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Background: Worldwide incidence and prevalence of both asthma and type 1 diabetes mellitus (T1DM) in children have been increasing in past decades. Association between the two diseases has been found in some but not in other studies. Objective:We conducted a meta-analysis to verify such an association, and bidirectional Mendelian randomization analysis to examine the potential cause-effect relationships.Methods: Three databases (PubMed, Embase, and Web of Science) were searched from their inception to February 1, 2021. Pooled hazard ratios (HR) or odds ratios (OR), and 95% confidence intervals, were calculated. Associations between singlenucleotide polymorphisms with childhood asthma and T1DM were selected based on genome-wide association studies. The outcome datasets were obtained from FinnGen study. We used the inverse-variance-weighted (IVW), weighted median and MR-Egger methods to estimate causal effects. To assess robustness and horizontal pleiotropy, MR-Egger regression and MR pleiotropy residual sum and outlier test were conducted. Results:In meta-analysis, childhood asthma was associated with an increased risk of T1DM (HR = 1.30, 95% CI 1.05-1.61, P = .014), whereas T1DM was not associated with the risk of asthma (HR = 0.98, 95% CI 0.64-1.51, P = .941; OR = 0.84, 95% CI 0.65-1.08, P = .168). MR analysis indicated increased genetic risk of T1DM in children with asthma (OR = 1.308; 95% CI 1.030-1.661; P = .028). Analysis using the IVW method indicated no association between T1DM and genetic risk of asthma (OR = 1.027, 95%CI 0.970-1.089, P = .358). Conclusion:Both meta-analysis and MR study suggested that childhood asthma was a risk factor for T1DM. No epidemiological or genetic evidence was found for an association of T1DM with asthma incidence. Further studies could be carried out to leverage

Background Patients with nasopharyngeal cancer (NPC) differ in prognosis, even at the same stage; therefore, new biomarkers are urgently required to identify early-stage NPC patients at high risk of poor prognosis. Although Epstein–Barr virus (EBV) DNA has been used for prognosis, the value of many other biomarkers expressed during the infection cycle of EBV remains unclarified. This study aimed to evaluate the prognostic potential of EA-IgA, VCA-IgA and d-dimer in patients with NPC. Methods Electronic databases, including PubMed, Embase and Web of Science, were searched up to February 1, 2021. Pooled data were extracted from studies that evaluated the relationship between NPC and overall survival (OS), distant metastasis-free survival (DMFS) or disease-free survival (DFS) and then were subjected to a meta-analysis. Results Nine studies with 5729 patients were included in this meta-analysis. In patients with NPC, EA-IgA levels significantly predicted OS (HR = 1.63, 95% CI 1.07–2.48). d-Dimer levels significantly predicted OS (HR = 1.75, 95% CI 1.24–2.47) and DMFS (HR = 1.91, 95% CI 1.31–2.79). However, high levels of VCA-IgA were not associated with OS (HR = 1.24, 95% CI 0.95–1.60), DMFS (HR = 1.41, 95% CI 0.92–2.17) or DFS (HR = 2.39, 95% CI 0.78–7.26). Conclusions The present findings reveal that EA-IgA and d-dimer, but not VCA-IgA, can be used as prognostic biomarkers in NPC.

Background: World-wide incidence and prevalence of both asthma and type 1 diabetes mellitus (T1DM) in children has been increasing in past decades. Association between the two diseases has been found in some but not other studies. Objective: We conducted a meta-analysis to verify such an association, and bidirectional Mendelian randomization analysis to examine the potential cause-effect relationships. Methods: Three databases (PubMed, Embase and Web of Science) were searched from their inception to February 1, 2021. Pooled hazard ratios (HR) or odds ratios (OR), and 95% confidence intervals, were calculated. Associations between single-nucleotide polymorphisms with childhood asthma and T1DM were selected based on genome-wide association studies. The outcome datasets were obtained from FinnGen study. We used the inverse variance-weighted, weighted median and MR-Egger methods to estimate causal effects. To assess robustness and horizontal pleiotropy, MR-Egger regression and MR pleiotropy residual sum and outlier test was conducted. Results: In meta-analysis, childhood asthma was associated with an increased risk of T1DM (HR=1.30, 95% CI 1.05-1.61, P=0.014), whereas T1DM was not associated with the risk of asthma (HR=0.98, 95% CI 0.64-1.51, P=0.941; OR=0.84, 95% CI 0.65-1.08, P=0.168). MR analysis indicated increased genetic risk of T1DM in children with asthma (OR=1.308; 95% CI 1.030-1.661; P =0.028). Analysis using the IVW method indicated not associated between T1DM and genetic risk of asthma (OR=1.027, 95%CI 0.970-1.089, P=0.358). Conclusion: Both meta-analysis and MR study suggested that childhood asthma was a risk factor for T1DM. No epidemiological or genetic evidence for an association of T1DM with asthma incidence. Further studies could be carried out to leverage this newfound insight into better clinical and experimental research in asthma and T1DM. Further studies could be carried out to leverage this newfound insight into better clinical and experimental research in asthma and T1DM.

Objectives: To develop and evaluate a new coordinate system for MRI of the vestibular system.Methods: In this study, 53 internal auditory canal MRI and 78 temporal bone CT datasets were analyzed. Mimics Medical software version 21.0 was used to visualize and three-dimensionally reconstruct the image data. We established a new coordinate system, named W–X, based on the center of the bilateral eyeballs and vertex of the bilateral superior semicircular canals. Using the W–X coordinate system and Reid's coordinate system, we measured the orientations of the planes of the anterior semicircular canal (ASCC), the lateral semicircular canal (LSCC), and the posterior semicircular canal (PSCC).Results: No significant differences between the angles measured using CT and MRI were found for any of the semicircular canal planes (p > 0.05). No statistical differences were found between the angles measured using Reid's coordinate system (CT) and the W–X coordinate system (MRI). The mean values of ∠ASCC & LSCC, ∠ASCC & PSCC, and ∠LSCC & PSCC were 84.67 ± 5.76, 94.21 ± 3.81, and 91.79 ± 5.22 degrees, respectively. The angle between the LSCC plane and the horizontal imaging plane was 15.64 ± 3.92 degrees, and the angle between the PSCC plane and the sagittal imaging plane was 48.79 ± 4.46 degrees.Conclusion: A new W–X coordinate system was developed for MRI studies of the vestibular system and can be used to measure the orientations of the semicircular canals.

Background: Causality between education and obstructive sleep apnea (OSA) is not known.Methods: Genetic variants, as instrumental variables for years of education, were derived from the Social Science Genetic Association Consortium. The outcome datasets related to OSA were from the FinnGen research project (www.finngen.fi/en/). Inverse variance-weighted, weighted-median, and Mendelian randomization-Egger analysis were used to estimate causal effects. To assess the robustness and horizontal pleiotropy of significant results, leave-one-out sensitivity analysis and Mendelian randomization-Egger regression analysis were conducted. The inverse variance-weighted method was undertaken to estimate the association between years of education and other known risk factors for OSA. Analyses were conducted using the Two Sample Mendelian Randomization package of R 4•0•3.Results: Genetic predisposition towards 4.2 years of additional education was associated with a 27.8% lower risk of OSA [odds ratio (OR) =0.722, 95% confidence interval (CI): 0.566-0.921; P=0.009]. Sensitivity analyses were consistent with a causal interpretation in which a major bias from genetic pleiotropy was unlikely. The Mendelian randomization assumptions did not seem to be violated. Genetic predisposition towards longer education was associated with a lower body mass index, fewer cigarettes smoked per day, and greater alcohol intake per week.Conclusions: Our data indicated that education could be a protective factor against OSA. Potential mechanisms could include body mass index, tobacco smoking, and alcohol intake.