Rho GDP dissociation inhibitors (rhoGDIs) are postulated to regulate the activity of small G proteins of the Rho family by a shuttling process involving the extraction of Rho from donor membranes, the formation of the inhibitory cytosolic Rho/rhoGDI complexes, and delivery of Rho to target membranes. However, the role of rhoGDIs in site-specific membrane targeting or extraction of Rho is still poorly understood. Here we investigated the molecular functions of two rhoGDIs, the specific rhoGDI-3 and the less specific but well studied rhoGDI-1, in HeLa cells using structure-based mutagenesis of the rhoGDI protein. We identified two sites in rhoGDI, which form conserved interactions with their Rho target, whose mutation results in the uncoupling of inhibitory and shuttling functions of rhoGDIs: D66GDI-3 (equivalent to D45GDI-1), a conserved residue in the helix-loop-helixGDI/switch 1Rho interface, and D206GDI-3 (equivalent to D185GDI-1) in the beta-sandwichGDI/switch 2Rho interface. Mutations of both sites result in the loss of rhoGDI-3 or rhoGDI-1 inhibitory activity but not of their ability to form cytosolic complexes with RhoG or Cdc42 in vivo. Remarkably, the mutants were detected at Rho-induced membrane ruffles or protrusions where they co-localized with RhoG or Cdc42, likely identifying for the first time the site of extraction of a Rho protein by a rhoGDI in vivo. We propose that these mutations act by modifying the steady-state kinetics of the shuttling process regulated by rhoGDIs, such that transient steps at the cell membranes now become detectable. They should provide valuable tools for future investigations of the dynamics of membrane extraction or delivery of Rho proteins and their regulation by cellular partners.
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Behav Res Methods
January 2025
CogNosco Lab, Department of Psychology and Cognitive Sciences, University of Trento, Trento, Italy.
We introduce EmoAtlas, a computational library/framework extracting emotions and syntactic/semantic word associations from texts. EmoAtlas combines interpretable artificial intelligence (AI) for syntactic parsing in 18 languages and psychologically validated lexicons for detecting the eight emotions in Plutchik's theory. We show that EmoAtlas can match or surpass transformer-based natural language processing techniques, BERT or large language models like ChatGPT 3.
View Article and Find Full Text PDFUltrasound Med Biol
January 2025
Department of Circulation and Medical Imaging, Norwegian University of Science and Technology - NTNU, Trondheim, Norway; Health Research, SINTEF, Trondheim, Norway.
Objective: To develop and compare methods to automatically estimate regional ultrasound image quality for echocardiography separate from view correctness.
Methods: Three methods for estimating image quality were developed: (i) classic pixel-based metric: the generalized contrast-to-noise ratio (gCNR), computed on myocardial segments (region of interest) and left ventricle lumen (background), extracted by a U-Net segmentation model; (ii) local image coherence: the average local coherence as predicted by a U-Net model that predicts image coherence from B-mode ultrasound images at the pixel level; (iii) deep convolutional network: an end-to-end deep-learning model that predicts the quality of each region in the image directly. These methods were evaluated against manual regional quality annotations provided by three experienced cardiologists.
Cytoskeleton (Hoboken)
January 2025
Department of Life Science, Faculty of Science, Gakushuin University, Mejiro, Tokyo, Japan.
Cytokinesis in animal and fungal cells requires the contraction of actomyosin-based contractile rings formed in the division cortex of the cell during late mitosis. However, the detailed mechanism remains incompletely understood. Here, we aim to develop a novel cell-free system by encapsulating cell extracts obtained from fission yeast cells within lipid vesicles, which subsequently leads to the formation of a contractile ring-like structure inside the vesicles.
View Article and Find Full Text PDFBioData Min
January 2025
Department of Computer Science, Hanyang University, Seoul, Republic of Korea.
Background: Understanding the molecular properties of chemical compounds is essential for identifying potential candidates or ensuring safety in drug discovery. However, exploring the vast chemical space is time-consuming and costly, necessitating the development of time-efficient and cost-effective computational methods. Recent advances in deep learning approaches have offered deeper insights into molecular structures.
View Article and Find Full Text PDFJ Appl Physiol (1985)
January 2025
Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
Disruption of the blood supply to a limb in conjunction with active movement boosts muscle growth, aids in rehabilitation, and allows controlled exploration of the sensorimotor system. Yet, the underlying neuromechanical changes have not been observed in great detail. This study aims to report the acute neuromuscular effects of temporary blood flow restriction (BFR) through behavioral changes at the level of motor units (MUs) using high-density surface electromyography on the abductor digiti minimi muscle during 20 trapezoidal and sinusoidal isometric force tracking tasks (5 pre-BFR, 5 during BFR, and 10 post-BFR).
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