Dupilumab in chronic rhinosinusitis with nasal polyposis: current status, challenges, and future perspectives.

INTRODUCTION: Chronic sinusitis with nasal polyposis (CRSwNP) is a common heterogeneous disease that mainly manifests as chronic inflammation of the sinus mucosa. The effect of conventional treatments for CRSwNP, such as oral corticosteroids, intranasal corticosteroids (INCS) and polypectomy, is not always obvious, and postoperative recurrence is common in some CRSwNP patients. In recent years, some biologics have been shown to be very effective in treating refractory CRSwNP, of which dupilumab has attracted much attention as the first monoclonal drug approved to treat nasal polyps. AREAS COVERED: In this review, we discuss the research status of dupilumab in treatment of CRSwNP and how dupilumab differs from other treatment methods. EXPERT OPINION: The European Union and United States have approved dupilumab as the first biological agent for treatment of CRSwNP. Dupilumab can improve symptoms of nasal congestion or obstruction, nasal secretion, and olfactory loss in patients with CRSwNP. It can also improve a patient's health-related quality of life (HR-QoL) and reduce the need for systemic corticosteroids and nasal polyp surgery. While subcutaneous injection of dupilumab is a novel method for treating CRSwNP, it is still necessary to reasonably evaluate which patients might benefit most from biological therapy.

The Tissue Lymphocyte-to-Eosinophil Ratio Predicted Long-Term Recurrence of Eosinophilic CRSwNP.

BACKGROUND: Eosinophilic chronic rhinosinusitis with nasal polyps (Eos-CRSwNP) remains a recalcitrant disease with a high recurrence rate. OBJECTIVE: This study aimed to identify a predictor of long-term recurrence in patients with Eos-CRSwNP. METHODS: A total of 39 Eos-CRSwNP patients who had their initial and recurrent nasal polyps surgically removed were retrospectively included in this study, with 49 Eos-CRSwNP patients without recurrence and 32 patients with non-Eos-CRSwNP matched by randomly chosen. Clinical characteristics were compared among or between groups. Spearman correlation analyses and a backward stepwise multivariate logistic regression analysis were performed to find factors associated with the recurrence and recurrence time of Eos-CRSwNP. Furthermore, a receiver operating characteristic (ROC) curve was used to determine the predictor of long-term Eos-CRSwNP recurrence. RESULTS: The number and ratio of tissue eosinophils were highest in Eos-CRSwNP with recurrence and lowest in non-Eos-CRSwNP. The ratio of tissue lymphocytes was highest in non-Eos-CRSwNP and lowest in Eos-CRSwNP with recurrence, with the number of tissue lymphocytes higher in Eos-CRSwNP without recurrence than the other two groups. The numbers of tissue lymphocytes in the initial nasal polyps were lower and the numbers of tissue eosinophils were higher in the group of recurrent nasal polyps that recurred at >5 years after surgery than in the nasal polyps that recurred at <5 years after surgery. The tissue lymphocyte-to-eosinophil ratio (LER) showed a significant negative correlation with the recurrence and the recurrence time of Eos-CRSwNP. A ROC curve revealed that a tissue LER value < 0.67 predicted long-term Eos-CRSwNP recurrence with 72.73% sensitivity and 82.35% specificity (area under the curve = 0.789). CONCLUSION: Tissue LER is strongly associated with Eos-CRSwNP recurrence and may play a key role in predicting long-term Eos-CRSwNP recurrence.

Artificial intelligence-based prediction of cervical lymph node metastasis in papillary thyroid cancer with CT.

OBJECTIVES: To develop an artificial intelligence (AI) system for predicting cervical lymph node metastasis (CLNM) preoperatively in patients with papillary thyroid cancer (PTC) based on CT images. METHODS: This multicenter retrospective study included the preoperative CT of PTC patients who were divided into the development, internal, and external test sets. The region of interest of the primary tumor was outlined manually on the CT images by a radiologist who has eight years of experience. With the use of the CT images and lesions masks, the deep learning (DL) signature was developed by the DenseNet combined with convolutional block attention module. One-way analysis of variance and least absolute shrinkage and selection operator were used to select features, and a support vector machine was used to construct the radiomics signature. Random forest was used to combine the DL, radiomics, and clinical signature to perform the final prediction. The receiver operating characteristic curve, sensitivity, specificity, and accuracy were used by two radiologists (R1 and R2) to evaluate and compare the AI system. RESULTS: For the internal and external test set, the AI system achieved excellent performance with AUCs of 0.84 and 0.81, higher than the DL (p = .03, .82), radiomics (p < .001, .04), and clinical model (p < .001, .006). With the aid of the AI system, the specificities of radiologists were improved by 9% and 15% for R1 and 13% and 9% for R2, respectively. CONCLUSIONS: The AI system can help predict CLNM in patients with PTC, and the radiologists' performance improved with AI assistance. CLINICAL RELEVANCE STATEMENT: This study developed an AI system for preoperative prediction of CLNM in PTC patients based on CT images, and the radiologists' performance improved with AI assistance, which could improve the effectiveness of individual clinical decision-making. KEY POINTS: • This multicenter retrospective study showed that the preoperative CT image-based AI system has the potential for predicting the CLNM of PTC. • The AI system was superior to the radiomics and clinical model in predicting the CLNM of PTC. • The radiologists' diagnostic performance improved when they received the AI system assistance.

Bone marrow mesenchymal stem cells paracrine TGF-ß1 to mediate the biological activity of osteoblasts in bone repair.

BACKGROUND: Bone marrow mesenchymal stem cells (BMSCs) are an important source of seed cells for regenerative medicine and tissue engineering therapy. BMSCs have multiple differentiation potentials and can release paracrine factors to facilitate tissue repair. Although the role of the osteogenic differentiation of BMSCs has been fully confirmed, the function and mechanism of BMSC paracrine factors in bone repair are still largely unclear. This study aimed to determine the roles of transforming growth factor beta-1 (TGF-ß1) produced by BMSCs in bone tissue repair. METHODS: To confirm our hypothesis, we used a Transwell system to coculture hBMSCs and human osteoblast-like cells without contact, which could not only avoid the interference of the osteogenic differentiation of hBMSCs but also establish the cell-cell relationship between hBMSCs and human osteoblast-like cells and provide stable paracrine substances. In the transwell coculture system, alkaline phosphatase activity, mineralized nodule formation, cell migration and chemotaxis analysis assays were conducted. RESULTS: Osteogenesis, migration and chemotaxis of osteoblast-like cells were regulated by BMSCs in a paracrine manner via the upregulation of osteogenic and migration-associated genes. A TGF-ß receptor I inhibitor (LY3200882) significantly antagonized BMSC-induced biological activity and related gene expression in osteoblast-like cells. Interestingly, coculture with osteoblast-like cells significantly increased the production of TGF-ß1 by BMSCs, and there was potential intercellular communication between BMSCs and osteoblast-like cells. CONCLUSIONS: Our findings provide evidence that the biological mechanism of BMSC-produced TGF-ß1 promotes bone regeneration and repair, providing a theoretical basis and new directions for the application of BMSC transplantation in the treatment of osteonecrosis and bone injury.