jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mikhail Frolov | Trofim A. Lozhkarev | Elmira A. Vasilieva | Л. А. Васильева | Almaz A. Zagidullin | Lucia Ya. Zakharova | Galim Alimzhanovich Kungurov | Natalia Trachtmann | Shamil Z. Validov
Source: Fermentation (article, 2026-02-01)
Field: Materials Science — Materials Chemistry

Novel Silicone–Polyol Antifoam Emulsions: Impact on Foam Control and Physiology of Diverse Microbial Cultures The selection of an optimal antifoam is critical for efficient fermentation, as industrial agents often have detrimental side effects like growth inhibition, while some can enhance productivity. We studied the efficacy of novel silicone–polyol antifoam emulsions for use in fermentation as defoamers. Except for agent 3L10, all antifoams tested did not show inhibition on six bacterial and one fungal culture. Interestingly, agent 3L10 strongly inhibited Gram-positive bacteria (especially Corynebacterium glutamicum) but not Gram-negative strains. A comprehensive evaluation protocol—combining chemical design, cytotoxicity screening across diverse microorganisms, the determination of minimum effective concentrations (MECs), and validation in model bioreactor fermentations—was established. Through this process, 6T80 was identified as a promising antifoam agent for fermentation. It exhibited a low MEC, high emulsion stability, and no cytotoxicity and did not impair growth or recombinant protein production in Bacillus subtilis or Pseudomonas putida fermentations. This study concludes that agent 6T80 is suitable for further application in processes involving Gram-negative and certain Gram-positive hosts. The developed methodology enables the targeted selection of highly efficient and biocompatible antifoams for specific biotechnological processes. Defoamer ; Bacillus subtilis ; Cytotoxicity ; Pseudomonas putida ; Bioreactor ; Fermentation ; Bacteria ; Corynebacterium glutamicum Pickering emulsions and particle stabilization ; Biopolymer Synthesis and Applications ; Fermentation and Sensory Analysis
Authors: Stephen C. Peterangelo
Source: ChemRxiv (article, 2026-03-30)
Field: Chemistry — Spectroscopy

Modeling Limits of Detection in Headspace GC/MS The limits of detection (LOD) for headspace Gas Chromatography-Mass Spectrometry (GC-MS) of a diverse series of compounds were accurately predicted using a simple linear regression model incorporating Henry’s law constants and a polarity descriptor. LODs were predicted with an R2 of 0.9154 and a standard error of the estimate (SEE) of 1184 nmol/L (approximately 17 μg/L) over a range of LODs from 2 μg/L to 585 μg/L using Henry’s law constants and dipole moment. Detection limit ; Linear regression ; Range (aeronautics) ; Limit (mathematics) ; Analytical Chemistry (journal) ; Mass spectrometry ; Series (stratigraphy) ; Polarity (international relations) Analytical Chemistry and Chromatography ; Pesticide Residue Analysis and Safety ; Analytical Methods in Pharmaceuticals
Authors: Rawan Fitaihi | Alanoud Altalal | Rihaf Alfaraj | Fai Alkathiri | Riyad F. Alzhrani | Shumukh AlDawsari | Shouq Alorayyidh | Meshal K. Alnefaie | Nojoud Al Fayez | Njoud Altuwaijri
Source: Biomedicines (article, 2026-03-20)
Field: Materials Science — Biomaterials

Electrospun PVA Nanofibers Co-Loaded with Atorvastatin and Zinc Oxide for Antibacterial and In Vitro Wound Healing Applications <b>Background:</b> The global rise in antimicrobial resistance (AMR) has created an urgent need for innovative antibacterial strategies and localized delivery systems. This study aimed to develop and characterize electrospun poly (vinyl alcohol) (PVA) nanofibers co-loaded with atorvastatin (ATR) and zinc oxide (ZnO) nanoparticles for use as a multifunctional topical platform for wound healing and infection control. <b>Methods:</b> ZnO nanoparticles were prepared via ball milling and characterized for size and zeta potential. Four PVA-based nanofiber formulations were fabricated using electrospinning: blank (F1), ZnO-loaded (F2), ATR-loaded (F3), and ATR/ZnO co-loaded (F4). The nanofibers were evaluated for morphology, thermal properties, crystallinity, and drug release. Antibacterial efficacy was tested against <i>S. aureus</i>, <i>S. epidermidis</i>, MRSA, and <i>P. aeruginosa</i> using broth microdilution and checkerboard assays. Biocompatibility and wound healing potential were assessed via MTT and fibroblast scratch assays on human foreskin fibroblasts (hFFs). <b>Results:</b> SEM imaging confirmed the production of uniform, bead-free nanofibers. ATR and ZnO nanoparticles were successfully incorporated in the nanofiber. The co-loaded formulation (F4) demonstrated a sustained release profile, releasing approximately 78.7% of ATR over 24 h. While all treatments showed limited activity against <i>P. aeruginosa</i>, the ATR/ZnO co-loaded nanofibers exhibited significantly enhanced antibacterial activity against Gram-positive strains, achieving the lowest MIC values (1.5-2.0 mg/mL). Synergy analysis confirmed an enhanced effect with ATR and ZnO against MRSA. Furthermore, F4 achieved the highest wound closure rate of 92.41% in 24 h while maintaining acceptable cytocompatibility. <b>Conclusions:</b> The integration of ATR and ZnO into PVA nanofibers provides an enhanced antibacterial effect consistent with the synergistic potential observed between free agents targeting Gram-positive wound pathogens. The platform's ability to simultaneously inhibit bacterial growth and promote rapid fibroblast migration positions it as a promising localized therapeutic for managing infected wounds. Nanofiber ; Wound healing ; Biocompatibility ; Antibacterial activity ; Electrospinning ; Nanoparticle ; Broth microdilution ; Zeta potential ; Antimicrobial Electrospun Nanofibers in Biomedical Applications ; Wound Healing and Treatments ; Silk-based biomaterials and applications
Authors: Grzegorz Janowski | Marta Wójcik | Irena Krešić | Wiesław Frącz | Łukasz Bąk | Ivan Gajdoš | Emil Spišák
Source: Materials (article, 2026-01-08)
Field: Materials Science — Biomaterials

The Influence of Sunflower Seed Hull Content on the Mechanical, Thermal, and Functional Properties of PHBV-Based Biocomposites This paper presents the potential use of sunflower seed hulls (SSH) as a sustainable filler for poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) biocomposites. Ground SSH were incorporated into the PHBV matrix at loadings of 15, 30, and 45 wt% via extrusion and injection molding. The Fourier Transform Infrared Spectroscopy (FTIR) analysis indicated the presence of possible interactions between the filler and the matrix. Mechanical testing revealed a significant increase in stiffness, with the tensile modulus increasing from 2.6 GPa for pure PHBV to approximately 4.5 GPa for the composite containing 45 wt% SSH. However, the tensile strength decreased by approximately 10-40%, while elongation at break dropped to 1.0-1.5%, depending on the SSH dosage, respectively. The thermal analysis indicated that high filler contents suppress crystallization during cooling under laboratory conditions in Differential Scanning Calorimetry (DSC) analysis due to the confinement effect. The key practical advantage is the exceptional improvement in dimensional stability with a processing shrinkage reduction of approximately 80% in the thickness direction. Although water absorption increased with filler loading, biocomposites containing 15-30 wt% SSH exhibited the optimal balance of high stiffness, hardness, and dimensional accuracy. These properties make the developed material a promising option for the production of precise technical molded parts. Ultimate tensile strength ; Differential scanning calorimetry ; Filler (materials) ; Fourier transform infrared spectroscopy ; Extrusion ; Composite number ; Absorption of water ; Thermal stability ; Sunflower biodegradable polymer synthesis and properties ; Natural Fiber Reinforced Composites ; Polymer composites and self-healing
Authors: Ian Carlos Bispo Carvalho | Luciellen da Costa Ferreira | Ana Régia de M. Neves | Alice Maria Silva Carvalho | Henrique Póvoa Rodrigues Lima | Maurício Rossato
Source: Frontiers in Plant Science (article, 2026-01-26)
Field: Chemistry — Analytical Chemistry

A hyperspectral imaging and machine learning approach for rapid and non-invasive diagnosis of cassava bacterial blight This study explores the use of hyperspectral imaging (HSI) combined with machine learning to detect physiological alterations in cassava leaves caused by <i>Xanthomonas phaseoli</i> pv. <i>manihotis</i> (Xpm), a bacterial plant disease that causes significant yield losses worldwide. Therefore, the use of hyperspectral images associated with machine learning can provide information rapidly and accurately, aiming to support decision-making. HSI captures spectral data that reflects biochemical changes in infected plant tissues. An image set of cassava healthy and symptomatic leaves (402 and 450, respectively) were imaged using a hyperspectral camera across wavelengths from 400 to 1000 nm, with image calibration and spectral normalization to improve data quality. Spectral parameters, such as mean reflectance and spectral differences (healthy vs. infected), were analyzed. Six machine learning models were tested for classification: Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), and Multi-Layer Perceptron (MLP). SVM performed best, achieving the highest accuracy (91.41%), followed by MLP (87.89%), XGBoost (79.69%), and RF (77.34%). DT and KNN had the lowest accuracy (71.88% and 70.31%, respectively). The results suggest that HSI, particularly when combined with SVM, offers a rapid and accurate method for diagnosing cassava bacterial blight, with potential for large-scale field applications. Hyperspectral imaging ; Support vector machine ; Random forest ; Boosting (machine learning) ; Multilayer perceptron ; Decision tree ; Pattern recognition (psychology) ; Multispectral image ; Normalization (sociology) Spectroscopy and Chemometric Analyses ; Plant Disease Management Techniques ; Smart Agriculture and AI
Authors: Daniil Nemirov | K. L. Ovchinnikov
Source: From Chemistry Towards Technology Step-By-Step (article, 2026-03-24)
Field: Materials Science — Materials Chemistry

Sintez 2,4,7,9-tetrafenil-4,4a,9,9a-tetragidrotiopirano[2,3-g]tiokhromen-5,10(5aH,10aH)-diona i analiz ego biologicheskoi aktivnosti -4,4a,9,9a-[2,3-g]-5,10(5aH,10aH)-. GABA B(1) , . PASS-Online . : .., .. 2,4,7,9--4,4a,9,9a-[2,3g]-5,10(5aH,10aH)- // .2026.. 7, . 1. . 43-53.URL: https://chemintech. Perspective (graphical) ; Affect (linguistics) ; Work (physics) ; Personality Photochromic and Fluorescence Chemistry ; Synthesis and pharmacology of benzodiazepine derivatives ; Cancer therapeutics and mechanisms
Authors: Nikita V. Valuуsky | Umida Ibragimova | Alexander Borisov | Elena N. Subcheva | Violetta R Raiberg | Denis K. Deryagin | I. S. Ukhorenko | Ksenia I. Zhukova | Svetlana Sorokina | Alexander S. Tarasov | Nikolai N. Lobanov | Roman A. Litvinov
Source: Journal of Volgograd State Medical University (article, 2026-04-07)
Field: Materials Science — Polymers and Plastics

Synthesis, characterization and biological properties of NiO nanoparticles Introduction: Nickel oxide nanoparticles (NiO-NPs) are regarded as promising materials; however, the expansion of their applications requires detailed toxicological assessment in relevant experimental systems. In a range of models, nanostructured metal oxides have been shown to induce oxidative and inflammatory responses which, under certain conditions, may be involved in mechanisms of fibrotic remodelling. Macrophages act as early sensors of such exposures; therefore, analysing their functional response enables the characterisation of potential risks associated with NiO-NP exposure and provides a rationale for subsequent stages of safety evaluation. Research methodology: In this study, NiO-NPs were produced by a sol–gel method followed by thermal annealing at different temperatures. For further biological experiments, we selected the sample annealed at 450 °C, which exhibited the most reproducible nanoscale characteristics and was therefore considered optimal. Morphology and size parameters were assessed by electron microscopy, while phase composition and crystallite size were determined by X-ray diffraction, providing a comprehensive physicochemical characterisation of the tested material. Primary murine peritoneal macrophages were used as target cells. Cytotoxicity was evaluated using the MTT assay and morphocytological analysis, and the intensity of the cellular inflammatory response was assessed by measuring nitrite production with the Griess reagent. Results: The optimal NiO-NP sample was characterised by a predominantly nanoscale fraction and structural homogeneity, which supported its use in a cellular model for the assessment of biological effects. Exposure to NiO-NPs caused concentration-dependent impairment of macrophage viability. Marked cellular alterations were observed at high nanoparticle concentrations, whereas lower concentrations induced minimal signs of cellular damage or produced no detectable injury. In parallel, increased nitrite production was recorded, indicating activation of inflammatory mechanisms. Conclusion: Collectively, these data suggest that NiO-NPs may act as inducers of early cellular responses which, under unfavourable exposure conditions, could contribute to the development of a profibrotic tissue phenotype. Cytotoxicity ; Nanoparticle ; Nanotoxicology ; Nanoscopic scale ; Nitrite ; Crystallite ; Biocompatibility ; Nickel oxide ; Oxide Transition Metal Oxide Nanomaterials ; Nanoparticles: synthesis and applications ; Magnesium Oxide Properties and Applications
Authors: Congrui Tan | Yu Gao | Marcus Buggert | Yuye Zhou | Renato Zenobi
Source: ACS Central Science (article, 2026-01-27)
Field: Chemistry — Spectroscopy

Integrating Functional Response and Target Binding for Mechanism-Centered Drug Screening by High-Mass MALDI-MS Early stage drug discovery is limited by the disjunction of function and binding assays, creating an information gap that leads to the high failure rate in hit advancement. This limitation is particularly pronounced for protein-protein interactions, whose large and shallow interfaces make it difficult to distinguish hits mechanistically. To address this, we developed a cross-linking matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) platform that integrates biochemical functional response and target binding in a single assay, thereby generating a multidimensional pharmacological profile. Using the SARS-CoV-2 RBD-ACE2 interaction and a set of 17 drug candidates for a proof-of-concept study, the platform revealed a clear difference between two inhibitors that appeared indistinguishable in conventional functional assays: one showed stronger affinity and preferential ACE2 binding, while the other showed weaker and less specific binding. These mechanistic differences were consistent with the results of a cellular antiviral assay, in which only the high-affinity inhibitor improved cell viability. This work presents a mechanism-centered, rapid screening strategy that provides early multiparameter insight, enables rational selection of high-quality leads for challenging drug targets, and is compatible with high-throughput formats. Drug discovery ; Drug ; Drug target ; Function (biology) ; Selection (genetic algorithm) ; Plasma protein binding ; Virtual screening ; High-throughput screening Mass Spectrometry Techniques and Applications ; Computational Drug Discovery Methods ; Advanced Proteomics Techniques and Applications
Authors: Toshiyuki Kowada | Toshizo Sato | Kento Kasahara | Satoshi Hamaguchi | Konoka Baba | Takato Mashita | Muhammad Wildan Saifudin | Hayashi Yamamoto | Nobuyuki Matubayasi | Shin Mizukami
Source: ChemRxiv (article, 2026-02-25)
Field: Materials Science — Materials Chemistry

Azopyrazole-based Photochromic Dimerizer Enables Optical Control of Cellular Signaling with Minimal Basal Activation Photochromic chemically induced dimerization (CID) system enables reversible optical control of protein–protein interactions in living cells, offering a powerful alternative to conventional optogenetic tools. We previously developed a photochromic CID system using an Escherischia coli dihydrofolate reductase (eDHFR)/HaloTag pair and an azobenzene-based photochromic dimerizer, pcDH, which achieved rapid and reversible protein translocation. However, undesirable background binding resulting from the high affinity of the E-isomer for eDHFR limited its precision. Here, we report an improved system employing an azopyrazole-based dimerizer, pcDH2b, and an engineered eDHFR mutant to reduce background binding. Molecular docking identified F31 as a key residue, prompting cell-based screening of F31 mutants. The eDHFR(F31I) showed minimal background binding while preserving efficient photoreversible dimerization. Fluorescence polarization assays confirmed reduced binding affinity in both dark and violet light-induced photostationary states. The optimized eDHFR(F31I)/Halo–pcDH2b pair exhibited rapid association and dissociation kinetics and enabled precise, lowbackground optical regulation of mitophagy in HeLa cells. Molecular dynamics simulations provided insights into the energetic and structural basis of E/Z selectivity. These results demonstrate that tuning ligand–protein affinity through protein mutation effectively minimizes background binding while maintaining fast photo-responses, providing a practical platform for reversible optical control of cellular signaling with minimal basal activation. Photochromism ; Mutant ; Optogenetics ; Fluorescence ; Kinetics ; Fluorescent protein ; Plasma protein binding ; Dihydrofolate reductase ; Intein Photochromic and Fluorescence Chemistry ; Liquid Crystal Research Advancements ; Light effects on plants
Authors: Jūratė Jolanta Petronienė | Rimantas Stonkus | Andrius Dzedzickis | Vytautas Bučinskas
Source: Materials (article, 2026-03-27)
Field: Materials Science — Polymers and Plastics

Rectification of Material Model for Fibrous Materials in Compressive Mode Fibrous natural-origin materials are not only attractive as raw materials in various applications but are also often produced as waste products in some manufacturing processes. Despite their comprehensive implementation as thermal or noise isolation materials, their behavior under mechanical load is not yet fully understood, and there are no assignments of existing universal material models for the category of fibrous materials. The conducted experimental research provides a methodology with which to evaluate the structural behavior of fibrous materials under applied compression force and classify these materials according to their mechanical properties based on a certain material model. As a result of this research, we observed that the mechanical properties of the fibrous material during compression mode are determined by the fibrous structure, with insignificant influence from the physical nature of the material itself. This investigation provides an analysis of the application of a hyperelastic incompressible isotropic model to fibrous material of different origins. Hyperelastic material models of the Money–Rivlin, Ogden, Yeoh, and polynomial type were implemented. The fitting quality of the Yeoh third-order model obtained the best fitting results for animal wool and mineral wool. Cotton wool showed the best fitting results with the polynomial fifth-order model. The outcome of this research will help create finite element models for structural analysis, efficiently modelling structural responses to vibration or noise. For most animal and mineral wool samples, the best agreement with the experimental compression curves was obtained using the Yeoh third-order hyperelastic model, with coefficients of determination R2 between 0.979 and 0.996, while fifth-order polynomial fits locally reached R2 up to 0.9999 for aged cotton wool. Hyperelastic material ; Material properties ; Isotropy ; Compression (physics) ; Polynomial ; Finite element method ; Elasticity (physics) ; Ogden Textile materials and evaluations ; Elasticity and Material Modeling ; Cellular and Composite Structures
Authors: Donghyeong Lee | Seokwan Roh | Jaewoo Jeong | Kuk‐Jin Yoon | Jungchul Lee | Youngsuk Nam
Source: Advanced Science (article, 2026-01-07)
Field: Materials Science — Surfaces, Coatings and Films

Analysis of Multiscale Condensation Phenomena Using a Zero‐Shot Computer Vision Framework Understanding and controlling condensation is central to diverse energy and water systems, yet quantifying its inherently multiscale droplet dynamics has remained elusive. Here, a label-free computer vision framework that leverages the Segment Anything Model (SAM) for zero-shot segmentation is demonstrated, achieving high accuracy by systematically detecting more than one million droplets without any annotated datasets or retraining. The framework extracted statistical features such as droplet radius, number of coalescences, mean coalescing diameter, growth rate, and condensation mass from microscale to macroscale observations. This enabled direct visualization of dynamic condensation cycle including nucleation, growth, coalescence, sweeping, and renucleation, while also revealing the role of surface properties, where contact angle hysteresis governed droplet departure size, morphology, and population statistics in agreement with classical models. To extend beyond characterization, a machine learning model was trained with Pearson correlation-selected parameters to predict condensation rates under diverse environmental conditions, achieving a mean absolute percentage error of 7.8%. These frameworks highlight the potential of artificial intelligence to understand dynamic phase-change mechanisms, and to guide the design of advanced surfaces and systems for thermal management, desalination, and water harvesting. Microscale chemistry ; Condensation ; Segmentation ; Hysteresis ; Population ; Visualization ; Thermal Surface Modification and Superhydrophobicity ; nanoparticles nucleation surface interactions ; Fluid Dynamics and Heat Transfer