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Severe genetic variants in children with a specific adrenal condition match predicted symptoms well, but milder variants do not.

The MDR1 C3435T polymorphism does not significantly affect methotrexate response in rheumatoid arthritis patients.

Finasteride treatment should be personalized to individual mental profiles.

COVID-19 treatments and vaccines face challenges due to genetic differences in people and the virus.

Finasteride and dutasteride's effects are mainly due to target binding saturation and slow enzyme turnover.

Drug repurposing offers a faster, cheaper way to find treatments for rare diseases.

The model successfully predicted new uses for existing drugs, like using certain hormonal and heart medications for respiratory and Parkinson's diseases, and a cancer drug for diabetes.

iEdgePathDDA effectively finds new drug-disease links, outperforming other methods.

Using computers to analyze drugs can find new uses for them, but actual experiments are needed to confirm these uses.

Signaling pathways are key targets for developing effective drugs.

Certain gene combinations may affect prostate cancer risk, and GSTP1 methylation is linked to tumor aggressiveness.

A specific gene variation increases the risk of high uric acid and cholesterol in young Mexican males.

Different crystal forms of drugs can change their effectiveness.

Studying rare genetic disorders can help us understand and treat common diseases better.

The research explores how gut bacteria and sleep patterns are related in mental health disorders.

Forensic DNA phenotyping can predict physical traits from DNA but faces challenges in knowledge and ethics.

A genetic mutation linked to longer life and less disease was found in the Amish, and a drug is being developed to replicate these benefits.

MendelVar is a tool that helps identify important genes by combining GWAS data with Mendelian disease information.

The model and estimator can predict drug exposure in kidney transplant patients well.

New gene discoveries have improved diagnosis and treatment for skin and hair disorders, but more research is needed to fully understand them.

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.

Forensic genetics can now predict physical traits and lifestyle habits, with future advancements expected from new technologies.

64 drugs can cause hair loss, needing better monitoring and updated labels.

A new tool can analyze hair to detect changes due to hormones, genetics, and aging.

Genosomes are promising for safe and effective gene delivery in therapy.

AnnoPharma effectively identifies substances causing adverse drug reactions in medical abstracts.

Molecular diagnostics help identify genetic defects causing endocrine diseases, improving diagnosis and treatment options.

Certain VDR gene changes can affect melanoma risk.

Redefining drug dosages is crucial when repurposing them for new uses.