Coagulation activation in an experimental pneumonia model in malnourished mice
Bibliographic record
Abstract
Malnutrition induces a decrease in immunity that affects the ability of the organism to deal with an infectious challenge. The clotting system is considered a branch of immunity and its activation is important in the pathogenesis of an infectious disease. This work was conducted to determine coagulation modifications in malnourished hosts before and during infection. Weaned mice were malnourished via a protein-free diet. Well-nourished control mice (WNC) consumed a balanced conventional diet. Malnourished mice (MN) and WNC were challenged intranasally with Streptococcus pneumoniae. Blood, bronchoalveolar lavages (BAL), and lung samples were taken at different times post infection. The results were that MN showed altered hemostatic tests and fibrin(ogen) deposits in the lung. Thus, an increase in thrombin-antithrombin complexes (TATc) in plasma and BAL was observed. In the MN group, infection induced a rise in TATc in plasma and BAL and increased plasma fibrinogen and fibrin(ogen) deposits in the lung. A decrease in activated protein C and antithrombin in BAL and an early decrease followed by an increase in plasma Factor VIII were also observed. Thus, malnourishment induced a procoagulant state increased by infection. This is the first work that presents results of an exhaustive study of coagulation in malnourished hosts before and during an infection.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".