jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jana K. Alwattar | Mohammad Assi | Sahar Nasser | Mohamad Rahal | Mohammed M. Mehanna
Source: Biomedicines (article, 2025-08-23)
Field: Materials Science — Biomaterials

Raloxifene-Loaded Lipid Nanovesicles: A Journey to Select the Optimal Nanocarrier Formulation Through Characterization and Cytotoxic Analysis <b>Background/Objectives</b>: Cancer ranks as the second most prevalent cause of death worldwide, according to the World Health Organization. Approximately one in six global deaths is attributed to cancer. Among females, breast cancer stands out as the most frequent type of tumor. Raloxifene (RLX), recognized as a selective estrogen receptor modulator, has been employed as a therapeutic option in treating breast cancer among postmenopausal women. The objective of this study was to investigate the anticancer potential of raloxifene-loaded hexosomes, nanoliposomes, and nanoniosomes to identify the most effective formulation. <b>Methods</b>: The particle size, zeta potential, entrapment efficiency, and structural elucidation of the various nanovesicle formulations was validated; <b>Results</b>: Each nanocarrier exhibited a negative surface charge, nanometric size, and a reasonable encapsulation efficiency. Cytotoxicity of the different raloxifene-loaded nanovesicles on MCF-7 breast cancer cell lines and MCF10 non tumorigenic cells revealed the substantial cytotoxic activity of the hexosomal nanocarrier compared to the other nanovesicles, exhibiting the lowest IC50 = 45.3 ± 1.10 µM. <b>Conclusions</b>: The RLX-loaded hexosomal formulation showed superior cytotoxic activity, indicating its potential as a highly effective therapeutic agent. To fully understand its capabilities and mechanisms, further in vitro characterization studies are necessary. Nanocarriers ; Raloxifene ; Chemistry ; Nanotechnology ; Materials science ; Medicine ; Drug delivery ; Internal medicine ; Cancer Nanoparticle-Based Drug Delivery ; Estrogen and related hormone effects ; RNA Interference and Gene Delivery
Authors: Thomas Vanhemel | Melanie Nijs | Angeliki Birmpili | Tim Hendriks | Eva Cuypers | Bart De Moor
Source: Rapid Communications in Mass Spectrometry (article, 2025-11-30)
Field: Chemistry — Spectroscopy

A Novel Peak‐Shape Aware Approach for Mass Alignment in Mass Spectrometry This paper presents a novel algorithm to reduce relative mass misalignment for mass spectrometry, validated on an extensive dataset. Thanks to the use of profile data, the peak shapes contribute to the computation of the warping function, and the warping function is approximated in a robust manner. An open-source Python implementation of the proposed methodology will be made accessible on GitHub: https://github.com/VanhemelThomas/psalign. Image warping ; Computation ; Python (programming language) ; Mass spectrometry ; Function (biology) Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Zhiwen Zhang | Luocheng Zhang | Xinxin Jiao | Sasa Zhao | Hua Wu | Junsong Xiao
Source: Foods (article, 2025-12-09)
Field: Chemistry — Organic Chemistry

Using Volatile Oxidation Products to Predict the Inflammatory Capacity of Oxidized Methyl Linoleate This study evaluated whether the volatile profile of methyl linoleate (MLO) can predict its pro-inflammatory capacity. MLO was subjected to two oxidation conditions simulating ambient storage and high-temperature frying. Free radicals, volatile compounds, and aldehydes were quantified using ESR, HS-SPME-GC-MS, and UPLC-MS/MS. Oxidized MLO was applied to RAW264.7 macrophages to evaluate inflammatory cytokines and oxidative stress responses, and PLSR models were developed to predict cellular outcomes based on volatile fingerprints. Both oxidation conditions induced substantial increases in short-chain and unsaturated aldehydes, with high-temperature oxidation generating markedly higher levels of key volatiles. Oxidized MLO significantly elevated TNF-α, IL-1β, COX-2, ROS, NO, and MDA while reducing SOD activity (<i>p</i> < 0.05), demonstrating strong pro-inflammatory and pro-oxidant effects. Volatile-based PLSR models achieved high predictive performance, with cross-validated and external R<sup>2</sup> values approaching 0.9 and RPD values exceeding 2. These findings show that volatile oxidation products reliably reflect the pro-inflammatory potency of oxidized lipids and can support the ranking of oxidized oils and lipid-rich foods, as well as guide processing and dietary strategies. Lipid oxidation ; Oxidative stress ; Oxidation reduction ; Autoxidation ; Potency ; Protein Carbonylation ; Oxidative phosphorylation Edible Oils Quality and Analysis ; Fatty Acid Research and Health ; Advanced Chemical Sensor Technologies
Authors: Chuirong Chi | Zhigang Fan | Qiang Song | Weiwei Cai | Huigao Duan
Source: Chinese Optics Letters (article, 2025-11-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multilayer topological metasurface-based color routers Topology (electrical circuits) ; Optical communication ; Network topology ; Beam splitter ; Field (mathematics) Metamaterials and Metasurfaces Applications ; Photonic Crystals and Applications ; Plasmonic and Surface Plasmon Research
Authors: Seniha Morsümbül
Source: Tekstil ve Mühendis (article, 2025-09-30)
Field: Materials Science — Polymers and Plastics

UV PROTECTION PROPERTIES OF CELLULOSIC-POLYESTER BLEND FABRICS: EFFECTS OF FIBER TYPE AND MOISTURE CONTENT This study investigates the effects of fiber type and moisture content on the ultraviolet (UV) protection properties of cellulosic–polyester blend fabrics. Twill-woven fabrics composed of cotton, viscose, and lyocell fibers blended with polyester, all with comparable structures and areal densities, were analyzed. Ultraviolet Protection Factor (UPF) measurements and air permeability tests were conducted to assess performance under both dry and wet conditions. The results revealed that polyester fibers provided the highest UV shielding effectiveness in blended fabrics, followed by cotton, viscose, and lyocell. Furthermore, the cross-sectional shape of polyester fibers significantly influenced UV protection, with hexa-channel fibers showing the highest UV protection, followed by micro- and circular-types. It was also observed that increasing moisture content reduced the UV protection of fabrics, while lower air permeability enhances their UV-blocking efficiency. These findings provide valuable insights for the development of UV-protective clothing, particularly for summer garments, and highlight opportunities for modeling and optimization in textile production. Lyocell ; Polyester ; Air permeability specific surface ; Ultraviolet ; Water content ; Moisture ; Fiber ; Permeability (electromagnetism) Textile materials and evaluations ; Dyeing and Modifying Textile Fibers ; Skin Protection and Aging
Authors: Harshal B. Desai | Vijay Togadiya | Promila Dhanda | K. Haleema | Ashish R. Tanna
Source: E3S Web of Conferences (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Photocatalytic activity of copper nanoferrite and activated carbon-copper nanoferrite composite The sol-gel auto-combustion method was used to synthesize copper nanoferrite and activated carbon-copper nanoferrite composite. The stoichiometric chemical proportions of Cu, Fe, and O were confirmed by EDX, and the porosity was checked by SEM of synthesized specimens. The spinel phase copper nanoferrite was confirmed by XRD. The octahedral and tetrahedral force constants were calculated using FTIR spectra of pristine and activated carbon–copper nanoferrite composite. The experiments of Methylene blue’s degradation in sunlight with H 2 O 2 and loading of synthesized specimens were carried out. The absorbance was checked for the degradation of MB using a UV-Visible spectrophotometer. It has been concluded that activated carbon-copper nanoferrite composite was more effective than spinel ferrites in degrading MB. Copper ; Photocatalysis ; Composite number ; Activated carbon ; Materials science ; Chemistry ; Chemical engineering ; Nuclear chemistry ; Metallurgy ; Adsorption ; Composite material ; Catalysis ; Organic chemistry Magnetic Properties and Synthesis of Ferrites ; Nanomaterials for catalytic reactions ; Pigment Synthesis and Properties
Authors: Ardillah Anggraini Sirtin | Muhammad Makky | Santosa Santosa | Dinah Cherie
Source: EKSAKTA Berkala Ilmiah Bidang MIPA (article, 2025-09-30)
Field: Chemistry — Analytical Chemistry

Non-Destructive Evaluation Quality of Oil Palm Fresh Fruit Bunch (FFB) (Elaeis guineensis Jacq.) Using Thermal Imaging in the Grading Process Determining the quality of oil palm Fresh Fruit Bunches (FFB) quickly and accurately is very important in the grading process to ensure the quality of production results and the efficiency of the post-harvest process. This study aims to evaluate the quality of oil palm FFB non-destructive using thermal image technology, focusing on two main parameters: moisture content and oil content. The oil palm FFB used was the Tenera variety. Thermal characteristic data were obtained from the RGB pseudo color thermal images and the oil palm FFB temperature. The model obtained using Artificial Neural Network (ANN) showed that the calibration model for moisture content produced a linear regression equation y = 0.9826x + 0.7159 (R² = 0.9827), and for oil content y = 0.9962x + 0.0289 (R² = 0.9973). At the validation stage, the moisture content prediction model gave y = 0.9056x + 10.721 (R² = 0.8908), and oil content y = 0.7683x + 1.6494 (R² = 0.8567). These results indicated that thermal imaging technology has great potential as an efficient and accurate non-destructive method in evaluating the quality of oil palm FFB, especially in supporting a more objective and sustainable grading system. Tenera ; Water content ; Palm oil ; Grading (engineering) ; Elaeis guineensis ; Moisture ; RGB color model Spectroscopy and Chemometric Analyses ; Oil Palm Production and Sustainability ; Date Palm Research Studies
Authors: Balázs Pál | László Dobos
Source: ArXiv.org (preprint, 2025-04-03)
Field: Chemistry — Analytical Chemistry

Denoising medium resolution stellar spectra with U-Net convolutional neural networks We investigated the use of a U-Net convolutional neural network for denoising simulated medium-resolution spectroscopic observations of stars. Simulated spectra were generated under realistic observational conditions resembling the Subaru Prime Focus Spectrograph (PFS). We found that our U-Net model effectively captured spectral features, achieving an average relative error of around $1\%$ across a broad range of stellar parameters, despite a limited training set of only $1000$ observations and a relatively short training period. Although U-Net did not reach the performance previously demonstrated by fully-connected denoising autoencoders (DAEs) consisting of dense layers and trained extensively on larger datasets, it outperformed dense networks trained under similarly constrained conditions. These results indicate that the U-Net architecture offers rapid, robust feature learning and may be particularly advantageous in scenarios involving initial denoising, subsequently refined by more accurate, but otherwise slower deep-learning models. Convolutional neural network ; Net (polyhedron) ; Resolution (logic) ; Spectral line ; Noise reduction ; Artificial neural network ; Astrophysics ; Computer science ; Pattern recognition (psychology) ; Artificial intelligence ; Physics ; Mathematics ; Astronomy Spectroscopy and Chemometric Analyses ; Blind Source Separation Techniques ; Astronomical Observations and Instrumentation
Authors: Duncan A. Greeley | H.T. Vo | Rodney J. McCabe | Matthew M. Schneider | C.N. Tomé | Laurent Capolungo
Source: Nature Communications (article, 2025-11-05)
Field: Materials Science — Materials Chemistry

A quantitative comparison of the fingerprint of twinned microstructures through surface and three-dimensional techniques Assessing the fingerprint of a material's microstructure is key for supporting materials design. With the emergence of a wide range of 3D characterization techniques, it is critical to understand the main differences in fingerprints reconstructed from 2D and 3D datasets. To this end, we introduce a graph-based microstructure reconstruction framework that enables structural comparisons of twin domain networks in high purity Ti using 3D and 2D electron backscatter diffraction. Insights into the structure of the twin networks are facilitated by combining statistical analysis of twin crystallography with visual and graphical analysis of the novel graph abstractions of the twins. We demonstrate that compared to 3D reconstructions, conventional 2D views of twinning miss key aspects of the microstructure including the high interconnectivity of domains into networks that span the full reconstruction volume. The reduced cross-grain and in-grain twin connectivity typically observed in 2D has notable implications on our understanding of how twinning mediates the plastic response of microstructures and how twin networks evolve. It is thus clear that 3D characterization is critical for accurately inferring both twin network morphologies as well as the key unit processes facilitating network formation. Crystal twinning ; Microstructure ; Characterization (materials science) ; Macle ; Interconnectivity ; Key (lock) ; Fingerprint (computing) Machine Learning in Materials Science ; 2D Materials and Applications ; Surface Chemistry and Catalysis
Authors: Damiano Squitieri | Roberta Vitali | Cecilia Bartoleschi | Giulia Lombardini | Margherita Cacaci | Lorenzo Degli Esposti | Camilla Fusacchia | Skerxho Osmani | Luca Gavioli | Francesca Bugli | D. Valerini
Source: Advanced Materials Interfaces (article, 2025-10-02)
Field: Materials Science — Materials Chemistry

Antimicrobial Multi‐Assay Evaluation of (Al‐Doped ZnO)‐Ag and TiO <sub>2</sub> ‐Ag Nanocoatings: Impact of Direct and Indirect Mechanisms Abstract Infectious diseases caused by pathogenic bacteria, fungi, and viruses pose a global health threat, aggravated by antimicrobial resistance (AMR). This study explores the antimicrobial efficacy of two nanostructured composite coatings —aluminum‐doped zinc oxide with silver (AZO‐Ag) and titanium dioxide with silver (TiO 2 ‐Ag)— on polyester substrates, against high‐priority pathogens: susceptible and resistant Klebsiella pneumoniae and Staphylococcus aureus bacterial strains, Candida albicans clinical fungal strain, and H1N1 influenza virus. A multimodal analytical approach, encompassing SEM, live/dead fluorescence assays, CFU counts, RT‐qPCR, and immunofluorescence, supported by ROS quantification, is adopted to evaluate antimicrobial activity and contribution of indirect and direct‐contact mechanisms. Both coatings exhibit robust antimicrobial effects especially through indirect mechanisms, with TiO 2 ‐Ag generally more effective than AZO‐Ag through indirect interactions while AZO‐Ag more effective in some direct‐contact scenarios. Bacterial reduction up to ≈99% and viral inactivation of 98% are observed. Cytotoxicity assays reveal some decline in fibroblast viability, underscoring the coatings’ potential mainly for non‐clinical applications, like packaging or high‐touch surfaces. Moreover, the study emphasizes limitations in using single antimicrobial tests and necessity of combining diverse methodologies to comprehensively assess performance and mechanisms of action, finally proposing strategic guidelines for selecting appropriate antimicrobial materials and evaluation techniques tailored to specific application contexts. Antimicrobial ; Titanium dioxide ; Antibiotic resistance ; Bacteria ; Cytotoxicity ; Zinc Nanoparticles: synthesis and applications ; Quantum Dots Synthesis And Properties ; Advanced Nanomaterials in Catalysis
Authors: Petra Čubáková | Andrej Hovan | Michal Koblížek | Alastair T. Gardiner | Tomáš Polı́vka | Miroslav Kloz
Source: Physical Chemistry Chemical Physics (article, 2025-01-01)
Field: Chemistry — Spectroscopy

Vibrational signature of 1 <sup>1</sup> B+u and hot 2 <sup>1</sup> A−g excited states of carotenoids revisited by femtosecond stimulated Raman spectroscopy The significance of carotenoids in biological systems cannot be overstated. Their functionality largely arises from unique excited-state dynamics, where photon absorption promotes the molecule to the optically allowed 1<sup>1</sup>B+u state (conventionally S<sub>2</sub>), which rapidly decays to the optically forbidden 2<sup>1</sup>A-g state (S<sub>1</sub>). While the vibrational signature of the S<sub>1</sub> state is well established, that of the initial S<sub>2</sub> state has remained elusive. In this work, we identify a consistent S<sub>2</sub>-state vibrational signature across five different carotenoids and explain the challenges in isolating this signature. Resonance conditions in the near infrared region cause the S<sub>2</sub> signal to appear as a complex superposition of contributions from stimulated emission to the ground state, excited-state absorption (S<sub>2</sub> to S<sub><i>m</i></sub>), and vibrationally inverted S<sub>1</sub> signals. This results in a mix of positive and negative features that are not trivial to disentangle. After careful analysis, we isolated the genuine S<sub>2</sub> signature, characterized by a CC stretch near 1600 cm<sup>-1</sup> and a C-C stretch near 1350 cm<sup>-1</sup>. The remaining signals originate from the ground or S<sub>1</sub> states but are virtually inseparable from the FSRS signal on S<sub>2</sub>-state timescales. Our findings resolve a long-standing spectroscopic challenge and clarify the early excited-state dynamics of carotenoids. Raman spectroscopy ; Femtosecond ; Excited state ; Spectroscopy ; Photochemistry ; Signature (topology) ; Chemistry ; Excited electronic state ; Atomic physics ; Laser ; Physics ; Optics ; Quantum mechanics Molecular spectroscopy and chirality ; Spectroscopy and Quantum Chemical Studies ; Photosynthetic Processes and Mechanisms
Authors: Sture Nordholm
Source: Pure and Applied Chemistry (article, 2025-10-27)
Field: Chemistry — Physical and Theoretical Chemistry

Quantum origin of atoms and molecules – role of electron dynamics and energy degeneracy in atomic reactivity and chemical bonding Abstract A simple physical model of atomic structure and reactivity is extracted from quantum mechanics using widely known facts and relations but no expert knowledge of quantum chemistry. The Aufbau model is included and extended to account for the role of electron dynamics and energy degeneracy of the atomic ground states. The periodically variable reactivity is found to arise due to dynamical constraints on electron motion which lead to degeneracy (coincidence or near-coincidence) in the atomic energy spectrum. Verification is found in a strong correlation between energy degeneracy and reactivity with the inert gas atoms found to display least degeneracy. Chemical bonding follows as a means of relaxing atomic reactivity and reducing energy degeneracy. This can be achieved by permanent electron rearrangement among atomic centers (ionic bonding) or by oscillatory electron motion between atoms (covalent bonding). Ionic bonding is directly related to the variable stability of atomic structures, not only of neutral atoms but also of atomic ions formed by permanent electron redistribution. The most stable ions then form nondegenerate molecular structures by electrostatic interaction in neutral ionic clusters. The covalent bonding mechanism is instead fundamentally dynamical and interatomic since it depends directly on the facility (rate and spatial extent) with which electrons can move between atomic centers in a molecule. Energy degeneracy is found to imply dynamical constraint on electron motion which is reduced by covalent bonding, normally, but not always, to form a nondegenerate molecular ground state. Facilitation of interatomic electron motion, and the corresponding decrease in degeneracy of the ground and lowest energy excited states, thus become the covalent bonding mechanism. Equilibrium molecular geometries optimally balance this attraction against interatomic repulsions of electrostatic and steric (Pauli) nature which dominate at short range. The fundamental role of electron dynamics in atomic properties and bonding is reflected in a corresponding importance of not only ground state energy but the spectrum of low energy states. Degeneracy (biology) ; Ionic bonding ; Electron ; Ion ; Chemical bond ; Molecular dynamics ; Reactivity (psychology) ; Covalent bond ; Potential energy History and advancements in chemistry ; Advanced Chemical Physics Studies ; Crystallography and molecular interactions
Authors: Технический университет Аль-Фурат Аль-Аусат | Фадель А. Джумаа | Хамдия Секеб Джасим | Мохаммед Обайес Юсиф | Анас Фуад Ахмед | Иракский университет
Source: Radioelectronics Nanosystems Information Technologies (article, 2025-08-13)
Field: Materials Science — Materials Chemistry

An Efficient and Robust Framework for Denoising and classification of Power Quality Events Based on the Adaptive Wavelet and SVM Techniques Надежность и эффективность современных систем электроснабжения зависят от точной идентификации и классификации проблем с качеством электроэнергии (PQ). В этой статье представлена инновационная адаптивная система вейвлет-машинного обучения, которая сочетает в себе выбор вейвлетов на основе энтропии, извлечение статистических признаков и классификацию методом опорных векторов (SVM). В отличие от традиционных методов с фиксированным вейвлетом, наш подход улучшает частотно-временную локализацию как переходных, так и нестационарных событий PQ за счет динамического выбора наиболее подходящего вейвлета для каждого сигнала, руководствуясь критерием минимальной энтропии. Сигнал анализируется с помощью 10-уровневого дискретного вейвлет-преобразования (DWT). Такие характеристики, как энергия, стандартное отклонение и пик, извлекаются в разных масштабах. Затем SVM на базе RBF-ядра обучается с помощью этих функций для классификации девяти типичных событий PQ. Среднее время вывода составляет всего 2.31 мс на сигнал, и система остается надежной в условиях шума (SNR &gt; 20 дБ). Экспериментальные данные показывают, что эта система обеспечивает среднюю точность классификации в 99.56%. Поскольку этот метод превосходит некоторые существующие модели глубокого обучения и фиксированных вейвлет-сигналов с точки зрения точности, интерпретируемости и вычислительной эффективности, он подходит для мониторинга PQ в режиме реального времени. Support vector machine ; Wavelet ; Pattern recognition (psychology) ; Computer science ; Power quality ; Artificial intelligence ; Noise reduction ; Quality (philosophy) ; Machine learning ; Data mining ; Power (physics) Material Properties and Failure Mechanisms ; Engineering Diagnostics and Reliability ; Power Quality and Harmonics