30 citations
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May 2016 in “Expert Opinion on Biological Therapy” This review discusses immune pathways involved in alopecia areata and explores emerging, more targeted therapeutic strategies, noting their potential for better safety and effectiveness compared to traditional immune suppressants.
4 citations
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May 2025 in “Frontiers in Immunology” This review examines the mechanisms of Janus kinase inhibitors in treating alopecia areata and evaluates their efficacy and safety, but reports no new clinical results.
November 2025 in “Open Repository of the University of Porto (University of Porto)” Pharmacists play a crucial role in customizing treatments and ensuring medication safety.
11 citations
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July 2022 in “Frontiers in immunology” This study reports that the global age-standardized incidence and disability-adjusted life-year rates of alopecia areata decreased from 1990 to 2019, with the highest increases in incidence seen in some low SDI regions and countries like Kuwait and South Sudan.
1 citations
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January 2026 in “Frontiers in Cell and Developmental Biology” This study reviews the transformative role of artificial intelligence in biomaterial design, highlighting its ability to reduce costs through virtual screening, enhance material performance, and predict biological interactions to advance personalized and precision medicine.
This study found that patients with androgenetic alopecia showed distinct scalp bacterial imbalances compared to healthy individuals, which were associated with unhealthy lifestyles. These microbial changes might contribute to follicular inflammation, potentially accelerating hair loss in these patients.
January 2026 in “Frontiers in Drug Discovery” This study highlights that while advances in dermatology, such as biologics and JAK inhibitors, have improved treatments for conditions like atopic dermatitis and psoriasis, challenges remain, including issues with lasting efficacy and the need for more personalized therapies.
January 2025 in “Bright Sky Publications eBooks” This abstract presents the book "Buy Medical Physics in Aesthetic Medicine," which explores future innovations and techniques for cosmetic procedures expected in 2025, though specific findings or results from the book are not reported.
February 2024 in “bioRxiv (Cold Spring Harbor Laboratory)” This study found that certain tandem repeats predict darker hair color across diverse ancestry groups and can contribute to a polygenic score for hair color, independent of SNP variation.
November 2025 in “Communications Biology” The researchers reported creating a Human Hair Atlas that maps over 1200 molecular species in hair, revealing up to 50% variation in metabolite and lipid levels along the hair's length, and identified 122 exposome-related compounds from personal care products.
October 2025 in “International Journal of Innovative Research in Technology” This review examines the evidence on nutritional and herbal supplements for women's health, emphasizing the need for more long-term studies to develop evidence-based guidelines for personalized supplementation.
July 2026 in “Postgraduate Medicine” Results are not reported in this commentary, but it discusses the influence of different control group choices—an active-comparator versus non-drug users—on measuring depression risk in studies of 5-alpha reductase inhibitors.
3 citations
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November 2024 in “Acta Dermato Venereologica” This study found that online materials about alopecia areata and its treatments are generally difficult to understand, with information on JAK inhibitors being particularly challenging, highlighting a need for clearer educational resources for patients.
January 2024 in “Skin appendage disorders” This study compared the effectiveness of topical finasteride, oral finasteride, and topical minoxidil over 12 months in postmenopausal women with androgenetic alopecia, exploring their therapeutic effects on this population. Results are not reported in the abstract.
29 citations
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November 2022 in “Nature Medicine” This study identified thousands of variant-metabolite associations in the human plasma metabolome, offering insights into the genetic bases of metabolism and potential adverse drug effects.
7 citations
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September 1991 in “PubMed” This study found that 2 percent topical minoxidil significantly increased nonvellus hair count and showed moderate regrowth compared to placebo in women with mild to moderate androgenetic alopecia, although participants did not notice the difference.
2 citations
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March 2022 in “PubMed” This review concludes that oral nutraceuticals like Nutrafol® and Viviscal® modestly promote hair growth in individuals with androgenetic alopecia and might be considered as supplementary treatments.
March 2026 in “Journal of the American Academy of Dermatology” This clinical review evaluates current evidence on various adjunctive therapies for androgenetic alopecia, highlighting modest benefits for some interventions but emphasizing significant gaps and the need for rigorous, high-quality research to guide effective management strategies.
4 citations
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March 2024 in “Forensic Sciences Research” This review found that current forensic DNA phenotyping panels for biogeographical ancestry and visible traits face significant limitations due to inconsistencies in terminology, genetic understanding, and genotyping technologies, highlighting the need for harmonization and further research.
October 2024 in “Journal of the European Academy of Dermatology and Venereology” This study reported that ritlecitinib 50 mg and baricitinib 4 mg showed similar efficacy in treating severe alopecia areata, with no significant difference in hair regrowth outcomes at Week 24, but there remains considerable uncertainty and a need for further research.
February 2026 in “Archiv Euromedica” In this narrative review, researchers reported that oral finasteride significantly improved hair count and density in male androgenetic alopecia but had higher systemic exposure and potential side effects compared to topical formulations, which provided similar efficacy with lower systemic DHT suppression.
August 2025 in “Aesthetic Plastic Surgery” This review explores the mechanisms, current products, challenges, and innovative approaches related to cosmetics for hair loss prevention and growth promotion, emphasizing the need for multidisciplinary cooperation to enhance product development and market success.
August 2025 in “Drug Design Development and Therapy” This review article examines current drugs for androgenetic alopecia, focusing on their mechanisms and clinical efficacy, noting that while finasteride and minoxidil are commonly approved treatments, new drugs targeting different pathogenic pathways have emerged, offering a broader understanding and reference for AGA treatment options.
September 2025 in “The Journal of Clinical Psychiatry” Current evidence reviewed in this study indicates that finasteride, a drug for hair loss, can cause depression and suicidality, with delayed recognition partly due to insufficient post-approval pharmacovigilance by manufacturers and regulators.
37 citations
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August 2020 in “BMC Genomics” This study found that while genetic variants contribute minimally to predicting hair greying in a Polish population, age remains the primary predictor, underscoring the complexity of hair greying as a genetic trait.
1 citations
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November 2022 in “Nutrients” This study found that piglets' rapid growth during nursery and lactation was linked to changes in microbiota composition and increased cortisol conversion, highlighting critical early life factors influencing adult microbiota establishment.
2 citations
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March 2023 in “Biomedicine & pharmacotherapy” This study found that platelet lysate significantly improved hair growth and follicle performance in both experimental settings and AGA patients, showing results comparable to platelet-rich plasma.
April 2026 in “BioNanoScience” A new microneedle system may improve hair loss treatment by delivering ketoconazole directly to hair follicles.
March 2025 in “Dermatology” Systemic therapies improve nail psoriasis but have high side effects; more research is needed.
79 citations
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July 2022 in “Sensors” In this study, researchers evaluated various machine learning models for predicting type 2 diabetes risk, finding that Random Forest and K-NN models performed best in terms of precision, recall, accuracy, and other metrics using common symptoms as features.