Bibliographic record
Abstract
Under physiological conditions, hematopoietic stem and progenitor cells (HSPCs) in the bone marrow niches are responsible for the highly regulated and interconnected hematopoiesis process. At the same time, they must recognize potential threats and respond promptly to protect the host. A wide spectrum of microbial agents/products and the consequences of infection-induced mediators (e.g. cytokines, chemokines, and growth factors) can have prominent impact on HSPCs. While COVID-19 starts as a respiratory tract infection, it is considered a systemic disease which profoundly alters the hematopoietic system. Lymphopenia, neutrophilia, thrombocytopenia, and stress erythropoiesis are the hallmark of SARS-CoV-2 infection. Moreover, thrombocytopenia and blood hypercoagulability are common among COVID-19 patients with severe disease. Notably, the invasion of erythroid precursors and progenitors by SARS-CoV-2 is a cardinal feature of COVID-19 disease which may in part explain the mechanism underlying hypoxia. These pieces of evidence support the notion of skewed steady-state hematopoiesis to stress hematopoiesis following SARS-CoV-2 infection. The functional consequences of these alterations depend on the magnitude of the effect, which launches a unique hematopoietic response that is associated with increased myeloid at the expense of decreased lymphoid cells. This article reviews some of the key pathways including the infectious and inflammatory processes that control hematopoiesis, followed by a comprehensive review that summarizes the latest evidence and discusses how SARS-CoV-2 infection impacts hematopoiesis.
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 | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".