Objective: To develop a non-invasive predictive model for coronary artery stenosis severity based on adaptive multi-modal integration of traditional Chinese and western medicine data. Methods: Clinical indicators, echocardiographic data, traditional Chinese medicine (TCM) tongue manifestations, and facial features were collected from patients who underwent coronary computed tomography angiography (CTA) in the Cardiac Care Unit (CCU) of Shanghai Tenth People's Hospital between May 1, 2023 and May 1, 2024. An adaptive weighted multi-modal data fusion (AWMDF) model based on deep learning was constructed to predict the severity of coronary artery stenosis. The model was evaluated using metrics including accuracy, precision, recall, F1 score, and the area under the receiver operating characteristic (ROC) curve (AUC). Further performance assessment was conducted through comparisons with six ensemble machine learning methods, data ablation, model component ablation, and various decision-level fusion strategies. Results: A total of 158 patients were included in the study. The AWMDF model achieved excellent predictive performance (AUC = 0.973, accuracy = 0.937, precision = 0.937, recall = 0.929, and F1 score = 0.933). Compared with model ablation, data ablation experiments, and various traditional machine learning models, the AWMDF model demonstrated superior performance. Moreover, the adaptive weighting strategy outperformed alternative approaches, including simple weighting, averaging, voting, and fixed-weight schemes. Conclusion The AWMDF model demonstrates potential clinical value in the non-invasive prediction of coronary artery disease and could serve as a tool for clinical decision support.

Objective:To retrospectively analyze the treatment status of tyrosine kinase inhibitors (TKI) in newly diagnosed patients with chronic myeloid leukemia (CML) in China.Methods:Data of chronic phase (CP) and accelerated phase (AP) CML patients diagnosed from January 2006 to December 2022 from 77 centers, ≥18 years old, and receiving initial imatinib, nilotinib, dasatinib or flumatinib-therapy within 6 months after diagnosis in China with complete data were retrospectively interrogated. The choice of initial TKI, current TKI medications, treatment switch and reasons, treatment responses and outcomes as well as the variables associated with them were analyzed.Results:6 893 patients in CP ( n=6 453, 93.6%) or AP ( n=440, 6.4%) receiving initial imatinib ( n=4 906, 71.2%), nilotinib ( n=1 157, 16.8%), dasatinib ( n=298, 4.3%) or flumatinib ( n=532, 7.2%) -therapy. With the median follow-up of 43 ( IQR 22-75) months, 1 581 (22.9%) patients switched TKI due to resistance ( n=1 055, 15.3%), intolerance ( n=248, 3.6%), pursuit of better efficacy ( n=168, 2.4%), economic or other reasons ( n=110, 1.6%). The frequency of switching TKI in AP patients was significantly-higher than that in CP patients (44.1% vs 21.5%, P<0.001), and more AP patients switched TKI due to resistance than CP patients (75.3% vs 66.1%, P=0.011). Multi-variable analyses showed that male, lower HGB concentration and ELTS intermediate/high-risk cohort were associated with lower cytogenetic and molecular responses rate and poor outcomes in CP patients; higher WBC count and initial the second-generation TKI treatment, the higher response rates; Ph + ACA at diagnosis, poor PFS. However, Sokal intermediate/high-risk cohort was only significantly-associated with lower CCyR and MMR rates and the poor PFS. Lower HGB concentration and larger spleen size were significantly-associated with the lower cytogenetic and molecular response rates in AP patients; initial the second-generation TKI treatment, the higher treatment response rates; lower PLT count, higher blasts and Ph + ACA, poorer TFS; Ph + ACA, poorer OS. Conclusion:At present, the vast majority of newly-diagnosed CML-CP or AP patients could benefit from TKI treatment in the long term with the good treatment responses and survival outcomes.

The modernization research of TCM tongue diagnosis involves a complex process of acquiring tongue diagnosis images of diseases and syndromes through machine vision and image processing technology,and conducting intelligent diagnosis and analysis.The development of artificial intelligence technology has brought new opportunities for the intelligent research of tongue diagnosis images in TCM.This article systematically reviewed the current status of the development and standard application of TCM tongue diagnosis instruments in the past decade,discussed the latest research progress in deep learning methods including tongue image quality assessment,tongue image segmentation,tongue color classification,tongue image pattern recognition,three-dimensional tongue image reconstruction,and clinical applications.It deeply analyzed the bottleneck problems existing in the current artificial intelligence tongue diagnosis technology,proposed to focus on clinical disease-syndrome combined applications,multi-level expansion,cross-modal fusion to enhance the depth and breadth of tongue diagnosis features,utilize general artificial intelligence methods to enhance the intelligence diagnosis technology of tongue images,innovate and construct a new model of intelligent tongue diagnosis with full-domain information perception,health assessment,and disease-syndrome diagnosis,in order to promote the leapfrog development of intelligent TCM diagnosis and treatment technology.

Objective To investigate the expression and clinical significance of serum long non-coding RNA small nucleolar RNA host gene 16(lncRNA SNHG16)and mothers against decapentaplegic homolog 4(SMAD4)in elderly patients with chronic obstructive pulmonary disease(COPD)and pulmonary infection(PI).Methods A total of 237 elderly COPD patients admitted to the hospital from January 2021 to January 2023 were enrolled in the study.Among them,117 patients with concomitant PI were classified as the concur-rent group,and 120 patients without concomitant PI were classified as the COPD group.Real-time fluores-cence quantitative polymerase chain reaction(qRT-PCR)was applied to detect the expression level of serum lncRNA SNHG16 in two groups.Enzyme linked immunosorbent assay(ELISA)was applied to detect the lev-el of SMAD4 in patients'serum.Simplified clinical pulmonary infection scale(sCPIS)was used to evaluate the degree of PI of patients in the concurrent group.Multivariate Logistic regression was applied to analyze the in-fluencing factors of PI in elderly COPD patients.Correlation between serum lncRNA SNHG16,SMAD4 levels and sCPIS in elderly COPD patients with PI was analyzed by using Spearman correlation analysis.Receiver op-erating characteristic(ROC)curve was applied to analyze the diagnostic value of serum lncRNA SNHG16 and SMAD4 levels in elderly COPD patients with PI.Results The serum relative expression level of lncRNA SNHG16 in the concurrent group was higher than that in the COPD group,but the serum SMAD4 level was lower than that in the COPD group(P<0.05).In addition,the proportions of patients with age≥70 years,smoking history,complicated with diabetes and COPD course≥5 years and the levels of tumor necrosis fac-tor-α(TNF-α),interferon-γ(INF-γ)in the concurrent group were higher than those in the COPD group,and FEV1/FVC and the level of interleukin-10(IL-10)in concurrent group were lower than those in COPD group(P<0.05).Multivariate Logistic analysis showed that age≥70 years old,complicated with diabetes,COPD course≥5 years,high levels of TNF-α,INF-γ and lncRNA SNHG16 were risk factors for elderly patients with COPD complicated with PI(P<0.05),but high FEV1/FVC and high levels of SMAD4 and IL-10 were protective factors(P<0.05).Spearman correlation analysis showed that serum relative expression level of ln-cRNA SNHG16 was positively correlated with sCPIS in COPD patients with PI(r=0.505,P<0.001),while SMAD4 level was negatively correlated with sCPIS(r=-0.550,P<0.001).The area under the curve(AUC)of the combined diagnosis of serum lncRNA SNHG16 and SMAD4 for PI in elderly COPD patients was higher than those of individual diagnosis(Z=2.416,P=0.016;Z=2.375,P=0.018).Conclusion The serum relative expression level of lncRNA SNHG16 increases and SMAD4 level decreases in elderly COPD pa-tients with PI,both are influencing factors for elderly COPD patients complicated with PI,and both are related to the degree of PI in patients,and both have diagnostic value for elderly COPD patients complicated with PI,and the diagnostic efficacy of combined detection is better.

Methods: From September 3, 2018, to March 23, 2024, participants with essential hypertension (receiving antihypertensive medication treatment, hypertension group) and normal blood pressure (control group) were recruited from the Cardiology Department of Shanghai Hospital of Traditional Chinese Medicine, the Coronary Care Unit of Shanghai Tenth People's Hospital, the Physical Examination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, and the Gaohang Community Health Service Center. This study employed the propensity score matching (PSM) method to reduce study participants selection bias. Spectral information in the facial visible light spectrum of the subjects was collected using a flame spectrometer, and the spectral chromaticity values were calculated using the equal-interval wavelength method. The study analyzed the differences in spectral reflectance across various facial regions, including the entire face, forehead, glabella, nose, jaw, left and right zygomatic regions, left and right cheek regions as well as differences in parameters within the Lab color space between the two subject groups. Feature selection was conducted using least absolute shrinkage and selection operator (LASSO) regression, followed by the application of various machine learning algorithms, including logistic regression (LR), support vector machine (SVM), random forest (RF), Naïve Bayes (NB), and eXtreme Gradient Boosting (XGB). The reduced-dimensional dataset was split in a 7 : 3 ratio to establish a classification and assessment model for facial coloration related to primary hypertension. Additionally, model fusion techniques were applied to enhance the predictive power. The performance of the models was evaluated using metrics including the area under the curve (AUC) and accuracy. Shapley Additive exPlanations (SHAP) was used to interpret the outcomes of the models. Results: A total of 114 participants were included in both hypertension and control groups. Reflectance analysis across the entire face and eight predefined areas revealed that the hypertensive group exhibited significantly higher reflectance of corresponding color light in the blue-violet region (P < 0.05) and a lower reflectance in the red region (P < 0.05) compared with control group. Analysis of Lab color space parameters across the entire face and eight predefined areas showed that hypertensive group had significantly lower a and b values than control group (P < 0.05). LASSO regression analysis identified a total of 18 facial color features that were highly correlated with hypertension, including the a values of the chin and the right cheek, the reflectance at 380 nm and at 780 nm of the forehead. The results of the multi-model classification showed that the RF classification model was the most effective, with an AUC of 0.74 and an accuracy of 0.77. The combined model of RF + LR + SVM outperformed a single model in their classification performance, achieving an AUC of 0.80 and an accuracy of 0.76. SHAP model visualization results indicated that the top three contributors to ideal prediction results based on the characteristics from the facial spectrum were the reflectance at 380 nm across the entire face and of the nose as well as the a value of the chin. Conclusion Within the same age group, patients with essential hypertension exhibited significant and regular changes in facial color and facial spectral reflectance parameters after the administration of antihypertensive drugs. Furthermore, facial reflectance indicators, such as the overall reflectance at 380 nm and the a value of the chin, could offer valuable references for clinically assessing the drug efficacy and health status of patients with essential hypertension.

Methods: Data of TCM indicators (tongue, facial, and pulse diagnostics) and clinical parameters from patients diagnosed with CHD at the Cardiology Department of Shanghai Baoshan Hospital of Integrated Traditional Chinese and Western Medicine, from October 3, 2023 to March 15, 2024, were collected. Important variables were identified using importance screening and correlation analysis with CHD risk factors and laboratory markers. Six machine learning models including logistic regression (LR), decision tree (DT), support vector machine (SVM), k-nearest neighbors (KNN), random forest (RF), and gradient boosting (GB), were applied to evaluate the risk of coronary artery obstruction by combining clinical and TCM data of CHD. Model performance was assessed using metrics such as accuracy, precision, and recall, with reliability validated through ten-fold cross-validation. Results: A total of 288 patients were included in the study. Fifteen clinical risk factors, including body mass index (BMI), myoglobin, and alcohol consumption history, were incorporated into the diagnostic models. The KNN model showed good performance when combining clinical data with tongue and facial data. The SVM model performed well when clinical data was combined with pulse data. Among all the models, the KNN model with 10-fold cross-validation, which integrates the three types of TCM diagnostic data (tongue, face, and pulse) with clinical data, performs the best (accuracy: 0.837, precision: 0.814, and recall: 0.809). Conclusion Incorporating TCM diagnostic data can enhance the accuracy of coronary artery obstruction risk assessment. The KNN prediction model that integrate tongue, facial, and pulse data performs the best and can be recommended as a clinical decision support tool.

Objective To investigate the correlation between tongue and pulse indicators and the out-come of live birth in patients undergoing frozen-thawed embryo transfer(FET),as well as the association between these indicators and patients'endocrine parameters. Methods This study was conducted at Reproductive Medicine Center,Shuguang Hospital Af-filiated to Shanghai University of Traditional Chinese Medicine,Shanghai,China,from March 8,2021 to January 5,2022.Patients undergoing FET were divided into live birth and non-live birth groups according to their live birth outcome.The differences between the endocrine pa-rameters[basic follicle stimulating hormone(b FSH),basic luteinizing hormone(b LH),basic estradiol(b E2),basic progesterone(b P),basal endometrial thickness,follicle stimulating hormone(FSH)on endometrial transition day,luteinizing hormone(LH)on endometrial transition day,estradiol(E2)on endometrial transition day,progesterone(P)on endometrial transition day,and endometrial thickness on endometrial transition day]and the tongue and pulse indicators[tongue body(TB)-L,TB-a,TB-b,tongue coating(TC)-L,TC-a,TC-b,perAll,perPart,h1,h4,h5,t1,h1/t1,and h4/h1]of patients in the two groups were analyzed,with the correlation between these variables analyzed as well using Spearman's correlation coefficient.Multivariate logistic regression was employed to identify the influential factors in the live birth prediction models across various datasets,including Model 1 consisting of endocrine indica-tors only,Model 2 solely consisting of tongue and pulse indicators,and Model 3 consisting of both tongue,pulse,and endocrine indicators,as well as to evaluate efficacy of the models de-rived from different datasets. Results This study included 78 patients in live birth group and 144 patients in non-live birth group.Compared with non-live birth group,live birth group exhibited higher levels of TB-L(P=0.01)and TB-a(P=0.04),while demonstrated lower levels of b FSH(P=0.01),perAll(P=0.04),and h4/h1(P=0.03).The Spearman's correlation coefficient analysis revealed statisti-cally significant correlation(P<0.05)between TB-L,TB-b,TC-L,TC-b,perAll,perPart,h4,h5,t1,h1/t1 and b FSH,b LH,basal endometrial thickness,LH on endometrial transition day,E2 on endometrial transition day,P on endometrial transition day,and endometrial thickness on endometrial transition day in live birth group.The multivariate logistic regression analysis showed that the prediction Model 3 for live birth outcome[area under the curve(AUC):0.917,95%confidence interval(CI):0.863-0.971,P<0.001]surpassed the Model 1(AUC:0.698,95%CI:0.593-0.803,P=0.001),or the Model 2(AUC:0.790,95%CI:0.699-0.880,P<0.001).The regression equations for the live birth outcomes,integrating tongue and pulse indicators with endocrine parameters,included the following measures:FSH on endometrial transition day[odds ratio(OR):0.523,P=0.025],LH on endometrial transition day(OR:1.277,P=0.029),TB-L(OR:2.401,P=0.001),perPart(OR:1.018,P=0.013),h1(OR:0.065,P=0.021),t1(OR:4.354,P=0.024),and h4/h1(OR:0.018,P=0.016). Conclusion In infertility patients undergoing FET,there exists a correlation between tongue and pulse indicators and endocrine parameters.The corporation of tongue and pulse indica-tors significantly improved the predictive capability of the model for live birth outcomes.Specifically,tongue and pulse indicators such as TB-L,perPart,h1,t1,and h4/h1 exhibited a discernible correlation with the ultimate live birth outcomes.

Objective To explore the objective indicators of tongue and pulse manifestations in patients with endometriosis diseases by collecting the data of tongue and pulse manifestations of patients with endometriosis diseases by digital tongue and pulse diagnostic instrument. Methods The endometriosis disease group included 72 patients with endometriosis diseases who were treated in Department of Gynecology (Professor ZHANG Tingting),Yueyang Hospital of Integrated Traditional Chinese and Western Medicine from Jun. 1,2021 to Sep. 15,2022. The normal group included 35 healthy adult women recruited by the Physical Examination Center of Shuguang Hospital,Shanghai University of Traditional Chinese Medicine. Results In terms of age,there was no significant difference between the endometriotic disease group and normal group (P>0.05). In terms of tongue color,the values of zhiCon,zhiASM,zhiENT,zhiMEAN,zhiClrB,zhiClrI,zhiClrLa,zhiClrCb,and zhiClrLb in the endometriosis disease group were significantly different from those in the normal group (all P<0.05),while there were no significant differences in the values of zhiClrR,zhiClrG,zhiClrS,zhiClrL,zhiClrY,or zhiClrCr between the 2 groups (all P>0.05). In terms of tongue coating color,the values of taiClrR,taiClrB,taiClrI,taiClrS,taiClrLa,taiClrLb,taiClrCr,and taiClrCb in the endometriosis disease group were significantly different from those in the normal group (all P<0.05),while there were no significant differences in the values of taiClrG,taiClrL,or taiClrY (all P>0.05). In terms of texture and thickness of tongue coating,there were no significant differences in the values of perAll,perPart,taiCon,taiASM,taiENT,or taiMEAN between the 2 groups (all P>0.05). In terms of pulse manifestation,the values of h3,h4,h5,t4,h3/h1,and h4/h1 in the endometriosis disease group were significantly different from those in the normal group (all P<0.05),while there were no significant differences in the values of h1,t,t1,or t5 (all P>0.05). Conclusion There are significant differences in tongue and pulse indicators between patients with endometriosis diseases and healthy individuals. It can provide objective indicators for further research on the pathogenesis changes and clinical differentiation of endometriosis diseases.

Objective To develop a Traditional Chinese Medicine(TCM)syndrome diagnosis scale suitable for evaluating the overall health status of participants in long-term simulated weightlessness experiments,and preliminarily evaluate its reliability and validity.Methods Based on the understanding of the pathogenesis of TCM in different stages of long-term manned spaceflight,a scale was developed through literature research and expert consultation.Test-retest reliability and internal consistency coefficient were used to test the reliability of the scale.Item analysis and factor principal component analysis were used to evaluate the validity of the scale,and a rotating component matrix was used to analyze the correlation between each item and dimension using 36 volunteers in a 90 days head down bed rest experiment as the research subjects.Results The scale contains eight dimensions and 57 items.The reliability analysis showed that the correlation coefficient of the total score of the scale for the first and second tests of 30 participants was 0.889,indicating high stability of the scale.The Cronbach coefficient of the scale was 0.934,indicating very good internal consistency.The split half reliability after correction was 0.858,indicating a high reliability of the scale.The validity analysis showed that the difference between the high score group and the low score one for each of the 57 items was statistically significant(P<0.01),and the Pearson correlation coefficient between each item and the total score of the scale was greater than 0.4(P<0.001).The cumulative contribution rate of 8 common factors extracted using principal component factor analysis was 55.293%,and the results of rotating component matrix analysis,after applying TCM theory and expert feedback,had a coincidence of up to 87.5%with the initial 8 dimensions,indicating good structural validity of the scale.Conclusion The scale has good reliability and validity,and can diagnose TCM syndromes.It is suitable for long-term simulated weightlessness experiment and provides an objective and quantitative new method for evaluating the subjective feelings of participants.

A strong animal survival instinct is to approach objects and situations that are of benefit and to avoid risk. In humans, a large proportion of mental disorders are accompanied by impairments in risk avoidance. One of the most important genes involved in mental disorders is disrupted-in-schizophrenia-1 (DISC1), and animal models in which this gene has some level of dysfunction show emotion-related impairments. However, it is not known whether DISC1 mouse models have an impairment in avoiding potential risks. In the present study, we used DISC1-N terminal truncation (DISC1-N
Animals ; Interneurons/metabolism* ; Mice ; Mice, Transgenic ; Nerve Tissue Proteins/metabolism* ; Neurons/metabolism* ; Nucleus Accumbens/metabolism* ; Parvalbumins/metabolism*