Evolution of Brain Activation with Good and Poor Motor Recovery after Stroke

2006 ◽  
Vol 20 (1) ◽  
pp. 24-41 ◽  
Author(s):  
Leeanne M. Carey ◽  
David F. Abbott ◽  
Gary F. Egan ◽  
Graham J. O’Keefe ◽  
Graham D. Jackson ◽  
...  
Keyword(s):  
Premotor Cortex ◽  
Brain Activation ◽  
Initial Study ◽  
Motor Recovery ◽  
Healthy Controls ◽  
Poor Recovery ◽  
Severe Impairment ◽  
Primary Sensorimotor Cortex ◽  
Posterior Shift ◽  
Over Time

Objective. To characterize the evolution of brain activation in stroke patients with variable motor recovery and quantify changes relative to healthy controls. Methods. Serial PET activation studies, using a simple finger-tapping task, and quantitative measures of motor performance were obtained in 9 patients (2-7 weeks poststroke and 6 months later) and compared with serial healthy volunteer data. Results. Patients with moderate impairment and good recovery ( n = 5) activated the primary sensorimotor cortex (SM1) contralateral to the paretic hand moved, bilateral supplementary motor area (SMA), contralateral cingulate gyrus, and ipsilateral lateral premotor cortex. Activation in the bilateral SMA was greater at the initial study but reduced over time compared to healthy controls and poor recoverers. Patients with severe impairment and poor recovery ( n =4) showed limited activation of contralateral SM1 and SMA at both studies and no significant change over time. A posterior shift in SM1 activation was evident in good and poor recoverers. Conclusions. Activation of typical motor regions and recruitment of additional sites occur subacutely poststroke, with evolution to normal patterns in moderately impaired patients who recover well. In comparison, severely impaired, poor-recovery patients show persistent, reduced activation. Dynamic changes in SMA, differentially observed in good recoverers over 6 months, highlight its importance in recovery.

scholarly journals Accumulation and Phytotoxicity of Two Commercial Biocides in the Lichen Evernia prunastri and the Moss Brachythecium sp.

Stresses ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 69-77
Author(s):  
Andrea Vannini ◽  
Giulia Canali ◽  
Sergio Enrico Favero-Longo ◽  
Stefano Loppi
Keyword(s):  
Benzalkonium Chloride ◽  
Photosynthetic Apparatus ◽  
Model Species ◽  
Evernia Prunastri ◽  
Active Compounds ◽  
Severe Impairment ◽  
Over Time

This study investigated the accumulation and phytotoxicity of two commercial biocides widely used for the removal of biological colonization from monuments, namely Biotin T® (3%) and Preventol RI80® (2%), on lichen and moss model species, specifically, Evernia prunastri and Brachythecium sp. The active compounds, benzalkonium chloride (BAC) for Preventol RI80 and isothiazolinone (OIT) for Biotin T, were accumulated in similar amounts in both species without significant changes for up to 21 days. Both compounds caused a severe impairment of the photosynthetic apparatus of these species, without any recovery over time, although Biotin T showed a faster and stronger action, and the moss was more sensitive than the lichen. By shedding light on the accumulation of BAC and OIT in lichens and mosses and quantifying their effectiveness to photosynthetically devitalize these organisms, the obtained results are a useful comparison for the implementation of green alternative products for the control of biodeteriogens.

scholarly journals Colonic Volume Changes in Paediatric Constipation Compared to Normal Values Measured Using MRI

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 974
Author(s):  
Hayfa Sharif ◽  
Caroline L. Hoad ◽  
Nichola Abrehart ◽  
Penny A. Gowland ◽  
Robin C. Spiller ◽  
...  
Keyword(s):  
Linear Regression ◽  
Physiological State ◽  
Functional Constipation ◽  
Initial Study ◽  
Healthy Controls ◽  
Volume Changes ◽  
Additional Information ◽  
Symptom Reports ◽  
Magnetic Resonance Imaging Mri ◽  
The Relationship

Background: Functional constipation in children is common. Management of this condition can be challenging and is often based on symptom reports. Increased, objective knowledge of colonic volume changes in constipation compared to health could provide additional information. However, very little data on paediatric colonic volume is available except from methods that are invasive or require unphysiological colonic preparations. Objectives: (1) To measure volumes of the undisturbed colon in children with functional constipation (FC) using magnetic resonance imaging (MRI) and provide initial normal range values for healthy controls, and (2) to investigate possible correlation of colonic volume with whole gut transit time (WGTT). Methods: Total and regional (ascending, transverse, descending, sigmoid, and rectum) colon volumes were measured from MRI images of 35 participants aged 7–18 years (16 with FC and 19 healthy controls), and corrected for body surface area. Linear regression was used to explore the relationship between total colon volume and WGTT. Results: Total colonic volume was significantly higher, with a median (interquartile range) of 309 mL (243–384 mL) for the FC group than for the healthy controls of 227 mL (180–263 mL). The largest increase between patients and controls was in the sigmoid colon–rectum region. In a linear regression model, there was a positive significant correlation between total colonic volume and WGTT (R = 0.56, p = 0.0005). Conclusions: This initial study shows increased volumes of the colon in children with FC, in a physiological state, without use of any bowel preparation. Increased knowledge of colonic morphology may improve understanding of FC in this age group and help to direct treatment.

Development of standardized regression-based formulas to assess meaningful cognitive change in early Parkinson’s disease

2020 ◽  
Author(s):  
Hannah L Combs ◽  
Kate A Wyman-Chick ◽  
Lauren O Erickson ◽  
Michele K York
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Test Scores ◽  
Prediction Models ◽  
Early Stage ◽  
Cognitive Change ◽  
Cognitive Test ◽  
Healthy Controls ◽  
Change Over Time ◽  
Over Time

Abstract Objective Longitudinal assessment of cognitive and emotional functioning in patients with Parkinson’s disease (PD) is helpful in tracking progression of the disease, developing treatment plans, evaluating outcomes, and educating patients and families. Determining whether change over time is meaningful in neurodegenerative conditions, such as PD, can be difficult as repeat assessment of neuropsychological functioning is impacted by factors outside of cognitive change. Regression-based prediction formulas are one method by which clinicians and researchers can determine whether an observed change is meaningful. The purpose of the current study was to develop and validate regression-based prediction models of cognitive and emotional test scores for participants with early-stage idiopathic PD and healthy controls (HC) enrolled in the Parkinson’s Progression Markers Initiative (PPMI). Methods Participants with de novo PD and HC were identified retrospectively from the PPMI archival database. Data from baseline testing and 12-month follow-up were utilized in this study. In total, 688 total participants were included in the present study (NPD = 508; NHC = 185). Subjects from both groups were randomly divided into development (70%) and validation (30%) subsets. Results Early-stage idiopathic PD patients and healthy controls were similar at baseline. Regression-based models were developed for all cognitive and self-report mood measures within both populations. Within the validation subset, the predicted and observed cognitive test scores did not significantly differ, except for semantic fluency. Conclusions The prediction models can serve as useful tools for researchers and clinicians to study clinically meaningful cognitive and mood change over time in PD.

Reward-Related Learning in Alcoholism

2011 ◽  
Vol 26 (S2) ◽  
pp. 2014-2014
Author(s):  
A. Heinz ◽  
A. Beck ◽  
S.Q. Park ◽  
L. Deserno ◽  
F. Schlagenhauf
Keyword(s):  
Reversal Learning ◽  
Ventral Striatum ◽  
Imaging Study ◽  
Brain Activation ◽  
Dopamine Synthesis ◽  
Healthy Controls ◽  
Reward Seeking ◽  
Positron Emission ◽  
Dorsolateral Prefrontal ◽  
Alcohol Dependent

The disposition and maintenance of alcohol addiction has been associated with dysfunctional learning, particularly with increased salience attribution to alcohol-associated stimuli and Pavlovian-to-instrumental transfer, which establishes an effect of alcohol-associated cues on operant alcohol seeking and consumption. Previous imaging studies showed that dopamine dysfunction in the ventral striatum is associated with increased brain activation elicited by alcohol-associated cues in brain areas associated with attention. Furthermore, brain activation elicited by non-alcohol (e.g. monetary) reward was decreased in detoxified alcohol-dependent patients. Neuroadaptation following addiction therefore seems to augment neuronal responses to well-established, drug-associated stimuli while interfering with the learning of new, reward-seeking behaviour patterns. Using functional magnetic resonance imaging (fMRI) we showed that in detoxified alcoholics, reward-dependent reversal learning is impaired compared to healthy controls, and that this impairment correlates with reduced functional connectivity between the ventral striatum and the dorsolateral prefrontal cortex. Furthermore, we will present first data from a multimodal imaging study combining fMRI and positron-emission-tomography (PET) to measure the association between dopamine synthesis reduction and impaired functional brain activation during reversal learning in detoxified alcohol-dependent patients compared with healthy controls.

scholarly journals OP0287 A MACHINE LEARNING APPROACH FOR PRECISION STRATIFICATION OF JUVENILE-ONSET SLE

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 179.2-179
Author(s):  
G. Robinson ◽  
J. Peng ◽  
P. Dönnes ◽  
L. Coelewij ◽  
M. Naja ◽  
...  
Keyword(s):  
Machine Learning ◽  
Logistic Regression ◽  
T Cell ◽  
B Cell ◽  
T Cell Subsets ◽  
Healthy Controls ◽  
Juvenile Onset ◽  
Immune Signature ◽  
Immune Phenotyping ◽  
Over Time

Background:Juvenile-onset systemic lupus erythematosus (JSLE) is a complex and heterogeneous disease characterised by diagnosis and treatment delays. An unmet need exists to better characterise the immunological profile of JSLE patients and investigate its links with the disease trajectory over time.Objectives:A machine learning (ML) approach was applied to explore new diagnostic signatures for JSLE based on immune-phenotyping data and stratify patients by specific immune characteristics to investigate longitudinal clinical outcome.Methods:Immune-phenotyping of 28 T-cell, B-cell and myeloid-cell subsets in 67 age and sex-matched JSLE patients and 39 healthy controls (HCs) was performed by flow cytometry. A balanced random forest (BRF) ML predictive model was developed (10,000 decision trees). 10-fold cross validation, Sparse Partial Least Squares-Discriminant Analysis (sPLS-DA) and logistic regression was used to validate the model. Longitudinal clinical data were related to the immunological features identified by ML analysis.Results:The BRF-model discriminated JSLE patients from healthy controls with 91% prediction accuracy suggesting that JSLE patients could be distinguished from HCs with high confidence using immunological parameters. The top-ranked immunological features from the BRF-model were confirmed using sPLS-DA and logistic regression and included CD19+ unswitched memory B-cells, naïve B-cells, CD14+monocytes and total CD4+, CD8+and memory T-cell subsets.K-mean clustering was applied to stratify patients using the validated signature. Four groups were identified, each with a distinct immune and clinical profile. Notably, CD8+T-cell subsets were important in driving patient stratification while B-cell markers were similarly expressed across the JSLE cohort. JSLE patients with elevated effector memory CD8+T-cell frequencies had more persistently active disease over time, and this was associated with increased treatment burden and prevalence of lupus nephritis. Finally, network analysis identified specific clinical features associated with each of the top JSLE immune-signature variables.Conclusion:Using a combined ML approach, a distinct immune signature was identified that discriminated between JSLE patients and HCs and further stratified patients. This signature could have diagnostic and therapeutic implications. Further immunological association studies are warranted to develop data-driven personalised medicine approaches for JSLE.Acknowledgments:Lupus UK, Rosetrees Trust, Versus ArthritisDisclosure of Interests:George Robinson: None declared, Junjie Peng: None declared, Pierre Dönnes: None declared, Leda Coelewij: None declared, Meena Naja: None declared, Anna Radziszewska: None declared, Chris Wincup: None declared, Hannah Peckham: None declared, David Isenberg Consultant of: Study Investigator and Consultant to Genentech, Yiannis Ioannou: None declared, Ines Pineda Torra: None declared, Coziana Ciurtin Grant/research support from: Pfizer, Consultant of: Roche, Modern Biosciences, Elizabeth Jury: None declared

scholarly journals Aberrant activation within auditory network is associated with psychiatric comorbidities in interictal migraineurs without aura

2020 ◽  
Author(s):  
Heng-Le Wei ◽  
Yu-Chen Chen ◽  
Yu-Sheng Yu ◽  
Xi Guo ◽  
Gang-Ping Zhou ◽  
...  
Keyword(s):  
Auditory Cortex ◽  
Resting State ◽  
Psychiatric Symptoms ◽  
Brain Activation ◽  
Superior Temporal Gyrus ◽  
Anxiety And Depression ◽  
Intracranial Volume ◽  
Healthy Controls ◽  
Postcentral Gyrus ◽  
Underlying Mechanisms

Abstract Background: Resting-state functional magnetic resonance imaging has confirmed auditory network dysfunction in migraine without aura (MwoA). Epidemiological investigations have disclosed that migraine is comorbid with many psychiatric symptoms. However, the underlying mechanisms of auditory cortex dysfunction linked to psychiatric disorders in MwoA remain unclear. The present study aimed to explore associations between brain activation in the auditory cortex and clinical and psychiatric characteristics in patients with MwoA during interictal periods.Methods: Resting-state data were acquired from patients with episodic MwoA (n=34) and healthy controls (n=30). Independent component analysis was used to extract and calculate the resting-state auditory network. Subsequently, we analyzed the correlations between spontaneous activation in the auditory cortex and clinical and psychiatric features in MwoA.Results: Compared with healthy controls, patients with MwoA showed increased activation in the left auditory cortex (i.e., superior temporal gyrus (STG), postcentral gyrus (PoCG) and insula). Brain activation in the left STG was positively correlated with anxiety scores, and activation in the left PoCG was negatively correlated with anxiety and depression scores. No significant differences were found in intracranial volume between the two groups.Conclusions: This study indicated that functional impairment and altered integration within the auditory cortex existed in patients with MwoA in the interictal period, suggesting that auditory cortex disruption as a biomarker may be implemented for the early diagnosis and prediction of neuropsychiatric impairment in MwoA.

scholarly journals Validation of Discrete and Regression-Based Performance and Cognitive Fatigability Normative Data for the Paced Auditory Serial Addition Test in Multiple Sclerosis

2021 ◽  
Vol 15 ◽  
Author(s):  
Caitlin S. Walker ◽  
Jason A. Berard ◽  
Lisa A. S. Walker
Keyword(s):  
Multiple Sclerosis ◽  
Normative Data ◽  
Cognitive Effort ◽  
Similar Proportion ◽  
Healthy Controls ◽  
Performance Decrement ◽  
Impaired Performance ◽  
Objective Performance ◽  
Serial Addition ◽  
Over Time

Cognitive fatigability is an objective performance decrement that occurs over time during a task requiring sustained cognitive effort. Although cognitive fatigability is a common and debilitating symptom in multiple sclerosis (MS), there is currently no standard for its quantification. The objective of this study was to validate the Paced Auditory Serial Addition Test (PASAT) discrete and regression-based normative data for quantifying performance and cognitive fatigability in an Ontario-based sample of individuals with MS. Healthy controls and individuals with MS completed the 3″ and 2″ versions of the PASAT. PASAT performance was measured with total correct, dyad, and percent dyad scores. Cognitive fatigability scores were calculated by comparing performance on the first half (or third) of the task to the last half (or third). The results revealed that the 3″ PASAT was sufficient to detect impaired performance and cognitive fatigability in individuals with MS given the increased difficulty of the 2″ version. In addition, using halves or thirds for calculating cognitive fatigability scores were equally effective methods for detecting impairment. Finally, both the discrete and regression-based norms classified a similar proportion of individuals with MS as having impaired performance and cognitive fatigability. These newly validated discrete and regression-based PASAT norms provide a new tool for clinicians to document statistically significant cognitive fatigability in their patients.

scholarly journals THE AGING BRAIN AND MOTOR LEARNING

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S655-S655
Author(s):  
Qu Tian ◽  
Roger Mullins ◽  
Abby Corkum ◽  
David Reiter ◽  
Daniel Pupo ◽  
...  
Keyword(s):  
Motor Learning ◽  
Repeated Measures ◽  
Middle Age ◽  
Brain Activation ◽  
Repeated Sequence ◽  
Learning Task ◽  
Initial Time ◽  
Aging Brain ◽  
Older Individuals ◽  
Over Time

Abstract The effect of aging on motor learning is poorly understood. This study investigated response time and patterns of brain activation induced over the course of a bimanual motor learning task in three age groups. Twenty-two cognitively unimpaired participants (32%women) were grouped into Young (<35,n=6), Middle-Age (36-59,n=10), and Old (60+,n=6). A self-paced bimanual motor learning task was performed during fMRI. The task consisted of using 2 capital and 2 lower case letters in strings of 16 cues with 6 novel alternating with 6 repeated sequence blocks. To assess learning, a repeated measures ANOVA tested whether average time per slide differed over time between novel and sequence conditions. Voxel-wise changes in brain activation between novel and sequence conditions over time were examined using a within-subject repeated measures model. Faster initial time per slide was associated with younger age (p0.05). Old had increased brain activation in repeated sequence than novel conditions in right postcentral and superior parietal regions during the early half of the task compared to the second half (p0.05). We found behavioral evidence of motor learning in Middle-Age and Old, but not Young, perhaps because younger individuals performed quickly and learned sequence almost immediately. Among older individuals, sequence-specific learning in parietal regions challenges the view that it is mediated by only motor areas.

scholarly journals High-Throughput Urinary Neopterin-to-Creatinine Ratio Monitoring of Systemic Inflammation

2019 ◽  
Vol 5 (1) ◽  
pp. 101-113
Author(s):  
Charlotte M Stuart ◽  
Elina Zotova ◽  
Grielof Koster ◽  
Aravinthan Varatharaj ◽  
Grace Richardson ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Systemic Inflammation ◽  
High Throughput ◽  
Healthy Controls ◽  
Creatinine Ratio ◽  
Clinical Scenarios ◽  
Inflammatory State ◽  
Urinary Neopterin ◽  
Pooled Sample ◽  
Over Time

Abstract Background Systemic inflammation is a marker of ill health and has prognostic implications in multiple health settings. Urinary neopterin is an excellent candidate as a nonspecific marker of systemic inflammation. Expression as urinary neopterin-to-creatinine ratio (UNCR) normalizes for urinary hydration status. Major attractions include (a) urine vs blood sampling, (b) integration of inflammation over a longer period compared with serum sampling, and (c) high stability of neopterin and creatinine. Methods A high-throughput ultraperformance LC-MS method was developed to measure neopterin and creatinine together from the same urine sample. The assay was applied in several clinical scenarios: healthy controls, symptomatic infections, and multiple sclerosis. Area under the curve was compared between weekly and monthly sampling scenarios. Analysis of a single pooled sample was compared with averaging results from analysis of individual samples. Results The assay has excellent intraassay and interassay precision, linearity of dilution, and spike and recovery. Higher UNCR was demonstrated in female vs male individuals, older age, inflammatory disease (multiple sclerosis), and symptomatic infections. In healthy controls, fluctuations in inflammatory state also occurred in the absence of symptomatic infection or other inflammatory triggers. Analysis of a single pooled sample, made up from weekly urine samples, integrates inflammatory activity over time. Conclusions UNCR is a useful biomarker of systemic inflammation. The method presented offers simplicity, speed, robustness, reproducibility, efficiency, and proven utility in clinical scenarios. UNCR fluctuations underline the importance of longitudinal monitoring, vs a single time point, to capture a more representative estimate of an individual's inflammatory state over time.

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