MétaCan
Menu
Back to cohort
Record W4283164478 · doi:10.1155/2022/7813921

Proteomic Analysis of Chicken Chorioallantoic Membrane (CAM) during Embryonic Development Provides Functional Insight

2022· article· en· W4283164478 on OpenAlexafffund
Tamer A. Ahmed, Cristianne Cordeiro, Oluwadara Elebute, Maxwell T. Hincke

Bibliographic record

VenueBioMed Research International · 2022
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAquaculture disease management and microbiota
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'EnvironnementStudium Loire Valley-Institute for Advanced Studies
KeywordsChorioallantoic membraneProteomeBiologyProteomicsCell biologyAngiogenesisComputational biologyBiochemistryEmbryoCancer research

Abstract

fetched live from OpenAlex

In oviparous animals, the egg contains all resources required for embryonic development. The chorioallantoic membrane (CAM) is a placenta‐like structure produced by the embryo for acid‐base balance, respiration, and calcium solubilization from the eggshell for bone mineralization. The CAM is a valuable in vivo model in cancer research for development of drug delivery systems and has been used to study tissue grafts, tumor metastasis, toxicology, angiogenesis, and assessment of bacterial invasion. However, the protein constituents involved in different CAM functions are poorly understood. Therefore, we have characterized the CAM proteome at two stages of development (ED12 and ED19) and assessed the contribution of the embryonic blood serum (EBS) proteome to identify CAM‐unique proteins. LC/MS/MS‐based proteomics allowed the identification of 1470, 1445, and 791 proteins in CAM (ED12), CAM (ED19), and EBS, respectively. In total, 1796 unique proteins were identified. Of these, 175 (ED12), 177 (ED19), and 105 (EBS) were specific to these stages/compartments. This study attributed specific CAM protein constituents to functions such as calcium ion transport, gas exchange, vasculature development, and chemical protection against invading pathogens. Defining the complex nature of the CAM proteome provides a crucial basis to expand its biomedical applications for pharmaceutical and cancer research.

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 score0.003
Threshold uncertainty score0.006

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)0.0000.000

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 head0.037
GPT teacher head0.296
Teacher spread0.259 · 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

Citations19
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueBioMed Research InternationalSame topicAquaculture disease management and microbiotaFrench-language works237,207