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"Zang, Yu"
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Quality of life in Parkinson's disease: A systematic review and meta‐analysis of comparative studies
Background Studies regarding the impact of Parkinson's disease (PD) on quality of life (QOL) have reported conflicting results, and the underlying QOL domains require further study. In order to understand the association between PD and QOL, we conducted this meta‐analysis to systematically compare QOL between PD patients and healthy controls. Method The PubMed, PsycINFO, EMBASE, and Web of Science databases were systematically searched. Data were analyzed using the random‐effects model. Results Twenty studies covering 2707 PD patients and 150,661 healthy controls were included in the study. Compared with healthy controls, PD patients had significantly poorer QOL overall and in most domains with moderate to large effects sizes. Different QOL measures varied in their association with quality of life, with the Parkinson's Disease Questionnaire‐39 (PDQ‐39) having the largest effect size (standard mean difference, SMD = −1.384, 95% CI: −1.607, −1.162, Z = 12.189, P < 0.001), followed by the Europe Quality of Life Questionnaire‐visual analogue scale (EQ‐VAS) (SMD = −1.081, 95% CI: −1.578, −0.584, Z = −4.265, P < 0.001), Europe Quality of Life Questionnaire‐5D (EQ‐5D) (SMD = −0.889, 95% CI: −1.181, −0.596, Z = −5.962, P < 0.001), and the Short‐form Health Survey (SF) scales (physical dimension: SMD = −0.826, 95% CI: −1.529, −0.123, Z = −2.303, P = 0.021; mental dimension: SMD = −0.376, 95% CI: −0.732, −0.019, Z = −2.064, P = 0.039). Conclusion PD patients had lower QOL compared with healthy controls in most domains, especially in physical function and mental health. Considering the negative impact of poor QOL on daily life and functional outcomes, effective measures should be developed to improve QOL in this population. Improving the QOL in patients with PD is an important concern, which can provide reference for decisions of policymakers and clinicians. PD patients had significantly poorer QOL, with moderate to large effect sizes in most domains. Moreover, different QOL measures had moderating effects on the results.
Journal Article
REST: A Toolkit for Resting-State Functional Magnetic Resonance Imaging Data Processing
Resting-state fMRI (RS-fMRI) has been drawing more and more attention in recent years. However, a publicly available, systematically integrated and easy-to-use tool for RS-fMRI data processing is still lacking. We developed a toolkit for the analysis of RS-fMRI data, namely the RESting-state fMRI data analysis Toolkit (REST). REST was developed in MATLAB with graphical user interface (GUI). After data preprocessing with SPM or AFNI, a few analytic methods can be performed in REST, including functional connectivity analysis based on linear correlation, regional homogeneity, amplitude of low frequency fluctuation (ALFF), and fractional ALFF. A few additional functions were implemented in REST, including a DICOM sorter, linear trend removal, bandpass filtering, time course extraction, regression of covariates, image calculator, statistical analysis, and slice viewer (for result visualization, multiple comparison correction, etc.). REST is an open-source package and is freely available at http://www.restfmri.net.
Journal Article
Percent amplitude of fluctuation: A simple measure for resting-state fMRI signal at single voxel level
The amplitude of low-frequency fluctuation (ALFF) measures resting-state functional magnetic resonance imaging (RS-fMRI) signal of each voxel. However, the unit of blood oxygenation level-dependent (BOLD) signal is arbitrary and hence ALFF is sensitive to the scale of raw signal. A well-accepted standardization procedure is to divide each voxel's ALFF by the global mean ALFF, named mALFF. Although fractional ALFF (fALFF), a ratio of the ALFF to the total amplitude within the full frequency band, offers possible solution of the standardization, it actually mixes with the fluctuation power within the full frequency band and thus cannot reveal the true amplitude characteristics of a given frequency band. The current study borrowed the percent signal change in task fMRI studies and proposed percent amplitude of fluctuation (PerAF) for RS-fMRI. We firstly applied PerAF and mPerAF (i.e., divided by global mean PerAF) to eyes open (EO) vs. eyes closed (EC) RS-fMRI data. PerAF and mPerAF yielded prominently difference between EO and EC, being well consistent with previous studies. We secondly performed test-retest reliability analysis and found that (PerAF ≈ mPerAF ≈ mALFF) > (fALFF ≈ mfALFF). Head motion regression (Friston-24) increased the reliability of PerAF, but decreased all other metrics (e.g. mPerAF, mALFF, fALFF, and mfALFF). The above results suggest that mPerAF is a valid, more reliable, more straightforward, and hence a promising metric for voxel-level RS-fMRI studies. Future study could use both PerAF and mPerAF metrics. For prompting future application of PerAF, we implemented PerAF in a new version of REST package named RESTplus.
Journal Article
ShadowEth: Private Smart Contract on Public Blockchain
Blockchain is becoming popular as a distributed and reliable ledger which allows distrustful parties to transact safely without trusting third parties. Emerging blockchain systems like Ethereum support smart contracts where miners can run arbitrary user-defined programs. However, one of the biggest concerns about the blockchain and the smart contract is privacy, since all the transactions on the chain are exposed to the public. In this paper, we present ShadowEth, a system that leverages hardware enclave to ensure the confidentiality of smart contracts while keeping the integrity and availability based on existing public blockchains like Ethereum. ShadowEth establishes a confidential and secure platform protected by trusted execution environment (TEE) off the public blockchain for the execution and storage of private contracts. It only puts the process of verification on the blockchain. We provide a design of our system including a protocol of the cryptographic communication and verification and show the applicability and feasibility of ShadowEth by various case studies. We implement a prototype using the Intel SGX on the Ethereum network and analyze the security and availability of the system.
Journal Article
DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging
Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies.
Journal Article
Prevalence of Nontraumatic Osteonecrosis of the Femoral Head and its Associated Risk Factors in the Chinese Population： Results from a Nationally Representative Survey
Background： Nontraumatic osteonecrosis of the femoral head （NONFH） is a debilitating disease that represents a significant financial burden for both individuals and healthcare systems. Despite its significance, however, its prevalence in the Chinese general population remains unknown. This study aimed to investigate the prevalence of NONFH and its associated risk factors in the Chinese population. Methods： A nationally representative survey of 30,030 respondents was undertaken from June 2012 to August 2013. All participants underwent a questionnaire investigation, physical examination of hip, and bilateral hip joint X-ray and/or magnetic resonance imaging exalnination. Blood samples were taken after overnight fasting to test serum total cholesterol, triglyceride, and high-density lipoprotein （HDL） and low-density lipoprotein （LDL） levels. We then used multivariate logistic regression analysis to investigate the associations between various metabolic, demographic, and lifestyle-related variables and NONFH. Results： NONFH was diagnosed in 218 subjects （0.725%） and the estimated NONFH cases were 8.12 million among Chinesepeople aged 15 years and over. The prevalence of NONFH was significantly higher in males than in females （1.02% vs. 0.51%, x^2 = 24.997, P 〈 0.001 ）. Among NONFH patients, North residents were subjected to higher prevalence of NONFH than that of South residents （0.85% vs. 0.61%,x^2= 5.847, P = 0.016）. Our multivariate regression analysis showed that high blood levels oftriglycerides, total cholesterol, LDL-cholesterol, and non-H DL-cholesterol, male, urban residence, family history of osteonecrosis of the femoral head. heavy smoking, alcohol abuse and glucocorticoid intake, overweight, and obesity were all significantly associated with an increased risk of NONFH. Conclusions： Our findings highlight that NONFH is a significantpublic health challenge in China and underscore the need for policy measures on the national level. Furthermore, NONFH shares a number of risk factors with atherosclerosis.
Journal Article
Default mode network mediates low‐frequency fluctuations in brain activity and behavior during sustained attention
The low‐frequency (<0.1 Hz) fluctuation in sustained attention attracts enormous interest in cognitive neuroscience and clinical research since it always leads to cognitive and behavioral lapses. What is the source of the spontaneous fluctuation in sustained attention in neural activity, and how does the neural fluctuation relate to behavioral fluctuation? Here, we address these questions by collecting and analyzing two independent fMRI and behavior datasets. We show that the neural (fMRI) fluctuation in a key brain network, the default‐mode network (DMN), mediate behavioral (reaction time) fluctuation during sustained attention. DMN shows the increased amplitude of fluctuation, which correlates with the behavioral fluctuation in a similar frequency range (0.01–0.1 Hz) but not in the lower (<0.01 Hz) or higher (>0.1 Hz) frequency range. This was observed during both auditory and visual sustained attention and was replicable across independent datasets. These results provide a novel insight into the neural source of attention‐fluctuation and extend the former concept that DMN was deactivated in cognitive tasks. More generally, our findings highlight the temporal dynamic of the brain–behavior relationship. DMN shows the increased amplitude of fluctuation, which correlates with the behavioral fluctuation only in the frequency range of 0.01–0.1 Hz. This mediation effect of DMN was observed during both auditory and visual sustained attention and could be replicated across independent datasets. These results provide a novel insight into the neural source of attention‐fluctuation and highlight the temporal dynamic of the brain–behavior relationship.
Journal Article
Abnormal individualized peak functional connectivity toward potential repetitive transcranial magnetic stimulation treatment of autism spectrum disorder
Functional connectivity (FC) derived from resting‐state functional magnetic resonance imaging has been widely applied to guide precise repetitive transcranial magnetic stimulation (rTMS). The left, right, and bilateral dorsolateral prefrontal cortices (DLPFC) have been used as rTMS treatment target regions for autism spectrum disorder (ASD), albeit with moderate efficacy. Thus, we aimed to develop an individualized localization method for rTMS treatment of ASD. We included 266 male ASDs and 297 male typically‐developed controls (TDCs) from the Autism Brain Imaging Data Exchange Dataset. The nucleus accumbens (NAc) was regarded as a promising effective region, which was used as a seed and individualized peak FC strength in the DLPFC was compared between ASD and TDC. Correlation analysis was conducted between individualized peak FC strength and symptoms in ASD. We also investigated the spatial distribution of individualized peak FC locations in the DLPFC and conducted voxel‐wise analysis to compare NAc‐based FC between the two groups. ASD showed stronger peak FC in the right DLPFC related to TDC (Cohen's d = −.19, 95% CI: −0.36 to −0.03, t = −2.30, p = .02). Moreover, negative correlation was found between the peak FC strength in the right DLPFC and Autism Diagnostic Observation Schedule (ADOS) scores, which assessed both the social communication and interaction (r = −.147, p = .04, uncorrected significant), and stereotyped behaviors and restricted interests (r = −.198, p = .02, corrected significant). Peak FC locations varied substantially across participants. No significant differences in NAc‐based FC in the DLPFC were found in the voxel‐wise comparison. Our study supports the use of individualized peak FC‐guided precise rTMS treatment of male ASD. Moreover, stimulating the right DLPFC might alleviate core symptoms of ASD. Abnormal individualized peak FC and its association with autism symptoms in the right DLPFC support the use of individualized peak FC‐guided precise rTMS treatment of male participants with ASD. Moreover, stimulating right DLPFC through individualized peak FC might alleviate symptoms of ASD.
Journal Article
Standardizing the intrinsic brain: Towards robust measurement of inter-individual variation in 1000 functional connectomes
As researchers increase their efforts to characterize variations in the functional connectome across studies and individuals, concerns about the many sources of nuisance variation present and their impact on resting state fMRI (R-fMRI) measures continue to grow. Although substantial within-site variation can exist, efforts to aggregate data across multiple sites such as the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data-sharing Initiative (INDI) datasets amplify these concerns. The present work draws upon standardization approaches commonly used in the microarray gene expression literature, and to a lesser extent recent imaging studies, and compares them with respect to their impact on relationships between common R-fMRI measures and nuisance variables (e.g., imaging site, motion), as well as phenotypic variables of interest (age, sex). Standardization approaches differed with regard to whether they were applied post-hoc vs. during pre-processing, and at the individual vs. group level; additionally they varied in whether they addressed additive effects vs. additive+multiplicative effects, and were parametric vs. non-parametric. While all standardization approaches were effective at reducing undesirable relationships with nuisance variables, post-hoc approaches were generally more effective than global signal regression (GSR). Across approaches, correction for additive effects (global mean) appeared to be more important than for multiplicative effects (global SD) for all R-fMRI measures, with the exception of amplitude of low frequency fluctuations (ALFF). Group-level post-hoc standardizations for mean-centering and variance-standardization were found to be advantageous in their ability to avoid the introduction of artifactual relationships with standardization parameters; though results between individual and group-level post-hoc approaches were highly similar overall. While post-hoc standardization procedures drastically increased test–retest (TRT) reliability for ALFF, modest reductions were observed for other measures after post-hoc standardizations—a phenomena likely attributable to the separation of voxel-wise from global differences among subjects (global mean and SD demonstrated moderate TRT reliability for these measures). Finally, the present work calls into question previous observations of increased anatomical specificity for GSR over mean centering, and draws attention to the near equivalence of global and gray matter signal regression.
•Global mean and SD for R-fMRI measures showed strong site, motion and age effects.•Post-hoc standardizations were more effective in reducing nuisance effects than GSR.•Correction for additive effects is more important than for multiplicative effects.•Group-level standardizations are advantageous to individual-level standardizations.
Journal Article