jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Cecilia Virginia Gheran | Guillaume Rigaux | Maïté Callewaert | Alexandre Berquand | Michaël Molinari | Françoise Chuburu | Sorina Nicoleta Voicu | Anca Dinischiotu
Source: Nanomaterials (article, 2018-03-28)
Field: Materials Science — Biomaterials

Biocompatibility of Gd-Loaded Chitosan-Hyaluronic Acid Nanogels as Contrast Agents for Magnetic Resonance Cancer Imaging Although the research on nanogels incorporating Gd chelates for theranostic applications has grown exponentially in recent years, knowledge about their biocompatibility is limited. We compared the biocompatibility of Gd-loaded hyaluronic acid-chitosan-based nanogels (GdCA⊂CS-TPP/HA) with two chitosan concentrations (2.5 and 1.5 mg·mL<sup>-1</sup> respectively) using SVEC4-10 murine lymph node endothelial cells. The sulforhodamine B method and released lactate dehydrogenase (LDH) activity were used as cell viability tests. Reactive oxygen species (ROS), reduced glutathione (GSH) and malondialdehyde (MDA) were measured by spectrophotometric and fluorimetric methods. Nrf-2 protein expression was evaluated by Western blot analysis and genotoxicity by alkaline comet assay. After 24 h, the cells viability was not affected by all types and doses of nanogels. The increase of ROS induced a low decrease of GSH concentration and a time-dependent raise of MDA one was produced by citric GdDOTA⊂CS-TPP/HA with a chitosan concentration of 1.5 mg·mL<sup>-1</sup>, at the highest dose applied. None of the tested nanogels induced changes in Nrf-2 protein expression. A slight but significant genotoxic effect was caused only by citric GdDOTA⊂CS-TPP/HA where CS concentration was 1.5 mg·mL<sup>-1</sup>. Our results showed a better biocompatibility with lymph node endothelial cells for Gd-loaded hyaluronic acid-chitosan based nanogels with a concentration in chitosan of 2.5 mg·mL<sup>-1</sup>. Biocompatibility ; Chitosan ; Hyaluronic acid ; Lactate dehydrogenase ; Chemistry ; Viability assay ; Reactive oxygen species ; Nuclear chemistry ; Glutathione ; Citric acid ; Biochemistry ; Apoptosis ; Medicine ; Organic chemistry ; Enzyme ; Anatomy Nanoparticle-Based Drug Delivery ; Angiogenesis and VEGF in Cancer ; Nanoplatforms for cancer theranostics
Authors: Yongjin Cui | Lanjun Xu | Dong An | Zhe Liu | Jiancheng Gu | Shaoming Li | Xiaodong Zhang | Dehai Zhu | 2. Beijing Agricultural Machinery Experiment Appraisal and Popularization Station, Beijing 100079, China
Source: International journal of agricultural and biological engineering (article, 2018-01-01)
Field: Chemistry — Analytical Chemistry

Identification of maize seed varieties based on near infrared reflectance spectroscopy and chemometrics False seeds can often be seen in the maize seed market, leading to a serious decline in maize yield. Those existing variety identification methods are expensive, time consuming, and destructive to seeds. The aim of this study is to develop a cheap, fast and non-destructive method which can robustly identify large amounts of maize seed varieties based on near-infrared reflectance spectroscopy (NIRS) and chemometrics. Because it is difficult to establish models for every variety in the market, this study mainly investigated the performance of models based on a large number of samples (more than 40 major varieties in the market). The reflectance spectra of maize seeds were collected by two modes (bulk kernels mode and single kernel mode). Both collection modes can be applied to identification, but only the single kernel mode can be applied to purity sorting. The spectra were pretreated with smoothing, the first derivative and vector normalization; and then principal component analysis (PCA), linear discriminant analysis (LDA) and biomimetic pattern recognition (BPR) were applied to establish identification models. The environmental factors such as producing areas and years have a significant influence on the performance of the models. Therefore, the method to improve the robustness of the models was investigated in this study. New indexes (correct acceptance degree (CAD), correct rejection degree (CRD) and correct degree (CD)) were defined to analyze the performance of the models more accurately. Finally, the models obtained a mean correct discrimination rate of over 90%, and exhibited robust properties for samples harvested from different areas and years. The results showed that NIR technology combined with chemometrics methods such as PCA, LDA, and BPR could be a suitable and alternative technique to identify the authenticity of maize seed varieties. Keywords: maize, seed variety identification, near-infrared reflectance spectroscopy (NIRS), biomimetic pattern recognition (BPR) DOI: 10.25165/j.ijabe.20181102.2815 Citation: Cui Y J, Xu L J, An D, Liu Z, Gu J C, Li S M, et al. Identification of maize seed varieties based on near infrared reflectance spectroscopy and chemometrics. Int J Agric & Biol Eng, 2018; 11(2): 177–183. Chemometrics ; Principal component analysis ; Linear discriminant analysis ; Smoothing ; Mathematics ; Biological system ; Pattern recognition (psychology) ; Normalization (sociology) ; Kernel (algebra) ; Support vector machine ; Artificial intelligence ; Robustness (evolution) ; Near infrared reflectance spectroscopy ; Statistics ; Computer science ; Near-infrared spectroscopy ; Machine learning ; Chemistry ; Biology Spectroscopy and Chemometric Analyses
Authors: Linwen Zhang | Nikkita Khattar | Ildikó Kemenes | György Kemenes | Zita Zrínyi | Zsolt Pirger | Ákos Vértes
Source: Scientific Reports (article, 2018-08-09)
Field: Chemistry — Spectroscopy

Subcellular Peptide Localization in Single Identified Neurons by Capillary Microsampling Mass Spectrometry Single cell mass spectrometry (MS) is uniquely positioned for the sequencing and identification of peptides in rare cells. Small peptides can take on different roles in subcellular compartments. Whereas some peptides serve as neurotransmitters in the cytoplasm, they can also function as transcription factors in the nucleus. Thus, there is a need to analyze the subcellular peptide compositions in identified single cells. Here, we apply capillary microsampling MS with ion mobility separation for the sequencing of peptides in single neurons of the mollusk Lymnaea stagnalis, and the analysis of peptide distributions between the cytoplasm and nucleus of identified single neurons that are known to express cardioactive Phe-Met-Arg-Phe amide-like (FMRFamide-like) neuropeptides. Nuclei and cytoplasm of Type 1 and Type 2 F group (Fgp) neurons were analyzed for neuropeptides cleaved from the protein precursors encoded by alternative splicing products of the FMRFamide gene. Relative abundances of nine neuropeptides were determined in the cytoplasm. The nuclei contained six of these peptides at different abundances. Enabled by its relative enrichment in Fgp neurons, a new 28-residue neuropeptide was sequenced by tandem MS. Cytoplasm ; FMRFamide ; Neuropeptide ; Peptide ; Nucleus ; Chemistry ; Subcellular localization ; Alternative splicing ; Biology ; Cell biology ; Biochemistry ; Gene ; Messenger RNA Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Yanpeng Hao | Jie Wei | Xiaolan Jiang | Lin Yang | Licheng Li | Junke Wang | Hao Li | Ruihai Li
Source: Energies (article, 2018-02-02)
Field: Materials Science — Materials Chemistry

Icing Condition Assessment of In-Service Glass Insulators Based on Graphical Shed Spacing and Graphical Shed Overhang Icing on transmission lines might lead to ice flashovers of insulators, collapse of towers, tripping faults of transmission lines, and other accidents. Shed spacing and shed overhang of insulators are clues for evaluating the probability of ice flashover. This paper researches image-processing methods for the natural icing of in-service glass insulators. Calculation methods of graphical shed spacing and graphical shed overhang are proposed via recognizing the convexity defects of the contours of an icing insulator string based on the GrabCut segmentation algorithm. The experiments are carried out with image data from our climatic chamber and the China Southern Power Grid Disaster (Icing) Warning System of Transmission Lines. The results show that the graphical shed overhang of insulators show evident change due to icing. This method can recognize the most serious icing conditions where the insulator sheds are completely bridged. Also, it can detect bridging positions including the left side, right side, or both sides of the insulator strings in the images. Icing ; Arc flash ; Insulator (electricity) ; Tripping ; Electric power transmission ; Engineering ; Structural engineering ; Forensic engineering ; Meteorology ; Electrical engineering ; Physics High voltage insulation and dielectric phenomena ; Icing and De-icing Technologies ; Power Line Inspection Robots
Authors: Naeem Agjee | Onisimo Mutanga | Kabir Peerbhay | Riyad Ismail
Source: Journal of Spectroscopy (article, 2018-01-01)
Field: Chemistry — Analytical Chemistry

The Impact of Simulated Spectral Noise on Random Forest and Oblique Random Forest Classification Performance Hyperspectral datasets contain spectral noise, the presence of which adversely affects the classifier performance to generalize accurately. Despite machine learning algorithms being regarded as robust classifiers that generalize well under unfavourable noisy conditions, the extent of this is poorly understood. This study aimed to evaluate the influence of simulated spectral noise (10%, 20%, and 30%) on random forest (RF) and oblique random forest (oRF) classification performance using two node-splitting models (ridge regression (RR) and support vector machines (SVM)) to discriminate healthy and low infested water hyacinth plants. Results from this study showed that RF was slightly influenced by simulated noise with classification accuracies decreasing for week one and week two with the addition of 30% noise. In comparison to RF, oRF-RR and oRF-SVM yielded higher test accuracies (oRF-RR: 5.36%–7.15%; oRF-SVM: 3.58%–5.36%) and test kappa coefficients (oRF-RR: 10.72%–14.29%; oRF-SVM: 7.15%–10.72%). Notably, oRF-RR test accuracies and kappa coefficients remained consistent irrespective of simulated noise level for week one and week two while similar results were achieved for week three using oRF-SVM. Overall, this study has demonstrated that oRF-RR can be regarded a robust classification algorithm that is not influenced by noisy spectral conditions. Random forest ; Support vector machine ; Artificial intelligence ; Noise (video) ; Mathematics ; Hyperspectral imaging ; Pattern recognition (psychology) ; Statistics ; Computer science ; Machine learning Spectroscopy and Chemometric Analyses ; Remote-Sensing Image Classification ; Remote Sensing in Agriculture
Authors: Rohil Daya | C. F. Desai | Bruce Vernham
Source: Emission Control Science and Technology (article, 2018-07-24)
Field: Materials Science — Materials Chemistry

Development and Validation of a Two-Site Kinetic Model for NH3-SCR over Cu-SSZ-13. Part 1. Detailed Global Kinetics Development Based on Mechanistic Considerations Catalysis ; Chemistry ; NOx ; Selective catalytic reduction ; Copper ; Desorption ; Decomposition ; Ion ; Inorganic chemistry ; Physical chemistry ; Adsorption ; Combustion ; Organic chemistry Catalytic Processes in Materials Science ; Ammonia Synthesis and Nitrogen Reduction ; Nanomaterials for catalytic reactions
Authors: Alberto Cingolani | Tommaso Casalini | Stefano Caimi | Antoine Klaue | Mattia Sponchioni | Filippo Rossi | Giuseppe Perale
Source: Polymers (article, 2018-08-01)
Field: Materials Science — Biomaterials

A Methodologic Approach for the Selection of Bio-Resorbable Polymers in the Development of Medical Devices: The Case of Poly(l-lactide-co-ε-caprolactone) In the last decades bioresorbable and biodegradable polymers have gained a very good reputation both in research and in industry thanks to their unique characteristics. They are able to ensure high performance and biocompatibility, at the same time avoiding post-healing surgical interventions for device removal. In the medical device industry, it is widely known that product formulation and manufacturing need to follow specific procedures in order to ensure both the proper mechanical properties and desired degradation profile. Moreover, the sterilization method is crucial and its impact on physical properties is generally underestimated. In this work we focused our attention on the effect of different terminal sterilization methods on two commercially available poly(l-lactide-<i>co</i>-ε-caprolactone) with equivalent chemical composition (70% PLA and 30% PCL) and relatively similar initial molecular weights, but different chain arrangements and crystallinity. Results obtained show that crystallinity plays a key role in helping preserve the narrow distribution of chains and, as a consequence, defined physical properties. These statements can be used as guidelines for a better choice of the most adequate biodegradable polymers in the production of resorbable medical devices. Crystallinity ; Biocompatibility ; Materials science ; Caprolactone ; Polymer ; Biodegradable polymer ; Polyester ; Lactide ; Biochemical engineering ; Process engineering ; Composite material ; Engineering biodegradable polymer synthesis and properties ; Additive Manufacturing and 3D Printing Technologies ; Electrospun Nanofibers in Biomedical Applications
Authors: Maria Hoppe | Pim de Voogt | Roland Franz
Source: Food Packaging and Shelf Life (article, 2018-07-15)
Field: Materials Science — Polymers and Plastics

Oligomers in polyethylene naphthalate and polybutylene terephthalate – Identification and exploring migration Oligomer ; Polybutylene terephthalate ; Trimer ; Polyethylene naphthalate ; Monomer ; Materials science ; Polyester ; Polymer chemistry ; Polyethylene terephthalate ; Polymer ; Chemical engineering ; Composite material ; Organic chemistry ; Chemistry ; Dimer Polymer crystallization and properties ; biodegradable polymer synthesis and properties ; Microplastics and Plastic Pollution
Authors: Frédéric A. Perras | Marek Pruski
Source: The Journal of Chemical Physics (article, 2018-10-19)
Field: Chemistry — Spectroscopy

Large-scale <i>ab initio</i> simulations of MAS DNP enhancements using a Monte Carlo optimization strategy Magic-angle-spinning (MAS) dynamic nuclear polarization (DNP) has recently emerged as a powerful technology enabling otherwise unrealistic solid-state NMR experiments. The simulation of DNP processes which might, for example, aid in refining the experimental conditions or the design of better performing polarizing agents, is, however, plagued with significant challenges, often limiting the system size to only 3 spins. Here, we present the first approach to fully <i>ab initio</i> large-scale simulations of MAS DNP enhancements. The Landau-Zener equation is used to treat all interactions concerning electron spins, and the low-order correlations in the Liouville space method is used to accurately treat the spin diffusion, as well as its MAS speed dependence. As the propagator cannot be stored, a Monte Carlo optimization method is used to determine the steady-state enhancement factors. This new software is employed to investigate the MAS speed dependence of the enhancement factors in large spin systems where spin diffusion is of importance, as well as to investigate the impacts of solvent and polarizing agent deuteration on the performance of MAS DNP. Monte Carlo method ; Spins ; Statistical physics ; Ab initio ; Kinetic Monte Carlo ; Physics ; Computational physics ; Condensed matter physics ; Quantum mechanics ; Mathematics Advanced NMR Techniques and Applications ; Solid-state spectroscopy and crystallography ; Muon and positron interactions and applications
Authors: Peng Chen | Jin‐Shi Sun | Lei Zhang | Wenyue Ma | Fuxing Sun | Guangshan Zhu
Source: Science China Materials (article, 2018-08-10)
Field: Chemistry — Inorganic Chemistry

Porous aromatic framework (PAF-1) as hyperstable platform for enantioselective organocatalysis Enantioselective synthesis ; Organocatalysis ; Cyclohexanone ; Catalysis ; Aldol reaction ; Organic chemistry ; Materials science ; Combinatorial chemistry ; Chemistry Metal-Organic Frameworks: Synthesis and Applications ; Covalent Organic Framework Applications ; Chemical Synthesis and Reactions
Authors: Kei Terayama | Tomoki Yamashita | Tamio Oguchi | Koji Tsuda
Source: npj Computational Materials (article, 2018-07-04)
Field: Materials Science — Materials Chemistry

Fine-grained optimization method for crystal structure prediction Abstract Crystal structure prediction based on first-principles calculations is often achieved by applying relaxation to randomly generated initial structures. Relaxing a structure requires multiple optimization steps. It is time consuming to fully relax all the initial structures, but it is difficult to figure out which initial structure leads to the optimal solution in advance. In this paper, we propose a optimization method for crystal structure prediction, called Look Ahead based on Quadratic Approximation, that optimally assigns optimization steps to each candidate structure. It allows us to identify the most stable structure with a minimum number of total local optimization steps. Our simulations using known systems Si, NaCl, Y 2 Co 17 , Al 2 O 3 , and GaAs showed that the computational cost can be reduced significantly compared to random search. This method can be applied for controlling all kinds of local optimizations based on first-principles calculations to obtain best results under restricted computational resources. Crystal structure prediction ; Relaxation (psychology) ; Quadratic equation ; Computer science ; Mathematical optimization ; Optimization algorithm ; Crystal structure ; Algorithm ; Mathematics ; Chemistry ; Geometry ; Crystallography Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Surface Chemistry and Catalysis
Authors: Ramin Nikzad‐Langerodi | Edwin Lughofer | Carlos Cernuda | Thomas Reischer | Wolfgang Kantner | Marcin Pawliczek | Markus Brandstetter
Source: Analytica Chimica Acta (article, 2018-02-08)
Field: Chemistry — Analytical Chemistry

Calibration model maintenance in melamine resin production: Integrating drift detection, smart sample selection and model adaptation Partial least squares regression ; Chemometrics ; Chemistry ; Calibration ; Sample (material) ; Detector ; Biological system ; Artificial intelligence ; Statistics ; Pattern recognition (psychology) ; Computer science ; Chromatography ; Mathematics Spectroscopy and Chemometric Analyses ; Fault Detection and Control Systems ; Advanced Chemical Sensor Technologies
Authors: Mathew Baldwin | Sarah Snelling | Stephanie G. Dakin | Andrew Carr
Source: Journal of The Royal Society Interface (review, 2018-04-25)
Field: Materials Science — Biomaterials

Augmenting endogenous repair of soft tissues with nanofibre scaffolds As our ability to engineer nanoscale materials has developed we can now influence endogenous cellular processes with increasing precision. Consequently, the use of biomaterials to induce and guide the repair and regeneration of tissues is a rapidly developing area. This review focuses on soft tissue engineering, it will discuss the types of biomaterial scaffolds available before exploring physical, chemical and biological modifications to synthetic scaffolds. We will consider how these properties, in combination, can provide a precise design process, with the potential to meet the requirements of the injured and diseased soft tissue niche. Finally, we frame our discussions within clinical trial design and the regulatory framework, the consideration of which is fundamental to the successful translation of new biomaterials. Biomaterial ; Tissue engineering ; Regeneration (biology) ; Nanotechnology ; Computer science ; Process (computing) ; Biochemical engineering ; Biocompatible material ; Soft tissue ; Biomedical engineering ; Materials science ; Engineering ; Biology ; Cell biology ; Medicine Electrospun Nanofibers in Biomedical Applications ; Bone Tissue Engineering Materials ; Tissue Engineering and Regenerative Medicine
Authors: Quang H. Luu | Kyle G. Lewis | Anik Banerjee | Nattamai Bhuvanesh | John A. Gladysz
Source: Chemical Science (article, 2018-01-01)
Field: Chemistry — Spectroscopy

The robust, readily available cobalt(<scp>iii</scp>) trication [Co(NH<sub>2</sub>CHPhCHPhNH<sub>2</sub>)<sub>3</sub>]<sup>3+</sup> is a progenitor of broadly applicable chirality and prochirality sensing agents When NMR spectra of chiral racemic organic molecules containing a Lewis basic functional group are recorded in the presence of air and water stable salts of the cobalt(iii) trication [Co((<i>S</i>,<i>S</i>)-NH<sub>2</sub>CHPhCHPhNH<sub>2</sub>)<sub>3</sub>]<sup>3+</sup> (<b>2</b><sup>3+</sup>), separate signals are usually observed for the enantiomers (28 diverse examples, >12 functional groups). Several chiral molecules can be simultaneously analyzed, and enantiotopic groups in prochiral molecules differentiated (16 examples). Particularly effective are the mixed bis(halide)/tetraarylborate salts Λ-<b>2</b><sup>3+</sup> 2X<sup>-</sup>BAr<sub>f</sub><sup>-</sup> (X = Cl, I; BAr<sub>f</sub> = B(3,5-C<sub>6</sub>H<sub>3</sub>(CF<sub>3</sub>)<sub>2</sub>)<sub>4</sub>), which are applied in CD<sub>2</sub>Cl<sub>2</sub> or CDCl<sub>3</sub> at 1-100 mol% (avg 34 and 14 mol%). Job plots establish 1 : 1 binding for Λ-<b>2</b><sup>3+</sup> 2Cl<sup>-</sup>BAr<sub>f</sub><sup>-</sup> and 1-phenylethyl acetate (<b>4</b>) or 1-phenylethanol (<b>10</b>), and <i>ca.</i> 1 : 2 binding with DMSO (CD<sub>2</sub>Cl<sub>2</sub>). Selected binding constants are determined, which range from 7.60-2.73 M<sup>-1</sup> for the enantiomers of <b>10</b> to 28.1-22.6 M<sup>-1</sup> for the enantiomers of <b>4</b>. The NH moieties of the <i>C</i><sub>2</sub> faces of the trication are believed to hydrogen bond to the Lewis basic functional groups, as seen in the crystal structure of a hexakis(DMSO) solvate of Λ-<b>2</b><sup>3+</sup> 3I<sup>-</sup>. These salts rank with the most broadly applicable chirality sensing agents discovered to date. Cobalt ; Chirality (physics) ; Chemistry ; Physics ; Crystallography ; Inorganic chemistry ; Nuclear physics Molecular Sensors and Ion Detection ; Crystallography and molecular interactions ; Molecular spectroscopy and chirality
Authors: Praveen Chappa | Arthanareeswari Maruthapillai | Rajasekhar Voguri | Archan Dey | Subhas Ghosal | Mohamed Amjad Basha
Source: Crystal Growth & Design (article, 2018-11-05)
Field: Chemistry — Physical and Theoretical Chemistry

Drug–Polymer Co-Crystals of Dapsone and Polyethylene Glycol: An Emerging Subset in Pharmaceutical Co-Crystals The role of a polymer as coformer is not a well-explored area for pharmaceutical co-crystals. To investigate this class of materials, a series of seven co-crystals, which are composed of dapsone and polyethylene glycol are reported. A promising strategy for fine-tuning physicochemical properties namely, crystallinity, thermal stability, hygroscopicity, and solubility was discussed via an in-depth structural understanding. Molecular insights into drug–polymer interactions and co-crystal formation are elaborated from the single crystal X-ray structure determination, Fourier transform infrared spectroscopy, differential scanning calorimetry, and hot-stage microscopy studies. Polyethylene glycol ; Crystallinity ; Differential scanning calorimetry ; Polymer ; Materials science ; Chemical engineering ; Solubility ; Fourier transform infrared spectroscopy ; Infrared spectroscopy ; Polyethylene ; Polymer chemistry ; Chemistry ; Organic chemistry ; Composite material Crystallography and molecular interactions ; Crystallization and Solubility Studies ; Analytical Chemistry and Chromatography