jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Swarna Ganesh | Krishnan Venkatakrishnan | Bo Tan
Source: Medical Devices & Sensors (article, 2019-12-23)
Field: Materials Science — Materials Chemistry

Quantum cytosensor for early detection of cancer Abstract Current use of graphene quantum dot for cancer detection is highly impeded by the low Raman cross‐section and used as a carrier for plasmonic materials. Hence, there is a need for a sensor an efficient Raman cross‐section, with maintaining the cellular homeostasis to attain accurate detection. Here, we report a SERS‐activated graphene oxide (GO) quantum Cytosensor for whole cell cancer detection capable for the early detection of cancer down to a single cellular level. On approaching quantum scale, we achieved SERS activation of GO quantum dots by introducing the functionality of quantum confinement. By altering the density of functional groups on the surface, we facilitated accelerated self‐cellular uptake resulting in increased SERS sensitivity. Here, we demonstrate cancer detection by two approaches: biomarker detection in external environment and intracellular detection using three cell lines. The quantum Cytosensor advances cancer detection to the molecular level by sensing the complex biomolecular processes transpiring intracellularly to detect and differentiate cancerous attributes of a cell. We observed a 3000‐, 2500‐ and 3500‐fold increase in enhancement of DNA, RNA and protein, respectively. Discernment of SERS spectral signatures was obtained by employing machine learning techniques which primarily identified the differences between cancer cells and normal cells. The classification and clustering techniques provided a high diagnostic sensitivity and specificity of 84.83% with unparalleled accuracy of 92.3%. Detection of cancer down to a single cellular level using quantum Cytosensor via SERS integrated with machine learning provides a new stepping stone towards adoption of SERS‐based early detection of cancer. Quantum dot ; Nanotechnology ; Cancer ; Graphene ; Cancer detection ; Cancer cell ; Quantum ; Biomarker ; Computer science ; Materials science ; Computational biology ; Biology ; Physics ; Biochemistry ; Genetics Carbon and Quantum Dots Applications ; Graphene and Nanomaterials Applications ; Advanced biosensing and bioanalysis techniques
Authors: A. V. Pavlov | J A Serdyuk | Alexander Ustinov
Source: Journal of Physics Conference Series (article, 2019-06-01)
Field: Materials Science — Materials Chemistry

Machine learning and the Schrödinger equation Abstract In this research several methods of machine learning (ML), such as decision trees and linear regression were used to predict ground-state energy (GSE) of an electron in a potential well. Analysis has been done for various types of the potentials: ones with exact solution as well as ones with only numerical one. It was shown that some methods can map the analytical solution and predict GSE with chemical accuracy along with ability to find GSE for systems which does not have analytical solutions. To increase the accuracy and performance of the ML algorithms we proposed several methods of data preprocessing. Preprocessor ; Computer science ; Energy (signal processing) ; Artificial intelligence ; Machine learning ; Algorithm ; Applied mathematics ; Mathematics ; Statistics Machine Learning in Materials Science ; Mass Spectrometry Techniques and Applications ; Neural Networks and Applications
Authors: Sean R. McConnell | Johannes Kästner
Source: Journal of Computational Chemistry (article, 2019-01-24)
Field: Materials Science — Materials Chemistry

Instanton rate constant calculations using interpolated potential energy surfaces in nonredundant, rotationally and translationally invariant coordinates A trivial flaw in the utilization of artificial neural networks in interpolating chemical potential energy surfaces (PES) whose descriptors are Cartesian coordinates is their dependence on simple translations and rotations of the molecule under consideration. A different set of descriptors can be chosen to circumvent this problem, internuclear distances, inverse internuclear distances or z-matrix coordinates are three such descriptors. The objective is to use an interpolated PES in instanton rate constant calculations, hence information on the energy, gradient, and Hessian is required at coordinates in the vicinity of the tunneling path. Instanton theory relies on smoothly fitted Hessians, therefore we use energy, gradients, and Hessians in the training procedure. A major challenge is presented in the proper back-transformation of the output gradients and Hessians from internal coordinates to Cartesian coordinates. We perform comparisons between our method, a previous approach and on-the-fly rate constant calcuations on the hydrogen abstraction from methanol and on the hydrogen addition to isocyanic acid. © 2018Wiley Periodicals, Inc. Orthogonal coordinates ; Cartesian coordinate system ; Log-polar coordinates ; Invariant (physics) ; Potential energy ; Hessian matrix ; Reaction rate constant ; Instanton ; Action-angle coordinates ; Generalized coordinates Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Molecular spectroscopy and chirality
Authors: Rana Honarnezhad | Mehrangiz Fathinia | Alireza Khataee
Source: Journal of Molecular Liquids (article, 2019-05-19)
Field: Materials Science — Materials Chemistry

Mechanical production and sonocatalytic application of Cu2S nanoparticles for degradation of isopropylxanthic acid: Kinetic modeling via white and black box methods Oxidizing agent ; Kinetic energy ; Biological system ; Nonlinear regression ; Degradation (telecommunications) ; Materials science ; Computer science ; Chemistry ; Regression analysis ; Organic chemistry ; Physics ; Machine learning Ultrasound and Cavitation Phenomena ; Advanced oxidation water treatment ; Advanced Photocatalysis Techniques
Authors: Mohammad Atif Faiz Afzal | Mojtaba Haghighatlari | Sai Prasad Ganesh | Chong Cheng | Johannes Hachmann
Source: ChemRxiv (preprint, 2019-02-06)
Field: Materials Science — Polymers and Plastics

Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining We present a high-throughput computational study to identify novel polyimides (PIs) with exceptional refractive index (RI) values for use as optic or optoelectronic materials. Our study utilizes an RI prediction protocol based on a combination of first-principles and data modeling developed in previous work, which we employ on a large-scale PI candidate library generated with the ChemLG code. We deploy the virtual screening software ChemHTPS to automate the assessment of this extensive pool of PI structures in order to determine the performance potential of each candidate. This rapid and efficient approach yields a number of highly promising leads compounds. Using the data mining and machine learning program package ChemML, we analyze the top candidates with respect to prevalent structural features and feature combinations that distinguish them from less promising ones. In particular, we explore the utility of various strategies that introduce highly polarizable moieties into the PI backbone to increase its RI yield. The derived insights provide a foundation for rational and targeted design that goes beyond traditional trial-and-error searches. Virtual screening ; Computer science ; High-throughput screening ; Throughput ; Data mining ; Software ; Machine learning ; Drug discovery ; Bioinformatics ; Programming language Synthesis and properties of polymers ; Computational Drug Discovery Methods ; Chemistry and Chemical Engineering
Authors: Oumaima Jamal Eddine | Mehdi El Bοuchti | Omar Cherkaοui | Hassan Hannache | Saïd Gmouh
Source: Mediterranean Journal of Chemistry (article, 2019-10-12)
Field: Materials Science — Ceramics and Composites

Elaboration and characterization of new phosphate glasses based on natural phosphate and red clay: influence of the chemical composition on the chemical durability New phosphate glass formulations based on Moroccan natural phosphate minerals alone or with Moroccan red clay additive (containing the P2O5-SiO2-CaO-Al2O3-MgO-Fe2O3-K2O-Na2O-TiO2 complex) have been successfully prepared by the quenching method. The chemical composition of each of the elaborated phosphate glasses was determined by X-ray fluorescence analysis (XRF). These investigated phosphate glasses have an excellent homogeneity as was verified by SEM. Their amorphous behavior was confirmed by XRD and DSC. The increase in density and glass transition temperature due to the addition of clay is believed to be related to the crosslinking of the phosphate chains. Structural investigation of these phosphate glasses was carried out using FTIR and Raman spectroscopies. The results obtained show that the composition of these glasses contains a mixture of ultraphosphate and polyphosphate structural units. The concentrations of this mixture depending on the initial composition of the glass components. A correlation between the chemical composition and the chemical durability of the investigated glasses was studied. The results showed that the dissolution rate of the glasses decreases by increasing the clay composition up to a point. This can be explained by assuming the formation of oxygen bridges and strong bonds within the various glasses. Phosphate ; Chemical composition ; Chemistry ; Dissolution ; Amorphous solid ; Iron phosphate ; Fourier transform infrared spectroscopy ; Raman spectroscopy ; Phosphate glass ; Composition (language) ; Glass transition ; Polyphosphate ; Quenching (fluorescence) ; Chemical engineering ; Mineralogy ; Fluorescence ; Organic chemistry ; Polymer Glass properties and applications ; Thermal and Kinetic Analysis ; Crystal Structures and Properties
Authors: Markus Tautz | Juan Torras | Santiago Grijalvo | Ramón Eritja | César Saldías | Carlos Alemán | David Díaz Díaz
Source: RSC Advances (article, 2019-01-01)
Field: Chemistry — Organic Chemistry

Expanding the limits of amide–triazole isosteric substitution in bisamide-based physical gels Gelation of organic solvents using <i>N</i>,<i>N</i>'-((1<i>S</i>,2<i>S</i>)-cyclohexane-1,2-diyl)didodecanamide (C<sub>12</sub>-Cyc) is driven by its self-assembly <i>via</i> antiparallel hydrogen bonds and van der Waals intermolecular interactions. In this work we carried out a dual isosteric substitution of the two amide groups with 1,2,3-triazole rings affording the corresponding isosteric gelator (click-C<sub>12</sub>-Cyc). A detailed comparative study in terms of the gelation ability and gel properties demonstrated that the 1,2,3-triazoles can take over all of the functions derived from the amide groups offering a versatile strategy for tuning the properties of the corresponding gels. This is not an obvious outcome because the directional amide groups in C<sub>12</sub>-Cyc constitute the source of the hydrogen bonds to build the 3D self-assembled network. Furthermore, theoretical calculations revealed that click-C<sub>12</sub>-Cyc can adopt a wide variety of interacting patterns, whose relative stability depends on the polarity of the environment, this is in good agreement with the experimental data obtained regarding its gelation ability. Other important features of click-C<sub>12</sub>-Cyc for potential practical applications are its non-cytotoxic character and its phase-selective gelation of water-oil mixtures. Amide ; Substitution (logic) ; Chemistry ; Triazole ; Combinatorial chemistry ; Organic chemistry ; Computer science Click Chemistry and Applications ; Supramolecular Self-Assembly in Materials ; Chemical Synthesis and Analysis
Authors: Lorenzo Sansalone | Joshua X. Bratsch-Prince | Sicheng Tang | Burjor Captain | David D. Mott | Françisco M. Raymo
Source: Proceedings of the National Academy of Sciences (article, 2019-10-01)
Field: Materials Science — Materials Chemistry

Photopotentiation of the GABA <sub>A</sub> receptor with caged diazepam As the inhibitory γ-aminobutyric acid-ergic (GABAergic) transmission has a pivotal role in the central nervous system (CNS) and defective forms of its synapses are associated with serious neurological disorders, numerous versions of caged GABA and, more recently, photoswitchable ligands have been developed to investigate such transmission. While the complementary nature of these probes is evident, the mechanisms by which the GABA receptors can be photocontrolled have not been fully exploited. In fact, the ultimate need for specificity is critical for the proper synaptic exploration. No caged allosteric modulators of the GABA<sub>A</sub> receptor have been reported so far; to introduce such an investigational approach, we exploited the structural motifs of the benzodiazepinic scaffold to develop a photocaged version of diazepam (CD) that was tested on basolateral amygdala (BLa) pyramidal cells in mouse brain slices. CD is devoid of any intrinsic activity toward the GABA<sub>A</sub> receptor before irradiation. Importantly, CD is a photoreleasable GABA<sub>A</sub> receptor-positive allosteric modulator that offers a different probing mechanism compared to caged GABA and photoswitchable ligands. CD potentiates the inhibitory signaling by prolonging the decay time of postsynaptic GABAergic currents upon photoactivation. Additionally, no effect on presynaptic GABA release was recorded. We developed a photochemical technology to individually study the GABA<sub>A</sub> receptor, which specifically expands the toolbox available to study GABAergic synapses. GABAergic ; Neuroscience ; GABAA receptor ; Long-term potentiation ; Schizophrenia (object-oriented programming) ; gamma-Aminobutyric acid ; Diazepam ; Neurotransmission ; Receptor ; ERBB4 ; Inhibitory postsynaptic potential ; GABA receptor ; Chemistry ; Psychology ; Biology ; Pharmacology ; Biochemistry ; Psychiatry Photochromic and Fluorescence Chemistry ; Photoreceptor and optogenetics research ; Neuroscience and Neuropharmacology Research
Authors: Fiorella Cravero | Santiago A. Schustik | María Jimena Martínez | Carlos D. Barranco | Mónica F. Díaz | Ignacio Ponzoni
Source: Chemometrics and Intelligent Laboratory Systems (article, 2019-06-19)
Field: Materials Science — Materials Chemistry

Computer-aided design of polymeric materials: Computational study for characterization of databases for prediction of mechanical properties under polydispersity Quantitative structure–activity relationship ; Context (archaeology) ; Computer science ; Polymer ; Dispersity ; Biochemical engineering ; Biological system ; Materials science ; Machine learning ; Engineering ; Composite material Machine Learning in Materials Science ; Computational Drug Discovery Methods
Authors: Jiřı́ Czernek | Jiřı́ Brus
Source: Molecules (article, 2019-05-03)
Field: Chemistry — Spectroscopy

Exploring Accuracy Limits of Predictions of the 1H NMR Chemical Shielding Anisotropy in the Solid State The <sup>1</sup>H chemical shielding anisotropy (CSA) is an NMR parameter that is exquisitely sensitive to the local environment of protons in crystalline systems, but it is difficult to obtain it experimentally due to the need to concomitantly suppress other anisotropic interactions in the solid-state NMR (SSNMR) pulse sequences. The SSNMR measurements of the <sup>1</sup>H CSA are particularly challenging if the fast magic-angle-spinning (MAS) is applied. It is thus important to confront the results of both the single-crystal (SC) and fast-MAS experiments with their theoretical counterparts. Here the plane-waves (PW) DFT calculations have been carried out using two functionals in order to precisely characterize the structures and the <sup>1</sup>H NMR chemical shielding tensors (CSTs) of the solid forms of maleic, malonic, and citric acids, and of L-histidine hydrochloride monohydrate. The level of agreement between the PW DFT and either SC or fast-MAS SSNMR <sup>1</sup>H CSA data has been critically compared. It has been found that for the eigenvalues of the <sup>1</sup>H CSTs provided by the fast-MAS measurements, an accuracy limit of current PW DFT predictions is about two ppm in terms of the standard deviation of the linear regression model, and sources of this error have been thoroughly discussed. Solid-state nuclear magnetic resonance ; Anisotropy ; Chemical shift ; Proton NMR ; Electromagnetic shielding ; Chemistry ; Materials science ; Nuclear magnetic resonance ; Physics ; Physical chemistry ; Stereochemistry ; Quantum mechanics Advanced NMR Techniques and Applications ; Solid-state spectroscopy and crystallography ; High-pressure geophysics and materials
Authors: Thales Kronenberger | Philipe de Oliveira Fernades | Isabella Drumond Franco | Antti Poso | Vinícius Gonçalves Maltarollo
Source: ChemMedChem (article, 2019-10-31)
Field: Chemistry — Organic Chemistry

Ligand‐ and Structure‐Based Approaches of <i>Escherichia coli</i> FabI Inhibition by Triclosan Derivatives: From Chemical Similarity to Protein Dynamics Influence Enoyl-acyl carrier protein reductase (FabI) is the limiting step to complete the elongation cycle in type II fatty acid synthase (FAS) systems and is a relevant target for antibacterial drugs. E. coli FabI has been employed as a model to develop new inhibitors against FAS, especially triclosan and diphenyl ether derivatives. Chemical similarity models (CSM) were used to understand which features were relevant for FabI inhibition. Exhaustive screening of different CSM parameter combinations featured chemical groups, such as the hydroxy group, as relevant to distinguish between active/decoy compounds. Those chemical features can interact with the catalytic Tyr156. Further molecular dynamics simulation of FabI revealed the ionization state as a relevant for ligand stability. Also, our models point the balance between potency and the occupancy of the hydrophobic pocket. This work discusses the strengths and weak points of each technique, highlighting the importance of complementarity among approaches to elucidate EcFabI inhibitor's binding mode and offers insights for future drug discovery. Triclosan ; Acyl carrier protein ; Drug discovery ; Escherichia coli ; Biology ; Docking (animal) ; Stereochemistry ; Ligand (biochemistry) ; In silico ; Enzyme ; Chemistry ; Biochemistry ; Combinatorial chemistry ; Computational biology ; Biosynthesis Antimicrobial agents and applications ; Chemical Synthesis and Analysis ; Computational Drug Discovery Methods
Authors: Kiran Haroon | Ali Arafeh | Philip A. Martin | Thomas L. Rodgers | César Mendoza | M. R. Baker
Source: International Journal of Cosmetic Science (article, 2019-05-02)
Field: Chemistry — Analytical Chemistry

Use of inline near‐infrared spectroscopy to predict the viscosity of shampoo using multivariate analysis This work provides a good starting point for developing robust predictive models for in situ viscosity measurements for shampoo manufacturing, where further work into different sources of variation and the extent of the modelling capability with regards to different formulations should be studied. Viscometer ; Rheometer ; Shampoo ; Viscosity ; Chemistry ; Viscosity index ; Materials science ; Process engineering ; Rheology ; Composite material ; Organic chemistry ; Engineering ; Base oil Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Fault Detection and Control Systems
Authors: Seung Ik Oh | In Hyuk Im | Chanyoung Yoo | Sung Yeon Ryu | Yong Kim | Seok Cheol Choi | Taeyong Eom | Cheol Seong Hwang | Byung Joon Choi
Source: Micromachines (article, 2019-04-27)
Field: Materials Science — Materials Chemistry

Effect of Electrode Material on the Crystallization of GeTe Grown by Atomic Layer Deposition for Phase Change Random Access Memory The electrical switching behavior of the GeTe phase-changing material grown by atomic layer deposition is characterized for the phase change random access memory (PCRAM) application. Planar-type PCRAM devices are fabricated with a TiN or W bottom electrode (BE). The crystallization behavior is characterized by applying an electrical pulse train and analyzed by applying the Johnson-Mehl-Avrami kinetics model. The device with TiN BE shows a high Avrami coefficient (>4), meaning that continuous and multiple nucleations occur during crystallization (set switching). Meanwhile, the device with W BE shows a smaller Avrami coefficient (~3), representing retarded nucleation during the crystallization. In addition, larger voltage and power are necessary for crystallization in case of the device with W BE. It is believed that the thermal conductivity of the BE material affects the temperature distribution in the device, resulting in different crystallization kinetics and set switching behavior. Materials science ; Crystallization ; Nucleation ; Tin ; Layer (electronics) ; Phase-change memory ; Deposition (geology) ; Electrical resistivity and conductivity ; Electrode ; Phase (matter) ; Optoelectronics ; Chemical engineering ; Thermodynamics ; Composite material ; Metallurgy ; Electrical engineering ; Chemistry Phase-change materials and chalcogenides ; Advanced Memory and Neural Computing ; Transition Metal Oxide Nanomaterials
Authors: Chuang Li | Kenli Li | Keqin Li | Xianghui Xie | Feng Lin
Source: International Journal of Biological Sciences (article, 2019-01-01)
Field: Chemistry — Spectroscopy

SWPepNovo: An Efficient De Novo Peptide Sequencing Tool for Large-scale MS/MS Spectra Analysis Tandem mass spectrometry (MS/MS)-based de novo peptide sequencing is a powerful method for high-throughput protein analysis. However, the explosively increasing size of MS/MS spectra dataset inevitably and exponentially raises the computational demand of existing de novo peptide sequencing methods, which is an issue urgently to be solved in computational biology. This paper introduces an efficient tool based on SW26010 many-core processor, namely SWPepNovo, to process the large-scale peptide MS/MS spectra using a parallel peptide spectrum matches (PSMs) algorithm. Our design employs a two-level parallelization mechanism: (1) the task-level parallelism between MPEs using MPI based on a data transformation method and a dynamic feedback task scheduling algorithm, (2) the thread-level parallelism across CPEs using asynchronous task transfer and multithreading. Moreover, three optimization strategies, including vectorization, double buffering and memory access optimizations, have been employed to overcome both the compute-bound and the memory-bound bottlenecks in the parallel PSMs algorithm. The results of experiments conducted on multiple spectra datasets demonstrate the performance of SWPepNovo against three state-of-the-art tools for peptide sequencing, including PepNovo+, PEAKS and DeepNovo-DIA. The SWPepNovo also shows high scalability in experiments on extremely large datasets sized up to 11.22 GB. The software and the parameter settings are available at https://github.com/ChuangLi99/SWPepNovo. Computer science ; Parallel computing ; Scalability ; Asynchronous communication ; Tandem mass spectrometry ; Multithreading ; Scheduling (production processes) ; Thread (computing) ; Mass spectrometry ; Chemistry ; Mathematics Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies