Objective To explore the role of E1A binding protein p300 (EP300)-mediated crotonylation (Kcr) modification of malic enzyme 1 (ME1) in ferroptosis of renal tubular epithelial cells. Methods C57BL/6 mice were divided into Sham operation group (Sham group), DMSO vehicle control + ischemia-reperfusion (IR) injury group (Vehi + IR group), and EP300 inhibitor C646 + IR injury group (C646 + IR group), with 12 mice in each group. Pathological changes in renal tissues were evaluated in each group, and indicators of renal function, ferroptosis, and fibrosis were assessed. Another 24 mice were used to establish the IR injury model to analyze changes in Kcr modification levels and EP300 expression over the 14-day course of IR injury. The in vitro HK-2 cell experimental model was established and divided into control group, hypoxia/reoxygenation (H/R) group, and C646 + H/R group. Corresponding HK-2 cells were transfected with the ME1-K337R plasmid, in which lysine 337 (K) was mutated to arginine (R) to mimic the de-Kcr modification. Small interfering RNA was used to target EP300 and transfect the cells in order to obtain EP300 knockdown cells (siEP300). The expression of ferroptosis-related proteins and fibrosis phenotypes was detected. Results At 14 d after IR injury, the protein Kcr level and EP300 expression were increased in mice. Compared with the Sham group, the Vehi+IR group showed markedly disrupted renal tissue structure, extensive red collagen deposition in the renal interstitium, decreased expression levels of glutathione, reduced nicotinamide adenine dinucleotide phosphate (NADPH), and glutathione peroxidase 4 (GPX4, P＜0.01), increased malondialdehyde and serum creatinine levels (P＜0.01), decreased ME1 enzymatic activity (P＜0.001), and increased expression of fibronectin 1 and smooth muscle actin-α (P＜0.001). Compared with the Vehi+IR group, the C646+IR group showed alleviated renal pathological injury, improved renal function, and reduced ferroptosis and fibrosis (P＜0.05). Compared with the control group, HK-2 cells subjected to H/R treatment exhibited aggravated ferroptosis and fibrosis (P＜0.05); compared with the H/R group, the C646+H/R group showed reduced ferroptosis and fibrosis (P＜0.05). Transfection with the ME1-K337R plasmid and siEP300 showed reduced ME1 Kcr, ferroptosis, and fibrosis. Conclusions EP300 contributes to ferroptosis in renal tubular epithelial cells by mediating ME1 crotonylation, and inhibition of EP300 may help alleviate the chronic progression following IR injury.

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 explore the diagnosis and treatment experience of tension hydrocele. [Methods] The clinical data of 2 patients with tension hydrocele treated in our hospital were retrospectively analyzed.Relevant literature was retrieved to analyze the clinical characteristics of this disease. [Results] Case 1 was diagnosed due to swelling and pain of the left scrotum after trauma for more than one month, which worsened for one day.Physical examination showed high tension in the left scrotum and positive light transmission test.Ultrasound examination revealed that the blood flow signal in the left testis disappeared.Emergency left scrotal exploration and hydrocelectomy were performed.There was no sign of testis torsion during the operation.Case 2 was diagnosed mainly due to hydrocele of the right testis for 1 year, which worsened for 1 week and complicated with testis distension and pain.Physical examination showed high tension in the right scrotum and positive light transmission test.Ultrasound examination revealed that the blood flow signal in the right testis decreased.After 40ml of fluid was extracted under ultrasound monitoring, the blood flow signal in the right testis recovered.Hydrocelectomy was performed the next day.During the follow-up of 8 months, there was no recurrence of hydrocele.A search of domestic and foreign literature showed that there were no reports in domestic literature, while a total of 11 cases were reported in foreign literature. [Conclusion] Tension hydrocele of the testis is a rare emergency of the scrotum.Surgery or decompression should be performed as soon as possible to restore testicular blood supply, and hydrocelectomy should be performed simultaneously or in stages to prevent recurrence.

[Objective] To explore the predictive value of HALP score for prognosis in patients with multiple myeloma (MM). [Methods] A retrospective analysis was conducted on laboratory indicators and related clinical data of newly diagnosed multiple myeloma (NDMM) patients, treated at the Affiliated Hospital of North Sichuan Medical College from January 2016 to October 2023, prior to their first treatment. The HALP score was calculated, and the optimal cutoff value for HALP was determined using X-tile software. Survival analysis was performed using Kaplan-Meier curves for high HALP and low HALP groups. Univariate and multivariate analyses were conducted using the Cox regression model, and a forest plot was generated using Graphpad Prism to illustrate factors that may impact patient prognosis. The predictive ability of HALP score combined with β2-microglobulin and ECOG score for prognosis in MM patients was evaluated using receiver operating characteristic curve (ROC) analysis. [Results] A total of 203 MM patients were included, with the optimal cutoff value for HALP score being 29.15 (P<0.05). Among them, 101 patients were in the low HALP score group, and 102 patients were in the high HALP score group. The results of univariate and multivariate analysis using the Cox regression model showed that a HALP score <29.15 was an independent risk factor for progression-free survival (PFS) and overall survival (OS) (P<0.05). ROC curve analysis indicated that the combination of HALP score with β2-microglobulin and ECOG score had a higher predictive value for prognosis in MM patients compared to using HALP score alone. [Conclusion] The HALP score is closely related to the prognosis of patients with NDMM. A low HALP score indicates a poorer prognosis, while the combination of HALP score with β2-microglobulin and ECOG score provides a higher predictive value when assessed together.

Objective: To establish a method for determining the molecular weight and molecular weight distribution of Poly(Lactide-co-Glycolide Acid) (PLGA) using Size Exclusion Chromatography-Refractive Index-Multiangle Laser Light Scattering (SEC-RI-MALLS) and Size Exclusion Chromatography-Refractive Index (SEC-RID), and to compare the results obtained from these two methods.
Methods: For SEC-RI-MALLS, tetrahydrofuran was used as the mobile phase, Shodex GPC KF-803L was employed as the chromatographic column with a flow rate of 1 mL·min^-1, column temperature at 30 ℃, and an injection volume of 100 μL. For SEC-RID, tetrahydrofuran was also used as the mobile phase, Agilent PLgel 5 μm MIXD-D was used as the chromatographic column with a flow rate of 1 mL·min^-1, column temperature at 30 ℃, differential detector temperature at 35 ℃, and an injection volume of 20 μL. The molecular weight and molecular weight distribution were calculated using Agilent’s GPC software. The newly established methods were validated methodologically, and the molecular weight and molecular weight distribution of 13 batches of samples were determined.
Results: The precision, accuracy, stability, and repeatability tests for SEC-RI-MALLS showed RSD values of 1.35%, 1.58%, 1.53%, and 1.26%, respectively. The SEC-RID method exhibited good linearity (r=0.999 9), with RSD values for precision, accuracy, stability, and repeatability tests (n=6) of 2.05%, 1.62%, 1.30%, and 2.97%, respectively. The results obtained from SEC-RI-MALLS were lower than those from SEC-RID, and the molecular weight distribution coefficient was smaller, but the results from the paired T-test performed with the value measured by SEC-RID method and the value measured by SEC-RI-MALLS method multiplied a conversion coefficient of 1.5 showed no significant difference between the two methods.
Conclusion: Both methods are stable and reliable, and can be used for the determination of PLGA molecular weight and molecular weight distribution based on the specific situations.

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.

To analyze the disease burden of hypertension in the elderly population from 1990 to 2021 and to predict future trends in China and globally, thereby providing insights for public health decision-making regarding older adults with hypertension in China.

This study aims to innovate a homogeneous outpatient service management system across multiple hospital campuses to enhance service quality.Based on the practical experience of a tertiary general hospital in Guangdong Province and in accordance with the"Interim Regulations on Outpatient Quality Management in Healthcare Institutions,"we constructed a"6+1"homogeneous outpatient service management system.This system includes:① a multi-stakeholder co-governance outpa-tient management system,②a vertical and cross-hierarchical management network,③ a democratic-centralized clinical coordina-tion strategy,④ a guidance-encouragement performance evaluation standard,⑤a collaborative dynamic supervision mechanism,⑥a spiral retrospective evaluation and improvement method,and ⑦ an integrated outpatient diagnosis and treatment system.Af-ter over two years of implementation,the hospital's outpatient volume has grown by an average of over 15％annually,patient waiting time after appointment has been reduced to 20 minutes,and patient satisfaction in the tertiary public hospital performance evaluation achieved full marks.The electronic medical record system functionality reached Level 6,significantly improving healthcare service efficiency and quality while enhancing homogeneous management across campuses.

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.