Olfactory receptors (ORs) form the largest superfamily of G protein-coupled receptors (GPCRs). Traditionally recognized for their role in the nasal olfactory epithelium, where they mediate the sense of smell, accumulating evidence has firmly established their ectopic expression in non-olfactory tissues, including the intestine, lungs, and kidneys. The intestine, as the primary site for nutrient digestion and absorption, harbors a highly complex chemical environment. To adapt to this environment, the gut employs a sophisticated network of “chemosensors” to monitor luminal contents and maintain homeostasis. Among these sensors, intestinal ORs have emerged as crucial functional components, serving as a molecular bridge that connects environmental chemical signals—such as food-derived odorants—to specific physiological responses. This discovery has significantly deepened our understanding of how dietary flavors and compounds influence intestinal physiology at the molecular level. This review systematically summarizes the expression profiles, ligand classification, and biological functions of ORs within the gastrointestinal tract. Studies indicate that intestinal ORs exhibit distinct spatial distribution patterns across different gut segments and display cell-type specificity, particularly within enterocytes and enteroendocrine cells. These receptors function as versatile sensors capable of recognizing a wide variety of ligands, including exogenous dietary components, gut microbiota metabolites such as short-chain fatty acids, and endogenous small molecules like azelaic acid. Upon activation by specific ligands, intestinal ORs trigger intracellular signaling cascades, primarily involving the AC-cAMP-PKA pathway or calcium influx channels. A major focus of this review is to elucidate the molecular mechanisms by which these receptors regulate the secretion of gut hormones. Activation of specific ORs in enteroendocrine cells has been shown to stimulate the release of hormones such as glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and serotonin (5-HT), thereby modulating systemic energy metabolism, glucose homeostasis, and gastrointestinal motility. Furthermore, the review addresses the critical roles of ORs in immune regulation and pathology. Evidence suggests that specific ORs contribute to the maintenance of intestinal immune homeostasis and may offer protection against inflammation. Beyond their involvement in inflammatory responses, ORs such as Olfr78 have been shown to regulate the differentiation and function of intestinal endocrine cells. Similarly, Olfr544 has been demonstrated to alleviate intestinal inflammation by remodeling the gut microbiome and metabolome. These findings collectively suggest that specific ORs hold promise as therapeutic targets for mitigating intestinal inflammation and maintaining gut homeostasis. Additionally, the review explores the emerging role of ORs in cancer. Although OR expression is often downregulated in tumor tissues compared to normal mucosa, activation of specific ORs by certain ligands can inhibit tumor cell proliferation and migration and induce apoptosis via pathways such as MEK/ERK and p38 MAPK. Conversely, other receptors, such as OR7C1, may serve as biomarkers for cancer-initiating cells. In conclusion, intestinal ORs represent a vital component of the gut’s sensory network. The review also discusses the translational potential of these findings. By elucidating the precise pairing relationships between dietary components and specific ORs, novel therapeutic strategies could be developed. Intestinal ORs may thus emerge as promising targets for nutritional and pharmacological interventions in metabolic diseases, inflammatory bowel diseases, and malignancies.

Objective To systematically review the studies on predictive models for delayed graft function (DGF) after kidney transplantation. Methods Databases including China Biology Medicine Database, China National Knowledge Infrastructure, Wanfang Database, VIP Database, PubMed, Web of Science and CINAHL were searched to collect studies on predictive models for DGF after kidney transplantation published from the establishment of each database to June 29, 2025. Two researchers screened the literatures according to the inclusion and exclusion criteria, evaluated the quality of the literatures using the prediction model risk of bias assessment tool (PROBAST), and conducted a meta-analysis of the common predictors of the models using R software. Results A total of 12 literatures were included, involving 14 predictive models with sample sizes ranging from 103 to 24 653 cases. Donor serum creatinine level, cold ischemia time, donor age and donor body mass index were the top four common predictors. All the predictive models were at high risk of bias and low in applicability. The results of meta-analysis showed that abnormal donor body mass index, advanced donor age, prolonged cold ischemia time and elevated donor serum creatinine level were all associated with an increased risk of DGF after transplantation (all P<0.01), but there was high heterogeneity among the studies. Fixed-effect model and random-effect model were used to re-pool the effect sizes separately. The results indicated that the fixed-effect model and random-effect model had good consistency in terms of donor body mass index, donor age and cold ischemia time, while there was a significant difference in the effect sizes of the two models for donor serum creatinine level. Conclusions The predictive models for DGF risk after kidney transplantation have good predictive performance, but the overall risk of bias is high. In the future, large-sample, multicenter and high-quality prospective clinical studies should be carried out to optimize the predictive models, so as to improve their predictive ability and clinical application value.

Abstract To promote adolescents active participation in physical activity and improve sleep quality, the article analyzes the relationship of adolescent physical activity with subjective sleep satisfaction, sleep latency, sleep continuity, sleep efficiency, and sleep duration. It explores potential mechanisms underlying the link between physical activity and sleep quality, including physiological mechanisms (circadian rhythms, body temperature, neuroendocrine systems, and immune function), and psychological mechanisms (stress relief, improvement of negative emotions, and promotion of mental relaxation). Based on existing research, it is recommended that adolescents engage in moderate to vigorous physical activity daily to promote improved sleep quality.

Objective To investigate the expression profile, prognostic value, gene co-expression network, and immunomodulatory role of BRF1 in a pan-cancer context, and to explore its biological functions and molecular regulatory mechanisms in esophageal squamous cell carcinoma (ESCC). Methods The pan-cancer dataset from The Cancer Genome Atlas (TCGA) was utilized to analyze the differential expression of BRF1 in tumor versus normal tissues, its association with patient survival, pathway enrichment for co-expressed genes, and immune features (including immune checkpoints, cytokines, and immune cell infiltration). The expression profile of BRF1 in ESCC was validated using the Gene Expression Omnibus (GEO) database. In vitro, BRF1 was knocked down in ESCC cells using siRNA. Cell proliferation and migration were assessed by MTT and Transwell assays, respectively. The expression levels of proliferation- and migration-related proteins were detected by Western blotting. The correlation between BRF1 and ferroptosis was analyzed using TCGA data. Results BRF1 was significantly upregulated in over 20 types of cancer, and its high expression was associated with poor prognosis in patients with adrenocortical carcinoma and prostate adenocarcinoma. BRF1 was found to positively regulate the T-cell-mediated cell death pathway in esophageal adenocarcinoma and was associated with the circadian rhythm regulation pathway in pancreatic adenocarcinoma. The correlation of BRF1 with immune checkpoints, cytokine networks, and immune cell infiltration was found to be cancer type-specific. In vitro experiments demonstrated that knocking down BRF1 significantly inhibited the proliferation of ESCC cells, accompanied by the downregulation of the proliferation marker PCNA. Cell migration was also significantly impaired, with decreased expression of Vimentin and MMPs and increased expression of E-cadherin. Furthermore, the expression of BRF1 was positively correlated with that of ferroptosis-antagonizing genes, such as GPX4, HSPA5, and SLC7A11. Conclusion BRF1 plays complex roles in pan-cancer, participating in the regulation of tumorigenesis, progression, and immune infiltration. BRF1 promotes the proliferation and migration of ESCC cells, a mechanism potentially associated with the regulation of ferroptosis resistance. These findings suggest that BRF1 could be a potential therapeutic target for ESCC.

Objective: We employed Mendelian randomization (MR) to test the traditional Chinese medicine (TCM) theory of emotional pathogenesis concept and explore the causal relationship between negative emotions and chronic obstructive pulmonary disease (COPD). Methods: Data of negative emotions, bronchitis, emphysema, and C-reactive protein (CRP) levels were downloaded from genome-wide association study (GWAS) public database for a two-sample MR analysis. Independent single-nucleotide polymorphisms (SNPs) associated with negative emotions, bronchitis, and emphysema were selected as instrumental variables. Primary causal estimates were derived using inverse-variance weighting (IVW), supplemented by weighted median (WM), and simple mode (SM) methods. Sensitivity analyses included MR-Egger regression and MR-PRESSO to assess pleiotropy, Cochran’s Q test for heterogeneity, and multivariate MR to adjust for smoking. Mediation analysis evaluated the role of inflammatory markers. Reverse MR was tested for bidirectional causality. Weak instrument bias was mitigated via F-statistic thresholds (> 10). All analyses were conducted in RStudio. Results: MR analysis identified significant causal effects of several negative emotions on COPD. Genetically, the IVW analysis of seen doctors for nerves anxiety tension or depression [ORIVW = 1.006, 95% CI = (1.002, 1.010), P = 0.002], sensitivity/hurt feelings [ORIVW = 1.024, 95% CI = (1.004, 1.044), P = 0.017], and irritability [ORIVW = 1.019, 95% CI = (1.003, 1.035), P = 0.019 were robustly associated with increased risks of COPD. No heterogeneity was detected among the different instrumental variables (IVs) for depression (P = 0.655) and irritability (P = 0.163). MR-Egger regression intercepts for all emotional exposures were close to zero and statistically non-significant, indicating no evidence of directional pleiotropy. The horizontal pleiotropy results showed that except for worry (MR-PRESSO P = 0.006), other emotion exposures confirming no substantial pleiotropic bias. Multivariable MR demonstrated that anxiety remained independently associated with COPD after adjusting for smoking (P = 0.002), while associations with other negative emotions were attenuated post-adjustment. The mediation analysis revealed that CRP mediated 3.93% of the total effect of anxiety on COPD. However, reverse MR analysis found no evidence of reverse causality. Conclusion This study confirmed the causal effects of negative emotions on COPD through MR analysis and revealed that negative emotions may trigger CRP production, which plays an essential mediating role in this relationship. This study provides a reliable modern theoretical basis for emotion theory in TCM.

ObjectiveTo investigate the mechanism by which Feixin decoction treats hypoxic pulmonary hypertension （HPH） by regulating the peroxisome proliferator-activated receptor gamma （PPARγ）/nuclear factor-kappa B （NF-κB）/NOD-like receptor pyrin domain containing 3 （NLRP3） signaling pathway. MethodsForty-eight male SD rats were randomly allocated into normal， hypoxia， and low-， medium- and high-dose （5.85， 11.7， 23.4 g·kg^-1， respectively） Feixin decoction groups， with 8 rats in each group. Except the normal group， the remaining five groups were placed in a hypoxia chamber with an oxygen concentration of （10.0±0.5）% for 8 h per day， 28 days， and administrated with corresponding drugs during the modeling process. After 4 weeks of treatment， echocardiographic parameters ［pulmonary artery acceleration time （PAT）， pulmonary artery ejection time （PET）， right ventricular anterior wall thickness （RVAWd）， and tricuspid annular plane systolic excursion （TAPSE）］ were measured for each group. The right ventricular systolic pressure （RVSP） was measured by the right heart catheterization method， and the right ventricular hypertrophy index （RVHI） was calculated by weighing the heart. The pathological changes in pulmonary arterioles were observed by hematoxylin-eosin staining. The co-localization of α-smooth muscle actin （α-SMA） with NLRP3， N-terminal gasdermin D （N-GSDMD）， and cysteinyl aspartate-specific proteinase-1 （Caspase-1） in pulmonary arteries was detected by immunofluorescence. The protein levels of PPARγ， NF-κB， NLRP3， apoptosis-associated speck-like protein containing a CARD （ASC）， N-GSDMD， interleukin-1β （IL-1β）， interleukin-18（IL-18）， and cleaved Caspase-1 in the lung tissue was determined by Western blot. The ultrastructural changes in pulmonary artery smooth muscle cells （PASMCs） were observed by transmission electron microscopy. ResultsCompared with the normal group， the hypoxia group showed increased RVSP and RVHI （P<0.01）， decreased right heart function （P<0.01）， increased pulmonary vascular remodeling （P<0.01）， increased co-localization of α-SMA with NLRP3， N-GSDMD， and Caspase-1 in pulmonary arterioles （P<0.01）， up-regulated protein levels of NF-κB， NLRP3， ASC， N-GSDMD， IL-1β， IL-18， and cleaved Caspase-1 in the lung tissue （P<0.05， P<0.01）， a down-regulated protein level of PPARγ （P<0.05， P<0.01）， and pyroptosis in PASMCs. Compared with the hypoxia group， Feixin decoction reduced RVSP and RVHI， improved the right heart function and ameliorated pulmonary vascular remodeling （P<0.05， P<0.01）， decreased the co-localization of α-SMA with NLRP3， N-GSDMD， and Caspase-1 （P<0.05， P<0.01）， down-regulated the protein levels of NF-κB， NLRP3， ASC， N-GSDMD， IL-1β， IL-18， and cleaved Caspase-1 in the lung tissue （P<0.05， P<0.01）， up-regulated the protein level of PPARγ （P<0.05， P<0.01）， and alleviated pyroptosis in PASMCs. ConclusionFeixin decoction can ameliorate pulmonary vascular remodeling and right heart dysfunction in chronically induced HPH rats by regulating pyroptosis in PASMCs through the PPARγ/NF-κB/NLRP3 pathway.

ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, functional impairment, and neuropsychiatric symptoms. It represents the most prevalent form of dementia among the elderly population. Accumulating evidence indicates that oxidative stress plays a pivotal role in the pathogenesis of AD. Notably, elevated levels of oxidative stress have been observed in the brains of AD patients, where excessive reactive oxygen species (ROS) can cause extensive damage to lipids, proteins, and DNA, ultimately compromising neuronal structure and function. Amyloid β‑protein (Aβ) has been shown to induce mitochondrial dysfunction and calcium overload, thereby promoting the generation of ROS. This, in turn, exacerbates Aβ aggregation and enhances tau phosphorylation, leading to the formation of two pathological features of AD: extracellular Aβ plaque deposition and intracellular neurofibrillary tangles (NFTs). These events ultimately culminate in neuronal death, forming a vicious cycle. The interplay between oxidative stress and these pathological processes constitutes a core link in the pathogenesis of AD. The signaling pathways mediating oxidative stress in AD include Nrf2, RCAN1, PP2A, CREB, Notch1, NF‑κB, ApoE, and ferroptosis. Nrf2 signaling pathway serves as a key regulator of cellular redox homeostasis, exerts important antioxidant capacity and protective effects in AD. RCAN1 signaling pathway, as a calcineurin inhibitor, and modulates AD progression through multiple mechanisms. PP2A signaling pathway is involved in regulating tau phosphorylation and neuroinflammation processes. CREB signaling pathway contributes to neuroplasticity and memory formation; activation of CREB improves cognitive function and reduce oxidative stress. Notch1 signaling pathway regulates neuronal development and memory, participates in modulation of Aβ production, and interacts with Nrf2 toco-regulate antioxidant activity. NF‑κB signaling pathway governs immune and inflammatory responses; sustained activation of this pathway forms “inflammatory memory”, thereby exacerbating AD pathology. ApoE signaling pathway is associated with lipid metabolism; among its isoforms, ApoE-ε4 significantly increases the risk of AD, leading to elevated oxidative stress, abnormal lipid metabolism, and neuroinflammation. The ferroptosis signaling pathway is driven by iron-dependent lipid peroxidation, and the subsequent release of lipid peroxidation products and ROS exacerbate oxidative stress and neuronal damage. These interconnected pathways form a complex regulatory network that regulates the progression of AD through oxidative stress and related pathological cascades. In terms of therapeutic strategies targeting oxidative stress, among the drugs currently used in clinical practice for AD treatment, memantine and donepezil demonstrate significant therapeutic efficacy and can improve the level of oxidative stress in AD patients. Some compounds with antioxidant effects (such asα-lipoic acid and melatonin) have shown certain potential in AD treatment research and can be used as dietary supplements to ameliorate AD symptoms. In addition, non-drug interventions such as calorie restriction and exercise have been proven to exerted neuroprotective effects and have a positive effect on the treatment of AD. By comprehensively utilizing the therapeutic characteristics of different signaling pathways, it is expected that more comprehensive multi-target combination therapy regimens and combined nanomolecular delivery systems will be developed in the future to bypass the blood-brain barrier, providing more effective therapeutic strategies for AD.

BACKGROUND: Treatment with chimeric antigen receptor-T (CAR-T) cells has shown promising effectiveness in patients with relapsed/refractory B-cell acute lymphoblastic leukemia (R/R B-ALL), although the process of preparing for this therapy usually takes a long time. We have recently created CD19 Fast-CAR-T (F-CAR-T) cells, which can be produced within a single day. The objective of this study was to evaluate and contrast the effectiveness and safety of CD19 F-CAR-T cells with those of CD19 conventional CAR-T cells in the management of R/R B-ALL. METHODS: A multicenter, retrospective analysis of the clinical data of 44 patients with R/R B-ALL was conducted. Overall, 23 patients were administered with innovative CD19 F-CAR-T cells (F-CAR-T group), whereas 21 patients were given CD19 conventional CAR-T cells (C-CAR-T group). We compared the rates of complete remission (CR), minimal residual disease (MRD)-negative CR, leukemia-free survival (LFS), overall survival (OS), and the incidence of cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) between the two groups. RESULTS: Compared with the C-CAR-T group, the F-CAR-T group had significantly higher CR and MRD-negative rates (95.7% and 91.3%, respectively; 71.4% and 66.7%, respectively; P = 0.036 and P = 0.044). No significant differences were observed in the 1-year or 2-year LFS or OS rates between the two groups: the 1-year and 2-year LFS for the F-CAR-T group vs.C-CAR-T group were 47.8% and 43.5% vs. 38.1% and 23.8% (P = 0.384 and P = 0.216), while the 1-year and 2-year OS rates were 65.2% and 56.5% vs. 52.4% and 47.6% (P = 0.395 and P = 0.540). Additionally, among CR patients who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) following CAR-T-cell therapy, there were no significant differences in the 1-year or 2-year LFS or OS rates: 57.1% and 50.0% vs. 47.8% and 34.8% (P = 0.506 and P = 0.356), 64.3% and 57.1% vs. 65.2% and 56.5% (P = 0.985 and P = 0.883), respectively. The incidence of CRS was greater in the F-CAR-T group (91.3%) than in the C-CAR-T group (66.7%) (P = 0.044). The incidence of ICANS was also greater in the F-CAR-T group (30.4%) than in the C-CAR-T group (9.5%) (P = 0.085), but no treatment-related deaths occurred in the two groups. CONCLUSION Compared with C-CAR-T-cell therapy, F-CAR-T-cell therapy has a superior remission rate but also leads to a tolerably increased incidence of CRS/ICANS. Further research is needed to explore the function of allo-HSCT as an intermediary therapy after CAR-T-cell therapy.

The circadian clock plays a critical role in regulating various physiological processes, including gene expression, metabolic regulation, immune response, and the sleep-wake cycle in living organisms. Post-translational modifications (PTMs) are crucial regulatory mechanisms to maintain the precise oscillation of the circadian clock. By modulating the stability, activity, cell localization and protein-protein interactions of core clock proteins, PTMs enable these proteins to respond dynamically to environmental and intracellular changes, thereby sustaining the periodic oscillations of the circadian clock. Different types of PTMs exert their effects through distincting molecular mechanisms, collectively ensuring the proper function of the circadian system. This review systematically summarized several major types of PTMs, including phosphorylation, acetylation, ubiquitination, SUMOylation and oxidative modification, and overviewed their roles in regulating the core clock proteins and the associated pathways, with the goals of providing a theoretical foundation for the deeper understanding of clock mechanisms and the treatment of diseases associated with circadian disruption.
Protein Processing, Post-Translational/physiology* ; Circadian Rhythm/physiology* ; Humans ; Animals ; CLOCK Proteins/physiology* ; Circadian Clocks/physiology* ; Phosphorylation ; Acetylation ; Ubiquitination ; Sumoylation