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There has been an increasing amount of research on regenerative medicine for the treatment of bone defects. Scaffolds are needed for the formation of new bone, and various scaffolding materials have been evaluated for bone regeneration. Materials with pores that allow cells to differentiate into osteocytes are preferred in scaffolds for bone regeneration, and porous materials and fibers are well suited for this application. Electrospinning is an effective method for producing a nanosized fiber by applying a high voltage to the needle tip containing a polymer solution. The use of electrospun nanofibers is being studied in the medical field, and its use as a scaffold for bone regeneration therapy has become a topic of growing interest. In this review, we will introduce the potential use of electrospun nanofiber as a scaffold for bone regenerative medicine with a focus on carbon nanofibers produced by the electrospinning method.The objective of this article is to discuss the inherent bias involved with artificial intelligence-based decision support systems for healthcare. In this article, the authors describe some relevant work published in this area. A proposed overview of solutions is also presented. The authors believe that the information presented in this article will enhance the readers' understanding of this inherent bias and add to the discussion on this topic. Finally, the authors discuss an overview of the need to implement transdisciplinary solutions that can be used to mitigate this bias.Several versions of convolutional neural network (CNN) were developed to classify hyperspectral images (HSIs) of agricultural lands, including 1D-CNN with pixelwise spectral data, 1D-CNN with selected bands, 1D-CNN with spectral-spatial features and 2D-CNN with principal components. The HSI data of a crop agriculture in Salinas Valley and a mixed vegetation agriculture in Indian Pines were used to compare the performance of these CNN algorithms. The highest overall accuracy on these two cases are 99.8% and 98.1%, respectively, achieved by applying 1D-CNN with augmented input vectors, which contain both spectral and spatial features embedded in the HSI data.Even though anti-TNF therapy significantly improves the rates of remission in inflammatory bowel disease (IBD) patients, there is a noticeable subgroup of patients who do not respond to treatment. Dysbiosis emerges as a key factor in IBD pathogenesis. The aim of the present study is to profile changes in the gut microbiome and transcriptome before and after administration of the anti-TNF agent Infliximab (IFX) and investigate their potential to predict patient response to IFX at baseline. Mucosal biopsy samples from 20 IBD patients and nine healthy controls (HC) were examined for differences in microbiota composition (16S rRNA gene sequencing) and mucosal gene expression (RT-qPCR) at baseline and upon completion of IFX treatment, accordingly, via an in silico pipeline. Significant differences in microbiota composition were found between the IBD and HC groups. Several bacterial genera, which were found only in IBD patients and not HC, had their populations dramatically reduced after anti-TNF treatment regardless of response. Alpha and beta diversity metrics showed significant differences between our study groups. Correlation analysis revealed six microbial genera associated with differential expression of inflammation-associated genes in IFX treatment responders at baseline. This study shows that IFX treatment has a notable impact on both the gut microbial composition and the inflamed tissue transcriptome in IBD patients. Importantly, our results identify enterotypes that correlate with transcriptome changes and help differentiate IFX responders versus non-responders at baseline, suggesting that, in combination, these signatures can be an effective tool to predict anti-TNF response.Biofilms located within the root canals of teeth are a unique and pressing concern in dentistry and in medical microbiology. These multispecies biofilms, which include fungi as well as bacteria, form in a protected site with low shear stress and low oxygen tension. Systemic antibiotics are of limited value because of the lack of blood flow of the site, and issues with innate and acquired resistance. Physical disruption using hand or rotary powered instruments does not reach all locations in the root canal system where biofilms are present. Alternative strategies including agitated irrigation fluids, continuous chelation, materials with highly alkaline pH, and antimicrobial nanoparticles are being explored to meet the challenge. Detection and quantification of biofilms using fluorescence-based optical methods could provide an indication of successful biofilm removal and an endpoint for physical and chemical treatments.PURPOSE Aging lowers brain functionality, and obesity accelerates this process. Resistance exercise can help reverse aging; however, studies examining how it affects brain function and body mass are limited. Thus, this study aimed to investigate the effect of resistance exercise on inflammation and neurotrophic factors in elderly women with obesity. METHODS Twenty-six elderly women with obesity were selected for this study and randomly assigned into a control group (CG, n = 13) and an experimental group (EG, n = 13). Selleck WZB117 The EG performed resistance training thrice weekly for 12 weeks using elastic bands, while the CG did not exercise. Serum lipid profile (total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C)) and nuclear factor Kappa B (NF-κB), interferon-gamma (IFN-γ), brain-derived neurotrophic factor (BDNF), vascular endothelial growth factor (VEGF), and eotaxin-1 levels were analyzed before and after the intervention. Body composition (soft lean mass (SLM), skeletal muscle mass (SMM), body fat mass (BFM), percent body fat (PBF), waist-hip-ratio (WHR), basal metabolic rates (BMR)) measurements and blood tests were performed. RESULTS Among the body composition variables, SLM, SMM, and BMR in the EG were significantly increased after intervention (p 0.05). After intervention, the levels of NF-κB, IFN-γ, and eotaxin-1 were significantly lower and BDNF and VEGF were significantly higher in the EG than in the CG (p less then 0.05 for all). CONCLUSIONS These results imply that regular resistance training in elderly women with obesity can increase muscle mass, reduce inflammation, and stimulate neurotrophic factors.