Multibarrier-penetrating drug delivery systems for deep tumor therapy based on synergistic penetration strategy.

Nanotherapies, valued for their high efficacy and low toxicity, frequently serve as antitumor treatments, but do not readily penetrate deep into tumor tissues and cells. Here we developed an improved tumor-penetrating peptide (TPP)-based drug delivery system. Briefly, the established TPP iNGR was modified to generate a linear NGR peptide capable of transporting nanotherapeutic drugs into tumors through a CendR pathway-dependent, neuropilin-1 receptor-mediated process. Although TPPs have been reported to reach intended tumor targets, they often fail to penetrate cell membranes to deliver tumoricidal drugs to intracellular targets. We addressed this issue by harnessing cell penetrating peptide technology to develop a liposome-based multibarrier-penetrating delivery system (mbPDS) with improved synergistic drug penetration into deep tumor tissues and cells. The system incorporated doxorubicin-loaded liposomes coated with nona-arginine (R9) CPP and cyclic iNGR (CRNGRGPDC) molecules, yielding Lip-mbPDS. Lip-mbPDS tumor-targeting, tumor cell/tissue-penetrating and antitumor capabilities were assessed using CD13-positive human fibrosarcoma-derived cell (HT1080)-based in vitro and in vivo tumor models. Lip-mbPDS evaluation included three-dimensional layer-by-layer confocal laser scanning microscopy, cell internalization/toxicity assays, three-dimensional tumor spheroid-based penetration assays and antitumor efficacy assays conducted in an animal model. Lip-mbPDS provided enhanced synergistic drug penetration of multiple biointerfaces for potentially deep tumor therapeutic outcomes.

Petascale pipeline for precise alignment of images from serial section electron microscopy.

The reconstruction of neural circuits from serial section electron microscopy (ssEM) images is being accelerated by automatic image segmentation methods. Segmentation accuracy is often limited by the preceding step of aligning 2D section images to create a 3D image stack. Precise and robust alignment in the presence of image artifacts is challenging, especially as datasets are attaining the petascale. We present a computational pipeline for aligning ssEM images with several key elements. Self-supervised convolutional nets are trained via metric learning to encode and align image pairs, and they are used to initialize iterative fine-tuning of alignment. A procedure called vector voting increases robustness to image artifacts or missing image data. For speedup the series is divided into blocks that are distributed to computational workers for alignment. The blocks are aligned to each other by composing transformations with decay, which achieves a global alignment without resorting to a time-consuming global optimization. We apply our pipeline to a whole fly brain dataset, and show improved accuracy relative to prior state of the art. We also demonstrate that our pipeline scales to a cubic millimeter of mouse visual cortex. Our pipeline is publicly available through two open source Python packages.

Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex.

Mammalian cortex features a vast diversity of neuronal cell types, each with characteristic anatomical, molecular and functional properties. Synaptic connectivity powerfully shapes how each cell type participates in the cortical circuit, but mapping connectivity rules at the resolution of distinct cell types remains difficult. Here, we used millimeter-scale volumetric electron microscopy1 to investigate the connectivity of all inhibitory neurons across a densely-segmented neuronal population of 1352 cells spanning all layers of mouse visual cortex, producing a wiring diagram of inhibitory connections with more than 70,000 synapses. Taking a data-driven approach inspired by classical neuroanatomy, we classified inhibitory neurons based on the relative targeting of dendritic compartments and other inhibitory cells and developed a novel classification of excitatory neurons based on the morphological and synaptic input properties. The synaptic connectivity between inhibitory cells revealed a novel class of disinhibitory specialist targeting basket cells, in addition to familiar subclasses. Analysis of the inhibitory connectivity onto excitatory neurons found widespread specificity, with many interneurons exhibiting differential targeting of certain subpopulations spatially intermingled with other potential targets. Inhibitory targeting was organized into "motif groups," diverse sets of cells that collectively target both perisomatic and dendritic compartments of the same excitatory targets. Collectively, our analysis identified new organizing principles for cortical inhibition and will serve as a foundation for linking modern multimodal neuronal atlases with the cortical wiring diagram.

CAVE: Connectome Annotation Versioning Engine.

Advances in Electron Microscopy, image segmentation and computational infrastructure have given rise to large-scale and richly annotated connectomic datasets which are increasingly shared across communities. To enable collaboration, users need to be able to concurrently create new annotations and correct errors in the automated segmentation by proofreading. In large datasets, every proofreading edit relabels cell identities of millions of voxels and thousands of annotations like synapses. For analysis, users require immediate and reproducible access to this constantly changing and expanding data landscape. Here, we present the Connectome Annotation Versioning Engine (CAVE), a computational infrastructure for immediate and reproducible connectome analysis in up-to petascale datasets (~1mm3) while proofreading and annotating is ongoing. For segmentation, CAVE provides a distributed proofreading infrastructure for continuous versioning of large reconstructions. Annotations in CAVE are defined by locations such that they can be quickly assigned to the underlying segment which enables fast analysis queries of CAVE's data for arbitrary time points. CAVE supports schematized, extensible annotations, so that researchers can readily design novel annotation types. CAVE is already used for many connectomics datasets, including the largest datasets available to date.

Neuronal wiring diagram of an adult brain.

Connections between neurons can be mapped by acquiring and analyzing electron microscopic (EM) brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative, yet inadequate for understanding brain function more globally. Here, we present the first neuronal wiring diagram of a whole adult brain, containing 5×107 chemical synapses between ~130,000 neurons reconstructed from a female Drosophila melanogaster. The resource also incorporates annotations of cell classes and types, nerves, hemilineages, and predictions of neurotransmitter identities. Data products are available by download, programmatic access, and interactive browsing and made interoperable with other fly data resources. We show how to derive a projectome, a map of projections between regions, from the connectome. We demonstrate the tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine, and descending neurons), across both hemispheres, and between the central brain and the optic lobes. Tracing from a subset of photoreceptors all the way to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviors. The technologies and open ecosystem of the FlyWire Consortium set the stage for future large-scale connectome projects in other species.

NEURD: automated proofreading and feature extraction for connectomics.

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium et al., 2021). Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML) (Lee et al., 2017; Wu et al., 2021; Lu et al., 2021; Macrina et al., 2021). Automated segmentation methods can now yield exceptionally accurate reconstructions of cells, but despite this accuracy, laborious post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons produced by these segmentations contain detailed morphological information, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting information about these features can require substantial effort to piece together existing tools into custom workflows. Building on existing open-source software for mesh manipulation, here we present "NEURD", a software package that decomposes each meshed neuron into a compact and extensively-annotated graph representation. With these feature-rich graphs, we implement workflows for state of the art automated post-hoc proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and other features that can enable many downstream analyses of neural morphology and connectivity. NEURD can make these new massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.

Functional connectomics reveals general wiring rule in mouse visual cortex.

To understand how the brain computes, it is important to unravel the relationship between circuit connectivity and function. Previous research has shown that excitatory neurons in layer 2/3 of the primary visual cortex of mice with similar response properties are more likely to form connections. However, technical challenges of combining synaptic connectivity and functional measurements have limited these studies to few, highly local connections. Utilizing the millimeter scale and nanometer resolution of the MICrONS dataset, we studied the connectivity-function relationship in excitatory neurons of the mouse visual cortex across interlaminar and interarea projections, assessing connection selectivity at the coarse axon trajectory and fine synaptic formation levels. A digital twin model of this mouse, that accurately predicted responses to arbitrary video stimuli, enabled a comprehensive characterization of the function of neurons. We found that neurons with highly correlated responses to natural videos tended to be connected with each other, not only within the same cortical area but also across multiple layers and visual areas, including feedforward and feedback connections, whereas we did not find that orientation preference predicted connectivity. The digital twin model separated each neuron's tuning into a feature component (what the neuron responds to) and a spatial component (where the neuron's receptive field is located). We show that the feature, but not the spatial component, predicted which neurons were connected at the fine synaptic scale. Together, our results demonstrate the "like-to-like" connectivity rule generalizes to multiple connection types, and the rich MICrONS dataset is suitable to further refine a mechanistic understanding of circuit structure and function.

Oligodendrocyte precursor cells ingest axons in the mouse neocortex.

Neurons in the developing brain undergo extensive structural refinement as nascent circuits adopt their mature form. This physical transformation of neurons is facilitated by the engulfment and degradation of axonal branches and synapses by surrounding glial cells, including microglia and astrocytes. However, the small size of phagocytic organelles and the complex, highly ramified morphology of glia have made it difficult to define the contribution of these and other glial cell types to this crucial process. Here, we used large-scale, serial section transmission electron microscopy (TEM) with computational volume segmentation to reconstruct the complete 3D morphologies of distinct glial types in the mouse visual cortex, providing unprecedented resolution of their morphology and composition. Unexpectedly, we discovered that the fine processes of oligodendrocyte precursor cells (OPCs), a population of abundant, highly dynamic glial progenitors, frequently surrounded small branches of axons. Numerous phagosomes and phagolysosomes (PLs) containing fragments of axons and vesicular structures were present inside their processes, suggesting that OPCs engage in axon pruning. Single-nucleus RNA sequencing from the developing mouse cortex revealed that OPCs express key phagocytic genes at this stage, as well as neuronal transcripts, consistent with active axon engulfment. Although microglia are thought to be responsible for the majority of synaptic pruning and structural refinement, PLs were ten times more abundant in OPCs than in microglia at this stage, and these structures were markedly less abundant in newly generated oligodendrocytes, suggesting that OPCs contribute substantially to the refinement of neuronal circuits during cortical development.

Reconstruction of neocortex: Organelles, compartments, cells, circuits, and activity.

We assembled a semi-automated reconstruction of L2/3 mouse primary visual cortex from ∼250 × 140 × 90 µm3 of electron microscopic images, including pyramidal and non-pyramidal neurons, astrocytes, microglia, oligodendrocytes and precursors, pericytes, vasculature, nuclei, mitochondria, and synapses. Visual responses of a subset of pyramidal cells are included. The data are publicly available, along with tools for programmatic and three-dimensional interactive access. Brief vignettes illustrate the breadth of potential applications relating structure to function in cortical circuits and neuronal cell biology. Mitochondria and synapse organization are characterized as a function of path length from the soma. Pyramidal connectivity motif frequencies are predicted accurately using a configuration model of random graphs. Pyramidal cells receiving more connections from nearby cells exhibit stronger and more reliable visual responses. Sample code shows data access and analysis.

FlyWire: online community for whole-brain connectomics.

Due to advances in automated image acquisition and analysis, whole-brain connectomes with 100,000 or more neurons are on the horizon. Proofreading of whole-brain automated reconstructions will require many person-years of effort, due to the huge volumes of data involved. Here we present FlyWire, an online community for proofreading neural circuits in a Drosophila melanogaster brain and explain how its computational and social structures are organized to scale up to whole-brain connectomics. Browser-based three-dimensional interactive segmentation by collaborative editing of a spatially chunked supervoxel graph makes it possible to distribute proofreading to individuals located virtually anywhere in the world. Information in the edit history is programmatically accessible for a variety of uses such as estimating proofreading accuracy or building incentive systems. An open community accelerates proofreading by recruiting more participants and accelerates scientific discovery by requiring information sharing. We demonstrate how FlyWire enables circuit analysis by reconstructing and analyzing the connectome of mechanosensory neurons.

Digital Museum of Retinal Ganglion Cells with Dense Anatomy and Physiology.

When 3D electron microscopy and calcium imaging are used to investigate the structure and function of neural circuits, the resulting datasets pose new challenges of visualization and interpretation. Here, we present a new kind of digital resource that encompasses almost 400 ganglion cells from a single patch of mouse retina. An online "museum" provides a 3D interactive view of each cell's anatomy, as well as graphs of its visual responses. The resource reveals two aspects of the retina's inner plexiform layer: an arbor segregation principle governing structure along the light axis and a density conservation principle governing structure in the tangential plane. Structure is related to visual function; ganglion cells with arbors near the layer of ganglion cell somas are more sustained in their visual responses on average. Our methods are potentially applicable to dense maps of neuronal anatomy and physiology in other parts of the nervous system.

Cardioprotective effect of valsartan in mice with short-term high-salt diet by regulating cardiac aquaporin 1 and angiogenic factor expression.

Hypertension is the most common risk factor for various cardiovascular and cerebrovascular diseases that affects approximately 61 million, or 25% of the population in United States. The dietary salt intake is one of the most important but modifiable factors for hypertension. In the current study, we aim to elucidate the role of aquaporin 1 in high-salt-induced hypertension and cardiac injuries and whether angiotensin II receptor blocker valsartan could ameliorate the effect of high salt on blood pressure. Mice were fed with normal diet, high-salt diet in the presence or absence of valsartan for 4 weeks. The body weight gain, feeding behavior, blood pressure, and cardiac pathology changes were monitored after 4 weeks. The expression of aquaporin 1, vascular endothelial growth factor, transforming growth factor ß1, and basic fibroblast growth factor were analyzed using quantitative real-time polymerase chain reaction, Western blot, and immunohistochemical staining. Valsartan partially reversed the effects of high-salt diet on hypertension, cardiac injuries such as fibrosis and inflammatory cell infiltration, and inhibition of aquaporin 1 and angiogenic factors; valsartan alone did not exert such effects. The current data demonstrated that the reduction of cardiac aquaporin 1 and angiogenic factor expression level might be associated with high-salt-induced hypertension and cardiac injuries in mice, which could be ameliorated by angiotensin II receptor blocker treatment.

In vivo 3D analysis of clavicular kinematics during scapular plane abduction: comparison of dominant and non-dominant shoulders.

The purpose of this study was to evaluate side-to-side differences in three-dimensional clavicle kinematics in normal shoulders during dynamic scapular plane elevation using model-image registration techniques. Twelve healthy males with a mean age of 32 years (range, 27-36 years old) were enrolled in this study. Clavicle rotations were computed with bilateral fluoroscopic images and CT-derived bone models using model-image registration techniques and compared between dominant and nondominant shoulders. There was no difference in retraction between both shoulders. The clavicle in dominant shoulders was less elevated during abduction than in nondominant shoulders (P=0.03). Backward rotation angles of dominant shoulders were significantly smaller than those of nondominant shoulders throughout the activity (P=0.03). Clavicular kinematics during scapular plane abduction were different according to hand-dominance.

In vivo knee kinematics during stair and deep flexion activities in patients with bicruciate substituting total knee arthroplasty.

Orthopedic surgeons and their patients continue to seek better functional outcomes after total knee arthroplasty. The bicruciate substituting (BCS) total knee arthroplasty design has been introduced to achieve more natural knee mechanics. The purpose of this study was to characterize kinematics in knees with BCS arthroplasty during deep flexion and stair activities using fluoroscopy and model-image registration. In 20 patients with 25 BCS knees, we observed average implant flexion of 128° during kneeling and consistent posterior condylar translations with knee flexion. Tibial rotations were qualitatively similar to those observed in the arthritic natural knee. Knee kinematics with BCS arthroplasty were qualitatively more similar to arthritic natural knees than knees with either posterior cruciate-retaining or posterior-stabilized arthroplasty.

In vivo 3-dimensional analysis of scapular kinematics: comparison of dominant and nondominant shoulders.

BACKGROUND: Alterations in scapular motion frequently are seen in association with various shoulder disorders. It is common clinically to compare the pathological shoulder with the contralateral shoulder, in spite of arm dominance, to characterize the disorder. However, there have been few articles that test the underlying assumption that dominant and nondominant shoulders exhibit comparable dynamic kinematics. The purpose of this study was to compare the 3-dimensional (3-D) scapular kinematics of dominant and nondominant shoulders during dynamic scapular plane elevation using 3-D-2-D (2-dimensional) registration techniques. MATERIALS AND METHODS: Twelve healthy males with a mean age of 32 years (range, 27-36) were enrolled in this study. Bilateral fluoroscopic images during scapular plane elevation and lowering were taken, and CT-derived 3-D bone models were matched with the silhouette of the bones in the fluoroscopic images using 3-D-2-D registration techniques. Angular values of the scapula and scapulohumeral rhythm were compared between dominant and nondominant shoulders with statistical analysis. RESULTS: There was a significant difference in upward rotation angles between paired shoulders (P < .001), while significant differences were not found in the other angular values and scapulohumeral rhythm. The dominant scapulae were 10° more downwardly rotated at rest and 4° more upwardly rotated during elevation compared to the nondominant scapulae. DISCUSSION/CONCLUSION: Scapular motion was not the same between dominant and nondominant arms in healthy subjects. The dominant scapula was rotated further downward at rest and reached greater upward rotation with abduction. These differences should be considered in clinical assessment of shoulder pathology.

Accuracy of single-plane fluoroscopy in determining relative position and orientation of total knee replacement components.

The accuracy of estimating the relative pose between knee replacement components, in terms of clinical motion, is important in the study of knee joint kinematics. The objective of this study was to determine the accuracy of the single-plane fluoroscopy method in calculating the relative pose between the femoral component and the tibial component, along knee motion axes, while the components were in motion relative to one another. The kinematics of total knee replacement components were determined in vitro using two simultaneous methods: single-plane fluoroscopic shape matching and an optoelectronic motion tracking system. The largest mean differences in relative pose between the two methods for any testing condition were 2.1°, 0.3°, and 1.1° in extension, abduction, and internal rotation respectively, and 1.3, 0.9, and 1.9 mm in anterior, distal, and lateral translations, respectively. For the optimized position of the components during dynamic trials, the limits of agreement, between which 95% of differences can be expected to fall, were -2.9 to 4.5° in flexion, -0.9 to 1.5° in abduction, -2.4 to 2.1° in external rotation, -2.0 to 3.9 mm in anterior-posterior translation, -2.2 to 0.4mm in distal-proximal translation and -7.2 to 8.6mm in medial-lateral translation. These mean accuracy values and limits of agreement can be used to determine whether the shape-matching approach using single-plane fluoroscopic images is sufficiently accurate for an intended motion tracking application.

In vivo 3D kinematics of normal forearms: analysis of dynamic forearm rotation.

BACKGROUND: Forearm rotation is an indispensable activity of daily living and comprises complex motions with rotational and translational components. It is thought that changes in these motions with injury or disease may affect diagnostic indices. Several studies have assessed in vivo forearm kinematics with static conditions, but dynamic forearm kinematics have not yet been reported. The purpose of this study was to analyze forearm kinematics during dynamic rotation using radiographic 3D-2D registration methods. METHODS: Ten forearms of five healthy males with the mean age of 37 years old were enrolled. Lateral fluoroscopic images were taken during forearm rotation from maximum supination to maximum pronation with their elbows flexed to approximately 45°. Geometric bone models were created from CT scans of the humerus, the radius and the ulna. Three-dimensional kinematics were determined using 3D-2D model registration techniques with the images and models, and the arc of axial rotation of the radius, volar/dorsal translation of the ulna at the distal radioulnar joint and rotation axis of forearm were computed. FINDINGS: The radial rotation arc was 157°. The ulna translated 3.9 mm (SD 1.5mm) dorsally during activity. The rotation axis of the forearm passed through the center of the radial head and the ulnar head at the 1.9 mm (SD 0.7 mm) posterior from its geometric centroid. INTERPRETATION: The posteriorly deviated rotation axis at the ulnar head may result in the ulnar head translating dorsally during pronation. These data provide a basis for objective assessment of pathological forearm function.