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This study suggests that variations in PCOS phenotypes observed across different ethnic groups may be due to a genetic gradient resulting from historical human migrations and genetic drift.

Oral JAK inhibitors are safe for alopecia areata, but baricitinib may cause more acne and infections.

In this study, researchers analyzed adverse events linked to avacopan using FDA data, finding no high-priority safety concerns but identifying five potential new adverse events, including alopecia, primarily among American patients, and noting a higher risk of liver dysfunction in Japanese patients.

In this study analyzing FDA data, researchers found that tralokinumab was associated with higher reports of conjunctivitis and keratitis compared to dupilumab, while dupilumab had more frequent injection site reactions, highlighting potential risks for clinical monitoring in atopic dermatitis treatments.

This study found that non-bleeding adverse events associated with NOACs affect multiple organ systems, emphasizing the importance of clinical vigilance. Specific NOACs like dabigatran, apixaban, edoxaban, and rivaroxaban were linked to distinct adverse reactions, including metabolic imbalances, thyroid disorders, and menstrual irregularities.

This study demonstrates that a proposed multi-stage framework improves the accuracy and faithfulness of drug-related responses generated by language models, compared to traditional methods.

This study mapped the safety profile of EGFR-TKIs by analyzing FDA adverse event reports, highlighting unexpected reactions like intestinal obstruction and hypokalaemia with gefitinib and erlotinib.

This study confirmed that a sulfotransferase enzyme test can effectively rule out 95.9% of nonresponders to 5% topical minoxidil for treating androgenetic alopecia.

This pharmacovigilance study found an increased association of suicidality and psychological adverse events with finasteride use, especially among younger patients using it for alopecia.

This study concluded that alopecia is a rare side effect of SSRIs, with sertraline showing a higher association compared to citalopram, particularly among women.

This review discusses the expression of PSA in hormonally-regulated tissues and female malignancies, emphasizing its potential as a diagnostic biomarker and role in antidoping initiatives.

The researchers reported that non-motor symptoms like taste disorders and alopecia are associated with myasthenia gravis, particularly in severe cases and those linked to thymoma.

This paper reviews the role of androgens in SARS-CoV-2 infection and their potential impact on disease severity, suggesting androgen-targeting strategies might influence outcomes, but reports no new clinical results.

This article discusses various treatment options for open-angle glaucoma, which include surgical and medical approaches, emphasizing the need for combining drugs with different mechanisms to manage intraocular pressure and prevent vision field narrowing.

Long-term estrogen therapy in postmenopausal women can improve certain health markers, hair loss is common regardless of hormone use, stopping estrogen doesn't increase breast cancer risk, smoking does, and a balanced BMI is linked to lower mortality.

The researchers reported that integrating the naturopathic complex Detoxil into standard therapy for chronic dermatoses enhances detoxification, normalizes metabolic markers, and accelerates symptom resolution, suggesting potential benefits for managing skin conditions.

This review suggests a causal relationship between finasteride, used for hair loss, and persistent neuropsychiatric side effects like depression, citing evidence that fulfills key causality criteria and calls for cautious use along with strengthened regulatory oversight.

This report describes a pancreatic mixed acinar-neuroendocrine carcinoma in a cat, underscoring its diagnostic complexity and the need to consider it in diagnoses of pancreatic masses with mixed features.

Combining low-level laser therapy with topical corticosteroids effectively improved Lichen Planopilaris symptoms.

This study developed new genetic prediction models for male pattern baldness with improved accuracy by utilizing a large set of markers and independent datasets, making them the most reliable available for this trait.

This study evaluated various NLP models for detecting bias in medical curricula, finding that fine-tuned BERT models perform well, whereas LLMs, despite being state-of-the-art in many tasks, are unsuitable for this application.

This review presents a comprehensive evaluation of medical reasoning using large language models, highlighting a significant gap between exam-level performance and true clinical decision-making accuracy.

This study found that a genetic model using SNPs can predict early-onset male-pattern baldness with moderate accuracy, which may assist in decisions about interventions.

In this study, researchers developed a novel computational framework using deep reinforcement learning to identify strategies for cellular reprogramming in gene regulatory networks, showing its effectiveness in a model of immune response against infection.

This paper introduces the first computational model of male baldness that simulates hair loss using the Hamilton-Norwood classification and has been deemed plausible for clinical use by a dermatologist.

This research reported that using J48 algorithms with bagging improves prediction accuracy of hair health through machine learning by analyzing factors like spatial-temporal images, gender, and age, achieving a real-time performance of 89.5%.

This study developed a mathematical model to explore the interactions between hair cycle dynamics and immune system activity in alopecia areata, providing insights into disease progression and potential targets for treatment by simulating immune response effects on hair follicles.

This study used a probabilistic Boolean network model to explore hair follicle cell fate regulation and predicted that varying TGF-β levels, in coordination with BMP and TNF, can influence either apoptosis or cell proliferation during different follicle growth stages.

This study reported that the PM-DBiGRU model enhances aspect-level sentiment classification in drug reviews, outperforming existing methods on the newly proposed SentiDrugs dataset.

This study reports that an Explainable AI-based hair health prediction system using a novel hybrid model outperformed traditional machine learning methods, achieving high accuracy in predicting key factors and providing personalized recommendations.