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In this paper, Chemistry42—a software integrating AI with computational and medicinal chemistry—demonstrated efficiency in designing novel molecular structures targeting DDR1 and CDK20, with properties validated in both in vitro and in vivo studies.

This case report describes the first confirmed instances of X-linked adrenomyeloneuropathy/adrenoleukodystrophy in two brothers from Bangladesh, noting their progressive neurological symptoms, MRI findings, and differing disease outcomes over several years of observation.

This study reports on a new semantic annotation approach used to identify substances in MEDLINE abstracts responsible for adverse drug reactions, with promising performance shown by a prototype system.

In this study, a novel compound named AH-001 demonstrated effective androgen receptor protein degradation, reducing hair loss progression in a mouse model of androgenetic alopecia, with minimal systemic exposure and side effects, suggesting potential for safer treatment.

This study demonstrated that the Alopecia Areata Disease Activity Index (ALADIN), a new biomarker, strongly correlates with treatment response in patients using JAK inhibitors for alopecia areata.

This study assessed an AI-based mobile app for evaluating androgenetic alopecia severity, finding that it achieved 94% accuracy compared to human dermatologists, while participants often underestimated their own hair loss severity.

AI can accurately measure hair loss severity in alopecia areata.

This study found that their newly developed ADRL framework significantly improved the accuracy of scalp tissue layer segmentation in HR-MR images compared to existing methods.

This study describes the PandaOmics platform, which uses AI and bioinformatics to identify new therapeutic targets and biomarkers for various diseases, demonstrating validation in laboratory and animal studies.

This study introduces ALUDWIG, an automated tool for assessing female androgenic alopecia severity from smartphone images, which may offer a more consistent alternative to current scoring methods like the Ludwig scale.

This abstract contains no research findings; it outlines website features and access options for the JAMA network's publications.

This study found that an Attention-based Balanced Multi-Task Deep learning system achieved a 95.11% accuracy in classifying Alopecia Areata conditions using hair and scalp images, outperforming classical methods.

This study suggests that autologous micrograft technology may be more effective than finasteride in promoting hair growth in patients with androgenetic alopecia.

In this study, subcutaneous injection of bone marrow mesenchymal stem cells in burned rats significantly improved wound healing by reducing inflammation, scar formation, and wound size, and restoring normal skin structures.

This study found that anagen stage protein homogenates and specific epitopes from melanogenesis proteins activated CD8 T cells, suggesting alopecia areata is an anagen-specific disease.

This paper discusses two preclinical models for studying alopecia areata and finds that testing new therapeutic agents should involve both the C3H/HeJ mouse model and the humanized mouse model for comprehensive insights.

This study developed a new neural network model (AA-GAN-AB-MTEDeep) to enhance Alopecia Areata classification using synthetic scalp images, achieving an accuracy of 96.94%.

This study found that intradermal injection of a cell-penetrating, AR-targeting asiRNA promoted hair growth and reduced androgen receptor expression in mouse models of androgenetic alopecia, suggesting its therapeutic potential.

In this case report, the authors describe a partial androgen insensitivity syndrome patient with a novel AR gene mutation, highlighting challenges in gender assignment decisions for infants with partial AIS.

This study found that targeting androgen receptors with prostate cancer drugs ARN509 and finasteride induced remission and increased survival in a leukemia mouse model, suggesting a potential new treatment approach for acute myeloid leukemia.

This study found that KSR1 is essential for v-Ha-ras-mediated skin tumor formation in mice but not for MT-driven mammary tumor genesis, suggesting its potential as a therapeutic target in Ras/MAPK signaling.

Farudodstat may effectively treat alopecia areata without harmful side effects.

In this study, AMP-303 injections demonstrated a trend toward increasing non-vellus hair count in men with mild to moderate androgenetic alopecia, notably showing a 14.5% peak increase at 60 days compared to saline, with effects lasting up to five months.

This study found that intradermal injection of a specially designed RNA molecule, cp-asiAR, successfully reduced androgen receptor levels and promoted hair growth in a mouse model of androgenetic alopecia, while also improving hair follicle characteristics in ex vivo human scalp tissues without significant toxicity.

This study found that in a mouse model, alopecia areata was associated with changes in heart structure, biochemistry, and gene expression linked to cardiac hypertrophy after ACTH exposure.

This study used machine learning to identify molecular predictors of drug response in alopecia areata, suggesting a tool for predicting treatment efficacy based on gene signatures.

This study found that the combination of MT-DADMe-ImmA and MTA selectively induced apoptosis in head and neck squamous cell carcinoma cell lines FaDu and Cal27, but not in normal fibroblasts or MTAP-deficient breast cancer cells.

This study demonstrated that AIRE-deficient rats exhibit key symptoms of APECED, making them a relevant model for exploring potential treatments.

This study developed BroadAMP-GPT, a computational-experimental framework, to discover new antimicrobial peptides, identifying candidates effective against multidrug-resistant pathogens. Notably, AMP_S13 showed strong stability, low toxicity, and efficacy in infection models, highlighting the platform's potential in combating antimicrobial resistance.