jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Felix J. Hartmann
Source: European Journal of Immunology (article, 2025-11-01)
Field: Chemistry — Spectroscopy

Spatial Immunometabolism: Integrating Technologies to Decode Cellular Metabolism in Tissues The metabolic programs of immune cells influence their activation, differentiation, and effector functions. While much of immunometabolism has focused on cell-intrinsic regulation, it is now clear that metabolic activity is profoundly influenced by the surrounding tissue environment. In tumors and other inflammatory settings, immune cells are shaped by nutrient gradients, hypoxia, and immunoregulatory metabolites, factors that are spatially heterogeneous and often poorly captured by traditional methods. This review highlights recent technological advances that enable spatially resolved analysis of immune metabolism, with an emphasis on multimodal integration and cancer as a model system. Mass spectrometry imaging (MALDI, DESI), high-resolution platforms like SIMS, and vibrational imaging approaches such as Raman microscopy enable direct visualization of metabolites in tissue. Transcriptomic and proteomic data can be used to infer metabolic states, and computational models are being developed to integrate these diverse data layers. Together, these technologies are transforming the study of immunometabolism from dissociated cells to the intact tissue context. Key challenges remain in resolution, annotation, and data integration, but spatial immunometabolism holds particular promise for illuminating mechanisms of immune regulation in health and disease. Immune system ; Effector ; Cellular metabolism ; Metabolomics ; Transcriptome ; Systems biology ; Human health Mass Spectrometry Techniques and Applications ; Spectroscopy Techniques in Biomedical and Chemical Research ; Single-cell and spatial transcriptomics
Authors: Bestem Esi | Kaan Polat | Öner Sarp
Source: Tekstilna industrija (article, 2025-01-01)
Field: Materials Science — Polymers and Plastics

Sustainable polypropylene filament yarn production for upholstery fabrics This study focuses on developing sustainable and cost-effective yarns for use in upholstery fabrics by incorporating recycled polypropylene. Polypropylene is widely used in textiles due to its low cost, easy procesability and high strength. The research aimed to produce durable weft yarns with granules derived from polypropylene textile waste. Recycled and virgin polypropylene granules were used in the yarns with different blend ratios. The effects of blend ratio and yarn fineness on yarn breaking strength were also investigated statistically. Using similar parameters, it was found that up to 20% recycled polypropylene could be used without significantly affecting the strength of the yarn. While determining the yarn fineness, the fineness values that could be used in upholstery fabric production were considered and were determined to be usable especially in weft yarn. This study contributes to the home textile industry by supporting more environmentally friendly and economically sustainable production practices. Polypropylene ; Yarn ; Fineness ; Textile ; Breaking strength ; Environmentally friendly Textile materials and evaluations ; Crafts, Textile, and Design ; Additive Manufacturing and 3D Printing Technologies
Authors: Chongchong Yan | Haonan Zhao | Dequan Zhu | Yuqing Yang | Rongjun Xing | Qixing Tang | Juan Liao
Source: INMATEH Agricultural Engineering (article, 2025-08-21)
Field: Chemistry — Analytical Chemistry

DETECTION OF EARLY BRUISING IN ‘HUANGGUAN’ PEAR BASED ON MCCDeepLabV3+ MODEL Due to their delicate and thin skin, ‘huangguan’ pears are very vulnerable to pressure and impact during picking, packing and transportation, which can cause bruising. Early detection of bruises allows for timely identification of affected fruits to reduce potential food safety risks. However, early bruises in ‘huangguan’ pears, particularly those that occur within the 30 minutes, often show no visible differences in external features compared to healthy tissue, making conventional techniques such as manual and machine vision sorting ineffective. Accordingly, a near-infrared (NIR) camera imaging technique combined with deep learning segmentation algorithm for early bruise ‘huangguan’ pears detection is proposed in this study. Firstly, a near-infrared camera imaging system is applied to collect early bruise images of ‘huangguan’ pears, and then a lightweight segmentation model based on the DeepLabV3+ architecture, referred to as MCC-DeepLabV3+ is presented. In the MCC-DeepLabV3+ model, MobileNetV2 is used as the backbone network, reducing the parameter size and enhancing deployment efficiency. Additionally, the coordinate attention (CA) mechanism is integrated into the shallow feature extraction and ASPP modules to improve the extraction of positional information across various features, minimizing the discrepancy between segmented areas and the actual bruised regions. Furthermore, a cascade feature fusion (CFF) strategy is incorporated into the encoder to reduce segmentation edge discontinuities and ensure effective multi-level semantic fusion, improving segmentation accuracy. The experimental results show that the proposed model has achieved a mIoU of 95.68%, and mPrecision of 97.58% on the self-built dataset of early bruising in ‘huangguan’ pears. Compared to benchmark models such as U-Net, SegNet, PSPNet and HRNet, the proposed model demonstrates superior segmentation performance, offering promising support for the development of nondestructive detection techniques for agricultural product quality. PEAR ; Computer science ; Materials science Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Plant Pathogens and Fungal Diseases
Authors: Rama Krishna Ubbani | Prof. Seema Tomar
Source: South Eastern European Journal of Public Health (article, 2025-01-30)
Field: Materials Science — Materials Chemistry

GREEN CHEMISTRY APPROACH FOR IMPROVEMENT IN PHYSICOCHEMICAL PROPERTIES OF GLIPIZIDE THROUGH COCRYSTAL FORMATION This study aims to improve the physicochemical properties of the poorly water-soluble antidiabetic drug, Glipizide, by forming cocrystals and eutectic mixtures using a green chemistry approach. Enhancing solubility, dissolution rate, and bioavailability is essential for optimizing therapeutic effectiveness. Environmentally sustainable methods, such as solvent-free grinding and mechanochemistry, were utilized to ensure eco-friendliness. Solid-state characterization techniques, including DSC, PXRD, FTIR, and SEM, were employed to confirm the successful formation of cocrystals and eutectic mixtures. This eco-friendly and efficient strategy provides a promising solution to address the solubility challenges of Glipizide. Cocrystal ; Glipizide ; Chemistry ; Chemical engineering ; Organic chemistry ; Engineering ; Medicine ; Diabetes mellitus ; Hydrogen bond Crystallization and Solubility Studies ; Chemical Thermodynamics and Molecular Structure ; Inorganic and Organometallic Chemistry
Authors: Dawei Zhou | A.K. Gupta | Vincent Ho | Kedong Bi | Melisa M. Gianetti | Astrid S. de Wijn | Peter Schall
Source: Friction (article, 2025-04-28)
Field: Chemistry — Organic Chemistry

Atomic alignment and friction behavior of dense fullerene packings revealed by molecular dynamics simulations Recent experimental and simulation work explores the possibility of scaling up the microscopic phenomenon of superlubricity to the macroscopic scale. Here, we investigate the lubrication behavior of dense packings of C<sub>60</sub> fullerenes sandwiched in between two rigid fullerene slabs using atomistic simulations. Using a range of atomic potentials common for carbon-based nanomaterials, we investigate the fullerenes’ atomic stacking and resulting friction properties of the packing as a function of boundary roughness and applied normal load. We find superlubric behavior for flat boundaries due to boundary slip, but finite friction for rough boundaries, due to bulk shear and the related energy dissipation in the bulk. The atomistic simulations reveal a preferred AA-type atomic stacking, which changes to TA-type stacking as the applied load is increased. This is accompanied by a loss of rolling motion of the particles in the highly condensed sheared packing. These results provide atomistic insight into the collective interactions of superlubric particles that exhibit many rotational and translational degrees of freedom in dense packings, and reveal their emergent frictional properties for friction-reduction applications. Molecular dynamics ; Fullerene ; Chemical physics ; Materials science ; Dynamics (music) ; Nanotechnology ; Crystallography ; Condensed matter physics ; Computational chemistry ; Physics ; Chemistry ; Quantum mechanics Fullerene Chemistry and Applications ; Boron and Carbon Nanomaterials Research ; Advanced Physical and Chemical Molecular Interactions
Authors: Feng Zhao | Qichang Guo | Wei Li | Xiaobin Zhao | Meihong Deng | Huayao Huang | Zicheng Zheng | Lin Hua | Wei Guo
Source: Polymer Engineering and Science (article, 2025-06-27)
Field: Materials Science — Polymers and Plastics

Asymmetric Cooling Dynamics in Foamed <scp>PP</scp> : Role of Metal/Polymer Films on Formability ABSTRACT Microcellular injection molding (MIM) is hindered by surface quality issues caused by bubble defects, which severely limit its industrial application. This study innovatively combines in‐mold decoration (IMD) with MIM, using copper foil (Cu) and polyethyleneterephthalate films to regulate the interface heat transfer and cell evolution. By integrating numerical simulations with experiments, the study reveals the asymmetric regulation mechanism of heat transfer paths by the film materials and explores the impact of the film material on the surface quality, cell structure, and mechanical properties of the molded parts. The experimental results indicate that IMD effectively improves the surface quality of microcellular molded parts, enhances surface hydrophilicity, and promotes surface crystallization. The copper foil accelerates cooling on the film side, reducing cell size and increasing cell density, while the core layer's cell structure shifts toward the nonfilm side. The PET film, with lower thermal conductivity, causes an increase in cell size, and the core layer's cell structure shifts toward the film side. Molded parts incorporating IMD exhibit markedly superior mechanical performance, with tensile, flexural, and impact strengths increased by 31.7%, 41.8%, and 32.8%, respectively, compared with nonfilm counterparts. This study provides scientific evidence and practical guidance for further optimizing the MIM process and part performance, contributing to the advancement of MIM technology for high‐strength, high‐appearance, and low‐density materials. Formability ; Materials science ; Polymer ; Metal ; Composite material ; Metallurgy Polymer Foaming and Composites ; Rheology and Fluid Dynamics Studies ; Epoxy Resin Curing Processes
Authors: Lisa Beran | Tobias Valentin Knapp | Albenc Nexha | Makara Lay | Bart‐Jan Niebuur | Tobias Kraus
Source: Advanced Engineering Materials (article, 2025-01-13)
Field: Materials Science — Materials Chemistry

Combining Structured Data with Domain Knowledge in Battery Materials Research: The Case of Conductive Networks Batteries contain combinations of materials that undergo electrochemical reactions to convert chemical into electrical energy. Battery research relies on experience and know‐how. Important materials and processing data can get overlooked, remain undocumented, or even lost. To bridge the gap between fundamental materials research and battery process engineering, it is essential to generate, analyze, and, most importantly, link intermediate knowledge for future use. Here, it is shown how to combine domain knowledge and a data‐driven approach to understanding material–property relationships in the case of conductivity networks of carbon black. The Battery Production and Characterisation Ontology (BPCO) is employed to identify hypotheses that connect battery processing to material domain knowledge. The material's interactions between carbon black, polyvinylidene flouride, and solvents in the BPCO are characterized. These materials combine to form the classical microstructure in battery electrodes for the electrical conductivity. It is demonstrated how new links to the BPCO, verified via materials‐processing relationships, and the interim results are identified as intermediate data. Battery (electricity) ; Materials science ; Carbon black ; Process (computing) ; Domain (mathematical analysis) ; Computer science ; Ontology ; Nanotechnology ; Power (physics) Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Electrochemical Analysis and Applications
Authors: Anthony M. Ciancone | Haitao Wu | Katerina Atallah-Yunes | Kitaik Lee | Chris Sibley | Jesse A. Spivey | Rolf E. Swenson | John S. Schneekloth | Francis J. O’Reilly
Source: Molecular & Cellular Proteomics (article, 2025-10-22)
Field: Chemistry — Spectroscopy

Expanding the Crosslinking Mass Spectrometry Toolbox With Vinyl Sulfone Crosslinkers Crosslinking mass spectrometry (MS) is a powerful approach for probing protein structures. However, most widely used crosslinkers rely on N-hydroxysuccinimide (NHS) esters, restricting reactivity primarily to lysine residues and protein N-termini, and rendering them incompatible with many amine-containing buffers (e.g., Tris) and key biochemical cofactors (e.g., ATP). To address these limitations, we introduce two novel vinyl-sulfone-based crosslinkers. Alkyne-BVSC is an enrichable, homobifunctional crosslinker featuring an acid-cleavable alkyne handle for downstream peptide enrichment. VSD is a heterobifunctional crosslinker combining a vinyl sulfone with a diazirine moiety for UV-activated photo-crosslinking. Both reagents are synthetically accessible from inexpensive precursors and retain reactivity in amine-rich biochemical environments. We show that vinyl sulfones react with cysteine, histidine, and lysine residues, thereby expanding crosslinkable residues beyond those accessible to NHS-esters. Moreover, we develop a stub-based post-search filtering strategy that leverages the MS-cleavable nature of vinyl sulfone linkages to improve crosslink identification sensitivity. Together, these advances establish vinyl-sulfone-based crosslinkers as versatile and complementary tools for structural proteomics. Moiety ; Sulfone ; Mass spectrometry ; Reactivity (psychology) ; Diazirine ; Alkyne Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Xu Zhang | Jihong Yang | Ruijie Zhao | Zhuolin Qin | Zhuojun Xie
Source: Inventions (article, 2025-09-24)
Field: Chemistry — Analytical Chemistry

An IoT-Enabled System for Monitoring and Predicting Physicochemical Parameters in Rosé Wine Storage Process The evolution of the winemaking industry towards intelligent and digitalized systems is crucial for precision winemaking and ensuring product safety. In this context, the Internet of Things (IoT) provides a key strategy for real-time monitoring and data management throughout the winemaking process. However, comprehensive multi-parameter IoT-based monitoring and time-series prediction of physicochemical parameters during storage are currently lacking, limiting the ability to assess storage conditions and provide early warning of quality deterioration. To address these gaps, a multi-parameter IoT monitoring system was designed and developed to track conductivity, dissolved oxygen, and temperature in real time. Data were transmitted via a 4th-generation (4G) mobile communication module to the TLINK cloud platform for storage and visualization. An 80-day storage experiment confirmed the system’s reliability for long-term monitoring, and analysis of parameter trends demonstrated its effectiveness in assessing storage conditions and wine quality evolution. Furthermore, Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Temporal Convolutional Network (TCN) models, and Autoregressive Integrated Moving Average (ARIMA) were implemented to predict physicochemical parameter trends. The TCN model achieved the highest predictive performance, with coefficients of determination (R2) of 0.955, 0.968, and 0.971 for conductivity, dissolved oxygen, and temperature, respectively, while LSTM and GRU showed comparable results. These results demonstrate that integrating IoT-based multi-parameter monitoring with deep learning time-series prediction enables real-time detection of abnormal storage and quality deterioration, providing a novel and practical framework for early warning throughout the wine storage process. Winemaking ; Wine ; Reliability (semiconductor) ; Process (computing) ; Limiting ; Computer data storage ; Partial least squares regression ; Quality (philosophy) ; Autoregressive integrated moving average Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Fermentation and Sensory Analysis
Authors: Doni Bowo Nugroho | Nada Nadzira Ayasha Kamal | Jenni Bunga Enjelita Sidabalok | Rosita Wati | Nova Resfita | Muhammad Wildan Gifari
Source: Journal of Energy Material and Instrumentation Technology (article, 2025-11-30)
Field: Materials Science — Biomaterials

Morphological Study of Electrospun Polyvinylpyrrolidone Fibers at High Concentration Using Water and Ethanol Solvents In this study, polyvinylpyrrolidone (PVP) (Mw ~40,000 g/mol) fibers were fabricated using distilled water and ethanol via an electrospinning approach. Morphological evaluations were carried out with a Scanning Electron Microscopy (SEM). Fiber diameters were analyzed with ImageJ. Solution Concentration of PVP with solvents adjusted to 50% (m/v), respectively. Then, the solution was electrospun with voltages of 8 and 12 kV. PVP/distilled water solution produced a relatively regular fiber network with enlarged junctions at 8 kV. However, it was ribbon-like, bead-like, and film-like in voltages of 12 kV. This structure was attributed to high surface tension and slow solvent evaporation. Another solution, PVP/ethanol, produced a relatively regular fiber network at 8 kV. The structure was different at 12 kV voltages. Globular and particle-like morphologies appear in these conditions. Fiber diameter was analyzed in the layers formed under 8 kV electrospinning conditions. The fiber diameter in PVP/distilled water was 1.05 ± 0.50 µm. Meanwhile, the fiber diameter in PVP/ethanol was 2.46 ± 0.64 µm. Although the fiber diameter was larger in PVP/ethanol, the resulting fiber was more continuous and more stable. Electrospinning ; Polyvinylpyrrolidone ; Distilled water ; Fiber ; Scanning electron microscope ; Solvent ; Nanofiber Electrospun Nanofibers in Biomedical Applications ; Advanced Cellulose Research Studies ; Silk-based biomaterials and applications
Authors: Paula Giarolla Silveira | Clara Mariana Gonçalves Lima | Dariush Khademi Shurmasti | Cristina Ferreira Silva | José Luís Contado | Virgílio Carvalho dos Anjos | Maria José Valenzuela Bell | Silvani Verruck | Roney Alves da Rocha
Source: Research Square (preprint, 2025-06-05)
Field: Chemistry — Analytical Chemistry

Detection and Quantification of Goat Milk Adulteration Using FT-NIR Spectroscopy combined with Partial Least Squares and Logistic Regression Partial least squares regression ; Logistic regression ; Statistics ; Mathematics ; Chromatography ; Analytical Chemistry (journal) ; Chemistry Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Meat and Animal Product Quality
Authors: Yu‐Qiang Jiang | Min-Bo Wang | Canhong Wu | Yifei Zhang | Jingjing Han | Dong Wa | Zhi-Fang Huang
Source: Kovove Materialy-Metallic Materials (article, 2025-11-26)
Field: Materials Science — Materials Chemistry

The microstructure and flow behavior of a hot-deformed titanium alloy Titanium alloys are ideal materials for load-bearing components, and hot forming is the primary method for manufacturing these parts.In this work, the hot deformation behavior and microstructure of an anti-damage titanium alloy are studied, and a phenomenological constitutive model is established.The results show that hot deformation has little effect on the shape of the equiaxial phase, and the phase retains its equiaxial morphology.The size and fraction of the phase vary with the hot-deformation parameters.The dynamic phase transformation, Ostwald ripening, and spheroidization occur simultaneously during hot deformation.An Arrhenius constitutive equation is established with a correlation coefficient of 0.9848, and the model can be utilized to predict the flow behavior of the studied titanium alloys at high-temperature deformation.K e y w o r d s : microstructure, hot Microstructure ; Titanium alloy ; Flow (mathematics) ; Alloy ; Metallography ; Deformation (meteorology) Titanium Alloys Microstructure and Properties ; Microstructure and mechanical properties ; Metallurgy and Material Forming
Authors: Alexander Ciupa
Source: Organic & Biomolecular Chemistry (article, 2025-12-23)
Field: Chemistry — Spectroscopy

High-throughput DoE synthesis of chalcones and pyrazolines for fluorescent sensing Pyrazolines are attractive scaffolds for fluorescent sensors due to their unique photophysical properties and the ease of their synthesis from chalcone precursors. While both chalcones and pyrazolines have been widely explored, a systematic optimization of their synthesis using design of experiments (DoE) has yet to be reported. Here, we apply a data-driven DoE strategy, evaluating multiple variables across more than 105 datapoints, to establish highly optimized conditions for the Claisen-Schmidt condensation of chalcones and their subsequent conversion to pyrazolines. High-throughput screening of the resulting library revealed pyrazoline P10 with unusual "turn on" fluorescence at 590 nm in the presence of Zn<sup>2+</sup> only. This integrated DoE-HTS workflow demonstrates a powerful approach for accelerating sensor discovery. Fluorescence ; Chalcone ; Pyrazoline ; Condensation ; Design of experiments ; Workflow Molecular Sensors and Ion Detection ; Luminescence and Fluorescent Materials ; Synthesis and biological activity