Interferon-Alpha Reduces Human Hippocampal Neurogenesis and Increases Apoptosis via Activation of Distinct STAT1-Dependent Mechanisms
Bibliographic record
Abstract
Background: In humans, interferon-α treatment for chronic viral hepatitis is a well-recognized clinical model for inflammation-induced depression, but the molecular mechanisms underlying these effects are not clear. Following peripheral administration in rodents, interferon-α induces signal transducer and activator of transcription-1 (STAT1) within the hippocampus and disrupts hippocampal neurogenesis. Methods: We used the human hippocampal progenitor cell line HPC0A07/03C to evaluate the effects of 2 concentrations of interferon-α, similar to those observed in human serum during its therapeutic use (500 pg/mL and 5000 pg/mL), on neurogenesis and apoptosis. Results: Both concentrations of interferon-α decreased hippocampal neurogenesis, with the high concentration also increasing apoptosis. Moreover, interferon-α increased the expression of interferon-stimulated gene 15 (ISG15), ubiquitin-specific peptidase 18 (USP18), and interleukin-6 (IL-6) via activation of STAT1. Like interferon-α, co-treatment with a combination of ISG15, USP18, and IL-6 was able to reduce neurogenesis and enhance apoptosis via further downstream activation of STAT1. Further experiments showed that ISG15 and USP18 mediated the interferon-α-induced reduction in neurogenesis (potentially through upregulation of the ISGylation-related proteins UBA7, UBE2L6, and HERC5), while IL-6 mediated the interferon-α-induced increase in apoptosis (potentially through downregulation of aquaporin 4). Using transcriptomic analyses, we showed that interferon-α regulated pathways involved in oxidative stress and immune response (e.g., Nuclear Factor (erythroid-derived 2)-like 2 [Nrf2] and interferon regulatory factor [IRF] signaling pathway), neuronal formation (e.g., CAMP response element-binding protein [CREB] signaling), and cell death regulation (e.g., tumor protein(p)53 signaling). Conclusions: We identify novel molecular mechanisms mediating the effects of interferon-α on the human hippocampus potentially involved in inflammation-induced neuropsychiatric symptoms.
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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".