Biology subjects

Near, J.

Publications and source records attributed to Near, J..

12 recordsLinked to original sources

bioRxiv2026

The Canadian Pediatric Imaging Platform (C-PIP) Reference Sample: Neuroimaging Protocol and Cross-site Validation for Harmonized Multimodal Pediatric Imaging

Understanding how the human brain matures from infancy through adolescence is essential for identifying factors that influence health outcomes. Magnetic resonance imaging (MRI) provides powerful tools for characterizing structural, microstructural, functional, and metabolic aspects of brain development; however, many pediatric imaging studies are constrained by small sample sizes, limited geographic diversity, lack of longitudinal measurement, restricted age ranges, and heterogeneous acquisition protocols. While recent large-scale neuroimaging consortia have begun to address these challenges, such resources remain limited in the Canadian context, creating a critical gap. The Canadian Pediatric Imaging Platform (C-PIP) has developed a multisite neuroimaging framework across three of Canada's largest pediatric hospitals: Alberta Children's Hospital (Calgary), Centre Hospitalier Universitaire Sainte-Justine (Montreal), and the Hospital for Sick Children (Toronto). These three sites were united through a national initiative, leveraging high-performance MRI systems to accelerate Canadian neurodevelopmental research. In addition, C-PIP has implemented a centralized data sharing infrastructure to facilitate open science and collaborative research across institutions. Here, we describe the development and implementation of a multimodal MRI acquisition protocol designed to support multimodal longitudinal studies of typical and atypical brain development spanning infancy through adolescence. Within-site stability and cross-site stability of C-PIP core MRI sequences were evaluated using a travelling-participant study. The C-PIP MRI protocol establishes a harmonized, multisite imaging framework that supports large-scale investigations of pediatric brain development and disorders.

neuroscience↗

bioRxiv2025

MRS4Brain: a processing toolbox for preclinical MR spectroscopy and spectroscopic imaging data

ObjectivesMagnetic resonance spectroscopy is a non-invasive technique for probing metabolism and underpins advanced methods such as magnetic resonance spectroscopic imaging (MRSI) and diffusion-weighted spectroscopy (DWS). MRSI enables spatial mapping of metabolite distributions, offering insights into regional metabolic heterogeneity that single-voxel spectroscopy (SVS) cannot capture. However, MRSI produces large multidimensional datasets and requires complex processing pipelines, limiting reproducibility and accessibility. While human studies benefit from advanced processing tools, similar developments in preclinical research remain scarce, highlighting a demand for practical tools accessible to non-experts. MethodsTo address this need, we introduce the MRS4Brain Toolbox, a freely available MATLAB-based platform for preclinical spectroscopy, including MRSI, SVS, and DWS. ResultsThe toolbox integrates reconstruction, preprocessing, quantification, quality control, brain segmentation automatically overlaid on metabolite maps, modeling, and statistical analysis into unified workflows accessible via a graphical interface. ConclusionBy streamlining data processing and reducing technical barriers, MRS4Brain Toolbox promotes reproducibility, harmonization, and broader adoption of advanced spectroscopic techniques in preclinical studies, ultimately facilitating translational research.

neuroscience↗

bioRxiv2025

Benchmarking the Impact of Anatomical Segmentation on In Vivo Magnetic Resonance Spectroscopy

PurposeEstimation of metabolite concentrations in brain magnetic resonance spectroscopy (MRS) requires correction for differences in tissue water content, relaxation properties, and the proportions of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). Accurate knowledge of the relative proportions of these tissue classes within the volume of interest is therefore essential for reliable quantification. Commonly used brain segmentation tools differ in their algorithms, priors, and implementation, potentially introducing variability in MRS-derived concentration estimates. This study investigates the impact of segmentation software on estimated absolute concentrations. MethodsThree segmentation software tools, ANTs, FSL, and SPM, were evaluated. Segmentations were applied to an in vivo test-retest MR dataset to assess (1) differences in estimated tissue fractions, and (2) how these differences propagate into tissue-corrected metabolite concentrations. As an additional validity check and biological benchmark of segmentation performance, age-related associations with GM and total creatine (tCr) were examined. ResultsSignificant differences (p < 0.0001) were observed in tissue fraction estimates between segmentation tools, leading to differences in metabolite concentration estimates of up to 9% under identical acquisition and modeling conditions. Although the strength of the correlation varied between segmentation methods, no statistically significant differences were found. ConclusionThe choice of segmentation methodology contributed substantially to variability in MRS "absolute" metabolite concentration estimates. These results underscore the need for transparent segmentation reporting to ensure reproducibility and cross-study comparability in MRS research. Quantifying the segmentation-driven variability allows researchers to contextualize cross-study differences, helping determine whether observed effects are methodological or biologically meaningful.

neuroscience↗

bioRxiv2024

Metabolic analysis in intact human-derived cerebral organoids by high-resolution magic-angle spinning NMR spectroscopy

Human-derived cerebral organoids (COs) are an emerging model system for the study of human neural development and physiology. Here, we describe the assessment of metabolism in human-derived COs using high-resolution magic-angle spinning (HR-MAS) NMR spectroscopy. Metabolic changes during development are assessed by studying COs at various stages of maturity. Our results suggest that COs exhibit a metabolic profile similar to in vivo human brain metabolism, albeit with a few notable metabolic differences.

biophysics↗

bioRxiv2024

NEUROG2 regulates a human-specific neurodevelopmental gene regulatory program

Unique hallmarks of human neocortical development include slower rates of neurogenesis and the establishment of an extracellular matrix-rich, outer-subventricular zone that supports basal neural progenitor cell expansion. How gene regulatory networks have evolved to support these human-specific neurodevelopmental features is poorly understood. Mining single cell data from cerebral organoids and human fetal cortices, we found that NEUROG2 expression is enriched in basal neural progenitor cells. To identify and purify NEUROG2-expressing cells and trace their short-term lineage, we engineered two NEUROG2-mCherry knock-in human embryonic stem cell lines to produce cerebral organoids. Transcriptomic profiling of mCherry-high organoid cells revealed elevated expression of PPP1R17, associated with a fast-evolving human-accelerated regulatory region, oligodendrocyte precursor cell and extracellular matrix-associated gene transcripts. Conversely, only neurogenic gene transcripts were enriched in mCherry-high cortical cells from Neurog2:mCherry knock-in mice. Finally, we show that Neurog2 is sufficient to induce Ppp1r17, which slows human neural progenitor cell division, and Col13a1, an extracellular matrix gene, in P19 cells. NEUROG2 thus regulates a human neurodevelopmental gene regulatory program implicated in supporting a pro-proliferative basal progenitor cell niche and tempering the neurogenic pace. SUMMARY STATEMENTTranscriptomic analyses of NEUROG2-mCherry knock-in human embryonic stem cell-derived cerebral organoids reveal a link between NEUROG2 and extracellular matrix remodeling during human cortical development.

developmental biology↗

bioRxiv2022

MRSCloud: a Cloud-based MR Spectroscopy Tool for Basis Set Simulation

BackgroundAccurate quantification of in vivo proton magnetic resonance spectra involves modeling with a linear combination of known metabolite basis functions. Basis sets can be generated by numerical simulation using the quantum mechanical density-matrix formalism. Accurate simulations for a basis set require correct sequence timings, and pulse shapes and durations. PurposeTo present a cloud-based spectral simulation tool MRSCloud. It allows community users of MRS to simulate a vendor- and sequence-specific basis set online in a convenient and timeefficient manner. This tool can simulate basis sets for 3 major MR scanner vendors (GE, Philips, Siemens), including conventional acquisitions and spectral editing schemes (MEGA, HERMES, HERCULES) with PRESS and semi-LASER localization. Study TypeProspective. SpecimenN/A Field Strength/SequenceSimulations of 3T basis sets for conventional and spectral-editing sequences (MEGA, HERMES, HERCULES) with PRESS and sLASER localizations. AssessmentSimulated metabolite basis functions generated by MRSCloud are compared to those generated by FID-A and MARSS, and a phantom-acquired basis-set from LCModel. Statistical TestsIntraclass correlation coefficients (ICC) were calculated to measure the agreement between individual metabolite basis functions generated using different packages. Statistical analysis was performed using R in RStudio. ResultsSimulation time for a full basis set is approximately 1 hour. ICCs between MRSCloud and FID-A were at least 0.98 and ICCs between MRSCloud and MARSS were at least 0.96. ICCs between simulated MRSCloud basis spectra and acquired LCModel basis spectra were lowest for Gln at 0.68 and highest for NAA at 0.96. Data ConclusionSubstantial reductions in runtime have been achieved by implementing the 1D projection method, coherence-order filtering, and pre-calculation of propagators. High ICC values indicated that the accelerating features are running correctly and produce comparable and accurate basis sets. The generated basis set has been successfully used with LCModel.

bioengineering↗

bioRxiv2021

Comparison of seven modelling algorithms for GABA-edited 1H-MRS

Edited MRS sequences are widely used for studying GABA in the human brain. Several algorithms are available for modelling these data, deriving metabolite concentration estimates through peak fitting or a linear combination of basis spectra. The present study compares seven such algorithms, using data obtained in a large multi-site study. GABA-edited (GABA+, TE = 68 ms MEGA-PRESS) data from 222 subjects at 20 sites were processed via a standardised pipeline, before modelling with FSL-MRS, Gannet, AMARES, QUEST, LCModel, Osprey and Tarquin, using standardised vendor-specific basis sets (for GE, Philips and Siemens) where appropriate. After referencing metabolite estimates (to water or creatine), systematic differences in scale were observed between datasets acquired on different vendors hardware, presenting across algorithms. Scale differences across algorithms were also observed. Using the correlation between metabolite estimates and voxel tissue fraction as a benchmark, most algorithms were found to be similarly effective in detecting differences in GABA+. An inter-class correlation across all algorithms showed single-rater consistency for GABA+ estimates of around 0.38, indicating moderate agreement. Upon inclusion of a basis set component explicitly modelling the macromolecule signal underlying the observed 3.0 ppm GABA peaks, single-rater consistency improved to 0.44. Correlation between discrete pairs of algorithms varied, and was concerningly weak in some cases. Our findings highlight the need for consensus on appropriate modelling parameters across different algorithms, and for detailed reporting of the parameters adopted in individual studies to ensure reproducibility and meaningful comparison of outcomes between different studies. HighlightsO_LIGABA-edited MRS data from 222 healthy adults across 20 research sites were analyzed C_LIO_LIData were modelled using seven different algorithms, yielding GABA+ and Glx estimates C_LIO_LIModerate agreement was seen across all the tested algorithms C_LIO_LIAdding a component to represent co-edited macromolecule signals improved concordance C_LIO_LIBaseline modelling emerged as major factor differentiating outcomes C_LI

neuroscience↗

bioRxiv2021

Longitudinal characterization of neuroanatomical changes in the Fischer 344 rat brain during normal aging and between sexes

Animal models are widely used to study the pathophysiology of disease and to evaluate the efficacy of novel interventions, crucial steps towards improving disease outcomes in humans. The Fischer 344 (F344) wildtype rat is a common experimental background strain for transgenic models of disease and is also one of the most frequently used models in aging research. Despite frequency of use, characterization of neuroanatomical change with age has not been performed in the F344 rat. To this end, we present a comprehensive longitudinal examination of morphometric change in 73 brain regions and at a voxel-wise level during normative aging in a mixed-sex cohort of F344 rats. We identified age- and sex-related changes in regions such as the cortex, hippocampus, cingulum, caudoputamen, and nucleus accumbens, which are implicated in memory and motor control circuits frequently affected by aging and neurodegenerative disease. These findings provide a baseline for neuroanatomical changes associated with aging in male and female F344 rats, to which data from transgenic models or other background strains can be compared. HIGHLIGHTSO_LIIn vivo magnetic resonance imaging reveals altered neuroanatomy in aging Fischer rats C_LIO_LILinear and curvilinear age effects exist in both grey and white matter structures C_LIO_LISex differences are primarily seen in grey matter structures C_LIO_LIThis study clarifies normal aging trajectories across 73 brain regions in both sexes C_LIO_LIImproved understanding of normal aging will inform future pathological aging studies C_LI

neuroscience↗

bioRxiv2020

MRS-measured Glutamate versus GABA reflects excitatory versus inhibitory neural activities in awake mice

To assess if magnetic resonance spectroscopy (MRS)-measured Glutamate (Glu) and GABA reflect excitatory and inhibitory neural activities, respectively, we conducted MRS measurements along with two-photon mesoscopic imaging of calcium signals in excitatory and inhibitory neurons of living, unanesthetized mice. For monitoring stimulus-driven activations of a brain region, MRS signals and mesoscopic neural activities were measured during two consecutive sessions of 15-min prolonged sensory stimulations. In the first session, putative excitatory neuronal activities were increased, while inhibitory neuronal activities remained at the baseline level. In the second half, while excitatory neuronal activities remained elevated, inhibitory neuronal activities were significantly enhanced. We also assessed regional neurochemical and functional statuses related to spontaneous neural firing by measuring MRS signals and neuronal activities in a mouse model of Dravet syndrome under a resting condition. Mesoscopic assessments showed that activities of inhibitory neurons in the cortex were diminished relative to wild-type mice in contrast to spared activities of excitatory neurons. Consistent with these observations, the Dravet model exhibited lower concentrations of GABA than wild-type controls. Collectively, the current investigations demonstrate that the MRS-measured Glu and GABA can reflect spontaneous and stimulated activities of neurons producing and releasing these neurotransmitters in an awake condition.

neuroscience↗

bioRxiv2020

The Impact of the Siemens Trio to Prisma Upgrade and Volumetric Navigators on MRI Indices: A Reliability Study with Implications for Longitudinal Study Designs

Many magnetic resonance imaging (MRI) indices are being studied longitudinally to explore topics such as biomarker detection and clinical staging. A pertinent concern to longitudinal work is MRI scanner upgrades. When upgrades occur during the course of a longitudinal MRI neuroimaging investigation, there may be an impact on the compatibility of pre- and post-upgrade measures. Similarly, subject motion is another issue that may be detrimental to longitudinal MRI work; however, embedding volumetric navigators (vNavs) within acquisition sequences has emerged as a technique that allows for prospective motion correction. Our research group recently implemented an upgrade from a Siemens MAGNETOM 3T Trio system to a Siemens MAGNETOM 3T Prisma Fit system. The goals of the current work were to: 1) investigate the impact of this upgrade on commonly used structural imaging measures and proton magnetic resonance spectroscopy indices ("Prisma Upgrade protocol") and 2) examine structural imaging measures in a sequence with vNavs alongside a standard acquisition sequence ("vNav protocol"). In both protocols, while high reliability was observed for most of the investigated MRI outputs, suboptimal reliability was observed for certain indices. Across the scanner upgrade, increases in frontal, temporal, and cingulate cortical thickness (CT) and thalamus volume, along with decreases in parietal CT, amygdala, globus pallidus, hippocampus, and striatum volumes were observed across the Prisma upgrade, and were linked to increases in signal-to-noise ratios. No significant impact of the upgrade was found in 1H-MRS analyses. Further, CT estimates were found to be larger in MPRAGE acquisitions compared to vNav-MPRAGE acquisitions mainly within temporal areas, while the opposite was found mostly in parietal brain regions. The results from this work should be considered in longitudinal study designs and comparable prospective motion correction investigations are warranted in cases of marked head movement.

neuroscience↗

bioRxiv2020

Longitudinal Quantification of Metabolites and Macromolecules Reveals Age- and Sex-Related Changes in the Healthy Fischer 344 Rat Brain

Normal aging is associated with numerous biological changes including altered brain metabolism and tissue chemistry. In vivo characterization of the neurochemical profile during aging is possible using magnetic resonance spectroscopy, a powerful non-invasive technique capable of quantifying brain metabolites involved in physiological processes that become impaired with age. A prominent macromolecular signal underlies those of brain metabolites and is particularly visible at high fields; parameterization of this signal into components improves quantification and expands the number of biomarkers comprising the neurochemical profile. The present study reports, for the first time, the simultaneous absolute quantification of brain metabolites and individual macromolecules in aging male and female Fischer 344 rats, measured longitudinally using proton magnetic resonance spectroscopy at 7T. We identified age- and sex-related changes in neurochemistry, with prominent differences in metabolites implicated in anaerobic energy metabolism, antioxidant capacity, and neuroprotection, as well as numerous macromolecule changes. These findings contribute to our understanding of the neurobiological processes associated with healthy aging, critical for the proper identification and management of pathological aging trajectories. HIGHLIGHTS[->] Magnetic resonance spectroscopy reveals altered chemistry in the aging rat brain [->]Age- and sex-dependent differences in metabolites and macromolecules are present [->]Metabolites and macromolecules are markers of processes involved in healthy aging [->]This study clarifies normative progression of brain chemistry and metabolism in vivo [->]Improved understanding will inform future studies in pathological aging

neuroscience↗

bioRxiv2019

An MRI-Derived Neuroanatomical Atlas of the Fischer 344 Rat Brain for Automated Anatomical Segmentation

This paper reports the development of a high-resolution 3-D MRI atlas of the Fischer 344 adult rat brain. The atlas is a 60 m isotropic image volume composed of 256 coronal slices with 71 manually delineated structures and substructures. The atlas was developed using Pydpiper image registration pipeline to create an average brain image of 41 four-month-old male and female Fischer 344 rats. Slices in the average brain image were then manually segmented, individually and bilaterally, on the basis of image contrast in conjunction with Paxinos and Watsons (2007) stereotaxic rat brain atlas. Summary statistics (mean and standard deviation of regional volumes) are reported for each brain region across the sample used to generate the atlas, and a statistical comparison of a chosen subset of regional brain volumes between male and female rats is presented. On average, the coefficient of variation of regional brain volumes across all rats in our sample was 4%, with no individual brain region having a coefficient of variation greater than 13%. A full description of methods used, as well as the atlas, the template that the atlas was derived from, and a masking file, can be found at Zenodo at https://doi.org/10.5281/zenodo.3555556. To our knowledge, this is the first MRI atlas created using Fischer 344 rats and will thus provide an appropriate neuroanatomical model for researchers working with this strain. HIGHLIGHTS Open-access high-resolution anatomical MRI template for Fischer 344 rat brain. Segmented atlas of 71 regions for use as a tool in Fischer 344 preclinical research paradigms. Analysis of population variability of regional brain volumes. Analysis of sex-differences in regional brain volumes KEYWORDS: Fischer 344; Structural MRI; Segmentation; Rat brain template; Digital brain atlas; Sex-differences;

neuroscience↗