research Alopecia areata − animal models
Alopecia areata is influenced by genetics and immune system factors, and better understanding could improve treatments.
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research Characterisation of Myotonic Dystrophy type I cell models and drug evaluation by a cell- based quantification platform.
Antisense oligonucleotides show promise for treating Myotonic Dystrophy type I.
research Mouse Hair Cycle Expression Dynamics Modeled as Coupled Mesenchymal and Epithelial Oscillators
The study concluded that hair growth in mice is regulated by a stable interaction between skin cell types, and disrupting this can cause hair loss.
research A flexible fixed-sequence testing method for hierarchically ordered correlated multiple endpoints in clinical trials
The flexible fixed-sequence testing method allows for more effective evaluation of multiple goals in a clinical trial while controlling the risk of false positives.
research Some progress in global existence of solutions to a higher-dimensional chemotaxis system modelling Alopecia Areata
The system can have a stable solution under certain conditions, helping understand hair loss in Alopecia Areata.
research Incidence of alopecia in brain tumour patients treated with pencil scanning proton therapy and validation of existing NTCP models
A standardized scoring system is needed to improve model reliability for predicting hair loss in brain tumor patients treated with proton therapy.
research Decision letter: Dynamics of nevus development implicate cell cooperation in the growth arrest of transformed melanocytes
Moles may stop growing due to cell cooperation, not just because of individual cell aging.
research Predictive Skin Permeation of Ethinylestradiol,α-Asarone,Finasteride and Risperidone
The Potts-Guy model best predicts skin permeability for the tested drugs.
research Group-ICA Model Order Highlights Patterns of Functional Brain Connectivity
Choosing the right model order in brain connectivity analysis can affect the detection of differences between healthy individuals and those with seasonal affective disorder.
research Genetic prediction of male pattern baldness
Genetic factors can help predict male pattern baldness risk.
research Complex genetic dependencies among growth and neurological phenotypes in healthy children: Towards deciphering developmental mechanisms
Genetic factors influence growth and brain development in children.
research QSAR Analysis of a Series of Hydantoin‐based Androgen Receptor Modulators and Corresponding Binding Affinities
Researchers developed reliable models to predict how well certain compounds bind to androgen receptors, emphasizing the importance of atomic electronegativity.
research Modeling of ionizing radiation induced hair follicle regenerative dynamics
Hair follicles can regenerate after radiation damage but not during a specific growth phase.
research Experimental Models and Molecular Pathogenesis: An Integrated Review of Alopecia
Current models for studying alopecia are inadequate, and more human-like systems are needed.
research Global and exponential stabilization of a chemotactic alopecia areata model with signal-dependent diffusion and sensitivity
Reducing CD8+ T cell growth can stabilize alopecia areata.
research Forensic DNA Phenotyping
Forensic DNA Phenotyping accurately predicts physical traits and is used in investigations, but needs more diverse population data for confirmation.
research Evaluation of DNA Variants Associated with Androgenetic Alopecia and Their Potential to Predict Male Pattern Baldness
DNA variants can predict male pattern baldness, with higher risk scores increasing baldness likelihood.
research A modular modeling approach for investigating wool critical buckling from biologically variable along-fiber microstructure
The model helps understand how wool fiber structure affects its strength and flexibility.
research A Comprehensive Review of Alopecia Areata Detection Using Self-Supervised Auto ML Models: Systematic Insights and Emerging Challenges
AI models are effective for detecting alopecia areata but face challenges like explaining results and data bias.
research The cycling hair follicle as an ideal systems biology research model
The hair follicle is a great model for research to improve hair growth treatments.
research Animal Models of Psoriasis – What Can We Learn from Them?
Rodent models helped understand psoriasis but none perfectly replicated the disease.
research A use-and-transformation model for evaluating public R&D: Illustrations from polycystic ovarian syndrome (PCOS) research
The document suggests a new model for evaluating public research that better captures the full value of knowledge creation and use, using PCOS research as an example.
research Prediction of therapeutic outcomes of female pattern hair loss patients based on clinical features with application of artificial intelligence
Artificial intelligence can accurately predict hair growth and treatment results in female pattern hair loss patients, with age of onset and duration being key factors.
research Developmental Mechanisms Controlling Cell Fate, Evolution of
The conclusion is that grasping how cells determine their roles through evolution is key, with expected progress from new research models and genome editing.
research BaldPredict: AI-Driven Prediction Model for Alopecia Areata
AI can improve alopecia areata diagnosis with high accuracy.
research An Expert System for Clinical Risk Assessment of Polycystic Ovary Syndrome under Uncertainty
The document concludes that the new expert system can assess the risk of PCOS effectively despite uncertainties in diagnosis.
research Biomechanics of hair fibre growth: A multi-scale modeling approach
The model shows that factors like follicle shape and stiffness are key for hair growth and anchoring.
research Forensic DNA phenotyping: a review on SNP panels, genotyping techniques, and prediction models
Forensic DNA phenotyping faces challenges like inconsistent terms and limited genetic knowledge.
research Identification of Stress-Related Hair Loss and Prevention Through the Application of a KNN Model Based on Machine Learning
Machine learning can predict stress-related hair loss and suggest prevention tips.
research 706 Predictive modeling of patient response to JAK/STAT inhibitors and dynamic patient-matching
Machine learning can predict how well patients with alopecia areata will respond to certain treatments.