jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yang Li | Nana Wang | Yao Wang | Dong Liu | Ya Gao | Lan Li | Xue‐Bao Li
Source: The Plant Journal (article, 2018-09-26)
Field: Materials Science — Biomaterials

The cotton <scp>XLIM</scp> protein (Gh<scp>XLIM</scp>6) is required for fiber development via maintaining dynamic F‐actin cytoskeleton and modulating cellulose biosynthesis LIM domain proteins are cysteine-rich proteins, and are often considered as actin bundlers and transcription factors in plants. However, the roles of XLIM proteins in plants (especially in cotton) remain unexplored in detail so far. In this study, we identified a cotton XLIM protein (GhXLIM6) that is preferentially expressed in cotton fiber during whole elongation stage and early secondary cell wall (SCW) synthesis stage. The GhXLIM6-silenced transgenic cotton produces shorter fibers with thinner cell walls, compared with wild-type (WT). GhXLIM6 protein could directly bind F-actin and promote actin polymerization both in vitro and in vivo. It also acts as a transcription factor to suppress GhKNL1 expression through binding the PAL-box element of GhKNL1 promoter, and subsequently regulate the expression of CesA genes related to cellulose biosynthesis and deposition in SCWs of cotton fibers. The cellulose content in fibers of GhXLIM6RNAi cotton is lower than that in WT. Taken together, these data reveal the dual roles of GhXLIM6 in fiber development. On one hand, GhXLIM6 functions in fiber elongation through binding to F-actin to maintain the dynamic F-actin cytoskeleton. On the other hand, GhXLIM6 fine-tunes fiber SCW formation, probably through directly suppressing transcription of GhKNL1 to promote cellulose biosynthesis. Cell biology ; Transcription factor ; Cytoskeleton ; Actin ; Actin cytoskeleton ; Transcription (linguistics) ; Actin-binding protein ; Secondary cell wall ; Biochemistry ; Chemistry ; Biology ; Biosynthesis ; Cellulose ; Gene ; Cell Advanced Cellulose Research Studies ; Research in Cotton Cultivation ; Polysaccharides and Plant Cell Walls
Authors: Ouldouz Ghashghaei | Samantha Caputo | Miquel Sintes | Marc Revés | Nicola Kielland | Carolina Estarellas | F. Javier Luque | Anna Aviñó | Ramón Eritja | Ana Serna‐Gallego | José Antonio Marrugal‐Lorenzo | Jerónimo Pachón | Javier Sánchez‐Céspedes | Ryan Treadwell | Fabio De Moliner | Marc Vendrell | Rodolfo Lavilla
Source: Chemistry - A European Journal (article, 2018-07-05)
Field: Chemistry — Organic Chemistry

Multiple Multicomponent Reactions: Unexplored Substrates, Selective Processes, and Versatile Chemotypes in Biomedicine Multiple multicomponent reactions rapidly assemble complex structures. Despite being very productive, the lack of selectivity and the reduced number of viable transformations restrict their general application in synthesis. Hereby, we describe a rationale for a selective version of these processes based in the preferential generation of intermediates which are less reactive than the initial substrates. In this way, applying the Groebke-Blackburn-Bienaymé reaction on a range of α-polyamino-polyazines, we prepared a family compact heterocyclic scaffolds with relevant applications in medicinal and biological chemistry (live cell imaging probes, selective binders for DNA quadruplexes, and antiviral agents against human adenoviruses). The approach has general character and yields complex molecular targets in a selective, tunable and direct manner. Biomedicine ; Combinatorial chemistry ; Nanotechnology ; DNA ; Chemistry ; Chemotype ; Computational biology ; Biology ; Materials science ; Bioinformatics ; Biochemistry Multicomponent Synthesis of Heterocycles ; Synthesis and Characterization of Heterocyclic Compounds ; Click Chemistry and Applications
Authors: Yimin Luo | Daniel A. Beller | Giuseppe Boniello | Francesca Serra | Kathleen J. Stebe
Source: Nature Communications (article, 2018-09-17)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Tunable colloid trajectories in nematic liquid crystals near wavy walls The ability to dictate the motion of microscopic objects is an important challenge in fields ranging from materials science to biology. Field-directed assembly drives microparticles along paths defined by energy gradients. Nematic liquid crystals, consisting of rod-like molecules, provide new opportunities in this domain. Deviations of nematic liquid crystal molecules from uniform orientation cost elastic energy, and such deviations can be molded by bounding vessel shape. Here, by placing a wavy wall in a nematic liquid crystal, we impose alternating splay and bend distortions, and define a smoothly varying elastic energy field. A microparticle in this field displays a rich set of behaviors, as this system has multiple stable states, repulsive and attractive loci, and interaction strengths that can be tuned to allow reconfigurable states. Microparticles can transition between defect configurations, move along distinct paths, and select sites for preferred docking. Such tailored landscapes have promise in reconfigurable systems and in microrobotics applications. Liquid crystal ; Colloid ; Materials science ; Optics ; Condensed matter physics ; Nanotechnology ; Optoelectronics ; Chemistry ; Physics Liquid Crystal Research Advancements ; Photonic Crystals and Applications ; Surfactants and Colloidal Systems
Authors: Karteek K. Bejagam | Yaxin An | Samrendra Singh | Sanket A. Deshmukh
Source: The Journal of Physical Chemistry Letters (article, 2018-10-29)
Field: Materials Science — Materials Chemistry

Machine-Learning Enabled New Insights into the Coil-to-Globule Transition of Thermosensitive Polymers Using a Coarse-Grained Model We present a computational framework that integrates coarse-grained (CG) molecular dynamics (MD) simulations and a data-driven machine-learning (ML) method to gain insights into the conformations of polymers in solutions. We employ this framework to study conformational transition of a model thermosensitive polymer, poly( N-isopropylacrylamide) (PNIPAM). Here, we have developed the first of its kind, a temperature-independent CG model of PNIPAM that can accurately predict its experimental lower critical solution temperature (LCST) while retaining the tacticity in the presence of an explicit water model. The CG model was extensively validated by performing CG MD simulations with different initial conformations, varying the radius of gyration of chain, the chain length, and the angle between the adjacent monomers of the initial configuration of PNIPAM (total simulation time = 90 μs). Moreover, for the first time, we utilize the nonmetric multidimensional scaling (NMDS) method, a data-driven ML approach, to gain further insights into the mechanisms and pathways of this coil-to-globule transition by analyzing CG MD simulation trajectories. NMDS analysis provides entirely new insights and shows multiple metastable states of PNIPAM during its coil-to-globule transition above the LCST. Lower critical solution temperature ; Radius of gyration ; Polymer ; Molecular dynamics ; Scaling ; Metastability ; Materials science ; Monomer ; Chemical physics ; Tacticity ; Chain (unit) ; Biological system ; Electromagnetic coil ; Statistical physics ; Thermodynamics ; Chemistry ; Physics ; Polymerization ; Computational chemistry ; Copolymer ; Mathematics Block Copolymer Self-Assembly ; Hydrogels: synthesis, properties, applications ; Electrostatics and Colloid Interactions
Authors: Yuqi Zhang | A.H.W. Ngan
Source: International Journal of Plasticity (article, 2018-11-16)
Field: Materials Science — Materials Chemistry

Extracting dislocation microstructures by deep learning Dislocation ; Materials science ; Microstructure ; Electron backscatter diffraction ; Convolutional neural network ; Condensed matter physics ; Crystal (programming language) ; Diffraction ; Artificial intelligence ; Statistical physics ; Crystallography ; Computer science ; Optics ; Composite material ; Physics Microstructure and mechanical properties ; Advanced Materials Characterization Techniques ; High Temperature Alloys and Creep
Authors: Atsuto Seko | Hiroyuki Hayashi | Isao Tanaka
Source: The Journal of Chemical Physics (article, 2018-03-27)
Field: Materials Science — Materials Chemistry

Compositional descriptor-based recommender system for the materials discovery Structures and properties of many inorganic compounds have been collected historically. However, it only covers a very small portion of possible inorganic crystals, which implies the presence of numerous currently unknown compounds. A powerful machine-learning strategy is mandatory to discover new inorganic compounds from all chemical combinations. Herein we propose a descriptor-based recommender-system approach to estimate the relevance of chemical compositions where crystals can be formed [i.e., chemically relevant compositions (CRCs)]. In addition to data-driven compositional similarity used in the literature, the use of compositional descriptors as a prior knowledge is helpful for the discovery of new compounds. We validate our recommender systems in two ways. First, one database is used to construct a model, while another is used for the validation. Second, we estimate the phase stability for compounds at expected CRCs using density functional theory calculations. Relevance (law) ; Construct (python library) ; Recommender system ; Similarity (geometry) ; Stability (learning theory) ; Knowledge extraction ; Inorganic Chemical Machine Learning in Materials Science ; Catalysis and Oxidation Reactions ; X-ray Diffraction in Crystallography
Authors: Wenqian Ruan | Jiwei Hu | Jimei Qi | Yu Hou | Rensheng Cao | Xionghui Wei
Source: Materials (article, 2018-05-22)
Field: Chemistry — Organic Chemistry

Removal of Crystal Violet by Using Reduced-Graphene-Oxide-Supported Bimetallic Fe/Ni Nanoparticles (rGO/Fe/Ni): Application of Artificial Intelligence Modeling for the Optimization Process Reduced-graphene-oxide-supported bimetallic Fe/Ni nanoparticles were synthesized in this study for the removal of crystal violet (CV) dye from aqueous solutions. This material was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDS), Raman spectroscopy, N₂-sorption, and X-ray photoelectron spectroscopy (XPS). The influence of independent parameters (namely, initial dye concentration, initial pH, contact time, and temperature) on the removal efficiency were investigated via Box⁻Behnken design (BBD). Artificial intelligence (i.e., artificial neural network, genetic algorithm, and particle swarm optimization) was used to optimize and predict the optimum conditions and obtain the maximum removal efficiency. The zero point of charge (pH<sub>ZPC</sub>) of rGO/Fe/Ni composites was determined by using the salt addition method. The experimental equilibrium data were fitted well to the Freundlich model for the evaluation of the actual behavior of CV adsorption, and the maximum adsorption capacity was estimated as 2000.00 mg/g. The kinetic study discloses that the adsorption processes can be satisfactorily described by the pseudo-second-order model. The values of Gibbs free energy change (Δ<i>G</i>⁰), entropy change (Δ<i>S</i>⁰), and enthalpy change (Δ<i>H</i>⁰) demonstrate the spontaneous and endothermic nature of the adsorption of CV onto rGO/Fe/Ni composites. Crystal violet ; Graphene ; Materials science ; Gibbs free energy ; Adsorption ; Freundlich equation ; Oxide ; Nanoparticle ; X-ray photoelectron spectroscopy ; Raman spectroscopy ; Bimetallic strip ; Chemical engineering ; Endothermic process ; Point of zero charge ; Nanotechnology ; Chemistry ; Thermodynamics ; Physical chemistry ; Metallurgy ; Metal Nanomaterials for catalytic reactions ; Adsorption and biosorption for pollutant removal ; Environmental remediation with nanomaterials
Authors: Xuyang Pan | Laijun Sun | Yingsong Li | Wenkai Che | Yamin Ji | Jinlong Li | Jie Li | Xu Xie | Yuantong Xu
Source: Journal of the Science of Food and Agriculture (article, 2018-09-17)
Field: Chemistry — Analytical Chemistry

Non‐destructive classification of apple bruising time based on visible and near‐infrared hyperspectral imaging Abstract BACKGROUND Bruising time of apple is one of the most important factors for internal quality assessment. The present study aimed to establish a non‐destructive method for the classification of apple bruising time using visible and near‐infrared (VNIR) hyperspectral imaging. In this study, VNIR hyperspectral images were obtained and analyzed at seven bruising periods. Moreover, regions of interest (ROIs) were chosen to construct the bruised region classification model, and spectra of bruised regions were collected and resampled based on four different methods. Subsequently, machine learning algorithms were employed and used for dealing with the time classification model of apples. In order to reduce data redundancy and improve the accuracy of the classification model, a tree‐based assembling learning model was used to select feature wavelengths, and linear discriminant analysis (LDA) was used to improve the discernibility of data. RESULTS The results revealed that the random forest (RF) model can precisely locate bruised regions, while the gradient boosting decision tree (GBDT) model can validly classify apple bruising times with 70.59% accuracy. Data of 128 wavebands were compressed to 13 wavebands, providing a high accuracy of 92.86%. CONCLUSION The results prove that the hyperspectral technique can be used for predicting apple bruising time, which will help to assess the internal quality and safety of apples. © 2018 Society of Chemical Industry Hyperspectral imaging ; VNIR ; Artificial intelligence ; Pattern recognition (psychology) ; Random forest ; Linear discriminant analysis ; Computer science ; Decision tree ; Mathematics ; Remote sensing ; Geography Spectroscopy and Chemometric Analyses ; Postharvest Quality and Shelf Life Management ; Horticultural and Viticultural Research
Authors: Hadi Parastar | Romá Tauler
Source: Angewandte Chemie International Edition (review, 2018-03-23)
Field: Chemistry — Analytical Chemistry

Big (Bio)Chemical Data Mining Using Chemometric Methods: A Need for Chemists This Review summarizes how big (bio)chemical data (BBCD) can be analyzed with multivariate chemometric methods and highlights some of the important challenges faced by modern analytical researches. Here, the potential of chemometric methods to solve BBCD problems that are being encountered in chromatographic, spectroscopic and hyperspectral imaging measurements will be discussed, with an emphasis on their applications to omics sciences. In addition, insights and perspectives on how to address the analysis of BBCD are provided along with a discussion of the procedures necessary to obtain more reliable qualitative and quantitative results. In this Review, the importance of "big data" and of their relevance to (bio)chemistry are first discussed. Thereafter, analytical tools which can produce BBCD are presented as well as the theoretical background of chemometric methods and their limitations when they are applied to BBCD. Finally, the importance of chemometric methods for the analysis of BBCD in different chemical disciplines is highlighted with some examples. In this work, we have tried to cover many of the current applications of big data analysis in the (bio)chemistry field. Chemometrics ; Computer science ; Data science ; Relevance (law) ; Big data ; Biochemical engineering ; Field (mathematics) ; Data mining ; Machine learning ; Mathematics ; Engineering Spectroscopy and Chemometric Analyses ; Metabolomics and Mass Spectrometry Studies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: D. Lerche
Source: KONA Powder and Particle Journal (article, 2018-07-30)
Field: Chemistry — Physical and Theoretical Chemistry

Comprehensive Characterization of Nano- and Microparticles by In-Situ Visualization of Particle Movement Using Advanced Sedimentation Techniques The state of a suspension is crucial with regard to processing pathways, functionality and performance of the end product. In the past decade, substantial progress has been made in designing highly specialized and functionalized particles. In current particle technology, besides classic particle properties such as particle size distribution, shape and density, surface properties play an essential role for processing, product specification and use. For example, in medical therapy, analytical diagnostic applications, as well as in separation processing and harvesting of high-valued materials, magnetic micro- and nanoparticles play an increasing role. In addition to traditional parameters such as size, the particle magnetization has to be quantified here. Materials science ; Characterization (materials science) ; Particle (ecology) ; Nanotechnology ; Nanoparticle ; Particle size ; Suspension (topology) ; Nano- ; Sedimentation ; Particle-size distribution ; Process engineering ; Chemical engineering ; Composite material ; Engineering Electrostatics and Colloid Interactions ; Microfluidic and Bio-sensing Technologies ; Characterization and Applications of Magnetic Nanoparticles
Authors: Qisheng Wang | Jie Li | Jean Besbas | Chuang‐Han Hsu | Kaiming Cai | Li Yang | Shuai Cheng | Yang Wu | Wenfeng Zhang | Kaiyou Wang | Tay‐Rong Chang | Hsin Lin | Haixin Chang | Hyunsoo Yang
Source: Advanced Science (article, 2018-04-14)
Field: Materials Science — Materials Chemistry

Room‐Temperature Nanoseconds Spin Relaxation in WTe<sub>2</sub> and MoTe<sub>2</sub> Thin Films The Weyl semimetal WTe<sub>2</sub> and MoTe<sub>2</sub> show great potential in generating large spin currents since they possess topologically protected spin-polarized states and can carry a very large current density. In addition, the intrinsic non-centrosymmetry of WTe<sub>2</sub> and MoTe<sub>2</sub> endows with a unique property of crystal symmetry-controlled spin-orbit torques. An important question to be answered for developing spintronic devices is how spins relax in WTe<sub>2</sub> and MoTe<sub>2</sub>. Here, a room-temperature spin relaxation time of 1.2 ns (0.4 ns) in WTe<sub>2</sub> (MoTe<sub>2</sub>) thin film using the time-resolved Kerr rotation (TRKR) is reported. Based on ab initio calculation, a mechanism of long-lived spin polarization resulting from a large spin splitting around the bottom of the conduction band, low electron-hole recombination rate, and suppression of backscattering required by time-reversal and lattice symmetry operation is identified. In addition, it is found that the spin polarization is firmly pinned along the strong internal out-of-plane magnetic field induced by large spin splitting. This work provides an insight into the physical origin of long-lived spin polarization in Weyl semimetals, which could be useful to manipulate spins for a long time at room temperature. Condensed matter physics ; Weyl semimetal ; Spintronics ; Spins ; Materials science ; Spin polarization ; Physics ; Semimetal ; Band gap ; Electron ; Ferromagnetism 2D Materials and Applications ; Topological Materials and Phenomena ; Heusler alloys: electronic and magnetic properties
Authors: Ibrahim Osama | Natalia Gorenkova | Craig Martin McKittrick | Thidarat Wongpinyochit | Andrew J. Goudie | F. Philipp Seib | H Carswell
Source: Scientific Reports (article, 2018-09-06)
Field: Materials Science — Biomaterials

In vitro studies on space-conforming self-assembling silk hydrogels as a mesenchymal stem cell-support matrix suitable for minimally invasive brain application Advanced cell therapies require robust delivery materials and silk is a promising contender with a long clinical track record. Our aim was to optimise self-assembling silk hydrogels as a mesenchymal stem cell (MSC)-support matrix that would allow future minimally invasive brain application. We used sonication energy to programme the transition of silk (1-5% w/v) secondary structure from a random coil to a stable β-sheet configuration. This allowed fine tuning of self-assembling silk hydrogels to achieve space conformity in the absence of any silk hydrogel swelling and to support uniform cell distribution as well as cell viability. Embedded cells underwent significant proliferation over 14 days in vitro, with the best proliferation achieved with 2% w/v hydrogels. Embedded MSCs showed significantly better viability in vitro after injection through a 30G needle when the gels were in the pre-gelled versus post-gelled state. Silk hydrogels (4% w/v) with physical characteristics matching brain tissue were visualised in preliminary in vivo experiments to exhibit good space conformity in an ischemic cavity (intraluminal thread middle cerebral artery occlusion model) in adult male Sprague-Dawley rats (n = 3). This study informs on optimal MSC-hydrogel matrix conditions for minimally invasive application as a platform for future experiments targeting brain repair. Self-healing hydrogels ; SILK ; Mesenchymal stem cell ; Biomedical engineering ; In vivo ; Matrix (chemical analysis) ; Materials science ; Embryonic stem cell ; Stem cell ; Medicine ; Chemistry ; Cell biology ; Biology ; Pathology ; Biotechnology ; Polymer chemistry ; Composite material Silk-based biomaterials and applications ; Nerve injury and regeneration ; Electrospun Nanofibers in Biomedical Applications
Authors: Nenad Ignjatović | Marija N. Sakač | Ivana Kuzminac | Vesna Kojić | Smilja Marković | Dana Vasiljević-Radović | Victoria Wu | Vuk Uskoković | Dragan Uskoković
Source: Journal of Materials Chemistry B (article, 2018-01-01)
Field: Materials Science — Biomaterials

Chitosan oligosaccharide lactate coated hydroxyapatite nanoparticles as a vehicle for the delivery of steroid drugs and the targeting of breast cancer cells Low targeting efficiency and fast metabolism of antineoplastic drugs are hindrances to effective chemotherapies and there is an ongoing search for better drugs, but also better carriers. Steroid derivatives, 3β-hydroxy-16-hydroxymino-androst-5-en-17-one (A) and 3β,17β-dihydroxy-16-hydroxymino-androst-5-ene (B) as cancer growth inhibitors were chemically synthesized and captured in a carrier composed of hydroxyapatite (HAp) nanoparticles coated with chitosan oligosaccharide lactate (ChOLS). The only difference between the two derivatives is that A has a carbonyl group at the C17 position of the five-membered ring and B has a hydroxyl. This small difference in the structure resulted not only in different physicochemical properties of the A- and B-loaded HAp/ChOSL, but also in different biological activities. The morphology of drug-loaded HAp/ChOSL particles was spherical, but the size depended on the drug identity: d<sub>50</sub>=138 nm for A-loaded HAp/ChOSL and d<sub>50</sub>=223 nm for B-loaded HAp/ChOSL. Cell-selective toxicity was tested against human breast carcinoma (MCF7 and MDA-MB-231), human lung carcinoma (A549) and human lung fibroblasts (MRC-5). The small selectivity of pure derivatives A and B toward breast cancer cells became drastically increased when they were delivered using HAp/ChOSL particles. Whereas the ratio of the cytotoxicity imposed onto breast cancer cells and the cytotoxicity imposed onto healthy MRC-5 fibroblasts ranged from 1.5 to 1.7 for pure A and from 1.5 to 2.3 for pure derivative B depending on the concentration, it increased to 5.4 for A-loaded HAp/ChOSL and 5.1 for B-loaded HAp/ChOSL. FACS analysis demonstrated poor uptake of HAp/ChOSL particles by MCF7 cells, suggesting that the drug release occurs extracellularly. The augmented activity of the drugs was most likely due to sustained release, although the favorable positive charge of the carrier, allowing it to adhere to the negatively charged plasma membrane and release the drugs steadily and directly to the hydrophobic cell membrane milieu, was delineated as a possible complementary mechanism. Chitosan ; Oligosaccharide ; Breast cancer ; Steroid ; Nanoparticle ; Materials science ; Cancer ; Nanotechnology ; Chemistry ; Biochemistry ; Medicine ; Internal medicine ; Hormone Nanoparticle-Based Drug Delivery ; Bone Tissue Engineering Materials ; Advanced Drug Delivery Systems