Deficiency of prolactin-inducible protein leads to a lower Th1 immune response in vitro and in vivo (70.2)
Bibliographic record
Abstract
Abstract The prolactin-inducible protein (PIP) is a secretory protein strategically located at several ports of pathogen entry into the body and hence might play a role in the first line of immune defense against invading pathogens. To date, there are no studies that address the contributions of PIP against infection. Our previous studies show that PIP knockout (KO) mice had enlarged submandibular lymph nodes and thymic medulla. Here, we assessed the phenotype and responsiveness of immune cells from PIP KO mice to polyclonal T cell stimulators and model antigens in vitro and in vivo. We found that PIP KO mice have comparable numbers or frequency of immune cells, including T, B, natural killer and dendritic cells. In depth phenotypic analysis revealed that the PIP KO mice had slightly but significantly lower numbers of CD4+ T cells in their spleens and lymph nodes. Furthermore, CD4+ T cells from PIP KO mice showed significantly decreased proliferation, IL-2 production and impaired differentiation into Th1 subsets in vitro. The impaired in vitro Th1 response was confirmed in vivo where CD4+ T cells from OVA-immunized PIP KO mice showed significantly impaired proliferation and IFN-γ production following restimulation with OVA. Collectively, our findings implicate PIP as an important CD4+ modulatory protein that enhances Th1 cell response, and suggest that this protein might play critical roles in cell-mediated immunity and resistance to intracellular pathogens.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".