ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

ObjectiveTo establish a geographical origin identification model for Foeniculi Fructus from Haiyuan， providing a new technical reference for the protection of Haiyuan's geo-authentic medicinal materials and its designation as a national geographical indication agricultural product. MethodsSamples of Foeniculi Fructus were collected from eight producing areas， including Minqin （Gansu）， Bozhou （Anhui）， Qingdao （Shandong）， Dezhou （Shandong）， Urumqi （Xinjiang）， Nujiang （Yunnan）， Gutuo （Inner Mongolia）， and Haiyuan （Ningxia）. Gas chromatography-ion mobility spectrometry （GC-IMS） was used to detect the volatile organic compounds （VOCs） in samples from these geographic origins. VOCs were qualitatively analyzed through dual matching with the National Institute of Standards and Technology （NIST） mass spectral database and the IMS drift time database. Using the Reporter module and Gallery Plot visualization tools within the LAV analytical platform， VOC fingerprint profiles characterizing geographic origins were constructed. A non-targeted analytical strategy was adopted， and 97 VOCs detected via GC-IMS were subjected to principal component analysis （PCA） and partial least squares discriminant analysis （PLS-DA） based on their differential distribution patterns to construct an origin identification model for Foeniculi Fructus from Haiyuan region. Key discriminative markers were screened using variable importance in projection （VIP） values greater than 1. ResultsA total of 97 VOCs were identified， including alcohols， aldehydes， ketones， esters， organic acids， terpenoids， ethers， alkenes， and benzenes. The PLS-DA model， based on VOCs data obtained by GC-IMS， effectively distinguished Foeniculi Fructus in Haiyuan region from those of other origins. During cross-validation， the model achieved a prediction parameter （Q²） of 0.976 and a goodness-of-fit parameter （R²） of 0.936， with no overfitting observed in permutation testing. Twelve key flavor markers with VIP > 1 were identified as characteristic indicators of Haiyuan origin. ConclusionA stable and highly predictive origin identification model for Foeniculi Fructus from Haiyuan was successfully established using GC-IMS technology， PLS-DA， and VIP-based marker screening. This model provides a novel technical strategy for accurately distinguishing Foeniculi Fructus in Haiyuan region from other regional varieties and offers new technical support for its protection as a geo-authentic medicinal material and a nationally designated geographical indication agricultural product in China.

AIM:To identify surrogate clinical bio-markers for profiling the eosinophilic status of an individual patient over induced sputum analysis.METHODS:We conducted a cross-sectional study on 100 asthmatic patients whose induced sputum was successfully collected.Subjects were further classified into either EA or NEA based on whether the percentage of sputum eosinophil count(SEC％)was≥3％.Demographic and clinical data were col-lected,including basic information,routine blood tests,lung function tests,bronchodilator reversibili-ty tests,fractional exhaled nitric oxide(FeNO),the Asthma Control Test(ACT)and the Asthma Control Questionnaire(ACQ).All variables significantly asso-ciated with EA were candidates for multivariate lo-gistic regression analysis.A scoring system present-ed as a nomogram for the prediction of EA was de-veloped.RESULTS:In the univariate analysis,com-pared with NEA subjects,those with EA were of older age and had worse asthma control and lung function in addition to higher values of blood eosin-ophils,serum IgE and FeNO.Multivariable logistic regression analysis revealed that age,FeNOx serum IgE and blood eosinophil count(BEC)were identi-fied as independent risk factors for eosinophilic asthma,which were all included in the nomogram.CONCLUSION:A combination assessment including age,FeNOx serum IgE and BEC could be applicable to clinicians in identifying eosinophilic asthma and is easier,faster,more inexpensive and more readily available than the induced sputum test.

Objective:To share our experience of single-port transoral Da Vinci robotic surgery for laryngeal and pharyngeal benign tumors.Methods:Three patients aged over 18 years and diagnosed respectively with epiglottic cyst, aryepiglottic fold cyst and thyroglossal duct cyst at tongue base were included who received operations in Hainan Hospital of Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine (Boao Research Hospital of Hainan) between August 1, 2023 and April 10, 2024. There were 1 male and 2 females, with an average age of 59 years old. The clinical diagnosis of these 3 patients was respectively epiglottic cyst, aryepiglottic fold cyst and thyroglossal duct cyst at tongue base. Intraoperative conversion rate, blood loss, operation time, hospital stay, pain score and swallowing function score were analyzed.Results:All three patients successfully underwent the operations with the single-port Da Vinci robotic system. The clean-contaminated resection rate of the tumors was 100%. The conversion rate was nil. The blood loss was 0-7 ml. The operation time was 5-30 minutes. There were no adverse events such as loosening of teeth and soft tissue abrasions of pharyngeal side wall. The rate of oral feeding within 24 hours after surgery was 100%. No postoperative coughing, bleeding, or dyspnea occurred. The average length of hospital stay was 3.7 days. The VAS score decreased 3 days after surgery compared to 1 day after surgery. The swallowing function recovered 1 month after surgery.Conclusion:The single-port transoral robotic surgery for laryngeal and pharyngeal benign lesions is safe and efficient, with fewer complications.

Objective To explore the biological characteristics associated with different subtypes and the response to immunotherapy by integrating multiomics analysis and artificial neural networks(ANN)to delineate the precise molecular subtypes of adrenocortical carcinoma(ACC)and establish a prognostic prediction model,in order to provide reference for the accurate prognosis assessment and individualized treatment of ACC.Methods The multiomics data of 44 Chinese ACC patients admitted to the Department of Urology,West China Hospital of Sichuan University during Jan.1,2012 and Dec.31,2022 were integrated,including genomic,transcriptomic and clinical features.Ten different clustering algorithms were employed for consensus clustering to identify robust molecular subtypes.The results were then incorporated into an ANN model to construct an ANN-driven prognostic index(ANPI)for patient stratification and survival prediction.Results Three distinct molecular subtypes(cancer subtypes,CS1-3)with significantly different prognoses were identified,among which CS1 exhibited the poorest survival outcomes.A set of 20 core genes was selected to form the basis of the ANPI model.ANPI effectively stratified patients into high-and low-risk groups:patients in the low-ANPI group had significantly better overall survival and exhibited"hot tumor"immune phenotypes,suggesting greater benefits from immunotherapy.In contrast,high-ANPI patients had worse prognoses and displayed"cold tumor"characteristics with weaker immunotherapy responses.Conclusion Our integrative multiomics analysis illustrated the molecular landscape of ACC in the Chinese population and uncovered the key immune-related features linked to clinical outcomes.The ANPI model demonstrated strong performance in prognostic prediction and immunotherapy response assessment,offering a valuable tool for precision oncology and clinical decision-making.

Infectious chronic refractory wounds are common in the department of dermatology,and have a great influence on the quality of life of patients.Their incidence is increasing year by year.The pathogensis of infectious chronic refractory wounds is due to the exuberance of pathogenic heat and toxin,disharmony between nutritive qi and defensive qi,and imbalance of zang-fu organs,which is related with the theory of qi-fluid and sweat pores.Therefore,it is proposed that stagnation and obstruction of sweat pores contribute to the pathological basis for the onset of infectious chronic refractory wounds,and therapeutic principle of opening sweat pores was presented.In the medication view of treating the skin diseases with the skin-related Chinese medicinals,skin-related Chinese medicinals are good at treating skin diseases,and consequently the application of skin-related Chinese medicinals to open sweat in treating infectious chronic refractory wounds was discussed.It is suggested that for the treatment of infectious chronic refractory wounds due to pathogenic fire-toxin accumulation in sweat pores,therapy of clearing heat and expelling fire to open sweat pores should be exployed,and skin-related Chinese medicinals such as Phellodendri Chinensis Cortex,Dictamni Cortex and Fraxini Cortex can be selected;for the treatment of infectious chronic refractory wounds due to blood-stasis stagnation in sweat pores,therapy of cooling and activating blood to open sweat pores should be exployed,and skin-related Chinese medicinals such as Moutan Cortex and Lycii Cortex can be selected;for the treatment of infectious chronic refractory wounds due to wind and dampness obstructing sweat pores,therapy of expelling wind and eliminating dampness to unblock sweat pores should be exployed,and skin-related Chinese medicinals such as Acanthopanacis Cortex,Citri Reticulatae Pericarpium,and Poriae Cutis can be selected;for the treatment of infectious chronic refractory wounds due to healthy qi deficiency resulting in the obstruction of sweat pores,therapy of invigorating spleen and tonifying kidney to nourish sweat pores should be exployed,and skin-related Chinese medicinals such as Cinnamomi Cortex,Eucommiae Cortex,and black soybean testa(Testa Glycinea Macids)can be chosen.Guided by the theory of qi-fluid and sweat pores,this paper explored the application of skin-related Chinese medicinals in the treating infectious chronic refractory wounds,which provides theoretical basis for such an approach,enriches the theory of traditional Chinese medicine for the treatment of infectious chronic refractory wounds,and expands the clinical application of the theory of sweat pores.

Objective To explore the biological characteristics associated with different subtypes and the response to immunotherapy by integrating multiomics analysis and artificial neural networks(ANN)to delineate the precise molecular subtypes of adrenocortical carcinoma(ACC)and establish a prognostic prediction model,in order to provide reference for the accurate prognosis assessment and individualized treatment of ACC.Methods The multiomics data of 44 Chinese ACC patients admitted to the Department of Urology,West China Hospital of Sichuan University during Jan.1,2012 and Dec.31,2022 were integrated,including genomic,transcriptomic and clinical features.Ten different clustering algorithms were employed for consensus clustering to identify robust molecular subtypes.The results were then incorporated into an ANN model to construct an ANN-driven prognostic index(ANPI)for patient stratification and survival prediction.Results Three distinct molecular subtypes(cancer subtypes,CS1-3)with significantly different prognoses were identified,among which CS1 exhibited the poorest survival outcomes.A set of 20 core genes was selected to form the basis of the ANPI model.ANPI effectively stratified patients into high-and low-risk groups:patients in the low-ANPI group had significantly better overall survival and exhibited"hot tumor"immune phenotypes,suggesting greater benefits from immunotherapy.In contrast,high-ANPI patients had worse prognoses and displayed"cold tumor"characteristics with weaker immunotherapy responses.Conclusion Our integrative multiomics analysis illustrated the molecular landscape of ACC in the Chinese population and uncovered the key immune-related features linked to clinical outcomes.The ANPI model demonstrated strong performance in prognostic prediction and immunotherapy response assessment,offering a valuable tool for precision oncology and clinical decision-making.

AIM:To identify surrogate clinical bio-markers for profiling the eosinophilic status of an individual patient over induced sputum analysis.METHODS:We conducted a cross-sectional study on 100 asthmatic patients whose induced sputum was successfully collected.Subjects were further classified into either EA or NEA based on whether the percentage of sputum eosinophil count(SEC％)was≥3％.Demographic and clinical data were col-lected,including basic information,routine blood tests,lung function tests,bronchodilator reversibili-ty tests,fractional exhaled nitric oxide(FeNO),the Asthma Control Test(ACT)and the Asthma Control Questionnaire(ACQ).All variables significantly asso-ciated with EA were candidates for multivariate lo-gistic regression analysis.A scoring system present-ed as a nomogram for the prediction of EA was de-veloped.RESULTS:In the univariate analysis,com-pared with NEA subjects,those with EA were of older age and had worse asthma control and lung function in addition to higher values of blood eosin-ophils,serum IgE and FeNO.Multivariable logistic regression analysis revealed that age,FeNOx serum IgE and blood eosinophil count(BEC)were identi-fied as independent risk factors for eosinophilic asthma,which were all included in the nomogram.CONCLUSION:A combination assessment including age,FeNOx serum IgE and BEC could be applicable to clinicians in identifying eosinophilic asthma and is easier,faster,more inexpensive and more readily available than the induced sputum test.

Objective:To share our experience of single-port transoral Da Vinci robotic surgery for laryngeal and pharyngeal benign tumors.Methods:Three patients aged over 18 years and diagnosed respectively with epiglottic cyst, aryepiglottic fold cyst and thyroglossal duct cyst at tongue base were included who received operations in Hainan Hospital of Ruijin Hospital affiliated to Shanghai Jiao Tong University School of Medicine (Boao Research Hospital of Hainan) between August 1, 2023 and April 10, 2024. There were 1 male and 2 females, with an average age of 59 years old. The clinical diagnosis of these 3 patients was respectively epiglottic cyst, aryepiglottic fold cyst and thyroglossal duct cyst at tongue base. Intraoperative conversion rate, blood loss, operation time, hospital stay, pain score and swallowing function score were analyzed.Results:All three patients successfully underwent the operations with the single-port Da Vinci robotic system. The clean-contaminated resection rate of the tumors was 100%. The conversion rate was nil. The blood loss was 0-7 ml. The operation time was 5-30 minutes. There were no adverse events such as loosening of teeth and soft tissue abrasions of pharyngeal side wall. The rate of oral feeding within 24 hours after surgery was 100%. No postoperative coughing, bleeding, or dyspnea occurred. The average length of hospital stay was 3.7 days. The VAS score decreased 3 days after surgery compared to 1 day after surgery. The swallowing function recovered 1 month after surgery.Conclusion:The single-port transoral robotic surgery for laryngeal and pharyngeal benign lesions is safe and efficient, with fewer complications.

Objective:To explore the relevant risk factors for deep venous thrombosis (DVT) of lower limb occurring 3 months after joint replacement surgery.Methods:A retrospective analysis was conducted on the clinical data of 1,782 patients who underwent joint replacement surgery at Drum Tower Hospital, School of Medicine of Nanjing University, from February 2015 to December 2018. Of these, 1,298 were male and 484 were female, with an average age of 65.4±12.3 years (range, 18-95 years). Fourteen factors associated with DVT occurrence at 3 months were investigated, including age, gender, body mass index (BMI), season of surgery, preoperative coagulation function, type of surgery, selection of minimally invasive approach, occurrence of lower limb venous thrombosis 1 day after surgery, history of previous thrombotic diseases, smoking, tumors, diabetes, hypertension, and heart disease. Independent sample t-tests and chi-square tests were used to analyze the risk factors for DVT occurrence. Indicators with statistically significant differences were included in a binary logistic regression analysis to determine the risk factors for DVT 3 months after surgery. The risk prediction model was established according to the results of logistic regression analysis, and the receiver operating characteristic curve was drawn. The area under the curve of the prediction model was calculated. Results:A total of 1,782 patients were included. The overall incidence of DVT occurring 3 months after joint replacement surgery was 10.5% (187/1,782). The thrombosis group included 5 symptomatic cases and 182 asymptomatic cases, with 13 proximal and 174 distal cases. DVT was found in the iliac vein (1 case), femoral vein (10 cases), popliteal vein (8 cases), peroneal vein (14 cases), and intramuscular vein (168 cases). Single-factor analysis showed that female gender, increasing age, previous thrombotic disease, hypertension, surgery in autumn, and the occurrence of DVT on the first day after surgery were correlated with DVT occurring 3 months after joint replacement surgery ( P<0.05). After excluding the missing data, a total of 1,744 patients were included in the final analysis. DVT occurrence on the first day after surgery [ OR=7.498, 95% CI (5.312, 10.584), P<0.001], surgery in autumn [ OR=1.834, 95% CI (1.215, 2.769), P=0.004], age [ OR=1.024, 95% CI (1.007, 1.042), P=0.009], female gender [ OR=1.863, 95% CI(1.184, 2.931), P=0.007], and history of previous thrombotic diseases [ OR=0.012, 95% CI (1.136, 2.830), P=0.012] were found to be associated with DVT occurrence at 3 months after surgery. The area under the curve (AUC) for predicting DVT three months after hip or knee arthroplasty was 0.803 [95% CI (0.761, 0.844)]. Conclusion:Advanced age, female gender, history of previous thrombotic diseases, occurrence of DVT on the first day after surgery, and surgery in autumn are risk factors for DVT occurring 3 months after joint replacement surgery.