As the core vehicle for preserving and transmitting traditional Chinese medicine（TCM） academic thought and clinical experience， the establishment of a robust quality evaluation system for TCM clinical case reports is a crucial component in the current standardization and modernization of TCM. Based on the practical experience of constructing the China Clinical Cases Library of Traditional Chinese Medicine by the China Association of Chinese Medicine， this study conducted a comprehensive analysis of critical challenges， including insufficient authenticity and unfocused evaluation criteria. It proposed a three-dimensional evaluation framework grounded in the structure-process-outcome logic， encompassing three dimensions of authenticity and standardization， characteristics and advantages， application and translational impact. This framework integrated 12 key evaluation indicators in a systematic manner. The model preserved the academic characteristics of TCM syndrome differentiation and treatment， while aligning with modern scientific research standards， achieving a balance between individualized TCM experience and standardized evaluation. Concurrently， this study provided theoretical foundations and methodological guidance for evaluating the quality of TCM clinical cases， contributing significantly to the inheritance of TCM knowledge， evidence-based practice， and the reform of talent evaluation mechanisms.

Background: Despite the fact that an increasing number of studies have focused on developing therapies for acute lung injury, managing acute respiratory distress syndrome (ARDS) remains a challenge in intensive care medicine.Whether the pathology of animal models with acute lung injury in prior studies differed from clinical symptoms of ARDS, resulting in questionable management for human ARDS. To evaluate precisely the therapeutic effect of trans‑ planted stem cells or medications on acute lung injury, we developed an animal model of severe ARDS with lower lung function, capable of keeping the experimental animals survive with consistent reproducibility. Establishing this animal model could help develop the treatment of ARDS with higher efficiency. Results: In this approach, we intratracheally delivered bleomycin (BLM, 5 mg/rat) into rats’ left trachea via a needle connected with polyethylene tube, and simultaneously rotated the rats to the left side by 60 degrees. Within sevendays after the injury, we found that arterial blood oxygen saturation ­(SpO2 ) significantly decreased to 83.7%, partial pressure of arterial oxygen ­(PaO2 ) markedly reduced to 65.3 mmHg, partial pressure of arterial carbon dioxide ­(PaCO2 )amplified to 49.2 mmHg, and the respiratory rate increased over time. Morphologically, the surface of the left lung appeared uneven on Day 1, the alveoli of the left lung disappeared on Day 2, and the left lung shrank on Day 7. A his‑ tological examination revealed that considerable cell infiltration began on Day 1 and lasted until Day 7, with a larger area of cell infiltration. Serum levels of IL-5, IL-6, IFN-γ, MCP-1, MIP-2, G-CSF, and TNF-α substantially rose on Day 7. Conclusions This modified approach for BLM-induced lung injury provided a severe, stable, and one-sided (left-lobe) ARDS animal model with consistent reproducibility. The physiological symptoms observed in this severe ARDS animal model are entirely consistent with the characteristics of clinical ARDS. The establishment of this ARDS animal model could help develop treatment for ARDS.

Geraniin, a polyphenol derived from the fruit peel of Nephelium lappaceum L., has been shown to possess anti-inflammatory and antioxidant properties in the cardiovascular system. The present study explored whether geraniin could protect against an isoproterenol (ISO)-induced cardiac hypertrophy model. Mice in the ISO group received an intraperitoneal injection of ISO (5 mg/kg) once daily for 9 days, and the administration group were injected with ISO after 5 days of treatment with geraniin or spironolactone. Potential therapeutic effects and related mechanisms analysed by anatomical coefficients, histopathology, blood biochemical indices, reverse transcription-PCR and immunoblotting. Geraniin decreased the cardiac pathologic remodeling and myocardial fibrosis induced by ISO, as evidenced by the modifications to anatomical coefficients, as well as the reduction in collagen I/III á1mRNA and protein expression and cross-sectional area in hypertrophic cardiac tissue. In addition, geraniin treatment reduced ISO-induced increase in the mRNA and protein expression levels of interleukin (IL)-6, IL-1β and tumor necrosis factor-α, whereas ISO-induced IL-10 showed the opposite behaviour in hypertrophic cardiac tissue.Further analysis showed that geraniin partially reversed the ISO-induced increase in malondialdehyde and nitric oxide, and the ISO-induced decrease in glutathione, superoxide dismutase and glutathione. Furthermore, it suppressed the ISO-induced cellular apoptosis of hypertrophic cardiac tissue, as evidenced by the decrease in Bcell lymphoma-2 (Bcl-2)-associated X/caspase-3/caspase-9 expression, increase in Bcl-2 expression, and decrease in TdT-mediated dUTP nick-end labeling-positive cells.These findings suggest that geraniin can attenuate ISO-induced cardiac hypertrophy by inhibiting inflammation, oxidative stress and cellular apoptosis.

Purpose: Cancer has become a significant major public health concern, making the discovery of new cancer markers or therapeutic targets exceptionally important. Elevated expression of tumor necrosis factor receptor superfamily member 12A (TNFRSF12A) expression has been observed in certain types of cancer. This project aims to investigate the function of TNFRSF12A in tumors and the underlying mechanisms. Materials and Methods: Various websites were utilized for conducting the bioinformatics analysis. Tumor cell lines with stable knockdown or overexpression of TNFRSF12A were established for cell phenotyping experiments and subcutaneous tumorigenesis in BALB/c mice. RNA-seq was employed to investigate the mechanism of TNFRSF12A. Results: TNFRSF12A was upregulated in the majority of cancers and associated with a poor prognosis. Knockdown TNFRSF12A hindered the colorectal cancer progression, while overexpression facilitated malignancy both in vitro and in vivo. TNFRSF12A overexpression led to increased nuclear factor кB (NF-κB) signaling and significant upregulation of baculoviral IAP repeat containing 3 (BIRC3), a transcription target of the NF-κB member RELA, and it was experimentally confirmed to be a critical downstream factor of TNFRSF12A. Therefore, we speculated the existence of a TNFRSF12A/RELA/BIRC3 regulatory axis in colorectal cancer. Conclusion TNFRSF12A is upregulated in various cancer types and associated with a poor prognosis. In colorectal cancer, elevated TNFRSF12A expression promotes tumor growth, potentially through the TNFRSF12A/RELA/BIRC3 regulatory axis.

Objective To control the stepwise release of vascular endothelial growth factor A(VEGF-A)within the microcapsules,and to analyze the effects of the microcapsules on cellular angiogenic capability.Methods VEGF-A encapsulated poly(lactic-co-gly-colic acid)(PLGA)microcapsules were prepared using a method combining dual-channel coaxial injection and continuous flow technol-ogy.The release and degradation performance of the microcapsules were characterized using a phosphate-buffered saline(PBS)soaking method.The biocompatibility of the microcapsules was assessed through the CCK-8 method and Calcein-AM/PI staining method.The impact of microcapsule extract on cellular angiogenesis ability was examined by conducting cell scratch assays and tubule formation ex-periments.Results The microcapsules were round in shape,with their particle diameter measuring in the range of hundreds of mi-crometers.Microcapsules with a molecular weight(Mw)-12 ku can release a large amount of VEGF-A in the initial phase,while Mw-30 ku ones had the capacity to provide a stable,long-term,low-dose release of VEGF-A.Microcapsules of Mw-12 ku exhibited outstanding potential for enhancing the healing of cell scratch wounds in the initial phase.Moreover,within the 0-12 day period,the two types of microcapsule extracts significantly enhanced the ability of cells to form tubules in vitro.Conclusion This study successfully regulated the release profile of VEGF-A by adjusting the molecular weight of PLGA,achieving an initial rapid and substantial release of VEGF-A followed by a sustained slow release over time,while maintaining its biological activity throughout the process.

Objective To observe the value of 18F-prostate specific membrane antigen(PSMA)-1007 PET/MRI for diagnosing seminal vesicle invasion(SVI)of prostatic cancer(PCa).Methods Totally 92 male patients with PCa who underwent radical prostatectomy were retrospectively enrolled and divided into positive group(n=26)and negative group(n=66)based on postoperative pathology showed SVI or not.PET/MRI parameters,including maximum standard uptake value(SUVmax),minimum apparent diffusion coefficient(ADCmin),mean apparent diffusion coefficient(ADCmean),SUVmax/ADCmin,SUVmax/ADCmean,PSMA tumor volume(PSMA-TV)and total lesion PSMA(TL-PSMA)were compared between groups.The receiver operating characteristic curve was drawn,and the efficacy of each parameter for diagnosing SVI was analyzed.Results Among 92 cases of PCa,18F-PSMA-1007 PET/MRI showed 30 cases with SVI and 62 cases without SVI,with accuracy of 73.91％,sensitivity of 61.54％,specificity of 78.79％,positive predictive value of 53.33％and negative predictive value of 83.87％.Significant differences of ADCmin,PSMA-TV and TL-PSMA were found between groups(all P＜0.05).The area under the curve(AUC)of SUVmax,ADCmin,ADCmean,SUVmax/ADCmin,SUVmax/ADCmean,PSMA-TV and TL-PSMA for diagnosing SVI of PCa was 0.554,0.341,0.396,0.603,0.581,0.755 and 0.705,respectively.The AUC of PSMA-TV was higher than other parameters except for TL-PSMA,with sensitivity of 84.60％and specificity of 56.10％.Conclusion 18 F-PSMA-1007 PET/MRI was helpful for diagnosing SVI of PCa.

In January 2023, a patient with soft tissue degloving defect of right index, middle, ring and little fingers was treated in the Department of Hand Surgery, Suzhou Ruihua Orthopaedic Hospital. Seven free flaps from a leg were harvested to reconstruct the defected wound of fingers in primary surgery. Flap thinning and plastic surgery were performed in stage-II surgery. Over the 22 months of postoperative follow-up, the flaps in right index, middle, ring and little fingers survived well with the colour and texture close to proximal skin. There was no obvious swelling of the flaps and sensation of the flaps recovered to S 3. The donor sites healed well and the donor leg walked normally.

Objective To develop and validate a machine learning-based predictive model to assess the in-hospital mortality risk of patients with myocardial infarction(MI)complicated by heart failure(HF)undergoing percutaneous coronary intervention(PCI).Methods This retrospective study analyzed MI patients with HF who underwent PCI at The First Affiliated Hospital of Xinjiang Medical University from January 2019 to January 2023.Patient data,including demographic characteristics,vital signs,laboratory test results,imaging parameters and medication use,were collected and randomly divided into a training set(70％)and a validation set(30％).The extreme gradient boosting(XGBoost)model was used to identify variables significantly associated with in-hospital mortality,and the Shapley additive explanations(SHAP)model was applied to assess feature importance.A predictive model was then constructed using univariate and multivariate Logistic regression analyses.Model performance was evaluated using receiver operating characteristic(ROC)curves,area under the curve(AUC)values,calibration curves,and decision curve analysis.Finally,a nomogram was developed for intuitive risk assessment.Results A total of 1 214 MI patients with HF were included in the study,with a median age of 64 years.The in-hospital mortality rate was 7.41％(90 deaths).XGBoost feature selection identified ten key predictive variables:age,myoglobin,albumin,fasting blood glucose,N-terminal pro-B-type natriuretic peptide(NT-proBNP),diabetes mellitus,creatinine,cystatin C,procalcitonin,and left ventricular ejection fraction.Based on these variables,a Logistic regression model was developed,with seven final predictors:age,diabetes mellitus,creatinine,fasting blood glucose,cystatin C,NT-proBNP,and albumin.The model demonstrated high predictive accuracy,with AUC value of 0.869(95％CI:0.84-0.89)in the training set and 0.827(95％CI:0.79-0.85)in the validation set.The calibration curve indicated that the predicted probabilities were consistent with the actual observed outcomes,and decision curve analysis showed that the model had a high net benefit across various decision thresholds.Conclusion This study developed a machine learning-based predictive model incorporating Logistic regression to assess the in-hospital mortality risk of MI patients with HF undergoing PCI.The model demonstrated high predictive performance and clinical utility.The nomogram derived from this model provides an intuitive tool for individualized risk assessment,aiding clinicians in the early identification of high-risk patients,optimizing intervention strategies,and improving patient outcomes.

Objective To construct and validate machine learning-based models to predict the risk of acute kidney injury(AKI)following percutaneous coronary intervention(PCI)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 2 315 STEMI patients who underwent PCI between January 2020 and June 2023 were included;306(13.2％)of them developed AKI.Baseline variables were screened using LASSO regression,with the optimal λ value selected via 10-fold cross-validation to identify AKI-associated features.Subsequently,eight distinct machine learning models were constructed and evaluated for their predictive performance.SHAP value analysis was employed to assess the impact of key variables on model predictions.Results LASSO regression identified seven variables significantly associated with AKI,including age,multivessel disease,preoperative creatinine,heart failure,white blood cell count,hemoglobin,and albumin levels.Among all the models,the light gradient boosting machine(LGBM)and extreme gradient boosting(XGB)demonstrated the best predictive performance,with training set AUCs being 0.899(95％CI:0.877-0.921)and 0.893(95％CI:0.868-0.918),and validation set AUCs being 0.809(95％CI:0.763-0.856)and 0.871(95％CI:0.833-0.909),respectively.SHAP analysis revealed that albumin,age,preoperative creatinine,and white blood cell count were the primary contributors to AKI risk.Conclusion This study successfully developed and validated machine learning-based predictive models capable of effectively identifying the risk of AKI following PCI in STEMI patients,thus providing valuable support for clinical decision-making.

In January 2023, a patient with soft tissue degloving defect of right index, middle, ring and little fingers was treated in the Department of Hand Surgery, Suzhou Ruihua Orthopaedic Hospital. Seven free flaps from a leg were harvested to reconstruct the defected wound of fingers in primary surgery. Flap thinning and plastic surgery were performed in stage-II surgery. Over the 22 months of postoperative follow-up, the flaps in right index, middle, ring and little fingers survived well with the colour and texture close to proximal skin. There was no obvious swelling of the flaps and sensation of the flaps recovered to S 3. The donor sites healed well and the donor leg walked normally.