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.

[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.

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.

Acute lung injury(ALI) is a critical clinical condition primarily characterized by refractory hypoxemia and infiltration of inflammatory cells in lung tissue, which can progress into a more severe form known as acute respiratory distress syndrome(ARDS). Immune cells and inflammatory cytokines play important roles in the progression of the disease. Due to its unclear pathogenesis and the lack of effective clinical treatments, ALI is associated with a high mortality rate and severely affects patients' quality of life, making the search for effective therapeutic agents particularly urgent. Ginseng Radix et Rhizoma, the dried root of the perennial herb Panax ginseng from the Araliaceae family, contains active ingredients such as saponins and polysaccharides, which possess various pharmacological effects including anti-tumor activity, immune regulation, and metabolic modulation. In recent years, studies have shown that ginsenosides exhibit notable effects in reducing inflammation, ameliorating epithelial and endothelial cell injury, and providing anticoagulant action, indicating their comprehensive role in alleviating lung injury. This review summarizes the pathogenesis of ALI and the molecular mechanisms through which ginsenosides act at different stages of ALI development. The aim is to provide a scientific reference for the development of ginsenoside-based drugs targeting ALI, as well as a theoretical basis for the clinical application of Ginseng Radix et Rhizoma in the treatment of ALI.
Ginsenosides/pharmacology* ; Humans ; Acute Lung Injury/immunology* ; Animals ; Panax/chemistry* ; Drugs, Chinese Herbal

OBJECTIVE: To explore the differences in clinical efficacy between enhanced workflows and express workflows in robotic-assisted total hip arthroplasty(THA). METHODS: A retrospective analysis was conducted on 46 patients who underwent robotic-assisted THA between November 2020 and May 2021. They were divided into the enhanced workflows group and the express workflows group based on the surgical methods. There were 20 patients in the enhanced workflows group, including 11 males and 9 females;aged from 51 to 78 years old with an average of (67.30±7.52) years old. The BMI ranged from 18.24 to 24.03 kg·m^-2 with an average of(23.80±3.01) kg·m^-2. There were 26 patients in the express workflows group, including 12 males and 14 females;aged from 57 to 84 years old with a mean age of (67.58±7.29) years old, and their BMI ranged from 19.72 to 30.08 kg·m^-2 with an average of (24.41 ±2.92) kg·m^-2. The operation time, hospital stay, and perioperative complications of the patients were recorded. The postoperative acetabular prosthesis anteversion angle, abduction angle, limb length, and offset distance data were measured. The Harris hip score at the latest follow-up was recorded. RESULTS: All patients completed the surgery as planned and were followed up, with the follow-up period ranging from 47 to 54 months with a mean of (49.78±1.85) months and the length of hospital stay ranging from 2 to 11 days with an average of (6.57±1.82 ) days. The operation time of enhanced workflows group was (93.41±16.41) minutes, which was longer than that of the express workflow groups (75.19±18.36) minutes, and the difference was statistically significant (P<0.05). In enhanced workflows group, the postoperative acetabular anteversion angle was (19.20±4.46)°, the limb length discrepancy was (-1.55±9.13) mm, and changes of the offset was (-5.15±6.77) mm. The corresponding values in express workflows group were (20.46±3.29)°, (2.19±4.39) mm, and (-2.39±4.34) mm, respectively. There was no statistically significant difference in these indicators between the two groups(P>0.05). One patient in the enhanced workflows group developed deep venous thrombosis after surgery. No cases of dislocation or periprosthetic infection. At the latest follow-up, all patients had well-positioned prostheses without loosening. Harris hip score was (90.50±1.67) points in enhanced workflows group and (90.73±2.36) points in the express workflows group, with no statistically significant difference between the two groups (P>0.05). CONCLUSION The clinical efficacy of robot assisted total hip arthroplasty technology is satisfactory. The enhanced workflows will increase the surgical time. For patients with normal anatomical hip joint disease, this study did not find significant advantages in joint stability and functional scoring for the enhanced workflows.
Humans ; Arthroplasty, Replacement, Hip/methods* ; Male ; Female ; Aged ; Middle Aged ; Robotic Surgical Procedures/methods* ; Retrospective Studies ; Aged, 80 and over ; Workflow ; Treatment Outcome

OBJECTIVE: To investigate the expression of CD19/CD73 in chronic lymphocytic leukemia (CLL) and its correlation with clinical features. METHODS: The clinical data of 60 CLL patients and 40 healthy volunteers (control group) from January 2022 to November 2023 were retrospectively analyzed. The levels of CD19 and CD73 in peripheral blood of CLL patients were measured by flow cytometry. Kaplan-Meier method was used for survival analysis. RESULTS: The hemoglobin (Hb) and CD19/CD73 levels in CLL group were significantly lower than those in control group, while CD19, CD73 and β₂-MG were significantly higher (all P <0.001). According to ROC curve analysis, the AUC value of CD19/CD73 for CLL diagnosis was 0.980 (95%CI : 0.949-1.000, P <0.05), the specificity was 92.50%, and the sensitivity was 98.30%. The CD19/CD73 level of CLL patients with splenomegaly was significantly lower than those without splenomegaly (P <0.01). There was no significant correlation between CD19/CD73 and Hb in CLL patients ( r =0.056, P >0.05). CD19/CD73 was positively correlated with β₂-MG ( r =0.837, 95%CI : 0.740 2-0.899 6, P <0.01). According to the median value (12.84) of CD19/CD73, the patients were divided into high and low expression groups. Kaplan-Meier survival analysis showed that the overall survival rate and progression-free survival rate at 18^th month in the low expression group were 87.08% and 93.25%, while those in the high expression group were 96.41% and 99.90%, respectively (both P <0.05). CONCLUSION The level of CD19/CD73 is low in CLL patients, which can be used as an auxiliary index for clinical diagnosis of CLL. CD19/CD73 is closely related to splenomegaly in CLL patients. Low expression of CD19/CD73 predicts poor prognosis.
Humans ; Leukemia, Lymphocytic, Chronic, B-Cell/metabolism* ; 5'-Nucleotidase/metabolism* ; Antigens, CD19/metabolism* ; Retrospective Studies ; Male ; Female ; Prognosis ; Middle Aged ; Aged ; Adult ; GPI-Linked Proteins

The design and development of electrocardiogram(ECG)monitoring cloud platform based on the Internet of Things(IoT)electrocardiograph is introduced.The platform is mainly composed of ECG acquisition module,algorithm module,diagnostic model comparison module,warning module,positioning module and medical aid system.The ECG acquisition module collects ECG signals of patients and displays them in real time on the mobile terminals.Then they are uploaded to the ECG monitoring cloud platform through the IoT.The algorithm module and the diagnostic model comparison module mark,process,analyze and diagnose the ECG.Meanwhile,the ECG diagnosis and warning results are pushed to patients and 120 emergency centers through the IoT.Furthermore,the cloud platform will guide patients to self-rescue and the emergency platform will open the green channel to save patients in time.The platform realizes from the onset to diagnosis and treatment in one step,and saves lives against time.