Investigating the IgM and IgG B Cell Receptor Repertoires and Expression of Ultralong Complementarity Determining Region 3 in Colostrum and Blood from Holstein-Friesian Cows at Calving
Bibliographic record
Abstract
In cattle, colostral maternal immunoglobulins and lymphocytes transfer across the neonate’s intestinal epithelium to provide protection against pathogens. This study aimed to compare repertoires of B cell populations in blood and colostrum in cows for the first time, with an emphasis on ultralong complementarity determining region 3 (CDR3, ≥40 amino acids). Blood mononuclear cells (BMCs, n= 7) and colostral cells (n = 7) were isolated from Holstein-Friesian dairy cows. Magnetic-activated cell sorting was used to capture IgM and IgG B cells from BMCs. Colostral cells were harvested by centrifugation. RNA was extracted and cDNA was produced; IgM and IgG transcripts were amplified using polymerase chain reactions. Amplicons were sequenced using the Nanopore Native barcoding kit 24 V14 and MinION with R10.4 flow cells. In colostrum, there was a significantly greater percentage of IgM B cells with ultralong CDR3s (8.09% ± 1.73 standard error of the mean) compared to blood (4.22% ± 0.70, p = 0.05). There was a significantly greater percentage of IgG B cells in colostrum with ultralong CDR3s (12.98% ± 1.98) compared to blood (6.61% ± 1.11, p = 0.05). A higher percentage of IgM and IgG B cells with ultralong CDR3s in colostrum may be indicative of a potential role in protecting the neonate.
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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 | 0.000 | 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".