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Connecting polymer collapse and the onset of jamming

Physical Review E 2024年第3期109卷 034406-034406页

作者： Alex T. Grigas Aliza Fisher Mark D. Shattuck Corey S. O'Hern Graduate Program in Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA Integrated Graduate Program in Physical and Engineering Biology Yale University New Haven Connecticut 06520 USA Department of Mechanical Engineering and Materials Science Yale University New Haven Connecticut 06520 USA Benjamin Levich Institute and Physics Department The City College of New York New York New York 10031 USA Department of Physics Yale University New Haven Connecticut 06520 USA Department of Applied Physics Yale University New Haven Connecticut 06520 USA

Previous studies have shown that the interiors of proteins are densely packed, reaching packing fractions that are as large as those found for static packings of individual amino-acid-shaped particles. How can the interiors of proteins take on such high packing fractions given that amino acids are connected by peptide bonds and many amino acids are hydrophobic with attractive interactions? We investigate this question by comparing the structural and mechanical properties of collapsed attractive disk-shaped bead-spring polymers to those of three reference systems: static packings of repulsive disks, of attractive disks, and of repulsive disk-shaped bead-spring polymers. We show that the attractive systems quenched to temperatures below the glass transition T≪Tg and static packings of both repulsive disks and bead-spring polymers possess similar interior packing fractions. Previous studies have shown that static packings of repulsive disks are isostatic at jamming onset, i.e., the number of interparticle contacts Nc matches the number of degrees of freedom, which strongly influences their mechanical properties. We find that repulsive polymer packings are hypostatic at jamming onset (i.e., with fewer contacts than degrees of freedom) but are effectively isostatic when including stabilizing quartic modes, which give rise to quartic scaling of the potential energy with displacements along these modes. While attractive disk and polymer packings are often considered hyperstatic with excess contacts over the isostatic number, we identify a definition for interparticle contacts for which they can also be considered as effectively isostatic. As a result, we show that the mechanical properties (e.g., scaling of the potential energy with excess contact number and low-frequency contribution to the density of vibrational modes) of weakly attractive disk and polymer packings are similar to those of isostatic repulsive disk and polymer packings. Our results demonstrate that static

关键词： Jamming Polymer folding Protein folding Single polymer chains

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Dimension reduction of dynamical systems on networks with leading and non-leading eigenvectors of adjacency matrices

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Physical Review Research 2022年第2期4卷 023257-023257页

作者： Naoki Masuda Prosenjit Kundu Department of Mathematics State University of New York at Buffalo New York 14260-2900 USA Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo Buffalo New York 14260-5030 USA

Dimension reduction techniques for dynamical systems on networks are considered to promote our understanding of the original high-dimensional dynamics. One strategy of dimension reduction is to derive a low-dimensional dynamical system whose behavior approximates the observables of the original dynamical system that are weighted linear summations of the state variables at the different nodes. Recently proposed methods use the leading eigenvector of the adjacency matrix of the network as the mixture weights to obtain such observables. In the present study, we explore performances of this type of one-dimensional reductions of dynamical systems on networks when we use non-leading eigenvectors of the adjacency matrix as the mixture weights. Our theory predicts that non-leading eigenvectors can be more efficient than the leading eigenvector and enables us to select the eigenvector minimizing the error. We numerically verify that the optimal non-leading eigenvector outperforms the leading eigenvector for some dynamical systems and networks. We also argue that, despite our theory, it is practically better to use the leading eigenvector as the mixture weights to avoid misplacing the bifurcation point too distantly and to be resistant against dynamical noise.

关键词： Network resilience

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DuFCALF: Enabling Computers to Feel Songs

SSRN

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SSRN 2022年

作者： Mukherjee, Himadri Marciano, Matteo Dhar, Ankita Roy, Kaushik Department of Computer Science West Bengal State University India Gazelien Records Lab Department of Arts and Humanities Music Program New York University Abu Dhabi United Arab Emirates Department of Computational Science Brainware University India

Music recommendation systems have evolved significantly in the past couple of years and have become extremely popular with the advancement of Artificial Intelligence (AI). Such systems categorize songs based on disparate perspectives, like genre, artist, tempo, etc. However, there have been lesser development in the purview of song categorization based on feelings. Songs amplify the mood of a person and often, listeners choose the type of song they want to listen to based on their mood. Hence, modeling the emotional content of songs is crucial. However, this is a challenging affair because songs embody multiple instruments and vocals in a single instance. Each of them is often modulated differently for a better experience for the listeners as well. In this paper, a system is presented to distinguish song clips based on their emotion. The clips were parameterized using two features which were fed to disparate deep networks. Thereafter, a dual feature cross architecture late fusion (DuFCALF) strategy was used to distinguish the moods. Experiments were performed with multitudinous sections of songs and the sadness of songs was captured with over 80% accuracy. © 2022, The Authors. All rights reserved.

关键词： Deep learning

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Enhanced removal of viral aerosols using nanosilver/TiO2-chitosan filters combined with a negative air ionizer

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Journal of Environmental Chemical Engineering 2024年第3期12卷

作者： Dlamini, Wonder Nathi Yao, Ting-Ching Lee, Hsin-Jui Berekute, Abiyu Kerebo Sallah-Ud-Din, Rasham Siregar, Sepridawati Yu, Kuo-Pin Institute of Environmental and Occupational Health Sciences National Yang-Ming Chiao-Tung University Taipei Taiwan Department of International Ph.D. Program in Environmental Sciences and Technology University System of Taiwan Taipei Taiwan Department of Chemistry College of Natural and Computational Sciences Arba Minch University Arbaminch Ethiopia Faculty of Mineral Technology AKPRIND Institute of Science & Technology Yogyakarta Indonesia

The presence of airborne viruses in bioaerosols is a significant and ongoing public health concern. In this context, this study aimed to develop a new filter that integrates nanosilver into a TiO2-chitosan matrix (nano-Ag/TiO2-CS) to inactivate the non-enveloped bacteriophage MS2 as a viral aerosol surrogate. The materials were characterized using various techniques, such as X-ray diffraction (XRD), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HR-TEM), and X-ray photoelectron spectroscopy (XPS). The SEM images showed that the nano-Ag particles were spheres with a high surface area for virus interactions and that the fiber surfaces were covered by nano-Ag, which enhanced contact with viruses. The optimal 5 wt% nano-Ag/TiO2-CS filter combined with a negative air ionizer (NAI) showed the highest viral aerosol removal efficiency, which reached 97 %. The use of an NAI during filtration enhanced the inactivation of the viral aerosols. A long-term antiviral efficacy assessment showed that the nano-Ag/TiO2-CS filter demonstrated robust durability, which is vital for real-world applications. The nanofilter proposed in this work is simple, safe, and cost-effective for inactivating viral aerosols to improve indoor air quality. © 2024 Elsevier Ltd

关键词： Aerosols

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Global variations in critical drought thresholds that impact vegetation

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National science Review 2023年第5期10卷 180-193页

作者： Xiangyi Li Shilong Piao Chris Huntingford Josep Pe?uelas Hui Yang Hao Xu Anping Chen Pierre Friedlingstein Trevor F.Keenan Stephen Sitch Xuhui Wang Jakob Zscheischler Miguel D.Mahecha Sino-French Institute for Earth System Science College of Urban and Environmental SciencesPeking University Key Laboratory of Alpine Ecology and Biodiversity Institute of Tibetan Plateau ResearchCenter for Excellence in Tibetan Earth ScienceChinese Academy of Sciences UK Centre for Ecology and Hydrology CSIC Global Ecology Unit CREAF-CSIC-UAB CREAF Cerdanyola de Vallès Department of Biogeochemical Integration Max Planck Institute for Biogeochemistry Department of Biology Colorado State University Graduate Degree Program in Ecology Colorado State University Department of Mathematics College of Engineering Mathematics and Physical SciencesUniversity of Exeter Laboratoire de Météorologie Dynamique Institut Pierre-Simon LaplaceCNRS-ENS-UPMC-XDépartement de GeósciencesEcole Normale Superieure Earth and Environmental Sciences Area Lawrence Berkeley National Laboratory Department of Environmental Science Policy&ManagementUniversity of California Berkeley Department of Geography College of Life and Environmental SciencesUniversity of Exeter Department of Computational Hydrosystems Helmholtz Centre for Environmental Research—Ufz Remote Sensing Centre for Earth System Research Leipzig University

Identifying the thresholds of drought that,if crossed,suppress vegetation functioning is vital for accurate quantification of how land ecosystems respond to climate variability and *** present a globally applicable framework to identify drought thresholds for vegetation responses to different levels of known soil-moisture deficits using four remotely sensed vegetation proxies spanning *** thresholds identified represent critical inflection points for changing vegetation responses from highly resistant to highly vulnerable in response to drought stress,and as a warning signal for substantial vegetation *** thresholds varied geographically,with much lower percentiles of soil-moisture anomalies in vegetated areas covered by more forests,corresponding to a comparably stronger capacity to mitigate soil water deficit stress in forested ***,those lower thresholds are detected in more humid ***-of-the-art land models,however,overestimated thresholds of soil moisture(*** drought impacts),especially in more humid areas with higher forest covers and arid areas with few forest *** on climate model projections,we predict that the risk of vegetation damage will increase by the end of the twenty-first century in some hotspots like East Asia,Europe,Amazon,southern Australia and eastern and southern *** data-based results will inform projections on future drought impacts on terrestrial ecosystems and provide an effective tool for drought management.

关键词： drought threshold inflection points vegetation response soil moisture drought impacts

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Theoretical insight and molecular recognition of fluconazole molecularly imprinted polymers: a combined computational and experimental analysis

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RSC advances 2025年第24期15卷 19158-19175页

作者： Untung Gunawan Slamet Ibrahim Atthar Luqman Ivansyah Sophi Damayanti Department of Pharmacy School of Medicine and Health Sciences Atma Jaya Catholic University of Indonesia 14440 Indonesia untung.gunawan@atmajaya.ac.id. Faculty of Pharmacy Universitas Jenderal Achmad Yani Cimahi 40531 Indonesia. Instrumentation and Computational Physics Research Group Department of Physics Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung 40132 Indonesia. Master Program in Computational Science Faculty of Mathematics and Natural Science Institut Teknologi Bandung 40132 Indonesia. Department of Pharmacochemistry School of Pharmacy Institut Teknologi Bandung 40132 Indonesia. University Center of Excellence on Artificial Intelligence for Vision Natural Language Processing & Big Data Analytics (U-CoE Al-VLB) Institut Teknologi Bandung 40132 Indonesia.

Insufficient surveillance and diagnosis result in a minimum of 150 million cases of serious fungal infections reported annually. The WHO has compiled a list of priority pathogens to encourage research and investment in fungal infections and antifungal resistance in late 2022. Among these, is classified as a critical pathogen. Fluconazole is widely recognized as an effective medication for the treatment and prevention of both mucosal and invasive candidiasis. Molecularly imprinted polymer (MIP) could enhance separation selectivity in fluconazole bioanalysis. The objective of this research is to develop an MIP for fluconazole by analyzing interactions identified in prior research and incorporating established improvements for MIP synthesis that cannot be observed through laboratory experimentation. Based on binding affinity, intermolecular hydrogen bonds, complexation energy, and thermodynamic characteristics, 2-acrylamido-1-ethanesulfonic acid was chosen as the optimal monomer. The HOMO-LUMO investigation revealed the localization of the orbitals from the guest to the host. The FMO study indicated that chloroform was the most suitable solvent for complex formation. The QTAIM, NBO, and NCI-RDG analyses identified the hydrogen bond formed between the H51 atom of the monomer and the N33 atom of fluconazole, determined to be the most significant hydrogen bond in the host-guest interaction. The interaction energy from multi-monomer interaction showed that a 1 : 6 ratio is the best ratio in forming a pre-polymerization complex between the template and monomer. Based on the findings of this study, it is anticipated that the computational analysis may be utilized for rational design for the enhancement of prior studies and future laboratory investigations.

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

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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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Empowering Optimal Control with Machine Learning: A Perspective from Model Predictive Control

arXiv

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arXiv 2022年

作者： Weinan, E. Han, Jiequn Long, Jihao AI for Science Institute Beijing China Center for Machine Learning Research School of Mathematical Sciences Peking University Beijing China Center for Computational Mathematics Flatiron Institute New York10010 United States Program of Applied and Computational Mathematics Princeton University Princeton08544 United States

Solving complex optimal control problems have confronted computational challenges for a long time. Recent advances in machine learning have provided us with new opportunities to address these challenges. This paper takes model predictive control, a popular optimal control method, as the primary example to survey recent progress that leverages machine learning techniques to empower optimal control solvers. We also discuss some of the main challenges encountered when applying machine learning to develop more robust optimal control algorithms. Copyright © 2022, The Authors. All rights reserved.

关键词： Machine learning

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arXiv

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arXiv 2024年

作者： Chen, Chi-Jane Yi, Haidong Stanley, Natalie Department of Computer Science The University of North Carolina at Chapel Hill Chapel HillNC27599 United States Computational Medicine Program The University of North Carolina at Chapel Hill Chapel HillNC27599 United States Department of Genetics The University of North Carolina at Chapel Hill Chapel HillNC27599 United States

Single-cell technologies enable comprehensive profiling of diverse immune cell-types through the measurement of multiple genes or proteins per individual cell. In order to translate immune signatures assayed from blood or tissue into powerful diagnostics, machine learning approaches are often employed to compute immunological summaries or per-sample featurizations, which can be used as inputs to models for outcomes of interest. Current supervised learning approaches for computing per-sample representations are trained only to accurately predict a single outcome and do not take into account relevant additional clinical features or covariates that are likely to also be measured for each sample. Here, we introduce a novel approach for incorporating measured covariates in optimizing model parameters to ultimately specify per-sample encodings that accurately affect both immune signatures and additional clinical information. Our introduced method CytoCoSet is a set-based encoding method for learning per-sample featurizations, which formulates a loss function with an additional triplet term penalizing samples with similar covariates from having disparate embedding results in per-sample representations. Overall, incorporating clinical covariates enables the learning of encodings for each individual sample that ultimately improve prediction of clinical outcome. Copyright © 2024, The Authors. All rights reserved.

关键词： Self-supervised learning

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Hyperuniformity scaling of maximally random jammed packings of two-dimensional binary disks

arXiv

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arXiv 2024年

作者： Maher, Charles Emmett Torquato, Salvatore Department of Chemistry Princeton University PrincetonNJ08544 United States Department of Physics Princeton University PrincetonNJ08544 United States Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

Jammed (mechanically rigid) polydisperse circular-disk packings in two dimensions (2D) are popular models for structural glass formers. Maximally random jammed (MRJ) states, which are the most disordered packings subject to strict jamming, have been shown to be hyperuniform. The characterization of the hyperuniformity of MRJ circular-disk packings has covered only a very small part of the possible parameter space for the disk-size distributions. Hyperuniform heterogeneous media are those that anomalously suppress large-scale volume-fraction fluctuations compared to those in typical disordered systems, i.e., their spectral densities χV (k) tend to zero as the wavenumber k ≡ |k| tends to zero and are often described by the power-law χV (k) ∼ kα as k → 0 where α is the so-called hyperuniformity scaling exponent. In this work, we generate and characterize the structure of strictly jammed binary circular-disk packings with a size ratio β = DL/DS, where DL and DS are the large and small disk diameters, respectively, and molar ratio of the two disk sizes is 1:1. In particular, by characterizing the rattler fraction φR, the fraction of configurations in an ensemble with fixed β that are isostatic, and the n-fold orientational order metrics n of ensembles of packings with a wide range of size ratios β, we show that size ratios 1.2 β 2.0 produce maximally random jammed (MRJ)-like states, which we show are the most disordered strictly jammed packings according to several criteria. Using the large-R scaling of the volume fraction variance σ2 V (R) associated with a spherical sampling window of radius R, we extract the hyperuniformity scaling exponent α from these packings, and find the function α (β) is maximized at β = 1.4 (with α = 0.450±0.002) within the range 1.2 ≤ β ≤ 2.0. Just outside of this range of β values, α (β) begins to decrease more quickly, and far outside of this range the packings are nonhyperuniform, i.e., α = 0. Moreover, we compute the spectral density χV (k

关键词： Disks (structural components)

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