OBJECTIVE To provide a scientific basis for the quality evaluation and clinical application of Qingwen hufei granules. METHODS Fourteen batches of Qingwen hufei granules were used as samples to establish high-performance liquid chromatography （HPLC） fingerprints using the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine （2012 Edition）. The chromatographic peaks were identified and the similarity was evaluated. Cluster analysis （CA）， principal component analysis （PCA）， and orthogonal partial least squares-discriminant analysis （OPLS-DA） were used to conduct chemical pattern recognition analysis on the 14 batches of samples. Meanwhile， the contents of neochlorogenic acid （NGA）， chlorogenic acid （CHA）， cryptochlorogenic acid （CGA）， forsythoside A （FTA）， 3，5-O-dicaffeoylquinic acid （3，5-O- DA）， 4，5-O-dicaffeoylquinic acid （4，5-O-DA）， and angoroside C （AGC） in the samples were determined by HPLC. RESULTS The methodological investigation results of both the fingerprint and the content determination complied with the relevant requirements. Fourteen common peaks were indicated in the HPLC fingerprints of the 14 batches of samples， and 7 of them were identified [NGA （peak 2）， CHA （peak 3）， CGA （peak 5）， FTA （peak 11）， 3，5-O-DA （peak 12）， 4，5-O-DA （peak 13）， and AGC （peak 14）]； the similarity of each sample was greater than 0.94. The results of CA and PCA showed that the samples could be classified into 3 categories； the results of OPLS-DA indicated that peak 4 （unknown）， peak 11 （FTA）， peak 8 （unknown）， peak 9 （unknown）， and peak 1 （unknown） were the differential components. The content ranges of NGA， CHA， CGA， 3，5-O-DA， FTA， 4，5-O-DA and AGC in the 14 batches of samples were 0.210 4-0.458 7， 0.269 1-0.506 3， 0.228 1-0.461 1， 0.443 9-1.044 6， 0.066 7-0.155 7， 0.062 8-0.143 8， and 0.057 4-0.105 7 mg/g， respectively. CONCLUSIONS The HPLC fingerprint and multi-component content determination methods established in this study are efficient and reliable， and can be used for the quality evaluation of Qingwen hufei granules.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

Medical therapy and surgical intervention are the two primary approaches for treating myocardial bridge.However,there remains controversy regarding the use of coronary artery bypass grafting(CABG)and myocardial bridge unroofing.Here,we report a case of myocardial infarction following CABG in a patient with a myocardial bridge.The patient was admitted to Lanzhou First Peopie's Hospital with persistent chest pain,chest tightness,and shortness of breath lasting 2 hours.Physical examination revealed no significant abnormalities.Electrocardiography(ECG)indicated extensive anterior wall myocardial infarction.Laboratory findings showed myoglobin levels of 140.1 ng/ml and troponin Ⅰ levels of 2.59 ng/ml,with no other significant abnormalities.The initial diagnosis was acute extensive anterior wall myocardial infarction.Emergency coronary angiography revealed a myocardial bridge in the mid-segment of the left anterior descending artery(LAD).Emergency CABG using the left internal mammary artery to the LAD was performed,leading to symptomatic improvement,and the patient was discharged in stable condition.However,the patient experienced a recurrent myocardial infarction seven years post-surgery and received secondary preventive medical therapy.The patient is currently under ongoing follow-up care.CABG is an effective treatment for myocardial bridge.However,based on the case reported in this study,we recommend careful evaluation of whether a patient may benefit from CABG.

Artificial intelligence(AI)technology has been demonstrated that have unique advantages in medical diagnosis based on massive clinical data.Its potential prospects has been found in the diagnosis and treatment of cardiovascular disease(CVD).AI technology has extent its priority in electrocardiogram reading,differential analysis and disease classification.Interventional therapy is an important part of the diagnosis and treatment of CVD.This paper aim to review the latest developments to summarize the AI-assisted CVD interventional diagnosis and treatment technology.

Objective:To plot Kaplan-Meier curves using simulated survival data and compare the characteristics of different survival probability extraction methods for Kaplan-Meier curves and their performance across various scenarios.Methods:Survival datasets were simulated using R-4.4.2 with parameters including sample sizes,censoring marker,and curve numbers.GetData Graph Digitizer,IPDfromKM getpoints,SurvdigitizeR survival_digitize were evaluated.A JavaScript script was developed to extract Kaplan-Meier curve.Root Mean Square Error(RMSE)was calculated to quantify deviations between digitized and true survival probabilities.Results:The JavaScript script method demonstrated the smallest RMSE across all simulated scenarios(RMSE=1.015×10-4),significantly outperforming the other three methods(P＜0.05),with statistically significant differences observed among methods(P＜0.05).Conclusion:For vector format illustrations,JavaScript scripts enable accurate and robust reverse engineering of Kaplan-Meier curves;for bitmaps,the GetData Graph Digitizer and SurvdigitizeR survival_digitize methods yield more accurate results,and the SurvdigitizeR survival_digitize method is the most efficient.Future research should focus on integrating intelligent algorithms for enhanced robustness and precision in survival data reconstruction.

Objective:To plot Kaplan-Meier curves using simulated survival data and compare the characteristics of different survival probability extraction methods for Kaplan-Meier curves and their performance across various scenarios.Methods:Survival datasets were simulated using R-4.4.2 with parameters including sample sizes,censoring marker,and curve numbers.GetData Graph Digitizer,IPDfromKM getpoints,SurvdigitizeR survival_digitize were evaluated.A JavaScript script was developed to extract Kaplan-Meier curve.Root Mean Square Error(RMSE)was calculated to quantify deviations between digitized and true survival probabilities.Results:The JavaScript script method demonstrated the smallest RMSE across all simulated scenarios(RMSE=1.015×10-4),significantly outperforming the other three methods(P＜0.05),with statistically significant differences observed among methods(P＜0.05).Conclusion:For vector format illustrations,JavaScript scripts enable accurate and robust reverse engineering of Kaplan-Meier curves;for bitmaps,the GetData Graph Digitizer and SurvdigitizeR survival_digitize methods yield more accurate results,and the SurvdigitizeR survival_digitize method is the most efficient.Future research should focus on integrating intelligent algorithms for enhanced robustness and precision in survival data reconstruction.

Objective To explore the effects of the disinfection port position and diameter and disinfectant concentration on the in-situ decontamination of the flow field-based biosafety high efficiency particulate air filter device with the computational fluid dynamics(CFD)method.Methods ANSYS DesignModeler was used to construct five models for the high efficiency particulate air filter device with the disinfection port at the side end in four ones and upper end in the remained one model,with the diameter being 70,100,150,260 and 260 mm respectively;secondly,a standard k-ε turbulence model was applied to simulating the velocity field and concentration field inside the high efficiency particulate air filter device,so as to analyze the influence of the vortex position inside the device and the structure of the device on the disinfection effect and to determine the optimal structure of the device;finally,H2O2 with the concentration of 0.45,0.35 or 0.30 mol/L was selected as the disinectant to investigate the effect of the disinfectant concentration on the disinfection under the optimal device structure.Results Simulation showed that there were vortexes existed the cavity between the filter compression structure and the filter of the high efficiency particulate air filter device.The disinfection effect in case of the disinfection port at the side end was higher than that in case of the disinfection port at the upper end;the diameter of the disinfection port had influences on the disinfection effect,and high-concentration disinfectant was found in the device when the diameter was 100 mm.The optimal structure with the disinfection port at the side end and the diameter of 100 mm was determined for the high efficiency particulate air filter device.An increase in H2O2 concentration was beneficial to improve disinfection without corroding and damaging the device when the in-situ decontamination of the flow field-based biosafety high efficiency particulate air filter device was carried out.Conclusion The characteristics of the internal flow field of the flow field-based biosafety high efficiency particulate air filter device and the influencing factors of the in-situ disinfection effect are revealed,and theoretical references are provided for the optimal design of the device.[Chinese Medical Equipment Journal,2025,46(9):22-27]

Generative artificial intelligence (GAI) represents a prominent research focus in medicine, with medical education being a key application area. GAI demonstrates potential to enhance residency training efficacy through personalized instruction, automated assessment item generation, question bank updating, and intelligent scoring systems. However, current limitations exist regarding output accuracy and content consistency. To address these constraints, strategic measures are required: continuous GAI model refinement, development of standardized usage guidelines, enhanced data quality control, and implementation of human verification protocols for generated content. Concurrently, residents should proactively acquire GAI utilization skills to strengthen the practical application of theoretical knowledge. With these advancements, GAI is anticipated to evolve into a valuable asset for improving the efficiency and quality of residency training programs.

Objective To investigate the factors influencing the occurrence of coma in patients with acute basilar artery occlusion(BAO)and the favorable prognosis in the coma patients after receiving mechanical thrombectomy(MT).Methods The clinical data and imaging materials of 102 patients with acute BAO,who received MT at the First Affiliated Hospital of Soochow University of China from January 2016 to April 2024,were retrospectively analyzed.According to whether the patient had a coma or not on admission,the patients were divided into non-coma group and coma group.The clinical data and imaging findings were compared between the two groups.Multivariate logistic regression analysis was performed to identify the factors influencing the occurrence of coma.The modified Rankin scale(mRS)score was used to evaluate 90-day clinical prognosis.The patients of coma group were further divided into favorable prognosis subgroup(mRS:0-3 points)and poor prognosis subgroup(mRS:4-6 points).Baseline date and surgical data were compared between the two subgroups,and multivariate logistic regression analysis was conducted to identify the factors associated with a favorable prognosis in coma patients after receiving mechanical thrombectomy.Results Of the 102 patients with acute BAO,54 were in unconscious state on admission(coma group)and 48 were in conscious state(non-coma group)on admission.Multivariate logistic regression analysis revealed that coexisting cardiovascular diseases with severe cardiac insufficiency or moderate to severe coronary artery stenosis(P=0.009)and low BATMAN score(P＜0.001)were the independent risk factors for the occurrence of coma in acute BAO patients.Among the 54 unconscious patients who received MT treatment,favorable prognosis was obtained in 13 and poor prognosis was seen in 41.Multivariate logistic regression analysis indicated that high BATMAN score(P=0.017)was the independent influencing factor for favorable prognosis in acute BAO patients with coma after receiving MT therapy.Conclusion Acute BAO patients having coexisting cardiovascular diseases with severe cardiac insufficiency or moderate to severe coronary artery stenosis or having low BATMAN score are more likely to develop coma.Acute BAO patients with coma having high BATMAN score are more likely to obtain a favorable prognosis after receiving MT therapy.

To explore the application effectiveness of generative artificial intelligence(GAI) in the standardized training assessment of critical care medicine residents.