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1. Population Atlas Analysis of Emerging Brain Structural Connections in the Human Fetus

   https://doi.org/10.1002/jmri.29057  

   Calixto, Camilo; Machado‐Rivas, Fedel; Karimi, Davood; Velasco‐Annis, Clemente; Cortes‐Albornoz, Maria Camila; Afacan, Onur; Warfield, Simon K.; Gholipour, Ali; Jaimes, Camilo (October 2023, Journal of Magnetic Resonance Imaging)

   BackgroundA lack of in utero imaging data hampers our understanding of the connections in the human fetal brain. Generalizing observations from postmortem subjects and premature newborns is inaccurate due to technical and biological differences. PurposeTo evaluate changes in fetal brain structural connectivity between 23 and 35 weeks postconceptional age using a spatiotemporal atlas of diffusion tensor imaging (DTI). Study TypeRetrospective. PopulationPublicly available diffusion atlases, based on 60 healthy women (age 18–45 years) with normal prenatal care, from 23 and 35 weeks of gestation. Field Strength/Sequence3.0 Tesla/DTI acquired with diffusion‐weighted echo planar imaging (EPI). AssessmentWe performed whole‐brain fiber tractography from DTI images. The cortical plate of each diffusion atlas was segmented and parcellated into 78 regions derived from the Edinburgh Neonatal Atlas (ENA33). Connectivity matrices were computed, representing normalized fiber connections between nodes. We examined the relationship between global efficiency (GE), local efficiency (LE), small‐worldness (SW), nodal efficiency (NE), and betweenness centrality (BC) with gestational age (GA) and with laterality. Statistical TestsLinear regression was used to analyze changes in GE, LE, NE, and BC throughout gestation, and to assess changes in laterality. Thet‐tests were used to assess SW.P‐values were corrected using Holm‐Bonferroni method. A correctedP‐value <0.05 was considered statistically significant. ResultsNetwork analysis revealed a significant weekly increase in GE (5.83%/week, 95% CI 4.32–7.37), LE (5.43%/week, 95% CI 3.63–7.25), and presence of SW across GA. No significant hemisphere differences were found in GE (P = 0.971) or LE (P = 0.458). Increasing GA was significantly associated with increasing NE in 41 nodes, increasing BC in 3 nodes, and decreasing BC in 2 nodes. Data ConclusionExtensive network development and refinement occur in the second and third trimesters, marked by a rapid increase in global integration and local segregation. Level of Evidence3 Technical EfficacyStage 2 

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2. Direct Quantification of Intervertebral Disc Water Content Using MRI

   https://doi.org/10.1002/jmri.27171  

   Yang, Bo; Wendland, Michael F.; O'Connell, Grace D. (April 2020, Journal of Magnetic Resonance Imaging)

   BackgroundWater content is a key parameter for simulating tissue swelling and nutrient diffusion. Accurately measuring water content throughout the intervertebral disc (NP = nucleus pulposus; AF = annulus fibrosus) is important for developing patient‐specific models. Water content is measured using destructive techniques, Quantitative MRI has been used to estimate water content and detect early degeneration, but it is dependent on scan parameters, concentration of free water molecules, and fiber architecture. PurposeTo directly measure disc‐tissue water content using quantitative MRI and compare MRI‐based measurements with biochemical assays, and to quantify changes in disc geometry due to compression. Study TypeBasic science, controlled. SpecimenTwenty bone‐disc‐bone motion segments from skeletally mature bovines. Field Strength/Sequence7T/3D fast low angle shot (FLASH) pulse sequence and a T₂rapid imaging with refocused echoes (RARE) sequence. AssessmentDisc volumes, NP and AF volumetric water content, and T₂relaxation times were measured through MRI; NP and AF tissue gravimetric water content, mass density, and glycosaminoglycan content were measured through a biochemical assay. Statistical TestsCorrelations between MRI‐based measurement and biochemical composition were evaluated using Pearson's linear regression. ResultsMechanical dehydration resulted in a decrease in disc volume by up to 20% and a decrease in disc height by up to 35%. Direct water content measurements for the NP was achieved by normalizing MRI‐based spin density by NP mass density (1.10 ± 0.03 g/cm³). However, the same approach underestimated water content in the AF by ~10%, which may be due to a higher concentration of collagen fibers and bound water molecules. Data ConclusionSpin density or spin density normalized by mass density to estimate NP and AF water content was more accurate than correlations between water content and relaxation times. Mechanical dehydration decreased disc volume and disc height, and increased maximum cross‐sectional area. Level of Evidence  Technical Efficacy Stage  J. Magn. Reson. Imaging 2020;52:1152–1162. 

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3. RCSB Protein Data Bank 1D3D module: displaying positional features on macromolecular assemblies

   https://doi.org/10.1093/bioinformatics/btac317  

   Segura, Joan; Rose, Yana; Bittrich, Sebastian; Burley, Stephen K.; Duarte, Jose M.; Cowen, ed., Lenore (May 2022, Bioinformatics)

   Abstract MotivationMapping positional features from one-dimensional (1D) sequences onto three-dimensional (3D) structures of biological macromolecules is a powerful tool to show geometric patterns of biochemical annotations and provide a better understanding of the mechanisms underpinning protein and nucleic acid function at the atomic level. ResultsWe present a new library designed to display fully customizable interactive views between 1D positional features of protein and/or nucleic acid sequences and their 3D structures as isolated chains or components of macromolecular assemblies. Availability and implementationhttps://github.com/rcsb/rcsb-saguaro-3d. Supplementary informationSupplementary data are available at Bioinformatics online. 

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4. Independent Component and Graph Theory Analyses Reveal Normalized Brain Networks on Resting‐State Functional MRI After Working Memory Training in People With HIV

   https://doi.org/10.1002/jmri.28439  

   Jia, Chunying; Long, Qunfang; Ernst, Thomas; Shang, Yuanqi; Chang, Linda; Adali, Tülay (September 2022, Journal of Magnetic Resonance Imaging)

   BackgroundCognitive training may partially reverse cognitive deficits in people with HIV (PWH). Previous functional MRI (fMRI) studies demonstrate that working memory training (WMT) alters brain activity during working memory tasks, but its effects on resting brain network organization remain unknown. PurposeTo test whether WMT affects PWH brain functional connectivity in resting‐state fMRI (rsfMRI). Study TypeProspective. PopulationA total of 53 PWH (ages 50.7 ± 1.5 years, two women) and 53HIV‐seronegative controls (SN, ages 49.5 ± 1.6 years, six women). Field Strength/SequenceAxial single‐shot gradient‐echo echo‐planar imaging at 3.0 T was performed at baseline (TL1), at 1‐month (TL2), and at 6‐months (TL3), after WMT. AssessmentAll participants had rsfMRI and clinical assessments (including neuropsychological tests) at TL1 before randomization to Cogmed WMT (adaptive training,n = 58: 28 PWH, 30 SN; nonadaptive training,n = 48: 25 PWH, 23 SN), 25 sessions over 5–8 weeks. All assessments were repeated at TL2 and at TL3. The functional connectivity estimated by independent component analysis (ICA) or graph theory (GT) metrics (eigenvector centrality, etc.) for different link densities (LDs) were compared between PWH and SN groups at TL1 and TL2. Statistical TestsTwo‐way analyses of variance (ANOVA) on GT metrics and two‐samplet‐tests on FC or GT metrics were performed. Cognitive (eg memory) measures were correlated with eigenvector centrality (eCent) using Pearson's correlations. The significance level was set atP < 0.05 after false discovery rate correction. ResultsThe ventral default mode network (vDMN) eCent differed between PWH and SN groups at TL1 but not at TL2 (P = 0.28). In PWH, vDMN eCent changes significantly correlated with changes in the memory ability in PWH (r = −0.62 at LD = 50%) and vDMN eCent before training significantly correlated with memory performance changes (r = 0.53 at LD = 50%). Data ConclusionICA and GT analyses showed that adaptive WMT normalized graph properties of the vDMN in PWH. Evidence Level1 Technical Efficacy1 

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5. SNAPSHOT USA 2019–2023: The First Five Years of Data From a Coordinated Camera Trap Survey of the United States

   https://doi.org/10.1111/geb.13941  

   Rooney, Brigit; Kays, Roland; Cove, Michael V; Jensen, Alex; Goldstein, Benjamin R; Pate, Christopher; Castiblanco, Paula; Abell, Maggie E; Adley, Jessie; Agenbroad, Briana; et al (January 2025, Global Ecology and Biogeography)

   ABSTRACT MotivationSNAPSHOT USA is an annual, multicontributor camera trap survey of mammals across the United States. The growing SNAPSHOT USA dataset is intended for tracking the spatial and temporal responses of mammal populations to changes in land use, land cover and climate. These data will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, as well as the impacts of species interactions on daily activity patterns. Main Types of Variables ContainedSNAPSHOT USA 2019–2023 contains 987,979 records of camera trap image sequence data and 9694 records of camera trap deployment metadata. Spatial Location and GrainData were collected across the United States of America in all 50 states, 12 ecoregions and many ecosystems. Time Period and GrainData were collected between 1st August and 29th December each year from 2019 to 2023. Major Taxa and Level of MeasurementThe dataset includes a wide range of taxa but is primarily focused on medium to large mammals. Software FormatSNAPSHOT USA 2019–2023 comprises two .csv files. The original data can be found within the SNAPSHOT USA Initiative in the Wildlife Insights platform. 

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