The Human Transcriptome During Nontyphoid Salmonella and HIV Coinfection Reveals Attenuated NFκB-Mediated Inflammation and Persistent Cell Cycle Disruption
Bibliographic record
Abstract
BACKGROUND: Invasive nontyphoid Salmonella (iNTS) disease is common and severe in adults with human immunodeficiency virus (HIV) infection in Africa. We previously observed that ex vivo macrophages from HIV-infected subjects challenged with Salmonella Typhimurium exhibit dysregulated proinflammatory cytokine responses. METHODS: We studied the transcriptional response in whole blood from HIV-positive patients during acute and convalescent iNTS disease compared to other invasive bacterial diseases, and to HIV-positive and -negative controls. RESULTS: During iNTS disease, there was a remarkable lack of a coordinated inflammatory or innate immune signaling response. Few interferon γ (IFNγ)-induced genes or Toll-like receptor/transcription factor nuclear factor κB (TLR/NFκB) gene pathways were upregulated in expression. Ex vivo lipopolysacharide (LPS) or flagellin stimulation of whole blood, however, showed that convalescent iNTS subjects and controls were competent to mount prominent TLR/NFκB-associated patterns of mRNA expression. In contrast, HIV-positive patients with other invasive bacterial infections (Escherichia coli and Streptococcus pneumoniae) displayed a pronounced proinflammatory innate immune transcriptional response. There was also upregulated mRNA expression in cell cycle, DNA replication, translation and repair, and viral replication pathways during iNTS. These patterns persisted for up to 2 months into convalescence. CONCLUSIONS: Attenuation of NFκB-mediated inflammation and dysregulation of cell cycle and DNA-function gene pathway expression are key features of the interplay between iNTS and HIV.
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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 | 0.000 | 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".