jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hyo In Yoon | Da Hye Ryu | Jai-Eok Park | Ho‐Youn Kim | Soo Hyun Park | Jung‐Seok Yang
Source: Horticulturae (article, 2024-10-31)
Field: Chemistry — Analytical Chemistry

Non-Destructive Prediction of Rosmarinic Acid Content in Basil Plants Using a Portable Hyperspectral Imaging System and Ensemble Learning Algorithms Rosmarinic acid (RA) is a phenolic antioxidant naturally occurring in the plants of the Lamiaceae family, including basil (Ocimum basilicum L.). Existing analytical methods for determining the RA content in leaves are time-consuming and destructive, posing limitations on quality assessment and control during cultivation. In this study, we aimed to develop non-destructive prediction models for the RA content in basil plants using a portable hyperspectral imaging (HSI) system and machine learning algorithms. The basil plants were grown in a vertical farm module with controlled environments, and the HSI of the whole plant was captured using a portable HSI camera in the range of 400–850 nm. The average spectra were extracted from the segmented regions of the plants. We employed several spectral data pre-processing methods and ensemble learning algorithms, such as Random Forest, AdaBoost, XGBoost, and LightGBM, to develop the RA prediction model and feature selection based on feature importance. The best RA prediction model was the LightGBM model with feature selection by the AdaBoost algorithm and spectral pre-processing through logarithmic transformation and second derivative. This model performed satisfactorily for practical screening with R2P = 0.81 and RMSEP = 3.92. From in-field HSI data, the developed model successfully estimated and visualized the RA distribution in basil plants growing in the greenhouse. Our findings demonstrate the potential use of a portable HSI system for monitoring and controlling pharmaceutical quality in medicinal plants during cultivation. This non-destructive and rapid method can provide a valuable tool for assessing the quality of RA in basil plants, thereby enhancing the efficiency and accuracy of quality control during the cultivation stage. Hyperspectral imaging ; Rosmarinic acid ; Artificial intelligence ; Content (measure theory) ; Algorithm ; Computer science ; Pattern recognition (psychology) ; Mathematics ; Chemistry Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Meat and Animal Product Quality
Authors: Jennifer Guergues | Jessica Wohlfahrt | John M. Koomen | Jonathan R. Krieger | Sameer Varma | Stanley M. Stevens
Source: PROTEOMICS (article, 2024-09-05)
Field: Chemistry — Spectroscopy

A semi‐automated workflow for DIA‐based global discovery to pathway‐driven PRM analysis Targeted proteomics, which includes parallel reaction monitoring (PRM), is typically utilized for more precise detection and quantitation of key proteins and/or pathways derived from complex discovery proteomics datasets. Initial discovery-based analysis using data independent acquisition (DIA) can obtain deep proteome coverage with low data missingness while targeted PRM assays can provide additional benefits in further eliminating missing data and optimizing measurement precision. However, PRM method development from bioinformatic predictions can be tedious and time-consuming because of the DIA output complexity. We address this limitation with a Python script that rapidly generates a PRM method for the TIMS-TOF platform using DIA data and a user-defined target list. To evaluate the script, DIA data obtained from HeLa cell lysate (200 ng, 45-min gradient method) as well as canonical pathway information from Ingenuity Pathway Analysis was utilized to generate a pathway-driven PRM method. Subsequent PRM analysis of targets within the example pathway, regulation of apoptosis, resulted in improved chromatographic data and enhanced quantitation precision (100% peptides below 10% CV with a median CV of 2.9%, n = 3 technical replicates). The script is freely available at https://github.com/StevensOmicsLab/PRM-script and provides a framework that can be adapted to multiple DDA/DIA data outputs and instrument-specific PRM method types. Python (programming language) ; Computer science ; Workflow ; Proteome ; Proteomics ; Computational biology ; Data mining ; Pathway analysis ; Scripting language ; Missing data ; Bioinformatics ; Biology ; Machine learning ; Database ; Programming language Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; RNA and protein synthesis mechanisms
Authors: Thais Gazzi | Benjamin Brennecke | Valentas Olikauskas | Remo Hochstrasser | Haiyan Wang | Suzan Keen Chao | Kenneth Atz | Yelena Mostinski | Andreas Topp | Dominik Heer | Isabelle Kaufmann | Martin Ritter | Luca Gobbi | Benoit Hornsperger | Bjoern Wagner | Hans Richter | Fionn O’Hara | Matthias Wittwer | Dennis Jul Hansen | Ludovic Collin | Bernd Kuhn | J. Benz | Uwe Grether | Marc Nazaré
Source: ChemBioChem (article, 2024-11-28)
Field: Chemistry — Organic Chemistry

Development of a Highly Selective NanoBRET Probe to Assess MAGL Inhibition in Live Cells Cell-free enzymatic assays are highly useful tools in early compound profiling due to their robustness and scalability. However, their inadequacy to reflect the complexity of target engagement in a cellular environment may lead to a significantly divergent pharmacology that is eventually observed in cells. The discrepancy that emerges from properties like permeability and unspecific protein binding may largely mislead lead compound selection to undergo further chemical optimization. We report the development of a new intracellular NanoBRET assay to assess MAGL inhibition in live cells. Based on a reverse design approach, a highly potent, reversible preclinical inhibitor was conjugated to the cell-permeable BODIPY590 acceptor fluorophore while retaining its overall balanced properties. An engineered MAGL-nanoluciferase (Nluc) fusion protein provided a suitable donor counterpart for the facile interrogation of intracellular ligand activity. Validation of assay conditions using a selection of known MAGL inhibitors set the stage for the evaluation of over 1'900 MAGL drug candidates derived from our discovery program. This evaluation enabled us to select compounds for further development based not only on target engagement, but also on favorable physicochemical parameters like permeability and protein binding. This study highlights the advantages of cell-based target engagement assays for accelerating compound profiling and progress at the early stages of drug discovery programs. Drug discovery ; Chemistry ; Target protein ; Cell permeability ; Computational biology ; Combinatorial chemistry ; Biochemistry ; Biology ; Gene Click Chemistry and Applications ; bioluminescence and chemiluminescence research ; Advanced biosensing and bioanalysis techniques
Authors: Xiao Yu | Shanshan Chang | Ziye Wang | Jiao Liu | Xing‐Zhou Tang | Jinhui Chen | Bingxiang Li | Yanqing Lu
Source: Laser & Photonics Review (article, 2024-06-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Dynamic Transition from Branched Flow of Light to Beam Steering in Disordered Nematic Liquid Crystal Abstract Orientational ordered soft matter possessing diverse microstructures has become a focal point of scientific research and technological exploration, thanks to its advancements in serving as an indispensable optical platform enabling propagation of light with multidimensional and manipulatable states. Herein, a facile way is developed to manipulate the in‐plane light beam transition dynamics by harnessing a time‐variable nematic liquid crystal (NLC) film through the electrical‐field‐induced topological defects. The results show that the dynamic change of optical branched flow is associated with the growth in the correlation length of optical potential and the reduction in the density of topological defects. The optical branching can continuously transform to deterministic and tunable beam steering at the low‐defect‐density regime through annihilation kinetics of defects. The explored soft matter system provides an excellent planar platform for the fundamental physics of light interacting with topological defects and may offer new perspectives for novel optics elements toward the applications of soft matter photonics. Liquid crystal ; Materials science ; Optics ; Flow (mathematics) ; Beam steering ; Beam (structure) ; Glass transition ; Optoelectronics ; Polymer ; Mechanics ; Physics ; Composite material Liquid Crystal Research Advancements ; Nonlinear Dynamics and Pattern Formation ; Advanced Materials and Mechanics
Authors: Yajun Tang | Jing Wang | He Qiu | Yang Xu | Zhanhong Liu | Lu Song | Hai Lin | Xingdong Zhang
Source: Collagen and Leather (article, 2024-12-01)
Field: Materials Science — Biomaterials

The chondrogenic differentiation of BMSCs in collagen hydrogels and the effect of MMPs among cell-material interactions Chondrogenesis ; Matrix metalloproteinase ; Self-healing hydrogels ; Chemistry ; Cell biology ; Cell ; Biophysics ; Biomedical engineering ; Polymer chemistry ; Biochemistry ; Biology ; Medicine Silk-based biomaterials and applications ; Osteoarthritis Treatment and Mechanisms ; Collagen: Extraction and Characterization
Authors: Charalambos Evangeli | Jacob L. Swett | Jean Spièce | Edward McCann | Jasper P. Fried | Achim Harzheim | Andrew R. Lupini | G. Andrew D. Briggs | Pascal Gehring | Stephen Jesse | Oleg Kolosov | Jan A. Mol | Ondrej Dyck
Source: ACS Nano (article, 2024-04-19)
Field: Materials Science — Materials Chemistry

Thermoelectric Limitations of Graphene Nanodevices at Ultrahigh Current Densities Graphene is atomically thin, possesses excellent thermal conductivity, and is able to withstand high current densities, making it attractive for many nanoscale applications such as field-effect transistors, interconnects, and thermal management layers. Enabling integration of graphene into such devices requires nanostructuring, which can have a drastic impact on the self-heating properties, in particular at high current densities. Here, we use a combination of scanning thermal microscopy, finite element thermal analysis, and <i>operando</i> scanning transmission electron microscopy techniques to observe prototype graphene devices in operation and gain a deeper understanding of the role of geometry and interfaces during high current density operation. We find that Peltier effects significantly influence the operational limit due to local electrical and thermal interfacial effects, causing asymmetric temperature distribution in the device. Thus, our results indicate that a proper understanding and design of graphene devices must include consideration of the surrounding materials, interfaces, and geometry. Leveraging these aspects provides opportunities for engineered extreme operation devices. Graphene ; Materials science ; Thermoelectric effect ; Nanotechnology ; Thermal conductivity ; Current (fluid) ; Nanoscopic scale ; Thermal ; Scanning thermal microscopy ; Optoelectronics ; Transistor ; Thermoelectric materials ; Current density ; Composite material ; Electrical engineering Graphene research and applications ; Thermal properties of materials ; Advanced Thermoelectric Materials and Devices
Authors: Chengchun Zhan | Hongyi Mao | Rongsheng Fan | Tianyang He | Qing Rui | Wenliang Zhang | Yi Lin | Kunyu Li | Lei Wang | T T Xia | Youli Wu | Zhiliang Kang
Source: Foods (article, 2024-11-06)
Field: Chemistry — Analytical Chemistry

Detection of Apple Sucrose Concentration Based on Fluorescence Hyperspectral Image System and Machine Learning China ranks first in apple production worldwide, making the assessment of apple quality a critical factor in agriculture. Sucrose concentration (SC) is a key factor influencing the flavor and ripeness of apples, serving as an important quality indicator. Nondestructive SC detection has significant practical value. Currently, SC is mainly measured using handheld refractometers, hydrometers, electronic tongues, and saccharimeter analyses, which are not only time-consuming and labor-intensive but also destructive to the sample. Therefore, a rapid nondestructive method is essential. The fluorescence hyperspectral imaging system (FHIS) is a tool for nondestructive detection. Upon excitation by the fluorescent light source, apples displayed distinct fluorescence characteristics within the 440-530 nm and 680-780 nm wavelength ranges, enabling the FHIS to detect SC. This study used FHIS combined with machine learning (ML) to predict SC at the apple's equatorial position. Primary features were extracted using variable importance projection (VIP), the successive projection algorithm (SPA), and extreme gradient boosting (XGBoost). Secondary feature extraction was also conducted. Models like gradient boosting decision tree (GBDT), random forest (RF), and LightGBM were used to predict SC. VN-SPA + VIP-LightGBM achieved the highest accuracy, with Rp2, RMSEp, and RPD reaching 0.9074, 0.4656, and 3.2877, respectively. These results underscore the efficacy of FHIS in predicting apple SC, highlighting its potential for application in nondestructive quality assessment within the agricultural sector. Hyperspectral imaging ; Fluorescence ; Sucrose ; Artificial intelligence ; Computer science ; Chemistry ; Computer vision ; Food science ; Optics ; Physics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Remote Sensing and Land Use
Authors: Jian Feng | Yangyang Liu | Anzhen Xie | Yun Yang | Feifei Lv | Jianhe Wei
Source: Frontiers in Plant Science (article, 2024-07-31)
Field: Chemistry — Organic Chemistry

Successful development of molecular diagnostic technology combining mini-barcoding and high-resolution melting for traditional Chinese medicine agarwood species based on single-nucleotide polymorphism in the chloroplast genome Agarwood is a valuable traditional medicine and fragrance. The production process is a typical injury-induced defense response. Currently, there are approximately 22 known species in the genus <i>Aquilaria</i> Lam., all of which can produce agarwood, whereas there are only two legal species of traditional Chinese medicinal agarwood, <i>Aquilaria sinensis</i> (Lour.) Spreng. and <i>Aquilaria agallocha</i> (Lour.) Roxb. The Taiwan herbal Pharmacopoeia of China stipulates that the medicinal agarwood species are <i>A. sinensis</i> and its relatives in the same genus. Moreover, there are five species of agarwood available for clinical medicinal use in Japan, including <i>A. agallocha</i> and <i>A. sinensis</i>, which are often confused with each other or used in a mixed way in the trade process. Therefore, accurate identification of traditional Chinese medicinal agarwood species is important to ensure the authenticity of traditional medicines and to guide the safety of clinical medication. In this study, 59 specific single-nucleotide polymorphism loci were screened and obtained from the chloroplast genomes of 12 species of the genus <i>Aquilaria</i> Lam. We established an identification method for traditional Chinese medicinal agarwood using mini-barcoding combined with high-resolution melting (HRM) and designed and validated 10 pairs of primers from the <i>psb</i>M-<i>trn</i>D, <i>psb</i>A, <i>rps</i>16, <i>pet</i>N, <i>ndh</i>E-<i>psa</i>C, <i>rps</i>4, <i>atp</i>E, <i>ycf</i>1, <i>rps</i>15-<i>trn</i>N, and <i>mat</i>K regions. The amplification products were all less than 200 bp, with a high success rate of amplification. The method was applied to successfully identify traditional Chinese medicinal agarwood species from commercial agarwood samples. Overall, the sensitivity of this method was sufficient to detect 1% of adulterants in medicinal agarwood products, proving that mini-barcoding HRM is a powerful and flexible tool. This method can be used as a fast and effective high-throughput method for authenticity testing of traditional Chinese medicinal agarwood and its raw materials containing agarwood-containing proprietary Chinese medicines and is recommended for industrial applications. High Resolution Melt ; Genome ; DNA barcoding ; Biology ; Agarwood ; Single-nucleotide polymorphism ; Chloroplast ; Computational biology ; High resolution ; Evolutionary biology ; Genetics ; Gene ; Medicine ; Polymerase chain reaction ; Genotype ; Geography Wood and Agarwood Research ; Identification and Quantification in Food ; Microbial Metabolism and Applications
Authors: Landry Blanc | Florent Grélard | Michael Tuck | Véronique Dartois | António Peixoto | Nicolas Desbenoît
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-03-23)
Field: Chemistry — Spectroscopy

In tissue spatial single-cell metabolomics by coupling mass spectrometry imaging and immunofluorescences Abstract In this work, we introduce a multimodal imaging workflow that integrates Matrix-assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) combined with Immunofluorescence (IF) microscopy to enhance in tissue spatial single-cell metabolomics. The workflow allows to correlate cell populations with associated small molecule distributions by conducting on the same tissue section MSI before IF staining, addressing tissue integrity challenges and joint image analysis. To process MSI data with IF guidance, we propose an original and advanced computational strategy utilizing Receiver Operating Characteristic (ROC) analysis, allowing to identify ions specific to targeted histological regions based on IF staining. Moreover, in a non-targeted strategy, we introduce a Spatial Coherence Measure (SCM) to distinguish genuine spatial patterns from noise within ion distributions, enhancing spatial metabolomics’ robustness. Then spatial clustering techniques are employed to group ions sharing similar spatial distribution to reveal histological structures, providing complementary insights into metabolite distributions. We validated our workflow mouse spleen section as this organ presents a spatially complex but well-detailed microenvironment. In conclusion, our multimodal and computational workflow opens new frontiers for diverse biomedical research applications by promoting precise spatial metabolomics in tissue sections. Mass spectrometry imaging ; Workflow ; Metabolomics ; Computer science ; MALDI imaging ; Spatial analysis ; Computational biology ; Biological system ; Pattern recognition (psychology) ; Mass spectrometry ; Data mining ; Artificial intelligence ; Chemistry ; Matrix-assisted laser desorption/ionization ; Bioinformatics ; Biology ; Remote sensing Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Hope E. Lackey | Gilbert L. Nelson | Heather M. Felmy | Xiaofeng Guo | Samuel A. Bryan | Amanda M. Lines
Source: ACS Omega (article, 2024-07-23)
Field: Chemistry — Analytical Chemistry

PCA and PLS Analysis of Lanthanides Using Absorbance and Single-Beam Visible Spectra During process monitoring applications, referenced optical spectroscopy, such as absorbance spectroscopy, can suffer from environmental and instrumental fluctuations that alter the intensity of irradiance reaching the spectrometer's detector at each detected frequency. Temperature, vibration, light source aging, instrument damage, detector aging, detector registry shifts, sampling cell degradation, and similar perturbations create situations in which a previously collected reference spectrum may no longer be valid for the current state of the system. This can lead to the calculation of poor-quality absorbance spectra that are unsuitable for qualitative or quantitative analysis based on prior calibration models. The use of single-beam spectra in the creation of multivariate calibration models circumvents the need for collecting and maintaining a stable reference spectrum throughout an ongoing chemical process. However, unlike absorbance spectra, which typically have a zero baseline, single-beam spectra contain a high background signal relative to an analyte signal, and they may also contain intense peaks from the light source. Here, multivariate principal component analysis (PCA) and partial least squares (PLS) regression models are built using single-beam and absorbance spectra to compare the efficacy of both types of spectra for qualitative and quantitative analyses of lanthanide solutions. A multileg fiber optic UV-visible spectrometer is utilized to collect samples under three distinct wavelength registries in three unique sampling cells and under lighting conditions spanning 0.2 to 2.0 relative transmittance. Under these conditions, single-beam spectral PCA models produced enhanced discrimination between sampling conditions, allowing spectra to be grouped by the instrumental conditions under which they were collected. Absorbance and single-beam PLS models produced equivalent quantitations of the lanthanide concentrations. Absorbance ; Spectrometer ; Partial least squares regression ; Spectral line ; Calibration ; Spectroscopy ; Detector ; Optics ; Analytical Chemistry (journal) ; Principal component analysis ; Transmittance ; Chemometrics ; Sampling (signal processing) ; Chemistry ; Materials science ; Physics ; Statistics ; Mathematics ; Chromatography Spectroscopy and Chemometric Analyses ; Fault Detection and Control Systems ; Water Quality Monitoring and Analysis
Authors: Andrej Škrlec | Tadej Kocjan | Marko Nagode | Jernej Klemenc
Source: Materials (article, 2024-05-13)
Field: Materials Science — Materials Chemistry

Modelling a Response of Complex-Phase Steel at High Strain Rates In this article, a response of the complex-phase high-strength steel SZBS800 was modelled by considering the strain-rate influence. The material's response was first measured with a series of standard tensile tests at lower strain rates. Higher strain rates were achieved using the unconventional test of shooting the ball into flat specimens. A viscoplastic formulation of the Cowper-Symonds material model was applied to consider the strain-rate effects. The parameters <i>SIGY</i>, <i>p</i>, and <i>C</i> of the material model were estimated using a step-wise procedure. First, rough estimates of the three parameters were obtained from the tensile tests using the grid search method. Then, the parameters <i>p</i> and <i>C</i> were fine-tuned using the reverse engineering approach. With the help of explicit dynamic simulations and all the experimental data, a multi-criteria cost function was defined and applied to obtain a smooth response function for the parameters <i>p</i> and <i>C</i>. Its optimum was determined by a real-valued genetic algorithm. The optimal values of the estimated parameters model the material response well, although a domain of optimum candidates spans two orders of magnitude for the parameter <i>p</i> and a few orders of magnitude for the parameter <i>C</i>. Materials science ; Strain (injury) ; Phase (matter) ; Strain rate ; Composite material ; Physics ; Medicine High-Velocity Impact and Material Behavior ; Material Properties and Failure Mechanisms ; Microstructure and Mechanical Properties of Steels