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Record W4393357592 · doi:10.1101/2024.03.28.585666

Biomechanical regulation of cell shapes promotes branching morphogenesis of the ureteric bud epithelium

2024· preprint· en· W4393357592 on OpenAlexaff
Kristen Kurtzeborn, Vladislav Iaroshenko, Tomáš Zárybnický, Julia Koivula, Heidi Anttonen, Darren Brigdewater, Ramaswamy Krishnan, Ping Chen, Satu Kuure

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsMcMaster University
FundersHelsinki Institute of Life Science, Helsingin YliopistoBiocenter FinlandHelsingin Yliopisto
KeywordsUreteric budMorphogenesisEpitheliumBranching (polymer chemistry)Cell biologyBiologyAnatomyKidney developmentChemistryGeneGenetics

Abstract

fetched live from OpenAlex

Abstract Background Branching morphogenesis orchestrates organogenesis in many tissues including kidney, where ureteric bud branching determines kidney size and nephron number. Defects in branching morphogenesis result in congenital renal anomalies which manifest as deviations in size, function, and nephron number thus critically compromising the lifelong renal functional capacity established during development. Advances in the genetic and molecular understanding of ureteric bud branching regulation have proved insufficient to improve prognosis of congenital renal defects. Thus, we addressed mechanisms regulating three-dimensional (3D) ureteric bud epithelial cell morphology and cell shape changes during novel branch initiation to uncover the contributions of cellular mechanics on cellular functions and tissue organization in normal and branching-compromised bud tips. Methods We explored epithelial cell behavior at all scales by utilizing a combination of mouse genetics and a custom machine-learning segmentation pipeline in MATLAB. Ureteric bud epithelial cell shapes and sizes were quantified in 3D wholemount kidneys. A combination with live imaging of fluorescently labelled UB cells, traction force microscopy, and primary UB cells were used to determine how basic cellular features and niche biomechanics contribute to complex novel branch point determination in the process that aims at gaining optimal growth and epithelial density in a limited space. Results Machine learning-based segmentation of tip epithelia identified geometrical round-to-elliptical transformation as a key cell shape change facilitating shifts in growth direction that enable propitious branching complexity. Cell shape and molecular analyses in branching-compromised epithelia demonstrated a failure to condense cell size and conformation. Analysis of branching-compromised ureteric bud derived epithelial cells demonstrated disrupted E-CADHERIN and PAXILLIN mediated adhesive forces and defective cytoskeletal dynamics as detected by fluorescent labelling of actin in primary ureteric bud epithelial cells. Branching-compromised ureteric bud epithelial cells showed wrinkled nuclear shapes and alterations in MYH9-based microtubule organization, which suggest a stiff cellular niche with disturbed sensing of and response to biomechanical cues. Conclusions Our results indicate that the adhesive forces within the epithelium and towards the niche composed of nephron progenitors must dynamically fluctuate to allow complexity in arborization during new branch formation. The data collectively propose a model where epithelial cell crowding in tandem with stretching transforms individual cells into elliptical and elongated shapes. This creates local curvatures that drive new branch formation during the ampulla-to-asymmetric ampulla transition of ureteric bud.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.006
GPT teacher head0.197
Teacher spread0.190 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations2
Published2024
Admission routes1
Has abstractyes

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