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Fermentation of Finasteride with Ocimum sanctum L. creates new metabolite that inhibits tyrosinase.

In this study, researchers found that the shape of polygonal domains, such as squares and triangles, significantly impacts Turing pattern formation, with domain geometry affecting the stability and type of bifurcations observed in simulations.

This study reported that AutoML effectively modeled itching and pain development, as well as app use, in patients with chronic eczema or psoriasis using a smartphone monitoring app, revealing that factors like BMI, age, and disease activity significantly influenced app engagement.

In this study, researchers found that Elastic Net DNA methylation clocks are not accurate for distinguishing between individuals or identifying health markers, but measuring biological "noise" in stable cytosines may serve as a potential biomarker of aging and disease.

This research reports that herb lotions for alopecia areata, particularly those containing salvia miltiorrhiza radix, were effective in promoting hair regrowth in 64.8% of severe cases, akin to DNCB and SADBE.

This study demonstrated that CD19-CAR T cell therapy may promote structural regeneration in the skin of systemic sclerosis patients, as evidenced by histological improvements and fibroblast population changes, suggesting its potential for tissue remodeling in fibrotic diseases.

This study reviews the transformative role of artificial intelligence in biomaterial design, highlighting its ability to reduce costs through virtual screening, enhance material performance, and predict biological interactions to advance personalized and precision medicine.

This study reviews methods to ensure the reliability of machine learning models in medical imaging, focusing on bias detection, data drift assessment, and accuracy estimation without ground truth labels to enhance integration into clinical settings.

In this study, the authors found that syntax-based neural networks performed comparably to pre-trained Transformers on tasks involving definitely unseen sentences, suggesting they are a more transparent and parameter-efficient alternative for certain Natural Language Processing applications.

In this study, 3D planned resection and reconstruction for skull defects after resection of cSCC with bony invasion led to accurate procedures, though patient-specific factors should guide treatment decisions.

In this study, researchers found that the efflux of calcium in root hairs of Arabidopsis thaliana, particularly through the ER-localized ACA2 and ACA7, is crucial for modulating cytoplasmic calcium signals and enabling proper root hair growth, with disruptions leading to impaired elongation.

Crickets have genetically controlled hair plates that help them sense and move their antennae.

This study introduces PROMETHEUS, a framework that organizes causal claims from scientific texts into navigable and persistent "causal atlases," enhancing research by highlighting localized evidence, agreement, and contradictions within complex data sets.

This study reports that using machine learning models, particularly XGBoost and Random Forest, can accurately predict PCOS phenotypes based on non-invasive data, with cycle length as the most significant predictor.

This study found that VPS13C variants are significantly enriched in patients with idiopathic REM sleep behavior disorder (iRBD), associating these variants with more severe symptoms, autonomic dysfunction, and faster progression from iRBD to overt α-synucleinopathy in the iRBD-first disease subtype.

This case study reported a 15-year-old girl with a nevus sebaceus of Jadassohn, where a secondary neoplasm potentially developed into either pigmented trichoblastoma or pigmented basal cell carcinoma, highlighting the importance of early recognition and evaluation of such lesions for effective management.

This study found that administering human amniotic mesenchymal stem cells (hAMSCs) in a mouse model of psoriasis improved skin lesions and reduced inflammation-related markers, suggesting potential therapeutic benefit and safety for treating psoriasis, and identified specific gene targets involved in the treatment's mechanism.

In this study, lower dihydrotestosterone and higher testosterone levels were linked to increased brain activation during response inhibition, although no behavioral changes were detected.

This study evaluated machine-learning models to predict PCOS among reproductive-aged women in Bangladesh, finding that the XGBoost model achieved high accuracy (99.63%) and effectiveness, particularly when prioritizing clinical features over psychological ones in the predictive process.

In this study, researchers explored drug repurposing as a potential strategy for treating psoriasis and identified Pioglitazone, Trimipramine, and Dimetindene as promising candidates for this indication, based on molecular docking and predictive algorithms.

In this study, the integration of obesity-related features and machine learning techniques significantly enhanced cardiovascular disease detection, with the XGBoost classifier achieving a 74% accuracy rate and improved metrics compared to other models.

Among maize plants, this study observed that root hairs tend to grow in air-filled pores at the root-soil interface, but their growth into the soil matrix is limited, posing potential constraints on nutrient uptake, anchorage, and rhizosheath formation.

This study developed a model for detecting sparse hair clusters using enhanced object detection neural networks and medical images, which accurately identifies and counts sparse hair clusters with greater accuracy and efficiency than existing methods.

This study demonstrated that a CNN-based model using VGG-16 architecture achieved a 94.5% accuracy in classifying ten types of hair diseases, implying a promising tool for aiding health professionals in diagnosing hair conditions accurately.

This study constructed a comprehensive atlas of prenatal human skin, revealing that innate immune cells, such as macrophages, play a crucial role in skin morphogenesis by interacting with non-immune cells, influencing hair follicle formation and angiogenesis beyond their traditional immune functions.

This study suggests that pre-trained Transformers only outperform syntactic and lexical neural networks on unseen DarkNet sentences after extreme domain adaptation, indicating unexpected advantages from their massive pre-training corpora.

This study evaluated the effects of a shampoo containing ginsenoside Rg3 on hair loss prevention and regrowth, with no conclusive clinical results reported.

Herman Bierens had a successful career in econometrics, contributed to education, and plans to continue research after retirement.

This study found that carbon and nitrogen isotope analysis of cattle hair reflects dietary and farm system differences, offering insights into cattle nutritional ecology and agroecosystem characteristics.

This study found that clove, olive, and turpentine oils completely prevented hair penetration by the fungi Microsporum gypseum and Trichophyton vanbreuseghemii.