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2. Author Correction: BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Author

Manubens-Gil, Linus, Zhou, Zhi, Chen, Hanbo, Ramanathan, Arvind, Liu, Xiaoxiao, Liu, Yufeng, Bria, Alessandro, Gillette, Todd, Ruan, Zongcai, Yang, Jian, Radojević, Miroslav, Zhao, Ting, Cheng, Li, Qu, Lei, Liu, Siqi, Bouchard, Kristofer E., Gu, Lin, Cai, Weidong, Ji, Shuiwang, Roysam, Badrinath, Wang, Ching-Wei, Yu, Hongchuan, Sironi, Amos, Iascone, Daniel Maxim, Zhou, Jie, Bas, Erhan, Conde-Sousa, Eduardo, Aguiar, Paulo, Li, Xiang, Li, Yujie, Nanda, Sumit, Wang, Yuan, Muresan, Leila, Fua, Pascal, Ye, Bing, He, Hai-yan, Staiger, Jochen F., Peter, Manuel, Cox, Daniel N., Simonneau, Michel, Oberlaender, Marcel, Jefferis, Gregory, Ito, Kei, Gonzalez-Bellido, Paloma, Kim, Jinhyun, Rubel, Edwin, Cline, Hollis T., Zeng, Hongkui, Nern, Aljoscha, Chiang, Ann-Shyn, Yao, Jianhua, Roskams, Jane, Livesey, Rick, Stevens, Janine, Liu, Tianming, Dang, Chinh, Guo, Yike, Zhong, Ning, Tourassi, Georgia, Hill, Sean, Hawrylycz, Michael, Koch, Christof, Meijering, Erik, Ascoli, Giorgio A., and Peng, Hanchuan

Published
2024
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3. PROJECT MINDSCOPE

Author

Koch, Christof, primary, Reid, Clay, additional, Zeng, Hongkui, additional, Mihalas, Stefan, additional, Hawrylycz, Mike, additional, Philips, John, additional, Dang, Chinh, additional, and Jones, Allan, additional

Published
2024
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5. BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Author

Manubens-Gil, Linus, Zhou, Zhi, Chen, Hanbo, Ramanathan, Arvind, Liu, Xiaoxiao, Liu, Yufeng, Bria, Alessandro, Gillette, Todd, Ruan, Zongcai, Yang, Jian, Radojević, Miroslav, Zhao, Ting, Cheng, Li, Qu, Lei, Liu, Siqi, Bouchard, Kristofer E, Gu, Lin, Cai, Weidong, Ji, Shuiwang, Roysam, Badrinath, Wang, Ching-Wei, Yu, Hongchuan, Sironi, Amos, Iascone, Daniel Maxim, Zhou, Jie, Bas, Erhan, Conde-Sousa, Eduardo, Aguiar, Paulo, Li, Xiang, Li, Yujie, Nanda, Sumit, Wang, Yuan, Muresan, Leila, Fua, Pascal, Ye, Bing, He, Hai-yan, Staiger, Jochen F, Peter, Manuel, Cox, Daniel N, Simonneau, Michel, Oberlaender, Marcel, Jefferis, Gregory, Ito, Kei, Gonzalez-Bellido, Paloma, Kim, Jinhyun, Rubel, Edwin, Cline, Hollis T, Zeng, Hongkui, Nern, Aljoscha, Chiang, Ann-Shyn, Yao, Jianhua, Roskams, Jane, Livesey, Rick, Stevens, Janine, Liu, Tianming, Dang, Chinh, Guo, Yike, Zhong, Ning, Tourassi, Georgia, Hill, Sean, Hawrylycz, Michael, Koch, Christof, Meijering, Erik, Ascoli, Giorgio A, and Peng, Hanchuan

Subjects
Biological Sciences, Bioengineering, Networking and Information Technology R&D (NITRD), Neurosciences, Benchmarking, Microscopy, Imaging, Three-Dimensional, Neurons, Algorithms, Technology, Medical and Health Sciences, Developmental Biology, Biological sciences
Abstract

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

Published
2023

14. Integrative functional genomic analysis of human brain development and neuropsychiatric risks

Author

Li, Mingfeng, Santpere, Gabriel, Imamura Kawasawa, Yuka, Evgrafov, Oleg V, Gulden, Forrest O, Pochareddy, Sirisha, Sunkin, Susan M, Li, Zhen, Shin, Yurae, Zhu, Ying, Sousa, André MM, Werling, Donna M, Kitchen, Robert R, Kang, Hyo Jung, Pletikos, Mihovil, Choi, Jinmyung, Muchnik, Sydney, Xu, Xuming, Wang, Daifeng, Lorente-Galdos, Belen, Liu, Shuang, Giusti-Rodríguez, Paola, Won, Hyejung, de Leeuw, Christiaan A, Pardiñas, Antonio F, Hu, Ming, Jin, Fulai, Li, Yun, Owen, Michael J, O’Donovan, Michael C, Walters, James TR, Posthuma, Danielle, Reimers, Mark A, Levitt, Pat, Weinberger, Daniel R, Hyde, Thomas M, Kleinman, Joel E, Geschwind, Daniel H, Hawrylycz, Michael J, State, Matthew W, Sanders, Stephan J, Sullivan, Patrick F, Gerstein, Mark B, Lein, Ed S, Knowles, James A, Sestan, Nenad, Willsey, A Jeremy, Oldre, Aaron, Szafer, Aaron, Camarena, Adrian, Cherskov, Adriana, Charney, Alexander W, Abyzov, Alexej, Kozlenkov, Alexey, Safi, Alexias, Jones, Allan R, Ashley-Koch, Allison E, Ebbert, Amanda, Price, Amanda J, Sekijima, Amanda, Kefi, Amira, Bernard, Amy, Amiri, Anahita, Sboner, Andrea, Clark, Andrew, Jaffe, Andrew E, Tebbenkamp, Andrew TN, Sodt, Andy J, Guillozet-Bongaarts, Angie L, Nairn, Angus C, Carey, Anita, Huttner, Anita, Chervenak, Ann, Szekely, Anna, Shieh, Annie W, Harmanci, Arif, Lipska, Barbara K, Carlyle, Becky C, Gregor, Ben W, Kassim, Bibi S, Sheppard, Brooke, Bichsel, Candace, Hahn, Chang-Gyu, Lee, Chang-Kyu, Chen, Chao, Kuan, Chihchau L, Dang, Chinh, Lau, Chris, Cuhaciyan, Christine, Armoskus, Christoper, Mason, Christopher E, Liu, Chunyu, Slaughterbeck, Cliff R, Bennet, Crissa, Pinto, Dalila, Polioudakis, Damon, Franjic, Daniel, Miller, Daniel J, Bertagnolli, Darren, and Lewis, David A

Subjects
Human Genome, Genetics, Neurosciences, Biotechnology, Pediatric, Mental Health, Brain, Epigenesis, Genetic, Epigenomics, Gene Expression Regulation, Developmental, Gene Regulatory Networks, Humans, Mental Disorders, Nervous System Diseases, Neurogenesis, Single-Cell Analysis, Transcriptome, BrainSpan Consortium, PsychENCODE Consortium, PsychENCODE Developmental Subgroup, General Science & Technology
Abstract

To broaden our understanding of human neurodevelopment, we profiled transcriptomic and epigenomic landscapes across brain regions and/or cell types for the entire span of prenatal and postnatal development. Integrative analysis revealed temporal, regional, sex, and cell type-specific dynamics. We observed a global transcriptomic cup-shaped pattern, characterized by a late fetal transition associated with sharply decreased regional differences and changes in cellular composition and maturation, followed by a reversal in childhood-adolescence, and accompanied by epigenomic reorganizations. Analysis of gene coexpression modules revealed relationships with epigenomic regulation and neurodevelopmental processes. Genes with genetic associations to brain-based traits and neuropsychiatric disorders (including MEF2C, SATB2, SOX5, TCF4, and TSHZ3) converged in a small number of modules and distinct cell types, revealing insights into neurodevelopment and the genomic basis of neuropsychiatric risks.

Published
2018

19. Acquisition of cephalosporin resistance genes blaCTX‐M‐55, blaCTX‐M‐65, and blaCMY‐2 leads to quinolone resistance in colistin‐resistant Escherichia coli harboring mcr‐1 gene

Author

Nakayama, Tatsuya, primary, Li, Hien Thi, additional, Ngo, Phong Thanh, additional, Tran, Doan Nguyen Minh, additional, Nguyen, Oanh Thi Hoang, additional, Hoang, Phuong Hoai, additional, Yamaguchi, Takahiro, additional, Jinnai, Michio, additional, Nguyen, Phuc Do, additional, Van Dang, Chinh, additional, Kumeda, Yuko, additional, and Hase, Atsushi, additional

Published
2024
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20. A comprehensive transcriptional map of primate brain development.

Author

Bakken, Trygve E, Miller, Jeremy A, Ding, Song-Lin, Sunkin, Susan M, Smith, Kimberly A, Ng, Lydia, Szafer, Aaron, Dalley, Rachel A, Royall, Joshua J, Lemon, Tracy, Shapouri, Sheila, Aiona, Kaylynn, Arnold, James, Bennett, Jeffrey L, Bertagnolli, Darren, Bickley, Kristopher, Boe, Andrew, Brouner, Krissy, Butler, Stephanie, Byrnes, Emi, Caldejon, Shiella, Carey, Anita, Cate, Shelby, Chapin, Mike, Chen, Jefferey, Dee, Nick, Desta, Tsega, Dolbeare, Tim A, Dotson, Nadia, Ebbert, Amanda, Fulfs, Erich, Gee, Garrett, Gilbert, Terri L, Goldy, Jeff, Gourley, Lindsey, Gregor, Ben, Gu, Guangyu, Hall, Jon, Haradon, Zeb, Haynor, David R, Hejazinia, Nika, Hoerder-Suabedissen, Anna, Howard, Robert, Jochim, Jay, Kinnunen, Marty, Kriedberg, Ali, Kuan, Chihchau L, Lau, Christopher, Lee, Chang-Kyu, Lee, Felix, Luong, Lon, Mastan, Naveed, May, Ryan, Melchor, Jose, Mosqueda, Nerick, Mott, Erika, Ngo, Kiet, Nyhus, Julie, Oldre, Aaron, Olson, Eric, Parente, Jody, Parker, Patrick D, Parry, Sheana, Pendergraft, Julie, Potekhina, Lydia, Reding, Melissa, Riley, Zackery L, Roberts, Tyson, Rogers, Brandon, Roll, Kate, Rosen, David, Sandman, David, Sarreal, Melaine, Shapovalova, Nadiya, Shi, Shu, Sjoquist, Nathan, Sodt, Andy J, Townsend, Robbie, Velasquez, Lissette, Wagley, Udi, Wakeman, Wayne B, White, Cassandra, Bennett, Crissa, Wu, Jennifer, Young, Rob, Youngstrom, Brian L, Wohnoutka, Paul, Gibbs, Richard A, Rogers, Jeffrey, Hohmann, John G, Hawrylycz, Michael J, Hevner, Robert F, Molnár, Zoltán, Phillips, John W, Dang, Chinh, Jones, Allan R, Amaral, David G, Bernard, Amy, and Lein, Ed S

Subjects
Brain, Neocortex, Animals, Macaca mulatta, Humans, Microcephaly, Risk Factors, Schizophrenia, Cell Adhesion, Species Specificity, Transcription, Genetic, Conserved Sequence, Aging, Female, Male, Neurogenesis, Intellectual Disability, Transcriptome, Spatio-Temporal Analysis, Autism Spectrum Disorder, Neurodevelopmental Disorders, Transcription, Genetic, General Science & Technology
Abstract

The transcriptional underpinnings of brain development remain poorly understood, particularly in humans and closely related non-human primates. We describe a high-resolution transcriptional atlas of rhesus monkey (Macaca mulatta) brain development that combines dense temporal sampling of prenatal and postnatal periods with fine anatomical division of cortical and subcortical regions associated with human neuropsychiatric disease. Gene expression changes more rapidly before birth, both in progenitor cells and maturing neurons. Cortical layers and areas acquire adult-like molecular profiles surprisingly late in postnatal development. Disparate cell populations exhibit distinct developmental timing of gene expression, but also unexpected synchrony of processes underlying neural circuit construction including cell projection and adhesion. Candidate risk genes for neurodevelopmental disorders including primary microcephaly, autism spectrum disorder, intellectual disability, and schizophrenia show disease-specific spatiotemporal enrichment within developing neocortex. Human developmental expression trajectories are more similar to monkey than rodent, although approximately 9% of genes show human-specific regulation with evidence for prolonged maturation or neoteny compared to monkey.

Published
2016

21. Single Image Super Resolution via Manifold Approximation

Author

Dang, Chinh and Radha, Hayder

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Image super-resolution remains an important research topic to overcome the limitations of physical acquisition systems, and to support the development of high resolution displays. Previous example-based super-resolution approaches mainly focus on analyzing the co-occurrence properties of low resolution and high-resolution patches. Recently, we proposed a novel single image super-resolution approach based on linear manifold approximation of the high-resolution image-patch space [1]. The image super-resolution problem is then formulated as an optimization problem of searching for the best matched high resolution patch in the manifold for a given low-resolution patch. We developed a novel technique based on the l1 norm sparse graph to learn a set of low dimensional affine spaces or tangent subspaces of the high-resolution patch manifold. The optimization problem is then solved based on the learned set of tangent subspaces. In this paper, we build on our recent work as follows. First, we consider and analyze each tangent subspace as one point in a Grassmann manifold, which helps to compute geodesic pairwise distances among these tangent subspaces. Second, we develop a min-max algorithm to select an optimal subset of tangent subspaces. This optimal subset reduces the computational cost while still preserving the quality of the reconstructed high-resolution image. Third, and to further achieve lower computational complexity, we perform hierarchical clustering on the optimal subset based on Grassmann manifold distances. Finally, we analytically prove the validity of the proposed Grassmann-distance based clustering. A comparison of the obtained results with other state-of-the-art methods clearly indicates the viability of the new proposed framework., Comment: This paper has been withdrawn by the author due to a crucial sign error in equation 1

Published
2014

22. RPCA-KFE: Key Frame Extraction for Consumer Video based Robust Principal Component Analysis

Author

Dang, Chinh, Moghadam, Abdolreza, and Radha, Hayder

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Key frame extraction algorithms consider the problem of selecting a subset of the most informative frames from a video to summarize its content., Comment: This paper has been withdrawn by the author due to a crucial sign error in equation 1

Published
2014
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23. Representative Selection for Big Data via Sparse Graph and Geodesic Grassmann Manifold Distance

Author

Dang, Chinh and Radha, Hayder

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

This paper addresses the problem of identifying a very small subset of data points that belong to a significantly larger massive dataset (i.e., Big Data). The small number of selected data points must adequately represent and faithfully characterize the massive Big Data. Such identification process is known as representative selection [19]. We propose a novel representative selection framework by generating an l1 norm sparse graph for a given Big-Data dataset. The Big Data is partitioned recursively into clusters using a spectral clustering algorithm on the generated sparse graph. We consider each cluster as one point in a Grassmann manifold, and measure the geodesic distance among these points. The distances are further analyzed using a min-max algorithm [1] to extract an optimal subset of clusters. Finally, by considering a sparse subgraph of each selected cluster, we detect a representative using principal component centrality [11]. We refer to the proposed representative selection framework as a Sparse Graph and Grassmann Manifold (SGGM) based approach. To validate the proposed SGGM framework, we apply it onto the problem of video summarization where only few video frames, known as key frames, are selected among a much longer video sequence. A comparison of the results obtained by the proposed algorithm with the ground truth, which is agreed by multiple human judges, and with some state-of-the-art methods clearly indicates the viability of the SGGM framework., Comment: This paper has been withdrawn by the author due to lacking details

Published
2014

24. Highly efficient adsorbent for the transformer oil purification by ZnO/Graphene composite

Author

T. Tan Vu, The Vinh La, Van Tuan Pham, Minh Khoi Vu, Dang Chinh Huynh, and Ngoc Khiem Tran

Subjects
Adsorbent, ZnO/Graphene composite, Transformer oil, Purification, Chemistry, QD1-999
Abstract

In this work, a highly efficient adsorbent consisting of the ZnO/Graphene composite was prepared for the first time via the sonification route using urea as an alkaline precursor. The synthesized ZnO/Graphene composite provides the highest specific surface area comparing to other ZnO/Graphene composites synthesized by different approaches presented in the literature. For all we know, this is the first time the obtained ZnO/Graphene composite was used as an adsorbent for the transformer oil purification. The results showed that the ZnO/Graphene composite has a higher purification capacity than the conventional adsorbent, a commercial zeolite. Several factors that may underpin this outstanding result, such as the unreduced oxygen functional groups, the vacancy defects on the surface of the RGO flake, the high specific surface area, and the suitable pore size of the ZnO/Graphene composite for oil refining. Besides, the 3D structure of the ZnO/Graphene composite can enlarge the residence purification time of the transformer oil, helping to improve the purification capacity of the ZnO/Graphene composite.

Published
2020
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27. A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex

Author

de Vries, Saskia E. J., Lecoq, Jerome A., Buice, Michael A., Groblewski, Peter A., Ocker, Gabriel K., Oliver, Michael, Feng, David, Cain, Nicholas, Ledochowitsch, Peter, Millman, Daniel, Roll, Kate, Garrett, Marina, Keenan, Tom, Kuan, Leonard, Mihalas, Stefan, Olsen, Shawn, Thompson, Carol, Wakeman, Wayne, Waters, Jack, Williams, Derric, Barber, Chris, Berbesque, Nathan, Blanchard, Brandon, Bowles, Nicholas, Caldejon, Shiella D., Casal, Linzy, Cho, Andrew, Cross, Sissy, Dang, Chinh, Dolbeare, Tim, Edwards, Melise, Galbraith, John, Gaudreault, Nathalie, Gilbert, Terri L., Griffin, Fiona, Hargrave, Perry, Howard, Robert, Huang, Lawrence, Jewell, Sean, Keller, Nika, Knoblich, Ulf, Larkin, Josh D., Larsen, Rachael, Lau, Chris, Lee, Eric, Lee, Felix, Leon, Arielle, Li, Lu, Long, Fuhui, Luviano, Jennifer, Mace, Kyla, Nguyen, Thuyanh, Perkins, Jed, Robertson, Miranda, Seid, Sam, Shea-Brown, Eric, Shi, Jianghong, Sjoquist, Nathan, Slaughterbeck, Cliff, Sullivan, David, Valenza, Ryan, White, Casey, Williford, Ali, Witten, Daniela M., Zhuang, Jun, Zeng, Hongkui, Farrell, Colin, Ng, Lydia, Bernard, Amy, Phillips, John W., Reid, R. Clay, and Koch, Christof

Published
2020
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30. A High-Resolution Spatiotemporal Atlas of Gene Expression of the Developing Mouse Brain

Author

Thompson, Carol L, Ng, Lydia, Menon, Vilas, Martinez, Salvador, Lee, Chang-Kyu, Glattfelder, Katie, Sunkin, Susan M, Henry, Alex, Lau, Christopher, Dang, Chinh, Garcia-Lopez, Raquel, Martinez-Ferre, Almudena, Pombero, Ana, Rubenstein, John LR, Wakeman, Wayne B, Hohmann, John, Dee, Nick, Sodt, Andrew J, Young, Rob, Smith, Kimberly, Nguyen, Thuc-Nghi, Kidney, Jolene, Kuan, Leonard, Jeromin, Andreas, Kaykas, Ajamete, Miller, Jeremy, Page, Damon, Orta, Geri, Bernard, Amy, Riley, Zackery, Smith, Simon, Wohnoutka, Paul, Hawrylycz, Michael J, Puelles, Luis, and Jones, Allan R

Subjects
Neurosciences, Biotechnology, Genetics, Pediatric, 1.1 Normal biological development and functioning, Underpinning research, Neurological, Animals, Brain, Brain Mapping, Gene Expression, Gene Expression Profiling, Gene Expression Regulation, Developmental, Mice, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract

To provide a temporal framework for the genoarchitecture of brain development, we generated in situ hybridization data for embryonic and postnatal mouse brain at seven developmental stages for ∼2,100 genes, which were processed with an automated informatics pipeline and manually annotated. This resource comprises 434,946 images, seven reference atlases, an ontogenetic ontology, and tools to explore coexpression of genes across neurodevelopment. Gene sets coinciding with developmental phenomena were identified. A temporal shift in the principles governing the molecular organization of the brain was detected, with transient neuromeric, plate-based organization of the brain present at E11.5 and E13.5. Finally, these data provided a transcription factor code that discriminates brain structures and identifies the developmental age of a tissue, providing a foundation for eventual genetic manipulation or tracking of specific brain structures over development. The resource is available as the Allen Developing Mouse Brain Atlas (http://developingmouse.brain-map.org).

Published
2014

31. Transcriptional landscape of the prenatal human brain.

Author

Miller, Jeremy A, Ding, Song-Lin, Sunkin, Susan M, Smith, Kimberly A, Ng, Lydia, Szafer, Aaron, Ebbert, Amanda, Riley, Zackery L, Royall, Joshua J, Aiona, Kaylynn, Arnold, James M, Bennet, Crissa, Bertagnolli, Darren, Brouner, Krissy, Butler, Stephanie, Caldejon, Shiella, Carey, Anita, Cuhaciyan, Christine, Dalley, Rachel A, Dee, Nick, Dolbeare, Tim A, Facer, Benjamin AC, Feng, David, Fliss, Tim P, Gee, Garrett, Goldy, Jeff, Gourley, Lindsey, Gregor, Benjamin W, Gu, Guangyu, Howard, Robert E, Jochim, Jayson M, Kuan, Chihchau L, Lau, Christopher, Lee, Chang-Kyu, Lee, Felix, Lemon, Tracy A, Lesnar, Phil, McMurray, Bergen, Mastan, Naveed, Mosqueda, Nerick, Naluai-Cecchini, Theresa, Ngo, Nhan-Kiet, Nyhus, Julie, Oldre, Aaron, Olson, Eric, Parente, Jody, Parker, Patrick D, Parry, Sheana E, Stevens, Allison, Pletikos, Mihovil, Reding, Melissa, Roll, Kate, Sandman, David, Sarreal, Melaine, Shapouri, Sheila, Shapovalova, Nadiya V, Shen, Elaine H, Sjoquist, Nathan, Slaughterbeck, Clifford R, Smith, Michael, Sodt, Andy J, Williams, Derric, Zöllei, Lilla, Fischl, Bruce, Gerstein, Mark B, Geschwind, Daniel H, Glass, Ian A, Hawrylycz, Michael J, Hevner, Robert F, Huang, Hao, Jones, Allan R, Knowles, James A, Levitt, Pat, Phillips, John W, Sestan, Nenad, Wohnoutka, Paul, Dang, Chinh, Bernard, Amy, Hohmann, John G, and Lein, Ed S

Subjects
Brain, Neocortex, Fetus, Animals, Humans, Mice, Anatomy, Artistic, Species Specificity, Gene Expression Regulation, Developmental, Conserved Sequence, Gene Regulatory Networks, Atlases as Topic, Transcriptome, Anatomy, Artistic, Gene Expression Regulation, Developmental, General Science & Technology
Abstract

The anatomical and functional architecture of the human brain is mainly determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of the mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and post-mitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and outer subventricular zones even though the outer zone is expanded in humans. Both germinal and post-mitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in the frontal lobe. Finally, many neurodevelopmental disorder and human-evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development.

Published
2014

32. Facile Template In-Situ Fabrication of ZnCo2O4 Nanoparticles with Highly Photocatalytic Activities under Visible-Light Irradiation

Author

Vu T. Tan, La The Vinh, Tran Ngoc Khiem, and Huynh Dang Chinh

Subjects
sacrificial template, znco2o4, photodegradation, methylene blue, zno, Chemical engineering, TP155-156
Abstract

High specific surface area ZnCo2O4 nanoparticles were prepared via a sacrificial template accelerated hydrolysis by using nanoparticles of ZnO with highly polar properties as a template. The obtained ZnCo2O4 nanoparticles were characterized by the method of scanning electron microscopy (SEM), X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET) surface area measurements, Transmission electron microscopy (TEM), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS). The obtained nanoparticles were performed as a photocatalyst for the degradation of methylene blue in aqueous solution under visible irradiation. The photocatalytic degradation rate of methylene blue onto the synthesized ZnCo2O4 was higher than that of commercial ZnO and synthesized ZnO template.

Published
2019
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33. Cost-effective porous carbon materials synthesized by carbonizing rice husk and K2CO3 activation and their application for lithium-sulfur batteries

Author

Thanh-Tung Mai, Duc-Luong Vu, Dang- Chinh Huynh, Nae-Li Wu, and Anh-Tuan Le

Subjects
Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

In this work, we developed highly porous activated carbon (AC) materials with micro/meso porosity through carbonizing rice husk and treating them with K2CO3. Elemental sulfur was then loaded to the micropores through a solution infiltration method to form rice husk-derived activated carbon (RHAC)@S composite materials. The as-prepared RHAC@S composites with 0.25 mg cm−1 and 0.38 mg cm−1 of sulfur loading were tested as cathodes for lithium-sulfur (Li-S) batteries. The 0.25 mg cm−1 sulfur loaded sample showed an initial discharge capacity of 1080 mA h/g at a 0.1 C rate. After 50 cycles of charge/discharge tests at the current density of 0.2 C, the reversible capacity is maintained at 312 mA h/g. The RHAC material delivered a capacity of more than 300 mA h/g at a current density of 1.7 C. These results demonstrate that the RHAC porous materials are very promising as cathode materials for the development of high-performance Li-S batteries. Keywords: Rice husk, Cathode material, Carbonization process, Activated carbon, Lithium-sulfur batteries

Published
2019
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34. Synthesis and structural characterization of uranium-doped Ca2CuO3, a 1D quantum antiferromagnet

Author

Hoang, Nam Nhat, Huynh, Dang Chinh, Nguyen, Duc Tho, Nguyen, Thuy Trang, Ngo, Duc The, Finnie, Michael, and Nguyen, Chau

Subjects
Condensed Matter - Materials Science
Abstract

The technological settings of a modified sol-gel method for preparation of highly fine homogeneous powder Ca2CuO3 doped with uranium 238 (x=0-0.05) is presented. The analysis of structure, purity of phases and the justification for the role of uranium in the given compounds are provided together with almost complete classification of observed optical phonons by means of the Raman, IR measurements and ab initio calculation. The significant reduction in particle size was achieved by doping and the strong correlation between resistivity and doping concentration was observed and explained using the phonon-assisted electron hopping conduction model. The persistence of covalent insulation state in all compounds is a key feature of this class of compounds., Comment: 32 pages, 10 figures

Published
2008

35. An anatomic transcriptional atlas of human glioblastoma

Author

Puchalski, Ralph B., Shah, Nameeta, Miller, Jeremy, Dalley, Rachel, Nomura, Steve R., Yoon, Jae-Guen, Smith, Kimberly A., Lankerovich, Michael, Bertagnolli, Darren, Bickley, Kris, Boe, Andrew F., Brouner, Krissy, Butler, Stephanie, Caldejon, Shiella, Chapin, Mike, Datta, Suvro, Dee, Nick, Desta, Tsega, Dolbeare, Tim, Dotson, Nadezhda, Ebbert, Amanda, Feng, David, Feng, Xu, Fisher, Michael, Gee, Garrett, Goldy, Jeff, Gourley, Lindsey, Gregor, Benjamin W., Gu, Guangyu, Hejazinia, Nika, Hohmann, John, Hothi, Parvinder, Howard, Robert, Joines, Kevin, Kriedberg, Ali, Kuan, Leonard, Lau, Chris, Lee, Felix, Lee, Hwahyung, Lemon, Tracy, Long, Fuhui, Mastan, Naveed, Mott, Erika, Murthy, Chantal, Ngo, Kiet, Olson, Eric, Reding, Melissa, Riley, Zack, Rosen, David, Sandman, David, Shapovalova, Nadiya, Slaughterbeck, Clifford R., Sodt, Andrew, Stockdale, Graham, Szafer, Aaron, Wakeman, Wayne, Wohnoutka, Paul E., White, Steven J., Marsh, Don, Rostomily, Robert C., Ng, Lydia, Dang, Chinh, Jones, Allan, Keogh, Bart, Gittleman, Haley R., Barnholtz-Sloan, Jill S., Cimino, Patrick J., Uppin, Megha S., Keene, C. Dirk, Farrokhi, Farrokh R., Lathia, Justin D., Berens, Michael E., Iavarone, Antonio, Bernard, Amy, Lein, Ed, Phillips, John W., Rostad, Steven W., Cobbs, Charles, Hawrylycz, Michael J., and Foltz, Greg D.

Published
2018

36. Characterization of Co2+- and Fe3+-Codoped TiO2 Nanomaterials for Photocatalytic Degradation of Organic Pollutants under Visible Light Irradiation

Author

Nguyen Thi Tuyet Mai, Nguyen Kim Nga, Dang Thi Minh Hue, Ta Ngoc Dung, Huynh Dang Chinh, and Tran Quang Huy

Subjects
Physical and theoretical chemistry, QD450-801
Abstract

In this study, TiO2 nanomaterials were prepared using a solvothermal method and codoped with Co2+ and Fe3+ ions for the photocatalytic degradation of organic pollutants under visible light. The physicochemical properties of the obtained materials were studied by powder X-ray diffraction, field emission electron scanning microscopy, energy-dispersive X-ray spectroscopy, and nitrogen adsorption isotherms. Optical absorption was characterized by UV-vis absorption spectroscopy. The photocatalytic activities of the prepared materials were evaluated through methylene blue (MB) degradation under visible light irradiation. Results showed the excellent performance of MB degradation investigated on TiO2 samples codoped with Co2+ and Fe3+ in comparison with undoped and Co2+-doped TiO2 samples. The codoped TiO2 samples degraded 85%–90% of MB after 120 min, whereas all the prepared TiO2 samples were composed of pure anatase phase and had a spherical-like shape and mean crystalline size ranging from 6.2 nm to 7.8 determined by Scherrer’s equation. The optical absorption of the TiO2 codoped with Co2+ and Fe3+ was significantly enhanced toward the visible light region. The pseudo-second-order kinetic model fits well for the degradation of MB on as-prepared TiO2 codoped with Co2+ and Fe3+.

Published
2021
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40. Prevalence, antibiotic resistance, and extended-spectrum and AmpC β-lactamase productivity of Salmonella isolates from raw meat and seafood samples in Ho Chi Minh City, Vietnam

Author

Nguyen, Dao Thi Anh, Kanki, Masashi, Nguyen, Phuc Do, Le, Hien Thi, Ngo, Phong Thanh, Tran, Doan Nguyen Minh, Le, Ninh Hoang, Dang, Chinh Van, Kawai, Takao, Kawahara, Ryuji, Yonogi, Shinya, Hirai, Yuji, Jinnai, Michio, Yamasaki, Shinji, Kumeda, Yuko, and Yamamoto, Yoshimasa

Published
2016
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41. Screening of antibiotic residues in pork meat in Ho Chi Minh City, Vietnam, using a microbiological test kit and liquid chromatography/tandem mass spectrometry

Author

Ngoc Do, Mai Hoang, Yamaguchi, Takahiro, Okihashi, Masahiro, Harada, Kazuo, Konishi, Yoshimasa, Uchida, Kotaro, Bui, Long Thi, Nguyen, Thinh Duc, Phan, Ha Bich, Bui, Huong Dang Thien, Nguyen, Phuc Do, Kajimura, Keiji, Kumeda, Yuko, Dang, Chinh Van, Hirata, Kazumasa, and Yamamoto, Yoshimasa

Published
2016
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43. The Allen Brain Atlas

Author

Hawrylycz, Michael, Ng, Lydia, Feng, David, Sunkin, Susan, Szafer, Aaron, Dang, Chinh, and Kasabov, Nikola, editor

Published
2014
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46. Neurodata Without Borders: Creating a Common Data Format for Neurophysiology

Author

Teeters, Jeffery L., Godfrey, Keith, Young, Rob, Dang, Chinh, Friedsam, Claudia, Wark, Barry, Asari, Hiroki, Peron, Simon, Li, Nuo, Peyrache, Adrien, Denisov, Gennady, Siegle, Joshua H., Olsen, Shawn R., Martin, Christopher, Chun, Miyoung, Tripathy, Shreejoy, Blanche, Timothy J., Harris, Kenneth, Buzsáki, György, Koch, Christof, Meister, Markus, Svoboda, Karel, and Sommer, Friedrich T.

Published
2015
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49. sj-docx-1-aph-10.1177_10105395231166544 – Supplemental material for Household Food Insecurity Negatively Impacts Diet Diversity in the Vietnamese Mekong Delta: A Cross-Sectional Study

Author

Vuong, Thuy Ngoc, Dang, Chinh Van, Jagals, Paul, Toze, Simon, Gallegos, Danielle, and Gatton, Michelle

Subjects
111799 Public Health and Health Services not elsewhere classified, FOS: Health sciences
Abstract

Supplemental material, sj-docx-1-aph-10.1177_10105395231166544 for Household Food Insecurity Negatively Impacts Diet Diversity in the Vietnamese Mekong Delta: A Cross-Sectional Study by Thuy Ngoc Vuong, Chinh Van Dang, Paul Jagals, Simon Toze, Danielle Gallegos and Michelle Gatton in Asia Pacific Journal of Public Health

Published
2023
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50. sj-docx-2-aph-10.1177_10105395231166544 – Supplemental material for Household Food Insecurity Negatively Impacts Diet Diversity in the Vietnamese Mekong Delta: A Cross-Sectional Study

Author

Vuong, Thuy Ngoc, Dang, Chinh Van, Jagals, Paul, Toze, Simon, Gallegos, Danielle, and Gatton, Michelle

Subjects
111799 Public Health and Health Services not elsewhere classified, FOS: Health sciences
Abstract

Supplemental material, sj-docx-2-aph-10.1177_10105395231166544 for Household Food Insecurity Negatively Impacts Diet Diversity in the Vietnamese Mekong Delta: A Cross-Sectional Study by Thuy Ngoc Vuong, Chinh Van Dang, Paul Jagals, Simon Toze, Danielle Gallegos and Michelle Gatton in Asia Pacific Journal of Public Health

Published
2023
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