22 research outputs found

    ΠŸΠžΠ‘Π’ΠœΠžΠ”Π•Π ΠΠ˜Π—Πœ И Π’ΠžΠŸΠ›ΠžΠ©Π•ΠΠ˜Π• Π•Π“Πž ΠžΠ‘ΠΠžΠ’ΠΠ«Π₯ ΠŸΠ Π˜ΠΠ¦Π˜ΠŸΠžΠ’ Π’ Π‘ΠžΠ’Π Π•ΠœΠ•ΠΠΠžΠœ ΠœΠ£Π›Π¬Π’Π€Π˜Π›Π¬ΠœΠ• «НЭЧЖА: Π ΠžΠ–Π”Π•ΠΠ˜Π• Π”Π¬Π―Π’ΠžΠ›ΠΒ»

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    The theoretical provisions of deconstruction are extremely important for postmodernity. Because deconstructions have strong features of innovation, radicalism, destructive ideas and theory. Films are art and a commodity, and the commercialization of art is a typical feature of postmodern art. The interpretation of films becomes the key to study of post-Β  modern art, and postmodern representation of film becomes a prism that reflects postmodernism. With unique methods of deconstruction and reconstruction of postmodern aesthetics, <> rewrote the traditional classical myth into a more modern one. Through a unique change in Nezha's characters, the cartoon transcends the ideological themes of anti-feudalism and anti-patriarchy and addresses distinctive contemporary themes such as individual destiny, subjective initiative, and attitudes towards prejudiceВСорСтичСскиС полоТСния дСконструкции Ρ‡Ρ€Π΅Π·Π²Ρ‹Ρ‡Π°ΠΉΠ½ΠΎ Π²Π°ΠΆΠ½Ρ‹ для постмодСрна. Π’Π°ΠΊ ΠΊΠ°ΠΊ дСконструкции ΠΎΠ±Π»Π°Π΄Π°ΡŽΡ‚ ΡΠΈΠ»ΡŒΠ½Ρ‹ΠΌΠΈ Ρ‡Π΅Ρ€Ρ‚Π°ΠΌΠΈ новаторства, Ρ€Π°Π΄ΠΈΠΊΠ°Π»ΠΈΠ·ΠΌΠ°, дСструктивными идСями ΠΈ Ρ‚Π΅ΠΎΡ€ΠΈΠ΅ΠΉ. Π€ΠΈΠ»ΡŒΠΌΡ‹ - это искусство ΠΈ Ρ‚ΠΎΠ²Π°Ρ€, Π° коммСрциализация искусства - типичная Ρ‡Π΅Ρ€Ρ‚Π° постмодСрнистского искусства. Π˜Π½Ρ‚Π΅Ρ€ΠΏΡ€Π΅Ρ‚Π°Ρ†ΠΈΡ Ρ„ΠΈΠ»ΡŒΠΌΠΎΠ² становится ΠΊΠ»ΡŽΡ‡ΠΎΠΌ ΠΊ ΠΈΠ·ΡƒΡ‡Π΅Π½ΠΈΡŽ постмодСрнистского искусства, Π° постмодСрнистская рСпрСзСнтация Ρ„ΠΈΠ»ΡŒΠΌΠ° становится ΠΏΡ€ΠΈΠ·ΠΌΠΎΠΉ, ΠΎΡ‚Ρ€Π°ΠΆΠ°ΡŽΡ‰Π΅ΠΉ постмодСрнизм. Π‘ ΠΏΠΎΠΌΠΎΡ‰ΡŒΡŽ ΡƒΠ½ΠΈΠΊΠ°Π»ΡŒΠ½Ρ‹Ρ… ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠ² дСконструкции ΠΈ рСконструкции постмодСрнистской эстСтики ΠΌΡƒΠ»ΡŒΡ‚Ρ„ΠΈΠ»ΡŒΠΌ «НэчТа: Π ΠΎΠΆΠ΄Π΅Π½ΠΈΠ΅ дьявола» пСрСписал Ρ‚Ρ€Π°Π΄ΠΈΡ†ΠΈΠΎΠ½Π½Ρ‹ΠΉ классичСский ΠΌΠΈΡ„ Π² соврСмСнный. Π§Π΅Ρ€Π΅Π· ΡƒΠ½ΠΈΠΊΠ°Π»ΡŒΠ½ΠΎΠ΅ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠ΅ пСрсонаТСй НэчТи, ΠΌΡƒΠ»ΡŒΡ‚Ρ„ΠΈΠ»ΡŒΠΌ Π²Ρ‹Ρ…ΠΎΠ΄ΠΈΡ‚ Π·Π° Ρ€Π°ΠΌΠΊΠΈ идСологичСской Ρ‚Π΅ΠΌΡ‹ Π°Π½Ρ‚ΠΈΡ„Π΅ΠΎΠ΄Π°Π»ΠΈΠ·ΠΌΠ° ΠΈ Π°Π½Ρ‚ΠΈΠΏΠ°Ρ‚Ρ€ΠΈΠ°Ρ€Ρ…Π°Ρ‚Π° ΠΈ обращаСтся ΠΊ ΠΎΡ‚Π»ΠΈΡ‡ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹ΠΌ соврСмСнным Ρ‚Π΅ΠΌΠ°ΠΌ, Ρ‚Π°ΠΊΠΈΠΌ ΠΊΠ°ΠΊ ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡƒΠ°Π»ΡŒΠ½Π°Ρ ΡΡƒΠ΄ΡŒΠ±Π°, ΡΡƒΠ±ΡŠΠ΅ΠΊΡ‚ΠΈΠ²Π½Π°Ρ ΠΈΠ½ΠΈΡ†ΠΈΠ°Ρ‚ΠΈΠ²Π° ΠΈ ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΠ΅ ΠΊ ΠΏΡ€Π΅Π΄ΡƒΠ±Π΅ΠΆΠ΄Π΅Π½ΠΈΡŽ

    The adenosine A2A receptor antagonist KW6002 distinctly regulates retinal ganglion cell morphology during postnatal development and neonatal inflammation

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    Adenosine A2A receptors (A2ARs) appear early in the retina during postnatal development, but the roles of the A2ARs in the morphogenesis of distinct types of retinal ganglion cells (RGCs) during postnatal development and neonatal inflammatory response remain undetermined. As the RGCs are rather heterogeneous in morphology and functions in the retina, here we resorted to the Thy1-YFPH transgenic mice and three-dimensional (3D) neuron reconstruction to investigate how A2ARs regulate the morphogenesis of three morphologically distinct types of RGCs (namely Type I, II, III) during postnatal development and neonatal inflammation. We found that the A2AR antagonist KW6002 did not change the proportion of the three RGC types during retinal development, but exerted a bidirectional effect on dendritic complexity of Type I and III RGCs and cell type-specifically altered their morphologies with decreased dendrite density of Type I, decreased the dendritic field area of Type II and III, increased dendrite density of Type III RGCs. Moreover, under neonatal inflammation condition, KW6002 specifically increased the proportion of Type I RGCs with enhanced the dendrite surface area and volume and the proportion of Type II RGCs with enlarged the soma area and perimeter. Thus, A2ARs exert distinct control of RGC morphologies to cell type-specifically fine-tune the RGC dendrites during normal development but to mainly suppress RGC soma and dendrite volume under neonatal inflammation

    RecV recombinase system for in vivo targeted optogenomic modifications of single cells or cell populations

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    Brain circuits comprise vast numbers of interconnected neurons with diverse molecular, anatomical and physiological properties. To allow targeting of individual neurons for structural and functional studies, we created light-inducible site-specific DNA recombinases based on Cre, Dre and Flp (RecVs). RecVs can induce genomic modifications by one-photon or two-photon light induction in vivo. They can produce targeted, sparse and strong labeling of individual neurons by modifying multiple loci within mouse and zebrafish genomes. In combination with other genetic strategies, they allow intersectional targeting of different neuronal classes. In the mouse cortex they enable sparse labeling and whole-brain morphological reconstructions of individual neurons. Furthermore, these enzymes allow single-cell two-photon targeted genetic modifications and can be used in combination with functional optical indicators with minimal interference. In summary, RecVs enable spatiotemporally precise optogenomic modifications that can facilitate detailed single-cell analysis of neural circuits by linking genetic identity, morphology, connectivity and function

    RecV recombinase system for in vivo targeted optogenomic modifications of single cells or cell populations

    Get PDF
    Brain circuits comprise vast numbers of interconnected neurons with diverse molecular, anatomical and physiological properties. To allow targeting of individual neurons for structural and functional studies, we created light-inducible site-specific DNA recombinases based on Cre, Dre and Flp (RecVs). RecVs can induce genomic modifications by one-photon or two-photon light induction in vivo. They can produce targeted, sparse and strong labeling of individual neurons by modifying multiple loci within mouse and zebrafish genomes. In combination with other genetic strategies, they allow intersectional targeting of different neuronal classes. In the mouse cortex they enable sparse labeling and whole-brain morphological reconstructions of individual neurons. Furthermore, these enzymes allow single-cell two-photon targeted genetic modifications and can be used in combination with functional optical indicators with minimal interference. In summary, RecVs enable spatiotemporally precise optogenomic modifications that can facilitate detailed single-cell analysis of neural circuits by linking genetic identity, morphology, connectivity and function

    Morphological diversity of single neurons in molecularly defined cell types.

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    Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis ofΒ which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level ofΒ major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in whichΒ different cell types and their individual members may contribute to the configuration and function of their respective circuits

    Cellular anatomy of the mouse primary motor cortex.

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    An essential step toward understanding brain function is to establish a structural framework with cellular resolution on which multi-scale datasets spanning molecules, cells, circuits and systems can be integrated and interpreted1. Here, as part of the collaborative Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based anatomical description of one exemplar brain structure, the mouse primary motor cortex, upper limb area (MOp-ul). Using genetic and viral labelling, barcoded anatomy resolved by sequencing, single-neuron reconstruction, whole-brain imaging and cloud-based neuroinformatics tools, we delineated the MOp-ul in 3D and refined its sublaminar organization. We defined around two dozen projection neuron types in the MOp-ul and derived an input-output wiring diagram, which will facilitate future analyses of motor control circuitry across molecular, cellular and system levels. This work provides a roadmap towards a comprehensive cellular-resolution description of mammalian brain architecture

    A multimodal cell census and atlas of the mammalian primary motor cortex

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    ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties

    A simplified morphological classification scheme for pyramidal cells in six layers of primary somatosensory cortex of juvenile rats

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    The majority of neurons in the neocortex are excitatory pyramidal cells (PCs). Many systematic classification schemes have been proposed based the neuronal morphology, the chemical composition, and the synaptic connectivity, etc. Recently, a cortical column of primary somatosensory cortex (SSC) has been reconstruction and functionally simulated (Markram et al., 2015). Putting forward from this study, here we proposed a simplified classification scheme for PCs in all layers of the SSC by mainly identifying apical dendritic morphology based on a large data set of 3D neuron reconstructions. We used this scheme to classify three types in layer 2, two in layer 3, three in layer 4, four in layer 5, and six types in layer 6. These PC types were visually distinguished and confirmed by quantitative differences in their morphometric properties. The classes yielded using this scheme largely corresponded with PC classes that were defined previously based on other neuronal and synaptic properties such as long-range projects and synaptic innervations, further validating its applicability. Therefore, the morphology information of apical dendrites is sufficient for a simple scheme to classify a spectrum of anatomical types of PCs in the SSC. Keywords: Somatosensory cortex, Cortical layers, Cell types, Pyramidal cells, Dendrites, Apical dendrite

    Identification of Long Non-Coding RNAs Related to Skeletal Muscle Development in Two Rabbit Breeds with Different Growth Rate

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    Skeletal muscle development plays an important role in muscle quality and yield, which decides the economic value of livestock. Long non-coding RNAs (lncRNAs) have been reported to be associated with skeletal muscle development. However, little is revealed about the function of lncRNAs in rabbits’ muscle development. LncRNAs and mRNAs in two rabbit breeds (ZIKA rabbits (ZKR) and Qixin rabbits (QXR)) with different growth rates at three developmental stages (0 day, 35 days, and 84 days after birth) were researched by transcriptome sequencing. Differentially expressed lncRNAs and mRNAs were identified for two rabbit breeds at the same stages by DESeq package. Co-expression correlation analysis of differentially expressed lncRNAs and mRNAs were performed to construct lncRNA–mRNA pairs. To explore the function of lncRNAs, Gene Ontology (GO) analysis of co-expression mRNAs in lncRNA–mRNA pairs were performed. In three comparisons, there were 128, 109, and 115 differentially expressed lncRNAs, respectively. LncRNAs TCONS_00013557 and XR_518424.2 differentially expressed in the two rabbit breeds might play important roles in skeletal muscle development, for their co-expressed mRNAs were significantly enriched in skeletal muscle development related GO terms. This study provides potentially functional lncRNAs in skeletal muscle development of two rabbit breeds and might be beneficial to the production of rabbits

    Characterization of major depressive disorder using a multiparametric classification approach based on high resolution structural images

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    BACKGROUND: Major depressive disorder (MDD) is one of the most disabling mental illnesses. Previous neuroanatomical studies of MDD have revealed regional alterations in grey matter volume and density. However, owing to the heterogeneous symptomatology and complex etiology, MDD is likely to be associated with multiple morphometric alterations in brain structure. We sought to distinguish first-episode, medication-naive, adult patients with MDD from healthy controls and characterize neuroanatomical differences between the groups using a multiparameter classification approach. METHODS: We recruited medication-naive patients with first-episode depression and healthy controls matched for age, sex, handedness and years of education. High-resolution T(1)-weighted images were used to extract 7 morphometric parameters, including both volumetric and geometric features, based on the surface data of the entire cerebral cortex. These parameters were used to compare patients and controls using multivariate support vector machine, and the regions that informed the discrimination between the 2 groups were identified based on maximal classification weights. RESULTS: Thirty-two patients and 32 controls participated in the study. Both volumetric and geometric parameters could discriminate patients with MDD from healthy controls, with cortical thickness in the right hemisphere providing the greatest accuracy (78%, p ≀ 0.001). This discrimination was informed by a bilateral network comprising mainly frontal, temporal and parietal regions. LIMITATIONS: The sample size was relatively small and our results were based on first-episode, medication-naive patients. CONCLUSION: Our investigation demonstrates that multiple cortical features are affected in medication-naive patients with first-episode MDD. These findings extend the current understanding of the neuropathological underpinnings of MDD and provide preliminary support for the use of neuroanatomical scans in the early detection of MDD
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