5 citations
,
February 2025 in “Frontiers in Immunology” Lactate is vital for skin health, influencing metabolism, the skin barrier, immune responses, and has therapeutic potential for skin disorders.
1 citations
,
January 2015 in “Hair transplant forum international” Strict regulations may slow down new LLLT treatments.
Hair movement can indicate hair quality and health.
7 citations
,
March 2023 in “The Journal of Biochemistry” LONRF1 is important for oxidative damage response and tissue remodeling during wound healing.
9 citations
,
January 2018 in “Dermatologic Therapy” The HairLux device safely and effectively promotes hair growth in people with hair loss.
47 citations
,
April 2012 in “Analytical and Bioanalytical Chemistry” 63 citations
,
February 2003 in “Australasian Journal of Dermatology” Global photography and phototrichogram techniques are the best current methods for measuring hair growth.
1 citations
,
March 2009 in “Hair transplant forum international” The TrichoScan method effectively measures hair growth and helps choose patients for hair restoration surgery.
Hair properties change under electromagnetic fields and are influenced by individual characteristics and the environment.
5 citations
,
January 2012 in “PubMed” A new method accurately measures finasteride levels in human plasma.
January 2018 in “Communications in computer and information science” Researchers developed a computer system to automatically diagnose hair loss by analyzing scalp images.
189 citations
,
January 2014 in “Journal of Visualized Experiments” Hair cortisol analysis effectively measures long-term stress.
2 citations
,
November 2020 in “Fertility Research and Practice” The survey helps identify menstrual irregularities and excess male hormones, aiming to detect conditions like Polycystic Ovary Syndrome.
January 2023 in “Zenodo (CERN European Organization for Nuclear Research)” March 2026 in “Folia Histochemica et Cytobiologica” LTBP1 is a key regulator in diseases and a potential target for new treatments.
October 2021 in “Journal of Investigative Dermatology” Skin changes in Pseudoxanthoma elasticum patients can indicate the severity of related health issues.
50 citations
,
February 2004 in “Genomics” A gene mutation causes lanceolate hair in rats by disrupting hair shaft integrity.
March 2025 in “Institutional Repositories DataBase (IRDB)” Hair cortisol can measure chronic stress but has inconsistent results.
2 citations
,
September 2020 in “bioRxiv (Cold Spring Harbor Laboratory)” The laser system helps study brain cell functions by precisely removing specific cells and observing changes.
January 2025 in “Dermatology Research and Practice” Higher activity in lichen planopilaris is linked to certain immune and tissue genes.
21 citations
,
January 2010 in “International Journal of Trichology” TrichoScan often makes mistakes and needs improvement for correct hair growth analysis.
February 2019 in “PubMed” The research found that twisting hair fibers can show changes in stiffness and damage, and help tell apart different hair treatments.
28 citations
,
May 2015 in “Molecular Neurobiology” LSD1 is crucial for regenerating hair cells in zebrafish.
April 2019 in “Journal of the Endocrine Society” Using LC-MS/MS for hormone measurement can prevent false high testosterone results and avoid unnecessary tests.
26 citations
,
April 2019 in “Genes” lncRNA XLOC_008679 and gene KRT35 affect cashmere fineness in goats.
32 citations
,
April 2015 in “British Journal of Dermatology” The hair shedding scale accurately identifies abnormal hair shedding in women with long hair, with grades 5 and 6 indicating excessive shedding.
22 citations
,
October 2004 in “Journal of Investigative Dermatology” The gene causing hair loss and heart issues in rough coat mice is still unknown.
18 citations
,
March 2015 in “Journal of Dermatological Case Reports” Rectangular black granules, solitary yellow dots, and mostly single-hair follicles suggest Loose Anagen Hair Syndrome.
2 citations
,
September 2023 in “JMIR. Journal of medical internet research/Journal of medical internet research” Machine learning can predict symptoms and quality of life in chronic skin disease patients using smartphone app data, and shows that app use varies with patient characteristics.