OBJECTIVE To introduce the development of an intelligent prescription review decision-support system for anti-tumor drugs and assess its clinical application outcomes. METHODS Relevant data sources， including national and local pharmaceutical administration policies， clinical practice guidelines/consensus， hospital information systems data， and genetic testing results， were integrated. Adhering to the principles of structure， standardization and dynamic updating， a knowledge base covering chemotherapeutic， targeted and immunotherapeutic agents was constructed using a dual-dimensional modeling approach that combined “drug attributes” and “clinical contexts”. This knowledge base was then embedded into the hospital’s electronic medical order system to establish the prescription review decision-support system. The application and performance of the system were evaluated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS A knowledge base containing 18 318 prescription review rules for anti-tumor drugs was constructed， and a closed-loop prescription review system was successfully established， encompassing pre-prescription real-time intervention， in-process interactive review， and post-prescription evaluation and analysis. From 2021 to 2024， the system generated a total of 57 879 alerts for prescriptions of five typical categories of anti-tumor drugs. For platinum-containing prescriptions， 22 577 alerts were generated， with Cisplatin for injection （lyophilized） being the most frequently alerted drug （13 445 alerts）， and “ototoxicity risk due to combined use” alerts remained high （7 682 alerts）. For methotrexate-containing prescriptions， 3 721 alerts were recorded， primarily related to “precaution-related issues” （76.4%， 2 843/3 721）. For doxorubicin-containing prescriptions， 17 301 alerts were triggered， primarily related to “dosage and administration” （14 315 alerts）. For human epidermal growth factor receptor 2-targeted agents-containing prescriptions， 1 007 alerts were issued， mostly related to “reimbursement restrictions” （956 alerts）. For programmed death-1/programmed death-ligand 1 inhibitors-containing prescriptions， the alerts increased year by year， totaling 13 273 alerts， primarily related to “inappropriate indication” （9 118 alerts）. Over the 4 years， the physician response rates to system alerts were 21.4%， 27.1%， 33.5% and 51.6%， respectively. CONCLUSIONS An intelligent decision-support system for anti-tumor drug prescription review， encompassing a closed-loop process of “real-time pre-event intervention， interactive in-event prescription review， post-event evaluation and analysis”， has been successfully constructed and implemented throughout the entire workflow. There is a discernible trend in this hospital， where the focus on monitoring anti-tumor drugs is shifting towards immunotherapy drugs. Additionally， the acceptance rate of physicians regarding prescription review opinions has been steadily increasing year by year.

Stroke is one of the leading causes of disability and mortality worldwide. Research into its mechanisms and the development of therapeutic strategies heavily rely on animal models that accurately replicate the pathological features of human disease. An ideal animal model for stroke should not only reproduce the neurological deficits and pathological changes observed in clinical patients but also demonstrate good reproducibility and translational value. This review focuses on the preparation and evaluation methods of ischemic stroke animal models. Firstly, it elaborates on the selection criteria, advantages, and disadvantages of experimental animals, including rodents (rats, mice) and non-rodents (non-human primates, miniature pigs, rabbits, zebrafish). Secondly, it provides a detailed overview of the modeling principles, key procedures, and application scopes for ischemic stroke models and hemorrhagic stroke models. Furthermore, the review summarizes advances in the applications of emerging technologies—including gene editing [e.g., clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) gene editing], multimodal imaging (e.g., two-photon microscopy, photoacoustic imaging), artificial intelligence, optogenetics, 3D bioprinting, organoid models, and multi-omics–in model optimization, precise assessment, and mechanistic investigation. Finally, based on a systematic analysis of relevant domestic and international literature from 2019 to 2024, this review discusses model selection strategies based on research objectives, a multidimensional evaluation system encompassing behavioral, imaging, and molecular pathological assessments, and envisions future directions involving technological integration to achieve model precision and individualization. This article aims to provide a comprehensive methodological reference to help researchers select appropriate animal models of stroke according to specific scientific questions.

Objective: To evaluate the diagnostic performance of magnetic resonance spectroscopy (MRS) in discriminating fumarate hydratase-deficient (FH-d) uterine leiomyomas (ULs) from FH-preserved ULs. Materials and Methods: This study consisted of three stages, with independent cohorts recruited for each stage: 1) sample-size estimation was retrospectively performed on UL specimens (diameter ≥3 cm; age, 20–40 years) from our database with immunohistochemistry (IHC) for 2-succinocysteine (2-SC) as the reference, without genetic testing, 2) MRS sequence optimization in confirmed FH germline mutation participants with ultrasound-detected ULs (diameter ≥3 cm), without IHC analysis, and 3) prospective diagnostic test accuracy was evaluated in consecutive participants with ultrasound-detected ULs (diameter ≥3 cm;age, 20–40 years), using IHC for 2-SC for determining the FH status and subsequent genetic testing in those with positive 2-SC results to identify whether FH mutations were germline or somatic in origin. The choline and fumarate peaks in MRS were classified as positive, negative, or technical failure (TF). TFs were analyzed separately and excluded from the primary diagnostic accuracy calculations. T1-, T2-, and diffusion-weighted images were interpreted as hyperintense or hypointense. The enhancement rate and apparent diffusion coefficient were also acquired. Diagnostic performance was compared between MRS and various magnetic resonance imaging (MRI) features. Results: The optimal MRS parameters for the fumarate peak were echo time (TE) = 140 ms and an average of 256. Among the 360 prospective participants, 37 were confirmed to have FH-dULs. MRS showed positive fumarate peaks in 35 of 37 FH-dULs.After excluding six TFs, the positive fumarate peak on MRS showed 94.6% (35/37) sensitivity, 99.7% (316/317) specificity, and 99.2% (351/354) accuracy, all of which were significantly superior to those of other MRI features (P ≤ 0.002). Conclusion A positive fumarate peak on MRS may be a useful imaging biomarker for diagnosing FH-dULs.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

The recombinant human thyroid-stimulating hormone (rhTSH) can be used for differentiated thyroid cancer (DTC) preparation before ¹³¹I therapy, and follow-up. Since its approval by the American Food and Drug Administration (FDA) in 1998, rhTSH has been clinically used in European countries, the United States, and other countries for nearly 30 years. In April 2024, China’s first independently developed rhTSH agent was approved. Based on clinical experience and evidence from domestic and international studies, an expert consensus on the application of rhTSH has been developed following thorough consultations among experts. The consensus offers evidence-based recommendations to guide the appropriate use of rhTSH in clinical practice.

Objective:To retrospectively analyse the clinical data of patients after NUSS procedure for pectus excavatum, and summary of surgical techniques for NUSS bar removal.Methods:Retrospectively collected the clinical data of 276 patients undergoing NUSS bar removal from January 2024 to September 2024 in Beijing Children's Hospital affiliated to Capital Medical University. The age of the patients ranged from 6 to 20 years old, 211 males and 65 females. The average time the bar was in place in the body was 36 months.Results:All 276 patients successfully completed the NUSS bar removal. The average operative time was 22.6 min, with an average blood loss of 3.3 ml. 90 patients with bone scabs, 104 patients with wire breakage were successfully removed. 2 cases of postoperative wound infection, no other intraoperative and postoperative complications. The average hospitalization time after surgery was 1.2 days. Follow up for 3 months after surgery, and no abnormalities were found on the chest X-ray.Conclusion:Mastering the surgical techniques for pectus excavatum bar removal enhances the safety and efficiency of the procedure. It effectively reduces the incidence of intraoperative and postoperative complications, shortens operative time, and alleviates postoperative pain in patients.

OBJECTIVE To construct a predictive tool for surgical site infections(SSIs)in spinal surgery for Chi-nese population to provide evidence support for reducing SSIs.METHODS A systematic review of Chinese and English database literature was conducted for Meta-analysis to obtain pooled risk values for influencing factors,and a risk prediction scoring tool was constructed based on the logistic regression model.Patients who underwent spinal surgery and completed postoperative follow-up in a tertiary hospital in Beijing from Jan.to Dec.2021 were selected to validate the predictive effect of the tool.RESULTS The predictive model for SSIs in Chinese spinal sur-gery patients was Logit(P)=—3.47+0.63(age 60 years)+0.31 ×(patient with cardiovascular disease)+0.69 ×(rheumatoid arthritis)+1.07 ×(diabetes)+1.06 ×(operation duration＞3 h)+1.17 ×(preopera-tive albumin＜35 g/L)+0.71 ×(history of spinal surgery)+0.67 ×(carrying internal implants)+0.73 ×(blood transfusion).The total score of the predictive tool was 92,with a cutoff score of≥24.50 indicating high-risk individuals.The area under the curve was 0.733,with the sensitivity 58.30％and the specificity 79.60％.CONCLUSION The established predictive model for SSIs in Chinese spine surgery demonstrates good predictive performance and can be used as a reference assessment tool in clinical practice.

AIM To explore the relieving effect of Er Miao Wan on atopic dermatitis in mice.METHODS In vivo experiment:BALB/c mice were randomly divided into normal group,model group,dexamethasone group(2 mg/kg)and high,medium and low dose groups of Er Miao Wan(4.68,2.34 and 1.17 g/kg).The mouse model of atopic dermatitis was established by repeatedly smearing DNCB solution,and the model was given orally for 21 days.The skin lesion condition on the back of mice,ear swelling degree,and the weight difference between ear lobes were observed and recorded.HE staining was used to observe the histopathological changes in the skin lesion tissues of mice.Toluidine blue(TB)staining was used to observe the infiltration of mast cells in skin lesions.The expression of macrophage marker F4/80 in skin lesions was detected by IHC.The serum levels of TSLP,IL-4,IL-5 and total IgE were detected by ELISA.In vitro experiment:RAW264.7 cells in logarithmic growth period were given 400,200 and 100 μg/mL Er Miao Wan for intervention.Cell proliferation was detected by CCK-8 method.NO level in cell supernatant was detected by Griess method.TNF-α,IL-1 β and IL-6 levels in cell supernatant were detected by ELISA method.The expressions of proteins related to the MAPK/NF-κB signaling pathway in cells was detected by Western blot.RESULTS In vivo experiment:Compared with the model group,the scores of back skin lesions,the swelling degree of right ear and the weight difference between left and right ear pieces in the high-dose group of Er Miao Wan decreased(P＜0.05,P＜0.01),the thickness of skin lesions decreased,the infiltration of mast cells and macrophages decreased(P＜0.05,P＜0.01),and the inflammatory factors TSLP,IL-4,IL-5 and total IgE levels in serum decreased(P＜0.05,P＜0.01),and the expression of F4/80 in the skin lesions decreased(P＜0.01).In vitro experiment:Compared with the model group,the levels of NO,TNF-α,IL-1 β and IL-6 in Er Miao Wan 400 and 200 μg/mL groups decreased(P＜0.05,P＜0.01),and the phosphorylation levels of P38,JNK and P65 proteins decreased(P＜0.05,P＜0.01).CONCLUSION Er Miao Wan can alleviate skin lesion inflammation in DNCB-induced atopic dermatitis mice,and its mechanism may be related to inhibiting the activation of MAPK/NF-κB signaling pathway of macrophage,reducing macrophage infiltration and reducing Th2 cytokines.

Objective To compare the diagnostic performance of three breast MRI measurement methods—RECIST 1.1,the optimal method,and three-dimensional(3D)volumetric assessment—in assessing the efficacy of neoadjuvant chemotherapy(NAC)in breast cancer patients,with the objective of identifying the most clinically practical approach.Methods A total of 110 breast cancer patients who underwent NAC followed by surgical treatment between 2019 and 2023 were included in the study.Breast magnetic resonance imaging(MRI)was conducted within one week before and after the completion of NAC.Tumor response was evaluated using RECIST 1.1 criteria,widely recognized as the optimal method,as well as 3D volume measurement.Pathological response was determined according to the Miller-Payne grading system.Sensitivity,specificity,accuracy,and the area under the receiver operating characteristic curve(AUC)were computed and compared using the DeLong test.Results The AUC values for RECIST 1.1,the optimal method,and 3D volumetric assessment were 0.768,0.795,and 0.883,respectively.The 3D volumetric assessment exhibited significantly better discriminative performance(P＜0.05),with the highest sensitivity(98.9％),specificity(77.8％),and accuracy(95.5％).Additionally,the optimal method demonstrated superior performance over RECIST 1.1 across multiple parameters.Conclusions 3D volumetric mea-surement demonstrates superior performance compared to RECIST 1.1 and the optimal method in evaluating the response to NAC,offering a more accurate and comprehensive assessment tool.Additionally,the optimal method shows advantages over RECIST 1.1 and may serve as a practical alternative in settings where 3D software is not available.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.