jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Danylo Komisar | Andrii Kutsyk | Oleksandr Vasyliev | Yaroslav V. Aulin | Sofus Boisen | Konstantinos Stergiou | Yuriy Pilgun | Lars Duelund | Rime El-Houri | Martin A.B. Hedegaard | Oleksii Ilchenko
Source: Journal of Raman Spectroscopy (article, 2025-08-10)
Field: Chemistry — Analytical Chemistry

Portable Raman Spectroscopy for Non‐Invasive Chemotype Identification and pCB Profiling in Cannabis ABSTRACT Cannabis plants are cultivated primarily for their fiber, seeds, and phytocannabinoids (pCBs): delta‐9‐tetrahydrocannabinol (THC), cannabidiol (CBD), etc. Each plant has a certain pCBs profile usually belonging to one of the known chemotypes: THC‐dominant (I), THC/CBD‐intermediate (II), CBD‐dominant (III), etc. Important tasks for ensuring profitability and legality in the cannabis industry are the differentiation of plants by chemotype (preferably in the vegetative stage) and the determination of pCBs contents (first, psychoactive THC) in plants/products. Chromatography‐coupled methods, commonly used for this, are bulky, invasive, time‐, cost‐, and infrastructure‐consuming, and thus are low‐effective for high‐throughput measurements, especially under field conditions. Fast hand‐held Raman spectroscopy can overcome these drawbacks. This study evaluates the performance of compact hand‐held Raman spectrometers in cannabis chemotype differentiation. Two instruments with 785‐nm/46‐mW and 830‐nm/76‐mW excitations were used to measure spectra from leaves of cannabis plants (chemotypes I and III; over 60 spectra for each), as well as THC distillate and CBD standard. Classification models based on partial least squares discriminant analysis (PLS‐DA) were developed using 70% of leaves spectra for training/cross‐validation and 30% for test‐set validation. A prediction accuracy of 90% was achieved for the device with 830‐nm excitation, confirming its effectiveness for rapid, non‐invasive, in vivo differentiation of plants by chemotype. Additionally, a detailed comparative analysis of spectra from cannabis leaves, THC distillate, CBD standard, and literature data revealed numerous pCB‐associated peaks, underscoring the method's capability for in‐depth pCB analysis. Principal component analysis (PCA) significantly improves peaks identifiability, potentially enabling pCBs contents quantification with appropriate calibration. Chemotype ; Cannabidiol ; Cannabis ; Chemistry ; Partial least squares regression ; Chromatography ; Mathematics ; Medicine ; Essential oil ; Statistics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; GABA and Rice Research
Authors: Hani Shanableh | Mohamed Barakat A. Gibril | Ahmed Mansour | Aditya Dixit | Rami Al‐Ruzouq | Nezar Hammouri | Fouad Lamghari | Safa M. Ahmed | Ratiranjan Jena | Tamer Mohamed | Mohammed Abdulraheem Almarzouqi | Nedal Salem Alafayfeh | Simon Zerisenay Ghebremeskel
Source: ISPRS annals of the photogrammetry, remote sensing and spatial information sciences (article, 2025-07-12)
Field: Chemistry — Organic Chemistry

A Comparative Analysis of Deep Learning Methods for Ghaf Tree Detection and Segmentation from UAV-based Images Abstract. The Prosopis cineraria, commonly known as the Ghaf tree, is an ecologically significant species that prevents desertification, enhances soil fertility, and supports biodiversity within arid ecosystems. Mapping and monitoring Ghaf trees using unmanned aerial systems (UAVs) and deep learning are essential for advancing conservation efforts through reliable, automated assessments. In this study, we performed a comparative analysis of several transformer-based deep learning models, including Mask DETR with Improved Denoising Anchor Boxes (Mask DINO) and Mask R-CNN models based on the Vision Transformer (ViT), Swin Transformer, and Enhanced Multiscale ViT (MViTv2), for mapping Ghaf trees from UAV images captured in diverse urban and agricultural environments. Results demonstrated strong potential for the assessed instance segmentation architectures in mapping Ghaf trees, achieving mean average precision values of 80% to 84.2% for detection and 82.2% to 85.1% for segmentation, with F1-scores ranging from 83.55% to 88.3% for detection and 85.5% to 88.6% for segmentation. This study underscores the effectiveness of transformer-based deep learning architectures for mapping Ghaf trees from UAV images, with findings and refinements that can be applied and extended to map other native tree species and support broader conservation initiatives. Artificial intelligence ; Segmentation ; Deep learning ; Tree (set theory) ; Computer science ; Pattern recognition (psychology) ; Computer vision ; Remote sensing ; Geography ; Mathematics Wood and Agarwood Research ; Remote Sensing and LiDAR Applications ; Smart Agriculture and AI
Authors: Bincy Raj | D.S. Seetharam | Sharangouda J. Patil
Source: Scripta Medica (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Green extraction of bioactive compounds from marine constituents Marine organisms house diverse bioactive compounds, making them a prime focus in marine pharmacology. This abstract explores eco-friendly extraction methods for isolating bioactive marine constituents and peptides from marine sources, underscoring their sustainability and environmental responsibility. Green extraction technologies include supercritical fluid extraction (SFE), pressurised solvent extraction (PSE) and enzyme extraction using microwaves and ultrasounds. Since there is less chemical interference, these newer, greener technologies would be safer. The extraction, isolation and characterisation of these marine constituents can lead to the identification of novel constituents from marine sources. Marine components and bioactive peptides made by marine species have a wide range of pharmacological capabilities, such as antioxidant, anti-inflammatory, antibacterial and anticancer activity. These attributes position marine-derived constituents as promising candidates for drug development and the creation of functional foods and nutraceuticals. Application of sustainable extraction methods aligns with responsible marine resource management principles; particularly important as marine ecosystems face increasing challenges from overexploitation and environmental stressors. Green extraction harmonises scientific exploration with ecological preservation within the area of marine pharmacology, promising advancements and responsible utilisation of marine resources. Extraction (chemistry) ; Chemistry ; Biochemical engineering ; Environmental chemistry ; Chromatography ; Engineering Chromatography in Natural Products ; Free Radicals and Antioxidants ; Computational Drug Discovery Methods
Authors: Sara I. Aboras | Mahmoud A. Abdel-Hakim | Hadir M. Maher | Rasha M. Youssef
Source: BMC Chemistry (article, 2025-05-23)
Field: Chemistry — Analytical Chemistry

Cutting-edge assays for mirabegron and tadalafil combo therapy for benign prostatic hyperplasia; insilico kinetics approach; multi trait sustainability assessment The combination therapy of mirabegron (MIR) and tadalafil (TAD) has gained significant attention in clinical practice for the treatment of Benign Prostatic Hyperplasia as well as overactive bladder syndrome. This study demonstrates the development and validation of two analytical methods for the concurrent determination of tadalafil and mirabegron in their synergistic combo therapy. Spectrophotometry and stability-indicating HPLC were employed for the accurate quantification of both drugs. The spectrophotometric methods were based on derivative, Fourier and ratio derivative of the two drugs, providing simpler, rapid alternatives for routine analysis. The stability-indicating HPLC method was developed using a reverse-phase column with a methanol-phosphate buffer gradient mobile phase, achieving optimal separation with detection at 250 nm for MIR and 225 nm for TAD. Forced degradation studies were performed under acidic, basic, oxidative, neutral, thermal, and photolytic conditions, confirming the method's ability to quantify MIR and TAD in presence of degradation products and establish drug stability. Both techniques were validated based on ICH guidelines, demonstrating excellent linearity, precision, accuracy, and sensitivity. The methods were successfully applied to the analysis of bulk powder and in dosage forms. Both methods were evaluated and found to be environmentally friendly, receiving approval as "green" according to the AGREE (Assessment Tool for Greenness) method, "white" under the RGB12 criteria, and "blue" according to the BAGI (Blue Analytical Greenness Index). These evaluations demonstrate the sustainability and eco-friendliness of the proposed analytical techniques. Furthermore, artificial intelligence was employed through an online tool to ensure that there were no potential drug-drug interactions between MIR and TAD, offering an additional layer of safety in clinical applications. This research contributes to the enhancement of quality control for patients undergoing combination therapy with MIR and TAD and stability testing. Tadalafil ; Chromatography ; Biomedical engineering ; Chemistry ; Medicine ; Internal medicine Analytical Methods in Pharmaceuticals ; Hormonal and reproductive studies ; Pesticide Residue Analysis and Safety
Authors: Zhixin Liu | Aizhi Qin | Yinpeng Zhang | Qianli Zhao | M Li | Hao Liu | Yaping Zhou | Mengmeng Zhou | Lulu Yan | Chunyang Li | Luyao Kong | Chun‐Peng Song | Xuwu Sun
Source: New Phytologist (article, 2025-12-25)
Field: Chemistry — Spectroscopy

Mass spectrometry imaging: principles and applications in plant research Mass spectrometry imaging (MSI) is an advanced analytical technique that combines mass spectrometry with spatial mapping, enabling the direct, label-free detection and visualization of molecular distributions within biological tissues. This review comprehensively outlines the fundamental principles, major technological platforms, and recent applications of MSI in plant science. We detail key ionization techniques - matrix-assisted laser desorption/ionization (MALDI), desorption electrospray ionization (DESI), and secondary ion mass spectrometry (SIMS) - focusing on their ionization mechanisms and instrumental characteristics. We then highlight the transformative impact of MSI in plant research, specifically covering: plant metabolomics, localization of bioactive compounds in medicinal plants, elucidation of plant-microbe interaction mechanisms, and studies of plant responses to environmental stresses. Finally, we discuss current challenges and future directions for the technology. Due to its high sensitivity, spatial resolution, and label-free capability, MSI has become a pivotal tool for uncovering plant physiological processes and metabolic regulatory networks, demonstrating significant potential for broad application in plant science. Mass spectrometry ; Mass spectrometry imaging ; Electrospray ionization ; Desorption electrospray ionization ; Metabolomics ; Ionization ; Ambient ionization ; Analytical Chemistry (journal) Mass Spectrometry Techniques and Applications ; Ion-surface interactions and analysis ; Metabolomics and Mass Spectrometry Studies
Authors: Xiaoyu Jiao | Junhong Jia | Wei Chen | Wenlong Yang
Source: Coatings (article, 2025-01-20)
Field: Materials Science — Materials Chemistry

Electrochemical Corrosion and Wear Behavior of Hot-Dip Galvanized Steel in Soils of Northern China The study examined the corrosion and wear characteristics of hot-dip galvanized steel in complex soil environments. The results showed that hot-dip galvanized steel exhibited improved corrosion resistance characteristics. Additionally, the sliding speed was observed to influence both the coefficient of friction (COF) and the state of the worn surface. Moreover, the corrosion resistance of hot-dip galvanized steel declined as the immersion period increased. Following the incorporation of friction behavior, the galvanized layer is prone to accelerated degradation. The wear of the galvanized layer resulted in the failure of its electrochemical protection, creating a pathway for corrosion to occur on the substrate as a result of the coupling effect of corrosion and wear. The use of hot-dip galvanized steel presents challenges when exposed to a tribocorrosion environment for a prolonged period. This study lays the groundwork for future research on the maintenance cycle of industrial structures constructed primarily with hot-dip galvanized steel. Galvanization ; Metallurgy ; Corrosion ; China ; Materials science ; Electrochemistry ; Soil water ; Environmental science ; Composite material ; Geography ; Archaeology ; Electrode ; Soil science ; Chemistry Corrosion Behavior and Inhibition ; Concrete Corrosion and Durability ; Hydrogen embrittlement and corrosion behaviors in metals
Authors: Thi H. Bui | Oluwakamisi Adetunji | Carson C. Cole | Le Yu | Caroline M. Peterson | Jeffrey D. Hartgerink
Source: Advanced Science (article, 2025-08-18)
Field: Materials Science — Biomaterials

De Novo Design of Specific Heterotrimeric Collagen‐Like Peptides via Genetic Algorithm Collagen, the most abundant protein by mass in mammals, features a triple-helical structure composed of three intertwined peptide strands. Nonequivalent strands can assemble, forming heterotrimeric structures, which are more prevalent among natural collagens. However, the design and application of heterotrimeric collagen mimetic peptides (CMPs) are constrained by the potential formation of competing compositions and registers, which impede the formation of target assemblies. Herein, a computational protocol is described, GRACE, utilizing a genetic algorithm to reproducibly generate peptide sequences having a strong tendency to self-assemble into heterotrimeric triple helices with high specificity. The approach leverages SCEPTTr1.2, a refined scoring function tailored to estimate CMP stability and structure, as the basis for fitness evaluation. Four sets of peptide sequences generated by the algorithm, including two with bio-relevant integrin-binding motifs, are experimentally synthesized and characterized. All computationally designed peptides are experimentally shown to self-assemble into heterotrimeric triple helices with expected registers having a minimum specificity of 13.5 °C. The study represents a robust method to overcome barriers in heterotrimeric CMP design providing a versatile framework for the fundamental study of collagen as well as engineering collagen-like materials. Heterotrimeric G protein ; Peptide ; Computational biology ; Chemistry ; Biology ; Computer science ; Biochemistry ; G protein ; Receptor Collagen: Extraction and Characterization ; Protein Hydrolysis and Bioactive Peptides ; Silk-based biomaterials and applications
Authors: AKASH HR | Kshama Devi | S. BELIN | Senthil Kumar G. P | MOHD ABDUL BAQI | N. VENKATHESHAN | M. Lakshmi Sucharitha | KOPPULA JAYANTHI
Source: International Journal of Applied Pharmaceutics (article, 2025-09-07)
Field: Chemistry — Organic Chemistry

EXPLORATION OF NICOTINOYL HYDRAZINE DERIVATIVES THROUGH IN SILICO STUDIES FOR NOVEL ANTI-TUBERCULAR DRUG DEVELOPMENT Objective: This study explores the interactions of structurally novel nicotinoyl hydrazine derivatives with enoyl-acyl carrier protein reductase (INHA), a key enzyme involved in cellular metabolism regulation. The focus is on the tuberculosis (TB)-associated INHA pathway (PDB ID: 2NSD), aiming to evaluate the anti-tubercular potential of these compounds as inhibitors of the INHA catalytic subunit. Notably, these derivatives, particularly compound 6 (Benzyl nicotinoyl acetamide), feature a unique nicotinoyl hydrazine scaffold with functional groups distinct from known INHA inhibitors such as triclosan or diazaborines. Methods: Molecular docking of the compounds was performed using the Glide module. An absorption, distribution, metabolism, and excretion (ADME) analysis was conducted using QikProp. The Prime Molecular Mechanics Generalized Born Surface Area (MM-GBSA) method was employed to calculate binding free energy. Results: Ten compounds exhibited significant binding affinity and interactions, forming hydrogen and pi-cation bonds with key residues such as SER 84, LYS 163, ALA 22, GLY 14, LYS 165, PHE 142, SER 86, TYR 153, LYS 145, TYR 158, MET 167, PHE 168, SER 88, ILE 186, TYR 188, SER 20, PHE 148, and ILE 184 within the INHA catalytic subunit (PDB ID: 2NSD). Among these, Compound 6 demonstrated an exceptional Glide extra precision (XP) docking score of –10.74 kcal/mol and a binding free energy (ΔG_bind) of –109.48 kcal/mol, indicating stronger binding potential than the standard drug isoniazid. Prime MM-GBSA analysis further confirmed its promising binding affinities, with ΔBind (-109.48 kcal/mol), ΔLipo (-45.99 kcal/mol), and ΔVdW (-73.62 kcal/mol). The ligand consistently interacted with residues SER 88, SER 86, ILE 186, and TYR 188. Conclusion: Benzyl nicotinoyl acetamide (Compound 6), with its structurally novel scaffold and potent binding metrics, exhibits significant potential as an INHA inhibitor. Characterized by functional groups such as a secondary amine (NH), ether (C-O-C), hydroxyl (OH), pyridine, carbonyl (C=O), and phenyl (C6H5), it shows potential application as an anti-tubercular agent, particularly for tuberculosis treatment. INHA ; Docking (animal) ; In silico ; Binding site ; Drug design ; Molecular model ; Enzyme ; Ligand (biochemistry) Synthesis and biological activity ; Bioactive Compounds and Antitumor Agents ; Computational Drug Discovery Methods
Authors: Muhammad Shehram
Source: Journal of Thermal Engineering (article, 2025-01-01)
Field: Materials Science — Surfaces, Coatings and Films

Enhancing flat plate collectors’ efficiency by minimizing optical losses through vacuum glazing and ethylene glycol-diamond-alumina nanofluid This study addresses the critical need to improve the efficiency of solar flat plate collectors (FPC) where the key factors influencing their performance include the choice of working fluids, exposure to sunlight, and minimizing heat loss.Carbon-based nanofluids, known for their exceptional thermal stability and heat transfer properties, emerge as a promising solution.This research presents an innovative approach by combining carbon-based (ethylene glycol-diamond) and metal-oxide-based (alumina) hybrid nanofluids to boost collector efficiency.Additionally, a two-step strategy is employed to reduce reflection losses.A triple glaze is applied to the collector's top surface, followed by vacuum glazing.The latter, consisting of three layers of low-iron glass with an emissivity of 0.20 and a solar transmittance of 0.87 which reduces the glass thickness.This integration of vacuum glass and hybrid nanofluid results in an 82% increase in FPC efficiency.The nanofluids, with nanoparticles sized between 100 and 200 nm and material volume fractions of 0.3% for carbon-based and 0.1% for metal-oxide-based components, circulate at 4 L/min.Ethylene glycol has an energy efficiency of 58%, alumina 68%, and diamond nanofluids 71.8%.Heat transfer coefficients are 0.88 for ethylene glycol, 0.93 for alumina-based nanofluids, and 0.98 for diamond-based fluid.The hybrid nanofluids also exhibit heat loss ranging from 2.4 W/m.K to 4.0 W/m.K. Triple glaze vacuum layers achieve an efficiency peak of 82%, significantly reducing heat loss to 700W compared to single and double layers.The study utilizes Python in an Anaconda Jupyter notebook for detailed system modeling, facilitating thorough simulation of the system. Nanofluid ; Glazing ; Materials science ; Ethylene glycol ; Diamond ; Composite material ; Optics ; Chemical engineering ; Nanoparticle ; Nanotechnology Optical Coatings and Gratings ; Semiconductor materials and devices ; Advanced Fiber Optic Sensors
Authors: Fränze Müller | Micha J. Birklbauer | Julia A. Bubis | Karel Stejskal | Viktoria Dorfer | Karl Mechtler
Source: Nature Communications (article, 2025-11-10)
Field: Chemistry — Spectroscopy

Breaking barriers in crosslinking mass spectrometry with enhanced throughput and sensitivity using Orbitrap Astral Crosslinking mass spectrometry is an essential tool for probing protein-protein interactions and structural organization. We here compare Orbitrap Astral and Orbitrap Eclipse instruments using Cas9 crosslinked with PhoX and DSSO under standardized chromatographic and acquisition conditions. The Astral identifies over 40% more unique residue pairs, largely due to increased MS1 sensitivity and efficient detection of low-abundance precursors. Implementation of high-field asymmetric ion mobility spectrometry further increases identifications by 30% through improved precursor filtering. On the Astral, single higher-energy collisional dissociation consistently outperforms stepped fragmentation, particularly at low sample amounts, whereas the Eclipse shows minimal dependence on fragmentation strategy. Gradient optimization experiments demonstrate that longer separations enhance identifications in purified crosslinked samples, while gains plateau in complex backgrounds, indicating the need for enrichment or isolation strategies. Column comparisons show that pore size and particle diameter affect separation efficiency, with the Aurora Ultimate column yielding sharper peaks and more crosslink identifications than PepMap. Together, these findings emphasize that instrument choice, fragmentation mode, and chromatographic design directly influence crosslinking performance. The Astral's combination of sensitivity and scan speed supports comprehensive detection of low-abundance crosslinks, providing deeper structural coverage of protein interaction networks. Orbitrap ; Mass spectrometry ; Fragmentation (computing) ; Analytical Chemistry (journal) ; Chromatographic separation ; Dissociation (chemistry) Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Ion-surface interactions and analysis