jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: V. Matveev
Source: Physics-Uspekhi (article, 2024-05-01)
Field: Materials Science — Materials Chemistry

The most important achievements in studies of fundamental problems in nuclear physics over the past 25—30 years and their prospects Sciences Division of the Russian Academy of Sciences, ``Tricentennial of the Academy, Achievements of and Progress in Physical Sciences in the 21st Century.''It covers the most important achievements in studying fundamental problems in nuclear physics over the past 2530 years and prospects for further progress in this area.The report is focused on the contribution of Russian researchers to the global advancement that has occurred over recent decades in the study of fundamental problems in nuclear physics, including elementary particle physics and high-energy physics, relativistic nuclear physics and heavy ion physics, neutrino physics and neutrino astrophysics, and the physics of ultra-high-energy cosmic rays.Presented are the achievements of Russian scientists in theoretical physics and cosmology, which largely determine the successes in the exploration of the basic properties of matter.The contribution of Russian researchers to the implementation of major international projects, which has largely been a driver of their progress in recent decades, in particular, the discovery of the Higgs boson, is outlined.The current state and projects for the development of the research infrastructure of Russian research institutions are reviewed.The important role of progress in accelerator science and technology in exploring fundamental problems in nuclear physics is highlighted.Particular attention is paid to megascience nuclear physics projects currently being developed and implemented in Russia and to emerging update of the strategy for the development of physical research and inno- Engineering ethics ; Physics ; Engineering Graphite, nuclear technology, radiation studies ; Nuclear reactor physics and engineering
Authors: Spyridon Chaskis | S. Maritsa | Paul Stavroulakis | Sofia Papadopoulou | Russell Goodall | Spyros Papaefthymiou
Source: Metals (article, 2024-05-24)
Field: Materials Science — Materials Chemistry

Compositional Design and Thermal Processing of a Novel Lead-Free Cu–Zn–Al–Sn Medium Entropy Brass Alloy In the current work, a novel medium entropy copper alloy was designed with the aim of avoiding the use of expensive, hazardous or scarce alloying elements and instead employing widely available and cost-effective alternatives. In order to investigate this unknown region of multicomponent alloy compositions, the thermo-physical parameters were calculated and the CALPHAD method was utilized. This led to the design of the Cu50Zn25Al20Sn5 at. % (Cu53.45Zn27.49Al9.08Sn9.98 wt. %) alloy with a relatively low density of 6.86 g/cm3 compared with conventional brasses. The designed alloy was manufactured through vacuum induction melting, producing two ingots weighing 1.2 kg each, which were subjected to a series of heat treatments. The microstructural evolution of the alloy in the as-cast and heat-treated conditions was assessed through optical and scanning electron microscopy. The hardness of the as-cast and heat-treated alloy at room temperature was also studied. The alloy was characterized by a multiphase microstructure containing a major Cu-rich (Cu–Zn–Al) matrix reinforced with a secondary Zn-rich (Zn–Cu) phase and pure Sn. In terms of mechanical properties, the developed alloy exhibited high hardness values of roughly 378 HV0.2 and 499 HV0.2 in the as-cast and heat-treated conditions, respectively. Brass ; Alloy ; Metallurgy ; Materials science ; Copper ; Lead (geology) ; Geology Metallurgy and Material Science
Authors: Marvin Thielert | Caroline A M Weiss | Matthias Mann | Florian A. Rosenberger
Source: Methods in molecular biology (article, 2024-01-01)
Field: Chemistry — Spectroscopy

Spatial Proteomics of Single Hepatocytes with Multiplexed Data-Independent Acquisition (mDIA) Spatially resolved mass spectrometry-based proteomics at single-cell resolution promises to provide insights into biological heterogeneity. We describe a protocol based on multiplexed data-independent acquisition (mDIA) with dimethyl labeling to enhance proteome depth, accuracy, and throughput while minimizing costs. It enables high-quality proteome analysis of single isolated hepatocytes and utilizes liver zonation for single-cell proteomics benchmarking. This adaptable, modular protocol will promote the use of single-cell proteomics in spatial biology. Computer science Advanced Proteomics Techniques and Applications ; Single-cell and spatial transcriptomics ; Advanced Biosensing Techniques and Applications
Authors: Khanda F.M. Amin
Source: MethodsX (article, 2024-03-28)
Field: Chemistry — Analytical Chemistry

Greenness-sustainability metrics for assessment smart-chemometric spectrophotometric strategy for evaluation of the combination of six gastric proton-pump inhibitors with two selected impurities Green analytical approaches are employed for the determination of active pharmaceutical ingredients, in conjunction with their impurities. Smart chemometric spectrophotometric techniques, including orthogonal partial least square (OPLS), variable selection such as genetic algorithm (GA-OPLS), and interval selection (i-OPLS), were utilized. These chemometric models were implemented for assessing six proton-pump inhibitors Omeprazole, Esomeprazole, Lansoprazole, Pantoprazole, Rabeprazole, and Dexlansoprazole along with two selected official impurities, namely 4-Desmethoxy omeprazole impurity and Rabeprazole-impurity B. Experimental design was implemented to separate impurities, in the process of multivariate calibration, a five-level eight-factor calibration design consisting of 25 samples was selected. This design was deliberately selected to guarantee that the components were mutually orthogonal to assess the model's performance and reliability, a separate validation set of 15 samples was constructed. The best-performing of the proposed techniques were identified by considering the least favorable values of the Correlation Coefficient (R ≥ 0.9995), the Root Mean Square Error of Prediction (RMSEP) values between (0.0102-0.5622), and the Relative Error of Prediction (REP) values between (0.2961-1.1917). The proposed and reported methods' greenness-sustainability was quantitatively evaluated, and a comparative study of the greenness profile was established through a spider chart, the National Environmental Method Index tool, advanced and modified NEMI along with the Hexagon tool, and the whiteness qualities of the presented approaches were assessed by implementing the recently adopted Red-Green-Blue paradigm and White Analytical Chemistry tool. These approaches are well-suited for use in quality control laboratories due to their observed acceptance, long-term sustainability, simplicity, and affordability. Lansoprazole ; Omeprazole ; Rabeprazole ; Chemometrics ; Correlation coefficient ; Chemistry ; Partial least squares regression ; Chromatography ; Mathematics ; Computer science ; Machine learning ; Proton-pump inhibitor Analytical Methods in Pharmaceuticals ; Spectroscopy and Chemometric Analyses ; Analytical Chemistry and Chromatography
Authors: Onyedika Emmanuel Okpala | Johana Rondevaldová | Hayford Osei-Owusu | Tomas Kudera | Tersia Kokoskova | Ladislav Kokoška
Source: Molecules (article, 2024-08-02)
Field: Chemistry — Organic Chemistry

Susceptibility of Staphylococcus aureus to Anti-Inflammatory Drugs with a Focus on the Combinatory Effect of Celecoxib with Oxacillin In Vitro Musculoskeletal infections (MIs) are among the most difficult-to-treat staphylococcal diseases due to antibiotic resistance. This has encouraged the development of innovative strategies, such as combination therapy, to combat MI. The aim of this study was to investigate the in vitro antistaphylococcal activity of anti-inflammatory drugs and the combined antimicrobial effect of celecoxib and oxacillin. The minimum inhibitory concentrations (MICs) of 17 anti-inflammatory drugs against standard strains and clinical isolates of <i>S. aureus</i>, including methicillin-resistant strains (MRSAs), were determined using the broth microdilution method. The fractional inhibitory concentration indices (FICIs) were evaluated using checkerboard assays. Celecoxib produced the most potent antistaphylococcal effect against all tested strains (MICs ranging from 32 to 64 mg/L), followed by that of diacerein against MRSA3 and MRSA ATCC 33592 (MIC 64 mg/L). Several synergistic effects were observed against the tested <i>S. aureus</i> strains, including MRSA (FICI ranging from 0.087 to 0.471). The strongest synergistic interaction (FICI 0.087) was against MRSA ATCC 33592 at a celecoxib concentration of 2 mg/L, with a 19-fold oxacillin MIC reduction (from 512 to 26.888 mg/L). This is the first report on the combined antistaphylococcal effect of celecoxib and oxacillin. These findings suggest celecoxib and its combination with oxacillin as perspective agents for research focused on the development of novel therapies for MI caused by <i>S. aureus.</i> This study further indicates that celecoxib could resensitize certain MRSA strains, in some cases, to be susceptible to β-lactams (e.g., oxacillin) that were not previously tested. It is essential to mention that the in vitro concentrations of anti-inflammatory drugs are higher than those typically obtained in patients. Therefore, an alternative option for its administration could be the use of a drug delivery system for the controlled slow release from an implant at the infection site. Celecoxib ; Staphylococcus aureus ; Antimicrobial ; In vitro ; Antibiotics ; Medicine ; Microbiology ; Anti-inflammatory ; Minimum inhibitory concentration ; Staphylococcus ; Pharmacology ; Chemistry ; Bacteria ; Biology ; Biochemistry Synthesis of β-Lactam Compounds ; Inflammatory mediators and NSAID effects ; Antimicrobial Resistance in Staphylococcus
Authors: Tina C. Dang | Lauren Fields | Lingjun Li
Source: Journal of the American Society for Mass Spectrometry (article, 2024-07-26)
Field: Chemistry — Spectroscopy

MotifQuest: An Automated Pipeline for Motif Database Creation to Improve Peptidomics Database Searching Programs Endogenous peptides are an abundant and versatile class of biomolecules with vital roles pertinent to the functionality of the nervous, endocrine, and immune systems and others. Mass spectrometry stands as a premier technique for identifying endogenous peptides, yet the field still faces challenges due to the lack of optimized computational resources for reliable raw mass spectra analysis and interpretation. Current database searching programs can exhibit discrepancies due to the unique properties of endogenous peptides, which typically require specialized search considerations. Herein, we present a high throughput, novel scoring algorithm for the extraction and ranking of conserved amino acid sequence motifs within any endogenous peptide database. Motifs are conserved patterns across organisms, representing sequence moieties crucial for biological functions, including maintenance of homeostasis. MotifQuest, our novel motif database generation algorithm, is designed to work in partnership with EndoGenius, a program optimized for database searching of endogenous peptides and that is powered by a motif database to capitalize on biological context to produce identifications. MotifQuest aims to quickly develop motif databases without any prior knowledge, a laborious task not possible with traditional sequence alignment resources. In this work we illustrate the utility of MotifQuest to expand EndoGenius' identification utility to other endogenous peptides by showcasing its ability to identify antimicrobial peptides. Additionally, we discuss the potential utility of MotifQuest to parse out motifs from a FASTA database file that can be further validated as new peptide drug candidates. Database ; Sequence database ; Biological database ; Computational biology ; Computer science ; UniProt ; Chemistry ; Bioinformatics ; Biology ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Antimicrobial Peptides and Activities
Authors: Chompunud Chompunud Na Ayudhya | Potchanapond Graidist | Varomyalin Tipmanee
Source: Scientific Reports (article, 2024-05-31)
Field: Chemistry — Organic Chemistry

Role of CSF1R 550th-tryptophan in kusunokinin and CSF1R inhibitor binding and ligand-induced structural effect Binding affinity is an important factor in drug design to improve drug-target selectivity and specificity. In this study, in silico techniques based on molecular docking followed by molecular dynamics (MD) simulations were utilized to identify the key residue(s) for CSF1R binding affinity among 14 pan-tyrosine kinase inhibitors and 15 CSF1R-specific inhibitors. We found tryptophan at position 550 (W550) on the CSF1R binding site interacted with the inhibitors' aromatic ring in a π-π way that made the ligands better at binding. Upon W550-Alanine substitution (W550A), the binding affinity of trans-(-)-kusunokinin and imatinib to CSF1R was significantly decreased. However, in terms of structural features, W550 did not significantly affect overall CSF1R structure, but provided destabilizing effect upon mutation. The W550A also did not either cause ligand to change its binding site or conformational changes due to ligand binding. As a result of our findings, the π-π interaction with W550's aromatic ring could be still the choice for increasing binding affinity to CSF1R. Nevertheless, our study showed that the increasing binding to W550 of the design ligand may not ensure CSF1R specificity and inhibition since W550-ligand bound state did not induce significantly conformational change into inactive state. Tryptophan ; Ligand (biochemistry) ; Chemistry ; Biochemistry ; Receptor ; Amino acid Synthesis and Biological Evaluation ; Pharmacological Receptor Mechanisms and Effects ; Bioactive Compounds and Antitumor Agents
Authors: Kezhu Tan | Qi Liu | Xi Chen | Haonan Xia | Shouao Yao
Source: Agriculture (article, 2024-03-03)
Field: Chemistry — Analytical Chemistry

Estimation of Soybean Internal Quality Based on Improved Support Vector Regression Based on the Sparrow Search Algorithm Applying Hyperspectral Reflectance and Chemometric Calibrations The nutritional components of soybean, such as fat and protein, directly decide soybean quality. The fast and accurate detection of these components is significant to soybean industries and soybean crop breeding. This study developed an improved SSA-SVM (support vector regression based on the sparrow search algorithm) for the rapid and accurate detection of the fat and protein in soybean seeds using hyperspectral reflectance data. In this work, 85 soybean samples were selected. After their fat and protein contents were analyzed using chemical methods, a total of 85 groups of hyperspectral image data were collected using the hyperspectral imaging system. An effective data preprocessing method was applied to reduce the noise for enhancing the prediction models. Some popular models, including partial least-square regression (PLSR), random forest regression (RFR), and support vector regression based on the genetic algorithm (GA-SVR), were also established in this study. The experimental results showed that the improved SSA-SVM model could predict the nutrient contents of the soybean samples with accuracies of 0.9403 and 0.9215 and RMSEs of 0.2234 and 0.325 for the fat and protein, respectively. The convergence speed was improved significantly. Therefore, hyperspectral data combined with the SSA-SVM algorithm presented in this study were effective for evaluating the soybean quality. Hyperspectral imaging ; Reflectivity ; Remote sensing ; Support vector machine ; Environmental science ; Sparrow ; Regression ; Mathematics ; Algorithm ; Computer science ; Statistics ; Biology ; Artificial intelligence ; Geography ; Ecology Spectroscopy and Chemometric Analyses ; Remote Sensing and Land Use
Authors: Razieh Khajehyar | Milad Vahidi | Robert R. Tripepi
Source: Plant Cell Tissue and Organ Culture (PCTOC) (article, 2024-05-27)
Field: Chemistry — Analytical Chemistry

Using hyperspectral signatures for predicting foliar nitrogen and calcium content of tissue cultured little-leaf mockorange (Philadelphus microphyllus A. Gray) shoots Abstract Determining foliar mineral status of tissue cultured shoots can be costly and time consuming, yet hyperspectral signatures might be useful for determining mineral contents of these shoots. In this study, hyperspectral signatures were acquired from tissue cultured little-leaf mockorange ( Philadelphus microphillus ) shoots to determine the feasibility of using this technology to predict foliar nitrogen and calcium contents. After using a spectroradiometer to take hyperspectral images for determining foliar N and Ca contents, the correlation between the hyperspectral bands, vegetation indices, and hyperspectral features were calculated from the spectra. Features with high correlations were selected to develop the models via different regression methods including linear, random forest (RF), and support vector machines. The results showed that non-linear regression models developed through machine learning techniques, including RF methods and support vector machines provided satisfactory prediction models with high R 2 values (%N by RF with R 2 = 0.72, and %Ca by RF with R 2 = 0.99), that can estimate nitrogen and calcium content of little-leaf mockorange shoots grown in vitro. Overall, the RF regression method provided the most accurate and satisfactory models for both foliar N and Ca estimation of little-leaf mockorange shoots grown in tissue culture. Shoot ; Botany ; Biology ; Hyperspectral imaging ; Nitrogen ; Calcium ; Horticulture ; Chemistry ; Artificial intelligence ; Computer science Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement ; Seed and Plant Biochemistry
Authors: Marie Soula | Fabienne Samyn | Sophie Duquesne | Véronic Landry
Source: Holzforschung (article, 2024-03-27)
Field: Materials Science — Polymers and Plastics

Impact of surface delignification on fire retardancy of wood treated with polyelectrolyte complexes Wood is a natural composite widely employed as a residential building interior finishing. Although wood is readily available and offers benefits to the occupants, such as enhanced well-being, it is rarely employed in commercial construction due, amongst others, to the potential hazard of fire propagation. The application of flame retardant (FR) treatments leads to a reduction of wood flammability and supports wood as interior finishing. Polyelectrolyte complexes (PECs) deposition is an innovative surface treatment that has already proven its efficiency for fabrics. For wood, recent studies have highlighted that the weight gain impacted the fire-retardancy, and a minimum of 2 wt.-% was set to obtain fire protection. This study explored the potential of surface delignification to activate the wood surface and facilitate the PEC impregnation. Yellow birch (<i>Betula alleghaniensis</i>, Britt.) was surface delignified (0.3 mm) using sodium chlorite. The treatment impact on wood was evaluated by spectroscopy analysis (FTIR, Raman), and the increase in wood wettability was demonstrated (contact angle decreases from 50° to 35° after the surface delignification). Then, PECs consisting of polyethyleneimine and sodium phytate were surface impregnated in wood and delignified wood. The flame retardancy was evaluated using a cone calorimeter. Despite the increase in weight gain (1.5 wt.-% ± 0.3 wt.-% to 4.3 wt.-% ± 2.5 wt.-%), fire performance was not improved. This study demonstrates that lignin strongly affects char formation, even in the presence of PECs. Cone calorimeter ; Fire retardant ; Engineered wood ; Composite material ; Lignin ; Contact angle ; Polyelectrolyte ; Flammability ; Materials science ; Wood flour ; Char ; Softwood ; Sodium chlorite ; Pulp and paper industry ; Chemistry ; Combustion ; Polymer ; Organic chemistry Flame retardant materials and properties ; Lignin and Wood Chemistry ; Natural Fiber Reinforced Composites
Authors: Oskar Basara | Józef Gorzelany
Source: Molecules (article, 2024-07-31)
Field: Materials Science — Materials Chemistry

Assessment of Selected Chemical and Morphological Properties of Lonicera var. kamtschatica and Lonicera var. emphyllocalyx Treated with Gaseous Ozone <i>Lonicera caerulea</i> L. fruits are a rich source of vitamins, organic acids, and phenolic compounds, which are characterised by their health-promoting properties. The content of bioactive compounds in this fruit may vary depending on the cultivar and the harvest date. This study analysed the effect of applying 5 ppm gaseous ozone for 1, 3, and 5 min on the chemical properties of <i>L. kamtschatica</i> varieties and newly created clones of <i>L. emphyllocalyx</i> for three years of cultivation. The fruits harvested from <i>L. emphyllocalyx</i>, depending on the year of harvest, had significantly larger size and weight compared to <i>L. kamtschatica</i>. On average, the acidity of the <i>L. emphyllocalyx</i> clones was 6% higher than other tested varieties. The average content of ascorbic acid was highest in <i>L. emphyllocalyx</i> clone '21-17'-57.80 mg·100 g<sup>-1</sup>; the year of harvest will significantly affect the content of vitamin C, reaching the highest level in 2022-53.92 mg·100 g<sup>-1</sup>. The total content of polyphenols was significantly dependent on the year of cultivation; reaching, on average, 54.8% more in 2022 compared to the rest of the years. The total antioxidant value using the FRAP, DPPH, and ABTS methods varied depending on the variety; exposure to ozone significantly increased the antioxidant value in each case. On the basis of the study, both botanical varieties can be used in food processing. Gaseous ozone exposure can significantly influence chemical composition, increasing the health-promoting value of fruit. Ozone ; Chemistry ; Organic chemistry Nanoparticles: synthesis and applications ; Medical and Biological Ozone Research ; Vitamin C and Antioxidants Research
Authors: Halifa Sekar Metha | Kusrini Kusrini | Dhani Ariatmanto
Source: SinkrOn (article, 2024-03-31)
Field: Chemistry — Analytical Chemistry

Classification of types Roasted Coffee Beans using Convolutional Neural Network Method In the current digital era, the role of technology in the agricultural industry is very necessary to increase yields which can have an impact on the productivity and welfare of farmers. Coffee is a drink that has been very popular for many years. Due to the high demand for coffee beans, this research aims to develop a system that can classify types of roasted coffee beans based on images using the Convolution Neural Network (CNN) method. Coffee bean processing is the most important stage in the coffee industry, classifying coffee beans often requires more in-depth knowledge and extensive experience regarding coffee beans. Therefore, this system can be a more effective solution. The author collects a dataset containing types of roasted coffee beans, then the Convolutional Neural Network (CNN) can analyze in the form of visual patterns each type of coffee bean. This implementation is expected to help the coffee industry identify coffee beans quickly and accurately. Convolutional neural network ; Artificial intelligence ; Computer science ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses