Bibliographic record
Abstract
The use of anti-retroviral protease inhibitors in combination with nucleoside analog or non nucleoside reverse transcriptase inhibitors (HAART) has led to dramatic decreases in the mortality seen with HIV infected patients. In concert with these treatment regimens, especially with the inclusion of the anti-retroviral protease inhibitors (PI), a complex series of metabolic complications occurred. These included alterations of fat and carbohydrate metabolism. In some patients, one could observe either lipoatrophy (fat wasting) as well as lipohypertrophy (fat deposition) or both. The problem is that the lack of a case definition of the altered fat metabolism confuses diagnoses. In vitro, interference with fat cell differentiation has been demonstrated by PI. Further, in vitro studies demonstrate that indinavir, a PI currently used in HIV treatment, can interact with the insulin responsive glucose transporter (GLUT4). The activity of the GLUT4 is inhibited by indinavir and eventual insulin resistance has been shown (i.e. in vivo and in vitro). Also, controversy exists regarding insulin signaling in fat cells. Finally, the relationships between hyperlipidemia and/or lipolysis and altered carbohydrate metabolism (i.e. mild glucose intolerance, insulin resistance) suggest an association with cardiovascular risk in protease treated patients (Metabolic Syndrome X). In short, while multiple problems exist, no one mechanism can account for the changes observed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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 teacher head, 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".