Autism Spectrum Disorders (ASDs) are reported as a group of neurodevelopmental disorders. The structural changes of brain regions including the hippocampus were widely reported in autistic patients and mouse models with dysfunction of ASD risk genes, but the underlying mechanisms are not fully understood. Here, we report that deletion of Trio, a high-susceptibility gene of ASDs, causes a postnatal dentate gyrus (DG) hypoplasia with a zigzagged suprapyramidal blade, and the Trio-deficient mice display autism-like behaviors. The impaired morphogenesis of DG is mainly caused by disturbing the postnatal distribution of postmitotic granule cells (GCs), which further results in a migration deficit of neural progenitors. Furthermore, we reveal that Trio plays different roles in various excitatory neural cells by spatial transcriptomic sequencing, especially the role of regulating the migration of postmitotic GCs. In summary, our findings provide evidence of cellular mechanisms that Trio is involved in postnatal DG morphogenesis.
Animals ; Dentate Gyrus/metabolism* ; Mice ; Morphogenesis/physiology* ; Neurons/pathology* ; Cell Movement ; Mice, Inbred C57BL ; Autism Spectrum Disorder/pathology* ; Mice, Knockout ; Neural Stem Cells ; Male ; Neurogenesis ; Autistic Disorder/genetics*

Schistosomiasis was once hyper-endemic in Yunnan Province. Following concerted efforts for over 70 years, remarkable achievements have been made for schistosomiasis control in the province. In 2004, the Mid- and Long-term Plan for Schistosomiasis Prevention and Control in Yunnan Province was initiated in Yunnan Province, and the target for transmission control of schistosomiasis was achieved in the province in 2009. Following the subsequent implementation of the Outline for Key Projects in Integrated Schistosomiasis Control Program (2009—2015) and the 13th Five - year Plan for Schistosomiasis Control in Yunnan Province, no acute schistosomiasis had been identified in Yunnan Province for successive 12 years, and no local Schistosoma japonicum infections had been detected in humans, animals or Oncomelania hupensis snails for successive 6 years in the province by the end of 2020. The transmission of schistosomiasis was interrupted in Yunnan Province in 2020. This review summarizes the history of schistosomiasis, changes in schistosomiasis prevalence and progress of schistosomiasis control in Yunnan Province, and proposes the future priorities for schistosomiasis control in the province.

Objective To predict the potential geographic distribution of Oncomelania hupensis in Yunnan Province using random forest (RF) and maximum entropy (MaxEnt) models, so as to provide insights into O. hupensis surveillance and control in Yunnan Province. Methods The O. hupensis snail survey data in Yunnan Province from 2015 to 2016 were collected and converted into O. hupensis snail distribution site data. Data of 22 environmental variables in Yunnan Province were collected, including twelve climate variables (annual potential evapotranspiration, annual mean ground surface temperature, annual precipitation, annual mean air pressure, annual mean relative humidity, annual sunshine duration, annual mean air temperature, annual mean wind speed, ≥ 0 ℃ annual accumulated temperature, ≥ 10 ℃ annual accumulated temperature, aridity and index of moisture), eight geographical variables (normalized difference vegetation index, landform type, land use type, altitude, soil type, soil textureclay content, soil texture-sand content and soil texture-silt content) and two population and economic variables (gross domestic product and population). Variables were screened with Pearson correlation test and variance inflation factor (VIF) test. The RF and MaxEnt models and the ensemble model were created using the biomod2 package of the software R 4.2.1, and the potential distribution of O. hupensis snails after 2016 was predicted in Yunnan Province. The predictive effects of models were evaluated through cross-validation and independent tests, and the area under the receiver operating characteristic curve (AUC), true skill statistics (TSS) and Kappa statistics were used for model evaluation. In addition, the importance of environmental variables was analyzed, the contribution of environmental variables output by the models with AUC values of > 0.950 and TSS values of > 0.850 were selected for normalization processing, and the importance percentage of environmental variables was obtained to analyze the importance of environmental variables. Results Data of 148 O. hupensis snail distribution sites and 15 environmental variables were included in training sets of RF and MaxEnt models, and both RF and MaxEnt models had high predictive performance, with both mean AUC values of > 0.900 and all mean TSS values and Kappa values of > 0.800, and significant differences in the AUC (t = 19.862, P < 0.05), TSS (t = 10.140, P < 0.05) and Kappa values (t = 10.237, P < 0.05) between two models. The AUC, TSS and Kappa values of the ensemble model were 0.996, 0.954 and 0.920, respectively. Independent data verification showed that the AUC, TSS and Kappa values of the RF model and the ensemble model were all 1, which still showed high performance in unknown data modeling, and the MaxEnt model showed poor performance, with TSS and Kappa values of 0 for 24%(24/100) of the modeling results. The modeling results of 79 RF models, 38 MaxEnt models and their ensemble models with AUC values of > 0.950 and TSS values of > 0.850 were included in the evaluation of importance of environmental variables. The importance of annual sunshine duration (SSD) was 32.989%, 37.847% and 46.315% in the RF model, the MaxEnt model and their ensemble model, while the importance of annual mean relative humidity (RHU) was 30.947%, 15.921% and 28.121%, respectively. Important environment variables were concentrated in modeling results of the RF model, dispersed in modeling results of the MaxEnt model, and most concentrated in modeling results of the ensemble model. The potential distribution of O. hupensis snails after 2016 was predicted to be relatively concentrated in Yunnan Province by the RF model and relatively large by the MaxEnt model, and the distribution of O. hupensis snails predicted by the ensemble model was mostly the joint distribution of O. hupensis snails predicted by RF and MaxEnt models. Conclusions Both RF and MaxEnt models are effective to predict the potential distribution of O. hupensis snails in Yunnan Province, which facilitates targeted O. hupensis snail control.

Objective:To investigate the therapeutic effect of naringenin on diabetes retinopathy (DR) rats by regulating Janus kinase 2 (JAK2) /signal transducer and activator of transcription 3 (STAT3) /suppressor of cytokine signaling 1 (SOCS1) signaling pathway.Methods:A DR rat model was constructed and randomly separated into DR group, naringenin group, activator group, and naringenin+activator group, with normal rats as the control group. After intervention according to corresponding groups, blood glucose and glycosylated hemoglobin of rats were detected. Retinal tissue was separated, and interleukin-6 (IL-6), IL-1β, glutathione (GSH), and catalase (CAT) were detected. The pathological changes in rats and blood retinal vascular barrier permeability were detected, and the retinal tissue adhesion factor 1 (VCAM-1), anti vascular endothelial growth factor (VEGF) mRNA, and JAK2/STAT3/SOCS1 pathway related proteins were detected.Results:In the control group, blood glucose levels were (5.16±0.53) mmoL, glycosylated hemoglobin (4.26±0.45) %, IL-6 (63.11±6.35) pg/mL, IL-1β (23.11±2.38) pg/mL, Evans blue (EB) content (4.72±0.49) ng/mg, VCAM-1 (1.02±0.11), VEGF mRNA expression (0.93±0.10), p-JAK2/JAK2 (0.24±0.03), p-STAT3/STAT3 (0.19±0.02), GSH (17.62±1.81) nmoL/mg, CAT (11.68±1.19) IU/mg, and SOCS1 expression 1.44±0.16; while in DR group, blood glucose were (18.85±1.89) mmoL, HBA1c (11.62±1.18) %, IL-6 (89.17±8.99) pg/mL, IL-1β (52.11±5.28) pg/mL, EB (10.24±1.08) ng/mg, VCAM-1 1.56±0.16, VEGF 1.61±0.18, P-JAK2/JAK2 0.55±0.06 and P-STAT3/STAT3 0.47±0.05, all decreased compared with that of the control group ( P<0.05). The expressions of GSH were (8.27±0.88) nmoL/mg, CAT (6.85±0.71) IU/mg and SOCS1 0.86±0.09 in group DR, all increased compared with those of the control group ( P<0.05). In naringin group, blood glucose was (13.11±1.34) mmoL, HBA1c (7.36±0.76) %, IL-6 (67.08±6.75) pg/mL, IL-1β (31.61±3.22) pg/mL, EB content was (6.15±0.63) ng/mg, VCAM-1 1.15±0.12, VEGF mRNA expression 1.17±0.12, P-JAK2 /JAK2 0.29±0.03, and P-STAT3 /STAT3 0.21±0.03, all lower than those in DR Group ( P<0.05). However, the expressions of GSH were (15.22±1.59) nmoL/mg, CAT (10.95±1.11) IU/mg, and SOCS1 (1.37±0.15) ,all higher than those of DR group ( P<0.05). The activator reversed the protective effect of naringenin on DR Rats. Conclusion:Naringenin improves DR rat injury by regulating the JAK2/STAT3/SOCS1 signaling pathway.

Objective To compare the anti-inflammatory,antitumor and anti-bacterial effects of the single extract(in granules)and the prepared drug in pieces of Forsythia Suspense(Lianqiao,a traditional Chinese herbal medicine).Methods In zebrafish embryo models of CuSO4 exposure,tail transection and LPS microinjection-induced inflammation,the anti-inflammatory effects of 10 μg/mL DEX,single extract of Forsythia Suspense,and the water extract of the prepared drug(400,600,and 800 μg/mL)were evaluated by observing neutrophil counts,RT-qPCR,HE staining and survival analysis.Zebrafish embryo models bearing different human tumor cell xenografts were used to assess the anti-tumor effect of the drugs in different dosage forms by fluorescence staining and HE staining.The microbroth dilution method was used to evaluate the antibacterial efficacy of the drugs.Results In the zebrafish embryo models of inflammation,both of the two dosage forms of Forsythia Suspense significantly inhibited neutrophil aggregation,reduced the mRNA expressions of TNF-α,IL-6,P38,Jnk,Erk and P65,and increased the survival rate of zebrafish.They both showed obvious inhibitory effects against xenografts of different human cancer cells including colon cancer cells(HCT116),pancreas adenocarcinoma cells(PANC-1),lung cancer cells(A549),liver cancer cells(Hep3B)and cervical carcinoma cells(Hela)in zebrafish embryos,and exhibited strong anti-bacterial effects at the concentration of 15.63 mg/mL.Conclusion The two dosage forms of Forsythia Suspense have similar anti-inflammatory,antitumor and antibacterial effects,but their effects for inhibiting IL-6,P65,and Jnk mRNA expressions and HCT116 cell proliferation differ significantly at low doses in zebrafish.

Objective To compare the anti-inflammatory,antitumor and anti-bacterial effects of the single extract(in granules)and the prepared drug in pieces of Forsythia Suspense(Lianqiao,a traditional Chinese herbal medicine).Methods In zebrafish embryo models of CuSO4 exposure,tail transection and LPS microinjection-induced inflammation,the anti-inflammatory effects of 10 μg/mL DEX,single extract of Forsythia Suspense,and the water extract of the prepared drug(400,600,and 800 μg/mL)were evaluated by observing neutrophil counts,RT-qPCR,HE staining and survival analysis.Zebrafish embryo models bearing different human tumor cell xenografts were used to assess the anti-tumor effect of the drugs in different dosage forms by fluorescence staining and HE staining.The microbroth dilution method was used to evaluate the antibacterial efficacy of the drugs.Results In the zebrafish embryo models of inflammation,both of the two dosage forms of Forsythia Suspense significantly inhibited neutrophil aggregation,reduced the mRNA expressions of TNF-α,IL-6,P38,Jnk,Erk and P65,and increased the survival rate of zebrafish.They both showed obvious inhibitory effects against xenografts of different human cancer cells including colon cancer cells(HCT116),pancreas adenocarcinoma cells(PANC-1),lung cancer cells(A549),liver cancer cells(Hep3B)and cervical carcinoma cells(Hela)in zebrafish embryos,and exhibited strong anti-bacterial effects at the concentration of 15.63 mg/mL.Conclusion The two dosage forms of Forsythia Suspense have similar anti-inflammatory,antitumor and antibacterial effects,but their effects for inhibiting IL-6,P65,and Jnk mRNA expressions and HCT116 cell proliferation differ significantly at low doses in zebrafish.

Syncytial giant cells (SGCs) are epithelial giant cells with multiple uniform and similar nuclei. Clear cell renal cell carcinoma (ccRCC) with SGCs is a rare microscopic morphology. A 70-year-old man was admitted to hospital with multiple nodules in both lungs found by chest CT examination 2 weeks before. A left renal carcinoma with lung metastasis was considered by PET-CT. Cytoreductive nephrectomy was performed, and postoperative pathological diagnosis confirmed ccRCC with SGCs of the left renal. Combined immunotherapy and targeted therapies were administered. There was no disease progression during follow-up period of 28 months.

Objective To predict the constitutive parameters of a superelastic model of plantar soft tissues based on random forest(RF)and backpropagation(BP)neural network algorithms to improve the efficiency and accuracy of the method for obtaining constitutive parameters.Methods First,a finite element model for a spherical indentation experiment of plantar soft tissues was established,and the spherical indentation experiment process was simulated to obtain a dataset of nonlinear displacement and indentation force,divided into training and testing sets.The established RF and BP neural network(BPNN)models were trained separately.The constitutive parameters of plantar soft tissues were predicted using experimental data.Finally,the mean square error(MSE)and coefficient of determination(R2)were introduced to evaluate the accuracy of the model prediction,and the effectiveness of the model was verified by comparison with the experimental curves.Results Combining the RF and BPNN models with finite element simulation was an effective and accurate method for determining the superelastic constitutive parameters of plantar soft tissues.After training,the MSE of the RF model reached 1.370 2×10-3,and R2 was 0.982 9,whereas the MSE of the BPNN model reached 4.858 1×10-5,and R2 was 0.999 3.The inverse-determined constitutive parameters of the plantar soft tissues suitable for simulation were obtained.The calculated response curves for the two predicted sets of constitutive parameters were in good agreement with the experimental curves.Conclusions The prediction accuracy for the superelastic constitutive parameters of plantar soft tissues based on an artificial intelligence algorithm model is high,and the relevant research results can be applied to study other mechanical properties of plantar soft tissues.This study provides a new method for obtaining the constitutive parameters of plantar soft tissues and helps to quickly diagnose clinical problems,such as plantar soft tissue lesions.

Objective To investigate the application of machine learning to predict the hemodynamic parameters of combined stenotic left coronary artery(LCA)aneurysms.Methods Parameterized modeling and simulation based on the geometric parameter range of combined stenosis LCA aneurysms in clinical statistics were conducted.The obtained simulation data was used as the dataset,and two common machine learning models were constructed and trained for optimization to predict two key hemodynamic parameters:wall shear stress(WSS)and pressure.By comparing and analyzing the performances of these models on the training and testing sets,the accuracy of each model was evaluated,and the effectiveness of the data-driven prediction of hemodynamic parameters for LCA aneurysms with concomitant stenosis was verified.Results The effectiveness of machine learning method in inverting the hemodynamic parameters of aneurysms was determined.For WSS prediction,the trained deep learning model and random forest model achieved mean squared error(MSE),mean absolute error(MAE),and determination coefficient R2 of 0.052 8,0.032 2,0.988 3,and 0.078 2,0.046 3,and 0.976 6,respectively.For pressure prediction,the accuracies of the deep learning models and random forest models were comparable,with MSE,MAE,and R2 of 4.67×10-6,3×10-4,0.999 7,and 1.07×10-5,5×10-4,and 0.999 3,respectively.Conclusions Machine learning methods show high accuracy in predicting the hemodynamic parameters of combined stenotic coronary artery aneurysm models.The predictive accuracy of the model,computational efficiency,and needs of the application scenarios need to be considered in machine learning prediction so that the appropriate model can be selected according to the specific situation.This study has clinical significance,helping doctors to more accurately evaluate a patient's condition and provide new ideas and method for the diagnosis and treatment of cardiovascular diseases.

Objective:To explore the mediating effect of distress disclosure between perceived social support and psychological distress in colorectal cancer patients.Methods:The convenient sampling method was used to select 220 postoperative colorectal cancer patients who were reviewed in China-Japan Union Hospital of Jilin University from February to August 2023 as the research objetcs. The Distress Disclosure Index (DDI), Perceived Social Support Scale (PSSS), and Chinese version of Screening Tool for Psychological Distress in Cancer Patients were used to conduct the survey.Results:A total of 220 questionnaires were distributed in this study, and 213 valid questionnaires were recovered, with a valid recovery rate of 96.82%. The total score of the Chinese version of Screening Tool for Psychological Distress in Cancer Patients for colorectal cancer patients was (4.31±2.46), the total score of the DDI was (37.26±9.97), and the total score of the PSSS was (57.82±14.60). Pearson correlation analysis showed that psychological distress was negatively correlated with distress disclosure in colorectal patients ( P<0.01), distress disclosure was positively correlated with perceived social support ( P<0.01), and psychological distress was negatively correlated with perceived social support ( P<0.01). The mediating effect results showed that the direct effect of perceived social support on psychological distress was -0.359 ( P<0.01), and the mediating effect between perceived social support and psychological distress was -0.227 ( P<0.01), which acted as a partial mediating effect with the mediating effect accounting for 38.74% of the total effect. Conclusions:Perceived social support can not only directly affect the psychological distress of colorectal cancer patients, but also indirectly affect psychological distress through distress disclosure. Clinical staffs should take certain interventions to improve the level of patients' perceived social support and distress disclosure, so as to improve the psychological distress of patients.