Objective To investigate the anti-intrahepatic cholangiocarcinoma （ICC） activity and mechanism of 2-heptyl-3-hydroxy-4（1H）-quinolone （PQS）, a secondary metabolite of polar marine microorganisms. Methods Patient-derived organoid （PDO） models were established using intrahepatic cholangiocarcinoma （ICC） tumor tissues obtained from Renji Hospital, Shanghai Jiao Tong University School of Medicine. Hematoxylin and eosin （HE） staining was performed to assess the histomorphological characteristics of both patient ICC tissues and corresponding PDOs. Immunohistochemistry （IHC） was employed to evaluate CYP3a expression in patient ICC tissues and PDOs. The antiproliferative activity of PQS against stably passaged PDOs was determined using an adenosine triphosphate （ATP）-based bioluminescence assay, and dose-response curves were fitted to calculate the half-maximal inhibitory concentration （IC₅₀） for assessing the anti-ICC efficacy of PQS. In the human intrahepatic cholangiocarcinoma RBE cell model, the effects of PQS on RBE cell proliferation were evaluated by the cell counting kit-8 （CCK-8） assay; colony formation capacity was assessed by the plate colony formation assay; cell cycle distribution and apoptosis were analyzed by flow cytometry; and the protein expression levels of cyclin-dependent kinase 2（CDK2）, CDK4, RelA（p65）, and nuclear factor-κB1（p50） were detected by Western blotting. Results Two ICC PDO models were successfully established. Histomorphological observation revealed that the PDO tissues after serial passaging exhibited morphological features essentially consistent with the corresponding patient ICC tissues, both presenting as cystic vesicle-like structures. Immunohistochemical analysis demonstrated that CYP3a was expressed in both PDO tissues and patient ICC tissues. ATP-based bioluminescence assay results indicated that PQS effectively suppressed ATP content in PDO tissues, with a fitted dose-response curve yielding an IC₅₀ value of 2.49 µmol/L. In the RBE cell model, PQS inhibited RBE cell viability in a concentration-dependent manner, and the fitted dose-response curve yielded an IC₅₀ value of 1.05 µmol/L. Furthermore, PQS at concentrations of 1, 2, and 4 µmol/L significantly suppressed colony formation of RBE cells, arrested the cell cycle at the S phase, induced apoptosis, and downregulated the expression of proteins associated with the NF-κB signaling pathway. Conclusion ICC PDO models were successfully established, confirming the anti-ICC activity of PQS. PQS inhibited RBE cell proliferation, potentially via the NF-κB signaling pathway, by arresting the cell cycle at the S phase and inducing apoptosis of RBE cells

Objective To investigate the anti-intrahepatic cholangiocarcinoma （ICC） activity and mechanism of 2-heptyl-3-hydroxy-4（1H）-quinolone （PQS）, a secondary metabolite of polar marine microorganisms. Methods Patient-derived organoid （PDO） models were established using intrahepatic cholangiocarcinoma （ICC） tumor tissues obtained from Renji Hospital, Shanghai Jiao Tong University School of Medicine. Hematoxylin and eosin （HE） staining was performed to assess the histomorphological characteristics of both patient ICC tissues and corresponding PDOs. Immunohistochemistry （IHC） was employed to evaluate CYP3a expression in patient ICC tissues and PDOs. The antiproliferative activity of PQS against stably passaged PDOs was determined using an adenosine triphosphate （ATP）-based bioluminescence assay, and dose-response curves were fitted to calculate the half-maximal inhibitory concentration （IC₅₀） for assessing the anti-ICC efficacy of PQS. In the human intrahepatic cholangiocarcinoma RBE cell model, the effects of PQS on RBE cell proliferation were evaluated by the cell counting kit-8 （CCK-8） assay; colony formation capacity was assessed by the plate colony formation assay; cell cycle distribution and apoptosis were analyzed by flow cytometry; and the protein expression levels of cyclin-dependent kinase 2（CDK2）, CDK4, RelA（p65）, and nuclear factor-κB1（p50） were detected by Western blotting. Results Two ICC PDO models were successfully established. Histomorphological observation revealed that the PDO tissues after serial passaging exhibited morphological features essentially consistent with the corresponding patient ICC tissues, both presenting as cystic vesicle-like structures. Immunohistochemical analysis demonstrated that CYP3a was expressed in both PDO tissues and patient ICC tissues. ATP-based bioluminescence assay results indicated that PQS effectively suppressed ATP content in PDO tissues, with a fitted dose-response curve yielding an IC₅₀ value of 2.49 µmol/L. In the RBE cell model, PQS inhibited RBE cell viability in a concentration-dependent manner, and the fitted dose-response curve yielded an IC₅₀ value of 1.05 µmol/L. Furthermore, PQS at concentrations of 1, 2, and 4 µmol/L significantly suppressed colony formation of RBE cells, arrested the cell cycle at the S phase, induced apoptosis, and downregulated the expression of proteins associated with the NF-κB signaling pathway. Conclusion ICC PDO models were successfully established, confirming the anti-ICC activity of PQS. PQS inhibited RBE cell proliferation, potentially via the NF-κB signaling pathway, by arresting the cell cycle at the S phase and inducing apoptosis of RBE cells

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

ObjectiveSpinal cord injury (SCI) directly impairs the regulatory function of the autonomic nervous system, induces intestinal dysfunction, and significantly reduces patients’ quality of life. Preclinical studies have shown that electroacupuncture (EA) therapy can regulate the brain-gut axis and is used to treat central nervous system diseases such as major depressive disorder, Alzheimer’s disease and Parkinson’s disease. Recent research has established that fecal microbiota transplantation (FMT) from EA-treated SCI rats restored intestinal motility and colonic morphology. However, it remains unclear whether the regulation of gut microbiota by EA therapy directly contributes to neural repair after SCI. This study aims to explore whether gut microbiota mediates the neuroprotective effect of EA in the treatment of SCI and its possible mechanism. MethodsThe study employed RNA transcriptome analysis of spinal cord tissue to characterize gene expression profiles and to identify key signaling pathways following EA treatment for SCI. Hematoxylin-Eosin (HE) staining and Nissl staining were used to observe the morphological changes in spinal cord tissue. Western blot (WB) and enzyme-linked immunosorbent assay (ELISA) were applied to detect the effects of EA on the expression of proteins related to nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) -dependent pyroptosis. Using 16S rDNA sequencing, the study observed alterations in gut microbiota diversity and community composition in SCI rats. Prior to establishing SCI models, rats were pretreated with an antibiotic cocktail to induce gut dysbiosis, and the effects on intestinal function and spinal cord neural repair were evaluated. FMT was performed to investigate the regulatory effects of post-EA FMT on motor function, general status, liver and spleen indices, and NLRP3-mediated pyroptosis in SCI rats. ResultsEA improved motor function and reduced regulated neuronal cell death in SCI rats. Transcriptomic analysis demonstrated the activation of immune- and inflammation-related pathways post-SCI, including NOD-like receptors, nuclear factor-kappa B(NF-κB), and Toll-like receptor (TLR) pathways. EA primarily influenced intestinal inflammation and autoimmune functions. 16S rDNA sequencing illustrated that EA did not alter the diversity of gut microbiota. However, EA altered the gut microbiota composition in SCI rats, increasing Lactobacillus and Akkermansia genera while rebalancing the Firmicutes/Bacteroidetes ratio. Furthermore, depletion of gut microbiota by antibiotics disrupted the intestinal barrier, reduced the expression of intestinal barrier proteins Zonula Occludens-1 (ZO-1) and Occludin, elevated serum lipopolysaccharide-binding protein (LBP) levels, exacerbated spinal cord tissue damage, and hindered motor function recovery in SCI rats. FMT from donors treated with EA reduced LBP levels in the intestine, blood, and spinal cord of rats, inhibited the TLR4 myeloid differentiation primary response protein 88 (MyD88)-NF‑κB pathway and NLRP3-dependent pyroptosis, and improved motor function. On the other hand, FMT treatment resulted in decreased body weight and food intake, whereas FMT using EA-treated donors effectively alleviated these alterations. ConclusionEA effectively alleviated neuroinflammatory responses in rats with SCI, primarily through regulating the gut microbiota and suppressing the NLRP3-dependent pyroptosis signaling pathway.

Background Diarrhea disease is a common intestinal infectious disease, and its incidence is affected by meteorological conditions. A better understanding of its epidemiological patterns and influencing factors, together with the construction of reliable prediction models, is of great significance for precise public health prevention and control. Objective To clarify the epidemic characteristics of adult diarrhea disease in Shanghai, analyze the associations of meteorological factors and a web search index with adult diarrhea disease, and develop and compare forecasting models to support precise regional prevention and control. Methods Weekly surveillance data of adult diarrhea disease cases from the Shanghai Comprehensive Surveillance Information System for Diarrhea Diseases, together with concurrent meteorological observation data and web search index (Baidu index) data from 2014 to 2019, were collected. A distributed lag non-linear model (DLNM) was adopted to analyze the associations of multiple meteorological factors and the web search index with the number of diarrhea disease cases. By integrating meteorological factors and web search index data, three types of forecasting models were developed, including autoregressive integrated moving average (ARIMA), Random Forest, and extreme gradient boosting (Xgboost), and their predictive performances were evaluated. Results Adult diarrhea disease in Shanghai exhibited seasonal variation, with an major incidence peak in summer and winter peaks in some years. The number of cases declined annually after 2015. Mean temperature was significantly associated with the risk of diarrhea disease, and both low and high temperature exposures were associated with increased risks. The highest risk was observed at 32.8°C (RR=2.04, 95%CI: 1.62, 2.55), while the strongest effect of low temperature was observed at 0.9 °C (RR=1.53, 95%CI: 1.25, 1.88). When relative humidity exceeded 69%, the risk of diarrhea disease increased with relative humidity, reaching a peak at 81% (RR=1.20, 95%CI: 1.07, 1.35). When weekly cumulative precipitation exceeded 16 mm, the risk also increased with increasing precipitation, reaching a maximum at 105 mm (RR=1.23, 95%CI: 1.07, 1.42). The web search index was positively associated with the risk of diarrhea disease. Model prediction indicated that both the Random Forest model and the Xgboost model adequately captured the overall trend in diarrhea disease cases, with R² values generally exceeding 0.7. Notably, the Xgboost model demonstrated greater accuracy in capturing peak intensities. Conclusion Meteorological factors are associated with adult diarrhea disease in Shanghai. The web search index may serve as an auxiliary indicator for diarrhea forecasting. Machine learning models, with advantages in integrating multisource data, may provide effective predictive tools for the prevention and control of diarrhea disease.

Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

Objective To establish an effective model for distinguishing glandular prodromal lesions(PGL)mixed with ground-glass nodules(mGGN)from minimally invasive adenocarcinoma(MIA)on CT based on artificial intelligence.Methods A retrospective analysis was conducted on the clinical and CT image data of 180 patients with lung adenocarcinoma confirmed by surgical pathology and with CT manifestations of mGGN in the First Affiliated Hospital of Wenzhou Medical University from January 2017 to June 2023,inclu-ding 66 patients with PGL and 114 patients with MIA.Patients were divided into the training set(n=144)and the test set(n=36)in an 8∶2 ratio using a completely random method.The quantitative parameters and radiomics features of the lesions in CT images were automatically extracted using artificial intelligence soft-ware(United Imaging Research Platform uRP).By incorporating the most obvious correlation features of omics through dimensionality reduction,five machine learning classifiers were established,including logistic regression(LR),support vector machine(SVM),Random forest(RF),Gaussian process(GP),and Decision Tree(DT).The classifier with the training set highest area under the curve(AUC)was selected as the best radiomics model,and output the result as radiomics score(Rad-score).The clinical information,CT morpho-logical characteristics and quantitative data of the two groups were included in the multivariate logistic regres-sion analysis to screen the independent influencing factors for effectively differentiating PGL and MIA,and a clinical model was established.Finally,a comprehensive prediction model was constructed based on Rad-score and clinical risk factors.The diagnostic performance of the three models was evaluated by using the AUC,sen-sitivity,specificity and accuracy of receiver operating characteristic(ROC)curve.Results Eleven radiomics features for distinguishing PGL from MIA were obtained through LASSO dimensionality reduction.Among the five machine learning classifiers,GP has the best diagnostic performance,with AUC of 0.865 in the train-ing set and 0.762 in the test set,respectively.Univariate and multivariate logistic regression analyses were used for clinical feature screening.The clinical model was constructed by using the average CT value,average long and short diameter,and solid partial long diameter of mGGN,and the AUCs of the training set and the test set were 0.870 and 0.794,respectively.The comprehensive prediction model demonstrated superior diag-nostic performance,with AUC,sensitivity,specificity,and accuracy in the training set being 0.948,81.1%,91.2%and 87.5%respectively,while 0.883,76.9%,91.3%and 86.1%respectively in the test set.Conclu-sion The comprehensive prediction model established based on the quantitative and omics feature analysis of pulmonary nodules by artificial intelligence can well distinguish mGGN mixed with PGL from MIA on CT,and can be used to guide clinical treatment decisions.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

ObjectiveTo reveal the mechanism of Zuogui Jiangtang Jieyu prescription against damage to hippocampal synaptic microenvironment via suppressing glutamate receptor 2 （GluR2）/Parkin signal-mediated mitophagy in rats with diabetes-related depression （DD）. MethodsEighty male SD rats underwent adaptive feeding for 5 days before the study. Ten rats were randomly assigned to the normal group. The model of DD rats was established with the rest by 2-week high-fat diet + streptozotocin （STZ） tail intravenous injection + 28 days of chronic unpredictable mild stress （CUMS） combined with isolation. The rats were randomly divided into a normal group， a model group， a GluR2 blocker group （5 μg·kg^-1）， a GluR2 agonist group （10 μg·kg^-1）， a metformin + fluoxetine group （0.18 g·kg^-1 metformin + 1.8 mg·kg^-1 fluoxetine）， and high- and low-dose Zuogui Jiangtang Jieyu prescription groups （20.52 and 10.26 g·kg^-1， respectively）. The rats in the GluR2 blocker group and the GluR2 agonist group were continuously injected with CNQX and Cl-HIBO in the dentate gyrus of the hippocampus once a week starting from stress modeling， respectively， while the metformin + fluoxetine group and the high- and low-dose Zuogui Jiangtang Jieyu prescription groups were continuously given intragastric administration for 28 d at the same time of stress modeling. Depression-like behavior was evaluated by open field and forced swimming experiments. The levels of serum insulin and adenosine triphosphate （ATP） in hippocampus were detected by biochemical analysis. The levels of 5-hydroxytryptamine （5-HT） and dopamine （DA） in hippocampus were detected by enzyme-linked immunosorbent assay （ELISA）. The autophagosomes of hippocampal neurons were observed by transmission electron microscopy. The morphology and structure of dendrites and spines of hippocampal neurons were evaluated by Golgi staining. Western blot detected the expression levels of GluR2 and Parkin proteins in hippocampus. The expression levels of GluR2， Parkin， regulating synaptic membrane exocytosis protein 3 （RIMS3）， and postsynaptic density protein 95 （PSD95） in the dentate gyrus of the hippocampus were detected by immunofluorescence. ResultsCompared with the normal group， the model group exhibited reduced total activity distance in the open field and increased immobility time in forced swimming （P<0.01）， lowered levels of serum insulin and ATP， 5-HT， and DA in hippocampus （P<0.01）， increased autophagosomes of hippocampal neurons， significantly damaged morphology and structure of dendrites and spines of hippocampal neurons， decreased expression levels of GluR2， RIMS3， and PSD95 in hippocampus， and an increased Parkin expression level （P<0.05， P<0.01）. Compared with the model group， the GluR2 blocker group and the GluR2 agonist group showed aggravation and alleviation of the above abnormal changes， respectively （P<0.05， P<0.01）. The above depression-like behavior was significantly improved in the high- and low-dose Zuogui Jiangtang Jieyu prescription groups to different degrees. Specifically， the two groups saw elevated levels of serum insulin and ATP， 5-HT， and DA in hippocampus （P<0.05， P<0.01）， restrained increase in autophagosomes and damage to morphology and structure of dendrites and spines of hippocampal neurons， up-regulated protein expression levels of GluR2， RIMS3， and PSD95， and down-regulated Parkin expression level （P<0.05， P<0.01）. ConclusionZuogui Jiangtong Jieyu prescription can ameliorate the mitophagy-mediated damage to hippocampal synaptic microenvironment in DD rats， the mechanism of which might be related to the regulation of GluR2/Parkin signaling pathway.

Pancreatic surgery remains one of the most challenging fields in general surgery due to its complex anatomy and high risk of complications.In recent years,the integration of digital intelligent technologies-such as three-dimensional(3D)reconstruction,fluorescence navigation,augmented/mixed reality(AR/MR),and artificial intelligence(AI)-has provided new strategies for achieving precision,safety,and intelligence in pancreatic surgery.This review summarizes the innovations and clinical applications of these technologies throughout the full perioperative process,including preoperative planning,intraoperative navigation,and postoperative monitoring.Preoperatively,the deep learning-based nnU-Net framework enables high-precision 3D reconstruction of peripancreatic vessels and pancreaticobiliary ducts for individualized surgical planning.Intraoperatively,multimodal image fusion combining indocyanine green fluorescence imaging with AR/MR navigation allows real-time visualization and spatial localization of key anatomical structures,enhancing surgical accuracy and safety.Postoperatively,AI-driven models integrated with wearable sensors and multimodal data support intelligent risk prediction and early intervention for complications.The systematic application of digital intelligence is reshaping the paradigm of pancreatic surgery,driving the transition from experience-based to data-driven and from surgeon-dependent to intelligent decision-making.With continuous algorithmic refinement and accumulation of clinical evidence,digital empowerment will further advance pancreatic surgery toward personalization,precision,and intelligence.