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Molecular Mechanisms Promoting Long-Term Cytopenia after BCMA CAR-T Therapy in Multiple Myeloma

BLOOD 2024年 144卷 4798-4799页

作者： [Anonymous] Hematology and Cell Therapy Department. Clinica Universidad de Navarra. IdiSNA. Pamplona Spain Hemato-Oncology Program. Cima Universidad de Navarra. IdiSNA. Pamplona Spain Computational Biology Program. Cima Universidad de Navarra. IdiSNA. Pamplona Spain Immunology and Immunotherapy Department. Clinica Universidad de Navarra. Pamplona Spain Centro de Investigación Biomedica en Red de Cancer (CIBERONC). Madrid Spain Cancer Center Clinica Universidad de Navarra (CCUN). Pamplona Spain Cancer Center Clinica Universidad de Navarra (CCUN) Pamplona Spain Immunology and Immunotherapy Program. Cima Universidad de Navarra. IdiSNA. Pamplona Spain Center for Data Science and Artificial Intelligence Institute (DATAI) Universidad de Navarra Pamplona Pamplona Spain Hematology and Cell Therapy Department Clinica Universidad de Navarra IdiSNA Pamplona Spain Centro de Investigación Biomedica en Red de Cancer (CIBERONC) Madrid Spain

Hematologic toxicity, specifically prolonged cytopenia, is a common side effect associated with CAR-T therapies, being particularly severe in patients with relapsed/refractory Multiple Myeloma (MM) (1). However, to date, its etiology is poorly understood. Thus, the main objective of this study was to identify and understand the underlying mechanisms of prolonged cytopenias associated with CAR-T therapy targeting BCMA. In our work, we combined the retrospective analysis of a cohort of 48 patients treated with BCMA CAR-T cells at Clinica Universidad de Navarra, with ex vivo transcriptomic analysis using single-cell RNA sequencing, to characterize the kinetics of cytopenia, identify predictive factors and determine potential mechanism underlying these toxicities. The overall incidence of cytopenia was 95.7%, and grade>3 thrombocytopenia and neutropenia one month after infusion, was observed in 57% and 53% of the patients, being still present after one year in 4 and 3 patients respectively. Presence of cytopenia at baseline and high peak inflammatory markers highly correlated with cytopenia persisting up to three months. To determine potential mechanisms underpinning cytopenias, we evaluated the paracrine effect of BCMA CAR-T cells on HSPCs differentiation, using an ex vivo myeloid differentiation model (2). Thus, supernatants from CAR-T cells or control T lymphocytes, co-cultured with MM tumor cell line U266, were added to the differentiation process. Phenotypic analysis by flow cytometry showed that supernatants from activated CAR-T cells (spCAR) halted HSPCs differentiation, promoting more immature phenotypes, with reduced expression of granulocytic, monocytic, and erythroid maturation markers, suggesting a paracrine effect related to CAR-T cells activation. Interestingly, this immature phenotype could be prevented by a combination of IFNγ, TNFα/β, TGFβ, IL-6, and IL-17 inhibitors, indicating the essential role of these cytokines and providing potential targets to pr

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Estimating international trade status of countries from global liner shipping networks

arXiv

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arXiv 2020年

作者： Xu, Mengqiao Pan, Qian Xia, Haoxiang Masuda, Naoki School of Economics and Management Dalian University of Technology No. 2 Linggong Road Ganjingzi District Dalian City Liaoning Province116024 China Department of Mathematics University at Buffalo BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-5030 United States

Maritime shipping is a backbone of international trade and thus the world economy. Vessels travel from a port of one country to another on networks of ports to carry cargos, which contribute to countries’ international trade values. We hypothesize that ports that involve transshipment activities serve as a third-party middleman to mediate trade between two foreign countries and contribute to the corresponding country's status in international trade. We test this hypothesis using a port-level data set of global liner shipping services. We propose two indices that quantify the importance of countries in the global liner shipping network and show that they explain a large amount of variation in the international trade value and related measures of individual countries. These results support a long-standing view in maritime economics, which has yet been directly tested, that countries that are strongly integrated into the global maritime transportation network have enhanced access to global markets and trade opportunities. Copyright © 2020, The Authors. All rights reserved.

关键词： International trade

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Cell2Sentence: Teaching Large Language Models the Language of Biology 41

Cell2Sentence: Teaching Large Language Models the Language o...

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41st International Conference on Machine Learning, ICML 2024

作者： Levine, Daniel Rizvi, Syed Asad Lévy, Sacha Pallikkavaliyaveetil, Nazreen Zhang, David Chen, Xingyu Ghadermarzi, Sina Wu, Ruiming Zheng, Zihe Vrkic, Ivan Zhong, Anna Raskin, Daphne Han, Insu de Oliveira Fonseca, Antonio Henrique Caro, Josue Ortega Karbasi, Amin Dhodapkar, Rahul M. van Dijk, David Department of Computer Science Yale University New HavenCT United States School of Engineering Applied Science University of Pennsylvania PhiladelphiaPA United States School of Computer and Communication Sciences Swiss Federal Institute of Technology Lausanne Lausanne Switzerland Department of Neuroscience Yale School of Medicine New HavenCT United States Wu Tsai Institute Yale University New HavenCT United States Google United States Yale Institute for Foundations of Data Science New HavenCT United States Yale School of Engineering and Applied Science New HavenCT United States Roski Eye Institute University of Southern California Los AngelesCA United States Yale School of Medicine New HavenCT United States Cardiovascular Research Center Yale School of Medicine New HavenCT United States Interdepartmental Program in Computational Biology & Bioinformatics Yale University New HavenCT United States

We introduce Cell2Sentence (C2S), a novel method to directly adapt large language models to a biological context, specifically single-cell transcriptomics. By transforming gene expression data into"cell sentences," C2S bridges the gap between natural language processing and biology. We demonstrate cell sentences enable the finetuning of language models for diverse tasks in biology, including cell generation, complex cell-type annotation, and direct data-driven text generation. Our experiments reveal that GPT-2, when fine-tuned with C2S, can generate biologically valid cells based on cell type inputs, and accurately predict cell types from cell sentences. This illustrates that language models, through C2S finetuning, can acquire a significant understanding of single-cell biology while maintaining robust text generation capabilities. C2S offers a flexible, accessible framework to integrate natural language processing with transcriptomics, utilizing existing models and libraries for a wide range of biological applications. Copyright 2024 by the author(s)

关键词： Gene expression

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Higher-order rich-club phenomenon in collaborative research grant networks

arXiv

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arXiv 2022年

作者： Nakajima, Kazuki Shudo, Kazuyuki Masuda, Naoki Department of Mathematical and Computing Science Tokyo Institute of Technology Meguro-ku Tokyo152-8552 Japan Department of Mathematics State University of New York at Buffalo Buffalo14260 United States Academic Center for Computing and Media Studies Kyoto University Sakyo-ku Kyoto606-8501 Japan Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo Buffalo14260 United States Faculty of Science and Engineering Waseda University Tokyo169-8555 Japan

Modern scientific work, including writing papers and submitting research grant proposals, increasingly involves researchers from different institutions. In grant collaborations, it is known that institutions involved in many collaborations tend to densely collaborate with each other, forming rich clubs. Here we investigate higher-order rich-club phenomena in networks of collaborative research grants among institutions and their associations with research impact. Using publicly available data from the National science Foundation in the US, we construct a bipartite network of institutions and collaborative grants, which distinguishes among the collaboration with different numbers of institutions. By extending the concept and algorithms of the rich club for dyadic networks to the case of bipartite networks, we find rich clubs both in the entire bipartite network and the bipartite subnetwork induced by the collaborative grants involving a given number of institutions up to five. We also find that the collaborative grants within rich clubs tend to be more productive in a per-dollar sense than the control. Our results highlight advantages of collaborative grants among the institutions in the rich clubs. Copyright © 2022, The Authors. All rights reserved.

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Epileptic seizure detection

Epileptic seizure detection

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作者： Schuyler, Ronald White, Andrew Staley, Kevin Cios, Krzysztof J. Computational Bioscience Ph.D. Program UCDHSC United States University of Colorado United States American Epilepsy Society Society for Neuroscience United States Department of Neurology Massachusetts General Hospital Harvard Medical School United States Staley Lab. United States University of Colorado at Denver Health Sciences Center United States University of Colorado Bioenergetics Institute United States Data Mining and Bioinformatics Laboratory Turkey Polish Academy of Arts and Sciences Poland Dept. of Computer Science and Engineering University of Colorado at Denver Health Sciences Center P.O. Box 173364 Denver CO 80217-3364 United States

No abstract available

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A growth model for water distribution networks with loops

arXiv

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arXiv 2021年

作者： Sugishita, Kashin Abdel-Mottaleb, Noha Zhang, Qiong Masuda, Naoki Department of Mathematics State University of New York at Buffalo BuffaloNY14260-2900 United States Department of Transdisciplinary Science and Engineering Tokyo Institute of Technology Tokyo152-8550 Japan Department of Civil and Environmental Engineering University of South Florida TampaFL33620 United States Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY14260-5030 United States Faculty of Science and Engineering Waseda University Tokyo169-8555 Japan

Water distribution networks (WDNs) expand their service areas over time. These growth dynamics are poorly understood. One facet of WDNs is that they have loops in general, and closing loops may be a functionally important process for enhancing their robustness and efficiency. We propose a growth model for WDNs which generates networks with loops and is applicable to networks with multiple water sources. We apply the proposed model to four empirical WDNs to show that it produces networks whose structure is similar to that of the empirical WDNs. The comparison between the empirical and modeled WDNs suggests that the empirical WDNs may realize a reasonable balance between cost, efficiency, and robustness in terms of the network structure. We also study the design of pipe diameters based on a biological positive feedback mechanism. Specifically, we apply a model inspired by Physarum polycephalum to find moderate positive correlations between the empirical and modeled pipe diameters. The difference between the empirical and modeled pipe diameters suggests that we may be able to improve the performance of WDNs by following organizing principles of biological flow networks. Copyright © 2021, The Authors. All rights reserved.

关键词： Water distribution systems

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相关性和一致性:这对相仿概念和测量方法的回顾与阐明（英文）

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上海精神医学 2016年第2期28卷 115-120页

作者： Liu JY Tang W Chen GQ Lu Y Feng CY Tu XM Department of Biostatistics and Computational Biology University of Rochester Rochester NY USA Department of Biostatistics & Bioinformatics School of Public Health and Tropical Medicine Tulane University New Orleans LA USA VA Cooperative Studies Program Palo Alto Coordinating Center VA Palo Alto Health Care System Palo Alto CA USA Department of Biomedical Data Science Stanford University Stanford CA USA

一致性(agreement)和相关性(correlation)是两个广泛使用的概念,用来评估变量之间的关联。虽然二者相似且相关,但是它们代表关联完全不同的概念。评估变量之间的一致性假设变量测量的是相同的结构,而在变量测量完全不同的结构时也可以... 详细信息

一致性(agreement)和相关性(correlation)是两个广泛使用的概念,用来评估变量之间的关联。虽然二者相似且相关,但是它们代表关联完全不同的概念。评估变量之间的一致性假设变量测量的是相同的结构,而在变量测量完全不同的结构时也可以评估它们之间的相关性。这种概念上的差异就要求使用不同的统计方法,并且当评估一致性或相关性时,统计方法根据数据的分布和研究者的兴趣可能会有所不同。例如,Pearson相关性,作为评估连续变量之间相关性的一种普遍测量方法,只有用于符合线性关系的变量时才能提供有用的信息;当用于不符合线性关系的变量时就无法提供准确信息甚至会产生误导。同样地,内部相关性,作为一种评估连续变量之间一致性的常用方法,如果一致性不好的实质正好是研究兴趣所在,那么该测量就不能为研究者提供充分的信息。本报告回顾了一致性和相关性的概念,并讨论了几种常用方法在应用中的差异。

关键词：积差相关性内部一致性 Kendall's tau 非线性相关 Pearson's相关性 Spearman's rho

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Critical mass effect in evolutionary games triggered by zealots

arXiv

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arXiv 2019年

作者： Cardillo, Alessio Masuda, Naoki Department of Engineering Mathematics University of Bristol BristolBS8 1UB United Kingdom Department of Computer Science and Mathematics University Rovira i Virgili TarragonaE-43007 Spain University of Zaragoza ZaragozaE-50018 Spain Department of Mathematics University at Buffalo BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-5030 United States

Tiny perturbations may trigger large responses in systems near criticality, shifting them across equilibria. Committed minorities are suggested to be responsible for the emergence of collective behaviors in many physical, social, and biological systems. Using evolutionary game theory, we address the question whether a finite fraction of zealots can drive the system to large-scale coordination. We find that a tipping point exists in coordination games, whereas the same phenomenon depends on the selection pressure, update rule, and network structure in other types of games. Our study paves the way to understand social systems driven by the individuals’ benefit in presence of zealots, such as human vaccination behavior or cooperative transports in animal groups. Copyright © 2019, The Authors. All rights reserved.

关键词： Game theory

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Opinion dynamics on tie-decay networks

arXiv

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arXiv 2020年

作者： Sugishita, Kashin Porter, Mason A. Beguerisse-Díaz, Mariano Masuda, Naoki Department of Mathematics State University of New York at Buffalo BuffaloNY14260-2900 United States Department of Mathematics University of California Los AngelesCA90095 United States Mathematical Institute University of Oxford OxfordOX2 6GG United Kingdom Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo BuffaloNY14260-5030 United States Faculty of Science and Engineering Waseda University Tokyo169-8555 Japan

In social networks, interaction patterns typically change over time. We study opinion dynamics on tie-decay networks in which tie strength increases instantaneously when there is an interaction and decays exponentially between interactions. Specifically, we formulate continuous-time Laplacian dynamics and a discrete-time DeGroot model of opinion dynamics on these tie-decay networks, and we carry out numerical computations for the continuous-time Laplacian dynamics. We examine the speed of convergence by studying the spectral gaps of combinatorial Laplacian matrices of tie-decay networks. First, we compare the spectral gaps of the Laplacian matrices of tie-decay networks that we construct from empirical data with the spectral gaps for corresponding randomized and aggregate networks. We find that the spectral gaps for the empirical networks tend to be smaller than those for the randomized and aggregate networks. Second, we study the spectral gap as a function of the tie-decay rate and time. Intuitively, we expect small tie-decay rates to lead to fast convergence because the influence of each interaction between two nodes lasts longer for smaller decay rates. Moreover, as time progresses and more interactions occur, we expect eventual convergence. However, we demonstrate that the spectral gap need not decrease monotonically with respect to the decay rate or increase monotonically with respect to time. Our results highlight the importance of the interplay between the times that edges strengthen and decay in temporal networks. Copyright © 2020, The Authors. All rights reserved.

关键词： Laplace transforms

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Interplay between k-core and community structure in complex networks

arXiv

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arXiv 2020年

作者： Malvestio, Irene Cardillo, Alessio Masuda, Naoki Department of Engineering Mathematics University of Bristol BristolBS8 1UB United Kingdom Department of Computer Science and Mathematics University Rovira i Virgili TarragonaE-43007 Spain University of Zaragoza ZaragozaE-50018 Spain Department of Mathematics University at Buffalo BuffaloNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York BuffaloNY14260-5030 United States

The organisation of a network in a maximal set of nodes having at least k neighbours within the set, known as k-core decomposition, has been used for studying various phenomena. It has been shown that nodes in the innermost k-shells play a crucial role in contagion processes, emergence of consensus, and resilience of the system. It is known that the k-core decomposition of many empirical networks cannot be explained by the degree of each node alone, or equivalently, random graph models that preserve the degree of each node (i.e., configuration model). Here we study the k-core decomposition of some empirical networks as well as that of some randomised counterparts, and examine the extent to which the k-shell structure of the networks can be accounted for by the community structure. We find that preserving the community structure in the randomisation process is crucial for generating networks whose k-core decomposition is close to the empirical one. We also highlight the existence, in some networks, of a concentration of the nodes in the innermost k-shells into a small number of communities. Copyright © 2020, The Authors. All rights reserved.

关键词： Complex networks

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