Toll-like receptor-4 genotype influences the survival of cystic fibrosis mice
Bibliographic record
Abstract
Toll-like receptor (Tlr) 4 is a lipopolysaccharide (LPS) receptor that contributes to the regulation of intestinal cell homeostasis, a condition that is altered in the intestines of cystic fibrosis mice. Herein, we assessed whether Tlr4 genotype influences cystic fibrosis intestinal disease by producing and phenotyping 12-wk (adult)- and 4-day (neonate)-old mice derived from BALB cystic fibrosis transmembrane conductance regulator, Cftr(+/tm1Unc) and C.C3-Tlr4(Lps-d)/J (Tlr4(-/-)), progenitors. Intestinal disease was assayed through mouse survival, crypt-villus axis (CVA) length, cell proliferation, bacterial load, bacterial classification, inflammatory cell infiltrate, and mucus content measures. Of the 77 Cftr(-/-) (CF) mice produced, only one Cftr/Tlr4 double-mutant mouse lived to the age of 12 wk while the majority of the remainder succumbed at approximately 4 days of age. The survival of CF Tlr4(+/-) mice exceeded that of both CF Tlr4(+/+) and Cftr/Tlr4 double-mutant mice. Adult CF mice presented increased Tlr4 expression, CVA length, crypt cell proliferation, and bacterial load relative to non-CF mice, but no differences were detected in Tlr4(+/-) compared with Tlr4(+/+) CF mice. The double-mutant neonates did not differ from Tlr4(+/+) or Tlr4(+/-) CF mice by intestinal CVA length or bacterial load, but fewer Tlr4(+/-) CF neonates presented with luminal mucus obstruction in the distal ileum, and the intestinal mast cell increase of CF mice was not evident in double-mutant neonates. We conclude that Tlr4 deficiency reduces the survival, but does not alter the intestinal phenotypes, of extended CVA or increased bacterial load in BALB CF mice.
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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 | 0.001 | 0.001 |
| 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".