DS_TECH783497 – Supplemental material for Full Factorial Microfluidic Designs and Devices for Parallelizing Human Pluripotent Stem Cell Differentiation

<p>Supplemental material, DS_TECH783497 for Full Factorial Microfluidic Designs and Devices for Parallelizing Human Pluripotent Stem Cell Differentiation by Duncan M. Chadly, Andrew M. Oleksijew, Kyle S. Coots, Jose J. Fernandez, Shun Kobayashi, John A. Kessler and Akihiro J. Matsuoka in SLAS Technology</p

Application of supervised machine learning algorithms for the evaluation of utricular function on patients with Meniere’s disease: utilizing subjective visual vertical and ocular-vestibular-evoked myogenic potentials

Research on the otolith organs remains inconclusive. This study seeks to further elucidate utricular function in patients with Meniere’s disease (MD) in three ways: (1) We aimed to disambiguate the role of the Subjective Visual Vertical (SVV) and Ocular Vestibular Evoked Myogenic Potential (o-VEMP) tests regarding which utricular subsystem each is measuring. (2) We sought to characterize the acute and chronic state of MD by identifying differences in the relationship of SVV and o-VEMP results across patients with acute and chronic MD. (3) We attempted to find a machine-learning algorithm that could predict acute versus chronic MD using SVV and o-VEMP. A prospective study with ninety subjects. (1) SVV and o-VEMP tests were found to have a moderate linear relationship in patients with acute MD, suggesting each test measures a different utricular subsystem. (2) Regression analyses statistically differed across the two patient populations, suggesting that SVV results were normalized in chronic MD patients. (3) Logistic regression and Naïve Bayes algorithms were found to predict acute and chronic MD accurately. A better understanding of what diagnostic tests measure will lead to a better classification system for MD and more targeted treatment options in the future.</p

L'Athlète : journal hebdomadaire de tous les sports

03 août 19271927/08/03 (N533)-1927/08/03.Appartient à l’ensemble documentaire : Aquit

Developmental profiling of microRNAs in the human embryonic inner ear

<div><p>Due to the extreme inaccessibility of fetal human inner ear tissue, defining of the microRNAs (miRNAs) that regulate development of the inner ear has relied on animal tissue. In the present study, we performed the first miRNA sequencing of otic precursors in human specimens. Using HTG miRNA Whole Transcriptome assays, we examined miRNA expression in the cochleovestibular ganglion (CVG), neural crest (NC), and otic vesicle (OV) from paraffin embedded (FFPE) human specimens in the Carnegie developmental stages 13–15. We found that in human embryonic tissues, there are different patterns of miRNA expression in the CVG, NC and OV. In particular, members of the miR-183 family (miR-96, miR-182, and miR-183) are differentially expressed in the CVG compared to NC and OV at Carnegie developmental stage 13. We further identified transcription factors that are differentially targeted in the CVG compared to the other tissues from stages 13–15, and we performed gene set enrichment analyses to determine differentially regulated pathways that are relevant to CVG development in humans. These findings not only provide insight into the mechanisms governing the development of the human inner ear, but also identify potential signaling pathways for promoting regeneration of the spiral ganglion and other components of the inner ear.</p></div

REVIGO treemap of relevance similarity analysis on enriched pathways comparing CVG vs. NC (stage 13).

<p>REVIGO treemap summarizing Gene Ontology biological process categories over-represented in CVG cells compared to NC cells at stage 13. All terms are included with a FDR adjusted <i>p</i>-value cutoff at 0.05 from the enrichment analysis. The relevance similarity C-score (uniqueness) cut-off is chosen at 0.7. The size of each rectangle is proportional to the uniqueness for that category. Red circles indicate relevant CVG-development pathways.</p

Transcription factor targeting network plots, CVG vs OV comparison.

<p>Network plots showing differentially targeted transcription factors between CVG and OV tissues. Green nodes represent differentially expressed miRNAs, while orange and purple nodes represent significantly (false discovery adjusted <i>p</i> < 0.10) targeted transcription factors more targeted in either CVG (purple) or OV (orange) tissue. Transcription factor node size is proportional to the number of differentially expressed miRNAs targeting the gene. Only results for stages 13 and 15 are shown, as there are too many significant factors to effectively visualize at stage 14.</p

Laser-microdissection of FFPE-human inner ear slides.

<p>(A) FFPE slides containing embryonic tissues. (B) Coronal section of a fetus with highlighted regions of interest (dashed black circles, CVG, NC, and OV). Further images are provided showing tissue before (C, E) and after (D, F) laser-captured microdissection of CVG (dashed white lines in D) and NC tissues (dashed white line in F). Other developmental regions also are highlighted. CVG: cochlear-vestibular ganglions, OV: otic vesicle, NC: neural crest; GG: geniculate ganglion, G-CVG: geniculate-cochleovestibular ganglions, E: epithelium; and NT: neural tube. Scale bar = 100 μm (B) and 150 μm (C-F).</p

Transcription factor targeting network plots, CVG vs NC comparison.

<p>Network plots showing differentially targeted transcription factors between CVG and NC tissues. Green nodes represent differentially expressed miRNAs, while orange and purple nodes represent significantly (false discovery adjusted <i>p</i> < 0.10) targeted transcription factors more targeted in either CVG (purple) or NC (orange) tissue. Transcription factor node size is proportional to the number of differentially expressed miRNAs targeting the gene.</p

Principal component analysis.

<p>(A) Principle components 1 and 2 are plotted for the 27 collected datasets. Loose clustering by tissue type is indicated with dashed colored circles. (B) As an alternative visualization, triplicate measures for each individual tissue/time point set are averaged and plotted with x- and y-standard error bars.</p

Predicted target genes for the MiR-183 family using TagetScanHuman and a Deafness Variation Database (version 8.0).

<p>Predicted target genes for the MiR-183 family using TagetScanHuman and a Deafness Variation Database (version 8.0).</p