Search for: All records

The diverse T cell receptor (TCR) repertoire confers the ability to recognize an almost unlimited array of antigens. Characterization of antigen specificity of tumor-infiltrating lymphocytes (TILs) is key for understanding antitumor immunity and for guiding the development of effective immunotherapies. Here, we report a large-scale comprehensive examination of the TCR landscape of TILs across the spectrum of pediatric brain tumors, the leading cause of cancer-related mortality in children. We show that a T cell clonality index can inform patient prognosis, where more clonality is associated with more favorable outcomes. Moreover, TCR similarity groups’ assessment revealed patient clusters with defined human leukocyte antigen associations. Computational analysis of these clusters identified putative tumor antigens and peptides as targets for antitumor T cell immunity, which were functionally validated by T cell stimulation assays in vitro. Together, this study presents a framework for tumor antigen prediction based on in situ and in silico TIL TCR analyses. We propose that TCR-based investigations should inform tumor classification and precision immunotherapy development. 

The functional connectome supports information transmission through the brain at various spatial scales, from exchange between broad cortical regions to finer-scale, vertex-wise connections that underlie specific information processing mechanisms. In adults, while both the coarse- and fine-scale functional connectomes predict cognition, the fine scale can predict up to twice the variance as the coarse-scale functional connectome. Yet, past brain-wide association studies, particularly using large developmental samples, focus on the coarse connectome to understand the neural underpinnings of individual differences in cognition. Using a large cohort of children (age 9–10 years;n = 1,115 individuals; both sexes; 50% female, including 170 monozygotic and 219 dizygotic twin pairs and 337 unrelated individuals), we examine the reliability, heritability, and behavioral relevance of resting-state functional connectivity computed at different spatial scales. We use connectivity hyperalignment to improve access to reliable fine-scale (vertex-wise) connectivity information and compare the fine-scale connectome with the traditional parcel-wise (coarse scale) functional connectomes. Though individual differences in the fine-scale connectome are more reliable than those in the coarse-scale, they are less heritable. Further, the alignment and scale of connectomes influence their ability to predict behavior, whereby some cognitive traits are equally well predicted by both connectome scales, but other, less heritable cognitive traits are better predicted by the fine-scale connectome. Together, our findings suggest there are dissociable individual differences in information processing represented at different scales of the functional connectome which, in turn, have distinct implications for heritability and cognition. 

Irrespective of the many strategies focused on dealing with spinal cord injury (SCI), there is still no way to restore motor function efficiently or an adequate regenerative therapy. One promising method that could potentially prove highly beneficial for rehabilitation in patients is to re-engage specific neuronal populations of the spinal cord following SCI. Targeted activation may maintain and strengthen existing neuronal connections and/or facilitate the reorganization and development of new connections. BioLuminescent-OptoGenetics (BL-OG) presents an avenue to non-invasively and specifically stimulate neurons; genetically targeted neurons express luminopsins (LMOs), light-emitting luciferases tethered to light-sensitive channelrhodopsins that are activated by adding the luciferase substrate coelenterazine (CTZ). This approach employs ion channels for current conduction while activating the channels through treatment with the small molecule CTZ, thus allowing non-invasive stimulation of all targeted neurons. We previously showed the efficacy of this approach for improving locomotor recovery following severe spinal cord contusion injury in rats expressing the excitatory luminopsin 3 (LMO3) under control of a pan-neuronal and motor-neuron-specific promoter with CTZ applied through a lateral ventricle cannula. The goal of the present study was to test a new generation of LMOs based on opsins with higher light sensitivity which will allow for peripheral delivery of the CTZ. In this construct, the slow-burn Gaussia luciferase variant (sbGLuc) is fused to the opsin CheRiff, creating LMO3.2. Taking advantage of the high light sensitivity of this opsin, we stimulated transduced lumbar neurons after thoracic SCI by intraperitoneal application of CTZ, allowing for a less invasive treatment. The efficacy of this non-invasive BioLuminescent-OptoGenetic approach was confirmed by improved locomotor function. This study demonstrates that peripheral delivery of the luciferin CTZ can be used to activate LMOs expressed in spinal cord neurons that employ an opsin with increased light sensitivity. 

Abstract Part quality manufactured by the laser powder bed fusion process is significantly affected by porosity. Existing works of process–property relationships for porosity prediction require many experiments or computationally expensive simulations without considering environmental variations. While efforts that adopt real-time monitoring sensors can only detect porosity after its occurrence rather than predicting it ahead of time. In this study, a novel porosity detection-prediction framework is proposed based on deep learning that predicts porosity in the next layer based on thermal signatures of the previous layers. The proposed framework is validated in terms of its ability to accurately predict lack of fusion porosity using computerized tomography (CT) scans, which achieves a F1-score of 0.75. The framework presented in this work can be effectively applied to quality control in additive manufacturing. As a function of the predicted porosity positions, laser process parameters in the next layer can be adjusted to avoid more part porosity in the future or the existing porosity could be filled. If the predicted part porosity is not acceptable regardless of laser parameters, the building process can be stopped to minimize the loss. 

Human cortex is patterned by a complex and interdigitated web of large-scale functional networks. Recent methodological breakthroughs reveal variation in the size, shape, and spatial topography of cortical networks across individuals. While spatial network organization emerges across development, is stable over time, and is predictive of behavior, it is not yet clear to what extent genetic factors underlie interindividual differences in network topography. Here, leveraging a nonlinear multidimensional estimation of heritability, we provide evidence that individual variability in the size and topographic organization of cortical networks are under genetic control. Using twin and family data from the Human Connectome Project ( n = 1,023), we find increased variability and reduced heritability in the size of heteromodal association networks ( h 2 : M = 0.34, SD = 0.070), relative to unimodal sensory/motor cortex ( h 2 : M = 0.40, SD = 0.097). We then demonstrate that the spatial layout of cortical networks is influenced by genetics, using our multidimensional estimation of heritability ( h 2 - multi; M = 0.14, SD = 0.015). However, topographic heritability did not differ between heteromodal and unimodal networks. Genetic factors had a regionally variable influence on brain organization, such that the heritability of network topography was greatest in prefrontal, precuneus, and posterior parietal cortex. Taken together, these data are consistent with relaxed genetic control of association cortices relative to primary sensory/motor regions and have implications for understanding population-level variability in brain functioning, guiding both individualized prediction and the interpretation of analyses that integrate genetics and neuroimaging. 

Abstract Materials in single crystal form are often sought after because the absence of grain boundaries can result in unique properties relative to the polycrystal, but producing these materials is typically a slow and complex process. In this work, pseudo single crystals of the pseudobrookite compound CoTi₂O₅were synthesized by solid‐state reaction from a duplex grain mixture of CoTiO₃and TiO₂. The size of the crystallites was >250 µm. The transformation and subsequent microstructural evolution of the CoTi₂O₅was studied by scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), transmission electron microscopy (TEM), scanning transmission electron microscopy (STEM), and X‐ray diffraction (XRD). A novel growth mechanism was identified whereby a single crystal CoTi₂O₅front advances simultaneously along multiple CoTiO₃/TiO₂diphasic boundaries. The single crystal domains were composed of subgrains approximately 5 µm in diameter; differences in the subgrain size and misorientation were related to the growth mechanism and the initial grain size of the duplex CoTiO₃–TiO₂mixture. CoTi₂O₅is a little characterized compound, and this study represents the most significant microstructural study of CoTi₂O₅to date. The findings may be applied to similar pseudobrookite compounds such as MgTi₂O₅and Al₂TiO₅.