Invited review: Role of bacterial endotoxins in the etiopathogenesis of periparturient diseases of transition dairy cows
Bibliographic record
Abstract
The dairy industry continues to suffer severe economic losses due to the increased disease incidence cows experience during the transition period. It has long been the classical view that the major contributing factor to the development of these periparturient diseases is the considerable increase in nutritional demands for milk production. This classical view, however, fails to account for the substantial correlation between both metabolic and infectious diseases and the detrimental effects that can occur with the provision of high-energy diets to support these nutritional demands. Currently, increasing evidence implicates bacterial endotoxins in the etiopathology of most periparturient diseases. Bacterial endotoxins are components of the outer cell wall of gram-negative and gram-positive bacteria that are highly immunostimulatory and can trigger proinflammatory immune responses. The ability of endotoxins to translocate from the mucosal tissues, including the gastrointestinal tract, mammary gland, and uterus, into the systemic circulation has been observed. Once they have entered the circulation, endotoxins potentially contribute to disease either directly, through eliciting an inflammatory response, or indirectly through other factors such as the overreaction of the natural protective mechanisms of the host. Although the evidence implicating a role of endotoxins in the pathogenesis of transition diseases continues to grow, our current knowledge of the host response to mucosal endotoxin exposure and pathogenic mechanisms remain largely unknown. Developing our understanding of the connection between endotoxemia and dairy cattle disease holds significant potential for the future development of preventative measures that could benefit the productivity of the dairy industry as well as animal welfare.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.031 | 0.013 |
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".