A Novel Role for Tumor Necrosis Factor-α in Regulating Susceptibility of Activated CD4+ T Cells From Human and Nonhuman Primates for Distinct Coreceptor Using Lentiviruses
Bibliographic record
Abstract
Summary: HIV infection has now been consistently identified as the major cause of death in young Africans in both urban and rural areas. In Africa, several studies have defined the clinical presentation of HIV disease but there have only been a limited number of autopsy studies. Because of the scarcity of autopsy data and the possibility of differing type and frequency of opportunistic infections between different geographic locations we set out to study consecutive new adult medical admissions to a tertiary referral hospital in Nairobi and perform autopsies on a sample of HIV-1positive and HIV-1-negative patients who died in the hospital ward. Basic demographic data were collected on all patients admitted to two acute medical wards over an 11-month period. Final outcome and final clinical diagnoses were recorded at discharge or death. An autopsy examination was requested if the patient died in the ward. Autopsy examination was performed in 75 HIV-1-positive (40 men, 35 women) and 47 HIV-1-negative (28 men, 19 women) adults who died in the hospital. This represented 48.4% of all HIV-1-positive deaths and 33.3% of all HIV-1-negative deaths. Tuberculosis (TB) and bacterial and interstitial bronchopneumonia accounted for 96% of the major pathology in patients found to be HIV-1-positive at autopsy. TB was present in half the HIV-1-positive autopsy patients and was disseminated in over 80% of cases. Meningeal involvement was present in 26% of those with disseminated TB. By contrast, TB was much less common in the HIV-1-negative patients at autopsy in whom bacterial bronchopneumonia and malignancies were the most common pathologies. The type pathology found in the HIV-1-positive autopsy patients was not different than that found in other areas in Africa so far studied.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".