Image_1_Shorter respiratory event duration is related to prevalence of type 2 diabetes.jpeg

BackgroundObstructive sleep apnea (OSA) is a heterogeneous sleep disorder often comorbid with metabolic diseases, and type 2 diabetes (T2DM) is one of them. Although apnea hypopnea index (AHI) is currently the diagnostic criteria for OSA severity, a controversial relationship between AHI and T2DM has been found. On the other hand, the duration of apnea–hypopnea events has been shown to be a useful metric for predicting mortality. This study aimed to test whether average respiratory event duration was associated with prevalence of T2DM.MethodsPatients referred to the sleep clinic were recruited in the study. Baseline clinical characteristics and polysomnography parameters including average respiratory event duration were collected. The association of average respiratory event duration with the prevalence of T2DM was evaluated by univariate and multivariate logistic regression analyses.ResultsA total of 260 participants were enrolled, and 92 (35.4%) had T2DM. Univariate analysis revealed that age, body mass index (BMI), total sleep time, sleep efficiency, history of hypertension, and shorter average respiratory event duration were associated with T2DM. In multivariate analysis, only age and BMI remained significant. While average respiratory event duration was insignificant in multivariate analysis, subtype event analysis showed that shorter average apnea duration was both significant in univariate (OR, 0.95; 95% CI, 0.92–0.98) and multivariate analyses (OR, 0.95; 95% CI, 0.91–0.99). Neither average hypopnea duration nor AHI was associated with T2DM. Significant association (OR, 1.19; 95% CI, 1.12–1.25) was observed between shorter average apnea duration and lower respiratory arousal threshold after multivariate adjustment. However, causal mediation analysis revealed no mediating effect of arousal threshold on average apnea duration and T2DM.ConclusionThe average apnea duration may be a useful metric in the diagnosis of OSA comorbidity. Shorter average apnea duration indicating poor sleep quality and augmented autonomic nervous system responses might be the potential pathological mechanisms leading to T2DM.</p

Table_1_Shorter respiratory event duration is related to prevalence of type 2 diabetes.docx

BackgroundObstructive sleep apnea (OSA) is a heterogeneous sleep disorder often comorbid with metabolic diseases, and type 2 diabetes (T2DM) is one of them. Although apnea hypopnea index (AHI) is currently the diagnostic criteria for OSA severity, a controversial relationship between AHI and T2DM has been found. On the other hand, the duration of apnea–hypopnea events has been shown to be a useful metric for predicting mortality. This study aimed to test whether average respiratory event duration was associated with prevalence of T2DM.MethodsPatients referred to the sleep clinic were recruited in the study. Baseline clinical characteristics and polysomnography parameters including average respiratory event duration were collected. The association of average respiratory event duration with the prevalence of T2DM was evaluated by univariate and multivariate logistic regression analyses.ResultsA total of 260 participants were enrolled, and 92 (35.4%) had T2DM. Univariate analysis revealed that age, body mass index (BMI), total sleep time, sleep efficiency, history of hypertension, and shorter average respiratory event duration were associated with T2DM. In multivariate analysis, only age and BMI remained significant. While average respiratory event duration was insignificant in multivariate analysis, subtype event analysis showed that shorter average apnea duration was both significant in univariate (OR, 0.95; 95% CI, 0.92–0.98) and multivariate analyses (OR, 0.95; 95% CI, 0.91–0.99). Neither average hypopnea duration nor AHI was associated with T2DM. Significant association (OR, 1.19; 95% CI, 1.12–1.25) was observed between shorter average apnea duration and lower respiratory arousal threshold after multivariate adjustment. However, causal mediation analysis revealed no mediating effect of arousal threshold on average apnea duration and T2DM.ConclusionThe average apnea duration may be a useful metric in the diagnosis of OSA comorbidity. Shorter average apnea duration indicating poor sleep quality and augmented autonomic nervous system responses might be the potential pathological mechanisms leading to T2DM.</p

Table_2_Shorter respiratory event duration is related to prevalence of type 2 diabetes.docx

BackgroundObstructive sleep apnea (OSA) is a heterogeneous sleep disorder often comorbid with metabolic diseases, and type 2 diabetes (T2DM) is one of them. Although apnea hypopnea index (AHI) is currently the diagnostic criteria for OSA severity, a controversial relationship between AHI and T2DM has been found. On the other hand, the duration of apnea–hypopnea events has been shown to be a useful metric for predicting mortality. This study aimed to test whether average respiratory event duration was associated with prevalence of T2DM.MethodsPatients referred to the sleep clinic were recruited in the study. Baseline clinical characteristics and polysomnography parameters including average respiratory event duration were collected. The association of average respiratory event duration with the prevalence of T2DM was evaluated by univariate and multivariate logistic regression analyses.ResultsA total of 260 participants were enrolled, and 92 (35.4%) had T2DM. Univariate analysis revealed that age, body mass index (BMI), total sleep time, sleep efficiency, history of hypertension, and shorter average respiratory event duration were associated with T2DM. In multivariate analysis, only age and BMI remained significant. While average respiratory event duration was insignificant in multivariate analysis, subtype event analysis showed that shorter average apnea duration was both significant in univariate (OR, 0.95; 95% CI, 0.92–0.98) and multivariate analyses (OR, 0.95; 95% CI, 0.91–0.99). Neither average hypopnea duration nor AHI was associated with T2DM. Significant association (OR, 1.19; 95% CI, 1.12–1.25) was observed between shorter average apnea duration and lower respiratory arousal threshold after multivariate adjustment. However, causal mediation analysis revealed no mediating effect of arousal threshold on average apnea duration and T2DM.ConclusionThe average apnea duration may be a useful metric in the diagnosis of OSA comorbidity. Shorter average apnea duration indicating poor sleep quality and augmented autonomic nervous system responses might be the potential pathological mechanisms leading to T2DM.</p

Just-in-Time Learning-Integrated Partial Least-Squares Strategy for Accurately Predicting 71 Chemical Constituents in Chinese Tobacco by Near-Infrared Spectroscopy

Near-infrared spectroscopy has been widely used to characterize the chemical composition of tobacco because it is fast, economical, and nondestructive. However, few predictive models perform ideally when applied to large spectral libraries of tobacco and its various chemical indicators. In this study, the just-in-time learning-integrated partial least-squares (JIT-PLS) modeling strategy was applied for the first time to quantitatively analyze 71 chemical components in Chinese tobacco. Approximately 18000 tobacco samples from China were analyzed to find appropriately similar measurements and propose suitable and flexible similar subsets from the calibration for each test sample. In total, 879 representative aged tobacco leaf samples and 816 cigarette samples were used as external instances to evaluate the practical predicting ability of the proposed method. The most suitable similar subsets for each test sample could be selected by limiting the Euclidean distance and number of similar subsets to 0–3.0 × 10–9 and 10–300, respectively. The majority of the JIT-PLS models performed significantly better than traditional PLS models. Specifically, using JIT-PLS instead of traditional PLS models increased the R2 values from 0.347–0.984 to 0.763–0.996, and from 0.179–0.981 to 0.506–0.989 for the prediction of 67 and 71 components in aged tobacco leaf and cigarette samples, respectively. Good prediction ability was demonstrated for routine chemical components, polyphenolic compounds, organic acids, and other compounds, with the mean ratios of prediction to deviation (RPDmean) being 7.74, 4.39, 4.05, and 5.48, respectively). The proposed methodology could simultaneously determine 67 major components in large and complicated tobacco spectral libraries with high precision and accuracy, which will assist tobacco and cigarette quality control in collecting as well as processing stages

Additional file 1 of USP40 promotes hepatocellular carcinoma cell proliferation, migration and stemness by deubiquitinating and stabilizing Claudin1

Additional file 1. Supplementary Tables

Morphologic and Functional Connectivity Alterations of Corticostriatal and Default Mode Network in Treatment-Naïve Patients with Obsessive-Compulsive Disorder

<div><p>Background</p><p>Previous studies have demonstrated that structural deficits and functional connectivity imbalances might underlie the pathophysiology of obsessive-compulsive disorder (OCD). The purpose of the present study was to investigate gray matter deficits and abnormal resting-state networks in patients with OCD and further investigate the association between the anatomic and functional alterations and clinical symptoms.</p> <p>Methods</p><p>Participants were 33 treatment-naïve OCD patients and 33 matched healthy controls. Voxel-based morphometry was used to investigate the regions with gray matter abnormalities and resting-state functional connectivity analysis was further conducted between each gray matter abnormal region and the remaining voxels in the brain.</p> <p>Results</p><p>Compared with healthy controls, patients with OCD showed significantly increased gray matter volume in the left caudate, left thalamus, and posterior cingulate cortex, as well as decreased gray matter volume in the bilateral medial orbitofrontal cortex, left anterior cingulate cortex, and left inferior frontal gyrus. By using the above morphologic deficits areas as seed regions, functional connectivity analysis found abnormal functional integration in the cortical-striatum-thalamic-cortical (CSTC) circuits and default mode network. Subsequent correlation analyses revealed that morphologic deficits in the left thalamus and increased functional connectivity within the CSTC circuits positively correlated with the total Y-BOCS score.</p> <p>Conclusion</p><p>This study provides evidence that morphologic and functional alterations are seen in CSTC circuits and default mode network in treatment-naïve OCD patients. The association between symptom severity and the CSTC circuits suggests that anatomic and functional alterations in CSTC circuits are especially important in the pathophysiology of OCD. </p> </div

Distribution of toxic chemicals in particles of various sizes from mainstream cigarette smoke

<p>To accurately estimate the risk of inhaling cigarette smoke containing toxic chemicals, it is important that the distribution of these chemicals is accurately measured in cigarette smoke aerosol particles of various sizes. In this study, a single-channel smoking machine was directly coupled to an electrical low-pressure impactor. The particles of mainstream cigarette smoke were collected using 12 polyester films, and the particulate matter (PM) was characterized. Nicotine, tobacco-specific N-nitrosamines (TSNAs, including NNN, NAT, NAB, and NNK), polycyclic aromatic hydrocarbons (PAHs, including benzo(a)pyrene (BaP), benzo(a)anthracene, and chrysene), and heavy metals (including Cr, As, Cd, and Pb) present in the particles of different sizes were analyzed by GC, HPLC-MS/MS, GC/MS, or ICP-MS, respectively. The results demonstrated that the nicotine, TSNAs, PAHs, and heavy metals in mainstream cigarette smoke were dispersed over a particle size ranging from 0.1 μm to 2.0 μm, and the concentration of these toxic chemicals initially increased and then decreased the particle size grew. The distribution of nicotine was uniform for the PM in the size ranges of less than 0.1 μm, 0.1–1.0 μm, and 1.0–2.0 μm, TSNAs and heavy metals in particles of less 0.1 μm were more abundant, and PAHs in fine particles were also more abundant.</p

Gray matter difference between OCD patients and healthy controls.

<p>The warm color denotes the brain regions having increased gray matter volume, and the cold color denotes the brain regions having reduced gray matter volume in OCD patients. Maps threshold were set at <i>p</i><0.05 with family-wise error correction. </p

Functional connectivity difference between OCD patients and healthy controls.

<p>The red line denotes the brain regions having increased functional connectivity, and the blue line denotes the brain regions having reduced functional connectivity in OCD patients. Maps threshold were set at <i>p</i><0.05 with AlphaSim correction. L, left; R, right; OFC, orbitofrontal cortex; ACC, anterior cingulate cortex; PCC, posterior cingulate cortex. IFG, inferior frontal gyrus; ITG, inferior temporal gyrus; STG, superior temporal gyrus; MTG, middle temporal gyrus. Results are displayed by using the BrainNet Viewer [84] (<a href="http://www.nitrc.org/projects/bnv/" target="_blank"><u>http://www.nitrc.org/projects/bnv/</u></a>).</p

Positive correlation between total Y-BOCS score and brain gray matter volume and functional connectivity strength in abnormal areas.

<p>L, left; R, right; LOFC, lateral orbitofrontal cortex; MOFC, medial orbitofrontal cortex.</p