Identification of Retinoic Acid in a High Content Screen for Agents that Overcome the Anti-Myogenic Effect of TGF-Beta-1

Transforming growth factor beta 1 (TGF-β1) is an inhibitor of muscle cell differentiation that is associated with fibrosis, poor regeneration and poor function in some diseases of muscle. When neutralizing antibodies to TGF-β1 or the angiotensin II inhibitor losartan were used to reduce TGF-β1 signaling, muscle morphology and function were restored in mouse models of Marfan Syndrome and muscular dystrophy. The goal of our studies was to identify additional agents that overcome the anti-myogenic effect of TGF-β1.A high-content cell-based assay was developed in a 96-well plate format that detects the expression of myosin heavy chain (MHC) in C2C12 cells. The assay was used to quantify the dose-dependent responses of C2C12 cell differentiation to TGF-β1 and to the TGF-β1 Type 1 receptor kinase inhibitor, SB431542. Thirteen agents previously described as promoting C2C12 differentiation in the absence of TGF-β1 were screened in the presence of TGF-β1. Only all-trans retinoic acid and 9-cis retinoic acid allowed a maximal level of C2C12 cell differentiation in the presence of TGF-β1; the angiotensin-converting enzyme inhibitor captopril and 10 nM estrogen provided partial rescue. Vitamin D was a potent inhibitor of retinoic acid-induced myogenesis in the presence of TGF-β1. TGF-β1 inhibits myoblast differentiation through activation of Smad3; however, retinoic acid did not inhibit TGF-β1-induced activation of a Smad3-dependent reporter gene in C2C12 cells.Retinoic acid alleviated the anti-myogenic effect of TGF-β1 by a Smad3-independent mechanism. With regard to the goal of improving muscle regeneration and function in individuals with muscle disease, the identification of retinoic acid is intriguing in that some retinoids are already approved for human therapy. However, retinoids also have well-described adverse effects. The quantitative, high-content assay will be useful to screen for less-toxic retinoids or combinations of agents that promote myoblast differentiation in the presence of TGF-β1

Impaired Release of Antimicrobial Peptides into Nasal Fluid of Hyper-IgE and CVID Patients

Patients with primary immunodeficiency (PID) often suffer from frequent respiratory tract infections. Despite standard treatment with IgG-substitution and antibiotics many patients do not improve significantly. Therefore, we hypothesized that additional immune deficits may be present among these patients.To investigate if PID patients exhibit impaired production of antimicrobial peptides (AMPs) in nasal fluid and a possible link between AMP-expression and Th17-cells.Nasal fluid, nasopharyngeal swabs and peripheral blood mononuclear cells (PBMCs) were collected from patients and healthy controls. AMP levels were measured in nasal fluid by Western blotting. Nasal swabs were cultured for bacteria. PBMCs were stimulated with antigen and the supernatants were assessed for IL-17A release by ELISA.In healthy controls and most patients, AMP levels in nasal fluid were increased in response to pathogenic bacteria. However, this increase was absent in patients with common variable immunodeficiency (CVID) and Hyper-IgE syndrome (HIES), despite the presence of pathogenic bacteria. Furthermore, stimulation of PBMCs revealed that both HIES and CVID patients exhibited an impaired production of IL-17A.CVID and HIES patients appear to have a dysregulated AMP response to pathogenic bacteria in the upper respiratory tract, which could be linked to an aberrant Th17 cell response

Expression of IL-23/Th17-related cytokines in basal cell carcinoma and in the response to medical treatments

Several immune-related markers have been implicated in basal cell carcinoma (BCC) pathogenesis. The BCC inflammatory infiltrate is dominated by Th2 cytokines, suggesting a specific state of immunosuppression. In contrast, regressing BCC are characterized by a Th1 immune response with IFN-γ promoting a tumor suppressive activity. IL-23/Th17-related cytokines, as interleukin (IL)-17, IL-23 and IL-22, play a significant role in cutaneous inflammatory diseases, but their involvement in skin carcinogenesis is controversial and is poorly investigated in BCC. In this study we investigated the expression of IFN-γ, IL-17, IL-23 and IL-22 cytokines in BCC at the protein and mRNA level and their modulation during imiquimod (IMQ) treatment or photodynamic therapy (PDT). IFN-γ, IL-17, IL-23 and IL-22 levels were evaluated by immunohistochemistry and quantitative Real Time PCR in 41 histopatho-logically-proven BCCs (28 superficial and 13 nodular) from 39 patients. All BCC samples were analyzed at baseline and 19 of 41 also during medical treatment (9 with IMQ 5% cream and 10 with MAL-PDT). Association between cytokines expression and clinico-pathological variables was evaluated. Higher levels of IFN-γ, IL-17, IL-23 and IL-22 were found in BCCs, mainly in the peritumoral infiltrate, compared to normal skin, with the expression being correlated to the severity of the inflammatory infiltrate. IFN-γ production was higher in superficial BCCs compared to nodular BCCs, while IL-17 was increased in nodular BCCs. A significant correlation was found between IFN-γ and IL-17 expression with both cytokines expressed by CD4+ and CD8+ T-cells. An increase of all cytokines occurred during the inflammatory phase induced by IMQ and at the early time point of PDT treatment, with significant evidence for IFN-γ, IL-23, and IL-22. Our results confirm the role of IFN-γ and support the involvement of IL-23/Th17-related cytokines in BCC pathogenesis and in the inflammatory response during IMQ and MAL-PDT treatments

Simultaneous Super-Resolution and Classification of Lung Disease Scans

Acute lower respiratory infection is a leading cause of death in developing countries. Hence, progress has been made for early detection and treatment. There is still a need for improved diagnostic and therapeutic strategies, particularly in resource-limited settings. Chest X-ray and computed tomography (CT) have the potential to serve as effective screening tools for lower respiratory infections, but the use of artificial intelligence (AI) in these areas is limited. To address this gap, we present a computer-aided diagnostic system for chest X-ray and CT images of several common pulmonary diseases, including COVID-19, viral pneumonia, bacterial pneumonia, tuberculosis, lung opacity, and various types of carcinoma. The proposed system depends on super-resolution (SR) techniques to enhance image details. Deep learning (DL) techniques are used for both SR reconstruction and classification, with the InceptionResNetv2 model used as a feature extractor in conjunction with a multi-class support vector machine (MCSVM) classifier. In this paper, we compare the proposed model performance to those of other classification models, such as Resnet101 and Inceptionv3, and evaluate the effectiveness of using both softmax and MCSVM classifiers. The proposed system was tested on three publicly available datasets of CT and X-ray images and it achieved a classification accuracy of 98.028% using a combination of SR and InceptionResNetv2. Overall, our system has the potential to serve as a valuable screening tool for lower respiratory disorders and assist clinicians in interpreting chest X-ray and CT images. In resource-limited settings, it can also provide a valuable diagnostic support