DPARSF: A MATLAB Toolbox for “Pipeline” Data Analysis of Resting-State fMRI

Resting-state functional magnetic resonance imaging (fMRI) has attracted more and more attention because of its effectiveness, simplicity and non-invasiveness in exploration of the intrinsic functional architecture of the human brain. However, user-friendly toolbox for “pipeline” data analysis of resting-state fMRI is still lacking. Based on some functions in Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST), we have developed a MATLAB toolbox called Data Processing Assistant for Resting-State fMRI (DPARSF) for “pipeline” data analysis of resting-state fMRI. After the user arranges the Digital Imaging and Communications in Medicine (DICOM) files and click a few buttons to set parameters, DPARSF will then give all the preprocessed (slice timing, realign, normalize, smooth) data and results for functional connectivity, regional homogeneity, amplitude of low-frequency fluctuation (ALFF), and fractional ALFF. DPARSF can also create a report for excluding subjects with excessive head motion and generate a set of pictures for easily checking the effect of normalization. In addition, users can also use DPARSF to extract time courses from regions of interest

High Throughput Sequencing Identifies MicroRNAs Mediating α-Synuclein Toxicity by Targeting Neuroactive-Ligand Receptor Interaction Pathway in Early Stage of Drosophila Parkinson\u27s Disease Model.

Parkinson\u27s disease (PD) is a prevalent neurodegenerative disorder with pathological features including death of dopaminergic neurons in the substantia nigra and intraneuronal accumulations of Lewy bodies. As the main component of Lewy bodies, α-synuclein is implicated in PD pathogenesis by aggregation into insoluble filaments. However, the detailed mechanisms underlying α-synuclein induced neurotoxicity in PD are still elusive. MicroRNAs are ~20nt small RNA molecules that fine-tune gene expression at posttranscriptional level. A plethora of miRNAs have been found to be dysregulated in the brain and blood cells of PD patients. Nevertheless, the detailed mechanisms and their in vivo functions in PD still need further investigation. By using Drosophila PD model expressing α-synuclein A30P, we examined brain miRNA expression with high-throughput small RNA sequencing technology. We found that five miRNAs (dme-miR-133-3p, dme-miR-137-3p, dme-miR-13b-3p, dme-miR-932-5p, dme-miR-1008-5p) were upregulated in PD flies. Among them, miR-13b, miR-133, miR-137 are brain enriched and highly conserved from Drosophila to humans. KEGG pathway analysis using DIANA miR-Path demonstrated that neuroactive-ligand receptor interaction pathway was most likely affected by these miRNAs. Interestingly, miR-137 was predicted to regulate most of the identified targets in this pathway, including dopamine receptor (DopR, D2R), γ-aminobutyric acid (GABA) receptor (GABA-B-R1, GABA-B-R3) and N-methyl-D-aspartate (NMDA) receptor (Nmdar2). The validation experiments showed that the expression of miR-137 and its targets was negatively correlated in PD flies. Further experiments using luciferase reporter assay confirmed that miR-137 could act on specific sites in 3\u27 UTR region of D2R, Nmdar2 and GABA-B-R3, which downregulated significantly in PD flies. Collectively, our findings indicate that α-synuclein could induce the dysregulation of miRNAs, which target neuroactive ligand-receptor interaction pathway in vivo. We believe it will help us further understand the contribution of miRNAs to α-synuclein neurotoxicity and provide new insights into the pathogenesis driving PD

Association between exposure to noise and risk of hypertension: A meta-analysis of observational epidemiological studies

Background and Objective: An increasing amount of original studies suggested that exposure to noise could be associated with the risk of hypertension, but the results remain inconsistent and inconclusive. We aimed to synthesize available epidemiological evidence about the relationship between various types of noise and hypertension, and to explore the potential dose-response relationship between them in an up-to-date meta-analysis. Methods: We conducted a literature search of PubMed and Embase from these databases’ inception through December 2016 to identify observational epidemiological studies examining the association between noise and risk of hypertension. A Random-effects model was used to combine the results of included studies. Dose-response meta-analysis was conducted to examine the potential dose-response relationship. Results: Thirty-two studies (five cohort studies, one case-control study, and twenty-six cross-section Studies) involving 264,678 participants were eligible for inclusion. Pooled result showed that living or working in environment with noise exposure was significantly associated with increase risk of hypertension (OR 1.62; 95% CI: 1.40 to 1.88). We found no evidence of a curve linear association between noise and risk of hypertension. Dose-response analysis suggested that, for an increment of per 10 dB(A) of noise, the combined odds ratio of hypertension was 1.06 (95% CI: 1.04 to 1.08). Conclusions: Integrated epidemiological evidence supports the hypothesis that exposure to noise may be a risk factor of hypertension, and there is a positive dose-response association between them

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

Altered spontaneous brain activity in Down Syndrome and its relation with cognitive outcome

Although Down syndrome (DS) is the most common genetic cause of neurodevelopmental delay, few neuroimaging studies have explored this population. This investigation aimed to study whole-brain resting-state spontaneous brain activity using fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) strategies to find differences in spontaneous brain activity among young people with DS and controls and to correlate these results with cognitive outcomes. The sample comprised 18 persons with DS (age mean = 28.67, standard deviation = 4.18) and 18 controls (age mean = 28.56, standard deviation = 4.26). fALFF and ReHo analyses were performed, and the results were correlated with other cognitive variables also collected (KBIT-2 and verbal fluency test). Increased activity was found in DS using fALFF in areas involving the frontal and temporal lobes and left cerebellum anterior lobe. Decreased activity in DS was found in the left parietal and occipital lobe, the left limbic lobe and the left cerebellum posterior lobe. ReHo analysis showed increased activity in certain DS areas of the left frontal lobe and left rectus, as well as the inferior temporal lobe. The areas with decreased activity in the DS participants were regions of the frontal lobe and the right limbic lobe. Altered fALFF and ReHo were found in the DS population, and this alteration could predict the cognitive abilities of the participants. To our knowledge, this is the first study to explore regional spontaneous brain activity in a population with DS. Moreover, this study suggests the possibility of using fALFF and ReHo as biomarkers of cognitive function, which is highly important given the difficulties in cognitively evaluating this population to assess dementia. More research is needed, however, to demonstrate its utility

Is carrot consumption associated with a decreased risk of lung cancer? A meta-analysis of observational studies

Findings of epidemiological studies regarding the association between carrot consumption and lung cancer risk remain inconsistent. The present study aimed to summarise the current epidemiological evidence concerning carrot intake and lung cancer risk with a meta-analysis. We conducted a meta-analysis of case–control and prospective cohort studies, and searched PubMed and Embase databases from their inception to April 2018 without restriction by language. We also reviewed reference lists from included articles. Prospective cohort or case–control studies reporting OR or relative risk with the corresponding 95 % CI of the risk lung cancer for the highest compared with the lowest category of carrot intake. A total of eighteen eligible studies (seventeen case–control studies and one prospective cohort study) were included, involving 202 969 individuals and 5517 patients with lung cancer. The pooled OR of eighteen studies for lung cancer was 0·58 (95%CI 0·45, 0·74) by comparing the highest category with the lowest category of carrot consumption. Based on subgroup analyses for the types of lung cancer, we pooled that squamous cell carcinoma (OR 0·52, 95 % CI 0·19, 1·45), small-cell carcinoma (OR 0·43, 95 % CI 0·12, 1·59), adenocarcinoma (OR 0·34, 95 % CI 0·15, 0·79), large-cell carcinoma (OR 0·40, 95 % CI 0·10, 1·57), squamous and small-cell carcinoma (OR 0·85, 95 % CI 0·45, 1·62), adenocarcinoma and large-cell carcinoma (OR 0·20, 95 % CI 0·02, 1·70) and mixed types (OR 0·61, 95 % CI 0·46, 0·81). Exclusion of any single study did not materially alter the pooled OR. Integrated epidemiological evidence from observational studies supported the hypothesis that carrot consumption may decrease the risk of lung cancer, especially for adenocarcinoma

Abnormal degree centrality and functional connectivity in Down syndrome: A resting-state fMRI study

Background/Objective: Neuroimaging studies have shown brain abnormalities in Down syndrome (DS) but have not clarified the underlying mechanisms of dysfunction. Here, we investigated the degree centrality (DC) abnormalities found in the DS group compared with the control group, and we conducted seed-based functional connectivity (FC) with the significant clusters found in DC. Moreover, we used the significant clusters of DC and the seed-based FC to elucidate differences between brain networks in DS compared with controls. Method: The sample comprised 18 persons with DS (M = 28.67, SD = 4.18) and 18 controls (M = 28.56, SD = 4.26). Both samples underwent resting-state functional magnetic resonance imaging. Results: DC analysis showed increased DC in the DS in temporal and right frontal lobe, as well as in the left caudate and rectus and decreased DC in the DS in regions of the left frontal lobe. Regarding seed-based FC, DS showed increased and decreased FC. Significant differences were also found between networks using Yeo parcellations, showing both hyperconnectivity and hypoconnectivity between and within networks. Conclusions: DC, seed-based FC and brain networks seem altered in DS, finding hypo- and hyperconnectivity depending on the areas. Network analysis revealed between- and within-network differences, and these abnormalities shown in DS could be related to the characteristics of the population

Meta-analysis on the association between the frequency of tooth brushing and diabetes mellitus risk

BACKGROUND AND OBJECTIVE: Epidemiological studies suggested that the frequency of tooth brushing might be associated with the risk of diabetes mellitus (DM), but the results were inconsistent and no systematic review was conducted to focus on this topic. In this meta-analysis, we synthesized available observational epidemiological evidences to identify the association between tooth brushing and DM risk and investigate the potential dose-response relationship of them. METHODS: We searched PubMed and Embase from their inception through December 2017 to identify observational studies examining the association between tooth brushing and the risk of DM. Reference lists from retrieved articles were also reviewed. We quantitatively combined results of the included studies using a random-effects model. Dose-response meta-analysis was conducted to further examine the effect of tooth brushing frequency on DM risk. RESULTS: We identified 20 relevant studies (one cohort study, 14 case-control studies, and five cross-sectional studies) involving161,189 participants and 10,884 patients with DM. Compared with the highest tooth brushing frequency, the lowest level was significantly associated with an increased risk of DM (OR 1.32, 95% CI: 1.19 to 1.47), and there was no significant heterogeneity across the included studies (P = 0.119, I2 = 28.1%). Exclusion of any single study did not materially alter the combined risk estimate. The dose-response analysis indicated that the summary odds of DM for an increment of one time of tooth brushing per day was 1.20 (95% CI: 1.16-1.24). CONCLUSIONS: Integrated epidemiological evidence supports the hypothesis that low frequency of tooth brushing may be a risk factor of DM, and lower frequencies of tooth brushing were significantly associated with higher risk of DM