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Functional relationships are essential for healthy aging and they rely on social cognition skills such as establishing and monitoring whom to trust. However, aging and loneliness can negatively affect social brain function, potentially leading to a vicious cycle. Using functional MRI and computational modeling, we investigated trust learning in a sample of neurotypical older (64-84 years, n = 29 f/23 m) compared to younger adults (20-33 years, n = 31 f/31 m). Older participants displayed lower initial trust and less trust learning when repeatedly interacting with a trustworthy and an untrustworthy trustee. Their basolateral and central amygdala activation was lower during trust decisions, and this was associated with less optimal trust behavior. Computational modeling also revealed that a crucial learning parameter, precision of the trust prediction error, and activation in the dopaminergic midbrain were decoupled from basolateral amygdala activation, and this effect was pronounced in lonely older adults. These findings indicate that differences in amygdala and dopamine function at older ages together with higher loneliness could impair trust learning, leading to poorer social cognition and putting individuals' sociality and well-being at risk.

Activating transcription factor 4 (ATF4) has emerged as a central mediator of cellular stress adaptation, exerting context-dependent and often opposing functions in cancer through the coordinated regulation of metabolism and tumor immunity. However, the mechanistic principles governing ATF4's functional switch between tumor promotion and suppression remain incompletely defined, and the translational challenges of targeting this pleiotropic transcription factor have not been systematically evaluated. In this review, we dissect the molecular frameworks by which ATF4 integrates stress signals from the endoplasmic reticulum, oxidative stress, and nutrient deprivation to orchestrate metabolic reprogramming and immune evasion. We further critically assess the therapeutic landscape, including pharmacological selectivity, toxicity, and druggability challenges, all of which must be addressed to harness ATF4 as a precision target in oncology.

To block endocytic viral entry, cells typically acidify endosomes via upregulated expression of the short isoform of human nuclear receptor 7 (NCOA7) which boosts vacuolar ATPase (V-ATPase) activity. In our study, primary T cells infected with HIV-1 triggered endosomal acidification, yet NCOA7 levels were only modestly altered. Instead, we observed a pronounced depletion of the 50 kDa form of the sodium/hydrogen exchanger 6 (NHE6). Remarkably, NHE6 overexpression or treating cells with low-dose concanamycin A, a V-ATPase inhibitor, selectively neutralized endosomal pH. This neutralization impaired Nef-driven major histocompatibility complex class I (MHC-I) downmodulation by our wild-type HIV reporter virus. Mechanistically, NHE6 overexpression disrupted Nef-mediated MHC-I loss by reducing recruitment of Nef to recycling endosome (Rab11+) compartments and blocking Nef interactions with β-COP and ARF-1. Together, these findings reveal NHE6 as a critical regulator of endosomal pH and HIV immune evasion.

Class I PI3Kβ is critical in controlling platelet activation and preserving thrombus stability under high shear. PI3Kβ is unique among class I phosphoinositide 3-kinases (PI3Ks) in being activated by Rho-family GTPases Rac and Cdc42, positioning it as a potential key link between Rho-family GTPases and platelet signaling. Here, we combined pharmacological inhibition with genetic approaches to define a direct Rho-PI3Kβ signaling axis in mouse platelets. Platelets from knockin mice carrying two point mutations within the Rho-binding domain (RBD) of the PI3Kβ catalytic subunit p110β exhibited impaired GPVI-mediated platelet signaling, functional responses, and spreading on fibrinogen. Pharmacological inhibition with the PI3Kβ-selective inhibitor AZD6482 demonstrated that these responses largely depend on the p110β RBD. Inhibition of Rac/Cdc42 in wild-type platelets phenocopied the knockin defects, supporting a direct role for Rho GTPases in PI3Kβ activation. Conversely, Rac activation was impaired in RBD-mutant and AZD6482-treated platelets, revealing a Rac-PI3Kβ feedback loop that amplifies GPVI-dependent platelet activation.

IRF2 is an interferon regulatory factor with context-dependent roles in cancer. We examined IRF2 expression and function in nasopharyngeal carcinoma (NPC) using immunohistochemistry, immunofluorescence, western blot, and functional assays in cell lines and a xenograft model. IRF2 was upregulated and predominantly nuclear in NPC, correlating with advanced T stage and higher EBV DNA load. ROC analysis indicated diagnostic value (AUC = 0.837). IRF2 overexpression promoted proliferation, migration, invasion, epithelial-mesenchymal transition (EMT) and suppressed apoptosis, whereas knockdown inhibited these phenotypes and reduced tumor growth in vivo. Mechanistically, IRF2 activated the Wnt/β-catenin pathway by upregulating β-catenin and facilitating its nuclear translocation. These findings establish IRF2 as an oncogenic driver in NPC and suggest the IRF2/Wnt/β-catenin axis as a potential therapeutic target.

Integral membrane protein 2A (ITM2A) is a type II transmembrane glycoprotein belonging to the BRICHOS superfamily. It primarily regulates organismal development and homeostasis and exhibits tumor-suppressive functions. Its expression is precisely regulated by a multidimensional network involving transcription factors, epigenetic modifications, and environmental signals. Within cellular signaling networks, ITM2A modulates multiple key pathways, including BMP, JAK/STAT, ERK, Hedgehog, and PKA-CREB. ITM2A is essential for the differentiation and functional maturation of various tissues, such as cartilage, bone, and muscle. Dysregulation of ITM2A function or expression is closely associated with malignancies, thyroid disorders, and acute transplant rejection. This review systematically summarizes the complex regulatory mechanisms of ITM2A in growth, development, and disease, with a particular focus on skeletal development and tumorigenesis, aiming to provide a theoretical basis for its potential use as a biomarker for development and disease diagnosis/treatment, as well as for the development of ITM2A-targeted therapeutics.

Dextran sulfate sodium (DSS) is widely used to model epithelial injury-driven colitis, but heterogeneous dosing complicates model selection and cross-study comparison. Here, we established a graded DSS dose-response framework by administering 0%, 1.5%, 2.0%, 2.5%, or 3.0% DSS to C57BL/6J mice for 5 days, followed by 2 days of recovery, and integrated pathological, microbial, transcriptomic, and immune profiling. Low-dose DSS (1.5%-2.0%) induced mild and largely reversible epithelial injury, early microbiota perturbation, and CD8+ T cell accumulation. Higher doses (2.5%-3.0%) caused sustained inflammation, pronounced mucosal damage, macrophage and granulocyte infiltration, and elevated pro-inflammatory cytokines. Transcriptomic analysis revealed shared activation of TNF, NF-κB, IL-17, and NOD-like receptor signaling, with greater amplitude at higher DSS concentrations. This framework supports rational DSS dose selection according to disease severity and experimental objectives.

Sensor less adaptive optics offers significant advantages over hardware-based wavefront sensing but faces persistent challenges: Its performance degrades when idealized models fail to capture system imperfections, it is largely restricted to spatially invariant aberrations, and it cannot accommodate dynamic biological samples due to static-object assumptions. Here we present graph-modeling and phase-diversity-based computational adaptive optics with self-calibration (GRAPHYCS), a differentiable graph-based modeling framework that addresses all three limitations. GRAPHYCS automatically self-calibrates to correct system-specific non-idealities, enables spatially variant wavefront sensing across extended fields of view by modeling local aberrations, and supports dynamic live-sample imaging where conventional computational methods fail. In simulations, GRAPHYCS achieves up to a 9-fold improvement in wavefront sensing accuracy compared to analytic phase diversity under system non-idealities. In real microscopy experiments, it consistently outperforms phase-diversity-based methods compared in this study. Furthermore, in live zebrafish brain imaging, GRAPHYCS enables simultaneous wavefront sensing and neuronal activity detection-an application beyond the reach of existing approaches without additional hardware complexity.

Neural microcircuits in the auditory cortex (AuC) are essential for auditory information processing. Recent studies identified the basal region of the ventromedial nucleus of the thalamus (bVM), which affects AuC neuronal responsiveness and contributes to sound discrimination. However, the microcircuit organization by which bVM influences AuC neuronal responsiveness remains unclear. Here, using anatomical tracing, slice electrophysiology, and optogenetics, we found that bVM formed monosynaptic connections with both neuron-derived neurotrophic factor-positive interneurons (NDNF-INs) in L1 and pyramidal neurons (PYRs) in L2/3, with polysynaptic engagement of other L2/3 interneuron subtypes. Notably, NDNF-INs selectively regulated bVM-driven inputs to parvalbumin-expressing interneurons (PV-INs), but not to vasoactive intestinal peptide-expressing interneurons (VIP-INs) or somatostatin-expressing interneurons (SST-INs), forming a possible cell-specific disinhibitory circuit in AuC L2/3 circuits. These findings define a circuit diagram of the bVM → AuC pathway and establish NDNF-INs as a key regulator of thalamocortical information flow.

Stanford type A aortic dissection (AAD) is a life-threatening cardiovascular disease characterized by tearing in the aortic wall. Using spatial transcriptomics and multiplex immunofluorescence, we comprehensively analyzed ascending aortas from eight AAD patients across different severities and segments. We demonstrate that SPP1-driven inflammatory signaling intensifies with AAD severity, identifying a nine-gene, layer-anchored severity scale: MYL6/CALD1/MYH9 (mild); CCL2/CP/COL4A1 (moderate); and TMSB4X/ATP5F1E/PKM (severe). Importantly, the collagen-remodeling triad COL1A1/COL3A1/MMP2 is concurrently up-regulated in the brachiocephalic, left subclavian, and left common carotid arteries, often before the ascending aorta meets surgical diameter thresholds. These molecular signatures provide a critical foundation for non-invasive biomarker discovery, risk stratification, and precision pharmacotherapy targeting the SPP1-inflammatory axis, ultimately offering new insights into AAD mechanisms and therapeutic targets.

Cumulative night-shift exposure may disrupt circadian homeostasis and adversely relate to respiratory health. In a cross-sectional analysis of 9,464 coal miners, we found that greater cumulative night-shift exposure was associated with lower lung function after accounting for cumulative respirable dust exposure. Mendelian randomization analyses supported a potential causal link between shift work and reduced lung function and further indicated that genetically predicted lower lung function was associated with higher chronic obstructive pulmonary disease (COPD) risk. In a coal miner subgroup, lower PER1 expression partly accounted for the associations of cumulative night-shift exposure with forced expiratory volume in one second (FEV1) and forced vital capacity (FVC). Public transcriptomic and single-cell analyses showed lower PER1 expression in COPD and lung cancer-related datasets and suggested links to NF-κB-related inflammatory signaling. These findings suggest that PER1-related inflammatory signaling may represent a candidate molecular link between occupational circadian disruption and respiratory health impairment.

Mangrove ecosystems are highly efficient natural carbon sinks, yet quantifying soil organic carbon density (SOCD) across stand ages is critical for evaluating restoration benefits. This study integrated WorldView-2, LiDAR, and Sentinel-1 SAR data with machine learning to map SOCD in Qinglan Harbor, China. eXtreme Gradient Boosting achieved the highest accuracy (R 2 = 0.72, RMSE = 2.87 kg m-2) among four regression methods. Lasso regression identified LiDAR-derived structural metrics and optical vegetation indices as key predictors, highlighting the importance of 3D canopy structure and spectral data. Results showed age-dependent SOCD accumulation: mangroves older than 15 years stored significantly more carbon (11.47 kg m-2) than 0-5 year stands (10.49 kg m-2). These findings underscore the value of long-term restoration for blue carbon sequestration and provide a scalable monitoring framework that integrates multi-sensor remote sensing and machine learning to support coastal management and climate mitigation.

China's green transition is advancing, yet fossil fuels remain dominant, underscoring the importance of energy-saving technological innovation (ESTI) for low-carbon development. Existing studies mainly focus on the impact of carbon emissions trading (CET) on broad green innovation, while evidence on CET-induced ESTI remains limited. Using 3.09 million patent texts from Chinese listed manufacturing firms during 2008-2023, we employ a large language model (LLM) to identify firm-level ESTI and estimate the effect of CET through a staggered difference-in-differences (DIDs) approach. Results show that CET significantly promotes ESTI, and the findings remain robust across multiple tests. Mechanism analysis reveals three channels: increased carbon-risk exposure, substitution between government subsidies and market incentives, and correction of market inefficiencies. The effect is stronger among firms with lower pollution intensity and those without greenwashing behavior. These findings provide micro-level evidence on how environmental regulation fosters ESTI and offer implications for carbon-market and subsidy design.

In the present study, we demonstrated that a synthetic peptide derived from the Mycobacterium tuberculosis PPE2 protein alleviates dextran sodium sulphate (DSS)-induced colitis in mice and markedly improves ulcerative colitis (UC) symptoms, as evidenced by improvement in body weight loss, disease activity index (DAI) score, colon length, and decrease in myeloperoxidase activity. PPE2-peptide treatment attenuated the induction of pro-inflammatory cytokines, enhanced the mRNA levels of tight junction proteins (Occludin, Claudin-1, and ZO-1), and prevented gut barrier function. PPE2 acts mainly by targeting the mast cells, as adoptive transfer of mast cells restored the symptoms of DSS-induced colitis in PPE2-treated mice. We further explored the development of a combination therapy aimed at targeting multiple pathways involved in inflammatory bowel disease (IBD) pathogenesis and showed that combination therapy of PPE2-peptide and mesalazine had better efficacy in improving UC symptoms. This study highlights a potential therapeutic strategy targeting fibroblast-mast cell crosstalk in IBD.

Reconciling lower environmental impacts from agriculture with food security is a core national objective in China. We develop spatially explicit projections for nine major crops to 2030 and 2060 under Business-as-Usual (BAU), BAU with carbon-efficiency constraints (BAU-CE), and Sustainable Development Goal (SDG)-aligned pathway (SDG-60). Despite improved input-use efficiency, national output declines modestly by 2030 relative to 2020 (-11.4% BAU and -11.5% BAU-CE). By 2060, efficiencies approach ∼90%, with substantial reductions in aggregate inputs (fertilizer -30%, pesticides -50%, and irrigation water -34.4%). Under SDG-60, cropping greenhouse-gas emissions are ∼72% lower than under BAU-CE, while aggregate production across the nine crops declines by ∼50.5%. Spatial heterogeneity reveals trade-off zones where large mitigation gains and reduced chemical and water use coincide with output and income losses, particularly in rice-intensive provinces. Provinces with below-median labor productivity and income but above-median mitigation burdens are identified as structurally disadvantaged, highlighting where differentiated targets, incentives, and transition support are most needed to balance mitigation, food security, and rural livelihoods.

Epidemiological modeling is critical to guide public health interventions, but model performance depends on data availability and quality. While clinical reports suffer from under-ascertainment and delays, wastewater-based surveillance (WBS) can rapidly capture community infection dynamics by detecting viral RNA from both symptomatic and asymptomatic cases. However, WBS data can be difficult to interpret. Here, we present a coupled model of infectious disease and wastewater dynamics designed for scalability to large cities. We calibrate the model to the first COVID-19 wave in Munich and quantify how sampling protocols, precipitation, viral decay, normalization strategies, and intervention timing shape the relationship between wastewater measurements and disease prevalence. We find that under appropriate normalization and analysis strategies, wastewater data can provide advance warning of increases in disease burden. Our results guide WBS design and integration into predictive early-warning systems, and our framework is generalizable to other COVID-19-like pathogens, thereby enabling robust disease monitoring.

Although a multitude of meta-analyses have indicated an association between air pollution and hypertension (HTN), substantial heterogeneity exists across these studies. This research aims to systematically assess the cumulative evidence on the link between air pollutants and both HTN and gestational hypertension (GH) through existing systematic reviews. A comprehensive literature search was performed in three databases (Embase, PubMed, and Web of Science) up to September 8, 2025. The AMSTAR 2 tool was adopted to evaluate the methodological quality of the included reviews. Totally, 11 eligible meta-analyses (8 on HTN and 3 on GH) were identified. Collectively, the available evidence supports a plausible role of PM2.5 and PM10 in elevating essential HTN risk; however, the association with GH remains inconclusive due to the limited studies. Further prospective cohort studies and investigations into biological mechanisms are needed to clarify the influences of air pollution on both HTN and GH.