<i>In vivo</i> quantitative analysis of the effect of hydration (immersion and Vaseline treatment) in skin layers using high‐resolution MRI and magnetisation transfer contrast<sup>*</sup>
Bibliographic record
Abstract
BACKGROUND/AIMS: Many claims are made as to the efficacy of topical preparations in moisturising the skin, yet most of these claims cannot be substantiated by scientific study for the skin layers beneath the stratum corneum, and yield no information on the remainder of the epidermis and dermis. This argues for an in vivo quantitative method for measuring the effect of water loading extended to various layers of the skin. METHODS: Detailed high-resolution in vivo MRI studies of hydration and dehydration of finger pad skin layers were conducted on one normal subject using two moisturisation methods (topical white soft paraffin (Vaseline) and water immersion). The dehydration study was carried out immediately following removal from prolonged skin moisturisation. Inter-individual variability for skin hydration (group study) was studied in seven healthy volunteers at 0 and 7 h hydration with Vaseline. Location dependence in skin hydration was investigated on the same subject by looking into the hydration of forearm and finger pad skin. System stability and measurement reproducibility was verified through a detailed phantom study. RESULTS: Images of normal and hydrated human skin were obtained in vivo at voxel dimensions of 50 micromx150 micromx1000 microm. The effect of hydration and dehydration as a function of exposure to moisturiser (i.e. water and Vaseline) on the image signal intensity, observed T1, and interaction of free and bound water in specific tissues were identified and correlated with existing physiological knowledge. Swelling of stratum corneum due to hydration was expressed as an in vivo model of tissue hydration. CONCLUSION: Results of the dehydration study showed that the changes due to the previous hydration of the skin are reversible for all skin layers. For both moisturisation methods (i.e. Vaseline and skin bathing), the effects of hydration and dehydration on the skin were similar. The trends of the MRI parameters for finger pad and arm skin were similar. The group study showed low inter-subject variability of hydration on stratum corneum and epidermis.
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 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 | 0.000 | 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) | 0.001 | 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".