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: 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.

ObjectiveTo investigate the clinical features and outcomes of recompensation in patients with autoimmune hepatitis （AIH）-related decompensated cirrhosis， to identify independent predictive factors， and to construct a nomogram prediction model for the probability of recompensation. MethodsA retrospective cohort study was conducted among the adult patients with AIH-related decompensated cirrhosis who were admitted to The Fifth Medical Center of PLA General Hospital from January 2015 to August 2023 （n=211）. The primary endpoint was achievement of recompensation， and the secondary endpoint was liver-related death or liver transplantation. According to the outcome of the patients at the end of the follow-up， the patients were divided into the recompensation group （n=16） and the persistent decompensation group（n=150）.The independent-samples t test was used for comparison of normally distributed continuous data with homogeneity of variance， and the Mann-Whitney U rank sum test was used for comparison of non-normally distributed continuous data with heterogeneity of variance； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups； the Kaplan-Meier method was used for survival analysis； the Cox proportional-hazards regression model was used to identify independent predictive factors， and a nomogram model was constructed and validated. ResultsA total of 211 patients were enrolled， with a median age of 55.0 years and a median follow-up time of 44.0 months， and female patients accounted for 87.2%. Among the 211 patients， 61 （with a cumulative proportion of 35.5%） achieved recompensation. Compared with the persistent decompensation group， the recompensation group had significantly higher white blood cell count， platelet count （PLT）， total bilirubin （TBil）， alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， total bile acid， prothrombin time， international normalized ratio （INR）， SMA positive rate， Model for End-Stage Liver Disease （MELD） score， Child-Pugh score， and rate of use of glucocorticoids （all P0.05）， as well as significantly lower age at baseline， number of complications， and death/liver transplantation rate （all P0.05）. At 3 and 12 months after treatment， the recompensation group had continuous improvements in AST， TBil， INR， IgG， MELD score， and Child-Pugh score， which were significantly lower than the values in the persistent decompensation group （all P0.05）， alongside with continuous increases in PLT and albumin， which were significantly higher than the values in the persistent decompensation group （P0.05）. The multivariate Cox regression analysis showed that baseline ALT （hazard ratio ［HR］=1.067， 95% confidence interval ［CI］： 1.010 — 1.127， P=0.021）， IgG （HR=0.463，95%CI：0.258 — 0.833， P=0.010）， SMA positivity （HR=3.122，95%CI：1.768 — 5.515， P0.001）， and glucocorticoid therapy （HR=20.651，95%CI：8.744 — 48.770， P0.001） were independent predictive factors for recompensation， and the nomogram model based on these predictive factors showed excellent predictive performance （C-index=0.87，95%CI：0.84 — 0.90）. ConclusionAchieving recompensation significantly improves clinical outcomes in patients with AIH-related decompensated cirrhosis. Baseline SMA positivity， a high level of ALT， a low level of IgG， and corticosteroid therapy are independent predictive factors for recompensation. The predictive model constructed based on these factors can provide a basis for decision-making in individualized clinical management.

In order to standardize the clinical diagnosis and treatment of upper airway cough syndrome (UACS) for children in China, Dongzhimen Hospital of Beijing University of Chinese Medicine and Affiliated Hospital of Liaoning University of Traditional Chinese Medicine initiated the development of this Traditional Chinese Medicine Diagnosis and Treatment Guidelines for Children with Upper Airway cough Syndrome based on evidence-based medical evidence. This guideline will process registration, write a plan, and develop relevant processes and writing norms, develop and publish official documents. This plan mainly introduces the scope of the guidelines, the purpose and significance, the composition of the guidelines working group, the management of conflicts of interest, the collection, selection and determination of clinical problems, the retrieval, screening and rating of evidence, and the consensus of recommendations. Registration information: This study has been registered in the international practice guidelines registry platform with the registration code of PREPARE-2023CN087.

Inflammatory bowel disease (IBD) is characterized by chronic relapsing intestinal inflammation and encompasses ulcerative colitis (UC) and Crohn's disease (CD). IBD has emerged as a global healthcare problem. Clinically efficacious therapeutic agents are deficient. This study concentrates on models of ulcerative colitis with the objective of discovering novel therapeutic strategies. Previous investigations have established that schisandrin A demonstrates anti-inflammatory effects in vitro, concurrently enhancing the transcriptional activity of farnesoid X receptor (FXR). FXR inversely modulates the transcriptional activity of NF-κB, which has an important role in regulating inflammatory responses. Consequently, the current study was to explore the safeguarding influence of schisandrin A on ulcerative colitis and delineate the mechanism by which it regulates this effect through the FXR signaling pathway. The effect of schisandrin A on the mRNA levels of inflammatory factors was evaluated in RAW264.7 cells. The dual luciferase reporter gene assay was used to verify the relationship between schisandrin A and FXR targeting. The animal experiments were performed in accordance with the regulations of the Animal Ethics Committee of Shanghai University of Traditional Chinese Medicine (approval No. PZSHUTCM2304250005). Acute ulcerative colitis was induced in wild-type or FXR knockout C57BL/6 mice by drinking 3% dextran sodium sulfate (DSS) for 7 days, and schisandrin A was administered via gavage for a continuous treatment period of 7 days. The body weight and faecal were monitored daily. The mRNA levels of inflammatory factors in colon tissue and FXR target genes were measured by RT-qPCR. The findings revealed that schisandrin A, in vitro, impeded the lipopolysaccharide (LPS)-induced elevation in mRNA levels of inflammatory factors and schisandrin A could augment transcriptional activity of FXR. In wild-type mice, schisandrin A significantly improved weight loss, colon shortening, loose stools and blood in stools in mice with acute ulcerative colitis, and schisandrin A significantly reduced the expression of pro-inflammatory factors genes and significantly increased the expression of FXR target genes in colon tissues. In FXR knockout mice, the administration of schisandrin A failed to yield ameliorative effect on acute ulcerative colitis in mice. In conclusion, schisandrin A can reduce intestinal inflammation through the FXR signaling pathway to alleviate acute ulcerative colitis in mice. Implications arise that Schisandra lignans could serve as lead compounds for drug development aimed at inflammatory bowel disease.

OBJECTIVE To analyze the evolution of the transition from unicellular organisms to multicellular organisms from a phylogenetic stratigraphy perspective, combining the "cancer atavism hypothesis". To investigate the evolutionary chronology of cancer-related genes to guide research on cancer mechanisms and the development of treatment strategies. METHODS Phylostratr was used to identify the systematic evolutionary strata of all human protein-coding genes, housekeeping genes, cancer driver genes, tumor suppressor genes, oncogenes, neutral genes, and differentiation genes. Differential distribution of genes from different functional categories and human protein-coding genes was analyzed using log-odds ratios and hypergeometric distributions. TCGA was utilized to investigate transcriptional expression datas in cancer tumor samples and normal samples, and calculations and analysis were performed using transcriptome age index. RESULTS A total of 20291 protein-coding genes were classified into 27 different strata based on the farthest homologous species in the sequence alignment results. Within the phylogenetic stratigraphic structure, the datasets of 4159 housekeeping genes, 527 cancer driver genes, 87 tumor suppressor genes, 134 oncogenes, 10755 neutral genes, and 4274 differentiation genes exhibit distinct distribution patterns. The overall distribution of these genes significantly differs from that of all human protein-coding genes. Cancer-related genes exhibited a more ancient phylogenetic stratigraphic distribution. Transcriptome age index results for bile duct cancer, colon cancer, lung cancer, liver cancer, head and neck cancer, and kidney chromophobe samples showed strong expression of highly conserved and ancient genes within the tumors. CONCLUSION Cancer-related genes exhibit older evolutionary origins within the phylogenetic context suggesting a more conserved function during species evolution. And the phenomenon of enhanced expression of highly conserved ancient genes in tumor tissues can be used to explore tumor gene expression patterns, and provide new ideas for the discovery of new anti-tumor drug targets and drug research.

Objective To investigate the clinical application value of contrast-enhanced chest CT in the detection of responsible vessels for hemoptysis before selective arterial embolization(SAE).Methods The clinical data of 74 patients with hemoptysis trea-ted with interventional therapy and preoperative contrast-enhanced chest CT and digital subtraction angiography(DSA)were ana-lyzed retrospectively.The responsible vessels were identified and then embolized via angiography.The detection of the responsible vessels via preoperative contrast-enhanced chest CT was analyzed.The patients were followed up to observe the efficacy and compli-cations,and the influencing factors of interventional efficacy and recurrence were analyzed.Results A total of 245 responsible ves-sels were detected by preoperative contrast-enhanced chest CT,including bronchial arteries(n=178),ectopic bronchial arteries(n=10)and non-bronchial systemic artery(NBSA)(n=57),which could accurately show the anatomical information of responsible vessels.A total of 4 posterior intercostal arteries were missed.The diagnostic accuracy was 98.4％(245/249).All patients were followed up for 12 to 25.6 months.The immediate hemostasis rate was 93.2％(69/74)and the effective rate was 79.7％(59/74),respectively.The factors affecting the efficacy were bronchial artery to pulmonary circulation fistula,pleural thickening at the bleeding site,and underly-ing lung disease.Among the 59 patients with effective treatment,underlying lung disease was the influencing factor for postoperative recurrence.Conclusion Contrast-enhanced chest CT can provide anatomical information about the responsible vessels for interven-tional therapy of hemoptysis,improving surgical efficiency and reducing the recurrence rate of hemoptysis.

Gastric cancer(GC)is one of the most common gastrointestinal tumors.As a newly discovered type of non-coding RNAs,transfer RNA(tRNA)-derived small RNAs(tsRNAs)play a dual biological role in cancer.Our previous studies have demonstrated the potential of tRF-23-Q99P9P9NDD as a diagnostic and prognostic biomarker for GC.In this work,we confirmed for the first time that tRF-23-Q99P9P9NDD can promote the proliferation,migration,and invasion of GC cells in vitro.The dual luciferase reporter gene assay confirmed that tRF-23-Q99P9P9NDD could bind to the 3'untranslated region(UTR)site of acyl-coenzyme A dehydrogenase short/branched chain(ACADSB).In addition,ACADSB could rescue the effect of tRF-23-Q99P9P9NDD on GC cells.Next,we used Gene Ontology(GO),the Kyoto Encyclopedia of Genes and Genomes(KEGG),and Gene Set Enrichment Analysis(GSEA)to find that downregulated ACADSB in GC may promote lipid accumulation by inhibiting fatty acid catabolism and ferroptosis.Finally,we verified the correlation between ACADSB and 12 ferroptosis genes at the transcriptional level,as well as the changes in reactive oxygen species(ROS)levels by flow cytometry.In summary,this study proposes that tRF-23-Q99P9P9NDD may affect GC lipid metabolism and ferroptosis by targeting ACADSB,thereby promoting GC progression.It provides a theoretical basis for the diagnostic and prognostic monitoring value of GC and opens up new possibilities for treatment.