A lamprey monoclonal VLR antibody against human CD5 (65.34)
Bibliographic record
Abstract
Abstract The recently identified VLRB antibodies of the agnathan sea lamprey use highly variable leucine-rich repeats (LRRs) that assume a solenoid shape to bind antigens. Solved structures of monoclonal VLRB antibodies complexed to the H-trisaccharide or HEL show that antigens bind to variable residues in the beta-sheets located on the concave surface of specific VLRB antibodies. In this study we screened clones of a lamprey VLR cDNA expression library prepared from animals immunized with human CD4+ T cells to identify a monoclonal VLRB antibody (T32) that bound to human T lymphocytes, but not mouse T cells. Modulation of the expression levels of the TCR/CD3 complex by mouse antibodies did not affect VLR T32 binding. Staining of T cells, tonsilar B cells and malignant B-CLL cells with VLRB T32 and a mouse anti-CD5 mAb (clone UCHT2) demonstrated a diagonal co-staining pattern for each population of the test cells. Transfection of the CD5-negative OCI-Ly3 cell line with a human CD5 cDNA construct resulted in VLR T32 binding of transfected but not of untransfected cells. Staining of CD5+ cells by VLR T32 was not blocked by pre-incubation with the mouse UCHT2 anti-CD5 mAb, which suggests that they recognizes different CD5 epitopes. We conclude that lamprey monoclonal VLR antibodies offer useful alternatives to conventional antibodies for biomedical purposes.
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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".