Browse Articles

Compound hydrogeomorphic cascades and rapid upstream to downstream hazard coupling in the Eastern Himalaya

Disruption of the brain-spleen axis impairs monocyte-microglia communication and accelerates disease progression in a mouse model of amyloidosis

Correlation between fecal eosinophil cationic protein and cow’s milk protein allergy in extremely preterm infants and its value in auxiliary diagnosis

A cyclin-polarity feedback network ensures healthy cell proliferation

Abstract Healthy proliferation requires the coordination of cell cycle progression with cell polarity. In budding yeast, polarity is established when G1-cyclin-Cdc28 Cdk1 triggers Cdc42 activation to generate a cell pole that is used as an axis for growth and division. While polarity defects delay the cell cycle temporally, permitting error correction, it is unknown if Cdc28 Cdk1 directly rectifies errant polarity. Here, we identify an adaptive response where G1-cyclin-Cdc28 Cdk1 participates in error correction via the augmentation of its kinase activity towards substrates that activate Cdc42. The response involves temporal and spatial cell cycle reconfiguration via extended G1 cyclin expression, nucleocytoplasmic rerouting and signaling. However, this strategy has a cost: if the defect is irreparable, high G1-cyclin levels enforce inexorable cell cycle commitment in the absence of a daughter cell, generating multinucleate cells. G1-cyclins therefore not only trigger G1 events, but also monitor their execution, employing feedback to coordinate polarity with cell cycle progression.

Controllable synthesis of small-sized Pd nanoparticles on acetic acid-modified halloysite for enhanced toluene oxidation

Scalable, fast and accurate differential gene expression testing from millions of cells of multiple patients

Abstract Since the development of DNA microarrays and later RNA bulk sequencing, testing with statistically independent samples has been the standard method for detecting genes with different transcription patterns. Single-cell assays challenge these assumptions because individual cells are statistically dependent, and all proposed methodologies present mathematical limitations or computational bottlenecks that prevent a seamless integration of data from many cells and patients simultaneously. In this work, we solve this crucial limitation by introducing a Bayesian framework that retrieves the independence structure at the level of individual patients, separating differences across individuals from actual transcriptional differences. Leveraging multi-GPU and variational inference, our approach excels across different experimental designs and scales to analyse over 10 million cells. This framework enables single-cell differential expression analysis that can finally integrate datasets from large clinical cohorts, atlas projects, or drug-response screens with thousands of samples and millions of cells.

Chronic exposure to LED lighting impairs prefrontal cortex-dependent cognitive functions in adolescent rats

Erosion-driven delayed warming and marine stress prior to the end-Permian mass extinction

Shielding assessment for multi-ion radiotherapy based on ion-specific dose-defined workloads

Abstract The expansion of heavy-ion radiotherapy toward multi-ion operation requires a reassessment of shielding design methods that have traditionally relied on particle-number-based workloads. In facilities employing multiple ion species, this approach becomes inconsistent because different ions require substantially different numbers of primary particles to deliver the same prescribed dose. In this study, neutron shielding characteristics for helium, carbon, oxygen, and neon ion beams were evaluated using dose-defined workloads that reflect actual clinical and operational practice. Shielding effectiveness was assessed per unit physical dose to represent quality assurance and commissioning activities, and per unit Relative Biological Effectiveness (RBE)-weighted dose to represent treatment-related workload, based on PHITS Monte Carlo simulations. Under physical-dose normalization, carbon consistently produced the largest neutron effective dose across all shielding configurations. Under RBE-weighted dose normalization, carbon generally remained the most conservative reference ion, although high-energy helium under metallic beam-loss target conditions approached the carbon reference in selected configurations. These findings demonstrate that shielding outcomes are strongly dependent on the dose quantity used to define workload and support the continued use of carbon as the primary reference ion for multi-ion shielding assessment, while indicating that high-energy helium may approach the carbon reference only under restricted treatment-related metallic-target conditions.

Volatile anaesthetics modulate voltage-gated sodium channel function at a site directly linked to channel gating

Pediatric pharmacokinetics and pharmacodynamics of guanabenz for the treatment of vanishing white matter

Large-scale genomic surveillance reveals immunosuppression drives mutation dynamics in persistent SARS-CoV-2 infections

Abstract Persistent SARS-CoV-2 infections have been hypothesized to play a key role in the emergence of variants of concern. However, the factors determining which individuals are at risk and their viral molecular signatures during infection remain poorly understood. Using Denmark’s extensive COVID-19 surveillance, comprising over 700,000 genomes, we identify 303 persistent infections and, critically, link them to health and sociodemographic data. Our analysis confirms the hypothesis that immunocompromised individuals are at the highest risk of experiencing persistent infections. Other disease groups associated with mortality, such as diabetes, show no such associations. Among these persistent infections, the viral sequences exhibit signs of positive selection, with recurrent mutations linked to treatment resistance. Our findings suggest that immunosuppression plays a key role in the emergence of novelty in persistent infections.

The effects of physical activity on the mental health of college students: chain mediation of smartphone addiction and perceived social support

Neuron-targeting piezoelectric microneedles disrupt pro-tumorigenic neuron-immune crosstalk and restore anti-tumor immunity in melanoma

Correction: Inference in conditioned dynamics through causality restoration

The post-fertilization archegonium gene network of seedless plants contributed to the origin of seeds

Abstract The evolution of seeds was a critical transition in plant evolution, but how ancestral seedless development was modified to form the first seed is only partly-answered through comparative morphology or the fossil record. We investigate seed origins by quantifying gene network conservation between seeds and seedless plant reproductive organs. Characterizing reproduction in the homosporous fern Ceratopteris richardii as a proxy for ancestral seedless reproduction, we create a gene expression atlas of fern diploid and haploid reproductive organ development and test for enrichment of these genes in Arabidopsis thaliana . Here we show ovule gene networks are enriched in genes regulating post-fertilization development of the fern haploid egg chamber (archegonium), a subset of which also show enrichment in sporophyll primordia, suggesting a mechanistic model to explain the origin of the ovule from a sporangium-bearing axis whereby gene networks in the ancestral post-fertilization archegonium became heterotopically expressed during development of the sporangium-bearing axis.

An EfficientNet-based hierarchical dual-encoder framework for multi-scale gastrointestinal disease detection

Abstract Gastrointestinal (GI) diseases represent a major global health burden, making accurate and early diagnosis critical for improved clinical outcomes. We propose a dual-backbone convolutional framework that integrates EfficientNet-B0 and EfficientNet-B4 to jointly capture fine-grained local details and high-level global context in endoscopic images. The two feature streams are fused through residual learning with channel expansion–reduction and 1 $$\times$$ 1 convolutions, followed by a Convolutional Block Attention Module (CBAM) that adaptively emphasizes diagnostically relevant regions while suppressing background noise. To improve generalization and training stability, MixUp augmentation and Stochastic Weight Averaging (SWA) are employed, and a dropout-regularized classifier is used to mitigate overfitting. Experimental results demonstrate that the proposed method achieves an overall accuracy of 84.11% and a Macro-F1-score of 72.11%, consistently outperforming single-backbone EfficientNet variants and other baseline models, validating the effectiveness of the proposed architecture in both performance and efficiency.

Paramagnetically driven superconducting re-entrance in Eu-doped infinite layer nickelates

Abstract The breakthrough discovery of superconductivity in infinite-layer nickelates, and subsequently in several superconducting nickelates with more complex layered structures, capped a search spanning more than two decades and opened an entirely new field of research. Significant efforts aim to increase the critical temperature, to determine the electronic structure of the system, the underlying pairing mechanism, and the similarities between this system and cuprates  − Ni 1+ in infinite-layer nickelates being isoelectronic to Cu 2+ in high-T c cuprates. Here, we explore the unique role of magnetic rare earth ions in superconducting Eu-doped NdNiO 2 . We show that the field-induced re-entrant superconductivity which we evidence in this compound is the result of a delicate balance between the competing effects of the Eu 2+ and Nd 3+ ions. Our analyses of the extraordinary Hall effect and modeling of the superconducting critical fields demonstrate that the influence of these ions on magneto-transport is only felt when they are polarized by a magnetic field.

The relocation of a psychiatric crisis intervention unit from a somatic to a psychiatric hospital: a multi-method observational study

Abstract The Crisis Intervention Ward relocated from a general hospital to a psychiatric hospital in Basel, Switzerland, on May 26, 2023. We hypothesize that this relocation influenced patient demographics, frequencies of main diagnoses, involuntary admissions, transfer rates, clinical outcomes, patient satisfaction, and clinician perceptions of the treatment setting. We compared two patient cohorts: one from a 12 month period pre-relocation and the other from a 12 month period post-relocation. Two outpatient clinician surveys—one conducted pre- and one post-relocation—assessed location ratings, treatment satisfaction, and the perceived benefits and disadvantages of each location. Prior to relocation, 625 cases were treated; after relocation, 686 cases. Patient’s age and gender showed no differences. The frequency of affective disorders (F3) was lower (Φ = − 0.124) at the psychiatric hospital. Clinical outcomes, involuntary patient admissions, and transfer rates to other psychiatric wards were comparable. Patient-reported satisfaction was lower at the psychiatric hospital (mean 4.6 vs. mean 5.2, r  = 0.23). Outpatient clinicians favored the general hospital setting strongly ( r  = 0.78–0.81). Clinical outcomes remained stable, but patient satisfaction was lower after relocation, and clinicians perceived barriers related to accessibility and stigma at the psychiatric hospital.

A light-driven multi-state heterojunction transistor for optoelectronic ternary logic circuits

Abstract A multi-state transistor that converts optical inputs into discrete logic outputs provides a device-level framework for optoelectronic computing beyond the binary paradigm. Here, we present a light-driven ternary heterojunction transistor (T-HTR), featuring three distinct states – off, on, and a light-tunable intermediate state – within a single device. The multi-state switching is achieved by a p-type/n-type heterojunction with a controlled charge injection barrier at the source electrode. This design enables the device to be maintained in the off-state in the absence of intermediate logic operations, thereby minimizing static power consumption. An optoelectronic ternary logic inverter based on the T-HTR is capable of full-swing pull-up and pull-down operations with a light-tunable intermediate state, realizing the functions of standard, positive, and negative ternary inverters within a single device. We further demonstrate a pixel-level sensory circuit as a proof-of-concept for in-sensor computing, enabling multifunctional image processing tasks, such as pixel integration and intersection, through dynamic switching of logic functions.