jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Atena Yaramiri | Rand Abo Asalh | Majd Abo Asalh | Nour AlSawaftah | Waad H. Abuwatfa | Ghaleb A. Husseini
Source: International Journal of Molecular Sciences (review, 2025-07-29)
Field: Materials Science — Biomaterials

A Comprehensive Review of Smart Thermosensitive Nanocarriers for Precision Cancer Therapy By 2030, millions of new cancer cases will be diagnosed, as well as millions of cancer-related deaths. Traditional drug delivery methods have limitations, so developing smart drug delivery systems (SDDs) has emerged as a promising avenue for more effective and precise cancer treatment. Nanotechnology, particularly nanomedicine, provides innovative approaches to enhance drug delivery, including the use of nanoparticles. One such type of SDD is thermosensitive nanoparticles, which respond to internal and external stimuli, such as temperature changes, to release drugs precisely at tumor sites and minimize off-target effects. On the other hand, hyperthermia is a cancer treatment mode that goes back centuries and has become popular because it can target cancer cells while sparing healthy tissue. This paper presents a comprehensive review of smart thermosensitive nanoparticles for cancer treatment, with a primary focus on organic nanoparticles. The integration of hyperthermia with temperature-sensitive nanocarriers, such as micelles, hydrogels, dendrimers, liposomes, and solid lipid nanoparticles, offers a promising approach to improving the precision and efficacy of cancer therapy. By leveraging temperature as a controlled drug release mechanism, this review highlights the potential of these innovative systems to enhance treatment outcomes while minimizing adverse side effects. Nanocarriers ; Nanomedicine ; Drug delivery ; Nanotechnology ; Cancer therapy ; Cancer ; Solid lipid nanoparticle ; Cancer treatment ; Self-healing hydrogels ; Drug ; Liposome ; Medicine ; Computer science ; Nanoparticle ; Materials science ; Pharmacology ; Internal medicine Nanoparticle-Based Drug Delivery ; Nanoplatforms for cancer theranostics ; Advancements in Transdermal Drug Delivery
Authors: Shiwei Zhang | Cheng‐Long Shen | Jiurong Li | Junfei Liao | Peng Miao | Xiujian Zhao | Xiao Gong
Source: Chemical Science (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Ultra-wide time-dependent phosphorescence color of carbon dots <i>via</i> a synergistic strategy of dual confinement structures constructing multiple luminescent centers Phosphorescent materials with time-dependent phosphorescent color (TDPC) output have significant potential for applications in advanced optical information encryption. However, the effective construction of TDPC composites compatible with multiple phosphorescent emission centers to achieve wider phosphorescent colors evolving over time in a single material system remains a huge challenge. Here, ultra-wide TDPC composites with time-dependent color evolution were realized for the first time in a single system by exploiting the synergistic effect of a doubly confined structure. Utilizing organosilanes to pretreat the reactive precursor, combined with a boric acid (BA) matrix, the composite (Si-CDs@B<sub>2</sub>O<sub>3</sub>) was prepared by direct calcination. Our results reveal that the Si-CDs@B<sub>2</sub>O<sub>3</sub> composite has significant ultra-wide TDPC properties, with the phosphorescent emission shifting from red to orange, yellow, green, and cyan blue. Characterization analysis reveals the important role of organosilanes in achieving ultra-wide TDPC properties. It also demonstrates that the red phosphorescence originates from the interaction of C[double bond, length as m-dash]O on the surface of CDs with the BA matrix, while the blue phosphorescence originates from the intrinsic emission of B-O bonds in the BA matrix. The distinctive dynamic room-temperature phosphorescence properties of the Si-CDs@B<sub>2</sub>O<sub>3</sub> composite were leveraged to develop a strategy for its use in information encryption on a precise time scale. Phosphorescence ; Luminescence ; Dual (grammatical number) ; Quantum dot ; Persistent luminescence ; Optoelectronics ; Materials science ; Nanotechnology ; Carbon fibers ; Aggregation-induced emission ; Fluorescence ; Physics ; Optics Luminescence and Fluorescent Materials ; Carbon and Quantum Dots Applications ; Nanocluster Synthesis and Applications
Authors: Ting Li | Zhong Ren | Chunyan Zhao | Gaoqiang Liang
Source: Foods (article, 2025-02-03)
Field: Chemistry — Analytical Chemistry

Geographical Origin Traceability of Navel Oranges Based on Near-Infrared Spectroscopy Combined with Deep Learning The quality and price of navel oranges vary depending on their geographical origin, thus providing a financial incentive for origin fraud. To prevent this phenomenon, it is necessary to explore a fast, non-destructive, and precise method for tracing the origin of navel oranges. In this study, a total of 490 Newhall navel oranges were selected from five major production regions in China, and the diffuse reflectance near-infrared spectrum in 4000-10,000 cm<sup>-1</sup> were non-invasively collected. We examined seven preprocessing techniques for the spectra, including Savitzky-Golay (SG) smoothing, first derivative (FD), multiplicative scattering correction (MSC), combinations of SG with MSC (SG+MSC), SG with FD (SG+FD), MSC with FD (MSC+FD), and three combined (SG+MSC+FD). A one-dimensional convolutional neural network (1DCNN) deep learning model for geographical origin tracing of navel orange was established, and five machine learning algorithms, i.e., partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), support vector machine (SVM), random forest (RF), and back-propagation neural network (BPNN), were compared with 1DCNN. The results show that the 1DCNN model based on the SG+FD preprocessing method achieved the optimal performance for the testing set, with prediction accuracy, precision, recall, and F1-score of 97.92%, 98%, 97.95%, and 97.90%, respectively. Therefore, NIRS combined with deep learning has a significant research and application value in the rapid, nondestructive, and accurate geographical origin traceability of agricultural products. Linear discriminant analysis ; Artificial intelligence ; Traceability ; Partial least squares regression ; Pattern recognition (psychology) ; Mathematics ; Computer science ; VNIR ; Preprocessor ; Algorithm ; Machine learning ; Statistics ; Hyperspectral imaging Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Advanced Chemical Sensor Technologies
Authors: Andrew Savinov | Sebastian Swanson | Amy E. Keating | Gene‐Wei Li
Source: Proceedings of the National Academy of Sciences (article, 2025-02-03)
Field: Chemistry — Spectroscopy

High-throughput discovery of inhibitory protein fragments with AlphaFold Peptides can bind to specific sites on larger proteins and thereby function as inhibitors and regulatory elements. Peptide fragments of larger proteins are particularly attractive for achieving these functions due to their inherent potential to form native-like binding interactions. Recently developed experimental approaches allow for high-throughput measurement of protein fragment inhibitory activity in living cells. However, it has thus far not been possible to predict de novo which of the many possible protein fragments bind to protein targets, let alone act as inhibitors. We have developed a computational method, FragFold, that employs AlphaFold to predict protein fragment binding to full-length proteins in a high-throughput manner. Applying FragFold to thousands of fragments tiling across diverse proteins revealed peaks of predicted binding along each protein sequence. Comparisons with experimental measurements establish that our approach is a sensitive predictor of fragment function: Evaluating inhibitory fragments from known protein-protein interaction interfaces, we find 87% are predicted by FragFold to bind in a native-like mode. Across full protein sequences, 68% of FragFold-predicted binding peaks match experimentally measured inhibitory peaks. Deep mutational scanning experiments support the predicted binding modes and uncover superior inhibitory peptides in high throughput. Further, FragFold is able to predict previously unknown protein binding modes, explaining prior genetic and biochemical data. The success rate of FragFold demonstrates that this computational approach should be broadly applicable for discovering inhibitory protein fragments across proteomes. Function (biology) ; Computational biology ; Proteome ; Inhibitory postsynaptic potential ; Peptide ; Fragment (logic) ; Protein–protein interaction ; Biology ; Plasma protein binding ; High-throughput screening ; Protein function ; Genetics ; Biochemistry ; Gene ; Computer science ; Algorithm Advanced Proteomics Techniques and Applications ; Protein Structure and Dynamics ; Machine Learning in Bioinformatics
Authors: Brinda Vallat | Benjamin Webb | Arthur O. Zalevsky | Hongsuda Tangmunarunkit | Monica Sekharan | Serban Voinea | Aref Shafaeibejestan | Jared Sagendorf | Jeffrey C. Hoch | Genji Kurisu | Kyle L. Morris | Sameer Velankar | Carl Kesselman | S.K. Burley | Helen M. Berman | Andrej Săli
Source: Journal of Molecular Biology (article, 2025-01-27)
Field: Materials Science — Materials Chemistry

PDB-IHM: A System for Deposition, Curation, Validation, and Dissemination of Integrative Structures Structures of many large biomolecular assemblies are now being determined using integrative approaches. In these approaches, information derived from multiple experimental and computational methods is combined to compute three-dimensional structures of multi-protein complexes and other macromolecular machines. A standalone prototype data resource for integrative structures called PDB-Dev was built, based on recommendations of the Integrative and Hybrid Methods (IHM) Task Force of the Worldwide Protein Data Bank (wwPDB). This effort included developing data standards and software tools for collecting, curating, validating, visualizing, archiving, and disseminating integrative structures that span diverse spatiotemporal scales and conformational states. Mechanisms have been created to validate integrative structures based on the experimental data underpinning them. Building upon this foundational framework, PDB-Dev has been further expanded to handle large dynamic macromolecular systems and integrative structures that combine, for example, experimental restraints with atomic coordinates computed by machine learning algorithms. Data standards and supporting tools have also been extended to capture information about biomolecular dynamics, such as conformational transitions and related kinetic data derived from biophysical methods. Recently, PDB-Dev was unified with the PDB archive and rebranded as PDB-IHM (pdb-ihm.org), further promoting FAIR (Findable, Accessible, Interoperable, and Reusable) principles of data stewardship for integrative structural biology. Protein Data Bank (RCSB PDB) ; Data curation ; Computational biology ; Computer science ; Chemistry ; Data science ; Biology ; Biochemistry Enzyme Structure and Function ; Protein Structure and Dynamics ; Scientific Computing and Data Management
Authors: Jean‐Baptiste Thomas | Pierre‐Jean Lapray | Steven Le Moan
Source: Sensors (article, 2025-01-23)
Field: Chemistry — Analytical Chemistry

Trends in Snapshot Spectral Imaging: Systems, Processing, and Quality Recent advances in spectral imaging have enabled snapshot acquisition, as a means to mitigate the impracticalities of spectral imaging, e.g., expert operators and cumbersome hardware. Snapshot spectral imaging, e.g., in technologies like spectral filter arrays, has also enabled higher temporal resolution at the expense of the spatio-spectral resolution, allowing for the observation of temporal events. Designing, realising, and deploying such technologies is yet challenging, particularly due to the lack of clear, user-meaningful quality criteria across diverse applications, sensor types, and workflows. Key research gaps include optimising raw image processing from snapshot spectral imagers and assessing spectral image and video quality in ways valuable to end-users, manufacturers, and developers. This paper identifies several challenges and current opportunities. It proposes considering them jointly and suggests creating a new unified snapshot spectral imaging paradigm that would combine new systems and standards, new algorithms, new cost functions, and quality indices. Snapshot (computer storage) ; Workflow ; Computer science ; Spectral imaging ; Image quality ; Real-time computing ; Computer vision ; Remote sensing ; Image (mathematics) ; Database Spectroscopy and Chemometric Analyses ; Remote-Sensing Image Classification ; Advanced Image Fusion Techniques
Authors: Abolfazl Malti | P Rashidfar | Arash Kardani | Abbas Montazeri
Source: Scientific Reports (article, 2025-06-02)
Field: Materials Science — Materials Chemistry

Microstructural evolution and phase transitions in porous Ta/Cu alloys under high strain rates Tantalum (Ta) and its alloys are widely used in electronics, dental implants, aerospace, and nuclear industries. Ta-based medical implants have also attracted considerable attention in recent years. However, challenges such as thermal conductivity, oxidation resistance, antibacterial properties, and the mismatch between bone and implant mechanical properties remain major concerns across various applications. The addition of alloying elements, such as copper (Cu), to Ta reduces bacterial adhesion in medical applications, while also improving thermal conductivity and oxidation resistance, making it beneficial for high-temperature environments. Furthermore, incorporating porosity into Ta-based materials mitigates stress shielding in implants, reduces weight, and enhances thermal dissipation in advanced engineering applications. While numerous studies have investigated the mechanical and physical properties of Ta-based alloys, the combined influence of porosity and alloying elements on the mechanical response of these biomaterials has not been systematically studied. This study employs molecular dynamics (MD) simulations to analyze the mechanical response and microstructural evolution of porous Ta/5 wt% Cu alloys under uniaxial tensile loading. Our results demonstrate that optimizing strain rates and introducing pores can modulate the mechanical characteristics of Ta/Cu alloys. Increasing the strain rate from 5 × 10<sup>8</sup> to 5 × 10<sup>11</sup> s<sup>- 1</sup> enhances properties due to the rapid BCC-to-FCC phase transformation at high strain rates, while increasing porosity from 0 to 10% reduces yield stress and elastic modulus by 12% and 14%, respectively. Moreover, the influence of porosity on deformation-induced microstructural transformations, such as twinning behavior and crystallographic changes, is examined. The study offers insights into designing porous Ta-based alloys with improved mechanical performance and microstructural characteristics. Strain (injury) ; Materials science ; Porosity ; Phase (matter) ; Metallurgy ; Composite material ; Chemistry ; Biology ; Anatomy High-Velocity Impact and Material Behavior ; Advanced materials and composites ; Powder Metallurgy Techniques and Materials
Authors: Oya Kılcı | Murat Köklü
Source: Food Analytical Methods (article, 2025-01-25)
Field: Chemistry — Analytical Chemistry

Automated Classification of Biscuit Quality Using YOLOv8 Models in Food Industry Abstract It is of great importance for food safety and consumer satisfaction that industrial food products are durable, hygienic, and flawless. Robust products protect the physical integrity of the product by preventing damage that may occur during the production and transportation processes, which meets the expectations of the consumer. Hygienic production conditions prevent foodborne diseases by minimizing the risk of microbial contamination and protect consumer health. Perfect products strengthen the brand image with their aesthetic and satisfactory features and increase consumer loyalty. In the study conducted in this context, the classification of defect and no defect conditions of biscuits in the food industry was examined using YOLOv8 models. A summary dataset consisting of 4990 biscuit images was created and the biscuits were initially divided into two categories: defect and no defect. Later, defect biscuits were classified into three subcategories: not complete, overcooked, and texture defect. As a result of experiments with YOLOv8 models, binary classification (defect, no defect), the highest accuracy rate was achieved in the YOLOv8-m, YOLOv8-l, and YOLOv8-x models with 96.78%, while the highest accuracy rate in the triple classification (not complete, overcooked, and texture defect) performance was achieved in the YOLOv8-m model with 96.99%. Food industry ; Quality (philosophy) ; Food science ; Food quality ; Business ; Chemistry Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Food Supply Chain Traceability
Authors: Shiju Liu | Chuhan Zhou | Ruiyang Tan | Mengqi Han | Zhijing Wu | Ping Chen
Source: Nanophotonics (article, 2025-04-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Bio‐inspired multispectral camouflage material for microwave, infrared, and visible bands based on single hierarchical metasurface Nature can significantly inspire humans. Chameleons, jellyfish, and many other creatures use unique camouflage methods. Multispectral camouflage materials are highly desirable to against progressive multispectral detection. The proposed structure should be simple and highly transparent to ensure a wide application range. In this study, a bio-inspired multispectral camouflage material with visible transparency, microwave diffusion, and infrared (IR) camouflage was designed, fabricated, and tested. Multispectral camouflage performance was achieved on a single metasurface by the following steps: First, a nanoscale multilayered film consisting of an oxide and metal was unitized to achieve a low IR emissivity and high visible transmittance. Then, two units were designed to obtain a phase difference, thus realizing the microwave diffusion performance. Based on the relationship between the area filling fraction and IR emissivity, the units can perform puzzled imaging under an IR thermal camera. The structural parameters were calculated and optimized through an equivalent circuit model-based artificial intelligence algorithm. Then, a 10 dB reduction in radar cross section from 7 GHz to 16 GHz, a puzzled IR thermal image, and a high optical transmittance (>0.7) were achieved. The work provides significant guidance for the design and fabrication of multispectral camouflage materials. Camouflage ; Multispectral image ; Emissivity ; Materials science ; Infrared ; Transmittance ; Optics ; Microwave ; Metamaterial ; Optoelectronics ; Computer science ; Remote sensing ; Artificial intelligence ; Physics ; Telecommunications ; Geology Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Thermal Radiation and Cooling Technologies
Authors: Mohammad Alqtish | Alessio Di Fatta | Giuseppe Rizzo | Ghulam Akbar | Vincenzo Li Vigni | Antonino Imburgia | Guido Ala | R. Candela | Pietro Romano
Source: Energies (review, 2025-05-16)
Field: Materials Science — Materials Chemistry

A Review of Partial Discharge Electrical Localization Techniques in Power Cables: Practical Approaches and Circuit Models This paper remedies the lack of comparison between studies specifically addressing partial discharge (PD) localization using electrical techniques. It identifies all the elements in need in each technique as well as the equations leading to a precise determination of the discharge site in a cable with a certain length and documents several circuit models set to simulate various types of PD. From the details in this paper, different detection methods can be combined based on the specific requirements of each method for detecting PD. This work thoroughly evaluates several electrical PD detection approaches, including time-based, frequency band, and electromagnetic time reversal (EMTR). Additionally, it gathers circuit modeling for various types of PD along cables to improve detection accuracy. It is evident that all time-dependent methods, despite their simplicity and requiring only a small number of components, face challenges when applied to long cables. This is primarily due to their reliance on signal propagation time. The authors provide profound insights into suggestions for future study areas. This review will provide essential insights and serve as a foundation for researchers to develop more effective methods for detecting PD in cables. Partial discharge ; Electrical engineering ; Power (physics) ; Electrical network ; Engineering ; Computer science ; Electronic engineering ; Voltage ; Physics High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation
Authors: Émilie Bertrand | Valérie Gabelica
Source: Mass Spectrometry Reviews (review, 2025-01-27)
Field: Chemistry — Spectroscopy

Thermometer Ions, Internal Energies, and In‐Source Fragmentation in Ambient Ionization Ionization and fragmentation are at the core of mass spectrometry. But they are not necessarily separated in space, as in-source fragmentation can also occur. Here, we survey the literature published since our 2005 review on the internal energy and fragmentation in electrospray ionization sources. We present new thermometer molecules to diagnose and quantify source heating, provide tables of recommended threshold (E<sub>0</sub>) and appearance energies (E<sub>app</sub>) for the survival yield method, and attempt to compare the softness of a variety of ambient pressure ionization sources. The droplet size distribution and desolvation dynamics play a major role: lower average internal energies are obtained when the ions remain protected by a solvation shell and spend less time nakedly exposed to activating conditions in the transfer interface. Methods based on small droplet formation without charging can thus be softer than electrospray. New dielectric barrier discharge sources can gas-phase ionize small molecules while conferring barely more internal energy than electrospray ionization. However, the tuning of the entire source interface often has an even greater influence on ion internal energies and fragmentation than on the ionization process itself. We hope that this review will facilitate further research to control and standardize in-source ion activation conditions, and to ensure the transferability of data and research results in mass spectrometry. Chemistry ; Ionization ; Fragmentation (computing) ; Ion source ; Electrospray ionization ; Ion ; Mass spectrometry ; Ambient ionization ; Electron ionization ; Atomic physics ; Chemical physics ; Analytical Chemistry (journal) ; Chromatography ; Physics ; Organic chemistry Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; Microfluidic and Capillary Electrophoresis Applications