The Landscape of microRNAs in βCell: Between Phenotype Maintenance and Protection

Diabetes mellitus is a group of heterogeneous metabolic disorders characterized by chronic hyperglycaemia mainly due to pancreatic β cell death and/or dysfunction, caused by several types of stress such as glucotoxicity, lipotoxicity and inflammation. Different patho-physiological mechanisms driving β cell response to these stresses are tightly regulated by microRNAs (miRNAs), a class of negative regulators of gene expression, involved in pathogenic mechanisms occurring in diabetes and in its complications. In this review, we aim to shed light on the most important miRNAs regulating the maintenance and the robustness of β cell identity, as well as on those miRNAs involved in the pathogenesis of the two main forms of diabetes mellitus, i.e., type 1 and type 2 diabetes. Additionally, we acknowledge that the understanding of miRNAs-regulated molecular mechanisms is fundamental in order to develop specific and effective strategies based on miRNAs as therapeutic targets, employing innovative molecules.     

Precision Oncology via NMR-Based Metabolomics: A Review on Breast Cancer

Precision oncology is an emerging approach in cancer care. It aims at selecting the optimal therapy for the right patient by considering each patient’s unique disease and individual health status. In the last years, it has become evident that breast cancer is an extremely heterogeneous disease, and therefore, patients need to be appropriately stratified to maximize survival and quality of life. Gene-expression tools have already positively assisted clinical decision making by estimating the risk of recurrence and the potential benefit from adjuvant chemotherapy. However, these approaches need refinement to further reduce the proportion of patients potentially exposed to unnecessary chemotherapy. Nuclear magnetic resonance (NMR) metabolomics has demonstrated to be an optimal approach for cancer research and has provided significant results in BC, in particular for prognostic and stratification purposes. In this review, we give an update on the status of NMR-based metabolomic studies for the biochemical characterization and stratification of breast cancer patients using different biospecimens (breast tissue, blood serum/plasma, and urine).     

The effect of ionising radiation on photosynthetic oxygenic microorganisms for survival in space flight revealed by automatic photosystem II-based biosensors

Photosynthetic microorganisms are expected to be useful to maintain an oxygenic atmosphere and to provide biomass for astronauts in the International Space Station as well as in future long-term space flights. However, fluxes of complex ionizing radiation of various intensities and energies make space an extreme environment for the microorganisms, affecting their photosynthetic efficiency. To automatically monitor the photosynthetic Photosystem II (PSII) activity of microorganisms under space conditions an optical biosensor, which utilizes chlorophyll fluorescence as biological transduction system, was built; the PSII activity was monitored by the biosensor during balloon flights at stratospheric altitudes of about 40 km. The effect of space stress on quantum yield of PSII varied among the tested species depending on the growth light conditions at which they were exposed during the flights.     

A Food-Grade Method for Enhancing the Levels of Low Molecular Weight Proanthocyanidins with Potentially High Intestinal Bioavailability

Proanthocyanidins (PACs) are a group of bioactive molecules found in a variety of plants and foods. Their bioavailability depends on their molecular size, with monomers and dimers being more bioavailable than those that have a higher polymerization degree. This study aimed to develop a method to convert high-molecular-weight PACs to low-molecular-weight ones in a grape seed extract (GSE) from Vitis vinifera L. Therefore, GSE was subjected to alkaline treatment (ATGSE), and its difference in chemical composition, compared to GSE, was evaluated using a molecular networking (MN) approach based on results obtained from HPLC-ESI HRMS/MS characterization analysis. The network analysis mainly noted the PAC cluster with about 142 PAC compounds identified. In particular, the obtained results showed a higher content of monomeric and dimeric PACs in ATGSE compared to GSE, with 58% and 49% monomers and 31% and 24% dimers, respectively. Conversely, trimeric (9%), polymeric (4%), and galloylated PACs (14%) were more abundant in GSE than in ATGSE (6%, 1%, and 4%, respectively). Moreover, in vitro antioxidant and anti-inflammatory activities were investigated, showing the high beneficial potential of both extracts. In conclusion, ATGSE could represent an innovative natural matrix rich in bioavailable and bioaccessible PACs for nutraceutical applications with potential beneficial properties.     

Bioinformatics Analysis of RNA-seq Data Reveals Genes Related to Cancer Stem Cells in Colorectal Cancerogenesis

Cancer stem cells (CSC) play one of the crucial roles in the pathogenesis of various cancers, including colorectal cancer (CRC). Although great efforts have been made regarding our understanding of the cancerogenesis of CRC, CSC involvement in CRC development is still poorly understood. Using bioinformatics and RNA-seq data of normal mucosa, colorectal adenoma, and carcinoma (n = 106) from GEO and TCGA, we identified candidate CSC genes and analyzed pathway enrichment analysis (PEI) and protein–protein interaction analysis (PPI). Identified CSC-related genes were validated using qPCR and tissue samples from 47 patients with adenoma, adenoma with early carcinoma, and carcinoma without and with lymph node metastasis and were compared to normal mucosa. Six CSC-related genes were identified: ANLN, CDK1, ECT2, PDGFD, TNC, and TNXB. ANLN, CDK1, ECT2, and TNC were differentially expressed between adenoma and adenoma with early carcinoma. TNC was differentially expressed in CRC without lymph node metastases whereas ANLN, CDK1, and PDGFD were differentially expressed in CRC with lymph node metastases compared to normal mucosa. ANLN and PDGFD were differentially expressed between carcinoma without and with lymph node metastasis. Our study identified and validated CSC-related genes that might be involved in early stages of CRC development (ANLN, CDK1, ECT2, TNC) and in development of metastasis (ANLN, PDGFD).     

How Can We Improve Vaccination Response in Old People? Part I: Targeting Immunosenescence of Innate Immunity Cells

Vaccination, being able to prevent millions of cases of infectious diseases around the world every year, is the most effective medical intervention ever introduced. However, immunosenescence makes vaccines less effective in providing protection to older people. Although most studies explain that this is mainly due to the immunosenescence of T and B cells, the immunosenescence of innate immunity can also be a significant contributing factor. Alterations in function, number, subset, and distribution of blood neutrophils, monocytes, and natural killer and dendritic cells are detected in aging, thus potentially reducing the efficacy of vaccines in older individuals. In this paper, we focus on the immunosenescence of the innate blood immune cells. We discuss possible strategies to counteract the immunosenescence of innate immunity in order to improve the response to vaccination. In particular, we focus on advances in understanding the role and the development of new adjuvants, such as TLR agonists, considered a promising strategy to increase vaccination efficiency in older individuals.     

An Ultra-Low Dose of ∆9-Tetrahydrocannabinol Alleviates Alzheimer’s Disease-Related Cognitive Impairments and Modulates TrkB Receptor Expression in a 5XFAD Mouse Model

Alzheimer’s disease (AD) is the most common form of dementia, but there is still no available treatment. Δ9-tetrahydrocannabinol (THC) is emerging as a promising therapeutic agent. Using THC in conventional high doses may have deleterious effects. Therefore, we propose to use an ultra-low dose of THC (ULD-THC). We previously published that a single injection of ULD-THC ameliorated cognitive functioning in several models of brain injuries as well as in naturally aging mice. Here, 5xFAD AD model mice received a single treatment of ULD-THC (0.002 mg/kg) after disease onset and were examined in two separate experiments for cognitive functions, neurotropic, and inflammatory factors in the hippocampus. We show that a single injection of ULD-THC alleviated cognitive impairments in 6- and 12-month-old 5xFAD mice. On the biochemical level, our results indicate an imbalance between the truncated TrkB receptor isoform and the full receptor, with AD mice showing a greater tendency to express the truncated receptor, and ULD-THC improved this imbalance. We also investigated the expression of three AD-related inflammatory markers and found an ameliorating effect of ULD-THC. The current research demonstrates for the first time the beneficial effects of a single ultra-low dose of THC in a mouse model of AD after disease onset.     

Effectiveness of Semi-Supervised Active Learning in Automated Wound Image Segmentation

Appropriate wound management shortens the healing times and reduces the management costs, benefiting the patient in physical terms and potentially reducing the healthcare system’s economic burden. Among the instrumental measurement methods, the image analysis of a wound area is becoming one of the cornerstones of chronic ulcer management. Our study aim is to develop a solid AI method based on a convolutional neural network to segment the wounds efficiently to make the work of the physician more efficient, and subsequently, to lay the foundations for the further development of more in-depth analyses of ulcer characteristics. In this work, we introduce a fully automated model for identifying and segmenting wound areas which can completely automatize the clinical wound severity assessment starting from images acquired from smartphones. This method is based on an active semi-supervised learning training of a convolutional neural network model. In our work, we tested the robustness of our method against a wide range of natural images acquired in different light conditions and image expositions. We collected the images using an ad hoc developed app and saved them in a database which we then used for AI training. We then tested different CNN architectures to develop a balanced model, which we finally validated with a public dataset. We used a dataset of images acquired during clinical practice and built an annotated wound image dataset consisting of 1564 ulcer images from 474 patients. Only a small part of this large amount of data was manually annotated by experts (ground truth). A multi-step, active, semi-supervised training procedure was applied to improve the segmentation performances of the model. The developed training strategy mimics a continuous learning approach and provides a viable alternative for further medical applications. We tested the efficiency of our model against other public datasets, proving its robustness. The efficiency of the transfer learning showed that after less than 50 epochs, the model achieved a stable DSC that was greater than 0.95. The proposed active semi-supervised learning strategy could allow us to obtain an efficient segmentation method, thereby facilitating the work of the clinician by reducing their working times to achieve the measurements. Finally, the robustness of our pipeline confirms its possible usage in clinical practice as a reliable decision support system for clinicians.     

Effects of Physiological and Pathological Urea Concentrations on Human Microvascular Endothelial Cells

Urea is the uremic toxin accumulating with the highest concentration in the plasma of chronic kidney disease (CKD) patients, not being completely cleared by dialysis. Urea accumulation is reported to exert direct and indirect side effects on the gastrointestinal tract, kidneys, adipocytes, and cardiovascular system (CVS), although its pathogenicity is still questioned since studies evaluating its side effects lack homogeneity. Here, we investigated the effects of physiological and pathological urea concentrations on a human endothelial cell line from the microcirculation (Human Microvascular Endothelial Cells-1, HMEC-1). Urea (5 g/L) caused a reduction in the proliferation rate after 72 h of exposure and appeared to be a potential endothelial-to-mesenchymal transition (EndMT) stimulus. Moreover, urea induced actin filament rearrangement, a significant increase in matrix metalloproteinases 2 (MMP-2) expression in the medium, and a significant up- or down-regulation of other EndMT biomarkers (keratin, fibrillin-2, and collagen IV), as highlighted by differential proteomic analysis. Among proteins whose expression was found to be significantly dysregulated following exposure of HMEC-1 to urea, dimethylarginine dimethylaminohydrolase (DDAH) and vasorin turned out to be down-regulated. Both proteins have been directly linked to cardiovascular diseases (CVD) by in vitro and in vivo studies. Future experiments will be needed to deepen their role and investigate the signaling pathways in which they are involved to clarify the possible link between CKD and CVD.