Journal: Frontiers in Physiology

Article Title: The SPARC DRC: Building a Resource for the Autonomic Nervous System Community

doi: 10.3389/fphys.2021.693735

Figure Lengend Snippet: Detail of an ApiNATOMY schematic diagram representing neural connectivity between the rodent spinal cord and the lower urinary tract (Surles-Zeigler et al., ). Note that the pathway information in diagrams such as this is stored in SPARC Connectivity Knowledge Base and used to render the pathways in the more anatomically oriented flatmaps (see ).

Article Snippet: As well as the continued curation, annotation, and mapping of datasets provided by the SPARC experimental community, future developments of the SPARC DRC infrastructure include: (i) more complete neural connectivity displayed on the flatmaps and more automated ways of drawing these pathways directly from the semantic annotations deposited into the SPARC Knowledge Graph hosted within SciCrunch; (ii) further organ scaffolds beyond the current set (heart, lungs, stomach, bladder, colon); (iii) whole body scaffolds for multiple species, into which the organ scaffolds and neural pathways can be algorithmically embedded; (iv) further development of tools to enable experimentalists to register their data into the organ and body scaffolds; (v) implementation of built-in quality assurance functionality; (vi) provision of extended data processing functionalities and support for sharing and publishing analyses; (vii) facilitation of in silico studies and provision of expert workflows; and (viii) an increasing focus on the interpretation of autonomic nervous system connectivity with models that explain function in order to facilitate the design, optimization, safety assessment, personalization, and control of effective device-based neuromodulation therapies.

Techniques:

Journal: Frontiers in Physiology

Article Title: The SPARC DRC: Building a Resource for the Autonomic Nervous System Community

doi: 10.3389/fphys.2021.693735

Figure Lengend Snippet: Flatmaps of individual species available through the SPARC portal at sparc.science/maps . Zooming in on these mapping diagrams provides additional levels of detail and clickable links that retrieve relevant SPARC data resources from Discover via the SKG (SPARC Knowledge Graph).

Article Snippet: As well as the continued curation, annotation, and mapping of datasets provided by the SPARC experimental community, future developments of the SPARC DRC infrastructure include: (i) more complete neural connectivity displayed on the flatmaps and more automated ways of drawing these pathways directly from the semantic annotations deposited into the SPARC Knowledge Graph hosted within SciCrunch; (ii) further organ scaffolds beyond the current set (heart, lungs, stomach, bladder, colon); (iii) whole body scaffolds for multiple species, into which the organ scaffolds and neural pathways can be algorithmically embedded; (iv) further development of tools to enable experimentalists to register their data into the organ and body scaffolds; (v) implementation of built-in quality assurance functionality; (vi) provision of extended data processing functionalities and support for sharing and publishing analyses; (vii) facilitation of in silico studies and provision of expert workflows; and (viii) an increasing focus on the interpretation of autonomic nervous system connectivity with models that explain function in order to facilitate the design, optimization, safety assessment, personalization, and control of effective device-based neuromodulation therapies.

Techniques:

Journal: Frontiers in Physiology

Article Title: The SPARC DRC: Building a Resource for the Autonomic Nervous System Community

doi: 10.3389/fphys.2021.693735

Figure Lengend Snippet: Scaffolds for the colon in the human (dataset available from https://sparc.science/datasets/95 ), pig (dataset available from https://sparc.science/datasets/98 ), and mouse (dataset available from https://sparc.science/datasets/76 ). The scaffolds for each species are built in three steps: (A–C) define a sub-scaffold that captures the cross-sectional anatomy of the colon for the three species, (D–F) define the centerline of the colon, (G–I) attach these sub-scaffolds sequentially to the centerline to form the final scaffold.

Article Snippet: As well as the continued curation, annotation, and mapping of datasets provided by the SPARC experimental community, future developments of the SPARC DRC infrastructure include: (i) more complete neural connectivity displayed on the flatmaps and more automated ways of drawing these pathways directly from the semantic annotations deposited into the SPARC Knowledge Graph hosted within SciCrunch; (ii) further organ scaffolds beyond the current set (heart, lungs, stomach, bladder, colon); (iii) whole body scaffolds for multiple species, into which the organ scaffolds and neural pathways can be algorithmically embedded; (iv) further development of tools to enable experimentalists to register their data into the organ and body scaffolds; (v) implementation of built-in quality assurance functionality; (vi) provision of extended data processing functionalities and support for sharing and publishing analyses; (vii) facilitation of in silico studies and provision of expert workflows; and (viii) an increasing focus on the interpretation of autonomic nervous system connectivity with models that explain function in order to facilitate the design, optimization, safety assessment, personalization, and control of effective device-based neuromodulation therapies.

Techniques:

Journal: Frontiers in Physiology

Article Title: The SPARC DRC: Building a Resource for the Autonomic Nervous System Community

doi: 10.3389/fphys.2021.693735

Figure Lengend Snippet: Front (left) and back (right) views of the (A) human (dataset available from https://sparc.science/datasets/100 ), (B) pig (dataset available from https://sparc.science/datasets/102 ), and (C) rat (dataset available from https://sparc.science/datasets/99 ) scaffolds (not to scale). The topology of the scaffold is different for each species as each has a different number of pulmonary veins entering the left atrium (4, 2, and 3, respectively).

Article Snippet: As well as the continued curation, annotation, and mapping of datasets provided by the SPARC experimental community, future developments of the SPARC DRC infrastructure include: (i) more complete neural connectivity displayed on the flatmaps and more automated ways of drawing these pathways directly from the semantic annotations deposited into the SPARC Knowledge Graph hosted within SciCrunch; (ii) further organ scaffolds beyond the current set (heart, lungs, stomach, bladder, colon); (iii) whole body scaffolds for multiple species, into which the organ scaffolds and neural pathways can be algorithmically embedded; (iv) further development of tools to enable experimentalists to register their data into the organ and body scaffolds; (v) implementation of built-in quality assurance functionality; (vi) provision of extended data processing functionalities and support for sharing and publishing analyses; (vii) facilitation of in silico studies and provision of expert workflows; and (viii) an increasing focus on the interpretation of autonomic nervous system connectivity with models that explain function in order to facilitate the design, optimization, safety assessment, personalization, and control of effective device-based neuromodulation therapies.

Techniques:

Journal: Frontiers in Physiology

Article Title: The SPARC DRC: Building a Resource for the Autonomic Nervous System Community

doi: 10.3389/fphys.2021.693735

Figure Lengend Snippet: Generating a whole rat body anatomical scaffold from data for integration with other organ scaffolds. (A) The 3D body coordinate system (dataset available from https://sparc.science/datasets/112 ) shows distinct anatomical regions with different colors. (B) The rat model (NeuroRat, IT'IS Foundation. 10.13099/VIP91106-04-0 ) in the vtk format with spinal cord and diaphragm visible. This model contains 179 segmented tissues with neuro-functionalized nerve trajectories (i.e., associated electrophysiological fiber models). (C) All tissue tissues from the rat body were resampled and converted into a data cloud to provide the means for generating the whole body scaffold. The data cloud is a 3D spatial representation of the tissue surface consisting of a certain density of points in the 3D Euclidean space. These points are used to define the objective function for the scaffold fitting procedure. The data cloud of the skin, inner core, spinal cord, and diaphragm are shown in (C) with the limbs and tail excluded. (D) The 3D body scaffold (A) was fitted to the rat data to generate the anatomical scaffold. (E) A generic rat heart scaffold was projected into the body scaffold using three corresponding fiducial landmarks (green arrows in heart and green spheres in the body). This transformation allows embedding of the organ scaffolds into their appropriate locations in the body scaffold, providing the required physical environment required for simulation and modeling. SCV, superior vena cava; RPV, right pulmonary vein; MPV, middle pulmonary vein; LPV, left pulmonary vein; RAA, right atrial appendage; RA, right atrium; LA, left atrium; LAA, left atrial appendage; PTo, pulmonary trunk outlet; RV, right ventricle; LV, left ventricle.

Article Snippet: As well as the continued curation, annotation, and mapping of datasets provided by the SPARC experimental community, future developments of the SPARC DRC infrastructure include: (i) more complete neural connectivity displayed on the flatmaps and more automated ways of drawing these pathways directly from the semantic annotations deposited into the SPARC Knowledge Graph hosted within SciCrunch; (ii) further organ scaffolds beyond the current set (heart, lungs, stomach, bladder, colon); (iii) whole body scaffolds for multiple species, into which the organ scaffolds and neural pathways can be algorithmically embedded; (iv) further development of tools to enable experimentalists to register their data into the organ and body scaffolds; (v) implementation of built-in quality assurance functionality; (vi) provision of extended data processing functionalities and support for sharing and publishing analyses; (vii) facilitation of in silico studies and provision of expert workflows; and (viii) an increasing focus on the interpretation of autonomic nervous system connectivity with models that explain function in order to facilitate the design, optimization, safety assessment, personalization, and control of effective device-based neuromodulation therapies.

Techniques: Transformation Assay