Objective: To develop a depression recognition model by integrating the spirit-expression diagnostic framework of traditional Chinese medicine (TCM) with machine learning algorithms. The proposed model seeks to establish a TCM-informed tool for early depression screening, thereby bridging traditional diagnostic principles with modern computational approaches. Methods: The study included patients with depression who visited the Shanghai Pudong New Area Mental Health Center from October 1, 2022 to October 1, 2023, as well as students and teachers from Shanghai University of Traditional Chinese Medicine during the same period as the healthy control group. Videos of 3 – 10 s were captured using a Xiaomi Pad 5, and the TCM spirit and expressions were determined by TCM experts (at least 3 out of 5 experts agreed to determine the category of TCM spirit and expressions). Basic information, facial images, and interview information were collected through a portable TCM intelligent analysis and diagnosis device, and facial diagnosis features were extracted using the Open CV computer vision library technology. Statistical analysis methods such as parametric and non-parametric tests were used to analyze the baseline data, TCM spirit and expression features, and facial diagnosis feature parameters of the two groups, to compare the differences in TCM spirit and expression and facial features. Five machine learning algorithms, including extreme gradient boosting (XGBoost), decision tree (DT), Bernoulli naive Bayes (BernoulliNB), support vector machine (SVM), and k-nearest neighbor (KNN) classification, were used to construct a depression recognition model based on the fusion of TCM spirit and expression features. The performance of the model was evaluated using metrics such as accuracy, precision, and the area under the receiver operating characteristic (ROC) curve (AUC). The model results were explained using the Shapley Additive exPlanations (SHAP). Results: A total of 93 depression patients and 87 healthy individuals were ultimately included in this study. There was no statistically significant difference in the baseline characteristics between the two groups (P > 0.05). The differences in the characteristics of the spirit and expressions in TCM and facial features between the two groups were shown as follows. (i) Quantispirit facial analysis revealed that depression patients exhibited significantly reduced facial spirit and luminance compared with healthy controls (P < 0.05), with characteristic features such as sad expressions, facial erythema, and changes in the lip color ranging from erythematous to cyanotic. (ii) Depressed patients exhibited significantly lower values in facial complexion L, lip L, and a values, and gloss index, but higher values in facial complexion a and b, lip b, low gloss index, and matte index (all P < 0.05). (iii) The results of multiple models show that the XGBoost-based depression recognition model, integrating the TCM “spirit-expression” diagnostic framework, achieved an accuracy of 98.61% and significantly outperformed four benchmark algorithms—DT, BernoulliNB, SVM, and KNN (P < 0.01). (iv) The SHAP visualization results show that in the recognition model constructed by the XGBoost algorithm, the complexion b value, categories of facial spirit, high gloss index, low gloss index, categories of facial expression and texture features have significant contribution to the model. Conclusion This study demonstrates that integrating TCM spirit-expression diagnostic features with machine learning enables the construction of a high-precision depression detection model, offering a novel paradigm for objective depression diagnosis.

Objective To observe the value of MR 3D-T1WI and T2WI radiomics for diagnosing early and middle stage Parkinson disease(PD).Methods A total of 96 patients with early or middle stage PD(Hoehn-Yahr[H-Y]stage≤2.5)and 96 matched healthy adults were retrospectively collected and divided into training set(n=135,including 67 cases of PD and 68 healthy adults)and validation set(n=57,including 28 cases of PD and 29 healthy adults)at the ratio of 7∶3.The optimal radiomics features of left red nucleus(LRN),right red nucleus(RRN),left substantia nigra(LSN)and right substantia nigra(RSN)were extracted and screened from cranial 3D-T1WI and T2WI in training set.Then radiomics models of single MR sequence and combined MR sequences were constructed,respectively,the radiomics scores(Radscore)were obtained,the diagnostic efficacy of each model for diagnosing early and middle stage PD was validated using validation set,and the correlations of Radscore of each model and clinical scale scores of PD patients were analyzed.Results Based on LRN,RRN,LSN and RSN on 3D-T1WI and T2WI,15,14,11 and 14,and 15,12,14 and 12 optimal radiomics features were obtained,respectively.Then models of single sequence,including LRN3D-T1W,I RRN3D-T1W,I LSN3D-T1W,I RSN3D-T1W,I LRNT2W,I RRNT2W,I LSNT2WI and RSNT2W,I as well as models of combined sequences,including LRN3D-T1WI+T2WI,RRN3D-T1WI+T2WI,LSN3D-T1WI+T2WI and RSN3D-T1WI+T2WI were constructed.The AUC of models in training and validation sets based on 3D-T1WI were 0.75-0.86,of models based on T2WI in training and validation sets were 0.82-0.90,while of combined models were 0.85-0.93.The Radscore of LRN3D-T1WI model in PD patients was negatively correlated with Hamilton depression scale(HAMD)and Hamilton anxiety scale(HAMA)scores(rs=-0.255,-0.242,P=0.011,0.016),while of RSNT2WI model was negatively correlated with HAMD score(rs=-0.254,P=0.010).Conclusion 3D-T1WI and T2WI radiomics could be used to diagnose early and middle stage PD.

Objective To explore the impact of suture configuration and fixation type on the biome-chanical strength of rotator cuff repair,using a factorial design study.Methods Sixteen fresh-frozen porcine shoulder samples were randomized into an anchorless double-row suture bridge transosseous su-tures(DS)group,an anchored double-row suture bridge transosseous-equivalent(DE)group,an an-chorless X-BOX construct transosseous sutures(XS)group,and an anchored X-BOX construct transos-seous-equivalent(XE)group,each of four,according to suture configuration(double-row suture bridge,traditional X-BOX construct)and fixation type(suture anchors,transosseous sutures).Then,their fatigue resistance(first-cycle excursion,gap length difference ratio,and the percentage of ex-posed footprints)and the failure strength(the maximum failure load and the re-tear type)were mea-sured using a biomechanical material testing machine.Results Different suture configurations affected failure strength(F=39.559,P<0.001),with the double-row suture bridge groups(693.07±58.35 N,746.76±138.57 N)showing significantly higher failure strength,compared to the traditional X-BOX groups(462.90±18.91 N,421.43±90.76 N).However,the fixation type did not significantly im-pact failure strength(F=1.161,P=0.302).Moreover,the suture configuration influenced the gap differ-ence ratio(F=7.781,P=0.016),but had no significant correlation with other fatigue resistance indica-tors(P>0.05).Meanwhile,failure strength and fatigue resistance were not correlated with fixation type,and the interaction between suture and fixation type(P>0.05).The incidence of failure types for the four suture configurations was as follows:Type I tendon tear:XS>XE>DS=DE;type II tendon tear:DS>XE>XS=DE;fixing material-related failure:DE>DS=XE=XS.Conclusion The failure strength and gap formation ratio in rotator cuff repair under fatigue loading are influenced by suture configuration,whereas no significant association has been observed with respect to fixation method,whether using transosseous sutures or suture anchors.

BACKGROUND:Cervical instability is a common orthopedic disease in young and middle-aged people,and is the early manifestation of cervical spondylosis,which has a great impact on the quality of life of patients.Therefore,early diagnosis of cervical instability to implement early intervention has positive clinical and social significance.OBJECTIVE:The clinical prediction model of cervical instability in young and middle-aged people was constructed based on machine learning to realize early screening of cervical instability in young and middle-aged people before X-ray examination.METHODS:From September 2022 to October 2023,155 young and middle-aged adults with cervical instability and 88 with non-cervical instability recruited through recruitment advertisements and spinal department outpatient of Wangjing Hospital,China Academy of Chinese Medical Sciences were selected as research subjects.The research subjects'general information,living and working habits,discomfort symptoms,visual analog scale score,Neck Disability Index,and 36-ltem Short Form Health Survey were collected on site based on questionnaires.The above information was used as predictive factors.After screening,six machine learning algorithms of Support Vector Machine,LightGBM,RandomForest,Logistic,AdaBoost,and XGBClassifier were used to train the model by ten-fold cross-validation method,and the clinical prediction model of cervical instability was constructed.Area under the curve was used as the main evaluation index.Univariate analysis was performed on the predictors,and SHAP method was used to rank the importance of the predictors.Correlation heat maps were used to show the degree of linear correlation between the predictors and the cervical instability.RESULTS AND CONCLUSION:(1)Among the six machine learning models,RandomForest model was chosen as the final prediction model,including nine predictors,such as age,body mass index,neck circumference/neck length,visual analog scale score,Neck Disability Index,bodily pain,general health,vitality,and mental health,area under the curve=0.725 4,and the calibration degree was good.It could be used as a reference tool for early screening of cervical instability in young and middle-aged people.(2)There were significant differences in age,visual analog scale score,Neck Disability Index,bodily pain,general health,and vitality between the two groups(P＜0.05).(3)The order of importance of predictors was age,Neck Disability Index,visual analog scale score,general health,body mass index,vitality,bodily pain,neck circumference/neck length,mental health,among which age,visual analog scale score,Neck Disability Index were positively correlated with cervical instability,while general health,body mass index,vitality,bodily pain,neck circumference/neck length,and mental health were negatively correlated with cervical instability.

To understand the current epidemiological status and biological characteristics of avian paramyxoviruses(APMV)in wild birds in China,a total of 1 384 fecal samples of wild birds were collected in eight provinces(autonomous regions),including Ningxia,in 2023,to detect avian pa-ramyxovirus infections by viral isolation and RT-PCR.Positive samples were subjected to F gene sequence amplification and genetic evolutionary analyses.The results showed that 10 strains of APMV were isolated and identified from 1 384 wild bird feces samples with a positive rate of 0.72％.Out of the 10 strains,4 strains were APMV-1,which was in the same branch to the Ameri-can goose APMV-1 strain and had the homology ranging from 93％to 97.3％.Three strains of APMV-4 were in the same branch with the Russian duck APMV-4 strain and the Russian pintail APMV-4 strain,with homology ranging from 99.1％to 99.5％.Three strains were APMV-6,they were in the same branch with the Russian ruddy bladdered duck APMV-6 strain,with homology ranging from 98.7％to 99.20％.The intracerebral inoculatable pathogenicity index(ICPI)of the four strains for 1-day-old chicks ranged from 0 to 0.48,which was low in pathogenicity for chick-ens.The above results enriches the epidemiological information and the biological characteristics of avian paramyxovirus in wild birds in China,which provides a reference for the early warning,scien-tific prevention and control of this disease.

Objective To explore the impact of suture configuration and fixation type on the biome-chanical strength of rotator cuff repair,using a factorial design study.Methods Sixteen fresh-frozen porcine shoulder samples were randomized into an anchorless double-row suture bridge transosseous su-tures(DS)group,an anchored double-row suture bridge transosseous-equivalent(DE)group,an an-chorless X-BOX construct transosseous sutures(XS)group,and an anchored X-BOX construct transos-seous-equivalent(XE)group,each of four,according to suture configuration(double-row suture bridge,traditional X-BOX construct)and fixation type(suture anchors,transosseous sutures).Then,their fatigue resistance(first-cycle excursion,gap length difference ratio,and the percentage of ex-posed footprints)and the failure strength(the maximum failure load and the re-tear type)were mea-sured using a biomechanical material testing machine.Results Different suture configurations affected failure strength(F=39.559,P<0.001),with the double-row suture bridge groups(693.07±58.35 N,746.76±138.57 N)showing significantly higher failure strength,compared to the traditional X-BOX groups(462.90±18.91 N,421.43±90.76 N).However,the fixation type did not significantly im-pact failure strength(F=1.161,P=0.302).Moreover,the suture configuration influenced the gap differ-ence ratio(F=7.781,P=0.016),but had no significant correlation with other fatigue resistance indica-tors(P>0.05).Meanwhile,failure strength and fatigue resistance were not correlated with fixation type,and the interaction between suture and fixation type(P>0.05).The incidence of failure types for the four suture configurations was as follows:Type I tendon tear:XS>XE>DS=DE;type II tendon tear:DS>XE>XS=DE;fixing material-related failure:DE>DS=XE=XS.Conclusion The failure strength and gap formation ratio in rotator cuff repair under fatigue loading are influenced by suture configuration,whereas no significant association has been observed with respect to fixation method,whether using transosseous sutures or suture anchors.

Ionizing radiation occurs not only during nuclear and radiological terrorist attacks or nuclear accidents but also in medical applications and daily life. In recent years, the potential toxic effects of low-dose ionizing radiation on the male reproductive system have raised public health concerns. Most specifically, for the testis, a highly sensitive target organ to ionizing radiation, there is an urgent need to determine the mechanisms underlying the association between radiation-induced spermatogenic failure and male infertility. Focusing on the potential injurious effects of low-dose ionizing radiation on spermatogenesis, this review presents a summary and analysis of various underlying mechanisms including oxidative stress, apoptosis, and DNA damage repair and reviews recent domestic and international strategies for protecting against radiation-induced reproductive system damage in order to offer references for future research on the injurious effects of low-dose radiation on spermatogenesis and relevant protection.

To understand the current epidemiological status and biological characteristics of avian paramyxoviruses(APMV)in wild birds in China,a total of 1 384 fecal samples of wild birds were collected in eight provinces(autonomous regions),including Ningxia,in 2023,to detect avian pa-ramyxovirus infections by viral isolation and RT-PCR.Positive samples were subjected to F gene sequence amplification and genetic evolutionary analyses.The results showed that 10 strains of APMV were isolated and identified from 1 384 wild bird feces samples with a positive rate of 0.72％.Out of the 10 strains,4 strains were APMV-1,which was in the same branch to the Ameri-can goose APMV-1 strain and had the homology ranging from 93％to 97.3％.Three strains of APMV-4 were in the same branch with the Russian duck APMV-4 strain and the Russian pintail APMV-4 strain,with homology ranging from 99.1％to 99.5％.Three strains were APMV-6,they were in the same branch with the Russian ruddy bladdered duck APMV-6 strain,with homology ranging from 98.7％to 99.20％.The intracerebral inoculatable pathogenicity index(ICPI)of the four strains for 1-day-old chicks ranged from 0 to 0.48,which was low in pathogenicity for chick-ens.The above results enriches the epidemiological information and the biological characteristics of avian paramyxovirus in wild birds in China,which provides a reference for the early warning,scien-tific prevention and control of this disease.

BACKGROUND:Cervical instability is a common orthopedic disease in young and middle-aged people,and is the early manifestation of cervical spondylosis,which has a great impact on the quality of life of patients.Therefore,early diagnosis of cervical instability to implement early intervention has positive clinical and social significance.OBJECTIVE:The clinical prediction model of cervical instability in young and middle-aged people was constructed based on machine learning to realize early screening of cervical instability in young and middle-aged people before X-ray examination.METHODS:From September 2022 to October 2023,155 young and middle-aged adults with cervical instability and 88 with non-cervical instability recruited through recruitment advertisements and spinal department outpatient of Wangjing Hospital,China Academy of Chinese Medical Sciences were selected as research subjects.The research subjects'general information,living and working habits,discomfort symptoms,visual analog scale score,Neck Disability Index,and 36-ltem Short Form Health Survey were collected on site based on questionnaires.The above information was used as predictive factors.After screening,six machine learning algorithms of Support Vector Machine,LightGBM,RandomForest,Logistic,AdaBoost,and XGBClassifier were used to train the model by ten-fold cross-validation method,and the clinical prediction model of cervical instability was constructed.Area under the curve was used as the main evaluation index.Univariate analysis was performed on the predictors,and SHAP method was used to rank the importance of the predictors.Correlation heat maps were used to show the degree of linear correlation between the predictors and the cervical instability.RESULTS AND CONCLUSION:(1)Among the six machine learning models,RandomForest model was chosen as the final prediction model,including nine predictors,such as age,body mass index,neck circumference/neck length,visual analog scale score,Neck Disability Index,bodily pain,general health,vitality,and mental health,area under the curve=0.725 4,and the calibration degree was good.It could be used as a reference tool for early screening of cervical instability in young and middle-aged people.(2)There were significant differences in age,visual analog scale score,Neck Disability Index,bodily pain,general health,and vitality between the two groups(P＜0.05).(3)The order of importance of predictors was age,Neck Disability Index,visual analog scale score,general health,body mass index,vitality,bodily pain,neck circumference/neck length,mental health,among which age,visual analog scale score,Neck Disability Index were positively correlated with cervical instability,while general health,body mass index,vitality,bodily pain,neck circumference/neck length,and mental health were negatively correlated with cervical instability.

Objective:To analyze the effects of low-molecular-weight heparin combined with insulin (LMWH+INS) and double filtration plasmapheresis (DFPP) on lipid profiles and clinical outcomes in patients with hypertriglyceridemic acute pancreatitis (HTG-AP) based on propensity score matching.Methods:The clinical data of 126 patients with HTG-AP from October 2022 to February 2024 in The Third Affiliated Hospital of Nanjing Medical University, Changzhou Traditional Chinese Medicine Hospital Affiliated to Nanjing Traditional Chinese Medicine University and Changzhou First People's Hospital were retrospectively included. Patients were divided into LMWH+INS group ( n=87) and DFPP group ( n=39) according to the treatment. Propensity score matching was applied at a 1∶1 ratio. The repeated measures analysis of variance was conducted to assess dynamic changes of blood lipids within the 5 days of admission between the LMWH+INS and DFPP groups after matching. Clinical symptoms and outcomes were compared between the two matched groups following matching. Results:29 patients were included in both LMWH+INS group and DFPP group after propensity score matching. No statistically significant differences were observed in triglycerides (TG), acute physiology and chronic health evaluation Ⅱ(APACHEⅡ) score, or bedside index for the severity of acute pancreatitis (BISAP) between the two groups (all P value >0.05), indicating comparability. Repeated measures analysis of variance revealed that TG and TC levels in the DFPP group were significantly lower than those in the LMWH+INS group at 2-5 days after admission [TG 2 d: (5.26±2.59) mmol/L vs (10.79±3.81) mmol/L, 3 d: (3.35±1.01) mmol/L vs (7.72±3.64) mmol/L, 4 d: (3.45±0.77) mmol/L vs (6.57±3.17) mmol/L, 5 d: (3.73±1.26) mmol/L vs (5.61±3.07) mmol/L; TC 2 d: (4.83±2.29) mmol/L vs (8.2±2.82) mmol/L, 3 d: (4.23±2.17) mmol/L vs (7.71±2.68) mmol/L, 4 d: (4.28±1.59) mmol/L vs (7.55±2.41) mmol/L, 5 d: (4.1±1.21) mmol/L vs (7.84±2.6) mmol/L], with a more rapid decrease. LDL levels in the LMWH+INS and DFPP groups showed similar trends, with significant decreases at 2 day after admission [(5.41±3.24) mmol/L vs (2.96±1.47) mmol/L, (4.99±3.51) mmol/L vs (2.47±1.53) mmol/L]. The differences mentioned above are all statistically significant (all P value <0.001). No significant changes were observed in HDL levels in either LMWH+INS and DFPP groups at 2-5 days after admission. After matching, the DFPP group had a significantly longer time of resuming feeding [3(2, 3) days vs 4(3, 6) days] and higher hospital cost [12113.87 (9055.31, 14401.84) yuan vs 28025.34 (25388.11, 36335.48) yuan] compared with the LMWH+INS group, with statistically significant differences. Conclusions:DFPP could reduce TG and TC levels more rapidly and effectively than LMWH combined with INS, but does not show an advantage in improving clinical outcomes and reducing hospitalization costs.