The mouse Char10 locus regulates severity of pyruvate kinase deficiency and susceptibility to malaria
Bibliographic record
Abstract
Pyruvate kinase (PKLR) deficiency protects mice and humans against blood-stage malaria. Although mouse strain AcB62 carries a malaria-protective PklrI90N genetic mutation, it is phenotypically susceptible to blood stage malaria induced by infection with Plasmodium chabaudi AS, suggesting a genetic modifier of the PklrI90N protective effect. Linkage analysis in a F2 cross between AcB62 (PklrI90N) and another PK deficient strain CBA/Pk (PklrG338D) maps this modifier (designated Char10) to chromosome 9 (LOD = 10.8, 95% Bayesian CI = 50.7-75Mb). To study the mechanistic basis of the Char10 effect, we generated an incipient congenic line (Char10C) that harbors the Char10 chromosome 9 segment from AcB62 fixed on the genetic background of CBA/Pk. The Char10 effect is shown to be highly penetrant as the Char10C line recapitulates the AcB62 phenotype, displaying high parasitemia following P. chabaudi infection, compared to CBA/Pk. Char10C mice also display a reduction in anemia phenotypes associated with the PklrG338D mutation including decreased splenomegaly, decreased circulating reticulocytes, increased density of mature erythrocytes, increased hematocrit, as well as decreased iron overload in kidney and liver and decreased serum iron. Erythroid lineage analyses indicate that the number of total TER119+ cells as well as the numbers of the different CD71+/CD44+ erythroblast sub-populations were all found to be lower in Char10C spleen compared to CBA/Pk. Char10C mice also displayed lower number of CFU-E per spleen compared to CBA/Pk. Taken together, these results indicate that the Char10 locus modulates the severity of pyruvate kinase deficiency by regulating erythroid responses in the presence of PK-deficiency associated haemolytic anemia.
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 | 0.000 | 0.001 |
| 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) | 0.000 | 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".