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IL-17-producing T helper (Th17) cells have been implicated in the pathogenesis of many inflammatory and autoimmune diseases. Targeting the effector cytokines IL-17 and GM-CSF secreted by autoimmune Th17 cells has been shown to be effective for the treatment of the diseases. Understanding a molecular basis of Th17 differentiation and effector functions is therefore critical for the regulation of the pathogenicity of tissue Th17 cells in chronic inflammation. Here, we discuss the roles of proinflammatory cytokines and environmental stimuli in the control of Th17 differentiation and chronic tissue inflammation by pathogenic Th17 cells in humans and in mouse models of autoimmune diseases. We also highlight recent advances in the regulation of pathogenic Th17 cells by gut microbiota and immunometabolism in autoimmune arthritis.

A pathological evaluation is one of the most important methods for the diagnosis of malignant lymphoma. A standardized diagnosis is occasionally difficult to achieve even by experienced hematopathologists. Therefore, established procedures including a computer-aided diagnosis are desired. This study aims to classify histopathological images of malignant lymphomas through deep learning, which is a computer algorithm and type of artificial intelligence (AI) technology. We prepared hematoxylin and eosin (H&E) slides of a lesion area from 388 sections, namely, 259 with diffuse large B-cell lymphoma, 89 with follicular lymphoma, and 40 with reactive lymphoid hyperplasia, and created whole slide images (WSIs) using a whole slide system. WSI was annotated in the lesion area by experienced hematopathologists. Image patches were cropped from the WSI to train and evaluate the classifiers. Image patches at magnifications of ×5, ×20, and ×40 were randomly divided into a test set and a training and evaluation set. The classifier was assessed using the test set through a cross-validation after training. The classifier achieved the highest levels of accuracy of 94.0%, 93.0%, and 92.0% for image patches with magnifications of ×5, ×20, and ×40, respectively, in comparison to diffuse large B-cell lymphoma, follicular lymphoma, and reactive lymphoid hyperplasia. Comparing the diagnostic accuracies between the proposed classifier and seven pathologists, including experienced hematopathologists, using the test set made up of image patches with magnifications of ×5, ×20, and ×40, the best accuracy demonstrated by the classifier was 97.0%, whereas the average accuracy achieved by the pathologists using WSIs was 76.0%, with the highest accuracy reaching 83.3%. In conclusion, the neural classifier can outperform pathologists in a morphological evaluation. These results suggest that the AI system can potentially support the diagnosis of malignant lymphoma. This study aims to classify histopathological images of malignant lymphoma through deep learning. The classifier achieved the high levels of accuracy in comparison to diffuse large B-cell lymphoma, follicular lymphoma, and reactive lymphoid hyperplasia, which were higher than those of pathologists. Artificial intelligence can potentially support diagnosis of malignant lymphoma.

Nyctinasty is the circadian rhythmic nastic movement of leguminous plants in response to the onset of darkness, a unique and intriguing phenomenon that has attracted attention for centuries. The movement itself is caused by the asymmetric volume change of motor cells between the adaxial and abaxial sides of the leaflet. Recently, we identified the ion channels responsible for the volume change of motor cells during the leaf-opening process of Samanea saman; the asymmetric expression of SsSLAH1, which is under the control of SsCCA1, was found to play a key role in this process. Here, we summarize the history of the study of nyctinasty, our current results and several insights for further study.

Foxp3+ regulatory T (Treg) cells are pivotal in maintaining immunological self-tolerance and tissue homeostasis; however, it remains unclear how tissue Treg cells respond to liver injury and regulate chronic inflammation, which can cause liver fibrosis. We report here that hepatic Treg cells play a critical role in preventing liver pathology by suppressing inflammatory cellular immunity that can promote liver damage and fibrosis. Chronic liver inflammation induced by injections of carbon tetrachloride (CCl4) led to preferential expansion of hepatic Treg cells that prevented liver fibrosis. In contrast, depletion of Treg cells in the CCl4-induced liver fibrosis model exacerbated the severity of liver pathology. Treg depletion unleashed tissue cellular immunity and drove the activation and expansion of the pro-fibrotic IL-4-producing T helper 2 cells, as well as CCR2high Ly-6Chigh inflammatory monocytes/macrophages in the inflamed liver. Although Treg expression of amphiregulin plays a key role in tissue remodeling and repair in various inflammation models, amphiregulin from hepatic Treg cells, the largest producer among liver immune cells, was dispensable for maintaining liver homeostasis and preventing liver fibrosis during CCl4-induced chronic inflammation. Our results indicate that Treg cells control chronic liver inflammation and fibrosis by regulating the aberrant activation and functions of immune effector cells. Harnessing Treg functions, which effectively regulate tissue cellular immunity, may be a therapeutic strategy for preventing and treating liver fibrosis.

In rheumatoid arthritis (RA), various hematopoietic and non-hematopoietic cells present in the synovial tissue secrete numerous inflammatory mediators including pro-inflammatory cytokines critical for the induction of chronic joint inflammation and bone destruction. Fibroblast-like synoviocytes (FLSs) in the non-hematopoietic cell compartment are key inflammatory cells activated in inflamed joints and driving the disease; yet how synovial tissue inflammation is modulated by autoimmune T cells is not fully understood. In this review, mainly based on recent findings with a mouse model of spontaneous autoimmune arthritis, we discuss the mechanism of Th17-mediated synovial tissue inflammation; that is, what environmental stimuli and arthritogenic self-antigens trigger arthritis, how arthritogenic T cells initiate joint inflammation by stimulating FLSs, and how the cellular sources of GM-CSF from lymphoid and tissue stromal cells in the synovium contribute to the development of arthritis. We also highlight possible plasticity of Th17 cells toward pathogenic GM-CSF producers, and the functional instability of regulatory T cells under inflammatory conditions in RA joints.

Histopathologic evaluation of muscle biopsy samples is essential for classifying and diagnosing muscle diseases. However, the numbers of experienced specialists and pathologists are limited. Although new technologies such as artificial intelligence are expected to improve medical reach, their use with rare diseases, such as muscle diseases, is challenging because of the limited availability of training datasets. To address this gap, we developed an algorithm based on deep convolutional neural networks (CNNs) and collected 4041 microscopic images of 1400 hematoxylin-and-eosin-stained pathology slides stored in the National Center of Neurology and Psychiatry for training CNNs. Our trained algorithm differentiated idiopathic inflammatory myopathies (mostly treatable) from hereditary muscle diseases (mostly non-treatable) with an area under the curve (AUC) of 0.996 and achieved better sensitivity and specificity than the diagnoses done by nine physicians under limited diseases and conditions. Furthermore, it successfully and accurately classified four subtypes of the idiopathic inflammatory myopathies with an average AUC of 0.958 and classified seven subtypes of hereditary muscle disease with an average AUC of 0.936. We also established a method to validate the similarity between the predictions made by the algorithm and the seven physicians using visualization technology and clarified the validity of the predictions. These results support the reliability of the algorithm and suggest that our algorithm has the potential to be used straightforwardly in a clinical setting. The authors developed a deep convolutional neural network-based algorithm to support pathological muscle diagnosis. The algorithm differentiated idiopathic inflammatory myopathies and outperformed nine human physicians under limited diseases and conditions. These results suggest that the algorithm has the potential to be used directly in clinical settings.

Programmed necrosis, such as necroptosis and pyroptosis, is a highly pro-inflammatory cellular event that is associated with chronic inflammation. Although there are various triggers of pyroptosis and necroptosis in autoimmune tissue inflammation and subsequent lytic forms of cell death release abundant inflammatory mediators, including damage-associated molecular patterns and IL-1β, capable of amplifying autoimmune Th17 effector functions, it remains largely unclear whether the programs play a crucial role in the pathogenesis of autoimmune arthritis. We herein report that Gasdermin D (Gsdmd) and receptor interacting serine/threonine kinase 3 (Ripk3)—key molecules of pyroptosis and necroptosis, respectively—are upregulated in inflamed synovial tissues, but dispensable for IL-1β production and the development of IL-17-producing T helper (Th17) cell-mediated autoimmune arthritis in SKG mice. Gsdmd −/− , Ripk3 −/− , or Gsdmd −/− Ripk3 −/− SKG mice showed severe arthritis with expansion of arthritogenic Th17 cells in the draining LNs and inflamed joints, which was comparable to that in wild-type SKG mice. Despite the marked reduction of IL-1β secretion from Gsdmd −/− or Ripk3 −/− bone marrow-derived DCs by canonical stimuli, IL-1β levels in the inflamed synovium were not affected in the absence of Gsdmd or Ripk3. Our results revealed that T cell-mediated autoimmune arthritis proceeds independently of the pyroptosis and necroptosis pathways.

Purpose Cytomegalovirus (CMV) corneal endotheliitis often causes severe visual impairment owing to irreversible corneal endothelial dysfunction. Given the side effects of systemic antiviral therapy, development of an approved topical antiviral agent for CMV corneal endotheliitis is desirable. This study evaluated the efficacy and safety of topical 0.15% GCV gel, ROH-101, in the treatment of CMV corneal endotheliitis in Japanese patients. Study design Open-label, multicenter, uncontrolled, phase 3 study (jRCT2051210064). Methods The study was conducted from August 2021 to December 2022, with a 2-week run-in period with 0.1% fluorometholone eye drops alone, a 12-week treatment period with additional ROH-101, and a 24-week post-treatment observation period after discontinuation of ROH-101. The primary endpoint was the proportion of patients achieving a CMV DNA copy number in the aqueous humor of less than 10 3 copies/mL at week 12. The clinical findings and safety were assessed over the treatment and post-treatment observation periods. Results Twelve eyes of 12 patients with PCR-proven CMV corneal endotheliitis were enrolled. Treatment was discontinued in 1 eye owing to an adverse event. The other 11 eyes completed 12 weeks of treatment with 63.6% achieving the primary endpoint. The clinical findings, such as corneal edema, coin-shaped lesions, and anterior chamber inflammation, improved in all 11 eyes and did not worsen in 8 eyes that completed the post-treatment observation period. Endothelial cell density was well maintained, and none of the 11 eyes showed corneal endothelial dysfunction. Mild adverse drug reactions were reported in 3 eyes (8.3%). Conclusion ROH-101 was a safe and efficacious treatment in Japanese patients diagnosed with CMV corneal endotheliitis.

Intramural esophageal dissection is a rare disease characterized by a laceration of the submucosal layer in the esophageal wall due to mechanical damage or esophageal pressure, resulting in the separation of the mucosal layer from the muscularis layer. This report presents a case of intramural esophageal dissection induced by vomiting during barium esophagography in a 70‐year‐old man undergoing evaluation for esophageal cancer. Preoperative assessments included endoscopic biopsies and the placement of a marking clip, followed by barium esophagography. During the procedure, the patient experienced vomiting and subsequent neck‐chest pain. Computed tomography revealed a barium‐filled dissection cavity within the esophagus. Esophagogastroduodenoscopy identified submucosal dissection proximal to esophageal cancer, exposing the muscularis layer and the entry site was at the same level as the biopsy site. The patient was treated conservatively with fasting, leading to symptom resolution. Follow‐up endoscopic evaluations confirmed that the entry site remained open but epithelialized, and the esophageal wound had healed.

During thymic negative selection, autoreactive thymocytes carrying T cell receptor (TCR) with overtly strong affinity to self-MHC/self-peptide are removed by Bim-dependent apoptosis, but how Bim is specifically regulated to link TCR activation and apoptosis induction is unclear. Here we identify a murine T cell-specific genomic enhancer E BAB ( Bub1 - Acoxl - Bim ) , whose deletion leads to accumulation of thymocytes expressing high affinity TCRs. Consistently, E BAB knockout mice have defective negative selection and fail to delete autoreactive thymocytes in various settings, with this defect accompanied by reduced Bim expression and apoptosis induction. By contrast, E BAB is dispensable for maintaining peripheral T cell homeostasis via Bim-dependent pathways. Our data thus implicate E BAB as an important, developmental stage-specific regulator of Bim expression and apoptosis induction to enforce thymic negative selection and suppress autoimmunity. Our study unravels a part of genomic enhancer codes that underlie complex and context-dependent gene regulation in TCR signaling. Autoreactive T cells are deleted in the thymus via thymic negative selection and Bim-mediated apoptosis. Here the authors identify a cis -acting enhancer, E BAB , that is essential for proper Bim expression and apoptosis induction, and show that E BAB deficiency specifically impairs thymic negative selection without affecting peripheral T cell homeostasis.