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.

The blood-brain barrier （BBB） is a physical and biochemical barrier that precisely regulates brain homeostasis and plays a central role in controlling the transport of endogenous and exogenous drugs and related metabolites across the blood-brain interface. These functions of the BBB are mediated by its major components， including brain microvascular endothelial cells （BMECs）， tight junction protein complexes， and influx and efflux transporter proteins. One of the pathological features of ischemic stroke （IS） is BBB disruption， which plays an important role in the development of post-stroke brain injury and subsequent neurological dysfunction. Therefore， given the increasing incidence of IS， there is an urgent need to develop new therapeutic strategies to prevent BBB dysfunction and thereby protect injured brain tissue after IS. This study describes the pathological mechanisms by which BMEC injury after IS leads to BBB dysfunction and elucidates the association between BMECs and IS， including the regulation of apoptosis， autophagy， inflammatory responses， oxidative stress， neurotoxic effects， and cerebral edema. In addition， this article summarizes Chinese herbal medicines that may prevent and treat IS by targeting BMECs. These include monomeric compounds and single herbs such as flavonoids， glycosides， phenols， phthalides， terpenoids， and Styrax. Traditional Chinese medicine （TCM） compound formulas and preparations include oral formulations such as Buyang Huanwu decoction， Sailuotong， Naoxintong capsules， Dandeng Tongnao capsules， and Shexiang Tongxin dropping pills， as well as injectable preparations such as Tongluo Jiunao injection， Xingnaojing injection， Danshen polyphenolic acid for injection， Yiqi Fumai injection， and Shuxuetong injection. This study aims to explore the protective effects of TCM against IS through targeted regulation of BMEC function， providing new insights into the mechanisms of IS and endovascular therapeutic strategies.

In March 2024, three male and two female specimens of the genus Lispe were intercepted on cargo ships inbound for Wan Zai Port under Gongbei Customs. Based on morphological characteristics and molecular analysis, the specimens were identified as Lispe pumila. In this study, we describe the morphological features, diagnostic characteristics, and geographical distribution of L. pumila, with the aim of providing a reference for the identification of this species when intercepted at ports.

Background and aims The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. Methods The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Results Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. Conclusions PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.

Skeletal muscle atrophy refers to a pathological condition characterized by muscle fiber atrophy as well as decreased muscle mass and muscle strength induced by various predisposing factors. It falls under the category of “flaccidity syndrome” in traditional Chinese medicine， and its pathogenesis is mainly associated with disturbed protein homeostasis， mitochondrial dysfunction and oxidative stress injury. Active ingredients of traditional Chinese medicine exerts synergistic regulatory effects via multiple pathways， thus possessing unique advantages in the clinical prevention and treatment of skeletal muscle atrophy. This paper reviews the mechanisms by which active ingredients of traditional Chinese medicine alleviate skeletal muscle atrophy. Existing studies have demonstrated that such active ingredients can ameliorate skeletal muscle atrophy through multiple approaches： regulating protein metabolic balance （geniposide， matrine， schisandrin A， etc.） and oxidative stress （astragaloside Ⅳ， Gastrodia elata polysaccharide， Angelica sinensis polysaccharide， etc.）， improving mitochondrial function （parthenolide， berberine， curcumin， etc.）， facilitating myogenesis and myogenic differentiation （cucurbitacin Ⅱb， saikosaponin A， saikosaponin D， etc.）， suppressing inflammatory response （ursolic acid， triptolide， emodin， etc.）， ameliorating insulin resistance （akebiasaponin D， etc.）. In the future， active ingredients of traditional Chinese medicine are expected to achieve breakthroughs in clinical treatment for skeletal muscle atrophy， providing novel ideas and strategies for the prevention and treatment of degenerative disorders.

Artificial intelligence (AI) has made preliminary advances in the management of postoperative follow up for lung cancer; however, a systematic review of its application value across the entire follow-up continuum remains lacking. Taking the four core dimensions of postoperative follow-up management as its framework, including surveillance candidate selection, follow-up interval optimization, follow-up protocol design, and follow-up modality selection, this review examines the progress of AI in patient risk stratification, surveillance frequency optimization, content design, and supportive platform development. The review further delineates the current challenges and future directions for AI in this domain, and ultimately seeks to promote the standardized and scaled application of AI in postoperative follow-up management for lung cancer, with the goal of establishing a "care beyond hospitalization" life-cycle management framework that improves the long-term quality of survival for patients undergoing lung cancer surgery.

Objective In this study, the resistance of Blattella germanica to D-cyphenothrin in Guangdong Province was analyzed. Further, the contact activity of eight types of plant essential oils against B. germanica and their synergistic effects with D-cyphenothrin were tested and screened, providing a basis for slowing down insecticide resistance in pests and developing plant synergists. Methods The drip test method was used to measure the resistance levels of B. germanica to D-cyphenothrin in four cities of Guangdong Province:Zhongshan City, Foshan City, Zhuhai City, and Jiangmen City. In addition, the contact killing activities of eight types of plant essential oils against B. germanica, namely, garlic, cinnamon, clove, camphor, eucalyptus leaves, tea tree, Angelica dahurica and peppermint, and their synergistic activities with D-cyphenothrin were evaluated. Results Except for B. germanica in the Xiaolan area of Zhongshan, which was moderately resistant, B. germanica in the other four towns in Guangdong were all highly resistant. Among the eight essential oils tested, garlic essential oil had the strongest toxic activity against B. germanica, with LD50 values of 45.01 μg/individual. A concentration of 2% essential oil plus D-cyphenothrin (LD20)was used to screen for synergistic activity. After 24 h of treatment, Angelica dahurica, garlic, peppermint, camphor, and tea tree essential oils showed synergistic activity. Of these, A. dahurica essential oil had the strongest synergistic activity, with a synergistic coefficient of 125%. Conclusions The essential oil of garlic had the strongest toxic activity against B. germanica, and the essential oils of A. dahurica and garlic together had the strongest synergistic activity with D-cyphenothrin, thereby providing a reference for developing natural plant synergists.

Purpose: This study assessed the performance of the ultrasound-guided attenuation parameter (UGAP) in diagnosing and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) served as the reference standard. Methods: Patients with hepatic steatosis were enrolled in this prospective study and underwent UGAP measurements. MRI-PDFF values of ≥5%, ≥15%, and ≥25% were used as references for the diagnosis of steatosis grades ≥S1, ≥S2, and S3, respectively. Spearman correlation coefficients and area under the receiver operating characteristic curves (AUCs) were calculated. Results: Between July 2023 and June 2024, the study included 88 patients (median age, 40 years; interquartile range [IQR], 36 to 46 years), of whom 54.5% (48/88) were men and 45.5% (40/88) were women. Steatosis grades exhibited the following distribution: 22.7% (20/88) had S0, 50.0% (44/88) had S1, 21.6% (19/88) had S2, and 5.7% (5/88) had S3. The success rate for UGAP measurements was 100%. The median UGAP value was 0.74 dB/cm/MHz (IQR, 0.65 to 0.82 dB/ cm/MHz), and UGAP values were positively correlated with MRI-PDFF (r=0.77, P<0.001). The AUCs of UGAP for the diagnoses of ≥S1, ≥S2, and S3 steatosis were 0.91, 0.90, and 0.88, respectively. In the subgroup analysis, 98.4% (60/61) of patients had valid controlled attenuation parameter (CAP) values. UGAP measurements were positively correlated with CAP values (r=0.65, P<0.001). Conclusion Using MRI-PDFF as the reference standard, UGAP demonstrates good diagnostic performance in the detection and grading of hepatic steatosis in patients with MASLD.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.