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A new method accurately measures college students' mental health by considering time perception and clustering techniques.

The new assay can track and measure melanosome transfer between skin cells, confirming filopodia's role in this process.

The device mimics human hair follicles and detects tiny forces and moments with high sensitivity.

The machine learning model accurately detected hair loss and scalp diseases using processed images.

QMSI is a valuable method for studying drug penetration in skin tissues.

A new image-based method improves accuracy in measuring hair loss in mice.

Hair cortisol levels can reflect salivary cortisol levels in humans.

Merkel cells are more densely found in hairless skin areas like palms and soles.

HairLossMultinet accurately classifies hair damage with 98% accuracy but needs a more diverse dataset for broader use.

The new microscope method helps study energy from pre-cancerous skin cells.

18-MEA is essential for hair's water resistance, and a conditioner with 18-MEA and SPDA can restore it.

Hair vibrancy involves how hair looks and feels, helping create better hair products.

Hair cuticles remain stable and resilient under stress due to strong protein content and crosslinking.

The gene for slick hair in Senepol cattle is located on chromosome 20 and may involve the SRD5A2 gene.

ChatGPT is more accurate at diagnosing hair disorders in lighter skin tones than darker ones.

The study found that the Marangoni effect causes the uneven wetting of surfactant-coated hair due to the surfactant moving into the water.

Different species have unique sensory adaptations to perceive their environments.

Balancing artistic design and precision improves hair transplant results.

The Brigham Eyelash Tool for Alopecia (BELA) is a reliable way to measure eyelash loss in alopecia areata patients.

Mouse skin cancer progression involves a unique group of cells marked by ABCG2 and MTS24.

MALDI Imaging Mass Spectrometry is a useful method for studying skin conditions, but sample preparation is crucial for accurate results.

The conclusion is that a new method to measure hair shine was confirmed to match people's visual assessments.

Meis2 is essential for touch sensation and proper nerve connection to touch receptors in certain skin areas of mice.

Raman micro-spectroscopy can help distinguish basal cell carcinoma from hair follicles in skin tissue.

The machine learning model accurately predicts Systemic Lupus Erythematosus in Omani patients.

Light scatters differently from elliptical hair fibers than from circular ones, and a new model better predicts this behavior, especially for shiny highlights.

The new AI software predicts melanoma outcomes more accurately than traditional methods.

The CLASI is a reliable tool for measuring the severity of cutaneous lupus erythematosus.

Researchers developed a new model for more realistic computer graphics of hair by considering how light scatters on hair fibers.