Latitude, sunshine, and human lactase phenotype distributions may contribute to geographic patterns of modern disease: the inflammatory bowel disease model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Countries with high lactase nonpersistence (LNP) or low lactase persistence (LP) populations have lower rates of some "western" diseases, mimicking the effects of sunshine and latitude. Inflammatory bowel disease (IBD), ie, Crohn's disease and ulcerative colitis, is putatively also influenced by sunshine. Recent availability of worldwide IBD rates and lactase distributions allows more extensive comparisons. The aim of this study was to evaluate the extent to which modern day lactase distributions interact with latitude, sunshine exposure, and IBD rates. National IBD rates, national distributions of LP/LNP, and population-weighted average national annual ultraviolet B exposure were obtained, estimated, or calculated from the literature. Negative binomial analysis was used to assess the relationship between the three parameters and IBD rates. Analyses for 55 countries were grouped in three geographic domains, ie, global, Europe, and non-Europe. In Europe, both latitude and ultraviolet B exposure correlate well with LP/LNP and IBD. In non-Europe, latitude and ultraviolet B exposure correlate weakly with LP/LNP, but the latter retains a more robust correlation with IBD. In univariate analysis, latitude, ultraviolet B exposure, and LP/LNP all had significant relationships with IBD. Multivariate analysis showed that lactase distributions provided the best model of fit for IBD. The model of IBD reveals the evolutionary effects of the human lactase divide, and suggests that latitude, ultraviolet B exposure, and LP/LNP mimic each other because LP/LNP follows latitudinal directions toward the equator. However, on a large scale, lactase patterns also follow lateral polarity. The effects of LP/LNP in disease are likely to involve complex interactions.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it