jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Vineet Thumuluri | Hannah-Marie Martiny | José Juan Almagro Armenteros | Jesper Salomon | Henrik Nielsen | Alexander Rosenberg Johansen
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-07-22)
Field: Materials Science — Materials Chemistry

NetSolP: predicting protein solubility in E. coli using language models Abstract Solubility and expression levels of proteins can be a limiting factor for large-scale studies and industrial production. By determining the solubility and expression directly from the protein sequence, the success rate of wet-lab experiments can be increased. In this study, we focus on predicting the solubility and usability for purification of proteins expressed in Escherichia coli directly from the sequence. Our model NetSolP is based on deep learning protein language models called transformers and we show that it achieves state-of-the-art performance and improves extrapolation across datasets. As we find current methods are built on biased datasets, we curate existing datasets by using strict sequence-identity partitioning and ensure that there is minimal bias in the sequences. The predictor is available at https://services.healthtech.dtu.dk/service.php?NetSolP-1.0 Solubility ; Extrapolation ; Usability ; Computer science ; Sequence (biology) ; Limiting ; Escherichia coli ; Protein sequencing ; Scale (ratio) ; Data mining ; Chemistry ; Artificial intelligence ; Machine learning ; Peptide sequence ; Biochemistry ; Mathematics ; Engineering ; Physics ; Statistics Machine Learning in Materials Science ; Protein Structure and Dynamics ; Machine Learning in Bioinformatics
Authors: Ayslan S. P. Da Costa | Joshua Goncalves | Hosana O. Á. Neta | Douglas Alves | Elton Franceschi | Cláudio Dariva | Gustavo R. Borges | Manuela Souza Leite
Source: South Florida Journal of Development (article, 2021-03-02)
Field: Chemistry — Analytical Chemistry

Machine learning applied as an in-situ monitoring technique for the water content in oil recovered by means of NIR spectroscopy The present work proposes a study on the combination of artificial neural network based model and multivariate calibration techniques, as principais component analysis (PCA) and partial least squares (PLS) combined with near infrared spectrophotometer (NIR) to formulate online water content monitoring models for recovered fuel oils after effluent treatment of a Brazilian thermoelectric plant. The database for adjustments of these models was built using oil samples supplied by the SUAPE II thermoelectric plant, where they were characterized in laboratories and analyzed via NIR. 450 spectra were used to construct the PLS model for predictive model calibration using the PLS technique and 118 spectra for the model based on artificiais neurais networks. In the obtained PLS model, it was possible to obtain correlations around 0.97, cross-validation error (RMSECV) of 0.0906 and test prediction error (RMSEP) of 0.0651. The RNA model presented coefficient of determination R² of 0.99 for training and R² of 0.98 for test with prediction error of 0.062 Partial least squares regression ; Calibration ; Near-infrared spectroscopy ; Artificial neural network ; Computer science ; Multivariate statistics ; Mean squared error ; Cross-validation ; Content (measure theory) ; Artificial intelligence ; Biological system ; Machine learning ; Mathematics ; Statistics ; Physics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Chemical Sensor Technologies
Authors: Zhengwei Huang | Fangqin Fu | Linjing Wu | Wenhao Wang | Wenhua Wang | Chaonan Shi | Ying Huang | Xin Pan | Chuanbin Wu
Source: Frontiers of Materials Science (article, 2021-11-18)
Field: Materials Science — Biomaterials

Bibliometric landscape of the researches on protein corona of nanoparticles Unclear biological fate hampers the clinical translation of nanoparticles for biomedical uses. In recent years, it is documented that the formation of protein corona upon nanoparticles is a critical factor leading to the ambiguous biological fate. Efforts have been made to explore the protein corona forming behaviors on nanoparticles, and rearrangement of the relevant studies will help to understand the current trend of such a topic. In this work, the publications about protein corona of nanoparticles in Science Citation Index Expanded database of Web of Science from 2007 to 2020 (1417 in total) were analyzed in detail, and the bibliometrics landscape of them was showcased. The basic bibliometrics characteristics were summarized to provide an overall understanding. Citation analysis was performed to scrutinize the peer interests of these papers. The research hotspots in the field were evaluated, based on which some feasible topics for future studies were proposed. In general, the results demonstrated that protein corona of nanoparticles was a prospective research area, and had attracted global research interests. It was believed that this work could comprehensively highlight the bibliometrics landscape, inspire further exploitation on protein corona of nanoparticles, and ultimately promote the clinical translation of nanoparticles. Bibliometrics ; Corona (planetary geology) ; Citation ; Nanotechnology ; Web of science ; Nanoparticle ; Science Citation Index ; Data science ; Computer science ; Materials science ; World Wide Web ; MEDLINE ; Chemistry ; Physics Nanoparticle-Based Drug Delivery ; Polymer Surface Interaction Studies ; Protein Interaction Studies and Fluorescence Analysis
Authors: Joshua Laniado | Kyle Meador | Todd O. Yeates
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-01-14)
Field: Materials Science — Materials Chemistry

A fragment-based protein interface design algorithm for symmetric assemblies ABSTRACT Theoretical and experimental advances in protein engineering have led to the creation of precisely defined, novel protein assemblies of great size and complexity, with diverse applications. One powerful approach involves designing a new attachment or binding interface between two simpler symmetric oligomeric protein components. The required methods of design, which present both similarities and key differences compared to problems in protein docking, remain challenging, and are not yet routine. With the aim of more fully enabling this emerging area of protein material engineering, we developed a computer program, Nanohedra, to introduce two key advances. First, we encoded in the program the construction rules ( i . e . the search space parameters) that underlie all possible symmetric material constructions. Second, we developed algorithms for rapidly identifying favorable docking/interface arrangements based on tabulations of empirical patterns of known protein fragment-pair associations. As a result, the candidate poses that Nanohedra generates for subsequent amino acid interface design appear highly native-like (at the protein backbone level), while simultaneously conforming to the exacting requirements for symmetry-based assembly. A retrospective computational analysis of successful vs failed experimental studies supports the expectation that this should improve the success rate for this challenging area of protein engineering. Computer science ; Fragment (logic) ; Interface (matter) ; Protein engineering ; Protein design ; Key (lock) ; Algorithm ; Protein structure ; Theoretical computer science ; Distributed computing ; Chemistry ; Parallel computing ; Biochemistry Enzyme Structure and Function ; Bacteriophages and microbial interactions ; Protein Structure and Dynamics
Authors: Tobias Binninger | Adrian Heinritz | Rhiyaad Mohamed
Source: ChemRxiv (preprint, 2021-10-11)
Field: Chemistry — Organic Chemistry

Ideal Gas Reference for Association and Dissociation Reactions: I. Basic Concepts Starting with a distance-based definition of molecules consisting of non-interacting atoms, which is in line with IUPAC terminology, we construct an ideal gas reference for chemical association and dissociation reactions. The corresponding ideal equations for equilibria and kinetics reveal the mathematical structure, known for real systems, in comprehensible clarity. The ideal gas reference corresponds to the limit of an entirely flat potential energy surface of the system where chemical equilibria and kinetics are determined by "unspecific" particle number combinatorics according to the reaction stoichiometry. The ideal equilibrium and rate constants provide a reference for the definition of excess equilibrium and rate constants of real reactions that quantify all "system-specific" contributions resulting from the particular shape of the potential energy surface. The ideal gas reference therefore enables a distinction between unspecific and system-specific aspects in the equilibria and kinetics of chemical association/dissociation reactions. Whereas conventional equilibrium and rate constants suffer from incompatibility between reactions of different stoichiometry, excess equilibrium and rate constants can be consistently compared across different reaction orders. Furthermore, whereas the conventional treatment requires an arbitrary specification of reference concentrations, e.g. at standard conditions, the ideal gas framework introduces an intrinsic concentration scale that is equal to the inverse of a molecular volume. Chemistry ; Thermodynamics ; Ideal gas ; Dissociation (chemistry) ; Equilibrium constant ; Stoichiometry ; Chemical equilibrium ; Reaction rate constant ; Chemical nomenclature ; Kinetics ; Chemical reaction ; Inverse ; Physical chemistry ; Statistical physics ; Mathematics ; Physics ; Organic chemistry ; Quantum mechanics Chemical Thermodynamics and Molecular Structure ; History and advancements in chemistry ; Chemistry and Stereochemistry Studies
Authors: Leon Amadeus Varga | Jan Makowski | Andreas Zell
Source:  (preprint, 2021-07-18)
Field: Chemistry — Analytical Chemistry

Measuring the Ripeness of Fruit with Hyperspectral Imaging and Deep Learning We present a system to measure the ripeness of fruit with a hyperspectral camera and a suitable deep neural network architecture. This architecture did outperform competitive baseline models on the prediction of the ripeness state of fruit. For this, we recorded a data set of ripening avocados and kiwis, which we make public. We also describe the process of data collection in a manner that the adaption for other fruit is easy. The trained network is validated empirically, and we investigate the trained features. Furthermore, a technique is introduced to visualize the ripening process. Ripeness ; Hyperspectral imaging ; Ripening ; Computer science ; Artificial intelligence ; Deep learning ; Process (computing) ; Measure (data warehouse) ; Pattern recognition (psychology) ; Data mining ; Horticulture ; Biology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Postharvest Quality and Shelf Life Management
Authors: Fabio Le Piane | Matteo Baldoni | Mauro Gáspari | Francesco Mercuri
Source: Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (article, 2021-11-03)
Field: Materials Science — Materials Chemistry

Introducing MAMBO: Materials And Molecules Basic Ontology Recent advances in computational and experimental technologies applied to the design and development of novel materials have brought out the need for systematic, rational and efficient methods for the organization of knowledge in the field. &#13;\nIn this work, we present the initial steps carried out in the development of MAMBO - an ontology focused on the organization of concepts and knowledge in the field of materials based on molecules and targeted to applications. &#13;\nOur approach is guided by the needs of the communities involved in the development of novel molecular materials with functional properties at the nanoscale. &#13;\nAs such, MAMBO aims at bridging the gaps of ongoing efforts in the development of ontologies in the materials science domain. &#13;\nBy extending current work in the field, the modular nature of MAMBO also allows straightforward extension of concepts and relations to neighboring domains. &#13;\nOur work is expected to enable the systematic integration of computational and experimental data in specific domains of interest &#13;\n(nanomaterials, molecular materials, organic an polymeric materials,&#13;\nsupramolecular and bio-organic systems, etc.). &#13;\nMoreover, MAMBO can be applied to the development of data-driven integrated predictive frameworks for the design of novel materials with tailored functional properties. Computer science ; Bridging (networking) ; Ontology ; Modular design ; Field (mathematics) ; Nanotechnology ; Data science ; Domain (mathematical analysis) ; Systems engineering ; Materials science ; Engineering ; Epistemology ; Programming language Machine Learning in Materials Science ; Computational Drug Discovery Methods ; History and advancements in chemistry
Authors: Xiaowei Song | Jia Li | Mohammad Mofidfar | Richard N. Zare
Source: Preprints.org (preprint, 2021-10-04)
Field: Chemistry — Spectroscopy

Distinguishing Between Isobaric Ions Using Microdroplet Hydrogen-Deuterium Exchange Mass Spectrometry Isobaric ions having the same mass-to-charge ratio cannot be separately identified by mass spectrometry (MS) alone, but this limitation can be overcome using hydrogen-deuterium exchange (HDX) in microdroplets. Because isobaric ions may contain a varied number of exchangeable sites and different types of functional groups, each one produces a unique MS spectral pattern after droplet spray HDX without the need for MS/MS experiments or introduction of ion mobility measurements. As an example of the power of this approach, isobaric ions in urinary metabolic profiles are identified and used to distinguish between healthy individuals and those having bladder cancer. Isobaric process ; Hydrogen–deuterium exchange ; Mass spectrometry ; Ion ; Deuterium ; Chemistry ; Ion-mobility spectrometry ; Isobaric labeling ; Hydrogen ; Analytical Chemistry (journal) ; Atomic physics ; Chromatography ; Physics ; Thermodynamics ; Tandem mass spectrometry ; Protein mass spectrometry ; Organic chemistry Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Isotope Analysis in Ecology
Authors: Yasir Musa Dakwar | Simon Lineykin | Moshe Sitbon
Source: Micromachines (article, 2021-10-31)
Field: Materials Science — Materials Chemistry

Analysis, Modeling, and Simulation of Thin-Film Cells-Based Photovoltaic Generator Combined with Multilayer Thermoelectric Generator A new model for a multi-stage thermoelectric generator (TEG) is developed. An electrical and thermal model is built and simulated for different configurations of photovoltaic (PV) stand-alone hybrid systems, combining different stages of a TEG. The approach is evaluated with and without cooling by coupling a cold plate to a multi-stage hybrid PVTEG system. The model can be adjusted by sizing and specifying the influence of stage number on the overall produced power. Amorphous silicon thin-film (a-Si) is less affected by rising temperature compared to other technology. Hence, it was chosen for evaluating the lower limit gain in a hybrid system under various ambient temperatures and irradiances. The dynamics of the PVTEG system are presented under different coolant water flow rates. Finally, comparative electrical efficiency in reference to PV stand-alone was found to be 99.2% for PVTEG without cooling, 113.5% for PVTEG, and 117.3% for multi-stage PVTEG, accordingly installing multi-stage PVTEG at Israel in a typical year with an average PV yield of 1750&nbsp;kWh/kW/year generates an extra 24&nbsp;kWh/year per module hence avoiding fossil energy and equivalent CO2 emissions. Photovoltaic system ; Thermoelectric generator ; Sizing ; Materials science ; Coolant ; Environmental science ; Nuclear engineering ; Automotive engineering ; Water cooling ; Thermoelectric effect ; Process engineering ; Mechanical engineering ; Computer science ; Electrical engineering ; Engineering ; Thermodynamics ; Physics Advanced Thermoelectric Materials and Devices ; Thermal Radiation and Cooling Technologies ; Advanced Thermodynamics and Statistical Mechanics
Authors: Grzegorz Chojnowski | Adam J. Simpkin | Diego A. Leonardo | Wolfram Seifert-Dávila | Dan E. Vivas-Ruiz | Ronan M. Keegan | Daniel J. Rigden
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-04-18)
Field: Materials Science — Materials Chemistry

Identification of unknown proteins in X-ray crystallography and cryo-EM Abstract Although experimental protein structure determination usually targets known proteins, chains of unknown sequence are often encountered. They can be purified from natural sources, appear as an unexpected fragment of a well characterized protein or as a contaminant. Regardless of the source of the problem, the unknown protein always requires tedious characterization. Here we present an automated pipeline for the identification of protein sequences from cryo-EM reconstructions and crystallographic data. We present the method’s application to characterize the crystal structure of an unknown protein purified from a snake venom. We also show that the approach can be successfully applied to the identification of protein sequences and validation of sequence assignments in cryo-EM protein structures. Identification (biology) ; Sequence (biology) ; Computational biology ; Characterization (materials science) ; Protein crystallization ; Protein sequencing ; Protein structure ; Crystallography ; Fragment (logic) ; Pipeline (software) ; Chemistry ; Peptide sequence ; Biology ; Computer science ; Biochemistry ; Algorithm ; Materials science ; Nanotechnology Enzyme Structure and Function ; Advanced Electron Microscopy Techniques and Applications ; Protein Structure and Dynamics
Authors: D. Josephine Selvarani Ruth
Source: Transactions of Indian National Academy of Engineering (article, 2021-03-03)
Field: Materials Science — Materials Chemistry

Design Concepts for NiTiNOL Wires to Function as a Sensor Abstract Nickel Titanium Naval Ordinance Laboratory (NiTiNOL) is widely called as a shape memory alloy (SMA), a class of nonlinear smart material inherited with the functionally programmed property of varying electrical resistance during the transformation enabling to be positioned as a sensing element. The major challenge to instrument the SMA wires is to suppress the wires’ nonlinearity by proper selection of two important factors. The first factor is influenced by the mechanical biasing element and the other is to identify the sensing current for the sensing device (SMA wires + biasing). This paper focuses on developing SMA wires for sensing in different orientation types and configurations by removing the non-linearity in the system’s output by introducing inverse hysteresis to the wires through the passive mechanical element. SMA* ; Shape-memory alloy ; Biasing ; Hysteresis ; Materials science ; Linearity ; Nonlinear system ; Smart material ; Nickel titanium ; Mechanical engineering ; Computer science ; Voltage ; Electronic engineering ; Electrical engineering ; Engineering ; Nanotechnology ; Composite material ; Physics Shape Memory Alloy Transformations ; Aeroelasticity and Vibration Control ; Ferroelectric and Piezoelectric Materials
Authors: Mahmoud M. Sebaiy
Source: Biomedical Journal of Scientific & Technical Research (article, 2021-02-24)
Field: Chemistry — Analytical Chemistry

Analytical Methods for Determination of Certain Antihypertensive Drugs Hypertension is a key risk factor for cardiovascular diseases. Currently, around a third of people with hypertension are undiagnosed, and of those diagnosed, around half are not taking antihypertensive medications. The World Health Organization (WHO) estimates that high blood pressure directly or indirectly causes deaths of at least nine million people globally every year. In this literature review, we will introduce all reported methods that have been developed for determination of certain antihypertensive drugs such as irbesartan, losartan, candesartan, atenolol, bisoprolol and hydrochlorothiazide in their pure form, combined form with other drugs, combined form with degradation products, and in biological samples. We also will shed the light on the most important combination of drugs that are used for treatment of hypertension. Pharmacy ; Medicine ; Traditional medicine ; Family medicine Analytical Methods in Pharmaceuticals ; Computational Drug Discovery Methods
Authors: R. N. Plotnikova
Source: Proceedings of the Voronezh State University of Engineering Technologies (article, 2021-12-22)
Field: Chemistry — Organic Chemistry

Kinetic aspects of bromination of a phthalate-type plasticizer The main characteristics of a complex system of unsaturated plasticizer-bromine using the main "working components" - isomers of 2-ethylhexyl-2-ethylhexene phthalate are considered. It is taken into account that the phthalate-type ester plasticizer is a polar compound with a dipole moment at the level of dioctyl phthalate included in its composition. It has been shown that in the process of bromination, molecular bromine enters into physical interaction with all components of the plasticizer. Dosed introduction of bromine into the system at high stirring speeds leads to the formation of a homogeneous thermodynamically stable system, since the solubility parameters of the components are practically the same. Using a model mixture of bromine-dioctyl phthalate-dibutyl phthalate, it was shown that mixing bromine with plasticizers in any investigated ratios does not lead to the appearance of the boundary “bromine in a plasticizer” or “plasticizer in bromine”. This established the unlimited solubility of bromine in the plasticizer under the conditions of its bromination. Using the method of UV spectroscopy on model mixtures of acetic acid-bromine-water; acetic acid-bromine-hexane, it was proved that in a real system, unsaturated plasticizer-bromine, bromination is most likely carried out only with molecular bromine without the formation of bromine dimers. The mechanism of bromination of unsaturated phthalates included in the plasticizer is shown. A system of kinetic equations in dimensionless variables is proposed. It was found that the nature of the theoretical curves significantly depends on the rate of introduction of bromine with a constant reaction mechanism. A change in the limiting stages of the bromination process was noted depending on the rate of bromine introduction into the system. Bromine ; Plasticizer ; Phthalate ; Chemistry ; Dibutyl phthalate ; Halogenation ; Organic chemistry ; Solubility Inorganic and Organometallic Chemistry ; Chemistry and Chemical Engineering ; Thermal and Kinetic Analysis
Authors: Katarzyna Kurpiewska | Tomasz Borowski
Source: Acta Biochimica Polonica (review, 2021-08-11)
Field: Materials Science — Materials Chemistry

Seven quick tips for beginners in protein crystallography The aim of this brief review is to provide a roadmap for beginning crystallographers who have little or no experience in structural biology and yet are keen to produce protein crystals and analyze their 3D structures to understand their biological roles. To achieve this goal it is crucial to perform crystallization, structure determination, visualization and analysis of the protein's structural features related to its biological function. Keeping that objective in mind, tips presented herein cover the most important steps in a crystallographic endeavor and present a selection of databases and software which can aid and accelerate the whole process. We hope that this short overview will help novices coming from different disciplines to navigate a protein crystallography project and, hopefully, allow avoiding some costly mistakes, even though being a crystallographer means learning by trial and error. Computer science ; Visualization ; Process (computing) ; Function (biology) ; Selection (genetic algorithm) ; Software ; Protein function ; Cover (algebra) ; Data science ; Chemistry ; Data mining ; Biology ; Artificial intelligence ; Programming language ; Engineering ; Biochemistry ; Evolutionary biology Enzyme Structure and Function ; Protein Structure and Dynamics ; Porphyrin Metabolism and Disorders