Raman spectral variation for human fingernails of postmenopausal women is dependent on fracture risk and osteoporosis status
Bibliographic record
Abstract
Patients diagnosed with osteoporosis have reported loss of fingernail resilience as the disease progresses. Keratin is the predominant protein in human nail tissue, and its structure has been postulated to be different in fingernails clipped from subjects who have sustained fragility fractures and those who have not, which may offer a window into the donor's bone health. This study was designed to qualify these differences, which may lead to the development of a novel screening tool for fracture risk. Raman spectroscopy was used to measure the fingernails of 633 postmenopausal women who presented at six fracture clinics located across the UK and Ireland. The Raman signals from donor's fingernails were compared between (1) fracture and nonfracture and (2) osteoporotic versus non‐osteoporotic donors The data presented show differences in the protein changes observed for pervasive osteoporosis compared to a general increased risk of fragility fracture. For fracture risk, compositional changes falling into broad classes of amino acid residue (aliphatic, aromatic, acidic, amide and sulphurous) were observed, while a difference in disulphide bonding levels was reaffirmed. For pervasive osteoporosis, the disulphide mode suggested increasing disorder in disulphide bonding orientation. Fractures were associated with a transition from alpha helical secondary structure to random, while the pervasive osteoporosis cases were associated with a transition to beta sheet structure. General fracture risk is associated with a change in the structure and composition of the keratin protein. Osteoporosis is associated with different protein structural changes and an increase in free acid groups. Copyright © 2017 John Wiley & Sons, Ltd.
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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 | 0.000 |
| 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) | 0.002 | 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".