jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hinako Takehisa | Ichiro Nagaoka | Akifumi Ikehata | Yutaka Sato
Source: Breeding Science (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Visible-near infrared spectral analysis for identification of physiological and genetic features in rice Visible-near infrared hyperspectral analysis is widely used for plant characterization and evaluation of agricultural products and food quality. On the other hand, it has remained un-certain whether this technique has a sufficient potential for evaluation of biological complexity during the growth of crop plants. In the present study, using a spectrometer and hyperspectral camera placed in a laboratory environment, we carried out continuous hyperspectral profiling of leaves derived from four rice cultivars grown under two field conditions. Combined analysis with transcriptome data revealed that the hyperspectral profile had potential to predict the degree of expression of developmentally regulated genes. In addition, principal component analysis of hyperspectral imaging data made it possible to detect growth-stage dependent dynamics and to distinguish differences between subspecies as well as field conditions by selecting an adequate pretreatment method. Furthermore, we obtained hyperspectral data for brown rice grains of recombinant inbred lines derived from a cultivar with high temperature tolerance during the ripening stage and with a good grain appearance. We then performed quantitative trait locus analysis using the extracted principal component scores and trait values re‍lated to grain appearance to explore the possibility of using spectral analysis for genetic studies. Hyperspectral imaging ; Principal component analysis ; Cultivar ; Quantitative trait locus ; Component analysis ; Independent component analysis Spectroscopy and Chemometric Analyses
Source: PLANT ARCHIVES (article, 2025-01-11)
Field: Chemistry — Analytical Chemistry

PRECISE CROP CLASSIFICATION OF HYPERSPECTRAL IMAGES USING NEURAL NETWORK-BASED FEATURE EXTRACTION AND CLASSIFICATION MODEL Precise crop classification is an essential step towards effective agricultural management.Information about different crop types growing in a region helps in crop monitoring and estimating yield.Advanced remote sensing technologies allow us to map different crops growing in a region more accurately and frequently than traditional field surveys.Hyperspectral data's spectral and spatial richness has made it possible to use this data for more accurate classification of various crops compared to multispectral datasets.The present research focuses on effectively utilizing high-resolution hyperspectral data for agricultural crop classification.Combining hyperspectral data with advanced machine learning techniques, i.e., autoencoder (AE) and artificial Neural Networks (ANN), are used for generating a hybrid crop classification technique based on unsupervised feature extraction and supervised classification.Unsupervised AE techniques are used for feature extraction of high dimensional hyperspectral data and supervised ANN is used for final crop classification with the help of learned features.This research focuses on developing a hybrid AE-ANNbased model to achieve classification with better discrimination.The hyperspectral data acquired by the Airborne Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) sensor from the Anand region of Gujarat, representing the study area, was used for crop classification.The developed model showed an overall accuracy (OA) of 97% using 20 extracted features.The proposed neural network model outperformed the popular SVM classifier, providing better classification accuracies and demonstrating the excellent discrimination of extracted features. Hyperspectral imaging ; Pattern recognition (psychology) ; Artificial intelligence ; Artificial neural network ; Feature extraction ; Contextual image classification ; Computer science ; Feature (linguistics) ; Image (mathematics) Spectroscopy and Chemometric Analyses ; Remote Sensing and Land Use ; Smart Agriculture and AI
Authors: Marisa Asadian | Seth Croslow | Timothy J. Trinklein | Stanislav S. Rubakhin | Fan Lam | Jonathan V. Sweedler
Source: ChemRxiv (preprint, 2025-04-17)
Field: Chemistry — Spectroscopy

High-throughput Fluorescence-guided Sequential Single-Cell MALDI-ICC Mass Spectrometry Lipids are a diverse class of biomolecules essential for brain function, yet their cell-type-specific distributions remain underexplored, presenting significant knowledge gaps in the era of single-cell biology. Traditional bulk measurements provide valuable insights into lipid composition across brain regions but lack the resolution to distinguish lipid profiles at the single-cell level. To address this, we introduce fluorescence-guided sequential single-cell mass spectrometry (SSMS), an automated workflow combining untargeted lipid profiling with antibody-targeted protein detection via photocleavable mass tags, enabling neurolipidomic classification of cell types and cell states. We applied this approach to rodent hippocampal cells, analyzing over a thousand single cells and annotating more than a hundred lipid species with complementary LC-MS/MS measurements. Our findings show that phosphatidylcholine (PC) species are predominantly enriched in oligodendrocytes and neurons compared to astrocytes, while hexosylceramide (HexCer) species are differentially expressed across these cell types. Furthermore, neuronal state analysis revealed an enrichment of phosphatidylethanolamines (PEs) in presynaptic neurons, while non-presynaptic neurons exhibited a more diverse lipid composition, including HexCer, PC, sphingomyelin, triacyl-glycerol, and PE. Our findings provide new insights into brain lipid heterogeneity with cell-type specificity and extend capabilities of next-generation single-cell mass spectrometry to map brain biochemistry. Fluorescence ; Mass spectrometry ; Throughput ; Mass spectrometry imaging ; Chemistry ; MALDI imaging ; Chromatography ; Computer science ; Matrix-assisted laser desorption/ionization ; Physics ; Optics ; Telecommunications Mass Spectrometry Techniques and Applications ; Analytical chemistry methods development ; Ion-surface interactions and analysis
Authors: Mario Franić | Igor Palčić | Šime Marcelić | Nikola Major | Dean Ban | Tvrtko Karlo Kovačević | Dominik Anđelini | Melissa Prelac | Danko Cvitan | Smiljana Goreta Ban | Zoran Užila | Marija Polić Pasković | Igor Pasković
Source: Sustainability (article, 2025-12-16)
Field: Chemistry — Organic Chemistry

Modulating Secondary Metabolite Content in Olive Leaves Through Foliar Application of Biochar and Olive Leaf-Based Phenolic Extracts This research focuses on the additional valorization of olive leaves, a by-product of regular olive pruning, by increasing their secondary metabolite content through the combined application of biochar and a phenolic extract from olive leaves. A suspension of biochar, obtained by the pyrolysis of grapevine pruning residues, was prepared by mixing it in demineralized water (1.5 g; 5 L; 24 h). The phenolic extract was obtained by extracting lyophilized and ground olive leaves in demineralized water (50 g; 5 L; 24 h), while the combined preparation was obtained in an analogous manner (1.5 g biochar; 50 g olive leaf powder; 5 L water; 24 h). Treatments were applied at the beginning of July, 50 days after anthesis (May 16th) and included the following: (i) control treatment (demineralized water), (ii) biochar solution, (iii) phenolic extract solution, and (iv) a combined aqueous preparation of biochar and phenolic extract, all with the addition of a wetting agent. Trees of the olive cultivars Leccino and Istarska bjelica were sprayed with the corresponding preparation until runoff. Olive leaves were sampled three weeks after treatment (July 26th) and, after washing and drying, and were prepared for LC-MSMS analysis. Both biochar-based treatments induced the most potent effects, although responses differed between cultivars. In particular, apigenin derivatives, hydroxytyrosol, luteolin-7-rutinoside, and the secoiridoid oleacein showed apparent differences between biochar treatments and the control. Overall, higher concentrations of the sum of detected secoiridoids were observed in the leaf samples of ‘Istarska bjelica’ under BCH and BCH+PH treatments, whereas no such differences were found for ‘Leccino’ cultivar. Further research is needed to clarify the cultivar-dependent response of secondary metabolism in these olive cultivars and the mechanisms by which biochar foliar application modulates metabolite profiles. Biochar ; Olive leaf ; Secondary metabolite ; Olea ; Pomace ; Cultivar ; Olive trees ; Metabolite Edible Oils Quality and Analysis ; Horticultural and Viticultural Research ; Plant Growth Enhancement Techniques
Authors: Raphael Henrique Teixeira da Silva | Andréa Carla Bastos Andrade | Reinaldo F. Teófilo | Jussara V. Roque | Luíz Alexandre Peternelli
Source: DELOS Desarrollo Local Sostenible (article, 2025-02-06)
Field: Chemistry — Analytical Chemistry

Prediction of sucrose in chocolate products employing NIR spectroscopy and multivariate calibration Considering the lower acquisition value and the practicality of obtaining data using a portable instrument (NIR-Portable), it is crucial to verify whether it offers spectra with prediction quality at least equal to those on a bench (NIR-Bench), which achieve higher spectral resolution. This study aimed to compare a NIR-Bench and a NIR-Portable to build and validate multivariate calibration models to predict sucrose in chocolate products. In Experiment 1, we evaluated cocoa mixtures with different concentrations of sucrose; in Experiment 2, fructose was added to the mixture. We built prediction models from the sample spectra via PLS regression. Considering both instruments and experiments, there were equivalent performances for the sucrose prediction models (RMSEP from 0.0597 to 0.0811 and rp2 from 0.9797 to 0.9943). A linear correlation existed between actual and predicted values ​​(0.9898 &lt; rp &lt; 0.997). The NIR-Portable presented, on average, greater relative errors (RE) without a predominance of greater RE per sample (p-value = 0.125). In the same spectral range, the rp was greater than 0.9874. There is no predominance of larger REs for the portable NIR (p-values ​​= 0.453 and 1 – Experiments 1 and 2, respectively). In commercial chocolate products, considerable values ​​were obtained for RMSE (0.1079 and 0.1478), r2 (0.9154 and 0.9301), and r (0.9568 and 0.9644) in Experiments 1 and 2, respectively. The fitted models allowed the detection of sucrose in both experiments. Portable NIR can replace bench-top NIR with good predictive capacity in commercial chocolate products. Multivariate statistics ; Calibration ; Sucrose ; Spectroscopy ; Multivariate analysis ; Dark chocolate ; Food science ; Analytical Chemistry (journal) ; Materials science ; Chemistry ; Mathematics ; Chromatography ; Statistics ; Physics Spectroscopy and Chemometric Analyses ; Food Chemistry and Fat Analysis ; Natural Products and Biological Research
Authors: Myrna Nurlatifah Zakaria | Sutriyo Sutriyo | Hayun Hayun | Taufiq Indra Rukmana
Source: Eduvest - Journal Of Universal Studies (article, 2025-01-20)
Field: Chemistry — Analytical Chemistry

Utilization of Near-Infrared Spectroscopy Combined with PLS-2 Regression Learner to Predict Metformin HCL Tablet Dissolution Profile One of the assurances of pharmaceutical tablet's quality, effectivity, and safety is the dissolution test, which is commonly known by pharmaceutical manufacturers. Conventionally, this test is performed by simulating the release rate of a drug using a Dissolution Tester, which mimics the human gastrointestinal condition. As stated by the current compendial for tablet dosage form, the dissolution rate is mandatory, with no exception for Metformin HCl tablets. This laboratory method is often time-consuming, unsafe for organic reagent exposure, and produces waste. This problem requires rapid, simple, and nondestructive technologies, hence having powerful analytical performance. One of the technologies that is widely used is Near Infrared (NIR) spectroscopy. This study utilized the NIR spectrum as a predictor to generate a mathematical model using Partial Least Square Regression (PLS-2) to build a dissolution rate model for the Metformin HCl tablet, which uses the Farmakope Indonesia IV &lt;1231&gt; (FI-IV) dissolution method as the compendial reference method. The PLS-2 model was built, which shows the low difference between SEC and SECV in each sampling point and a good correlation in the coefficient of determination (R2) of each point's time of dissolution within 0.900 to 0.953. The challenge test was performed to prove the predictability of the PLS-2 model with NIR against the actual reference FI-IV method using differential and similarity Factors (f2 &amp; f1), enabling real-time release testing (RTRT). Dissolution ; Regression analysis ; Near-infrared spectroscopy ; Metformin ; Analytical Chemistry (journal) ; Chemometrics ; Linear regression ; Principal component regression ; Spectroscopy ; Chemistry ; Materials science ; Chromatography ; Medicine ; Mathematics ; Statistics ; Internal medicine ; Optics ; Organic chemistry ; Physics Spectroscopy and Chemometric Analyses ; Analytical Methods in Pharmaceuticals
Authors: Hongcheng Guo | Marissa M. Tremblay | Peter K. Zeitler | B. D. Idleman | A. Fayon
Source:  (preprint, 2025-05-27)
Field: Materials Science — Materials Chemistry

Systematics of Helium Diffusion Sinks in Apatite Demonstrated by 4 He/ 3 He Degassing Experiments and Modeling Widely reported overdispersion of apatite (U-Th)/He ages has encouraged efforts to explore He diffusion kinetics and systematics in apatite. Studies such as continuous ramped heating (CRH) of apatite have revealed complex laboratory He behavior that i Apatite ; Helium ; Diffusion ; Systematics ; Isotopes of helium ; Geology ; Materials science ; Geochemistry ; Mineralogy ; Thermodynamics ; Physics ; Atomic physics ; Biology Nuclear Materials and Properties ; High-pressure geophysics and materials ; Nuclear Physics and Applications
Authors: Femke Roig Kuhn | Remco V. Klaassen | Frank Koopmans | Tiara S.Z. Koolman | August B. Smit | Sabine Spijker
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-06-08)
Field: Chemistry — Spectroscopy

A Tiered Approach to Human Synapse Proteomics: Optimized LC-MS/MS Analysis of Whole-Tissue and Synaptosome Preparations from Frozen Post-Mortem Brain Samples Abstract Recent advancements in neuroproteomics have enabled detailed analysis of protein expression and function in the human brain. Post-mortem human brain studies have significantly advanced our understanding of the relationship between genetics, cell biology of neurological and psychiatric disorders and their clinical diagnosis. Synaptic dysfunction often has a central role in these disorders. Therefore, we specifically evaluated the sensitivity of liquid chromatography-tandem mass spectrometry (LC-MS/MS) to detect synaptic proteins in whole-tissue lysates versus synaptosome preparations. First, we optimized sample preparation protocols for frozen human gray matter (GM), refining the suspension TRAPping (sTRAP) digestion method to improve protein solubilization and Cysteine reduction and alkylation using thin human tissue sections, and to accomplish low technical variation by minimizing sample handling. We achieved a highly reproducible sample preparation workflow by rigorously applying standardization and randomization across dissection, processing, and LC-MS/MS runs. Second, comparative LC-MS/MS analysis showed that cortical whole-tissue lysates are a practical solution for large-scale studies and broadly detected synaptic proteins focusing on excitatory neurons. However, enrichment by synaptosome isolation offered improved resolution of synapse-specific proteins. Because synapse-proteomics enables insight into spatial regulation—i.e., alterations at the synapse that are not reflected in the soma–we recommend a tiered approach: initial whole-tissue analysis for broad disease-associated changes, followed by targeted synaptosome proteomics to deepen insight into synaptic alterations. This strategy optimally balances throughput, reproducibility, and biological relevance, and enhances the study of brain disorders through proteomics. Moreover, analyzing synaptic proteins first at the tissue level improves insight into overall regulation of synaptic proteins induced by synapse loss or gain. Synaptosome ; Synapse ; Brain tissue ; Proteomics ; Neuroscience ; Chemistry ; Biology ; Biochemistry ; Central nervous system Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Cell Image Analysis Techniques
Authors: Andrii Klym | Yaroslav Blikharskyy | Zinoviy Blikharskyy | Jacek Selejdak | Oleksandr Panchenko
Source: IOP Conference Series Earth and Environmental Science (article, 2025-05-01)
Field: Materials Science — Materials Chemistry

Stress-strain state of RC beams after restoration of the compressed concrete zone Abstract The article presents the results of a study on the stress-strain state (SSS) of reinforced concrete beams after the restoration of the compressed concrete zone damaged due to physical loading. The experimental samples included beams with reinforcement turned down to a diameter of 20 mm to simulate corrosion processes, with and without subsequent restoration of the compressed concrete zone. To restore the damaged compressed concrete zone, a high-strength repair mortar, Sika MonoTop-4012, was used, significantly improving the mechanical properties of the structures. The results confirm the effectiveness of the applied mortar, achieving a 22% increase in the load-bearing capacity of the beams beyond the yield limit of the reinforcement compared to undamaged samples. A reduction in deflections was observed, indicating increased structural stiffness. The application of digital image correlation (DIC), integrated with computerized sub-micron indicators, enabled the acquisition of a detailed stress distribution and localized deformations with reduced measurement errors compared to traditional methods. This approach ensured precise monitoring of SSS changes under loading conditions and validated the effectiveness of the restoration efforts. The obtained data demonstrate the feasibility of using high-strength repair mortars in combination with modern monitoring techniques for restoring reinforced concrete structures. Future research may focus on assessing the long-term durability of restored beams under real operational conditions. Materials science ; Structural engineering ; Stress–strain curve ; Strain (injury) ; Stress (linguistics) ; Geotechnical engineering ; Compressive strength ; Composite material ; Geology ; Deformation (meteorology) ; Engineering Structural mechanics and materials ; Concrete Corrosion and Durability ; Concrete and Cement Materials Research
Authors: Antonietta Greco | Esther Imperlini | Gha Young Lee | Maciej Serda | Santiago Alonso Tobar Leitão | Claudia Corbo
Source: Nanoscale (article, 2025-01-01)
Field: Materials Science — Biomaterials

Study of the biomolecular corona of surface-modified polystyrene and silica nanoparticles: application to cancer Nanotechnology offers promising tools for disease diagnosis through the unique biomolecular corona (BC) that surrounds nanoparticles (NPs) when exposed to biological fluids, creating personalized profiles. In this study, we investigated the capability of BC of polystyrene and silica NPs with diverse surface functionalization in distinguishing eight types of cancer (breast, ovarian, kidney, lung, colon, bladder, uterus, and thyroid) using a straightforward method based on one-dimensional gel electrophoresis. A total of six NPs, silica and polystyrene NPs with various functional groups (plain, NH<sub>2</sub>, and COOH), were exposed to a total of 43 plasmas, 5 for each of the 8 investigated cancers plus 3 controls, to create personalized BCs. By analyzing the densitometric profiles of proteins' molecular weights, we demonstrated that the BC signatures of NPs can distinguish healthy individuals from those affected by cancer. We revealed that certain BCs could discriminate against specific types of cancer, <i>i.e.</i> ovarian and kidney cancer, and that amination could improve the diagnostic power of the platform. Being fast, cheap, and requiring only a blood sample, if validated on a more comprehensive cohort of patients, this method could serve as a first-line diagnostic tool, guiding decisions on further invasive testing and/or patient monitoring post-surgery or during treatment. Polystyrene ; Cancer ; Surface modification ; Nanoparticle ; Cancer detection ; Nanomaterials ; Microfluidics Nanoparticle-Based Drug Delivery ; Bone Tissue Engineering Materials ; Diatoms and Algae Research
Authors: Rani Arielly
Source: Sensors (article, 2025-04-29)
Field: Chemistry — Analytical Chemistry

Transmission Raman Spectroscopy for Inner Layers Chemical Analysis of Fresh Produce Identification of chemical properties in the inner tissues of fresh produce would enable us to identify major issues plaguing the agriculture supply chain, like off-flavors and core rot since these are caused by or accompanied by known chemical elements. We show the development of transmission Raman spectroscopy system for identifying these elements by addressing several issues: we located an optimal spectral window by conducting optical attenuation measurements and calculated the required LASER power in that range. For apple tissues, this optical window was found in the 700-950 nm range, and the required LASER power range was calculated to be in the 40-700 mW range. We also calculated that the optimal shifted-excitation Raman difference spectroscopy wavelengths should be separated by 0.7 nm in order to optimally produce narrow and high-intensity Raman peak features and eliminate the competing fluorescence signal. Finally, we provide a complete optical system design with exact optimal parameters. In contrast to other fields like pharmaceuticals and medicine, transmission Raman spectroscopy has not been applied extensively in agriculture. Therefore, this study fills a gap in that field's applicability. Raman spectroscopy ; Transmission (telecommunications) ; Spectroscopy ; Surface-enhanced Raman spectroscopy ; Materials science ; Analytical Chemistry (journal) ; Telecommunications ; Optoelectronics ; Chemistry ; Computer science ; Optics ; Physics ; Raman scattering ; Chromatography Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Fermentation and Sensory Analysis