jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Gabriela C. Schröder | Flora Meilleur
Source: Journal of Visualized Experiments (article, 2020-12-01)
Field: Materials Science — Materials Chemistry

Neutron Crystallography Data Collection and Processing for Modelling Hydrogen Atoms in Protein Structures Neutron crystallography is a structural technique that allows determination of hydrogen atom positions within biological macromolecules, yielding mechanistically important information about protonation and hydration states while not inducing radiation damage. X-ray diffraction, in contrast, provides only limited information on the position of light atoms and the X-ray beam rapidly induces radiation damage of photosensitive cofactors and metal centers. Presented here is the workflow employed for the IMAGINE and MaNDi beamlines at Oak Ridge National Laboratory (ORNL) to obtain a neutron diffraction structure once a protein crystal of suitable size (> 0.1 mm3) has been grown. We demonstrate mounting of hydrogenated protein crystals in quartz capillaries for neutron diffraction data collection. Also presented is the vapor exchange process of the mounted crystals with D2O-containing buffer to ensure replacement of hydrogen atoms at exchangeable sites with deuterium. The incorporation of deuterium reduces the background arising from the incoherent scattering of hydrogen atoms and prevents density cancellation caused by their negative coherent scattering length. Sample alignment and room temperature data collection strategies are illustrated using quasi-Laue data collection at IMAGINE at the High Flux Isotope Reactor (HFIR). Furthermore, crystal mounting and rapid freezing in liquid nitrogen for cryo-data collection to trap labile reaction intermediates is demonstrated at the MaNDi time-of-flight instrument at the Spallation Neutron Source (SNS). Preparation of the model coordinate and diffraction data files and visualization of the neutron scattering length density (SLD) maps will also be addressed. Structure refinement against neutron data-only or against joint X-ray/neutron data to obtain an all-atom structure of the protein of interest will finally be discussed. The process of determining a neutron structure will be demonstrated using crystals of the lytic polysaccharide monooxygenase Neurospora crassa LPMO9D, a copper-containing metalloprotein involved in the degradation of recalcitrant polysaccharides via oxidative cleavage of the glycosidic bond. Neutron diffraction ; Neutron ; Neutron scattering ; Deuterium ; Materials science ; Crystallography ; Oak Ridge National Laboratory ; Spallation Neutron Source ; Scattering ; Neutron source ; Chemistry ; Crystal structure ; Optics ; Nuclear physics ; Physics Enzyme Structure and Function ; Nuclear Physics and Applications ; Protein Structure and Dynamics
Authors: Alexander Ovchinnikov | Svilen Bobev
Source: Zeitschrift für anorganische und allgemeine Chemie (article, 2020-05-25)
Field: Chemistry — Inorganic Chemistry

Studied and Forgotten. A Fresh Look at the Li–Mn–Ge System The crystal structure of the ternary germanide Li 2 MnGe has been re‐evaluated from single‐crystal X‐ray diffraction data. This compound crystallizes in a non‐centrosymmetric superstructure of the ZrCuSiAs type (space group P 4 bm , Pearson code tP 16), with the lattice parameters a = 6.088(4) Å, c = 6.323(4) Å. First‐principle calculations for the idealized structure predict antiferromagnetic exchange in the square Mn nets and semimetallic ground state. In addition, a new ternary phase with the composition Li 2– x Mn 4+ x Ge 5 ( x ≈ 1.2) was discovered. It adopts the V 6 Si 5 structure type (space group Ibam , Pearson code oI 44), with the lattice parameters a = 7.570(2) Å, b = 16.323(3) Å, c = 5.057(1) Å. DSC/TG measurements show that this compound is thermally stable below 995 K. Germanide ; Crystal structure ; Crystallography ; Antiferromagnetism ; Ternary operation ; Superstructure ; Lattice (music) ; Diffraction ; Materials science ; Condensed matter physics ; Chemistry ; Physics ; Thermodynamics ; Germanium ; Metallurgy Inorganic Chemistry and Materials ; Iron-based superconductors research ; Rare-earth and actinide compounds
Authors: A‐Andrew D. Jones | David Medina-Cruz | Na Yoon Kim | Gujie Mi | Caterina Bartomeu Garcia | Lorena Baranda-Pellejero | Nicole Bassous | Thomas J. Webster
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-07-19)
Field: Chemistry — Physical and Theoretical Chemistry

Statistical classification of dynamic bacterial growth with sub-inhibitory concentrations of nanoparticles and its implications for disease treatment Nanoparticles are promising alternatives to antibiotics since nanoparticles are easy to manufacture, non-toxic, and do not promote resistance. Nanoparticles act via physical disruption of the bacterial membrane and/or the generation of high concentrations of reactive-oxygen species locally. Potential for physical disruption of the bacterial membrane may be quantified by free energy methods, such as the extended Derjuan-Landau-Verwey-Overbeek theory, which predicts the initial surface-material interactions. The generation of reactive-oxygen species may be quantified using enthalpies of formation to predict minimum inhibitory concentrations. Neither of these two quantitative structure-activity values describes the dynamic, in situ behavioral changes in the bacteria’s struggle to survive. In this paper, borrowing parameters from logistic, oscillatory, and diauxic growth models, we use principal component analysis and agglomerative hierarchical clustering to classify survival modes across nanoparticle types and concentrations. We compare the growth parameters of 170 experimental interactions between nanoparticles and bacteria. The bacteria studied include Escherichia coli , Staphylococcus aureus , Methicillin-Resistant Staphylococcus aureus , Staphylococcus epidermidis , Pseudomonas aeruginosa , and Helicobacter pylori , and were tested across multiple concentrations of liposomal drug delivery systems, amphiphilic peptide, and silver and selenium nanoparticles. Clustering reveals specific pairs of bacteria and nanoparticles where the nanoparticle induced growth dynamics could potentially spread the infection through the development of resistance and tolerance. This rapid screening also shows that bacteria generated nanoparticles do not induce growth modes indicative of the development of resistance. This methodology can be used to rapidly screen for novel therapeutics that do not induce resistance before using more robust intracellular content screening. This methodology can also be used as a quality check on batch manufactured nanoparticles. Bacteria ; Nanoparticle ; Staphylococcus aureus ; Biophysics ; Pseudomonas aeruginosa ; Chemistry ; Minimum inhibitory concentration ; Escherichia coli ; Microbiology ; Antibiotic resistance ; Antibiotics ; Bacterial growth ; Biology ; Nanotechnology ; Materials science ; Biochemistry thermodynamics and calorimetric analyses ; Spectroscopy and Quantum Chemical Studies ; Material Dynamics and Properties
Authors: Mahmoud M. Sebaiy | Sobhy M. El-Adl | Amr A. Mattar
Source: The Gazette of Medical Sciences (article, 2020-05-31)
Field: Chemistry — Analytical Chemistry

Different techniques for Analysis of Aspirin, Caffeine, Diclofenac Sodium and Paracetamol: Review Article Early treatment of pain is of a great importance as unrelieved pain can have profound psychological effects on the patient, and acute pain that is poorly managed initially can degenerate into chronic pain, which may prove to be much more difficult to treat. It is important to assess and treat the mental and emotional aspects of the pain as well as its physical aspects. Although drug therapy is a mainstay of pain treatment, physical methods such as physiotherapy (including massage and the application of heat and cold), surgery, and drug monitoring are also very valuable. In this review article, we will shed the light on different ways of some analgesic drugs monitoring and analysis using different techniques in addition to the most recommended combinations of our cited drugs for pain relief. Medicine ; Analgesic ; Massage ; Diclofenac Sodium ; Aspirin ; Intensive care medicine ; Pain relief ; Physical therapy ; Pain ladder ; Anesthesia ; Alternative medicine ; Pharmacology ; Internal medicine ; Cancer pain Analytical Methods in Pharmaceuticals ; Pharmacological Effects and Assays ; Pain Mechanisms and Treatments
Authors: Martín Leandro Paleico | Jörg Behler
Source: The Journal of Chemical Physics (preprint, 2020-03-04)
Field: Materials Science — Materials Chemistry

A flexible and adaptive grid algorithm for global optimization utilizing basin hopping Monte Carlo Global optimization is an active area of research in atomistic simulations, and many algorithms have been proposed to date. A prominent example is basin hopping Monte Carlo, which performs a modified Metropolis Monte Carlo search to explore the potential energy surface of the system of interest. These simulations can be very demanding due to the high-dimensional configurational search space. The effective search space can be reduced by utilizing grids for the atomic positions, but at the cost of possibly biasing the results if fixed grids are employed. In this paper, we present a flexible grid algorithm for global optimization that allows us to exploit the efficiency of grids without biasing the simulation outcome. The method is general and applicable to very heterogeneous systems, such as interfaces between two materials of different crystal structures or large clusters supported at surfaces. As a benchmark case, we demonstrate its performance for the well-known global optimization problem of Lennard-Jones clusters containing up to 100 particles. Despite the simplicity of this model potential, Lennard-Jones clusters represent a challenging test case since the global minima for some "magic" numbers of particles exhibit geometries that are very different from those of clusters with only a slightly different size. Monte Carlo method ; Maxima and minima ; Global optimization ; Grid ; Computer science ; Benchmark (surveying) ; Statistical physics ; Algorithm ; Mathematical optimization ; Physics ; Mathematics ; Geometry Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; nanoparticles nucleation surface interactions
Authors: Alexey M. Vervald | Oleg S. Kudryavtsev | Andrey V. Lachko | Sergey Burikov | O. Shenderova | И. И. Власов | Tatiana A. Dolenko
Source: NANOCOM ... (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

THE SOURCE OF THE SURFACE FLUORESCENCE OF NANODIAMONDS In this paper photoluminescence properties of aqueous suspensions of carbon nanoparticles (nanodiamonds, carbon dots and complexes on their basis) with different ratio of surface carbon in sp 3 -and sp 2 -hybridizations were studied by methods of Raman, fluorescence and IR absorption spectroscopy. It was found that intensity of photoluminescence correlates with amount of carbon in non-diamond phase on the surface of nanoparticles. Nanoparticles with high non-diamond carbon phase content revealed more intense photoluminescence. The obtained results support the hypothesis about surface nature of photoluminescence of nanodiamonds and carbon dots. Fluorescence ; Surface (topology) ; Materials science ; Nanotechnology ; Computer science ; Physics ; Optics Diamond and Carbon-based Materials Research
Authors: Na Wu | Fei Liu | Yidan Bao | Mu Li | Wei Huang | Fanjia Meng | Chu Zhang | Yong He
Source: Research Square (preprint, 2020-11-20)
Field: Chemistry — Analytical Chemistry

Rapid and Accurate Varieties Identification of Different Crop Seeds Under Sample-Limited Condition Based on Hyperspectral Imaging and Deep Transfer Learning Abstract Background: Varieties identification of crop seeds is significant for breeders to screen out seeds with specific traits and for market regulators to detect seeds purity. Hyperspectral imaging technology provides a fast and non-destructive means for varieties identification. And deep learning algorithm is suitable for effective analysis of redundant spectral data. However, deep learning algorithms have serious big data dependency, while collecting high-quality large-scale samples was high-cost in many cases. This made it difficult to build an accurate identification model. This study aimed to explore a rapid and accurate method for varieties identification of different crop seeds under sample-limited condition based on hyperspectral imaging and deep transfer learning. Results: Three deep neural networks with typical structures were designed based on a samples-rich Pea dataset. Obtained the highest accuracy of 99.57 %, VGG-MODEL was transferred to classify four target datasets (Rice, Oat, Wheat, Cotton) with limited samples. The accuracies of deep transferred model achieved 95 %, 99 %, 80.8 %, and 83.86 % on the four datasets, respectively. Using training sets with different sizes, deep transferred model could always obtain higher performance than other traditional methods. Visualization of training process and classification results confirmed the portability of common features of seed spectra and provided an interpreted method for rapid and accurate varieties identification of crop seeds. Conclusions: This study combined hyperspectral imaging and deep transfer learning to identify varieties of different crop seeds, which was proved to be efficient under sample-limited condition. This facilitated crop variety screening process under the scenario of sample scarcity. It also provided a new idea for the detection of other qualities of crop seeds based on hyperspectral imaging under sample-limited condition. Hyperspectral imaging ; Crop ; Identification (biology) ; Sample (material) ; Transfer of learning ; Artificial intelligence ; Computer science ; Pattern recognition (psychology) ; Agronomy ; Biology ; Botany ; Chemistry ; Chromatography Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; GABA and Rice Research
Authors: Thien Dinh Hoang | Balázs Kovács | Tamás Madarász | Imre Czinkota
Source: Periodica Polytechnica Mechanical Engineering (article, 2020-12-02)
Field: Materials Science — Materials Chemistry

Changes in Mechanical Properties of Metallic Pipes Subjected to Accelerated Corrosion Test One of the most significant current discussions in fluid transport industry is how to prolong the service life of a metallic pipeline system under severe physical and chemical conditions. Electrochemical corrosion is a persistent problem, causing material degradation and sometimes resulting in serious consequences. Here more than 150 three-point bending tests were done on 82 corroded carbon steel pipes to examine their remaining strength. The current work proposes an artificial protocol to accelerate the electrochemical corrosion of ferrous tubes in a controllable system and analyzed correlations between removed iron mass, the depth of corroded sites, and the deterioration in the mechanical properties of the sample pipes. Based on these correlations, a rough estimate for the retirement life of pipelines is put forward as a referable option. Corrosion ; Service life ; Pipeline transport ; Materials science ; Electrochemical noise ; Metallurgy ; Carbon steel ; Bending ; Pipeline (software) ; Electrochemistry ; Forensic engineering ; Composite material ; Environmental science ; Engineering ; Mechanical engineering ; Electrode ; Environmental engineering Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Structural Integrity and Reliability Analysis
Authors: Joscha Nehrkorn | Igor A. Valuev | A.S. Bogomyakov | Elizaveta A. Suturina | Alena M. Sheveleva | В.И. Овчаренко | K. Holldack | Carmen Herrmann | Matvey V. Fedin | Alexander Schnegg | Sergey L. Veber
Source: Research Square (preprint, 2020-08-24)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Controlling Molecular Nanomagnet Properties by the Host Lattice Nanomagnet ; Host (biology) ; Lattice (music) ; Nanotechnology ; Materials science ; Physics ; Biology ; Genetics Magnetism in coordination complexes ; Porphyrin and Phthalocyanine Chemistry ; Organic and Molecular Conductors Research
Authors: Liliana Calzadiaz Ramirez | Carla Calvó‐Tusell | Gabriele Stoffel | Steffen N. Lindner | Sílvia Osuna | Tobias J. Erb | Marc Garcia‐Borràs | Arren Bar‐Even | Carlos G. Acevedo‐Rocha
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-04-03)
Field: Materials Science — Materials Chemistry

<i>In vivo</i> selection for formate dehydrogenases with high efficiency and specificity towards NADP <sup>+</sup> Abstract Efficient regeneration of cofactors is vital for the establishment of continuous biocatalytic processes. Formate is an ideal electron donor for cofactor regeneration due to its general availability, low reduction potential, and benign byproduct (CO 2 ). However, formate dehydrogenases (FDHs) are usual specific to NAD + , such that NADPH regeneration with formate is challenging. Previous studies reported naturally occurring FDHs or engineered FDHs that accept NADP + , but these enzymes show low kinetic efficiencies and specificities. Here, we harness the power of natural selection to engineer FDH variants to simultaneously optimize three properties: kinetic efficiency with NADP + , specificity towards NADP + , and affinity towards formate. By simultaneously mutating multiple residues of FDH from Pseudomonas sp. 101, which exhibits no initial activity towards NADP + , we generate a library of &gt;10 6 variants. We introduce this library into an E. coli strain that cannot produce NADPH. By selecting for growth with formate as sole NADPH source, we isolate several enzyme variants that support efficient NADPH regeneration. We find that the kinetically superior enzyme variant, harboring five mutations, has 5-fold higher efficiency and 13-fold higher specificity than the best enzyme previously engineered, while retaining high affinity towards formate. By using molecular dynamics simulations, we reveal the contribution of each mutation to the superior kinetics of this variant. We further determine how non-additive epistatic effects improve multiple parameters simultaneously. Our work demonstrates the capacity of in vivo selection to identify superior enzyme variants carrying multiple mutations which would be almost impossible to find using conventional screening methods. Formate ; Formate dehydrogenase ; Cofactor ; NAD+ kinase ; Enzyme ; Biochemistry ; Stereochemistry ; Directed evolution ; Chemistry ; Biology ; Mutant ; Gene ; Catalysis Enzyme Structure and Function ; Enzyme Catalysis and Immobilization ; Amino Acid Enzymes and Metabolism
Authors: Shaheer Rizwan | Douglas H. Pike | Saroj Poudel | Vikas Nanda
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-11-20)
Field: Materials Science — Materials Chemistry

Alternating handedness motifs in proteins classify structure and cofactor binding Abstract Cofactor binding sites in proteins often are composed of favorable interactions of specific cofactors with the sidechains and/or backbone protein fold motifs. In many cases these motifs contain left-handed conformations which enable tight turns of the backbone that present backbone amide protons in direct interactions with cofactors termed ‘cationic nests’. Here, we defined alternating handedness of secondary structure as a search constraint within the PDB to systematically identify these cofactor binding nests. We identify unique alternating handedness structural motifs which are specific to the cofactors they bind. These motifs can guide the design of engineered folds that utilize specific cofactors and also enable us to gain a deeper insight into the evolution of the structure of cofactor binding sites. Cofactor ; Protein Data Bank (RCSB PDB) ; Chemistry ; Binding site ; Structural motif ; Stereochemistry ; Computational biology ; Biology ; Biochemistry ; Enzyme Enzyme Structure and Function ; Protein Structure and Dynamics ; RNA and protein synthesis mechanisms
Authors: OLEG V. KOLMOGOROV | ANNA V. DEIKUN | EKATERINA V. CHEMESOVA
Source: H&ES Research (article, 2020-01-01)
Field: Chemistry — Analytical Chemistry

INSTALLATION FOR MEASURING SIGNAL PROPAGATION DELAYS IN OPTICAL ELEMENTS The results of the development of an installation for measuring signal propagation delays in optical elements and optical fibers are presented. Measuring the delays of signal propagation in optical elements and optical fibers required for the development of various instruments, in particular, the development of fiber-optic systems, the synchronization time scales for complexes of metrological support of the global navigation satellite system GLONASS and measuring means of ground-based GLONASS, the development of metrological maintenance of fiber-optic communication systems, the development radiophonic systems (e.g., phased arrays with fiber-optical channels, measuring systems with remote antennas). It is shown that the installation allows to implement phase and pulse methods for measuring signal propagation delays introduced by optical elements, as well as a modified pulse method designed to determine the delays in optical elements with a large signal attenuation, when the accuracy of measurements by other methods is reduced due to the increasing influence of noise measuring equipment. The developed method is based on registration of the pulse shape with the help of analog-to-digital Converter, the approximation was a data taking into account information about the original form of pulses to reduce random error caused by the influence of noise, and subsequent determination of temporal characteristics of pulses using parameters approximating functions. The application of the developed method for various forms of laser pulses is considered, the scheme of the installation implementing these methods is presented, and the results of experimental studies of the installation are presented. It is shown that the modified pulse method allows to reduce the measurement error of signal propagation delays in optical fibers and optical elements by 15–20% or more, depending on the introduced attenuation, and the installation for measuring signal propagation delays can be used to control the characteristics of optical fibers and optical elements of various fiber-optic systems. SIGNAL (programming language) ; GLONASS ; Optical fiber ; Attenuation ; Electronic engineering ; Computer science ; Noise (video) ; Metrology ; Optics ; Engineering ; Telecommunications ; Physics ; GNSS applications ; Global Positioning System Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Advanced Scientific Techniques and Applications
Authors: Michiko Yoshitake | Takashi KONO | Takuya Kadohira
Source: Journal of Computer Chemistry Japan (article, 2020-01-01)
Field: Materials Science — Surfaces, Coatings and Films

Program for Automatic Numerical Conversion of a Line Graph (Line Plot) A program for fully automatic conversion of line plots in scientific papers into numerical data has been developed. By the conversion of image data into numerical data, users can treat so-called 'spectra' such as X-ray photoelectron spectra and optical absorption spectra in their purpose, plotting them in different ways such as inverse of wave number, subtracting them from users' data, and so forth. This article reports details of the program consisting of many parts, with several deep-learning models with different functions, elimination of literal characters, color separation, etc. Most deep-learning models achieve accuracy higher than 95%. The usability is demonstrated with some examples. Usability ; Computer science ; Graph ; Line (geometry) ; Plot (graphics) ; Raw data ; Spectral line ; Artificial intelligence ; Algorithm ; Theoretical computer science ; Computer graphics (images) ; Mathematics ; Statistics ; Human–computer interaction ; Programming language ; Geometry ; Physics Electron and X-Ray Spectroscopy Techniques