jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Cinzia Cafarella | Domenica Mangraviti | Francesca Rigano | Paola Dugo | Luigi Mondello
Source: Journal of Separation Science (article, 2024-05-01)
Field: Chemistry — Spectroscopy

Rapid evaporative ionization mass spectrometry: A survey through 15 years of applications Rapid evaporative ionization mass spectrometry (REIMS) is a relatively recent MS technique explored in many application fields, demonstrating high versatility in the detection of a wide range of chemicals, from small molecules (phenols, amino acids, di- and tripeptides, organic acids, and sugars) to larger biomolecules, that is, phospholipids and triacylglycerols. Different sampling devices were used depending on the analyzed matrix (liquid or solid), resulting in distinct performances in terms of automation, reproducibility, and sensitivity. The absence of laborious and time-consuming sample preparation procedures and chromatographic separations was highlighted as a major advantage compared to chromatographic methods. REIMS was successfully used to achieve a comprehensive sample profiling according to a metabolomics untargeted analysis. Moreover, when a multitude of samples were available, the combination with chemometrics allowed rapid sample differentiation and the identification of discriminant features. The present review aims to provide a survey of literature reports based on the use of such analytical technology, highlighting its mode of operation in different application areas, ranging from clinical research, mostly focused on cancer diagnosis for the accurate identification of tumor margins, to the agri-food sector aiming at the safeguard of food quality and security. Chemistry ; Chromatography ; Mass spectrometry ; Sample preparation ; Chemometrics ; Complex matrix ; Process engineering ; Reproducibility ; Biochemical engineering Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Analytical Chemistry and Chromatography
Authors: Kevin Y. Huang | Lizette Cardenas | Andrew D. Ellington | David J. F. Walker
Source: Nature Communications (article, 2024-10-24)
Field: Materials Science — Materials Chemistry

Supercharged fluorescent proteins detect lanthanides via direct antennae signaling A sustainable operation for harvesting metals in the lanthanide series is needed to meet the rising demand for rare earth elements across diverse global industries. However, existing methods are limited in their capacity for detection and capture at environmentally and industrially relevant lanthanide concentrations. Supercharged fluorescent proteins have solvent-exposed, negatively charged residues that potentially create multiple direct chelation pockets for free lanthanide cations. Here, we demonstrate that negatively supercharged proteins can bind and quantitatively report concentrations of lanthanides via an underutilized lanthanide-to-chromophore pathway of energy transfer. The top-performing sensors detect lanthanides in the micromolar to millimolar range and remain unperturbed by environmentally significant concentrations of competing metals. As a demonstration of the versatility and adaptability of this energy transfer method, we show proximity and signal transmission between the lanthanides and a supramolecular assembly of supercharged proteins, paving the way for the detection of lanthanides via programmable protein oligomers and materials. Fluorescence ; Fluorescent protein ; Signaling proteins ; Computational biology ; Cell biology ; Chemistry ; Signal transduction ; Biology ; Green fluorescent protein ; Biochemistry ; Physics ; Gene Lanthanide and Transition Metal Complexes ; Radioactive element chemistry and processing ; Geochemistry and Elemental Analysis
Authors: Reyhaneh Gorji | Jan Škvařil | Monica Odlare
Source: Horticulturae (article, 2024-03-28)
Field: Chemistry — Analytical Chemistry

Determining Moisture Content of Basil Using Handheld Near-Infrared Spectroscopy Accurate and rapid determination of moisture content is essential in crop production and decision-making for irrigation. Near-infrared (NIR) spectroscopy has been shown to be a promising method for determining moisture content in various agricultural products, including herbs and vegetables. This study tested the hypothesis that NIR spectroscopy is effective in accurately measuring the moisture content of Genovese basil (Ocimum basilicum L.), with the objective of developing a respective calibration model. Spectral data were obtained from a total of 120 basil leaf samples over a period of six days. These included freshly harvested and detached leaves, as well as those left in ambient air for 1–6 days. Five spectra were taken from each leaf using a handheld NIR spectrophotometer, which covers the first and second overtones of the NIR spectral region: 950–1650 nm. After the spectral acquisition, the leaves were weighed for fresh mass and then put in an oven for 72 h at 80 °C to determine the dry weight and calculate the reference moisture content. The calibration model was developed using multivariate analysis in MATLAB, including preprocessing and regression modeling. The data obtained from 75% of the samples were used for model training and 25% for validation. The final model demonstrates strong performance metrics. The root mean square error of calibration (RMSEC) is 2.9908, the root mean square error of cross-validation (RMSECV) is 3.2368, and the root mean square error of prediction (RMSEP) reaches 2.4675. The coefficients of determination for calibration (R2C) and cross-validation (R2CV) are consistent, with values of 0.829 and 0.80, respectively. The model’s predictive ability is indicated by a coefficient of determination for prediction (R2P) of 0.86. The range error ratio (RER) stands at 11.045—highlighting its predictive performance. Our investigation, using handheld NIR spectrophotometry, confirms NIR’s usefulness in basil moisture determination. The rapid determination offers valuable insights for irrigation and crop management. Near-infrared spectroscopy ; Water content ; Calibration ; Basilicum ; Ocimum ; Mean squared error ; Moisture ; Partial least squares regression ; Spectroscopy ; Coefficient of determination ; Mathematics ; Chemistry ; Analytical Chemistry (journal) ; Remote sensing ; Environmental science ; Horticulture ; Statistics ; Chromatography ; Optics ; Physics ; Geology Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement ; Smart Agriculture and AI
Authors: Alessandro Benelli | Chiara Cevoli | Angelo Fabbri | Søren Balling Engelsen | Klavs Martin Sørensen
Source: Smart Agricultural Technology (article, 2024-03-01)
Field: Chemistry — Analytical Chemistry

Precision viticulture: Automatic selection of the regions of interest from moving wagon hyperspectral images of grapes for efficient SSC prediction Precision viticulture is increasingly being applied to automate and optimize grape production in the vineyard. This paper describes the development of a method for automatic selection of regions of interest from hyperspectral images obtained of a row of vines and intended for prediction of soluble solids content. For this purpose, a dataset consisting of hyperspectral images of a row of ‘Sangiovese’ wine grapes was adopted. Hyperspectral images were acquired directly in the field by means of a hyperspectral imaging Vis/NIR system (400–1000 nm) mounted on a ground-based vehicle. The analyses were carried out on 17 different days, under clear or partly cloudy conditions, in the period between post-veraison and harvest. The vineyard row of Sangiovese vines was divided into 11 sections and a hyperspectral image for each section for each day of analysis was acquired. The regions of interest of the hyperspectral images, comprising the areas representing the grapes, were selected using a PLS-DA-based method. The best PLS-DA model provided excellent results, with sensitivity and specificity values of 0.991 and 0.996, respectively. The mean spectra of the selected regions of interest (ROI) were finally used to predict the soluble solids content (SSC) of the grapes by PLS regression to a primary reference analysis. The results of SSC predictions using the automatic selection of ROIs (R2CV = 0.74 and RMSECV = 0.86 °Brix) were on par with similar regression based on carefully manual selection of ROIs (R2CV = 0.73 and RMSECV = 0.87 °Brix). Hyperspectral imaging ; Vineyard ; Veraison ; Viticulture ; Wine ; Artificial intelligence ; Mathematics ; Brix ; Selection (genetic algorithm) ; Computer science ; Pattern recognition (psychology) ; Vitis vinifera ; Horticulture ; Chemistry ; Biology ; Food science Spectroscopy and Chemometric Analyses ; Horticultural and Viticultural Research ; Fermentation and Sensory Analysis
Authors: Billy G. Ram | Joseph Mettler | Kirk Howatt | Michael Ostlie | Xin Sun
Source: Data in Brief (article, 2024-08-14)
Field: Chemistry — Analytical Chemistry

WeedCube: Proximal hyperspectral image dataset of crops and weeds for machine learning applications WeedCube dataset consists of hyperspectral images of three crops (canola, soybean, and sugarbeet) and four invasive weeds species (kochia, common waterhemp, redroot pigweed, and common ragweed). Plants were grown in two separate greenhouses and plant canopies were captured from a top-down camera angle. A push-broom hyperspectral sensor in the visible near infrared region of 400-1000 nm was used for data collection. The dataset includes 160 calibrated images. The number of images can be further increased by selection of smaller region of interests (ROIs). Dataset is supplemented by Jupyter Notebook scripts that help in data augmentation, spectral pre-processing, ROI selection for points and images, and data visualization. The primary purpose of this dataset is to support weed classification or identification studies by enhancing existing training datasets and validating the generalization capabilities of existing models. Owing to the three-dimensional (3D) nature of hyperspectral images, this dataset can also be utilized by researchers and educators across various domains for the development and testing of deep learning algorithms, the creation of automated data processing pipelines effective for 3D data, the development of tools for 3D data visualization, the creation of innovative solutions for data compression, and addressing system memory issues associated with high-dimensional data. Hyperspectral imaging ; Computer science ; Artificial intelligence ; Agricultural engineering ; Machine learning ; Engineering Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Remote Sensing in Agriculture
Authors: Saqib Qamar | Abu Imran Baba | Stéphane Verger | Magnus Andersson
Source: Plant Methods (article, 2024-08-14)
Field: Chemistry — Organic Chemistry

Segmentation and characterization of macerated fibers and vessels using deep learning By leveraging YOLOv8's advances, this work provides a deep learning solution to enable efficient quantification and analysis of wood cells suitable for practical applications. Segmentation ; Artificial intelligence ; Computer science ; Robustness (evolution) ; Pixel ; Tracheid ; Microscopy ; Deep learning ; Image segmentation ; Characterization (materials science) ; Materials science ; Pattern recognition (psychology) ; Computer vision ; Chemistry ; Optics ; Biology ; Physics ; Nanotechnology ; Botany Wood and Agarwood Research ; Industrial Vision Systems and Defect Detection ; Remote Sensing and LiDAR Applications
Authors: Menghan Shi | Daming Sun | Johan F. S. Christensen | Lars R. Jensen | Deyong Wang | Morten M. Smedskjær
Source: Journal of the American Ceramic Society (article, 2024-08-26)
Field: Materials Science — Ceramics and Composites

Improving the mechanical properties of a sodium borosilicate glass through spinodal decomposition Abstract The brittleness of oxide glasses remains a critical problem, limiting their suitability for high‐performance and safety‐critical applications. In this study, we attempt to address this by synthesizing nanostructures in sodium borosilicate glasses through phase separation. While most previous work on the mechanical properties of phase‐separated glasses has focused on phase separation through nucleation and growth, we here create interconnected structures through spinodal decomposition. Interestingly, this leads to improvements in Vickers hardness (from 5.8 to 6.2 GPa), crack initiation resistance (from 4.9 to 8.1 N), and fracture toughness (from 0.85 to 1.09 MPa⋅m 1/2 ). We show that the interconnected glassy phases deflect the propagating cracks, causing the required energy for cracks to cross phase boundaries to increase when subjected to external stress. This study deepens the understanding of how to address the brittleness problem of oxide glasses and provides a promising way to design high‐performance glass materials. Borosilicate glass ; Spinodal decomposition ; Decomposition ; Materials science ; Sodium ; Composite material ; Chemical engineering ; Mineralogy ; Phase (matter) ; Chemistry ; Metallurgy ; Organic chemistry Glass properties and applications ; Nuclear materials and radiation effects ; Advanced ceramic materials synthesis
Authors: Yiying Zhu
Source: Protein and Peptide Letters (article, 2024-03-01)
Field: Chemistry — Spectroscopy

Plasma/Serum Proteomics based on Mass Spectrometry Human blood is a window of physiology and disease. Examination of biomarkers in blood is a common clinical procedure, which can be informative in diagnosis and prognosis of diseases, and in evaluating treatment effectiveness. There is still a huge demand on new blood biomarkers and assays for precision medicine nowadays, therefore plasma/serum proteomics has attracted increasing attention in recent years. How to effectively proceed with the biomarker discovery and clinical diagnostic assay development is a question raised to researchers who are interested in this area. In this review, we comprehensively introduce the background and advancement of technologies for blood proteomics, with a focus on mass spectrometry (MS). Analyzing existing blood biomarkers and newly-built diagnostic assays based on MS can shed light on developing new biomarkers and analytical methods. We summarize various protein analytes in plasma/serum which include total proteome, protein post-translational modifications, and extracellular vesicles, focusing on their corresponding sample preparation methods for MS analysis. We propose screening multiple protein analytes in the same set of blood samples in order to increase success rate for biomarker discovery. We also review the trends of MS techniques for blood tests including sample preparation automation, and further provide our perspectives on their future directions. Proteomics ; Biomarker discovery ; Proteome ; Biomarker ; Extracellular vesicles ; Computational biology ; Blood proteins ; Analyte ; Diagnostic biomarker ; Bioinformatics ; Medicine ; Chemistry ; Chromatography ; Biology ; Internal medicine ; Biochemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Miguel Ochmann | Jessica Harich | Rory Ma | Antonia Freibert | Yujin Kim | Madhusudana Gopannagari | Da Hong | Daewoong Nam | Sangsoo Kim | Minseok Kim | Intae Eom | Jae Hyuk Lee | Briony A. Yorke | Tae Kyu Kim | Nils Huse
Source: Nature Communications (article, 2024-10-13)
Field: Chemistry — Physical and Theoretical Chemistry

UV photochemistry of the L-cystine disulfide bridge in aqueous solution investigated by femtosecond X-ray absorption spectroscopy The photolysis of disulfide bonds is implicated in denaturation of proteins exposed to ultraviolet light. Despite this biological relevance in stabilizing the structure of many proteins, the mechanisms of disulfide photolysis are still contested after decades of research. Herein, we report new insight into the photochemistry of L-cystine in aqueous solution by femtosecond X-ray absorption spectroscopy at the sulfur K-edge. We observe homolytic bond cleavage upon ultraviolet irradiation and the formation of thiyl radicals as the single primary photoproduct. Ultrafast thiyl decay due to geminate recombination proceeds at a quantum yield of >80 % within 20 ps. These dynamics coincide with the emergence of a secondary product, attributed to the generation of perthiyl radicals. From these findings, we suggest a mechanism of perthiyl radical generation from a vibrationally excited parent molecule that asymmetrically fragments along a carbon-sulfur bond. Our results point toward a dynamic photostability of the disulfide bridge in condensed-phase. Photochemistry ; Radical ; Chemistry ; Photodissociation ; Ultrafast laser spectroscopy ; Spectroscopy ; Aqueous solution ; Femtosecond ; Absorption spectroscopy ; Absorption (acoustics) ; Materials science ; Organic chemistry ; Laser Photochemistry and Electron Transfer Studies ; Redox biology and oxidative stress ; Free Radicals and Antioxidants
Authors: Alexa Fiorante | Lan Anna Ye | Alessandra Tata | Taira Kiyota | Michael Woolman | Francis Talbot | Yasamine Farahmand | Darah Vlaminck | Lauren Katz | Andrea Massaro | Howard J. Ginsberg | Asma M. Aman | Arash Zarrine‐Afsar
Source: International Journal of Molecular Sciences (review, 2024-03-20)
Field: Chemistry — Spectroscopy

A Workflow for Meaningful Interpretation of Classification Results from Handheld Ambient Mass Spectrometry Analysis Probes While untargeted analysis of biological tissues with ambient mass spectrometry analysis probes has been widely reported in the literature, there are currently no guidelines to standardize the workflows for the experimental design, creation, and validation of molecular models that are utilized in these methods to perform class predictions. By drawing parallels with hurdles that are faced in the field of food fraud detection with untargeted mass spectrometry, we provide a stepwise workflow for the creation, refinement, evaluation, and assessment of the robustness of molecular models, aimed at meaningful interpretation of mass spectrometry-based tissue classification results. We propose strategies to obtain a sufficient number of samples for the creation of molecular models and discuss the potential overfitting of data, emphasizing both the need for model validation using an independent cohort of test samples, as well as the use of a fully characterized feature-based approach that verifies the biological relevance of the features that are used to avoid false discoveries. We additionally highlight the need to treat molecular models as "dynamic" and "living" entities and to further refine them as new knowledge concerning disease pathways and classifier feature noise becomes apparent in large(r) population studies. Where appropriate, we have provided a discussion of the challenges that we faced in our development of a 10 s cancer classification method using picosecond infrared laser mass spectrometry (PIRL-MS) to facilitate clinical decision-making at the bedside. Computer science ; Workflow ; Classifier (UML) ; Mass spectrometry ; Artificial intelligence ; Overfitting ; Data science ; Data mining ; Chemistry ; Database ; Chromatography Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Advanced Chemical Sensor Technologies
Authors: Vicente Rubio | Nicholas McInchak | Genesis Fernandez | Dana Benavides | Diana Herrera | Catherine Jimenez | Haylee Mesa | Jonathan Meade | Qi Zhang | Maciej Stawikowski
Source: Scientific Reports (article, 2024-12-28)
Field: Chemistry — Spectroscopy

Development and characterization of fluorescent cholesteryl probes with enhanced solvatochromic and pH-sensitive properties for live-cell imaging We present novel fluorescent cholesteryl probes (CNDs) with a modular design based on the solvatochromic 1,8-phthalimide scaffold. We have explored how different modules-linkers and head groups-affect the ability of these probes to integrate into lipid membranes and how they distribute intracellularly in mouse astrocytes and fibroblasts targeting lysosomes and lipid droplets. Each compound was assessed for its solvatochromic behavior in organic solvents and model membranes. Molecular dynamics simulations and lipid partitioning using giant unilamellar vesicles showed how these analogs behave in model membranes compared to cholesterol. Live-cell imaging demonstrated distinct staining patterns and cellular uptake behaviors, further validating the utility of these probes in biological systems. We compared the empirical results with those of BODIPY-cholesterol, a well-regarded fluorescent cholesterol analog. The internalization efficiency of fluorescent CND probes varies in different cell types and is affected mainly by the head groups. Our results demonstrate that the modular design significantly simplifies the creation of fluorescent cholesteryl probes bearing distinct spectral, biophysical, and cellular targeting features. It is a valuable toolkit for imaging in live cells, measuring cellular membrane dynamics, and studying cholesterol-related processes. Fluorescence ; Solvatochromism ; Membrane ; Biophysics ; Live cell imaging ; Chemistry ; Fluorescence-lifetime imaging microscopy ; Fluorescence microscope ; Cell membrane ; Cell ; Cell biology ; Biochemistry ; Biology Molecular Sensors and Ion Detection ; Lipid Membrane Structure and Behavior ; Photochromic and Fluorescence Chemistry
Authors: Cristina Cuadrado | Francisco Cen‐Pacheco | Antonio Hernández Daranas
Source: Organic Letters (article, 2024-06-18)
Field: Chemistry — Spectroscopy

Computationally Assisted Analysis of NMR Chemical Shifts as a Tool in Conformational Analysis A key to understanding the properties of functional molecules is to determine their conformation in solution. A conformational analysis procedure that relies on quantum mechanical calculations and the widely used DP4+ probability was evaluated to decipher the structural information encoded in NMR chemical shifts. The results underscore the potential utility of using NMR chemical shifts in advancing conformational analysis studies of complex molecules in solution. Chemical shift ; Chemistry ; Molecule ; Quantum chemical ; Molecular conformation ; Nuclear magnetic resonance spectroscopy ; DECIPHER ; Computational chemistry ; Stereochemistry ; Bioinformatics ; Organic chemistry ; Physical chemistry Molecular spectroscopy and chirality ; Metabolomics and Mass Spectrometry Studies ; Analytical Chemistry and Chromatography