Browse Articles

Polymeric Hydrogel Interphase Enables Transport-Compatible Fe Stabilization for Hectowatt-Scale Alkaline Water Electrolysis

Decoding cytokine interactions for psoriasis therapy through computational repurposing of antihypertensive drugs

Heat waves impair foraging initiation and directional movement toward a floral scent in the buff-tailed bumblebee (Bombus terrestris)

Abstract Global climate change is disrupting key ecological processes and species interactions. In particular, the frequency and severity of heat waves have increased dramatically over the last decade. Bumblebees are key pollinators in natural and agricultural systems, representing great economic and biodiversity value. However, these insects are particularly vulnerable to heat stress, because they are exceptionally well adapted to cold environments. Previous studies showed that heat stress has negatively impacted bumblebee foraging in terms of flight performance and foraging success, but its effect on chemosensory orientation is still unknown. In this study, we experimentally investigated if heat wave-treated bumblebees have difficulties in sensing or locating the source of a synthetic floral blend. We found that the proportion of individuals that initiated foraging was significantly lower in the heat wave-treated group than in the control group. Moreover, heat wave-treated bees started foraging later and approached scent sources randomly, although they reached the first scent source with a latency comparable to that of control individuals. Contrary to our initial expectations, the heat wave treatment influenced the antennal response of bumblebees only in a body size-dependent manner. Our findings provide evidence that heat waves can reduce foraging activity and impair directional movements toward floral scents in buff-tailed bumblebees, and support the idea that climate change may be one of the most harmful anthropogenic factors affecting the foraging performance of this pollinator species.

From Oxo to Oxyl to Biradical: Systematic Multireference Calculations of Methane Activation at MOF Nodes

Role of theobromine and caffeine in resistance to Phytophthora spp. in Theobroma cacao

Bioorthogonal Activation of Protein Function through a retro-Cope/Cope Elimination Cascade

Prioritizing dairy cattle dystocia risk factors using a comparative fuzzy multi-criteria decision-making algorithms

Revealing the Hydrophobic Interactions between Annular Lipids and Transmembrane Peptides via Photo-Tagging and Mass Spectrometry

Arginine decarboxylase activity in the cattle tick Rhipicephalus microplus suggests an alternative polyamine biosynthetic pathway

Visualizing Electrochemical Oxidation and Dissolution of Platinum Surfaces at the Atomic Scale

A fault diagnosis method for aero-engine inter-shaft bearings based on 1DCNN-Transformer-BiGRU

Abstract To address the challenges of difficult fault feature extraction and feature aliasing in aero-engine inter-shaft bearings under strong noise conditions, this paper proposes a fusion diagnostic method that integrates a dual-scale one-dimensional convolutional neural network, a multi-head self-attention Transformer, and a bidirectional gated recurrent unit. The method employs a three-stage progressive network architecture for end-to-end fault diagnosis. The dual-scale 1DCNN extracts local temporal features from vibration signals, and batch normalization and dropout are applied to stabilize training and reduce potential overfitting. The Transformer encoder models dependencies among the extracted feature representations, supporting the representation of fault-sensitive features. The BiGRU captures bidirectional temporal dependencies in the fault evolution process. Experimental validation on the Harbin Institute of Technology aero-engine inter-shaft bearing dataset shows that the proposed model achieves 97% diagnostic accuracy under extreme noise conditions (SNR = −5 dB). Compared with existing methods, these results indicate that the proposed network effectively maintains diagnostic performance under controlled noise conditions.

Stabilizing Cu ⁺ Sites at Cu ₂ O(111)–ZrO ₂ Heterointerfaces for Durable and Selective CO ₂ -to-C ₂ H ₄ Electroreduction

CAMBRA caries risk stratification is associated with distinct salivary and supragingival plaque microbiomes in pre-orthodontic patients

An economic analysis of biogas production using swine manure in ZOMAC territories of Colombia

Naturally occurring ACE2 stalk variants are differentially released from the cell

Abstract Angiotensin-converting enzyme 2 (ACE2) is a key regulator of the renin–angiotensin–aldosterone system (RAAS). It also acts as a receptor for SARS-CoV-2 and stabilises the B0AT1 amino acid transporter at the cell surface. Therefore, surface expression of ACE2 is crucial for these physiological processes. ACE2 is released as a soluble, catalytically active form, partly through ectodomain shedding. This process mainly involves the sheddases ADAM10 and ADAM17, but the exact regulatory mechanisms remain unclear. We assessed 11 naturally occurring single-point mutations in the ACE2 stalk region. Most variants showed significantly reduced release compared to wild-type (WT) ACE2; however, the single point mutations P734L and G726R significantly increased their release. ACE2_P734L also exhibits higher surface expression, directly increasing the surface levels of B0AT1. Despite B0AT1 and ACE2 forming a tight tetrameric complex, this did not affect ACE2 shedding. This suggests that complex formation does not restrict sheddase access. Overall, these data identify the ACE2 stalk region as a major determinant of shedding efficiency. Naturally occurring variants in this region can substantially affect the release of soluble ACE2, potentially contributing to interindividual differences that are relevant for pathophysiological processes.

<i>De Novo</i> Boronic Acid-Containing Macrocyclic Peptides That Selectively Bind a Sialylated <i>N</i> -Glycan

Lack of evidence for Initial Upper Paleolithic attribution at Cueva Millán in Iberia’s hinterland

Revealing the Biological Effect of the <i>N</i> -glycosylation of High-Mobility Group Box 1 (HMGB1) Facilitated by Chemical Protein Synthesis

Stable isotope insights into the feeding ecology of common dolphin (Delphinus delphis) in the East Sea of Korea

Abstract Understanding the trophic ecology of top marine predators is crucial for assessing ecosystem structure and resilience. We investigated the feeding ecology of the common dolphin ( Delphinus delphis ) in the East Sea of Korea using stable isotope analysis of carbon (δ 13 C) and nitrogen (δ 15 N). Dolphin and prey muscle samples collected between 2020 and 2023 were analyzed to determine trophic position, habitat use, and seasonal dietary variation. δ 13 C values (−18.5‰ to −17.9‰) indicated consistent utilization of mid-shelf pelagic habitats, while significant seasonal shifts in δ 15 N values (12.3‰–13.1‰) suggested temporal variations in prey trophic levels. Bayesian mixing models identified Pacific herring ( Clupea pallasii ) as the dominant prey, contributing up to 56% in summer, whereas sand lance ( Ammodytes personatus ) and sandfish ( Arctoscopus japonicus ) were secondary and seasonally restricted prey. Isotopic niche analyses revealed broader trophic flexibility during periods of lower prey abundance (winter–fall) and narrower niches during summer, reflecting opportunistic but seasonally structured feeding behavior. These findings establish an isotopic baseline for D. delphis in Korean waters, highlighting its ecological role as a key mesopredator linking pelagic fish dynamics to higher trophic levels and underscoring the need for continued monitoring under accelerating climatic and anthropogenic changes in the East Sea ecosystem.

Topology Switching in Polymetallic Fragments Governed by Metal Encapsulation