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 construct a decision tree model to predict the risk of breast cancer in patients with pathological nipple discharge.Methods:A total of 157 patients with pathological nipple discharge,who were diagnosed and treated at Weifang Municipal Hospital of Traditional Chinese Medicine from January 2019 to April 2024 and met the inclusion criteria,were selected.A risk prediction model for concurrent breast cancer in patients with pathological nipple discharge was developed using Logistic regression analysis.A decision tree was then constructed,and the predictive performance of the model was assessed based on the area under the receiver operating characteristic curve(AUC).Re-sults:The incidence of concurrent breast cancer among patients with pathological nipple discharge was 24.2%.Accord-ing to the results of binary Logistic regression analysis,elevated CEA and CA 153 levels in nipple discharge,as well as bloody discharge,emerged as independent risk factors for the development of breast cancer in such patients(P<0.05).Based on these findings,a decision tree model was constructed to predict the risk of concurrent breast cancer in patients with pathological nipple discharge.The validation results showed that the Logistic regression model had an AUC value of 0.800,while the decision tree model achieved an AUC value of 0.889.Conclusions:The decision tree model,built upon the identified influencing factors,exhibits strong predictive power for the risk of developing concurrent breast can-cer in patients with pathological nipple discharge,thus facilitating more precise preoperative diagnoses by clinicians for these patients.

Objective:To analyze the factors associated with long-term survival after radical resection of hepatitis B virus(HBV)-associated hepatocellular carcinoma(HCC),and to construct random forest and Cox regression models,to evaluate the two models.Methods:A total of 368 patients with HBV-infected HCC who underwent radical resection were selected retrospectively.These patients were categorized as having a good prognosis(n=266)or a poor prognosis(n=102)based on their survival and mortality status.Univariate and Cox regression analysis were used to identify fac-tors that predict poor prognosis in HCC patients after surgery,and Cox regression and random forest prediction models were constructed and evaluated.Results:There were significant differences in smoking history,Child-Pugh classifica-tion,cirrhosis,microvascular invasion,TNM staging,tumor capsule integrity,platelet-to-lymphocyte ratio(PLR),regular antiviral therapy,HBV-DNA load,alpha-fetoprotein(AFP),neutrophil-to-lymphocyte ratio(NLR),systemic immune in-flammatory index(SII),and albumin-to-globulin ratio(AGR)between the two groups(P<0.05);Cox regression showed that cirrhosis,microvascular invasion,regular antiviral treatment,HBV-DNA load,NLR,PLR,SII,and AGR were related factors that negatively affected the prognosis of patients with HBV-infected HCC after surgery(P<0.05),with an AUC of 0.870 for predicting prognosis;the importance ranking obtained by the random forest model was HBV-DNA load,cirrho-sis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII,with an AUC of 0.926 for predicting prog-nosis;the AUC predicted by the random forest model was greater than that predicted by the Cox regression model(Z=2.411,P=0.016).Conclusion:HBV-DNA load,cirrhosis,regular antiviral therapy,microvascular invasion,NLR,PLR,AGR,and SII are factors that affect the poor prognosis of patients with HBV-related HCC after surgery.The random for-est prediction model constructed based on these factors has high predictive value and is superior to the Cox regression prediction model.

Aim To identify the underlying target of bullatine A(BA)against rheumatoid arthritis(RA)u-sing limited proteolysis-small molecule mapping(LiP-SMap)drug target proteomics and to provide a scientif-ic basis for clinical application of Aconiti brachypodi Radix in the treatment of RA.Methods LiP-SMap drug target proteomics was employed to perform bioin-formatics analysis for comparing and validating the dif-ferential protein expression after BA intervention.A collagen-induced arthritis(CIA)model was estab-lished in DBA/1 mice using bovine type Ⅱ collagen.The mice were then divided into the CIA model group,methotrexate-positive control group(MTX group),and BA groups(10 mg·kg-1 and 20 mg·kg-1)based on their clinical scores.After drug intervention,the thera-peutic efficacy against RA was assessed by joint index scores and foot thickness measurements.Histopatholog-ical changes in the arthritic joints of CIA mice were e-valuated using hematoxylin and eosin(HE)staining.Enzyme-linked immunosorbent assay(ELISA)was employed to detect inflammatory cytokines interleukin-17(IL-17)and total IgG and IgG3 anti-collagen-spe-cific antibodies levels from the serum of CIA mice.Flow cytometry was used to detect the expression levels of intracellular Th17 cells(IL-17+CD4+T cells)and Th1 cells(IFN-γ+CD4+T cells).Fluorescent quanti-tative PCR was performed to detect the expression of genes related to differential proteins.Results The proteomic analysis identified Serpinb1a as a protein with strong binding affinity to BA,and KEGG enrich-ment analysis indicated IL-17 signaling pathway was a crucial pathway of BA in against RA.BA treatment significantly reduced clinical scores and foot thickness,improved local arthritis symptoms in CIA mice,and al-leviated inflammatory cell infiltration into arthritic joints(P＜0.05).Differential protein validation re-sults showed that BA had strong affinity with Serpinb1a(-5.92 kJ·mol-1)and downregulated the expres-sion of Serpinb1a mRNA.Furthermore,the administra-tion of BA markedly reduced serum IL-17 A levels from CIA mice,inhibited the expression of intracellular IL-17 A and IFN-γ cytokines in splenic CD4+T cells(P＜0.05),and significantly downregulated the transcrip-tional expression of IL-17F(P＜0.05).Conclusion BA exhibits therapeutic effects on collagen-induced arthritis,and its mechanism of action may involve the regulation of Serpinb1a and the IL-17 signaling path-way.

Objective To investigate the effects of ischemia time and storage periods on RNA quality in fresh-frozen breast cancer(BC)and esophageal cancer(EC)tissue samples in order to establish evidence-based protocols for biobank sample management.Methods The tumor(T)and paired normal(N)tissue samples from 6 cases of BC and 6 cases of EC were collected and cryopreserved in Biobank,Shantou Central Hospital.Mirror paraffin-embedded tissues were simultaneously prepared into sections for morphological analysis.The samples were divided into two groups of<15 min and 15-30 min according to ischemia time,and RNA quality was analyzed at 4 storage periods of 8-10 months(T1),14-16 months(T2),26-28 months(T3)and 38-40 months(T4).Results In 96 analyzed samples,93.8%(90/96)exhibited high quality(RIN≥6),with 89.6%(43/48)in BC and 97.9%(47/48)in EC.Significant differences in RIN were observed between BC group and EC group(8.050 vs.8.600,P=0.009).In EC group,RIN value was significantly negatively correlated with RNA yield(P<0.001).Moreover,RIN values of tumor-normal pairs exhibited markedly significant differences(7.550 vs.9.000,P<0.001).In contrast,no significant difference was detected in BC group(8.200 vs.7.700,P=0.348).Statistical analysis showed that RIN value was positively correlated with 28S/18S(P<0.001),but had no correlation with tumor content(P=0.676)and necrotic content(P=0.055).Neither ischemia time(<15 min vs.15-30 min:8.200 vs.8.300,P=0.932)nor storage periods(T1-T4:8.400,7.700,8.450,8.600,P=0.163)compromised RNA quality.Conclusion Organ origin and tissue type could influence RNA quality of fresh-frozen tissue samples.However,limited ischemia time(≤30 min)and long-term storage period(38-40 months)do not adversely affect RNA quality in fresh-frozen breast cancer and esophageal cancer tissue samples.

Risks of food safety induced by small molecule drug residues in animal food and environment have become an increasing public concern,so it is necessary to develop highly sensitive and easy-to-operate techniques to detect small molecules.Herein,a metasurface plasma resonance(MetaSPR)sensor chip coupled with gold nanoparticles(AuNPs)was developed for detection of enrofloxacin(ENR)based on competitive immunoassay.The detection range of the sensor for ENR was 0.025-3.2 ng/mL,and the detection limit(3σ)was 20 pg/mL.The biosensor showed excellent performance including high selectivity,good stability,ease to operate and high throughput,etc.The developed method was applied to detection of ENR residues in real samples,with recoveies of 96.0% -105.0%.The proposed sensing strategy provided new technique reference for detection of other small molecules in the field of residue analysis in food safety and environment monitoring.

Hepatocellular carcinoma(HCC)is one of common cancer that seriously endangers human health.Designing methods for early,rapid,and accurate diagnosis of HCC has become the key point.Golgi protein 73(GP73),a novel potential biomarker for HCC,is crucial for diagnosis and treatment of HCC.In this study,a colorimetric sensor with rapidity,smplicity and high specificity was established for detection of GP73 based on peroxidase-like activity of hemin-reduced graphene oxide-manganese dioxide(H-rGO-MnO2).The H-rGO-MnO2-GP73Apt1 signal probe was synthesized by carboxyl of H-rGO-MnO2 nanozyme and amination of GP73 aptamer(GP73Apt1)though amide reaction.In the presence of GP73,the sulfhydryl-modifed GP73 aptamer(GP73Apt2),as the capture probe,and the signal probe both specifically recognized GP73,forming a sandwich structure(GP73Apt2-GP73-H-rGO-MnO2-GP73Apt1).This structure could catalyze the oxidation of H2O2 to produce hydroxyl radical(·OH),thereby oxidizing the colorless phthalenediamine(OPD)into the yellow 2,3-diaminophenazine(DPA).The quantitative detection of GP73 was achieved by measuring the characteristic absorbance of DPA at 450 nm.In the GP73 concentration range of 10-150 ng/mL,there was a good linear relationship between the DPA absorbance at 450 nm(A450 nm)and the GP73 concentration under optimal conditions.The linear equation was A450 nm=0.00321CGP73+0.8988,with the correlation coefficient(R2)of 0.9960 and the detection limit(LOD)of 5.38 ng/mL.The colorimetric sensor was applied to detection of GP73 in human serum samples,with recoveries of 88.4%?98.8%.This sensor showed high specificity,sensitivity,and stability,and had potential for clinical detection of GP73,providing a new approach for the early diagnosis of HCC.

Malonylation is an important post-translational modification of proteins.In this work,a comprehensive malonylation proteomics study on hepatocellular carcinoma(HCC)tumorous and non-tumorous tissues using antibody enrichment combined with high performance liquid chromatography-mass spectrometry for discovery of early diagnostic biomarkers or potential new drug targets of HCC was performed.A total of 1299 malonylated peptides containing 1064 malonylated sites were identified from HCC tissues,corresponding to 511 malonylated proteins.Quantitative results showed that 56 and 80 malonylated proteins were up-regulated and down-regulated in HCC tissues,including 60 and 101 malonylated sites,respectively.Kyoto encyclopedia of genes and genomes(KEGG)pathway analysis showed that these differentially modified proteins were involved in various important pathways such as metabolic pathways,fatty acid degradation,and glycolysis/gluconeogenesis.As a key enzyme in glycolysis/gluconeogenesis,phosphoenolpyruvate carboxykinase 1(PCK1)was malonylated at lysine 244(K244)and the malonylation was only detected in HCC tumorous tissues.More importantly,the K244 site served as a binding site for Mn2+and highly conserved across different species.Therefore,it could speculate that the malonylation of K244 would affect its activity and played a role in liver cancer by affecting its binding with Mn2+,which requied further verification through site mutation experiments.Western blot analysis by malonylation pan antibody showed that the malonylation level reduced markedly in HCC tumorous tissues compared with adjacent non-tumorous tissues,which was consistent with mass spectrometry data.In addition,the proliferation and invasion of PLC/PRF/5 cell was significantly inhibited and protein malonylation level was increased obviously when treated with sodium malonate.All the evidence indicated that protein malonylation played an important role in HCC pathogenesis,and its molecular mechanism deserved further investigation.Furthermore,the 136 differentially malonylated proteins provided rich source of candidate targets for further research on HCC pathogenesis.

In recent years,micro photoionization detectors(μPID),with their rapid response speed and excellent sensitivity,have attracted widespread attention in both scientific research and industry.This study developed a portable gas chromatograph based on μPID technology(GC-μPID),and examined its key performance characteristics such as reproducibility,sensitivity,and online analytical capability.The results showed that the method's relative standard deviation(RSD)was controlled within 2.7%,demonstrating good reproducibility;for the standard curves of 27 kinds of volatile organic compounds(VOCs),the linearity was excellent(R2≥0.99),with detection limits of≤10 μg/m3 and benzene series compounds reaching detection limits as low as 0.5 μg/m3.In field applications at an industrial park,this method successfully identified and quantified 17 kinds of VOCs,accurately capturing their diurnal concentration variations.The results above validated that the method developed here had the capability of onsite real-time monitoring and provided an effective tool for in situ monitoring atmospheric pollutants.

Objective:To construct a nomogram based on preoperative MRI imaging features for the prediction of muscle-invasive upper urinary tract urothelial carcinoma（UTUC）and evaluate its performance.Methods:This retrospective cohort study analyzed the clinical data of 99 UTUC patients treated at the First Affiliated Hospital of Nanjing Medical University from April 2018 to May 2024. Among them，69（69.7%）were male and 30（30.3%）were female，with a median age of 67.0 years. All patients underwent preoperative MRI and radical nephroureterectomy. According to postoperative pathology，tumors staged ≥ T 2 were assigned to the muscle-invasive group，and those staged ≤ T 1 were assigned to the non-muscle-invasive group. Baseline data，pathological information，and imaging characteristics were collected and compared between the two groups. Logistic regression analysis was performed to identify risk factors for muscle-invasive UTUC，and a nomogram was constructed. The diagnostic performance of the model was assessed using receiver operating characteristic（ROC）curves，calibration curves，and decision curve analysis（DCA）. Results:Among the 99 patients，70（70.7%）were diagnosed with muscle-invasive UTUC，and 29（29.3%）with non-muscle-invasive UTUC. The muscle-invasive group had significantly larger tumor size［4.5（2.8，7.0）cm vs. 3.0（2.3，4.5）cm， P = 0.029］，a higher incidence of multifocal tumors［37.1%（26/70）vs. 3.5%（1/29）， P < 0.001］，patchy tumors［30.0%（21/70）vs. 6.9%（2/29）， P = 0.019］，spiculated tumor margins［52.9%（37/70）vs. 17.2%（5/29）， P = 0.001］，tumor compression on renal parenchyma or periureteral/peripelvic fat［68.6%（48/70）vs. 10.3%（3/29）， P < 0.001］，high-grade pathology［92.9%（65/70）vs. 75.9%（22/29）， P = 0.043］，lymph node metastasis［28.6%（20/70）vs. 0， P = 0.001］，and lymphovascular invasion［42.9%（30/70）vs. 10.3%（3/29）， P=0.002］. The apparent diffusion coefficient（ADC）values［0.9（0.8，1.1）× 10 -3 mm2/s vs. 1.1（1.0，1.4）× 10 -3 mm2/s， P < 0.001］and normalized ADC（NADC）values［0.8（0.7，1.0）vs. 0.9（0.8，1.1）， P = 0.002］were significantly lower in the muscle-invasive group. Univariate logistic regression identified multifocality，patchy tumor patterns，spiculated tumor margins，tumor compression on renal parenchyma or periureteral/peripelvic fat，and low NADC values as risk factors for muscle-invasive UTUC（all P < 0.05）. Multivariate analysis revealed multifocality（ OR = 17.903，95% CI 1.650 - 194.253， P = 0.018），tumor compression on renal parenchyma or perirenal / ureteral fat（ OR = 14.690，95% CI 3.069 - 70.323， P < 0.001），and low NADC value（ OR = 0.016，95% CI 0.001 - 0.471， P = 0.017）as independent risk factors. A nomogram was constructed based on these factors. The area under the ROC curve（AUC）of the model was 0.898（95% CI 0.838 - 0.957），with an optimal cutoff value of 0.639. The model showed an accuracy of 83.8%，sensitivity of 81.4%，and specificity of 89.7%. Calibration curves indicated good calibration，and DCA showed that the model provided substantial clinical net benefit. Conclusions:This study constructed a nomogram based on preoperative MRI features，including tumor multifocality，compression on renal parenchyma or periureteral/peripelvic fat and NADC value，which demonstrates good predictive performances for muscle-invasive UTUC.