Bibliographic record
Abstract
This article reviews current literature on the role of micronutrients in human immunodeficiency virus (HIV) infection. Deficiencies of micronutrients are common in HIV-infected persons. They occur due to malabsorption, altered metabolism, gut infection, and altered gut barrier function. There is a compelling association of deficiencies of micronutrients in HIV-infection with immune deficiency, rapid disease progression, and mortality. Also, there is increased risk of vertical HIV transmission from mother to child with deficiency of vitamin A, and of neurological impairment with vitamin B12. The last five years have been exciting in micronutrient research, and there is promise that some micronutrients may be key factors in maintaining health in HIV immunodeficiency, and in reducing mortality. Selenium appears important in reducing virulence of HIV and slowing disease progression. Vitamin A supplementation in pregnant women with HIV may reduce maternal mortality and improve birth outcomes. Supplementation in children with HIV may accelerate growth. Carotenoid supplementation is being evaluated. Vitamin B12 may slow HIV immune deficiency disease progression, and reverse neurological compromise. Clinical benefit of supplementation with some micronutrients may be measurable in the presence of pre-existing deficiency. Apart from improved general nutrition, the impact of micronutrient supplements on health and their optimal use in HIV infection is controversial because there are so few controlled clinical trials. Further research is needed to elucidate the role of micronutrient deficiencies on the course of HIV infection, and the preventive and therapeutic role of supplementation in its clinical management. Nevertheless, current knowledge supports the use of routine multivitamin and trace element supplementation as adjuvant to conventional antiretroviral drug treatment as a relatively low-cost intervention.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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 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".