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 analyze the genetic characteristics and variations of influenza A (H3N2) viruses in Ma'anshan from 2022 to 2024, and to provide a scientific basis for local influenza prevention and control. Methods From April 2022 to March 2024, influenza-like illness (ILI) specimens were collected from three national influenza surveillance sentinel hospitals in Ma’anshan. Samples positive for influenza by real-time PCR were subjected to virus culture and identification. A total of 40 representative A/H3N2 strains with hemagglutination titers ≥8 were selected for whole-genome sequencing. Genetic evolution, homology, amino acid variations, and glycosylation sites were analyzed. Results All H3N2 representative strains from the 2022–2023 influenza season belonged to clade 3C.2a1b.2a.1a.1, while those from the 2023–2024 season fell into clade 3C.2a1b.2a.2a.3a.1. The nucleotide and amino acid sequence similarities of HA and NA between the 40 representative strains and the vaccine strain A/Darwin/6/2021 were all above 97.35%. Compared with the vaccine strain, amino acid mutations were identified in antigenic sites A, B, C, and E, as well as in receptor-binding sites of the HA protein. An I222V substitution was detected in the NA protein. The HA protein contained four additional glycosylation sites compared to the vaccine strain, while the glycosylation pattern of the NA protein remained consistent. Conclusion No antigenic drift was observed in the influenza A/H3N2 viruses in Ma'anshan City from 2022 to 2024, but genetic changes such as branching variations, key amino acid substitutions, and an increase in HA glycosylation sites were observed. These findings underscore the importance of sustained molecular surveillance of local influenza viruses.

Objective: To investigate the correlation between color parameters (L^*, a^*, b^*, Eab^*) and the contents of reducing sugars, total polysaccharides, total oligosaccharides, as well as four saccharides (fructose, glucose, sucrose, and kestose) during the nine cycles of steaming and sun-drying processing of Polygonatum kingianum, and to preliminarily explore the optimal processing duration.
Methods: The color changes were objectively evaluated using a colorimeter. The anthrone-sulfuric acid method was employed to determine total polysaccharides and oligosaccharides. The 3,5-dinitrosalicylic acid (DNS) colorimetric method was used to measure total reducing sugar content. High-performance liquid chromatography coupled with charged aerosol detection (HPLC-CAD) was applied for quantitative analysis of fructose, glucose, sucrose, and kestose. Multivariate statistical analysis was conducted to assess samples from different processing stages.
Results: Significant variations in color and component contents were observed across processing stages. The herbal pieces progressively darkened with increased processing cycles: brightness (L^*) and total color difference (Eab^*) initially decreased then stabilized, while a^* (red-green) and b^* (yellow-blue) values first increased then declined. Total polysaccharides and oligosaccharides showed overall decreasing trends, whereas reducing sugars initially increased before stabilizing. Fructose and glucose levels rose continuously, while sucrose and kestose decreased progressively, becoming undetectable after five cycles.
Conclusion: The chromatic alteration and saccharide composition of P. kingianum showed significant correlation with processing duration. Both total color difference (Eab^*) and reducing sugar content stabilized after four processing cycles (12 hours), suggesting that four cycles of steaming and sun-drying may represent the optimal processing duration.

Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

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.

ObjectiveTo explore the molecular mechanism through which modified Guizhi Fulingwan （MGZFLW） promotes apoptosis and inhibits prostate cancer through the miR-34a-5p/δ-like protein 1 （DLL1）/Notch signaling pathway based on the traditional Chinese medicine theory of Yang transforming Qi while Yin constituting form. MethodsThe optimal intervention conditions of MGZFLW-containing serum and docetaxel （DXT） were screened by the cell counting kit-8 （CCK-8） method. Human prostate cancer cells （PC-3） were allocated into blank， MGZFLW （10%）， and DXT （30 nmol·L^-1） groups. The effects of MGZFLW-containing serum on the migration and proliferation of PC-3 cells were evaluated by cell scratch and colony formation assays， and the apoptosis of PC-3 cells was detected by terminal-deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling （TUNEL） assay. The cells were transfected with miR-34a-5p mimics and miR-34a-5p inhibitor. The mRNA levels of miR-34a-5p， DLL1， Notch1 and its downstream effector factors Notch1 intracellular domain （NICD1）， Hes family basic helix-loop-helix transcription factor 1 （Hes1）， and hairy/enhancer-of-split related with YRPW motif 1 （Hey1） were determined by Real-time PCR. The protein levels of DLL1， Notch1， NICD1， Hes1， and Hey1 were determined by a WES fully automatic protein system. The effect of miR-34a-5p on the DLL1-mediated Notch pathway was evaluated based on the results. Further， after MGZFLW-containing serum intervention， the expression of DLL1 and Notch1 was detected by the immunofluorescence （IF） assay， and the mRNA and protein levels of miR-34a-5p/DLL1/Notch pathway-related molecules were quantified by Real-time PCR and the WES fully automatic protein system， respectively， to explore the regulatory effect of MGZFLW-containing serum on the miR-34a-5p/DLL1/Notch pathway. ResultsMGZFLW-containing serum inhibited the viability， migration， and proliferation and promote the apoptosis of PC-3 cells （P<0.01）. The overexpression of miR-34a-5p down-regulated the mRNA and protein levels of key molecules in the DLL1/Notch signaling pathway and promoted cell apoptosis （P<0.01）， while inhibition of miR-34a-5p had the opposite effects. MGZFLW-containing serum reversed the activation of the DLL1/Notch pathway and the inhibition of apoptosis caused by miR-34a-5p inhibition， up-regulated the expression of miR-34a-5p， and down-regulated the expression of related molecules in this pathway （P<0.01）. ConclusionMGZFLW can up-regulate the expression of miR-34a-5p to inhibit the DLL1/Notch signaling pathway and promote the apoptosis of prostate cancer cells， thereby inhibiting prostate cancer. This study provides experimental evidence for clarifying the molecular mechanism of the anti-prostate cancer effect of this formula.

ObjectiveTo develop a systematic case management model based on the International Classification of Functioning, Disability and Health (ICF) Vocational Rehabilitation Core Set (VR-CS) and explore its application pathways and efficacy in vocational rehabilitation. The 13 core categories of VR-CS are applied in vocational rehabilitation case management practices, utilizing comprehensive functional assessments to design and implement structured and individualized case management plans. This, in turn, seeks to enhance individuals' vocational independence, social participation and overall quality of life. MethodsThis study adopted a combined approach of theoretical research and empirical case analysis. Based on the 13 core categories of VR-CS, a comprehensive vocational assessment was conducted across three dimensions: body function and structure, activities and participation, and environmental factors. The study theoretically analyzed how to develop and implement holistic and individualized vocational rehabilitation plans, along with dynamic monitoring processes. Three types of typical vocational rehabilitation cases were examined, including individuals with major depressive disorder, high-functioning autism and mild cognitive impairment, to illustrate the evidence and effectiveness of VR-CS-based case management. ResultsThe VR-CS-based case management method, grounded in the ICF bio-psycho-social model, constructed an integrated and individualized case management system. This system combined the assessment and analysis of vocational rehabilitation needs, goal setting and planning, multidisciplinary team intervention, individualized interventions, process monitoring and dynamic adjustments, return-to-work activities, and long-term follow-up services.The case management model developed through VR-CS demonstrated significant and systematic efficacy in promoting vocational independence and social participation. This study provided a detailed analysis of the primary methods and steps involved in designing and implementing case management and elaborates on the practical applications of this model from the three representative cases. At the body function and structure level, case management included the evaluation of energy and drive functions (b130), high-level cognitive training (b164), and the enhancement of exercise tolerance (b455). Case management focused on accurately setting short- and long-term goals around functional limitations and needs. Dynamic monitoring during interventions ensured timely adjustments to intervention measures. This process improved physical endurance and cognitive function, enhanced sustained work capacity in complex vocational environments. At the activities and participation level, the focus was on skill acquisition (d155), stress management and psychological adjustment (d240), and the cultivation of complex interpersonal communication abilities (d720). Individuals engaged in regular professional skills training, role-playing and simulated work scenarios to progressively enhance vocational adaptability and social interaction skills. Through this process, individuals acquired practical skills, gradually boosting self-efficacy and vocational confidence, thereby facilitating the reshaping of their social roles. At the environmental and personal factors level, case management pathways involved active participation from immediate family (e310), positive shifts in societal attitudes (e460), and the effective utilization of health and employment policy resources (e580, e590). By integrating social and community resources comprehensively, the program created a more inclusive and supportive rehabilitation environment. By designing and implementing systematic case management programs, individuals showed significant improvements in psychological well-being, vocational adaptability and social interaction skills. The majority of cases achieved stable employment or continued participation in social activities following the intervention. ConclusionVR-CS provides a systematic, multidimensional and person-centered case management framework. This framework applies the bio-psycho-social model, analyzing individuals' primary functional impairments and vocational rehabilitation needs from the perspectives of body functions, psychological states and environmental factors. On this basis, a comprehensive, targeted and holistic case management plan is developed and implemented. The VR-CS-based case management approach not only enhances vocational capabilities but also improves overall quality of life and social adaptability.

Background: The genetic basis for hyperglycaemia in pregnancy remain unclear. This study aimed to uncover the genetic determinants of gestational diabetes mellitus (GDM) and investigate their applications. Methods: We performed a meta-analysis of genome-wide association studies (GWAS) for GDM in Chinese women (464 cases and 1,217 controls), followed by de novo replications in an independent Chinese cohort (564 cases and 572 controls) and in silico replication in European (12,332 cases and 131,109 controls) and multi-ethnic populations (5,485 cases and 347,856 controls). A polygenic risk score (PRS) was derived based on the identified variants. Results: Using the genome-wide scan and candidate gene approaches, we identified four susceptibility loci for GDM. These included three previously reported loci for GDM and type 2 diabetes mellitus (T2DM) at MTNR1B (rs7945617, odds ratio [OR], 1.64; 95% confidence interval [CI],1.38 to 1.96]), CDKAL1 (rs7754840, OR, 1.33; 95% CI, 1.13 to 1.58), and INS-IGF2-KCNQ1 (rs2237897, OR, 1.48; 95% CI, 1.23 to 1.79), as well as a novel genome-wide significant locus near TBR1-SLC4A10 (rs117781972, OR, 2.05; 95% CI, 1.61 to 2.62; Pmeta=7.6×10-9), which has not been previously reported in GWAS for T2DM or glycaemic traits. Moreover, we found that women with a high PRS (top quintile) had over threefold (95% CI, 2.30 to 4.09; Pmeta=3.1×10-14) and 71% (95% CI, 1.08 to 2.71; P=0.0220) higher risk for GDM and abnormal glucose tolerance post-pregnancy, respectively, compared to other individuals. Conclusion Our results indicate that the genetic architecture of glucose metabolism exhibits both similarities and differences between the pregnant and non-pregnant states. Integrating genetic information can facilitate identification of pregnant women at a higher risk of developing GDM or later diabetes.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective: To understand the current situation and influencing factors of comorbidity of depressive and anxiety symptoms among middle school students in Chongqing, so as to provide a scientific basis for formulating a comprehensive strategy for the co prevention of multiple diseases among middle school students. Methods: From September to December 2024, 12 327 middle school students were selected from 6 districts and counties in Chongqing by the combination of stratified cluster sampling and convenience sampling method. The current status of depressive and anxiety symptoms was investigated by using the Center for Epidemiological Survey-Depression Scale (CES-D) and the Generalized Anxiety Disorder-7 (GAD-7). The Chi-squared test was used to compare the differences between groups with comorbidity of depressive and anxiety symptoms, multivariate Logistic regression analysis was used to analyze its related factors, and a nomogram prediction model was drawn. Results: The detection rates of depressive symptoms, anxiety symptoms and comorbidity among middle school students in Chongqing were 26.34%, 34.55% and 21.16%, respectively. Among them, the detection rates of the three types of symptoms in girls (29.80%, 40.99%, 25.15%) were all higher than those in boys (23.22%, 28.73%, 17.55%) ( χ 2=68.61, 204.23, 106.51, all P <0.01). Statistical significance was observed in the distribution of depressive and anxious symptoms among middle school students across different gender, academic stage, school district, family type, physical activity levels, parental discipline, smoking, alcohol consumption, sleep deprivation, excessive screen time, Internet addiction, and bullying ( χ 2=14.49-991.46, all P <0.01). Multivariate Logistic regression analysis showed that compared with junior high school students, ordinary high school students had a higher risk of comorbidity ( OR=2.71, 95% CI = 2.41-3.05); girls ( OR=2.17, 95%CI =1.95-2.40), non-core family ( OR=1.20, 95%CI =1.08-1.32), and good neighborhood ( OR=1.16, 95%CI =1.02-1.30), campus bullying ( OR=4.88, 95%CI =4.32-5.50), Internet addiction ( OR=4.77, 95%CI = 3.41 -6.68), parental beating and scolding ( OR=3.18, 95%CI =2.72-3.71), alcohol consumption ( OR=2.10, 95%CI =1.86- 2.37 ), and insufficient sleep ( OR=1.73, 95%CI =1.54-1.95) had higher risks with comorbidity of depression and anxiety symptoms (all P <0.05). A nomogram prediction model was constructed based on significant variables shows that C-index=0.75 (AUC= 0.75 , 95% CI=0.74-0.76, P <0.05), and the model had good predictive performance. Conclusions The current situation of comorbidity of depressive and anxiety symptoms among middle school students in Chongqing is not optimistic. The nomograms can be used to effectively predict the risk of comorbidity of depressive and anxiety symptoms in middle school students.