Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Aim To explore the effects of Huannao Yicong decoction(HYD)on the learning and memory ability and brain iron metabolism in APP/PS1 mice and the correlation of HAMP knockout mice and APP/PS1 double transgenic model mice.Methods The ex-periment was divided into five groups,namely,HAMP-/-group(6-month HAMP gene knockout mice),APP/PS1 group(6-month APP/PS1-double-transgenic mice),HAMP-/-+HYD,APP/PS1+HYD,and negative control group(6-month C57BL/6J mice),with six mice in each group.The dose was ad-ministered(13.68 g·kg-1 weight),and the other groups received distilled water for gavage once a day for two months.After the administration of the drug,the mice in each group were tested for learning and memory in the Morris water maze;Biochemical detec-tion was performed to detect iron ion content in each mouse brain;Western blot and RT-qPCR were carried out to analyze hippocampal transferrin(TF),transfer-rin receptor1(TFR1),membrane iron transporter1(FPN1)divalent metal ion transporter 1(DMT1)and β-amyloid protein(Aβ)protein and mRNA expression levels in each group.Results Compared with the normal group,both HAMP-/-mice and APP/PS1 mice had reduced the learning and memory capacity,in-creased iron content in brain tissue,Aβ protein ex-pression increased in hippocampus of HAMP-/-group and APP/PS1 group mice(P＜0.01),the protein and mRNA expression of TF,TFR1 and DMT1 increased in hippocampal tissues of HAMP-/-and APP/PS1 groups(P＜0.01),and the FPN1 protein and mRNA expres-sion decreased(P＜0.01).Compared with the HAMP-and APP/PS1 groups,respectively,HAMP-/-+HYD group and APP/PS1+HYD group had improved learning and memory ability,decreased iron content,decreased Aβ protein expression(P＜0.01),decreased TF,TFR1,DMT1 protein and mR-NA expression(P＜0.01),and increased expression of FPN1 protein and mRNA(P＜0.01).Conclusions There is some association between HAMP-/-mice and APP/PS1 mice,HYD can improve the learning and memory ability of HAMP-/-and APP/PS1 mice and reduce the Aβ deposition.The mechanism may be related to the regulation of TF,TFR1,DMT1,FPN1 expression and improving brain iron overload.

Aim To investigate the effect of total glu-cosides of paeony on inflammatory injury and TLR4/NF-κB/NLRP3 pathway in autoimmune thyroiditis(AIT)rats.Methods The experiment was divided into control group,model group,total glucosides of pae-ony(TGP),TLR4 inhibitor group and TGP+TLR4 ag-onist group,with 10 animals in each group.Except for the control group,the rats in other groups were subcu-taneously injected with thyroglobulin and Freund's ad-juvant to induce the AIT rat model.After six weeks of administration,thyroid histopathological changes were observed using hematoxylin-eosin(HE)staining;ser-um levels of TPOAb,TgAb,TSH,T3,T4,TNF-α,INF-γ,IL-1 β and IL-1 β were detected by enzyme-linked immunosorbent assay(ELISA);TLR4/NF-κB/NLRP3 pathway mRNAs and proteins expression in thyroid tis-sues were detected by RT-qPCR and Western blot.Re-sults Compared with the control group,the thyroid follicular epithelium of rats was significantly damaged,and the serum levels of TPOAb,TgAb,TSH,T3,T4,TNF-α,INF-γ,IL-1 β and IL-1 β increased(P＜0.01).The expression of TLR4/NF-κB/NLRP3 path-way mRNAs and proteins increased in the model group(P＜0.01).Compared with the model group,the damage of thyroid follicular epithelium was alleviated,and the serum levels of TPOAb,TgAb,TSH,T3,T4,TNF-α,INF-γ,IL-1 β and IL-1 β were reduced(P＜0.01),the expression of TLR4/NF-κB/NLRP3 path-way mRNAs and proteins were down-regulated in the TGP group and TLR4 inhibitor group(P＜0.01).Compared with TGP group,the damage of thyroid follic-ular epithelium was aggravated,and the levels of serum TPOAb,TgAb,TSH,T3,T4,TNF-α,INF-γ,IL-1 β and IL-1 β were elevated(P＜0.05 or P＜0.01),the pro-tein expressions of TLR4/NF-κB/NLRP3 pathway mR-NAs and proteins were up-regulated in TGP+TLR4 ag-onist group(P＜0.05 or P＜0.01).Conclusions TGP may play a protective role in thyroid by inhibiting the TLR4/NF-κB/NLRP3 pathway and improving the inflammatory injury of thyroid tissues.

Objective To establish the finite element model of spinal canal reconstruction and internal fixation,analysis influence of spinal canal reconstruction and internal fixation on spinal stability,and verify the effectiveness and reliability of spinal canal reconstruction and internal fixation in spinal canal surgery.Methods A 30-year-old male healthy volunteer with a height of 172 cm and weight of 75 kg was selected and his lumbar CT data were collected to establish a finite element model of normal lumbar Lo3-L,and the results were compared with in vitro solid results and published finite element analysis results to verify the validity of the model.They were divided into normal group,laminectomy group and spinal canal reconstruction group according to different treatment methods.Under the same boundary fixation and physiological load conditions,six kinds of ac-tivities were performed,including forward bending,backward extension,left bending,right bending,left rotation and right rota-tion,and the changes of range of motion(ROM)of L3-L4,L4-L5 segments and overall maximum ROM of L3-L5 were analyzed under the six conditions.Results The ROM displacement range of each segment of the constructed L3-L5 finite element model was consistent with the in vitro solid results and previous literature data,which confirms the validity of the model.In L3-L4,ROM of spinal canal reconstruction group was slightly increased than that of normal group during posterior extension(＞5％dif-ference),and ROM of other conditions was similar to that of normal group(＜5％difference).ROM in laminectomy group was significantly increase than that in normal group and spinal canal reconstruction group under the condition of flexion,extension,left and right rotation.In L4-L5,ROM in spinal canal reconstruction group was similar to that in normal group(＜5％differ-ence),while ROM in laminectomy group was significantly higher than that in normal group and spinal canal reconstruction group(＞5％difference).In the overall maximum ROM of L3-L5,spinal canal reconstruction group was only slightly higher than normal group under the condition of posterior extension(＞5％difference),while laminectomy was significantly higher than normal group and spinal canal reconstruction group under the condition of anterior flexion,posterior extension,left and right rotation(＞5％difference).The changes of each segment ROM and overall ROM of L3-L5 showed laminectomy group＞spinal canal reconstruction group＞normal group.Conclusion Laminectomy could seriously affect biomechanical stability of the spine,but application of spinal canal reconstruction and internal fixation could effectively reduce ROM displacement of the responsi-ble segment of spine and maintain its biomechanical stability.

Molecular Biology is a key basic professional course for all the students specializing in Biolo-gy,Biotechnology,and Bioengineering.With the promotion of double world-class project and first-class undergraduate construction,the development of English-taught course faces challenges.We started to teach the Molecular Biology course in English at the East China University of Science and Technology since 2019,the construction of Molecular Biology course has been reformed and practiced,including the combination of imagery,vividness and classroom teaching,the combination of advanced,cutting-edge and classical theories,and the comprehensive coverage of the teaching process,which has effectively pro-moted the construction and practice of Molecular Biology course.The Molecular Biology course taught in English greatly increased the students'professional and scientific research ability,international vision and English academic communication ability,comprehensive ability and satisfaction,and teachers'teaching and research ability.This course provides an effective reference for fostering innovative profes-sional first-class undergraduates and the construction of Molecular Biology course.

Objective:To investigate the protective effect of endogenous ω-3 polyunsaturated fatty acid(PUFA)against cisplatin-induced myelosuppression and the mechanism of reducing apoptosis in bone marrow nucleated cells using mfat-1 transgenic mice.Methods:The experimental animals were divided into 4 groups:wild-type mice normal control group,mfat-1 transgenic mice normal control group,wild-type mice model group and mfat-1 transgenic mice model group.The mice in the model group were injected intraperitoneally with 7.5 mg/kg cisplatin on day 0 and day 7 to construct a myelosuppression model,while the mice in the normal control group were injected intraperitoneally with an equal amount of saline,and their status was observed and their body weight was measured daily.Peripheral blood was taken after 14 day for routine blood analysis,and the content and proportion of PUFA in peripheral blood were detected using gas chromatography.Bone marrow nucleated cells in the femur of mice were counted.The histopathological changes in bone marrow were observed by histopathological staining.The apoptosis of nucleated cells and the expression level changes of apoptosis-related genes in the bone marrow of mice were detected by flow cytometry and fluorescence quantitative PCR.Results:Compared with wild-type mice,mfat-1 transgenic mice showed significantly increased levels of ω-3 PUFA in peripheral blood and greater tolerance to cisplatin.Peripheral blood analysis showed that endogenous ω-3 PUFA promoted the recovery of leukocytes,erythrocytes,platelets and haemoglobin in peripheral blood of myelosuppressed mice.The results of HE staining showed that endogenous ω-3 PUFA significantly improved the structural damage of bone marrow tissue induced by cisplatin.Flow cytometry and PCR showed that,compared with wild-type mice model group,the apoptosis rate of bone marrow nucleated cells in mfat-1 transgenic mice was significantly reduced(P＜0.001),and the expression of anti-apoptotic genes Bcl-2 mRNA was significantly increased(P＜0.01),while the expressions of pro-apoptotic genes Bax and Bak mRNA were significantly reduced(P＜0.001,P＜0.05).Conclusion:Endogenous ω-3 PUFA can reduce cisplatin-induced apoptosis in bone marrow nucleated cells,increase the number of peripheral blood cells and exert a protective effect against cisplatin-induced myelosuppression by regulating the expression of apoptosis-related genes.