Introduction: Hypertension is common in obesity and increases cardiovascular risk. Bariatric surgery improves metabolic health, but subgroup differences in blood pressure response remain unclear. This study examined 1-year changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP) after bariatric surgery across sex, age group, and diabetes status. Methodology: This study included 32 obese adults undergoing bariatric surgery, with blood pressure measured at baseline, 6 and 12 months. Generalized estimating equation models were used to evaluate changes in SBP and DBP over time, adjusting for age, sex, surgery type, diabetes category, baseline body mass index, antihypertensive medication use, and baseline blood pressure. Interaction terms were tested to assess differences in blood pressure trajectories across subgroups. Results: Participants were predominantly female (67.4%), with a mean age of 36.9 ± 6.2 years and a mean body mass index of 40.7 ± 8.8 kg/m². Hypertension and diabetes were present in 40.6 and 31.3% of participants, respectively. There was a significant time effect for both SBP (p <0.001) and DBP (p = 0.004). At 12 months post-surgery, mean SBP decreased by 15 mmHg and DBP by 7.9 mmHg compared with baseline (both p <0.001). No significant interactions were observed between time and sex, diabetes category, or age category, indicating that blood pressure improvements were comparable across subgroups. Conclusion Bariatric surgery was associated with clinically meaningful reductions in both SBP and DBP, with similar improvement patterns observed across demographic and metabolic subgroups. These findings support the effectiveness of bariatric surgery as a strategy for blood pressure reduction and cardiovascular risk management in patients with obesity.
Blood Pressure ; Bariatric Surgery

Objective To explore the recognition capabilities of electronic nose combined with machine learning in identifying the breath odor map of benign and malignant pulmonary nodules and Traditional Chinese Medicine (TCM) syndrome elements. Methods The study design was a single-center observational study. General data and four diagnostic information were collected from 108 patients with pulmonary nodules admitted to the Department of Cardiothoracic Surgery of Hospital of Chengdu University of TCM from April 2023 to March 2024. The patients' TCM disease location and nature distribution characteristics were analyzed using the syndrome differentiation method. The Cyranose 320 electronic nose was used to collect the odor profiles of oral exhalation, and five machine learning algorithms including random forest (RF), K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and eXtreme gradient boosting (XGBoost) were employed to identify the exhaled breath profiles of benign and malignant pulmonary nodules and different TCM syndromes. Results (1) The common disease locations in pulmonary nodules were ranked in descending order as liver, lung, and kidney; the common disease natures were ranked in descending order as Yin deficiency, phlegm, dampness, Qi stagnation, and blood deficiency. (2) The electronic nose combined with the RF algorithm had the best efficacy in identifying the exhaled breath profiles of benign and malignant pulmonary nodules, with an AUC of 0.91, accuracy of 86.36%, specificity of 75.00%, and sensitivity of 92.85%. (3) The electronic nose combined with RF, LR, or XGBoost algorithms could effectively identify the different TCM disease locations and natures of pulmonary nodules, with classification accuracy, specificity, and sensitivity generally exceeding 80.00%.Conclusion Electronic nose combined with machine learning not only has the potential capabilities to differentiate the benign and malignant pulmonary nodules, but also provides new technologies and methods for the objective diagnosis of TCM syndromes in pulmonary nodules.

In recent years,cancer incidence has been rising.Chemotherapy is a key clinical treatment,yet long-term use of antitumor drugs can lead to multidrug resistance(MDR).This review introduces the causes and mechanisms of MDR,mainly including genomic mutations,cellular autophagy,tumor micro-environment,and apoptosis.Subsequently,the concept and mo-lecular mechanisms of Cuproptosis are introduced,pointing out that the abnormal accumulation of Cu2+in cells and the chain reaction triggered by the binding of excess Cu2+with mitochon-drial enzymes ultimately lead to cell death.Finally,copper ionophores,copper complexes as drugs,and strategies for indu-cing cuproptosis to reverse drug resistance are introduced.The prospects for exploring antitumor drugs that can reverse MDR are briefly discussed,bringing new ideas to overcoming tumor resist-ance.

Premature ovarian insufficiency(POI),also known as premature ovarian failure(POF),is one of the major causes of female infertility.Its incidence has been increasing year by year,seriously af-fecting women's reproductive health and becoming an increasingly serious public health problem world-wide.The pathogenesis of POI is complex and may be related to genetic,immune and environmental fac-tors,but in recent years,oxidative stress(OS)has received widespread attention as a key factor that can affect the function of ovarian granulosa cells(GCs),which can lead to the occurrence of POI.Reactive oxygen species(ROS)regulate the proliferation,survival and apoptosis of GCs through multiple signaling pathways,such as PI3K-Akt,MAPK,TGF-β/Smad,Notch,etc.AMPK and mitochondrial autophagy play important roles in attenuating the ROS damage and protecting the ovarian function.Excessive ROS disrupts the autophagy and lysosomal functions,leading to the accumulation of intracellular waste prod-ucts,thus affecting the physiological function and endocrine stability of GCs.In addition,OS can in-crease the risk of POI by affecting hormone synthesis and disrupting the function of GCs,leading to an imbalance in estrogen and progesterone levels.Herein we review the mechanism of OS in POI,explore how OS affects ovarian decline through the regulation of signaling pathways and cellular functions,and provide a theoretical basis for the clinical treatment of POI,which in turn provides new research ideas for its early diagnosis and prevention.

In recent years,cancer incidence has been rising.Chemotherapy is a key clinical treatment,yet long-term use of antitumor drugs can lead to multidrug resistance(MDR).This review introduces the causes and mechanisms of MDR,mainly including genomic mutations,cellular autophagy,tumor micro-environment,and apoptosis.Subsequently,the concept and mo-lecular mechanisms of Cuproptosis are introduced,pointing out that the abnormal accumulation of Cu2+in cells and the chain reaction triggered by the binding of excess Cu2+with mitochon-drial enzymes ultimately lead to cell death.Finally,copper ionophores,copper complexes as drugs,and strategies for indu-cing cuproptosis to reverse drug resistance are introduced.The prospects for exploring antitumor drugs that can reverse MDR are briefly discussed,bringing new ideas to overcoming tumor resist-ance.

Premature ovarian insufficiency(POI),also known as premature ovarian failure(POF),is one of the major causes of female infertility.Its incidence has been increasing year by year,seriously af-fecting women's reproductive health and becoming an increasingly serious public health problem world-wide.The pathogenesis of POI is complex and may be related to genetic,immune and environmental fac-tors,but in recent years,oxidative stress(OS)has received widespread attention as a key factor that can affect the function of ovarian granulosa cells(GCs),which can lead to the occurrence of POI.Reactive oxygen species(ROS)regulate the proliferation,survival and apoptosis of GCs through multiple signaling pathways,such as PI3K-Akt,MAPK,TGF-β/Smad,Notch,etc.AMPK and mitochondrial autophagy play important roles in attenuating the ROS damage and protecting the ovarian function.Excessive ROS disrupts the autophagy and lysosomal functions,leading to the accumulation of intracellular waste prod-ucts,thus affecting the physiological function and endocrine stability of GCs.In addition,OS can in-crease the risk of POI by affecting hormone synthesis and disrupting the function of GCs,leading to an imbalance in estrogen and progesterone levels.Herein we review the mechanism of OS in POI,explore how OS affects ovarian decline through the regulation of signaling pathways and cellular functions,and provide a theoretical basis for the clinical treatment of POI,which in turn provides new research ideas for its early diagnosis and prevention.

ObjectiveTo investigate the effects of jujuboside A （JuA） on the learning and memory abilities and histopathological changes in the rat model of vascular cognitive impairment （VCI） and explore the potential mechanisms by which JuA treats VCI. MethodsA total of 50 male SPF-grade SD rats were randomized into a sham operation group （n=10）， a blank control group （n=10）， and a modeling group （n=30）. The rats in the modeling group underwent bilateral carotid artery ligation （2-VO） for the modeling of VCI. After stabilization， the VCI rats were randomized into model， JuA （20 mg·kg^-¹）， and donepezil （0.45 mg·kg^-¹） groups. After 4 weeks of gavage， the novel object recognition and Morris water maze tests were conducted to evaluate the learning and memory abilities of rats. Nissl staining was employed to evaluate the morphology and number of hippocampal neurons. Real-time PCR was employed to measure the mRNA levels of glycogen synthase kinase-3β （GSK-3β）， cAMP response element-binding protein （CREB）， B cell lymphoma-2 （Bcl-2）， phosphatidylinositol 3-kinase （PI3K）， and protein kinase B （Akt） in the hippocampal tissue. Western blot was employed to quantify the protein levels of GSK-3β， p-GSK-3β， p-CREB， Bcl-2， PI3K， p-PI3K， Akt， and p-Akt in the hippocampal tissue. ResultCompared with the sham operation group， the model group exhibited declines in the learning and memory abilities （P<0.01）， neuronal damage and decreased neurons in the hippocampal CA1 region （P<0.01）， up-regulation in the mRNA level of GSK-3β （P<0.01）， and down-regulation in the mRNA levels of PI3K， Akt， CREB， and Bcl-2， as well as the protein levels of p-PI3K， p-Akt， p-GSK-3β， p-CREB， and Bcl-2 （P<0.01）. In comparison to the model group， both the JuA and donepezil groups demonstrated improvements in the learning and memory abilities （P<0.05， P<0.01）， with reduced neuronal damage and increased neurons （P<0.05， P<0.01）. In addition， the two groups showed down-regulation in the mRNA level of GSK-3β （P<0.01） and up-regulation in the mRNA levels of PI3K， Akt， CREB， and Bcl-2 and the protein levels of p-PI3K， p-Akt， p-GSK-3β， p-CREB， and Bcl-2 （P<0.05， P<0.01）. There were no statistically significant differences between the blank control and sham operation groups in terms of the learning and memory abilities， neuron count， and mRNA and protein levels of PI3K/Akt/GSK-3β pathway-related factors. ConclusionJuA can ameliorate the cognitive impairment in the rat model of VCI by activating the PI3K/Akt signaling pathway， reducing the apoptosis of hippocampal neurons， and alleviating the hippocampal neuronal damage.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

Objective To explore the risk signals of niraparib and provide references for rational and safe clinical medication.Methods Niraparib-related adverse drug events(ADEs)reports from Q1 2017 to Q2 2023 were extracted from the US FDA Adverse Event Reporting System(FAERS)database.Risk signals were identified using the reporting odds ratio(ROR),proportional reporting ratio(PRR),Bayesian confidence propagation neural network(BCPNN),and multi-item gamma Poisson shrinker(MGPS)methods.The Risk signals were described and classified by preferred system organ classes(SOCs)and preferred terms(PTs)from the Medical Dictionary for Regulatory Activities(MedDRA)version 26.1,and the occurrence of niraparib-related ADEs was also analyzed.Results A total of 16,961 ADE reports with niraparib as the primary suspected drug were extracted.Through screening and analysis,32 PTs were identified involving 11 SOCs,which were largely consistent with the information in the drug label.However,suspicious signals not mentioned in the label,including neuropathy peripheral,decreased red blood cell count,reduced hematocrit,dehydration,and hot flashes,require further attention.The median occurrence time was 22 days(IQR 2-98 days),and the Weibull distribution test indicated an early failure-type curve.Conclusion When using niraparib,particularly in early stages of treatment,it is essential to monitor not only the ADEs mentioned in the drug instructions,such as decreased platelet count,nausea and fatigue,but also to pay close attention to the ADEs not included in the instructions,such as peripheral neuropathy and decreased red blood cell count,which exhibit strong signal values,to ensure patient medication safety.

Objective To investigate the perioperative outcomes and postoperative pregnancy outcomes of patients with intrauterine adhesions(IUA)treated by see-and-treat hysteroscopy and traditional hysteroscopy in transcervical resection of adhesions(TCRA).Methods A retrospective cohort study was performed on 485 patients with moderate-to-severe IUA who met the inclusion criteria and admitted in our hospital from January 2019 to December 2021.According to surgical approaches,the patients were assigned into a see-and-treat mode group and a traditional mode group.After clinical diagnosis(ultrasound and symptoms)of IUA,the patients from the former group received direct hysteroscopic adhesion separation surgery,and those of the latter group were diagnosed by outpatient hysteroscopy first and then hysteroscopic adhesion separation surgery.The perioperative indicators,postoperative three-dimensional transvaginal ultrasound(3D-TVUS)examination related characteristics,postoperative menstrual recovery,postoperative pregnancy outcomes,obstetric related complications,and neonatal outcomes were collected and compared between the 2 groups.Results Among the enrolled 485 patients,there were 277 in the see-and-treat group and 208 in the traditional group.The success rate of surgical treatment was 89.89%in the see-and-treat group and 92.79%in the traditional group,but no statistical difference was seen between them(Chi-square=1.234,P=0.267).3D-TVUS examination displayed that the see-and-treat mode group obtained better improvement of endometrial morphology,uterine morphology and menstruation after operation than the traditional group(P<0.001).The postoperative pregnancy rate was slightly higher in the see-and-treat group than the traditional mode group(58.84%vs 58.17%,P=0.882).However,the see-and-treat mode showed obvious advantage in the postoperative natural pregnancy rate,with a rate of 90.80%,obviously higher than that in the traditional mode group(81.82%,P=0.026).The live birth rate was 70.55%in the see-and-treat mode group,excluding 1 case with ongoing pregnancy in the second trimester and 1 case with ongoing pregnancy in the third trimester,and the rate was 74.38%in the traditional group,excluding 3 cases with ongoing pregnancy in the third trimester,but there was no statistical difference between the 2 groups(P=0.303).In terms of obstetric-related complications,there were 0 cases of blood transfusion during delivery hospitalization in the see-and-treat group,while there were 7 cases in the traditional group(P=0.003).In neonatal outcomes,the rate of transfer to the pediatric department was 10.43%in the see-and-treat mode group and 22.22%in the traditional mode group(P=0.021).For health economics,the see-and-treat hysteroscopy group demonstrated a significant advantage over the traditional hysteroscopy group(P<0.001).There was no significant difference in pain scores between the 2 groups.Conclusion The see-and-treat approach is a safe,feasible,and highly efficient strategy for integrating the diagnosis and treatment of IUA,enabling maximal minimization of surgical trauma while optimizing time and cost efficiency.