The identification of constitutional types in traditional Chinese medicine(TCM)is a crucial component in realizing the concept of"treatment before the onset of disease".In recent years,the"Constitution in Chinese Medicine Questionnaire"has been employed as a standardized tool and has achieved notable success in the field of TCM constitution identification.However,there remains scope for further enhancement of its validity and applicability.Techniques for identifying TCM constitutions based on multidimensional phenotypes continue to emerge,yet a universally applicable constitutional determination model has yet to be established.We propose three research and development directions:The self-assessment questionnaires,the non-invasive point-of-care testing models based on TCM constitution phenotype,and the multidimensional phenotype-based constitution identification platforms.By way of an example,we outline specific developmental ideas with a focus on TCM constitution identification technology based on the analysis of exhaled breath.

Objective:To explore the clinical application effects of tissue flaps prepared from the discarded limbs after amputation in patients with destructive wounds in the lower limbs.Methods:The study was a retrospective observational study. From March 2019 to March 2024, 7 male patients with destructive wounds in the lower limbs who met the inclusion criteria were admitted to the Department of Burns and Plastic Surgery of Xiangya Hospital of Central South University, aged 35 to 57 years. After clinical treatment, the damaged limbs were still difficult to preserve. Five patients with destructive wounds in the lower limbs were repaired with pedicled tissue flaps prepared from the discarded limbs after amputation, with wound areas of 15 cm×10 cm to 25 cm×15 cm and tissue flap incision areas of 15 cm×10 cm to 20 cm×15 cm. Two patients with destructive wounds in the lower limbs were repaired with free tissue flaps prepared from the discarded limbs after amputation, with wound areas of 22 cm×18 cm and 25 cm×15 cm and tissue flap incision areas of 23 cm×20 cm and 25 cm×18 cm. The survival of the tissue flap, the healing and appearance of wounds in the recipient site were followed up. At the last follow-up, the recovery status of the recipient site was evaluated according to the comprehensive flap evaluation scale, and the status of corrective prosthesis fitting was recorded.Results:During the follow-up of 6 to 24 months, all the tissue flaps successfully survived, with good healing and appearance of wounds in the recipient site. At the last follow-up, the scores of the recovery status of the recipient site ranged from 36 to 39 (with an average of 37.2). All amputated limbs were able to accommodate corrective prostheses with no distal ulceration.Conclusions:Utilizing tissue flaps prepared from the discarded limbs after amputation in patients with destructive wounds in the lower limbs to repair wounds effectively uses the discarded tissue and avoid creating new donor sites, which is a method to be considered for repairing multiple destructive wounds.

OBJECTIVE To investigate the inhibitory effect and mechanism of the active components of Alpinia katsumadai （ACAK） on tumor xenograft growth and tumor angiogenesis of human pancreatic cancer PANC-1 cells in nude mice. METHODS A tumor xenograft model in nude mice was established using human pancreatic cancer PANC-1 cells. The mice were randomly divided into model control group （intragastric administration of 0.9% normal saline）， solvent control group （intragastric administration of 0.5% carboxymethyl cellulose sodium）， positive control group （intraperitoneal injection of 0.5% carboxymethyl cellulose sodium+bevacizumab suspension 5 mg/kg ）， and ACAK 50， 100， and 200 mg/kg groups （intragastric administration of 0.5% carboxymethyl cellulose sodium+ACAK suspension 50， 100， 200 mg/kg）. The administration was carried out for 5 consecutive days followed by a 2-day interval， and this cycle was repeated for a total duration of 28 days. The tumor volume （TV）， relative tumor volume （RTV）， and relative tumor proliferation rate （T/C） at various time points from day 1 to day 28 after drug administration were measured and calculated for each group of nude mice. After the drug administration， the tumor weights were measured， and microvessel density （MVD） in the tumor xenograft tissues of nude mice， as well as relative protein expression levels of vascular endothelial growth factor （VEGF） and its receptor [fas-like tyrosine kinase-1 （Flt-1）， kinase insert domain receptor （KDR）] were detected. RESULTS On the 24th day of ACAK administration，compared with the model control group， the TV and RTV （except for ACAK 50 and 100 mg/kg groups） of nude mice in the positive control group and ACAK dose groups were significantly decreased （P＜0.05 or P＜0.01）， and the T/C of ACAK dose groups showed a dose-dependent decrease； the microvascular distribution of nude mice in the positive control group and ACAK dose groups was relatively sparse， and the tumor weight （except for the ACAK 50 mg/kg group）， MVD， and relative expression levels of VEGF， KDR， and Flt-1 in the tumor xenograft tissues were significantly reduced （P＜0.05 or P＜0.01）. CONCLUSIONS ACAK has a good anti-pancreatic cancer effect， and its mechanism may be related to its inhibition of VEGF/ VEGFR signaling pathway， thereby inhibiting angiogenesis in pancreatic cancer.

Objective:To investigate the clinicopathological characteristics and prognostic influencing factors in young breast cancer patients.Methods:A retrospective case series study was conducted. The clinical data of 408 young patients with breast cancer in the Fifth Medical Center of Chinese PLA General Hospital from January 2005 to December 2020 were retrospectively analyzed. The clinical characteristics and prognostic influencing factors of patients were observed. The Kaplan-Meier method was used to analyze overall survival (OS) and disease-free survival (DFS) of patients. Univariate analysis of prognostic factors was conducted by using the log-rank test, and multivariate analysis was performed by using Cox proportional risk model.Results:The median age [ M ( Q1, Q3)] of 408 young female patients with breast cancer was 36 (33, 39) years; the 5-year OS and 5-year DFS rates were 89.9%, 84.0% of 387 breast cancer patients in early and middle stage (except for stage Ⅳ). There were statistically significant differences in the 5-year OS and 5-year DFS rates (excluding stage Ⅳ of DFS) of patients with different clinical staging and molecular subtypes (all P < 0.05). The differences were statistically significant in the 5-year DFS rate of patients with different pathological types and histological grades (all P < 0.05). There were no statistically significant differences in the 5-year OS and DFS rates between the patients receiving breast-conserving surgery or mastectomy (all P > 0.05). The results of multivariate Cox regression analysis indicated that clinical staging ( HR = 3.121, 95% CI: 2.301-4.233, P < 0.001) and molecular classification ( HR = 1.441, 95% CI: 1.126-1.845, P = 0.004) were independent prognostic factors for OS. Additionally, clinical staging ( HR = 3.001, 95% CI: 2.174-4.141, P < 0.001) was identified as an independent prognostic factor for DFS. Conclusions:The prognosis of young breast cancer patients is closely related to clinical staging and molecular subtype. The later the clinical stage is, the poorer prognosis is. Luminal-type breast cancer has a better prognosis than other subtypes. For early-stage breast cancer patients who meet the criteria for breast-conserving surgery, breast-conserving surgery is the first-choice alternative.

Objective:To screen the optimal machine learning model for predicting the recurrence condition of hepatocellular carcinoma (HCC) at different time points post-surgery, based on the cutoff value of the Ki67 positive proliferation index condition calculated from recurrence-free survival and combined with various clinical features.Methods:retrospective study included initially treated patients with solitary HCC who underwent radical surgery at the Fifth Medical Center of the PLA General Hospital from January 2013 to March 2023. Data included general clinical data, preoperative laboratory parameters, and surgical pathology information about the subjects. The postoperative recurrence status was assessed by querying the medical record system or by telephone follow-up. The Ki67 positive index cutoff value was determined by the X-tile software based on the patient's recurrence-free survival status and time analysis. Survival rates were calculated using the Kaplan-Meier method, and survival curves were plotted. The study population was randomly divided into training and testing groups in a 7:3 ratio using a computer-generated random number method. The minimum redundancy maximum relevance (mRMR) method was used for feature variable selection. Predictive models for postoperative HCC recurrence conditions in patients with HCC were constructed using random forest, support vector machine, logistic regression, and gradient boosting decision tree machine learning algorithms. Inter-group comparisons for continuous data were performed using the t-test or Mann-Whitney U test. Inter-group comparisons of enumeration data were performed using the Pearson χ2 test, continuity-corrected χ2 test, or Fisher's exact test. Results:The cutoff values for the Ki67 positivity index were 0.3 and 0.5 in 510 cases, with a follow-up time ranging from 1.2 to 11.4 years (median: 6.2 years). The recurrence-free survival time was between 1 and 135 months (median: 32 months), with recurrence-free survival rates post-surgery at 1, 2, 3, and 5 years were 87.5%, 77.1%, 61.2%, and 54.5%, respectively. The top five variables predicted HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years, in accordance with information obtained by the mRMR screen out. The Ki67 positivity index screened a successfully constructed machine learning model to predict HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years. The machine learning model based on the gradient boosting decision tree algorithm had the best prediction performance among them (areas under the receiver operating characteristic curves for predicting HCC recurrence within six months in the training and validation sets were 0.996 and 0.946, and accuracies were 0.972 and 0.935, respectively).Conclusion:A machine learning model was successfully constructed using the Ki67 positivity index combined with four readily available clinical features to predict HCC recurrence. The machine learning model based on the gradient boosting decision tree algorithm demonstrated the best performance in terms of predicting HCC recurrence within six months after surgery.

The identification of constitutional types in traditional Chinese medicine(TCM)is a crucial component in realizing the concept of"treatment before the onset of disease".In recent years,the"Constitution in Chinese Medicine Questionnaire"has been employed as a standardized tool and has achieved notable success in the field of TCM constitution identification.However,there remains scope for further enhancement of its validity and applicability.Techniques for identifying TCM constitutions based on multidimensional phenotypes continue to emerge,yet a universally applicable constitutional determination model has yet to be established.We propose three research and development directions:The self-assessment questionnaires,the non-invasive point-of-care testing models based on TCM constitution phenotype,and the multidimensional phenotype-based constitution identification platforms.By way of an example,we outline specific developmental ideas with a focus on TCM constitution identification technology based on the analysis of exhaled breath.

Objective:To screen the optimal machine learning model for predicting the recurrence condition of hepatocellular carcinoma (HCC) at different time points post-surgery, based on the cutoff value of the Ki67 positive proliferation index condition calculated from recurrence-free survival and combined with various clinical features.Methods:retrospective study included initially treated patients with solitary HCC who underwent radical surgery at the Fifth Medical Center of the PLA General Hospital from January 2013 to March 2023. Data included general clinical data, preoperative laboratory parameters, and surgical pathology information about the subjects. The postoperative recurrence status was assessed by querying the medical record system or by telephone follow-up. The Ki67 positive index cutoff value was determined by the X-tile software based on the patient's recurrence-free survival status and time analysis. Survival rates were calculated using the Kaplan-Meier method, and survival curves were plotted. The study population was randomly divided into training and testing groups in a 7:3 ratio using a computer-generated random number method. The minimum redundancy maximum relevance (mRMR) method was used for feature variable selection. Predictive models for postoperative HCC recurrence conditions in patients with HCC were constructed using random forest, support vector machine, logistic regression, and gradient boosting decision tree machine learning algorithms. Inter-group comparisons for continuous data were performed using the t-test or Mann-Whitney U test. Inter-group comparisons of enumeration data were performed using the Pearson χ2 test, continuity-corrected χ2 test, or Fisher's exact test. Results:The cutoff values for the Ki67 positivity index were 0.3 and 0.5 in 510 cases, with a follow-up time ranging from 1.2 to 11.4 years (median: 6.2 years). The recurrence-free survival time was between 1 and 135 months (median: 32 months), with recurrence-free survival rates post-surgery at 1, 2, 3, and 5 years were 87.5%, 77.1%, 61.2%, and 54.5%, respectively. The top five variables predicted HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years, in accordance with information obtained by the mRMR screen out. The Ki67 positivity index screened a successfully constructed machine learning model to predict HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years. The machine learning model based on the gradient boosting decision tree algorithm had the best prediction performance among them (areas under the receiver operating characteristic curves for predicting HCC recurrence within six months in the training and validation sets were 0.996 and 0.946, and accuracies were 0.972 and 0.935, respectively).Conclusion:A machine learning model was successfully constructed using the Ki67 positivity index combined with four readily available clinical features to predict HCC recurrence. The machine learning model based on the gradient boosting decision tree algorithm demonstrated the best performance in terms of predicting HCC recurrence within six months after surgery.

Objective:To explore the clinical application effects of tissue flaps prepared from the discarded limbs after amputation in patients with destructive wounds in the lower limbs.Methods:The study was a retrospective observational study. From March 2019 to March 2024, 7 male patients with destructive wounds in the lower limbs who met the inclusion criteria were admitted to the Department of Burns and Plastic Surgery of Xiangya Hospital of Central South University, aged 35 to 57 years. After clinical treatment, the damaged limbs were still difficult to preserve. Five patients with destructive wounds in the lower limbs were repaired with pedicled tissue flaps prepared from the discarded limbs after amputation, with wound areas of 15 cm×10 cm to 25 cm×15 cm and tissue flap incision areas of 15 cm×10 cm to 20 cm×15 cm. Two patients with destructive wounds in the lower limbs were repaired with free tissue flaps prepared from the discarded limbs after amputation, with wound areas of 22 cm×18 cm and 25 cm×15 cm and tissue flap incision areas of 23 cm×20 cm and 25 cm×18 cm. The survival of the tissue flap, the healing and appearance of wounds in the recipient site were followed up. At the last follow-up, the recovery status of the recipient site was evaluated according to the comprehensive flap evaluation scale, and the status of corrective prosthesis fitting was recorded.Results:During the follow-up of 6 to 24 months, all the tissue flaps successfully survived, with good healing and appearance of wounds in the recipient site. At the last follow-up, the scores of the recovery status of the recipient site ranged from 36 to 39 (with an average of 37.2). All amputated limbs were able to accommodate corrective prostheses with no distal ulceration.Conclusions:Utilizing tissue flaps prepared from the discarded limbs after amputation in patients with destructive wounds in the lower limbs to repair wounds effectively uses the discarded tissue and avoid creating new donor sites, which is a method to be considered for repairing multiple destructive wounds.

Objective:To investigate the clinicopathological characteristics and prognostic influencing factors in young breast cancer patients.Methods:A retrospective case series study was conducted. The clinical data of 408 young patients with breast cancer in the Fifth Medical Center of Chinese PLA General Hospital from January 2005 to December 2020 were retrospectively analyzed. The clinical characteristics and prognostic influencing factors of patients were observed. The Kaplan-Meier method was used to analyze overall survival (OS) and disease-free survival (DFS) of patients. Univariate analysis of prognostic factors was conducted by using the log-rank test, and multivariate analysis was performed by using Cox proportional risk model.Results:The median age [ M ( Q1, Q3)] of 408 young female patients with breast cancer was 36 (33, 39) years; the 5-year OS and 5-year DFS rates were 89.9%, 84.0% of 387 breast cancer patients in early and middle stage (except for stage Ⅳ). There were statistically significant differences in the 5-year OS and 5-year DFS rates (excluding stage Ⅳ of DFS) of patients with different clinical staging and molecular subtypes (all P < 0.05). The differences were statistically significant in the 5-year DFS rate of patients with different pathological types and histological grades (all P < 0.05). There were no statistically significant differences in the 5-year OS and DFS rates between the patients receiving breast-conserving surgery or mastectomy (all P > 0.05). The results of multivariate Cox regression analysis indicated that clinical staging ( HR = 3.121, 95% CI: 2.301-4.233, P < 0.001) and molecular classification ( HR = 1.441, 95% CI: 1.126-1.845, P = 0.004) were independent prognostic factors for OS. Additionally, clinical staging ( HR = 3.001, 95% CI: 2.174-4.141, P < 0.001) was identified as an independent prognostic factor for DFS. Conclusions:The prognosis of young breast cancer patients is closely related to clinical staging and molecular subtype. The later the clinical stage is, the poorer prognosis is. Luminal-type breast cancer has a better prognosis than other subtypes. For early-stage breast cancer patients who meet the criteria for breast-conserving surgery, breast-conserving surgery is the first-choice alternative.

Objective To investigate the clinical diagnostic value of extra-spindle pole-like protein 1(ESPL1)in the progression of hepatitis B virus(HBV)-related liver fibrosis.Methods A total of 228 patients with HBV infection who were admitted to The First Affiliated Hospital of Guangxi Medical University from June 2017 to August 2023 were enrolled.The transient elastography system FibroScan was used to determine liver stiffness measurement(LSM)for all patients,and according to the LSM value,they were divided into non-liver fibrosis group with 80 patients,mild liver fibrosis group with 83 patients,advanced liver fibrosis group with 30 patients,and liver cirrhosis group with 35 patients.ELISA was used to measure the serum level of ESPL1.The Kruskal-Wallis H test was used for comparison of the serum level of ESPL1 between the four groups;the Spearman correlation analysis was used to investigate the correlation between ESPL1 and LSM;the receiver operating characteristic(ROC)curve was used to analyze the value of serum ESPL1 in predicting the progression of liver fibrosis.Results The liver cirrhosis group had a significantly higher serum level of ESPL1 than the non-liver fibrosis group and the mild liver fibrosis group(both P<0.05),and the advanced liver fibrosis group and the mild liver fibrosis group had a significantly higher serum level of ESPL1 than the non-liver fibrosis group(both P<0.05).The correlation analysis showed that there was a positive correlation between serum ESPL1 and LSM in the patients with HBV infection and varying degrees of liver fibrosis(r=0.515,P<0.001).Serum ESPL1 had an area under the ROC curve(AUC)of 0.809 in predicting liver cirrhosis and an AUC of 0.638 in predicting advanced liver fibrosis,with a sensitivity of 87.5%and 100%,respectively,and a specificity of 59.7%and 31.3%,respectively.Conclusion There is a certain correlation between serum ESPL1 and HBV-related liver fibrosis,and higher serum ESPL1 may indicate a higher degree of liver fibrosis.Serum ESPL1 is expected to become one of the serum markers for assisting in the diagnosis of liver cirrhosis and an important clinical method for dynamically monitoring the progression of liver fibrosis in patients with HBV infection.