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Kahali, S.

Publications and source records attributed to Kahali, S..

4 recordsLinked to original sources

Metal homeostasis is remodeled in response to different quiescence triggers

Cells can enter a reversible non-proliferative state called quiescence either spontaneously or in response to nutrient deprivations. Metal ions are essential nutrients and play wide-ranging regulatory and signaling roles in biological processes. We previously showed that zinc is an essential nutrient for the mammalian cell cycle as zinc deprivation drives cells into quiescence, and this quiescent state is associated with changes in iron, copper, and manganese, suggesting broad remodeling of metal homeostasis. Here we examine whether metal remodeling is a general feature of quiescence by inducing quiescence via different triggers (zinc deficiency, serum starvation, and growth factor withdrawal) in MCF10A cells. Fluorescence microscopy and elemental analysis reveal significant trigger-dependent changes in the labile and total metal pools of quiescent cells. To gain insight into these differences, we carried out RNA sequencing and differential expression analysis, focusing on metal associated, metal regulatory, and metal homeostasis genes. While core quiescence pathways are shared across triggers, quiescence states remain molecularly distinct. A significant percent of 2458 metal homeostasis annotated genes are differentially expressed including 55% in starvation-induced quiescence, 50% in zinc deficiency-induced quiescence and 21% in growth factor withdrawal-induced quiescence. Our results also showed unique alteration of genes involved in major metal dependent processes including antioxidant activity, oxidative phosphorylation, heme metabolism, and chromatin accessibility in different quiescence states. Overall, this work demonstrates that metal homeostasis is systematically rewired during cellular quiescence with associated effects on genes that regulate critical biological processes. Significance StatementCells constantly evaluate their nutrient and energy status and integrate these signals into proliferation-quiescence decisions. Quiescence prevents cells from passing damage to daughter cells. Metals are essential micronutrients for biological processes. While limitation of zinc can drive cells into quiescence and alter other metals, how metals are remodeled and whether this is a common feature of quiescence was unknown. Here we examined three quiescence triggers by modifying growth media and serum, the primary source of metals. We report significant changes in labile and total Cu, Fe, Zn and Mn pools, and metal associated genes in response to distinct quiescence triggers. These changes converge on mitochondrial function, cellular antioxidant activity, and heme biosynthesis in a trigger specific manner.

cell biology↗

Deep-Learning-Based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient Recalled Echo (qGRE) MRI metrics associated with Human Brain Neuronal Structure and Hemodynamic Properties

PurposeTo introduce a Deep-Learning-Based Accelerated and Noise-Suppressed Estimation (DANSE) method for reconstructing quantitative maps of biological tissue cellular-specific, R2t* and hemodynamic-specific, R2' from Gradient-Recalled-Echo (GRE) MRI data with multiple gradient-recalled echoes. MethodsDANSE method adapts supervised learning paradigm to train a convolutional neural network for robust estimation of R2t* and R2' maps free from the adverse effects of macroscopic (B0) magnetic field inhomogeneities directly from the GRE magnitude images without utilizing phase images. The corresponding ground-truth maps were generated by means of a voxel-by-voxel fitting of a previously-developed biophysical quantitative GRE (qGRE) model accounting for tissue, hemodynamic and B0-inhomogeneities contributions to GRE signal with multiple gradient echoes using nonlinear least square (NLLS) algorithm. ResultsWe show that the DANSE model efficiently estimates the aforementioned brain maps and preserves all features of NLLS approach with significant improvements including noise-suppression and computation speed (from many hours to seconds). The noise-suppression feature of DANSE is especially prominent for data with SNR characteristic for typical GRE data (SNR~50), where DANSE-generated R2t* and R2' maps had three times smaller errors than that of NLLS method. ConclusionsDANSE method enables fast reconstruction of magnetic-field-inhomogeneity-free and noise-suppressed quantitative qGRE brain maps. DANSE method does not require any information about field inhomogeneities during application. It exploits spatial patterns in the qGRE MRI data and previously-gained knowledge from the biophysical model, thus producing clean brain maps even in the environments with high noise levels. These features along with fast computational speed can lead to broad qGRE clinical and research applications.

neuroscience↗

The Role of the Human Brain Neuron-Glia-Synaptic Composition in Forming Resting State Functional Connectivity Networks

While significant progress has been achieved in studying resting state functional networks in a healthy human brain and in a wide range of clinical conditions, many questions related to their relationship to the brains cellular constituents remain open. Herein we use quantitative Gradient-Recalled-Echo (qGRE) MRI for mapping human brain cellular composition, and BOLD (blood oxygen level dependent) MRI to explore how the brain cellular constituents relate to resting state functional networks. Results show that the BOLD-signal-defined synchrony of connections between cellular circuits in network-defined individual functional units is mainly associated with the regional neuronal density, while the between-functional-units connectivity strength is also influenced by the glia and synaptic components of brain tissue cellular constituents. These mechanisms lead to a rather broad distribution of resting state functional networks properties. Visual networks with the highest neuronal density (but lowest density of glial cells and synapses) exhibit the strongest coherence of BOLD signal, as well as the strongest intra-network connectivity. The Default Mode Network (DMN) is positioned near the opposite part of the spectrum with relatively low coherence of the BOLD signal but a remarkably balanced cellular content enabling DMN prominent role in the overall organization of the brain and the hierarchy of functional networks.

neuroscience↗