RESUMEN
Dexamethasone, a synthetic glucocorticoid, is often used to induce osteoblast commitment of mesenchymal stem cells (MSCs), and this process requires RhoA-dependent cellular tension. The underlying mechanism is unclear. In this study, we show that dexamethasone stimulates expression of fibronectin and integrin α5 (ITGA5), accompanied by an increase in the interaction of GEF-H1 (also known as ARHGEF2) with Sec5 (also known as EXOC2), a microtubule (MT)-regulated RhoA activator and a component of the exocyst, respectively. Disruption of this interaction abolishes dexamethasone-induced cellular tension and GEF-H1 targeting to focal adhesion sites at the cell periphery without affecting dexamethasone-induced levels of ITGA5 and fibronectin, and the extracellular deposition of fibronectin at adhesion sites is specifically inhibited. We demonstrate that dexamethasone stimulates the expression of serum-glucocorticoid-induced protein kinase 1 (SGK1), which is necessary and sufficient for the induction of the Sec5-GEF-H1 interaction. Given the function of SGK1 in suppressing MT growth, our data suggest that the induction of SGK1 through treatment with dexamethasone alters MT dynamics to increase Sec5-GEF-H1 interactions, which promote GEF-H1 targeting to adhesion sites. This mechanism is essential for the formation of fibronectin fibrils and their attachment to integrins at adhesion sites in order to generate cellular tension.
Asunto(s)
Dexametasona/farmacología , Inducción Enzimática/efectos de los fármacos , Proteínas Inmediatas-Precoces/metabolismo , Microtúbulos/metabolismo , Proteínas Serina-Treonina Quinasas/metabolismo , Factores de Intercambio de Guanina Nucleótido Rho/metabolismo , Proteínas de Transporte Vesicular/metabolismo , Adhesión Celular/efectos de los fármacos , Humanos , Proteínas Inmediatas-Precoces/genética , Microtúbulos/genética , Proteínas Serina-Treonina Quinasas/genética , Factores de Intercambio de Guanina Nucleótido Rho/genética , Proteínas de Transporte Vesicular/genéticaRESUMEN
African Swine Fever (ASF) is a reportable disease of swine that causes far-reaching losses to affected countries and regions. Early detection is critically important to contain and mitigate the impact of ASF outbreaks, for which timely available data is essential. This research examines the potential use of Google Trends data as an early indicator of ASF outbreaks in Southeast Asia, focusing on the three largest swine producing countries, namely, Vietnam, the Philippines, and Thailand. Cross-correlation and Kullback-Leibler (KL) divergence indicators were used to evaluate the association between Google search trends and the number of ASF outbreaks reported. Our analysis indicate strong and moderate correlations between Google search trends and number of ASF outbreaks reported in Vietnam and the Philippines, respectively. In contrast, Thailand, the country of this group in which outbreaks were reported last, exhibits the weakest correlation (KL = 2.64), highlighting variations in public awareness and disease dynamics. These findings suggest that Google search trends are valuable for early detection of ASF. As the disease becomes endemic, integrating trends with other epidemiological data may support the design and implementation of surveillance strategies for transboundary animal diseases in Southeast Asia.
RESUMEN
ROCK (Rho-associated protein kinase), a downstream effector of RhoA, plays an important role in many cellular processes. Accumulating evidence has shown the involvement of ROCK activation in the pathogenesis of many diseases. However, a reagent capable of detecting ROCK activation directly is lacking. In the present study, we show autophosphorylation of ROCKII in an in vitro kinase reaction. The phosphorylation sites were identified by MS, and the major phosphorylation site was found to be at the highly conserved residue Ser1366. A phospho-specific antibody was generated that can specifically recognize ROCKII Ser1366 phosphorylation. We found that the extent of Ser1366 phosphorylation of endogenous ROCKII is correlated with that of myosin light chain phosphorylation in cells in response to RhoA stimulation, showing that Ser1366 phosphorylation reflects its kinase activity. In addition, ROCKII Ser1366 phosphorylation could be detected in human breast tumours by immunohistochemical staining. The present study provides a new approach for revealing the ROCKII activation status by probing ROCKII Ser1366 phosphorylation directly in cells or tissues.
Asunto(s)
Activación Enzimática , Serina/metabolismo , Quinasas Asociadas a rho/metabolismo , Amidas/farmacología , Secuencia de Aminoácidos , Sustitución de Aminoácidos , Animales , Anticuerpos/aislamiento & purificación , Western Blotting , Células HEK293 , Humanos , Inmunoprecipitación , Ratones , Datos de Secuencia Molecular , Mutagénesis Sitio-Dirigida , Fosforilación , Unión Proteica , Piridinas/farmacología , Conejos , Quinasas Asociadas a rho/antagonistas & inhibidores , Quinasas Asociadas a rho/genética , Quinasas Asociadas a rho/inmunología , Proteína de Unión al GTP rhoA/metabolismoRESUMEN
The problem of the efficient design of material microstructures exhibiting desired properties spans a variety of engineering and science applications. The ability to rapidly generate microstructures that exhibit user-specified property distributions can transform the iterative process of traditional microstructure-sensitive design. We reformulate the microstructure design process using a constrained generative adversarial network (GAN) model. This approach explicitly encodes invariance constraints within GANs to generate two-phase morphologies for photovoltaic applications obeying design specifications: specifically, user-defined short-circuit current density and fill factor combinations. Such invariance constraints can be represented by differentiable, deep learning-based surrogates of full physics models mapping microstructures to photovoltaic properties. Furthermore, we propose a multi-fidelity surrogate that reduces expensive label requirements by a factor of five. Our framework enables the incorporation of expensive or non-differentiable constraints for the fast generation of microstructures (in 190 ms) with user-defined properties. Such proposed physics-aware data-driven methods for inverse design problems can be used to considerably accelerate the field of microstructure-sensitive design.
RESUMEN
PURPOSE: Chemotherapy-induced peripheral neuropathy often results in a reduction in drug dose. However, the serum level of anticancer drugs varies with time after intravenous infusion, and this factor has seldom been considered in previous in vitro studies. The goals of this study were to build an automatic dosage control system and to evaluate the influence of drug infusion rate on the cells. METHODS: Neurons and melanoma cells were used as the samples. The 3-h (average and peak concentration: 0.024 and 0.287 µM) and 24-h infusion (average and peak concentration: 0.020 and 0.042 µM) schemes were investigated. For evaluations, cell indentation tests by an atomic force microscope, serial immunofluorescent images, and cell viability analysis was performed. RESULTS: For the neurons, Young's modulus first increased and then remained unchanged in the 3-h scheme, but was stationary throughout the observation period in the 24-h scheme. For the cancer cells, Young's modulus increased in both infusion schemes, and the increase was larger in the 3-h scheme. Morphologically, axons swelled and shortened, and the number of their branches decreased in the 3-h scheme. In contrast, there was only slowed growth of axons without obvious morphological changes in the 24-h scheme. Viability analysis of the cancer cells revealed that the 3-h scheme had a better anticancer effect. CONCLUSION: A dosage-control system simulating the pharmacodynamic changes of drugs was successfully constructed for in vitro cell cultures. The 3-h scheme of paclitaxel showed better anticancer effects but more adverse effects on neuronal growth and morphology.