jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Agnieszka Kowalska-Baron
Source: International Journal of Molecular Sciences (article, 2025-06-11)
Field: Chemistry — Organic Chemistry

Theoretical Insight into Antioxidant Mechanisms of Trans-Isoferulic Acid in Aqueous Medium at Different pH This study presents the first comprehensive theoretical investigation of the antioxidant mechanisms of trans-isoferulic acid against hydroperoxyl (HOO<sup>•</sup>) radicals in aqueous solution, using the DFT/M062X/6-311+G(d,p)/PCM method. Thermodynamic and kinetic parameters, including reaction energy barriers and bimolecular rate constants, were determined for the three major pathways: hydrogen transfer (HT), radical adduct formation (RAF), and single electron transfer (SET). The results indicate that, at physiological pH, the RAF mechanism is both more exergonic and approximately eight-times faster than HT. At a higher pH, where the phenolate anion dominates, antioxidant activity is enhanced by an additional fast, diffusion-limited SET pathway. Isoferulic acid was also found to effectively chelate Fe<sup>2+</sup> ions at pH 7.4 and above, forming stable complexes that could inhibit Fenton-type hydroxyl radical generation. Moreover, its strong UV absorption suggests a role in limiting photo-induced free radical formation. These findings not only clarify the antioxidant behavior of isoferulic acid but also provide novel theoretical insights applicable to related phenolic compounds. The compound's multi-target antioxidant profile highlights its potential as a photoprotective agent in sunscreen formulations. Antioxidant ; Chemistry ; Aqueous solution ; Biochemistry ; Organic chemistry Free Radicals and Antioxidants ; Electrochemical Analysis and Applications ; Chemical and Physical Properties in Aqueous Solutions
Authors: Amy Barton Pai | Zhoumeng Lin | Heather H. Gustafson | Beat Flühmann | Reinaldo Digigow | Vanesa Ayala‐Nunez | Stephan Schmidt
Source: Clinical Pharmacokinetics (review, 2025-08-15)
Field: Materials Science — Biomaterials

Challenging Traditional ADME Assumptions for Physiologically Based Pharmacokinetic Models for Intravenous Administration of Iron–Carbohydrate Nanomedicines: Potential Utility of Gold Nanoparticle Models as a Roadmap Intravenous iron-carbohydrate complexes are a class of nanomedicines that are widely used globally to treat iron deficiency and iron deficiency anemia associated with a wide spectrum of disease states. Despite being widely used in clinical practice for more than seven decades, the understanding of their in vivo disposition including tissue biodistribution and kinetics of the nanoparticle degradation at the cellular level is not well-understood. Moreover, the critical quality attributes that influence in vivo pharmacokinetics have not been fully defined. In particular, the carbohydrate moiety plays an influential role in how the nanoparticulate iron-carbohydrate complex interacts with the biological system. Developing a physiologically based pharmacokinetic (PBPK) model would facilitate a deeper understating of the key nanomedicine attributes that predict in vivo performance. Because endogenous iron metabolism complicates pharmacokinetic modeling for this complex class of drugs, models of gold nanoparticles may provide a substantive roadmap to begin to build a viable PBPK model for iron-carbohydrate nanomedicines. In the future, PBPK models that integrate recent mechanistic data regarding tissue biodistribution and intracellular iron kinetics for parameterization have the potential to improve manufacturing quality and clinical use of these complex drugs. Physiologically based pharmacokinetic modelling ; Biodistribution ; Pharmacokinetics ; Nanomedicine ; ADME ; Pharmacology ; Chemistry ; In vivo ; Computational biology ; Nanotechnology ; Biochemical engineering ; Medicine ; Nanoparticle ; Biochemistry ; Biology ; Materials science ; Biotechnology ; Engineering ; In vitro Nanoparticle-Based Drug Delivery ; Advanced Drug Delivery Systems ; Drug Solubulity and Delivery Systems
Authors: Fran Nekvapil | Cosmin Farcǎu
Source: Nanoscale Advances (article, 2025-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

The role of focused laser plasmonics in shaping SERS spectra of molecules on nanostructured surfaces Over fifty years have passed since the groundbreaking discovery of Surface Enhanced Raman Scattering (SERS), yet many aspects of this phenomenon remain elusive. In this study, we unveil novel observations concerning the spatial variation of SERS signal profiles through vertical (<i>Z</i> axis) scans, performed by varying the distance between the laser focus and a solid, planar, nanostructured SERS substrate. The signal strength profile manifests a Lorentzian shape during axial scans along the <i>Z</i> direction, consistently peaking above the actual sample surface. More intriguingly, the intensity ratio of various spectral regions-including SERS bands and background-exhibits significant non-constancy along the <i>Z</i> axis. Finite-Difference Time-Domain (FDTD) simulations suggest that these variations can be attributed to specific plasmonic near-field responses induced by the focused/defocused beam at the SERS substrate. This research highlights the critical need to consider that focus imprecision can alter spectral profiles in SERS analyses on solid nanostructured SERS substrates, particularly when devising quantitative assays based on band intensity ratios. Plasmon ; Raman spectroscopy ; Materials science ; Molecule ; Laser ; Spectral line ; Nanotechnology ; Optoelectronics ; Optics ; Chemistry ; Physics Gold and Silver Nanoparticles Synthesis and Applications ; Nonlinear Optical Materials Studies ; Quantum Dots Synthesis And Properties
Authors: Burak Erman
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-05-15)
Field: Materials Science — Materials Chemistry

Extending the Gaussian Network Model: Integrating Local, Allosteric, and Structural Factors for Improved Residue-Residue Correlation Analysis Abstract The Gaussian Network Model (GNM) has been successful in explaining protein dynamics by modeling proteins as elastic networks of alpha carbons connected by harmonic springs. However, its uniform interaction assumption and neglect of higher-order correlations limit its accuracy in predicting experimental B-factors and residue cross-correlations critical for understanding allostery and information transfer. This study introduces an information-theoretic enhancement to the GNM, incorporating mutual information-based corrections to the Kirchhoff matrix to account for multi-body interactions and contextual residue dynamics. By iteratively optimizing B-factor predictions and applying a Monte Carlo-driven maximum entropy approach to refine covariances, our method achieves significant improvements, reducing RMSDs between predicted and experimental B-factors by 26–46% across eight representative proteins. The model contextualizes residue assignments based on local density, secondary structure, solvent exposure, and allosteric roles, showing complex dynamic patterns beyond simple neighbor counts. Enhanced predictions of mutual information and entropy transfer in proteins like KRAS highlight improved capture of allosteric communication pathways. This evolvable framework, capable of incorporating additional effects and utilizing contextual residue assignments, enables precise studies of mutation effects on protein dynamics, with improved cross-correlation predictions potentially increasing accuracy in drug design and function prediction. Residue (chemistry) ; Allosteric regulation ; Gaussian ; Gaussian network model ; Correlation ; Econometrics ; Mathematics ; Biological system ; Computer science ; Statistics ; Chemistry ; Biology ; Computational chemistry ; Biochemistry ; Geometry Graphite, nuclear technology, radiation studies ; Integrated Circuits and Semiconductor Failure Analysis ; Nuclear Materials and Properties
Authors: Ying Chen | Xiaomeng Xu | Chunping Tang
Source: Molecules (article, 2025-08-01)
Field: Chemistry — Analytical Chemistry

A Metabolomics Exploration of Young Lotus Seeds Using Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging Lotus (<i>Nelumbo nucifera</i> Gaertn.) is a quintessential medicinal and edible plant, exhibiting marked differences in therapeutic effects among its various parts. The lotus seed constitutes a key component of this plant. Notably, the entire seed and the plumule display distinct medicinal properties. To investigate the "homologous plants with different effects" phenomenon in traditional Chinese medicine, this study established a Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) method. This study employed immature lotus seeds as the experimental material, diverging from the mature seeds conventionally used. Conductive double-sided tape was employed for sample preparation, and complete longitudinal sections of the seeds were obtained, followed by MALDI-MSI analysis to identify and visualize the spatial distribution of characteristic secondary metabolites within the entire seeds. The results unveiled the diversity of metabolites in lotus seeds and their differential distribution across tissues, with pronounced distinctions in the plumule. A total of 152 metabolites spanning 13 categories were identified in lotus seeds, with 134, 89, 51, and 98 metabolites discerned in the pericarp, seed coat, cotyledon, and plumule, respectively. Strikingly, young lotus seeds were devoid of liensinine/isoliensinine and neferine, the dominant alkaloids of mature lotus seed plumule, revealing an early-stage alkaloid profile that sharply contrasts with the well-documented abundance found in mature seeds and has rarely been reported. We further propose a biosynthetic pathway to explain the presence of the detected benzylisoquinoline and the absence of the undetected bisbenzylisoquinoline alkaloids in this study. These findings present the first comprehensive metabolic atlas of immature lotus seeds, systematically exposing the pronounced chemical divergence from their mature counterparts, and thus lays a metabolomic foundation for dissecting the spatiotemporal mechanisms underlying the nutritional and medicinal value of lotus seeds. Lotus ; Metabolomics ; Lotus effect ; Botany ; Mass spectrometry ; Mass spectrometry imaging ; Biology ; Chemistry ; Horticulture ; Chromatography Chromatography in Natural Products ; Analytical Chemistry and Chromatography ; Metabolomics and Mass Spectrometry Studies
Authors: Öyküm Kanbir | Kadir AYAS | Kadir Çavdar
Source: Materials Testing (article, 2025-04-01)
Field: Materials Science — Surfaces, Coatings and Films

Effect of atmospheric pressure plasma treatment on the wettability and aging behavior of metal surfaces Abstract Atmospheric pressure plasma (APP) applications have started to come to the fore today because of their fast and stable applicability to material surfaces and many advantages compared to plasma applications made under vacuum. With APP, it is possible to improve the surface energies, adhesion behavior and surface mechanical properties of materials. However, the changes obtained are not permanent since the surface tends to return to its untreated original state after plasma treatment. In this study, the wettability of APP treated metal surfaces, aging behavior and storage conditions that can delay the return of the surface to its untreated initial state were investigated. While one type of material (H300LAD), two different plasma treatments (cold and hot) and three different plasma treatment numbers (1, 2 and 3 times) were determined as test parameters; two different ambient conditions such as air and water (for 1, 10 and 60 min) were chosen as the storage conditions that can delay the return of the plasma treated surfaces to their original state. In addition, the effects of temperature on the aging time were investigated for two different temperature values (−20 °C and 30 °C). The effects of the applied plasma type, plasma treatment number, the storage conditions in which the samples were kept and the temperature on the aging behavior were evaluated and the conditions that could delay the aging time were investigated. The results showed that aging is greatly affected by the type of plasma applied to the surfaces, the storage conditions in which the samples were kept and the temperature. Wetting ; Atmospheric-pressure plasma ; Metal ; Atmospheric pressure ; Materials science ; Plasma ; Composite material ; Metallurgy ; Meteorology ; Geography ; Physics Surface Modification and Superhydrophobicity ; Additive Manufacturing and 3D Printing Technologies ; Adhesion, Friction, and Surface Interactions
Authors: Nuzhat Noor Islam Prova
Source:  (preprint, 2025-01-31)
Field: Chemistry — Analytical Chemistry

Enhancing Agricultural Research with an Attention-Based Hybrid Model for Precise Classification of Rice Varieties As a staple food feeding over half of the world's population, rice needs well defined classification techniques to improve agricultural yields, the supply chain, and food safety. To meet these needs, this work presents an Attention-Based Hybrid Model Agriculture ; Computer science ; Agricultural engineering ; Artificial intelligence ; Machine learning ; Geography ; Engineering ; Archaeology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Callum Gassner | Jitraporn Vongsvivut | Meguya Ryu | Soon Hock Ng | Marko Toplak | Vijayakumar Anand | Pooja Takkalkar | Mary Louise Fac | Natalie A. Sims | Bayden R. Wood | Mark J. Tobin | Saulius Juodkazis | Junko Morikawa
Source: Computers in Biology and Medicine (article, 2025-07-06)
Field: Chemistry — Spectroscopy

Bridging spectroscopy and advanced molecular orientation analysis with new 4＋ angle polarization toolbox in Quasar Anisotropy plays a critical role in governing the mechanical, thermal, electrical, magnetic, and optical properties of materials, influencing their behavior across diverse applications. Probing and quantifying this directional dependence is crucial for advancing materials science and biomedical research, as it provides a deeper understanding of structural orientations at the molecular level, encompassing both scientific and industrial benefits. This study introduces the "4＋ Angle Polarization" widget, an innovative extension to the open-source Quasar platform (https://quasar.codes/), tailored for advanced multiple-angle polarization analysis. This toolbox enables precise in-plane molecular orientation analysis of complex microspectroscopic datasets through a streamlined workflow. Using polarized Fourier transform infrared (p-FTIR) spectroscopy, we demonstrate its versatility across various sample types, including polylactic acid (PLA) organic crystals, murine cortical bone, and human osteons. By overcoming the limitations of traditional two-angle methods, the widget significantly enhances the accuracy of structural and orientational analysis. This novel analytical tool expands the potential of multiple-angle p-FTIR techniques into advanced characterization of structural anisotropy in heterogeneous systems, providing transformative insights for materials characterization, biomedical imaging and beyond. Toolbox ; Bridging (networking) ; Polarization (electrochemistry) ; Spectroscopy ; Molecular spectroscopy ; Quasar ; Computer science ; Optics ; Materials science ; Physics ; Chemistry ; Astronomy ; Galaxy ; Physical chemistry Analytical Chemistry and Chromatography ; Molecular spectroscopy and chirality ; Spectroscopy and Chemometric Analyses
Authors: Shangye Ma | Samuel J. Baxter | Changyong Park | Stella Chariton | A. M. dos Santos | Jamie J. Molaison | Angus P. Wilkinson
Source: Chemistry of Materials (article, 2025-02-04)
Field: Materials Science — Materials Chemistry

Helium Incorporation into Scandium Fluoride, a Model Negative Thermal Expansion Material Scandium trifluoride is a model negative thermal expansion (NTE) material. Its simple structure can be described as an A-site vacant perovskite, and it shows isotropic NTE over a very wide temperature range (up to ∼1100 K), due to transverse vibrational motion of the fluoride. Like many framework NTE materials, it undergoes a phase transition at low pressures, adopting a rhombohedral (<i>R</i>3̅<i>c</i>) structure at >0.7 GPa and 300 K in commonly used nonpenetrating pressure media, such as silicone oil. High pressure X-ray diffraction data and gas uptake/release measurements indicate that, on compression in helium above ∼200 K, helium is inserted into ScF<sub>3</sub> to form the defect perovskite He <sub><i>x</i></sub> ScF<sub>3</sub>. The incorporation of helium stiffens the structure and changes its phase behavior. At room temperature, complete filling of the structure with helium does not occur until >1.5 GPa. On compression, a cubic perovskite structure is maintained until ∼5 GPa. As the pressure was increased to ∼9.5 GPa, a further transition occurred at ∼7 GPa. The first transition at ∼5 GPa is likely to a tetragonal (<i>P</i>4/<i>mbm</i>) perovskite, but the detailed structure of the perovskite phase formed on compression above ∼7 GPa is unclear. Cooling down from 300 to 100 K in helium at ∼0.4 GPa leads to an approximate composition of He<sub>0.1</sub>ScF<sub>3</sub>. High pressure neutron diffraction measurements, in the temperature range 15-150 K show that the incorporation of helium increases the pressure at which the cubic (<i>Pm</i>3̅<i>m</i>) to rhombohedral (<i>R</i>3̅<i>c</i>) putative quantum structural phase transition occurs from close to 0 GPa to ∼0.2 GPa at 0 K. Scandium ; Fluoride ; Helium ; Materials science ; Thermal expansion ; Thermal ; Mineralogy ; Inorganic chemistry ; Chemistry ; Thermodynamics ; Physics ; Metallurgy ; Atomic physics Thermal Expansion and Ionic Conductivity ; Microwave Dielectric Ceramics Synthesis ; Inorganic Chemistry and Materials
Authors: Jung-Kyu Lee | Min Suk Kang | Dong-Hoon Lee
Source: Agriculture (article, 2025-04-16)
Field: Chemistry — Analytical Chemistry

Non-Destructive Prediction of Apple Moisture Content Using Thermal Diffusivity Phenomics for Quality Assessment With the surge in digital farming, real-time quality management of fresh produce has become essential. For apples (Malus domestica Borkh.), consumer demand extends beyond sweetness, texture, and appearance to internal quality factors such as moisture content. Existing non-destructive methods, however, involve costly equipment, complex calibration, and sensitivity to environmental conditions. This study hypothesizes that thermal diffusivity indices derived from surface heating and cooling patterns can accurately predict apple moisture content non-destructively. A total of 823 apples from seven varieties were analyzed using a thermal imaging sensor in a 120-s process comprising 40 s of heating and 80 s of cooling. Key thermal diffusivity indices—minimum, maximum, mean, and max–min values—were extracted and correlated with actual moisture content measured via the drying method. Multiple linear regression and leave-one-out cross-validation confirmed that mean temperature-based models provided the most stable predictions (RCV2 ≥ 0.90 for some varieties). Frame optimization and artificial neural networks further improved prediction accuracy for varieties exhibiting higher variability. The proposed method is cost-effective, requires minimal calibration, and is less affected by surface reflectance, outperforming conventional optical methods (e.g., NIR spectroscopy, hyperspectral imaging), especially regarding robustness against surface reflectance variability and calibration complexity. This offers a practical solution for monitoring apple freshness and quality during sorting and distribution processes, with expanded research on sugar content and acidity expected to accelerate commercialization. Phenomics ; Thermal diffusivity ; Water content ; Quality (philosophy) ; Moisture ; Environmental science ; Materials science ; Chemistry ; Composite material ; Engineering ; Physics Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Food Drying and Modeling
Authors: Mayur Dandekar | Umesh B. Telrandhe | Yash Salve | Isha A. Mirzapure
Source: International Journal of Applied Pharmaceutics (article, 2025-11-07)
Field: Materials Science — Biomaterials

RECENT ADVANCES IN NANOCARRIERS FOR TARGETED CANCER THERAPY One treatment option is detailed re-evaluating cancer for a very innovative and efficacious form of therapy. Nanocarrier-based delivery systems have offered an impetus in the form of targeted cancer drug delivery under better drug solubility, controlled release, and selective accumulation in tumour tissue. This review intends to address the major advances in applying nanocarrier-based cancer treatment, such as liposomes, polymeric nanoparticles, dendrimers, micelles, and carbon-and inorganic nanoparticle-based medication. Every type of nanocarrier has very clear and peculiar features that determine the increase in bioavailability and tumour targeting through passive (enhanced permeability retention effect) and active targeting (ligand-receptor interactions, pH-sensitive mechanisms, and stimuli-responsive drug release). Nanocarriers, including liposomes, polymeric nanoparticles, dendrimers, and micelles, have shown significant promise in targeted cancer therapy due to their ability to improve drug solubility, prolong circulation time, and enhance site-specific delivery while minimising systemic toxicity. Among the various platforms discussed, polymeric nanoparticles-particularly those utilising biodegradable polymers like PLGA-emerged as the most promising due to their tunable surface properties, sustained drug release profiles, and favorable biocompatibility. Despite their advantages, challenges such as biological heterogeneity, off-target accumulation, and regulatory barriers hinder clinical translation. Future efforts should focus on developing smart nanocarriers capable of stimuli-responsive release and patient-specific adaptability to overcome these limitations. The future of cancer therapy can, therefore, be expected to see a fantastic horizon in patient outcomes with the integration of such innovative platforms coming from nanocarrier with personalized medicine approaches. Nanocarriers ; Cancer therapy ; Drug delivery ; Targeted drug delivery ; Drug ; Cancer ; Targeted therapy ; Cancer treatment Nanoparticle-Based Drug Delivery ; Graphene and Nanomaterials Applications ; Dendrimers and Hyperbranched Polymers
Authors: Robert Fraczkiewicz
Source: Physical Chemistry Chemical Physics (article, 2025-01-01)
Field: Chemistry — Organic Chemistry

Thermodynamics-informed neural networks and extensive data sets: key factors to accurate blind predictions of apparent p<i>K</i><sub>a</sub> values in the euroSAMPL challenge Microscopic and macroscopic p<i>K</i>a values for 35 compounds selected by the organizers of euroSAMPL 1 challenge were blindly predicted with our thermodynamics-informed empirical S + p<i>K</i>a model (ranked submission 0x4cb7101f). Our results have received the first overall rank from the challenge organizers. We describe our methodology and discuss evaluation methods. Thermodynamics ; Key (lock) ; Artificial neural network ; Statistical physics ; Rank (graph theory) ; Physics ; Computer science ; Mathematics ; Artificial intelligence ; Combinatorics Free Radicals and Antioxidants ; Computational Drug Discovery Methods ; Machine Learning in Materials Science