Background Arsenic is an environmentally harmful substance that causes hepatic insulin resistance and liver damage, increasing the risk of type 2 diabetes mellitus. Objective To explore whether the insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) is involved in insulin resistance in HepG2 cells after arsenic exposure through the peroxisome-proliferator-activated receptor γ (PPAR-γ) / glucose transporter 4 (GLUT4) pathway. Methods Cell viability was determined using cell counting kit 8 (CCK8) and an appropriate NaAsO₂ infection dose was determined. A cellular arsenic exposure model of HepG2 cells was established by four concentrations of NaAsO₂ solution for 24 h (the experiment was divided into four groups: 0, 2, 4, and 8 μmol·L⁻¹); HepG2 cells were firstly treated with pcDNA3.1-IGF2BP2 and pcDNA3.1-NC respectively for 6 h, then with 8 μmol·L⁻¹ NaAsO₂ for 24 h to establish a IGF2BP2 overexpression cell model (the experiment was divided into 4 groups: control, NaAsO₂, NaAsO₂+pcDNA3.1-IGF2BP2, and NaAsO₂+pcDNA3.1-NC); finally the cells were subject to 100 nmol·L⁻¹ insulin stimulation for 30 min. Glycogen and glucose in HepG2 cells were determined by glycogen and glucose assay kits; mRNA expression levels of IGF2BP2 were measured by quantitative real-time PCR; protein expression levels of IGF2BP2, PPAR-γ, and GLUT4 in HepG2 were detected by Western blot (WB); and the binding of IGF2BP2 to PPAR-γ and PPAR-γ to GLUT4 was verified by co-immunoprecipitation (CO-IP) experiment. Results The results of CCK8 experiment showed a dose-effect relationship between NaAsO₂ concentration and cell viability. When the concentration of NaAsO₂ was ≥4 μmol·L⁻¹ , the cell viabilities were lower than that of the control group (P <0.05). With the increasing dose of NaAsO₂ infection, reduced glucose consumption and glycogen levels in HepG2 cells were found in the 2, 4, and 8 μmol·L⁻¹ NaAsO₂ treatment groups compared to the control group (P <0.05). The difference between the mRNA expression level of IGF2BP2 in the HepG2 cells treated with 4 or 8 μmol L⁻¹ NaAsO₂ and the control group was significant (P <0.05). In the IGF2BP2 overexpression cell model, compared with the control group, glucose consumption and glycogen levels were lowered in the NaAsO₂ group (P <0.05), the mRNA expression level of IGF2BP2 and the protein expression levels of IGF2BP2, PPAR-γ, and GLUT4 in the cell membrane were all decreased (P <0.05). Compared with the NaAsO₂ group, the glucose consumption and glycogen levels were increased in the NaAsO₂+pcDNA3.1-IGF2BP2 group (P <0.05), and the mRNA expression level of IGF2BP2 and the protein expression levels of IGF2BP2, PPAR-γ, and GLUT4 in the cell membrane were all increased (P <0.05). The results of CO-IP experiments showed that IGF2BP2 interacted with PPAR-γ as well as PPAR-γ with GLUT4 protein. Conclusion IGF2BP2 is involved in arsenic exposure-induced insulin resistance in HepG2 cells by acting on the PPAR-γ/GLUT4 pathway.

ObjectiveThis study aims to develop a prediction model for the compatibility of Chinese medicinal pairs based on Graph Convolutional Networks （GCN）， named HC-GCN. The model integrates the properties of herbs with modern pharmacological mechanisms to predict pairs with specific therapeutic effects. It serves as a demonstration by applying the model to predict and validate the efficacy of blood-activating herb pairs. MethodsThe training dataset for herb pair prediction was constructed by systematically collecting commonly used herb pairs along with their characteristic data， including Qi， flavor， meridian tropism， and target genes. Integrating traditional characteristics of herb with modern bioinformatics， we developed an efficacy-oriented herb pair compatibility prediction model （HC-GCN） using graph convolutional networks （GCN）. This model leverages machine learning to capture the complex relationships in herb pair compatibility， weighted by efficacy features. The performance of the HC-GCN model was evaluated using accuracy （ACC）， recall， precision， F1 score （F1）， and area under the ROC curve （AUC）. Its predictive effectiveness was then compared to five other machine learning models： eXtreme Gradient Boosting （XGBoost）， logistic regression （LR）， Naive Bayes， K-nearest neighbor （KNN）， and support vector machine （SVM）. ResultsUsing herb pairs with blood-activating effects as a demonstration， a prediction model was constructed based on a foundational dataset of 46 blood-activating herb pairs， incorporating their Qi， flavor， meridian tropism， and target gene characteristics. The HC-GCN model outperforms other commonly used machine learning models in key performance metrics， including ACC， recall， precision， F1 score， and AUC. Through the predictive analysis of the HC-GCN model， 60 herb pairs with blood-activating effects were successfully identified. Among of these potential herb pairs， 44 include at least one herb with blood-activating effects. ConclusionIn this study， we established an efficacy-oriented compatibility prediction model for herb pairs based on GCN by integrating the unique characteristics of traditional herbs with modern pharmacological mechanisms. This model demonstrated high predictive performance， offering a novel approach for the intelligent screening and optimization of traditional Chinese medicine prescriptions， as well as their clinical applications.

Objective To explore the normal reference range of perchlorate content in the urine of primary school students, and compare whether there are differences in their urine perchlorate contents among different populations, and to provide reference for the health care of primary school students. Methods A total of 441 primary school students aged 6 to 15 years old in a certain city were selected, and their urine samples were collected. The contents of perchlorate in the urine were determined by ultra-high performance liquid chromatography coupled with mass spectrometry, and the measurement data was statistically analyzed using SPSS software. Results There was no significant gender difference in the content of perchlorate in the urine of primary school students, but there was an age difference. The normal reference range for the content of perchlorate in the urine of primary school students aged 6-9 years old was 0-99.09 μg/L, and the normal reference range for the content of perchlorate in the urine of primary school students aged 10-15 years old was 0-74.56 μg/L. Conclusion Through the measurement and analysis of a large number of samples, a normal reference range for the content of urinary perchlorate in primary school students have been recommended.

Objective:To observe the anti-inflammatory and glycometabolic effects of glutathione(GSH)on macrophages in collagen induced arthritis(CIA)mice.Methods:①CIA model establishment and groups:A total of 14 female DBA/1J mice were ran-domly divided into:CIA+PBS group and CIA+GSH group.The mice were sacrificed on the 50th day,collecting serum and isolating bone marrow derived macrophages(BMDM),which were marked as BMDM1.②Trained immunity model establishment and groups:BMDM were isolated from normal DBA/1J mice,and were pretreated with histone H3K27 demethylases inhibitor(GSKJ1)or PBS for 2 h.Then,serum from CIA model mice in vivo was incubated for 24 h,and the samples were grouped as follows:(CIA+GSH)+PBS group,(CIA+GSH)+GSKJ1 group,(CIA+PBS)+PBS group,(CIA+PBS)+GSKJ1 group.Lipopolysaccharide(LPS)was adopted to stimulated cells on the 6th day,which were marked as BMDM2.③RNA sequencing was used to detect differentially expressed genes(DEGs)and their function in BMDM1 and BMDM2.q-PCR was adopted to estimate the mRNA levels of PFK and Idh3g.The culture supernatants were used to measure the protein levels of TNF-α and IL-6 by ELISA.Results:①Compared with CIA+PBS group,the mice in CIA+GSH group showed lighter of joint swelling(P<0.05),less arthritis index(P<0.05),HE staining suggested less inflam-matory cell infiltration,Safranin O-fast green staining showed more chondrocytes,TRAP staining indicated reduced osteoclasts.②In BMDM1,GO analysis showed that DEGs were mainly involved in glutathione derivative metabolic process,IL-6 production,inflammatory response,innate immune response,regulation of primary metabolic process and glycolipid binding,compared with CIA+GSH and CIA+PBS group.In CIA+GSH group,the mRNA level of PFK was significantly decreased(P<0.05),while Idh3g was also significantly up-regulated(P<0.05),and the expression of TNF-α,IL-6 were both reduced(P<0.05)compared with CIA+PBS group.③In BMDM2,GO analysis showed that DEGs were also involved in inflammatory response,activation of innate immune response,regulation of tumor necrosis factor production,positive regulation of IL-6 production,regulation of glycolytic process and 1,3-β-D-glucan binding between CIA+GSH and CIA+PBS group.Furthermore,in(CIA+GSH)+PBS group,PFK was decreased(P<0.05),Idh3g was up-regulated(P<0.05),and IL-6 was also significantly down-regulated(P<0.05)compared with(CIA+PBS)+PBS group.However,there was no significant difference in the expression of Idh3g and PFK,moreover,TNF-α and IL-6 were significantly up-regulated compared with(CIA+GSH)+GSKJ1 group and(CIA+GSH)+PBS group.Conclusion:GSH can regulate glycometabolism and inflammatory response of macrophages via demethylation of histone H3K27,and it can also alleviate CIA in mice.

Lipophosphatidic acid(LTA)was used to stimulate Mac-T cells,and the expression lev-els and phosphorylation levels of key proteins of nuclear factor-κB(NF-κB)and mitogen-activated protein kinase(MAPK)signaling pathway and the expression levels of upstream key action factors TLR4 and MyD88 proteins were detected by Western blot,and EDU assay was used to detect cell proliferation levels and flow cytometry was used to detect apoptosis.The results showed that acti-vation of GPR120 significantly decreased the phosphorylation levels of LTA-induced NF-κB(P65 and IκBα)(P＜0.01)and MAPK(JNK,ERK,p38)(P＜0.01)in Mac-T cells;inhibition of GPR120 was able to upregulate LTA-induced NF-κB(p65 and IκBα)in Mac-T cells(P＜0.01)and MAPK(JNK,ERK,p38)phosphorylation levels(P＜0.01);and activation of GPR120 significantly allevia-ted LTA-induced upregulation of TLR4 and MyD88(P＜0.01);inhibition of GPR120 significantly exacerbated LTA-induced upregulation of TLR4 and MyD88(P＜0.05);LTA stimulation led to a trend of diminished Mac-T cell proliferation and significantly increased apoptosis,whereas activa-tion of the GPR120 gene significantly increased cell activity(P＜0.01),promoted cell proliferation and significantly reduced apoptosis(P＜0.05)thereby alleviating the damage to Mac-T cells by LTA;LTA stimulation led to a highly significant increase in apoptosis(P＜0.01).In contrast,acti-vation of the GPR120 gene significantly reversed the increase in the apoptosis rate of Mac-T cells induced by LTA(P＜0.01),while inhibition of the GPR120 gene enhanced the apoptosis-promo-ting effect of LTA(P＜0.05),indicating that activation of the GPR120 gene attenuated the in-crease of apoptosis rate caused by LTA-induced inflammatory Mac-T cells.The results suggest that GPR120 can regulate inflammation by mediating TLR4 and MyD88 expression to inhibit NF-κB/MAPK inflammatory pathway activation and can promote cell proliferation.

Cerebrospinal fluid morphology examination is an important method of diagnosing central nervous system diseases, but manual microscopy has shortcomings such as low efficiency, long staff training period, and poor homogeneity of test results. In recent years, the application of artificial intelligence in the medical field has developed rapidly, providing new technical means for cerebrospinal fluid morphology examination. In the future, AI-assisted morphological examination of cerebrospinal fluid will not only realize digitalization and networking, but also improve the level and efficiency of intelligent diagnosis of cerebrospinal fluid morphology, which has a broad application prospect in the intelligent assisted diagnosis of cerebrospinal fluid.

Objective:To investigate the application of CT image omics model in the differential diagnosis of ganglioneuroblastoma (GNB) and neuroblastoma (NB) in childhood.Methods:A retrospective case series study was performed. The clinical and imaging data of 23 NB and 23 GNB pediatric patients confirmed by surgery and pathology in Shanxi Children's Hospital from January 2013 to December 2013 were collected. The original CT images in the normal scan phase, arterial phase and venous phase of all the children before operation were extracted from the PACS system in DICOM format. ITK-SNAP (ver.3.4.0) software was applied to manually outline and extract the image omics features layer by layer of the lesions in the normal scan phase, arterial phase and venous phase of each patient before surgery. The minimum absolute contraction selection operator and stepwise multi-factor logistic regression method were used to screen out effective features in different scan phases. The corresponding phase image omics model was established by using logistic model. The diagnostic efficiency of each phase of the image omics model was evaluated by using the receiver operating characteristic curve, calibration curve and decision curve.Results:A total of 1 361 image omics features were extracted from the original CT images in the 3 phases. The model was established by using multi-factor logistic regression to extract 4 features in the normal scan phase, 2 features in the arterial phase, 3 features in the venous phase and 7 features in the combination of the 3 phases. The area under the curve (AUC) of the model in the normal scan phase was 0.940, the accuracy was 89.1%, the sensitivity was 91.3% and the specificity was 87.0%; the AUC of the model in the arterial phase was 0.923, the accuracy was 84.8%, the sensitivity was 82.6%, and the specificity was 87.0%; the AUC of the model in the venous phase was 0.949, the accuracy was 87.8%, the sensitivity was 83.3%, and the specificity was 91.3%; the AUC of 3 phases combined model was 0.964, the accuracy was 95.1%, the sensitivity was 94.7%, and the specificity was 95.5%. The results showed that the single-phase image omics model was effective in the differential diagnosis of NB and GNB in childhood; the AUC, accuracy, sensitivity and specificity of the 3 phases combined imaging model were higher than those of the single-phase imaging model. The calibration curve and decision curve showed that the probability of differential diagnosis of NB and GNB in childhood by the 3 phases combined model had a high consistency with the observed value, and a good net benefit could be achieved.Conclusions:CT-based image omics model has a high clinical value in the differential diagnosis of NB and GNB in childhood.

Atrial fibrillation(AF)is one of the most common arrhythmias in clinical practice,with a high rate of death and disability.In recent years,with the help of catheter ablation and other techniques,some patients can maintain sinus rhythm,achieving the goal of eradicating AF.However,the recurrence rate of atrial arrhythmias after the first radiofrequency ablation is still around 20%to 30%at present,and the efficacy of radiofrequency ablation for AF has not yet reached the expected level.Exploring the risk factors for recurrence after ablation,inter-vening and continuously and improving the catheter ablation procedure are extremely important for reducing the risk of recurrence.This article reviews the latest research progress on the recurrence of atrial arrhythmias after catheter ablation for AF.

Objective To investigate the relationship between upper limb joint angles and muscle fatigue in overhead tasks and develop a muscle fatigue prediction model based on residual neural networks(ResNet).Methods Through the simulation of drilling experiments performed with different working postures and on different operating surfaces,the maximum voluntary contraction,maximum endurance time,maximum residual muscle force,and subjective fatigue ratings were measured.The collected data were processed and used as input for the ResNet prediction model,which was constructed to predict muscle fatigue levels.Results The ResNet model exhibited outstanding predictive accuracy,with a root mean square error(RMSE)of 0.028.Compared with traditional backpropagation neural networks(RMSE=0.053)and multilayer perceptron neural networks(RMSE=0.059),they displayed smaller errors and better fitting.Conclusions The proposed residual neural network muscle fatigue prediction model can effectively and accurately predict muscle fatigue,providing strong support for improving work efficiency and reducing the risk of work-related musculoskeletal disorders.

Objective To explore the action mechanism of tauroursodeoxycholic acid(TUDCA)promoting intracellular clearance of Burkholderia pseudomallei(B.pseudomallei)in RAW264.7 macrophages.Methods After TUDCA of different concentrations were used to treat RAW264.7 cells pre-infected with B.pseudomallei for 8 h or not,flow cytometry was applied to detect the apoptosis of the infected and control cells.In addition,another endoplasmic reticulum stress(ERS)inhibitor 4-PBA was used to detect the apoptosis and proliferation of host cells after B.pseudomallei infection with Annexin-V/PI double staining and MTT cell proliferation assay.Furthermore,after transfected with CHOP siRNA,Western blotting and flow cytometry were employed to detect the effect of TUDCA on the expression levels of Caspase-3 and Caspase-12 and the changes in apoptotic rate after B.pseudomallei infection,respectively.Finally,the effect of TUDCA on intracellular multiplication of infected RAW264.7 cells were observed to estimate the CFU value in the presence and absence of CHOP siRNA.Results Under different concentrations of TUDCA,100 or 200 μmol/L TUDCA significantly reduced B.pseudomallei-induced apoptosis in RAW264.7 cells(P＜0.05).Meanwhile,both TUDCA and 4-PBA treatment could decrease the apoptosis induced by B.pseudomallei infection by ERS(P＜0.05).Further,the expression levels of Caspase-3 and Caspase-12 were obviously increased after B.pseudomallei infection compared with uninfected groups,but their expression levels in the siCHOP group was significantly lower than that in the siC group.Besides,flow cytometry also showed that TUDCA could reduce apoptosis induced by B.pseudomallei infection(P＜0.05),but no significant effect of TUDCA on apoptosis was observed under CHOP knockdown.Finally,intracellular CFU assay indicated that TUDCA treatment promoted the host cell clearance of B.pseudomallei(P＜0.05),but no such effect was observed in siCHOP group.Conclusion In B.pseudomallei infected RAW264.7 cells,TUDCA promotes the intracellular clearance of the bacteria by inhibiting ERS-induced apoptosis.