Invasion of Bovine Peripheral Blood Mononuclear Cells and Erythrocytes by<i>Mycoplasma bovis</i>
Bibliographic record
Abstract
Mycoplasma bovis is a small, cell wall-less bacterium that contributes to a number of chronic inflammatory diseases in both dairy and feedlot cattle, including mastitis and bronchopneumonia. Numerous reports have implicated M. bovis in the activation of the immune system, while at the same time inhibiting immune cell proliferation. However, it is unknown whether the specific immune-cell population M. bovis is capable of attaching to and potentially invading. Here, we demonstrate that incubation of M. bovis Mb1 with bovine peripheral blood mononuclear cells (PBMC) resulted in a significant reduction in their proliferative responses while still remaining viable and capable of gamma interferon secretion. Furthermore, we show that M. bovis Mb1 can be found intracellularly (suggesting a role for either phagocytosis or attachment/invasion) in a number of select bovine PBMC populations (T cells, B cells, monocytes, γδ T cells, dendritic cells, NK cells, cytotoxic T cells, and T-helper cells), as well as red blood cells, albeit it at a significantly lower proportion. M. bovis Mb1 appeared to display three main patterns of intracellular staining: diffuse staining, an association with the intracellular side of the cell membrane, and punctate/vacuole-like staining. The invasion of circulating immune cells and erythrocytes could play an important role in disease pathogenesis by aiding the transport of M. bovis from the lungs to other sites.
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 | 0.000 | 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".