scholarly journals The efficacy of different preprocessing steps in reducing motion-related confounds in diffusion MRI connectomics

2020 ◽  
Author(s):  
Stuart Oldham ◽  
Aurina Arnatkevic̆iūtė ◽  
Robert E. Smith ◽  
Jeggan Tiego ◽  
Mark A. Bellgrove ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Motion Correction ◽  
Healthy Adult ◽  
Structural Connectivity ◽  
Head Motion ◽  
List Type ◽  
Edge Weighting ◽  
Quantitative Metrics ◽  
The Impact ◽  
Connectivity Strength

AbstractHead motion is a major confounding factor in neuroimaging studies. While numerous studies have investigated how motion impacts estimates of functional connectivity, the effects of motion on structural connectivity measured using diffusion MRI have not received the same level of attention, despite the fact that, like functional MRI, diffusion MRI relies on elaborate preprocessing pipelines that require multiple choices at each step. Here, we report a comprehensive analysis of how these choices influence motion-related contamination of structural connectivity estimates. Using a healthy adult sample (N = 252), we evaluated 240 different preprocessing pipelines, devised using plausible combinations of different choices related to explicit head motion correction, tractography propagation algorithms, track seeding methods, track termination constraints, quantitative metrics derived for each connectome edge, and parcellations. We found that an approach to motion correction that includes outlier replacement and within-slice volume correction led to a dramatic reduction in cross-subject correlations between head motion and structural connectivity strength, and that motion contamination is more severe when quantifying connectivity strength using mean tract fractional anisotropy rather than streamline count. We also show that the choice of preprocessing strategy can significantly influence subsequent inferences about network organization, with the location of network hubs varying considerably depending on the specific preprocessing steps applied. Our findings indicate that the impact of motion on structural connectivity can be successfully mitigated using recent motion-correction algorithms that include outlier replacement and within-slice motion correction.HighlightsWe assess how motion affects structural connectivity in 240 preprocessing pipelinesMotion contamination of structural connectivity depends on preprocessing choicesAdvanced motion correction tools reduce motion confoundsFA edge weighting is more susceptible to motion effects than streamline count

scholarly journals The impact of in-scanner head motion on structural connectivity derived from diffusion MRI

NeuroImage ◽  
2018 ◽  
Vol 173 ◽  
pp. 275-286 ◽  
Author(s):  
Graham L. Baum ◽  
David R. Roalf ◽  
Philip A. Cook ◽  
Rastko Ciric ◽  
Adon F.G. Rosen ◽  
...  
Keyword(s):  
Diffusion Mri ◽  
Structural Connectivity ◽  
Head Motion ◽  
The Impact

Effect of interictal epileptiform discharges on EEG-based functional connectivity networks

2019 ◽  
Author(s):  
Derek K. Hu ◽  
Daniel W. Shrey ◽  
Beth A. Lopour
Keyword(s):  
Functional Connectivity ◽  
Network Structure ◽  
Infantile Spasms ◽  
List Type ◽  
Interictal Spikes ◽  
Epileptiform Discharges ◽  
Interictal Epileptiform Discharges ◽  
Network Strength ◽  
The Impact ◽  
Connectivity Strength

AbstractObjectiveFunctional connectivity networks (FCNs) based on interictal electroencephalography (EEG) can identify pathological brain networks associated with epilepsy. FCNs are altered by interictal epileptiform discharges (IEDs), but it is unknown whether this is due to the morphology of the IED or the underlying pathological activity. Therefore, we characterized the impact of IEDs on the FCN through simulations and EEG analysis.MethodsWe introduced simulated IEDs to sleep EEG recordings of eight healthy controls and analyzed the effect of IED amplitude and rate on the FCN. We then generated FCNs based on epochs with and without IEDs and compared them to the analogous FCNs from eight subjects with infantile spasms (IS), based on 1,340 visually marked IEDs. Differences in network structure and strength were assessed.ResultsIEDs in IS subjects caused increased connectivity strength but no change in network structure. In controls, simulated IEDs with physiological amplitudes and rates did not alter network strength or structure.ConclusionsIncreases in connectivity strength in IS subjects are not artifacts caused by the interictal spike waveform and may be related to the underlying pathophysiology of IS.SignificanceDynamic changes in EEG-based FCNs during IEDs may be valuable for identification of pathological networks associated with epilepsy.HighlightsInfantile spasms subjects exhibit broadly increased connectivity strength during interictal spikesFunctional connectivity network structure is unaltered by interictal spikes in infantile spasmsSimulated spikes in healthy control EEG did not alter network strength or structure

scholarly journals Benchmarking common preprocessing strategies in early childhood functional connectivity MRI

2020 ◽  
Author(s):  
Kirk Graff ◽  
Ryann Tansey ◽  
Amanda Ip ◽  
Christiane Rohr ◽  
Dennis Dimond ◽  
...  
Keyword(s):  
Early Childhood ◽  
Functional Connectivity ◽  
Young Children ◽  
Noise Removal ◽  
Head Motion ◽  
List Type ◽  
Unique Challenge ◽  
Global Signal ◽  
Passive Viewing ◽  
The Impact

AbstractFunctional connectivity magnetic resonance imaging (FC-MRI) has been widely used to investigate neurodevelopment. However, FC-MRI is vulnerable to head motion, which is associated with age and distorts FC estimates. Numerous preprocessing strategies have been developed to mitigate confounds, each with advantages and drawbacks. Preprocessing strategies for FC-MRI have typically been validated and compared using resting state data from adults. However, FC-MRI in young children presents a unique challenge due to relatively high head motion and a growing use of passive viewing paradigms to mitigate motion. This highlights a need to compare processing choices in pediatric samples. To this end, we leveraged longitudinal, passive viewing fMRI data collected from 4 to 8-year-old children. We systematically investigated combinations of widely used and debated preprocessing strategies, namely global signal regression, volume censoring, ICA-AROMA, and bandpass filtering. We implemented commonly used metrics of noise removal (i.e. quality control-functional connectivity), metrics sensitive to individual differences (i.e. connectome fingerprinting), and, because data was collected during a passive viewing task, we also assessed the impact on stimulus-evoked responses (i.e. intersubject correlations; ISC). We found that the most efficacious pipeline included censoring, global signal regression, bandpass filtering, and head motion parameter regression. Despite the drawbacks of noise-mitigation steps, our findings show benefits for both noise removal and information retention in a high-motion early childhood sample.Highlights- We evaluated 27 preprocessing pipelines in passive viewing data from young children- Pipelines were evaluated on noise-removed and information retained- Pipelines that included censoring and GSR outperformed alternatives across benchmarks- For high-motion scans, preprocessing choices substantially alter connectomes

scholarly journals The Impact of In-Scanner Head Motion on Structural Connectivity Derived from Diffusion Tensor Imaging

2017 ◽  
Author(s):  
Graham L. Baum ◽  
David R. Roalf ◽  
Philip A. Cook ◽  
Rastko Ciric ◽  
Adon F.G. Rosen ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Data Quality ◽  
Diffusion Tensor ◽  
Brain Networks ◽  
Structural Connectivity ◽  
Head Motion ◽  
Dependent Manner ◽  
Assessment Protocol ◽  
The Impact ◽  
Structural Brain

ABSTRACTMultiple studies have shown that data quality is a critical confound in the construction of brain networks derived from functional MRI. This problem is particularly relevant for studies of human brain development where important variables (such as participant age) are correlated with data quality. Nevertheless, the impact of head motion on estimates of structural connectivity derived from diffusion tractography methods remains poorly characterized. Here, we evaluated the impact of in-scanner head motion on structural connectivity using a sample of 949 participants (ages 8-23 years old) who passed a rigorous quality assessment protocol for diffusion tensor imaging (DTI) acquired as part of the Philadelphia Neurodevelopmental Cohort. Structural brain networks were constructed for each participant using both deterministic and probabilistic tractography. We hypothesized that subtle variation in head motion would systematically bias estimates of structural connectivity and confound developmental inference, as observed in previous studies of functional connectivity. Even following quality assurance and retrospective correction for head motion, eddy currents, and field distortions, in-scanner head motion significantly impacted the strength of structural connectivity in a consistency-and length-dependent manner. Specifically, increased head motion was associated with reduced estimates of structural connectivity for high-consistency network edges, which included both short-and long-range connections. In contrast, motion inflated estimates of structural connectivity for low-consistency network edges that were primarily shorter-range. Finally, we demonstrate that age-related differences in head motion can both inflate and obscure developmental inferences on structural connectivity. Taken together, these data delineate the systematic impact of head motion on structural connectivity, and provide a critical context for identifying motion-related confounds in studies of structural brain network development.

scholarly journals Is it Time to Switch Your T1W Sequence? Assessing the Impact of Prospective Motion Correction on the Reliability and Quality of Structural Imaging

2019 ◽  
Author(s):  
Lei Ai ◽  
R. Cameron Craddock ◽  
Nim Tottenham ◽  
Jonathan P Dyke ◽  
Ryan Lim ◽  
...  
Keyword(s):  
Quality Control ◽  
Motion Correction ◽  
Intraclass Correlation ◽  
Brain Network ◽  
Motion Artifacts ◽  
Head Motion ◽  
Morphometric Measurements ◽  
Human Connectome Project ◽  
Quality Control Metrics ◽  
The Impact

AbstractNew large neuroimaging studies, such as the Adolescent Brain Cognitive Development study (ABCD) and Human Connectome Project (HCP) Development studies are adopting a new T1-weighted imaging sequence with prospective motion correction (PMC) in favor of the more traditional 3-Dimensional Magnetization-Prepared Rapid Gradient-Echo Imaging (MPRAGE) sequence. Here, we used a developmental dataset (ages 5-21, N=348) from the Healthy Brain Network (HBN) Initiative to directly compare two widely used MRI structural sequences: one based on the Human Connectome Project (MPRAGE) and another based on the ABCD study (MPRAGE+PMC). We aimed to determine if the morphometric measurements obtained from both protocols are equivalent or if one sequence has a clear advantage over the other. The sequences were also compared through quality control measurements. Inter- and intra-sequence reliability were assessed with another set of participants (N=71) from HBN that performed two MPRAGE and two MPRAGE+PMC sequences within the same imaging session, with one MPRAGE (MPRAGE1) and MPRAGE+PMC (MPRAGE+PMC1) pair at the beginning of the session and another pair (MPRAGE2 and MPRAGE+PMC2) at the end of the session. Intraclass correlation coefficients (ICC) scores for morphometric measurements such as volume and cortical thickness showed that intra-sequence reliability is the highest with the two MPRAGE+PMC sequences and lowest with the two MPRAGE sequences. Regarding inter-sequence reliability, ICC scores were higher for the MPRAGE1 - MPRAGE+PMC1 pair at the beginning of the session than the MPRAGE1 - MPRAGE2 pair, possibly due to the higher motion artifacts in the MPRAGE2 run. Results also indicated that the MPRAGE+PMC sequence is robust, but not impervious, to high head motion. For quality control metrics, the traditional MPRAGE yielded better results than MPRAGE+PMC in 5 of the 8 measurements. In conclusion, morphometric measurements evaluated here showed high inter-sequence reliability between the MPRAGE and MPRAGE+PMC sequences, especially in images with low head motion. We suggest that studies targeting hyperkinetic populations use the MPRAGE+PMC sequence, given its robustness to head motion and higher reliability scores. However, neuroimaging researchers studying non-hyperkinetic participants can choose either MPRAGE or MPRAGE+PMC sequences, but should carefully consider the apparent tradeoff between relatively increased reliability, but reduced quality control metrics when using the MPRAGE+PMC sequence.

scholarly journals Using Satellite Data for CBRN (Chemical, Biological, Radiological, and Nuclear) Threat Detection, Monitoring, and Modelling

2021 ◽  
Author(s):  
Gary Sutlieff ◽  
Lucy Berthoud ◽  
Mark Stinchcombe
Keyword(s):  
Satellite Data ◽  
Meteorological Data ◽  
Atmospheric Composition ◽  
Chemical Detection ◽  
List Type ◽  
Data Types ◽  
Wide Range ◽  
Future Technologies ◽  
The Impact ◽  
Near Future

Abstract CBRN (Chemical, Biological, Radiological, and Nuclear) threats are becoming more prevalent, as more entities gain access to modern weapons and industrial technologies and chemicals. This has produced a need for improvements to modelling, detection, and monitoring of these events. While there are currently no dedicated satellites for CBRN purposes, there are a wide range of possibilities for satellite data to contribute to this field, from atmospheric composition and chemical detection to cloud cover, land mapping, and surface property measurements. This study looks at currently available satellite data, including meteorological data such as wind and cloud profiles, surface properties like temperature and humidity, chemical detection, and sounding. Results of this survey revealed several gaps in the available data, particularly concerning biological and radiological detection. The results also suggest that publicly available satellite data largely does not meet the requirements of spatial resolution, coverage, and latency that CBRN detection requires, outside of providing terrain use and building height data for constructing models. Lastly, the study evaluates upcoming instruments, platforms, and satellite technologies to gauge the impact these developments will have in the near future. Improvements in spatial and temporal resolution as well as latency are already becoming possible, and new instruments will fill in the gaps in detection by imaging a wider range of chemicals and other agents and by collecting new data types. This study shows that with developments coming within the next decade, satellites should begin to provide valuable augmentations to CBRN event detection and monitoring. Article Highlights There is a wide range of existing satellite data in fields that are of interest to CBRN detection and monitoring. The data is mostly of insufficient quality (resolution or latency) for the demanding requirements of CBRN modelling for incident control. Future technologies and platforms will improve resolution and latency, making satellite data more viable in the CBRN management field

scholarly journals Does agricultural intensification cause tipping points in ecosystem services?

2021 ◽  
Author(s):  
Stephen C. L. Watson ◽  
Adrian C. Newton ◽  
Lucy E. Ridding ◽  
Paul M. Evans ◽  
Steven Brand ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Agricultural Intensification ◽  
Spatial Dynamics ◽  
Policy Option ◽  
List Type ◽  
Tipping Points ◽  
Software Models ◽  
Non Linear ◽  
Study Interval ◽  
The Impact

Abstract Context Agricultural intensification is being widely pursued as a policy option to improve food security and human development. Yet, there is a need to understand the impact of agricultural intensification on the provision of multiple ecosystem services, and to evaluate the possible occurrence of tipping points. Objectives To quantify and assess the long-term spatial dynamics of ecosystem service (ES) provision in a landscape undergoing agricultural intensification at four time points 1930, 1950, 1980 and 2015. Determine if thresholds or tipping points in ES provision may have occurred and if there are any detectable impacts on economic development and employment. Methods We used the InVEST suite of software models together with a time series of historical land cover maps and an Input–Output model to evaluate these dynamics over an 85-year period in the county of Dorset, southern England. Results Results indicated that trends in ES were often non-linear, highlighting the potential for abrupt changes in ES provision to occur in response to slight changes in underlying drivers. Despite the fluctuations in provision of different ES, overall economic activity increased almost linearly during the study interval, in line with the increase in agricultural productivity. Conclusions Such non-linear thresholds in ES will need to be avoided in the future by approaches aiming to deliver sustainable agricultural intensification. A number of positive feedback mechanisms are identified that suggest these thresholds could be considered as tipping points. However, further research into these feedbacks is required to fully determine the occurrence of tipping points in agricultural systems.

128 Development of an M1-polarized, non-viral chimeric antigen receptor macrophage (CAR-M) platform for cancer immunotherapy

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A141-A141
Author(s):  
Yumi Ohtani ◽  
Kayleigh Ross ◽  
Aditya Dandekar ◽  
Rashid Gabbasov ◽  
Michael Klichinsky
Keyword(s):  
Cancer Immunotherapy ◽  
Chimeric Antigen Receptor ◽  
Scale Up ◽  
Antigen Receptor ◽  
Innate Immune ◽  
List Type ◽  
M1 Phenotype ◽  
The Impact ◽  
Anti Tumor Activity ◽  
Immunosuppressive Factors

BackgroundWe have previously developed CAR-M as a novel cell therapy approach for the treatment of solid tumors.1 CAR-M have the potential to overcome key challenges that cell therapies face in the solid tumor setting – tumor infiltration, immunosuppression, lymphocyte exclusion – and can induce epitope spreading to overcome target antigen heterogeneity. While macrophages transduced with the adenoviral vector Ad5f35 (Ad CAR-M) traffic to tumors, provide robust anti-tumor activity, and recruit and activate T cells, we sought to identify a robust non-viral method of macrophage engineering in order to reduce the cost of goods, manufacturing complexity, and potential immunogenicity associated with viral vectors.MethodsAs innate immune cells, macrophages detect exogenous nucleic acids and respond with inflammatory and apoptotic programs. Thus, we sought to identify a means of mRNA delivery that avoids recognition by innate immune sensors. We screened a broad panel of mRNA encoding an anti-HER2 CAR comprising multiplexed 5’Cap and base modifications using an optimized and scalable electroporation approach and evaluated the impact of interferon-β priming on CAR-M phenotype and function.ResultsWe identified the optimal multiplexed mRNA modifications that led to maximal macrophage viability, transfection efficiency, intensity of CAR expression, and duration of expression. Non-viral HER2 CAR-M phagocytosed and killed human HER2+ tumor cells. Unlike Ad CAR-M, mRNA CAR-M were not skewed toward an M1 state by mRNA electroporation. Priming non-viral CAR-M with IFN-β induced a durable M1 phenotype, as shown by stable upregulation of numerous M1 markers and pathways. IFN-β priming significantly enhanced the anti-tumor activity of CAR but not control macrophages. IFN-β primed mRNA CAR-M were resistant to M2 conversion, maintaining an M1 phenotype despite challenge with various immunosuppressive factors, and converted bystander M2 macrophages toward M1. Interestingly, priming mRNA CAR-M with IFN-β significantly enhanced the persistence of CAR expression, overcoming the known issue of rapid mRNA turnover. RNA-seq analysis revealed that IFN-β priming affected pathways involved in increasing translation and decreasing RNA degradation in human macrophages.ConclusionsWe have established a novel, optimized non-viral CAR-M platform based on chemically modified mRNA and IFN-β priming. IFN-β priming induced a durable M1 phenotype, improved CAR expression, improved CAR persistence, led to enhanced anti-tumor function, and rendered resistance to immunosuppressive factors. This novel platform is amenable to scale-up, GMP manufacturing, and represents an advance in the development of CAR-M.ReferenceKlichinsky M, Ruella M, Shestova O, et al. Human chimeric antigen receptor macrophages for cancer immunotherapy. Nat Biotechnol 2020;38(8):947–953.

scholarly journals Research on the impact of ship traffic flow on the restricted channel segment of the middle Yangtze River based on traffic wave theory

2021 ◽  
Vol 3 (8) ◽  
Author(s):  
Ting Liu ◽  
Gabriel Lodewijks
Keyword(s):  
Traffic Flow ◽  
Flow Rate ◽  
Flow Simulation ◽  
Wave Theory ◽  
Flow Density ◽  
List Type ◽  
Ship Traffic ◽  
Traffic Wave ◽  
The Impact ◽  
Channel Segment

Abstract Abstract On the basis of the influence of dry season on ship traffic flow, the gathering and dissipating process of ship traffic flow was researched with Greenshields linear flow—density relationship model, the intrinsic relationship between the ship traffic congestion state and traffic wave in the unclosed restricted channel segment was emphatically explored when the ship traffic flow in a tributary channel inflows, and the influence law of multiple traffic waves on the ship traffic flow characteristics in unclosed restricted segment is revealed. On this basis, the expressions of traffic wave speed and direction, dissipation time of queued ships and the number of ships affected were provided, and combined with Monte Carlo method, the ship traffic flow simulation model in the restricted channel segment was built. The simulation results show that in closed restricted channel segment the dissipation time of ships queued is mainly related to the ship traffic flow rate of segments A and C, and the total number of ships affected to the ship traffic flow rate of segment A. And in unclosed restricted channel segment, the dissipation time and the total number of ships affected are also determined by the meeting time of the traffic waves in addition to the ship traffic flow rate of segments. The research results can provide the theoretical support for further studying the ship traffic flow in unclosed restricted channel segment with multiple tributaries Article Highlights The inflow of tributaries' ship traffic flows has an obvious impact on the traffic conditions in the unenclosed restricted channel segment. The interaction and influence between multiple ship traffic waves and the mechanism of generating new traffic waves are explained. The expression of both dissipation time of queued ships and the total number of ships affected in the closed and unclosed restricted channel segment are given.

scholarly journals Antibiotics at birth and later antibiotic courses: effects on gut microbiota

2021 ◽  
Author(s):  
Sofia Ainonen ◽  
Mysore V Tejesvi ◽  
Md. Rayhan Mahmud ◽  
Niko Paalanne ◽  
Tytti Pokka ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Control Group ◽  
List Type ◽  
Antibiotic Exposure ◽  
Microbiota Composition ◽  
Long Term Effects ◽  
The Impact ◽  
Antibiotic Courses ◽  
Gut Microbiota Composition

Abstract Background Intrapartum antibiotic prophylaxis (IAP) is widely used, but the evidence of the long-term effects on the gut microbiota and subsequent health of children is limited. Here, we compared the impacts of perinatal antibiotic exposure and later courses of antibiotic courses on gut microbiota. Methods This was a prospective, controlled cohort study among 100 vaginally delivered infants with different perinatal antibiotic exposures: control (27), IAP (27), postnatal antibiotics (24), and IAP and postnatal antibiotics (22). At 1 year of age, we performed next-generation sequencing of the bacterial 16S ribosomal RNA gene of fecal samples. Results Exposure to the perinatal antibiotics had a clear impact on the gut microbiota. The abundance of the Bacteroidetes phylum was significantly higher in the control group, whereas the relative abundance of Escherichia coli was significantly lower in the control group. The impact of the perinatal antibiotics on the gut microbiota composition was greater than exposure to later courses of antibiotics (28% of participants). Conclusions Perinatal antibiotic exposure had a marked impact on the gut microbiota at the age of 1 year. The timing of the antibiotic exposure appears to be the critical factor for the changes observed in the gut microbiota. Impact Infants are commonly exposed to IAP and postnatal antibiotics, and later to courses of antibiotics during the first year of life. Perinatal antibiotics have been associated with an altered gut microbiota during the first months of life, whereas the evidence regarding the long-term impact is more limited. Perinatal antibiotic exposure had a marked impact on the infant’s gut microbiota at 1 year of age. Impact of the perinatal antibiotics on the gut microbiota composition was greater than that of the later courses of antibiotics at the age of 1 year.

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