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This study describes how shotgun proteomics can identify over 300 proteins in hair shafts, potentially allowing for the diagnosis of diseases through noninvasive human proteome sampling.

This study reported that machine learning analysis of protein profiles in hair segments achieved high accuracy in distinguishing women with non-suicidal self-injury disorder from healthy controls, suggesting hair proteomics as a promising non-invasive biomarker for stress-related psychopathology with potential clinical applications.

This study found that hair proteomics may serve as a promising, non-invasive biomarker source for stress-associated psychopathology, showing high accuracy in distinguishing patients with non-suicidal self-injury disorder from healthy controls.

This study found that the PLEE method increased hair protein extraction efficiency threefold and that bleaching hair reduced the coverage of keratin and associated proteins, leading to poorer hair quality, though it did not affect the overall protein identification.

This study discusses the proteomic profile associated with hair damage but does not report new experimental findings.