Nkx6.2 synergizes with Cdx-2 in stimulating proglucagon gene expression
Bibliographic record
Abstract
AIM: To investigate whether the transactivator of the proglucagon gene (Gcg), Cdx-2, synergizes with other transcription factors in stimulating Gcg expression and the trans-differentiation of Gcg-expressing cells. METHODS: We conducted affinity chromatography to identify proteins that interact with Cdx-2, using GST-tagged Cdx-2 against cell lysates from pancreatic InR1-G9 and intestinal GLUTag cell lines. This was followed by a mass-spectrometry analysis. From a potential Cdx-2 interaction protein identified, we examined its expression in pancreatic and gut endocrine cells, confirmed its interaction with Cdx-2 by GST-pull down and determined its effect in provoking Gcg expression in cell lines that do not express endogenous Gcg. RESULTS: We identified 18 potential Cdx-2 interacting proteins. One of them is Nkx6.2. This homeodomain (HD) protein is expressed in pancreatic α and intestinal endocrine L cells but not in insulin producing cell lines, including In111. Nkx6.2, but not Nkx6.1, was shown to interact with Cdx-2, detected by GST-pull down. Furthermore, Nkx6.2 was found to synergize with Cdx-2 in provoking Gcg expression when they were ectopically expressed in the In111 cell line. Finally, when Cdx-2 and Nkx6.2 were co-transfected into the undifferentiated rat intestinal IEC-6 cell line, it produced detectable amount of Gcg mRNA. CONCLUSION: Cdx-2 recruits Nkx6.2 in exerting its effect in stimulating Gcg expression. Our observations further support the notion that multiple HD proteins, including Cdx-2 and Nkx6.2, are involved in the regulation of Gcg expression and the genesis of Gcg-producing 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 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".