A Biodegradable Nano-Drug Delivery Platform for Co-Delivery of Minocycline and Chitosan to Achieve Efficient and Safe Non-Surgical Periodontitis Therapy.

INTRODUCTION: Mesoporous silica nanoparticles (MSN) are widely used as ideal nanovehicles for the delivery of chemotherapeutic drugs. However, the balance between high anti-periodontitis activity and low biotoxicity has been challenging to maintain in most relevant studies owing to the slow degradation of silica in living organisms. METHOD: In this study, -responsive hydroxyapatite (HAP) was doped into the MSN skeleton, and the chemotherapeutic drug minocycline hydrochloride (MH) was loaded into the pores of MSN, forming a negatively charged drug delivery system. Cationic chitosan (COS) is a biodegradable material with high antibacterial performance and good biosafety. In this study, COS was immobilized on the surface of the drug-loaded particles through stable charge interaction to construct a composite drug delivery system (MH@MSNion@COS). RESULTS: In vitro and cellular experiments demonstrated effective degradation of the nanocarrier system and synchronized controlled release of the drug. Notably, compared with single MH administration, this system, in which MH and COS jointly regulated the expression levels of periodontitis- associated inflammatory factors (TNF-α, IL-6, IL-1ß, and iNOS), better inhibited the progress of periodontitis and induced tissue regeneration without showing significant toxic side effects in cells. CONCLUSION: This system provides a promising strategy for the design of intelligent, efficient, and safe anti-periodontitis drug delivery systems.

Uncertainty-Aware Distillation for Semi-Supervised Few-Shot Class-Incremental Learning.

Given a model well-trained with a large-scale base dataset, few-shot class-incremental learning (FSCIL) aims at incrementally learning novel classes from a few labeled samples by avoiding overfitting, without catastrophically forgetting all encountered classes previously. Currently, semi-supervised learning technique that harnesses freely available unlabeled data to compensate for limited labeled data can boost the performance in numerous vision tasks, which heuristically can be applied to tackle issues in FSCIL, i.e., the semi-supervised FSCIL (Semi-FSCIL). So far, very limited work focuses on the Semi-FSCIL task, leaving the adaptability issue of semi-supervised learning to the FSCIL task unresolved. In this article, we focus on this adaptability issue and present a simple yet efficient Semi-FSCIL framework named uncertainty-aware distillation with class-equilibrium (UaD-ClE), encompassing two modules: uncertainty-aware distillation (UaD) and class equilibrium (ClE). Specifically, when incorporating unlabeled data into each incremental session, we introduce the ClE module that employs a class-balanced self-training (CB_ST) to avoid the gradual dominance of easy-to-classified classes on pseudo-label generation. To distill reliable knowledge from the reference model, we further implement the UaD module that combines uncertainty-guided knowledge refinement with adaptive distillation. Comprehensive experiments on three benchmark datasets demonstrate that our method can boost the adaptability of unlabeled data with the semi-supervised learning technique in FSCIL tasks. The code is available at https://github.com/yawencui/UaD-ClE.

A Self-Cleaning TiO2 Bacterial Cellulose Super-Hydrophilic Underwater Super-Oleophobic Composite Membrane for Efficient Oil-Water Separation.

Due to the increasingly serious problem of offshore oil spills, research related to oil-water separation has attracted more and more attention. Here, we prepared a super-hydrophilic/underwater super-oleophobic membrane (hereinafter referred to as BTA) using poly-dopamine (PDA) to adhesive TiO2 nanoparticles on the surface of bacterial cellulose, coated with sodium alienate by vacuum-assisted filtration technique. This demonstrates its excellent underwater super-oleophobic property. Its contact angle is about 153°. Remarkably, BTA has 99% separation efficiency. More importantly, BTA still showed excellent anti-pollution property under ultraviolet light after 20 cycles. BTA has the advantages of low cost, environmentally friendliness and good anti-fouling performance. We believe it can play an important role in dealing with problems related to oily wastewater.

Study on Springback Straightening after Bending of the U-Section of TC4 Material under High-Temperature Conditions.

The thin-walled structures of titanium alloys have peculiar characteristics involving thin curved surfaces, complicated structures, and a poor rigidity. Therefore, bending or twisting distortion frequently occurs in forging, extrusion, drawing, transportation, cooling, and manufacturing. Straightening theory focuses on the straightening curvature or bending moment at room temperature, and a unified analytical model of the straightening curvature, the straightening bending moment, and the straightening stroke, as well as a study on springback straightening under high-temperature conditions, have not been investigated comprehensively. In order to understand the inherent mechanism of springback straightening and quantitative prediction of springback under high-temperature conditions, uniaxial tension tests were carried out to obtain the true stress-strain model of material and stress relaxation under the stress relaxation model. This paper is based on the theory of elastic-plastic mechanics and combines this with the mechanism of stress relaxation to establish springback and residual relative curvature equations of springback. The law of springback straightening is further explored, and springback and residual deflection equations are provided. The results of the study showed that the relative errors of the theoretical residual deflection of the bending deformation and residual deflections obtained by the experiment were less than 20%, with an average absolute error of less than 10%. Therefore, the hardening models adopted can achieve an allowable relative error if hardening parameters are properly selected. The proposed research provides basic data for the prediction of springback straightening, and the design of springback compensation tools can be applied in practical applications.

PPARD rs2016520 polymorphism affects repaglinide response in Chinese Han patients with type 2 diabetes mellitus.

Repaglinide is a short-acting insulin secretagogue, which often results in considerable interindividual variability in therapeutic efficacy when widely used in a clinical setting. Among various reasons under discussion is genetic polymorphism, especially the genes related to insulin secretion and resistance. Recent studies have described the importance of PPARD in regulating the secretion and resistance of insulin. However, little is known about the impacts of PPARD genetic polymorphism on the efficacy of repaglinide. Therefore, the current study was designed to investigate the associations of PPARD rs2016520 polymorphism with type 2 diabetes mellitus (T2DM) susceptibility and repaglinide therapeutic efficacy in Chinese Han T2DM patients. A total of 338 T2DM patients and 200 healthy subjects were genotyped for PPARD rs2016520 polymorphism by polymerase chain reaction-restriction fragment length polymorphism assay. A total of 84 patients with the same genotypes of CYP2C8*3 139Arg and OATP1B1 521TT were randomized to orally take repaglinide for 8 weeks. Then the pharmacodynamic parameters of repaglinide and biochemical indicators were determined before and after repaglinide treatment. No significant difference was found in either allelic frequency (P = 0.298) or genotype distribution (P = 0.151) of PPARD rs2016520 between T2DM patients and healthy subjects. However, T2DM patients carrying genotype TC showed a significantly lower increase in postprandial serum insulin (mU/L) than those with wild-type TT (P < 0.05). These findings suggest that PPARD rs2016520 polymorphism might influence the therapeutic effect of repaglinide rather than T2DM susceptibility in Chinese Han T2DM patients.