Renal and Hematological Effects of CLCF-1, a B-Cell-Stimulating Cytokine of the IL-6 Family
Bibliographic record
Abstract
CLCF-1 is a cytokine known for B-cell stimulation and for neurotrophic properties. We have identified CLCF-1 as a potential injurious factor in the human renal disease focal segmental glomerulosclerosis (FSGS). We investigated its effects on renal cells and renal function in in vitro and in vivo studies. Methods include measurement of the effect of CLCF-1 on phosphorylation of target molecules of the JAK/STAT pathway, on cytoskeleton and cell morphology in cultured podocytes, on albumin permeability of isolated rat glomeruli, and on tissue phosphorylation and urine albumin after acute or chronic CLCF-1 injection. In addition, cell sorting was performed to determine the presence of cells expressing CLCF-1 in spleen and bone marrow of normal mice and the effect of CLCF-1 infusion on splenic B-cell populations. CLCF-1 increased phosphorylation of STAT3 in multiple cell types, activated podocytes leading to formation of lamellipodia and decrease in basal stress fibers, increased glomerular albumin permeability, and increased STAT3 phosphorylation of peripheral blood cells and renal cortex. CLCF-1 increased urine albumin/creatinine ratio in mice and increased B-cell expression of IgG in mouse spleen. We conclude that CLCF-1 has potentially important systemic effects, alters podocyte function, and may contribute to renal dysfunction and albuminuria.
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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 | 0.001 |
| 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".