Objective To explore the relationship between circadian rhythm genes and the occurrence, development, prognosis, and tumor microenvironment (TME) of lung adenocarcinoma (LUAD). Methods The Cancer Genome Atlas data were used to evaluate the expression, copy number variation, and somatic mutation frequency of circadian gene sets in LUAD. Gene ontology, Kyoto encyclopedia of genes and genomes, and gene set enrichment analysis were used to explore the potential mechanisms by which circadian rhythm genes affected LUAD progression. Cox regression, least absolute shrinkage and selection operator regression, support vector machine recursive feature elimination, and random forest screened circadian genes and established prognostic models, and on this basis constructed nomogram to predict patients’ 1-, 3-, and 5-year survival rates. Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves were drawn to evaluate the predictive ability of the model, and the external dataset of GEO further verified the prognostic value of the prediction model. In addition, we evaluated the association of the prognostic model with immune cells and immune checkpoint genes. Single cell RNA sequencing (scRNA-seq) analysis was used to explore the molecular characteristics between prognostically relevant circadian genes and different immune cell populations in TME. Results Differentially expressed circadian rhythm genes were mainly enriched in biological processes related to cGMP-PKG signaling pathway, lipid and atherosclerosis, and JAK-STAT signaling pathway. Seven circadian rhythm genes: LGR4, CDK1, KLF10, ARNTL2, RORA, NPAS2, PTGDS were screened out, and a RiskScore model was established. According to the median RiskScore, samples were divided into a high-risk group and a low-risk group. Compared with patients in the low-risk group, patients in the high-risk group showed a poorer prognosis (P<0.001). Immunological characterization analysis showed that there were differences in the infiltration of multiple immune cells between the low-risk group and high-risk group. Most immune checkpoint genes had higher expression levels in the high-risk group than those in the low-risk group, and RiskScore was positively correlated with the expression of CD276, TNFSF4, PDCD1LG2, CD274, and TNFRSF9, and negatively correlated with the expression of CD40LG and TNFSF15. The scRNA-seq analysis showed that RORA and KLF10 were mainly expressed in natural killer cells. Conclusion The prognostic model based on seven feature circadian rhythm genes has certain predictive value for predicting survival of LUAD patients. Dysregulated expression of circadian genes may regulate the occurrence, progression as well as prognosis of LUAD through affecting TME, which provides a possible direction for finding potential strategies for treating LUAD from the perspective of mechanism by which circadian disorder affects immune cells.

Diabetic kidney disease （DKD） is one of the most common microvascular complications of diabetes. Traditional Chinese medicine （TCM） plays a unique role in improving clinical symptoms， reducing proteinuria， and delaying the initiation of dialysis. Over time， scholars have held diverse views on the etiology， pathogenesis， and treatment strategies of DKD. This paper systematically reviews the etiology and pathogenesis， syndrome differentiation and treatment， and medication rules of DKD， aiming to provide a reference for clinical practice. Regarding etiology， DKD is closely related to insufficient innate endowment， improper diet， emotional disorders， overexertion， and prolonged diabetes. Its pathogenesis evolves dynamically. Specifically， early stage is characterized by Yin deficiency with dryness-heat and subtle discharge. Middle stage involves both Qi and Yin deficiency with dampness and blood stasis. Late stage presents Yin and Yang deficiency with intrinsic turbidity toxins. Blood stasis and sugar toxicity are the core pathological factors， persisting throughout the disease course and accelerating renal collateral damage and fibrosis. In terms of diagnosis and treatment， contemporary scholars advocate stage-specific treatment， emphasize the integration of prevention and therapy， recommend whole-course management， and support comprehensive TCM and Western medicine approaches. Analysis of medication rules shows that treatment consistently addresses the core principle of deficiency at the root and excess at the surface， strengthens the body while dispelling pathogenic factors， emphasizes promoting blood circulation and removing blood stasis， consolidates the kidney and astringes essence， clears Fu-organs and eliminates turbidity and toxins， invigorates the spleen， replenishes Qi， protects the stomach， and advocates treatment based on pathogenic wind. Further refinement of the academic thoughts of classical TCM masters and research into innovative pathogenesis theories and clinically effective prescriptions are needed to enhance TCM's ability to prevent and treat major clinical diseases， including DKD.

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.

Objective:To investigate the clinical significance of monitoring SIL::TAL1 fusion transcripts in the evaluation of treatment response and prognosis of children with T-acute lymphoblastic leukemia (T-ALL).Methods:A retrospective cohort study was conducted to analyze the clinical data of 46 newly diagnosed pediatric T-ALL with SIL::TAL1 fusion transcripts treated at Beijing Children′s Hospital Capital Medical University from November 2004 to December 2022. The SIL::TAL1 fusion transcripts were quantitatively detected at the initial diagnosis (TP0) and early stage of induction therapy (TP1), at the end of induction remission therapy (TP2), before consolidation therapy (TP3) and subsequent treatment. Patients were divided into negative and positive groups on SIL::TAL1 fusion transcripts level, differences of clinical features and survival among groups at TP0 to TP3 were analyzed. The χ2 test or Fisher exact test or Mann-Whitney U test was used to compare the clinical difference. Survival analysis was estimated by Kaplan-Meier method with Log-Rank testing. Multivariate analysis was conducted by Cox proportional hazards models. Results:Among the 46 children with SIL::TAL1 fusion transcripts, 36 were males and 10 were females, with the onset age of 6.8 (3.4, 9.5) years. The negative rates of SIL::TAL1 fusion transcripts for TP1,TP2, TP3, before delayed intensification Ⅰ treatment (TP4), before maintenance therapy (TP5) were 36% (13/36), 78% (32/41), 76% (32/42), 15/16, and 12/12, respectively. No significant difference was found on clinical features and prednisone response between groups at TP0-TP3 (all P>0.05). The 5-year events free survival (EFS) rate of patients classified as negative (32 cases) and positive (9 cases) groups at TP2 was (78±8)% and (33±16)%, respectively ( χ2=9.86, P=0.002), the 5-year overall survival (OS) rate was (81±7)% and (44±17)%, respectively ( χ2=6.40, P=0.011). The 5-year EFS rate of patients classified as negative (32 cases) and positive (10 cases) groups at TP3 was (78±8)% and (30±15)%, respectively ( χ2=13.04, P<0.001) and the 5-year OS rate was (84±6)% and (30±15)%, respectively ( χ2=15.95, P<0.001). Cox multivariate regression showed that positive of SIL::TAL1 transcript at TP3 was adverse independent prognostic factors for EFS and OS (EFS: HR=6.70, 95% CI 2.01-22.35, P=0.002; OS: HR=10.73, 95% CI 2.50-46.09, P=0.001). Conclusions:Monitoring SIL::TAL1 fusion transcripts can reflect the clinical treatment response. The level of SIL::TAL1 fusion transcripts at early period can predict long-term outcomes of these patients.

Objective:To analyze the epidemiological characteristics and infection sources of cholera in China from 2005 to 2024.Methods:A total of 2 066 cholera cases were included in the study, which were obtained from the China Disease Control and Prevention Information System (CDPCIS) of China CDC. The information on cholera clusters was downloaded from the National Public Health Emergency Event Surveillance System (PHEESS) of China CDC. A total of 128 cholera clusters were included and analyzed in this study. The epidemiological characteristics and infection sources of cholera were analyzed. The Jointpoint model was applied to analyze the incidence trend, and annual percentage change (APC) was also quantified.Results:From 2005 to 2024, a total of 2 066 cholera cases were reported, with an average of 103 cases reported annually. Specifically, the incidence showed a marked downward trend from 2004 to 2015 ( APC=-26.78%, P=0.006). During 2015-2024, the disease remained at low endemic levels, with an average of 18 reported cases annually ( APC=-2.68%, P=0.807). Cholera peak season was from May to October. A total of 24 provinces reported cholera cases, which were mainly distributed in Zhejiang, Fujian, Beijing, Jiangsu, Anhui, Guangdong, and Hainan provinces, accounting for 78.03% of the total cases. Pathogen surveillance indicated an alternating prevalence of Vibrio cholerae serogroups O1 and O139 among laboratory-confirmed cases between 2005 and 2024. There was a disparity in the dominant serogroup of Vibrio cholerae by region. The results from 128 cholera clusters indicated that cholera outbreaks frequently occurred in rural banquets (64.84%), followed by regular restaurants (13.28%). Among these, 63 clusters (49.22%) with identified infection sources indicated that foodborne transmission (95.24%) was the primary mode of cholera transmission, which mainly through seafood and aquatic products, such as soft-shelled turtles, shrimp and shellfish. The characteristics of cholera clusters caused by Vibrio cholerae serogroups O1 and O139 showed statistically significant differences in scale, attack rate, place of residence, setting, and infection source ( P<0.05). Conclusion:Cholera incidence has remained consistently low since 2015 in China, mainly in sporadic cases. Rural gatherings (e.g., wedding banquets) are the main settings for cholera clusters. The main infection sources are predominantly caused by cross-contamination due to improper processing practices of aquatic products, such as soft-shelled turtles.

Objective:The objective of this study was to understand the incidence, spatial and temporal distribution characteristics and trends of bacillary dysentery in China from 2005 to 2024 in order to identify the high-risk groups and reveal the potential risk factors and to provide a scientific basis for optimizing the allocation of preventive and control resources, formulating targeted intervention strategies and assessing the effectiveness of the measures.Methods:The nationally reported incidence data of bacillary dysentery was collected from 2005 to 2024 in the Chinese Center for Disease Control and Prevention National Notifiable Diseases Reporting Information System. Descriptive epidemiological methods were used to analyze the population characteristics of bacillary dysentery cases. A Joinpoint regression model was constructed to examine long-term trends in reported incidence rates and spatial dynamic window scanning statistics were applied to detect spatial clusters of bacillary dysentery cases.Results:Between 2005 and 2024, 3 520 247 cases of bacillary dysentery were reported across China, with an average incidence rate of 12.88 per 100 000 people, after which the rate of decline decreased. The incidence rate showed a general downward trend, featuring a significant inflection point in 2016. It exhibited marked seasonality, peaking from May to October (summer-autumn), which weakened over time. From 2005 to 2024, the most likely clusters were in Beijing and Tianjin. Males, infants, the elderly, farmers, and children not in daycare showed many cases.Conclusions:The results revealed that the peak incidence of bacillary dysentery in China from 2005 to 2024 was featured in the summer-autumn months. High-incidence areas were mainly Beijing and Tianjin. The key groups, including males, infants, the elderly, farmers and children not in daycare, were identified. Enhancing surveillance, targeted health education, and preventive measures, especially in these key populations and in regions where the disease shows a high incidence should be strengthened.

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.

Nigella sativa L. seeds have been traditionally utilized in Chinese folk medicine for centuries to treat vitiligo. This study revealed that the ethanolic extract of Nigella sativa L. (HZC) enhances melanogenesis and mitigates oxidative stress-induced cellular senescence and dysfunction in melanocytes. In accordance with established protocols, the ethanol fraction from Nigella sativa L. seeds was extracted, concentrated, and lyophilized to evaluate its herbal effects via 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays, tyrosinase activity evaluation, measurement of cellular melanin contents, scratch assays, senescence-associated β-galactosidase (SA-β-gal) staining, enzyme-linked immunosorbent assay (ELISA), and Western blot analysis for expression profiling of experimentally relevant proteins. The results indicated that HZC significantly enhanced tyrosinase activity and melanin content while notably increasing the protein expression levels of Tyr, Mitf, and gp100 in B16F10 cells. Furthermore, HZC effectively mitigated oxidative stress-induced cellular senescence, improved melanocyte condition, and rectified various functional impairments associated with melanocyte dysfunction. These findings suggest that HZC increases melanin synthesis in melanocytes through the activation of the MAPK, PKA, and Wnt signaling pathways. In addition, HZC attenuates oxidative damage induced by H₂O₂ therapy by activating the nuclear factor E2-related factor 2-antioxidant response element (Nrf2-ARE) pathway and enhancing the activity of downstream antioxidant enzymes, thus preventing premature senescence and dysfunction in melanocytes.
Oxidative Stress/drug effects* ; Melanocytes/cytology* ; Cellular Senescence/drug effects* ; Nigella sativa/chemistry* ; Plant Extracts/pharmacology* ; Seeds/chemistry* ; Mice ; Animals ; Melanins/metabolism* ; Monophenol Monooxygenase/metabolism* ; Humans