T-Cell Responses Against Meningococcal Antigens
Bibliographic record
Abstract
T-cells recognize protein antigens as short peptide fragments (8-20 amino acids) bound to major histocompatibility complex (MHC) molecules on the surface of antigen-presenting cells (APCs). A prerequisite for antigen-specific T-cell activation is antigen uptake, enzymatic degradation, and recycling of MHC-peptide complexes to the surface of APCs. Whereas CD8+ T cells recognize endogenously derived antigen (virus and other intracellular pathogens) bound to MHC class I molecules, CD4+ T cells recognize exogenously derived antigen in complex with MHC class II molecules. Hence, extracellular bacteria, such as meningococci during invasive disease, will be presented to CD4+ T cells in the context of MHC class II molecules, after uptake and processing by professional APCs like B cells, macrophages, or dendritic cells. Antigen-specific CD4+ T cells can be classified as Th1 or Th2 subpopulations on the basis of different cytokine production and effector functions (1). Intracellular microbes often induce Th1-dominated responses, whereas extracellular pathogens and parasites typically trigger Th2 responses. Th1 cells produce mainly interleukin (IL)-2, interferon (IFN)-γ, and tumor necrosis factor (TNF)-β, which represent important inducers of the cell-mediated immune responses. The principal Th1 cytokine IFN-γ activates macrophages by enhancing their ability to phagocytize and destroy microbes by intracellular bactericidal mechanisms. In contrast, Th2 cells produce IL-4, IL-5, IL-6, and IL-13, which are important factors for inducing and regulating B-cell responses (1).
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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".