With the rapid development of artificial intelligence and machine learning algorithms in the med-ical field,as well as the high-quality development requirements put forward by the state for hospitals and vari-ous departments,the development of laboratory medicine shows a new trend.The development of clinical labo-ratory has evolved from the initial test suite to the test pathway based on clinical pathway and diagnosis-relat-ed groups payment,and then to clinical laboratory omics.Clinical laboratory omics refers to the use of high-throughput methods to obtain a large number of laboratory project results data.Combined with the clinical characteristics of patients,statistical methods and machine learning algorithms are commonly used to reveal the information behind a large number of medical data to assist clinicians in diagnosis and treatment.Clinical laboratory omics may be a new trend in the future development of laboratory medicine,and it is likely to play an important role in the field of laboratory medicine.

Background and purpose:Gastric cancer,as one of the most common malignant tumors,requires early diagnosis and treatment to improve patient prognosis.This study,based on serum quantitative proteomics research of early-stage gastric cancer patients and non-gastric cancer patients,aims to identify potential diagnostic biomarkers for early gastric cancer.Methods:Serum samples from primary gastric cancer patients and healthy control individuals were collected from Lanzhou University Second Hospital between June and December 2023,following inclusion and exclusion criteria.A protein spectral library was established using Data-Dependent Acquisition(DDA)mode,and each sample was analyzed using Data-Independent Acquisition(DIA)mode.The STRING database was used to analyze protein-protein interactions of upregulated proteins in gastric cancer serum.Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)were used to analyze the pathways and functional annotations of the corresponding genes.Gene expression levels in gastric cancer and non-gastric cancer tissues were analyzed using GEPIA 2,and overall survival of each gene in gastric cancer was analyzed using Kaplan-Meier Plotter.Differential gene expression in clinical gastric cancer and adjacent tissues was validated by quantitative reverse transcription polymerase chain reaction(qRT-PCR)This study was approved by the Ethics Committee of Lanzhou University Second Hospital(Ethical No.:2023A-459)and was exempt from the informed consent.Results:Finally,serum samples from 30 primary gastric cancer patients,29 healthy control individuals,along with the para-cancerous tissues from 8 patients were collected.A total of 666 intersecting proteins were identified through serum quantitative proteomics.Among them,16 proteins showed upregulated expression and 22 proteins showed downregulated expression in the gastric cancer group(P＜0.05,|FC|≥1.5).STRING database analysis showed that 10 upregulated proteins were involved in interaction networks.KEGG and GO analysis indicated that these genes were closely related to the biological processes of cancer occurrence and development.GEPIA 2 and Kaplan-Meier Plotter analysis showed that 6 genes,B2M,TAGLN2,CTSD,HSP90AB1,SH3BGRL3,and CFL1,which were highly expressed in the gastric cancer group(P＜0.05)and associated with poor prognosis.Clinical verification by qRT-PCR confirmed that TAGLN2,CTSD,SH3BGRL3,CFL1 and HSP90AB1 were highly expressed in gastric cancer tissues(P＜0.05).Conclusion:TAGLN2,CTSD,SH3BGRL3,CFL1,and HSP90AB1 have the potential to serve as clinical early gastric cancer diagnostic serum biomarkers,which may facilitate early diagnosis and treatment of gastric cancer.

Background and purpose:Gastric cancer,as one of the most common malignant tumors,requires early diagnosis and treatment to improve patient prognosis.This study,based on serum quantitative proteomics research of early-stage gastric cancer patients and non-gastric cancer patients,aims to identify potential diagnostic biomarkers for early gastric cancer.Methods:Serum samples from primary gastric cancer patients and healthy control individuals were collected from Lanzhou University Second Hospital between June and December 2023,following inclusion and exclusion criteria.A protein spectral library was established using Data-Dependent Acquisition(DDA)mode,and each sample was analyzed using Data-Independent Acquisition(DIA)mode.The STRING database was used to analyze protein-protein interactions of upregulated proteins in gastric cancer serum.Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)were used to analyze the pathways and functional annotations of the corresponding genes.Gene expression levels in gastric cancer and non-gastric cancer tissues were analyzed using GEPIA 2,and overall survival of each gene in gastric cancer was analyzed using Kaplan-Meier Plotter.Differential gene expression in clinical gastric cancer and adjacent tissues was validated by quantitative reverse transcription polymerase chain reaction(qRT-PCR)This study was approved by the Ethics Committee of Lanzhou University Second Hospital(Ethical No.:2023A-459)and was exempt from the informed consent.Results:Finally,serum samples from 30 primary gastric cancer patients,29 healthy control individuals,along with the para-cancerous tissues from 8 patients were collected.A total of 666 intersecting proteins were identified through serum quantitative proteomics.Among them,16 proteins showed upregulated expression and 22 proteins showed downregulated expression in the gastric cancer group(P＜0.05,|FC|≥1.5).STRING database analysis showed that 10 upregulated proteins were involved in interaction networks.KEGG and GO analysis indicated that these genes were closely related to the biological processes of cancer occurrence and development.GEPIA 2 and Kaplan-Meier Plotter analysis showed that 6 genes,B2M,TAGLN2,CTSD,HSP90AB1,SH3BGRL3,and CFL1,which were highly expressed in the gastric cancer group(P＜0.05)and associated with poor prognosis.Clinical verification by qRT-PCR confirmed that TAGLN2,CTSD,SH3BGRL3,CFL1 and HSP90AB1 were highly expressed in gastric cancer tissues(P＜0.05).Conclusion:TAGLN2,CTSD,SH3BGRL3,CFL1,and HSP90AB1 have the potential to serve as clinical early gastric cancer diagnostic serum biomarkers,which may facilitate early diagnosis and treatment of gastric cancer.

Atherosclerosis is a multifocal, smoldering, immunoinflammatory disease caused by lipid accumulation. Acute cardio-cerebrovascular disease caused by AS is one of the most serious life threats in the world. Endothelial cell injury, vascular inflammatory stimulation, abnormal lipid metabolism and coagulation disorder are the main pathological mechanisms of AS. Thrombomodulin (TM) is a transmembrane glycoprotein mainly expressed on the surface of endothelium. It plays a key role in maintaining the dynamic equilibrium of the vascular system through its functions of anti-coagulation, anti-inflammation and cell protection. Recombinant human soluble thrombomodulin (rhsTM), a soluble form of human TM containing the extracellular domain of TM, might be effective in the treatment of AS. This review summarizes the structure and function of TM and the mechanism of rhsTM in the treatment of AS. Aiming to provide new ideas for the prevention and treatment of AS.

Objective:To explore the level changes of common laboratory indexes in patients with ischemic stroke (IS) with different infarct sizes and their clinical application value.Methods:The baseline data of 237 patients hospitalized in Lanzhou University Second Hospital from June 2019 to December 2020 and their laboratory indicators within 24 hours of admission were collected. The patients were divided into lacunar group ( n=80) and infarct group ( n=157) according to the infarct area. The experimental indexes and clinical data of the two groups were compared. Binary logistic regression was used to screen the independent influencing factors of infarct size and establish a joint diagnostic model. The receiver operating characteristic (ROC) curve and model calibration chart were used to verify the clinical application value of each index. Results:The levels of cholesterol (CHO)/high density lipoprotein (HDL), low density lipoprotein (LDL)/HDL, neutrophil count, Cystatin C (Cys C), phosphorus (PHOS), indirect bilirubin (IBIL), LDL, apolipoprotein (ApoB), homocysteine (HCY), D-dimer, smoking, drinking, overweight and arterial stenosis in the infarct group were higher than those in the lacunar group (all P<0.05), and the levels of apolipoprotein A Ⅰ (ApoAⅠ)/ApoB, ApoAⅠ and carbon dioxide (CO 2) in the infarct group were lower than those in the lacunar group (all P<0.05). ApoA Ⅰ/ApoB and CO 2 were independent protective factors of infarct size (all P<0.05); Cys C, PHOS and IBIL were independent risk factors of infarct size (all P<0.05). The combined prediction model of CO 2, PHOS, IBIL, ApoA Ⅰ/ApoB and Cys C has good prediction efficiency for infarct area, and the area under the curve (AUC) of combined diagnosis was 0.739. Conclusions:Laboratory indicators are closely related to the infarct size of IS. The model developed in this study have good clinical value, which provides a new basis for IS evaluation and early warning.

OBJECTIVE: To explore the pathogenesis of gastric cancer through a bioinformatic approach to provide evidence for the prevention and treatment of gastric cancer. METHODS: The differentially expressed genes (DEGs) in gastric cancer and normal gastric mucosa in GSE79973 dataset were analyzed using GEO2R online tool. GO analysis and KEGG pathway enrichment analysis of the DEGs in DAVID database were performed. The protein interaction network was constructed using STRING database, and the key genes (Hub genes) were screened and their functional modules were analyzed using Cytoscape software. The GEPIA database was used to validate the Hub genes, and the Target Scan database was used to predict the microRNAs that regulate the target genes; OncomiR was used to analyze the expressions of the microRNAs in gastric cancer tissues and their relationship with the survival outcomes of the patients. RESULTS: A total of 181 DEGs were identified in gastric cancer, and 10 hub genes were screened by the protein- protein interaction network. Functional analysis showed that these DEGs were involved mainly in protein digestion and absorption, PI3K-Akt signaling pathway, ECM-receptor interaction and platelet activation signal pathway. GEPIA database validation showed that COL1A1 was highly expressed in gastric cancer tissues and was associated with a poor prognosis of patients with gastric cancer. MiR-129-5p was found to bind to the 3'UTR of COL1A1 mRNA, and compared with that in normal tissues, miR-129-5p expression was obviously down-regulated in gastric cancer tissues, and was correlated with the prognosis of the patients. CONCLUSIONS COL1A1 under regulation by MiR-129-5p is a potential therapeutic target for gastric cancer.
Collagen Type I ; drug effects ; Computational Biology ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Humans ; MicroRNAs ; therapeutic use ; Phosphatidylinositol 3-Kinases ; Stomach Neoplasms ; drug therapy

Objective To evaluate the utility of fluorescent dye SYTO 13 for high -resolution melting ( HRM) detection in single nucleotide polymorphism ( SNP) genotyping and its clinical application . Methods This is a performance verification study .36 genotype defined samples were divided into three groups:SNP rs3125734 C>T (class Ⅰ SNP) ,rs255758 A>C (class ⅡSNP) and rs688C>T.These samples were used to evaluate SYTO 13′s SNP genotyping capability of class ⅠSNP, classⅡSNP, and two PCR products of different lengths (52 and 107 bp) covering the same SNP of rs688C>T.The commercial HRM dye of LCGreen Plus was used as the control .The genotyping capability is indicated by the Tm difference(ΔTm) between wild type and homozygous mutant genotypes .The Tm differences between wild genotype and homozygous mutant genotype were compared using the Independent Samples t test.Paired t test was used to evaluate genotyping capability of the two dyes .The clinical applicability is evaluated by synchronously performing PCR amplification and HRM analysis on thirty -five randomly selected DNA samples with known genotypes of the three SNPs .Results The SNPs of class Ⅰ and class Ⅱ can be genotyped directly and clearly with SYTO13 (ΔTmclas Ⅰ =0.36 ±0.05,tclas Ⅰ =14.827,Pclas Ⅰ =0.000;ΔTm clas Ⅱ =0.42 ±0.110,tclasⅡ =9.539,Pclas Ⅱ =0.000).The classⅠSNP genotyping results was better using SYTO13 (ΔTmSYTO13 =0.39 ±0.027), while the SNP genotyping for small amplicon did not discriminated clearly in this study .Long amplicons of class ⅠandⅡSNPs can be identified directly except for several samples which can be genotyped accurately after having performed reexamination .Conclusion SYTO13 can apply for HRM analysis of genotyping classⅠand ⅡSNPs with long amplicon and for clinical routine detection.

OBJECTIVE To measure the compliance of laboratory personnel with different components of hand hygiene and improve their concerns for prevention.METHODS By checking and evaluating the exposing risks factors,including HIV,HBV and HCV source of infections,we found and formulated effective ways for preventing occupational disease.RESULTS The level of compliance at the end of duty was 95.0%.Pathogenic microorganisms were exclusively found on hands of laboratory personnel who wore jewelry.CONCLUSIONS Accurate evaluation and practical preventive strategies are key factors to reduce the professional exposing risks.Hand hygiene should be directed not only at healthcare workers but also at laboratory personnel.

Objective:To discuss mice cellular immune response to the hepatitis C viral nucleic acid vaccine.Methods:Hepatitis C viral nucleic acid vaccine pSVL HCV/C+E 1 was inoculated BALB/C mice by subcutaneous injection.To detect the CTL activity of immune mice,Made the standard 4 hours lysis test by labeling the target cells with (Na) 2 51 CrO 4,which was prepared from the syngentic BALB/C mouse myeloma derived cell strain SP2/0 transfected by the eukaryotic expression recombinant plasmid pEGFP N 1 HCV/C+E 1.Results:The kill ratio of CTL is up to 40.7%.Conclusion:The result suggested hepatitis C viral nucleic acid vaccine could induce strong cellular immune response