Protease activity, localization and inhibition in the human hair follicle
Bibliographic record
Abstract
OBJECTIVE: In humans, the process of hair shedding, referred to as exogen, is believed to occur independently of the other hair cycle phases. Although the actual mechanisms involved in hair shedding are not fully known, it has been hypothesized that the processes leading to the final step of hair shedding may be driven by proteases and/or protease inhibitor activity. In this study, we investigated the presence of proteases and protease activity in naturally shed human hairs and assessed enzyme inhibition activity of test materials. METHODS: We measured enzyme activity using a fluorescence-based assay and protein localization by indirect immunohistochemistry (IHC). We also developed an ex vivo skin model for measuring the force required to pull hair fibres from skin. RESULTS: Our data demonstrate the presence of protease activity in the tissue material surrounding club roots. We also demonstrated the localization of specific serine protease protein expression in human hair follicle by IHC. These data provide evidence demonstrating the presence of proteases around the hair club roots, which may play a role during exogen. We further tested the hypothesis that a novel protease inhibitor system (combination of Trichogen) and climbazole) could inhibit protease activity in hair fibre club root extracts collected from a range of ethnic groups (U.K., Brazil, China, first-generation Mexicans in the U.S.A., Thailand and Turkey) in both males and females. Furthermore, we demonstrated that this combination is capable of increasing the force required to remove hair in an ex vivo skin model system. CONCLUSION: These studies indicate the presence of proteolytic activity in the tissue surrounding the human hair club root and show that it is possible to inhibit this activity with a combination of Trichogen and climbazole. This technology may have potential to reduce excessive hair shedding.
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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 | 0.000 |
| 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".