Bibliographic record
Abstract
The tissue specificity and age-related etiology of Shiga toxin (Stx)-induced pathology strongly implicate receptor binding as a major determinant of Stxinduced hemolytic uremic syndarome (HUS) (). In this review, Shiga toxin receptor binding is considered in relation to the following: (1) the multivalency and multiple valencies of the Shiga toxin B- subunit pentamer and the molecular basis of its specificity, including the important role played by the lipid moiety of globotriaosyl ceramide (Gb3) and its plasma membrane microenvironment; (2) the internalization of the toxin-receptor complex and subsequent intracellular trafficking; (3) the role of Gb3 in cell signaling pathways; (4) the upregulation of Gb3 synthesis and Stx sensitivity in cancers, particularly drug-resistant cancers and the involvement of the P-glycoprotein in Gb3 biosynthesis; (5) the ability of Gb3 synthesis to be upregulated by cytokines or short-chain fatty acids to increase Stx susceptibility; 6) Gb3 as a risk factor for the development of HUS, because in summa, these properties define the mechanism by which Shiga toxemia results in clinical sequellae. However, these properties also imbue Stx with characteristics that can be utilized as tools in cell biology to measure aspects of homeostasis and to provide new methods for immunization and DNA transfection.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".