Biology subjects

Hoang, H.

Publications and source records attributed to Hoang, H..

10 recordsLinked to original sources

bioRxiv2025

A single-cell fixed RNA profiling of liver fibrosis progression and regression reveals SEMA4D and LMCD1 as key mediators of fibrogenesis

Liver fibrosis progression and regression are dynamic processes involving diverse hepatic and immune cell populations. Here, we utilize single-cell fixed RNA profiling (FLEX) of a TAA-induced mouse liver cirrhosis model, with and without a recovery phase, to depict the cellular landscape and molecular mechanisms of fibrosis resolution. The regression phase was characterized by the emergence of pericentral hepatocytes enriched in detoxification and antioxidant genes (e.g., Cyp2e1, Txn1), which secreted Rarres2 to modulate hepatic stellate cell (HSC) function. This was accompanied by the upregulation of scar-resolving genes (Mmp14, Ctsl), restoration of fenestrae in liver sinusoidal endothelial cells, anti-inflammatory phenotypes of Kupffer cells, a decrease in fibrogenic cholangiocyte subsets, and recovery-associated signatures in NK/T cells, B cells, and neutrophils. In contrast, SEMA4D secreted by monocyte-derived macrophages during fibrosis progression activated Plxnb2 HSCs, and its blockade attenuated fibrosis in vivo. Furthermore, LMCD1 was identified as a novel marker for HSC activation and regulation. This single-cell atlas reveals key transcriptional programs and intercellular signaling pathways dependent on the fibrotic condition, offering new therapeutic targets for liver cirrhosis.

cell biology↗

bioRxiv2024

Dopamine-induced Relaxation of Connectivity Diversifies Burst Patterns in Cultured Hippocampal Networks

The intricate interplay of neurotransmitters orchestrates a symphony of neural activity in the hippocampus, with dopamine emerging as a key conductor in this complex ensemble. Despite numerous studies uncovering the cellular mechanisms of dopamine, its influence on hippocampal neural networks remains elusive. Combining in vitro electrophysiological recordings of rat embryonic hippocampal neurons, pharmacological interventions, and computational analyses of spike trains, we found that dopamine induces a relaxation in network connectivity, characterised by a reduction in spike coherence. This relaxation expands the repertoire of burst dynamics within these hippocampal networks, a phenomenon notably absent under the administration of dopamine antagonists. Our study provides a thorough understanding of the roles of dopamine signalling in shaping functional networks of hippocampal neurons.

neuroscience↗

bioRxiv2023

Negative reward-prediction errors of climbing fiber inputs for cerebellar reinforcement learning algorithm

Although the cerebellum is typically linked to supervised learning algorithms, it also exhibits extensive involvement in reward processing. In this study, we investigated the cerebellums role in executing reinforcement learning algorithms, with a particular emphasis on essential reward-prediction errors. We employed the Q-learning model to accurately reproduce the licking responses of mice in a Go/No-go auditory-discrimination task. This method enabled the calculation of reinforcement learning variables, such as reward, predicted reward, and reward-prediction errors in each learning trial. By tensor component analysis of two-photon Ca2+ imaging data from more than 6,000 Purkinje cells, we found that climbing fiber inputs of the two distinct components, which were specifically activated during Go and No-go cues in the learning process, showed an inverse relationship with predictive reward-prediction errors. By assuming bidirectional parallel-fiber Purkinje-cell synaptic plasticity, we constructed a cerebellar neural-network model with 5,000 spiking neurons of granule cells, Purkinje cells, cerebellar nuclei neurons, and inferior olive neurons. The network model qualitatively reproduced distinct changes in licking behaviors, climbing-fiber firing rates and their synchronization during discrimination learning separately for Go/No-go conditions. We found that Purkinje cells in the two components could develop specific motor commands for their respective auditory cues, guided by the predictive reward-prediction errors from their climbing fiber inputs. These results indicate a possible role of context-specific actors in modular reinforcement learning, integrating with cerebellar supervised learning capabilities.

neuroscience↗

bioRxiv2022

Dynamic organization of cerebellar climbing fiber response and synchrony in multiple functional modules reduces dimensions for reinforcement learning

Daynamic functional organization by synchronization is theorized to be essential for dimension reduction of the cerebellar learning space. We analyzed a large amount of coordinate-localized, two-photon imaging data from cerebellar Crus II in mice undergoing "Go/No-go" reinforcement learning. Tensor component analysis revealed that a majority of climbing fiber inputs to Purkinje cells were reduced to only four functional components, corresponding to accurate timing control of motor initiation related to a Go cue, cognitive error-based learning, reward processing, and inhibition of erroneous behaviors after a No-go cue. Spatial distribution of these components coincided well with the boundaries of Aldolase-C/zebrin II expression in Purkinje cells, whereas several components are mixed in single neurons. Synchronization within individual components was bidirectionally regulated according to specific task contexts and learning stages. These findings suggest that the cerebellum, based on anatomical compartments, reduces dimensions by self-organization of components, a feature that may inspire new-generation AI designs.

neuroscience↗

bioRxiv2022

Functional analysis of a novel de novo variant in PPP5C associated with microcephaly, seizures, and developmental delay

We describe a proband evaluated through the Undiagnosed Diseases Network (UDN) who presented with microcephaly, developmental delay, and refractory epilepsy with a de novo p.Ala47Thr missense variant in the protein phosphatase gene, PPP5C. This gene has not previously been associated with a Mendelian disease, and based on the population database, gnomAD, the gene has a low tolerance for loss-of-function variants (pLI=1, o/e=0.07). We functionally evaluated the PPP5C variant in C. elegans by knocking the variant into the orthologous gene, pph-5, at the corresponding residue, Ala48Thr. We employed assays in three different biological processes where pph-5 was known to function through opposing the activity of genes, mec-15 and sep-1. We demonstrated that, in contrast to control animals, the pph-5 Ala48Thr variant suppresses the neurite growth phenotype and the GABA signaling defects of mec-15 mutants, and the embryonic lethality of sep-1 mutants. The Ala48Thr variant did not display dominance and behaved similarly to the reference pph-5 null, indicating that the variant is likely a strong hypomorph or complete loss-of-function. We conclude that pph-5 Ala48Thr is damaging in C. elegans. By extension in the proband, PPP5C p.Ala47Thr is likely damaging, the de novo dominant presentation is consistent with haplo-insufficiency, and the PPP5C variant is likely responsible for one or more of the probands phenotypes.

genetics↗

bioRxiv2020

WHOLE-GENOME SEQUENCING AND DE NOVO ASSEMBLY OF A 2019 NOVEL CORONAVIRUS (SARS-COV-2) STRAIN ISOLATED IN VIETNAM

The pandemic COVID-19 caused by the zoonotic virus SARS-CoV-2 has devastated countries worldwide, infecting more than 4.5 million people and leading to more than 300,000 deaths. Whole genome sequencing (WGS) is an effective tool to monitor emerging strains and provide information for intervention, thus help to inform outbreak control decisions. Here, we reported the first effort to sequence and de novo assemble the whole genome of SARS-CoV-2 using PacBios SMRT sequencing technology in Vietnam. We also presented the annotation results and a brief analysis of the variants found in our SARS-CoV-2 strain, which was isolated from a Vietnamese patient. The sequencing was successfully completed and de novo assembled in less than 30 hours, resulting in one contig with no gap and a length of 29,766 bp. All detected variants as compared to the NCBI reference were highly accurate as confirmed by Sanger sequencing. The results have shown the potential of long read sequencing to provide high quality WGS data to support public health responses, and advance understanding of this and future pandemics.

genomics↗

bioRxiv2019

A translational kidney organoid system bolsters human relevance of clinical development candidate

A major challenge in drug discovery is gaining confidence in the human relevance of pre-clinical animal studies. While human iPSC-derived organoids offer exciting opportunities to address this, concerns about applicability and scalability remain. Here, we report a high-throughput organoid platform for assessment of kidney disease targeting compounds in a human system. We confirmed platform reproducibility by single cell RNA-Seq (scRNA-Seq) and derived a NanoString panel for efficient quality control (QC). Organoid transplantation in rats for 2 to 4 weeks promoted organoid maturation and vascularization. In functional studies, cyclosporine A (CsA) and GFB-887, a novel TRPC5 channel blocker, protected kidney organoids from injury. Pharmacodynamic studies with GFB-887 delivered orally to rats were also successfully performed in human transplanted organoids. These data show how human organoids can deliver confidence in taking development candidate compounds to the clinic, fulfilling their promise to revolutionize drug discovery.

genomics↗

bioRxiv2019

Precise hyperacuity estimation of spike timing from calcium imaging

Two-photon imaging is a major recording technique in neuroscience, but it suffers from several limitations, including a low sampling rate, the nonlinearity of calcium responses, the slow dynamics of calcium dyes and a low signal-to-noise ratio, all of which impose a severe limitation on the application of two-photon imaging in elucidating neuronal dynamics with high temporal resolution. Here, we developed a hyperacuity algorithm (HA_time) based on an approach combining a generative model and machine learning to improve spike detection and the precision of spike time inference. First, Bayesian inference estimates the calcium spike model by assuming the constancy of the spike shape and size. A support vector machine employs this information and detects spikes with higher temporal precision than the sampling rate. Compared with conventional thresholding, HA_time improved the precision of spike time estimation up to 20-fold for simulated calcium data. Furthermore, the benchmark analysis of experimental data from different brain regions and simulation of a broader range of experimental conditions showed that our algorithm was among the best in a class of hyperacuity algorithms. We encourage experimenters to use the proposed algorithm to precisely estimate hyperacuity spike times from two-photon imaging.

neuroscience↗

bioRxiv2019

Physics-based predictive simulations to explore the differential effects of motor control and musculoskeletal deficits on gait dysfunction in cerebral palsy: a retrospective case study

Model-based simulations of walking have the theoretical potential to support clinical decision making by predicting the functional outcome of treatments in terms of walking performance. Yet before using such simulations in clinical practice, their ability to identify the main treatment targets in specific patients needs to be demonstrated. In this study, we generated predictive simulations of walking with a medical imaging based neuro-musculoskeletal model of a child with cerebral palsy presenting crouch gait. We explored the influence of altered muscle-tendon properties, reduced neuromuscular control complexity, and spasticity on gait function in terms of joint kinematics, kinetics, muscle activity, and metabolic cost of transport. We modeled altered muscle-tendon properties by personalizing Hill-type muscle-tendon parameters based on data collected during functional movements, simpler neuromuscular control by reducing the number of independent muscle synergies, and spasticity through delayed muscle activity feedback from muscle force and force rate. Our simulations revealed that, in the presence of aberrant musculoskeletal geometries, altered muscle-tendon properties rather than reduced neuromuscular control complexity and spasticity were the primary cause of the crouch gait pattern observed for this child, which is in agreement with the clinical examination. These results suggest that muscle-tendon properties should be the primary target of interventions aiming to restore a more upright gait pattern for this child. This suggestion is in line with the gait analysis following muscle-tendon property and bone deformity corrections. The ability of our simulations to distinguish the contribution of different impairments on walking performance opens the door for identifying targeted treatment strategies with the aim of designing optimized interventions for neuro-musculoskeletal disorders.

bioengineering↗

bioRxiv2019

Electrical coupling controls dimensionality and chaotic firing of inferior olive neurons

One of the main challenges facing online neural learning systems with numerous modifiable parameters (or "degrees-of-freedom") such as the cerebellum, is how to avoid "overfitting". We previously proposed that the cerebellum controls the degree-of-freedoms during learning by gradually modulating the electric coupling strength between inferior olive neurons. Here, we develop a modeling technique to estimate effective coupling strengths between inferior olive neurons from in vivo recordings of Purkinje cell complex spike activity in three different coupling conditions. We show that high coupling strengths induce synchronous firing and decrease the dimensionality of inferior olive firing dynamics. In contrast, intermediate coupling strengths induce chaotic firing and increase the dimensionality of firing dynamics. Our results thus support the hypothesis that effective coupling controls the dimensionality of inferior olive firing, which may allow the olivocerebellar system to learn effectively from a small training sample set despite the low firing frequency of inferior olive neurons.

neuroscience↗