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Visual learning often occurs in a specific context, where an agent acquires skills through exploration and tracking of its location in a consistent environment. The historical spatial context of the agent provides a similarity signal for self-supervised contrastive learning. We present a unique approach, termed environmental spatial similarity (ESS), that complements existing contrastive learning methods. Using images from simulated, photorealistic environments as an experimental setting, we demonstrate that ESS outperforms traditional instance discrimination approaches. Moreover, sampling additional data from the same environment substantially improves accuracy and provides new augmentations. ESS allows remarkable proficiency in room classification and spatial prediction tasks, especially in unfamiliar environments. This learning paradigm has the potential to enable rapid visual learning in agents operating in new environments with unique visual characteristics. Potentially transformative applications span from robotics to space exploration. Our proof of concept demonstrates improved efficiency over methods that rely on extensive, disconnected datasets.
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Biomaterial-based agents have been demonstrated to regulate the function of immune cells in models of autoimmunity. However, the complexity of the kinetics of immune cell activation can present a challenge in optimizing the dose and frequency of administration. Here, we report a model of autoreactive T cell activation, which are key drivers in autoimmune inflammatory joint disease. The model is termed a multi-scale Agent-Based, Cell-Driven model of Inflammatory Arthritis (ABCD of IA). Using kinetic rate equations and statistical theory, ABCD of IA simulated the activation and presentation of autoantigens by dendritic cells, interactions with cognate T cells and subsequent T cell proliferation in the lymph node and IA-affected joints. The results, validated with in vivo data from the T cell driven SKG mouse model, showed that T cell proliferation strongly correlated with the T cell receptor (TCR) affinity distribution (TCR-ad), with a clear transition state from homeostasis to an inflammatory state. T cell proliferation was strongly dependent on the amount of antigen in antigenic stimulus event (ASE) at low concentrations. On the other hand, inflammation driven by Th17-inducing cytokine mediated T cell phenotype commitment was influenced by the initial level of Th17-inducing cytokines independent of the amount of arthritogenic antigen. The introduction of inhibitory artificial antigen presenting cells (iaAPCs), which locally suppress T cell activation, reduced T cell proliferation in a dose-dependent manner. The findings in this work set up a framework based on theory and modeling to simulate personalized therapeutic strategies in IA.
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Artrite , Camundongos , Animais , Linfócitos T , Autoantígenos , Ativação Linfocitária , Citocinas , Receptores de Antígenos de Linfócitos T/genéticaRESUMO
ABSTRACT: Chimeric antigen receptor (CAR) natural killer (NK) cells can eliminate tumors not only through the ability of the CAR molecule to recognize antigen-expressed cancer cells but also through NK-cell receptors themselves. This overcomes some of the limitations of CAR T cells, paving the way for CAR NK cells for safer and more effective off-the-shelf cellular therapy. In this study, CD70-specific (a pan-target of lymphoma) fourth-generation CAR with 4-1BB costimulatory domain and interleukin-15 (IL-15) was constructed and transduced into cord blood-derived NK cells by Baboon envelope pseudotyped lentiviral vector. CD70-CAR NK cells displayed superior cytotoxic activity in vitro and in vivo against CD19-negative B-cell lymphoma when compared with nontransduced NK cells and CD19-specific CAR NK cells. Importantly, mice that received 2 doses of CD70-CAR NK cells showed effective eradication of tumors, accompanied by increased concentration of plasma IL-15 and enhanced CAR NK cell proliferation and persistence. Our study suggests that repetitive administration-based CAR NK-cell therapy has clinical advantage compared with a single dose of CAR NK cells for the treatment of B-cell lymphoma.
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Antígenos CD19 , Ligante CD27 , Imunoterapia Adotiva , Interleucina-15 , Células Matadoras Naturais , Linfoma de Células B , Receptores de Antígenos Quiméricos , Células Matadoras Naturais/imunologia , Células Matadoras Naturais/metabolismo , Animais , Humanos , Camundongos , Linfoma de Células B/terapia , Linfoma de Células B/imunologia , Receptores de Antígenos Quiméricos/imunologia , Receptores de Antígenos Quiméricos/metabolismo , Receptores de Antígenos Quiméricos/genética , Imunoterapia Adotiva/métodos , Antígenos CD19/imunologia , Ensaios Antitumorais Modelo de Xenoenxerto , Linhagem Celular Tumoral , Citotoxicidade ImunológicaRESUMO
Positron Emission Tomography (PET) is a powerful medical imaging technique widely used for detection and monitoring of disease. However, PET imaging can be adversely affected by patient motion, leading to degraded image quality and diagnostic capability. Hence, motion gating schemes have been developed to monitor various motion sources including head motion, respiratory motion, and cardiac motion. The approaches for these techniques have commonly come in the form of hardware-driven gating and data-driven gating, where the distinguishing aspect is the use of external hardware to make motion measurements vs. deriving these measures from the data itself. The implementation of these techniques helps correct for motion artifacts and improves tracer uptake measurements. With the great impact that these methods have on the diagnostic and quantitative quality of PET images, much research has been performed in this area, and this paper outlines the various approaches that have been developed as applied to whole-body PET imaging.
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The Canadian government aims to achieve a 40-45 % reduction of oil and gas (O&G) methane (CH4) emissions by 2025, and 75 % by 2030, although recent studies consistently show that Canada's federal inventory underestimates emissions by a factor of 1.4 to 2.0. We conducted aerial mass balance measurements at sixteen upstream O&G facilities in Alberta between September 29 and November 6, 2021, and our measurements revealed that emissions were, on average, 1.7 (standard deviation (SD): 0.6) times higher than the reported emissions for the same year. On a subsequent campaign from August 12 to September 27, 2022, we focused on understudied O&G sectors covering 24 midstream and end-use facilities. These sites were found to be emitting, on average, 3.4 (SD: 1.1) times more CH4 than reported. By extrapolating our measurements to Alberta, we found that underground gas storage contributed to 1.6 % of provincial O&G emissions, followed by natural gas power stations/refineries less than 1.0 %. The widespread underreporting of CH4 emissions highlights the necessity for more empirical measurements of midstream and end-use facilities.
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The prostacyclin (PGI2) receptor (IP) is a Gs-coupled receptor associated with blood pressure regulation, allergy, and inflammatory response. It is a main therapeutic target for pulmonary arterial hypertension (PAH) and several other diseases. Here we report cryo-electron microscopy (cryo-EM) structures of the human IP-Gs complex bound with two anti-PAH drugs, treprostinil and MRE-269 (active form of selexipag), at global resolutions of 2.56 and 2.41 angstrom, respectively. These structures revealed distinct features governing IP ligand binding, receptor activation, and G protein coupling. Moreover, comparison of the activated IP structures uncovered the mechanism and key residues that determine the superior selectivity of MRE-269 over treprostinil. Combined with molecular docking and functional studies, our structures provide insight into agonist selectivity, ligand recognition, receptor activation, and G protein coupling. Our results provide a structural template for further improving IP-targeting drugs to reduce off-target activation of prostanoid receptors and adverse effects.
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Acetatos , Anti-Hipertensivos , Proteínas de Ligação ao GTP , Pirazinas , Humanos , Anti-Hipertensivos/farmacologia , Anti-Hipertensivos/uso terapêutico , Microscopia Crioeletrônica , Ligantes , Simulação de Acoplamento Molecular , Receptores de Epoprostenol/agonistasRESUMO
Regulatory T (Treg) cells play a critical regulatory role in the immune system by suppressing excessive immune responses and maintaining immune balance. The effective migration of Treg cells is crucial for controlling the development and progression of inflammatory diseases. However, the mechanisms responsible for directing Treg cells into the inflammatory tissue remain incompletely elucidated. In this study, we identified BAF60b, a subunit of switch/sucrose nonfermentable (SWI/SNF) chromatin remodeling complexes, as a positive regulator of Treg cell migration that inhibits the progression of inflammation in experimental autoimmune encephalomyelitis (EAE) and colitis animal models. Mechanistically, transcriptome and genome-wide chromatin-landscaped analyses demonstrated that BAF60b interacts with the transcription factor RUNX1 to promote the expression of CCR9 on Treg cells, which in turn affects their ability to migrate to inflammatory tissues. Our work provides insights into the essential role of BAF60b in regulating Treg cell migration and its impact on inflammatory diseases.
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Movimento Celular , Inflamação , Camundongos Endogâmicos C57BL , Linfócitos T Reguladores , Linfócitos T Reguladores/imunologia , Linfócitos T Reguladores/metabolismo , Animais , Camundongos , Inflamação/patologia , Inflamação/metabolismo , Montagem e Desmontagem da Cromatina , Proteínas Cromossômicas não Histona/metabolismo , Encefalomielite Autoimune Experimental/imunologia , Encefalomielite Autoimune Experimental/patologia , Encefalomielite Autoimune Experimental/metabolismo , Encefalomielite Autoimune Experimental/genética , Humanos , Fatores de Transcrição/metabolismo , Subunidade alfa 2 de Fator de Ligação ao Core/metabolismo , Subunidade alfa 2 de Fator de Ligação ao Core/genética , Colite/metabolismo , Colite/patologia , Colite/imunologia , Colite/genéticaRESUMO
We apply spatial transcriptomics and proteomics to select pancreatic cancer surface receptor targets for molecular imaging and theranostics using an approach that can be applied to many cancers. Selected cancer surfaceome epithelial markers were spatially correlated and provided specific cancer localization, whereas the spatial correlation between cancer markers and immune- cell or fibroblast markers was low. While molecular imaging of cancer-associated fibroblasts and integrins has been proposed for pancreatic cancer, our data point to the tight junction protein claudin-4 as a theranostic target. Claudin-4 expression increased â¼16 fold in cancer as compared with normal pancreas, and the tight junction localization conferred low background for imaging in normal tissue. We developed a peptide-based molecular imaging agent targeted to claudin-4 with accumulation to â¼25% injected activity per cc (IA/cc) in metastases and â¼18% IA/cc in tumors. Our work motivates a new approach for data-driven selection of molecular targets.
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Tendon injuries, while prevalent, present significant challenges regarding their structural and functional restoration. Utilizing alpha-smooth muscle actin (α-SMA)-Ai9-scleraxis (Scx)-green fluorescent protein (GFP) transgenic mice, which exhibit both Scx (a tendon cell marker) and α-SMA (a myofibroblast marker), we explored the effects of metformin (Met) on tendon healing, repair, and its mechanisms of action. Our findings revealed that intraperitoneal (IP) injections of Met, administered before or after injury, as well as both, effectively prevented the release of HMGB1 into the tendon matrix and reduced circulating levels of HMGB1. Additionally, Met treatment increased and activated AMPK and suppressed TGF-ß1 levels within the healing tendon. Tendon healing was also improved by blocking the migration of α-SMA+ myofibroblasts, reducing the prevalence of disorganized collagen fibers and collagen type III. It also enhanced the presence of collagen type I. These outcomes highlight Met's anti-fibrotic properties in acutely injured tendons and suggest its potential for repurposing as a therapeutic agent to minimize scar tissue formation in tendon injuries, which could have profound implications in clinical practice.
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Specific learning disability of reading, or dyslexia, affects 5-17% of the population in the United States. Research on the neurobiology of dyslexia has included studies with relatively small sample sizes across research sites, thus limiting inference and the application of novel methods, such as deep learning. To address these issues and facilitate open science, we developed an online platform for data-sharing and advanced research programs to enhance opportunities for replication by providing researchers with secondary data that can be used in their research (https://www.dyslexiadata.org). This platform integrates a set of well-designed machine learning algorithms and tools to generate secondary datasets, such as cortical thickness, as well as regional brain volume metrics that have been consistently associated with dyslexia. Researchers can access shared data to address fundamental questions about dyslexia and development, replicate research findings, apply new methods, and educate the next generation of researchers. The overarching goal of this platform is to advance our understanding of a disorder that has significant academic, social, and economic impacts on children, their families, and society.
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The placenta is a valuable organ that can aid in understanding adverse events during pregnancy and predicting issues post-birth. Manual pathological examination and report generation, however, are laborious and resource-intensive. Limitations in diagnostic accuracy and model efficiency have impeded previous attempts to automate placenta analysis. This study presents a novel framework for the automatic analysis of placenta images that aims to improve accuracy and efficiency. Building on previous vision-language contrastive learning (VLC) methods, we propose two enhancements, namely Pathology Report Feature Recomposition and Distributional Feature Recomposition, which increase representation robustness and mitigate feature suppression. In addition, we employ efficient neural networks as image encoders to achieve model compression and inference acceleration. Experiments validate that the proposed approach outperforms prior work in both performance and efficiency by significant margins. The benefits of our method, including enhanced efficacy and deployability, may have significant implications for reproductive healthcare, particularly in rural areas or low- and middle-income countries.
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Nature harnesses exquisite enzymatic cascades to construct N-heterocycles and further uses these building blocks to assemble the molecules of life. Here we report an enzymatic platform to construct important chiral N-heterocyclic products, pyrrolidines and indolines, via abiological intramolecular C(sp3)-H amination of organic azides. Directed evolution of cytochrome P411 (a P450 enzyme with serine as the heme-ligating residue) yielded variant P411-PYS-5149, capable of catalyzing the insertion of alkyl nitrene into C(sp3)-H bonds to build pyrrolidine derivatives with good enantioselectivity and catalytic efficiency. Further evolution of activity on aryl azide substrates yielded variant P411-INS-5151 that catalyzes intramolecular C(sp3)-H amination to afford chiral indolines. In addition, we show that these enzymatic aminations can be coupled with a P411-based carbene transferase or a tryptophan synthase to generate an α-amino lactone or a noncanonical amino acid, respectively, underscoring the power of new-to-nature biocatalysis in complexity-building chemical synthesis.
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Acute and chronic tendon injuries(i.e.tendinopathy)are common,yet current treatments cannot restore normal structure and function to injured tendons.This problem mainly stems from our incomplete understanding of tendon cell properties and responses to biomechanical and biochemical environments surrounding the cells.However,significant progress has been made in recent years on two fronts.The first is the new discovery that tendons contain a population of multi-potent tendon stem cells(TSCs).The second is the wide application of platelet-rich plasma(PRP)in orthopaedics and sports medicine to treat injured tendons.This mini-review aims to discuss the studies on TSCs,with a focus on their differential properties with respect to tenocytes and their differential mechano-responses when subjected to small and large mechanical loading conditions.In light of the critical importance of the safety and efficacy of PRP treatment in clinic,basic scientific research related to PRP effects on TSCs,particularly on their differentiation,is also presented.Finally,the urgent need for rigorous basic scientific research to justify PRP applications in clinic settings is proposed.