January 2024 in “Wiadomości Lekarskie” The ABI1 gene contributes to prostate cancer progression and treatment resistance.
March 1999 in “Hair transplant forum international” The document's conclusion cannot be determined from the provided text.
3 citations
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November 2017 in “PubMed” Alopecia areata progression is linked to stress and hormone changes, suggesting new treatment targets.
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December 2013 in “Journal of Investigative Dermatology Symposium Proceedings” A new mouse model helps understand and find treatments for alopecia areata.
The model accurately diagnoses hair diseases with 95% accuracy using deep learning.
July 2018 in “Hair transplant forum international” The document's content couldn't be processed to provide a conclusion.
May 2018 in “Hair transplant forum international” The document's content couldn't be processed to provide a conclusion.
March 2018 in “Hair transplant forum international” The document's content couldn't be processed to provide a conclusion.
September 2018 in “Hair transplant forum international” The document's content couldn't be processed to provide a conclusion.
January 2024 in “International Journal of Dermatology” Targeting Interleukin-13 could help treat alopecia areata linked with atopic dermatitis.
45 citations
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May 2024 in “International Journal of Molecular Sciences” Alopecia areata is caused by immune attacks on hair follicles, affecting hair growth and quality of life.
January 2026 in “European Journal of Dermatology” Understanding alopecia is crucial to improving care and addressing hair loss concerns.
September 2023 in “Medicine” The research suggests immune system changes and specific gene expression may contribute to male hair loss, proposing potential new treatments.
114 citations
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August 2002 in “Journal of Investigative Dermatology” Alopecia areata is caused by an immune response, and targeting immune cells might help treat it.
April 2017 in “The journal of investigative dermatology/Journal of investigative dermatology” Researchers found three different ways drugs work to treat hair loss from alopecia areata and identified key factors for personalized treatment.
The model accurately classifies hair conditions with 97% accuracy.
60 citations
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January 1987 in “Dermatology” Alopecia areata may appear differently depending on the individual's type of hair loss and scalp condition.
June 2025 in “British Journal of Dermatology” Certain hair and scalp features can predict the severity of alopecia areata.
January 2025 in “International Journal of Pharma Medicine and Biological Sciences” DP cells interact with immune cells, possibly causing hair loss in Alopecia Areata.
October 1993 in “Proceedings of The Nutrition Society”
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January 2020 in “Experimental Dermatology” The document concludes that understanding and treatments for alopecia areata have significantly advanced, now recognizing it as an autoimmune disorder.
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December 2014 in “Journal of Biomedical Informatics” Researchers created LabeledIn, a detailed list of drug uses, showing the importance of human input in making such lists.
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December 2016 in “British journal of dermatology/British journal of dermatology, Supplement” Cancer patients treated with immune checkpoint inhibitors may develop alopecia, but some hair regrowth is possible with treatment.
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July 2021 in “Anais brasileiros de dermatologia/Anais Brasileiros de Dermatologia” Interleukin levels are higher in alopecia areata patients but don't predict disease severity or duration.
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October 2006 in “European Journal of Immunology” The CD44-CD49d complex boosts T cell activation and survival in autoimmune disease.
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July 2017 in “Skin appendage disorders” Alfredo Rebora suggests a simpler classification for hair loss and a new test for easier diagnosis.
The document cannot be understood or processed.
4 citations
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November 1996 in “Hair transplant forum international” The document could not be processed for a summary.
May 1997 in “Hair transplant forum international” The document's conclusion cannot be summarized because the content is not accessible.
June 2013 in “The mental health clinician” Large data can lead to new medical discoveries and personalized medicine.