September 2022 in “Journal of Investigative Dermatology” Patient-reported outcomes better reflect the quality of life impact of alopecia areata than traditional severity scores.
1 citations
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April 2022 in “Dermatologic Surgery” The Progressive Loss Risk Scale is a system that shows the long-term risks of hair restoration surgery, which can change based on factors like age and transplant area.
50 citations
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February 2004 in “Genomics” A gene mutation causes lanceolate hair in rats by disrupting hair shaft integrity.
82 citations
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July 2012 in “Brain pathology” High LGR5 levels in glioblastoma indicate poor prognosis and are essential for cancer stem cell survival.
1 citations
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June 1998 in “Journal of Forestry Research” Mammalian hair scales change from smooth to wavy due to friction.
5 citations
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November 2022 in “Genetics selection evolution” Low-coverage sequencing is a cost-effective way to find genetic factors affecting rabbit wool traits.
April 2023 in “Journal of Investigative Dermatology” A new pain-measuring system using sensors and AI can effectively detect pain in mice, which may help assess pain in humans and develop treatments.
March 2026 in “Mendeley Data” rwSALT provides precise hair regrowth measurement from scalp photos.
A new method allows detailed, continuous imaging of crustacean leg regeneration without harming the cells.
86 citations
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January 2020 in “British Journal of Dermatology” The AA-IGA scale reliably measures treatment success in alopecia areata by considering both clinician and patient views.
April 2013 in “The Journal of Urology” Researchers created a simple tool to predict bladder blockage from prostate enlargement using urine flow rate and prostate volume.
October 2023 in “The Journal of Dermatology” The HSVS-A is an effective tool for quickly screening hair shedding in Asian women.
24 citations
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June 2021 in “Journal of the European Academy of Dermatology and Venereology” Use specific tools to measure quality of life in alopecia areata patients and improve future treatments.
July 2023 in “Dermatology practical & conceptual” The machine learning model effectively assesses the severity of hair loss and could help dermatologists with treatment decisions.
4 citations
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June 2022 in “Clinical, cosmetic and investigational dermatology” The new SFS Scale predicts hair transplant difficulty using hair and skin types, with thick skin and coily hair being hardest to work with.
The curly mutation in SELH/Bc mice affects hair and may help study human genetic disorders.
1 citations
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April 2015 in “The FASEB Journal” Blocking androgens in male rats increased estrogen and made them more active.
2 citations
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June 2019 in “International Journal of Dermatology” The modified hair loss classification is more detailed but less user-friendly.
November 2020 in “Journal of The American Academy of Dermatology” Ankle braces reduce motion, while external focus improves hip and knee movements.
9 citations
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July 2010 in “British Journal of Dermatology” The document suggests a rare skin condition might be caused by a genetic phenomenon.
2 citations
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November 2023 in “Skin Research and Technology” RCM and dermoscopy help identify different types of hair loss in children.
5 citations
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December 2023 in “Current Biology” A feedback loop between LRH and RSL4 controls root hair growth in Arabidopsis.
March 2026 in “Mendeley Data” rwSALT accurately measures hair regrowth in alopecia areata using scalp photos.
1 citations
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January 2023 in “Annals of Dermatology” The BASP classification helps predict patient behavior and improve treatment for hair loss.
January 2000 in “The Mouseion at the JAXlibrary (Jackson Laboratory)” The lanceolate hair-J mutation in mice helps understand human hair disorders like Netherton's syndrome.
105 citations
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October 2018 in “Nature” A small group of slow-growing cells causes basal cell carcinoma to return after treatment.
3 citations
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October 2017 in “Journal of Cosmetic Dermatology” Dr. Muhammad Ahmad created a hair classification system to help improve hair restoration surgery outcomes.
November 2009 in “Hair transplant forum international” Dr. Bernard Cohen created a new system to classify hair loss using numbers and a detailed scalp map.
5 citations
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May 2018 in “Statistics in Medicine” Model improves accuracy in predicting hair loss effects.
18 citations
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September 2024 in “Journal of the European Academy of Dermatology and Venereology” The DLQI is a key tool for measuring quality of life in dermatology.