Biology subjects

Son, J.

Publications and source records attributed to Son, J..

24 records · Page 2Linked to original sources

bioRxiv2019

AFF3 and BACH2 are master regulators of metabolic inflexibility, β/α-cell transition, and dedifferentiation in type 2 diabetes

Type 2 Diabetes is associated with defective insulin secretion, reduced {beta}-cell mass, and increased glucagon production. Cell lineage-tracing in rodents and human autopsy surveys support the notion of {beta}-cell dedifferentiation as a unifying mechanism for these abnormalities. Yet, mechanistic determinants of human {beta}-cell failure remain elusive. Using regulatory-network-based single-cell analysis of human islets, we identify aberrant, diabetes-enriched transitional states characterized by metabolic inflexibility, /{beta}-transition, and endocrine progenitor/stem cell features. A coordinated transcription factor hierarchy mediating cell state transition emerged and was validated using barcoded guide-based, single-cell gene transfer and calcium flux measures in primary human islet cells. Specifically, two master regulators and associated epigenetic drivers emerged, one (AFF3) controlling {beta}- to -like-cell reprogramming, the other (BACH2) transition to a dedifferentiated endocrine progenitor-like cell. The findings provide mechanistic insight into diabetic islet cell dysfunction and suggest actionable pathways for pharmacological intervention.

physiology↗

bioRxiv2019

Inhibition of RNA Polymerase I Transcription Activates Targeted DNA Damage Response and Enhances the Efficacy of PARP Inhibitors in High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) accounts for the majority of ovarian cancer and has a dismal prognosis. PARP inhibitors (PARPi) have revolutionized disease management of patients with homologous recombination (HR) DNA repair-deficient HGSOC. However, acquired resistance to PARPi by complex mechanisms including HR restoration and stabilisation of replication forks is a major challenge in the clinic. Here, we demonstrate CX-5461, an inhibitor of RNA polymerase I transcription of ribosomal RNA genes (rDNA), induces replication stress at rDNA leading to activation of DNA damage response and DNA damage involving MRE11-dependent degradation of replication forks. CX-5461 cooperates with PARPi in exacerbating DNA damage and enhances synthetic lethal interactions of PARPi with HR deficiency in HGSOC-patient-derived xenograft (PDX) in vivo. We demonstrate CX-5461 has a different sensitivity spectrum to PARPi and destabilises replication forks irrespective of HR pathway status, overcoming two well-known mechanisms of resistance to PARPi. Importantly, CX-5461 exhibits single agent efficacy in PARPi-resistant HGSOC-PDX. Further, we identify CX-5461-sensitivity gene expression signatures in primary and relapsed HGSOC. Therefore, CX-5461 is a promising therapy alone and in combination therapy with PARPi in HR-deficient HGSOC. CX-5461 is also an exciting treatment option for patients with relapsed HGSOC tumors that have poor clinical outcome.

cancer biology↗

bioRxiv2019

Thermal sensors improve wrist-worn position tracking

Wearable devices provide a means of tracking hand position in relation to the head, but have mostly relied on wrist-worn inertial measurement unit sensors and proximity sensors, which are inadequate for identifying specific locations. This limits their utility for accurate and precise monitoring of behaviors or providing feedback to guide behaviors. A potential clinical application is monitoring body-focused repetitive behaviors (BFRBs), recurrent, injurious behaviors directed toward the body, such as nail biting and hair pulling, that are often misdiagnosed and undertreated. Here, we demonstrate that including thermal sensors achieves higher accuracy in position tracking when compared against inertial measurement unit and proximity sensor data alone. Our Tingle device distinguished between behaviors from six locations on the head across 39 adult participants, with high AUROC values (best was back of the head: median (1.0), median absolute deviation (0.0); worst was on the cheek: median (0.93), median absolute deviation (0.09)). This study presents preliminary evidence of the advantage of including thermal sensors for position tracking and the Tingle wearable devices potential use in a wide variety of settings, including BFRB diagnosis and management.

bioinformatics↗

bioRxiv2018

Evaluating fMRI-Based Estimation of Eye Movement during Naturalistic Viewing

The collection of eye gaze information during functional magnetic resonance imaging (fMRI) is important for monitoring variations in attention and task compliance, particularly for naturalistic viewing paradigms (e.g., movies). However, the complexity and setup requirements of current in-scanner eye-tracking solutions can preclude many researchers from accessing such information. Predictive eye estimation regression (PEER) is a previously developed support vector regression-based method for retrospectively estimating eye gaze from the fMRI signal in the eyes orbit using a 1.5-minute calibration scan. Here, we provide confirmatory validation of the PEER methods ability to infer eye gaze on a TR-by-TR basis during movie viewing, using simultaneously acquired eye tracking data in five individuals (median angular deviation < 2{degrees}). Then, we examine variations in the predictive validity of PEER models across individuals in a subset of data (n=448) from the Child Mind Institute Healthy Brain Network Biobank, identifying head motion as a primary determinant. Finally, we accurately classify which of two movies is being watched based on the predicted eye gaze patterns (area under the curve = .90 {+/-} .02) and map the neural correlates of eye movements derived from PEER. PEER is a freely available and easy-to-use tool for determining eye fixations during naturalistic viewing.

neuroscience↗

bioRxiv2018

Passive Audio Vocal Capture and Measurement in the Evaluation of Selective Mutism

Selective Mutism (SM) is an anxiety disorder often diagnosed in early childhood and characterized by persistent failure to speak in certain social situations but not others. Diagnosing SM and monitoring treatment response can be quite complex, due in part to changing definitions of and scarcity of research about the disorder. Subjective self-reports and parent/teacher interviews can complicate SM diagnosis and therapy, given that similar speech problems of etiologically heterogeneous origin can be attributed to SM. The present perspective discusses the potential for passive audio capture to help overcome psychiatrys current lack of objective and quantifiable assessments in the context of SM. We present evidence from two pilot studies indicating the feasibility of using a digital wearable device to quantify child vocalization features affected by SM. We also highlight limitations in the design and implementation of this preliminary work that can help guide future efforts.

neuroscience↗

bioRxiv2017

Assessment of the impact of shared data on the scientific literature

Data sharing is increasingly recommended as a means of accelerating science by facilitating collaboration, transparency, and reproducibility. While few oppose data sharing philosophically, a range of barriers deter most researchers from implementing it in practice (e.g., workforce and infrastructural demands, sociocultural and privacy concerns, lack of standardization). To justify the significant effort required for sharing data (e.g., organization, curation, distribution), funding agencies, institutions, and investigators need clear evidence of benefit. Here, using the International Neuroimaging Data-sharing Initiative, we present a brain imaging case study that provides direct evidence of the impact of open sharing on data use and resulting publications over a seven-year period (2010-2017). We dispel the myth that scientific findings using shared data cannot be published in high-impact journals and demonstrate rapid growth in the publication of such journal articles, scholarly theses, and conference proceedings. In contrast to commonly used pay to play models, we demonstrate that openly shared data can increase the scale (i.e., sample size) of scientific studies conducted by data contributors, and can recruit scientists from a broader range of disciplines. These findings suggest the transformative power of data sharing for accelerating science and underscore the need for the scientific ecosystem to embrace the challenge of implementing data sharing universally.

bioinformatics↗