Substance P concentrations in the blood plasma and serum of adult cattle and calves during different painful procedures and conditions – a systematic review
Bibliographic record
Abstract
Abstract Background Pain in cattle is a major welfare problem, as cattle mask their pain. Subjective and objective parameters to assess pain in cattle have been described. Among the objective parameters to evaluate pain in cattle is substance P (SP). SP is a neurotransmitter, which is involved in the processing of noxious information to the brain; it seems to be a more objective indicator for nociception than cortisol, which has long been used as a biomarker for pain and stress in cattle. The objective of this systematic review was to assess the existing literature about SP during painful procedures, conditions, and diseases in cattle in form of a systematic review. Results Following the PRISMA statement, 36 out of 236 studies were included in this systematic review. Study design, grouping, age and weight of animals, processing of blood samples for the assessment of SP, and results were heterogenous. The largest number of studies originated from the United States of America and Canada and were published in 2018. A higher number of studies were done on calves (69.4%, n = 25) compared with adult cattle (30.6%, n = 11). Most studies were done to assess SP concentrations after administration of analgesics prior to husbandry procedures in calves. Conclusions There is a manageable number of studies assessing SP concentrations during painful procedures, conditions, and diseases in cattle. SP seems to be a suitable biomarker for nociception in cattle, but results of research work are heterogenous, and SP concentrations of calves and adult cattle differ throughout studies. Basic research work is missing and is needed to assess factors others than nociception which might influence the SP concentrations in the blood plasma.
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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 | 0.005 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".