The relationship between AGR2 levels and intestinal barrier function in high-fat diet animal models.

This study aimed to observe the effect of anterior gradient protein 2 (AGR2) levels on intestinal barrier function in HFD animal models. For this purpose, thirty healthy male clean-grade C57BL/6 mice were randomly separated into a normal control group and a high-fat group. The normal control group was fed a normal diet, while the high-fat group was fed an HFD for a total of 8 weeks. It collected body weight changes before and after modeling of two groups of rats and serum samples and detected fasting blood glucose, total cholesterol, triglycerides, AGR2, and diamine oxidase (DAO) concentrations. It collected the expression levels of AGR2 in the colon of rats after modeling, evaluated the permeability of the colon and small intestine barrier by Ussing chamber and Evan's blue (EB) methods, and analyzed the correlation between AGR2 levels and intestinal barrier function using Pearson correlation. Results showed that when the two groups of mice were fed for 8 weeks, their body weight, fasting blood glucose, total cholesterol, and triglycerides all met the characteristics of an HFD mouse model, and the model was successfully established. When the two groups of mice were fed for 8 weeks, the serum AGR2 concentration, relative expression of AGR2 in colon tissue, Gt, and EB content of the high-fat group mice were higher than those of the normal control group, and the difference was significant (P<0.05); Meanwhile, the serum DAO concentration and Isc of the high-fat group mice were lower than those of the normal control group, with statistically significant differences (P<0.05); The relative expression levels of serum AFR2 and colon AGR2 were negatively correlated with Isc (r=-0.503, -0.623, P<0.05), and positively correlated with Gt (r=0.461, 0.560, P<0.05). There was a homogeneous distribution characteristic between the relative expression levels of serum AFR2 and serum DAO, colon AGR2, and Isc variables. It was concluded that HFD could upregulate the expression of AGR2 in mice, downregulate the level of DAO, and damage the intestinal barrier function of mice. Both serum AGR2 concentration and colonic AGR2 relative expression can participate in the regulation of colonic intestinal barrier function and can serve as potential indicators for evaluating intestinal barrier damage.

Preparation and characterization of self-assembled ZnO nanowire devices: nanowire strain sensor and homogeneous p-n junction.

In this work, intrinsic and p-type ZnO nanowires (NWs) have been synthesized. Pure intrinsic ZnO nanowires have been fabricated by direct oxidation method and their aspect ratio reached up to 271.3. Sb-doped ZnO nanowires were uniformly grown on Si substrates by chemical vapor deposition with diameters ranging from 0.5 to 5µm and lengths ranging from 100µm to 3 mm. Directional arrangement of nanowires has been realized by two self-assembly methods, pulling method and water flow method, and two kinds of ZnO nanodevices (strain sensor and homogenous p-n junction) were prepared and characterized based on the directional arranged nanowires. According to the current response of ZnO nanowire strain sensor, the deformation quantities of elastic plate under the action of external forces in orthogonalXandYdirection were calculated respectively. The ZnO nanowire homogenous p-n junction was made of two vertical Sb-doped and intrinsic ZnO nanowires. TheI-Vcharacteristic curve showed good rectification characteristics, and the forward turn-on voltage was about 10 V. However, since the current was too small due to the small carrier concentration in the ZnO single crystal, it is difficult to achieve electroluminescence at present.

Local H2 release remodels senescence microenvironment for improved repair of injured bone.

The senescence microenvironment, which causes persistent inflammation and loss of intrinsic regenerative abilities, is a main obstacle to effective tissue repair in elderly individuals. In this work, we find that local H2 supply can remodel the senescence microenvironment by anti-inflammation and anti-senescence effects in various senescent cells from skeletally mature bone. We construct a H2-releasing scaffold which can release high-dosage H2 (911 mL/g, up to 1 week) by electrospraying polyhydroxyalkanoate-encapsulated CaSi2 nanoparticles onto mesoporous bioactive glass. We demonstrate efficient remodeling of the microenvironment and enhanced repair of critical-size bone defects in an aged mouse model. Mechanistically, we reveal that local H2 release alters the microenvironment from pro-inflammation to anti-inflammation by senescent macrophages repolarization and secretome change. We also show that H2 alleviates the progression of aging/injury-superposed senescence, facilitates the recruitment of endogenous cells and the preservation of their regeneration capability, thereby creating a pro-regenerative microenvironment able to support bone defect regeneration.

Efficacy and Safety of Anlotinib in Overall and Disease-Specific Advanced Gynecological Cancer: A Real-World Study.

Purpose: Anlotinib is a novel oral small-molecule multi-target tyrosine kinase inhibitor that has been approved for treating non-small cell lung cancer. However, its efficacy and safety among patients with advanced gynecological cancer have not been comprehensively evaluated. We conducted this study to address this issue in the real-world setting. Patients and Methods: Data from patients treated with Anlotinib for persistent, recurrent or metastatic gynecological cancer were collected from 17 centers from August 2018. The database lock-time was on March 2022. Anlotinib was administered orally on days 1-14 every 3 weeks until disease progression, severe toxicity occurred, or death. In this study, disease-specific advanced gynecological cancer was mainly referred to cervical, endometrial, and ovarian cancer. The outcomes included objective response rate (ORR), disease control rate (DCR), and progression-free survival (PFS). Results: A total of 249 patients were analyzed, with a median follow-up of 14.5 months. The overall ORR and DCR were 28.1% [95% confidence interval (CI) 22.6% to 34.1%] and 80.7% (95% CI 75.3% to 85.4%), respectively. Specifically, the ORR varied from 19.7% to 34.4% and the DCR differed from 81.7% to 90.0% in disease-specific advanced gynecological cancer. The median PFS was 6.1 months and ranged from 5.6 to 10.0 months in the overall and disease-specific advanced gynecological cancer, respectively. Larger cumulative dosage of Anlotinib (>700 mg) was in general associated with longer PFS in the overall and disease-specific advanced gynecological cancer. The most common adverse event related to Anlotinib treatment was pain/arthralgia (18.3%). Conclusion: In conclusion, Anlotinib holds promise in treating patients with advanced gynecological cancer including its disease-specific types, with reasonable efficacy and tolerable safety.

An Unsupervised Deep Learning-Based Model Using Multiomics Data to Predict Prognosis of Patients with Stomach Adenocarcinoma.

Methods: Patients (363 in total) with stomach adenocarcinoma from The Cancer Genome Atlas (TCGA) cohort were included. An autoencoder was constructed to integrate the RNA sequencing, miRNA sequencing, and methylation data. The features of the bottleneck layer were used to perform the k-means clustering algorithm to obtain different subgroups for evaluating the prognosis-related risk of stomach adenocarcinoma. The model's robustness was verified using a 10-fold cross-validation (CV). Survival was analyzed by the Kaplan-Meier method. Univariate and multivariate Cox regression was used to estimate hazard risk. The model was validated in three independent cohorts with different endpoints. Results: The patients were divided into low-risk and high-risk groups according to the k-means clustering algorithm. The high-risk group had a significantly higher risk of poor survival (log-rank P value = 2.80e - 06; adjusted hazard ratio = 2.386, 95% confidence interval: 1.607~3.543), a concordance index (C-index) of 0.714, and a Brier score of 0.184. The model performed well both in the 10-fold CV procedure and three independent cohorts from the Gene Expression Omnibus (GEO) repository. Conclusions: A robust and generalizable model based on the autoencoder was proposed to integrate multiomics data and predict the prognosis of patients with stomach adenocarcinoma. The model demonstrates better performance than two alternative approaches on prognosis prediction. The results might provide the grounds for further exploring the potential biomarkers to predict the prognosis of patients with stomach adenocarcinoma.