Bovine Mammary Gland Biopsy Techniques
Bibliographic record
Abstract
Bovine mammary gland biopsies allow researchers to collect tissue samples to study cell biology including gene expression, histological analysis, signaling pathways, and protein translation. This article describes two techniques for biopsy of the bovine mammary gland (MG). Three healthy Holstein dairy cows were the subjects. Before biopsies, cows were milked and subsequently restrained in a cattle chute. An analgesic (flunixin meglumine, 1.1 to 2.2 mg/kg of body weight) was administered via jugular intravenous [IV] injection 15-20 min prior to biopsy. For standing sedation, xylazine hydrochloride (0.01-0.05 mg/kg of body weight) was injected via the coccygeal vessels 5-10 min before the procedure. Once adequately sedated, the biopsy site was aseptically prepared and locally anaesthetized with 6 mL of 2% lidocaine hydrochloride via subcutaneous injection. Using aseptic technique, a 2 to 3 cm vertical incision was made using a number 10 scalpel. Core and needle biopsy tools were used. The core biopsy tool was attached to a cordless drill and inserted into the MG tissue through the incision using a clock-wise drill action. The needle biopsy tool was manually inserted into the incision site. Immediately after the procedure, an assistant applied pressure on the incision site for 20 to 25 min using a sterile towel to achieve hemostasis. Stainless steel surgical staples were used to oppose the skin incision. The staples were removed 10 days post-procedure. The main advantages of core and needle biopsies is that both approaches are minimally invasive procedures that can be safely performed in healthy cows. Milk yield following the biopsy was unaffected. These procedures require a short recovery time and result in fewer risks of complications. Specific limitations may include bleeding after the biopsy and infection on the biopsy site. Applications of these techniques include tissue collection for clinical diagnosis and research purposes, such as primary cell culture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".