The iridoid glycosides from Veronica anagallis-aquatica L. alleviate heart failure by modulating the gut microbiota and influencing the production of two metabolites with potential antihypertrophic effects, HVA and 2OH-VA.Image 1.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

BACKGROUND:Osteoporosis affects the quality of life of patients and is prone to pathological fractures,and plant-derived exosome-like nanovesicles play an important role in regulating bone balance in patients with osteoporosis.OBJECTIVE:To review the research status and prospect of different plant-derived exosome-like nanovesicles in the treatment of osteoporosis.METHODS:Relevant literature in PubMed,Web of Science,and CNKI databases were searched by computer.Search time was from January 1995 to March 2024.The Chinese and English search terms were"osteoporosis,plant-derived exosome-like nanovesicles,exosomes,osteoblasts,osteoclasts."Finally,53 articles were included and analyzed.RESULTS AND CONCLUSION:Plant-derived exosom-like nanovesicles have the advantages of low biocompatibility,low toxicity,and natural targeting.These properties not only ensure its stable presence and effective effect in the body,but also avoid unnecessary immune responses,laying the foundation for the design of long-term treatment strategies.Plant-derived exosome-like nanovesicles can be anti-osteoporosis by stimulating osteoblast proliferation,inhibiting osteoclast differentiation,and promoting osteo-inhibition osteoclasts.In addition,some plant-derived exosome-like nanovesicles may be widely used in the diagnosis and treatment of osteoporosis in the future as novel tracer targets and treatment options due to their bone-targeting.

Objective To investigate the correlation between single nucleotide polymorphisms(SNPs)of the EGF gene,including rs11569017(A>T),rs2237051(A>G),rs3733625(C>T),and rs4444903(A>G),and the risk of non-small cell lung cancer(NSCLC)in a Han population of Yunnan.Methods A total of 439 patients with NSCLC and 520 healthy controls were recruited in Yunnan Province between January 2022 and December 2023.Genotyping of four SNP loci in the EGF gene was performed using TaqMan probes,followed by analysis of allele,genotype,genetic model,and haplotype distribution frequencies between NSCLC and control groups.Stratified analyses were further conducted based on NSCLC pathological types and clinical stages.Results The rs2237051 locus showed significant differences in allele(P=0.011)and genotype(P=0.042)frequencies between the squamous cell carcinoma(SCC)group and the control group.The frequency of the A allele was lower in the SCC group than in the control group(OR=0.71,95%CI 0.54～1.85),but there was no difference after Bonferroni correction(P>0.0125).Under the log-additive model,the rs2237051-2G/G+A/G genotype was associated with an increased risk of SCC(P=0.01;OR=1.42,95%CI 1.08～1.86).However,the association lost statistical significance after Bonferroni correction(P>0.0125).The haplotype rs11569017-rs2237051-rs3733625-rs4444903 has no difference between the two groups(P>0.0125).The stratified analysis revealed no significant associations between the genetic loci and different disease stages(P>0.0125).Conclusion In the Yunnan Han population,the individuals carrying the rs2237051-A allele of the EGF gene have a significantly lower risk of squamous lung cancer,but further functional experiments are needed to verify the protective mechanism.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

BACKGROUND:Osteoporosis affects the quality of life of patients and is prone to pathological fractures,and plant-derived exosome-like nanovesicles play an important role in regulating bone balance in patients with osteoporosis.OBJECTIVE:To review the research status and prospect of different plant-derived exosome-like nanovesicles in the treatment of osteoporosis.METHODS:Relevant literature in PubMed,Web of Science,and CNKI databases were searched by computer.Search time was from January 1995 to March 2024.The Chinese and English search terms were"osteoporosis,plant-derived exosome-like nanovesicles,exosomes,osteoblasts,osteoclasts."Finally,53 articles were included and analyzed.RESULTS AND CONCLUSION:Plant-derived exosom-like nanovesicles have the advantages of low biocompatibility,low toxicity,and natural targeting.These properties not only ensure its stable presence and effective effect in the body,but also avoid unnecessary immune responses,laying the foundation for the design of long-term treatment strategies.Plant-derived exosome-like nanovesicles can be anti-osteoporosis by stimulating osteoblast proliferation,inhibiting osteoclast differentiation,and promoting osteo-inhibition osteoclasts.In addition,some plant-derived exosome-like nanovesicles may be widely used in the diagnosis and treatment of osteoporosis in the future as novel tracer targets and treatment options due to their bone-targeting.

Objective To utilize a 3D technology in the design of a female bed urinal and to evaluate its clinical efficacy.Methods A total of 102 adult female fracture patients with normal urination function admitted to a tertiary hospital in Hangzhou City from October 2022 to June 2023 were included in the study.They were divided into a control group(n=51)and an experimental group(n=51)according to random number method.Patients in control group used a regular urinal,while patients in the experimental group used the 3D technology-based female bed urinal.The level of physical pain caused by urination,the rate of urine immersion in the sacrococcygeal or gluteal cleft and the rate of bed unit or clothing of contamination were compared between the 2 groups.Results There was no significant difference in the rate of bed unit or clothing contamination between the 2 groups(P＞0.05).However,the experimental group experienced significantly lower pain caused by urination,a lower rate of urine impregnation in the sacrococcygeal or gluteal fissure(P＜0.001),compared to the control group.Conclusion The 3D technology-based female bed urinal has reasonable structure and simple operation,which can significantly reduce the physical pain caused by the change of body position,reduce the incidence of urine immersion events.

Objective This study aimed to explore the prognostic value of 18F-FDG PET/CT Metabolic and Heterogeneity Parameters Combined with Clinical Features Before Definitive Chemoradiotherapy(D-CRT)in predicting the prognosis of esophageal squamous cell carcinoma(ESCC)Patients.Methods A retrospective analysis was conducted on clinical data from 106 patients with ESCC who received D-CRT at the first affiliated Hospital of University of Science and Technology of China between January 2017 and December 2021.All patients underwent 18F-FDG PET/CT examination before the treatment.The primary tumor′s metabolic and heterogeneity parameters were obtained through data processing.All patients were followed up for overall survival.The Kaplan-Meier method and Cox proportional hazards models were used to analyze the association between clinical features,tumor metabo-lism and heterogeneity parameters and patient prognosis.Results The 1-and 1.5-year overall survival rates of all patients were 77.4%and 51.9%.The median survival time was 20 months.Univariate analysis showed that N stage,M stage,metabolic tumor volume,total lesion glycolysis,heterogeneity index-2(HI-2),and coefficient of variation with a threshold of 40%maximum standard uptake value(CV40%)were correlated with the prognosis of ESCC(all P<0.05).Multivariate analysis showed that N stage and CV40%were independent predictors of prognosis in patients with ESCC(P = 0.039 and P<0.001,respectively).Conclusion N stage and tumor metabolic heterogeneity parameter CV40%,which offering a degree of predictive value,are closely related to the prognosis of patients with ESCC treated with D-CRT.