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Record W1980446289 · doi:10.1242/dev.120279

Vascular patterning regulates interdigital cell death by a ROS-mediated mechanism

2015· article· en· W1980446289 on OpenAlexaff
Idit Eshkar-Oren, Sharon Krief, Napoleone Ferrara, Alison M. Elliott, Elazar Zelzer

Bibliographic record

VenueDevelopment · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHippo pathway signaling and YAP/TAZ
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBiologyCell biologyProgrammed cell deathReactive oxygen speciesLimb developmentAnatomyApoptosisBiochemistry

Abstract

fetched live from OpenAlex

Blood vessels serve as key regulators of organogenesis by providing oxygen, nutrients and molecular signals. During limb development, programmed cell death (PCD) contributes to separation of the digits. Interestingly, prior to the onset of PCD, the autopod vasculature undergoes extensive patterning that results in high interdigital vascularity. Here, we show that in mice, the limb vasculature positively regulates interdigital PCD. In vivo, reduction in interdigital vessel number inhibited PCD, resulting in syndactyly, whereas an increment in vessel number and distribution resulted in elevation and expansion of PCD. Production of reactive oxygen species (ROS), toxic compounds that have been implicated in PCD, also depended on interdigital vascular patterning. Finally, ex vivo incubation of limbs in gradually decreasing oxygen levels led to a correlated reduction in both ROS production and interdigital PCD. The results support a role for oxygen in these processes and provide a mechanistic explanation for the counterintuitive positive role of the vasculature in PCD. In conclusion, we suggest a new role for vascular patterning during limb development in regulating interdigital PCD by ROS production. More broadly, we propose a double safety mechanism that restricts PCD to interdigital areas, as the genetic program of PCD provides the first layer and vascular patterning serves as the second.

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 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 score0.094
Threshold uncertainty score0.719

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.014
GPT teacher head0.207
Teacher spread0.194 · 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.

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

Citations20
Published2015
Admission routes1
Has abstractyes

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