Exploring individual fixel-based white matter abnormalities in epilepsy.

Diffusion MRI has provided insight into the widespread structural connectivity changes that characterize epilepsies. Although syndrome-specific white matter abnormalities have been demonstrated, studies to date have predominantly relied on statistical comparisons between patient and control groups. For diffusion MRI techniques to be of clinical value, they should be able to detect white matter microstructural changes in individual patients. In this study, we apply an individualized approach to a technique known as fixel-based analysis, to examine fibre-tract-specific abnormalities in individuals with epilepsy. We explore the potential clinical value of this individualized fixel-based approach in epilepsy patients with differing syndromic diagnoses. Diffusion MRI data from 90 neurologically healthy control participants and 10 patients with epilepsy (temporal lobe epilepsy, progressive myoclonus epilepsy, and Dravet Syndrome, malformations of cortical development) were included in this study. Measures of fibre density and cross-section were extracted for all participants across brain white matter fixels, and mean values were computed within select tracts-of-interest. Scanner harmonized and normalized data were then used to compute Z-scores for individual patients with epilepsy. White matter abnormalities were observed in distinct patterns in individual patients with epilepsy, both at the tract and fixel level. For patients with specific epilepsy syndromes, the detected white matter abnormalities were in line with expected syndrome-specific clinical phenotypes. In patients with lesional epilepsies (e.g. hippocampal sclerosis, periventricular nodular heterotopia, and bottom-of-sulcus dysplasia), white matter abnormalities were spatially concordant with lesion location. This proof-of-principle study demonstrates the clinical potential of translating advanced diffusion MRI methodology to individual-patient-level use in epilepsy. This technique could be useful both in aiding diagnosis of specific epilepsy syndromes, and in localizing structural abnormalities, and is readily amenable to other neurological disorders. We have included code and data for this study so that individualized white matter changes can be explored robustly in larger cohorts in future work.

Dual function of OmpM as outer membrane tether and nutrient uptake channel in diderm Firmicutes.

The outer membrane (OM) in diderm, or Gram-negative, bacteria must be tethered to peptidoglycan for mechanical stability and to maintain cell morphology. Most diderm phyla from the Terrabacteria group have recently been shown to lack well-characterised OM attachment systems, but instead have OmpM, which could represent an ancestral tethering system in bacteria. Here, we have determined the structure of the most abundant OmpM protein from Veillonella parvula (diderm Firmicutes) by single particle cryogenic electron microscopy. We also characterised the channel properties of the transmembrane ß-barrel of OmpM and investigated the structure and PG-binding properties of its periplasmic stalk region. Our results show that OM tethering and nutrient acquisition are genetically linked in V. parvula, and probably other diderm Terrabacteria. This dual function of OmpM may have played a role in the loss of the OM in ancestral bacteria and the emergence of monoderm bacterial lineages.

Connectomes for 40,000 UK Biobank participants: A multi-modal, multi-scale brain network resource.

We mapped functional and structural brain networks for more than 40,000 UK Biobank participants. Structural connectivity was estimated with tractography and diffusion MRI. Resting-state functional MRI was used to infer regional functional connectivity. We provide high-quality structural and functional connectomes for multiple parcellation granularities, several alternative measures of interregional connectivity, and a variety of common data pre-processing techniques, yielding more than one million connectomes in total and requiring more than 200,000 h of compute time. For a single subject, we provide 28 out-of-the-box versions of structural and functional brain networks, allowing users to select, e.g., the parcellation and connectivity measure that best suit their research goals. Furthermore, we provide code and intermediate data for the time-efficient reconstruction of more than 1000 different versions of a subject's connectome based on an array of methodological choices. All connectomes are available via the UK Biobank data-sharing platform and our connectome mapping pipelines are openly available. In this report, we describe our connectome resource in detail for users, outline key considerations in developing an efficient pipeline to map an unprecedented number of connectomes, and report on the quality control procedures that were completed to ensure connectome reliability and accuracy. We demonstrate that our structural and functional connectivity matrices meet a number of quality control checks and replicate previously established findings in network neuroscience. We envisage that our resource will enable new studies of the human connectome in health, disease, and aging at an unprecedented scale.

Evaluation of tractogram filtering methods using human-like connectome phantoms.

Tractography algorithms are prone to reconstructing spurious connections. The set of streamlines generated with tractography can be post-processed to retain the streamlines that are most biologically plausible. Several microstructure-informed filtering algorithms are available for this purpose, however, the comparative performance of these methods has not been extensively evaluated. In this study, we aim to evaluate streamline filtering and post-processing algorithms using simulated connectome phantoms. We first establish a framework for generating connectome phantoms featuring brain-like white matter fiber architectures. We then use our phantoms to systematically evaluate the performance of a range of streamline filtering algorithms, including SIFT, COMMIT, and LiFE. We find that all filtering methods successfully improve connectome accuracy, although filter performance depends on the complexity of the underlying white matter fiber architecture. Filtering algorithms can markedly improve tractography accuracy for simple tubular fiber bundles (F-measure deterministic- unfiltered: 0.49 and best filter: 0.72; F-measure probabilistic- unfiltered: 0.37 and best filter: 0.81), but for more complex brain-like fiber architectures, the improvement is modest (F-measure deterministic- unfiltered: 0.53 and best filter: 0.54; F-measure probabilistic- unfiltered: 0.46 and best filter: 0.50). Overall, filtering algorithms have the potential to improve the accuracy of connectome mapping pipelines, particularly for weighted connectomes and pipelines using probabilistic tractography methods. Our results highlight the need for further advances tractography and streamline filtering to improve the accuracy of connectome mapping.

Notes on fiber length measurements: A case study in the underbelly of open source neuroscience.

Being on the bleeding edge of research requires the use of new and regularly updated software. The result is the occasional and inevitable occurrence of bugs. In the following work we present a case study where a feature request introduced a bug in a neuroimaging software package, which had consequences for the quality of results in a published article. We discuss the process of diagnosis, rectification and analysis replication.

Investigating Tissue-Specific Abnormalities in Alzheimer's Disease with Multi-Shell Diffusion MRI.

BACKGROUND: Most studies using diffusion-weighted MRI (DW-MRI) in Alzheimer's disease (AD) have focused their analyses on white matter (WM) microstructural changes using the diffusion (kurtosis) tensor model. Although recent works have addressed some limitations of the tensor model, such as the representation of crossing fibers and partial volume effects with cerebrospinal fluid (CSF), the focus remains in modeling and analyzing the WM. OBJECTIVE: In this work, we present a brain analysis approach for DW-MRI that disentangles multiple tissue compartments as well as micro- and macroscopic effects to investigate differences between groups of subjects in the AD continuum and controls. METHODS: By means of the multi-tissue constrained spherical deconvolution of multi-shell DW-MRI, underlying brain tissue is modeled with a WM fiber orientation distribution function along with the contributions of gray matter (GM) and CSF to the diffusion signal. From this multi-tissue model, a set of measures capturing tissue diffusivity properties and morphology are extracted. Group differences were interrogated following fixel-, voxel-, and tensor-based morphometry approaches while including strong FWE control across multiple comparisons. RESULTS: Abnormalities related to AD stages were detected in WM tracts including the splenium, cingulum, longitudinal fasciculi, and corticospinal tract. Changes in tissue composition were identified, particularly in the medial temporal lobe and superior longitudinal fasciculus. CONCLUSION: This analysis framework constitutes a comprehensive approach allowing simultaneous macro and microscopic assessment of WM, GM, and CSF, from a single DW-MRI dataset.

Phytochemical Analysis of the Fruit Pulp Extracts from Annona crassiflora Mart. and Evaluation of Their Antioxidant and Antiproliferative Activities.

Annona crassiflora Mart., the marolo fruit of the Cerrado biome, is one of the most frequently consumed species from the Brazilian Midwest. This study aimed to evaluate the chemical composition and the antioxidant and cytotoxic properties of the fruit pulp of A. crassiflora collected at Chapada das Mesas, Maranhão, Brazil. The volatile concentrate was identified as mainly ethyl octanoate, ethyl hexanoate, and methyl octanoate. From the ethanol (LFP-E) and ethyl acetate (LFP-A) extracts were identified phenolic acids (p-coumaric, gallic, quinic, and ferulic), flavones and derivatives (apigenin, epicatechin, 2'-5-dimethoxyflavone, 3',7-dimethoxy-3-hydroxyflavone, kaempferol-3-O-glucoside and 3-O-rutinoside, quercetin-3-O-glucoside, procyanidin B2, and rutin), aporphine alkaloids (xylopine, stephagine, and romucosine), and acetogenin (annonacin). For the LFP-E and LFP-A extracts, the total phenolic compound values were 15.89 and 33.16 mg GAE/g, the flavonoid compound content values were 2.53 and 70.55 mg QE/g, the DPPH radical scavenging activity showed EC50 values of 182.54 and 57.80 µg/mL, and the ABTS radical activity showed TEAC values of 94.66 and 192.61 µM TE/g. The LFP-E extract showed significant cytotoxicity and cell selectivity for the U251-glioma strain, presenting a GI50 value of 21.34 µg/mL, which is close to doxorubicin (11.68 µg/mL), the standard chemotherapeutic drug. The marolo fruit seems to be a promising source for developing innovative and healthy products for the food industry.

Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review.

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.

Connectome spatial smoothing (CSS): Concepts, methods, and evaluation.

Structural connectomes are increasingly mapped at high spatial resolutions comprising many hundreds-if not thousands-of network nodes. However, high-resolution connectomes are particularly susceptible to image registration misalignment, tractography artifacts, and noise, all of which can lead to reductions in connectome accuracy and test-retest reliability. We investigate a network analogue of image smoothing to address these key challenges. Connectome Spatial Smoothing (CSS) involves jointly applying a carefully chosen smoothing kernel to the two endpoints of each tractography streamline, yielding a spatially smoothed connectivity matrix. We develop computationally efficient methods to perform CSS using a matrix congruence transformation and evaluate a range of different smoothing kernel choices on CSS performance. We find that smoothing substantially improves the identifiability, sensitivity, and test-retest reliability of high-resolution connectivity maps, though at a cost of increasing storage burden. For atlas-based connectomes (i.e. low-resolution connectivity maps), we show that CSS marginally improves the statistical power to detect associations between connectivity and cognitive performance, particularly for connectomes mapped using probabilistic tractography. CSS was also found to enable more reliable statistical inference compared to connectomes without any smoothing. We provide recommendations for optimal smoothing kernel parameters for connectomes mapped using both deterministic and probabilistic tractography. We conclude that spatial smoothing is particularly important for the reliability of high-resolution connectomes, but can also provide benefits at lower parcellation resolutions. We hope that our work enables computationally efficient integration of spatial smoothing into established structural connectome mapping pipelines.

Daratumumab utilization and cost analysis among patients with multiple myeloma in a US community oncology setting.

Background: The introduction of daratumumab into the treatment of multiple myeloma has improved outcomes in patients; however, community oncologists often dose more frequently than the US FDA-approved label. Materials and methods: Integra analyzed its database to elucidate daratumumab treatment patterns and the impact of increased utilization on the cost of care for multiple myeloma. Results: Following week 24, 671 (65%) of 1037 patients remained on daratumumab-containing regimens, with 330 patients continuing more frequent treatments than the expected once-every-4-weeks dosing described in the standard dosing schedule. Patients received an average of 14% more daratumumab doses than the FDA-approved label indicates, increasing the 1-year daratumumab costs by an estimated US$31,353. Conclusion: Daratumumab is utilized more frequently than the FDA-recommended dosing, leading to higher multiple myeloma treatment costs.

Lay abstract Since its first approval in 2015, daratumumab has become the backbone of many multiple myeloma treatment regimens. While its approval has improved outcomes in many patients who undergo treatment, it is expensive and has largely contributed to the increasing costs of care in multiple myeloma. In its most common treatment schedule, patients should transition from weekly and biweekly dosing to treatment once every 4 weeks. However, many providers maintain their patients on a more frequent dosing schedule, which increases Medicare 1-year costs by an estimated US$31,353 and may have unforeseen impacts on adverse events and patient outcomes.

Real-world estimate of the value of one metabolic equivalent in a population of patients planning major surgery.

BACKGROUND: One metabolic equivalent (MET) is equal to resting oxygen consumption. The average value for one MET in humans is widely quoted as 3.5 mL/kg/min. However, this value was derived from a single male participant at the end of the 19th century and has become canonical. Several small studies have identified varied estimates of one MET from widely varying populations. The ability of a patient to complete 4 MET (or 14 mL/kg/min) is considered an indicator of their fitness to proceed to surgery. AIMS: To define a typical value of one MET from a real-world patient population, as well as determine factors that influenced the value. METHODS: A database of cardiopulmonary exercise testing (CPET) was interrogated to find a total of 1847 adult patients who had undergone CPET testing in the previous 10 years. From this database, estimates of oxygen consumption (VO2 ) at rest and at the anaerobic threshold and several other variables were obtained. The influence of age, body mass index (BMI), sex and the use of beta-blockers was tested. RESULTS: The median resting VO2 at rest was 3.6 mL/kg/min (interquartile range (IQR): 3.0-4.2). Neither sex, age >65 years or the use of beta-blockers produced a significant difference in resting VO2 , while those with a BMI >25 kg/m2 had a significantly lower VO2 at rest (3.4 mL/kg/min vs 4.0 mL/kg/min; P < 0.001). CONCLUSIONS: The estimate of 3.6 mL/kg/min for resting VO2 presented here is consistent with the previous literature, despite this being the first large study of its kind. This estimate can be safely used for pre-operative risk stratification.

Characterisation of white matter asymmetries in the healthy human brain using diffusion MRI fixel-based analysis.

The diffusion tensor model for diffusion MRI has been used extensively to study asymmetry in the human brain white matter. However, given the limitations of the tensor model, the nature of any underlying asymmetries remains uncertain, particularly in crossing fibre regions. Here, we provide a more robust characterisation of human brain white matter asymmetries based on fibre-specific diffusion MRI metrics and a whole-brain data-driven approach. We used high-quality diffusion MRI data (n = 100) from the Human Connectome Project, the spherical deconvolution model for fibre orientation distribution estimation, and the Fixel-Based Analysis framework to utilise crossing fibre information in registration, data smoothing and statistical inference. We found many significant asymmetries, widespread throughout the brain white matter, with both left>right and right>left dominances observed in different pathways. No influences of sex, age, or handedness on asymmetry were found. We also report on the relative contributions of microstructural and morphological white matter properties toward the asymmetry findings. Our findings should provide important information to future studies focussing on how these asymmetries are affected by disease, development/ageing, or how they correlate to functional/cognitive measures.

ß-Barrel proteins tether the outer membrane in many Gram-negative bacteria.

Gram-negative bacteria have a cell envelope that comprises an outer membrane (OM), a peptidoglycan (PG) layer and an inner membrane (IM)1. The OM and PG are load-bearing, selectively permeable structures that are stabilized by cooperative interactions between IM and OM proteins2,3. In Escherichia coli, Braun's lipoprotein (Lpp) forms the only covalent tether between the OM and PG and is crucial for cell envelope stability4; however, most other Gram-negative bacteria lack Lpp so it has been assumed that alternative mechanisms of OM stabilization are present5. We used a glycoproteomic analysis of PG to show that ß-barrel OM proteins are covalently attached to PG in several Gram-negative species, including Coxiella burnetii, Agrobacterium tumefaciens and Legionella pneumophila. In C. burnetii, we found that four different types of covalent attachments occur between OM proteins and PG, with tethering of the ß-barrel OM protein BbpA becoming most abundant in the stationary phase and tethering of the lipoprotein LimB similar throughout the cell cycle. Using a genetic approach, we demonstrate that the cell cycle-dependent tethering of BbpA is partly dependent on a developmentally regulated L,D-transpeptidase (Ldt). We use our findings to propose a model of Gram-negative cell envelope stabilization that includes cell cycle control and an expanded role for Ldts in covalently attaching surface proteins to PG.

Adrenarcheal hormone-related development of white matter during late childhood.

The aim of the current study was to longitudinally examine how adrenarcheal hormones influence the development of white matter structure from age 8.5 to 10 years. Participants were 120 children (66 female; mean age 8.45 years at Time 1 and 9.97 years at Time 2) who completed two diffusion-weighted imaging scans 1.5 years apart. Morning saliva samples were taken at both assessment time points to measure levels of dehydroepiandrosterone (DHEA), its sulphate (DHEAS), and testosterone. Fixel-based analysis was performed to examine how changes in white matter fibre density (FD) and cross-section (FC) over time were associated with initial levels of hormones, and changes in hormone levels over time. Both FD and FC increased over time in a wide range of white matter tracts. Increases in testosterone over time were related to relatively weaker increases in FC in the inferior fronto-occipital fasciculus. Levels and change in DHEA and DHEAS were not related to FD or FC changes. The results demonstrated development of white matter fibre density and cross-section from age 8.5 to 10 years. Changes in adrenarcheal hormone levels showed limited, localized associations with development of white matter FC. Future research should examine the relevance of adrenarcheal hormone-related white matter development for cognitive functioning; as well as directly compare analysis techniques of white matter structure.

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

Head 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 = 294), 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.

Maturation and interhemispheric asymmetry in neurite density and orientation dispersion in early childhood.

BACKGROUND: The brain's white matter undergoes profound changes during early childhood, which are believed to underlie the rapid development of cognitive and behavioral skills during this period. Neurite density, and complexity of axonal projections, have been shown to change across the life span, though changes during early childhood are poorly characterized. Here, we utilize neurite orientation dispersion and density imaging (NODDI) to investigate maturational changes in tract-wise neurite density index (NDI) and orientation dispersion index (ODI) during early childhood. Additionally, we assess hemispheric asymmetry of tract-wise NDI and ODI values, and longitudinal changes. METHODS: Two sets of diffusion weighted images with different diffusion-weighting were collected from 125 typically developing children scanned at baseline (N = 125; age range = 4.14-7.29; F/M = 73/52), 6-month (N = 8; F/M = 8/0), and 12-month (N = 52; F/M = 39/13) timepoints. NODDI and template-based tractography using constrained spherical deconvolution were utilized to calculate NDI and ODI values for major white matter tracts. Mixed-effects models controlling for sex, handedness, and in-scanner head motion were utilized to assess developmental changes in tract-wise NDI and ODI. Additional mixed-effects models were used to assess interhemispheric differences in tract-wise NDI and ODI values and hemispheric asymmetries in tract-wise development. RESULTS: Maturational increases in NDI were seen in all major white matter tracts, though we did not observe the expected tract-wise pattern of maturational rates (e.g. fast commissural/projection and slow frontal/temporal tract change). ODI did not change significantly with age in any tract. We observed greater NDI and ODI values in the right as compared to the left hemisphere for most tracts, but no hemispheric asymmetry for rate of change with age. CONCLUSIONS: These findings suggest that neurite density, but not orientation dispersion, increases with age during early childhood. In relation to NDI growth trends reported in infancy and late-childhood, our results suggest that early childhood may be a transitional period for neurite density maturation wherein commissural/projection fibers are approaching maturity, maturation in long range association fibers is increasing, and changes in limbic/frontal fibers remain modest. Rightward asymmetry in NDI and ODI values, but no asymmetry in developmental changes, suggests that rightward asymmetry of neurite density and orientation dispersion is established prior to age 4.

A minimalistic model of bias, polarization and misinformation in social networks.

Online social networks provide users with unprecedented opportunities to engage with diverse opinions. At the same time, they enable confirmation bias on large scales by empowering individuals to self-select narratives they want to be exposed to. A precise understanding of such tradeoffs is still largely missing. We introduce a social learning model where most participants in a network update their beliefs unbiasedly based on new information, while a minority of participants reject information that is incongruent with their preexisting beliefs. This simple mechanism generates permanent opinion polarization and cascade dynamics, and accounts for the aforementioned tradeoff between confirmation bias and social connectivity through analytic results. We investigate the model's predictions empirically using US county-level data on the impact of Internet access on the formation of beliefs about global warming. We conclude by discussing policy implications of our model, highlighting the downsides of debunking and suggesting alternative strategies to contrast misinformation.

Phenolic Compounds and Metals in Some Edible Annonaceae Fruits.

The concentrations of 3,4-dihydroxybenzoic acid, caffeic acid, catechin, chlorogenic acid, epicatechin, gallic acid, p-coumaric acid, quercetin, rutin, ferulic acid, and the major metals in graviola (Annona muricata), atemoya (A. squamosa x A. cherimola), fruta do conde (A. squamosa), biribá (Rollinia mucosa), and the North American pawpaw (Asimina triloba) were determined by UPLC-ESI (-)-MS/MS. It enabled the identification and quantification of phenolic compounds. Catechin was only found in atemoya, at a concentration of 38.6 µg/g-dw. Only 3,4-dihydroxybenzoic acid was found in the fruit pulps of all five fruits analyzed. Atemoya stands out for not only having catechin but also for having much more epicatechin (239 µg/g-dw) than the other fruits. At the same time, graviola had more p-coumaric acid (62.6 µg/g-dw), and the North American pawpaw had more chlorogenic acid (48.1 µg/g-dw) than the other fruits. Metals were determined by ICP equipped with axially viewed plasma. All five fruit pulps had relatively high levels of potassium, with concentrations ranging from 7640 to 15,000 µg/g-dw, with pawpaw being the lowest and atemoya being the highest. The concentrations of other metals ranged from Ca 547 to 1110, Na 14.3 to 123, P 1210 to 1690, Mg 472 to 980, Mn 1.86 to 5.27, and Zn 5.55 to 7.32 µg/g-dw. All five fruits in the Annonaceae family that were analyzed in this study have several phenolic compounds in them and were good sources of potassium, calcium, phosphorus, and magnesium.