Objective: To fabricate a hydrogel loaded with inositol hexaphosphate-zinc and preliminarily evaluate its performance in self-mineralization and osteoinduction, thereby providing a theoretical basis for the development of bone regeneration materials. Methods: The hydrogel framework (designated DF0) was formed by copolymerizing methacryloyloxyethyltrimethylammonium chloride and four-armed poly(ethylene glycol) acrylate, followed by sequentially loading inositol hexaphosphate anions via electrostatic interaction and zinc ions via chelation. The hydrogel loaded only with inositol hexaphosphate anions was named DF1, while the co-loaded hydrogel was named DF2. The self-mineralization efficacy of the DF0 , DF1 and DF2 hydrogels was characterized using scanning electron microscopy, transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), and selected area electron diffraction (SAED). The biocompatibility was assessed via live/dead cell staining and a CCK-8 assay. The osteoinductive capacity of the DF0 , DF1 and DF2 hydrogels on MC3T3-E1 cells was assessed via alkaline phosphatase (ALP) and Alizarin Red S (ARS) staining. In the aforementioned cell experiments, cells cultured in standard medium served as the control group Results: The DF0, DF1, and DF2 hydrogels were successfully synthesized. Notably, DF1 and DF2 exhibited distinct self-mineralization within 6 days. Results from TEM, EDS, and SAED confirmed that the mineralization products were amorphous calcium phosphate in group DF1, and amorphous calciumzinc phosphate in group DF2. Biocompatibility tests revealed that none of the hydrogels (DF0, DF1, and DF2) adversely affected cell viability or proliferation. In osteogenic induction experiments, both ALP and ARS staining were intensified in the DF1 and DF2 groups, with the most profound staining observed in the DF2 group. Conclusion The developed inositol hexaphosphate-zinc hydrogel (DF2) demonstrates the dual capacity to generate calcium-phosphate compounds through self-mineralization while exhibiting excellent osteoinductive properties. This biocompatible, dual-promoting osteogenic hydrogel presents a novel strategy for bone regeneration.

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 correlation and lag effects of environmental factors on pediatric respiratory disease visits at hospital, so as to provide scientific basis for disease prediction and optimizing clinical diagnosis and treatment. Methods: Data from 503 889 pediatric respiratory disease outpatient and emergency visits a central hospital in Minhang District of Shanghai between 2017 and 2019, along with concurrent meteorological data were collected. A distributed lag non-linear models (DLNM) was constructed to explore the specific relationship between pediatric respiratory disease consultations and various environmental factors and to quantify the cumulative lag effects of environmental factors on respiratory disease consultations. Results: Among the environmental factors, temperature, fine particulate matter (PM 2.5 ), inhalable particulate matter (PM 10 ), nitrogen dioxide (NO 2), and sulfur dioxide (SO 2) were associated with pediatric respiratory disease visits. After adjusting for temperature, PM 2.5 and PM 10 concentrations did not show significant immediate or lag effects. The relative risk (RR) of pediatric respiratory disease visits increased with rising NO 2 concentrations. When NO 2 concentration ≥55 μg/m 3, significant immediate and lagged effects (lag 3, 5, and 7 days) were observed. The RR values were 1.05, 1.13, 1.17, and 1.21( P <0.05). The RR values showed an inverted “U” shaped relationship with SO 2 concentrations. When SO 2 concentration ≥5 μg/m 3, significant lagged effects (lag 3, 5, and 7 days) were observed. The RR values were 1.03 , 1.03, and 1.04 ( P <0.05). Conclusion High concentrations of NO 2 and SO 2 increase the risk of pediatric respiratory disease visits, with observable lag effects.

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.

Diabetic nephropathy is one of the important causes of end-stage renal disease, and kidney transplantation is the best treatment option for patients with end-stage renal disease due to diabetes (DN-ESRD). However, patients with DN-ESRD have multiple complex factors that affect glucose homeostasis. Long-term hyperglycemia leads to disordered internal environment and extensive involvement of systemic organs, increasing the risks during the perioperative period of kidney transplantation. This article reviews the perioperative management strategies for kidney transplantation in patients with DN-ESRD, discusses the perioperative risk factors, preoperative evaluation and management, intraoperative volume and internal environment management and early postoperative management, and elaborates on the latest progress in this field.

Objective: To evaluate the efficacy and safety of plasma exchange (PE) in thymoma-associated myasthenia gravis (MG), thereby to provide theoretical support for its application in the treatment of thymoma-associated MG. Methods: A total of 133 patients with thymoma-associated MG admitted from January 2018 to September 2024 were retrospectively analyzed. Patients were matched using propensity score to reduce selection bias, yielding 22 matched pairs for both PE group (n=22) and non-PE group (n=22). Patient characteristics including gender, age of disease onset, course of disease, history of thymoma resection, clinical absolute scores [clinical absolute scores (CAS) and clinical relative scores (CRS)], and synchronized immunotherapy regimen of the two groups were analyzed. The CAS scores before and after treatment were compared between the two groups, and the CRS was used to assess the treatment efficiency. Safety of the two treatment regimens were also compared. Continuous variables were compared using the t-test or ANOVA, while categorical data were compared by the chi-square test. Results: A total of 133 patients were included and divided into two groups according to whether they underwent plasma exchange treatment: the PE group (n=22) and the non-PE group (n=111). To exclude bias caused by large difference in the number of cases between the two groups, we performed propensity score matching. After matching, the number of cases in both groups was 22. There was no significant difference in baseline clinical characteristics between the two groups (P>0.05), including gender, age of onset, duration of disease course, history of thymectomy and baseline CAS score before treatment. Compared to the non-PE group, patients in the PE group showed more significant improvement in CAS score (5.09±1.95 vs 3.59±1.50, P<0.05) and a higher CRS score (75.00% vs 50.00%, P<0.001). Compared to the non-PE group, PE group had significantly longer ICU stay, longer hospital stay and higher hospitalization cost (P<0.05). There was no statistically significant difference in adverse events between the two groups during treatment (P>0.05). During long-term follow-up, both the PE and non-PE groups showed relatively low 1-, 3-, and 5-year recurrence rate, with no significant difference between the two groups (P>0.05). Conclusion: This study indicates that plasma exchange has clear value in the treatment of patients with thymoma-associated myasthenia gravis. It can not only significantly improve patients' muscle strength to alleviate motor dysfunction and enhance quality of life, but also does not significantly increase the incidence of adverse reactions. Therefore, it can be regarded as one of the preferred treatment options that achieve a "balance between efficacy and safety" for such patients, and provides an important basis for optimizing treatment strategies, improving prognosis, and promoting the application of subsequent treatment regimens.

Eucommiae Cortex, the dried bark of Eucommia ulmoides( Eucommiaceae), has both medicinal and edible values.Modern research has shown that Eucommiae Cortex contains various components such as flavonoids, lignans, iridoids, phenolic acids,terpenoids, and steroids, which have anti-osteoporosis, antioxidant, anti-inflammatory, blood glucose-lowering, and gastrointestinal tract-protecting effects. Eucommiae Cortex has applications in multiple fields such as healthcare, industry, and animal husbandry,demonstrating broad development prospects. This article reviews the chemical constituents, pharmacological effects, and quality control status of Eucommiae Cortex. Furthermore, according to the concept of quality marker(Q-marker), this article predicts the Q-markers of Eucommiae Cortex from traditional medicinal properties, traditional medicinal effects, new medicinal effects, measurability of chemical components, compatibility, harvesting periods, and geographical origins. The components such as pinoresinol diglucoside,chlorogenic acid, caffeic acid, quercetin, baicalein, baicalin, olivil, coniferyl ferulate, and kaempferol can be used as Q-markers for Eucommiae Cortex, which provide reference for establishing a systematic quality control system for Eucommiae Cortex.
Eucommiaceae/chemistry* ; Drugs, Chinese Herbal/pharmacology* ; Quality Control ; Humans ; Animals

This study investigated the effect of Wuling San on transforming growth factor-β1(TGF-β1)-induced fibrosis, inflammation, and oxidative stress in human renal tubular epithelial cells(HK-2) and its mechanism of antioxidant stress injury. HK-2 cells were cultured in vitro and divided into a control group, a TGF-β1 model group, and three treatment groups receiving Wuling San-containing serum at low(2.5%), medium(5.0%), and high(10.0%) doses. TGF-β1 was used to establish the model in all groups except the control group. CCK-8 was used to analyze the effect of different concentrations of Wuling San on the activity of HK-2 cells with or without TGF-β1 stimulation. The expression of key fibrosis molecules, including actin alpha 2(Acta2), collagen type Ⅰ alpha 1 chain(Col1α1), collagen type Ⅲ alpha 1 chain(Col3α1), TIMP metallopeptidase inhibitor 1(Timp1), and fibronectin 1(Fn1), was detected using qPCR. The expression levels of inflammatory cytokines, including tumor necrosis factor-α(TNF-α), interleukin-1β(IL-1β), interleukin-6(IL-6), interleukin-8(IL-8), and interleukin-4(IL-4), were measured using ELISA kits. Glutathione peroxidase(GSH-Px), malondialdehyde(MDA), catalase(CAT), and superoxide dismutase(SOD) biochemical kits were used to analyze the effect of Wuling San on TGF-β1-induced oxidative stress injury in HK-2 cells, and the expression of nuclear factor E2-related factor 2(Nrf2), heme oxygenase 1(HO-1), and NAD(P)H quinone oxidoreductase 1(NQO1) was analyzed by qPCR and immunofluorescence. The CCK-8 results indicated that the optimal administration concentrations of Wuling San were 2.5%, 5.0%, and 10.0%. Compared with the control group, the TGF-β1 model group showed significantly increased levels of key fibrosis molecules(Acta2, Col1α1, Col3α1, Timp1, and Fn1) and inflammatory cytokines(TNF-α, IL-1β, IL-6, IL-8, and IL-4). In contrast, the Wuling San administration groups were able to dose-dependently inhibit the expression levels of key fibrosis molecules and inflammatory cytokines compared with the TGF-β1 model group. Wuling San significantly increased the activities of GSH-Px, CAT, and SOD enzymes in TGF-β1-stimulated HK-2 cells and significantly inhibited the level of MDA. Furthermore, compared with the control group, the TGF-β1 model group exhibited a significant reduction in the expression of Nrf2, HO-1, and NQO1 genes and proteins. After Wuling San intervention, the expression of Nrf2, HO-1, and NQO1 genes and proteins was significantly increased. Correlation analysis showed that antioxidant stress enzymes(GSH-Px, CAT, and SOD) and Nrf2 signaling were significantly negatively correlated with key fibrosis molecules and inflammatory cytokines in the TGF-β1-stimulated HK-2 cell model. In conclusion, Wuling San can inhibit TGF-β1-induced fibrosis in HK-2 cells by activating the Nrf2 signaling pathway, improving oxidative stress injury, and reducing inflammation.
Humans ; Oxidative Stress/drug effects* ; Transforming Growth Factor beta1/metabolism* ; Fibrosis/genetics* ; Cell Line ; Drugs, Chinese Herbal/pharmacology* ; Epithelial Cells/immunology* ; Inflammation/metabolism*