jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xiaowei Mo | Zeyu Zhang | Jinyan Song | Yushi Wang | Zhilin Yu
Source: Journal of Materials Chemistry B (review, 2024-01-01)
Field: Materials Science — Biomaterials

Self-assembly of peptides in living cells for disease theranostics The past few decades have witnessed substantial progress in biomedical materials for addressing health concerns and improving disease therapeutic and diagnostic efficacy. Conventional biomedical materials are typically created through an <i>ex vivo</i> approach and are usually utilized under physiological environments <i>via</i> transfer from preparative media. This transfer potentially gives rise to challenges for the efficient preservation of the bioactivity and implementation of theranostic goals on site. To overcome these issues, the <i>in situ</i> synthesis of biomedical materials on site has attracted great attention in the past few years. Peptides, which exhibit remarkable biocompability and reliable noncovalent interactions, can be tailored <i>via</i> tunable assembly to precisely create biomedical materials. In this review, we summarize the progress in the self-assembly of peptides in living cells for disease diagnosis and therapy. After a brief introduction to the basic design principles of peptide assembly systems in living cells, the applications of peptide assemblies for bioimaging and disease treatment are highlighted. The challenges in the field of peptide self-assembly in living cells and the prospects for novel peptide assembly systems towards next-generation biomaterials are also discussed, which will hopefully help elucidate the great potential of peptide assembly in living cells for future healthcare applications. Biocompatible material ; Nanotechnology ; Chemistry ; Biophysics ; Materials science ; Medicine ; Biology ; Biomedical engineering Supramolecular Self-Assembly in Materials ; Advanced biosensing and bioanalysis techniques ; Nanoplatforms for cancer theranostics
Authors: Abderrahmane Aït‐Kaddour | M. Loudiyi | Oumayma Boukria | Jasur Safarov | Shakhnoza Sultanova | Donato Andueza | Anne Listrat | Yana Cahyana
Source: Meat Science (article, 2024-05-07)
Field: Chemistry — Analytical Chemistry

Beef muscle discrimination based on two-trace two-dimensional correlation spectroscopy (2T2D COS) combined with snapshot visible-near infrared multispectral imaging The purpose of this work was to assess the potential of 2T2D COS PLS-DA (two-trace two-dimensional correlation spectroscopy and partial least squares discriminant analysis) in conjunction with Visible Near infrared multispectral imaging (MSI) as a quick, non-destructive, and precise technique for classifying three beef muscles -Longissimus thoracis, Semimembranosus, and Biceps femoris- obtained from three breeds - the Blonde d'Aquitaine, Limousine, and Aberdeen Angus. The experiment was performed on 240 muscle samples. Before performing PLS-DA, spectra were extracted from MSI images and processed by SNV (Standard Normal Variate), MSC (Multivariate Scattering Correction) or AREA (area under curve equal 1) and converted in synchronous and asynchronous 2T2D COS maps. The results of the study highlighted that combining synchronous and asynchronous 2T2D COS maps before performing PLS-DA was the best strategy to discriminate between the three muscles (100% of classification accuracy and 0% of error). Longissimus Thoracis ; Multispectral image ; Partial least squares regression ; Linear discriminant analysis ; Artificial intelligence ; Spectroscopy ; Medius ; Pattern recognition (psychology) ; Near-infrared spectroscopy ; Computer science ; Mathematics ; Chemistry ; Optics ; Biology ; Anatomy ; Statistics ; Physics Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Tomas L. Roldan | Shike Li | Christophe Guillon | Ned D. Heindel | Jeffrey D. Laskin | In Heon Lee | Dayuan Gao | Patrick J. Sinko
Source: Pharmaceutics (article, 2024-03-27)
Field: Chemistry — Organic Chemistry

Optimizing Nanosuspension Drug Release and Wound Healing Using a Design of Experiments Approach: Improving the Drug Delivery Potential of NDH-4338 for Treating Chemical Burns NDH-4338 is a highly lipophilic prodrug comprising indomethacin and an acetylcholinesterase inhibitor. A design of experiments approach was used to synthesize, characterize, and evaluate the wound healing efficacy of optimized NDH-4338 nanosuspensions against nitrogen mustard-induced skin injury. Nanosuspensions were prepared by sonoprecipitation in the presence of a Vitamin E TPGS aqueous stabilizer solution. Critical processing parameters and material attributes were optimized to reduce particle size and determine the effect on dissolution rate and burn healing efficacy. The antisolvent/solvent ratio (A/S), dose concentration (DC), and drug/stabilizer ratio (D/S) were the critical sonoprecipitation factors that control particle size. These factors were subjected to a Box-Behnken design and response surface analysis, and model quality was assessed. Maximize desirability and simulation experiment optimization approaches were used to determine nanosuspension parameters with the smallest size and the lowest defect rate within the 10-50 nm specification limits. Optimized and unoptimized nanosuspensions were prepared and characterized. An established depilatory double-disc mouse model was used to evaluate the healing of nitrogen mustard-induced dermal injuries. Optimized nanosuspensions (A/S = 6.2, DC = 2% <i>w</i>/<i>v</i>, D/S = 2.8) achieved a particle size of 31.46 nm with a narrow size range (PDI = 0.110) and a reduced defect rate (42.2 to 6.1%). The optimized nanosuspensions were stable and re-dispersible, and they showed a ~45% increase in cumulative drug release and significant edema reduction in mice. Optimized NDH-4338 nanosuspensions were smaller with more uniform sizes that led to improved physical stability, faster dissolution, and enhanced burn healing efficacy compared to unoptimized nanosuspensions. Drug delivery ; Drug ; Medicine ; Pharmacology ; Wound healing ; Intensive care medicine ; Nanotechnology ; Surgery ; Materials science Antimicrobial agents and applications ; Hydrogels: synthesis, properties, applications ; Wound Healing and Treatments
Authors: Khadiga M. Kelani | Maha M. Ibrahim | Nesreen Khamis Ramadan | Eman S. Elzanfaly | Sherif M. Eid
Source: BMC Chemistry (article, 2024-03-23)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Comparing silver and gold nanoislands’ surface plasmon resonance for bisacodyl and its metabolite quantification in human plasma Gold and silver nanoparticles have witnessed increased scientific interest due to their colourful colloidal solutions and exceptional applications. Comparing the localized surface plasmon resonance (LSPR) of gold and silver nanoparticles is crucial for understanding and optimizing their optical properties. This comparison informs the design of highly sensitive plasmonic sensors, aids in selecting the most suitable nanoparticles for applications like surface-enhanced infrared spectroscopy (SEIRA) and biomedical imaging, and guides the choice between gold and silver nanoparticles based on their catalytic and photothermal properties. Ultimately, the study of LSPR facilitates the tailored use of these nanoparticles in diverse scientific and technological applications. Two SEIRA methods combined with partial least squares regression (PLSR) chemometric tools were developed. This development is based on the synthesis of homogeneous, high-dense deposited metal nanoparticle islands over the surface of glass substrates to be used as lab-on-chip SEIRA sensors for the determination of bisacodyl (BIS) and its active metabolite in plasma. SEM micrographs revealed the formation of metallic islands of colloidal citrate-capped gold and silver nanoparticles of average sizes of 29.7 and 15 nm, respectively. BIS and its active metabolite were placed on the nanoparticles' coated substrates to be directly measured, then PLSR chemometric modelling was used for the quantitative determinations. Plasmonic citrate-capped gold nanoparticle substrates showed better performance than those prepared using citrate-capped silver nanoparticles in terms of preparation time, enhancement factor, PLSR model prediction, and quantitative results. This study offers a way to determine BIS and its active metabolite in the concentration range 15-240 ng/mL in human plasma using inexpensive disposable glass-coated substrates that can be prepared in 1 h to get results in seconds with good recovery between 98.77 and 100.64%. The sensors provided fast, simple, selective, molecular-specific and inexpensive procedures to determine molecules in their pure form and biological fluid. Surface plasmon resonance ; Silver nanoparticle ; Colloidal gold ; Nanoparticle ; Materials science ; Nanotechnology ; Photothermal therapy ; Plasmon ; Bisacodyl ; Spectroscopy ; Metabolite ; Chemistry ; Optoelectronics Gold and Silver Nanoparticles Synthesis and Applications ; Protein Interaction Studies and Fluorescence Analysis ; Biosensors and Analytical Detection
Authors: Alex Aubert | Konstantin Skokov | Andreï Rogalev | I. М. Chirkova | Benedikt Beckmann | Fernando Maccari | Elvina Dilmieva | Fabrice Wilhelm | Vivian Nassif | L.V.B. Diop | Enrico Bruder | Julia Löfstrand | Daniel Primetzhofer | Martin Sahlberg | Esmaeil Adabifiroozjaei | Leopoldo Molina‐Luna | Gabriel Gomez | Benedikt Eggert | Katharina Ollefs | Heiko Wende | Oliver Gutfleisch
Source: ACS Applied Materials & Interfaces (article, 2024-10-29)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Residual Ferromagnetic Regions Affecting the First-Order Phase Transition in Off-Stoichiometric Fe–Rh Among the magnetocaloric materials featuring first-order phase transitions (FOPT), FeRh is considered as a reference system to study the FOPT because it is a "simple" binary system with a CsCl structure exhibiting a large adiabatic temperature change. Recently, ab initio theory predicted that changes in the Fe/Rh stoichiometry in the vicinity of equiatomic composition strongly influence the FOPT characteristics. However, this theoretical prediction was not clearly verified experimentally. Here, we investigated the composition dependence of the transitional hysteresis in FeRh. It is shown that a Fe excess of only 1 at. % induces a ferromagnetic state in the whole temperature range (from 5 K up to <i>T</i><sub>c</sub>) for a minor portion of the sample (≈10%), while 5 at. % is enough to completely eliminate the FOPT. Element-specific X-ray magnetic circular dichroism (XMCD) measurements suggest that this ferromagnetic contribution arises from residual FeRh ferromagnetic regions. We attribute the formation of such domains to Fe antisite defects, as Mössbauer spectroscopy demonstrates the presence of Fe atoms located at the 1b (Rh) sites in the CsCl-type structure. As a consequence, compared with the equiatomic composition, the slightly Fe-rich sample exhibits completely different FOPT properties, influencing the magnetocaloric performances. Thus, our study sheds light on the origin of the remarkable stoichiometric sensitivity of the FOPT behavior in FeRh. These insights have broader implications for understanding FOPT dynamics and the role of residual ferromagnetic domains. Magnetic refrigeration ; Materials science ; Ferromagnetism ; Stoichiometry ; Condensed matter physics ; Phase (matter) ; Phase transition ; Analytical Chemistry (journal) ; Magnetization ; Magnetic field ; Physical chemistry ; Chemistry ; Physics Magnetic and transport properties of perovskites and related materials ; Shape Memory Alloy Transformations ; Magnetic Properties of Alloys
Authors: Thijs Stuyver
Source: Journal of Computational Chemistry (article, 2024-06-08)
Field: Materials Science — Materials Chemistry

TS‐tools: Rapid and automated localization of transition states based on a textual reaction SMILES input Here, TS-tools is presented, a Python package facilitating the automated localization of transition states (TS) based on a textual reaction SMILES input. TS searches can either be performed at xTB or DFT level of theory, with the former yielding guesses at marginal computational cost, and the latter directly yielding accurate structures at greater expense. On a benchmarking dataset of mono- and bimolecular reactions, TS-tools reaches an excellent success rate of 95% already at xTB level of theory. For tri- and multimolecular reaction pathways - which are typically not benchmarked when developing new automated TS search approaches, yet are relevant for various types of reactivity, cf. solvent- and autocatalysis and enzymatic reactivity - TS-tools retains its ability to identify TS geometries, though a DFT treatment becomes essential in many cases. Throughout the presented applications, a particular emphasis is placed on solvation-induced mechanistic changes, another issue that received limited attention in the automated TS search literature so far. Computer science ; Python (programming language) ; Benchmarking ; Reactivity (psychology) ; Solvation ; Transition state ; Computational chemistry ; Counterintuitive ; Chemistry ; Autocatalysis ; Combinatorial chemistry ; Solvent ; Catalysis ; Physics ; Organic chemistry ; Programming language ; Quantum mechanics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemical Synthesis and Analysis
Authors: Mátyás Lukács | Flóra Vitális | A Bárdŏs | Judit Tormási | Krzysztof B. Beć | Justyna Grabska | Zoltán Gillay | Rita Tömösközi‐Farkas | László Abrankó | Donatella Albanese | Francesca Malvano | Christian W. Huck | Zoltán Kovács
Source: Foods (article, 2024-12-23)
Field: Chemistry — Analytical Chemistry

Comparison of Multiple NIR Instruments for the Quantitative Evaluation of Grape Seed and Other Polyphenolic Extracts with High Chemical Similarities Grape seed extract (GSE), one of the world's bestselling dietary supplements, is prone to frequent adulteration with chemically similar compounds. These frauds can go unnoticed within the supply chain due to the use of unspecific standard analytical methods for quality control. This research aims to develop a near-infrared spectroscopy (NIRS) method for the rapid and non-destructive quantitative evaluation of GSE powder in the presence of multiple additives. Samples were prepared by mixing GSE with pine bark extract (PBE) and green tea extract (GTE) on different levels between 0.5 and 13% in singular and dual combinations. Measurements were performed with a desktop and three different handheld devices for performance comparison. Following spectral pretreatment, partial least squares regression (PLSR) and support vector regression (SVR)-based quantitative models were built to predict extract concentrations and various chemical parameters. Cross- and external-validated models could reach a minimum <i>R</i><sup>2</sup><sub>p</sub> value of 0.99 and maximum RMSEP of 0.27% for the prediction of extract concentrations using benchtop data, while models based on handheld data could reach comparably good results, especially for GTE, caffeic acid and procyanidin content prediction. This research shows the potential applicability of NIRS coupled with chemometrics as an alternate, rapid and accurate quality evaluation tool for GSE-based supplement mixtures. Grape seed extract ; Partial least squares regression ; Chemometrics ; Caffeic acid ; Grape seed ; Polyphenol ; Proanthocyanidin ; Food science ; Chemistry ; Near-infrared spectroscopy ; Mathematics ; Chromatography ; Statistics ; Biology ; Antioxidant ; Medicine Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Hend M. Nagieb | Nada S. Abdelwahab | Maha M. Abdelrahman | Hala E. Zaazaa | Nermine S. Ghoniem
Source: BMC Chemistry (article, 2024-01-22)
Field: Chemistry — Analytical Chemistry

AQbD TLC-densitometric method approach along with green fingerprint and whiteness assessment for quantifying two combined antihypertensive agents and their impurities Preserving the environment, reducing the amount of waste resulting from chemical trials, and reducing the amount of energy consumed have currently become a pivotal global trend. An analytical quality by design (AQbD) based eco-friendly TLC-densitometric method was implemented for quantifying two antihypertensive agents, captopril (CPL) and hydrochlorothiazide (HCZ), along with their impurities; captopril disulphide (CDS), chlorothiazide (CTZ) and salamide (SMD). The analytical target profile (ATP) was first identified, followed by selecting the critical analytical attributes (CAAs), such as retardation factors and resolution between the separated peaks. Critical method parameters (CMPs) that may have a crucial influence on CAAs were identified and emanated through the quality risk assessment phase. A literature survey-based preliminary studies were performed, followed by optimization of the selected CMPs through a custom experimental design to attain the highest resolution with optimum retardation factors. Moreover, method robustness was also tested by testing the design space. Complete separation of the drugs and their impurities was achieved using ethyl acetate: glacial acetic acid (6: 0.6, v/v) as a developing system applied to a 12 cm length TLC plate at room temperature with UV scanning at 215 nm. Calibration graphs were found to be linear in the ranges of (0.70-6.00), (0.10-2.00), (0.20-1.00), (0.07-1.50) and (0.05-1.00) µg/band corresponding to CPL, HCZ, CDS, CTZ, and SMD, respectively. Four different green metric tools were used to evaluate the greenness profile of the proposed method, and results showed that it is greener than the reported HPLC method. Method whiteness assessment was also conducted. Moreover, the method performance was evaluated following the ICH guidelines, and the outcomes fell within the acceptable limits. The developed method could be approved for routine assay of the cited components in their pharmaceutical formulations and bulk powder without interference from the reported impurities. The issue of concern is saving money, especially in developing countries. Fingerprint (computing) ; Chromatography ; Impurity ; Medicine ; Traditional medicine ; Chemistry ; Artificial intelligence ; Computer science ; Organic chemistry Analytical Methods in Pharmaceuticals ; Analytical Chemistry and Chromatography ; Computational Drug Discovery Methods
Authors: Jos Ruizendaal | G. Polder | Gert Kootstra
Source: Biosystems Engineering (article, 2024-04-27)
Field: Chemistry — Analytical Chemistry

Automated and non-destructive estimation of soluble solid content of tomatoes on the plant under variable light conditions In this study, a method is proposed to deal with the variable light conditions in a greenhouse to non-destructively predict the soluble solid content (SSC) of tomatoes on the plant. It was investigated how well the SSC – measured as °Brix – of tomatoes could be predicted based on spectral data in the range of 470–900 nm, where data acquired in situ (in the greenhouse) was compared to post-harvest data captured under controlled laboratory conditions. To deal with the variation in illumination in the greenhouse, a dynamic-calibration method is proposed, using a grey reference in the image. Ground-truth SSC data of the tomatoes was acquired using a refractometer. Data was collected of three different types of truss tomatoes with a wide range of SSC. Different PLS regression models were then trained on the spectral data in relation to the refractometer values. Trained and tested on all types, the in situ measurements showed a predicted coefficient of determination on the test set, Q2, of 0.95 with a Root Mean Squared Error of Prediction (RMSEP) of 0.29 °Brix using the dynamic calibration, and a Q2 of 0.93 with RMSEP of 0.35 °Brix without using the dynamic-calibration method. The post-harvest measurements resulted in a Q2 of 0.95 with RMSEP of 0.31 °Brix. The results show that spectral imaging using dynamic calibration is applicable for in situ non-destructive prediction of SSC. This method enables high-throughput and non-destructive quality estimation of fruits on the plant in commercial greenhouse conditions. Variable (mathematics) ; Estimation ; Content (measure theory) ; Environmental science ; Process engineering ; Computer science ; Biological system ; Engineering ; Mathematics ; Biology ; Systems engineering Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Leaf Properties and Growth Measurement
Authors: Xinjing Dou | Katharina N ́Diaye | Said El Harkaoui | Ina Willenberg | Fei Ma | Liangxiao Zhang | Peiwu Li | Bertrand Matthäus
Source: European Journal of Lipid Science and Technology (article, 2024-12-22)
Field: Chemistry — Organic Chemistry

Authentication of Virgin Olive Oil Based on Untargeted Metabolomics and Chemical Markers ABSTRACT Virgin extra olive oil as a high‐value edible oil is a potential object of adulteration. Refined camellia oil (RCO) could be one of the most challenging potential adulterants of olive oil to detect due to its high similarity in the fatty acid composition. In this study, an untargeted metabolomics strategy based on data from ultra‐performance liquid chromatography‐electrospray ionization‐quadrupole‐time of flight (UPLC‐ESI‐qTOF) measurements combined with statistical methods was applied to identify the unauthorized addition of RCO to extra virgin olive oil (EVOO). Untargeted fingerprints of the olive oil and RCO could be classified into two groups via unsupervised principal component analysis (PCA) that shows the significant difference of the fingerprints of polar components extracted from olive oil and CAOs, respectively. Orthogonal partial least squares‐discriminant analysis (OPLS‐DA) and volcano plots were used to identify markers with significant difference between these two oils. The results show that 927 and 780 features (positive and negative ESI modes), respectively, were higher regulated in virgin extra olive oil, whereas 439 and 479 features, respectively, were higher regulated in RCO. From these features, 28 markers for olive oil and 7 markers for CAO were tentatively identified. Further adulteration experiments showed that virgin extra olive oil containing more than 15% RCO could be distinguished from the olive oil by this untargeted UPLC‐ESI‐qTOF measurement, followed by unsupervised PCA. Furthermore, camelliagenin A (519.3695/12.22, [M + FA − H] − ) could still be detected when EVOOs were mixed with at least 5% CAO. Olive oil ; Chemistry ; Principal component analysis ; Food science ; Chromatography ; Metabolomics ; Electrospray ionization ; Mass spectrometry ; Mathematics Edible Oils Quality and Analysis ; Metabolomics and Mass Spectrometry Studies ; Spectroscopy and Chemometric Analyses