Balkan Endemic Nephropathy Risk Associates to the hs1.2 Ig Enhancer Polymorphism
Bibliographic record
Abstract
Balkan Endemic Nephropathy (BEN) is a kidney degenerative disease with a high incidence in the valleys of the Danube and tributary rivers. Many studies describe it as a multifactorial disease. Environmental as well immuno-inflammatory and genetic cofactors have been suggested to trigger the onset of the disease. Recently, high levels of C-reactive protein were demonstrated in BEN patients. We performed this study to evaluate the possible correlation of BEN with the polymorphism of the Ig heavy chain 3'Regulatory Region enhancer hsl.2 that is related to changes of consensus for trans activators binding within the DNA sequence and probably consequently autoimmune and inflammatory diseases. Therefore, we studied three cohorts: 1) 111 control subjects, 2) 95 BEN patients in dialysis therapy and 3) 133 components of a large family “J” in the same geographical area. The allelic frequencies of hsl.2 of BEN patients and family “J” components had similar decrease frequency of allele *1 and increase of allele *2 in respect to the controls. This trend suggests the association of allele *1 as a protective and allele *2 as a risk component for the disease. The presence of a consensus sequence for NF-Kb in the allele *2 may link the polymorphism to the inflammatory activity of BEN. This study supports the presence of an inflammatory pathway in BEN through the involvement of polymorphic enhancer hsl.2 influencing differently binding complexes and consequently the 3D structure of 3' Regulatory Region of IgH. Our work is the first study that clearly links BEN to a gene involved in the regulation of immune response.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".