Browse Articles

Differential activity of nonmuscle myosin IIA and IIB isoforms generates a dynamic actomyosin network in a concentration-dependent manner

Immunometabolic determinants of hepatitis B vaccine seroprotection among Ethiopian adults

In Situ Raman Spectroscopic Insight of Hydrogen Spillover in Electrocatalytic Hydrogenation

Adult patients with autoinflammation of unknown origin partially phenocopy the immune presentation of Still’s disease

Abstract Autoinflammation of unknown origin remains amongst the most enigmatic of systemic autoinflammatory disorders (SAID), with systemic autoinflammatory symptoms in the absence of a molecular or clinical diagnosis with a recognized SAID. Here, we aim to understand the immunological process behind patients with autoinflammation of unknown origin. We collect samples from 36 patients manifesting recent disease activity across 30 European medical centers, and employ deep immunophenotyping and plasma proteomics to compare to 58 healthy controls and an additional demographically similar cohort comprising 92 SAID patients. Machine-learning approaches identify key immunological changes, including the upregulation of CD38 and HLA across T cell subsets and the upregulation of acute-phase plasma proteins in autoinflammation of unknown origin patients. The immunological traits of these previously poorly characterised patients partially phenocopy Still’s disease presentation. Thus, this study identifies potential biomarkers and disease mediators in autoinflammation of unknown origin.

Structural insights into specific recognition of the histone variant H2A.Z by the YL1 subunit of SRCAP chromatin-remodeling complex

Comparative performance analysis of U-Net and DeepLabV3+ for semantic segmentation in traffic environments

Abstract Computer vision is an important field of artificial intelligence that enables machines to interpret and understand visual information from images. It is the basis of automated visual understanding in smart systems. Monitoring of streets, recognizing different vehicles and pedestrians, and comprehending the ever-changing traffic conditions for making right decisions are some of the features of modern intelligent traffic systems. It is indispensable for a computer to visually recognize the semantic segmentation (SS) of a scene, as it maps each and every pixel of the image to the categories like roads, vehicles, pedestrians, traffic lights, etc. However, existing traffic scene segmentation models often perform poorly under challenging conditions such as low lighting, blur, noise, and low resolution. These limitations limit the robustness of these methods. They can be a major obstacle to the development of autonomous vehicle technologies because they reduce the ability of perception systems to recognize a wide range of situations. This work proposes a new method for processing poor quality traffic images by sequentially applying super-resolution (SR), semantic segmentation (SS), and object detection with YOLOv8x. The SR module transforms degraded inputs, while U-Net and DeepLabV3+ are exploited for accurate pixel-level segmentation mask generation. Besides, YOLOv8x provides the precise object detection, which is really one of the critical steps for the avoidance of the errors in the crowded and complicated TSs. YOLOv8x uses bounding boxes to check segmentation and raise mAP. U-Net delivers PSNR of 41.93 dB, SSIM of 0.997, mIoU of 0. 750, and mAP of 0.950, whereas DeepLabV3+ yields PSNR of 46.03 dB, SSIM of 0.938, mIoU of 0.819, and mAP of 0.937.

Electrocatalytic C–S Coupling for Efficient Organosulfur Electrosynthesis from Mixed Polyols with >99% of Carbon Selectivity

Deciphering the Hidden Ecology and Connectivity of Vibrio in the Oceans

Abstract Long-range dispersals of marine bacteria in the oceans have remained largely indecipherable, which is particularly relevant for Vibrio , responsible for global epidemics in humans and animals. Here, we combine the analysis of 40 terabases of metagenomic data and satellite-tracked surface drifter data, from across the globe revealing that Vibrio are abundant members of the ocean surface and show a strong association with microplankton, which appears to govern their distribution and connectivity at a global scale. We identify long-distance biological corridors connecting Vibrio communities, including potentially pathogenic Vibrio . These corridors allow movement over thousands of kilometres in a fairly short time, with estimates of less than 1.5 years to cross an ocean basin. These findings have deep implications for the demography and community dynamics of Vibrio species and the epidemiology of associated diseases.

Deficient mitochondrial tRNA modifications arising from TRMU mutation led to the liver-specific failure

Coral morphology detection in underwater imagery using YOLOv12 with CNN and transformer encoder fusion

Pillar[5]arene-catalyzed anti-Markovnikov halogenations through cationic intermediates stabilization in confined spaces

Abstract The confinement of reactants within catalytic cavities is important for achieving efficient and selective chemical transformations. Macrocyclic organic covalent hosts, which mimic enzymatic environments, offer well-defined, tunable cavities capable of substrate accommodation. These robust and synthetically accessible hosts can be engineered into catalysts by functionalizing their rims, where substrate selectivity emerges from size- or shape-complementary binding. This positioning brings reactive sites into proximity with catalytic functional groups at the rims of covalent hosts, accelerating reactions. Cationic intermediates are pivotal in many chemical transformations, and stabilizing these reactive species within confined microenvironments could unlock unconventional selectivity for synthesizing high-value compounds. Despite this potential, leveraging the cavities of covalent hosts to stabilize and confine cationic intermediates for regioselective reactions remains underexplored. Here we report that the π-basic cavity of pillar[ n ]arenes can effectively stabilize bromiranium intermediates generated during olefin halogenation, confining them in a controlled microenvironment. This strategy overrides the intrinsic Markovnikov preference, enabling highly selective anti-Markovnikov halogenation. Furthermore, we extend this catalytic system to achieve size-selective anti-Markovnikov halogenation of olefins. This approach opens new pathways for selective transformations through the confinement of a cationic intermediate.

Human pumilio proteins use fuzzy multivalent hydrophobic interactions to recruit the CCR4–NOT deadenylase complex to repress mRNAs

Enhancing island biogeography: improving identification of potential species pools via environmental filtering

Bidirectional yet asymmetric causality between urban systems and traffic dynamics in 30 cities worldwide

Abstract Understanding how urban systems and traffic dynamics co-evolve is crucial for advancing sustainable and resilient cities. However, their bidirectional causal relationships remain underexplored due to challenges of simultaneously inferring spatial heterogeneity, temporal variation, and feedback mechanisms. Here we present a spatio-temporal causality framework that bridges correlation and causation by integrating spatio-temporal weighted regression with spatio-temporal convergent cross-mapping. Characterizing cities through urban structure, form, and function, the framework uncovers bidirectional causal patterns between urban systems and traffic dynamics across 30 cities on six continents. Our findings reveal asymmetric bidirectional causality, with urban systems exerting stronger influences on traffic dynamics than the reverse in most cities. Urban form and function shape mobility more profoundly than structure, even though structure often exhibits higher correlations. This does not preclude the reversed causal direction, whereby long-established mobility patterns can also reshape the built environment over time. Finally, we identify three causal archetypes: tightly coupled, pattern-heterogeneous, and workday-attenuated, which support city-to-city learning and inform context-sensitive strategies in sustainable urban and transport planning.

G protein Gαq subunits engage targets in the nucleus involved in chromatin remodeling and gene expression

Ecological legacies of pre-Columbian settlements evident in palm clusters of neotropical mountain forests

Single-event fast neutron time-of-flight spectrometry with a petawatt-laser-driven neutron source

Abstract Laser-driven neutron sources (LDNSs) offer unique advantages for fundamental physics and applications: ultrashort pulses providing superior energy resolution, high instantaneous flux, and a reduced footprint. While single-event neutron spectroscopy has been demonstrated with epithermal neutrons, its application for fast neutrons is more challenging and remains unproven. This demands stable multi-shot operation and detectors resilient to this particularly extreme environment. Here, a proof-of-concept experiment at the DRACO PW laser is presented. This setup stably produced  ~ 10 8 fast neutrons per shot sustained over more than 200 shots at a shot-per-minute rate. Neutron time-of-flight measurements with a diamond detector at only 150 cm from the source resolved individual neutron-induced reactions at a rate consistent with simulations informed by real-time diagnostics of accompanying gammas, ions, and electrons. Combined with the recent advances in the field, this work establishes LDNSs as a promising, scalable platform for future fast neutron-induced reaction studies, particularly those involving short-lived isotopes.

Sialic acids modulate immune responses in cancer: Therapeutic opportunities

Correction: Reciprocal cooperative gating fusion of SqueezeNet and ShuffleNetV2 for breast cancer detection in histopathology images

Disulfide modification and thiol protection via tris(trimethylsilyl)silane-mediated hydrosilylation of disulfides

Abstract Thiol functionalities are indispensable in both biological and synthetic chemistry. However, unlike the powerful silylation strategies for hydroxyl groups, widespread applications in sulfur chemistry are severely hampered by the weak and hydrolytically labile nature of the Si–S bond. Here, we report that tris(trimethylsilyl)silane (TTMSS), a unique trisilyl-substituted reagent, efficiently enables the rapid hydrosilylation of disulfides under exceptionally mild conditions. This reaction affords robust silyl sulfides that show significantly enhanced hydrolytic stability compared to conventional analogues. The robust platform enables a practical, readily available strategy for orthogonal thiol protection and late-stage disulfide modification in complex molecules. Crucially, this finding reveals that the kinetic and thermodynamic properties of the Si–S bond can be finely tuned by strategic silyl substitution, establishing a general principle that reinvigorates silyl-protective methods for challenging sulfur chemistry.