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This research presents the Dodatek A model, elaborating on androgen function through new mathematical indices and methodological improvements, shifting focus from serum hormone concentrations to system interactions to better describe androgen activity comprehensively.

This study presents a follicular automaton model that simulates human hair cycle dynamics and can reproduce hair patterns similar to diffuse or androgenetic alopecia by incorporating spatially heterogeneous parameters and follicle miniaturization.

This study introduced Neurospectrum, a framework that effectively identifies meaningful neural dynamics by encoding neural activity into latent trajectories, and reported that it outperformed traditional methods in tracking synchronization, reconstructing stimuli, and identifying fMRI biomarkers in various datasets.

This study found that GoogLeNet outperformed other CNN models in accurately identifying the type of folliculitis.

This study developed the CATNIP computational model, which uses biological and chemical information to successfully identify drug repurposing opportunities for various conditions, including Parkinson’s disease and Type 2 Diabetes.

This study found that a stochastic follicular automaton model replicates hair follicle cycle fluctuations, with deterministic simulations aligning with steady-state levels as follicle numbers increase.

This study found that a lightweight Convolutional Neural Network model can accurately and quickly determine natural hair tone from high-resolution images of hair roots, outperforming other popular methods.

This study found that the DNN-DTIs prediction model achieved high accuracy in predicting drug-target interactions, suggesting its potential application in drug repositioning and the discovery of new uses for existing drugs.

This source establishes prior art for treating androgenic alopecia and sexual dysfunction by restoring gap-junction-mediated connectivity in tissue networks, highlighting a mechanism independent of commonly targeted pathways.

This study found that the WNMFDDA model effectively predicts drug-disease associations, achieving high accuracy in cross-validation and confirming most candidate associations through existing databases.

In this study, researchers developed a mathematical model of outer hair cell hair bundles that replicates experimental responses to mechanical stimuli, providing insights into the stimulus-dependent adaptation mechanisms and the functional significance of their three-row stereocilia configuration in mammalian hearing.

This paper argues that the cycling hair follicle serves as a valuable model for systems biology research, highlighting its potential for translational medicine.

The researchers reported that differences in brain functional connectivity between unmedicated seasonal affective disorder patients and healthy controls vary with ICA model order, peaking in volume at model order 70.

This study developed a tissue-engineered model of innervated skin, allowing for examination of how epidermis and capillaries affect nerve growth and offering a tool for further research on skin-related processes.

This study developed a follicular automaton model that simulates human hair cycle dynamics and can replicate hair pattern changes associated with diffuse or androgenetic alopecia.

This study evaluates a framework using neural networks and machine learning techniques to classify and detect Alopecia Areata from hair images, aiming for accurate differentiation between healthy hair and the condition.

In this study, researchers developed an in vitro airway-organoid model using human lung-derived cell lines on RADA16-I hydrogels to serve as a potential tool for studying adenovirus isolation, pathogenesis, and antiviral drug screening.

In this research, investigators used in vitro models to study the Merkel cell-neurite complex and reported that mechanical stimulation, similar to gentle touch, can induce molecular changes that are potentially relevant to hair growth, thus contributing to the understanding of its underlying mechanisms.

This study found that gap junctional communication influences feather patterning by modulating Turing-type activator-inhibitor systems in chicken skin, suggesting its role in propagating inhibitory signals crucial for pattern formation.

This study reviewed evidence for six minimally invasive treatments for androgenetic alopecia, finding consistent support for platelet-rich plasma and topical finasteride, while other options like microneedling and intradermal dutasteride showed promise but need further and standardized research.

This review discusses the causes of nail pitting in children and adolescents, noting that while most cases are idiopathic, significant associations exist with conditions like psoriasis, juvenile arthritis, and alopecia areata, among others.

This study found that a topical hair ampoule containing human follicle stem cells significantly improved hair growth and scalp coverage in women with androgenetic alopecia after four months of use.

This study found that a nutraceutical containing vitamins and trace elements was effective in reducing telogen strands and improving hair and nail conditions in individuals with telogen effluvium and brittle nails syndrome.

This review suggests that platelet-rich plasma therapy may be an effective treatment for androgenetic alopecia, with low downtime and minimal adverse effects reported in the studies analyzed.

This study reported that combining Erbium Glass 1550nm laser therapy with scalp injections of minoxidil, finasteride, growth factors, and vitamins was an effective and safe treatment for androgenetic alopecia, with 96.77% of participants expressing satisfaction, especially those who underwent more than six sessions.

This study found that platelet-rich plasma injections may lead to improved hair growth and follicle health in individuals with androgenic alopecia, showing a higher average improvement in women compared to men.

This study found that neurosteroids and benzodiazepines decrease network excitability in neuronal cultures, with specific long-term depressive effects on inhibitory neurons.

This paper introduces the first computational model of male baldness that simulates hair loss using the Hamilton-Norwood classification and has been deemed plausible for clinical use by a dermatologist.