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Record W4388923798 · doi:10.1101/2023.11.22.568246

In the murine and bovine maternal mammary gland signal transducer and activator of transcription 3 is activated in clusters of epithelial cells around the day of birth

2023· preprint· en· W4388923798 on OpenAlexaff
Laura J.A. Hardwick, Benjamin P. Davies, Sara Pensa, Maedee Burge-Rogers, Claire Davies, André Figueiredo Baptista, Robert Knott, Ian McCrone, Eleonora Po, B. W. Strugnell, Katie Waine, Paul M. Wood, Walid T. Khaled, Huw D. Summers, Paul Rees, John W. Wills, Katherine Hughes

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversity of Calgary
FundersAnatomical Society
KeywordsMammary glandSTAT proteinSTAT3Transcription factorActivator (genetics)BiologyMessenger RNACell biologyInvolution (esoterism)Internal medicineMedicineGeneSignal transductionReceptorNeuroscienceGeneticsCancer

Abstract

fetched live from OpenAlex

Abstract Signal Transducers and Activators of Transcription (STATs) regulate mammary gland development. Here we investigate the expression of pSTAT3 in the murine and bovine mammary gland around the day of birth. We identify polarisation of mammary alveoli towards either a low- or high-proportion of pSTAT3 positive alveolar epithelial cells. We present localised colocation analysis applicable to other mammary studies where identification, quantification and interrogation of significant, spatially congregated events is required. We demonstrate that pSTAT3-positive events are multifocally clustered in a non-random and statistically significant fashion. This finding represents a new facet of mammary STAT3 biology meriting further functional investigation.

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 score0.002
Threshold uncertainty score0.007

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)0.0020.000

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 head0.021
GPT teacher head0.213
Teacher spread0.192 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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