Browse Articles

Urokodia sheds light on the origin of chelicerae and book gills of Chelicerata

The cannabinoid receptor 1 suppresses neuropeptide Y transcription in the peripheral nervous system to mediate analgesia

Absolute chronology of the Early Palaeolithic Karatau Culture in Central Asia

Abstract Central Asia represents a key region for our understanding of early human dispersal patterns, because it served as a migration corridor that linked the Levant and southern Caucasus with Northeast Asia. However, no Early Palaeolithic sites in Central Asia are anchored with reliable age constraints, including the thick loess-palaeosol sections in Tajikistan that recorded early human activities and environmental changes over multiple glacial-interglacial cycles. This lack of absolute age constraints is presently a key factor limiting our understanding of the early human occupation history of this region. Here, we provide a comprehensive description and an absolute chronological framework for the Early Palaeolithic Karatau Culture; defined by the rich lithic assemblages found in palaeosols in the Khovaling Loess Plateau, Tajikistan. Age constraints are provided through multi-method analysis of three loess-palaeosol sections in the Khovaling Loess Plateau, combining luminescence ages, cosmogenic 26 Al- 10 Be concentrations, and magnetostratigraphic boundaries into a probabilistic inverse age-depth model. This model shows that the Karatau Culture flourished with the onset of Marine Isotope Stage 15, thrived during Marine Isotope Stage 13 and 11, but disappeared around onset of Marine Isotope Stage 10. We frame the archaeological occupations within local and regional ecological settings to better understand the drivers of Pleistocene human migrations in Central Asia.

Top-down and bottom-up attention for joint pattern classification and reconstruction

We introduce a recurrent inference framework for the Classification and Reconstruction of Overlapping Patterns (CROP) in mixtures formed by overlapping two patterns drawn from the same distribution. The framework alternates between bottom-up classification and top-down generative reconstruction within an iterative inference procedure. At each iteration, the method estimates the most likely class present in the mixture, reconstructs the corresponding signal using a conditional generative model, and applies a mask to isolate that component. This classification-guided reconstruction progressively separates the overlapping signals while also producing their class labels. The objective is therefore to iteratively separate and classify the overlapping patterns rather than perform general blind source separation. An important feature of the framework is that the generative model can be trained using only clean samples, without requiring paired mixed–clean training data. The iterative procedure implicitly implements a form of attention in which saliency- and priority-driven estimates guide the masking and reconstruction of individual patterns. Experimental results on mixtures of handwritten digits show that the proposed framework can successfully separate and classify overlapping patterns through this iterative classification–reconstruction process.

Development of a hemolysis filter system for the selective removal of free hemoglobin, haem and iron from blood envisaged for use in extracorporeal circuits

Abstract Hemolysis, the rupture of red blood cells, releases hemoglobin, haem, and redox-active iron into the bloodstream. When the body’s scavenging capacity is overwhelmed, these species can exert deleterious effects, as seen in hemolytic disorders. Hemolysis can also occur in extracorporeal circuits due to mechanical forces acting on blood during circulation. To mitigate these effects, we developed a filter designed for integration into extracorporeal circuits that is designed to capture hemolysis-associated byproducts using immobilised ligands. The filter prototype comprises glyoxal-functionalized agarose beads covalently immobilized with three binding agents: haptoglobin (Hp, binds cell-free hemoglobin [cfHb]), human serum albumin (HSA, binds haem), and desferrioxamine (DFO, binds free iron). Ligand immobilization was optimized to achieve strong covalent attachment to the agarose matrix. Optimized immobilization produced high ligand loading per milliliter of beads (mean ± SD): Hp 74.4 ± 11.7 mg/mL, HSA 84.6 ± 8.2 mg/mL, and DFO 43.3 ± 4.8 mg/mL. In vitro studies showed removal capacities of 12.7 ± 0.2 mg/mL for cfHb, 2708.5 ± 18.5 µg/mL for haem, and 309.7 ± 13.7 µg/mL for iron. The system retained binding activity in plasma and hemolyzed whole blood, and no increase in TAT or D-dimer was detected under the tested ex vivo conditions. These findings demonstrate the potential of this affinity-based filtration system to reduce hemolysis-associated complications in extracorporeal circulation.

The deubiquitinase CYLD inhibits thrombin-induced p38 MAPK–p65 NF-κB signaling and inflammatory cytokine production to suppress triple-negative breast cancer progression

High-rate single-crystalline Li-rich layered oxide with diversified surface-phase cation ordering for Li-ion batteries

Enhancing Magneto-Optical Activity via Coordination Distortion in Chiral Er ₄ M ₈ Clusters

Motivational and psychological variables related to unethical uses of artificial intelligence across multiple life domains (academics and online interactions)

Past studies about unethical uses of generative artificial intelligence (AI) have focused within a specific life domain (e.g., how AI is used for cheating in academics). An online survey was conducted to investigate how AI users utilized AI across multiple domains, how unethical behaviors in one domain related to behaviors in others, and which motivational and psychological variables corresponded with those uses. The goal was to help create a foundational understanding of how people use AI more broadly, including what the largest motivations for unethical use are and if unethical use had psychological consequences for the user. Creating this foundation can help develop successful interventions for unethical AI use. Findings supported that performing potentially unethical behaviors in one area of life (e.g., academics) were positively related to unethical behaviors in another area of life (e.g., social media interactions). Using AI unethically was positively related to knowing that the use was unethical. Unethical AI use was not related to intrinsic or extrinsic motivation, but was positively related to results pressure (prioritizing outcomes), external pressure (unethical use is normative and unlikely to be penalized), and time pressure (saving time by completing a task more quickly). Unethical AI use was also positively related to a desire for social media popularity and narcissism. Unethical uses of AI were not related to self-esteem, self-efficacy, or loneliness, but were positively related to satisfaction with life, making social comparisons, internalizing the perspective of others about their own body, prioritizing physical appearance over other attributes, and comparing one’s physical appearance with others. This study provided evidence that despite ethical misuse, generative AI is being used across multiple domains of life and is largely associated with positive consequences for the user. Unethical AI use was applied across multiple areas of life and was associated with variables related to elevating status, achieving good outcomes, behaving within broader cultural norms, and saving time. Future applications could explore if a more wholistic approach that targets motivations is more effective than a domain-specific approach when attempting to create interventions to curb unethical AI use.

Numerical investigation of the behaviour of shallow foundations under reverse fault rupture using concrete damage plasticity model

Listening in on the human brain cells that produce speech

A revised model for PHF20L1 Tudor function: DNA binding overrides methylation selectivity on nucleosomes

Activating in-plane dead zones of anode catalyst layers in proton exchange membrane water electrolyzers

Abstract The utilization of iridium-based anode catalysts in proton exchange membrane water electrolyzers is largely limited by the presence of electrochemically inactive “dead zones” within the catalyst layer. Here, by combining in-situ visualization of gas bubble evolution with quantitative conductivity measurements and electrochemical analysis, we establish that the limited in-plane electronic conductivity, dictated by the ionomer disrupting the conductive network of IrO 2 nanocatalysts, is the dominant factor. A sequential spray-coating strategy is further developed, which decouples the deposition of a pristine conductive catalyst layer from the ionomer and thereby preserves continuous electron transport pathways. This approach effectively activates the in-plane dead zones, resulting in membrane electrode assemblies that exhibit over 30% higher activity (4.2 A cm −2 @2.0 V@80 °C; membrane: Nafion 115) than those prepared by the conventional one-step method based on IrO 2 /ionomer mixed inks. Crucially, this approach achieves both low iridium loading (0.25 mg cm –2 ) with standard catalysts and demonstrates extended stability over 8300 hours under practical current densities.

Construction of an Interpretable Regression Model for Yield Prediction and Mechanistic Insight Enabled by Automated Reaction Path Exploration

Spatial association of seabirds and aquatic birds with highly pathogenic avian influenza (H5N1) outbreaks in Brazil: A nationwide ecological and statistical modelling approach

Identifying wild bird species associated with highly pathogenic avian influenza (HPAI) is essential for optimizing surveillance and mitigating spillover risks. This study analyzes Brazil’s nationwide HPAI surveillance data (up to July 2025), comprising 1,153 records across 127 bird and mammal species from 525 municipalities. Using a multi-model framework—including chi-square association tests, binary logistic regression, and spatial Generalized Additive Models (GAMs). Species–outbreak associations were significative and positive for Thalasseus maximus (χ² = 237.34, p < 0.0001), Thalasseus acuflavidus (χ² = 216.12, p < 0.0001), Sterna hirundo (χ² = 83.88, p < 0.0001), and Sterna hirundinacea (χ² = 77.56, p < 0.0001). An optimized logistic regression model (model 3) highlighted T. acuflavidus as the strongest predictor of HPAI (OR = 80.74; 95% CI: 21.85–298.39; p < 0.001), achieving good predictive performance (AUC = 0.85; Pseudo R² = 0.48). To account for spatial dependence, we fit a binomial GAM incorporating a bivariate longitude–latitude spatial smoother, significantly improving model fit (AUC = 0.96; Pseudo R² = 0.58) and effectively accounting for residual spatial autocorrelation (Moran’s I = 0.0399, z = 2.10, p = 0.044). Outbreaks were concentrated along Brazil’s southeastern coast, overlapping with high-density poultry zones, while inland spread remained sporadic, suggesting migratory routes as key transmission pathways. These results underscore the critical role of seabirds—particularly T. acuflavidus —in HPAI H5N1 dynamics in Brazil. The enhanced predictive power of the spatial GAM supports its utility in risk mapping. We recommend integrating biodiversity data with spatial modeling to guide targeted surveillance in high-risk coastal areas, reducing spillover threats to poultry and wild populations.

A study on the stability of amphiphilic cellulosic materials and the CO2-responsiveness of their interpenetrating network derivative with polyacrylamide

The retinol-metabolizing enzyme DHRS3 coordinates antigen presentation, endothelial stability, and cholesterol metabolism to suppress hepatocellular carcinoma progression

Changes in El Niño–Southern Oscillation and global frequency entrainment

Automated High-Throughput Virtual Screening of Catalysts via Templated Organic Reaction Pathway Construction: A Case Study on Suzuki–Miyaura Coupling Reaction

A practical and safe alternative method for skeletal cleaning for museum specimens using superworms (Zophobas morio)

Clean and undamaged skeletons that maintain natural anatomical shape are essential for anatomical collections and natural history museums. Conventional methods, such as maceration, chemical treatments, or dermestid beetle colonies, although commonly used, often require long processing times, pose biohazard risks, and may damage delicate bones. This study explores the use of superworms ( Zophobas morio ) as a biological alternative for skeletal cleaning. Controlled cleaning trials were conducted using specimens from various vertebrate groups and a range of size classes, categorized as small, medium, and large after removal of superficial tissues. As the larva to specimen ratio strongly influences cleaning time and effectiveness, we first standardized our setup by processing all specimens in identical containers, each with approximately 700 grams of superworms, allowing us to assess the optimal ratio. Our results showed that a high larva to specimen ratio led to damage of fragile bones, while lower ratios resulted in increased cleaning times. Through multiple trials, we suggest that a larva to specimen ratio of 10–15 balances efficient cleaning with minimal risk of bone damage. Applying this ratio to additional bird skulls resulted in thorough cleaning with no observed bone damage. Superworms removed soft tissues within hours to days, depending on specimen size, and were able to clean internal cavities that are typically difficult to reach. Unlike dermestid beetle colonies, which include multiple life stages and pose a higher risk of infestation or egg dispersal, superworms are limited to the larval stage, reducing such risks. Our findings demonstrate that superworms offer a rapid, adaptable, and museum-safe alternative to conventional skeletal cleaning methods, providing an efficient and practical option for scientific and curatorial settings. Superworms are readily available from commercial breeders, and maintaining a colony is straightforward, further supporting their use as a viable alternative for skeletal preparation.