BACKGROUND: Oral squamous cell carcinoma (OSCC) is a prevalent type of cancer with a high mortality rate in its late stages. One of the major challenges in OSCC treatment is the resistance to epidermal growth factor receptor (EGFR) inhibitors. Therefore, it is imperative to elucidate the mechanism underlying drug resistance and develop appropriate precision therapy strategies to enhance clinical efficacy. METHODS: To evaluate the efficacy of the combination of the Ca 2+ /calmodulin-dependent protein kinase II (CAMK2) inhibitor KN93 and EGFR inhibitors, we performed in vitro and in vivo experiments using two FAT atypical cadherin 1 ( FAT1 )-deficient (SCC9 and SCC25) and two FAT1 wild-type (SCC47 and HN12) OSCC cell lines. We assessed the effects of EGFR inhibitors (afatinib or cetuximab), KN93, or their combination on the malignant phenotype of OSCC in vivo and in vitro . The alterations in protein expression levels of members of the EGFR signaling pathway and SRY-box transcription factor 2 (SOX2) were analyzed. Changes in the yes-associated protein 1 (YAP1) protein were characterized. Moreover, we analyzed mitochondrial dysfunction. Besides, the effects of combination therapy on mitochondrial dynamics were also evaluated. RESULTS: OSCC with FAT1 mutations exhibited resistance to EGFR inhibitors treatment. The combination of KN93 and EGFR inhibitors significantly inhibited the proliferation, survival, and migration of FAT1 -mutated OSCC cells and suppressed tumor growth in vivo . Mechanistically, combination therapy enhanced the therapeutic sensitivity of FAT1 -mutated OSCC cells to EGFR inhibitors by modulating the EGFR pathway and downregulated tumor stemness-related proteins. Furthermore, combination therapy induced reactive oxygen species (ROS)-mediated mitochondrial dysfunction and disrupted mitochondrial dynamics, ultimately resulting in tumor suppression. CONCLUSION Combination therapy with EGFR inhibitors and KN93 could be a novel precision therapeutic strategy and a potential clinical solution for EGFR-resistant OSCC patients with FAT1 mutations.
Humans ; ErbB Receptors/metabolism* ; Mouth Neoplasms/metabolism* ; Cell Line, Tumor ; Animals ; Drug Resistance, Neoplasm/genetics* ; Cadherins/metabolism* ; Carcinoma, Squamous Cell/metabolism* ; Mice ; Mutation/genetics* ; Mice, Nude ; Protein Kinase Inhibitors/therapeutic use* ; Cetuximab/pharmacology* ; Afatinib/therapeutic use* ; Cell Proliferation/drug effects* ; Signal Transduction/drug effects*

G protein-coupled receptors (GPCRs) are the largest family of membrane proteins in eukaryotes, with nearly 800 genes coding for these proteins. They are involved in many physiological processes, such as light perception, taste and smell, neurotransmitter, metabolism, endocrine and exocrine, cell growth and migration. Importantly, GPCRs and their ligands are the targets of approximately one third of all marketed drugs. GPCRs are traditionally known for their role in transmitting signals from the extracellular environment to the cell's interior via the plasma membrane. However, emerging evidence suggests that GPCRs are also localized on mitochondria, where they play critical roles in modulating mitochondrial functions. These mitochondrial GPCRs (mGPCRs) can influence processes such as mitochondrial respiration, apoptosis, and reactive oxygen species (ROS) production. By interacting with mitochondrial signaling pathways, mGPCRs contribute to the regulation of energy metabolism and cell survival. Their presence on mitochondria adds a new layer of complexity to the understanding of cellular signaling, highlighting the organelle's role as not just an energy powerhouse but also a crucial hub for signal transduction. This expanding understanding of mGPCR function on mitochondria opens new avenues for research, particularly in the context of diseases where mitochondrial dysfunction plays a key role. Abnormalities in the phase conductance pathway of GPCRs located on mitochondria are closely associated with the development of systemic diseases such as cardiovascular disease, diabetes, obesity and Alzheimer's disease. In this review, we examined the various types of GPCRs identified on mitochondrial membranes and analyzed the complex relationships between mGPCRs and the pathogenesis of various diseases. We aim to provide a clearer understanding of the emerging significance of mGPCRs in health and disease, and to underscore their potential as therapeutic targets in the treatment of these conditions.

OBJECTIVE: Peritoneal fibrosis (PF) is an adverse event that occurs during long-term peritoneal dialysis, significantly impairing treatment efficiency and adversely affecting patient outcomes. Astragaloside IV (AS-IV), a principal active component derived from Astragalus membranaceus (Fisch.) Bunge, has exhibited anti-inflammatory and antifibrotic effects in various settings. This study aims to investigate the potential therapeutic efficacy and mechanism of AS-IV in the treatment of PF. METHODS: The PF mouse model was established by intraperitoneal injection of 4.25% peritoneal dialysis fluid (100 mL/kg). The epithelial-mesenchymal transition (EMT) of HMrSV5 cells was induced by the addition of 10 ng/mL transforming growth factor β (TGF-β). The differentially expressed genes in HMrSV5 cells treated with AS-IV were screened using transcriptome sequencing analysis. The potential targets of AS-IV were screened using network pharmacology and analyzed using molecular docking and molecular dynamics simulations. RESULTS: Administration of AS-IV at doses of 20, 40, or 80 mg/kg effectively mitigated the increase in peritoneal thickness and the development of fibrosis in mice with PF. The expression of the fibrosis marker α-smooth muscle actin in the peritoneum was significantly decreased in AS-IV-treated mice. The treatment of AS-IV (10, 20, and 40 μmol/L) significantly delayed the EMT of HMrSV5 cells induced by TGF-β, as demonstrated by the decreased number of 5-ethynyl-2'-deoxyuridine-positive cells, reduced migrated area, and decreased expression of fibrosis markers. A total of 460 differentially expressed genes were detected in AS-IV-treated HMrSV5 cells through transcriptome sequencing, with notable enrichment in the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)-AKT serine/threonine kinase 1 (AKT) signaling pathway. The reduced levels of phosphorylated PI3K (p-PI3K) and p-AKT were detected in HMrSV5 cells with AS-IV treatment. Epidermal growth factor receptor (EGFR) was predicted as a direct target of AS-IV, exhibiting strong hydrogen bond interactions. The activation of the PI3K-AKT pathway by the compound 740Y-P, and the activation of the EGFR pathway by NSC 228155 each partially counteracted the inhibitory effect of AS-IV on the EMT of HMrSV5 cells. CONCLUSION AS-IV delayed the EMT process in peritoneal mesothelial cells and slowed the progression of PF, potentially serving as a therapeutic agent for the early prevention and treatment of PF. Please cite this article as: Huang Y, Chu CL, Qiu WH, Chen JY, Cao LX, Ji SY, Zhu B, Wang GK, Shen QQ. Astragaloside IV delayed the epithelial-mesenchymal transition in peritoneal fibrosis by inhibiting the activation of EGFR and PI3K-AKT pathways. J Integr Med. 2025; 23(6):694-705.
Epithelial-Mesenchymal Transition/drug effects* ; Animals ; Saponins/pharmacology* ; Triterpenes/pharmacology* ; Mice ; Peritoneal Fibrosis/pathology* ; Proto-Oncogene Proteins c-akt/metabolism* ; ErbB Receptors/metabolism* ; Phosphatidylinositol 3-Kinases/metabolism* ; Signal Transduction/drug effects* ; Male ; Humans ; Molecular Docking Simulation ; Cell Line ; Mice, Inbred C57BL

OBJECTIVE: The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks. METHODS: A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). RESULTS: During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43). CONCLUSION Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans ; China/epidemiology* ; Male ; Female ; Stroke/etiology* ; Middle Aged ; Prospective Studies ; Incidence ; Aged ; Animals ; Fishes ; Risk Factors ; Diet ; Seafood ; Adult ; Cohort Studies

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged

Objective:To investigate the differences of the glymphatic system (GS) function between patients with mesial temporal lobe epilepsy with hippocampal sclerosis (mTLE-HS) and healthy controls and between different seizure types by using diffusion tensor imaging along perivascular space (DTI-ALPS), and to analyze the correlation between GS function and the course of disease, as well as the efficacy of predicting the surgical outcome.Methods:This study was a cross-sectional study. A total of 171 patients with mTLE-HS (mTLE-HS group) and 75 healthy volunteers (HC group) were retrospectively enrolled from July 2009 to July 2021 at Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University. The general information of all subjects, such as seizure type (partial seizure, secondary generalized seizure), surgical outcome, etc., was analyzed. The 3D magnetization prepared rapid gradient echo T 1WI and DTI sequence images were collected. The VBM analysis method was used to segment cerebrospinal fluid and calculate the volume. The ALPS index of the bilateral brain was calculated using the Atlas-based DTI-ALPS method. Independent sample t-test or paired t test were used to compare the ALPS index between the mTLE-HS group and HC group, and between patients with different seizure types. Pearson correlation analysis was used to analyze the correlation between bilateral ALPS index and disease duration in mTLE-HS group. The predictive value of the ALPS index for surgical outcomes was evaluated by receiver operating characteristics curve and area under the curve. Results:Among the 171 mTLE-HS patients, 98 patients were mTLE with left-side HS (mTLE-LHS) and 73 patients were mTLE with right-side HS (mTLE-RHS); 37 patients underwent surgical treatment, including 27 with good prognosis and 10 with poor prognosis. Compared with the HC group, the left-side ALPS index of mTLE-LHS and mTLE-RHS were both decreased ( P<0.05). The right-side ALPS index in mTLE-RHS was lower than that in the HC group ( P<0.001). There was no significant difference in the right-side ALPS index between mTLE-LHS and HC group ( P=0.080). The ALPS index on the affected side of patients with secondary generalized seizures was significantly lower than that of patients with only partial seizures (all P<0.05), but the difference in ALPS index on the healthy side was not statistically significant( P>0.05). The left-side and right-side ALPS index in mTLE-LHS were negatively correlated with disease duration ( r=-0.272, P=0.007; r=-0.307, P=0.002), but no significant correlation was found between the left-side or right-side ALPS index in mTLE-RHS (all P>0.05). The DTI-ALPS index on the affected side in mTLE-HS patients exhibited good diagnostic accuracy for surgical outcome classification, with an area under the curve of 0.778. Conclusions:The patients with mTLE-HS exhibit dysfunction of the GS, and the degree of impairment is related to the type of seizure and the course of epilepsy. The ALPS index, which characterizes the function of GS, demonstrates good diagnostic accuracy for classifying surgical outcomes.

Objective To develop and validate a machine learning-based predictive model to assess the in-hospital mortality risk of patients with myocardial infarction(MI)complicated by heart failure(HF)undergoing percutaneous coronary intervention(PCI).Methods This retrospective study analyzed MI patients with HF who underwent PCI at The First Affiliated Hospital of Xinjiang Medical University from January 2019 to January 2023.Patient data,including demographic characteristics,vital signs,laboratory test results,imaging parameters and medication use,were collected and randomly divided into a training set(70％)and a validation set(30％).The extreme gradient boosting(XGBoost)model was used to identify variables significantly associated with in-hospital mortality,and the Shapley additive explanations(SHAP)model was applied to assess feature importance.A predictive model was then constructed using univariate and multivariate Logistic regression analyses.Model performance was evaluated using receiver operating characteristic(ROC)curves,area under the curve(AUC)values,calibration curves,and decision curve analysis.Finally,a nomogram was developed for intuitive risk assessment.Results A total of 1 214 MI patients with HF were included in the study,with a median age of 64 years.The in-hospital mortality rate was 7.41％(90 deaths).XGBoost feature selection identified ten key predictive variables:age,myoglobin,albumin,fasting blood glucose,N-terminal pro-B-type natriuretic peptide(NT-proBNP),diabetes mellitus,creatinine,cystatin C,procalcitonin,and left ventricular ejection fraction.Based on these variables,a Logistic regression model was developed,with seven final predictors:age,diabetes mellitus,creatinine,fasting blood glucose,cystatin C,NT-proBNP,and albumin.The model demonstrated high predictive accuracy,with AUC value of 0.869(95％CI:0.84-0.89)in the training set and 0.827(95％CI:0.79-0.85)in the validation set.The calibration curve indicated that the predicted probabilities were consistent with the actual observed outcomes,and decision curve analysis showed that the model had a high net benefit across various decision thresholds.Conclusion This study developed a machine learning-based predictive model incorporating Logistic regression to assess the in-hospital mortality risk of MI patients with HF undergoing PCI.The model demonstrated high predictive performance and clinical utility.The nomogram derived from this model provides an intuitive tool for individualized risk assessment,aiding clinicians in the early identification of high-risk patients,optimizing intervention strategies,and improving patient outcomes.

Objective To construct and validate machine learning-based models to predict the risk of acute kidney injury(AKI)following percutaneous coronary intervention(PCI)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 2 315 STEMI patients who underwent PCI between January 2020 and June 2023 were included;306(13.2％)of them developed AKI.Baseline variables were screened using LASSO regression,with the optimal λ value selected via 10-fold cross-validation to identify AKI-associated features.Subsequently,eight distinct machine learning models were constructed and evaluated for their predictive performance.SHAP value analysis was employed to assess the impact of key variables on model predictions.Results LASSO regression identified seven variables significantly associated with AKI,including age,multivessel disease,preoperative creatinine,heart failure,white blood cell count,hemoglobin,and albumin levels.Among all the models,the light gradient boosting machine(LGBM)and extreme gradient boosting(XGB)demonstrated the best predictive performance,with training set AUCs being 0.899(95％CI:0.877-0.921)and 0.893(95％CI:0.868-0.918),and validation set AUCs being 0.809(95％CI:0.763-0.856)and 0.871(95％CI:0.833-0.909),respectively.SHAP analysis revealed that albumin,age,preoperative creatinine,and white blood cell count were the primary contributors to AKI risk.Conclusion This study successfully developed and validated machine learning-based predictive models capable of effectively identifying the risk of AKI following PCI in STEMI patients,thus providing valuable support for clinical decision-making.