Advancing the design of conductive composite cryogels based on hydroxypropyl cellulose derivatives for improving the compressibility and anti-freezing properties.

Conductive hydrogels are an appealing class of "smart" materials with great application potential, as they combine the stimuli-responsiveness of hydrogels with the conductivity of magnetic fillers. However, fabricating multifunctional conductive hydrogels that simultaneously exhibit conductivity, self-healing, adhesiveness, and anti-freezing properties remains a significant challenge. To address this issue, we introduce here a freeze-thawing approach to develop versatile, multiresponsive composite cryogels able to preserve their features under low-temperature conditions.

Chemical Modification of Acrylonitrile-Divinylbenzene Polymer Supports with Aminophosphonate Groups and Their Antibacterial Activity Testing.

Bacterial contamination is a major public health concern on a global scale. Treatment resistance in bacterial infections is becoming a significant problem that requires solutions. We were interested in obtaining new polymeric functionalized compounds with antibacterial properties.

Enhancing orthopaedic implant efficacy: the development of cerium-doped bioactive glass and polyvinylpyrrolidone composite coatings via MAPLE technique.

This study investigates the potential of combining Cerium-doped bioactive glass (BBGi) with Polyvinylpyrrolidone (PVP) to enhance the properties of titanium (Ti) implant surfaces using the Matrix-Assisted Pulsed Laser Evaporation (MAPLE) technique. The primary focus is on improving osseointegration, corrosion resistance, and evaluating the cytotoxicity of the developed thin films towards host cells. The innovative approach involves synthesizing a composite thin film comprising BBGi and PVP, leveraging the distinct benefits of both materials: BBGi's biocompatibility and osteoinductive capabilities, and PVP's film-forming and biocompatible properties.

QSAR Regression Models for Predicting HMG-CoA Reductase Inhibition.

Background/objectives: HMG-CoA reductase is an enzyme that regulates the initial stage of cholesterol synthesis, and its inhibitors are widely used in the treatment of cardiovascular diseases.

Methods: We have created a set of quantitative structure-activity relationship (QSAR) models for human HMG-CoA reductase inhibitors using nested cross-validation as the primary validation method. To develop the QSAR models, we employed various machine learning regression algorithms, feature selection methods, and fingerprints or descriptor datasets.