jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Magdalena M. Stevanović | Kun Qian | Lin Huang | Marija Vukomanović
Source: Pharmaceutics (article, 2025-12-15)
Field: Materials Science — Biomaterials

PLGA-Based Co-Delivery Nanoformulations: Overview, Strategies, and Recent Advances Poly (lactic-co-glycolic acid) (PLGA) is a widely used copolymer with applications across medical, pharmaceutical, and other industrial fields. Its biodegradability and biocompatibility make it one of the most versatile polymers for nanoscale drug delivery. The present review addresses current knowledge and recent advances in PLGA-based co-delivery nanoformulations with a special reference to design strategies, functional mechanisms, and translational potential. Conventional and advanced fabrication methods, the structural design of PLGA-based nanocarriers, approaches to scale-up and reproducibility, classification of co-delivery types, mechanisms governing drug release, surface modification and functionalization are all discussed. Special attention is given to PLGA-based co-delivery systems, encompassing drug-drug, drug-gene, gene-gene and multi-modal combinations, supported by recent studies demonstrating synergistic therapeutic outcomes. The review also examines clinical translation efforts and the regulatory landscape for PLGA-based nanocarriers. Unlike most existing reviews that typically focus either on PLGA fundamentals or on co-delivery approaches in isolation, this article bridges these domains by providing an integrated, comparative analysis of PLGA-based co-delivery systems and elucidating a critical gap in linking design strategies with translational requirements. In addition, by emphasising the relevance of PLGA-based co-delivery for combination therapies, particularly in cancer and other complex diseases, the review highlights the strong clinical and translational potential of these platforms. Key challenges, such as reproducibility, large-scale manufacturing, and complex regulatory pathways, are discussed alongside emerging trends and future perspectives. Taken together, this review positions PLGA-based co-delivery strategies as a critical driver for advancing precision therapeutics and shaping the future landscape of nanomedicine. Translational research ; Relevance (law) ; Cancer therapy ; Clinical Practice ; Scope (computer science) ; Drug development Nanoparticle-Based Drug Delivery ; Advanced Drug Delivery Systems ; Graphene and Nanomaterials Applications
Authors: Julian Schauer | Payman Goodarzi | Jannis Morsch | Andreas Schütze
Source: Sensors (article, 2025-09-11)
Field: Materials Science — Materials Chemistry

A Performance Study of Deep Neural Network Representations of Interpretable ML on Edge Devices with AI Accelerators With the rising adoption of machine learning (ML) and deep learning (DL) applications, the demand for deploying these algorithms closer to sensors has grown significantly, particularly in sensor-driven use cases such as predictive maintenance (PM) and condition monitoring (CM). This study investigated a novel application-oriented approach to representing interpretable ML inference as deep neural networks (DNNs) regarding the latency and energy efficiency on the edge, to tackle the problem of inefficient, high-effort, and uninterpretable-implementation ML algorithms. For this purpose, the interpretable deep neural network representation (IDNNRep) was integrated into an open-source interpretable ML toolbox to demonstrate the inference time and energy efficiency improvements. The goal of this work was to enable the utilization of generic artificial intelligence (AI) accelerators for interpretable ML algorithms to achieve efficient inference on edge hardware in smart sensor applications. This novel approach was applied to one regression and one classification task from the field of PM and validated by implementing the inference on the neural processing unit (NPU) of the QXSP-ML81 Single-Board Computer and the tensor processing unit (TPU) of the Google Coral. Different quantization levels of the implementation were tested against common Python and C++ implementations. The novel implementation reduced the inference time by up to 80% and the mean energy consumption by up to 76% at the lowest precision with only a 0.4% loss of accuracy compared to the C++ implementation. With the successful utilization of generic AI accelerators, the performance was further improved with a 94% reduction for both the inference time and the mean energy consumption. Inference ; Artificial neural network ; Deep learning ; Edge device ; Efficient energy use ; Adaptive neuro fuzzy inference system ; Toolbox ; Python (programming language) ; Energy consumption Machine Learning in Materials Science ; Advanced Neural Network Applications ; Machine Learning and Data Classification
Authors: Frédérique Vilenne | Simon Appeltans | Manor Askenazi | Dirk Valkenborg
Source: Mass Spectrometry Reviews (review, 2025-04-18)
Field: Chemistry — Spectroscopy

Defining Spectral Quality in Mass Spectrometry‐Based Proteomics: A Retrospective Review Mass spectrometry-based proteomics is essential for advancing preventive and personalised medicine. Technological advancements have greatly increased both the number and sensitivity of spectra generated in a single experiment. Traditionally, spectra are identified using database search engines that depend on large and continuously expanding databases. This expansion enlarges the search space, posing challenges for controlling the false discovery rate in peptide identification. While many bioinformatic workflows employ rescoring algorithms as a post-processing step to manage false discoveries, preprocessing spectra offers a promising alternative. One such method, spectral quality assessment, classifies spectra as "high" quality (likely containing a peptide) or "low" quality (predominantly consisting of noise). This review provides a comprehensive perspective on spectral quality assessment, examining existing tools and their underlying principles. We discuss key considerations such as the definition of spectral quality, normalisation, the use of experimental training data, and future research in the field. By highlighting the potential of spectral quality assessment to improve peptide identification and reduce false discoveries, we aim to elaborate on its potential for the proteomics community. Workflow ; Preprocessor ; Identification (biology) ; Quality (philosophy) ; Proteomics ; Computer science ; Data science ; Mass spectrometry ; Data quality ; Chemistry ; Database search engine ; Quality assessment ; Data mining ; Artificial intelligence ; Information retrieval ; Search engine ; Database ; Chromatography ; Reliability engineering ; Engineering ; Evaluation methods ; Physics Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Maarit Karonen
Source: Macromol—A Journal of Macromolecular Research (article, 2025-01-12)
Field: Chemistry — Physical and Theoretical Chemistry

Polyphenol–Macromolecule Interactions by Isothermal Titration Calorimetry Isothermal titration calorimetry (ITC) is a widely used and valuable technique for studying the binding interactions and the formation and dissociation of molecular complexes. ITC directly measures the energetics associated with the interactions and allows for a precise and complete thermodynamic description of association and binding processes, thereby providing an understanding of the interaction mechanisms. In this review, the role, practical aspects related to the experimental design and setup, advantages, and challenges of using ITC to evaluate polyphenol–macromolecule binding are discussed in detail. The focus is on the possibilities offered by ITC, but at the same time, its limitations are taken into account, especially in the study of complex biological processes and in the subsequent reliable determination of thermodynamic parameters. Polyphenols and proteins typically exhibit exothermic interactions, producing strong signals and distinctive titration curves that can be fitted by one- or two-site binding models; of course, there are exceptions to this. Tannins and tannin fractions usually have a high binding stoichiometry and stronger interactions with proteins than the smaller polyphenols. The driving forces behind these interactions vary, but in many cases, both hydrogen bonding and hydrophobic interactions have been reported. The interactions between polyphenols and polysaccharides or lipid bilayers have been far less studied by ITC in comparison to polyphenol–protein interactions. ITC could be utilized more extensively to study polyphenol–macromolecule interactions, as it is an excellent tool for evaluating the thermodynamic parameters of these interactions, and when used together with other techniques, ITC can also help understand how these interactions affect bioavailability, food applications, and other uses of polyphenols. Isothermal titration calorimetry ; Chemistry ; Polyphenol ; Macromolecule ; Hydrophobic effect ; Hydrogen bond ; Titration ; Protein–protein interaction ; Molecule ; Biochemistry ; Organic chemistry thermodynamics and calorimetric analyses ; Chemical and Physical Properties in Aqueous Solutions ; Analytical Chemistry and Chromatography
Authors: Vishant Garg | Maxime Magnan | Sandrine Zanna | Antoine Seyeux | Frédéric Wiame | Vincent Maurice | Philippe Marcus
Source: npj Materials Degradation (article, 2025-08-03)
Field: Materials Science — Materials Chemistry

Corrosion inhibition mechanisms of 2-mercaptobenzothiazole on AA2024 T3 aluminium alloy The mechanisms of 2-mercaptobenzothiazole (2-MBT) adsorption and corrosion inhibition on the aerospace AA2024 T3 aluminium alloy have been investigated using electrochemistry and advanced surface analyses. Electrochemical methods were used to measure the degree of corrosion protection in neutral chloride media, while advanced surface analysis techniques were employed to determine the interfacial interaction and inhibitor action mechanisms. It is shown that 2-MBT effectively inhibits corrosion of the alloy, reducing its susceptibility to corrosion attack and its corrosion rate. Surface analysis, including the use of ToF-SIMS 3-D chemical mapping, confirms 2-MBT adsorption on partially dealloyed intermetallic particles (IMPs) along with the presence of a thin 2-MBT layer on the top-most alloy surface. Chloride ions breakdown the native oxide film, allowing 2-MBT to adsorb on IMPs, thereby inhibiting further localized corrosion on these particles, while the 2-MBT layer on the surface protects the alloy matrix from surface oxidation. Alloy ; Corrosion ; Aluminium ; Metallurgy ; Materials science ; Aluminium alloy ; 6111 aluminium alloy Corrosion Behavior and Inhibition ; Electron and X-Ray Spectroscopy Techniques ; Aluminum Alloy Microstructure Properties
Authors: Jessica P. Metherall | Philip Corner | James F. McCabe | Michael R. Probert | Michael J. Hall
Source: Chemical Science (article, 2025-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

High-throughput encapsulated nanodroplet screening for accelerated co-crystal discovery Co-crystals are composed of two or more chemically inequivalent molecular species, excluding solvents, generally in a stoichiometric ratio. Co-crystals are particularly important in pharmaceutical development, where a suitable co-crystal can significantly improve the physiochemical and pharmacokinetic properties of an active pharmaceutical ingredient. However, co-crystal discovery remains both practically challenging and resource intensive, requiring the extensive searching of complex experimental space. Herein, we demonstrate a high-throughput (HTP) nanoscale co-crystallisation method for the rapid screening of large areas of co-crystallisation space with minimal sample requirements, based on Encapsulated Nanodroplet Crystallisation (ENaCt). HTP co-crystallisation screening by ENaCt allowed rapid access to all 18 possible binary co-crystal combinations of 3 small molecules and 6 co-formers (A/B), through the use of 3456 individual experiments exploring solvent, encapsulating oil and stoichiometry, including 10 novel binary co-crystal structures elucidated by single crystal X-ray diffraction (SCXRD). Higher-order co-crystal (HOC) discovery, accessing co-crystals containing three or more molecules, is one of the most challenging co-crystal research areas, due to the highly complex experimental landscape that must be navigated. Herein, we further exemplify the power of ENaCt co-crystallisation by application to HOC discovery. HTP ENaCt co-crystallisation screening of three component (A/B/C) and four component (A/B/C/D) combinations gave ready access to both ternary and quaternary HOCs, each containing three or four different molecular species respectively. In total, 13 056 individual ENaCt experiments are presented resulting in 54 co-crystal structures by SCXRD, including 17 novel binary co-crystals, 8 novel ternary co-crystals and 4 novel quaternary co-crystals. ENaCt co-crystallisation is thus demonstrated to be a highly impactful and efficient tool in the search for small molecule co-crystals, through the employment of parallelised HTP nanoscale experimental workflows. Throughput ; High-throughput screening ; Nanotechnology ; Chemistry ; Materials science ; Computer science ; Biochemistry Crystallography and molecular interactions ; Machine Learning in Materials Science ; Crystallization and Solubility Studies
Authors: Weiqiang Tang | Jinwen Liu | Katharina Doblhoff-Dier | Jun Huang
Source: Physical Review Letters (article, 2025-12-22)
Field: Chemistry — Physical and Theoretical Chemistry

Mesoscopic Rough Electrical Double Layers Fundamental understanding of electrical double layers (EDL) has been gleaned mostly on ideally planar electrodes, while realistic electrodes usually exhibit surface roughness on multiple scales. The influence of mesoscopic roughness (1-10 nm) is elusive, representing a cutting-edge challenge to theoretical modeling as both quantum- and classical-mechanical effects should be treated efficiently on the same footing. Addressing this challenge, we combine semiclassical models and Kohn-Sham density functional theory calculations to study the influence of mesoscopic roughness on the work function and the potential of zero free charge (PZFC) of silver electrodes. While the work function decreases at rougher electrodes as expected, the change in the PZFC is, unexpectedly, much smaller. The weakened correlation between work function and PZFC is ascribed to the decreased interfacial permittivity in the valley caused by a large, local, electron-spilling-induced electric field. In addition, the rough EDL at PZFC is heterogeneously charged with excess cations in the valley and excess anions near the peak, leading to the deviation of the potential of minimal capacitance from the PZFC. Mesoscopic physics ; Surface finish ; Capacitance ; Semiclassical physics ; Permittivity ; Surface roughness ; Work (physics) ; Planar ; Electrode Electrostatics and Colloid Interactions ; Molecular Junctions and Nanostructures ; Electrowetting and Microfluidic Technologies
Authors: Lixuan Zhang | Yifan Wu | Wenshi Huang | Li Lin | Liwei Wang | Zeyun Wu | Huihuang Fang | Dabiao Wang | Chongqi Chen | Yu Luo | Lilong Jiang
Source: AIChE Journal (article, 2025-02-13)
Field: Materials Science — Materials Chemistry

Multiscale modeling of a low‐temperature <scp> NH <sub>3</sub> </scp> decomposition reactor for precious metal reduction and temperature control Abstract Ammonia is a carbon‐free energy carrier with 17.6 wt% hydrogen content. The design of an efficient and compact ammonia decomposition reactor based on low‐temperature catalysts is the key to realizing industrial hydrogen production from ammonia. In this work, a multiscale model was developed by bridging the particle‐scale characteristics of catalysts and reactor performances, to fully comprehend the ammonia decomposition process. The effects of catalyst porosity and pore diameters on the reactor size, precious metal loading, and the profile of temperature and heat flux were systematically evaluated. An improved reactor design was further proposed by applying the segmented reactor packed with two‐stage egg‐shell‐type low‐temperature catalysts, which decreased the precious metal usage by 61.6% and the temperature drop by 42.9 K. This segmentation strategy balanced the reaction rate and heat flux, indicating a significant potential in highly efficient, economical, and reliable hydrogen production from ammonia. Decomposition ; Reduction (mathematics) ; Temperature control ; Precious metal ; Chemical engineering ; Metal ; Chemistry ; Materials science ; Thermodynamics ; Metallurgy ; Engineering ; Physics ; Organic chemistry ; Mathematics Catalytic Processes in Materials Science ; Ammonia Synthesis and Nitrogen Reduction ; Hydrogen Storage and Materials
Authors: Marcus Vinicius Mendes Vale Amaral | Claudia Carraro | Amanda Antoniêto | Mariana Costa Nascimento | Thais Fernanda de Campos Fraga‐Silva | Ualter Guilherme Cipriano | Rodrigo Paolo Flores Abuna | Tamara Silva Rodrigues | Ronaldo B. Martins | Andreia M. Luzenti | Glaucia Rigotto Caruso | Priscyla D. Marcato | Vânia Luiza Deperon Bonato | Dario S. Zamboni | Bergmann Morais Ribeiro | Sônia Nair Báo | João S. Silva | Flávio P. Veras | Roberto Nascimento Silva
Source: Current Research in Biotechnology (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Biogenic silver nanoparticles produced by Trichoderma reesei inhibit SARS-CoV-2 infection, reduce lung viral load and ameliorate acute pulmonary inflammation • Biogenic silver nanoparticles inhibit SARS-CoV-2 infection in Syrian hamsters. • AgNP treatment reduces viral load and pulmonary inflammation in hamsters. • AgNPs synthesized by T. reesei show high affinity for the SARS-CoV-2 spike protein. • Silver nanoparticles prevent inflammasome activation and IL-1β production. • Green AgNP synthesis method shows therapeutic potential against COVID-19. The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), posed a significant global health challenge and still demands efforts to develop new therapies. In this study, we investigated the potential of biogenic silver nanoparticles (AgNPs) synthesized by the fungus Trichoderma reesei to combat SARS-CoV-2 infection. In silico studies showed that AgNPs, ranging from 7 nm to 50 nm, have high affinity for spike protein from different variant of SARS-CoV-2. Our findings show that AgNPs effectively do not affect cell viability in Calu-3 cells, inhibit viral infection in Vero-E6 cells and progression of infection in vitro . Additionally, AgNPs impair caspase-1 activation, lactate dehydrogenase release and IL-1β production by human monocytes. Moreover, our study reveals that AgNPs treatment significantly alleviated acute lung injury induced by SARS-CoV-2 infection in Syrian hamsters. This suggests that AgNPs treatment effectively impairs viral replication or propagation within lung tissue, highlighting its potential as an antiviral agent against SARS-CoV-2. Further investigations are warranted to elucidate the underlying mechanisms of action of AgNPs and to assess their safety and efficacy in clinical settings. Nonetheless, our findings offer promising insights into the development of novel therapeutic strategies for combating COVID-19 and reducing its associated morbidity and mortality. Inflammation ; Lung ; Viral load ; Medicine ; Silver nanoparticle ; Coronavirus disease 2019 (COVID-19) ; Lung infection ; Microbiology ; Virology ; Viral infection ; Pulmonary infection ; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ; Immunology ; Human immunodeficiency virus (HIV) ; Virus ; Biology ; Nanoparticle ; Pathology ; Internal medicine ; Materials science ; Nanotechnology ; Infectious disease (medical specialty) ; Disease Nanoparticles: synthesis and applications ; Medicinal Plants and Neuroprotection
Authors: Azalina Zainuddin | Raniya Razif | Aifa Asyhira Khairul Nizam | Manira Maarof | Nur Izzah Md Fadilah | Yang‐Hee Kim | Ebrahim Mahmoudi | Mh Busra Fauzi
Source: Polymers (article, 2025-09-27)
Field: Materials Science — Biomaterials

Kelulut Honey-Incorporated Hybrid Gelatin-PVA Hydrogel for Wound Healing: Fabrication and In Vitro Characterization Hydrogels are attractive biomaterials for skin replacement and tissue regeneration, offering advantages over split-skin grafts for large or irregular wounds. Honey-containing hydrogels are of particular interest, combining honey's natural healing properties with the versatility of hydrogel matrices. This study aimed to develop a biocompatible, biodegradable, and mechanically stable hydrogel as a cutaneous substitute. To achieve this, different formulations were prepared using gelatin (GE), polyvinyl alcohol (PVA), and Kelulut honey (KH). The formulations were designated as: GE-PVA (6% (<i>w</i>/<i>v</i>) GE: 5% (<i>w</i>/<i>v</i>) PVA, without KH), GE-PVA-H1 (containing 1% (<i>v</i>/<i>v</i>) KH), GE-PVA-H5 (containing 5% (<i>v</i>/<i>v</i>) KH), and GE-PVA-H10 (containing 10% (<i>v</i>/<i>v</i>) KH). All formulations were crosslinked with 0.1% (<i>w</i>/<i>v</i>) genipin (GNP). GE-PVA-H1 and GE-PVA-H1-GNP showed swelling ratios of 110.18 ± 20.14% and 86.31 ± 14.27%, lower than GE-PVA-H5 (125.79 ± 23.76%), GE-PVA-H10 (132.79 ± 20.86%), and their crosslinked counterparts. All formulations had WVTR <1500 g/m<sup>-2</sup>h<sup>-1</sup>, with GE-PVA-H1-GNP at 501.21 ± 41.35 g/m<sup>-2</sup>h<sup>-1</sup>, GE-PVA-H5-GNP at 473.77 ± 44.10 g/m<sup>-2</sup>h<sup>-1</sup>, and GE-PVA-H10-GNP at 467.51 ± 73.59 g/m<sup>-2</sup>h<sup>-1</sup>. GE-PVA-H1-GNP exhibited the slowest biodegradation (0.0036 ± 0.0003 g/h vs. 0.0096-0.0206 g/h for other groups). Contact angle was lowest for GE-PVA-H1-GNP (38.46° ± 3.89°), confirming higher hydrophilicity compared with GE-PVA-H5/H10 groups. Resilience (98.85% ± 1.03%) and compression strength (77.42% ± 7.17%) of GE-PVA-H1-GNP were comparable to GE-PVA-H5-GNP and GE-PVA-H10-GNP. MTT assays confirmed cytocompatibility across all groups. Collectively, GE-PVA-H1-GNP emerged as the optimal formulation, combining mechanical stability, hydrophilicity, and biocompatibility for wound healing applications. Genipin ; Self-healing hydrogels ; Biocompatibility ; Polyvinyl alcohol ; Gelatin ; Swelling ; Biodegradation ; Mechanical strength ; Wound healing Electrospun Nanofibers in Biomedical Applications ; Wound Healing and Treatments ; Hydrogels: synthesis, properties, applications