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Machine learning can predict symptoms and quality of life in chronic skin disease patients using smartphone app data, and shows that app use varies with patient characteristics.

Scientists successfully created and analyzed the structure of a part of the human androgen receptor with specific modulators and a peptide to understand how it binds differently in various tissues.

Combining multiple algorithms predicts hair fall more accurately than using single algorithms.

Finasteride affects brain processes related to neurotransmission and metabolism, potentially helping with neuropsychiatric conditions.

12-Methoxy carnosic acid from rosemary might be a good natural treatment for hair loss.

Arteannuin might work against cancer and Alzheimer's by targeting neprilysin.

Multi-omics techniques help understand the molecular causes of androgenetic alopecia.

The research found new potential mechanisms in mouse hair growth by studying RNA interactions.

The study found specific proteins that could mark different growth stages of cashmere goat hair and may help improve cashmere production.

Researchers found genes and microRNAs that control curly fleece in Chinese Tan sheep.

The analysis shows where minoxidil's atoms are likely to react and describes its electronic transitions and behavior with temperature changes.

Whale oil significantly promotes hair growth and may be a safe, effective alternative to minoxidil.

UV exposure reduced hair shine in mice, but minoxidil helped restore it.

The research identified key molecules that help hair matrix and dermal papilla cells communicate and influence hair growth in cashmere goats.

Protein tyrosine kinases are key in male pattern baldness, affecting skin structure, hair growth, and immune responses.

Different types of RNAs are found in varying amounts in patients with Polycystic Ovary Syndrome, suggesting they could be important in the disease's development and potentially used as disease markers.

Rare genetic variants in five specific genes are linked to male-pattern hair loss but only account for a small part of the risk.

The peer review highlighted the need for clearer data handling, questioned the study's validity, and recognized improvements from the original version.

Reviewers suggested the study on finding new drug uses through social media side-effects needs better methods and clearer limitations.

Reviewers criticized the study for assuming drugs with similar side-effects work the same way and questioned the validity of its findings due to potential biases and data quality issues.

The study improved and was accepted despite initial concerns about data clarity, methodology, and potential overfitting.

Reviewers criticized the study's methods and suggested focusing on drug mechanisms instead of repositioning due to social media data quality concerns.

Reviewers criticized the study for its assumptions, social media data collection issues, and lack of comparison to existing methods.

New method finds genetic links between Type 2 Diabetes and Prostate Cancer not seen before.

The document concludes that computational methods using networks and various data can improve the process of finding new uses for existing drugs.

Alopecia areata patients show unique protein activity patterns, suggesting imbalanced signaling pathways.

The document concludes that computational models are useful for understanding immune responses and could improve cancer immunotherapy.

The study found key factors in the cause of hidradenitis suppurativa, its link to other diseases, and identified existing drugs that could potentially treat it.

Scientists found new genetic areas that affect how rice root hairs grow and develop.

Genetic factors could lead to personalized treatments for hair loss.