence criterion of 10 −6 , and appropriate viscous models (laminar and k–ω SST) selected according to the flow regime. Experimental investigations on the Savonius turbine were carried out in a calibrated subsonic wind tunnel using 3D-printed Polylactic Acid (PLA) models over a Re range of 2.53 × 10 4 to 1.27 × 10 5 . The numerical study examined the influence of freestream velocity and tip speed ratio (2.0 ≤ TSR ≤ 3.0) on the lift coefficient, drag coefficient, and aerodynamic torque of the Darrieus turbine. At TSR = 2.5 and 6–10 m/s, the NACA0015 airfoil produced 21.9–84.3% higher cycle-averaged aerodynamic torque while reducing the Moment Fluctuation Index (MFI) by 14.8–22.6% compared to the NACA0012 airfoil. The experimental observations on the Savonius rotor further confirm its suitability for low-wind-speed operation and provide practical validation of VAWT performance under realistic conditions. The study highlights the influence of airfoil geometry on Darrieus turbine performance while demonstrating the effectiveness of Savonius rotors for low-speed applications, offering useful design insights for decentralized wind energy systems in regions with limited wind resources.

Author Correction: Synthesis of enantioenriched atropisomers by biocatalytic deracemization

Versatile electronic phases enabled by intertwined multiple frustrations in an antiferromagnetic two-dimensional semimetal

Abstract Following the discovery of graphene, van der Waals materials have become a major platform for quantum matter, yet strongly interacting phases beyond graphene remain elusive. Using scanning tunneling microscopy and spectroscopy, we uncover three competing stripe- and checkerboard-type multiple-q antiferromagnetic charge-ordered states in the van der Waals semimetal CeTe 3 , beyond the conventional charge density wave. These field-tunable states exhibit propagation vectors of (0.33, 0), (0, 0.08), and (0.19, ±0.19), and are controlled by a modest in-plane magnetic field (~1.5 T). Quasiparticle-interference imaging identifies corresponding three distinct nesting channels and associated Fermi-surface reconstructions. At the same time, spectroscopy reveals a broad electronic reconstruction extending to ±30 meV around the Fermi level, beyond a simple Kondo-coupling picture. Our results establish CeTe 3 as a platform for tunable nanoscale antiferromagnetic electronic phases characterized by intertwined correlations, exotic symmetry-breaking, and nontrivial topology.

Clinical Long-Read Genome Sequencing for Rare-Disease Diagnostics

Distribution network resilience enhancement with coordinated mobile V2G stations and electric vehicles from parking lots

Discrete distributions are learnable from metastable samples

Abstract Physically motivated stochastic dynamics are widely used to sample from high-dimensional distributions. However, such samplers often get trapped in metastable states, approximately sampling from a distribution that differs significantly from the desired stationary state. We rigorously show that for multivariable discrete distributions, the true stationary model can nevertheless be recovered from these metastable samples. This relies on a fundamental observation: for distributions satisfying a strong metastability condition, their single-variable conditional probabilities are on average extremely close to those of the true stationary distribution. This remains true even when the two distributions are far apart under global metrics such as Kullback-Leibler divergence. Consequently, we can effectively learn the true model using a conditional-likelihood estimator even when the samples are drawn from a restricted state space. Extending these general results to Ising models, we prove rigorous parameter and structure learning guarantees. Finally, we demonstrate this phenomenon numerically on higher-alphabet spin glass models.

Left Atrial Appendage Closure in Atrial Fibrillation