Browse Articles

Targets for disease modification in schizophrenia: New findings add to evidence for the involvement of the immune complement system

Sustainable bridge strengthening techniques with UHPC overlay systems for jointless structures

Pressure-induced thermal expansion anomalies in dhcp iron hydride associated with magnetoelastic coupling

Iron hydride with a double hexagonal close-packed structure (dhcp-FeHx) undergoes a ferromagnetic–paramagnetic transition without changing its crystal structure. Despite its relevance to metal–hydrogen interactions and magnetically driven elasticity, the extensive investigation of this phase is almost limited to room temperature. Here, we performed x-ray diffraction measurements at high pressure and high temperature, identifying the singularity in the temperature–volume relationship as the Curie temperature (TC). Pressurization lowered the TC of dhcp-FeHx and produced pronounced volume anomalies, indicating that pressure enhanced magnetoelastic coupling. Density functional theory combined with dynamical mean-field theory (DFT + DMFT) reproduced the spontaneous magnetization and its negative pressure dependence of TC, consistent with our experimental results. This establishes a methodology for determining magnetic transition temperatures and magnetoelastic coupling effects and highlights dhcp-FeHx as a unique model system for providing new insights into itinerant-electron magnetism.

ILK binding to β1 integrin is indirect and mediated by kindlin-2

Integrin-linked kinase (ILK) and kindlin-2 (K2) are key components of focal adhesions (FAs) that regulate cell–matrix adhesion and integrin signaling. Both proteins directly bind each other, but how they influence each other’s localization to FAs and binding to integrins remains a subject of ongoing debate. Here, we establish a sensitive workflow to study protein–protein interactions in cells by combining methods from biochemistry, cell biology, and superresolution microscopy. Together with an analytical framework, this approach allowed us to distinguish direct from indirect molecular interactions and construct detailed interaction networks. Disrupting the ILK–K2 interaction reduced ILK localization to FAs and compromised integrin function, whereas K2 recruitment was unaffected. Our interdisciplinary approach also revealed that ILK does not directly bind β1-integrin cytosolic domains in vitro and in cells. Instead, ILK was recruited to integrins exclusively through a K2-dependent mechanism, primarily via K2 bridging ILK and β1 integrins. These findings define the hierarchical relationship between ILK and K2 in FAs and highlight the essential role of K2-mediated ILK recruitment for integrin adhesion and signaling.

Antioxidant potential and molecular diversity of passion fruit genotypes from Northeast India

A data-driven modeling study on the accurate identification of Doppler-free saturated absorption spectra in diatomic tellurium (130Te2)

The accurate identification of electronic transitions in high resolution molecular spectra is central to elucidating the complex energy level structures of excited states and characterizing intramolecular interactions in diatomic molecules. Here, we introduce a data-driven model that integrates the Dunham model with grid search iterative optimization and stepwise predictive matching methods to simultaneously characterize multiple coupled electronic excited states. Using Doppler-free saturated absorption spectra of molecular tellurium (130Te2) as a benchmark, our strategies enable the identification of 3701 lines across B0u+ ← X0g+, A0u+ ← X0g+, B1u− ← X1g−, and B1u+ ← X1g+ transitions with an accuracy on the order of MHz (∼10−4 cm−1) and extend the reliable assignment of rotational quantum numbers (J) up to ∼200. The diatomic constants and potential energy curves for both A0u+ and B0u+ of 130Te2 were updated, and the energy-level perturbations between B0u+ and B1u+ were also exhibited. The present data-driven framework establishes a universal paradigm for high resolution spectroscopic analysis of homonuclear diatomic molecules, offering a robust approach for analyzing highly congested spectra and enabling reliable spectral assignment.

Linking compromise and responsibility attribution to risky decision-making in dyadic foraging

From hunting to financial planning, many decisions are made under risk and alongside social partners whose decisions and outcomes are coupled with our own. Joint decision-making can create challenges, such as navigating conflicting risk preferences, evaluating each other’s actions, and deciding whether to compromise. Yet when and why people compromise, how they evaluate each other’s responsibilities during joint decision-making, and the computational and psychological underpinnings of these processes remain unclear. We introduce a dyadic foraging paradigm designed to capture diverse risk preferences, where two participants jointly choose between locations that yield rewards but carry risks and evaluate each other’s responsibility for shared outcomes. Across two studies (exploratory N = 250, confirmatory N = 514), people tended to compromise rather than counteract their partner, especially under diverging risk preferences and when compromise was reciprocated. Computationally, compromise was explained by a reinforcement learning model showing that individuals integrate their preferences with that of their partner. Responsibility attributions exhibited egocentric biases—with participants claiming more credit for wins than blame for losses—and these biases were associated with individual differences in compromise behavior. The interplay between individual differences in risk and responsibility attribution further shaped coordination patterns. Finally, we show that compromising improved performance for risk-averse individuals, increased desirability as a social partner, and led to more favorable responsibility attributions, suggesting multiple benefits of compromising. By linking decisions about risk–reward trade-offs to metacognitive judgments about responsibility, our study reveals the social and cognitive processes underlying compromise in risky foraging and, more broadly, in collaborative contexts with conflicting preferences.

Physics-guided monotone stacking for reliable prediction of pile load–settlement curves using SPT–$$\sigma '$$ profiles and geometry

Electrochemical porosification of n-GaN across acidic–neutral–alkaline electrolytes: From morphology to surface chemistry

Electrochemical etching is a scalable route to engineer nanoporous architectures in doped GaN, but cross-comparative investigations spanning the full electrolyte chemical window are still very limited. Here, we explore the electrochemical etching of Si-doped n-GaN in acidic, alkaline, and neutral electrolytes and correlate morphology, optical properties, and surface chemistry by using various characterization and simulation methodologies. Our findings reveal that the electrolyte with different pH values not only affects the pore size and density but also alters the dominant etching mode, which leads to morphologies ranging from interconnected “sponge-like” three-dimensional pore networks to intact surfaces with slightly and anisotropically etched pores beneath. We have established semiquantitative models to elaborate the changes in near-band edge absorption due to disorders of the pores and to describe the surface oxidation/hydroxylation, through respective optical and x-ray photoelectron spectroscopy measurements. The models are further corroborated with the Raman observations, supporting a unified picture in which porosification increases disorder/local strain fluctuations. We envisage that this work offers important information on the electrochemical etching of III-nitrides using electrolytes in full pH ranges and proposes new analytical methods, which are valuable in developing power-efficient GaN optoelectronic devices.

Ferment to survive: How an aerobic bacterium persists during hypoxia

Correction: Identification and testing of sex pheromone components of the invasive Australian redback spider (Latrodectus hasseltii)

Optical frequency comb double-resonance spectroscopy of the 9030–9175 cm−1 states of ethylene

We use optical–optical double-resonance (OODR) spectroscopy to measure for the first time hot-band transitions of ethylene between states in the 3000 and 9000 cm−1 energy ranges. A 3.2 μm continuous wave (CW) pump is used to populate selected states in the ν9 vibrational mode. The sub-Doppler OODR transitions are then probed with two different cavity-enhanced probes tunable around 1.7 μm: a frequency comb probe that allows for broadband measurements and simultaneous detection of many OODR lines and a CW probe that measures individual lines with higher signal-to-noise ratio and better frequency accuracy. We report center frequencies and relative intensities of 90 ladder-type hot-band transitions from three different states in the ν9 vibrational mode. We exploit combination differences and measurements of polarization-dependent intensity ratios to determine the final state rotational quantum numbers J. Comparison to theoretical predictions from ExoMol allows tentative assignments for 28 transitions. We also report improved line center frequencies for the three pump transitions in the ν9 band. Furthermore, we observe 18 sub-Doppler V-type transitions from the depleted ground state to the 6000 cm−1 region and assign 14 of them using ExoMol and the variational line list of Mraidi et al. [J. Quant. Spectrosc. Radiat. Transfer 310, 108734 (2023)].

Dynamic positioning of Rpc34 winged helix in RNA polymerase III elongation complex for its stability with implications for reinitiation

RNA polymerase III (Pol III) is specialized for the high-throughput synthesis of short RNAs, a capability linked to its unique TFIIE- and TFIIF-like subcomplexes that are stably associated through different stages of transcription. To date, the role of a winged helix domain (WH2) of Rpc34 subunit in the TFIIE-like subcomplex during elongation has remained a conundrum because its density is consistently absent in cryo-EM structures of Pol III elongation complexes (ECs), suggesting its high conformational mobility. In this study, we employed single-molecule Förster resonance energy transfer (smFRET) and nano-positioning triangulation to characterize the dynamics and determine the position of the Rpc34-WH2 domain within transcription-competent but nontranslocating Pol III ECs. To achieve the required site-specific labeling, we developed a chemical biology framework that utilizes azido-carrying unnatural amino acid incorporation and a thiol-capping strategy to eliminate off-target alkyne-thiol cross-reactivity. With the acceptor at Rpc34-WH2 and the donor at a defined position on the DNA template as the reference point, our smFRET results reveal that Rpc34-WH2 dynamically transitions among three discrete states, corresponding to preferred positional sites in downstream, middle, and upstream regions across the DNA-binding cleft. One of these sites coincides with Rpc34-WH2’s position in the preinitiation complex, indicating positional similarity across transcriptional states. Together with prior Pol I and Pol II studies, these findings establish Rpc34-WH2 as a mobile regulatory element that engages the Pol III EC through transient, weak interactions. Additionally, the bio-orthogonal labeling strategy presented here provides a robust, generalizable route for smFRET studies of large, multisubunit protein assemblies.

HoST: integrating Heuristic knowledge with attention-based LSTM networks for Thunderstorm prediction

Insights into the unexpected small reduction of the temperature of maximum density of water by lithium chloride addition

When lithium chloride is dissolved in water under isobaric conditions, it induces a reduction in the temperature of maximum density, TMD, of water that is smaller than that observed for the other alkali chlorides. In this work, we relate this phenomenon to the pressure variation produced by salt addition under isochoric conditions. We found that the thermal insensitivity of the lithium–water interaction contribution to the pressure variation is at the origin of this unexpected small reduction in TMD.

Evolution of quantitative traits with background selection

Optimizing subsurface carbon-energy synergy by balancing diffusion and convection via physics-informed Bayesian learning

Single-reference coupled-cluster theory based on the multi-purpose cluster operator

In this paper, we develop a theoretical framework that extends single-reference (SR) coupled-cluster (CC) theory beyond its conventional role of describing a single electronic state—typically the lowest-energy state within the symmetry sector defined by the reference determinant. Rather than viewing the SR-CC cluster operator solely as a device for reproducing one target state, we consider more general constructions in which different components of the cluster operator play distinct roles, ranging from encoding states of different symmetry than the reference to enabling the SR-CC ansatz to describe multiple states simultaneously. These developments lead to a new class of SR-CC downfolding formalisms in which the resulting active-space effective Hamiltonians are capable of concurrently representing multiple correlated states non-orthogonal to the reference function. We establish three theorems that formalize this extension and demonstrate that standard CC downfolding emerges as a special case of the proposed framework. Finally, we introduce a Hermitian variant based on a unitary CC representation, which enables realistic simulations of ground and excited states while reducing the quantum resources required.

BetaDescribe: Providing rich descriptions from protein sequences

Deciphering protein function is fundamental to advancements in medicine and biotechnology. However, conventional experimental characterization remains resource-intensive. Public large language models (LLMs), though proficient in natural language processing, often fail to accurately interpret and predict the functional and structural properties of proteins, limiting their utility in bioinformatics. To address this gap, we introduce BetaDescribe, designed to generate detailed and rich textual descriptions of proteins, including their function, catalytic activity, involvement in specific metabolic pathways, subcellular localizations, and the presence of specific domains. The trained BetaDescribe model receives protein sequences as input and outputs a textual description of these properties. BetaDescribe starting point was the LLAMA2 model, which was trained on trillions of tokens. Our model was next trained on datasets containing both biological and English text, which allowed the incorporation of biological knowledge. In addition to the description generator, BetaDescribe comprises multiple validator models and a judge, which together enable accurate ranking of alternative generated descriptions. We demonstrate the utility of BetaDescribe by providing descriptions for proteins that share little to no sequence similarity to proteins with functional descriptions in public datasets. Using in silico mutagenesis, we further show that BetaDescribe relies on functionally important regions, as part of its prediction, suggesting that the model identifies regions of importance for the protein functionality without needing homologous sequence. BetaDescribe offers a powerful tool to explore protein functionality, augmenting existing approaches such as annotation transfer based on sequence or structure similarity.

A comparative analysis of routine hospital admission data for sickle cell anaemia, cystic fibrosis and haemophilia in England

Abstract Recent evidence of inequalities in healthcare for sickle cell disease in the UK is lacking. We aimed to describe trends in hospital admissions for sickle cell anaemia (SCA), cystic fibrosis (CF) and haemophilia in England. We conducted a historical cohort study using Hospital Episode Statistics data of individuals with a primary diagnosis of SCA ( n  = 19,506), CF ( n  = 9,569) or haemophilia ( n  = 7,289) between 1st January 2013 and 31st December 2022. We compared the number and proportion of hospital admissions, 30-day emergency readmissions, length of stay (LoS) and costs of hospitalisations over time for the three conditions considered. The proportion of people with SCA who had frequent elective admissions (i.e. ≥ 5 per year) was higher and increased over time (43.4% to 52.1% compared with 14.3%-22.3% for CF and 10.4%-14.5% for haemophilia). The proportion of 30-day emergency readmissions was higher for SCA (9.0%) and CF (7.5%) compared with haemophilia (3.2%). Overall mean LoS (days) was longer for people with CF admitted for sepsis (24.3 vs . 16.7 in SCA and 20.8 in haemophilia) and acute appendicitis (6.1 vs . 5.9 for SCA and 5.4 for haemophilia). Estimated hospitalisation costs were higher for SCA (£109.9 M) compared with CF (£44.2 M) and haemophilia (£14.4 M) in 2021/22. We found substantial inequalities in all the indicators considered for SCA, CF and haemophilia. Our findings can inform public health policies to reduce preventable emergency readmissions and healthcare costs.