Hydrogel Based on Riclin Cross-Linked with Polyethylene Glycol Diglycidyl Ether as a Soft Filler for Tissue Engineering.

Hydrogels composed of natural polysaccharides have been widely used as filling materials, with a growing interest in medical cosmetology and skin care. However, conventional commercial dermal fillers still have limitations, particularly in terms of mechanical performance and durability in vivo. In this study, a novel injectable and implantable hydrogel with adjustable characteristics was prepared from succinoglycan riclin by introducing PEG diglycidyl ether as a cross-linker. FTIR spectra confirmed the cross-linking reaction. The riclin hydrogels exhibited shear-thinning behavior, excellent mechanical properties, and cytocompatibility through in vitro experiments. Furthermore, when compared with subcutaneous injection of a commercial hyaluronic acid hydrogel, the riclin hydrogels showed enhanced persistence and biocompatibility in Balb/c mice after 16 weeks. These results demonstrate the great potential of the riclin-based hydrogel as an alternative to conventional commercial soft tissue fillers.

Indium Tin Oxide Induced Internal Positive Feedback and Indium Ion Transport in Perovskite Solar Cells.

Stability is the most pressing challenge hindering the commercialization of perovskite solar cells (PSCs), and previous efforts focused more on enhancing the resistance of PSCs to external stimulus. Here, we found that the indium tin oxide (ITO) will deteriorate the photovoltaic performance of PSCs through positive feedback cycles. Specifically, the perovskite degradation products will cross the electron transport layer to chemically etch the electrode ITO to generate In3+, which will migrate upwards into the perovskite film. Then, the reaction that corrodes ITO consumes the decomposition products of perovskite and shifts the balance of the perovskite decomposition reaction, further promoting the degradation and thus falling into a positive feedback cycle. Moreover, the In3+ in the perovskite film was found to accumulate at the upper surface, which would lead to n-type doping of perovskite film to form the energy barrier for interface carrier extraction. Subsequently, the chelating molecule ethylenediaminetetraacetic acid disodium salt (EDTA-2Na) was introduced onto ITO to firmly chelate the In3+ and prevent it from migrating upward, thus breaking this internal positive feedback cycle and significantly enhancing the efficiency and stability of PSCs. This work provides new perspectives for understanding the mechanism of photovoltaic performance loss and ionic transport in PSCs.

Hemoadhican-Based Bioabsorbable Hydrogel for Preventing Postoperative Adhesions.

Postoperative peritoneal adhesions are a prevalent clinical issue following abdominal and pelvic surgery, frequently resulting in heightened personal and societal health burdens. Traditional biomedical barriers offer limited benefits because of practical challenges for doctors and their incompatibility with laparoscopic surgery. Hydrogel materials, represented by hyaluronic acid gels, are receiving increasing attention. However, existing antiadhesive gels still have limited effectiveness or carry the risk of complications in clinical applications. Herein, we developed a novel hydrogel using polysaccharide hemoadhican (HD) as the base material and polyethylene glycol diglycidyl ether (PEGDE) as the cross-linking agent. The HD hydrogels exhibit appropriate mechanical properties, injectability, and excellent cytocompatibility. We demonstrate resistance to protein adsorption and L929 fibroblast cell adhesion to the HD hydrogel. The biodegradability and efficacy against peritoneal adhesion are further evaluated in C57BL/6 mice. Our results suggest a potential strategy for anti-postoperative tissue adhesion barrier biomaterials.

Cuproptosis gene-related, neural network-based prognosis prediction and drug-target prediction for KIRC.

BACKGROUND: Kidney renal clear cell carcinoma (KIRC), as a common case in renal cell carcinoma (RCC), has the risk of postoperative recurrence, thus its prognosis is poor and its prognostic markers are usually based on imaging methods, which have the problem of low specificity. In addition, cuproptosis, as a novel mode of cell death, has been used as a biomarker to predict disease in many cancers in recent years, which also provides an important basis for prognostic prediction in KIRC. For postoperative patients with KIRC, an important means of preventing disease recurrence is pharmacological treatment, and thus matching the appropriate drug to the specific patient's target is also particularly important. With the development of neural networks, their predictive performance in the field of medical big data has surpassed that of traditional methods, and this also applies to the field of prognosis prediction and drug-target prediction. OBJECTIVE: The purpose of this study is to screen for cuproptosis genes related to the prognosis of KIRC and to establish a deep neural network (DNN) model for patient risk prediction, while also developing a personalized nomogram model for predicting patient survival. In addition, sensitivity drugs for KIRC were screened, and a graph neural network (GNN) model was established to predict the targets of the drugs, in order to discover potential drug action sites and provide new treatment ideas for KIRC. METHODS: We used the Cancer Genome Atlas (TCGA) database, International Cancer Genome Consortium (ICGC) database, and DrugBank database for our study. Differentially expressed genes (DEGs) were screened using TCGA data, and then a DNN-based risk prediction model was built and validated using ICGC data. Subsequently, the differences between high- and low-risk groups were analyzed and KIRC-sensitive drugs were screened, and finally a GNN model was trained using DrugBank data to predict the relevant targets of these drugs. RESULTS: A prognostic model was built by screening 10 significantly different cuproptosis-related genes, the model had an AUC of 0.739 on the training set (TCGA data) and an AUC of 0.707 on the validation set (ICGC data), which demonstrated a good predictive performance. Based on the prognostic model in this paper, patients were also classified into high- and low-risk groups, and functional analyses were performed. In addition, 251 drugs were screened for sensitivity, and four drugs were ultimately found to have high sensitivity, with 5-Fluorouracil having the best inhibitory effect, and subsequently their corresponding targets were also predicted by GraphSAGE, with the most prominent targets including Cytochrome P450 2D6, UDP-glucuronosyltransferase 1A, and Proto-oncogene tyrosine-protein kinase receptor Ret. Notably, the average accuracy of GraphSAGE was 0.817 ± 0.013, which was higher than that of GAT and GTN. CONCLUSION: Our KIRC risk prediction model, constructed using 10 cuproptosis-related genes, had good independent prognostic ability. In addition, we screened four highly sensitive drugs and predicted relevant targets for these four drugs that might treat KIRC. Finally, literature research revealed that four drug-target interactions have been demonstrated in previous studies and the remaining targets are potential sites of drug action for future research.

Quasi-type-II Cu-In-Zn-S/Ni-MOF heterostructure with prolonged carrier lifetime for photocatalytic hydrogen production.

Visible-driven photocatalytic hydrogen production using narrow-bandgap semiconductors has great potential for clean energy development. However, the widespread use of these semiconductors is limited due to problems such as severe charge recombination and slow surface reactions. Herein, a quasi-type-II heterostructure was constructed by combining bifunctional Ni-based metal-organic framework (Ni-MOF) nanosheets with BDC (1,4-benzenedicarboxylic acid) linker coupled with Cu-In-Zn-S quantum dots (CIZS QDs). This heterostructure exhibited a prolonged charge carrier lifetime and abundant active sites, leading to significantly improved hydrogen production rate. The optimized rate achieved by the CIZS/Ni-MOF heterostructure was 2642 µmol g-1 h-1, which is 5.28 times higher than that of the CIZS QDs. This improved performance can be attributed to the quasi-type-II band alignment between the CIZS QDs and Ni-MOF, which facilitates effective delocalization of the photogenerated electrons within the system. Additional photoelectrochemical tests confirmed the well-maintained photoluminescence and prolonged charge carrier lifetime of the CIZS/Ni-MOF heterostructure. This study provides valuable insights into the use of multifunctional MOFs in the development of highly efficient composite photocatalysts, extending beyond their role in light harvesting and charge separation.

Exploring the mediating role of calcium homeostasis in the association between diabetes mellitus, glycemic traits, and vascular and valvular calcifications: a comprehensive Mendelian randomization analysis.

BACKGROUND: The interplay between diabetes mellitus (DM), glycemic traits, and vascular and valvular calcifications is intricate and multifactorial. Exploring potential mediators may illuminate underlying pathways and identify novel therapeutic targets. METHODS: We utilized univariable and multivariable Mendelian randomization (MR) analyses to investigate associations and mediation effects. Additionally, the multivariable MR analyses incorporated cardiometabolic risk factors, allowing us to account for potential confounders. RESULTS: Type 2 diabetes mellitus (T2DM) and glycated hemoglobin (HbA1c) were positively associated with both coronary artery calcification (CAC) and calcific aortic valvular stenosis (CAVS). However, fasting glucose (FG) was only linked to CAVS and showed no association with CAC. Additionally, CAVS demonstrated a causal effect on FG. Calcium levels partially mediated the impact of T2DM on both types of calcifications. Specifically, serum calcium was positively associated with both CAC and CAVS. The mediation effects of calcium levels on the impact of T2DM on CAC and CAVS were 6.063% and 3.939%, respectively. The associations between T2DM and HbA1c with calcifications were influenced by body mass index (BMI) and smoking status. However, these associations were generally reduced after adjusting for hypertension. CONCLUSION: Our findings suggest a genetically supported causal relationship between DM, glycemic traits, and vascular and valvular calcifications, with serum calcium playing a critical mediating role.

Prenatal chromosomal microarray analysis in a large Chinese cohort of fetuses with congenital heart defects: a single center study.

BACKGROUND AND OBJECTIVES: Congenital heart defect (CHD) is one of the most common birth defects. The aim of this cohort study was to evaluate the prevalence of chromosomal abnormalities and the clinical utility of chromosomal microarray analysis (CMA) in fetuses with different types of CHD, aiming to assist genetic counseling and clinical decision-making. METHODS: In this study, 642 fetuses with CHD were enrolled from a single center over a six-year period (2017-2022). Both conventional karyotyping and CMA were performed simultaneously on these fetuses. RESULTS: The diagnostic yield of CMA in fetuses with CHD in our study was 15.3% (98/642). Our findings revealed a significant increase in the diagnostic yield of CMA compared to karyotyping in fetuses with CHD. Among CHD subgroups, the diagnostic yields were high in complex CHD (34.9%), conotruncal defects (28.6%), right ventricular outflow tract obstructive defects (RVOTO) (25.9%), atrioventricular septal defects (AVSD) (25.0%) and left ventricular outflow tract obstructive defects (LVOTO) (24.1%), while those in other CHD (10.6%) and septal defects (10.9%) were relatively low. The overall detection rate of clinically significant chromosomal abnormalities was significantly higher in the non-isolated CHD group compared to the isolated CHD group (33.1% vs. 9.9%, P < 0.0001). Interestingly, numerical chromosomal abnormalities were more likely to occur in the non-isolated CHD group than in the isolated CHD group (20.3% vs. 2.0%, P < 0.0001). The rate of termination of pregnancy (TOP)/Still birth in the non-isolated CHD group was significantly higher than that in the isolated CHD group (40.5% vs. 20.6%, P < 0.0001). Compared to the isolated CHD group, the detection rate of clinically significant chromosomal abnormalities was significantly higher in the group of CHD with soft markers (35.6% vs. 9.9%, P < 0.0001) and in the group of CHD with additional structural anomalies (36.1% vs. 9.9%, P < 0.0001). CONCLUSIONS: CMA is a reliable and high-resolution technique that should be recommended as the front-line test for prenatal diagnosis of fetuses with CHD. The prevalence of chromosomal abnormalities varies greatly among different subgroups of CHD, and special attention should be given to prenatal non-isolated cases of CHD, especially those accompanied by additional structural anomalies or soft markers.