April 2023 in “Journal of Investigative Dermatology” The research updated the skin cell profile, finding new skin cell markers and showing fibroblasts' key role in skin health.
34 citations
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March 2009 in “Journal of Investigative Dermatology” Proteomic analysis can identify genetic differences in mouse hair, helping understand hair defects and variations.
2 citations
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December 2019 in “Bioanalysis” Accurate quantitative bioanalysis using LC-MS/MS is challenging due to matrix effects, but using internal standards and new methods like in-sample calibration could improve results.
December 2022 in “Research Square (Research Square)” The QuantAnts machines can find cancer markers and create CRISPR targets for them.
7 citations
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January 2005 in “Dermatology” A new method for studying hair follicles is easier and more precise, useful for hair loss and cancer treatment research.
75 citations
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March 2007 in “Journal of Biological Chemistry” QSOX enzymes help form protein bonds in cells, especially in tissues with high secretory activity.
1 citations
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June 2012 in “OhioLink ETD Center (Ohio Library and Information Network)” A new 3-D bioreactor system improves drug screening and reduces animal testing.
Keratin peptide signatures in hair may help identify gender and ethnicity.
June 2024 in “Journal of medicinal chemistry” A new AI-driven method shows promise for treating hair loss with a peptide-based drug.
4 citations
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May 2017 in “Data in Brief” Five molecular elements identified as potential future targets for hair loss therapy.
January 2026 in “OSF Preprints (OSF Preprints)” This paper introduces a comprehensive therapeutic framework for androgenetic alopecia (AGA) that combines PROTAC-mediated androgen receptor (AR) degradation with regenerative and micro-environmental strategies. It highlights GT20029 as a topical AR-PROTAC and compares AR degradation with antagonism. The study also explores early-intervention models based on genetic predisposition and pre-miniaturization biomarkers. The framework integrates stem-cell biology, dermal papilla senescence, perifollicular fibrosis, and niche-engineering into a three-phase protocol: stabilization, reversal, and maintenance. Additionally, it proposes a development timeline for therapies and testable hypotheses to guide future research and clinical applications in AGA.
July 2025 in “PNAS Nexus” A new tool accurately identifies human cornea cell states and key factors.
Machine learning improves DNA predictions for eye and hair color, but challenges remain for skin tone and facial features.
8 citations
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August 2020 in “PLOS Computational Biology” A machine learning model called CATNIP can predict new uses for existing drugs, like using antidepressants for Parkinson's disease and a thyroid cancer drug for diabetes.
January 2026 in “Metabolites” This study investigates the molecular connections between obesity and immune vulnerability by analyzing gene expression profiles across various tissues, including liver, skeletal muscle, blood, and adipose tissues. The research identifies differentially expressed genes (DEGs) and highlights the significant roles of RPL15 and RBM39 genes. It finds that cancer, particularly leukemia, lymphoma, and gastric cancer, is strongly associated with obesity. The study also reveals a host-pathogen interaction network with Influenza A virus showing the highest interaction. Key metabolites common across tissues include 2-Oxoglutarate, Adenosine, Succinate, and D-mannose. The findings suggest a link between obesity and immune-related processes, with potential overlaps in pathways related to viral infections, cytokine signaling, and insulin metabolism, indicating a possible interaction between immune and metabolic processes in obese individuals. Further experimental validation is needed to confirm these relationships.
31 citations
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October 2016 in “PLoS ONE” The ubiquitin-mediated proteolysis pathway is crucial for hair follicle development in cashmere goats.
April 2026 in “Zenodo (CERN European Organization for Nuclear Research)” The package offers tools for exploring potential miRNA changes in female hair loss.
July 2024 in “Frontiers in Microbiology” Data-driven methods can help understand microbiota's role in diseases and develop personalized treatments.
8 citations
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February 2025 in “Cell Systems” Engineered bacteria can deliver antioxidants to protect skin.
November 2022 in “Journal of Investigative Dermatology” A new tool helps study hair follicle cells to develop better treatments for hair disorders.
68 citations
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August 2014 in “PeerJ” Human hair proteins vary by individual, body site, and ethnicity, useful for forensics.
January 2025 in “PROTEOMICS” Drug repositioning is a promising way to quickly develop new treatments, especially for rare diseases.
June 2013 in “The mental health clinician” Large data can lead to new medical discoveries and personalized medicine.
2 citations
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December 2024 in “Journal of Cosmetic Dermatology” SNP profiling allows personalized skincare treatments for better results and fewer side effects.
17 citations
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October 2021 in “Cellular & Molecular Biology Letters” New biomarkers and potential treatments for skin diseases were identified.
158 citations
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January 2015 in “Artificial Intelligence in Medicine” DrugNet effectively identifies new uses for existing drugs and may save resources in drug development.
14 citations
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June 2021 in “British Journal of Dermatology” The BIOMAP glossary standardizes data to improve research on atopic dermatitis and psoriasis.
April 2026 in “Zenodo (CERN European Organization for Nuclear Research)” The study provides exploratory findings on miRNA changes in female hair loss.