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Record W2980175834 · doi:10.1101/803478

High resolution, serial imaging of early mouse and human liver bud morphogenesis in three dimensions

2019· preprint· en· W2980175834 on OpenAlexaboutno aff
Ogechi Ogoke, Daniel Guiggey, Tala Mon, Claire Shamul, Shatoni Ross, Saroja Rao, Natesh Parashurama

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldMedicine
TopicLiver physiology and pathology
Canadian institutionsnot available
Fundersnot available
KeywordsOrganogenesisBiologyMorphogenesisMesenchymeCell biologyHuman liverEmbryoPathologyAnatomyGeneticsMedicineGene

Abstract

fetched live from OpenAlex

ABSTRACT Background Liver organogenesis has thus far served as a paradigm for solid organ formation. The developing liver bud is a well established model of organogenesis, and murine genetic studies demonstrate key molecules involved in key morphogenetic changes. However, the analysis of the liver bud is typically limited to 2D tissue sections, which precludes extensive visualization, quantitation, and analysis. Further, the lack of human liver bud data has further hindered our understanding of human liver organogenesis. Therefore, new analytical and visualization approaches are needed to elicit further morphogenetic details of liver organogenesis and to elucidate differences between mouse and human liver bud growth. Results To address this need, we focused on high resolution imaging, visualization, and analysis of early liver growth by using available online databases for both mouse (EMAP, Toronto Phenogenomics center) and human (3D Atlas of Human Embryology), noninvasive multimodality imaging studies of the murine embryo, and mouse/human liver weight data. First, we performed three-dimensional (3D reconstructions) of stacked, digital tissue sections that had been initially segmented for the liver epithelium and the septum transversum mesenchyme (STM). 3D reconstruction of both mouse and human data sets enabled visualization and analysis of the dynamics of liver bud morphogenesis, including hepatic cord formation and remodeling, mechanisms of growth, and liver-epithelial STM interactions. These studies demonstrated potentially under-appreciated mechanisms of growth, including rapid exponential growth that is matched at the earliest stages by STM growth, and unique differences between mouse and human liver bud growth. To gain further insight into the exponential liver bud growth that was observed, we plotted volumetric data from 3D reconstruction together with fetal liver growth data from multimodality (optical projection tomography, magnetic resonance imaging, micro-CT) and liver weight data to compose complete growth curves during mouse (E8.5-E18) and human (day 25-300) liver development. For further analysis, we performed curve fitting and parameter estimation, using Gompertzian models, which enables the comparison between mouse and human liver bud growth, as well as comparisons to processes like liver regeneration. To demonstrate the importance of mesenchyme in rapid liver bud growth and morphogenesis in the human liver bud, we performed functional analysis in which human pluripotent stem cell (hPSC)-derived hepatic organoids were used to model collective migration that occurs in vivo, demonstrating that migration is strongly dependent upon mesenchyme. Discussion Our data demonstrates improved visualization with 3D images, under-appreciated and potentially new mechanisms of growth, complete liver growth curves with quantitative analysis through embryonic and fetal stages, and a new functional human stem cell-derived liver organoid assay demonstrating mesenchyme-driven collective migration. These data enhance our understanding of liver organogenesis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.592
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.226
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2019
Admission routes1
Has abstractyes

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