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Dynamic functional networks (DFN) have considerably advanced modelling of the brain communication processes. The prevailing implementation capitalizes on the system and network-level correlations between time series. However, this approach does not account for the continuous impact of non-dynamic dependencies within the statistical correlation, resulting in relatively stable connectivity patterns of DFN over time with limited sensitivity for communication dynamic between brain regions. Here, we propose an activation network framework based on the activity of functional connectivity (AFC) to extract new types of connectivity patterns during brain communication process. The AFC captures potential time-specific fluctuations associated with the brain communication processes by eliminating the non-dynamic dependency of the statistical correlation. In a simulation study, the positive correlation (r=0.966,p

ObjectiveInflammatory bowel disease (IBD) and alcohol use has become a significant and growing public health concern. Alcohol use has been reported to be the most-avoided diet item among IBD patients. However, knowledge regarding the impact of different classes of alcoholic beverages on the management of IBD is limited. Our study aims to evaluate the association of different frequencies, amounts, and subtypes of alcoholic beverages with IBD risk.MethodsThe UK Biobank comprised 7,095 subjects with IBD and 4,95,410 subjects without IBD. Multivariate Logistic regression, stratifying analysis, and interaction terms were used to estimate the odds ratios (ORs) and 95% confidence intervals (95% CIs) of IBD. A generalized additive model was used to evaluate the linearity associations of the total amount of all alcoholic beverages or that of each of five alcoholic beverages with IBD risk.ResultsCompared with non-drinkers, the IBD risk was 12 to 16% lower in red wine consumers (1–2 glasses/week, OR [95%CI], 0.88 [0.80, 0.97]; 3–4 glasses/week, 0.84 [0.76, 0.93]; ≥5 glasses/week, 0.86 [0.78, 0.95]), whereas 12% higher in white wine and champagne consumers (1–2 glasses/week, 1.12 [1.03, 1.22]). Stratifying analysis showed low-frequency red wine consumers were associated with a lower IBD risk (0.85 [0.74, 0.97]), whereas spirits consumers were associated with a higher risk (1.28 [1.03, 1.59]). High doge of red wine consumers were associated with a lower IBD risk (above guidelines, 0.80 [0.67, 0.97]; double above, 0.83 [0.71, 0.97]), whereas high doge white wine and champagne (1.32 [1.09, 1.61]) and beer and cider (1.26 [1.02, 1.54]) consumers were associated with a higher IBD risk. White wine and champagne showed a significant interaction effect with high doge alcohol consumption (1.27 [1.03–1.58], p = 0.029). The dose-response association showed an increased IBD risk with more number of alcohol consumption of white wine and champagne, beer and cider, or the total amount of all alcoholic beverages. However, red wine is at low risk across the whole dose cycle.ConclusionsThe IBD risk appears to vary across different frequencies, amounts, and subtypes of alcoholic beverages. Overall, alcohol intake is not recommended.

BackgroundThe purpose of the study was to examine the association of long and short sleep duration with risk of Parkinson’s disease (PD) across RORA rs2028122 genotypes.MethodsIn the present prospective study with a large sized UK Biobank cohort, we performed multivariate logistic regression analyses, generalized additive model, interaction terms, stratification analysis, and mediation analysis to evaluate the association of long and short sleep duration with risk of PD across RORA rs2028122 genotypes.ResultsThe GG genotype [1.16 (1.01, 1.33)], a short sleep duration [1.23 (1.10, 1.37)], and a long sleep duration [1.19 (1.03, 1.37)] were identified as the independent risk factors for PD. Sleep duration exhibited a curvilinear U-shaped correlation with the risk of PD; first, the risk of PD gradually decreased as the length of sleep increase, but then, the risk began to increase as the length of sleep increase. Among habitual long sleepers, AG carriers had a higher risk of PD compared with AA carriers [1.67 (1.09, 2.55)]. Among AG carriers, both habitual short [1.28 (1.09, 1.50)] and long [1.38 (1.13, 1.69)] sleepers increased the risk of PD compared with habitual normal sleepers. Among GG carriers, habitual short sleepers have a higher risk of PD [1.26 (1.06, 1.50)] compared with habitual normal sleepers. A mediation model suggested that the rs2028122 genotype partially mediated the causal pathway of sleep duration leading to the development of PD on a positive effect.ConclusionOur study demonstrated that the association between sleep duration and PD risk varied across different RORA rs2028122 genotypes. Our findings could help individuals to identify their potential risk profile and take timely actions to prevent the PD.

Objectives: To evaluate the associations of status, amount, and frequency of alcohol consumption across different alcoholic beverages with coronavirus disease 2019 (COVID-19) risk and associated mortality.Methods: This study included 473,957 subjects, 16,559 of whom tested positive for COVID-19. Multivariate logistic regression analyses were used to evaluate the associations of alcohol consumption with COVID-19 risk and associated mortality. The non-linearity association between the amount of alcohol consumption and COVID-19 risk was evaluated by a generalized additive model.Results: Subjects who consumed alcohol double above the guidelines had a higher risk of COVID-19 (1.12 [1.00, 1.25]). Consumption of red wine above or double above the guidelines played protective effects against the COVID-19. Consumption of beer and cider increased the COVID-19 risk, regardless of the frequency and amount of alcohol intake. Low-frequency of consumption of fortified wine (1–2 glasses/week) within guidelines had a protective effect against the COVID-19. High frequency of consumption of spirits (≥5 glasses/week) within guidelines increased the COVID-19 risk, whereas the high frequency of consumption of white wine and champagne above the guidelines decreased the COVID-19 risk. The generalized additive model showed an increased risk of COVID-19 with a greater number of alcohol consumption. Alcohol drinker status, frequency, amount, and subtypes of alcoholic beverages were not associated with COVID-19 associated mortality.Conclusions: The COVID-19 risk appears to vary across different alcoholic beverage subtypes, frequency, and amount. Red wine, white wine, and champagne have chances to reduce the risk of COVID-19. Consumption of beer and cider and spirits and heavy drinking are not recommended during the epidemics. Public health guidance should focus on reducing the risk of COVID-19 by advocating healthy lifestyle habits and preferential policies among consumers of beer and cider and spirits.

Objective To investigate the functional connectivity changes of benign epilepsy of childhood with centrotemporal spikes (BECTS) by using degree centrality (DC) analysis. Methods Choose 27 children diagnosed as BECTS from January 2010 to December 2017 as object of observation and 27 age/ sex⁃matched normal children as control. All subjects were performed fMRI in resting state. DC analysis was used to characterize the connectome patterns of whole⁃brain functional networks. Pearson correlation analysis was performed to evaluate the relationship between DC values of brain regions that differed between BECTS and normal children and the behavioral factors, including Raven's Standard Progressive Matrices (RSPM) intelligence quotient (IQ) and Integrated Visual and Auditory Continuous Performance Test (IVA⁃CPT). Results Compared with normal children, BECTS children exhibited higher DC valuesinthe right superior frontal gyrus and right posterior cingulate gyrus, and lower DC values in the bilateral cerebellar posterior lobes, subcortical mass in bilateral corpus striatum and/or thalami and right superior frontal gyrus. The higher DC value in the right posterior cingulate gyrus showed significant negative correlations with RSPM IQ score(r=⁃0.597, P=0.001) and full scale attention quotient score(r=⁃0.400, P=0.039). The RSPM IQ score showed significant positive correlations with the lower DC values in left cerebellar posterior lobe (r=0.442, P =0.021) and right corpus striatum/thalamus (r=0.452, P =0.018). Conclusions BECTS is associated with functional abnormalities in thalamic⁃cortical networks. DC analysis could provide a brand⁃new method for exploring the neurobiological mechanisms of epileptic discharges in BECTS.

Coronavirus disease 2019 (COVID-19), a respiratory disease of unknown origin, has a high rate of morbidity and mortality. Individuals with mental disorders may have a higher risk of infection and worse clinical outcomes because of a variety of factors such as poorer general resilience and lower immune function. However, there have been no studies to date specifically investigating the risk of COVID-19 and associated mortality in these patients. This was addressed in the present study by analyzing the data of 473,958 subjects included in the UK Biobank, 14,877 of whom tested positive for COVID-19 infection. Logistic regression analysis was performed to evaluate the associations between mental disorders and risks of COVID-19 infection and associated mortality. The results showed that subjects who were diagnosed with a mental disorder had a significantly higher risk of developing COVID-19 and a worse outcome as evidenced by higher rates of COVID-19-related mortality, with the strongest effects observed for dementia. Among dementia subtypes, Alzheimer disease patients had the highest risks of COVID-19 infection (7.39-fold increase) and associated mortality (2.13-fold increase). Late-life anxiety only increased the risk of developing COVID-19 while late-life depression not only was associated with a higher risk of infection but also a worse outcome. These findings highlight the need to prioritize patients with mental disorders-especially those who experience these disorders later in life—when implementing preventive strategies such as vaccinations.

Brain structural covariance network (SCN) can delineate the brain synchronized alterations in a long-range time period. It has been used in the research of cognition or neuropsychiatric disorders. Recently, causal analysis of structural covariance network (CaSCN), winner-take-all and cortex–subcortex covariance network (WTA-CSSCN), and modulation analysis of structural covariance network (MOD-SCN) have expended the technology breadth of SCN. However, the lack of user-friendly software limited the further application of SCN for the research. In this work, we developed the graphical user interface (GUI) toolkit of brain structural covariance connectivity based on MATLAB platform. The software contained the analysis of SCN, CaSCN, MOD-SCN, and WTA-CSSCN. Also, the group comparison and result-showing modules were included in the software. Furthermore, a simple showing of demo dataset was presented in the work. We hope that the toolkit could help the researchers, especially clinical researchers, to do the brain covariance connectivity analysis in further work more easily.

BackgroundDigestive system cancers (DSCs) are associated with high morbidity and mortality. S100P has been reported as a prognostic biomarker in DSCs, but its prognostic value remains controversial. Accordingly, we conducted a meta-analysis to investigate whether S100P is correlated with overall survival (OS) of patients with DSCs. The relationship between S100P and clinicopathological features was also evaluated.MethodsWe systematically searched PubMed, Embase, Web of Science and Cochrane Library for eligible studies up to January 2020. In total, 16 publications with 1,925 patients were included.ResultsS100P overexpression was associated with poor OS of patient with DSCs (HR=1.54, 95% CI: 1.14–2.08, P=0.005). When stratified by anatomic structure, S100P overexpression was associated with poor prognosis in non-gastrointestinal tract cancers (HR=1.98, 95% CI: 1.44–2.72, P

Abstract Primary insomnia (PIs) is highly prevalent and can lead to adverse socioeconomic impacts, but the underlying mechanism of its complex brain network impairment remains largely unknown. Functional studies are too few and diverse in methodology, which makes it difficult to glean general conclusions. To answer this question, we first used graph theory-based network analyse, together with seed-based functional connectivity approach, to characterize the topology architecture of whole-brain functional networks associated with PIs. Forty-eight subjects with PIs and 48 age/sex/education-matched good sleepers were recruited. We found PIs is associated with altered connection properties of intra-networks within the executive control network, default mode network and salience network, and inter-network between auditory language comprehension center and executive control network. These complex networks were correlated with negative emotions and insomnia severity in the PIs group. Altered connection properties of these network hubs appeared to be neural risk factors for neuropsychological changes of PIs, and might be used as potential neuroimaging markers to distinguish the PIs from the good sleepers. These findings highlight the role of functional connectivity in the pathophysiology of PIs, and may underlie the neural mechanisms of etiology of PIs.

Objectives: To investigate the performance of substate classification of children with benign epilepsy with centrotemporal spikes (BECTS) by granger causality density (GCD) based support vector machine (SVM) model.Methods: Forty-two children with BECTS (21 females, 21 males; mean age, 8.6 ± 1.96 years) were classified into interictal epileptic discharges (IEDs; 11 females, 10 males) and non-IEDs (10 females, 11 males) substates depending on presence of central-temporal spikes or not. GCD was calculated on four metrics, including inflow, outflow, total-flow (inflow + outflow) and int-flow (inflow – outflow) connectivity. SVM classifier was applied to discriminate the two substates.Results: The Rolandic area, caudate, dorsal attention network, visual cortex, language networks, and cerebellum had discriminative effect on distinguishing the two substates. Relative to each of the four GCD metrics, using combined metrics could reach up the classification performance (best value; AUC, 0.928; accuracy rate, 90.83%; sensitivity, 90%; specificity, 95%), especially for the combinations with more than three GCD metrics. Specially, combined the inflow, outflow and int-flow metric received the best classification performance with the highest AUC value, classification accuracy and specificity. Furthermore, the GCD-SVM model received good and stable classification performance across 14 dimension reduced data sets.Conclusions: The GCD-SVM model could be used for BECTS substate classification, which might have the potential to provide a promising model for IEDs detection. This may help assist clinicians for administer drugs and prognosis evaluation.

Objective: To identify the underlying intrinsic functional connectome changes in patients with alcohol dependence.Methods: A functional connectivity density (FCD) analysis was used to report on the functional connectivity changes in 24 male patients with alcohol dependence (age, 47.83 ± 6.93 years) and 24 healthy male subjects (age, 47.67 ± 6.99 years). We defined the voxels with a correlated threshold of r > 0.25 inside their neighborhood (radius sphere ≤ 6 mm) as shortFCD, and radius sphere > 6 mm as longFCD. We repeated the network analysis using a range of correlation r thresholds (r = 0.30, 0.35, 0.40, 0.45, 0.50, 0.6, and 0.75) to determine whether between-group differences were substantially affected by the selection of the different R-value thresholds used. A ROC curve was used to test the ability of the FCD in discriminating between the two groups. Pearson's correlation was used to evaluate the relationships between the FCD differences in brain areas and demographic characteristics.Results: The covered differences in brain areas in binarized shortFCD were larger than binarized longFCD in both groups. The intra-group FCD differences did not depend on the selection of different thresholds used. Patients with alcohol dependence were associated with the longFCD deficit in the cerebellum posterior lobe, and shortFCD deficit in the ventral system of the visual pathway and increased shortFCD in the left precentral gyrus, right salience network and right cingulate gyrus. A ROC curve demonstrated that these specific brain areas alone discriminated between the two groups with a high degree of sensitivity and specificity. In the alcohol dependence group, the cerebellum posterior lobe, visual association cortex and the salience network displayed significant correlations with demographic characteristics.Conclusions: The shortFCD analysis was more sensitive than the longFCD analysis in finding differences in the brain areas. The ventral visual pathway-cerebellar circuit deficit appeared to be altered in patients with alcohol dependence.

Background: Insufficient sleep is common in daily life and can lead to cognitive impairment. Sleep disturbance also exists in neuropsychiatric diseases. However, whether and how acute and chronic sleep loss affect brain morphology remain largely unknown.Methods: We used voxel-based morphology method to study the brain structural changes during sleep deprivation (SD) at six time points of rested wakefulness, 20, 24, 32, 36 h SD, and after one night sleep in 22 healthy subjects, and in 39 patients with chronic primary insomnia relative to 39 status-matched good sleepers. Attention network and spatial memory tests were performed at each SD time point in the SD Procedure. The longitudinal data were analyzed using one-way repeated measures ANOVA, and post-hoc analysis was used to determine the between-group differences.Results: Acute SD is associated with widespread gray matter volume (GMV) changes in the thalamus, cerebellum, insula and parietal cortex. Insomnia is associated with increased GMV in temporal cortex, insula and cerebellum. Acute SD is associated with brain atrophy and as SD hours prolong more areas show reduced GMV, and after one night sleep the brain atrophy is restored and replaced by increased GMV in brain areas. SD has accumulative negative effects on attention and working memory.Conclusions: Acute SD and insomnia exhibit distinct morphological changes of GMV. SD has accumulative negative effects on brain morphology and advanced cognitive function. The altered GMV may provide neurobiological basis for attention and memory impairments following sleep loss.Statement of significanceSleep is less frequently studied using imaging techniques than neurological and psychiatric disorders. Whether and how acute and chronic sleep loss affect brain morphology remain largely unknown. We used voxel-based morphology method to study brain structural changes in healthy subjects over multiple time points during sleep deprivation (SD) status and in patients with chronic insomnia. We found that prolonged acute SD together with one night sleep recovery exhibits accumulative atrophic effect and recovering plasticity on brain morphology, in line with behavioral changes on attentional tasks. Furthermore, acute SD and chronic insomnia exhibit distinct morphological changes of gray matter volume (GMV) but they also share overlapping GMV changes. The altered GMV may provide structural basis for attention and memory impairments following sleep loss.

Recent fMRI studies have demonstrated that resting-state functional connectivity (FC) is of nonstationarity. Temporal variability of FC reflects the dynamic nature of brain activity. Exploring temporal variability of FC offers a new approach to investigate reorganization and integration of brain networks after stroke. Here, we examined longitudinal alterations of FC temporal variability in brain networks after stroke. Nineteen stroke patients underwent resting fMRI scans across the acute stage (within-one-week after stroke), subacute stage (within-two-weeks after stroke), and early chronic stage (3-4 months after stroke). Nineteen age- and sex-matched healthy individuals were enrolled. Compared with the controls, stroke patients exhibited reduced regional temporal variability during the acute stages, which was recovered at the following two stages. Compared with the acute stage, the subacute stage exhibited increased temporal variability in the primary motor, auditory, and visual cortices. Across the three stages, the temporal variability in the ipsilesional precentral gyrus (PreCG) was increased first and then reduced. Increased temporal variability in the ipsilesional PreCG from the acute stage to the subacute stage was correlated with motor recovery from the acute stage to the early chronic stage. Our results demonstrated that temporal variability of brain network might be a potential tool for evaluating and predicting motor recovery after stroke.

Functional connectivity maps using resting-state functional magnetic resonance imaging (rs-fMRI) can closely resemble task fMRI activation patterns, suggesting that resting-state brain activity may predict task-evoked activation or behavioral performance. However, this conclusion was mostly drawn upon a healthy population. It remains unclear whether the predictive ability of resting-state brain activity for task-evoked activation would change under different pathological conditions. This study investigated dynamic changes of coupling between patterns of resting-state functional connectivity (RSFC) and motion-related activation in different stages of cerebral stroke. Twenty stroke patients with hand motor function impairment were involved. rs-fMRI and hand motion-related fMRI data were acquired in the acute, subacute, and early chronic stages of cerebral stroke on a 3-T magnetic resonance (MR) scanner. Sixteen healthy participants were enrolled as controls. For each subject, an activation map of the affected hand was first created using general linear model analysis on task fMRI data, and then an RSFC map was determined by seeding at the peak region of hand motion activation during the intact hand task. We then measured the extent of coupling between the RSFC maps and motion-related activation maps. Dynamic changes of the coupling between the two fMRI maps were estimated using one-way repeated measures analysis of variance across the three stages. Moreover, imaging parameters were correlated with motor performances. Data analysis showed that there were different coupling patterns between motion-related activation and RSFC maps associating with the affected motor regions during the acute, subacute, and early chronic stages of stroke. Coupling strengths increased as the recovery from stroke progressed. Coupling strengths were correlated with hand motion performance in the acute stage, while coupling recovery was negatively correlated with the recovery outcome of hand motion performance in the early chronic stages. Couplings between RSFC and motion-related activation were dynamically changed with stroke progression, which suggested changes in the prediction of resting-state brain activity for task-evoked brain activity in different pathological states. The changes in coupling strength between these two types of brain activity implicate a reparative mechanism of brain injury and may represent a biomarker for predicting motor recovery in cerebral stroke.

Sleep deprivation (SD) adversely affects brain function and is accompanied by frequency dependent changes in EEG. Recent studies have suggested that BOLD fluctuations pertain to a spatiotemporal organization with different frequencies. The present study aimed to investigate the frequency-dependent SD-related brain oscillatory activity by using the amplitude of low-frequency fluctuation (ALFF) analysis. The ALFF changes were measured across different frequencies (Slow-4: 0.027-0.073 Hz; Slow-5: 0.01-0.027 Hz; and Typical band: 0.01-0.08 Hz) in 24 h SD as compared to rested wakeful during resting-state fMRI. Sixteen volunteers underwent two fMRI sessions, once during rested wakefulness and once after 24 h of SD. SD showed prominently decreased ALFF in the right inferior parietal lobule (IPL), bilateral orbitofrontal cortex (OFC) and dorsolateral prefrontal cortex (DLPFC), while increased ALFF in the visual cortex, left sensorimotor cortex and fusiform gyrus. Across the Slow-4 and Slow-5, results differed significantly in the OFC, DLPFC, thalamus and caudate in comparison to typical frequency band; and Slow-4 showed greater differences. In addition, negative correlations of behavior performance and ALFF patterns were found mainly in the right IPL across the typical frequency band. These observations provided novel insights about the physiological responses of SD, identified how it disturbs the brain rhythms, and linked SD with frequency-dependent alterations in amplitude patterns.

Objective: To explore the abnormal intrinsic functional hubs in alcohol dependence using voxelwise degree centrality analysis approach, and their relationships with clinical features. Materials and methods: Twenty-four male alcohol dependence subjects free of medicine (mean age, 50.21±9.62 years) and 24 age- and education-matched male healthy controls (mean age, 50.29±8.92 years) were recruited. The alcohol use disorders identification test and the severity of alcohol dependence questionnaire (SADQ) were administered to assess the severity of alcohol craving. Voxelwise degree centrality approach was used to assess the abnormal intrinsic functional hubs features in alcohol dependence. Simple linear regression analysis was performed to investigate the relationships between the clinical features and abnormal intrinsic functional hubs. Results: Compared with healthy controls, alcohol dependence subjects exhibited significantly different degree centrality values in widespread left lateralization brain areas, including higher degree centrality values in the left precentral gyrus (BA 6), right hippocampus (BA 35, 36), and left orbitofrontal cortex (BA 11) and lower degree centrality values in the left cerebellum posterior lobe, bilateral secondary visual network (BA 18), and left precuneus (BA 7, 19). SADQ revealed a negative linear correlation with the degree centrality value in the left precentral gyrus (R2=0.296, P=0.006). Conclusion: The specific abnormal intrinsic functional hubs appear to be disrupted by alcohol intoxication, which implicates at least three principal neural systems: including cerebellar, executive control, and visual cortex, which may further affect the normal motor behavior such as an explicit type of impaired driving behavior. These findings expand our understanding of the functional characteristics of alcohol dependence and may provide a new insight into the understanding of the dysfunction and pathophysiology of alcohol dependence. [ABSTRACT FROM AUTHOR]

Background: Duplex kidney is a common anomaly that is frequently associated with multiple complications. Typical computed tomography urography (CTU) includes four phases (unenhanced, arterial, parenchymal and excretory) and has been suggested to considerably aid in the duplex kidney diagnosi. Unfortunately, regarding duplex kidney with prolonged dilatation, the affected parenchyma and tortuous ureters demonstrate a lack of or delayed excretory opacification. We used prolonged-delay CTU, which consists of another prolonged-delay phase (1- to 72-h delay; mean delay: 24 h) to opacify the duplicated ureters and affected parenchyma.Methods: Seventeen patients (9 males and 8 females; age range: 2.5-56 y; mean age: 40.4 y) with duplex kidney were included in this study. Unenhanced scans did not find typical characteristics of duplex kidney, except for irregular perirenal morphology. Duplex kidney could not be confirmed on typical four-phase CTU, whereas it could be easily diagnosed in axial and CT-3D reconstruction using prolonged CTU (prolonged-delay phase).Results: Between January 2005 and October 2010, in this review board-approved study (with waived informed consent), 17 patients (9 males and 8 females; age range: 2.5 ~ 56 y; mean age: 40.4 y) with suspicious duplex kidney underwent prolonged CTU to opacify the duplicated ureters and confirm the diagnosis.Conclusion: Our results suggest the validity of prolonged CTU to aid in the evaluation of the function of the affected parenchyma and in the demonstration of urinary tract malformations. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study is to explore the resting-state functional connectivity (FC) differences between the paired default mode network (DMN) subregions in patients with primary insomnia (PIs). Methods: Forty-two PIs and forty-two age- and sex-matched good sleepers (GSs) were recruited. All subjects underwent the resting-state functional magnetic resonance imaging scans. The seed-based region-to-region FC method was used to evaluate the abnormal connectivity within the DMN subregions between the PIs and the GSs. Pearson correlation analysis was used to investigate the relationships between the abnormal FC strength within the paired DMN subregions and the clinical features in PIs. Results: Compared with the GSs, the PIs showed higher Pittsburgh Sleep Quality Index score, Hamilton Anxiety Rating Scale score, Hamilton Depression Rating Scale score, Self-Rating Depression Scale score, Self Rating Anxiety Scale score, Self-Rating Scale of Sleep score, and Profile of Mood States score (P,0.001). Compared with the GSs, the PIs showed significant decreased region-to-region FC between the medial prefrontal cortex and the right medial temporal lobe (t=-2.275, P=0.026), and between the left medial temporal lobe and the left inferior parietal cortices (t=-3.32, P=0.001). The abnormal FC strengths between the DMN subregions did not correlate with the clinical features. Conclusion: PIs showed disrupted FC within the DMN subregions. [ABSTRACT FROM AUTHOR]

Central nervous system (CNS) cryptococcosis is an opportunistic fungal infection that typically occurs in patients with reduced immunological function, such as patients with AIDS, patients receiving organ transplants, or patients receiving corticosteroid and immunosuppressive therapy. CNS cryptococcosis rarely occurs in immunocompetent patients. CNS cryptococcosis is characterized by meningitis and encephalitis and occasionally forms isolated granulomas. Isolated cerebellar cryptococcoma is a rare condition, especially in immunocompetent patients, and the misdiagnosis rate is high. A definite diagnosis must be based on pathology. To raise awareness of this disease, the clinical data of a patient with cryptococcomas in the right side of the cerebellum are reported. [ABSTRACT FROM AUTHOR]

Background: The majority of previous neuroimaging studies have demonstrated both structural and functional abnormalities in obstructive sleep apnea (OSA). However, few studies have focused on the regional intensity of spontaneous fluctuations during the resting state and the relationship between the abnormal properties and the behavioral performances. In the present study, we employed the amplitude of low-frequency fluctuation (ALFF) method to explore the local features of spontaneous brain activity in OSA patients (OSAs). Methods: Twenty-five untreated male severe OSAs and 25 age-matched and years-of-educationmatched male good sleepers (GSs) were included in this study. The ALFF method was used to assess the local features of spontaneous brain activity. The mean signal values of the altered ALFF areas were analyzed with receiver operating characteristic curve. Partial correlation analysis was used to explore the relationship between the observed mean ALFF values of the different areas and the behavioral performances. Results: Compared with GSs, OSAs had significantly higher scores for body mass index, apnea- hypopnea index, arterial oxygen saturation <90%, arousal index, and Epworth Sleepiness Scale (ESS) score; furthermore, OSAs had significantly lower scores for rapid eye movement sleep and in the Montreal Cognitive Assessment (MoCA). Compared with GSs, OSAs showed significant lower-ALFF areas in the cluster of the right precuneus and bilateral posterior cingulate gyrus, as well as a higher-ALFF area in the left inferior frontal gyrus. The area under the curve values of the lower- and higher-ALFF areas were 0.90 and 0.93, respectively. Further diagnostic analysis exhibited that the sensibility and specificity of the two clusters were 80% and 92%, respectively. The mean signal value of the lower-ALFF cluster displayed significant positive correlations with lowest oxygen saturation (r=0.447, P=0.025) and MoCA score (r=0.405, P=0.045). Conclusion: OSAs may involve in a dysfunction in the default mode network and an adaptive compensatory response in the frontal lobe, which reflect the underlying pathophysiology of cognitive impairment. [ABSTRACT FROM AUTHOR]

Study objective: To prospectively explore the underlying regional homogeneity (ReHo) brain-activity deficit in patients with chronic primary insomnia (PCPIs) and its relationship with clinical features. Design: The ReHo method and Statistical Parametric Mapping 8 software were used to evaluate whether resting-state localized brain activity was modulated between PCPIs and good sleepers (GSs), and correlation analysis between altered regional brain areas and clinical features was calculated. Patients and participants: Twenty-four PCPIs (17 females, seven males) and 24 (12 females, 12 males) age-, sex-, and education-matched GSs. Measurements and results: PCPIs disturbed subjective sleep quality, split positive mood, and exacerbated negative moods. Compared with GSs, PCPIs showed higher ReHo in left fusiform gyrus, and lower ReHo in bilateral cingulate gyrus and right cerebellum anterior lobe. Compared with female GSs, female PCPIs showed higher ReHo in the left fusiform gyrus and right posterior cingulate, and lower ReHo in the left cerebellum anterior lobe and left superior frontal gyrus. Compared with male GSs, male PCPIs showed higher ReHo in the right temporal lobe and lower ReHo in the bilateral frontal lobe. The fusiform gyrus showed strong positive correlations and the frontal lobe showed negative correlations with the clinical measurements. Conclusion: The ReHo analysis is a useful noninvasive imaging tool for the detection of cerebral changes and the indexing of clinical features. The abnormal spontaneous activity areas provided important information on the neural mechanisms underlying emotion and sleep-quality impairment in PCPIs. [ABSTRACT FROM AUTHOR]

Background: Previous studies have demonstrated that obstructive sleep apnea (OSA) is associated with abnormal brain structural deficits. However, little is known about the changes in local synchronization of spontaneous activity in patients with OSA. The primary aim of the present study was to investigate spontaneous brain activity in patients with OSA compared with good sleepers (GSs) using regional homogeneity (ReHo) analysis based on resting-state functional magnetic resonance imaging (MRI). Methods: Twenty-five untreated male patients with severe OSA and 25 male GSs matched for age and years of education were included in this study. The ReHo method was calculated to assess the strength of local signal synchrony and was compared between the two groups. The observed mean ReHo values were entered into Statistical Package for the Social Sciences software to assess their correlation with behavioral performance. Results: Compared with GSs, patients with OSA showed significantly lower ReHo in the right medial frontal gyrus (BA11), right superior frontal gyrus (BA10), right cluster of the precuneus and angular gyrus (BA39), and left superior parietal lobule (BA7), and higher ReHo in the right posterior lobe of the cerebellum, right cingulate gyrus (BA23), and bilateral cluster covering the lentiform nucleus, putamen, and insula (BA13). The lower mean ReHo value in the right cluster of the precuneus and angular gyrus had a significant negative correlation with sleep time (r=-0.430, P=0.032), and higher ReHo in the right posterior lobe of the cerebellum showed a significant positive correlation with stage 3 sleep (r=0.458, P=0.021) and in the right cingulate gyrus showed a significant positive correlation with percent rapid eye movement sleep (r=0.405, P=0.045). Conclusion: Patients with OSA showed significant regional spontaneous activity deficits in default mode network areas. The ReHo method is a useful noninvasive imaging tool for detection of early changes in cerebral ReHo in patients with OSA. [ABSTRACT FROM AUTHOR]