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This study identified a network of interactions between miRNAs and mRNAs that involve key signaling pathways, suggesting new insights into the mechanisms behind androgenetic alopecia.

This article reviews existing domestic and international research on social networks for finding partners, revealing insights into preferences and the success rates of online dating compared to traditional methods, and may guide future psychological and sociological studies in this area.

This study found that individuals with androgenetic alopecia had higher scalp microbiome diversity and more complex scalp-gut microbiome networks than those without, suggesting a link between skin-gut microorganisms and hair loss development.

In this study, researchers used EHR data from two large PCORnet networks to identify a range of long COVID diagnoses, highlighting varying post-acute risks across populations in NYC and Florida.

This study reported that the Computational Analysis of Novel Drug Opportunities platform effectively uses integrated biological data, including side effects and pathways, to generate potential drug candidates for colon cancer and migraine disorders.

In this study, researchers identified novel long non-coding RNAs related to cashmere fineness in goats, highlighting a potential regulatory network involving lncRNA XLOC_008679 and its target gene KRT35.

In this review, researchers explored the potential of a curcumin–piperine combination in alopecia management through computational analyses, highlighting its capacity to modulate multiple pathways involved in hair follicle homeostasis, although further experimental and clinical validation is necessary to confirm its efficacy.

In this study, researchers conducted a whole-transcriptome analysis of Dazu Black Goats and Inner Mongolia Cashmere Goats to explore differences in hair follicle development and melanin production, revealing variations in hair characteristics and 640 differentially expressed RNAs that could inform goat breeding and textile applications.

This study applied semantic text-mining to identify phenotypes linked to over 6,000 diseases, demonstrating that these phenotypes can accurately identify known disease-associated genes, creating a human disease network based on phenotypic similarity.

This study identified several DPC-specific proteins, including ITGB1, IGFBP3, and THBS1, as potential biomarkers for hair growth modulation through proteomic and network analysis.

This study reported the first comprehensive transcriptome atlas of the extraorbital lacrimal gland in mice, identifying over 41 cell subclasses and revealing significant cell-cell communication networks, particularly among innate lymphoid cells.

This study found that patients with alopecia areata, particularly those with severe cases, exhibit significant systemic immune dysregulation, including altered cell communication networks and epigenetic remodeling in immune cells, suggesting potential pathways for therapeutic targeting.

This study investigated protein expression changes during mouse hair follicle cycles and suggested their involvement in biological networks, potentially identifying targets for hair disease therapy.

This study reported that Tianma Gouteng decoction improved hair follicle regeneration in mice and identified its potential mechanism, primarily involving the Wnt/β-catenin signaling pathway, through a combination of network pharmacology, molecular docking, and experimental validation.

Low-level laser therapy effectively improves hair growth in androgenetic alopecia with minimal side effects.

This article is from the ASPS Education Network and does not report any new research findings.

This study used integrated single-cell chromatin and transcriptomic analyses in developing mouse skin to uncover gene networks involved in skin lineage specification and identified Mef2c+ upper fibroblasts as potential precursors to certain muscle-like structures, with cross-species findings in human skin.

In this study, researchers used proteomic and metabolomic analyses to explore hair follicle development in embryonic cashmere goats, identifying significant roles for the oxytocin signalling pathway and associated networks in this process.

This study identified altered mRNA and lncRNA profiles in NS scalp tissues, highlighting CDKN2AIP as a downregulated gene involved in a ceRNA network.

A deep learning model was developed to help diagnose trichothiodystrophy by analyzing hair patterns.

This study found distinct expression patterns of various transcription types during hair follicle morphogenesis, providing a foundation for understanding hair development mechanisms and aiding selective breeding for desirable wool traits in a specific breed.

This study found that the Qing Cuo Formula significantly reduced serum androgen and inflammatory cytokine levels in hamsters with damp-heat acne and identified potential molecular mechanisms and active compounds involved.

This study explored the expression and potential functions of long non-coding RNAs in the skin pigmentation of Koi carp, revealing their involvement in pigmentation and differentiation mechanisms.

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 found that taxol induces apoptosis in dermal papilla cells, affecting protein expression related to biological processes and potentially contributing to taxol-induced alopecia.

This study used computational methods to explore the potential of betulinic acid from Ziziphus spina-christi in treating alopecia, suggesting its possible protective effects on hair follicles by enhancing genomic stability and reducing oxidative damage, meriting further experimental validation.

This study found that an extract from the herbal medicine Ophioglossum vulgatum Linn. showed potential hair growth promotion and increased ATP and catalase activity in cell assays, suggesting its use in treating alopecia.

In this study, researchers proposed a deep learning approach combining genetic, hormonal, scalp health, and lifestyle data to predict hair loss, employing CNNs for image analysis and RNNs for modeling data over time, although specific results are not reported.

This study suggests that 20 vital medicinal herbs may exert therapeutic effects on alopecia by regulating specific target genes and proteins, offering insights into their novel mechanisms distinct from conventional drugs.

This study found that NIH hairless mice exhibit abnormalities in hair growth and immune-related pathways, with Pik3r1 and Pik3r3 identified as key genes for further investigation.