jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yinuo Hou | Yan Gao | Shudi Guo | Zhibin Zhang | Ruibing Chen | Xiangyang Zhang
Source: Frontiers in Endocrinology (review, 2023-01-10)
Field: Chemistry — Spectroscopy

Applications of spatially resolved omics in the field of endocrine tumors Endocrine tumors derive from endocrine cells with high heterogeneity in function, structure and embryology, and are characteristic of a marked diversity and tissue heterogeneity. There are still challenges in analyzing the molecular alternations within the heterogeneous microenvironment for endocrine tumors. Recently, several proteomic, lipidomic and metabolomic platforms have been applied to the analysis of endocrine tumors to explore the cellular and molecular mechanisms of tumor genesis, progression and metastasis. In this review, we provide a comprehensive overview of spatially resolved proteomics, lipidomics and metabolomics guided by mass spectrometry imaging and spatially resolved microproteomics directed by microextraction and tandem mass spectrometry. In this regard, we will discuss different mass spectrometry imaging techniques, including secondary ion mass spectrometry, matrix-assisted laser desorption/ionization and desorption electrospray ionization. Additionally, we will highlight microextraction approaches such as laser capture microdissection and liquid microjunction extraction. With these methods, proteins can be extracted precisely from specific regions of the endocrine tumor. Finally, we compare applications of proteomic, lipidomic and metabolomic platforms in the field of endocrine tumors and outline their potentials in elucidating cellular and molecular processes involved in endocrine tumors. Metabolomics ; Endocrine system ; Proteomics ; Mass spectrometry ; Computational biology ; Lipidomics ; Laser capture microdissection ; Mass spectrometry imaging ; Chemistry ; Glycomics ; Biology ; Bioinformatics ; Chromatography ; Biochemistry ; Hormone Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Ion-surface interactions and analysis
Authors: Ahmed Khalil | Mohamed Elkafrawy | Rami A. Hawileh | Mohammad AlHamaydeh | Wael Abuzaid
Source: Journal of Composites Science (article, 2023-06-19)
Field: Materials Science — Materials Chemistry

Numerical Investigation of Flexural Behavior of Reinforced Concrete (RC) T-Beams Strengthened with Pre-Stressed Iron-Based (FeMnSiCrNi) Shape Memory Alloy Bars Shape memory alloy (SMA) is a material that can change shape in response to external stimuli such as temperature, stress, or magnetic fields. SMA types include nitinol (nickel-titanium), copper-aluminum-nickel, copper-zinc-aluminum, iron-manganese-silicon, and various nickel-titanium-X alloys, each exhibiting unique shape memory properties for different applications. Reinforced concrete (RC) T-beams strengthened and pre-stressed with Fe-SMA bars are numerically investigated for their flexural response under the influence of various parameters. The bars are embedded in a concrete layer attached to the beam’s soffit. Based on the numerical results, it was found that increasing the compression strength from 30 to 60 MPa slightly improves the beam’s strength (by 2%), but it significantly increases its ductility by approximately 45%. As opposed to this, the strength and ductility of the pre-stressed T-beam are considerably improved by using a larger diameter of Fe-SMA bars. Specifically, using 12 mm Fe-SMA bar over 6 mm resulted in 65% and 47% greater strength and ductility, respectively. Furthermore, this study examines the importance of considering the flange in the flexural design of pre-stressed beams. It is seen that considering a 500 mm flange width enhanced the ductility by 25% compared to the rectangular-section beam. The authors recommend further experimental work to validate and supplement the calculations and methodology used in the current numerical analysis. Materials science ; Flexural strength ; Ductility (Earth science) ; SMA* ; Shape-memory alloy ; Beam (structure) ; Composite material ; Flange ; Bending ; Structural engineering ; Stress (linguistics) ; Engineering Shape Memory Alloy Transformations ; Structural Behavior of Reinforced Concrete ; Structural Engineering and Vibration Analysis
Authors: Ji Hye Kang | Meena Seshadri | Kellye A. Cupp‐Sutton | Si Wu
Source: Frontiers in Analytical Science (article, 2023-06-22)
Field: Chemistry — Spectroscopy

Toward the analysis of functional proteoforms using mass spectrometry-based stability proteomics Functional proteomics aims to elucidate biological functions, mechanisms, and pathways of proteins and proteoforms at the molecular level to examine complex cellular systems and disease states. A series of stability proteomics methods have been developed to examine protein functionality by measuring the resistance of a protein to chemical or thermal denaturation or proteolysis. These methods can be applied to measure the thermal stability of thousands of proteins in complex biological samples such as cell lysate, intact cells, tissues, and other biological fluids to measure proteome stability. Stability proteomics methods have been popularly applied to observe stability shifts upon ligand binding for drug target identification. More recently, these methods have been applied to characterize the effect of structural changes in proteins such as those caused by post-translational modifications (PTMs) and mutations, which can affect protein structures or interactions and diversify protein functions. Here, we discussed the current application of a suite of stability proteomics methods, including thermal proteome profiling (TPP), stability of proteomics from rates of oxidation (SPROX), and limited proteolysis (LiP) methods, to observe PTM-induced structural changes on protein stability. We also discuss future perspectives highlighting the integration of top-down mass spectrometry and stability proteomics methods to characterize intact proteoform stability and understand the function of variable protein modifications. Proteomics ; Proteome ; Mass spectrometry ; Chemistry ; Quantitative proteomics ; Computational biology ; Proteolysis ; Lysis ; Biology ; Biochemistry ; Chromatography ; Enzyme Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Burak Yenigün | Muhammad Salman Chaudhry | Elli Gkouti | Aleksander Czekanski
Source: Nanomaterials (article, 2023-05-25)
Field: Materials Science — Materials Chemistry

Characterization of Mode I and Mode II Interlaminar Fracture Toughness in CNT-Enhanced CFRP under Various Temperature and Loading Rates This study investigates the influence of temperature and loading rate on the Mode I and Mode II interlaminar fracture behavior of carbon-nanotubes-enhanced carbon-fiber-reinforced polymer (CNT-CFRP). CNT-induced toughening of the epoxy matrix is characterized by producing CFRP with varying loading of CNT areal density. CNT-CFRP samples were subjected to varying loading rates and testing temperatures. Fracture surfaces of CNT-CFRP were analyzed using scanning electron microscopy (SEM) imaging. Mode I and Mode II interlaminar fracture toughness increased with increasing amount of CNT to an optimum value of 1 g/m<sup>2</sup>, then decreased at higher CNT amounts. Moreover, it was found that CNT-CFRP fracture toughness increased linearly with the loading rate in Mode I and Mode II. On the other hand, different responses to changing temperature were observed; Mode I fracture toughness increased when elevating the temperature, while Mode II fracture toughness increased with increasing up to room temperature and decreased at higher temperatures. Materials science ; Composite material ; Carbon nanotube ; Fracture toughness ; Scanning electron microscope ; Epoxy ; Fracture (geology) ; Toughening ; Polymer ; Carbon fiber reinforced polymer ; Toughness ; Composite number Carbon Nanotubes in Composites ; Mechanical Behavior of Composites ; Smart Materials for Construction
Authors: Michael Kloster | Andrea M. Burfeid-Castellanos | Daniel Langenkämper | Tim W. Nattkemper | Bánk Beszteri
Source: PLoS ONE (article, 2023-02-24)
Field: Materials Science — Biomaterials

Improving deep learning-based segmentation of diatoms in gigapixel-sized virtual slides by object-based tile positioning and object integrity constraint Diatoms represent one of the morphologically and taxonomically most diverse groups of microscopic eukaryotes. Light microscopy-based taxonomic identification and enumeration of frustules, the silica shells of these microalgae, is broadly used in aquatic ecology and biomonitoring. One key step in emerging digital variants of such investigations is segmentation, a task that has been addressed before, but usually in manually captured megapixel-sized images of individual diatom cells with a mostly clean background. In this paper, we applied deep learning-based segmentation methods to gigapixel-sized, high-resolution scans of diatom slides with a realistically cluttered background. This setup requires large slide scans to be subdivided into small images (tiles) to apply a segmentation model to them. This subdivision (tiling), when done using a sliding window approach, often leads to cropping relevant objects at the boundaries of individual tiles. We hypothesized that in the case of diatom analysis, reducing the amount of such cropped objects in the training data can improve segmentation performance by allowing for a better discrimination of relevant, intact frustules or valves from small diatom fragments, which are considered irrelevant when counting diatoms. We tested this hypothesis by comparing a standard sliding window / fixed-stride tiling approach with two new approaches we term object-based tile positioning with and without object integrity constraint. With all three tiling approaches, we trained Mask-R-CNN and U-Net models with different amounts of training data and compared their performance. Object-based tiling with object integrity constraint led to an improvement in pixel-based precision by 12-17 percentage points without substantially impairing recall when compared with standard sliding window tiling. We thus propose that training segmentation models with object-based tiling schemes can improve diatom segmentation from large gigapixel-sized images but could potentially also be relevant for other image domains. Object (grammar) ; Computer science ; Constraint (computer-aided design) ; Artificial intelligence ; Segmentation ; Computer vision ; Virtual image ; Tile ; Engineering ; Geography Diatoms and Algae Research ; Water Quality Monitoring Technologies ; Geochemistry and Geologic Mapping
Authors: Rania Jradi | Christophe Marvillet | Mohamed Razak Jeday
Source: Scientific Reports (article, 2023-10-19)
Field: Materials Science — Biomaterials

Estimation and sensitivity analysis of fouling resistance in phosphoric acid/steam heat exchanger using artificial neural networks and regression methods One of the most frequent problem in phosphoric acid concentration plant is the heat exchanger build-up. This problem causes a reduction of the performance of this equipment and an increase of energy losses which lead to damage the apparatus. In this study, estimation of fouling resistance in a cross-flow heat exchanger was solved using a linear [Partial Least Squares (PLS)] and non linear [Artificial Neural Network (ANN)] methods. Principal Component Analysis (PCA) and Step Wise Regression (SWR) were preceded the modeling in order to determine the highest relation between operating parameters with the fouling resistance. The values of correlation coefficient (r<sup>2</sup>) and predictive ability which are equal to 0.992 and 87%, respectively showed a good prediction of the developed PLS model. In order to improve the results obtained by PLS method, an ANN model was developed. 361 experimental data points was used to design and train the network. A network containing 6 hidden neurons trained with Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm and hyperbolic tangent sigmoid transfer function for the hidden and output layers was selected to be the optimal configuration. The Garson's equation was applied to determine the sensitivity of input parameters on fouling resistance based on ANN results. Results indicated that acid inlet and outlet temperatures were the high relative important parameters on fouling resistance with importance equal to 56% and 15.4%, respectively. Fouling ; Artificial neural network ; Heat exchanger ; Sigmoid function ; Broyden–Fletcher–Goldfarb–Shanno algorithm ; Computer science ; Sensitivity (control systems) ; Mathematics ; Biological system ; Artificial intelligence ; Engineering ; Chemistry ; Mechanical engineering Calcium Carbonate Crystallization and Inhibition ; Neural Networks and Applications ; Freezing and Crystallization Processes
Authors: Alieh Rezagholizade-shirvan | Mahboubeh Kalantarmahdavi | Mohammad Reza Amiryousefi
Source: Heliyon (article, 2023-06-01)
Field: Materials Science — Biomaterials

Evaluation of the effect of basil seed gum, tragacanth gum, pectin, and coating formulation with corn flour on oil absorption and sensory properties of watermelon rind chips The current study aims to produce coated watermelon rind chips with the approach of reducing oil absorption and optimal use of waste and investigating its physicochemical, textural, and sensory characteristics. The effect of coating with basil seed gum, Tragacanth gum, pectin, and coating formulation with corn flour on oil absorption rate, moisture loss, and color of white skin slices of fried watermelon was studied. The results indicated that due to the controlling role of water in the amount of oil absorption, the amount of oil in all the samples coated with gum and corn flour was decreased compared to the samples coated with gum and the samples without coating. The pretreatment of osmotic dehydration reduces oil absorption in compared to fresh and blanched samples. The color changes in the sample with two pre-treatments of osmosis and blanching were less than other samples, as a result, the brightness of this sample was also higher than others. The lowest amount of oil absorption was observed in samples coated with basil gum and 0.5% and 1% corn flour (0.33 and 0.29, respectively). The highest amount of moisture loss during frying was related to the coated samples was observed with the combination of basil gum and corn flour (0.5%) and pectin and corn flour (2%). The highest level of antioxidant activity of the fried samples was related to the sample coated with 0.5% basil gum. Significant color changes were also observed in the coated samples. Tragacanth ; Food science ; Xanthan gum ; Chemistry ; Absorption of water ; Pectin ; Coating ; Blanching ; Moisture ; Materials science ; Rheology Nanocomposite Films for Food Packaging ; Food composition and properties ; Polysaccharides Composition and Applications
Authors: Dong He | Qizhen Hong | Fei Li | Quanhua Sun | Ting Si | Xisheng Luo
Source: The Journal of Chemical Physics (article, 2023-12-18)
Field: Chemistry — Spectroscopy

Experimental and numerical studies on the thermal nonequilibrium behaviors of CO with Ar, He, and H2 The time-dependent rotational and vibrational temperatures were measured to study the shock-heated thermal nonequilibrium behaviors of CO with Ar, He, and H2 as collision partners. Three interference-free transition lines in the fundamental vibrational band of CO were applied to the fast, in situ, and state-specific measurements. Vibrational relaxation times of CO were summarized over a temperature range of 1110-2820 K behind reflected shocks. The measured rotational temperature instantaneously reached an equilibrium state behind shock waves. The measured vibrational temperature experienced a relaxation process before reaching the equilibrium state. The measured vibrational temperature time histories were compared with predictions based on the Landau-Teller model and the state-to-state approach. The state-to-state approach treats the vibrational energy levels of CO as pseudo-species and accurately describes the detailed thermal nonequilibrium processes behind shock waves. The datasets of state-specific inelastic rate coefficients of CO-Ar, CO-He, CO-CO, and CO-H2 collisions were calculated in this study using the mixed quantum-classical method and the semiclassical forced harmonic oscillator model. The predictions based on the state-to-state approach agreed well with the measured data and nonequilibrium (non-Boltzmann) vibrational distributions were found in the post-shock regions, while the Landau-Teller model predicted slower vibrational temperature time histories than the measured data. Modifications were applied to the Millikan-White vibrational relaxation data of the CO-Ar and CO-H2 systems to improve the performance of the Landau-Teller model. In addition, the thermal nonequilibrium processes behind incident shocks, the acceleration effects of H2O on the relaxation process of CO, and the characterization of vibrational temperature were highlighted. Vibrational energy relaxation ; Non-equilibrium thermodynamics ; Relaxation (psychology) ; Atomic physics ; Harmonic oscillator ; Thermal equilibrium ; Thermodynamic equilibrium ; Physics ; Boltzmann constant ; Thermodynamics ; Chemistry ; Excited state ; Quantum mechanics Spectroscopy and Laser Applications ; Atmospheric Ozone and Climate ; Gas Dynamics and Kinetic Theory
Authors: Patrice Koehl | Arseniy Akopyan | Herbert Edelsbrunner
Source: Journal of Chemical Information and Modeling (article, 2023-01-13)
Field: Materials Science — Materials Chemistry

Computing the Volume, Surface Area, Mean, and Gaussian Curvatures of Molecules and Their Derivatives Geometry is crucial in our efforts to comprehend the structures and dynamics of biomolecules. For example, volume, surface area, and integrated mean and Gaussian curvature of the union of balls representing a molecule are used to quantify its interactions with the water surrounding it in the morphometric implicit solvent models. The Alpha Shape theory provides an accurate and reliable method for computing these geometric measures. In this paper, we derive homogeneous formulas for the expressions of these measures and their derivatives with respect to the atomic coordinates, and we provide algorithms that implement them into a new software package, AlphaMol. The only variables in these formulas are the interatomic distances, making them insensitive to translations and rotations. AlphaMol includes a sequential algorithm and a parallel algorithm. In the parallel version, we partition the atoms of the molecule of interest into 3D rectangular blocks, using a <i>kd</i>-tree algorithm. We then apply the sequential algorithm of AlphaMol to each block, augmented by a buffer zone to account for atoms whose ball representations may partially cover the block. The current parallel version of AlphaMol leads to a 20-fold speed-up compared to an independent serial implementation when using 32 processors. For instance, it takes 31 s to compute the geometric measures and derivatives of each atom in a viral capsid with more than 26 million atoms on 32 Intel processors running at 2.7 GHz. The presence of the buffer zones, however, leads to redundant computations, which ultimately limit the impact of using multiple processors. AlphaMol is available as an OpenSource software. Partition (number theory) ; Curvature ; Block (permutation group theory) ; Computer science ; Computation ; Gaussian ; Algorithm ; Surface (topology) ; Computational science ; Geometry ; Mathematics ; Combinatorics ; Computational chemistry ; Chemistry Enzyme Structure and Function ; Protein Structure and Dynamics ; Computational Drug Discovery Methods
Authors: Melvyn Larranaga | Sylvie Lartigue‐Korinek | M. Legros | Nicolas Combe | F. Mompiou
Source: Acta Materialia (article, 2023-03-29)
Field: Materials Science — Materials Chemistry

High temperature plasticity at twin boundary in Al: An in-situ TEM perspective Materials science ; Dislocation ; Burgers vector ; Condensed matter physics ; Grain boundary ; Glide plane ; Plasticity ; Shear (geology) ; Microstructure ; Physics ; Composite material Microstructure and mechanical properties ; Aluminum Alloys Composites Properties ; Electromagnetic Effects on Materials
Authors: Ehsan Aghdamifar | Vali Rasooli Sharabiani | Ebrahim Taghinezhad | Adel Rezvanivand Fanaei | Mariusz Szymanek
Source: European Food Research and Technology (article, 2023-04-10)
Field: Chemistry — Analytical Chemistry

Non-destructive method for identification and classification of varieties and quality of coffee beans based on soft computing models using VIS/NIR spectroscopy Abstract Coffee is one of the most popular and frequently consumed beverages on the planet. Coffee has a significant commercial value, estimated to be in the billions of dollars and consumption has risen steadily over the last two decades. Near-infrared spectroscopy is one of the non-destructive optical technologies for the evaluation of agricultural products to identify food adulteration. Thus, it is an interesting and worthwhile subject to research and study. In this research, a near-infrared spectroscopy approach along with statistical methods of principal component analysis (PCA), partial-least-squares regression (PLSR), latent dirichlet allocation (LDA), and artificial neural network (ANN) as a fast and non-destructive method was used with to detect and classify coffee beans using reference data obtained by gas chromatography–mass spectrometry (GC–MS). Results showed that the accuracy of PLSR, LDA, and ANN while our reference data was palmitic acid, respectively were 97.3%, 97.92%, and 97.3% and while reference data was caffeine, accuracy results were 94.71%, 95.83%, and 98.96%, respectively. Partial least squares regression ; Principal component analysis ; Mathematics ; Chemometrics ; Statistics ; Food science ; Artificial intelligence ; Pattern recognition (psychology) ; Chemistry ; Computer science ; Chromatography Spectroscopy and Chemometric Analyses ; Coffee research and impacts ; Advanced Chemical Sensor Technologies
Authors: Preeti Choudhary | Stephen Anyango | John M. Berrisford | James Tolchard | Mihály Váradi | Sameer Velankar
Source: Scientific Data (article, 2023-04-12)
Field: Materials Science — Materials Chemistry

Unified access to up-to-date residue-level annotations from UniProtKB and other biological databases for PDB data More than 61,000 proteins have up-to-date correspondence between their amino acid sequence (UniProtKB) and their 3D structures (PDB), enabled by the Structure Integration with Function, Taxonomy and Sequences (SIFTS) resource. SIFTS incorporates residue-level annotations from many other biological resources. SIFTS data is available in various formats like XML, CSV and TSV format or also accessible via the PDBe REST API but always maintained separately from the structure data (PDBx/mmCIF file) in the PDB archive. Here, we extended the wwPDB PDBx/mmCIF data dictionary with additional categories to accommodate SIFTS data and added the UniProtKB, Pfam, SCOP2, and CATH residue-level annotations directly into the PDBx/mmCIF files from the PDB archive. With the integrated UniProtKB annotations, these files now provide consistent numbering of residues in different PDB entries allowing easy comparison of structure models. The extended dictionary yields a more consistent, standardised metadata description without altering the core PDB information. This development enables up-to-date cross-reference information at the residue level resulting in better data interoperability, supporting improved data analysis and visualisation. UniProt ; Protein Data Bank (RCSB PDB) ; Metadata ; Computer science ; Database ; Information retrieval ; XML ; Interoperability ; World Wide Web ; Biology Enzyme Structure and Function ; Genomics and Phylogenetic Studies ; RNA and protein synthesis mechanisms