Author Identification : One view on the infrastructure building in Open Access environment

DRF国際会議2009：オープンアクセスリポジトリの現在と未来:世界とアジアへの視点から＝International Conference 2009：Open access repositories now and in the future : from the global and Asia-Pacific points of view(Dec.3-4,2009, Tokyo)のポスターセッション用資

Diffusion tensor model links to neurite orientation dispersion and density imaging at high b-value in cerebral cortical gray matter

Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are widely used models to infer microstructural features in the brain from diffusion-weighted MRI. Several studies have recently applied both models to increase sensitivity to biological changes, however, it remains uncertain how these measures are associated. Here we show that cortical distributions of DTI and NODDI are associated depending on the choice of b-value, a factor reflecting strength of diffusion weighting gradient. We analyzed a combination of high, intermediate and low b-value data of multi-shell diffusion-weighted MRI (dMRI) in healthy 456 subjects of the Human Connectome Project using NODDI, DTI and a mathematical conversion from DTI to NODDI. Cortical distributions of DTI and DTI-derived NODDI metrics were remarkably associated with those in NODDI, particularly when applied highly diffusion-weighted data (b-value = 3000 sec/mm2). This was supported by simulation analysis, which revealed that DTI-derived parameters with lower b-value datasets suffered from errors due to heterogeneity of cerebrospinal fluid fraction and partial volume. These findings suggest that high b-value DTI redundantly parallels with NODDI-based cortical neurite measures, but the conventional low b-value DTI is hard to reasonably characterize cortical microarchitecture

Towards HCP-Style macaque connectomes: 24-Channel 3T multi-array coil, MRI sequences and preprocessing

© 2020 The Author(s) Macaque monkeys are an important animal model where invasive investigations can lead to a better understanding of the cortical organization of primates including humans. However, the tools and methods for noninvasive image acquisition (e.g. MRI RF coils and pulse sequence protocols) and image data preprocessing have lagged behind those developed for humans. To resolve the structural and functional characteristics of the smaller macaque brain, high spatial, temporal, and angular resolutions combined with high signal-to-noise ratio are required to ensure good image quality. To address these challenges, we developed a macaque 24-channel receive coil for 3-T MRI with parallel imaging capabilities. This coil enables adaptation of the Human Connectome Project (HCP) image acquisition protocols to the in-vivo macaque brain. In addition, we adapted HCP preprocessing methods to the macaque brain, including spatial minimal preprocessing of structural, functional MRI (fMRI), and diffusion MRI (dMRI). The coil provides the necessary high signal-to-noise ratio and high efficiency in data acquisition, allowing four- and five-fold accelerations for dMRI and fMRI. Automated FreeSurfer segmentation of cortex, reconstruction of cortical surface, removal of artefacts and nuisance signals in fMRI, and distortion correction of dMRI all performed well, and the overall quality of basic neurobiological measures was comparable with those for the HCP. Analyses of functional connectivity in fMRI revealed high sensitivity as compared with those from publicly shared datasets. Tractography-based connectivity estimates correlated with tracer connectivity similarly to that achieved using ex-vivo dMRI. The resulting HCP-style in vivo macaque MRI data show considerable promise for analyzing cortical architecture and functional and structural connectivity using advanced methods that have previously only been available in studies of the human brain

Development of nuclear DNA markers to characterize genetically diverse groups of Misgurnus anguillicaudatus and its closely related species

Repetitive DNA sequences, ManDra and ManBgl, were isolated from the DraI and BglII digests of the genomic DNA of Misgurnus anguillicaudatus, respectively. A primer set of ManDra distinguished two genetically different groups (A and B) of M. anguillicaudatus by specific electrophoretograms. A primer set of ManBgl amplified the DNA of M. anguillicaudatus and M. mizolepis. The individuals of M. anguillicaudatus were divided into two groups depending on the fragment sizes, in which the groups A and B (B-1 and B-2) showed 400 and 460 bp, respectively. M. mizolepis was distinguished by a different pattern (400-, 460-, and 510-bp fragments). PCR-RFLP analyses of recombination activating gene 1 gave a clear difference between A or B-2 (443-bp fragment) and B-1 groups (296- and 147-bp fragments). Clonal lineages and hybrids between B-1 and B-2 groups could be identified by appearance of three fragments (443, 296, and 147 bp). The combined analyses using the above three nuclear markers discriminated among nuclear genomes of genetic groups (A, B-1 and B-2) of M. anguillicaudatus and M. mizolepis. In several localities, natural hybridizations between the group B-1 and B-2 loaches and introgressions of clonal mitochondrial genomes into the group B-1 loaches were detected

Intravoxel incoherent motion (IVIM) and non-Gaussian diffusion MRI of the lactating breast

Purpose: To investigate the effect of breastfeeding on IVIM and non-Gaussian diffusion MRI in the breast. Materials and methods: An IRB approved prospective study enrolled seventeen volunteers (12 in lactation and 5 with post-weaning, range 31–43 years; mean 35.4 years). IVIM (fIVIM and D*) and non-Gaussian diffusion (ADC0 and K) parameters using 16 b values, plus synthetic apparent diffusion coefficients (sADCs) from 2 key b values (b = 200 and 1500 s/mm2) were calculated using regions of interest. ADC0 maps of the whole breast were generated and their contrast patterns were evaluated by two independent readers using retroareolar and segmental semi-quantitative scores. To compare the diffusion and IVIM parameters, Wilcoxon signed rank tests were used between pre- and post-breastfeeding and Mann-Whitney tests were used between post-weaning and pre- or post-breastfeeding. Results: ADC0 and sADC values significantly decreased post-breastfeeding (1.90 vs. 1.72 × 10−3 mm2/s, P < 0.001 and 1.39 vs. 1.25 × 10−3 mm2/s, P < 0.001) while K values significantly increased (0.33 vs. 0.44, P < 0.05). fIVIM values significantly increased after breastfeeding (1.97 vs. 2.97%, P < 0.01). No significant difference was found in D* values. There was significant heterogeneity in ADC0 maps post-breastfeeding, both in retroareolar and segmental scores (P < 0.0001 and =0.0001). Conclusion: IVIM and non-Gaussian diffusion parameters significantly changed between pre- and post-breastfeeding status, and care needs to be taken in interpreting diffusion-weighted imaging (DWI) data in lactating breasts. Keywords: Diffusion-weighted imaging, Intravoxel incoherent motion, Kurtosis, Lactation, Breas