Evaluation of variation in serum globulin concentrations in dairy cattle
Bibliographic record
Abstract
BACKGROUND: Several factors may influence the concentration of serum globulins in healthy cows and thereby affect clinical interpretation; however, few studies have addressed sources of variation in globulin values. OBJECTIVES: The purpose of this study was to compare colorimetry-based total serum globulin values with electrophoretically-determined serum globulin fractions and with IgG concentration, and to evaluate diurnal and long-term physiological variation and the effects of lactation and venipuncture site on serum globulin concentrations in Holstein dairy cattle. METHODS: Serum total globulin and albumin concentrations were analyzed by colorimetry and electrophoresis in 86 lactating cows; IgG concentrations were determined by radial immunodiffusion in 41 dry and 34 lactating cows. Serum globulins were analyzed hourly for 24 hours in 8 lactating cows and weekly for 15 weeks in 6 additional cows. Globulin concentrations were compared in samples obtained from jugular and coccygeal venipuncture sites in 4 cows. Results were analyzed using parametric statistical tests. RESULTS: Colorimetry-based total serum globulin concentrations correlated well with gamma-globulin fractions (r2 = 0.87) and IgG concentrations (r2 = 0.91). Diurnal variation of total serum globulins concentration was significant (P =.01); however, globulins did not vary significantly over a 15-week period. Mean serum globulins concentration in samples obtained from the jugular vein was 2.35 g/L higher than that in samples obtained by coccygeal venipuncture (P <.0001). CONCLUSIONS: The colorimetric method used widely in routine laboratory analyses remains a useful test for globulins determination in dairy cattle. However, time of sampling and venipuncture site should be considered in the interpretation of serum globulins on serial or interindividual specimens.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".