Transforming growth factor-β (TGF-β) isoforms are secreted as inactive complexes formed through non-covalent interactions between bioactive TGF-β entities and their N-terminal pro-domains called latency-associated peptides (LAP). Extracellular activation of latent TGF-β within this complex is a crucial step in the regulation of TGF-β activity for tissue homeostasis and immune cell function. We previously showed that the matrix glycoprotein Tenascin-X (TN-X) interacted with the small latent TGF-β complex and triggered the activation of the latent cytokine into a bioactive TGF-β. This activation most likely occurs through a conformational change within the latent TGF-β complex and requires the C-terminal fibrinogen-like (FBG) domain of the glycoprotein. As the FBG-like domain is highly conserved among the Tenascin family members, we hypothesized that Tenascin-C (TN-C), Tenascin-R (TN-R) and Tenascin-W (TN-W) might share with TN-X the ability to regulate TGF-β bioavailability through their C-terminal domain. Here, we demonstrate that purified recombinant full-length Tenascins associate with the small latent TGF-β complex through their FBG-like domains. This association promotes activation of the latent cytokine and subsequent TGF-β cell responses in mammary epithelial cells, such as cytostasis and epithelial-to-mesenchymal transition (EMT). Considering the pleiotropic role of TGF-β in numerous physiological and pathological contexts, our data indicate a novel common function for the Tenascin family in the regulation of tissue homeostasis under healthy and pathological conditions.
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http://dx.doi.org/10.3389/fimmu.2021.613438 | DOI Listing |
Front Cardiovasc Med
December 2024
Emergency Center, Hubei Clinical Research Center for Emergency and Resuscitaion, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China.
Background: Artificial intelligence (AI) has been widely adopted for the prediction of latent shock occurrence in critically ill patients in intensive care units (ICUs). However, the usefulness of an ICU-based model to predict latent shock risk in an emergency department (ED) setting remains unclear. This study aimed to develop an AI model to predict latent shock risk in patients admitted to EDs.
View Article and Find Full Text PDFBackground Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR. Methods Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.
View Article and Find Full Text PDFHomelessness is a growing concern in the United States, especially among people who use drugs (PWUD). The degree of material hardship among this population may be linked to worse health outcomes. PWUD experiencing homelessness in urban areas are increasingly subjected to policies and social treatment, such as forced displacement, which may worsen material hardship.
View Article and Find Full Text PDFSexual and gender minority young adult (SGM YA) populations use tobacco at higher rates than their non-SGM YA peers. Prior studies have identified significant correlations between interpersonal stigma and tobacco use, yet structural stigma may also influence tobacco use among SGM YA. This study aimed to assess the indirect effects of structural stigma on current tobacco use among SGM YA and non-SGM YA via depletion of economic resources, interpersonal discrimination, and perceived psychological stress.
View Article and Find Full Text PDFFront Psychol
December 2024
Department of Industrial/Organizational and Social Psychology, Institute of Psychology, Technical University Braunschweig, Braunschweig, Germany.
Companies have to undergo many change processes to succeed in the transforming economy. However, many change processes fail because employees are insufficiently accompanied through the process in a targeted manner. This study of N = 427 employees from a steel industry company undergoing a transformation process examines whether the organizational readiness for change (ORC) of highly affected employees can be classified into profiles, how these profiles can be predicted by various antecedents, and whether outcome variables such as job satisfaction can be explained by profile membership.
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