Objective: To explore the value of contrast-enhanced computed tomography (CT) radiomics combined with machine learning algorithms in the preoperative prediction of perineural invasion (PNI) in oral squamous cell carcinoma (OSCC), aiming to provide evidence for assisting clinical treatment decision-making. Methods​: This study was approved by the Ethics Committee of the Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine. A total of 250 OSCC patients confirmed by postoperative pathology were included, comprising 128 PNI-positive and 122 PNI-negative cases. The dataset was randomly divided into training (n=175), validation (n=38), and independent testing (n=37) sets in a ratio of 7:1.5:1.5. Regions of interest were delineated on preoperative images, and radiomic features were extracted. After dimensionality reduction and feature selection using methods like Least Absolute Shrinkage and Selection Operator (LASSO) regression, multiple machine learning models, including support vector machine (SVM), random forest, Light gradient boosting machine (LightGBM), and a Stacking ensemble model, were constructed. Model performance was evaluated using metrics such as the area under the receiver operating characteristic curve (AUC), sensitivity, calibration curves, and decision curve analysis (DCA). Model interpretability was analyzed using Shapley additive explanations (SHAP) and grouped permutation feature importance analysis. Results ​: ​ Among the 250 samples analyzed, the LightGBM model based on radiomics demonstrated the best performance on the independent test set, with an AUC of 0.781, outperforming models like SVM (AUC = 0.730) and Random Forest (AUC = 0.691), as well as clinical models (AUCs ranging 0.549-0.711). The LightGBM model showed good calibration (Brier score 0.198), and DCA indicated high clinical net benefit over a wide threshold probability range. Paired DeLong tests revealed no statistically significant differences in AUC between the ensemble (Stacking) model and the corresponding best-performing radiomics-based model. SHAP analysis and grouped permutation feature importance analysis further indicated that the primary discriminative information for the model came from radiomic texture features. Conclusion ​ The LightGBM model based on contrast-enhanced CT radiomics demonstrated good discriminative ability for preoperative prediction of PNI in OSCC. In the independent test set, it achieved the highest AUC. This model holds promise as a non-invasive auxiliary tool for preoperative risk assessment. Given the limited sample size of the independent test set, these results require further validation in larger cohorts and external datasets.

OBJECTIVE To explore a synergistic medication strategy integrating stage-specific modifications of Bushen huoxue decoction with hormone replacement therapy （HRT） for premature ovarian insufficiency （POI）. METHODS The connotation of Academician Tong Xiaolin’s “state-target differentiation and treatment” theory and the disease stage characteristics of POI were summarized. The latent stage， subclinical stage， clinical stage and exhaustion stage of POI were classified into corresponding core pathogenesis “states” and key objective indicator “targets”. Taking Bushen huoxue decoction as the basic prescription， its staged modification scheme and its sequential combination with HRT were analyzed. RESULTS & CONCLUSIONS The four stages of POI correspond to four pathogenic states respectively： kidney yin deficiency， kidney deficiency and blood stasis， heart-kidney disharmony， and deficiency of both yin and yang. Follicle-stimulating hormone （FSH）， anti-Müllerian hormone （AMH）， antral follicle count （AFC） and Kupperman score were taken as the evaluation targets of staging. Combined with the “state-target” characteristics of each stage， a medication principle based on Bushen huoxue decoction with syndrome differentiation modification and stage-adjusted administration was established： traditional Chinese medicine dominates in the latent stage， a sequential collaborative regimen is adopted in the subclinical stage， HRT is dominant supplemented by traditional Chinese medicine in the clinical stage， and integrated traditional Chinese and Western medicine is applied to consolidate the root cause in the exhaustion stage.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

BACKGROUND:The phosphatidylinositol 3-kinase/protein kinase(PI3K/AKT)signaling pathway plays a pivotal role in regulating osteoclast activation,which is essential for maintaining bone homeostasis.Bone destruction in osteoarticular tuberculosis is caused by aberrant osteoclastogenesis induced by Mycobacterium tuberculosis infection.However,the role of the PI3K signaling pathway in Mycobacterium tuberculosis-induced aberrant osteoclastogenesis remains unclear. OBJECTIVE:To investigate the effects and mechanisms of the PI3K/AKT signaling pathway inhibitor BYL-719 on aberrant osteoclastogenesis induced by Mycobacterium tuberculosis. METHODS:RAW264.7 cells were infected with bovine Mycobacterium tuberculosis bacillus calmette-cuerin vaccine,and Ag85B was used for cellular immunofluorescence staining.The cell counting kit-8 assay was employed to determine the safe concentration of BYL-719.There were four groups in the experiment:blank control group,BYL-719 group,BCG group,and BCG+BYL-719 group.Under the induction of receptor activator of nuclear factor kappa-B ligand,the effects of BYL-719 on post-infection osteoclast differentiation and fusion were explored through tartrate-resistant acid phosphatase staining and phalloidin staining.RT-PCR and western blot were used to detect the expression of osteoclast-related genes and proteins,and further investigate the mechanism of action. RESULTS AND CONCLUSION:Immunofluorescence staining showed that RAW264.7 cells phagocytosed Mycobacterium tuberculosis.Cell counting kit-8 data indicated that 40 nmol/L BYL-719 was non-toxic to cells.Tartrate-resistant acid phosphatase staining and phalloidin staining showed that BYL-719 inhibited the generation and fusion ability of osteoclasts following infection.RT-PCR and western blot results also indicated that BYL-719 suppressed the upregulation of osteoclast-specific genes(including c-Fos,NFATc1,matrix metalloproteinase 9,and CtsK)induced by Mycobacterium tuberculosis infection(P<0.05).Western blot and immunofluorescence staining revealed that BYL-719 inhibited excessive osteoclast differentiation induced by Mycobacterium tuberculosis by downregulating the expression of IκBα-p65.To conclude,BYL-719 inhibits aberrant osteoclastogenesis induced by Mycobacterium tuberculosis through the downregulation of IκBα/p65.Therefore,the IκBα/p65 signaling pathway is a potential therapeutic target for osteoarticular tuberculosis,and BYL-719 holds potential value for the preventing and amelioration of bone destruction in osteoarticular tuberculosis.BYL-719 has the potential to prevent and ameliorate bone destruction in osteoarticular tuberculosis.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

Abelmoschi Corolla, the dried corolla of Abelmoschus manihot, has anti-inflammatory, antioxidant, and anti-fibrosis activities. Its chemical constituents mainly include flavonoids, organic acids, steroids, and polysaccharides. This study reviewed the research progress in the chemical constituents and pharmacological activities of Abelmoschi Corolla in recent 20 years. According to the concept of quality marker(Q-marker), the Q-markers of Abelmoschi Corolla were predicted from plant phylogeny, chemical constituent specificity, traditional efficacy, chemical constituent measurability, and absorbed constituents. The primary Q-markers for Abelmoschi Corolla were anticipated to include quercetin-3'-O-β-D-glucopyranoside, gossypetin-8-O-β-D-glucuronide, isoquercetin, myricetin,quercetin, and hyperoside, with the aim of providing reference data for improving the quality evaluation system of Abelmoschi Corolla.
Abelmoschus/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Flowers/chemistry* ; Humans ; Animals ; Quality Control ; Flavonoids/chemistry*

This study aims to investigate the optimal ratio of Astragali Radix-Curcumae Rhizoma(AC) for inhibiting the proliferation of 143B osteosarcoma cells, and to investigate the mechanism by which AC inhibits osteosarcoma growth and metastasis through angiogenesis and cell adhesion mediated by the phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt)/hypoxia inducible factor-1α(HIF-1α) pathway. A subcutaneous 143B tumor-bearing nude mouse model was successfully established and randomly divided into the model group, and the AC 1∶1, 2∶1, and 4∶1 groups. Body weight, tumor volume, and tumor weight were recorded. Real-time quantitative polymerase chain reaction(RT-qPCR) and Western blot were used to detect the mRNA and protein expression levels of PI3K, Akt, phosphorylated Akt(p-Akt), HIF-1α, vascular endothelial growth factor A(VEGFA), transforming growth factor-β1(TGF-β1), epithelial cadherin(E-cadherin), neural cadherin(N-cadherin), vimentin, matrix metalloproteinase 2(MMP2), matrix metalloproteinase 9(MMP9), B-cell lymphoma-2(Bcl-2), Bcl-2-associated X protein(Bax), and caspase-3 in the hypoxic core region of the tumor tissue. A cell hypoxia model was established, and the effects of AC-medicated serum(model group, AC 1∶1, 2∶1, and 4∶1 groups) on angiogenesis, proliferation, adhesion, invasion, and migration of 143B osteosarcoma cells were examined through CCK-8, flow cytometry, Transwell assay, cell adhesion assay, and HUVEC tube formation assay. The results showed that compared with the model group, the tumor weight and volume were smallest in the 2∶1 group. The expression levels of PI3K, Akt, p-Akt, HIF-1α, VEGFA, and TGF-β1 were significantly decreased, and the protein expression of E-cadherin was significantly increased, while the protein expression of N-cadherin, vimentin, MMP2, and MMP9 was significantly decreased. Additionally, the protein expression of Bax and caspase-3 was significantly increased, and Bcl-2 protein expression was significantly decreased. In vitro experiments showed that after intervention with AC-medicated serum at a 2∶1 ratio, the cell activity, adhesion, invasion, and migration of 143B cells were significantly reduced, apoptosis was significantly increased, and HUVEC tube formation was significantly decreased. In conclusion, the 2∶1 ratio of AC showed the most effective inhibition of 143B cell growth. AC can inhibit the growth and metastasis of osteosarcoma 143B cells by regulating the PI3K/Akt/HIF-1α signaling pathway, inhibiting angiogenesis and reducing cell adhesion, invasion, and migration.
Osteosarcoma/pathology* ; Animals ; Proto-Oncogene Proteins c-akt/genetics* ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Humans ; Mice ; Cell Adhesion/drug effects* ; Cell Proliferation/drug effects* ; Neovascularization, Pathologic/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Phosphatidylinositol 3-Kinases/genetics* ; Cell Line, Tumor ; Mice, Nude ; Signal Transduction/drug effects* ; Astragalus Plant/chemistry* ; Bone Neoplasms/physiopathology* ; Male ; Rhizome/chemistry* ; Mice, Inbred BALB C ; Angiogenesis

Microbial detection and control of traditional Chinese medicine(TCM) decoction pieces are crucial for the quality control of TCM preparations. It is also a key area of research in the measurement technology and equipment development for TCM manufacturing. Guided by TCM manufacturing measurement methodologies, this study presented a design of a novel portable microbial detection device, using Atractylodis Macrocephalae Rhizoma decoction pieces as a demonstration. Immunomagnetic separation technology was employed for specific isolation and labeling of target microorganisms. Enzymatic signal amplification was utilized to convert weak biological signals into colorimetric signals, constructing an optical biosensor. A self-developed smartphone APP was further applied to analyze the colorimetric signals and quantify target concentrations. A portable and automated detection system based on Arduino microcontroller was developed to automatically perform target microbial separation/extraction, as well as mimetic enzyme labeling and catalytic reactions. The developed equipment specifically focuses on the rapid and quantitative microbial analysis of TCM active pharmaceutical ingredients, intermediates in TCM manufacturing, and final TCM products. Experimental results demonstrate that the equipment could detect Salmonella in samples within 2 h, with a detection limit as low as 5.1 × 10~3 CFU·mL~(-1). The equipment enables the rapid detection of microorganisms in TCM decoction pieces, providing a potential technical solution for on-site rapid screening of microbial contamination indicators in TCM. It has broad application prospects in measurement technology for TCM manufacturing and offers strong technical support for the modernization, industrialization, and intelligent development of TCM.
Drugs, Chinese Herbal/analysis* ; Atractylodes/microbiology* ; Rhizome/microbiology* ; Biosensing Techniques/methods* ; Medicine, Chinese Traditional ; Colorimetry/instrumentation* ; Quality Control