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.

Diabetes mellitus, characterized by glucose metabolism disorders and marked by insulin deficiency or insulin resistance, has seen a continuous rise in prevalence. In recent years, islet transplantation has matured as a therapeutic approach for diabetes, becoming an important method for glycemic control and the reduction of diabetes-related complications. Donor selection directly influences transplant outcomes, and various research institutions worldwide have proposed multiple scoring systems to optimize donor assessment, such as the University of Alberta scoring system and the North American Islet Donor Score. This article explores the impact of key factors such as donor age, body mass index and ischemia time on islet transplantation. Combining practical experience in pancreatic donor selection from Shanghai Changzheng Hospital, it proposes screening criteria for pancreatic donors suitable for China, aiming to provide new evidence for improving the success rate of islet transplantation.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

OBJECTIVE To analyze the differences in chemical composition of mussels from Shengsi,Zhoushan in different har-vest months,and to compare the differences in the composition of mussels from different origins,so as to provide ideas for the compre-hensive utilization of its resources.METHODS Ultra-high performance liquid chromatography-triple quadrupole mass spectrometry(UHPLC-QqQ-MS)and spectrophotometry were used to analyze and evaluate the contents of nucleosides,amino acids,water-soluble proteins,total sugars and polysaccharides in mussels from Shengsi,Zhoushan in 12 months of the year and from 5 different origins;principal component analysis(PCA),partial least squares discriminant method(PLS-DA)and TOPSIS method were used to compre-hensively evaluate mussels.RESULTS A total of 16 amino acids and 11 nucleosides were detected in mussels.The average content of total amino acids in Shengsi mussels throughout the year was 4 851.74 μg·g-1,the average content of total nucleosides was 921.40 μg·g-1,and the average contents of water-soluble protein,polysaccharides,and total sugars were 51.32 mg·g-1,74.39 μg·g-1,and 417.22 mg·g-1,respectively.The nucleosides of Shengsi mussels were the highest in March and April,the ami-no acids and water-soluble proteins were the highest in April and May,and the polysaccharides and total sugars were the highest in Oc-tober and November.The PCA and PLS-DA results of the chemical components of different resources showed that there were great differences in Shengsi mussel samples harvested in different seasons.The entropy weight TOPSIS analysis showed that the comprehen-sive scores of Shengsi mussels in March and April(S7 and S8)were better than those in other areas,and the comprehensive score of Shengsi mussels in April(S8)was the highest,which was determined to be the best harvesting month.CONCLUSION The comparison results of multi-type resource chemistry show that there are great differences in the chemical compo-sition of Shengsi mussels in different harvesting seasons;the quality of Shengsi mussels is better than that of other areas;April is the best harvesting season,providing a reference for the quality evaluation and comprehensive development and utilization of mussels.

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.

BACKGROUND:The cryopreservation technology enables tissues/cells to be stored for a long time in a low-temperature environment while maintaining the integrity of their activity and function,which is of great significance for the construction of cell therapy,tissue engineering and biological sample banks.Cryoprotective agents often contain dimethyl sulfoxide and serum.To avoid the toxic side effects of dimethyl sulfoxide,the complexity of serum components and immune responses,although some finished cryoprotective agents have been marketed,they are faced with many difficulties such as high cost and limited application.Therefore,there is an urgent need to develop a cryoprotective agent with clear components and the ability to solve the above problems.OBJECTIVE:To evaluate the effects of a novel cryoprotectant on cryopreservation efficiency of different tissue and cell sources.METHODS:By applying the novel cryoprotectant as an experimental group with the commercially available and widely used cryoprotectant(control group)to umbilical cord Wharton's jelly tissue,umbilical cord mesenchymal stem cells,umbilical cord blood/peripheral blood mononuclear cells,NK and CIK cells,comparative analyses were conducted in terms of cell morphology,number,viability,surface markers,differentiation potential,and cell-killing toxicity assay before cryopreservation and after resuscitation thawing.We confirmed the cryopreservation effect of the new cryoprotectant and its potential application value.RESULTS AND CONCLUSION:(1)The novel cryoprotectant facilitated the normal growth of cryopreserved Wharton's jelly tissue upon recovery,exhibiting mesenchymal stem cell morphology.No significant differences were observed between the experimental and control groups in terms of cell recovery rate,surface markers,and differentiation potential.(2)There was no significant difference in the number and viability of cells between the experimental group and the control group after cryopreservation of cord blood/peripheral blood mononuclear cells,and the cryo-resuscitated cell numbers and viability of derived NK cells/CIK cells did not show significant difference between the experimental and control groups.(3)For NK cells derived and differentiated from cord blood/peripheral blood mononuclear cells,there was no significant difference in the proportion of CD56+CD16+cell subpopulations between the experimental group and the control group.For CIK cells derived and differentiated from cord blood/peripheral blood mononuclear cells,there was no significant difference in the proportions of CD3+CD8+and CD3+CD56+cell subpopulations between the experimental group and the control group.(4)In terms of cytotoxicity testing,when the effective-target ratio of immune cells and melanoma cell line Mel624 was 20:1,whether it was NK cells/CIK cells derived from cord blood or peripheral blood mononuclear cells,there was no significant difference in the tumoricidal activity of cells between the experimental group and the control group.These findings suggest that the novel cryoprotectant can replace existing commercially available and widely used cryoprotectants,and is applicable to Wharton's jelly tissue,umbilical cord mesenchymal stem cells,umbilical cord blood/peripheral blood mononuclear cells,as well as NK and CIK cells,providing a solid technical foundation for the scaling,standardization,and commercialization of universal cryoprotectants.

BACKGROUND: Prolonged occupational noise exposure poses potential health risks, but its impact on mitochondrial DNA (mtDNA) damage and methylation patterns remains unclear. METHOD: We recruited 306 factory workers, using average binaural high-frequency hearing thresholds from pure-tone audiometry to assess noise exposure. MtDNA damage was evaluated through mitochondrial DNA copy number (mtDNAcn) and lesion rate, and mtDNA methylation changes were identified via pyrophosphate sequencing. RESULTS: There was a reduction in MT-RNR1 methylation of 4.52% (95% CI: -7.43% to -1.62%) among workers with abnormal hearing, whereas changes in the D-loop region were not statistically significant (β = -2.06%, 95% CI: -4.44% to 0.31%). MtDNAcn showed a negative association with MT-RNR1 methylation (β = -0.95, 95% CI: -1.23 to -0.66), while no significant link was found with D-loop methylation (β = -0.05, 95% CI: -0.58 to 0.48). Mediation analysis indicated a significant increase in mtDNAcn by 10.75 units (95% CI: 3.00 to 21.26) in those with abnormal hearing, with MT-RNR1 methylation mediating 35.9% of this effect. CONCLUSIONS These findings suggest that occupational noise exposure may influence compensatory increases in mtDNA content through altered MT-RNR1 methylation.
Humans ; DNA, Mitochondrial ; DNA Methylation ; Male ; Adult ; Noise, Occupational/adverse effects* ; Middle Aged ; Occupational Exposure/adverse effects* ; Biomarkers/blood* ; Female

The dysregulation of cyclin-dependent kinase 12 (CDK12), which may result from genomic alterations or modulation by upstream effectors, is implicated in cancer oncogenesis and progression. CDK12 overexpression or activation is sufficient to induce tumor initiation, recurrence, and therapeutic resistance. However, CDK12 may also exert tumor-suppressive functions in a context-dependent manner. Therefore, caution is warranted when targeting CDK12 in future clinical trials. A comprehensive elucidation of the dual roles and underlying mechanisms of CDK12 in carcinogenesis is urgently needed to advance precision oncology. This review provides an overview of the current understanding of the dysregulation and biological roles of CDK12 in cancer. Subsequently, we systematically summarize the functions and mechanisms of the oncogenic and tumor-suppressive roles of CDK12 in different contexts. Finally, we discuss the potential of CDK12 as a novel therapeutic target and its implications in clinical oncology, offering insights into future directions for innovative cancer treatment strategies.

OBJECTIVE: To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease. METHODS: This prospective cohort study included 318,085 biobank participants from the UK. Physical activity was assessed using the short form of the International Physical Activity Questionnaire. The participants were stratified into low-, intermediate-, and high-genetic-risk groups based on their polygenic risk scores. Multivariate Cox regression models and multiplicative interaction analyses were used. RESULTS: During a median follow-up period of 13 years, 9,209 participants were diagnosed with chronic obstructive pulmonary disease. For low genetic risk, compared to low physical activity, the hazard ratios ( HRs) for moderate and high physical activity were 0.853 (95% confidence interval [ CI]: 0.748-0.972) and 0.831 (95% CI: 0.727-0.950), respectively. For intermediate genetic risk, the HRs were 0.829 (95% CI: 0.758-0.905) and 0.835 (95% CI: 0.764-0.914), respectively. For participants with high genetic risk, the HRs were 0.809 (95% CI: 0.746-0.877) and 0.818 (95% CI: 0.754-0.888), respectively. A significant interaction was observed between genetic risk and physical activity. CONCLUSION Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups, highlighting the need to tailor activity interventions for genetically susceptible individuals.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Exercise ; Male ; Female ; Middle Aged ; Prospective Studies ; Aged ; Genetic Predisposition to Disease ; Risk Factors ; United Kingdom/epidemiology* ; Incidence ; Adult