Objective To explore the effect of pristimerin combined with cisplatin on proliferation and apoptosis of nasopharyngeal carcinoma cells.Methods CCK-8 assay was used to examine the survival rate of HNE-1 and CNE-2Z cells following treatment for 24 h with different concentrations of pristimerin,cisplatin or their combination.The changes in colony formation ability,apoptosis,and intracellular reactive oxygen species(ROS)levels of the treated cells were analyzed using colony formation assay and flow cytometry.Western blotting was performed to detect the changes in protein expressions in the cells.The effects of pre-treatment with NAC on proliferation,apoptosis,and PI3K/AKT signaling pathway were observed in pristimerin-and/or cisplatin-treated cells.Results Both pristimerin and cisplatin significantly lowered the survival rate of HNE-1 and CNE-2Z cells(P<0.05).Compared with pristimerin or cisplatin alone,their combination more strongly inhibited survival and colony formation ability of the cells,increased cell apoptosis rate and intracellular ROS levels,upregulated the protein expressions of Bax,cleaved caspase-3,and cleaved PARP,and downregulated the protein expressions of Bcl-2,Mcl-1,PARP and p-PI3K and p-AKT(P<0.05).NAC pretreatment significantly attenuated proliferation inhibition and apoptosis-promoting effects of pristimerin combined with cisplatin,and partially restored the downregulated protein expressions of p-PI3K and p-AKT in HNE-1 and CNE-2Z cells with the combined treatment(P<0.05).Conclusion Pristimerin can enhance cisplatin-induced proliferation inhibition and apoptosis in nasopharyngeal carcinoma cells,the mechanism of which may involve ROS-mediated deactivation of the PI3K/AKT signaling pathway.

Objective To investigate the expression of TSR2 in gastric cancer and explore its correlation with progression of gastric cancer and the possible mechanism.Methods We retrospectively analyzed TSR2 expression in clinical specimens from 105 gastric cancer patients and the impact of TSR2 expression level on disease progression and 5-year postoperative survival of the patients.GO and KEGG enrichment analyses were used to predict the biological functions and mechanisms of TSR2.In gastric cancer MGC-803 cells with lentivirus-mediated TSR2 overexpression or knockdown,the changes in cell proliferation,invasion,and migration were assessed with CCK-8 and Transwell assays,and the expressions of p-PI3K and p-AKT were detected using Western blotting.Results TSR2 expression was significantly lower in gastric cancer tissues than in the adjacent tissues with significant correlations with CEA level,CA19-9 level,and T and N staging(P<0.05).A low TSR2 expression,CEA≥5 μg/L,CA19-9≥37 kU/L,T3-T4 stages,and N2-N3 staged were identified as independent risk factors affecting 5-year survival rate of the patients following radical surgery(P<0.05),and a high TSR2 expression was associated with a higher 5-year survival rate of the patients(P<0.001).Bioinformatics analysis suggested the functional involvement of TSR2 with the PI3K/AKT signaling pathway.MGC-803 cells overexpressing TSR2 showed significantly lowered proliferation,migration,and invasion capacities(P<0.05),while TSR2 knockdown produced the opposite effects(P<0.05).Western blotting showed that TSR2 overexpression reduced the phosphorylation of PI3K and AKT,and TSR2 knockdown caused the opposite changes in MGC-803 cells(P<0.05).Conclusion TSR2 is lowly expressed in gastric cancer tissues to adversely affect the patients'prognosis,and its overexpression inhibits gastric cancer cell proliferation,invasion,and migration possibly by downregulating the PI3K/AKT pathway.

Objective To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related genes.Methods The GSE95065 and GSE59785 datasets of scleroderma from GEO database were used for analyzing expressions of mitochondria-related genes,and the differential genes were identified by Random forest,LASSO regression and SVM algorithms.Based on these differential genes,an artificial neural network model was constructed,and its diagnostic accuracy was evaluated by 10-fold crossover verification and ROC curve analysis using the verification dataset GSE76807.The mRNA expressions of the key genes were verified by RT-qPCR in a mouse model of scleroderma.The CIBERSORT algorithm was used to estimate the bioinformatic association between scleroderma and the screened biomarkers.Results A total of 24 differential genes were obtained,including 11 up-regulated and 13 down-regulated genes.Seven most relevant mitochondria-related genes(POLB,GSR,KRAS,NT5DC2,NOX4,IGF1,and TGM2)were screened using 3 machine learning algorithms,and the artificial neural network diagnostic model was constructed.The model showed an area under the ROC curves of 0.984 for scleroderma diagnosis(0.740 for the verification dataset and 0.980 for cross-over validation).RT-qPCR detected significant up-regulation of POLB,GSR,KRAS,NOX4,IGF1 and TGM2 mRNAs and significant down-regulation of NT5DC2 in the mouse models of scleroderma.Immune cell infiltration analysis showed that the differential genes in scleroderma were associated with follicular helper T cells,immature B cells,resting dendritic cells,memory activated CD4+T cells,M0 macrophages,monocytes,resting memory CD4+T cells and mast cell activation.Conclusion The artificial neural network diagnostic model for scleroderma established in this study provides a new perspective for exploring the pathogenesis of scleroderma.

Objective To explore the pharmacologically active components in areca nut that induce oral submucosal fibrosis(OSF)and the possible mechanism.Methods The chemical components in areca nut were analyzed using Thermo QE plus liquid chromatography tandem high-resolution mass spectrometer and Compound discover 3.2 data processing software.The chemical activity of the top 20 compounds was analyzed based on Chinese Pharmacopoeia(2015),PubChem,Chemical book,and SciFinder databases.The potential active components,core targets,biological functions and signaling pathways affecting OSF were analyzed by network pharmacology.The targets of OSF were obtained by integrating Genecards and KEGG databases.The compounds acting on the targets were selected from the Systematic Pharmacology Technology Platform of Traditional Chinese Medicine(TCMSP),and the target-compound,compound-TCM,target-compound-TCM network was constructed.Molecular docking was used to analyze the component-target binding.Immunohistochemistry was used to examine the expressions of key proteins in the PI3K-Akt and MAPK pathways in clinical samples of OSF.Results The core intersection target genes between the top 10 active ingredients in areca nut extract and OSF involved mainly the PI3K-Akt and MAPK pathways.In the clinical samples,the expressions of PI3K protein decreased and the expressions p-PI3K,AKT1 and P-Akt all increased significantly in OSF tissue,where increased JNK protein expression and enhanced activity of c-Jun and c-Fos transcriptional factors were also detected.The OSF patients had significantly elevated plasma levels of IL-6 and IL-8 compared with healthy individuals.Conclusion The main active ingredients including arecoline,arecaine,and guvacine are capable of activating the PI3K-Akt and MAPK pathways to promote the expressions of inflammatory mediators IL-6 and IL-8 and induce collagen hyperplasia,thus leading to the occurrence of oral submucosal fibrosis.

Objective To explore the potential pathogenic genes of intestinal metaplasia.Methods Twenty-one patients with intestinal metaplasia admitted to the Department of Gastroenterology at the Second Affiliated Hospital of Anhui University of Chinese Medicine from January,2022 to June,2022,and 21 healthy subjects undergoing gastroscopic examination during the same period were enrolled in this study.All the participants underwent gastroscopy and pathological examination,and gastric tissue samples were collected for transcriptome sequencing to screen for differentially expressed genes(DEGs).The biological functions of the DEGs were analyzed using bioinformatics analysis,and qRT-PCR was used to validate the results.Results Transcriptomic sequencing identified a total of 1373 DEGs,including 827 upregulated and 546 downregulated ones.The top 6 upregulated genes(AGMAT,CCL25,FABP1,CDX1,SPINK4,and MUC2),ranked based on their significance and average expression level,were selected for validation,and qRT-PCR showed significant upregulation of their mRNAs in the gastric tissues of patients with intestinal metaplasia(P<0.05).Conclusion AGMAT,CCL25,FABP1,CDX1,SPINK4,and MUC2 participate in the occurrence and development of intestinal metaplasia,and may serve as potential biomarkers for diagnosing intestinal metaplasia.

Objective To propose a CT truncated data reconstruction model(DDTrans)based on projection and image dual-domain Transformer coupled feature learning for reducing truncation artifacts and image structure distortion caused by insufficient field of view(FOV)in CT scanning.Methods Transformer was adopted to build projection domain and image domain restoration models,and the long-range dependency modeling capability of the Transformer attention module was used to capture global structural features to restore the projection data information and enhance the reconstructed images.We constructed a differentiable Radon back-projection operator layer between the projection domain and image domain networks to enable end-to-end training of DDTrans.Projection consistency loss was introduced to constrain the image forward-projection results to further improve the accuracy of image reconstruction.Results The experimental results with Mayo simulation data showed that for both partial truncation and interior scanning data,the proposed DDTrans method showed better performance than the comparison algorithms in removing truncation artifacts at the edges and restoring the external information of the FOV.Conclusion The DDTrans method can effectively remove CT truncation artifacts to ensure accurate reconstruction of the data within the FOV and achieve approximate reconstruction of data outside the FOV.

Objective To assess the effects of repeated mild traumatic brain injury(rmTBI)in the parietal cortex on neuronal morphology and synaptic plasticity in the medulla oblongata of mice.Methods Thirty-two male ICR mice were randomly divided into sham operation group(n=8)and rmTBI group(n=24).The mice in the latter group were subjected to repeated mild impact injury of the parietal cortex by a free-falling object.The mice surviving the injuries were evaluated for neurological deficits using neurological severity scores(NSS),righting reflex test and forced swimming test,and pathological changes of the neuronal cells in the medulla oblongata were observed with HE and Nissl staining.Western blotting and immunofluorescence staining were used to detect the expressions of neuroligin 1(NLG-1)and postsynaptic density protein 95(PSD-95)in the medulla oblongata of the mice that either survived rmTBI or not.Results None of the mice in the sham-operated group died,while the mortality rate was 41.67%in rmTBI group.The mice surviving rmTBI showed significantly reduced NSS,delayed recovery of righting reflex,increased immobility time in forced swimming test(P<0.05),and loss of Nissl bodies;swelling and necrosis were observed in a large number of neurons in the medulla oblongata,where the expression levels of NLG-1 and PSD-95 were significantly downregulated(P<0.05).The mice that did not survive rmTBI showed distorted and swelling nerve fibers and decreased density of neurons in the medulla oblongina with lowered expression levels of NLG-1 and PSD-95 compared with the mice surviving the injuries(P<0.01).Conclusion The structural and functional anomalies of the synapses in the medulla oblongata may contribute to death and neurological impairment following rmTBI in mice.

Objective To develop the'E-Bone',a comprehensive one-stop preoperative planning system for reverse total shoulder arthroplasty with improved accuracy and efficiency.Methods The nnU-net deep neural network was utilized for scapula segmentation to obtain precise scapula segmentation results.Based on the 3 key factors,namely bone density,upward and downward angle and nail length,the base was automatically positioned.The quantitative parameters required for surgical planning were calculated.A personalized guide plate was generated by combining glenoid morphology and base positioning information.The system interface was developed to modularize various functions for easy use,providing interactive operation and real-time display.Results Compared with the Mimics system,the'E-bone'preoperative planning system reduced complex manual adjustments during the planning process.The average planned nail length was longer than that of the Mimics system,and the planning time was reduced by 86%.The scapula segmentation accuracy of this system reached 99.93%,better than that of Mimics to achieve a higher precision.Conclusion The"E-bone"system provides a one-stop,efficient,and accurate preoperative planning system for reverse shoulder replacement and potentially broader clinical applications.

Objective To analyze the expression level of ATP5A1 in gastric carcinoma and its influence on the prognosis of the patients and glucose metabolism in the tumor cells.Methods We retrospectively analyzed the data of 115 patients undergoing radical resection of gastric carcinoma in our hospital from February,2013 to November,2016.ATP5A1 expression in the surgical specimens were detected using immunohistochemistry,and the long-term prognosis of the patients with high(n=58)and low ATP5A1 expression(n=57)were analyzed.In gastric carcinoma MGC803 cells,the effects of lentivirus-mediated ATP5A1 knockdown or overexpression on glucose metabolism were investigated.We also observed the growth and glucose metabolism of xenografts derived from MGC803 cells with ATP5A1 knockdown or overexpression in nude mice.Results ATP5A1 was significantly overexpressed in gastric carcinoma tissues in close correlation with blood CEA and CA19-9 levels,pathological grade,T stage and N stage(P<0.05).ATP5A1 overexpression was an independent risk factor for a significantly lowered 5-year survival rate of patients with gastric carcinoma(P<0.05).ROC curve analysis demonstrated the predictive value of high ATP5A1 expression for the patients'prognosis(P<0.001).In MGC803 cells,ATP5A1 overexpression significantly up-regulated cellular glucose uptake and lactate production and increased the protein levels of HK2,PFK1,and LDHA(P<0.05),while ATP5A1 knockdown produced the opposite changes(P<0.05).In the tumor-bearing mice,overexpression of ATP5A1 increased glucose metabolism of the tumor cells and promoted tumor growth(P<0.05).Overexpression of ATP5A1 promoted the expressions of p-JNK and p-JUN in MGC803 cells(P<0.05),and the JNK inhibitor SP600125 significantly inhibited the enhancement of cellular glucose metabolism induced by ATP5A1 overexpression(P<0.05).Conclusion High ATP5A1 expression in gastric cancer is associated a poor long-term prognosis of the patients,and its effect is mediated at least partly by promoting glucose metabolism of the cells through the JNK/JUN pathway.

Objective To investigate cyclin D2(CCND2)expression in papillary thyroid carcinoma(PTC)and its association with the clinicopathological features.Methods The public databases TCGA,TIMER 2.0 and UALCAN were used to explore CCND2 expression level in PTC and adjacent tissues,and its diagnostic value for PTC was analyzed using ROC curves.GO enrichment analysis of CCND2-related differentially expressed genes(DEGs)in PTC was performed,and tumor immune infiltration of CCND2 in thyroid cancer was analyzed using TIMER database and CIBERSORT data source.RT-qPCR and Western blot were used to detect CCND2 expression in normal human thyroid cell line Nthy-ori-3-1 and human PTC cell lines TPC-1 and BCPAP.CCND2 expression was also detected in clinical specimens of PTC and adjacent tissues by immunohistochemistry,and its correlation with clinicopathological features of the patients were analyzed.Results Informatic analysis revealed significantly higher CCND2 mRNA expression in thyroid cancer than in the adjacent tissues(P<0.001)in close correlation with tumor stage,gender,age,pathological subtype,and lymph node involvement(P<0.05).ROC curve analysis showed that at the cutoff value of 4.983,the diagnostic sensitivity,specificity,and accuracy of CCND2 expression for PTC was 83.6%,94.9%,and 78.5%,respectively.CCND2 expression was positively correlated with B cells,CD4+T cells,and macrophages(P<0.001)and negatively with CD8+T cells(P<0.01),and also correlated with memory B-cell infiltration,CD4+T-cell memory activation,M2 macrophages,resting mast cells,and mast cell activation(P<0.05).RT-qPCR,Western blot and immunohistochemistry showed significantly higher CCND2 expression in the PTC cells than in Nthy-ori-3-1 cells(P<0.01)and also in clinical PTC tissues than in the adjacent tissues(P<0.05)in correlation with tumor size,lymph node metastasis and TNM stage(P<0.05).Conclusion CCND2 overexpression is closely correlated with tumor progression and immune cell infiltration in PTC patients..