research How a reaction-diffusion signal can control spinal cord regeneration in axolotls: A modeling study
Axolotl spinal cord regeneration may be controlled by a specific signal affecting cell sensitivity and diffusion.
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30-60 / 1000+ resultsresearch How a reaction-diffusion signal can control spinal cord regeneration in axolotls: A modelling study
Axolotls regenerate their spinal cord through a signal that recruits cells, influenced by cell sensitivity and signal spread.
research A review on computer‐aided chemogenomics and drug repositioning for rationalCOVID ‐19 drug discovery
Computer-aided methods can speed up COVID-19 drug discovery and help find new uses for existing drugs.
research Molecular modeling and structural characterization of a high glycine–tyrosine hair keratin associated protein
The 3D structure of a key hair protein was modeled, revealing specific helical structures and stabilization features.
research Foundations of Bayesian Networks
Bayesian networks are tools for modeling variables' probabilistic relationships, which can efficiently represent complex probabilities and help in making inferences.
research Deep Learning Approaches for Hair Disease Classification: A Comparative Analysis of MobileNetV2 and VGG19 Architectures
VGG19 is more accurate, but MobileNetV2 is faster and uses fewer resources.
research Mechanotransduction in Androgenetic Alopecia: An In Silico Repositioning Study of PIEZO1 + MLCK Axis Using Cofolding and Pilosebaceous Single-Cell Atlas Constraints
Potential compounds may inhibit hair loss by targeting a non-androgen pathway.
research Mechanotransduction in Androgenetic Alopecia: An In Silico Repositioning Study of PIEZO1 + MLCK Axis Using Cofolding and Pilosebaceous Single-Cell Atlas Constraints
Potential compounds may inhibit hair loss by targeting a non-androgen pathway.
research Gap junctions in Turing-type periodic feather pattern formation
Gap junctions help control feather pattern formation by enabling cell communication.
research Role of β-Catenin Activation Levels and Fluctuations in Controlling Cell Fate
Proper control of β-catenin activity is crucial for development and preventing diseases like cancer.
research Machine learning for nanozyme development in anti‐inflammatory applications
Rational design strategies are crucial for developing effective nanozymes for anti-inflammatory uses.
research A molecular systems architecture of the mesenchymal stromal cell microenvironment
A systems biology approach helps improve mesenchymal stromal cell therapies by mapping interactions and identifying treatment targets.
research ZASTOSOWANIE SZTUCZNEJ INTELIGENCJI W ECHOGRAFII SERCOWEJ: KORZYŚCI I RYZYKO
AI in heart scans improves diagnosis and treatment but has risks like misdiagnosis and high costs.
research Dataset from the uniaxial tensile testing of human curly hair fibers under different conditions
Curly hair's strength and flexibility vary with moisture and temperature.
research Predisposing and Overall Effects of Reproductive Hormones on Breast Cancer: A Review
Reproductive hormones play a crucial role in breast cancer development and treatment challenges.
research Touch Receptors Undergo Rapid Remodeling in Healthy Skin
Touch sensitivity in mouse skin decreases during hair growth due to changes in touch receptors.
research Therapeutic small extracellular vesicles from key human stem and immune cellular sources: A review
Small extracellular vesicles from stem and immune cells show promise for treating various diseases but face challenges in clinical use.
research Hair Tone Estimation at Roots via Imaging Device with Embedded Deep Learning
The device accurately estimates natural hair color at the roots in real time.
research Pharmacophore Models for Toxicology Prediction
Pharmacophore models can predict liver toxicity and central nervous system toxicity, but they have limitations and specific requirements.
research Scalp disease analysis using deep learning models
Deep learning models can analyze scalp diseases effectively.
research A machine learning and network framework to discover new indications for small molecules
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.
research In Search of Predictive Models for Inhibitors of 5-alpha Reductase 2 Based on the Integration of Bioactivity and Molecular Descriptors Data.
The models can help find better inhibitors for conditions like baldness and prostate disorders.
research A model for the turnover of dihydrotestosterone in the presence of the irreversible 5α-reductase inhibitors GI198745 and finasteride
Both drugs lower DHT levels, with GI198745 being more effective.
research Computational design and development of a novel voltammetric sensor for minoxidil detection based on electropolymerized molecularly imprinted polymer
New sensor detects minoxidil accurately and effectively.
research Computational derivation of a molecular framework for hair follicle biology from disease genes
The research provides a gene-based framework for hair biology, highlighting the Hippo pathway's importance and suggesting links between hair disorders, cancer pathways, and the immune system.
research Three-row stereocilia model predicts mammalian hair bundle behavior
The model explains how mammal ear hair cells respond to sound and adapt.
research A Temporal Mathematical Model of Alopecia Areata: Investigating Hair Cycle Dynamics and Disease Progression
The model helps understand alopecia areata and suggests ways to improve treatment by targeting immune issues.
research Computational Evaluation of Dibenzo Compounds as Potential Dual Inhibitors of Androgen Receptor and 5α-Reductase
Some dibenzo compounds might help treat cancer with fewer side effects.
research Computational screening of repurposed drugs and natural products against SARS-Cov-2 main protease (Mpro) as potential COVID-19 therapies
Some existing drugs and natural products might work against COVID-19 by targeting the virus's main protease.
research Trichoscopy of Alopecia Areata: Hair Loss Feature Extraction and Computation Using Grid Line Selection and Eigenvalue
Researchers developed an algorithm for self-diagnosing scalp conditions with high accuracy using smart device-attached microscopes.