Implication of mammaglobin 1 and lipophilin B in breast cancer
Bibliographic record
Abstract
Mammaglobin 1 (MGB1) is a protein fairly specific to mammary tissues and is often over expressed in breast cancer. It belongs to the secretoglobin family and binds to another secretoglobin, lipophilin B (LPB), to form an active complex. The complete expression profiles of MGB1 and LPB have not been determined, however it seems certain that they are expressed in healthy mammary cells and overexpressed in cancerous mammary cells. The function of the MGB1/LPB complex is still unknown. Nonetheless, several recent studies have shed some light on one possible effect this complex could have on cancerous cells; it has been shown that the presence of MGB1 in primary breast tumors seems to reflect a less aggressive tumor phenotype and a better prognosis for this type of cancer. The objective of this study is to try to clarify the implications of the MGB1/LPB complex and its components, MGB1 and LPB individually, in breast cancer. More precisely, this study investigates the ability of the MGB1/LPB complex or the MGB1 and LPB proteins individually, to inverse or slow down the cancerous phenotype of mammary cells in terms of proliferation, apoptosis and extracellular matrix invasion. We will also investigate whether MGB1 can influence the expression levels of LPB and vice versa. Overall, the importance of the research is to deepen our knowledge on the MGB1/LPB complex, which seems to play an important role in the biological processes of mammary cells. Research support from New Brunswick Innovation Foundation, Canadian Institutes in Health Research and Atlantic Innovation Foundation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".