Objective To explore the feasibility of using high-definition thoracoscopy to identify sympathetic ganglia during thoracic sympathicotomy for primary palmar hyperhidrosis. Methods The clinical data of patients with primary palmar hyperhidrosis who underwent high-definition thoracoscopic sympathicotomy in Taikang Xianlin Drum Tower Hospital from June to July 2023 were retrospectively analyzed. Intraoperative visualization rates and anatomical variations of sympathetic ganglia were recorded, and the consistency between white-light thoracoscopy and near-infrared fluorescence imaging was compared. Additionally, surgical videos from previous fluorescence-guided procedures were reviewed. Results Finally 100 patients were collected, including 54 females and 46 males, with an average age of (21.92±6.56) years. All patients underwent endoscopic thoracic sympathicotomy at R3 level. The overall intraoperative ganglion visualization rate was 92.5% (740/800), with G2-G5 rates of 95.5% (191/200), 94.0% (188/200), 94.0% (188/200), and 86.5% (173/200), respectively. Ganglion variations occurred in 32.0% (237/740), predominantly at G3 (29.8%) and G4 (42.6%). In 5 indocyanine green-enhanced patients, the concordance rate between white-light and near-infrared fluorescence imaging was 100.0% (38/38). Video analysis of 14 near-infrared fluorescence-guided surgeries demonstrated a 99.1% (107/108) consistency rate. Postoperative palmar hyperhidrosis improvement reached 100.0% (100/100) with no Horner’s syndrome. Conclusion With the wide clinical application of high-definition thoracoscopy, accurate thoracic sympathicotomy has the feasibility of clinical application.

BACKGROUND:Curcumin is the main active ingredient of turmeric and has significant medicinal value in anti-tumor,anti-inflammatory,antioxidant and other aspects.However,its poor water solubility,unstable chemical properties and easy decomposition lead to difficulty in extracting curcumin and low extraction yield.Therefore,it is particularly important to optimize the curcumin extraction method.OBJECTIVE:To enhance the extraction yield and utilization value of curcumin and optimize the curcumin extraction process and curcumin nanoparticle preparation process.METHODS:Curcumin was extracted from turmeric by ethanol extraction,ultrasonic extraction,ionic liquid extraction,enzyme extraction,and ionic liquid combined with ultrasonic assisted enzyme extraction.The curcumin extraction yield was detected by high performance liquid chromatography;the best extraction method was determined,and subsequent process optimization experiments were carried out.The curcumin extraction yield was the response value with the type of ionic liquid,reaction temperature,ultrasonic time,liquid-to-solid ratio,ionic liquid concentration,and enzyme-drug mass ratio as parameters.The optimal production process of ionic liquid combined with ultrasonic assisted enzyme extraction was determined by single factor combined response surface experiment.The optimal process for preparing curcumin nanoparticles by ionic crosslinking method was determined by single factor combined response surface experiment with acetic acid concentration,chitosan to sodium tripolyphosphate mass ratio,stirring rate,curcumin mass concentration,sodium tripolyphosphate mass concentration,and chitosan mass concentration as parameters,and drug encapsulation efficiency as response value.Curcumin nanoparticles were prepared under the optimal process,and the particle size,polydispersity index,Zata potential value,drug loading,stability,hemolysis rate,and antioxidant capacity in vivo and in vitro of the nanoparticles were detected.RESULTS AND CONCLUSION:(1)Among the five extraction methods,the curcumin yield of ionic liquid combined with ultrasound-assisted enzyme extraction was the highest,and this method was selected as the curcumin extraction method for subsequent experiments.The results of single factor combined response surface experiment showed that the optimal process for curcumin extraction was:ionic liquid selected 1-hexyl-3-methylimidazolium chloride,reaction temperature 55 ℃,liquid-to-solid ratio 40 mL/g,ultrasound time 57 minutes,ionic liquid concentration 57％,enzyme-drug mass ratio 3.5:10,and the obtained turmeric extraction yield was 3.10％.The optimal preparation process of curcumin nanoparticles was:glacial acetic acid concentration 0.5％,chitosan and sodium tripolyphosphate mass ratio 5.0:1,stirring speed 150 r/min,curcumin mass concentration 2.23 mg/mL,sodium tripolyphosphate mass concentration 1.45 mg/mL,chitosan mass concentration 3.63 mg/mL,and the obtained drug encapsulation efficiency was 90.61％.(2)The drug loading of curcumin nanoparticles was(14.49±0.23)％,the average particle size was(76.95±1.65)nm,the polydispersity coefficient was 0.15±0.02,and the Zata potential value was(32.37±1.46)mV.The curcumin nanoparticles had good stability and blood compatibility,did not induce hemolysis,and had stronger antioxidant capacity in vivo and in vitro than free curcumin.(3)The results show that the process optimization not only solves the problems of low extraction yield,poor solubility,and low bioavailability of curcumin,but also enhances its antioxidant activity in vivo and in vitro.

BACKGROUND:Curcumin is the main active ingredient of turmeric and has significant medicinal value in anti-tumor,anti-inflammatory,antioxidant and other aspects.However,its poor water solubility,unstable chemical properties and easy decomposition lead to difficulty in extracting curcumin and low extraction yield.Therefore,it is particularly important to optimize the curcumin extraction method.OBJECTIVE:To enhance the extraction yield and utilization value of curcumin and optimize the curcumin extraction process and curcumin nanoparticle preparation process.METHODS:Curcumin was extracted from turmeric by ethanol extraction,ultrasonic extraction,ionic liquid extraction,enzyme extraction,and ionic liquid combined with ultrasonic assisted enzyme extraction.The curcumin extraction yield was detected by high performance liquid chromatography;the best extraction method was determined,and subsequent process optimization experiments were carried out.The curcumin extraction yield was the response value with the type of ionic liquid,reaction temperature,ultrasonic time,liquid-to-solid ratio,ionic liquid concentration,and enzyme-drug mass ratio as parameters.The optimal production process of ionic liquid combined with ultrasonic assisted enzyme extraction was determined by single factor combined response surface experiment.The optimal process for preparing curcumin nanoparticles by ionic crosslinking method was determined by single factor combined response surface experiment with acetic acid concentration,chitosan to sodium tripolyphosphate mass ratio,stirring rate,curcumin mass concentration,sodium tripolyphosphate mass concentration,and chitosan mass concentration as parameters,and drug encapsulation efficiency as response value.Curcumin nanoparticles were prepared under the optimal process,and the particle size,polydispersity index,Zata potential value,drug loading,stability,hemolysis rate,and antioxidant capacity in vivo and in vitro of the nanoparticles were detected.RESULTS AND CONCLUSION:(1)Among the five extraction methods,the curcumin yield of ionic liquid combined with ultrasound-assisted enzyme extraction was the highest,and this method was selected as the curcumin extraction method for subsequent experiments.The results of single factor combined response surface experiment showed that the optimal process for curcumin extraction was:ionic liquid selected 1-hexyl-3-methylimidazolium chloride,reaction temperature 55 ℃,liquid-to-solid ratio 40 mL/g,ultrasound time 57 minutes,ionic liquid concentration 57％,enzyme-drug mass ratio 3.5:10,and the obtained turmeric extraction yield was 3.10％.The optimal preparation process of curcumin nanoparticles was:glacial acetic acid concentration 0.5％,chitosan and sodium tripolyphosphate mass ratio 5.0:1,stirring speed 150 r/min,curcumin mass concentration 2.23 mg/mL,sodium tripolyphosphate mass concentration 1.45 mg/mL,chitosan mass concentration 3.63 mg/mL,and the obtained drug encapsulation efficiency was 90.61％.(2)The drug loading of curcumin nanoparticles was(14.49±0.23)％,the average particle size was(76.95±1.65)nm,the polydispersity coefficient was 0.15±0.02,and the Zata potential value was(32.37±1.46)mV.The curcumin nanoparticles had good stability and blood compatibility,did not induce hemolysis,and had stronger antioxidant capacity in vivo and in vitro than free curcumin.(3)The results show that the process optimization not only solves the problems of low extraction yield,poor solubility,and low bioavailability of curcumin,but also enhances its antioxidant activity in vivo and in vitro.

Zhishi Shaoyaosan is the 34^th prescription in the Catalogue of Ancient Classic Formulas （Second Batch） published by the National Administration of Traditional Chinese Medicine in 2023. It is widely used in clinical practice and has a definite curative effect. However， there is currently a lack of its ancient literature analysis and textual research， and there is no corresponding Chinese patent medicine preparation. By consulting and combing the relevant ancient books of traditional Chinese medicine， this paper analyzes and conducts textual research of the origin， composition， measurement， administration， and efficacy of Zhishi Shaoyaosan. The results show that Zhishi Shaoyaosan is derived from Essentials from the Golden Cabinet written by Zhang Zhongjing in the Eastern Han Dynasty. It is mainly recorded in the name of Zhishi Shaoyaosan in the literature of the past dynasties. The prescription is composed of Aurantii Fructus Immaturus and Paeoniae Radix Alba. The processing method is stir-frying Aurantii Fructus Immaturus to scorch and using raw Paeoniae Radix Alba. The dose of the prescription recorded in the ancient books is mainly an equal amount of Aurantii Fructus Immaturus and Paeoniae Radix Alba in one square-cun spoon， taken three times a day， which is converted into a modern dose of 1.5 g each time （0.75 g Aurantii Fructus Immaturus and 0.75 g Paeoniae Radix Alba each time）. The components of the prescription are ground into powder and taken with barley porridge， three times a day. The efficacy is to break stagnated Qi， harmonize blood， and relieve restlessness and pain. It is mainly used to treat postpartum abdominal pain， acute pelvic inflammatory disease， acute cholecystitis and intestinal diseases， stroke sequelae， and other diseases. This study combs and analyzes the ancient literature recording Zhishi Shaoyaosan and clarifies the key information of the prescription， which provides a basis for promoting the research and development of its patent medicine.

ObjectiveTo investigate the role of paraventricular nucleus (PVN) corticotropin releasing hormone (CRH) neurons in chronic restraint stress (CRS)-induced anxiety-like behavior. And whether exercise relieves chronic restraint stress-induced anxiety through PVN CRH neurons. MethodsTwenty 8-week-old male C57BL/6J mice were randomly divided into control (Ctrl) group and chronic restraint stress (CRS) group. The open field test (OFT) and elevated plus maze (EPM) were used to evaluate anxiety-like behavior of the mice. Food intake was recorded after CRS. Immunofluorescence staining was used to label the expression of c-Fos expression in PVN and calculate the co-expression of c-Fos and CRH neurons. We used chemogenetic activation of PVN CRH neurons to observed the anxiety-like behavior. 8-week treadmill training (10-16 m/min, 60 min/d, 6 d/week) were used to explore the role of exercise in ameliorating CRS-induced anxiety behavior and how PVN CRH neurons involved in it. ResultsCompared with Ctrl group, CRS group exhibited significant anxiety-like behavior. In OFT, the mice in CRS groups spent less time in center area (P<0.001). In EPM, the time in open arm in CRS group were significantly decreased (P<0.001). Besides, food intake was also suppressed in CRS group compared with Ctrl group (P<0.05). Compared with Ctrl group, CRS significantly increase c-Fos expression in PVN and most of CRH neurons co-express c-Fos (P<0.001). Chemogenetic activation of PVN CRH neurons induced anxiety-like behavior (P<0.05) and inhibited feeding behavior (P<0.01). Exercise relieves chronic restraint stress-induced anxiety (P<0.001) and relieved the anorexia caused by chronic restraint stress (P<0.05). Aerobic exercise inhibited the CRS labeled c-Fos in PVN CRH neurons (P<0.001). Furthermore, ablation of PVN CRH neurons attenuated CRS induced anxiety-like behavior. ConclusionCRS activated PVN CRH neurons, induced anxiety-like behavior and reduced food intake. 8-week exercise attenuated CRS-induced anxiety-like behavior through inhibiting PVN CRH neuron. Ablation of CRH PVN neurons ameliorated CRS-induced anxiety-like behavior. These finding reveals a potential neural mechanism of exercise-relieving CRS-induced anxiety-like behavior. This provides a new idea and theoretical basis for the treatment of anxiety and related mental disorders.

Objective To identify and cluster non-O1/O139 Vibrio cholerae(NOVC)using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry(MALDI-TOF MS),and evaluate the feasibility of MALDI-TOF MS as a method for the identification and clustering of NOVC.Methods The NOVC was identified by the MALDI-TOF MS equipped with V5 database,V12 database,highly pathogenic bacteria database,and V5 database combined with self-built spectrum projection and analyzed by the principal com-ponent analysis(PCA)and main spectrum projection(MSP)clustering.Results The NOVC was incorrectly identified as Vibrio al-bensis by the MALDI-TOF MS equipped with V5 database or V12 database,while the MALDI-TOF MS equipped with highly pathogenic bacteria database or V5 database combined with self-built spectrum projection could correctly identify NOVC.The PCA clustering of MALDI-TOF MS could distinguish NOVC from other bacterial strains and refine the differentiation of NOVC species to show the dis-tance relationship between NOVC species.Some spectrum projections of NOVC were extremely similar to the reference strains used to establish the database,and MSP clustering could not distinguish the differences between NOVC species.Conclusion The identifica-tion ability of MALDI-TOF MS for NOVC is limited by its database.The MALDI-TOF MS equipped with highly pathogenic bacteria da-tabase or V5 database combined with the self-built spectrum projection can accurately identify NOVC.The PCA clustering of MALDI-TOF MS has certain reference significance for the intra-and inter-species identification and homology analysis of NOVC.

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.

OBJECTIVE To analyze the biological characteristics and genomic features of highly lytic bacteriopha-ges isolated from sewage in tropical hospitals and provide references for the hospital-associated infection prevention and control of multidrug-resistant Acinetobacter baumannii(MDR-Ab).METHODS With MDR-Ab as the host bacterium,bacteriophages were isolated from sewage.Transmission electron microscopy was employed to observe their morphology,and determine the optimal multiplicity of infection(MOI),one-step growth curve and environ-mental stability.Whole-genome sequencing and bioinformatics analysis were conducted to annotate functional genes and construct a phylogenetic tree.RESULTS A virulent bacteriophage,HN_Aba_01,was isolated.Elec-tron microscopy revealed that it belonged to the Myoviridae family,with a head diameter of 50 nm and a tail length of 90 nm.This bacteriophage exhibited strong lytic activity,with an optimal MOI of 0.000 000 1,a latent period of 5 minutes and a lysis yield of 15 PFU/cell.It remained stable at temperatures ranging from 4 ℃ to 60 ℃and pH values from 3 to 10.Genomic analysis identified 85 ORFs,including lyase,perforin and depolymerase genes.It shared 98.12％identity with the bacteriophage AbP2 genome(reference genome)and was classified into the Obolenskvirus genus.CONCLUSIONS The bacteriophage isolated from tropical hospital sewage,with high lyt-ic activity and good environmental adaptability,can be used for the hospital-associated infection prevention and control of MDR-Ab.

Objective:To apply artificial intelligence（AI）in classifying ovarian tumors on ultrasound images，and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures，i.e.，Alexnet，Densenet121，and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors，while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently，the benign and malignant results of the model's predictions were disclosed to each sonographer，and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941，sensitivity of 0.936，and specificity of 0.944 on the internal test dataset，and maintained robust performance on the external test dataset with accuracy of 0.891，sensitivity of 0.880，and specificity of 0.907. Compared to junior sonographers，the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors（0.880 vs. 0.723，0.602；all P<0.05）. No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1（ P=0.05）. With assistance from the optimal model，junior sonographers achieved significant improvements in both sensitivity and specificity（sensitivity：0.723 vs. 0.843，0.602 vs. 0.819；specificity：0.778 vs. 0.833，0.685 vs. 0.741；all P<0.05）. Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance，the diagnostic performance of junior sonographers is significantly improved.

AIM To investigate the effects of Huazhuo Jiedu Shugan Formula(HJSGF)on improving learning and memory impairment in a rat model of vascular dementia(VD)via SIRT1/PGC-1α/PPARγ pathway.METHODS The SD rats were randomly divided into the sham control group,the model group,the donepezil group(0.5 mg/kg),and the low-,medium-and high-dose HJSGF groups(2.7,5.4,10.8 g/kg),with 10 rats in each group.The VD rat models established by bilateral common carotid artery permanent ligation(2-VO)had their neurological behavior assessment using the Longa5-point scale,and their modeling success confirmed by the Morris water maze test and their 3-week corresponding dosing of drugs by gavage afterward.After the drug administration,the rats had their spatial memory ability tested through behavioral experiments;their serum levels of IL-18 and IL-1β measured by ELISA;their histopathological changes and neuronal morphology in the hippocampal CA1 region observed by HE staining and Nissl staining;and their hippocampal protein expressions of SIRT1,PGC-1α and PPARγ detected by immunohistochemistry and Western blot.RESULTS Compared with the sham control group,the model group showed prolonged escape latency(P＜0.01);decreased platform crossing times and target quadrant residence time(P＜0.01);disorganized arrangement of hippocampal CA1 neurons,nuclear condensation,reduced Nissl bodies,increased secretion and protein expressions of IL-1β and IL-18(P＜0.01);and reduced hippocampal protein expressions of SIRT1,PGC-1α and PPARγ(P＜0.01).Compared with the model group,the groups intervened with donepezil or HJSGF showed shortened escape latency(P＜0.05,P＜0.01);increased platform crossing times and target quadrant residence time(P＜0.05,P＜0.01);alleviated damage of the hippocampal CA1 region,reduced secretion and protein expressions of IL-1β and IL-18(P＜0.05,P＜0.01);and elevated hippocampal protein expressions of SIRT1,PGC-1α and PPARγ(P＜0.05,P＜0.01).CONCLUSION HJSGF may alleviate the inflammatory responses in VD rats and therefore improve their learning and memory impairment by activating the SIRT1/PGC-1α/PPARγ signaling pathway.