Browse Articles

The role of teacher-student relationships in mediating the impact of peer relationships and grit on student engagement

A synaptic mechanism for encoding the learned value of action-derived safety

Abstract Adaptive behavior requires that behaviorally relevant signals gain access to neural circuits guiding action. The thalamus has long been proposed to regulate information flow to cortical and subcortical systems, yet whether it also tracks internally generated goal signals remains unclear. Here, we show that neurons in the paraventricular thalamus (PVT) projecting to the nucleus accumbens (NAc) encode the motivational value of safety during active avoidance. As mice learn to avoid threat, PVT→NAc neurons develop a signal that emerges selectively at successful avoidance, is experience-dependent, and diminishes following outcome devaluation. Selective silencing of the PVT→NAc pathway at safety onset reduces the motivational value assigned to safety without impairing action–outcome learning. Mechanistically, PVT input engages cholinergic interneurons (CIN) in the NAc to regulate dopamine release via synaptic potentiation mediated by GluA2-lacking AMPA receptors at PVT–CIN synapses. Disrupting this plasticity reduces the motivational impact of safety. These findings identify a thalamostriatal mechanism through which learned goals gain stable access to motivational circuitry.

Synergistic corrosion protection and bacterial control in a UV-cured UA coating containing TiO2–polyaniline–calixarene nanocomposite

Inference of spatial chromatin accessibility via integration of spatial transcriptomics and single-cell multi-omics data

BMI–adiposity discrepancy across weight categories in primary school children: a prospective school-based cohort study

Activating lattice oxygen in metal oxyhydroxides as durable electrodes for industrial-scale seawater splitting

Perineural dexamethasone as an adjuvant to erector spinae plane block for acute and chronic pain after cardiac surgery

Abstract Pain control after cardiac surgery remains suboptimal. The erector spinae plane (ESP) block offers a safer regional alternative to neuraxial techniques, but its duration is limited. We tested whether perineural dexamethasone added to bilateral ESP blocks reduces acute postoperative pain intensity and attenuates chronic post surgical pain (CPSP) after coronary artery bypass grafting (CABG). In this randomized, double-blind trial (NCT04313959), 43 patients undergoing elective CABG received bilateral ESP blocks with 0.2% ropivacaine alone (control, n  = 21) or ropivacaine plus 8 mg perineural dexamethasone (dexamethasone, n  = 22). Primary outcome: pain intensity at rest on postoperative day 1, measured using the numerical rating scale (NRS). Pre-specified secondary outcomes were mechanical ventilation duration, 48-hour opioid consumption, and pain interference at 30, 60, and 90 days measured using the Brief Pain Inventory (BPI). The primary outcome was not significantly different between groups: NRS pain at rest on day 1 was 1.35 ± 1.95 (control) vs. 1.57 ± 2.27 (dexamethasone), p  = 0.781 (Fig. 1). Acute pain scores and 48-hour opioid consumption were comparable (Fig. 3). Mechanical ventilation was shorter in the dexamethasone group (median 11.6 vs. 14.7 h; p  = 0.041; Table 2). At 30 days, no significant between-group differences were found in any BPI domain (all p  > 0.05; Table 3). At 60 days, pain intensity scores were lower in the dexamethasone group (composite score 0.47 ± 0.88 vs. 1.21 ± 1.28; p  = 0.019; Table 3; Fig. 2). By 90 days, all outcomes were comparable (all p  > 0.05). One procedure-related adverse event occurred (pneumothorax, control group). Addition of dexamethasone to ropivacaine did not add to the reduction of acute pain. The secondary exploratory findings of shorter mechanical ventilation time and lower pain intensity at 60 days are hypothesis-generating and should be evaluated using larger, adequately powered multicenter trials with intraoperative blinding and a systemic comparator arm. Trial registry: NCT04313959.

Ventrolateral prefrontal cortex in macaques guides decisions in different learning conditions

Developing molecular classifiers to detect environmental stressors and smolt stages in sockeye salmon, Oncorhynchus nerka

Abstract Climate change is increasingly affecting Pacific salmon to combinations of thermal, hypoxic, and osmotic stressors that can impair survival. Although genomic tools have enabled detailed insight into stressor responses under controlled conditions, field applications remain limited by the lack of species-specific classifiers capable of resolving physiological condition across multiple stressor contexts. In this study, we developed and experimentally validated transcriptional classifiers for juvenile sockeye salmon ( Oncorhynchus nerka ) using controlled multi-stressor challenges. Fish exposed to a full factorial design of three temperatures (10 °C, 14 °C, 18 °C), three salinities (0, 20, 28 ppt), and two dissolved oxygen levels (> 8 mg L -1 , 3–3.5 mg L -1 ) over six days, across smolt and de-smolt stages; pre-smolts were additionally challenged with seawater (28 ppt). Gill tissue, a primary interface between fish and their environment, was analyzed using the “Salmon Fit-Chips” microfluidic qPCR tool to quantify gene expression responses. Random Forest models were then used to develop classifiers detecting transcriptional signatures of thermal stress, hypoxic stress, salinity acclimation, and smolt stage. Classifiers achieved high predictive accuracy (85.5%–100%) across all stressors and life stages. Recovery analysis showed that transcriptional stress signals diminished within three days for hypoxia, but lingered longer for thermal stress. By developing sockeye salmon–specific molecular classifiers within a multi-stressor experimental framework, this study advances the Fit-Chip approach and provides a foundation for future field applications, including potential non-lethal monitoring using gill biopsies.

Prevalent gut phages encode modular adhesins mediating epithelial binding and endoplasmic reticulum trafficking

Abstract Bacteriophages are crucial components of the human microbiome and hold promise as therapeutic agents. Yet, their physical interactions with mammalian cells remain poorly understood. Here, we developed a high-throughput platform to identify phages that adhere to epithelial layers and the proteins that mediate this interaction. The identified phages encode immunoglobulin (Ig)-like domain-containing proteins that, when displayed on a non-adherent phage, confer epithelial binding and internalization in vitro, and increased phage retention in the mouse gut in vivo. Phages encoding these adhesins are among the most abundant and prevalent human gut phages, including crAss-like phages and myoviruses closely related to the recently proposed Flandersviridae family. Domain sequence variation alters epithelial interaction profiles, and internalized phages traffic to the endoplasmic reticulum through the Golgi apparatus, suggesting access to non-degradative internalization pathways. These findings reveal widespread phage-human interactions in the human viral community, with potential impacts on health and implications for next-generation phage therapeutics.

Decentralized graph attention multi-agent reinforcement learning for adaptive urban traffic routing

Opto-optical edge defect mitigation in solution-processed WSe2 thin films for high-efficiency optical modulation

Rule-guided Skip-GCN in neural latent information diffusion network for social recommendation

Craton-margin lithosphere drives rare earth element ore-forming carbonatite magmatism

Renal function and cardiovascular events in predialysis care

ATP is dispensable for E. coli DNA replication and eukaryotic helicase activity

Abstract Adenosine triphosphate (ATP) hydrolysis is the main cellular source of energy used to drive biochemical reactions that are otherwise energetically unfavourable. The chemical energy stored in phosphoanhydride bonds is released upon hydrolysis of ATP to ADP and is used to drive mechanical work and conformational change. DNA replication is a canonical process in which the multi-enzyme replisome is thought to rely on ATP hydrolysis for its function. Here we show, through single-molecule visualisation of DNA replication by the Escherichia coli replisome, that the replicative DnaB helicase does not rely on hydrolysis of ATP in the context of the elongating replisome. Even in the presence of physiologically-relevant concentrations of ATP, dTTP is hydrolysed preferably. Finally, we show that the replicative helicases from S. cerevisiae , D. melanogaster , and Homo sapiens  can also use dTTP to unwind DNA. Our observations suggest that replicative helicases across domains of life are ‘flex-fuel’ helicases.

CircRNAs derived from the tyrosine phosphatase PTPN22 impact chemosensitivity in ALK-positive T-cell lymphomas

Dynamics of the β-cardiac myosin auto-inhibited state explain cardiomyopathy pathogenesis

Abstract Cardiac contractility requires precise regulation. A recently discovered form of regulation of cardiac contractility involves a β-cardiac myosin off-state, the Interacting-Heads Motif ( Car IHM). Despite its central role in cardiac physiology and disease, Car IHM structural dynamics remain poorly understood. Here, we integrate near-atomic resolution cryo-EM with all-atom molecular dynamics to characterize Car IHM in solution and in the context of the filament. We describe its conformational ensembles maintained by dynamic interfaces, and the stabilizing effect of the dilated cardiomyopathy mutation E525K, which limits S2 coiled-coil flexibility and impairs myosin activation. Intrinsically disordered regions of Car IHM and MyBP-C further modulate these dynamics. Our findings provide evidence for how Car IHM ensembles balance off/on states and anchor myosin heads in distinct thick filament environments. This integrated structural and dynamic approach enhances the understanding of thick filament regulation and facilitates predictions of the effects of genetic variants in inherited cardiomyopathies.

Cytoplasmic competition between separate parental pronuclei in zygotes

Measuring human capital with social media data and machine learning

Abstract Timely data on educational attainment at granular geographic levels remains scarce in many countries, limiting evidence-based policy-making. Recent advances in machine learning have enabled the use of non-traditional data sources like satellite imagery and mobile phone records to measure development indicators. While these approaches have been successful in predicting outcomes such as wealth, poverty, or population density, previous attempts to predict educational attainment have achieved only modest accuracy. Here we show that language patterns and user behavior in social media can explain up to 70 percent of the variance in regional educational attainment. Our machine learning framework leverages linguistic features, user behavior, and network characteristics from 25 million geolocated tweets from the United States and Mexico. It performs particularly well in predicting higher education levels and maintains a good performance even with limited data collection periods. These results show that digital communication patterns can serve as reliable proxies for human capital. In light of the rapid expansion of social media use around the globe, this represents a promising approach to tracking educational outcomes in regions lacking granular and timely survey data.