Biology subjects

Lee, D.

Publications and source records attributed to Lee, D..

At least 271 records · Page 15Linked to original sources

bioRxiv2020

Whole Slide Preview Image Segmentation and Setup for Digital Pathology Scanners

The problem of tissue finding is of special interest in automating WSI scanners where it decomposes the preview image of tissue glass slides into a simplified and abstract level of localization and identification to setup WSI scanner for high-resolution scan. Prior to such scanning, a preview image is captured to calibrate the scanners parameters. Scan parameters such as focus depth and scan region are determined using a tissue finding software package. This paper introduces a series of pipelines (e.g. binary mask segmentation, tissue/artifact classification, region-of-interest allocation) to automate tissue preview segmentation in both brightfield and darkfield microscopy.

pathology↗

bioRxiv2020

Multiple timescales of neural dynamics and integration of task-relevant signals across cortex

Recent studies have proposed the orderly progression in the time constants of neural dynamics as an organizational principle of cortical computations. However, relationships between these timescales and their dependence on response properties of individual neurons are unknown. We developed a comprehensive method to simultaneously estimate multiple timescales in neuronal dynamics and integration of task-relevant signals along with selectivity to those signals. We found that most neurons exhibited multiple timescales in their response, which consistently increased from parietal to prefrontal to cingulate cortex. While predicting rates of behavioral adjustments, these timescales were not correlated across individual neurons in any cortical area, resulting in independent parallel hierarchies of timescales. Additionally, none of these timescales depended on selectivity to task-relevant signals. Our results not only suggest multiple canonical mechanisms for increasing timescales of neural dynamics across cortex but also point to additional mechanisms that allow decorrelation of these timescales to enable more flexibility.

neuroscience↗

bioRxiv2020

Reliable data collection in participatory trials to assess digital healthcare apps.

The number of digital healthcare mobile apps on the market is increasing exponentially owing to the development of the mobile network and widespread usage of smartphones. However, only a few of these apps have undergone adequate validation. As with many mobile apps, healthcare apps are generally considered safe to use, making them easy for developers and end-users to exchange them in the marketplace. The existing platforms are not suitable to collect reliable data for evaluating the effectiveness of the apps. Moreover, these platforms only reflect the perspectives of developers and experts, not of end-users. For instance, data collection methods typical of clinical trials are not appropriate for participant-driven assessment of healthcare apps because of their complexity and high cost. Thus, we identified a need for a participant-driven data collection platform for end-users that is interpretable, systematic, and sustainable --as a first step to validate the effectiveness of the apps. To collect reliable data in the participatory trial format, we defined distinct stages for data preparation, storage, and sharing. Interpretable data preparation consists of a protocol database system and semantic feature retrieval method to create a protocol without professional knowledge. Collected data reliability weight calculation belongs to the systematic data storage stage. For sustainable data collection, we integrated the weight method and the future reward distribution function. We validated the methods through statistical tests conducted on 718 human participants. The validation results demonstrate that the methods have significant differences in the comparative experiment and prove that the choice of the right method is essential for reliable data collection. Furthermore, we created a web-based system for our pilot platform to collect reliable data in an integrated pipeline. We validate the platform features with existing clinical and pragmatic trial data collection platforms. In conclusion, we show that the method and platform support reliable data collection, forging a path to effectiveness validation of digital healthcare apps.

bioinformatics↗

bioRxiv2020

Epigenome-based Splicing Prediction using a Recurrent Neural Network

Alternative RNA splicing provides an important means to expand metazoan transcriptome diversity. Contrary to what was accepted previously, splicing is now thought to predominantly take place during transcription. Motivated by emerging data showing the physical proximity of the spliceosome to Pol II, we surveyed the effect of epigenetic context on co-transcriptional splicing. In particular, we observed that splicing factors were not necessarily enriched at exon junctions and that most epigenetic signatures had a distinctly asymmetric profile around known splice sites. Given this, we tried to build an interpretable model that mimics the physical layout of splicing regulation where the chromatin context progressively changes as the Pol II moves along the guide DNA. We used a recurrent-neural-network architecture to predict the inclusion of a spliced exon based on adjacent epigenetic signals, and we showed that distinct spatio-temporal features of these signals were key determinants of model outcome, in addition to the actual nucleotide sequence of the guide DNA strand. After the model had been trained and tested (with >80% precision-recall curve metric), we explored the derived weights of the latent factors, finding they highlight the importance of the asymmetric time-direction of chromatin context during transcription. Author SummaryIn humans, only about 2% of the genome is comprised of so-called coding regions and can give rise to protein products. However, the human transcriptome is much more diverse than the number of genes found in these coding regions. Each gene can give rise to multiple transcripts through a process during transcription called alternative splicing. There is a limited understanding of the regulation of splicing and the underlying splicing code that determines cell-type-specific splicing. Here, we studied epigenetic features that characterize splicing regulation in humans using a recurrent neural network model. Unlike feedforward neural networks, this method contains an internal memory state that learns from spatiotemporal patterns - like the context in language - from a sequence of genomic and epigenetic information, making it better suited for characterizing splicing. We demonstrated that our method improves the prediction of spicing outcomes compared to previous methods. Furthermore, we applied our method to 49 cell types in ENCODE to investigate splicing regulation and found that not only spatial but also temporal epigenomic context can influence splicing regulation during transcription.

genomics↗

bioRxiv2020

Single-cell transcriptome maps of myeloid blood cell lineages in Drosophila

Drosophila lymph gland, the larval hematopoietic organ comprised of prohemocytes and hemocytes, has been a valuable model for understanding mechanisms underlying hematopoiesis and immunity. Three types of mature hemocytes have been characterized in the lymph gland: plasmatocytes, lamellocytes, and crystal cells, which are analogous to vertebrate myeloid cells. Here, we used single-cell RNA sequencing to comprehensively analyze heterogeneity of developing hemocytes in the lymph gland, and discovered novel hemocyte types, stem-like prohemocytes, and intermediate prohemocytes. Additionally, we identified the emergence of the lamellocyte lineage following active cellular immunity caused by wasp infestation. We unraveled similarities and differences between embryonically derived- and larval lymph gland hemocytes. Finally, the comparison of Drosophila lymph gland hemocytes and human immune cells highlights similarities between prohemocytes and hematopoietic stem cell, and between mature hemocytes and myeloid cells across species. Altogether, our study provides detailed insights on the development and evolution of hematopoiesis at single-cell resolution.

developmental biology↗

bioRxiv2020

Viscous medium-based crystal support in sample holder for fixed-target serial femtosecond crystallography

Serial femtosecond crystallography (SFX) enables the determination of a room-temperature crystal structure of macromolecules without causing radiation damage, as well as provides time-resolved molecular dynamics data in pump-probe experiments. Fixed-target SFX (FT-SFX) can minimize sample consumption and physical effects to crystals during sample delivery. Various types of sample holders have been developed and applied in FT-SFX; however, no sample holder has been developed that can universally mount crystals of various sizes and shapes. Here, we introduce a viscous media-based crystal support in a sample holder for FT-SFX. Crystal samples were embedded in viscous media such as gelatin and agarose, which were enclosed in a polyimide film. In the vertically placed sample holder, the viscous medium stably supported crystals between the two polyimide films without crystal sinking due to gravity. Using this method, we performed FT-SFX experiments with glucose isomerase and lysozyme embedded in gelatin and agarose, respectively. The room-temperature crystal structures of glucose isomerase and lysozyme were successfully determined at 1.75 and 1.80 [A] resolutions, respectively. Viscous media used in this experiment showed negligible background scattering in data processing. This method is useful for delivering crystal samples of various sizes and shapes in FT-SFX experiments.

biophysics↗

bioRxiv2019

Confluence of timing and reward biases in perceptual decision-making dynamics

Although the decisions of our daily lives often occur in the context of temporal and reward structures, the impact of such regularities on decision-making strategy is poorly understood. Here, to explore how temporal and reward context modulate strategy, we trained rhesus monkeys to perform a novel perceptual decision-making task with asymmetric rewards and time-varying evidence reliability. To model the choice and response time patterns, we developed a computational framework for fitting generalized drift-diffusion models (GDDMs) which flexibly accommodates diverse evidence accumulation strategies. We found that a dynamic urgency signal and leaky integration, in combination with two independent forms of reward biases, best capture behavior. We also tested how temporal structure influences urgency by systematically manipulating the temporal structure of sensory evidence, and found that the time course of urgency was affected by temporal context. Overall, our approach identified key components of cognitive mechanisms for incorporating temporal and reward structure into decisions.

neuroscience↗

bioRxiv2019

TopicNet: a framework for measuring transcriptional regulatory network change

Next generation sequencing data highlights comprehensive and dynamic changes in the human gene regulatory network. Moreover, changes in regulatory network connectivity (network "rewiring") manifest different regulatory programs in multiple cellular states. However, due to the dense and noisy nature of the connectivity in regulatory networks, directly comparing the gains and losses of targets of key TFs is not that informative. Thus, here, we seek a abstracted lower-dimensional representation to understand the main features of network change. In particular, we propose a method called TopicNet that applies latent Dirichlet allocation (LDA) to extract meaningful functional topics for a collection of genes regulated by a TF. We then define a rewiring score to quantify the large-scale changes in the regulatory network in terms of topic change for a TF. Using this framework, we can pinpoint particular TFs that change greatly in network connectivity between different cellular states. This is particularly relevant in oncogenesis. Also, incorporating gene-expression data, we define a topic activity score that gives the degree that a topic is active in a particular cellular state. Furthermore, we show how activity differences can highlight differential survival in certain cancers.

bioinformatics↗

bioRxiv2019

Neurocognitive mechanisms of social inferences in typical and autistic adolescents

BackgroundMany of our efforts in social interactions are dedicated to learning about others. Adolescents with autism have core deficits in social learning, but a mechanistic understanding of these deficits and how they relate to neural development is lacking. The current study aimed to specify how adolescents with and with autism represent and acquire social knowledge and how these processes are implemented in neural activity. MethodsTypically developing (TD) adolescents (N=26) and adolescents with autism (N=20) rated in the MR scanner how much three peers liked a variety of items and received trial-by-trial feedback about the peers actual preference ratings. In a separate study, we established the preferences of a new sample of adolescents (N=99), used to examine population preference structures. Using computational models, we tested whether participants in the MR study relied on preference structures during learning and how model predictions were implemented in brain activity. ResultsTD adolescents relied on average population preferences and prediction error (PE) updating. Importantly, PE updating was scaled by the similarity between items. In contrast, preferences of adolescents with autism were best described by a No-learning model that relied only on participants own preferences for each item. Model predictions were encoded in neural activity. TD adolescents encoded PEs in the putamen and adolescents with autism showed greater encoding of own preferences in the angular gyrus. ConclusionsWe specified how adolescents represent and update social knowledge during learning. Our findings indicate that adolescents with ASD rely only on their own preferences when making social inferences.

neuroscience↗

bioRxiv2019

Robotic light touch assists human balance control during maximum forward reaching

ObjectiveWe investigated how light interpersonal touch (IPT) provided by a robotic system supports human individuals performing a challenging balance task compared to IPT provided by a human partner. BackgroundIPT augments the control of body balance in contact receivers without a provision of mechanical body weight support. The nature of the processes governing the social haptic interaction, whether they are predominantly reactive or predictive, is uncertain. MethodTen healthy adult individuals performed maximum forward reaching (MFR) without visual feedback while standing upright. We evaluated their control of reaching behaviour and of body balance during IPT provided by either another human individual or by a robotic system in two alternative control modes (reactive vs predictive). ResultsChanges in reaching behaviour under the robotic IPT, such as lower speed and straighter direction were linked to reduced body sway. MFR of the contact receiver was influenced by the robotic control mode such as that a predictive mode reduced movement variability and increased postural stability to a greater extend in comparison to human IPT. The effects of the reactive robotic system, however, more closely resembled the effects of IPT provided by human contact provider. ConclusionThe robotic IPT system was as supportive as human IPT. Robotic IPT seemed to afford more specific adjustments, such as trading reduced speed for increased accuracy, to meet the intrinsic demands and constraints of the robotic system. Possibly, IPT provided by a human contact provider reflected reactive interpersonal postural coordination more similar to the robotic systems follower mode. PrecisInterpersonal touch support by a robotic system was evaluated against support provided a human partner during maximum forward reaching. Human contact receivers showed comparable benefits in their reaching postural performance between the support conditions. Coordination with the robotic system, nevertheless, afforded specific adaptations in the reaching behaviour.

neuroscience↗

bioRxiv2019

Trading Mental Effort for Confidence: The Metacognitive Control of Value-Based Decision-Making

Why do we sometimes opt for actions or items that we do not value the most? Under current neurocomputational theories, such preference reversals are typically interpreted in terms of errors that arise from the unreliable signaling of value to brain decision systems. But, an alternative explanation is that people may change their mind because they are reassessing the value of alternative options while pondering the decision. So, why do we carefully ponder some decisions, but not others? In this work, we derive a computational model of the metacognitive control of decisions or MCD. In brief, we assume that fast and automatic processes first provide initial (and largely uncertain) representations of options values, yielding prior estimates of decision difficulty. These uncertain value representations are then refined by deploying cognitive (e.g., attentional, mnesic) resources, the allocation of which is controlled by an effort-confidence tradeoff. Importantly, the anticipated benefit of allocating resources varies in a decision-by-decision manner according to the prior estimate of decision difficulty. The ensuing MCD model predicts response time, subjective feeling of effort, choice confidence, changes of mind, and choice-induced preference change and certainty gain. We test these predictions in a systematic manner, using a dedicated behavioral paradigm. Our results provide a quantitative link between mental effort, choice confidence, and preference reversals, which could inform interpretations of related neuroimaging findings.

neuroscience↗

bioRxiv2019

Representations of the amacrine cell population underlying retinal motion anticipation

Retinal amacrine cells are a diverse population of inhibitory interneurons, posing a challenge to understand the specific roles of those interneurons in computations of the similarly diverse ganglion cell population. Here we study the predictive computation of motion anticipation, which is thought to compensate for processing delays when encoding moving objects. We recorded the membrane potential of the salamander amacrine cell population optically while recording electrically from ganglion cells with a multielectrode array. We find unexpectedly that ganglion cells with the greatest anticipation for moving stimuli exhibit a new type of predictive motion anticipation that is inconsistent with prior models of delayed inhibition. Based on the spatiotemporal correlations between thousands of amacrine and ganglion cell pairs, we modeled the contribution of the traveling wave of activity for different amacrine cell populations to the encoding of a moving bar. These models indicate that the population responses of slow biphasic amacrine cells create the greatest contribution to both types of ganglion cell motion anticipation, supporting a role for this specific amacrine cell class in the predictive encoding of moving stimuli. Significance StatementThe prediction of moving stimuli is a widespread function occurring in both visual and auditory systems. The diversity of interneuron populations makes it a challenge to understand the mechanisms of these computations. To analyze how the retina anticipates motion, we optically measured inhibitory amacrine cell population activity simultaneously with electrical recording from ganglion cell populations. We then used computational modelling to assess which amacrine cell types have the right spatiotemporal responses to generate motion anticipation. In contrast to previous suggestions of a general role for inhibition, we find that slow biphasic amacrine cells specifically have the greatest contribution to motion anticipation, thus highlighting the need to directly measure and model the effects of interneuron populations in complex sensory computations.

neuroscience↗

bioRxiv2019

Analysis of putative cis-regulatory elements regulating blood pressure variation

Hundreds of loci have been associated with blood pressure traits from many genome-wide association studies. We identified an enrichment of these loci in aorta and tibial artery expression quantitative trait loci in our previous work in [~]100,000 Genetic Epidemiology Research on Aging (GERA) study participants. In the present study, we subsequently focused on determining putative regulatory regions for these and other tissues of relevance to blood pressure, to both fine-map these loci by pinpointing genes and variants of functional interest within them, and to identify any novel genes.\n\nWe constructed maps of putative cis-regulatory elements using publicly available open chromatin data for the heart, aorta and tibial arteries, and multiple kidney cell types. Sequence variants within these regions may be evaluated quantitatively for their tissue- or cell-type-specific regulatory impact using deltaSVM functional scores, as described in our previous work. In order to identify genes of interest, we aggregate these variants in these putative cis-regulatory elements within 50Kb of the start or end of genes considered as \"expressed\" in these tissues or cell types using publicly available gene expression data, and use the deltaSVM scores as weights in the well-known group-wise sequence kernel association test (SKAT). We test for association with both blood pressure traits as well as expression within these tissues or cell types of interest, and identify several genes, including MTHFR, C10orf32, CSK, NOV, ULK4, SDCCAG8, SCAMP5, RPP25, HDGFRP3, VPS37B, and PPCDC. Although our study centers on blood pressure traits, we additionally examined two known genes, SCN5A and NOS1AP involved in the cardiac trait QT interval, in the Atherosclerosis Risk in Communities Study (ARIC), as a positive control, and observed an expected heart-specific effect. Thus, our method may be used to identify variants and genes for further functional testing using tissue- or cell-type-specific putative regulatory information.\n\nAuthor SummarySequence change in genes (\"variants\") are linked to the presence and severity of different traits or diseases. However, as genes may be expressed in different tissues and at different times and degrees, using this information is expected to more accurately identify genes of interest. Variants within the genes are essential, but also in the sequences (\"regulatory elements\") that control the genes expression in different tissues or cell types. In this study, we aim to use this information about expression and variants potentially involved in gene expression regulation to better pinpoint genes and variants in regulatory elements of interest for blood pressure regulation. We do so by taking advantage of such data that are publicly available, and use methods to combine information about variants in aggregate within a genes putative regulatory elements in tissues thought to be relevant for blood pressure, and identify several genes, meant to enable experimental follow-up.

genomics↗

bioRxiv2019

An interactive retrieval system for clinical trial studies with context-dependent protocol elements

A clinical trial protocol defines the procedures that should be performed during a clinical trial. Every clinical trial begins with the design of its protocol. While designing the protocol, most researchers refer to electronic databases and extract protocol elements using a keyword search. However, state-of-the-art retrieval systems only offer text-based searches for user-entered keywords. In this study, we present an interactive retrieval system with a context-dependent and protocol-element-selection function for successfully designing a clinical trial protocol. To do this, we first introduce a database for a protocol retrieval system constructed from individual protocol data extracted from 184,634 clinical trials and 13,210 frame structures of clinical trial protocols. The database contains various semantic information that enables the protocols to be filtered during the search operation. Based on the database, we developed a web application called the clinical trial protocol database system (CLIPS; available at https://corus.kaist.edu/clips), which enables an interactive search by utilizing protocol elements. CLIPS provides the options to select the next element according to the previous element in the form of a connected tree, thus enabling an interactive search for combinations of protocol elements. The validation results show that our method achieves better performance than existing databases in predicting phenotypic features.

bioinformatics↗

bioRxiv2019

Integrative genomic, transcriptomic, and epigenomic analyses of benign prostatic hyperplasia reveal new options for therapy

Benign prostatic hyperplasia (BPH), a nonmalignant enlargement of the prostate, is one of the most common diseases affecting aging men, but the underlying molecular features of BPH remain poorly understood, and therapeutic options are limited. Here we employed a comprehensive molecular investigation of BPH, including genomic, transcriptomic and epigenetic profiling of 18 BPH cases. At the molecular level, we found no evidence of neoplastic features in BPH: no evidence of driver genomic alterations, including low coding mutation rates, mutational signatures consistent with aging tissues, minimal copy number alterations, and no genomic rearrangements. Similarly at the epigenetic level, we found global hypermethylation was the dominant process (unlike most neoplastic processes). By integrating transcriptional and methylation signatures, we identified two BPH subgroups with distinct clinical features and associated signaling pathways, which were validated in two independent cohorts. Finally, our analyses nominated mTOR inhibitors as a potential subtype-specific therapeutic option. Supporting this, a cohort of men exposed to mTOR inhibitors showed a significant decrease in prostate size. Our results demonstrate that BPH consists of distinct molecular subgroups, with potential for subtype-specific precision therapy via mTOR inhibition.

genomics↗

bioRxiv2019

Compositional and functional differences of the mucosal microbiota along the intestine of healthy individuals

Gut mucosal microbes evolved closest to the host, developing specialized local communities. There is, however, insufficient knowledge of these communities as most studies have employed sequencing technologies to investigate faecal microbiota. This work used shotgun metagenomics of mucosal biopsies to explore the microbial communities compositions of terminal ileum and large intestine in 5 healthy individuals. Functional annotations and genome-scale metabolic modelling of selected species were then employed to identify local functional enrichments. While faecal metagenomics provided a good approximation of the average gut microbiome composition, mucosal biopsies allowed detecting the subtle variations of local microbial communities. Given their significant enrichment in the mucosal microbiota, we highlight the roles of Bacteroides species and describe the antimicrobial resistance biogeography along the intestine. We also detail which species, at which locations, are involved with the tryptophan/indole pathway, whose malfunctioning has been linked to pathologies including inflammatory bowel disease. Our study thus provides invaluable resources for investigating mechanisms connecting gut microbiota and host pathophysiology.

systems biology↗

bioRxiv2019

Highly efficient site-directed gene insertion in primary human natural killer cells using homologous recombination and CRISPaint delivered by AAV

Human peripheral blood natural killer (NK) cells have strong antitumor activity and have been used successfully in several clinical trials. Modifying NK cells with a chimeric antigen receptor (CAR) can improve their targeting and increase specificity. However, genetic modification of NK cells has been challenging due to the high expression of innate sensing mechanisms for viral nucleic acids. Recently, we described an efficient vector-free method using Cas9/ribonucleoprotein complexes for gene deletion in NK cells. Here, we combined this approach with single-stranded (ss) or self-complementary (sc) Adeno-associated virus (AAV)-mediated gene delivery for gene insertion into a user-defined locus using homology repair (HR) and non-homologous directed CRISPR-assisted insertion tagging (CRISPaint) approaches. Using these approaches, we identified scAAV6 as the superior serotype for successful generation of stable mCherry-expressing primary NK cells (up to 89%). To maximize transgene packaging in HR-directed gene insertion, we identified minimum optimal homology arm lengths of 300bp for the flanking region of the Cas9-targeting site. Lastly, we demonstrate that mCherry positive NK cells can be expanded to large numbers using feeder cells expressing membrane-bound IL-21. This efficient method for site-directed insertion of genetic material into NK cells has broad potential for basic discovery and therapeutic applications for primary NK cells.

immunology↗

bioRxiv2019

Simulating bipedal walking using a translating center of pressure

During walking, foot orientation and foot placement allow humans to stabilize their gait and to move forward. Consequently the upper body adapts to the ground reaction force (GRF) transmitted through the feet. The foot-ground contact is often modeled as a fixed pivot in bipedal models for analysis of locomotion. The fixed pivot models, however, cannot capture the effect of shift in the pivot point from heel to toe. In this study, we propose a novel bipedal model, called SLIPCOP, which employs a translating center of pressure (COP) in a spring loaded inverted pendulum (SLIP) model. The translating COP has two modes: one with a constant speed of translation and the other as the weighted function of the GRF in the fore aft direction. We use the relation between walking speed and touchdown (TD) angle as well as walking speed and COP speed, from existing literature, to restrict steady state solutions within the human walking domain. We find that with these relations, SLIPCOP provides steady state solutions for very slow to very fast walking speeds unlike SLIP. SLIPCOP for normal to very fast walking speed shows good accuracy in estimating COM amplitude and swing stance ratio. SLIPCOP is able to estimate the distance traveled by the COP during stance with high precision.

physiology↗