The human cerebral cortex, pivotal for advanced cognitive functions, is composed of six distinct layers and dozens of functionally specialized areas. The layers and areas are distinguished both molecularly, by diverse neuronal and glial cell subtypes, and structurally, through intricate spatial organization. While single-cell transcriptomics studies have advanced molecular characterization of human cortical development, a critical gap exists due to the loss of spatial context during cell dissociation. Here, we utilized multiplexed error-robust fluorescence in situ hybridization (MERFISH), augmented with deep-learning-based cell segmentation, to examine the molecular, cellular, and cytoarchitectural development of human fetal cortex with spatially resolved single-cell resolution. Our extensive spatial atlas, encompassing 16 million single cells, spans eight cortical areas across four time points in the second and third trimesters. We uncovered an early establishment of the six-layer structure, identifiable in the laminar distribution of excitatory neuronal subtypes by mid-gestation, long before the emergence of cytoarchitectural layers. Notably, while anterior-posterior gradients of neuronal subtypes were generally observed in most cortical areas, a striking exception was the sharp molecular border between primary (V1) and secondary visual cortices (V2) at gestational week 20. Here we discovered an abrupt binary shift in neuronal subtype specification at the earliest stages, challenging the notion that continuous morphogen gradients dictate mid-gestation cortical arealization. Moreover, integrating single-nuclei RNA-sequencing and in situ whole transcriptomics revealed an early upregulation of synaptogenesis in V1-specific Layer 4 neurons, suggesting a role of synaptogenesis in this discrete border formation. Collectively, our findings underscore the crucial role of spatial relationships in determining the molecular specification of cortical layers and areas. This work not only provides a valuable resource for the field, but also establishes a spatially resolved single-cell analysis paradigm that paves the way for a comprehensive developmental atlas of the human brain.
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http://dx.doi.org/10.1101/2024.06.05.597673 | DOI Listing |
J Struct Biol
December 2024
Program in Cellular and Molecular Medicine, Boston Children's Hospital, 200 Longwood Ave, Boston, MA 02115, USA; Department of Cell Biology, Harvard Medical School, 200 Longwood Ave, Boston, MA 02115, USA; Department of Pediatrics, Harvard Medical School, 200 Longwood Ave, Boston, MA 02115, USA. Electronic address:
Cryogenic electron tomography (cryo-ET) has rapidly advanced as a high-resolution imaging tool for visualizing subcellular structures in 3D with molecular detail. Direct image inspection remains challenging due to inherent low signal-to-noise ratios (SNR). We introduce CryoSamba, a self-supervised deep learning-based model designed for denoising cryo-ET images.
View Article and Find Full Text PDFMikrochim Acta
December 2024
Department of Analytical Chemistry and Food Technology, Environmental Sciences Institute (ICAM), University of Castilla-La Mancha, Avda. Carlos III S/N, 45071, Toledo, Spain.
Single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) is a powerful tool for metallic nanoparticle (NP) characterisation in terms of concentration and, taking into account several assumptions, also size. However, this technique faces challenges, such as the intrinsic matrix effect, which significantly impact the results when analysing real complex samples. This issue is critical for the calculations of key SP-ICP-MS parameters ultimately altering the final outcomes.
View Article and Find Full Text PDFEur J Med Res
December 2024
Department of Ophthalmology, Zhongshan City People's Hospital, Zhongshan, Guangdong, China.
Background: Age-related macular degeneration (AMD), is a neurodegenerative ocular disease. This study investigated the role of ferroptosis-related genes and their interaction with immune cell infiltration in AMD.
Methods: We screened differential expression genes (DEGs) of AMD from data sets in Gene Expression Omnibus.
BMC Bioinformatics
December 2024
Institute for the Advanced Study of Human Biology, Kyoto University Institute for Advanced Study, Kyoto University, Yoshida-Konoe-cho, Sakyo-ku, Kyoto, 606-8501, Japan.
Background: Time-series scRNA-seq data have opened a door to elucidate cell differentiation, and in this context, the optimal transport theory has been attracting much attention. However, there remain critical issues in interpretability and computational cost.
Results: We present scEGOT, a comprehensive framework for single-cell trajectory inference, as a generative model with high interpretability and low computational cost.
Brief Bioinform
November 2024
Guangdong Provincial Clinical Research Center for Geriatrics; Shenzhen Clinical Research Center for Geriatrics, Shenzhen People's Hospital, the Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology, 1017 Dongmen Rd N, Luohu District, Shenzhen 518020, China.
Sepsis, caused by infections, sparks a dangerous bodily response. The transcriptional expression patterns of host responses aid in the diagnosis of sepsis, but the challenge lies in their limited generalization capabilities. To facilitate sepsis diagnosis, we present an updated version of single-cell Pair-wise Analysis of Gene Expression (scPAGE) using transfer learning method, scPAGE2, dedicated to data fusion between single-cell and bulk transcriptome.
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