Paeoniflorin (PF) possesses multiple biological functions including anti-oxidization. PF is the major bioactive ingredient of total glycosides of paeony (TGP), which could promote re-pigmentation of vitiligo. The study was sought to investigate the effects and potential signaling pathways of PF on hydrogen peroxide (H₂O₂)-induced oxidative stress in melanocytes. The results showed that pretreatment with 50 µM PF significantly inhibited cell apoptosis, enhanced cell viability, and suppressed reactive oxygen species (ROS) accumulation by enhancing the productions of superoxide dismutase (SOD) and antioxidant enzymes catalase (CAT). Furthermore, PF activated c-Jun amino terminal kinase (JNK) and the nuclear factor E2-related factor 2 (Nrf2)/heme oxygenase-1 (HO-1) pathway to counteract H₂O₂-induced oxidative damage in PIG1 and PIG3V. Taken together, our study firstly demonstrates that PF resists H₂O₂-induced oxidative stress in melanocytes probably by activating JNK/Nrf2/HO-1 signaling, suggesting a potential therapeutic application of PF on vitiligo.

Based on the expertise of pathologists, the pixelwise manual annotation has provided substantial support for training deep learning models of whole slide images (WSI)-assisted diagnostic. However, the collection of pixelwise annotation demands massive annotation time from pathologists, leading to a high burden of medical manpower resources, hindering to construct larger datasets and more precise diagnostic models. To obtain pathologists’ expertise with minimal pathologist workloads then achieve precise diagnostics, we collect the image review patterns of pathologists by eye-tracking devices. Simultaneously, we design a deep learning system: Pathology Expertise Acquisition Network (PEAN), based on the collected visual patterns, which can decode pathologists’ expertise and then diagnose WSIs. Eye-trackers reduce the time required for annotating WSIs to 4%, of the manual annotation. We evaluate PEAN on 5881 WSIs and 5 categories of skin lesions, achieving a high area under the curve of 0.992 and an accuracy of 96.3% on diagnostic prediction. This study fills the gap in existing models’ inability to learn from the diagnostic processes of pathologists. Its efficient data annotation and precise diagnostics provide assistance in both large-scale data collection and clinical care.

Background: Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive tumors in the world. Aryl hydrocarbon receptor (AHR) has been reported to promote tumor metastasis and epithelial-mesenchymal transition (EMT) is a vital process of conferring cancer cells capabilities of migration and invasion. However, the mechanism by which modulation of AHR can inhibit tumor metastasis remains unknown. Thus, we aim to investigate the underlying mechanism regarding reversing EMT process of ESCC through modulation of AHR.Methods: We used AHR selective modulator 3,3′-diindolylmethane (DIM) to treat ESCC cell lines TE1 and KYSE150 so as to examine alterations of migration and invasion by wound healing and Transwell assay. Western blotting (WB) and qPCR were performed to detect relative genes and proteins changes regarding EMT process. Cell transfection was utilized for confirming pathways involved in DIM-induced reversal of EMT and in vivo assay was conducted for verification of the underlying mechanism. Co-IP assay was conducted for detecting protein-protein interactions.Results: AHR was overexpressed in ESCC and modulation of AHR by DIM could inhibit migration and invasion as well as downregulate mesenchymal cell markers β-Catenin, Vimentin and Slug and upregulate epithelial cell marker Claudin-1. Meanwhile, synergically overexpression of AHR, RhoA and ROCK1 correlated with poor clinical outcomes. DIM could inhibit COX2/PGE₂pathway by targeting AHR, and COX2 selective inhibitor Celecoxib could suppress EMT and metastasis. Results of PGE₂treatment were opposite to that of Celecoxib. Meanwhile, blockade of RhoA/ROCK1 pathway also exerted prohibitive effects on EMT and metastasis. WB results showed COX2/PGE₂pathway could be regulated by RhoA/ROCK1 pathway and DIM could inhibit RhoA/ROCK1 pathway through modulation of AHR. In vivo assay verified the results in vitro. Co-IP results showed DIM could modulate AHR to reverse EMT directly through inhibition of interaction between AHR and EGFR (epidermal growth factor receptor) so as to block RhoA/ROCK1-mediated COX2/PGE₂pathway which was connected by NF-κB.Conclusions: In brief, modulation of AHR by DIM can reverse EMT process and inhibit metastasis of ESCC through repressing RhoA/ROCK1-mediated COX2/PGE₂pathway.

Psoriasis is an immune‑mediated cutaneous disorder with a high incidence and prevalence. Patients with psoriasis may experience irritation, pain and psychological problems. The cause and underlying molecular etiology of psoriasis remains unknown. In an attempt to achieve a more comprehensive understanding of the molecular pathogenesis of psoriasis, the gene expression profiles of 175 pairs of lesional and corresponding non‑lesional skin samples were downloaded from 5 data sets in the Gene Expression Omnibus (GEO) database. Integrated differentially expressed genes (DEGs) were obtained with the use of R software. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed using the DAVID online analysis tool. The protein‑protein interaction (PPI) network was constructed on the STRING platform and hub genes were calculated with the use of Cytoscape software. Finally, GEO2R was used to determine the expression of the hub genes in scalp psoriasis. A total of 373 genes from the 5 data sets were identified as DEGs, including 277 upregulated and 96 downregulated genes. GO analysis revealed that immune responses and epidermal differentiation/development were the most enriched terms in biological processes, extracellular space/matrix was the most enriched term in cellular components, and endopeptidase inhibitor activity was the most enriched term in molecular functions. In the KEGG pathway enrichment, DEGs were mainly enriched in the metabolic and viral infection‑associated pathways. A total of 17 hub genes were calculated, including CSK2, CDC45, MCM10, SPC25, NDC80, NUF2, AURKA, CENPE, RRM2, DLGP5, HMMR, TTK, IFIT1, RSAD2, IFI6, IFI27 and ISG20, among which interferon‑α‑inducible genes were revealed to display a similar expression pattern as that obtained in scalp psoriasis. This comprehensive bioinformatic re‑analysis of GEO data provides new insights on the molecular pathogenesis of psoriasis and the identification of potential therapeutic targets for the treatment of psoriasis.