Improved dynamic connection detection power in estimated dynamic functional connectivity considering multivariate dependencies between brain regions

To estimate dynamic functional connectivity (dFC), the conventional method of sliding window correlation (SWC) suffers from poor performance of dynamic connection detection. This stems from the equal weighting of observations, suboptimal time scale, nonsparse output, and the fact that it is bivariate. To overcome these limitations, we exploited the kernel‐reweighted logistic regression (KELLER) algorithm, a method that is common in genetic studies, to estimate dFC in resting state functional magnetic resonance imaging (rs‐fMRI) data. KELLER can estimate dFC through estimating both spatial and temporal patterns of functional connectivity between brain regions. This paper compares the performance of the proposed KELLER method with current methods (SWC and tapered‐SWC (T‐SWC) with different window lengths) based on both simulated and real rs‐fMRI data. Estimated dFC networks were assessed for detecting dynamically connected brain region pairs with hypothesis testing. Simulation results revealed that KELLER can detect dynamic connections with a statistical power of 87.35% compared with 70.17% and 58.54% associated with T‐SWC (p‐value = .001) and SWC (p‐value <.001), respectively. Results of these different methods applied on real rs‐fMRI data were investigated for two aspects: calculating the similarity between identified mean dynamic pattern and identifying dynamic pattern in default mode network (DMN). In 68% of subjects, the results of T‐SWC with window length of 100 s, among different window lengths, demonstrated the highest similarity to those of KELLER. With regards to DMN, KELLER estimated previously reported dynamic connection pairs between dorsal and ventral DMN while SWC‐based method was unable to detect these dynamic connections.     

Interpretable generalized neural additive models for mortality prediction of COVID-19 hospitalized patients in Hamadan,Iran

Psychometrically sound resilience outcome measures are essential to establish how health and care services or interventions can enhance the resilience of people living with dementia (PLWD) and their carers. This paper systematically reviews the literature to identify studies that administered a resilience measurement scale with PLWD and/or their carers and examines the psychometric properties of these measures. Electronic abstract databases and the internet were searched, and an international network contacted to identify peer-reviewed journal articles. Two authors independently extracted data. They critically reviewed the measurement properties from the available psychometric data in the studies, using a standardised checklist adapted for purpose. Fifty-one studies were included in the final review, which applied nine different resilience measures, eight developed in other populations and one developed for dementia carers in Thailand. None of the measures were developed for use with people living with dementia. The majority of studies (N?=?47) focussed on dementia carers, three studies focussed on people living with dementia and one study measured both carers and the person with dementia. All the studies had missing information regarding the psychometric properties of the measures as applied in these two populations. Nineteen studies presented internal consistency data, suggesting seven of the nine measures demonstrate acceptable reliability in these new populations. There was some evidence of construct validity, and twenty-eight studies hypothesised effects a priori (associations with other outcome measure/demographic data/differences in scores between relevant groups) which were partially supported. The other studies were either exploratory or did not specify hypotheses. This limited evidence does not necessarily mean the resilience measure is not suitable, and we encourage future users of resilience measures in these populations to report information to advance knowledge and inform further reviews. All the measures require further psychometric evaluation in both these populations. The conceptual adequacy of the measures as applied in these new populations was questionable. Further research to understand the experience of resilience for people living with dementia and carers could establish the extent current measures -which tend to measure personal strengths -are relevant and comprehensive, or whether further work is required to establish a new resilience outcome measure.

     

Diet,Nutrition, Obesity,and Their Implications for COVID-19 Mortality: Development of a Marginalized Two-Part Model for Semicontinuous Data

BackgroundNutrition is not a treatment for COVID-19, but it is a modifiable contributor to the development of chronic disease, which is highly associated with COVID-19 severe illness and deaths. A well-balanced diet and healthy patterns of eating strengthen the immune system, improve immunometabolism, and reduce the risk of chronic disease and infectious diseases.ObjectiveThis study aims to assess the effect of diet, nutrition, obesity, and their implications for COVID-19 mortality among 188 countries by using new statistical marginalized two-part models.MethodsWe globally evaluated the distribution of diet and nutrition at the national level while considering the variations between different World Health Organization regions. The effects of food supply categories and obesity on (as well as associations with) the number of deaths and the number of recoveries were reported globally by estimating coefficients and conducting color maps.ResultsThe findings show that a 1% increase in supplementation of pulses reduced the odds of having a zero death by 4-fold (OR 4.12, 95% CI 11.97-1.42). In addition, a 1% increase in supplementation of animal products and meat increased the odds of having a zero death by 1.076-fold (OR 1.076, 95% CI 1.01-1.15) and 1.13-fold (OR 1.13, 95% CI 1.0-1.28), respectively. Tree nuts reduced the odds of having a zero death, and vegetables increased the number of deaths. Globally, the results also showed that populations (countries) who consume more eggs, cereals excluding beer, spices, and stimulants had the greatest impact on the recovery of patients with COVID-19. In addition, populations that consume more meat, vegetal products, sugar and sweeteners, sugar crops, animal fats, and animal products were associated with more death and less recoveries in patients. The effect of consuming sugar products on mortality was considerable, and obesity has affected increased death rates and reduced recovery rates.ConclusionsAlthough there are differences in dietary patterns, overall, unbalanced diets are a health threat across the world and not only affect death rates but also the quality of life. To achieve the best results in preventing nutrition-related pandemic diseases, strategies and policies should fully recognize the essential role of both diet and obesity in determining good nutrition and optimal health. Policies and programs must address the need for change at the individual level and make modifications in society and the environment to make healthier choices accessible and preferable.     

Automated iterative reclustering framework for determining hierarchical functional networks in resting state fMRI

To spatially cluster resting state‐functional magnetic resonance imaging (rs‐fMRI) data into potential networks, there are only a few general approaches that determine the number of networks/clusters, despite a wide variety of techniques proposed for clustering. For individual subjects, extraction of a large number of spatially disjoint clusters results in multiple small networks that are spatio‐temporally homogeneous but irreproducible across subjects. Alternatively, extraction of a small number of clusters creates spatially large networks that are temporally heterogeneous but spatially reproducible across subjects. We propose a fully automatic, iterative reclustering framework in which a small number of spatially large, heterogeneous networks are initially extracted to maximize spatial reproducibility. Subsequently, the large networks are iteratively subdivided to create spatially reproducible subnetworks until the overall within‐network homogeneity does not increase substantially. The proposed approach discovers a rich network hierarchy in the brain while simultaneously optimizing spatial reproducibility of networks across subjects and individual network homogeneity. We also propose a novel metric to measure the connectivity of brain regions, and in a simulation study show that our connectivity metric and framework perform well in the face of low signal to noise and initial segmentation errors. Experimental results generated using real fMRI data show that the proposed metric improves stability of network clusters across subjects, and generates a meaningful pattern for spatially hierarchical structure of the brain. Hum Brain Mapp 36:3303–3322, 2015. © 2015 Wiley Periodicals, Inc .     

Light-soaking free organic photovoltaic devices with sol–gel deposited ZnO and AZO electron transport layers

This paper investigates light-soaking effects in inverted organic photovoltaic (OPV) devices with zinc oxide (ZnO) and aluminum doped ZnO (AZO) electron transport layers (ETL), which is important for the development of low-cost and stable solar cells. The samples demonstrated high solar harvesting properties with power conversion efficiency up to 3.9%. Air-stability tests of up to 150 days were performed on devices with different Al doping levels. The devices maintained higher than 60% of the initial PCE after 50 days of open-air exposure. The light-soaking mechanism was investigated with experiments and simulations and shown to be eliminated when the Al fraction of the AZO is higher than 4%. The simulated band diagram of the OPV devices indicates that the low carrier density in the ZnO layer by virtue of depletion is the main reason of the light-soaking effect. Doping the ZnO layer as well as exposing the devices under UV irradiation will introduce additional free carriers into the ETL and reduce the width of the depletion region at both sides of the ETL.

This paper investigates the mechanism of light-soaking effects in inverted organic photovoltaic devices with zinc oxide and aluminum doped ZnO electron transport layers, which is important for development of low-cost and stable solar cells.