Browse Articles

Dual promoter–enhancer activities reflect a unified regulatory logic

Early Permian terrestrial apex predator regurgitalite indicates opportunistic feeding behaviour

Abstract Fossilised digestive remains (bromalites) provide unique insights into extinct animals’ behavioural ecology, physiology and diet. We describe fossilised regurgitated stomach content from the early Permian Bromacker locality (Thuringia, Germany) using micro-CT, osteological, chemical and taphonomical analyses. The regurgitalite consists of a compact cluster of 41 bones with a unique taphonomic signature, including sub-articulated, aligned long bones, an irregular overall shape, and low phosphorus contents in the near-bone matrix. The multitaxic elements comprise a maxilla attributed to the captorhinomorph Thuringothyris mahlendorffae , postcranial elements of the bolosaurid Eudibamus cursoris and an unidentified diadectid, along with several unassignable elements, indicating opportunistic feeding behaviour. The regurgitalite size and composition suggest an apex predator as producer, such as the sphenacodontid Dimetrodon teutonis or the varanopid Tambacarnifex unguifalcatus , both known from Bromacker. This specimen represents the geologically oldest terrestrial regurgitalite and reveals novel insights into the feeding behaviours and the trophic network in a late Palaeozoic continental ecosystem.

Ectopic cambia in wisteria vines are associated with the expression of conserved KNOX genes

The mTOR signaling pathway regulates key steps of mammary gland organoid genesis in a temporal manner

Inverse palladocenes

Developing digital biomarker for predicting cognitive response to multi-domain intervention

Abstract Computerized cognitive training allows real-time tracking of performance metrics that may serve as digital biomarkers. This study investigated the value of a novel in-game digital biomarker, RTACC (Reaction Time-Accuracy Correlation), the correlation between reaction time and accuracy, using data from 130 participants with mild cognitive impairment enrolled in the intervention arm of the SUPERBRAIN-MEET randomized controlled trial. Participants underwent a 24-week multi-domain intervention, consisting of computerized cognitive training, physical exercise, nutritional education, vascular/metabolic risk management, and motivation enhancement. RTACC was derived from task-level RT and accuracy and examined in relation to cognitive and biomarker outcomes. Linear regression analysis revealed a significant association between RTACC and changes in Repeatable Battery for the Assessment of Neuropsychological Status scores from baseline to 24 weeks (beta coefficient = -11.90 ± 3.78, T = − 3.14, P  = 0.002). RTACC also showed a marginal effect on changes in brain-derived neurotrophic factor levels (beta coefficient = − 3.13 ± 1.64, P  = 0.057). Logistic regression analysis demonstrated that RTACC combined with clinical information identified good responders with an area under the receiver operating characteristic curve of 0.73 (95% CI: 0.62–0.84). These findings suggest that this in-game digital biomarker (RTACC) may help identify individuals likely to benefit from multi-domain intervention.

Growth of rhombohedral-stacked single-crystal WS2/MoS2 vertical heterostructures

Correction: Systematic review and meta-analysis of virome profiles and quantification of Torque teno virus load in blood of acute febrile illness patients

Multistep receptor binding of the hepatitis B virus preS1 domain

Clinical relevance of tissue copper, selenium, and cadmium alterations in colorectal cancer

Signatures of Edge States in Antiferromagnetic Van der Waals Josephson Junctions

ABSTRACT The combination of superconductivity and magnetic textures leads to unconventional superconducting phenomena, including new correlated and topological phases. Van der Waals (vdW) materials emerge as a versatile platform for exploring the interplay between these two competing orders. Here, we report on individual // Josephson junctions behaving as superconducting quantum interference devices (SQUIDs), which we attribute to the interplay between the superconductivity of and the spin texture of the vdW antiferromagnetic insulator . This behavior persists for in‐plane magnetic fields of at least 6 T and is the result of interference between separated transport channels. Microscopic modeling of the antiferromagnet insulator/superconductor (AFI/S) interface reveals the formation of localized states at the edges of the junction that can lead to channels that dominate transport. Our findings highlight AFI/S heterostructures as a platform for engineering novel superconducting phenomena and establish a new route for lithography‐free SQUIDs that operate in high magnetic fields.

Anti-TLR2 immunotherapy modulates neuron-to-oligodendrocyte propagation of α-synuclein in mouse and human models

Dynamic community detection using class preserving time series generation with Fourier Markov diffusion

Abstract Generating class-consistent time series necessitates the maintenance of both overarching structure and detailed temporal dynamics–an endeavor that current GAN and diffusion models find challenging. We introduce FMD-GAN, a Fourier–Markov diffusion framework that integrates spectral clustering, state-conditioned frequency-domain noise modulation, and a dual-branch temporal–spectral discriminator to generate realistic and class-consistent sequences. In four UCR datasets (ECG200, GunPoint, FordA, ChlorineConc), FMD-GAN attains state-of-the-art or competitive outcomes, with up to a 50% reduction in FID and consistent enhancements in DTW, class consistency accuracy (CCA), and spectral distance (SD) compared to six representative baselines. Ablation studies validate the roles of spectrum masking, Markov-guided diffusion, and adversarial learning, whilst sensitivity analysis illustrates resilience to hyperparameters. Qualitative visualizations demonstrate significant semantic congruence between actual and produced samples. These findings indicate that the integration of spectral priors with probabilistic diffusion facilitates the production of time series that preserve structure and are cognizant of class distinctions, pertinent to biomedical monitoring, sensor analytics, and Tiny AI systems.

Cancer cachexia in STK11/LKB1-mutated non-small cell lung cancer is dependent on tumor-secreted GDF15

Abstract Cachexia is a wasting syndrome involving adipose, muscle, and body weight loss in cancer patients. Tumor loss-of-function mutations in STK11 / LKB1 , a regulator of AMP-activated protein kinase, induce cancer cachexia (CC) in preclinical models and are linked to weight loss in non-small cell lung cancer (NSCLC) patients. This study examines the role of the integrated stress response (ISR) cytokine growth differentiation factor 15 (GDF15) in regulating cachexia using patient-derived and engineered STK11/LKB1 -mutant NSCLC lines. Tumor cell-derived serum GDF15 levels are elevated in mice bearing these tumors. Treatment with a GDF15-neutralizing antibody or silencing GDF15 from tumor cells prevents adipose/muscle loss, strength decline, and weight reduction, identifying tumors cells as the GDF15 source. Restoring wild-type STK11/LKB1 in NSCLC lines with endogenous STK11/LKB1 loss reverses the ISR and reduces GDF15 expression rescuing the cachexia phenotype. Collectively, these findings implicate tumor-derived GDF15 as a key mediator and therapeutic target in STK11/LKB1 -mutant NSCLC-associated cachexia.

Leveraging metabolic similarity in a 1H NMR database of medicinal plants to advance pharmacognostic insights

Harmonic non-Hermitian skin effect

Reduced expression of BIRC2 and BIRC3 associated with longer survival in pediatric high-grade gliomas

Abstract Inhibitors of apoptosis proteins (IAPs), coded by BIRC genes, are cellular checkpoints that can regulate and inhibit pro-apoptotic caspase signaling. Overexpression of BIRC genes has been associated with cancer progression, multidrug resistance, poor prognosis, and shorter survival in several types of cancer. Using quantitative real-time polymerase chain reaction, we examined the expression of IAP family genes and their regulators: NAIP , BIRC2 , BIRC3 , XIAP , BIRC5 , BIRC6 , BIRC7 , CASP3 , CASP9 , DIABLO and XAF1 . We also evaluated the impact of clinical parameters (programmed death receptor 1 [PD1] expression, oligodendrocyte transcription factor 2 [Olig2] expression, Ki-67 antigen expression, tumor protein p53 expression in tumor cells, patient survival time, and progression-free survival) on gene expression levels. The expression of BIRC3 ( p  = 0.049), NAIP ( p  = 0.008), and XAF1 ( p  = 0.032) was significantly higher in tumors negative for Ki67, whereas the remaining genes showed no significant correlation with Ki67 expression. In contrast, BIRC2 ( r =-0.478 p  < 0.05) and BIRC3 ( r =-0.536 p  < 0.05) expression levels were negatively correlated with overall survival. A similar negative association was observed between progression-free survival and the expression of BIRC2 ( r =–0.481, p  < 0.05) and BIRC3 ( r =-0.540, p  < 0.05). To our knowledge, this is the first study to comprehensively assess the relationship between the expression of IAP family genes and their regulators in a homogeneous group of patients diagnosed with pediatric high-grade gliomas (pHGGs). Our findings provide new insights into molecular mechanisms involved in the pathogenesis of pHGGs, however, these preliminary results require confirmation in larger and more detailed studies.

Twist engineering induced spin-orbit coupling for photosynthesis of ethane from carbon dioxide and water

Hydrodynamic response of an Antarctic glacial bay to cross-bay winds and its potential impact on primary production

Abstract Antarctic glacial bays are important, productive regions of the Southern Ocean. Certain glacial bays, including our research area, Admiralty Bay, are less favorable for phytoplankton growth due to wind-enhanced high energy levels, but they still host localized biological blooms. Westerly winds are predominant in Admiralty Bay; the strongest storms are from the east. These winds act perpendicular to the main axis of the bay. This study investigates the impact of cross-bay winds on the bay’s hydrodynamics and its potential effects on primary production. A hydrodynamic model, coupled with a Lagrangian model tracking potential iron sources, was run under seven wind scenarios. Results indicate that all winds reduce water column stratification, but energy increase rates and circulation pattern shifts vary with wind direction. Westerly winds restrict outflow and promote the formation of submesoscale eddies near inner inlet openings, concentrating water masses that are expected to be iron-rich, potentially stimulating phytoplankton growth. Conversely, easterly winds enhance outflow, flushing bay waters and likely negatively impacting productivity. Limited observational and satellite-derived biological data provide supportive evidence for the model-based hypothesis that the direction of cross-bay winds, rather than just their magnitude, significantly influences local productivity.

Crowdsourced biodiversity monitoring fills gaps in global plant trait mapping

Abstract Plant functional traits are fundamental to ecosystem dynamics and Earth system processes, but their global characterization is limited by available field surveys and trait measurements. Recent expansions in biodiversity data aggregation—including vegetation surveys, citizen science observations, and trait measurements—offer new opportunities to overcome these constraints. Here we demonstrate that combining these diverse data sources with high-resolution Earth observation data enables accurate modeling of key plant traits at up to 1 km 2 resolution. Our approach achieves correlations up to 0.63 (15 of 31 traits exceeding 0.50) and improved spatial transferability, effectively bridging gaps in under-sampled regions. By capturing a broad range of traits with high spatial coverage, these maps can enhance understanding of plant community properties and ecosystem functioning, while serving as tools for modeling global biogeochemical processes and informing conservation efforts. Our framework highlights the power of crowdsourced biodiversity data in addressing longstanding extrapolation challenges in global plant trait modeling, with continued advancements in data collection and remote sensing poised to further refine trait-based understanding of the biosphere.