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New methods can detect finasteride's major urinary metabolite in urine for up to 49 hours.

The study showed that brown planaria can be used to cheaply test if local plants can stop cell growth.

Computational methods help design drugs targeting prostate cancer proteins.

Rational design strategies are crucial for developing effective nanozymes for anti-inflammatory uses.

Terbinafine effectively stops fungal invasion of human keratin.

Reliable machine learning in medical imaging needs bias checks and data drift detection for consistent performance.

Skin-on-a-chip devices better mimic human skin for research.

Mathematical modeling helps understand and predict the MAPK cell signaling pathway.

The method can measure multiple steroids in human hair to study long-term steroid metabolism, especially in newborns and children.

Machine learning can predict how well patients with alopecia areata will respond to certain treatments.

A new diagnostic model can help better diagnose and understand Alopecia Areata.

Fish cell spheroids are a promising tool for replicating real-life conditions in research.

Combining advanced sensors with portable devices could enhance on-site food safety monitoring.

Researchers found three different ways drugs work to treat hair loss from alopecia areata and identified key factors for personalized treatment.

Equilibrium dialysis can accurately measure testosterone levels when lab results are inconsistent.

The study found that diseases can be grouped by symptoms and that the accuracy of predicting disease-related genes varies with the data source.

Researchers developed a quick and sensitive way to measure finasteride in blood using a small sample size.

The CUBIC protocol allows detailed 3D visualization of proteins in mouse skin biopsies.

Serum biotin levels can indicate biotin deficiency in sows.

Hair can be used to measure cancer-related chemicals noninvasively.

Researchers developed a quick and sensitive method to identify and measure hair growth-promoting substances in a herbal mix.

Multiomics is revolutionizing biology by enabling breakthroughs in research and disease diagnosis.

Machine learning can use blood tests to help predict moderate-to-severe alopecia areata.

Researchers developed a method to measure different forms of a drug that could help treat prostate issues and hair loss, and found how these forms behave in animals.

Hair analysis for drugs in psychosis patients is unreliable due to varying hair growth rates.

A fast and accurate method was developed to measure alfuzosin and dutasteride in human plasma.

The method effectively detects MeT and TP in dried blood spots after cream application.

The method effectively predicts new drug uses, including potential COVID-19 treatments.

A model called PM-DBiGRU was developed for analyzing sentiments in drug reviews, and it performed better than other models, but struggled with complex sentences and situations requiring background knowledge.

A new method was created to measure metformin in hair, showing potential for monitoring treatment and medical investigations.