Phenotype-based and Self-learning Inter-individual Sleep Apnea Screening with a Level IV Monitoring System

Purpose: We propose a phenotype-based artificial intelligence system that can self-learn and is accurate for screening purposes, and test it on a Level IV monitoring system. Methods: Based on the physiological knowledge, we hypothesize that the phenotype information will allow us to find subjects from a well-annotated database that share similar sleep apnea patterns. Therefore, for a new-arriving subject, we can establish a prediction model from the existing database that is adaptive to the subject. We test the proposed algorithm on a database consisting of 62 subjects with the signals recorded from a Level IV wearable device measuring the thoracic and abdominal movements and the SpO2. Results: With the leave-one cross validation, the accuracy of the proposed algorithm to screen subjects with an apnea-hypopnea index greater or equal to 15 is 93.6%, the positive likelihood ratio is 6.8, and the negative likelihood ratio is 0.03. Conclusion: The results confirm the hypothesis and show that the proposed algorithm has great potential to screen patients with SAS

Effectiveness of influenza vaccination in patients with end-stage renal disease receiving hemodialysis: a population-based study.

BackgroundLittle is known on the effectiveness of influenza vaccine in ESRD patients. This study compared the incidence of hospitalization, morbidity, and mortality in end-stage renal disease (ESRD) patients undergoing hemodialysis (HD) between cohorts with and without influenza vaccination.MethodsWe used the insurance claims data from 1998 to 2009 in Taiwan to determine the incidence of these events within one year after influenza vaccination in the vaccine (N = 831) and the non-vaccine (N = 3187) cohorts. The vaccine cohort to the non-vaccine cohort incidence rate ratio and hazard ratio (HR) of morbidities and mortality were measured.ResultsThe age-specific analysis showed that the elderly in the vaccine cohort had lower hospitalization rate (100.8 vs. 133.9 per 100 person-years), contributing to an overall HR of 0.81 (95% confidence interval (CI) 0.72-0.90). The vaccine cohort also had an adjusted HR of 0.85 [95% CI 0.75-0.96] for heart disease. The corresponding incidence of pneumonia and influenza was 22.4 versus 17.2 per 100 person-years, but with an adjusted HR of 0.80 (95% CI 0.64-1.02). The vaccine cohort had lowered risks than the non-vaccine cohort for intensive care unit (ICU) admission (adjusted HR 0.20, 95% CI 0.12-0.33) and mortality (adjusted HR 0.50, 95% CI 0.41-0.60). The time-dependent Cox model revealed an overall adjusted HR for mortality of 0.30 (95% CI 0.26-0.35) after counting vaccination for multi-years.ConclusionsESRD patients with HD receiving the influenza vaccination could have reduced risks of pneumonia/influenza and other morbidities, ICU stay, hospitalization and death, particularly for the elderly

A powerful and efficient multivariate approach for voxel-level connectome-wide association studies

We describe an approach to multivariate analysis, termed structured kernel principal component regression (sKPCR), to identify associations in voxel-level connectomes using resting-state functional magnetic resonance imaging (rsfMRI) data. This powerful and computationally efficient multivariate method can identify voxel-phenotype associations based on the whole-brain connectivity pattern of voxels, and it can detect linear and non-linear signals in both volume-based and surface-based rsfMRI data. For each voxel, sKPCR first extracts low-dimensional signals from the spatially smoothed connectivities by structured kernel principal component analysis, and then tests the voxel-phenotype associations by an adaptive regression model. The method's power is derived from appropriately modelling the spatial structure of the data when performing dimension reduction, and then adaptively choosing an optimal dimension for association testing using the adaptive regression strategy. Simulations based on real connectome data have shown that sKPCR can accurately control the false-positive rate and that it is more powerful than many state-of-the-art approaches, such as the connectivity-wise generalized linear model (GLM) approach, multivariate distance matrix regression (MDMR), adaptive sum of powered score (aSPU) test, and least-square kernel machine (LSKM). Moreover, since sKPCR can reduce the computational cost of non-parametric permutation tests, its computation speed is much faster. To demonstrate the utility of sKPCR for real data analysis, we have also compared sKPCR with the above methods based on the identification of voxel-wise differences between schizophrenic patients and healthy controls in four independent rsfMRI datasets. The results showed that sKPCR had better between-sites reproducibility and a larger proportion of overlap with existing schizophrenia meta-analysis findings. Code for our approach can be downloaded from https://github.com/weikanggong/sKPCR. [Abstract copyright: Copyright © 2018 Elsevier Inc. All rights reserved.

Is the whole greater than the sum of its parts? De novo assembly strategies for bacterial genomes based on paired-end sequencing

Number of misassemblies for different assembly strategies. Number of misassemblies for the de novo assembly results for E. coli DH1 and S. Parasanguinis FW213 are shown together with their standard errors of the mean. Group A [PE] and Group A [SE] represent all reads assembled as paired-end reads and single end reads, respectively. Group A [PE + SE] represents all the non-overlapped paired-end reads assembled together with merged reads. Group M [PE] and Group M [SE] represent Group M reads assembled as paired-end reads and single end reads, respectively. The numbers of misassemblies fluctuate a lot when depths of read number are low and gradually decreases until they reach a steady number. The paired-end reads (Group A [PE] and Group M [PE]) in S. Parasanguinis FW213 gave the lowest number of misassemblies when depths of read number are high. (TIFF 669 kb

Die Bewegung des Absoluten in Hegels „Wissenschaft der Logik“

Ich verstehe die Bewegung des Absoluten in der „Wissenschaft der Logik“ als eine Wechselwirkung in Form des Wechselbestimmens von Sein und Begriff durch das Wesen, wobei dieses, sofern es als Beziehung bzw. Tätigkeit begriffen werden kann, als vermittelnde Wechselwirkung aufgefasst wird. Diese kommt als letztes Moment der Wesenslogik zum Vorschein, so dass die Vermittlungs-Bedeutung der Wesenslogik statt der Substantialitäts-Bedeutung derselben in den Vordergrund gerückt wird. Anschließend sollte die Lesart der „Wissenschaft der Logik“ so vorgestellt werden, dass sich die Logik statt als in zwei Teile, also in die objektive Logik und die subjektive Logik - man könnte diese jeweils als die Logik der Substantialität und die Logik der Subjektivität verstehen - als in drei Momente, also in das Sein, das Wesen und den Begriff, eingeteilt begreift. Dabei werden zwei Pole, also das Sein und der Begriff, mit ihrer Vermittlung, also dem Wesen, zusammen aufgehellt. Jene werden bei Hegel als zwei Gründe in einem Ganzen der Bewegung betrachtet. Jeder von den beiden stellt sich vermittels Heideggers Terminologie zugleich als eine Leere und eine Fülle, oder zugleich als eine unbestimmte Unmittelbarkeit und eine vermittelte Unmittelbarkeit dar, so dass das Sein mit der Idee zu identifizieren ist, obzwar es zuerst als ein unbestimmtes Unmittelbares gilt, und der Begriff, obzwar er im Kontrast zum Sein das entfaltete Ganze besagt, auch noch als ein bestimmender unbestimmter Anfang, d.h. als die transzendentale Apperzeption, festgestellt wird, die von Hegel als ein allumfassendes, an sich Konkretes umgedeutet wird. Als Resultat der vermittelnden Bewegung stellt sich jeder Pol als eine Fülle dar; als Anfang derselben stellt er sich wiederum als eine Leere dar. Der Anfang ist zugleich das Resultat wie das Resultat zugleich der Anfang ist. Der Anfang und das Resultat konstruieren sich in der Ganzheit zur Wechselseitigkeit von Subjekt und Objekt

Be Stars in the Open Cluster NGC 6830

We report the discovery of 2 new Be stars, and re-identify one known Be star in the open cluster NGC 6830. Eleven H-alpha emitters were discovered using the H-alpha imaging photometry of the Palomar Transient Factory Survey. Stellar membership of the candidates was verified with photometric and kinematic information using 2MASS data and proper motions. The spectroscopic confirmation was carried out by using the Shane 3-m telescope at Lick observatory. Based on their spectral types, three H-alpha emitters were confirmed as Be stars with H-alpha equivalent widths > -10 Angstrom. Two objects were also observed by the new spectrograph SED-Machine on the Palomar 60 inch Telescope. The SED-Machine results show strong H-alpha emission lines, which are consistent with the results of the Lick observations. The high efficiency of the SED-Machine can provide rapid observations for Be stars in a comprehensive survey in the future.Comment: 11 pages, 8 figures, AJ in pres

Functional connectivity of the human amygdala in health and in depression

To analyze the functioning of the amygdala in depression, we performed the first voxel-level resting state functional-connectivity neuroimaging analysis of depression of voxels in the amygdala with all other voxels in the brain, with 336 patients with major depressive disorder and 350 controls. Amygdala voxels had decreased functional connectivity with the orbitofrontal cortex, temporal lobe areas, including the temporal pole, inferior temporal gyrus, and the parahippocampal gyrus. The reductions in the strengths of the functional connectivity of the amygdala voxels with the medial orbitofrontal cortex and temporal lobe voxels were correlated with increases in the Beck Depression Inventory score and in the duration of illness measures of depression. Parcellation analysis in 350 healthy controls based on voxel-level functional connectivity showed that the basal division of the amygdala has high functional connectivity with medial orbitofrontal cortex areas, and the dorsolateral amygdala has strong functional connectivity with the lateral orbitofrontal cortex and related ventral parts of the inferior frontal gyrus. In depression, the basal amygdala division had especially reduced functional connectivity with the medial orbitofrontal cortex which is involved in reward; and the dorsolateral amygdala subdivision had relatively reduced functional connectivity with the lateral orbitofrontal cortex which is involved in non-reward