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Molecular docking simulation of interaction between insulin and silica nanoparticle 2

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Molecular docking simulation of interaction between insulin ...

2nd Annual Conference of science and Technology, ANCOSET 2020

作者： Hertadi, R. Ivansyah, A.L. Biochemistry Research Group Department of Chemistry Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jl. Ganesha No. 10 Bandung40132 Indonesia Master Program in Computational Science Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jl. Ganesha No. 10 Bandung40132 Indonesia Analytical Chemistry Research Group Department of Chemistry Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jl. Ganesha No. 10 Bandung40132 Indonesia

Molecular docking simulation has been done in this research by using Hex version 8.0 software package, respectively, to explore the interaction between insulin and silica nanoparticle. Silica nanoparticle acts as receptor and insulin acts as ligand in this research. It was found that insulin form more stable interaction when it is in the pore of silica nanochannel than on the surface of silica nanosheet. Insulin prefer to interact with silica atoms than oxygen atoms in the pore of silica nanochannel © Published under licence by IOP Publishing Ltd.

关键词： Insulin

Machine learning based non-Newtonian fluid model with molecular fidelity

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arXiv 2020年

作者： Lei, Huan Wu, Lei Weinan, E. Department of Computational Mathematics Science & Engineering Department of Statistics & Probability Michigan State University MI48824 United States Department of Mathematics and Program in Applied and Computational Mathematics Princeton University NJ08544 United States

We introduce a machine-learning-based framework for constructing continuum non-Newtonian fluid dynamics model directly from a micro-scale description. Polymer solution is used as an example to demonstrate the essential ideas. To faithfully retain molecular fidelity, we establish a micro-macro correspondence via a set of encoders for the micro-scale polymer configurations and their macro-scale counterparts, a set of nonlinear conformation tensors. The dynamics of these conformation tensors can be derived from the micro-scale model and the relevant terms can be parametrized using machine learning. The final model, named the deep non-Newtonian model (DeePN2), takes the form of conventional non-Newtonian fluid dynamics models, with a new form of the objective tensor derivative. Numerical results demonstrate the accuracy of DeePN2. Copyright © 2020, The Authors. All rights reserved.

关键词： Viscous flow

Conserved expression of the zebrafish syt4 gene in GABAergic neurons in the cerebellum of adult fishes revealed by mammalian SYT4 immunoreactive-like signals

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Heliyon 2024年第9期10卷 e30575页

作者： Shiao, Meng-Shin Liu, Sian-Tai Siriwatcharapibool, Ganchai Thongpradit, Supranee Khunpanich, Punnakorn Tong, Sok-Keng Huang, Chih-Hsuan Jinawath, Natini Chou, Ming-Yi Research Center Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok 10400 Thailand Department of Life Science National Taiwan University Taipei 10617 Taiwan International College Mahidol University Salaya Nakhon Pathom 73170 Thailand Program in Translational Medicine Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok 10400 Thailand Integrative Computational Bioscience (ICBS) Center Mahidol University Nakhon Pathom 73170 Thailand Chakri Naruebodindra Medical Institute Faculty of Medicine Ramathibodi Hospital Mahidol University Samut Prakan 10540 Thailand

Synaptotagmin 4 (syt4) belongs to the synaptotagmin protein family, which has 17 and 28 family members in human and zebrafish, respectively. In zebrafish and rodents, syt4 is known to express abundantly in the entire central nervous system in the early developmental stages. In adult rodents, the gene expression shifts to be predominant in the cerebellum, mostly in Purkinje cells, a type of GABAergic neurons. However, there is no report of the expression pattern of syt4 in the adult zebrafish brain. Therefore, we hypothesize that the expression of syt4 is conserved in adult zebrafish and is specific to the GABAergic neurons, likely Purkinje cells, in the cerebellum. To examine the hypothesis, we first show that only one copy of syt4 gene remains in the zebrafish genome, and it is orthologous to the gene in other vertebrates. We further observe mammalian SYT4 antibody immunoreactive-like (mSYT4-ir) signals in several structures in the hindbrain including the medial divisions of the valvula cerebelli and the corpus cerebelli. In addition, our observations indicate the presence of mSYT4-ir signals in GABAergic neurons, most notably in the Purkinje cell layer of the molecular layer in the aforementioned structures. Conversely, mSYT4-ir signals are not observed in glutamatergic or cholinergic neurons. Therefore, we deduce that the syt4 gene in zebrafish exhibits a homologous expression pattern to those of previously studied vertebrate species, which is revealed by the positive immunoreactive-like signals of mammalian SYT4 antibodies. © 2024

关键词： Brain Cerebellum GABAergic neurons Synaptotagmin 4 syt4 Zebrafish

High-resolution dynamic imaging of chromatin DNA communication using Oligo-LiveFISH

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Cell 2025年第12期188卷 3310-3328.e27页

作者： Zhu, Yanyu Balaji, Ashwin Han, Mengting Andronov, Leonid Roy, Anish R. Wei, Zheng Chen, Crystal Miles, Leanne Cai, Sa Gu, Zhengxi Tse, Ariana Yu, Betty Chentzu Uenaka, Takeshi Lin, Xueqiu Spakowitz, Andrew J. Moerner, W.E. Qi, Lei S. Department of Bioengineering Stanford University Stanford 94305 CA United States Department of Chemistry Stanford University Stanford 94305 CA United States Biophysics PhD Program Stanford University Stanford 94305 CA United States Computational Biology Program Public Health Sciences Division and Translational Data Science IRC Fred Hutchinson Cancer Center Seattle 98109 WA United States Department of Chemical Engineering Stanford University Stanford 94305 CA United States Department of Materials Science and Engineering Stanford University Stanford 94305 CA United States Institute for Stem Cell Biology & Regenerative Medicine and Department of Pathology Stanford University School of Medicine Stanford 94305 CA United States Sarafan ChEM-H Stanford University Stanford 94305 CA United States Chan Zuckerberg Biohub San Francisco 94080 CA United States

Three-dimensional (3D) genome dynamics are crucial for cellular functions and disease. However, real-time, live-cell DNA visualization remains challenging, as existing methods are often confined to repetitive regions, suffer from low resolution, or require complex genome engineering. Here, we present Oligo-LiveFISH, a high-resolution, reagent-based platform for dynamically tracking non-repetitive genomic loci in diverse cell types, including primary cells. Oligo-LiveFISH utilizes fluorescent guide RNA (gRNA) oligo pools generated by computational design, in vitro transcription, and chemical labeling, delivered as ribonucleoproteins. Utilizing machine learning, we characterized the impact of gRNA design and chromatin features on imaging efficiency. Multi-color Oligo-LiveFISH achieved 20-nm spatial resolution and 50-ms temporal resolution in 3D, capturing real-time enhancer and promoter dynamics. Our measurements and dynamic modeling revealed two distinct modes of chromatin communication, and active transcription slows enhancer-promoter dynamics at endogenous genes like FOS. Oligo-LiveFISH offers a versatile platform for studying 3D genome dynamics and their links to cellular processes and disease. © 2025 Elsevier Inc.

关键词： CRISPR imaging DNA communication dynamic tracking enhancer-promoter interaction high-resolution imaging live DNA imaging non-repetitive genome imaging Oligo-LiveFISH polymer modeling primary cell

Molecular interaction volume model of mixing enthalpy for molten salt system: An integrated calorimetry-model case study of LaCl3-(LiCl-KCl)

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arXiv 2024年

作者： Goncharov, Vitaliy G. Smith, William Li, Jiahong Eakin, Jeffrey A. Reinhart, Erik D. Boncella, James Gibson, Luke D. Bryantsev, Vyacheslav S. Gong, Rushi Shang, Shun-Li Liu, Zi-Kui Xu, Hongwu Clark, Aurora Guo, Xiaofeng Department of Chemistry Washington State University PullmanWA99164 United States Materials Science and Engineering Program Washington State University PullmanWA99164 United States Computational Sciences and Engineering Division Oak Ridge National Laboratory P.O. Box 2008 Oak RidgeTN37831 United States Chemical Science Division Oak Ridge National Laboratory P.O. Box 2008 Oak RidgeTN37831 United States Department of Materials Science and Engineering Pennsylvania State University University ParkPA16802 United States Earth and Environmental Sciences Division Los Alamos National Laboratory Los Alamos New MexicoNM87545 United States Arizona State University TempeAZ United States Department of Chemistry The University of Utah Salt Lake CityUT84112 United States

Calorimetric determination of enthalpies of mixing (ΔHmix) of multicomponent molten salts often employs empirical models that lack parameters with clear physical interpretation (e.g., coordination numbers, molar volumes, and pair potentials). Although such physics informed models are not always needed, a thermodynamic understanding of the relationships between excess energies of mixing and local to intermediate solvation structures is particularly important for pyrochemical separation, as is the case for lanthanides (Ln), which are common neutron poisons and critical industrial elements found in spent nuclear fuels. Here we implement the molecular interaction volume model (MIVM) to synthesize information from experimentally measured ΔHmix (using high temperature melt drop calorimetry) and the distribution of solvation structures from ab initio molecular dynamics (AIMD) simulations. This was demonstrated by a case study of molten salt system consisted of LaCl3 mixing with a eutectic LiCl-KCl (58mol% - 42mol%) at 873 K and 1133 K. The parameters modelled from MIVM were used to extrapolate excess Gibbs energy (ΔGmix), and compositional dependence of La3+ activity in the LaCl3-(LiCl-KCl) system. In contrast, by AIMD or polarizable ion model (PIM) simulations, a significant deviation regarding the predicted ΔHmix was seen if computed directly from the molecular dynamic trajectories. The integrated experimental and simulation data within the MIVM formalism are generalizable to a wide variety of molten salts and demonstrate a significant improvement over currently employed methods to study molten salts for nuclear and separations sciences. Copyright © 2024, The Authors. All rights reserved.

关键词： Enthalpy

NNP/MM: Accelerating molecular dynamics simulations with machine learning potentials and molecular mechanics

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arXiv 2022年

作者： Galvelis, Raimondas Varela-Rial, Alejandro Doerr, Stefan Fino, Roberto Eastman, Peter Markland, Thomas E. Chodera, John D. De Fabritiis, Gianni Acellera Labs C/ Doctor Trueta 183 Barcelona08005 Spain Acellera Ltd Devonshire House 582 HA7 1JS United Kingdom Computational Science Laboratory Universitat Pompeu Fabra PRBB C/ Doctor Aiguader 88 Barcelona08003 Spain Department of Chemistry Stanford University 337 Campus Drive StanfordCA94305 United States Computational and Systems Biology Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New YorkNY10065 United States Passeig Lluis Companys 23 Barcelona08010 Spain

Machine learning potentials have emerged as a means to enhance the accuracy of biomolecular simulations. However, their application is constrained by the significant computational cost arising from the vast number of parameters compared to traditional molecular mechanics. To tackle this issue, we introduce an optimized implementation of the hybrid method (NNP/MM), which combines neural network potentials (NNP) and molecular mechanics (MM). This approach models a portion of the system, such as a small molecule, using NNP while employing MM for the remaining system to boost efficiency. By conducting molecular dynamics (MD) simulations on various protein-ligand complexes and metadynamics (MTD) simulations on a ligand, we showcase the capabilities of our implementation of NNP/MM. It has enabled us to increase the simulation speed by ∼5 times and achieve a combined sampling of 1 µs for each complex, marking the longest simulations ever reported for this class of simulation. Copyright © 2022, The Authors. All rights reserved.

关键词： Complex networks

Self-interaction corrected Kohn-Sham effective potentials using the density-consistent effective potential method

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arXiv 2021年

作者： Diaz, Carlos M. Basurto, Luis Adhikari, Santosh Yamamoto, Yoh Ruzsinszky, Adrienn Baruah, Tunna Zope, Rajendra R. Department of Physics University of Texas at El Paso El PasoTX79968 United States Computational Science Program University of Texas at El Paso El PasoTX79968 United States Department of Physics Temple University PhiladelphiaPA19122 United States

Density functional theory (DFT) and beyond-DFT methods are often used in combination with photoelectron spectroscopy to obtain physical insights into the electronic structure of molecules and solids. The Kohn-Sham eigenvalues are not electron removal energies except for the highest occupied orbital. The eigenvalues of the highest occupied molecular orbitals often underestimate the electron removal or ionization energies due to the self-interaction (SI) errors in approximate density functionals. In this work, we adapt and implement the density-consistent effective potential (DCEP) method of Kohut, Ryabinkin, and Staroverov to obtain SI corrected local effective potentials from the SI corrected Fermi-Löwdin orbitals and density in the FLOSIC scheme. The implementation is used to obtain the density of states (photoelectron spectra) and HOMO-LUMO gaps for a set of molecules and polyacenes. Good agreement with experimental values is obtained compared to a range of SI uncorrected density functional approximations. Copyright © 2021, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

Surface Functional Groups Effect on the Absorption Spectrum of Carbon Dots: Initial TD-DFT Study 9

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Surface Functional Groups Effect on the Absorption Spectrum ...

9th Asian Physics Symposium 2021, APS 2021

作者： Umami, Reza Permatasari, Fitri Aulia Sundari, Citra Deliana Dewi Muttaqien, Fahdzi Iskandar, Ferry Department of Physics Faculty Mathematics and Natural Sciences Institut Teknologi Bandung Jalan Ganesha 10 West Java Bandung40132 Indonesia Inorganic and Physical Chemistry Division Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jl. Ganesha 10 West Java Bandung40132 Indonesia Department of Chemistry Education UIN Sunan Gunung Djati Bandung Jl. Cimincrang West Java Bandung40292 Indonesia Master Program in Computational Science Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jalan Ganesha 10 Bandung40132 Indonesia Research Center for Nanoscience and Nanotechnology Institut Teknologi Bandung Jalan Ganesha 10 West Java Bandung40132 Indonesia

Carbon dots (CDs) have attracted considerable interest due to their remarkable performance, low cost and ease of preparation, and wide range of potential applications. Surface engineering, including modifying the surface functional group and subsequent chemical modification, is preferable to achieve the requirement of the specific application. Oxygen and Nitrogen-based surface functional groups are two common functionalizations on CDs that are subsequently generated during the synthetic process. In this study, we elucidate the optical properties of oxygen and nitrogen-functionalized CDs using time-dependent density functional theory (TD-DFT). Both considered functional groups, the carbon-oxygen double bond (-C=O) and amino groups (-NH2), are quite favourable to tailor the optical properties of CDs, especially in enhancing its absorption spectrum. Moreover, the carbonyl (-C=O) and amino (-NH2) functional groups effectively serve a new absorption peak in the first near-infrared window (650-900 nm). Our results suggest the potential application of the amino and carbonyl functionalized CDs as a photothermal agent in photothermal cancer therapy. © Published under licence by IOP Publishing Ltd.

关键词： Optical properties

Predicting Obstructive Hydronephrosis Based on Ultrasound Alone 1

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23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020

作者： Erdman, Lauren Skreta, Marta Rickard, Mandy McLean, Carson Mezlini, Aziz Keefe, Daniel T. Blais, Anne-Sophie Brudno, Michael Lorenzo, Armando Goldenberg, Anna Department of Computer Science University of Toronto Toronto Canada Program in Genetics and Genome Biology Hospital for Sick Children Toronto Canada Vector Institute Toronto Canada Center for Computational Medicine SickKids Hospital Toronto Canada Department of Surgery Division of Urology Hospital for Sick Children Toronto Canada Toronto Canada

ISBN: (数字)9783030597160

ISBN: (纸本)9783030597153

Prenatal hydronephrosis (HN) makes up nearly 30% of pediatric Urology Department visits, yet remains challenging to prognosticate without repeated ultrasounds and invasive clinical tests. We build a deep learning model, which uses still images from kidney ultrasound as input and predicts whether HN is due to an obstruction that will receive surgical intervention. We compare our custom convolutional neural network performance against other existing state-of-the-art models. Our best model predicts obstruction with an AUC of 0.93 and an AUPRC of 0.75 in a prospective test set of 89 patients (286 repeated kidney ultrasounds). We show that while maintaining a 5% false negative rate, our classifier identifies 58% of those who will have surgery due to obstruction yet received a functional renogram, indicating that this model could feasibly reduce the amount of testing done in more than half of non-surgical cases. This work demonstrates the ability of deep learning to predict obstructive HN with clinically relevant accuracy based on kidney ultrasound alone, without requiring other clinical variables as input. This algorithm has the potential to change clinical practice by stratifying HN patient risk, reducing repeated follow ups and invasive testing for less severe cases, and bringing more consistency to clinical management. © 2020, Springer Nature Switzerland AG.

关键词： Urology