Highly Porous, Ultralight, Biocompatible Silk Fibroin Aerogel-Based Triboelectric Nanogenerator.

This study presents the fabrication of an ultralight, porous, and high-performance triboelectric nanogenerator (TENG) utilizing silk fibroin (SF) aerogels and PDMS sponges as the friction layer. The transition from two-dimensional film friction layers to three-dimensional porous aerogels significantly increased the specific surface area, offering an effective strategy for designing high-performance SF aerogel-based TENGs. The TENG incorporating the porous SF aerogel exhibited optimal output performance at a 3% SF concentration, achieving a maximum open circuit voltage of 365 V, a maximum short-circuit current of 11.8 µA, and a maximum power density of 7.52 W/m2. In comparison to SF-film-based TENGs, the SF-aerogel based TENG demonstrated a remarkable 6.5-fold increase in voltage and a 4.5-fold increase in current. Furthermore, the power density of our SF-based TENG surpassed the previously reported optimal values for SF-based TENGs by 2.4 times. Leveraging the excellent mechanical stability and biocompatibility of TENGs, we developed an SF-based TENG self-powered sensor for the real-time monitoring of subtle biological movements. The SF-based TENG exhibits promising potential as a wearable bioelectronic device for health monitoring.

Comparative Gene Expression Analysis of Salmonella Typhimurium DT104 in Ground Chicken Extract and Brain Heart Infusion Broth.

Salmonella enterica Typhimurium DT104 (S. Typhimurium DT104) is an important foodborne pathogen that is associated with poultry and poultry products. Currently, there is very little information on the underlying molecular mechanisms that allow DT104 to survive and propagate in poultry meat and the poultry processing environment. The current study assessed the global gene expression of DT104 in ground chicken extract (GCE) compared to brain heart infusion (BHI) medium using RNA-Seq technology. DT104 was grown to the early stationary phase (ESP), inoculated into GCE or BHI, and then re-grown to the log phase before RNA was extracted and transcripts were quantified by RNA-Seq. Gene expression for DT104 grown in GCE was then compared to that of DT104 grown in BHI for samples grown to the ESP. Growth in GCE resulted in the up-regulated expression of genes related to translation, carnitine metabolism (23-283-fold change), and cobalamin (vitamin B12) biosynthesis (14-fold change). In particular, the presence of carnitine in chicken meat, and thus, in GCE, which lacks carbohydrates, may allow Salmonella to utilize this compound as a carbon and nitrogen source. This study demonstrates that RNA-Seq data can provide a comprehensive analysis of DT104 gene expression in a food model for poultry products. This study also provides additional evidence for the importance of metabolic adaptation in the ability of S. enterica to successfully adapt to and occupy niches outside of its host and provides potential targets that could be used to develop intervention strategies to control Salmonella in poultry.

Druggability Analysis of Protein Targets for Drug Discovery to Combat Listeria monocytogenes.

Extensive research has been conducted to identify key proteins governing stress responses, virulence, and antimicrobial resistance, as well as to elucidate their interactions within Listeria monocytogenes. While these proteins hold promise as potential targets for novel strategies to control L. monocytogenes, given their critical roles in regulating the pathogen's metabolism, additional analysis is needed to further assess their druggability-the chance of being effectively bound by small-molecule inhibitors. In this work, 535 binding pockets of 46 protein targets for known drugs (mainly antimicrobials) were first analyzed to extract 13 structural features (e.g., hydrophobicity) in a ligand-protein docking platform called Molsoft ICM Pro. The extracted features were used as inputs to develop a logistic regression model to assess the druggability of protein binding pockets, with a value of one if ligands can bind to the protein pocket. The developed druggability model was then used to evaluate 23 key proteins from L. monocytogenes that have been identified in the literature. The following proteins are predicted to be high-potential druggable targets: GroEL, FliH/FliI complex, FliG, FlhB, FlgL, FlgK, InlA, MogR, and PrfA. These findings serve as an initial point for future research to identify specific compounds that can inhibit druggable target proteins and to design experimental work to confirm their effectiveness as drug targets.

Investigation of Potential Drug Targets Involved in Inflammation Contributing to Alzheimer's Disease Progression.

Alzheimer's disease has become a major public health issue. While extensive research has been conducted in the last few decades, few drugs have been approved by the FDA to treat Alzheimer's disease. There is still an urgent need for understanding the disease pathogenesis, as well as identifying new drug targets for further drug discovery. Alzheimer's disease is known to arise from a build-up of amyloid beta (Aß) plaques as well as tangles of tau proteins. Along similar lines to Alzheimer's disease, inflammation in the brain is known to stem from the degeneration of tissue and build-up of insoluble materials. A minireview was conducted in this work assessing the genes, proteins, reactions, and pathways that link brain inflammation and Alzheimer's disease. Existing tools in Systems Biology were implemented to build protein interaction networks, mainly for the classical complement pathway and G protein-coupled receptors (GPCRs), to rank the protein targets according to their interactions. The top 10 protein targets were mainly from the classical complement pathway. With the consideration of existing clinical trials and crystal structures, proteins C5AR1 and GARBG1 were identified as the best targets for further drug discovery, through computational approaches like ligand-protein docking techniques.