Biology subjects

Park, C.

Publications and source records attributed to Park, C..

5 recordsLinked to original sources

bioRxiv2018

Real-time non-invasive intracranial state estimation using unscented Kalman filter

Intracranial pressure (ICP) monitoring is desirable as a first-line measure to assist decision-making in cases of increased ICP. Clinically, non-invasive ICP monitoring is also required to avoid infection and hemorrhage in patients. The relationships among the arterial blood pressure (Pa), ICP, cerebral blood flow, and its velocity (QCBFv) measured by transcranial Doppler ultrasound measurement have been reported. However, real-time non-invasive ICP estimation using these modalities is less well documented. Here, we present a novel algorithm for real-time and non-invasive ICP monitoring with QCBFv and Pa, called direct-current (DC)-ICP. This technique is compared with invasive ICP for 11 traumatic-brain-injury patients admitted to Cheju Halla Hospital and Gangnam Severance Hospital from July 2017 to June 2018. The inter-subject correlation coefficient between true and estimate was 0.70. The AUCs of the ROCs for prediction of increased ICP for the DC-ICP methods are 0.816. Thus, QCBFv monitoring can facilitate reliable real-time ICP tracking with our novel DC-ICP algorithm, which can provide valuable information under clinical conditions.

neuroscience↗

bioRxiv2018

Three-dimensional refractive index distributions of individual angiosperm pollen grains

Three-dimensional (3D) refractive index (RI) imaging and quantitative analyses of angiosperm pollen grains are presented. Using optical diffraction tomography, the 3D RI structures of individual angiosperm pollen grains were measured without using labeling or other preparation techniques. Various physical quantities, including volume, surface area, exine volume, and sphericity, were determined from the measured RI tomograms of pollen grains. Exine skeletons, the distinct internal structures of angiosperm pollen grains, were identified and systematically analyzed.

plant biology↗

bioRxiv2018

Whole-genome deep learning analysis reveals causal role of noncoding mutations in autism

We address the challenge of detecting the contribution of noncoding mutations to disease with a deep-learning-based framework that predicts specific regulatory effects and deleterious disease impact of genetic variants. Applying this framework to 1,790 Autism Spectrum Disorder (ASD) simplex families reveals autism disease causality of noncoding mutations by demonstrating that ASD probands harbor transcriptional (TRDs) and post-transcriptional (RRDs) regulation-disrupting mutations of significantly higher functional impact than unaffected siblings. Importantly, we detect this significant noncoding contribution at each level, transcriptional and post-transcriptional, independently and after multiple hypothesis correction. Further analysis suggests involvement of noncoding mutations in synaptic transmission and neuronal development, and reveals a convergent genetic landscape of coding and noncoding (TRD and RRD) de novo mutations in ASD. We demonstrate that sequences carrying prioritized proband de novo mutations possess transcriptional regulatory activity and drive expression differentially, and highlight a link between noncoding mutations and IQ heterogeneity in ASD probands. Our predictive genomics framework illuminates the role of noncoding mutations in ASD, prioritizes high impact transcriptional and post-transcriptional regulatory mutations for further study, and is broadly applicable to complex human diseases.

genomics↗

bioRxiv2017

Population genomic analysis reveals contrasting demographic changes of two closely related dolphin species in the last glacial

Population genomic data can be used to infer historical effective population sizes (Ne), which help study the impact of past climate changes on biodiversity. Previous genome sequencing of one individual of the common bottlenose dolphin Tursiops truncatus revealed an unusual, sharp rise in Ne during the last glacial, raising questions about the reliability, generality, underlying cause, and biological implication of this finding. Here we first verify this result by additional sampling of T. truncatus. We then sequence and analyze the genomes of its close relative, the Indo-Pacific bottlenose dolphin T. aduncus. The two species exhibit contrasting demographic changes in the last glacial, likely through actual changes in population size and/or alterations in the level of gene flow among populations. Our findings demonstrate that even closely related species can have drastically different responses to climatic changes, making predicting the fate of individual species in the ongoing global warming a serious challenge.

evolutionary biology↗

bioRxiv2016

Intra- and inter-specific variations of gene expression levels in yeast are largely neutral

It is commonly, although not universally, accepted that most intra- and inter-specific genome sequence variations are more or less neutral, whereas a large fraction of organism-level phenotypic variations are adaptive. Gene expression levels are molecular phenotypes that bridge the gap between genotypes and corresponding organism-level phenotypes. Yet, it is unknown whether natural variations in gene expression levels are mostly neutral or adaptive. Here we address this fundamental question by genome-wide profiling and comparison of gene expression levels in nine yeast strains belonging to three closely related Saccharomyces species and originating from five different ecological environments. We find that the transcriptome-based clustering of the nine strains approximates the genome sequence-based phylogeny irrespective of their ecological environments. Remarkably, only [~]0.5% of genes exhibit similar expression levels among strains from a common ecological environment, no greater than that among strains with comparable phylogenetic relationships but different environments. These and other observations strongly suggest that most intra- and inter-specific variations in yeast gene expression levels result from the accumulation of random mutations rather than environmental adaptations. This finding has profound implications for understanding the driving force of gene expression evolution, genetic basis of phenotypic adaptation, and general role of stochasticity in evolution.

evolutionary biology↗