Objective:To analyze the changes of serum metabolites in patients with acute pancreatitis (AP) by non-targeted metabolomics method.Methods:Serum samples and clinical data of 15 AP patients hospitalized in the Affiliated Hospital of Jiangnan University from August to September 2024 were collected and included in the AP group, including 9 males and 6 females, aged (55.4±15.3) years. The serum and clinical data of 25 patients with colon polyps in the same hospital during the same period of time were collected, including 15 males and 10 females, aged (61.2±11.5) years, and were included in the control group. Serum metabolomic detection was performed using the ultra-high performance liquid chromatography tandem Fourier transform mass spectrometer. The modeling method was orthogonal partial least square discriminant analysis, and principal component analysis was performed on the data matrix to screen the differential metabolites in serum of AP patients. The Kyoto Encyclopedia database of Genes and Genomes was used to annotate differential metabolites, and the pathway of differential metabolite enrichment was analyzed by software.Results:The principal component analysis showed that the contribution ratio of the first principal component was 15.1%, the proportion of the second principal component was 10.8%, and the total proportion of the two was 25.9%. In principal component analysis, two groups of samples can be clearly distinguished and show obvious clustering characteristics. According to the analysis of OPLS-DA model, there were significant differences in serum metabolic profiles between AP group and control group. There were 683 differentially expressed metabolites between the two groups, with 367 differentially expressed metabolites up-regulated compared with the control group and 316 differentially expressed metabolites down-regulated compared with the control group. It is mainly Phosphatidic Acid (Lte4/8: 0) (+ 218%), Omeprazole Sulphone (-38%), and 2-(Propylthio) Nicotinic Acid (2-propyl thionicotinic acid) (-58%), Gein (salicyricetin) (-47%) and so on. Pathway enrichment analysis showed that the differential metabolites in AP patients were mainly concentrated in citric acid cycle, arginine biosynthesis and glycerophospholipid metabolism pathways.Conclusion:Serum metabolites in AP patients change significantly, including citric acid cycle, arginine biosynthesis, glycerophospholipid metabolism.

BACKGROUND:Osteoporosis is a significant contributor to the global burden of disease and disability.Plasma proteins are involved in complex biological processes and play a crucial role in uncovering disease mechanisms and identifying potential therapeutic targets.Although existing studies have suggested an association between plasma proteins and osteoporosis,the causal nature of these associations is not fully clarified.Therefore,it is imperative to identify the causal proteins associated with osteoporosis and potential therapeutic targets for the amelioration and management of this condition using large-scale plasma protein data.OBJECTIVE:To evaluate the causal relationship between plasma proteins and osteoporosis based on the UK Biobank database as source information using the two-sample Mendelian randomization.METHODS:A total of 1 001 plasma protein-related genome-wide significant quantitative trait loci(P<5×10-8)were obtained from the UK Biobank database and used as instrumental variables,with linkage disequilibrium excluded.Summary data on osteoporosis were collected from the FinnGen database,which included 438 872 individuals of European descent.The study was analyzed using inverse variance weighting,MR-Egger regression,weighted median,and several sensitivity analyses to ensure the robustness of the results.Further,a protein-protein interaction network was constructed,and Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted to explore the functional relevance and potential mechanisms of plasma proteins.RESULTS AND CONCLUSION:(1)The Mendelian randomization analysis using the inverse variance weighted method identified 50 plasma proteins that have causal associations with osteoporosis(P<0.05).Among them,20 plasma proteins,including chromosome 19 open reading frame 12(odds ratio[OR]=0.610;95%confidence interval[CI]:0.483-0.769,P=2.967×10-5)and epidermal growth factor(EGF;OR=0.877;95%CI:0.770-0.999,P=0.049),might be associated with a reduced risk of osteoporosis.In contrast,30 plasma proteins,such as C-C motif chemokine ligand(CCL)18(OR=1.091;95%CI:1.037-1.147,P=0.001)and CD209(OR=1.036;95%CI:1.003-1.070,P=0.034),might be associated with an increased risk of osteoporosis.After Bonferroni correction,only chromosome 19 open reading frame 12 showed a significant causal association with osteoporosis.(2)Multiple sensitivity analyses revealed no evidence of pleiotropy or heterogeneity,indicating the robustness of the results.(3)The construction of the PPI network identified core proteins such as EGF,CCL5,C-X-C motif chemokine ligand(CXCL)13,CXCL5,vascular endothelial growth factor C,CCL17,CCL18,TEK receptor tyrosine kinase,tyrosine kinase with immunoglobulin like and EGF like domains 1,and CCL23.(4)Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis suggested that these plasma proteins play essential roles in the immune system,influencing osteoporosis through processes such as signal transduction,cell migration,and chemotaxis.(5)This study reveals the potential causal associations between 1 001 plasma proteins and osteoporosis,highlighting the utility of a large-scale,data-driven approach to identify new biomarkers and drug targets in diverse populations.Additionally,our findings suggest that processes such as immune signaling,cell migration,and chemotaxis play significant roles in the pathogenesis of osteoporosis,offering new directions for research under specific genetic backgrounds and environmental factors.Finally,the core proteins identified in this study(e.g.,EGF,CCL5,and CXCL13)may serve as novel biomarkers or therapeutic targets,providing a new basis for the precise prevention and treatment of osteoporosis.

BACKGROUND:Osteoporosis is a significant contributor to the global burden of disease and disability.Plasma proteins are involved in complex biological processes and play a crucial role in uncovering disease mechanisms and identifying potential therapeutic targets.Although existing studies have suggested an association between plasma proteins and osteoporosis,the causal nature of these associations is not fully clarified.Therefore,it is imperative to identify the causal proteins associated with osteoporosis and potential therapeutic targets for the amelioration and management of this condition using large-scale plasma protein data.OBJECTIVE:To evaluate the causal relationship between plasma proteins and osteoporosis based on the UK Biobank database as source information using the two-sample Mendelian randomization.METHODS:A total of 1 001 plasma protein-related genome-wide significant quantitative trait loci(P<5×10-8)were obtained from the UK Biobank database and used as instrumental variables,with linkage disequilibrium excluded.Summary data on osteoporosis were collected from the FinnGen database,which included 438 872 individuals of European descent.The study was analyzed using inverse variance weighting,MR-Egger regression,weighted median,and several sensitivity analyses to ensure the robustness of the results.Further,a protein-protein interaction network was constructed,and Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted to explore the functional relevance and potential mechanisms of plasma proteins.RESULTS AND CONCLUSION:(1)The Mendelian randomization analysis using the inverse variance weighted method identified 50 plasma proteins that have causal associations with osteoporosis(P<0.05).Among them,20 plasma proteins,including chromosome 19 open reading frame 12(odds ratio[OR]=0.610;95%confidence interval[CI]:0.483-0.769,P=2.967×10-5)and epidermal growth factor(EGF;OR=0.877;95%CI:0.770-0.999,P=0.049),might be associated with a reduced risk of osteoporosis.In contrast,30 plasma proteins,such as C-C motif chemokine ligand(CCL)18(OR=1.091;95%CI:1.037-1.147,P=0.001)and CD209(OR=1.036;95%CI:1.003-1.070,P=0.034),might be associated with an increased risk of osteoporosis.After Bonferroni correction,only chromosome 19 open reading frame 12 showed a significant causal association with osteoporosis.(2)Multiple sensitivity analyses revealed no evidence of pleiotropy or heterogeneity,indicating the robustness of the results.(3)The construction of the PPI network identified core proteins such as EGF,CCL5,C-X-C motif chemokine ligand(CXCL)13,CXCL5,vascular endothelial growth factor C,CCL17,CCL18,TEK receptor tyrosine kinase,tyrosine kinase with immunoglobulin like and EGF like domains 1,and CCL23.(4)Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis suggested that these plasma proteins play essential roles in the immune system,influencing osteoporosis through processes such as signal transduction,cell migration,and chemotaxis.(5)This study reveals the potential causal associations between 1 001 plasma proteins and osteoporosis,highlighting the utility of a large-scale,data-driven approach to identify new biomarkers and drug targets in diverse populations.Additionally,our findings suggest that processes such as immune signaling,cell migration,and chemotaxis play significant roles in the pathogenesis of osteoporosis,offering new directions for research under specific genetic backgrounds and environmental factors.Finally,the core proteins identified in this study(e.g.,EGF,CCL5,and CXCL13)may serve as novel biomarkers or therapeutic targets,providing a new basis for the precise prevention and treatment of osteoporosis.

Objective:To analyze the changes of serum metabolites in patients with acute pancreatitis (AP) by non-targeted metabolomics method.Methods:Serum samples and clinical data of 15 AP patients hospitalized in the Affiliated Hospital of Jiangnan University from August to September 2024 were collected and included in the AP group, including 9 males and 6 females, aged (55.4±15.3) years. The serum and clinical data of 25 patients with colon polyps in the same hospital during the same period of time were collected, including 15 males and 10 females, aged (61.2±11.5) years, and were included in the control group. Serum metabolomic detection was performed using the ultra-high performance liquid chromatography tandem Fourier transform mass spectrometer. The modeling method was orthogonal partial least square discriminant analysis, and principal component analysis was performed on the data matrix to screen the differential metabolites in serum of AP patients. The Kyoto Encyclopedia database of Genes and Genomes was used to annotate differential metabolites, and the pathway of differential metabolite enrichment was analyzed by software.Results:The principal component analysis showed that the contribution ratio of the first principal component was 15.1%, the proportion of the second principal component was 10.8%, and the total proportion of the two was 25.9%. In principal component analysis, two groups of samples can be clearly distinguished and show obvious clustering characteristics. According to the analysis of OPLS-DA model, there were significant differences in serum metabolic profiles between AP group and control group. There were 683 differentially expressed metabolites between the two groups, with 367 differentially expressed metabolites up-regulated compared with the control group and 316 differentially expressed metabolites down-regulated compared with the control group. It is mainly Phosphatidic Acid (Lte4/8: 0) (+ 218%), Omeprazole Sulphone (-38%), and 2-(Propylthio) Nicotinic Acid (2-propyl thionicotinic acid) (-58%), Gein (salicyricetin) (-47%) and so on. Pathway enrichment analysis showed that the differential metabolites in AP patients were mainly concentrated in citric acid cycle, arginine biosynthesis and glycerophospholipid metabolism pathways.Conclusion:Serum metabolites in AP patients change significantly, including citric acid cycle, arginine biosynthesis, glycerophospholipid metabolism.

Objective:To investigate the application value of pepsinogen, Helicobacter pylori combined with endoscopic Kimura-Takemoto classification in the diagnosis of early gastric cancer. Methods:Sixty patients with gastric cancer who received treatment in the Department of Gastroenterology, the First People's Hospital of Huzhou from January to June 2022 were included in the gastric cancer group. An additional 60 patients with benign gastric lesions (benign gastric lesion group) and 60 patients with precancerous lesions of the stomach (precancerous lesion group) were also included in this study. Serologic testing for pepsinogen and Helicobacter pylori antibody combined with endoscopic Kimura-Takemoto classification was performed to evaluate their application value in the diagnosis of early gastric cancer. Results:Compared with the benign gastric lesion and precancerous lesion groups, the pepsinogen I/pepsinogen II ratio was significantly lower, and the pepsinogen II level and Helicobacter pylori infection rate [71.67% (43/60)] were significantly higher in the gastric cancer group ( F = 108.14, 71.75, 38.43, χ2 = 6.89, all P < 0.05). Compared with the benign gastric lesion and precancerous lesion groups, the Kimura-Takenmoto classification in the gastric cancer group was significantly higher ( H = 38.91, P < 0.05). In the gastric cancer group, pepsinogen I level and pepsinogen I/pepsinogen II ratio decreased and pepsinogen II level increased with the increase of pathological stage ( F = 65.79, 5.66, 53.32, all P < 0.01). There was no significant difference in Helicobacter pylori infection rate between different stages of gastric cancer ( P < 0.05) in the gastric cancer group. There was no significant difference in Kimura-Takenmoto classification between different stages of gastric cancer (all P > 0.05) in the gastric cancer group. The area under the receiver operating characteristic curve plotted for evaluating pepsinogen I, pepsinogen II, and pepsinogen I/pepsinogen II ratio for diagnosis of gastric cancer was 0.865, 0.664, and 0.881, respectively. Conclusion:Serum pepsinogen, Helicobacter pylori combined with endoscopic Kimura-Takemoto classification can increase the diagnostic rate of early gastric cancer. The Kimura Takemoto classification is helpful for risk stratification in the endoscopic screening of gastric cancer, and its results are consistent with pepsinogen levels. The combined application is of a high application value.

Objective:To evaluate the post-marketing safety and immunogenicity of a 23-valent pneumococcal polysaccharide vaccine (PPV23).Methods:From September 2020 to June 2021, a clinical trial of single-dose PPV23 was conducted in people ≥3 years old in Centers for Disease Control and Prevention of Guizhou, Hunan and Fujian provinces. Blood samples were collects from the subjects before and 30 d after vaccination. ELISA was used to quantitatively detect IgG antibodies against capsular polysaccharides of 23 Streptococcus pneumoniae serotypes in serum samples. The adverse events (AEs) were monitored within 7 d after vaccination. Results:A total of 409 subjects were enrolled and included in safety analysis. Except for one with antibody level inversion, the other 408 participants were included in immunogenicity analysis. The levels of antibodies against the 23 Streptococcus pneumoniae serotypes were all increased after vaccination by an average of 4.24 folds. The two-fold growth rates of the antibodies ranged from 51.72% to 96.81% with a total two-fold growth rate of 78.59%. The overall rate of AEs was 27.14% (111/409). Local AEs were mainly pain, induration, redness and swollen. No serious adverse events related to vaccination occurred. Conclusions:This study preliminarily demonstrated the good immunogenicity and safety of PPV23 vaccine.