The expression of FIZZ/resistin/RELM family in mouse hypoxia lung
Bibliographic record
Abstract
The FIZZ/resistin/RELM family contains 2 human and 4 murine genes. This important gene family has been implicated in a variety of human diseases. In mouse, hypoxia‐induced mitogenic factor (HIMF), also called FIZZ1 or RELMα has been shown to have potent mitogenic, angiogenic and vasoconstrictive effects in the lung vasculature. Among the four members, HIMF and FIZZ4/RELMγ are the most closely related proteins, with 72% identity in amino acid sequence. Whether FIZZ4/RELMγ also plays similar role as HIMF in lung tissue, remains unclear. Using polymerase chain reaction (PCR) and RT (reverse transcriptase)‐PCR, we have analyzed the expression of FIZZ/resistin/RELM family in normal and hypoxic murine lung tissue. Mouse lung cDNA library and lung cDNAs prepared from normoxic and hypoxic mice were used in the PCR. HIMF, FIZZ2/RELMβ and FIZZ4/RELMγ mRNA are shown to be expressed in mouse lung tissue but not resistin. The expression of FIZZ4/RELMγ is the most abundant among the FIZZ/resistin/RELM family in lung tissue and is also upregulated in hypoxic murine lung. Along with HIMF, We have demonstrated that FIZZ4/RELMγ is another member of FIZZ/resistin/RELM family highly expressed in murine lung. Like HIMF, the expression of RELMγ can be regulated by hypoxia. Our results suggest that FIZZ4/RELMγ may be another factor involved in inflammation in lung. ( Funded By: NIH grant HL39706)
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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 | 0.001 | 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".