Explore the vast range of titles available.

The global burden of liver diseases continues to rise, encompassing diverse pathologies such as viral hepatitis, alcohol-associated liver disease (ALD), metabolic dysfunction-associated steatotic liver disease (MASLD), and hepatocellular carcinoma (HCC). In recent years, TNFR1-associated death domain protein (TRADD), a pivotal adaptor molecule in the TNF signaling pathway, has been found to play a dual regulatory role in the pathogenesis of liver diseases. Through its death domain, TRADD binds to TNFR1 and dynamically recruits downstream factors (e.g., TRAF2, RIPK1, FADD) to form Complex I or IIa, thereby activating pro-survival or pro-apoptotic signals that dictate hepatocyte fate and modulate the inflammatory microenvironment. This review systematically summarizes the molecular structure and functional networks of TRADD, along with its mechanistic roles in liver diseases: in HCC, TRADD expression correlates with tumor differentiation and is regulated by miRNA targeting; in ALD and MASLD, TRADD-mediated apoptosis is closely linked to fibrotic progression; and in acute liver injury, TRADD signaling is modulated by factors such as HO-1 to mitigate damage. Furthermore, TRADD inhibitors and antisense oligonucleotides demonstrate therapeutic potential. This review highlights the clinical translational value of TRADD as a diagnostic, therapeutic, and prognostic biomarker for liver diseases, providing a theoretical foundation for future precision medicine strategies.

Bitter taste receptors, particularly TAS2R14, play central roles in discerning a wide array of bitter substances, ranging from dietary components to pharmaceutical agents 1 , 2 . TAS2R14 is also widely expressed in extragustatory tissues, suggesting its extra roles in diverse physiological processes and potential therapeutic applications 3 . Here we present cryogenic electron microscopy structures of TAS2R14 in complex with aristolochic acid, flufenamic acid and compound 28.1 , coupling with different G-protein subtypes. Uniquely, a cholesterol molecule is observed occupying what is typically an orthosteric site in class A G-protein-coupled receptors. The three potent agonists bind, individually, to the intracellular pockets, suggesting a distinct activation mechanism for this receptor. Comprehensive structural analysis, combined with mutagenesis and molecular dynamic simulation studies, elucidate the broad-spectrum ligand recognition and activation of the receptor by means of intricate multiple ligand-binding sites. Our study also uncovers the specific coupling modes of TAS2R14 with gustducin and G i1 proteins. These findings should be instrumental in advancing knowledge of bitter taste perception and its broader implications in sensory biology and drug discovery. A cryogenic electron microcopy study of structures of a human receptor for bitter taste finds that cholesterol can activate the receptor, while the tastant molecule acts allosterically on the receptor.

Recent studies have shown that transforming microglia phenotype from pro-inflammation of M1 phenotype to anti-inflammation and tissue-repairing M2 phenotype may be an effective therapeutic strategy for preventing ischemic stroke brain injury. Isosteviol Sodium (STV-Na) has shown promise as a neuroprotective agent in cerebral ischemia model, although its effect on microglial polarization and chronic recovery after stroke is not clear. Here, we demonstrated that STV-Na treatment significantly reduced cerebral ischemic damage at both acute and chronic time points. STV-Na has a profound regulatory effect on microglia response after stroke. It can promote M2 polarization and inhibit microglia-mediated inflammation (M1) response following stroke in vivo and in vitro . Furthermore, we also found that Growth Arrest-Specific 5 (GAS5) altered OGD/R-induced microglial activation by increasing Notch1 expression via miR-146a-5p, the mRNA level of GAS5 and the protein level of Notch1 in vivo and in vitro , were discovered that both downgraded with STV-Na. Taken together, the present study demonstrated that STV-Na exerted neuroprotective effects by modulating microglia/macrophage polarization in ischemic stroke via the GAS5/miR-146a-5p sponge. These findings provide new evidence that targeting STV-Na could be a treatment for the prevention of stroke-related brain damage.

Development of quantum systems supporting collective many-body states is crucial for advancement of quantum technologies, and perovskite quantum dots (QDs) have emerged as promising quantum light sources. However, photon bunching, a key signature of collective states, has been observed in perovskites only at cryogenic temperatures. Here, we report collective blinking and photon bunching in perovskite QD superlattices at room temperature. Sub-wavelength-sized CsPbBr 3 superlattices exhibit distinct two-level blinking, and demonstrate photon bunching with a degree of up to 3.9. Time-resolved photoluminescence and super-resolution imaging reveal long lifetime components, and emission spatially confined to regions tens of nanometers in size, observations consistent with long-range exciton migration to a localized energy trap within the superlattice. Power-dependent degree of bunching and analysis of the bunching dynamics point to biexciton–exciton cascade emission as the origin of photon bunching. These findings establish perovskite QD superlattices as a promising platform for room-temperature collective optical phenomena. Perovskite quantum dot superlattices have emerged as a promising platform for studying collective optical phenomena. Here the authors report collective photoluminescence blinking and photon bunching in a self-assembled CsPbBr 3 quantum dot superlattice, which they attribute to cascade-like biexciton-exciton emission.

The intratumoral microbiota, as an important component of the tumor microenvironment, is increasingly recognized as a key factor in regulating responses to cancer immunotherapy. Recent studies have revealed that the intratumoral microbiota is not uniformly distributed but instead exhibits significant spatial heterogeneity, with its distribution patterns influenced by factors such as tumor anatomy, local immune status, and therapeutic interventions. This spatial heterogeneity not only alters the interactions between microbes and the host immune system but may also reshape the immunogenic and immunosuppressive landscapes of tumors. The enrichment or depletion of microbiota in different tumor regions can influence immune cell infiltration patterns, metabolic pathway activities, and immune checkpoint molecule expression, thereby driving the development of resistance to immunotherapy. Moreover, certain bacterial metabolites form concentration gradients between the tumor core and margins, thereby regulating immune cell function. Therefore, understanding and manipulating the spatial distribution of intratumoral microbiota, particularly in resistant patients, holds promise for developing new strategies to overcome immunotherapy resistance. In the future, precise modulation strategies targeting microbial spatial heterogeneity, such as engineered bacterial vectors, probiotic combinations, and phage therapy, may open new avenues for immunotherapy.

Background Aortic dissection (AD) patients with malperfusion present significant challenges and are associated with high postoperative mortality rates. Limited data exist regarding the management of patients with AD and acute lower extremity ischemia. Early diagnosis of the extent of malperfusion and timely intervention are critical for improving patient prognosis. Methods A total of 104 patients diagnosed with AD were enrolled in this observational retrospective study, of which 11 (10.6%) presented with lower limb ischemia (LLI). A comparative analysis was conducted on the clinical data of the AD group and the AD + LLI group. Plasma concentrations of SBDP145, a specific indicator of Calpain activity, were quantified in Control, AD, and AD + LLI groups using ELISA. To explore the role of Calpain in LLI and AD, pharmacological inhibition with Calpeptin and transgenic mice overexpressing calpastatin (Tg-CAST) were utilized in mouse models. RNA sequencing and functional assays were employed to identify the downstream effectors of Calpain. Results Patients in the AD + LLI group exhibited significantly elevated leukocyte counts, percentages of neutrophils and lymphocytes, as well as increased serum levels of AST, creatinine, total cholesterol, low-density lipoprotein, uric acid, and creatine kinase compared to those in the AD group. Furthermore, the mean calcium ion concentration and Ca 2+ -dependent Calpain activation were significantly higher in the AD + LLI patients. Both endogenous and exogenous Calpain inhibitors effectively promoted the restoration of blood flow to ischemic hind limbs by inhibiting the inflammatory response and promoting vascular regeneration. Additionally, Calpain inhibition prevented the onset and progression of AD. RNA sequencing and Western Blot assays demonstrated that Calpain inhibition significantly increased levels of Fabp3, which is involved in the ischemia-induced fatty acid metabolism pathway. Conclusions Inhibition of Calpain has been demonstrated to decrease the incidence of AD and enhance the restoration of blood flow perfusion in ischemic lower extremities. This effect may be mediated by the upregulation of Fabp3. These findings highlight the potential for targeted interventions against Calpain as a novel therapeutic strategy in the treatment of cardiovascular disease.

Application programming interfaces (APIs) form the backbone of modern power system digitalization, enabling real-time data exchange, remote control, and cross-domain orchestration across SCADA, substation automation, and dispatching systems. However, as the digital grid evolves toward highly interconnected architectures, these APIs have become increasingly exposed to adversarial manipulation and stealthy misuse. Their reliability directly impacts the stability and resilience of grid operation and long-term cybersecurity assurance. Existing anomaly detection approaches in power systems often rely on statistical correlations or isolated secure aggregation mechanisms, which face two key challenges: (i) high sensitivity to benign operational drifts, leading to spurious false alarms under changing load and communication patterns; and (ii) lack of guarantees, resulting in fabricated or un anomaly reports under adversarial interference. To address these issues, we propose CausalVeri, a causality-aware verification framework that integrates causal representation learning with a verifiably secure aggregation protocol. Experiments demonstrate that CausalVeri reduces false positives by up to 17%, maintains stable detection accuracy under non-stationary grid communication patterns, and ensures cryptographic verifiability of anomaly alerts, providing a auditable foundation for secure API-based interactions in digital power systems.

G protein-coupled receptors （GPCRs） are involved in all human physiological systems where they are responsible for transducing extracellular signals into cells. GPCRs signal in response to a diverse array of stimuli including light, hormones, and lipids, where these signals affect downstream cascades to impact both health and disease states. Yet, despite their importance as therapeutic tar- gets, detailed molecular structures of only 30 GPCRs have been determined to date. A key challenge to their structure determination is adequate protein expression. Here we report the quantification of protein expression in an insect cell expression system for all 826 human GPCRs using two different fusion constructs. Expression char- acteristics are analyzed in aggregate and among each of the five distinct subfamilies. These data can be used to identify trends related to GPCR expression between dif- ferent fusion constructs and between different GPCR families, and to prioritize lead candidates for future structure determination feasibility.

In recent years, entity matching methods based on graph neural networks have significantly improved the ability of entity structure representation through multilayer neighborhood aggregation. However, such methods still suffer from oversmoothing and noise diffusion in local structures, as well as insufficient global topological consistency and limited geometric expression. Existing methods usually rely on local aggregation to obtain structural representations, making it difficult to explicitly model the global topological patterns and hierarchical structures between entities. Especially in heterogeneous or cross‐lingual graphs, traditional Euclidean embedding spaces cannot fully represent complex semantic hierarchies and multiscale geometric relationships. To this end, this paper proposes a Triview Dual‐space Contrastive Perception Matching (TriDCPM) method, which unifies the modeling of local correlations, global topologies, and cross‐graph consistency under a multiview representation and geometric collaborative learning framework. Specifically, TriDCPM constructs a triview framework consisting of local, global, and cross‐graph views and simultaneously learns multiscale entity representations in both Euclidean and hyperbolic geometric spaces. A global structure enhancement module based on singular value decomposition (SVD) is adopted to extract key topological patterns, and a gated residual unit (GRU) is introduced to alleviate noise propagation and oversmoothing. In the local encoding stage, multilayer attention aggregation and a degree‐aware relation fusion mechanism are employed to further enhance heterogeneous neighborhood and relational semantic features. Finally, a dual‐level contrastive consistency learning mechanism is adopted to jointly optimize feature consistency between the local–global levels and the Euclidean–hyperbolic spaces, achieving collaborative perception and discriminative unification of multiview representations. Experimental results on four public benchmark datasets demonstrate that the proposed method significantly outperforms existing structure‐driven entity alignment approaches in terms of Hit@1, MRR, and other metrics, with particularly outstanding performance in relation‐heterogeneous and cross‐lingual scenarios. Further ablation experiments and visualization analysis verify the effectiveness and stability of the proposed method in global structure modeling, noise suppression, and multispace contrastive optimization.