Browse Articles

Enhancing long-term structure in symbolic music generation via a cascaded Skeleton-to-texture framework

Use of a cytochrome P450 humanized mouse model to refine schistosomiasis drug discovery

Control of schistosomiasis, a neglected tropical disease caused by infection with Schistosoma spp ., remains reliant on a single chemotherapy, praziquantel (PZQ). This strategy presents a risk to global health should PZQ-resistant schistosomes establish in endemic areas and justifies the search for new drugs. However, species-specific metabolic differences between humans and preclinical models hinder the optimization of next-generation anti-schistosomal therapeutics. Here, to bypass these species-specific limitations, we exploited a humanized mouse model, 8HUM, engineered to express the principal human Phase I cytochrome P450 enzymes (CYP1A1/2, CYP2C9, CYP2D6, CYP3A4/7) as well as the transcription factors constitutive androstane receptor and pregnane X receptor in place of 35 murine orthologs. We characterized Schistosoma mansoni development, immunopathology, hepatic transcriptomic responses, intestinal microbiome changes, and PZQ metabolism as well as PZQ efficacy in 8HUM vs. wild-type (WT) mice. 8HUM mice supported normal S. mansoni maturation, infection-associated microbiome dysbiosis, Th2-dominant immune responses, and characteristic hepatic pathology. PZQ intrinsic clearance in 8HUM hepatic microsomes mirrored human levels and was >10-fold lower than that found for WT microsomes. Oral dosing revealed human-like PZQ exposures of ( R )-PZQ and 4OH-PZQ in 8HUM mice at 25 mg/kg bodyweight and >90% reductions in worm burdens at 100 mg/kg bodyweight (equivalent to that seen in WT mice administered PZQ at 400 mg/kg bodyweight). Our results revealed that 8HUM mice recapitulate key features of murine schistosomiasis while exhibiting human-relevant drug metabolism. These findings establish 8HUM as a refined translational platform for anti-schistosomal drug development, improving predictive accuracy and accelerating therapeutic discovery.

Application of a new assignment algorithm based on the minimax difference in earthquake emergency rescue

Daily briefing: The air is full of DNA — here’s what it can teach us

Spinal pain and associated factors among young motorcyclists a cross-sectional study with mediating analysis

Reciprocal regulation of TNF receptor 1–mediated signaling and inflammatory damages by MARCH2 and USP22

The tumor necrosis factor (TNF) receptor 1 (TNF-R1) plays critical roles in inflammatory response and autoimmune diseases. The underlying mechanisms on posttranslational regulation of TNF-R1 and its functional significance remain enigmatic. In this study, we identified the deubiquitinase USP22 as a positive regulator of TNF-R1. USP22 is minimally associated with TNF-R1, which is markedly increased following TNF stimulation. USP22 deconjugates K27-linked polyubiquitination of TNF-R1 at K340, which reverses its proteasomal degradation. USP22 deficiency reduces TNF-triggered signaling and transcriptional induction of proinflammatory genes in human cell lines and primary mouse immune cells. Conversely, the membrane-associated E3 ligase MARCH2 is constitutively associated with TNF-R1, resulting in K27-linked polyubiquitination of TNF-R1 at K340 and its proteasomal degradation. MARCH2 deficiency promotes TNF-triggered signaling in various cell types. In mice, USP22 deficiency alleviates imiquimod (IMQ)-induced psoriasis-like dermatitis with reduced inflammatory cell infiltration and splenomegaly. In an acute liver injury model, USP22 deficiency reduces TNF/D-gal-induced inflammatory cytokine expression, liver damage, and inflammatory death, whereas MARCH2 deficiency increases TNF/D-gal-induced inflammatory cytokine expression and exacerbates pathological features of acute liver injury. These findings demonstrate that MARCH2 and USP22 reciprocally regulate K27-linked polyubiquitination and stability of TNF-R1, revealing regulatory mechanisms on TNF-R1-mediated inflammatory response.

Integrated HPLC and STOCSY reveal two new lanaroft type biflavonoids from Selaginella plants

A high-efficiency multi-port bidirectional converter for renewable energy and hybrid electric vehicle applications

Many paths to destruction: Family-specific turnover and stress responses for tRNA introns

In organisms ranging from Archaea to humans, a subset of genes encoding tRNAs contain introns. Upon splicing, the tRNA exons are joined and the released free introns are rapidly degraded. Although tRNAs introns were previously considered to be “junk” sequences, we recently reported that free tRNA introns (fitRNAs) of Saccharomyces cerevisiae serve as negative regulators of the cellular levels of mRNAs that bear long stretches of open reading frame sequence complementarity to tRNA introns. We also reported that 2 of the 10 families of tRNA introns accumulate to elevated levels when cells suffer oxidative stress. The results led to the current investigations of the regulation of tRNA intron cellular levels. We document that tRNA intron turnover occurs by combinations of 5’ RNA kinases, 5’ to 3’ and 3’ to 5’ exonucleases as well as by at least three endonucleases and, generally, the levels of each tRNA intron family are regulated by a unique combination of nucleases/kinases. Similarly, one family of excised intron forms circles whereas the other free tRNA intron families do not. Further, levels of individual tRNA introns differ in response to environmental conditions including type of media, stage in growth curves, and exposure to elevated temperature. Together, the findings highlight the many cellular pathways utilized to regulate tRNA intron levels and the specificity of these pathways for different tRNA families and varying cellular conditions. The results underscore the likely important roles of the discovered individual fitRNAs in regulation of cell biology and responses to environmental conditions.

Construction duration prediction for ultra-high-rise buildings using PCA and an improved sparrow-search–optimized BPNN

Energetics of biomolecular shells in core–shell nanocomplexes

In this work, the stabilization enthalpy of patchy core–shell nanocomplexes is used to assess their thermodynamic stability. It is defined as the enthalpy of formation of a hydrated core–shell complex from hydrated (uncoated) core and hydrated shell species. Instead of the macroscopic bulk phase, the reference state is taken as the hydrated (uncoated) core of the nanocomplex with the same crystallite size. The stabilization enthalpies of three patchy magnetite (Fe 3 O 4 ) nanoparticles coated with three model biomolecules, bovine serum albumin, potato starch, and lauric acid were determined experimentally and the contributions of the primary hydration enthalpy and the adsorption of the biomolecules on the magnetite surface are measured and discussed. The findings establish the stabilization enthalpy as a quantitative basis to describe nanoparticle stability and interactions in biological and other complex media, which are crucial for biomedical applications.

Author Correction: Regional biodiversity monitoring reveals severe population decline of the Atlantic horseshoe crab (Limulus polyphemus) in Long Island Sound, USA

CDAF: a co-evolutionary decoupled attention framework for explainable weak thermal fault diagnosis of marine diesel engines

Abstract As marine diesel engines serve as the primary power source for ships. Traditional intelligent fault diagnosis methods fundamentally struggle to extract weak drift trends masked by strong noise, lacking adaptive parameter optimisation prevents the accurate delineation of fuzzy health-state boundaries in high-dimensional space, as well as poor explainability due to the black-box dynamic fusion of multi-source parameters during inference. This paper develops a novel Co-evolutionary Decoupled Attention Framework (CDAF). Driven by the Cooperative Rime Information Migration Evolutionary (CRIME) optimisation algorithm, to overcome the local minima inherent in manual tuning, the framework seamlessly integrates physically-informed dual-path feature decoupling (DPFD) to isolate weak drifts in high-noise environments, and employs a joint channel-spatial attention mechanism to resolve the fuzzy boundaries of highly similar fault states in high-dimensional space and accurate multi-source feature fusion. Fusion-CAM is further introduced to establish ensure interpretability throughout the inference process, which quantifies branch contributions of the fusion layer and maps thermal parameter responses to engine health status. Validation using real-ship and simulation data shows that the proposed method achieves 99.71% and 95% accuracy under standard and high-noise conditions, respectively. DPFD and CRIME modules enhance accuracy by over 2.2%, demonstrating the value of feature decoupling and global optimisation. Furthermore, Fusion Class Activation Mapping (Fusion-CAM) outperforms Grad-CAM + + in visualization accuracy, as confirmed by feature occlusion tests. Fusion-CAM quantitative analysis reveals that the weight of the trend-guided path exceeds that of the average path. This indicates that parameters such as maximum pressure during combustion, maximum temperature during combustion, brake mean effective pressure, exhaust gas pressure after the turbocharger, and exhaust manifold temperature are critical indicators for diagnosing subtle intake valve leakage.

Perceiving material qualities from moving contours

Abstract While research on the perception of line drawings has long demonstrated the importance of contours in object recognition, recent work shows that contours can also convey material properties. For example, even simple 2D shapes with varying contours have been shown to evoke vivid impressions of different materials. However, such static representations capture only a single moment in time. When a material moves, its contours shift, evolve, or deform over time, creating contour motion. Does this contour motion convey diagnostic information about material properties, independent of surface appearance? Existing studies on the role of dynamic cues in material perception either use fully rendered 3D stimuli, where contour motion is confounded with rich surface information, or motion-only displays (dynamic dot stimuli or noise patches), which eliminate surface cues but also lack clearly defined contours. As a result, the relative contribution of contour motion to material perception remains unclear. To address this gap, we measured how human observers perceive materials from dynamic line drawings (“line”), compared to animations of fully textured stimuli that carry optical and motion information (“full”), as well as dynamic dot stimuli (“dot”). Stimuli were three rendered versions (full, dot, line) of material animations from five material categories (jelly, liquid, smoke, fabric, and rigid-breakable). In one experiment, participants rated five material attributes (dense, flexible, wobbly, fluid, airy motion), and in a second experiment, participants were asked to choose one of the two materials that is more similar to a third material across all possible combinations. Results from both experiments consistently show that perceptual organization in both line and dot conditions strongly corresponds to that observed in the full condition. A control rating experiment with static line drawings (single images) showed significantly weaker correspondence to the full condition than between dynamic line drawings and the full condition, indicating that contour motion, not static shape alone, drives the effect. Together, these findings show that contour motion provides diagnostic information for material perception by jointly conveying contour shape and its time-varying dynamics, extending beyond what can be inferred from static contour cues alone.

Conformational equilibria in the activation of cystine-knot hormone receptors

Human glycoprotein hormones such as thyroid-stimulating hormone (TSH) and follicle-stimulating hormone (FSH) belong to a broader family of cystine-knot hormones (CKHs), all of which act through leucine-rich-repeat (LRR)-containing G protein–coupled receptors (LGRs) with which they have coevolved from evolutionary predecessors in metazoan animals. There is substantial evidence for LGR dimers being required in the transmission of G-protein signals elicited by mammalian CKHs acting on their cognate LGRs. Yet, human LGRs are monomeric as extracted from cell membranes and also in cryo-EM structures, both when in apo, inactive state and when hormone bound in an LRR-elevated active state. Fortunately, the LGR from the nematode Caenorhabditis elegans ( Ce LGR) remains dimeric as detergent extracted for structure determination. In this study, we synthesize structural information from Ce LGR, Hs TSHR, and the other human LGRs together with biophysical evidence about physiological dimers to produce a theoretical description of conformational equilibria involved in CKH activation of LGRs. We develop a theory for the equilibria among conformations that govern signal transmission from hormone to G protein, we define the transitions of receptor activation in quantifiable terms, and we build and validate energetically feasible models for Ce LGR and Hs TSHR in their relevant 0:2, 1:2, and 2:2 hormone:receptor complexes. These developments provide a framework for understanding of signaling through CKH receptors and for devising structure-based hypotheses to test such conceptions.

Adding a weight to constrain the trunk increases knee joint kinetics during sidestep cutting in female athletes

High-intensity exercise training alters gut microbiota to mitigate the development of experimental autoimmune encephalomyelitis

Researchers: here’s how to audit your fragmented digital identity

Activating GPR55 protects cochlear hair cells against cisplatin-induced ototoxicity via inhibiting MAPK pathway

Abstract Cisplatin (CDDP) is an effective chemotherapeutic agent used to treat solid tumors, but it can cause irreversible hearing loss. Currently, there are no specific preventive measures available for this side effect. G protein-coupled receptor 55 (GPR55) exhibits antioxidant, anti-inflammatory, and anti-apoptotic properties and is implicated in various disease processes. Nevertheless, whether GPR55 plays a role in CDDP-induced hearing loss remains unclear. We explored the effects and mechanisms of O-1602, a GPR55 agonist, on CDDP-induced ototoxicity. Our results showed that GPR55 is present in cochlear hair cells and HEI-OC1 cells, with increased expression following CDDP exposure. Moreover, O-1602-induced activation of GPR55 markedly mitigated the ototoxic effects of CDDP in HEI-OC1 cells, cochlear explants, and mouse models by preventing oxidative stress and apoptosis. In addition, GPR55 protected against CDDP-induced damage via inhibiting the MAPK pathway. Therefore, GPR55 is a potential therapeutic target for preventing CDDP-induced ototoxicity.

Fast automated adjoints for spectral PDE solvers

We present an automated procedure for computing model gradients for partial differential equation (PDE) solvers built on sparse spectral methods, a broad class of numerical techniques widely used in the study of fluid dynamics, continuum mechanics, waves, and pattern formation across disciplines. Our approach applies reverse-mode automatic differentiation to symbolic graph representations of PDEs and efficiently constructs adjoint solvers that retain the speed and flexibility of modern Fourier and polynomial spectral methods. We demonstrate the advantages of this approach with a comprehensive implementation in the open-source Dedalus framework. This work uniquely provides a differentiable spectral solver that supports a broad class of equations, geometries, and boundary conditions, and runs efficiently in parallel. It enables users to compute gradients and perform PDE-based optimization for a wide range of time-dependent and nonlinear models with minimal additional code. We demonstrate this system’s capabilities using canonical problems from the literature, showing both strong performance and practical utility for a wide variety of optimization tasks. By integrating automatic adjoints into a flexible solver, our work enables researchers to perform sensitivity analyses in spectral simulations with ease and efficiency.