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.

AIM To investigate the renal protective effects of Qizhi Tongluo Formula on a mouse model of diabetic nephropathy.METHODS The male db/db mice were randomly divided into the model group,the dapagliflozin group(0.76 mg/kg)and the low,medium and high dose Qizhi Tongluo Formula groups(7.83,15.65 and 31.3 g/kg),with 6 mice in each group,in contrast to the 6 db/m mice of the control group.When the mice of the control group and the model group were given distilled water by gavage,those of the other administration groups were dosed with the corresponding drug by gavage once daily for 8 weeks.After the drug administration,the mice had their levels of FBG,BUN,Scr and 24 h-UTP detected;their renal pathological changes observed by transmission electron microscopy(TEM)and HE staining;their levels of serum Nrf2,HO-1,Keap1 and renal oxidative stress assessed by ELISA;their renal Nrf2 protein expression observed by immunofluorescence(IF);their renal protein expressions of Nrf2,HO-1 and Keap1 detected by Western blot;and their renal Nrf2,HO-1,and Keap1 mRNA expressions detected by RT-qPCR.RESULTS Compared with the control group,the model group displayed increased levels of 24 h-UTP,Scr,FBG and renal MDA(P＜0.01);decreased renal activities of SOD,CAT and GSH-Px(P＜0.01);mild glomerular mesangial hyperplasia,vacuolated renal tubular epithelial cells,widely fused podocyte foot processes,disappearance of tear film,decreased secretion levels of serum Nrf2 and HO-1 and renal protein and mRNA expressions of Nrf2 and HO-1(P＜0.05,P＜0.01);and decreased secretion levels of serum Keap1 and renal Keap1 protein and mRNA expressions(P＜0.01).Compared with the model group,the high-dose Qizhi Tongluo Formula group demonstrated decreased levels of 24 h-UTP,Scr,FBG and renal MDA(P＜0.01);increased renal activities of SOD,CAT and GSH-Px(P＜0.01);alleviated renal pathological damage,increased secretion levels of serum Nrf2 and HO-1 and renal protein and mRNA expressions of Nrf2 and HO-1(P＜0.01);and increased level of serum Keap1 secretion and renal Keap1 protein and mRNA expressions(P＜0.01).CONCLUSION Qizhi Tongluo Formula can inhibit oxidative stress and alleviate kidney damage in db/db mice by activating Nrf2/Keap1/ARE signaling pathway.

OBJECTIVE To explore the epidemiological characteristics of the children with acute respiratory tract in-fection and analyze the changes of peripheral blood prealbumin(PA),serum amyloid protein A(SAA)and pro-calcitonin(PCT)so as to provide bases for the clinical diagnosis.METHODS A total of 177 children with acute re-spiratory tract infection who were treated in Qingdao Haici Hospital Affiliated to Qingdao University from Nov.2021 to Nov.2023 were assigned as the infection group,meanwhile,195 healthy children who received physical examination were chosen as the healthy group.The distribution of pathogens isolated from the patients of the in-fection group was statistically analyzed.The levels of PA,SAA,CRP and PCT were compared between the two groups.The values of the indexes in diagnosis of the acute respiratory tract infection were analyzed.RESULTS The total positive rate of isolation of pathogens was 31.07％(55/177)among the children with acute respiratory tract infection,and Mycoplasma pneumoniae was the predominant species of pathogen.There was significant difference in the isolation rate of pathogens among the different age groups of children with acute respiratory tract infection(x2=8.270,P=0.041);the children of the preschool age group were dominant.There was significant difference in the isolation rate of pathogens from the children with acute respiratory tract infection among the different sea-sons(x2=9.557,P=0.023);the isolation rates were relatively high in spring and winter.There were significant differences in the levels of serum PA,SAA,CRP and PCT between the infection group and the healthy group(P＜0.05);the CRP level was(13.48±4.25)mg/L in the infection group,(7.85±2.51)mg/L in the healthy group,with the difference value maximum(t=15.724,P＜0.001).The area under the curve(AUC)value of the joint detection of the four indexes was higher than that of the single detection in diagnosis of the acute respiratory tract infection in the children(P＜0.05).CONCLUSIONS M.pneumoniae is dominant among the pathogens isolated from the children with acute respiratory tract infection,the preschool age children are in the majority.The infec-tion is prevalent in spring and winter.The children with the infection show the abnormal expressions of PA,SAA,CRP and PCT,and the joint detection of the four indexes has high value in diagnosis of the infection.

Objective:To investigate the risk factors for tibial tuberosity avulsion fractures (TTAF) in adolescents and develop a clinically applicable nomogram prediction model for rapid risk assessment and identification of high-risk populations.Methods:A retrospective study was conducted to analyze the data of 58 adolescent patients (61 sides) who had been treated for TTAF at Department of Orthopaedics, Children's Hospital of Soochow University between January 2018 and October 2024. There were 57 males and 1 female, with an age of 14.0 (13.0, 14.0) years, designated as the observation group. The control group enrolled another contemporary 52 patients who, matched with age and gender, had a clear history of trauma and clinical symptoms of knee injury but no bone continuity destruction of the knee joint by the final imaging examination. They were 50 males and 2 females, with an age of 13.5 (12.0, 15.0) years. Baseline characteristics, pre-injury physical activity profiles, and imaging-derived anatomical parameters were compared between the 2 groups. Variables with P<0.05 in the univariate analysis were included in a multivariable logistic regression model to identify independent risk factors for adolescent TTAF, based on which a nomogram prediction model was developed and internally validated using bootstrapping (1,000 resamples). Results:Multivariable logistic regression analysis identified the following independent risk factors for adolescent TTAF: short-term high-frequency exercise ( OR=5.653, 95% CI: 1.068 to 29.918, P=0.042), a large body mass index (BMI) ( OR=1.445, 95% CI: 1.197 to 1.743, P<0.001), a large posterior tibial slope (PTS) ( OR=1.637, 95% CI: 1.140 to 2.353, P=0.008), and an increased tibial tubercle-trochlear groove (TT-TG) distance ( OR=1.227, 95% CI: 1.021 to 1.474, P=0.029). The area under the receiver operating characteristic curve (AUC) was 0.927 for the model incorporating CT-derived variables and 0.907 for the model excluding CT variables. Decision curve analysis (DCA) and calibration curves demonstrated favorable clinical utility and alignment between predicted and observed outcomes in both models. Conclusions:Short-term high-frequency exercise, a large body mass index, a large PTS, and an increased TT-TG distance are risk factors for adolescent TTAF. The established prediction model is suitable for rapid clinical assessment and demonstrates good predictive capability.

Objective By analyzing the gene expression data in TCGA-THCA dataset,the differentially expressed genes related to thyroid carcinoma(THCA)were identified,a risk model was construct,and the role of CCL chemokine family in the development of THCA and its effect on the tumor immune microenvironment were investigated.Methods TCGA-THCA dataset was downloaded and analyzed,including 512 cancer samples and 59 adjacent tissue samples.The differentially expressed genes were obtained by taking the intersection of R packages of differential analysis,and the principal component analysis(PCA),Gene Ontology(GO),and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were performed.CellMarker,monocle,and CellChat were used to explore the Cell atlas,pseudotemporal trajectory,and cellular communication.Results A total of 698 up-regulated genes and 285 down-regulated genes were identified.PCA showed that there were significant differences in gene expression patterns between the THCA group and the normal group.GO and KEGG enrichment analysis revealed that differentially expressed genes were mainly involved in biological processes such as extracellular matrix tissue,cell junction assembly,and complement system.The results of risk model showed that the CCL genes was significantly correlated with poor prognosis(P=0.005).Single cell analysis revealed that fibroblasts played a key role in the development of THCA,and the expression of CCL gene was significantly up-regulated in fibroblasts(P<0.05).The results of pseudotemporal trajectory analysis showed that CCL gene was differentially expressed during cellular differentiation;the results of cellular communication analysis showed that the interaction between fibroblasts and endothelial cells is crucial in the tumor microenvironment.Conclusion The expression of CCL chemokine family in THCA is closely related to poor prognosis,especially CCL4,which activates the downstream signaling pathways by interacts with CCR receptors of cancer-associated fibroblasts,thereby promoting the development of cancer.These findings provide novel insights for understanding the role of CCL chemokine family in THCA and its regulation of the tumor immune microenvironment.

Widespread utilization of glyphosate has led to environmental residues,posing potential threats to ecological systems and human health.Traditional methods for detection of glyphosate are limited by specialized equipment and operational techniques,resulting in inefficient responses.Therefore,it is urgent to develop a convenient,sensitive and accurate detection method for detection of glyphosate.Herein,a new naphthalenesulfonamide-based"Turn-on"fluorescent probe was synthesized using 2-chloroaniline and dansyl chloride as raw materials through a one-step process,which showed a good linear relationship between the glyphosate concentration in concentration range of 0.003-70 μmol/L and the fluorescence intensity(R2=0.995),with a detection limit of 2.73 nmol/L(S/N=3).Analytical techniques such as nuclear magnetic resonance(NMR)spectroscopy and high-resolution mass spectrometry(HRMS)were used to investigate the interaction mechanism between the fluorescent probe and glyphosate.The results indicated that a nucleophilic substitution reaction occurred between the probe and the secondary amine(—NH—)of glyphosate,inducing a photoinduced electron transfer(PET)effect which enhanced the fluorescence intensity by 11.2 times.The probe showed good anti-interference ability towards coexisting metal ions,anions and pesticides in water.When applied to determination of glyphosate in the samples such as tap water,river water(Xiangxi River Reservoir),soil,soybeans,and corn,the spiking recoveries ranged from 94.7％to 109.9％,demonstrating the high accuracy and broad applicability of this detection method.A portable test strip based on this fluorescent probe was developed for rapid semi-quantitative analysis of glyphosate.The developed method was rapid,sensitive,and portable,providing theoretical and technical support for on-site measurement of environmental contaminants.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.