ObjectiveTo develop and validate a diagnostic prediction model for differentiating pulmonary tuberculosis from community-acquired pneumonia based on routine blood parameters. MethodsA total of 642 patients with pulmonary tuberculosis and 503 patients with community-acquired pneumonia were retrospectively enrolled from the Seventh Hospital of Tangshan. They were randomly divided into a training set and an internal validation set at a 7∶3 ratio. Additionally， 218 patients from the 981st Hospital were independently included as an external validation set. The Boruta algorithm and recursive feature elimination were employed to select predictors from 82 blood parameters， sex， and age. A multivariate Logistic regression model was established and evaluated using receiver operating characteristic （ROC） curves， calibration curves， and decision curve analysis. ResultsThe final model incorporated eight predictors， namely uric acid， urea nitrogen， alkaline phosphatase， monoamine oxidase， alanine aminotransferase， glutathione， neutrophil percentage， and age. The model achieved areas under the curve （AUCs） of 0.800 （95%CI： 0.769-0.830）， 0.787 （95%CI： 0.738-0.836）， and 0.736 （95%CI： 0.667-0.835） in the training， internal validation， and external validation sets， respectively. The model demonstrated good calibration， and decision curve analysis showed clinical net benefit within the threshold probability range of 10%-80%. ConclusionThe developed model exhibits good discriminative ability and clinical utility， serving as an effective early screening tool for primary healthcare institutions.

ObjectiveTo observe the clinical efficacy and possible mechanisms of Xianglian Huazhuo Granules （香连化浊颗粒， XHG） in the treatment of chronic atrophic gastritis with intestinal metaplasia. MethodsA total of 140 patients with chronic atrophic gastritis and intestinal metaplasia were randomly divided into a treatment group and a control group， with 70 cases in each group. The treatment group received 12.5 g of XHG orally， twice daily. The control group received 12.5 g of placebo orally， twice daily. Both groups were treated for 6 months. The traditional Chinese medicine （TCM） symptom scores， pathological types， serum tumor markers of the digestive system， and serum bile acids （TBA）， interleukin-23 （IL-23）， and Dickkopf-related protein 1 （DKK-1） levels were observed before and after treatment. Safety indicators and adverse events were recorded. After treatment， TCM syndrome efficacy and pathological types were evaluated， and patients were followed up for 18 months with gastric endoscopy and pathological results， which were compared with the results after treatment finished. ResultsTwo patients dropped out in the control group， and a total of 168 cases were included in the final analysis， 70 in the treatment group and 68 in the control group. The treatment group showed a significant reduction in TCM symptom scores， serum TBA， IL-23， and DKK-1 levels， and a significant increase in alpha-fetoprotein （AFP）， carbohydrate antigen 125 （CA125）， carbohydrate antigen 199 （CA199） levels； in the control group， carcinoembryonic antigen （CEA）， CA125， CA199 levels significantly increased （P＜0.05 or P＜0.01）； and carbohydrate antigen 242 （CA242） level in both the treatment group and the control group decreased significantly （P＜0.01）. The treatment group had lower TCM symptom scores and lower levels of serum TBA， IL-23， and DKK-1 compared to the control group （P＜0.05）. The effective rate for TCM syndrome efficacy in the treatment group was 80.00% （56/70）， significantly higher than the 20.59% （14/68） in the control group （P < 0.05）. The effective rate for pathological classification in the treatment group was 72.73% （8/11） for mixed intestinal metaplasia， significantly better than 46.15% （6/13） in the control group （P＜0.05）. No adverse events were reported in either group. Among 40 patients who had a follow-up endoscopy after one year， 21 were from the treatment group， of whom 11 showed reduced intestinal metaplasia， 9 showed no significant changes， and 1 had worsened； while 19 patients in the control group had 4 with reduced intestinal metaplasia， 13 with no significant changes， and 2 with worsened conditions. No cancer was detected in either group. The treatment group showed significantly better improvement in intestinal metaplasia on follow-up gastric endoscopy pathology than the control group （P＜0.05）. ConclusionXHG can significantly improve the clinical symptoms in patients with chronic atrophic gastritis and intestinal metaplasia and reduce the degree of mixed intestinal metaplasia. The mechanism may involve lowering serum TBA， DKK-1， and IL-23 levles， thus delaying the progression from inflammation to cancer.

In current clinical practice, various dermal templates and skin substitutes are used to enhance wound healing. However, the role of wound commensal microbiome in regulating scaffold performance and the healing process remains unclear. In this study, we investigated the influence of both natural and synthetic scaffolds on the wound commensal microbiome and wound repair in three distinct models including diabetic wounds, burn injuries, and germ-free (GF) wounds. Remarkably, synthetic electrospun polycaprolactone (PCL) scaffolds were observed to positively promote microbiome diversity, leading to enhanced diabetic wound healing compared to the natural scaffolds Integra® (INT) and MatriDerm® (MAD). In contrast, both natural and synthetic scaffolds exhibited comparable effects on the diversity of the microbiome and the healing of burn injuries. In GF wounds with no detectable microorganisms, a reversed healing rate was noted showing natural scaffold (MAD) accelerated wound repair compared to the open or the synthetic scaffold (PCL) treatment. Furthermore, the response of the wound commensal microbiome to PCL scaffolds appears pivotal in promoting anti-inflammatory factors during diabetic wound healing. Our results emphasize that the wound commensal microbiome, mediated by different scaffolds plays an important role in the wound healing process.

Triple-negative breast cancer (TNBC) is a highly aggressive malignancy predominantly managed via chemotherapy. Our clinical sample analysis revealed a significant correlation between elevated CD24 expression in TNBC tumor cells and patient survival rates. We developed a novel antibody-drug conjugate (ADC), named HN03, consisting of an antibody with engineered cysteines for site-specific conjugation with a low toxic nitric oxide (NO) precursor as its payload through a novel Pt(IV)-mediated bioorthogonal self-cleavable linker. HN03 specifically targets tumor cells expressing high levels of CD24, concurrently generating cisplatin and releasing NO upon activation. HN03 also exhibited potent in vitro and in vivo antitumor activity. It significantly reduced tumor growth at various doses, prevented tumor metastasis, with markedly lower toxicity than traditional chemotherapy agents. We found that a key mechanism of its action involved inducing apoptosis and endoplasmic reticulum stress, substantially decreasing the number of M2-type macrophages. Overall, HN03 stands out as a promising therapeutic option for TNBC, offering a targeted treatment with reduced side effects and the potential for improved outcomes. Furthermore, using Pt(IV) in the linker and an NO precursor as the payload enhances the versatility of the Antibody-NO donor Conjugate (ANC), offering new avenues for the design of the next generation of ADCs.

OBJECTIVES: To construct an intelligent analysis model for classifying fetal orientation during intrapartum ultrasound videos based on multi-feature fusion. METHODS: The proposed model consists of the Input, Backbone Network and Classification Head modules. The Input module carries out data augmentation to improve the sample quality and generalization ability of the model. The Backbone Network was responsible for feature extraction based on Yolov8 combined with CBAM, ECA, PSA attention mechanism and AIFI feature interaction module. The Classification Head consists of a convolutional layer and a softmax function to output the final probability value of each class. The images of the key structures (the eyes, face, head, thalamus, and spine) were annotated with frames by physicians for model training to improve the classification accuracy of the anterior occipital, posterior occipital, and transverse occipital orientations. RESULTS: The experimental results showed that the proposed model had excellent performance in the tire orientation classification task with the classification accuracy reaching 0.984, an area under the PR curve (average accuracy) of 0.993, and area under the ROC curve of 0.984, and a kappa consistency test score of 0.974. The prediction results by the deep learning model were highly consistent with the actual classification results. CONCLUSIONS The multi-feature fusion model proposed in this study can efficiently and accurately classify fetal orientation in intrapartum ultrasound videos.
Humans ; Female ; Ultrasonography, Prenatal/methods* ; Pregnancy ; Fetus/diagnostic imaging* ; Neural Networks, Computer ; Video Recording

Objective:The minimal ablative margin (MAM) after radiofrequency ablation (RFA) was evaluated based on magnetic resonance imaging (MRI) image registration to analyze its effect on the prognosis of patients with hepatocellular carcinoma (HCC).Methods:Clinical data of 120 patients with HCC undergoing RFA in the General Hospital of Ningxia Medical University from January 2017 to April 2022 were retrospectively analyzed, including 88 males and 32 females, aged (58.4±8.5) years. The enhanced MRI images of patients before and after treatment were imported into a 3D Slicer software to show the ablative margin, and patients were divided into two groups according to whether MAM exceeded the peritumor safety boundary of 5 mm: MAM<5 mm group ( n=75) and MAM≥5 mm group ( n=45). Clinical data were recorded such as gender, age, tumor length and location. Patients were followed up by outpatient review to record whether local tumour progression occurred. Kaplan-Meier method was used for survival analysis, and log-rank test was used for survival comparison. Cox regression analysis was performed to analyze the risk factors of local tumour progression after RFA in patients with HCC. Results:There were significant differen-ces in tumor volume, whether the tumor is located around the vessels, and the mode of RFA guidance between the two groups (all P<0.05). The cumulative local tumour progression-free survival rates at 6, 12 and 24 months after RFA were 100%, 100% and 98% in MAM ≥5 mm group, superior to those in MAM<5 mm group (92%, 84% and 69%, respectively, χ2=47.22, P<0.001). Multivariate Cox regression analysis showed that MAM<5 mm ( OR=9.992, 95% CI: 4.358-22.913), tumor diameter ≥2 cm ( OR=1.758, 95% CI: 1.025-3.015) and perivascular tumor ( OR=2.344, 95% CI: 1.379-3.985) were risk factors for local tumour progression after RFA in patients with HCC (all P<0.05). Conclusion:The MAM evaluated based on MRI image registration is an influential factor on prognosis of patients with HCC. Patients with MAM<5 mm suffer an increased risk of postoperative local tumour progression.

Objective:To construct a prediction model for local tumor progression (LTP) in patients with hepatocellular carcinoma (HCC) after radiofrequency ablation (RFA) based on the radiomics features of enhanced MRI.Methods:Clinical data of 120 patients with HCC undergoing RFA in the General Hospital of Ningxia Medical University from June 2017 to June 2022 were retrospectively analyzed, including 90 males and 30 females, aged (58.2±8.2) years. The patients were divided into training set ( n=84) and validation set ( n=36) in a ratio of 7∶3. According to whether LTP occurred within 2 years after RFA, the patients in training set were divided into LTP positive group ( n=32) and LTP negative group ( n=52). Logistic regression analysis was performed to analyze the risk factors for LTP after RFA in patients with HCC in training set. In the advanced arterial phase of preoperative enhanced MRI, the region of interest of tumor and peritumoral 5 mm area were mapped, and the radiomics features were extracted. The maximum correlation-minimum redundancy algorithm, the minimum absolute value shrinkage and selection operator algorithm were used to screen the radiomics features closely related to LTP, and the radiomics score was established. A nomogram model was constructed by combining the radiomics score with clinical tumor characteristics. The predictive performance and clinical practical value of different models were compared by the area under the receiver operating characteristic curve, calibration curve, clinical decision curve analysis (DCA) and clinical impact curve (CIC). Results:Tumor located around the blood vessels ( OR=4.574, 95% CI: 1.454-14.393, P=0.009) and ablation margin <5 mm ( OR=5.724, 95% CI: 1.996-16.420, P=0.001) were independent risk factors for LTP in patients with HCC after RFA. Five higher-order radiomics features were extracted and screened, including three tumoral features (glrlm_ShortRunHighGrayLevelEmphasis, ngtdm_Complexity and glcm_Imc1) and two peritumoral features (firstorder_Mean and glszm_SmallAreaHighGrayLevelEmphasis). Delong test showed that the area under curve of the combined model was higher than that of the radiomics model ( Z=2.90, P=0.004) and the clinical tumor characteristic model ( Z=2.56, P=0.010). Calibration curves, DCA and CIC curves all show that the combined model had a better clinical net benefit. Conclusion:Combining the radiomics features extracted from enhanced MRI images with clinical tumor characteristics can effectively predict the risk of LTP in patients with HCC after RFA.

The in-depth research of artificial intelligence in the medical field has greatly improved the workflow and diagnostic ability of diagnostic radiology.This article focuses on artificial intelligence technology in the field of interventional medicine,and enumerates its potential application scenarios,including improving image analysis capabilities to assist diagnosis and predict treatment response.It also describes the challenges that need to be overcome for practical application.Finally,with the continuous development of artificial intelligence in interventional medicine,artificial intelligence will further optimize the channels of interventional medicine and bring revolutionary changes to the clinical practice of interventional medicine.

Objective:To investigate the protection effect of a new 360-degree radiation protection and position fixation device on the pelvic cavity during chest CT examination.Methods:Three shielding methods were applied to the pelvic cavity of the standard simu-lated human model,i.e.,no shielding(group A),traditional 180-degree front protection with a lead square towel(group B),and 360-degree protection with a new protection device(group C).Philips IQon Spectral CT was used to perform chest CT scan at a tube voltage of 80 kVp,100 kVp,and 120 kVp,respectively,and the cumulative radiation doses from the front,side,and back of the pelvic cavity were measured and analyzed statistically.Results:Compared with groups A and B,group C had significantly lower cumulative radiation doses of the front,side,and back of the pelvic cavity in the simulated human model(all P<0.05);at the tube voltages of 80,100,and 120 kVp,the cumulative dose of the pelvic cavity in group C was reduced by 85%,84%,and 67%,respectively,compared with that in group B,and was reduced by 88%,87%,and 76%,respectively,compared with that in group A.Compared with group A,group B had significant reductions in the radiation doses of the side and back of the pelvic cavity(P<0.05)and a significantly higher radiation dose of the front of the pelvic cavity,which was increased by 19%,23%,and 10%,respectively,at the tube voltages of 80,100,and 120 kVp,and there were significant differences in all tube voltage conditions(P<0.05)except under the tube voltage condition of 120 kVp(P=0.190).In addition,after the application of the device for protection,the reduction rate of pelvic radiation dose under the tube voltages of 80 and 100 kVp was higher than that under the tube voltage of 120 kVp.Conclusion:The new 360-degree radiation protection and position fixation device can significantly reduce the cumulative radiation dose of pelvic organs during chest CT scan,and it holds promise for clinical application due to its characteristics of conve-nient wearing and fixed patient position.

Animal experiments are an essential component of life sciences and medical research. However, the external validity and reliability of individual animal studies are frequently challenged by inherent limitations such as small sample sizes, high design heterogeneity, and poor reproducibility, which impede the effective translation of research findings into clinical practice. Systematic reviews and meta-analysis represent a key methodology for integrating existing evidence and enhancing the robustness of conclusions. Currently, however, the application of systematic reviews and meta-analysis in the field of animal experiments lacks standardized guidelines for their conduct and reporting, resulting in inconsistent quality and, to some extent, diminishing their evidence value. To address this issue, this paper aims to systematically delineate the reporting process for systematic reviews and meta-analysis of animal experiments and to propose a set of standardized recommendations that are both scientific and practical. The article's scope encompasses the entire process, from the preliminary preparatory phase [including formulating the population， intervention， comparison and outcome （PICO） question, assessing feasibility, and protocol pre-registration] to the key writing points for each section of the main report. In the core methods section, the paper elaborates on how to implement literature searches, establish eligibility criteria, perform data extraction, and assess the risk of bias, based on the Preferred Reporting Items for Systematic Reviews and Meta-analysis （PRISMA) statement, in conjunction with relevant guidelines and tools such as Animal Research： Reporting of in Vivo Experiments （ARRIVE) and a risk of bias assessment tool developed by the Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE). For the presentation of results, strategies are proposed for clear and transparent display using flow diagrams and tables of characteristics. The discussion section places particular emphasis on how to scientifically interpret pooled effects, thoroughly analyze sources of heterogeneity, evaluate the impact of publication bias, and cautiously discuss the validity and limitations of extrapolating findings from animal studies to clinical settings. Furthermore, this paper recommends adopting the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology to comprehensively grade the quality of evidence. Through a modular analysis of the entire reporting process, this paper aims to provide researchers in the field with a clear and practical guide, thereby promoting the standardized development of systematic reviews and meta-analysis of animal experiments and enhancing their application value in scientific decision-making and translational medicine.