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Record W3102829085 · doi:10.3892/ol.2020.12313

Nidogen 1 regulates proliferation and migration/invasion in murine claudin‑low mammary tumor cells

2020· article· en· W3102829085 on OpenAlexafffund
Rebecca Jagroop, Courtney Martin, Roger A. Moorehead

Bibliographic record

VenueOncology Letters · 2020
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsUniversity of Guelph
FundersCanadian Institutes of Health Research
KeywordsGene knockdownOncogeneCancer researchBiologyClaudinMammary tumorCell growthLamininCell migrationCell biologyCell cycleCell cultureCancerBreast cancerTight junctionExtracellular matrix

Abstract

fetched live from OpenAlex

Nidogen 1 (NID1) is a glycoprotein found in basement membranes involved in cross‑linking collagen IV and laminin. The role of NID in breast cancer has only been evaluated in a small number of studies and the findings of these studies have been inconsistent. Our previous work revealed that highly tumorigenic murine mammary tumor cells express high levels of Nid1 while weakly tumorigenic mammary tumor cells express low levels of Nid1. To investigate Nid1, two stable knockdown lines were created, and Nid1 knockdown was confirmed at both the mRNA and protein level. Nid1 knockdown significantly reduced cell proliferation and migration/invasion and these reductions in proliferation and migration/invasion could be rescued by conditioned media containing NID1 protein. The reduced migration/invasion observed in the Nid1 knockdown cells was not associated with significant alterations in the epithelial gene Cdh1 or the mesenchymal genes Snai1, Snai2, Twist1, Twist2, Zeb1 and Zeb2. Therefore, suppression of Nid1 expression reduces proliferation and migration/invasion in claudin‑low murine mammary tumor cells.

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 score0.004

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 integrity0.0000.001
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 head0.021
GPT teacher head0.277
Teacher spread0.255 · 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

Citations15
Published2020
Admission routes2
Has abstractyes

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