High-Throughput Phenotyping Methods for Quantifying Hair Fiber Morphology

November 2020 in “ bioRxiv (Cold Spring Harbor Laboratory) ”

Tina Lasisi, Arslan Zaidi, Timothy H. Webster, Nicholas B. Stephens, Kendall Routch, Nina G. Jablonski, Mark D. Shriver

hair fiber morphology longitudinal morphology cross-sectional morphology human scalp hair phenotyping methods

Preprint — not peer reviewed. This was posted to a preprint server or data repository. It has not been through a journal's review process, and its findings may change or not hold up.

Studysummary This study introduced a new high-throughput method for analyzing scalp hair morphology and found that quantifying hair form provides more accurate information than traditional classification based on racial categories, challenging the belief that cross-sectional morphology predicts hair curvature.

Automatically generated from the study's abstract, not written by a person, and not a review of the full paper. Not medical advice or a treatment recommendation. Read the original study, and consult a qualified healthcare professional before changing treatment. Full disclaimer

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