Gender differences in brain areas involved in silent counting by means of fMRI

Background

Pattern of brain asymmetries varies with handedness, gender, age, and with variety of genetic and social factors. Large-scale neuroimaging analyses can optimize the detection of asymmetric features and confirm the factors that might modulate pattern of brain asymmetries. We attempted to evaluate eventual differences between genders in hemodynamic responses to a simple language task.

Methods

12 healthy right-handed volunteers (age 24-46), 6 men and 6 women underwent fMRI scanning while performing the simple cognitive - language processing task – silent number counting in Serbian.

Results

Group analysis of hemodynamic responses shows activation in expected brain language areas of inferior frontal gyrus (IFG) and superior temporal gyrus (STG) in both hemispheres. In the male group, aside from dedicated language areas in IFG and STG, activation was noted in right frontal region and interhemispheric supplementary motor area. On the other hand, in the female group, besides activation in dedicated language areas, activation was noted, in right hippocampus, limbic brain and cerebellum bilaterally.

Conclusions

Our results on differences in silent counting by means of fMRI suggest that those differences may be based on different brain pattern activation in men and women. The relation between performance, strategies and regional brain activation should be the topic of further studies when considering not only gender differences in language processing but also differences that may be attributed to the variations in the task details, stimuli, and the stimulus presentation methods.

     

Visual fixation in the vegetative state: an observational case series PET study

Background

Assessment of visual fixation is commonly used in the clinical examination of patients with disorders of consciousness. However, different international guidelines seem to disagree whether fixation is compatible with the diagnosis of the vegetative state (i.e., represents "automatic" subcortical processing) or is a sufficient sign of consciousness and higher order cortical processing.

Methods

We here studied cerebral metabolism in ten patients with chronic post-anoxic encephalopathy and 39 age-matched healthy controls. Five patients were in a vegetative state (without fixation) and five presented visual fixation but otherwise showed all criteria typical of the vegetative state. Patients were matched for age, etiology and time since insult and were followed by repeated Coma Recovery Scale-Revised (CRS-R) assessments for at least 1 year. Sustained visual fixation was considered as present when the eyes refixated a moving target for more than 2 seconds as defined by CRS-R criteria.

Results

Patients without fixation showed metabolic dysfunction in a widespread fronto-parietal cortical network (with only sparing of the brainstem and cerebellum) which was not different from the brain function seen in patients with visual fixation. Cortico-cortical functional connectivity with visual cortex showed no difference between both patient groups. Recovery rates did not differ between patients without or with fixation (none of the patients showed good outcome).

Conclusions

Our findings suggest that sustained visual fixation in (non-traumatic) disorders of consciousness does not necessarily reflect consciousness and higher order cortical brain function.

     

Rare variants in the splicing regulatory elements of EXOC3L4 are associated with brain glucose metabolism in Alzheimer’s disease

Background

Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases that causes problems related to brain function. To some extent it is understood on a molecular level how AD arises, however there are a lack of biomarkers that can be used for early diagnosis. Two popular methods to identify AD-related biomarkers use genetics and neuroimaging. Genes and neuroimaging phenotypes have provided some insights as to the potential for AD biomarkers. While the field of imaging-genomics has identified genetic features associated with structural and functional neuroimaging phenotypes, it remains unclear how variants that affect splicing could be important for understanding the genetic etiology of AD.

Methods

In this study, rare variants (minor allele frequency?<?0.01) in splicing regulatory element (SRE) loci from whole genome sequencing (WGS) in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort, were used to identify genes that are associated with global brain cortical glucose metabolism in AD measured by FDG PET-scans. Gene-based associated analyses of rare variants were performed using the program BioBin and the optimal Sequence Kernel Association Test (SKAT-O).

Results

The gene, EXOC3L4, was identified as significantly associated with global cortical glucose metabolism (FDR (false discovery rate) corrected p?<?0.05) using SRE coding variants only. Three loci that may affect splicing within EXOC3L4 contribute to the association.

Conclusion

Based on sequence homology, EXOC3L4 is likely a part of the exocyst complex. Our results suggest the possibility that variants which affect proper splicing of EXOC3L4 via SREs may impact vesicle transport, giving rise to AD related phenotypes. Overall, by utilizing WGS and functional neuroimaging we have identified a gene significantly associated with an AD related endophenotype, potentially through a mechanism that involves splicing.

     

Integrating fMRI and SNP data for biomarker identification for schizophrenia with a sparse representation based variable selection method

Background

In recent years, both single-nucleotide polymorphism (SNP) array and functional magnetic resonance imaging (fMRI) have been widely used for the study of schizophrenia (SCZ). In addition, a few studies have been reported integrating both SNPs data and fMRI data for comprehensive analysis.

Methods

In this study, a novel sparse representation based variable selection (SRVS) method has been proposed and tested on a simulation data set to demonstrate its multi-resolution properties. Then the SRVS method was applied to an integrative analysis of two different SCZ data sets, a Single-nucleotide polymorphism (SNP) data set and a functional resonance imaging (fMRI) data set, including 92 cases and 116 controls. Biomarkers for the disease were identified and validated with a multivariate classification approach followed by a leave one out (LOO) cross-validation. Then we compared the results with that of a previously reported sparse representation based feature selection method.

Results

Results showed that biomarkers from our proposed SRVS method gave significantly higher classification accuracy in discriminating SCZ patients from healthy controls than that of the previous reported sparse representation method. Furthermore, using biomarkers from both data sets led to better classification accuracy than using single type of biomarkers, which suggests the advantage of integrative analysis of different types of data.

Conclusions

The proposed SRVS algorithm is effective in identifying significant biomarkers for complicated disease as SCZ. Integrating different types of data (e.g. SNP and fMRI data) may identify complementary biomarkers benefitting the diagnosis accuracy of the disease.

     

Pseudo current density maps of electrophysiological heart,nerve or brain function and their physical basis

Background

In recent years the visualization of biomagnetic measurement data by so-called pseudo current density maps or Hosaka-Cohen (HC) transformations became popular.

Methods

The physical basis of these intuitive maps is clarified by means of analytically solvable problems.

Results

Examples in magnetocardiography, magnetoencephalography and magnetoneurography demonstrate the usefulness of this method.

Conclusion

Hardware realizations of the HC-transformation and some similar transformations are discussed which could advantageously support cross-platform comparability of biomagnetic measurements.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

Using network dynamic fMRI for detection of epileptogenic foci

Background

Epilepsy is one of the most prevalent neurological disorders. It remains medically intractable for about one-third of patients with focal epilepsy, for whom precise localization of the epileptogenic zone responsible for seizure initiation may be critical for successful surgery. Existing fMRI literature points to widespread network disturbances in functional connectivity. Per previous scalp and intracranial EEG studies and consistent with excessive local synchronization during interictal discharges, we hypothesized that, relative to same regions in healthy controls, epileptogenic foci would exhibit less chaotic dynamics, identifiable via entropic analyses of resting state fMRI time series.

Methods

In order to first validate this hypothesis on a cohort of patients with known ground truth, here we test individuals with well-defined epileptogenic foci (left mesial temporal lobe epilepsy). We analyzed voxel-wise resting-state fMRI time-series using the autocorrelation function (ACF), an entropic measure of regulation and feedback, and performed follow-up seed-to-voxel functional connectivity analysis. Disruptions in connectivity of the region exhibiting abnormal dynamics were examined in relation to duration of epilepsy and patients’ cognitive performance using a delayed verbal memory recall task.

Results

ACF analysis revealed constrained (less chaotic) functional dynamics in left temporal lobe epilepsy patients, primarily localized to ipsilateral temporal pole, proximal to presumed focal points. Autocorrelation decay rates differentiated, with 100 % accuracy, between patients and healthy controls on a subject-by-subject basis within a leave-one-subject out classification framework. Regions identified via ACF analysis formed a less efficient network in patients, as compared to controls. Constrained dynamics were linked with locally increased and long-range decreased connectivity that, in turn, correlated significantly with impaired memory (local left temporal connectivity) and epilepsy duration (left temporal – posterior cingulate cortex connectivity).

Conclusions

Our current results suggest that data driven functional MRI methods that target network dynamics hold promise in providing clinically valuable tools for identification of epileptic regions.

     

Neural correlates of body comparison and weight estimation in weight-recovered anorexia nervosa: a functional magnetic resonance imaging study

Background

The neural mechanisms underlying body dissatisfaction and emotional problems evoked by social comparisons in patients with anorexia nervosa (AN) are currently unclear. Here, we elucidate patterns of brain activation among recovered patients with AN (recAN) during body comparison and weight estimation with functional magnetic resonance imaging (fMRI).

Methods

We used fMRI to examine 12 patients with recAN and 13 healthy controls while they performed body comparison and weight estimation tasks with images of underweight, healthy weight, and overweight female bodies. In the body comparison task, participants rated their anxiety levels while comparing their own body with the presented image. In the weight estimation task, participants estimated the weight of the body in the presented image. We used between-group region of interest (ROI) analyses of the blood oxygen level dependent (BOLD) signal to analyze differences in brain activation patterns between the groups. In addition, to investigate activation outside predetermined ROIs, we performed an exploratory whole-brain analysis to identify group differences.

Results

We found that, compared to healthy controls, patients with recAN exhibited significantly greater activation in the pregenual anterior cingulate cortex (pgACC) when comparing their own bodies with images of underweight female bodies. In addition, we found that, compared with healthy controls, patients with recAN exhibited significantly smaller activation in the middle temporal gyrus corresponding to the extrastriate body area (EBA) when comparing their own bodies, irrespective of weight, during self-other comparisons of body shape.

Conclusions

Our findings from a group of patients with recAN suggest that the pathology of AN may lie in an inability to regulate negative affect in response to body images via pgACC activation during body comparisons. The findings also suggest that altered body image processing in the brain persists even after recovery from AN.

     

Sequencing bilateral and unilateral task-oriented training versus task oriented training alone to improve arm function in individuals with chronic stroke

Background

Recovering useful hand function after stroke is a major scientific challenge for patients with limited motor recovery. We hypothesized that sequential training beginning with proximal bilateral followed by unilateral task oriented training is superior to time-matched unilateral training alone. Proximal bilateral training could optimally prepare the motor system to respond to the more challenging task-oriented training.

Methods

Participants: Twenty-six participants with moderate severity hemiparesis Intervention: Participants received either 6-weeks of bilateral proximal training followed sequentially by 6-weeks unilateral task-oriented training (COMBO) or 12-weeks of unilateral task-oriented training alone (SAEBO). A subset of 8 COMB0 and 9 SAEBO participants underwent three functional magnetic resonance imaging (fMRI) scans of hand and elbow movement every 6 weeks. Main Outcome Measures: Fugl-Meyer Upper extremity scale, Modified Wolf Motor Function Test, University of Maryland Arm Questionnaire for Stroke, Motor cortex activation (fMRI).

Results

The COMBO group demonstrated significantly greater gains between baseline and 12-weeks over all outcome measures (p?=?.018 based on a MANOVA test) and specifically in the Modified Wolf Motor Function test (time). Both groups demonstrated within-group gains on the Fugl-Meyer Upper Extremity test (impairment) and University of Maryland Arm Questionnaire for Stroke (functional use). fMRI subset analyses showed motor cortex (primary and premotor) activation during hand movement was significantly increased by sequential combination training but not by task-oriented training alone.

Conclusions

Sequentially combining a proximal bilateral before a unilateral task-oriented training may be an effective way to facilitate gains in arm and hand function in those with moderate to severe paresis post-stroke compared to unilateral task oriented training alone.

     

Human amylin proteotoxicity impairs protein biosynthesis,and alters major cellular signaling pathways in the heart,brain and liver of humanized diabetic rat model in vivo

Introduction

Chronic hypersecretion of the 37 amino acid amylin is common in type 2 diabetics (T2D). Recent studies implicate human amylin aggregates cause proteotoxicity (cell death induced by misfolded proteins) in both the brain and the heart.

Objectives

Identify systemic mechanisms/markers by which human amylin associated with cardiac and brain defects might be identified.

Methods

We investigated the metabolic consequences of amyloidogenic and cytotoxic amylin oligomers in heart, brain, liver, and plasma using non-targeted metabolomics analysis in a rat model expressing pancreatic human amylin (HIP model).

Results

Four metabolites were significantly different in three or more of the four compartments (heart, brain, liver, and plasma) in HIP rats. When compared to a T2D rat model, HIP hearts uniquely had significant DECREASES in five amino acids (lysine, alanine, tyrosine, phenylalanine, serine), with phenylalanine decreased across all four tissues investigated, including plasma. In contrast, significantly INCREASED circulating phenylalanine is reported in diabetics in multiple recent studies.

Conclusion

DECREASED phenylalanine may serve as a unique marker of cardiac and brain dysfunction due to hyperamylinemia that can be differentiated from alterations in T2D in the plasma. While the deficiency in phenylalanine was seen across tissues including plasma and could be monitored, reduced tyrosine was seen only in the brain. The 50 % reduction in phenylalanine and tyrosine in HIP brains is significant given their role in supporting brain chemistry as a precursor for catecholamines (dopamine, norepinephrine, epinephrine), which may contribute to the increased morbidity and mortality in diabetics at a multi-system level beyond the effects on glucose metabolism.

     

Statistical analysis of fractionation resistance by functional category and expression

Background

The current literature establishes the importance of gene functional category and expression in promoting or suppressing duplicate gene loss after whole genome doubling in plants, a process known as fractionation. Inspired by studies that have reported gene expression to be the dominating factor in preventing duplicate gene loss, we analyzed the relative effect of functional category and expression.

Methods

We use multivariate methods to study data sets on gene retention, function and expression in rosids and asterids to estimate effects and assess their interaction.

Results

Our results suggest that the effect on duplicate gene retention fractionation by functional category and expression are independent and have no statistical interaction.

Conclusion

In plants, functional category is the more dominant factor in explaining duplicate gene loss.

     

A lost opportunity for science: journals promote data sharing in metabolomics but do not enforce it

Introduction

Data sharing is being increasingly required by journals and has been heralded as a solution to the ‘replication crisis’.

Objectives

(i) Review data sharing policies of journals publishing the most metabolomics papers associated with open data and (ii) compare these journals’ policies to those that publish the most metabolomics papers.

Methods

A PubMed search was used to identify metabolomics papers. Metabolomics data repositories were manually searched for linked publications.

Results

Journals that support data sharing are not necessarily those with the most papers associated to open metabolomics data.

Conclusion

Further efforts are required to improve data sharing in metabolomics.

     

High salt and fat intake,inflammation, and risk of cancer

Background

Inflammatory conditions are involved in the pathophysiology of cancer. Recent findings have revealed that excessive salt and fat intake is involved in the development of severe inflammatory reactions.

Methods

literature search was performed on various online databases (PubMed, Scopus, and Google Scholar) regarding the roles of high salt and fat intake in the induction of inflammatory reactions and their roles in the etiopathogenesis of cancer.

Results

The results indicate that high salt and fat intake can induce severe inflammatory conditions. However, various inflammatory conditions have been strongly linked to the development of cancer. Hence, high salt and fat intake might be involved in the pathogenesis of cancer progression via putative mechanisms related to inflammatory reactions.

Conclusion

Reducing salt and fat intake may decrease the risk of cancer.

     

Effect of experimental gingivitis induction and erythritol on the salivary metabolome and functional biochemistry of systemically healthy young adults

Introduction

Understanding the changes occurring in the oral ecosystem during development of gingivitis could help improve prevention and treatment strategies for oral health. Erythritol is a non-caloric polyol proposed to have beneficial effects on oral health.

Objectives

To examine the effect of experimental gingivitis and the effect of erythritol on the salivary metabolome and salivary functional biochemistry.

Methods

In a two-week experimental gingivitis challenge intervention study, non-targeted, mass spectrometry-based metabolomic profiling was performed on saliva samples from 61 healthy adults, collected at five time-points. The effect of erythritol was studied in a randomized, controlled trial setting. Fourteen salivary biochemistry variables were measured with antibody- or enzymatic activity-based assays.

Results

Bacterial amino acid catabolites (cadaverine, N-acetylcadaverine, and α-hydroxyisovalerate) and end-products of bacterial alkali-producing pathways (N-α-acetylornithine and γ-aminobutyrate) increased significantly during the experimental gingivitis. Significant changes were found in a set of 13 salivary metabolite ratios composed of host cell membrane lipids involved in cell signaling, host responses to bacteria, and defense against free radicals. An increase in mevalonate was also observed. There were no significant effects of erythritol. No significant changes were found in functional salivary biochemistry.

Conclusions

The findings underline a dynamic interaction between the host and the oral microbial biofilm during an experimental induction of gingivitis.

     

Metabolomic profiling of maternal hair suggests rapid development of intrahepatic cholestasis of pregnancy

Introduction

Intrahepatic cholestasis of pregnancy (ICP) is a common maternal liver disease; development can result in devastating consequences, including sudden fetal death and stillbirth. Currently, recognition of ICP only occurs following onset of clinical symptoms.

Objective

Investigate the maternal hair metabolome for predictive biomarkers of ICP.

Methods

The maternal hair metabolome (gestational age of sampling between 17 and 41 weeks) of 38 Chinese women with ICP and 46 pregnant controls was analysed using gas chromatography–mass spectrometry.

Results

Of 105 metabolites detected in hair, none were significantly associated with ICP.

Conclusion

Hair samples represent accumulative environmental exposure over time. Samples collected at the onset of ICP did not reveal any metabolic shifts, suggesting rapid development of the disease.

     

Identifying directed links in large scale functional networks: application to brain fMRI

Background

Biological experiments increasingly yield data representing large ensembles of interacting variables, making the application of advanced analytical tools a forbidding task. We present a method to extract networks of correlated activity, specifically from functional MRI data, such that: (a) network nodes represent voxels, and (b) the network links can be directed or undirected, representing temporal relationships between the nodes. The method provides a snapshot of the ongoing dynamics of the brain without sacrificing resolution, as the analysis is tractable even for very large numbers of voxels.

Results

We find that, based on topological properties of the networks, the method provides enough information about the dynamics to discriminate between subtly different brain states. Moreover, the statistical regularities previously reported are qualitatively preserved, i.e. the resulting networks display scale-free and small-world topologies.

Conclusion

Our method expands previous approaches to render large scale functional networks, and creates the basis for an extensive and -due to the presence of mixtures of directed and undirected links- richer motif analysis of functional relationships.

     

Invulnerability of bromelain against oxidative degeneration and cholinergic deficits imposed by dichlorvos in mice brains

Background

The present study elucidates the protective potential of bromelain against dichlorvos intoxication in mice brains. Dichlorvos induces the oxidative stress by disproportionating the balance between free radicals generation and their scavenging in neurons which leads to neuronal degeneration.

Methods

In this study, mice were divided into four groups-group I (control), group II (dichlorvos treated), group III (bromelain treated) and group IV (exposed to both bromelain and dichlorvos both).

Results

Dichlorvos treatment increased the levels of thiobarbituric acid reactive substances (TBARS) and protein carbonyl content (PCC) which indicate the increased oxidative stress. Meanwhile, brain endogenous antioxidants and cholinesterases level was decreased after dichlorvos exposure. Levels of TBARS and PCC decreased whereas cholinesterases level was recorded to be elevated after bromelain exposure.

Conclusion

Bromelain offered neuroprotection by decreasing oxidative stress and augmenting cholinesterases in mice brains. This study highlights the invulnerability of bromelain against oxidative and cholinergic deficits in mice brains.

     

Quantitative analysis of tetrahydrofolate metabolites from <Emphasis Type="Italic">clostridium autoethanogenum</Emphasis>

Introduction

Quantification of tetrahydrofolates (THFs), important metabolites in the Wood–Ljungdahl pathway (WLP) of acetogens, is challenging given their sensitivity to oxygen.

Objective

To develop a simple anaerobic protocol to enable reliable THFs quantification from bioreactors.

Methods

Anaerobic cultures were mixed with anaerobic acetonitrile for extraction. Targeted LC–MS/MS was used for quantification.

Results

Tetrahydrofolates can only be quantified if sampled anaerobically. THF levels showed a strong correlation to acetyl-CoA, the end product of the WLP.

Conclusion

Our method is useful for relative quantification of THFs across different growth conditions. Absolute quantification of THFs requires the use of labelled standards.

     

Untargeted metabolomics suffers from incomplete raw data processing

Introduction

Untargeted metabolomics is a powerful tool for biological discoveries. To analyze the complex raw data, significant advances in computational approaches have been made, yet it is not clear how exhaustive and reliable the data analysis results are.

Objectives

Assessment of the quality of raw data processing in untargeted metabolomics.

Methods

Five published untargeted metabolomics studies, were reanalyzed.

Results

Omissions of at least 50 relevant compounds from the original results as well as examples of representative mistakes were reported for each study.

Conclusion

Incomplete raw data processing shows unexplored potential of current and legacy data.