Ethnopharmacological Relevance: Dahuang-Gancao decoction (DGD) is a traditional Chinese medicinal formula that is recorded in the Synopsis of the Golden Chamber, and is widely used to treat damp-heat in the body. Since the pathological factors of androgenetic alopecia (AGA) also reflect damp-heat blockage, DGD has great potential for the treatment of AGA and has been used effectively in clinical practice.
Aim Of The Study: The aim of the study was to investigate whether external application of DGD could promote the activation and proliferation of hair follicle stem cells (HFSCs) and improve AGA through the Wnt/β-catenin pathway.
Materials And Methods: The main chemical components of DGD-contained serum were identified by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and database search. Cell Counting Kit-8 (CCK8) was used to investigate the appropriate concentration. Hair regeneration was assessed by hair growth score and histopathological staining. The proliferation of HFSCs and the activation of Wnt/β-catenin pathway were detected by Western blot, immunofluorescence staining, real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and enzyme-linked immunosorbent assay (ELISA). The AGA mouse model was induced by external application of testosterone (T). Immunofluorescence staining was performed to localize HFSCs by CK15, followed by staining with Ki67, β-catenin, and Cyclin D1, respectively.
Results: The results illustrated that the 10% DGD group and the 10% DGD + HLY78 group could significantly promote the expression of Wnt10b and β-catenin and the proliferation of HFSCs in vitro, while the 10% DGD + IWR-1 group could reverse the promotion effect of DGD. Animal experiments showed that compared with the model group (T group), DGD promoted hair follicles to enter the anagen phase, as evidenced by an increase in hair growth score, an increase in the number of hair follicles in hematoxylin and eosin (HE) staining, and a significant increase in the ratio of the number of anagen follicles to the total number of hair follicles (AF/AF + TF). In addition, DGD upregulated the expression of Wnt/β-catenin signaling pathway proteins in the skin tissues of AGA mice. It also promoted the proliferation of HFSCs and the expression of β-catenin and Cyclin D1 cytokines in the region of HFSCs.
Conclusion: Both oral and external application of DGD can promote the proliferation of HFSCs by activating the Wnt/β-catenin signalling pathway. External application of DGD can promote the hair follicles to enter the anagen phase, which can ameliorate the symptoms of alopecia in AGA mice. Therefore, compared to oral DGD, external application of DGD is an effective and safer way of administration for the treatment of AGA.
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http://dx.doi.org/10.1016/j.jep.2025.119347 | DOI Listing |
JMIR Med Educ
January 2025
Department of Orthopedics, First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
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PLoS One
January 2025
Electrical, Mechanical & Computer Engineering School, Federal University of Goias, Goiania, Brazil.
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View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
Jilin University, College of Electronic Science and Engineering, State Key Laboratory of Integrated Optoelectronics, Qianjin Avenue 2699, Changchun, 130012, Changchun, CHINA.
Stable luminescent diradicals, characterized by the presence of two unpaired electrons, exhibit unique photophysical properties that are sensitive to external stimuli such as temperature, magnetic fields, and microwaves. This sensitivity allows the manipulation of their spin states and luminescence, setting them apart from traditional closed-shell luminescent molecules and luminescent monoradicals. As a result, luminescent diradicals are emerging as promising candidates for a variety of applications.
View Article and Find Full Text PDFAlzheimers Dement (N Y)
January 2025
Indiana Alzheimer Disease Research Center and Center for Neuroimaging, Department of Radiology and Imaging Sciences Indiana University School of Medicine Indianapolis Indiana USA.
Introduction: The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk.
View Article and Find Full Text PDFCureus
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To enhance patient outcomes in pediatric cancer, a better understanding of the medical and biological risk variables is required. With the growing amount of data accessible to research in pediatric cancer, machine learning (ML) is a form of algorithmic inference from sophisticated statistical techniques. In addition to highlighting developments and prospects in the field, the objective of this systematic study was to methodically describe the state of ML in pediatric oncology.
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