Infection-Susceptibility Alleles of Mannose-Binding Lectin are Associated with Increased Carotid Plaque Area
Bibliographic record
Abstract
The MBL gene, encoding mannose-binding lectin, deter- mines interindividual variation in susceptibility to certain infectious agents, such as Chlamydia pneumoniae . We exam- ined whether infection-susceptibility alleles of MBL, called “non-A alleles,” would be associated with increased carotid plaque area (CPA), an intermediate phenotype of atheroscle- rosis. In 164 subjects, we measured CPA with 2-dimensional ultrasound. We also determined traditional atherosclerosis risk factors and genotyped all subjects for MBL codons 52, 54, and 57. We used ANOVA to determine sources of varia- tion for CPA and tested the hypothesis that the presence of a single MBL non-A “infection-susceptibility” allele was asso- ciated with increased CPA; 45.7% of subjects had at least one non-A allele. ANOVA showed that CPA was significantly associated with MBL genotype, age, smoking, hypertension, and hyperlipidemia (P<0.05). When MBL was used as the sole independent variable in the regression analysis, the as- sociation with CPA was even more significant (P=0.009). Subjects with at least one MBL non-A allele had significantly higher CPA than subjects homozygous for the MBL A allele and were significantly more likely to have CPA in excess of the sample median. Thus, infection-susceptibility alleles of MBL were associated with increased CPA in this study sam- ple; these alleles may be a determinant of interindividual differences in atherosclerosis risk.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 0.000 |
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".