Marcussengauthier5393

The major form of cell death in normal as well as malignant cells is apoptosis, which is a programmed process highly regulated by the BCL-2 family of proteins. This includes the antiapoptotic proteins (BCL-2, BCL-XL, MCL-1, BCLW, and BFL-1) and the proapoptotic proteins, which can be divided into two groups the effectors (BAX, BAK, and BOK) and the BH3-only proteins (BIM, BAD, NOXA, PUMA, BID, BIK, HRK). Notably, the BCL-2 antiapoptotic proteins are often overexpressed in malignant cells. While this offers survival advantages to malignant cells and strengthens their drug resistance capacity, it also offers opportunities for novel targeted therapies that selectively kill such cells. This review provides a comprehensive overview of the extensive preclinical and clinical studies targeting BCL-2 proteins with various BCL-2 proteins inhibitors with emphasis on venetoclax as a single agent, as well as in combination with other therapeutic agents. This review also discusses recent advances, challenges focusing on drug resistance, and future perspectives for effective targeting the Bcl-2 family of proteins in cancer.Transforming growth factor-β1 (TGF-β1)-induced myofibroblast transdifferentiation from orbital fibroblasts is known to dominate tissue remodeling and fibrosis in Graves' ophthalmopathy (GO). However, the signaling pathways through which TGF-β1 activates Graves' orbital fibroblasts remain unclear. This study investigated the role of the mitogen-activated protein kinase (MAPK) pathway in TGF-β1-induced myofibroblast transdifferentiation in human Graves' orbital fibroblasts. The MAPK pathway was assessed by measuring the phosphorylation of p38, c-Jun N-terminal kinase (JNK), and extracellular-signal-regulated kinase (ERK) by Western blots. The expression of connective tissue growth factor (CTGF), α-smooth muscle actin (α-SMA), and fibronectin representing fibrogenesis was estimated. Fludarabine supplier The activities of matrix metalloproteinases (MMPs) and tissue inhibitors of metalloproteinases (TIMPs) responsible for extracellular matrix (ECM) metabolism were analyzed. Specific pharmacologic kinase inhibitors were used to confirm the involvement of the MAPK pathway. After treatment with TGF-β1, the phosphorylation levels of p38 and JNK, but not ERK, were increased. CTGF, α-SMA, and fibronectin, as well as TIMP-1 and TIMP-3, were upregulated, whereas the activities of MMP-2/-9 were inhibited. The effects of TGF-β1 on the expression of these factors were eliminated by p38 and JNK inhibitors. The results suggested that TGF-β1 could induce myofibroblast transdifferentiation in human Graves' orbital fibroblasts through the p38 and JNK pathways.Recent reports highlighted the significant neuroprotective effects of thyronamines (TAMs), a class of endogenous thyroid hormone derivatives. In particular, 3-iodothyronamine (T1AM) has been shown to play a pleiotropic role in neurodegeneration by modulating energy metabolism and neurological functions in mice. However, the pharmacological response to T1AM might be influenced by tissue metabolism, which is known to convert T1AM into its catabolite 3-iodothyroacetic acid (TA1). Currently, several research groups are investigating the pharmacological effects of T1AM systemic administration in the search of novel therapeutic approaches for the treatment of interlinked pathologies, such as metabolic and neurodegenerative diseases (NDDs). A critical aspect in the development of new drugs for NDDs is to know their distribution in the brain, which is fundamentally related to their ability to cross the blood-brain barrier (BBB). To this end, in the present study we used the immortalized mouse brain endothelial cell line bEnd.3 to develop an in vitro model of BBB and evaluate T1AM and TA1 permeability. Both drugs, administered at 1 µM dose, were assayed by high-performance liquid chromatography coupled to mass spectrometry. Our results indicate that T1AM is able to efficiently cross the BBB, whereas TA1 is almost completely devoid of this property.Parkinson's disease (PD) is a neurodegenerative disorder that affects 1% of the population over the age of 60. Diabetes Mellitus (DM) is a metabolic disorder that affects approximately 25% of adults over the age of 60. Recent studies showed that DM increases the risk of developing PD. The link between DM and PD has been discussed in the literature in relation to different mechanisms including mitochondrial dysfunction, oxidative stress, and protein aggregation. In this paper, we review the common microRNA (miRNA) biomarkers of both diseases. miRNAs play an important role in cell differentiation, development, the regulation of the cell cycle, and apoptosis. They are also involved in the pathology of many diseases. miRNAs can mediate the insulin pathway and glucose absorption. miRNAs can also regulate PD-related genes. Therefore, exploring the common miRNA biomarkers of both PD and DM can shed a light on how these two diseases are correlated, and targeting miRNAs is a potential therapeutic opportunity for both diseases.Oral cancer/oral squamous cell carcinoma is among the top ten most common cancers globally, with over 500,000 new cases and 350,000 associated deaths every year worldwide. There is a critical need for objective, novel technologies that facilitate early, accurate diagnosis. For this purpose, we have developed a method to classify images as "suspicious" and "normal" by performing transfer learning on Inception-ResNet-V2 and generated automated heat maps to highlight the region of the images most likely to be involved in decision making. We have tested the developed method's feasibility on two independent datasets of clinical photographic images of 30 and 24 patients from the UK and Brazil, respectively. Both 10-fold cross-validation and leave-one-patient-out validation methods were performed to test the system, achieving accuracies of 73.6% (±19%) and 90.9% (±12%), F1-scores of 97.9% and 87.2%, and precision values of 95.4% and 99.3% at recall values of 100.0% and 81.1% on these two respective cohorts. This study presents several novel findings and approaches, namely the development and validation of our methods on two datasets collected in different countries showing that using patches instead of the whole lesion image leads to better performance and analyzing which regions of the images are predictive of the classes using class activation map analysis.