OBJECTIVES: To explore the association between GPSM2 expression level and gastric cancer progression and analyze the functional pathways and action mechanism of GPSM2. METHODS: We analyzed GPSM2 expression levels in gastric cancer tumors based on data from the GEPIA database and the clinical data of 109 patients. Public databases enrichment analysis were used to assess the impact of GPSM2 expression level on survival outcomes and the functional pathways and action mechanism of GPSM2. We further observed the effects of GPSM2 knockdown and overexpression on proliferation, migration and apoptosis of MGC803 cells using CCK-8 assay, colony formation assay, flow cytometry and immunoblotting and on the growth of MGC803 cell xenografts in nude mice. RESULTS: Bioinformatic analysis and immunohistochemical staining of the clinical specimens both revealed high GPSM2 expressions in gastric cancer (P<0.01). A high GPSM2 expression was significantly correlated with T3-4 stages, N2-3 stages, a carcinoembryonic antigen (CEA) level ≥5 μg/L, and a carbohydrate antigen (CA) 19-9 level ≥37 kU/L (P<0.05). Cox regression analysis identified high GPSM2 expression as an independent risk factor affecting 5-year survival of the patients (P<0.05). Gene ontology (GO) analysis suggested that GPSM2 was involved in cell cycle regulation. In MGC803 cells, GPSM2 overexpression significantly promoted cell proliferation and G1/S transition and xenograft growth in nude mice. KEGG pathway enrichment analysis indicated that GPSM2 executed its biological functions by regulating the p53 signaling pathway, which was confirmed by the results of immunoblotting experiments showing suppression of p53 signaling pathway activity in GPSM2-over expressing MGC803 cells. CONCLUSIONS GPSM2 is highly expressed in gastric cancer to affect patient prognosis by promoting tumor cell proliferation and G1/S transition possibly via inhibiting the p53 pathway.
Stomach Neoplasms/metabolism* ; Humans ; Cell Proliferation ; Prognosis ; Animals ; Mice, Nude ; Cell Line, Tumor ; Mice ; Apoptosis ; Tumor Suppressor Protein p53/metabolism* ; Cell Movement

OBJECTIVES: To analyze MYO1B expression in gastric cancer, its association with long-term prognosis and its role in regulating biological behaviors of gastric cancer cells. METHODS: We analyzed MYO1B expression in gastric cancer and its correlation with tumor grade, tumor stage, and patient survival using the Cancer Public Database. We also examined MYO1B expression with immunohistochemistry in gastric cancer and paired adjacent tissues from 105 patients receiving radical surgery and analyzed its correlation with cancer progression and postoperative 5-year survival of the patients. GO and KEGG enrichment analyses were used to explore the biological functions of MYO1B and the key pathways. In cultured gastric cancer cells, we examined the changes in cell proliferation, migration and invasion following MYO1B overexpression and knockdown. RESULTS: Data from the Cancer Public Database showed that MYO1B expression was significantly higher in gastric cancer tissues than in normal tissues with strong correlations with tumor grade, stage and patient prognosis (P<0.05). In the clinical tissue samples, MYO1B was significantly overexpressed in gastric cancer tissues in positive correlation with Ki67 expression (r=0.689, P<0.05) and the parameters indicative of gastric cancer progression (CEA ≥5 μg/L, CA19-9 ≥37 kU/L, G3-4, T3-4, and N2-3) (P<0.05). Kaplan-Meier analysis and multivariate Cox regression analysis suggested that high MYO1B expression was associated with decreased postoperative 5-year survival and was an independent risk factor (HR: 3.522, 95%CI: 1.783-6.985, P<0.05). MYO1B expression level was a strong predictor of postoperative survival (cut-off value: 3.11, AUC: 0.753, P<0.05). GO and KEGG analyses suggested that MYO1B may regulate cell migration and the mTOR signaling pathway. In cultured gastric cancer cells, MYO1B overexpression significantly enhanced cell proliferation, migration, and invasion and promoted the phosphorylation of Akt and mTOR. CONCLUSIONS High MYO1B expression promotes proliferation, migration and invasion of gastric cancer cells and is correlated with poor patient prognosis.
Humans ; Stomach Neoplasms/metabolism* ; Cell Proliferation ; Prognosis ; Cell Movement ; Myosin Type I/genetics* ; Neoplasm Invasiveness ; Cell Line, Tumor ; Female ; Male

OBJECTIVES: To investigate the impact of high expression of transmembrane and coiled helix structural domain 1 (TMCO1) on prognosis of gastric cancer and the possible mechanisms. METHODS: TMCO1 expression in gastric cancer and its effect on gastric cancer progression and prognosis were analyzed using publicly available databases and clinical data of patients undergoing radical surgery in our hospital, and its possible biological functions were explored using KEGG and GO analyses. In gastric cancer HGC-27 cells, the effects of lentivirus-mediated TMCO1 overexpression and TMCO1 silencing on cell apoptosis, proliferation, invasion and migration were examined. RESULTS: TMCO1 expression was significantly elevated in gastric cancer tissues (P<0.05), and its high expression was positively correlated with cancer progression (P<0.001) and a lowered postoperative 5-year survival rate of the patients (P<0.05). Bioinformatic analyses suggested that TMCO1 may affect gastric cancer cell apoptosis via Wnt signaling. In HGC-27 cells, TMCO1 overexpression significantly promoted tumor cell proliferation, inhibited cell apoptosis, and enhanced cell migration and invasion, whereas TMCO1 silencing produced the opposite effects. Western blotting showed that β-catenin levels were significantly upregulated in TMCO1-overexpressing cells and downregulated in cells with TMCO1 silencing. CONCLUSIONS TMCO1 is overexpressed in gastric cancer tissues, and its high expression promotes gastric cancer progression and affects long-term prognosis of the patients possibly by activating the Wnt/ β-catenin signaling pathway to inhibit apoptosis of gastric cancer cells.
Humans ; Stomach Neoplasms/metabolism* ; Apoptosis ; Prognosis ; Cell Line, Tumor ; Cell Proliferation ; Cell Movement ; Wnt Signaling Pathway ; beta Catenin/metabolism* ; Gene Expression Regulation, Neoplastic

Objective:To summarize the current application status of sarcopenia screening tools among community-dwelling older adults and explore the suitability of various tools in different contexts.Methods:A comprehensive search was conducted in China National Knowledge Infrastructure, Wanfang Data, VIP, China Biology Medicine disc, PubMed, Web of Science, Cochrane Library, and Embase for literature related to sarcopenia screening tools, from database inception to November 30, 2024. Two researchers independently screened the literature and extracted relevant data.Results:A total of 19 articles were included, covering seven screening tools: the Sarcopenia-Five (SARC-F) questionnaire, Sarcopenia combined with Calf Circumference (SARC-CALF), Sarcopenia-Five combined with Elderly and Body Mass Index Information (SARC-F+EBM), Calf Circumference, Ishii score, Mini Sarcopenia Risk Assessment-5 (MSRA-5), and the finger-ring test.Conclusions:Research on sarcopenia screening tools for the elderly population in China is still in its early stages, primarily focusing on the localization of tools developed abroad. Future research should further develop, optimize, and validate screening tools tailored to the characteristics of the Chinese elderly population to support the prevention and management of sarcopenia.

Objective:To study the comparative genomic characteristics of Marmota himalayana-derived (referred to as marmota-derived) Brucella abortus (B.ab). Methods:The species and types of one strain of marmota-derived Brucella and one strain of human-derived Brucella isolated from the brucellosis epidemic area in Qinghai Province in the same year were identified. Meanwhile, DNA was extracted for whole genome sequencing and comparative genomics analysis (including phylogenetic tree construction, gene family clustering analysis, common/specific gene analysis, and genomic structural variation analysis, etc.). Results:Two Brucella strains from different hosts were identified as B.ab. By constructing a phylogenetic tree, the marmota-derived B.ab strain was grouped with strains from Heilongjiang Province and showed genetic correlation with strains from Russia. Human-derived B.ab strain was classified as a strain in Inner Mongolia Autonomous Region, Hebei Province, Beijing City, and Gansu Province. The multilocus sequence typing (MLST) of the two strains belonged to the ST2 type. Multiple locus variable-number tandem repeat analysis (MLVA) belonged to two new MLVA-8 and MLVA-11 genotypes, which were clustered in two subclusters of the same cluster and clustered with the strains from Inner Mongolia Autonomous Region, Xinjiang Uygur Autonomous Region, and Hebei Province. The pan-genome numbers of the marmota-derived B.ab and human-derived B.ab were 283 and 8, respectively; the number of core genes (common genes) was 68 and 2, respectively; and the number of unique genes was 3 and 4, respectively. The unique gene encoded proteins were inconsistent. In marmota-derived B.ab, the main ones were the ABC transporter ATP-binding protein, N-terminal acetyltransferase, and glucose/galactose transporter. The number of homologous genes of the marmota-derived B.ab and human-derived B.ab was 16 and 20, respectively; the number of translocation and inversion genes was 13 and 8, respectively; the number of deletion mutation genes was 11 and 14, respectively. Pathogenicity analysis showed that both strains had the mprF resistance gene, and the marmota-derived B.ab strain also carried bacitracin and macrolide resistance genes. Conclusions:Brucella exhibits cross-species genetic diversity. The proteins encoded by the unique genes of the marmota-derived B.ab mainly play a role in metabolic and epigenetic regulation. The strains cluster with B.ab strains from northern China, providing a reference for molecular epidemiology and pathogen tracing of B.ab infection.

Objective:To summarize the current application status of sarcopenia screening tools among community-dwelling older adults and explore the suitability of various tools in different contexts.Methods:A comprehensive search was conducted in China National Knowledge Infrastructure, Wanfang Data, VIP, China Biology Medicine disc, PubMed, Web of Science, Cochrane Library, and Embase for literature related to sarcopenia screening tools, from database inception to November 30, 2024. Two researchers independently screened the literature and extracted relevant data.Results:A total of 19 articles were included, covering seven screening tools: the Sarcopenia-Five (SARC-F) questionnaire, Sarcopenia combined with Calf Circumference (SARC-CALF), Sarcopenia-Five combined with Elderly and Body Mass Index Information (SARC-F+EBM), Calf Circumference, Ishii score, Mini Sarcopenia Risk Assessment-5 (MSRA-5), and the finger-ring test.Conclusions:Research on sarcopenia screening tools for the elderly population in China is still in its early stages, primarily focusing on the localization of tools developed abroad. Future research should further develop, optimize, and validate screening tools tailored to the characteristics of the Chinese elderly population to support the prevention and management of sarcopenia.

Objective To explore the correlation between glycolysis related indexes of peripheral blood mononuclear cells(PBMCs)[glucose transporter 1(GLUT1),fructose-2,6-diphosphatase 3(PFKFB3)and lactate kinase M2(PKM2)]and intracranial pressure and clinical prognosis of patients with hypertensive cerebral hemorrhage(HICH)who broke into the ventricle.Methods 85 HICH patients hospitalized in our hospital from January 2021 to June 2022 were retrospectively collected as the research participants.The levels of PKM2,GLUT1 and PFKFB3 in PBMCs were analyzed by enzyme-linked immunosorbent assay kit.Six months after the onset of HICH,the short-term outcome was evaluated by modified Rankin scale(mRS),and the patients were divided into good prognosis(mRS score≤2)and poor prognosis(mRS score≥3).Results The levels of PKM2,PFKFB3 and GLUT1 in PBMCs of HICH patients with ventricular rupture were further lower than those of the patients without ventricular rupture(P<0.05).Six months after discharge,8 patients(22.9%)with HICH in non-ventricular rupture group had poor prognosis,while 28 patients(56.0%)with HICH in ventricular rupture group had poor prognosis,and the difference was statistically significant(χ2=9.263,P=0.002).Compared with the group with good prognosis,the levels of PKM2 and GLUT1 in PBMCs of HICH patients with poor prognosis were lower(P<0.05).Compared with the good prognosis group,the levels of PKM2 and GLUT1 in PBMCs of HICH patients with poor prognosis group were lower in HICH patients with ventricular rupture(P<0.05).In HICH patients who broke into the ventricle,the AUC of PKM2 and GLUT1 in predicting the poor prognosis of HICH patients were 0.879(95%CI:0.807～0.951)and 0.897(95%CI:0.831～0.963),respectively.Conclusion The levels of PKM2 and GLUT1 in PBMCs of patients with HICH breaking into ventricles decrease significantly,and are negatively correlated with intracranial pressure,which can be used to predict the short-term prognosis of the patients.

ObjectiveTo explore the role of flurochloridone (FLC) on osteogenic differentiation and the potential mechanism of inhibiting bone formation, and to provide new insights into bone health risks associated with FLC pesticide exposure. MethodsNeonatal rat skull differentiation primary osteoblast model was used to investigate the effects of 1, 10 and 100 μmol·L^-1 FLC exposure on cell viability, osteogenic differentiation alkaline phosphatase (ALP) activity, and bone mineralization nodule formation, respectively. The potential mechanism underlying the inhibition of FLC on osteoblast differentiation was analyzed using osteogenic differentiation gene chip technique, and the expression of key genes and proteins in the pathway was validated using reverse transcription polymerase chain reaction (RT-PCR) and protein immunoblotting (Western blot) methods. ResultsExposure to FLC at a concentration of 100 μmol·L⁻¹ reduced cell proliferation, ALP activity, and the formation of mineralized nodules in primary osteoblasts. Gene chip analyses revealed that exposure to 10 μmol·L⁻¹ FLC induced 15 differentially expressed genes (DEGs). Among these, MMP9 and Tnf were up-regulated, while Nkx3⁃2, Tuft1, Bmp2, Col12a1, Pparg, Enam, Igf1, Bmp5, Bmp3, Calcr, Egf, Igfbp3, and Col14a1 were down-regulated. Results of protein-protein interaction analyses and gene ontology enrichment analyses indicated that FLC inhibited the BMP/SMAD pathway involved in osteogenic differentiation. FLC suppressed the protein expression of BMP2 and Osterix, as well as the expression of key genes critical for osteogenic differentiation and ossification, such as BMP2, Runx2, SMAD1, and SMAD5 in the BMP/SMAD pathway. ConclusionFLC affects osteogenic differentiation and bone formation potential by regulating the BMP/SMAD axis and the expression of osteogenic genes, suggesting its potential risk in bone metabolism.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.

BACKGROUND:Cervical spondylosis is a chronic degenerative disease that has become one of the most common and frequent diseases threatening human health.At present,the initial diagnosis of the cervical spine and its surrounding structures mainly relies on the interpretation of medical images by radiologists,which not only requires a high level of technical requirements for operators,but also has the disadvantages of strong subjectivity,high labor intensity,and low efficiency.With the rapid development of artificial intelligence technology,its powerful data processing and image recognition capabilities have shown broad application prospects in the medical field.Deep learning has also made certain progress in the research of spinal diseases.OBJECTIVE:To summarize the current status and research progress in the application of artificial intelligence technology in cervical spine imaging images in recent years,evaluating the performance of artificial intelligence models as well as future trends and challenges to be overcome.METHODS:The first author searched the relevant articles in WanFang,CNKI,and PubMed in June 2024.The Chinese search terms were"artificial intelligence,deep learning,cervical spine."English serach terms were"artificial intelligence,Al,cervical vertebrae,cervical."Finally,101 articles were included and analyzed.RESULTS AND CONCLUSION:(1)Artificial intelligence technology can realize automatic segmentation of cervical vertebrae and measurement of curvature change by segmentation,classification,landmarks recognition of medical image parts,detect cervical vertebral fracture,nerve root,and spinal cord type cervical spondylosis,identify cervical spine ossification of posterior longitudinal ligament,and predict post-surgery related risk factors and cervical vertebra maturation classification.(2)Although artificial intelligence technology has shown great potential in the field of cervical spine research,it is still in the early stages of exploration and rapid development,with unlimited room for development and innovation.