Psoriasis is a chronic inflammatory skin disease characterized by excessive proliferation and abnormal keratinocyte development, in which T helper type 17 cells and signal transducer and activator of transcription 3 (STAT3) activation have pivotal roles. Moreover, caveolin-1 (CAV-1) has been implicated in the regulation of signal transduction, and aberrant CAV-1 expression is involved in a variety of diseases. However, whether CAV-1 is involved in psoriasis is unknown. Here we examined CAV-1 expression in the psoriatic epidermis and investigated its role in the pathogenesis of psoriasis. CAV-1 was markedly reduced in lesional epidermis of psoriasis patients. CAV1 silencing in keratinocytes in vitro revealed significant activation of STAT3, leading to increased expression of keratin 16 and several cytokine/chemokines, such as IL-6, C-X-C chemokine ligand 8 (CXCL8), CXCL9, and C-C chemokine ligand 20. In addition, psoriasis-related cytokines, including tumor necrosis factor-α (TNF-α), decreased CAV-1 expression in keratinocytes. Finally, administration of CAV-1 scaffolding domain peptide in a murine model of psoriasis-like skin inflammation induced by imiquimod improved the skin phenotype and reduced epidermal thickness and infiltrating cell counts. Furthermore, expression of TNF-α, IL-17A, and IL-23 was significantly suppressed by this treatment. Collectively, our study indicated that CAV-1 participates in the pathogenesis of psoriasis by regulating the STAT3 pathway and cytokine networks.
The stomatal density (SD) can be a promising target to improve the leaf photosynthesis in soybeans ( Glycine max (L.) Merr). In a conventional SD evaluation, the counting process of the stomata during a manual operation can be time-consuming. We aimed to develop a high-throughput technique for evaluating the SD and elucidating the variation in the SD among various soybean accessions. The central leaflet of the first trifoliolate was sampled, and microscopic images of the leaflet replica were obtained among 90 soybean accessions. The Single Shot MultiBox Detector, an algorithm for an object detection based on deep learning, was introduced to develop an automatic detector of the stomata in the image. The developed detector successfully recognized the stomata in the microscopic image with high-throughput. Using this technique, the value of R 2 reached 0.90 when the manually and automatically measured SDs were compared in the 150 images. This technique discovered a variation in SD from 93 ± 3 to 166 ± 4 mm −2 among the 90 accessions. Our detector can be a powerful tool for a SD evaluation with a large-scale population in crop species, accelerating the identification of useful alleles related to the SD in future breeding programs.
Immune checkpoint inhibitors (ICIs) are monoclonal antibodies that block key mediators of tumor-mediated immune evasion. The frequency of its use has increased rapidly and has extended to numerous cancers. ICIs target immune checkpoint molecules, such as programmed cell death protein 1 (PD-1), PD ligand 1 (PD-L1), and T cell activation, including cytotoxic T-lymphocyte-associated protein-4 (CTLA-4). However, ICI-driven alterations in the immune system can induce various immune-related adverse events (irAEs) that affect multiple organs. Among these, cutaneous irAEs are the most common and often the first to develop. Skin manifestations are characterized by a wide range of phenotypes, including maculopapular rash, psoriasiform eruption, lichen planus-like eruption, pruritus, vitiligo-like depigmentation, bullous diseases, alopecia, and Stevens-Johnson syndrome/toxic epidermal necrolysis. In terms of pathogenesis, the mechanism of cutaneous irAEs remains unclear. Still, several hypotheses have been proposed, including activation of T cells against common antigens in normal tissues and tumor cells, increased release of proinflammatory cytokines associated with immune-related effects in specific tissues/organs, association with specific human leukocyte antigen variants and organ-specific irAEs, and acceleration of concurrent medication-induced drug eruptions. Based on recent literature, this review provides an overview of each ICI-induced skin manifestation and epidemiology and focuses on the mechanisms underlying cutaneous irAEs.
Toll-like receptors (TLRs) are an essential component of the innate immune response to microbial pathogens. TLR3 is localized in intracellular compartments, such as endosomes, and initiates signals in response to virus-derived double-stranded RNA (dsRNA). The TLR3 ectodomain (ECD), which is implicated in dsRNA recognition, is a horseshoe-shaped solenoid composed of 23 leucine-rich repeats (LRRs). Recent mutagenesis studies on the TLR3 ECD revealed that TLR3 activation depends on a single binding site on the nonglycosylated surface in the C-terminal region, comprising H539 and several asparagines within LRR17 to -20. TLR3 localization within endosomes is required for ligand recognition, suggesting that acidic pH is the driving force for TLR3 ligand binding. To elucidate the pH-dependent binding mechanism of TLR3 at the structural level, we focused on three highly conserved histidine residues clustered at the N-terminal region of the TLR3 ECD: His 39 in the N-cap region, His 60 in LRR1, and His 108 in LRR3. Mutagenesis of these residues showed that His 39 , His 60 , and His 108 were essential for ligand-dependent TLR3 activation in a cell-based assay. Furthermore, dsRNA binding to recombinant TLR3 ECD depended strongly on pH and dsRNA length and was reduced by mutation of His 39 , His 60 , and His 108 , demonstrating that TLR3 signaling is initiated from the endosome through a pH-dependent binding mechanism, and that a second dsRNA binding site exists in the N-terminal region of the TLR3 ECD characteristic solenoid. We propose a novel model for the formation of TLR3 ECD dimers complexed with dsRNA, which incorporates this second binding site.
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