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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 found that the WNMFDDA model effectively predicts drug-disease associations, achieving high accuracy in cross-validation and confirming most candidate associations through existing databases.

This study developed a new clustering model to improve detection of drug-induced cognitive disorder risk signals, finding that it identified drugs with moderate risk signals, like Carbidopa/Levodopa, missed by traditional methods, enhancing clinical assessment comprehensiveness.

This study developed a deep learning-based tool to quantify individual hair fibers in mice, revealing distinct hair phenotypes linked to hormonal, genetic, and age-related factors, and suggesting its potential for new diagnostic methods through hair analysis.

This study discusses the challenges in translating organoid models from laboratory settings to clinical and commercial applications, emphasizing the need for engineering approaches like environmental recapitulation and matrix engineering to bridge this gap.

This study developed a two-step diagnostic model using transcriptome biomarkers from hair follicles to improve the accuracy of methamphetamine use disorder diagnosis, achieving high prediction accuracy in distinguishing non-recovered and almost-recovered patients from healthy controls.

This study found that PRMT5 inhibitors showed potent anti-tumor activity in models of adenoid cystic carcinoma and that combining these inhibitors with lenvatinib may have additional growth-inhibitory effects.

In this study, researchers identified KRT6A as a potentially important gene in mesenchymal stem cell-derived treatments for alopecia areata, revealing its role as a diagnostic marker, predictor of disease severity, and a protective factor, with overexpression alleviating hair loss in experimental models.

This study found that blocking the chemokine CXCL12 in a testosterone-induced mouse model of androgenetic alopecia restored hair regeneration and reduced fibrosis and immune alterations.

This study developed the TLMG hydrogel, a seamless in situ biointerface platform, demonstrating robust adhesion, high conductivity, and therapeutic effects for intelligent wound management in complex animal models and human tests, indicating its promise for integrated bioelectronic medicine.

This review highlights recent advances in ultrasound-based radiomics and radiogenomics for ovarian cancer, suggesting these techniques improve diagnostic accuracy and patient-specific treatment strategies, despite ongoing challenges with standardization and model interpretability.

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.

This study demonstrated that a wearable bioelectronic patch with combined therapy significantly accelerated chronic wound healing in a rodent model by monitoring and treating wounds noninvasively.

In this review, researchers examined advanced sensing technologies and bioelectronic interfaces that could improve understanding of the skin–brain axis, highlighting challenges and strategies for integrating these platforms into models for studying skin and neural interactions.

This study reported that dutasteride, identified through a drug repurposing strategy, showed the potential to reduce neuroinflammation and cognitive impairment in LPS-stimulated models.

This study introduced a new computational method for simulating vibrational frequencies, finding that the multi-molecular fragment model showed the best agreement with experimental data for Finasteride, Lamivudine, and Repaglinide, outperforming traditional models in accuracy.

This study found that both primary Covid-19 infections and exacerbations of existing health conditions influence mortality, with long-term effects being predictable from GLM models.

In this study, a deficiency in the zinc finger protein Zfp462 in mice led to anxiety-like behaviors and excessive self-grooming, providing a new model for studying anxiety disorders.

This review discusses various drugs and chemicals potentially causing hair loss, mechanisms involved, and suggests models for testing but reports no new clinical findings.

This study found that quercitrin, a natural compound, enhances Wnt/β-catenin signaling and may help mitigate synapse loss and memory impairment in Alzheimer's models.

In this study, the researchers reviewed psychiatric drugs approved between 2002 and 2022 to analyze trends in drug repurposing, finding an increased application of repurposing methods, especially through fixed-dose combinations, and highlighting technologies like SmartCube® to predict efficacy from animal models.

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.

In this study, a novel GAN-based image translation method focusing on regions of interest showed improved predictive performance for post-hair transplant images compared to existing methods, using an ensemble approach to enhance robustness and detection accuracy.

This study introduced an innovative metric for assessing college students' mental health, incorporating temporal perception and a hybrid clustering algorithm, and found it achieved over 90% accuracy, outperforming existing methods in evaluating mental health during public health challenges.

This article provides industry updates on stem cell research and regenerative medicine from December 2019 and reports no new research findings.

This review summarizes advancements in forensic DNA phenotyping for appearance, ancestry, and age prediction from crime scene samples, reporting no new research findings but highlighting areas needing further research and validation.

This review highlights the need for inclusive dermatology practices to address variations in skin conditions globally by incorporating tools like AI, teledermatology, and culturally competent education.

This scoping review reports that while empirical evidence suggests an overlap between Long/Post Covid-19 syndrome, chronic fatigue syndrome, and fibromyalgia, the underlying molecular mechanisms remain unclear, highlighting the need for standardized definitions and rigorous methodologies in Long Covid research.

This review highlights recent advancements in engineered probiotics for wound healing, reporting that genetically engineered strains of Lactobacillus reuteri and Lactococcus cremoris have shown promise in promoting faster wound healing in pre-clinical and clinical settings, particularly for diabetic foot ulcers.

This review outlines computational strategies, including chemogenomics and drug repositioning, for coronavirus drug discovery and reports no new clinical findings; the authors highlight the advantages of these methods in rapidly identifying therapeutic candidates.