Histological Severity Risk Factors Identification in Juvenile-Onset Recurrent Respiratory Papillomatosis: How Immunohistochemistry and AI Algorithms Can Help?

Juvenile-onset recurrent respiratory papillomatosis (JoRRP) is a condition characterized by the repeated growth of benign exophytic papilloma in the respiratory tract. The course of the disease remains unpredictable: some children experience minor symptoms, while others require multiple interventions due to florid growth. Our study aimed to identify histologic severity risk factors in patients with JoRRP. Forty-eight children from two French pediatric centers were included retrospectively. Criteria for a severe disease were: annual rate of surgical endoscopy ≥ 5, spread to the lung, carcinomatous transformation or death. We conducted a multi-stage study with image analysis. First, with Hematoxylin and eosin (HE) digital slides of papilloma, we searched for morphological patterns associated with a severe JoRRP using a deep-learning algorithm. Then, immunohistochemistry with antibody against p53 and p63 was performed on sections of FFPE samples of laryngeal papilloma obtained between 2008 and 2018. Immunostainings were quantified according to the staining intensity through two automated workflows: one using machine learning, the other using deep learning. Twenty-four patients had severe disease. For the HE analysis, no significative results were obtained with cross-validation. For immunostaining with anti-p63 antibody, we found similar results between the two image analysis methods. Using machine learning, we found 23.98% of stained nuclei for medium intensity for mild JoRRP vs. 36.1% for severe JoRRP (p = 0.041); and for medium and strong intensity together, 24.14% for mild JoRRP vs. 36.9% for severe JoRRP (p = 0.048). Using deep learning, we found 58.32% for mild JoRRP vs. 67.45% for severe JoRRP (p = 0.045) for medium and strong intensity together. Regarding p53, we did not find any significant difference in the number of nuclei stained between the two groups of patients. In conclusion, we highlighted that immunochemistry with the anti-p63 antibody is a potential biomarker to predict the severity of the JoRRP.

Deep Learning-Based Classification of Inherited Retinal Diseases Using Fundus Autofluorescence.

Background. In recent years, deep learning has been increasingly applied to a vast array of ophthalmological diseases. Inherited retinal diseases (IRD) are rare genetic conditions with a distinctive phenotype on fundus autofluorescence imaging (FAF). Our purpose was to automatically classify different IRDs by means of FAF images using a deep learning algorithm. Methods. In this study, FAF images of patients with retinitis pigmentosa (RP), Best disease (BD), Stargardt disease (STGD), as well as a healthy comparable group were used to train a multilayer deep convolutional neural network (CNN) to differentiate FAF images between each type of IRD and normal FAF. The CNN was trained and validated with 389 FAF images. Established augmentation techniques were used. An Adam optimizer was used for training. For subsequent testing, the built classifiers were then tested with 94 untrained FAF images. Results. For the inherited retinal disease classifiers, global accuracy was 0.95. The precision-recall area under the curve (PRC-AUC) averaged 0.988 for BD, 0.999 for RP, 0.996 for STGD, and 0.989 for healthy controls. Conclusions. This study describes the use of a deep learning-based algorithm to automatically detect and classify inherited retinal disease in FAF. Hereby, the created classifiers showed excellent results. With further developments, this model may be a diagnostic tool and may give relevant information for future therapeutic approaches.

Requirement of Mucosa-Associated Lymphoid Tissue Lymphoma Translocation Protein 1 Protease Activity for Fcγ Receptor-Induced Arthritis, but Not Fcγ Receptor-Mediated Platelet Elimination, in Mice.

OBJECTIVE: Fcγ receptors (FcγR) play important roles in both protective and pathogenic immune responses. The assembly of the CBM signalosome encompassing caspase recruitment domain-containing protein 9, B cell CLL/lymphoma 10, and mucosa-associated lymphoid tissue lymphoma translocation protein 1 (MALT-1) is required for optimal FcγR-induced canonical NF-κB activation and proinflammatory cytokine release. This study was undertaken to clarify the relevance of MALT-1 protease activity in FcγR-driven events and evaluate the therapeutic potential of selective MALT-1 protease inhibitors in FcγR-mediated diseases. METHODS: Using genetic and pharmacologic disruption of MALT-1 scaffolding and enzymatic activity, we assessed the relevance of MALT-1 function in murine and human primary myeloid cells upon stimulation with immune complexes (ICs) and in murine models of autoantibody-driven arthritis and immune thrombocytopenic purpura (ITP). RESULTS: MALT-1 protease function is essential for optimal FcγR-induced production of proinflammatory cytokines by various murine and human myeloid cells stimulated with ICs. In contrast, MALT-1 protease inhibition did not affect the Syk-dependent, FcγR-mediated production of reactive oxygen species or leukotriene B4 . Notably, pharmacologic MALT-1 protease inhibition in vivo reduced joint inflammation in the murine K/BxN serum-induced arthritis model (mean area under the curve for paw swelling of 45.42% versus 100% in control mice; P = 0.0007) but did not affect platelet depletion in a passive model of ITP. CONCLUSION: Our findings indicate a specific contribution of MALT-1 protease activity to FcγR-mediated events and suggest that MALT-1 protease inhibitors have therapeutic potential in a subset of FcγR-driven inflammatory disorders.

DPP9 enzymatic activity in hematopoietic cells is dispensable for mouse hematopoiesis.

Dipeptidyl peptidase 9 (DPP9) is a ubiquitously expressed intracellular prolyl peptidase implicated in immunoregulation. However, its physiological relevance in the immune system remains largely unknown. We investigated the role of DPP9 enzyme in immune system by characterizing DPP9 knock-in mice expressing a catalytically inactive S729A mutant of DPP9 enzyme (DPP9ki/ki mice). DPP9ki/ki mice show reduced number of lymphoid and myeloid cells in fetal liver and postnatal blood but their hematopoietic cells are fully functional and able to reconstitute lymphoid and myeloid lineages even in competitive mixed chimeras. These studies demonstrate that inactivation of DPP9 enzymatic activity does not lead to any perturbations in mouse hematopoiesis.

Vitamin D receptor agonists as anti-inflammatory agents.

1alpha,25-dihydroxyvitamin D3 (1,25-[OH]2D3), the biologically active form of vitamin D, is a secosteroid hormone that is essential for bone and mineral homeostasis. In addition, this hormone regulates the growth and differentiation of many cell types and has pronounced immunoregulatory and anti-inflammatory properties. Current therapeutic indications include osteoporosis, secondary hyperparathyroidism and psoriasis, but the anti-proliferative, prodifferentiative, antibacterial, immunomodulatory and anti-inflammatory properties of vitamin D receptor agonists could be exploited in a variety of additional clinical conditions. In particular, the pleiotropic anti-inflammatory effects induced by vitamin D receptor agonists could turn out to be beneficial in different pathologies mediated by chronic inflammatory responses.