Identification and characterization of lipases from<i>Malassezia restricta</i>, a causative agent of dandruff
Bibliographic record
Abstract
Dandruff, a skin disorder affecting 50% of the world population, is linked with proliferation of lipophilic yeasts of the genus Malassezia (particularly Malassezia globosa and M. restricta). Most Malassezia species show a unique lipid dependency and require external lipids for growth. Genome mining of the incomplete M. restricta genome led to the identification of eight lipase sequences. Sequences representing the class 3 and LIP lipase families were used to clone the lipases MrLip1, MrLip2 and MrLip3, recombinantly expressed in Pichia pastoris, and tested for their activity using mono-, di- and triacylglycerol substrates. Hydrolysis by the M. restricta lipase MrLip1 and MrLip2 (family class 3) was limited to the mono- and diacylglycerol, while MrLip3 (family LIP) hydrolyzed all three substrates. This result confirms that Malassezia family LIP lipases are responsible for the hydrolysis of triacylglycerols, the main component of human sebum. Furthermore, the information regarding lipases from M. restricta presented here might aid in the search for anti-dandruff agents.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".