Measurement of messenger RNA encoding the α-chain, polymeric immunoglobulin receptor, and J-chain in duodenal mucosa from dogs with and without chronic diarrhea by use of quantitative real-time reverse transcription-polymerase chain reaction assays
Bibliographic record
Abstract
OBJECTIVE: To examine the difference in expression of messenger RNA (mRNA) transcripts for polymeric immunoglobulin receptor (plgR), alpha-chain, and J-chain determined by use of quantitative real-time reverse transcription-polymerase chain reaction (QRT-PCR) assays in duodenal biopsy specimens obtained from dogs with and without chronic diarrhea. SAMPLE POPULATION: Biopsy specimens of the proximal portion of the duodenum were obtained endoscopically from 39 dogs evaluated because of chronic diarrhea (12 German Shepherd Dogs and 27 non-German Shepherd Dog breeds); specimens were also obtained from a control group of 7 dogs evaluated because of other gastrointestinal tract diseases and 2 dogs that were euthanatized as a result of nongastrointestinal tract disease. PROCEDURE: Dogs were anesthetized, and multiple mucosal biopsy specimens were obtained endoscopically at the level of the caudal duodenal flexure by use of biopsy forceps; in 2 control dogs, samples were obtained from the descending duodenum within 5 minutes of euthanasia. One-step QRT-PCR was used to quantify the level of expression of transcripts for the housekeeper gene glyceraldehyde-3-phosphate dehydrogenase, plgR, alpha-chain, and J-chain in duodenal mucosal tissue. RESULTS: There was no significant difference in the level of expression of any transcript among non-German Shepherd Dog breeds without diarrhea (control group), non-German Shepherd Dog breeds with chronic diarrhea, and German Shepherd Dogs with chronic diarrhea. Conclusions and Clinical Relevance-Results indicated that the susceptibility of German Shepherd Dogs to chronic diarrhea is not a result of simple failure of transcription of the key genes that encode molecules involved in mucosal IgA secretion.
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) | 0.001 | 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".