Copper-Catalyzed Asymmetric Allylation of N-Aryl Aldimines.

The copper-catalyzed enantioselective allylation reaction of N-aryl aldimines has been developed using a combination of Cu(OAc)2 and SPINOL-based phosphonamidite. This protocol significantly broadens the substrate scope, such that imines bearing various ortho-substituents on the N-aryl were converted smoothly into homoallylic amines in up to 99% yield and 98% ee. Taking advantage of the diversity of the N-aryl motif, three kinds of N-heterocyclic compounds were constructed, respectively, from the corresponding homoallylic amines in merely one step.

Inflammatory endotypes of adenoidal hypertrophy based on a cluster analysis of biomarkers.

OBJECTIVE: To identify adenoid inflammatory endotypes based on inflammatory markers, match endotypes to phenotypes, and predict endotypes. METHODS: This cross-sectional study included 72 children with adenoid hypertrophy. Thirteen inflammatory markers and total immunoglobulin E (TIgE) in adenoid tissue were analyzed using Luminex and enzyme-linked immunosorbent assay (ELISA) for performing cluster analysis. Correlation analysis was used to examine the characteristics of each cluster. Receiver operating characteristic (ROC) curve analysis was performed to screen for preoperative characteristic data with predictive value for adenoid inflammation endotype. RESULTS: The patients were divided into four clusters. Cluster 1 exhibited non-type 2 signatures with low inflammatory marker concentrations, except for the highest expression of Th1-related cytokines. Cluster 2 showed a non-type 2 endotype with the highest concentration of interleukin (IL)-17A and IL-22. Cluster 3 exhibited moderate type 2 inflammation, with the highest concentration of neutrophil factors. Cluster 4 demonstrated significant type 2 inflammation and moderate neutrophil levels. The proportions of AR and serum TIgE levels increased from clusters 1 to 4, and there was a gradual increase in the prevalence of chronic sinusitis from low to high neutrophilic inflammation. The area under the ROC curve for serum TIgE was higher than those for combined or other separate preoperative characteristics for predicting non-type 2 and type 2 inflammation in the adenoid tissue. CONCLUSIONS: The evaluation of cytokines in adenoid tissue revealed four endotypes. Serum TIgE level was an important indicator of the endotype of adenoid inflammation. Identification of adenoid inflammatory endotypes can facilitate targeted treatment decisions.

Association of Dietary Polyunsaturated Fatty Acid Intake with Allergic Rhinitis in Adults: A Cross-Sectional Study of NHANES 2005-2006.

INTRODUCTION: The incidence of allergic rhinitis (AR) is increasing year by year, and the pathogenesis is complex, in which diet may play an important role. The role of polyunsaturated fatty acids (PUFAs) in AR is still controversial. Previous studies have looked at the effects of PUFA during pregnancy, childhood, and adolescence. In this study, we aimed to determine the association between dietary intake of PUFA and AR in adults. METHODS: We used the NHANES database from 2005 to 2006 to include a total of 4,211 adult subjects. We collected dietary PUFA intake data and information on AR. Logistic regression and restricted cubic spline models were constructed to examine the association between PUFA intake and AR in adults. The t test was used to compare daily PUFA intakes in patients with and without AR. RESULTS: In the fully adjusted model (OR: 1.016; 95% CI: 1.003; 1.028), PUFA intake was positively correlated with allergic symptoms, hay fever, and AR in adults (p < 0.05). In addition, daily PUFA intake was significantly higher in people with allergic symptoms, hay fever, and AR than in people without the disease (p < 0.01). CONCLUSIONS: Our results suggest a positive association between dietary PUFA intake and AR in adults to a certain extent. Future studies on dietary PUFA dose will provide new strategies for the prevention and treatment of allergic diseases such as AR related to non-pharmaceutical interventions.

Calpeptin may reverse glucocorticoid-resistance of allergic rhinitis associated with cigarette smoke exposure by down-regulating interferon regulatory factor 1.

Cigarette smoke exposure is an important factor in chronic inflammation in patients with allergic rhinitis (AR); however, the relationship between cigarette smoke and AR-related glucocorticoid resistance requires further study. In mice, calpeptin significantly reduces inflammation of the lower respiratory tract caused by cigarette smoke, but whether it can treat glucocorticoid-resistant AR caused by cigarette smoke requires further research. In this study, we confirmed that cigarette smoke exposure can aggravate the Th2 inflammatory response in AR leading to glucocorticoid resistance. The underlying mechanism may be related to decreased expression of DNA methyltransferase 3a (Dnmt3a), and increased expression of interferon regulatory factor 1 (IRF1). In addition, we found that calpeptin can inhibit the expression of IRF1 and thus treat AR-associated glucocorticoid resistance in rats exposed to cigarette smoke. These data suggest that calpeptin may downregulate IRF1 and therefore treat glucocorticoid resistance in AR-associated with cigarette smoke exposure.

Deep learning for the prediction of residual tumor after radiotherapy and treatment decision-making in patients with nasopharyngeal carcinoma based on magnetic resonance imaging.

Background: Concurrent chemoradiotherapy (CCRT) and induction chemotherapy (IC) plus CCRT (IC + CCRT) are the main treatments for patients with advanced nasopharyngeal carcinoma (NPC). We aimed to develop deep learning (DL) models using magnetic resonance (MR) imaging to predict the risk of residual tumor after each of the 2 treatments and to provide a reference for patients to select the best treatment option. Methods: A retrospective study was conducted on 424 patients with locoregionally advanced NPC who underwent CCRT or IC + CCRT between June 2012 and June 2019 in the Renmin Hospital of Wuhan University. According to the evaluation of MR images taken 3 to 6 months after radiotherapy, patients were divided into 2 categories: residual tumor and non-residual tumor. Transferred U-net and Deeplabv3 neural networks were trained, and the better-performance segmentation model was used to segment the tumor area on axial T1-weighted enhanced MR images. Then, 4 pretrained neural networks for prediction of residual tumors were trained with CCRT and IC + CCRT datasets, and the performances of the models trained using each image and each patient as a unit were evaluated. Patients in the test cohort of CCRT and IC + CCRT datasets were successively classified by the trained CCRT and IC + CCRT models. Model recommendations were formed according to the classification and compared with the treatment decisions of physicians. Results: The Dice coefficient of Deeplabv3 (0.752) was higher than that of U-net (0.689). The average area under the curve (aAUC) of the 4 networks was 0.728 for the CCRT and 0.828 for the IC + CCRT models trained using a single image as a unit, whereas the aAUC for models trained using each patient as a unit was 0.928 for the CCRT and 0.915 for the IC + CCRT models, respectively. The accuracy of the model recommendation and the decision of physicians was 84.06% and 60.00%, respectively. Conclusions: The proposed method can effectively predict the residual tumor status of patients after CCRT and IC + CCRT. Recommendations based on the model prediction results can protect some patients from receiving additional IC and improve the survival rate of patients with NPC.

Predicting prognosis of nasopharyngeal carcinoma based on deep learning: peritumoral region should be valued.

BACKGROUND: The purpose of this study was to explore whether incorporating the peritumoral region to train deep neural networks could improve the performance of the models for predicting the prognosis of NPC. METHODS: A total of 381 NPC patients who were divided into high- and low-risk groups according to progression-free survival were retrospectively included. Deeplab v3 and U-Net were trained to build segmentation models for the automatic segmentation of the tumor and suspicious lymph nodes. Five datasets were constructed by expanding 5, 10, 20, 40, and 60 pixels outward from the edge of the automatically segmented region. Inception-Resnet-V2, ECA-ResNet50t, EfficientNet-B3, and EfficientNet-B0 were trained with the original, segmented, and the five new constructed datasets to establish the classification models. The receiver operating characteristic curve was used to evaluate the performance of each model. RESULTS: The Dice coefficients of Deeplab v3 and U-Net were 0.741(95%CI:0.722-0.760) and 0.737(95%CI:0.720-0.754), respectively. The average areas under the curve (aAUCs) of deep learning models for classification trained with the original and segmented images and with images expanded by 5, 10, 20, 40, and 60 pixels were 0.717 ± 0.043, 0.739 ± 0.016, 0.760 ± 0.010, 0.768 ± 0.018, 0.802 ± 0.013, 0.782 ± 0.039, and 0.753 ± 0.014, respectively. The models trained with the images expanded by 20 pixels obtained the best performance. CONCLUSIONS: The peritumoral region NPC contains information related to prognosis, and the incorporation of this region could improve the performance of deep learning models for prognosis prediction.

Association between 19 Allergens and Chronic Constipation in Adults: NHANES 2005-2006.

INTRODUCTION: There are increasing reports of a link between chronic constipation and allergies in children. However, similar epidemiological evidence is limited in the general adult population. Therefore, in this study, we attempted to assess the association between chronic constipation and allergy in adults aged ≥20 years in the USA. METHODS: We established a logistic regression model to test the relationship between chronic constipation and 19 specific immunoglobulin E (sIgE) types in adults aged ≥20 years using large-sample data from the National Health and Nutrition Examination Survey database (2005-2006). The weekly defecation times of the allergic and non-allergic groups were compared using the t test. RESULTS: We found that sIgE-sensitized participants had a 0.723 lower risk of chronic constipation than the general population (95% confidence interval (CI) = 0.566-0.923). There was a negative association between chronic constipation and sensitizations to peanut (odds ratio (OR) = 0.579, 95% CI = 0.381-0.935), egg (OR = 0.335, 95% CI = 0.134-0.838), dog (OR = 0.723, 95% CI = 0.522-0.965), and cockroach (OR = 0.540, 95% CI = 0.373-0.784). In addition, the frequency of defecation per week increased significantly in people allergic to peanuts and cockroaches (p < 0.05). DISCUSSION/CONCLUSION: The results of this study demonstrate an inverse relationship between sIgE sensitization and chronic constipation in adults. However, the specific association mechanism needs to be further studied.

Fasting Plasma Glucose and Glycohemoglobin with Allergic Symptoms and Specific Sensitization: Results from NHANES 2005-2006.

OBJECTIVE: The National Health and Nutrition Examination Survey (NHANES) data has been used to study the relationship between fasting plasma glucose (FPG) and glycohemoglobin (A1c) in patients with allergic symptoms and specific sensitization, respectively. METHODS: A total of 1,687 participants and a variety of logistic regression models were selected based on the 2005-2006 NHANES (n = 10,348) for our study to describe the relationship between FPG and A1c in subjects with the sensitivity of allergic symptoms, specific sensitization and specific sensitization of 19 allergens, respectively. On this basis, a variety of logistic regression models were further established for hierarchical analysis to study the limiting conditions when FPG and A1c were related to allergic symptoms. RESULTS: We adjusted the confounding factors and found that the risk of specific sensitization increased with the increase in FPG and A1c. Stratified analysis showed that the risk of allergic symptoms increased with the increase in FPG and A1c when born elsewhere other than in the U.S. and Mexico or underweight or overweight or with hypertension. Furthermore, we found that the risk of egg sensitization increased with the increase in FPG and A1c, while the risk of rat sensitization decreased with the increase in FPG. CONCLUSION: Under certain conditions, FPG and A1c were risk factors for allergic symptoms. FPG and A1c were risk factors for specific sensitization, especially egg sensitization. These findings indicate a possible link between diabetes and allergies.

Giant Cell Tumor and Giant Cell Reparative Granuloma of Bone of the Head: CT and MR Imaging Findings.

BACKGROUND: This study aimed to determine the features and differentiation of Giant Cell Reparative Granuloma (GCRG) and Giant Cell Tumor (GCT) of the head on CT and MRI. METHODS: This retrospective study included six patients with histopathology-confirmed head GCRG and 5 patients with histopathology-confirmed head GCT. All images were independently reviewed by two radiologists. The growth pattern, bone changes, MRI signal intensity, enhancement patterns and other image features were recorded. All patients received CT scans and MR images. RESULTS: All the lesions were located centrally in the bone. Osteolytic bone destruction and expansive growth patterns were observed on CT images. Four of six cases broke the cortical bone with residual cortical bone, and the last two showed a thin cortex in GCRG. Five cases broke the cortical bone with residual cortical bone in GCT. There were enhancing septations in GCT lesions on contrast- enhanced T1-Weighted Images (T1WI) while enhancing septations were not present in GCRG cases. The size of GCT lesions was larger than that of GRCG. GCRG and GCT showed iso-low signals on T1WI and iso-high signals on T2-Weighted Images (T2WI). There was a case with cystic or necrotic lesions in each of the two types of lesions. Osteolytic bone destruction and expansive growth patterns were observed in GCTs and GCRGs. CONCLUSION: The size of the GRCG lesion was smaller than that of the GCT. The presence of enhancing septations and the size of the lesion may distinguish GCTs from GCRG.

Differentiation of eosinophilic and non-eosinophilic chronic rhinosinusitis on preoperative computed tomography using deep learning.

OBJECTIVES: This study aimed to develop deep learning (DL) models for differentiating between eosinophilic chronic rhinosinusitis (ECRS) and non-ECRS (NECRS) on preoperative CT. DESIGN: Axial spiral CT images were pre-processed and used to build the dataset. Two semantic segmentation models based on U-net and Deeplabv3 were trained to segment the sinus area on CT images. All patient images were segmented using the better-performing segmentation model and used for training and testing of the transferred efficientnet_b0, resnet50, inception_resnet_v2, and Xception neural networks. Additionally, we evaluated the performances of the models trained using each image and each patient as a unit. PARTICIPANTS: A total of 878 chronic rhinosinusitis (CRS) patients undergoing nasal endoscopic surgery at Renmin Hospital of Wuhan University (Hubei, China) between October 2016 to June 2021 were included. MAIN OUTCOME MEASURES: The precision of each model was assessed based on the receiver operating characteristic curve. Further, we analyzed the confusion matrix and accuracy of each model. RESULTS: The Dice coefficients of U-net and Deeplabv3 were 0.953 and 0.961, respectively. The average area under the curve and mean accuracy values of the four networks were 0.848 and 0.762 for models trained using a single image as a unit, while the corresponding values for models trained using each patient as a unit were 0.893 and 0.853, respectively. CONCLUSIONS: Combining semantic segmentation with classification networks could effectively distinguish between patients with ECRS and those with NECRS based on preoperative sinus CT images. Furthermore, labeling each patient to build a dataset for classification may be more reliable than labeling each medical image.

Deep Learning for Predicting Distant Metastasis in Patients with Nasopharyngeal Carcinoma Based on Pre-Radiotherapy Magnetic Resonance Imaging.

IMPORTANCE: Accurate pre-treatment prediction of distant metastasis in patients with Nasopharyngeal Carcinoma (NPC) enables the implementation of appropriate treatment strategies for high-risk individuals. PURPOSE: To develop and assess a Convolutional Neural Network (CNN) model using pre-therapy Magnetic Resonance (MR) imaging to predict distant metastasis in NPC patients. METHODS: We retrospectively reviewed data of 441 pathologically diagnosed NPC patients who underwent complete radiotherapy and chemotherapy at Renmin Hospital of Wuhan University (Hubei, China) between February 2012 and March 2018. Using Adobe Photoshop, an experienced radiologist segmented MR images with rectangular regions of interest. To develop an accurate model according to the primary tumour, Cervical Metastatic Lymph Node (CMLN), the largest area of invasion of the primary tumour, and image segmentation methods, we constructed intratumoural and intra-peritumoural datasets that were used for training and test of the transfer learning models. Each model's precision was assessed according to its receiver operating characteristic curve and accuracy. Generated high-risk-related Grad-Cams demonstrated how the model captured the image features and further verified its reliability. RESULTS: Among the four models, all intra-peritumoural datasets performed better than the corresponding intratumoural datasets, with the CMLN intra-peritumoural dataset exhibiting the best performance (average area under the curves (AUCs) = 0.88). There was no significant difference between average AUCs of the Max and NPC tumour datasets. AUCs of the eight datasets for the four models were higher than those of the Tumour-Node-Metastasis staging system (AUC=0.67). In most datasets, the xception model had higher AUCs than other models. The efficientnet-b0 and xception models efficiently extracted high-risk features. CONCLUSION: The CNN model predicted distant metastasis in NPC patients with high accuracy. Compared to the primary tumour, the CMLN better predicted distant metastasis. In addition to intratumoural data, peritumoural information can facilitate the prediction of distant metastasis. With a larger sample size, datasets of the largest areas of tumour invasion may achieve meaningful accuracy. Among the models, xception had the best overall performance.

The effect of mind wandering on cognitive flexibility is mediated by boredom.

Cognitive theory of boredom presumes that boredom, an important potential indicator for self-dysregulation, represents to be the result of attention failure. And lapses of attention have been shown to act as a key signal in mind wandering (especially spontaneous mind wandering), which has been found to be positively associated with boredom. If both mind wandering and boredom concurrently occupy individuals' on-task processing resources, it would definitely influence their cognitive flexibility, which is an essential component for self-regulation. Until now, however, there has been little discussion about mind wandering, boredom, and cognitive flexibility at the same time. The present study investigated the hypothesis that boredom can mediate the effect of mind wandering on cognitive flexibility at trait-level by adopting a cross-sectional exploratory study design and anonymous structured questionnaires in three studies (N = 449,182 and 190 for Studies 1, 2 and 3, respectively). Correlation analysis demonstrated that mind wandering (especially spontaneous mind wandering) was positively related to boredom, and that cognitive flexibility was negatively related to mind wandering and boredom, respectively. Mediation analysis revealed an indirect effect of mind wandering (especially spontaneous mind wandering) on cognitive flexibility through boredom. In conclusion, these findings are useful to build a theoretical framework for future clinical practice. An implication of these findings is the possibility that efficacious strategies targeting at reducing boredom are needed to decrease the detriment effect of spontaneous mind wandering on cognitive flexibility.

Corrigendum: The impacts of mind-wandering on flow: Examining the critical role of physical activity and mindfulness.

[This corrects the article DOI: 10.3389/fpsyg.2022.674501.].

Notch2-dependent GATA3+ Treg cells alleviate allergic rhinitis by suppressing the Th2 cell response.

The aim of this study was to investigate the role and mechanism of Notch2-dependent GATA3+ Treg cells in allergic rhinitis (AR). Samples were collected from patients in the control and AR groups to detect differences in the numbers of GATA3+ Treg cells and their intracellular Notch2 levels. The effects of Notch2 on GATA3+ Treg cell differentiation and function in vitro were detected. AR mice were subjected to adoptive transfer of GATA3+ Treg cells to detect changes in the allergic inflammatory response and Th2 cells. Mice with Treg cell-specific knockout of Notch2 were constructed, and an AR model was established to detect the changes. The number of GATA3+ Treg cells and intracellular Notch2 expression in peripheral blood of the AR group were decreased compared with the controls (P < 0.05), and the number of GATA3+ Treg cells was significantly negatively correlated with the level of allergen-specific IgE (sIgE; P < 0.01). In vitro experiments showed that Notch2 promoted the differentiation and immunosuppressive function of GATA3+ Treg cells, and Notch2 directly promoted GATA3 transcription in Treg cells (P < 0.05). Animal experiments indicated that adoptive transfer of GATA3+ Treg cells reduced the allergic inflammatory response in AR mice (P < 0.05). The number of GATA3+ Treg cells was decreased in gene knockout mice (P < 0.05), and autoimmune inflammation was observed. After modeling, the allergic inflammatory response was further aggravated (P < 0.05). Overall, our findings indicate that Notch2 alleviates AR by specifically increasing GATA3+ Treg cell differentiation. Notch2 expressed in Treg cells is expected to be a new therapeutic target for AR.

Diagnostic Value of a Novel Eosinophil Cationic Protein-Myeloperoxidase Test Paper Before and After Treatment for Allergic Rhinitis.

Purpose: To develop and evaluate the effectiveness/clinical application of an eosinophil cationic protein-myeloperoxidase (ECP-MPO) test paper before and after treatment in patients with allergic rhinitis (AR). Patients and Methods: We included 40 controls and 106 AR patients who were enrolled in the Allergy Clinic of Renmin Hospital of Wuhan University. Total IgE, specific IgE and skin prick test (SPT) were detected in all participants. AR patients were treated with oral cetirizine hydrochloride for 14 days. The ECP-MPO test paper results, nasal secretion smear and eosinophil counts, rhinoconjunctivitis total nasal symptom score (TNSS), quality of life questionnaire (RQLQ), visual analogue scale (VAS), serum Th1/Th2/Th17 cytokine, and chemokine data were collected pre- and post-treatment. ECP concentrations in nasal secretions were assessed by ELISA. Pearson correlation test and Kappa consistency test were used for statistical analysis. Results: The post-treatment colour grade of the ECP-MPO test paper was lower in AR patients than the pre-treatment grade. The chromogenic grade correlated positively with the ECP concentration and the eosinophil count in nasal secretions both before and after treatment. Positive ECP-MPO test paper results were consistent with positive SPT, Der p-IgE and Der f-IgE result (Kappa values, 0.843, 0.810, 0.795, respectively). The pre- and post-treatment chromogenic grades correlated positively with the TNSS (r1=0·691; r2=0·539), RQLQ (r1=0·783; r2=0·625), and VAS (r1=0·703; r2=0·682) scores in AR patients. Conclusion: The ECP-MPO test paper can effectively detect ECP in nasal secretions, and its results are consistent with those from the SPT, Der p-IgE and Der f-IgE result. Its chromogenic grade can reflect the symptom severity and specific cytokine and chemokine levels in AR patients.

The impacts of mind-wandering on flow: Examining the critical role of physical activity and mindfulness.

Background: Individuals with mind-wandering experience their attention decoupling from their main task at hand while others with flow experience fully engage in their task with the optimum experience. There seems to be a negative relationship between mind-wandering and flow. However, it remains unclear to what extent mind-wandering exerts an impact on flow. And it is also elusive whether physical activity and mindfulness, which are as important factors that affected individuals' attentional control and psychological health, are beneficial in explaining the association between mind-wandering and flow. The current study investigated the relationship between mind-wandering and flow, and the potential mediation effects of physical activity and mindfulness in this association. Methods: A cross-sectional exploratory study design, including multiple scales such as the Mind-Wandering Questionnaire (MWQ), the International Physical Activity Questionnaire Short Form (IPAQ), Mindfulness Attention and Awareness Scale (MAAS), and the Short Dispositional Flow Scale (S-DFS) was applied. Descriptive statistics and bivariate correlation coefficients were applied in the analysis of these data. A multiple mediation model was used to examine the relationships between mind-wandering, flow, physical activity, and mindfulness. Results: Mind-wandering was inversely associated with physical activity, mindfulness and flow, respectively; and flow was positively related to physical activity and mindfulness, respectively. Moreover, multiple mediation results demonstrated that physical activity and mindfulness, respectively, mediated the relationship between mind-wandering and flow. Conclusion: These findings are helpful to understand how our minds attend to the present moment, and the crucial roles of physical activity and mindfulness in the association between mind-wandering and flow. An implication of these is the possibility that the effective strategies aimed at enhancing both the levels of physical activity and mindfulness are needed to reduce the negative impact of mind-wandering on flow.

Allergen immunotherapy enhances the immunosuppressive effects of Treg cells to alleviate allergic rhinitis by decreasing PU-1+ Treg cell numbers.

OBJECTIVE: To investigate the role of Tregs and their subtypes in the treatment of allergic rhinitis with allergen immunotherapy (AIT) as well as the underlying mechanism. METHODS: 1. Thirty-one healthy controls, 29 Allergic rhinitis (AR) patients and 16 AR patients treated with AIT were recruited. The total nasal symptom scores (TNSSs) were calculated. The serum levels of IgE, IL-2, TNF-α, IFN-γ, IL-4, IL-5, IL-6, IL-10 and IL-17 were measured. 2. Changes in the proportions of CD4+ T cells, Treg cells, Treg subtypes and Th1/Th2/Th9/Th17/Tfh cells in the peripheral blood of the subjects in the three groups were measured. 3. The correlations of Treg cells, Treg subtypes and TNSS with the levels of various cytokines in the AR group and AIT group were analysed. RESULTS: 1. Compared with the control group, the TNSS and IgE, IL-5 and IL-6 levels in the AR group were significantly increased, while the IL-2, IFN-γ and IL-10 levels were significantly decreased (P < 0.05). Compared with the AR group, the TNSS and IgE, IL-5 and IL-6 levels in the AIT group were significantly decreased, while the IL-2, IFN-γ and IL-10 levels were significantly increased (P < 0.05). 2. Compared with the control group, the proportions of Tregs, GATA3+ Tregs and Th1 cells in the AR group were significantly reduced, while the proportions of PU-1+ Tregs, T-bet+ Tregs and Th2 cells were significantly increased (P < 0.05). Compared with the AR group, the proportions of Tregs and Th1 cells in the AIT group were significantly increased, while the proportions of PU-1+ Tregs and Th2 cells were decreased (P < 0.05). 3. Correlation analysis showed that Treg cell proportions were negatively correlated with the TNSS, sIgE levels, IL-5 levels and IL-6 levels but positively correlated with the IL-2 and IL-10 levels (P < 0.05). PU-1+ Treg cell proportions were positively correlated with the TNSS, sIgE levels, IL-5 levels and IL-6 levels but negatively correlated with the Treg cell proportions, IL-2 levels and IL-10 levels (P < 0.05). CONCLUSIONS: AIT can reduce the proportions of PU-1+ Treg subtypes in AR patients. PU-1+ Treg cell numbers can potentially be used as an indicator to monitor the therapeutic effect of AIT on AR.

Deep learning for locally advanced nasopharyngeal carcinoma prognostication based on pre- and post-treatment MRI.

PURPOSE: We aimed to predict the prognosis of advanced nasopharyngeal carcinoma (stage Ⅲ-Ⅳa) using Pre- and Post-treatment MR images based on deep learning (DL). METHODS: A total of 206 patients with primary nasopharyngeal carcinoma who were diagnosed and treated at the Renmin Hospital of Wuhan University between June 2012 and January 2018 were retrospectively selected. A rectangular region of interest (ROI), which included the tumor area, surrounding tissues and organs, was delineated on each Pre- and Post-treatment MR image. Two Inception-Resnet-V2 based transfer learning models, named Pre-model and Post-model, were trained with the Pre-treatment images and the Post-treatment images, respectively. In addition, an ensemble learning model based on the Pre-model and Post-models was established. The three established models were evaluated by receiver operating characteristic curve (ROC), confusion matrix, and Harrell's concordance indices (C-index). High-risk-related gradient-weighted class activation mapping (Grad-CAM) images were developed according to the DL models. RESULTS: The Pre-model, Post-model, and ensemble model displayed a C-index of 0.717 (95% CI: 0.639 to 0.795), 0.811 (95% CI: 0.745-0.877), 0.830 (95% CI: 0.767-0.893), and AUC of 0.741 (95% CI: 0.584-0.900), 0.806 (95% CI: 0.670-0.942), and 0.842 (95% CI: 0.718-0.967) for the test cohort, respectively. In comparison with the models, the performance of Post-model was better than the performance of Pre-model, which indicated the importance of Post-treatment images for prognosis prediction. All three DL models performed better than the TNM staging system (0.723, 95% CI: 0.567-0.879). The captured features presented on Grad-CAM images suggested that the areas around the tumor and lymph nodes were related to the prognosis of the tumor. CONCLUSIONS: The three established DL models based on Pre- and Post-treatment MR images have a better performance than TNM staging. Post-treatment MR images are of great significance for prognosis prediction and could contribute to clinical decision-making.

Allergy-related outcomes and sleep-related disorders in adults: a cross-sectional study based on NHANES 2005-2006.

BACKGROUND: Epidemiological evidence between the sleep disorders and allergy-related outcomes is limited. OBJECTIVES: The purpose of the present study was to estimate the relationship between sleep disorders and allergy-related outcomes in adults. METHODS: We built logistic regression models to examine the associations between sleep disorders and allergy-related outcomes in adult participants using the 2005-2006 NHANES database. Allergy-related outcomes included sIgE levels, asthma, hay fever, sneezing, wheezing, and eczema. Sleep disorders included sleep latency, sleep length, sleep problems, OSA symptoms, and daytime sleepiness. A t-test was used for between-group comparisons. RESULTS: Participants with OSA symptoms had 2.72 × higher odds of experiencing hay fever and 1.54 × higher odds of having eczema compared to Non-OSA symptoms participants. Participants with insufficient sleep (≤ 6 h/night) had 1.27 × higher odds of developing allergic sensitisation compared to participants with adequate sleep (7-8 h/night). Sneezing was positively associated with sleep problems (OR: 1.706; 95% CI 1.386, 2.099), OSA symptoms (OR: 1.297; 95% CI 1.049, 1.605), and daytime sleepiness (OR: 1.569; 95% CI 1.205, 2.04). CONCLUSION: Our findings suggest a positive association between allergy-related outcomes and sleep disorders. In particular, OSA symptoms, daytime sleepiness, and sleep problems are strongly associated with allergic conditions.

Anatomical Partition-Based Deep Learning: An Automatic Nasopharyngeal MRI Recognition Scheme.

BACKGROUND: Training deep learning (DL) models to automatically recognize diseases in nasopharyngeal MRI is a challenging task, and optimizing the performance of DL models is difficult. PURPOSE: To develop a method of training anatomical partition-based DL model which integrates knowledge of clinical anatomical regions in otorhinolaryngology to automatically recognize diseases in nasopharyngeal MRI. STUDY TYPE: Single-center retrospective study. POPULATION: A total of 2485 patients with nasopharyngeal diseases (age range 14-82 years, female, 779[31.3%]) and 600 people with normal nasopharynx (age range 18-78 years, female, 281[46.8%]) were included. SEQUENCE: 3.0 T; T2WI fast spin-echo sequence. ASSESSMENT: Full images (512 × 512) of 3085 patients constituted 100% of the dataset, 50% and 25% of which were randomly retained as two new datasets. Two new series of images (seg112 image [112 × 112] and seg224 image [224 × 224]) were automatically generated by a segmentation model. Four pretrained neural networks for nasopharyngeal diseases classification were trained under the nine datasets (full image, seg112 image, and seg224 image, each with 100% dataset, 50% dataset, and 25% dataset). STATISTICAL TESTS: The receiver operating characteristic curve was used to evaluate the performance of the models. Analysis of variance was used to compare the performance of the models built with different datasets. Statistical significance was set at P < 0.05. RESULTS: When the 100% dataset was used for training, the performances of the models trained with the seg112 images (average area under the curve [aAUC] 0.949 ± 0.052), seg224 images (aAUC 0.948 ± 0.053), and full images (aAUC 0.935 ± 0.053) were similar (P = 0.611). When the 25% dataset was used for training, the mean aAUC of the models that were trained with seg112 images (0.823 ± 0.116) and seg224 images (0.765 ± 0.155) was significantly higher than the models that were trained with full images (0.640 ± 0.154). DATA CONCLUSION: The proposed method can potentially improve the performance of the DL model for automatic recognition of diseases in nasopharyngeal MRI. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 1.