jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yomna Adel Gabr | Germeen NS Girgis | H M Elsabbagh
Source: Journal of Pharmaceutical Research International (article, 2023-07-10)
Field: Materials Science — Biomaterials

Surface-Decorated Nanocarrier as a Targeted Drug Delivery Cargo to Folate Receptor-Overexpressing Cells for Enhancing Anti-cancer and Anti-inflammatory Activity Aims: Folate receptor (FR) is overexpressed in most cancer cells and activated macrophages entailed in rheumatoid arthritis (RA). The aim of the current study was the fabrication of FR-targeted nanocarrier loaded with methotrexate (MTX) to magnify its therapeutic efficacy and limit its toxicity. Methodology: Folic acid-chitosan (FA-CS) conjugate was synthesized and characterized. MTX loaded poly(d,l-lactide-co-glycolide) (PLGA) nanoparticles (NPs) were prepared, optimized and coated with different concentrations of FA-CS conjugate. The selected FA-CS coated MTX NPs formulation (F10) was evaluated via in vitro and in vivo studies. Results: F10 had satisfactory encapsulation efficiency (76.2%), homogenous particle size (278.6 nm) and positive zeta potential (34.0 mV) and displayed biphasic drug release pattern in different pH media. Further characterization of F10 cinched MTX incorporation in the polymeric matrix of the targeted nanocarrier. In vitro cytotoxicity assay to FR-positive and FR-negative cancer cells revealed the improved anticancer effect of F10 to FR-positive cancer cells, which was absent in FR-negative cells, compared to free MTX or uncoated MTX NPs (F2). F10 showed appropriate storage stability at refrigerated temperature up to 3 months. Moreover, oral administration of F10 in the treatment of complete Freund’s adjuvant (CFA)-induced RA in BALB/c mice conferred prodigious therapeutic outcomes and declined systemic toxicity compared to oral treatment with conventional pure MTX or commercial MTX tablets. Conclusion: The fabricated targeted nanocarrier could enhance the anticancer activity of MTX to FR-overexpressing cancer cells and could be a promising novel approach for oral administration of MTX in the treatment of RA or other inflammatory conditions associated with FR-overexpressing activated macrophages. Nanocarriers ; Folate receptor ; Pharmacology ; Cytotoxicity ; In vivo ; Cancer cell ; Chemistry ; In vitro ; Methotrexate ; PLGA ; Chitosan ; Toxicity ; Cancer ; Medicine ; Drug ; Immunology ; Biochemistry ; Internal medicine ; Biology Nanoparticle-Based Drug Delivery ; Cancer Research and Treatment
Authors: Tingyi Wangyan | Qi Sun | Pamela J. Grizzard | Jinze Liu | Yifan Peng
Source: PubMed (article, 2023-01-01)
Field: Chemistry — Spectroscopy

A new deep learning framework to process Matrix-assisted Laser Desorption/Ionisation Mass Spectrometry Imaging (MALDI-MSI) data of Tissue Microarrays (TMAs). Matrix-Assisted Laser Desorption Ionization mass spectrometry imaging (MALDI-MSI) is a mass spectrometry ionization technique that can be used to directly analyze tissues and has led the way in the development of biological and clinical applications for imaging mass spectrometry. One of its advantages is measuring the distribution of a large number of analytes at one time without destroying the sample, making it a useful method in tissue-based studies. However, analysis of the MALDI-MSI images from tissue microarrays (TMAs) remains less studied. While several automated systems have been developed for tissue classification (e.g., cancer vs non-cancer), they process the MALDI data at the measuring point level, which ignores spatial relationships among individual points within the tissue sample. In this work, we propose mNet, a new deep learning framework to analyze MALDI-MSI data of TMAs at the tissue-needle-core level to ensure that the samples maintain their original spatial context. In addition, we introduced data augmentation techniques to increase data size which is often limited in biomedical data. We applied our framework to analyzing TMAs from breast and lung cancer. We found that our framework outperforms conventional machine learning methods in the challenging race detection task. The results highlight the potential of deep learning to assist pathologists in analyzing tissue specimens in a label-free, high-throughput manner. Mass spectrometry imaging ; MALDI imaging ; Computer science ; Artificial intelligence ; Context (archaeology) ; Mass spectrometry ; Tissue microarray ; Matrix-assisted laser desorption/ionization ; Chemistry ; Pattern recognition (psychology) ; Desorption ; Chromatography ; Cancer ; Medicine ; Biology ; Internal medicine Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Hesti Lina Wiraswati | Muhammad Hasan Bashari | Nayla Majeda Alfarafisa | Ilma Fauziah Ma’ruf | Eti Nurwening Sholikhah | Tutik Dwi Wahyuningsih | Pamungkas Bagus Satriyo | Mustofa Mustofa | Denny Satria | Ema Damayanti
Source: Journal of Pharmacy & Pharmacognosy Research (article, 2023-07-01)
Field: Chemistry — Organic Chemistry

Virtual screening of anticancer activity of chalcones and pyrazolines as potential EGFR, VEGFR, and cytochrome P450 inhibitors Context: Metastatic breast cancer is still categorized as an incurable disease because all available therapies are palliative treatments to relieve symptoms and increase life expectancy. Our previous study showed that N-pyrazoline-derived compounds have the potential as an antiproliferative drug in cervical cancer cells line. Therefore, virtual screening is conducted in this study to predict the anticancer potential of several molecules (chalcone and pyrazoline derivatives) against breast cancer cells before in vitro testing. Aims: To screen potential anticancer compounds of chalcone and pyrazoline derivatives through in silico approach. Methods: In this study were carried out multiple virtual screening steps to predict drug-likeness, pharmacokinetic, toxicity, and interactions between drug candidates and receptors involved cell in proliferation (EGFR, PDB.id 7LGS), angiogenesis (VEGFR1, PDB.id 3HNG; VEGFR2, PDB.id 4AG8), and oxidative stress (cytochrome P450, PDB.id 3UA1). Results: Results revealed that pyrazolines A, A1, A2, B, C2, D, and M could potentially be anticancer agents since the molecules qualify Lipinski’s rule, are predicted to have good pharmacokinetics, are indicated as harmless, and exhibit the best binding affinity based on molecular docking analysis. Conclusions: The EGFR appears to be the main pathway targeted by pyrazoline derivates. Meanwhile, the ligand will go through the VEGFR1, VEGFR2, or P450 pathways when it successfully overcomes the binding obstacle. In addition, pyrazolines A, A1, A2, B, C2, D, and M need to be synthesized and evaluated the in vitro and in vivo anticancer activity. Chalcone ; Protein Data Bank (RCSB PDB) ; Virtual screening ; Pharmacology ; In silico ; Chemistry ; Docking (animal) ; Lipinski's rule of five ; Cancer research ; Drug discovery ; Biochemistry ; Medicine ; Stereochemistry Synthesis and biological activity ; Computational Drug Discovery Methods ; Click Chemistry and Applications
Authors: Alessandro Pontefisso | Michele Zappalorto
Source: Materials (article, 2023-07-12)
Field: Materials Science — Materials Chemistry

Percolation in Carbon Nanotube-Reinforced Polymers for Strain-Sensing Applications: Computational Investigation on Carbon Nanotube Distribution, Curvature, and Aggregation The present article investigates the possibility of simulating the electrical conductivity of carbon nanotube-reinforced polymer composites by numerical methods. Periodic representative volume elements are generated by randomly distributing perfectly conductive reinforcements in an insulating matrix and are used to assemble an electrical network representative of the nanocomposite, where the nanotube-nanotube contacts are considered equivalent resistors modeled by means of Simmons' equation. A comparison of the results with experimental data from the literature supports the conclusion that a random distribution of reinforcements is not suitable for simulating this class of materials since percolation thresholds and conductivity trends are different, with experimental percolation taking place before the expectations. Including nanotube curvature does not solve the issue, since it hinders percolation even further. In agreement with experimental observations, the investigation suggests that a suitable approach requires the inclusion of aggregation during the volume element generation to reduce the volume fraction required to reach percolation. Some solutions available in the literature to generate properly representative volume elements are thus listed. Concerning strain sensing, the results suggest that representative volume elements generated with random distributions overestimate the strain sensitivity of the actual composites. Carbon nanotube ; Percolation (cognitive psychology) ; Materials science ; Percolation threshold ; Nanotube ; Nanocomposite ; Curvature ; Composite material ; Percolation theory ; Representative elementary volume ; Volume fraction ; Conductivity ; Resistor ; Electrical conductor ; Electrical resistivity and conductivity ; Mathematics ; Physics ; Microstructure ; Geometry Carbon Nanotubes in Composites ; Smart Materials for Construction ; Graphene research and applications
Authors: Yeliz Durgun
Source: Uluslararası mühendislik araştırma ve geliştirme dergisi (article, 2023-12-23)
Field: Chemistry — Analytical Chemistry

Classification of Starch Adulteration in Milk Using Spectroscopic Data and Machine Learning In this comprehensive research, an in-depth evaluation of several machine learning algorithms, including Multilayer Perceptron, IBk, KStar, M5Rules, and RandomForest, is conducted to ascertain their effectiveness in detecting adulteration in milk products using spectroscopic data. The algorithms were rigorously deployed and assessed through a series of controlled experiments involving both raw and adulterated milk samples. Notably, IBk and KStar algorithms emerged with a perfect accuracy rate of 100% in identifying adulteration, highlighting their superior capability in this domain. Additionally, the Decision Table algorithm also performed exceptionally well, achieving a remarkable correlation coefficient of 0.9871. These promising results emphasize the undeniable potential of machine learning algorithms as reliable and precise tools for detecting adulteration in milk. Such technological interventions play a critical role in elevating the safety and quality standards of milk and milk-based products in the market. Moreover, the deployment of these advanced machine-learning techniques provides an invaluable layer of consumer protection, plays a significant role in combating widespread fraudulent practices in the milk industry, and ensures compliance with stringent food safety standards. These methodologies could be indispensable for both industry players and regulatory bodies, significantly contributing to the safeguarding of public health. Machine learning ; Computer science ; Food safety ; Artificial intelligence ; Algorithm ; Data mining ; Food science ; Chemistry Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Nouby M. Ghazaly | Ahmed N. Abdulhameed
Source: Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (review, 2023-10-18)
Field: Materials Science — Materials Chemistry

Performance and Emissions of Nanoadditives in Diesel Engine: A review Nowadays, the demand for energy and fossil fuels has widely increased as a result of the continuous growth of the population. However, the continued use of traditional fuels as the primary source of energy has resulted in various environmental challenges related to climate change and global warming. This has prompted researchers to look for more eco-friendly and sustainable fuel alternatives with a minimal amount of engine modification and emission treatment techniques. Amongst the suggested alternative fuels, biofuels, biofuel/diesel blends, and the incorporation of nanoparticles into fuels. The nanoparticle diesel additives played a vital role in increasing engine performance as well as retarding harmful emissions such as nitrogen oxides (NOx), carbon monoxide (CO), unburned hydrocarbon (UHC), and particulate matter (PM). Metal-oxides nanoadditive such as aluminum oxide (Al2O3), ceric oxide (CeO2), and titanium dioxide (TiO2) act as oxygen catalysts and promote proper mixing of fuel and air, resulting in more efficient combustion and decreased emissions. The incorporation of nanometal-based additives, including iron (Fe), copper (Cu), and aluminum (Al) accelerated the fuel evaporation rate and increased the probability of fuel ignition. Carbon-based nanoparticles such as carbon nanotubes (CNTs), graphene nanoplatelets (GNPs), and graphene oxide (GO) are promising fuel nanoadditives owing to their metal-free composition. In addition, carbon-based additives enhanced the thermal conductivity of fuel and increased active sites available for chemical reactions, which led to improved engine performance. Diesel engine ; Diesel exhaust ; Environmental science ; Automotive engineering ; Diesel fuel ; Engineering Catalytic Processes in Materials Science ; Biodiesel Production and Applications ; Vehicle emissions and performance
Authors: Maurice de Jonker | P.E.G. Leonards | M.H. Lamoree | Sicco H. Brandsma
Source: Toxics (article, 2023-01-23)
Field: Chemistry — Spectroscopy

A Rapid Screening Method for the Detection of Additives in Electronics and Plastic Consumer Products Using AP-MALDI-qTOF-MS A novel method was developed and optimized for the fast-screening analysis of additives in electronics and plastic consumer products using atmospheric pressure matrix-assisted laser desorption ionization (AP-MALDI) coupled with a high-resolution quadrupole time-of-flight (qTOF) mass spectrometer (MS). To simplify sample preparation and increase sample throughput, an innovative 48 well graphene nanoplatelets (GNP) doped AP-MALDI target plate was developed. The GNP incorporated in the target plate fulfilled the role of the MALDI matrix and, therefore, sample extracts could be directly transferred to the AP-MALDI 48 well target plate and analyzed without a subsequent matrix addition. The homogeneously dispersed and immobilized GNP target plates also provided increased signal intensity and reproducibility. Furthermore, analytical standards of various plastic additives and plastic products with known concentrations of additives were studied to assess the AP-MALDI ionization mechanisms and method capability. The analysis time was 15 s per measurement using an automated sequence. The GNP-doped target plates exhibited high desorption/ionization of low molecular weight molecules (<1000 Da) and can be used in both positive and negative ionization modes. The AP-MALDI-qTOF-MS method was applied to screen for additives in various electronics and plastic consumer products. Suspect screening was performed using a database containing 1366 compounds. A total of 56 additives including antioxidants, flame retardants, plasticizers, UV-stabilizers, and UV-filters were identified (confidence level 4). Identification of certain plastic additives in plastic children's toys may indicate that they are recycled from waste electronic and electronic equipment (WEEE). Desorption ; Mass spectrometry ; Matrix (chemical analysis) ; Sample preparation ; Plasticizer ; Electronics ; Materials science ; Chromatography ; Reproducibility ; Ionization ; Matrix-assisted laser desorption/ionization ; Analytical Chemistry (journal) ; Ambient ionization ; Chemistry ; Chemical ionization ; Composite material ; Adsorption ; Organic chemistry Mass Spectrometry Techniques and Applications ; Analytical chemistry methods development ; Effects and risks of endocrine disrupting chemicals
Authors: S.P. Bielykh | L. Lucchetti | Victor Reshetnyak
Source: Crystals (article, 2023-07-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Photoaligned Tunable Liquid Crystal Lenses with Parabolic Phase Profile We present a theoretical model of a cylindrical tunable liquid crystal lens based on the modulation of anchoring energy. The latter can be easily obtained using photoalignment techniques. The liquid crystal cell we propose exhibits strong anchoring at the top substrate and anchoring energy with a parabolic profile at the bottom substrate. The model describes the dependence of the focal length on the applied voltage and presents a theoretical study of the lens aberrations. The results obtained are of general relevance and can be used to optimize the performances of every type of liquid crystal lens with a parabolic profile. Liquid crystal ; Anchoring ; Lens (geology) ; Optics ; Materials science ; Substrate (aquarium) ; Phase (matter) ; Phase modulation ; Optoelectronics ; Modulation (music) ; Voltage ; Crystal (programming language) ; Focal length ; Physics ; Computer science ; Acoustics ; Engineering Liquid Crystal Research Advancements ; Electrowetting and Microfluidic Technologies ; Photonic Crystals and Applications
Authors: Anna Gonzàlez‐Rosell | Sami Malola | Rweetuparna Guha | Nery Arevalos | María Francisca Matus | Meghen E. Goulet | Esa Haapaniemi | Benjamin B. Katz | Tom Vosch | Jiro Kondo | Hannu Häkkinen | Stacy M. Copp
Source: ChemRxiv (preprint, 2023-02-03)
Field: Materials Science — Materials Chemistry

Chloride ligands on DNA-stabilized silver nanoclusters DNA-stabilized silver nanoclusters (AgN-DNAs) are known to have one or two DNA oligomer ligands per nanocluster. Here, we present the first evidence that AgN-DNA species can possess additional chloride ligands that lead to increased stability in biologically relevant concentrations of chloride. Mass spectrometry of five chromatographically isolated near infrared (NIR) emissive AgN-DNA species with previously reported X-ray crystal structures determines their molecular formulas to be (DNA)2[Ag16Cl2]8+. Chloride ligands can be exchanged for bromides, which redshifts the optical spectra of these emitters. Density functional theory (DFT) calculations of the 6-electron nanocluster show that the two newly identified chloride ligands were previously assigned as low-occupancy silvers by X-ray crystallography. DFT also confirms the stability of chloride in the crystallographic structure, yields qualitative agreement between computed and measured UV-vis absorption spectra, and provides interpretation of the 35Cl-nuclear magnetic resonance spectrum of the (DNA)2[Ag16Cl2]8+. A reanalysis of the X-ray crystal structure confirms that the two previously assigned low-occupancy silvers are, in fact, chlorides, yielding (DNA)2[Ag16Cl2]8+. Using the unusual stability of (DNA)2[Ag16Cl2]8+ in biologically relevant saline solutions as a possible indicator of other chloride-containing AgN-DNAs, we identified an additional AgN-DNA with chloride ligands by high-throughput screening. Inclusion of chlorides on AgN-DNAs presents a promising new route to expand the diversity of AgN-DNA structure-property relationships and to imbue these emitters with favorable stability for biophotonics applications. Nanoclusters ; Chloride ; DNA ; Chemistry ; Crystallography ; Crystal (programming language) ; Organic chemistry Nanocluster Synthesis and Applications ; Gold and Silver Nanoparticles Synthesis and Applications
Authors: Н. А. Болдырев | E. I. Sitalo | Lidia A. Shilkina | А. В. Назаренко | A. D. Ushakov | V. Ya. Shur | Л. А. Резниченко | Е. В. Глазунова
Source: Ceramics (article, 2023-08-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Structure and Relaxor Behavior of (0.5 − x)BiFeO3-0.5PbFe0.5Nb0.5O3-xPbTiO3 Ternary Ceramics Ceramics of the quasi-binary concentration section (0.1 ≤ x ≤ 0.2, Δx = 0.025) of the ternary solid solution system (0.5 − x)BiFeO3-0.5PbFe0.5Nb0.5O3-xPbTiO3 were prepared by the conventional solid-phase reaction method. An X-ray study at different temperatures revealed that (0.5 − x)BF-0.5PFN-xPT ceramics have a cluster morphology. Clusters have different modulation, crystal lattice symmetry, and chemical composition. The presence of a cluster structure in a solid solution with heterovalent substitution, consisting of regions rich in Ti+4, Nb+5, or Fe3+, has led to the appearance of Maxwell–Wagner polarization in the studied ceramics. The study of the dielectric characteristics revealed the relaxor-like behavior of the studied ceramics. The grain morphology, dielectric, pyroelectric, and piezoelectric properties of the selected solid solutions were investigated. The highest piezoelectric coefficient, d33 = 280 pC/N, was obtained in the 0.3BiFeO3-0.5PbFe0.5Nb0.5O3-0.2PbTiO3 ceramics. Study of the dielectric characteristics of all samples revealed relaxor ferroelectric behavior and a region of diffuse phase transition from the paraelectric to ferroelectric phase in the temperature range of 140–170 °C. Materials science ; Dielectric ; Solid solution ; Pyroelectricity ; Ceramic ; Ternary operation ; Piezoelectricity ; Ferroelectricity ; Phase transition ; Piezoelectric coefficient ; Polarization (electrochemistry) ; Ternary numeral system ; Crystal structure ; Phase (matter) ; Condensed matter physics ; Analytical Chemistry (journal) ; Mineralogy ; Crystallography ; Composite material ; Physical chemistry ; Metallurgy ; Chemistry ; Optoelectronics ; Physics Multiferroics and related materials ; Ferroelectric and Piezoelectric Materials ; Dielectric properties of ceramics
Authors: L. Cuadra | Sancho Salcedo‐Sanz | José Carlos Nieto Borge
Source: International Journal of Molecular Sciences (article, 2023-02-14)
Field: Materials Science — Materials Chemistry

Carrier Transport in Colloidal Quantum Dot Intermediate Band Solar Cell Materials Using Network Science Colloidal quantum dots (CQDs) have been proposed to obtain intermediate band (IB) materials. The IB solar cell can absorb sub-band-gap photons via an isolated IB within the gap, generating extra electron-hole pairs that increase the current without degrading the voltage, as has been demonstrated experimentally for real cells. In this paper, we model the electron hopping transport (HT) as a network embedded in space and energy so that a node represents the first excited electron state localized in a CQD while a link encodes the Miller-Abrahams (MA) hopping rate for the electron to hop from one node (=state) to another, forming an "electron-HT network". Similarly, we model the hole-HT system as a network so that a node encodes the first hole state localized in a CQD while a link represents the MA hopping rate for the hole to hop between nodes, leading to a "hole-HT network". The associated network Laplacian matrices allow for studying carrier dynamics in both networks. Our simulations suggest that reducing both the carrier effective mass in the ligand and the inter-dot distance increases HT efficiency. We have found a design constraint: It is necessary for the average barrier height to be larger than the energetic disorder to not degrade intra-band absorption. Solar cell ; Multiple exciton generation ; Quantum dot ; Colloid ; Optoelectronics ; Materials science ; Nanotechnology ; Physics ; Chemistry ; Physical chemistry Quantum Dots Synthesis And Properties ; Electrochemical Analysis and Applications ; Electrochemical sensors and biosensors