Glycans, galectins, and HIV‐1 infection
Bibliographic record
Abstract
During sexual transmission, HIV-1 must overcome physiological barriers to establish a founder cell population. Viral adhesion represents a bottleneck for HIV-1 propagation that the virus widens by exploiting some specific host factors. Recognition of oligomannosyl glycans of gp120 by C-type lectins is one such example. Recent works suggest that complex glycans of gp120 are recognized by another host lectin, galectin-1. This interaction results in rapid association of HIV-1 to susceptible cells and facilitates infection. The peculiar presentation of complex glycans on gp120 seems to impart specificity for galectin-1, as another member of the same family, galectin-3, is unable to bind gp120 or enhance HIV-1 infection. Other studies have shown that galectin-9 could also increase HIV-1 infectivity but via an indirect mechanism. Thus, current research suggests that galectins play various roles in HIV-1 pathogenesis. Drug discovery approaches targeting host lectins at early steps could benefit the current arsenal of antiretrovirals.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".