jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mikiya Doi | Yoshihiro Nakao | Takuro Tanaka | Masami Sako | Masayuki Ohzeki
Source: Frontiers in Computer Science (article, 2023-12-12)
Field: Materials Science — Materials Chemistry

Exploration of new chemical materials using black-box optimization with the D-wave quantum annealer In materials informatics, searching for chemical materials with desired properties is challenging due to the vastness of the chemical space. Moreover, the high cost of evaluating properties necessitates a search with a few clues. In practice, there is also a demand for proposing compositions that are easily synthesizable. In the real world, such as in the exploration of chemical materials, it is common to encounter problems targeting black-box objective functions where formalizing the objective function in explicit form is challenging, and the evaluation cost is high. In recent research, a Bayesian optimization method has been proposed to formulate the quadratic unconstrained binary optimization (QUBO) problem as a surrogate model for black-box objective functions with discrete variables. Regarding this method, studies have been conducted using the D-Wave quantum annealer to optimize the acquisition function, which is based on the surrogate model and determines the next exploration point for the black-box objective function. In this paper, we address optimizing a black-box objective function containing discrete variables in the context of actual chemical material exploration. In this optimization problem, we demonstrate results obtaining parameters of the acquisition function by sampling from a probability distribution with variance can explore the solution space more extensively than in the case of no variance. As a result, we found combinations of substituents in compositions with the desired properties, which could only be discovered when we set an appropriate variance. Black box ; Bayesian optimization ; Quadratic unconstrained binary optimization ; Computer science ; Context (archaeology) ; Mathematical optimization ; Function (biology) ; Variance (accounting) ; Set (abstract data type) ; Algorithm ; Mathematics ; Machine learning ; Quantum ; Quantum computer ; Artificial intelligence Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Quantum Computing Algorithms and Architecture
Authors: Konstantin Rusakov | S. Demianiuk | Ewelina Jalonicka | P Hańczyc
Source: ACS Applied Optical Materials (article, 2023-10-05)
Field: Chemistry — Physical and Theoretical Chemistry

Cavity Lasing Characteristics of Thioflavin T and Thioflavin X in Different Solvents and Their Interaction with DNA for the Controlled Reduction of a Light Amplification Threshold in Solid-State Biofilms The lasing characteristics of Thioflavin T (ThT) and Thioflavin X (ThX) dyes were investigated in solvents with increasing viscosity: water, ethanol, butanol, ethylene glycol, and glycerol and three forms of DNA (double-helix natural, fragmented, and aggregated). The results identified that lasing thresholds and photostability depend on three critical factors: the solvation shell surrounding dye molecules, the organization of their dipole moments, which is driven by the DNA structure, and the molecules diffusion coefficient in the excitation focal spot. The research highlights that dye doped to DNA accumulated in binding sites fosters long-range dye orientation, facilitating a marked reduction of lasing thresholds in the liquid phase as well as amplified spontaneous emission (ASE) thresholds in the solid state. Leveraging insights from lasing characteristics obtained in liquid, ASE in the solid state was optimized in a controlled way by changing the parameters influencing the DNA structure, i.e., magnesium salt addition, heating, and sonication. The modifications led to a large decrease in the ASE thresholds in the dye-doped DNA films. It was shown that the examination of lasing in cavities can be useful for preparing optical materials with improved architectures and functionalities for solid-state lasers. Lasing threshold ; Thioflavin ; Dye laser ; Solvation ; Materials science ; Molecule ; Chemistry ; Photochemistry ; Laser ; Optoelectronics ; Optics ; Organic chemistry Photochemistry and Electron Transfer Studies ; Photoreceptor and optogenetics research ; Plant and animal studies
Authors: Martin Rusilowicz | David W. Newman | Declan R. Creamer | James R. Johnson | Kareena Adair | Victoria M. Harman | Chris M. Grant | Robert J. Beynon | Simon J. Hubbard
Source: Journal of Proteome Research (article, 2023-01-23)
Field: Chemistry — Spectroscopy

AlacatDesigner─Computational Design of Peptide Concatamers for Protein Quantitation Protein quantitation via mass spectrometry relies on peptide proxies for the parent protein from which abundances are estimated. Owing to the variability in signal from individual peptides, accurate absolute quantitation usually relies on the addition of an external standard. Typically, this involves stable isotope-labeled peptides, delivered singly or as a concatenated recombinant protein. Consequently, the selection of the most appropriate surrogate peptides and the attendant design in recombinant proteins termed QconCATs are challenges for proteome science. QconCATs can now be built in a "a-la-carte" assembly method using synthetic biology: ALACATs. To assist their design, we present "AlacatDesigner", a tool that supports the peptide selection for recombinant protein standards based on the user's target protein. The user-customizable tool considers existing databases, occurrence in the literature, potential post-translational modifications, predicted miscleavage, predicted divergence of the peptide and protein quantifications, and ionization potential within the mass spectrometer. We show that peptide selections are enriched for good proteotypic and quantotypic candidates compared to empirical data. The software is freely available to use either via a web interface AlacatDesigner, downloaded as a Desktop application or imported as a Python package for the command line interface or in scripts. Peptide ; Python (programming language) ; Proteome ; Mass spectrometry ; Computational biology ; Recombinant DNA ; Computer science ; Database ; Chemistry ; Data mining ; Biology ; Bioinformatics ; Biochemistry ; Chromatography ; Programming language Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; RNA and protein synthesis mechanisms
Authors: Yawen Liu | Yushu Li | Qiyue Wang | Jing Ren | Chao Ye | Fangyuan Li | Shengjie Ling | Yilun Liu | Daishun Ling
Source: Advanced Science (article, 2023-08-18)
Field: Materials Science — Biomaterials

Biomimetic Silk Architectures Outperform Animal Horns in Strength and Toughness Structural biomimicry is an intelligent approach for developing lightweight, strong, and tough materials (LSTMs). Current fabrication technologies, such as 3D printing and two-photon lithography often face challenges in constructing complex interlaced structures, such as the sinusoidal crossed herringbone structure that contributes to the ultrahigh strength and fracture toughness of the dactyl club of peacock mantis shrimps. Herein, bioinspired LSTMs with laminated or herringbone structures is reported, by combining textile processing and silk fiber "welding" techniques. The resulting biomimetic silk LSTMs (BS-LSTMs) exhibit a remarkable combination of lightweight with a density of 0.6-0.9 g cm<sup>-3</sup> , while also being 1.5 times stronger and 16 times more durable than animal horns. These findings demonstrate that BS-LSTMs are among the toughest natural materials made from silk proteins. Finite element simulations further reveal that the fortification and hardening of BS-LSTMs arise primarily from the hierarchical organization of silk fibers and mechanically transferable meso-interfaces. This study highlights the rational, cost-effective, controllable mesostructure, and transferable strategy of integrating textile processing and fiber "welding" techniques for the fabrication of BS-LSTMs with advantageous structural and mechanical properties. These findings have significant implications for a wide range of applications in biomedicine, mechanical engineering, intelligent textiles, aerospace industries, and beyond. SILK ; Biomimetics ; Materials science ; Toughness ; Textile ; Computer science ; Welding ; 3D printing ; Fabrication ; Nanotechnology ; Lithography ; Composite material Silk-based biomaterials and applications ; Advanced Materials and Mechanics ; Advanced Sensor and Energy Harvesting Materials
Authors: Jun‐qin Qiao | Xiaolan Liu | Chao Liang | Ju Wang | Hong‐zhen Lian | Li Mao
Source: Molecules (article, 2023-02-28)
Field: Chemistry — Spectroscopy

Prediction of the n-Octanol/Water Partition Coefficients of Basic Compounds Using Multi-Parameter QSRR Models Based on IS-RPLC Retention Behavior in a Wide pH Range The <i>n</i>-octanol-water partition coefficient (log<i>P</i>) is an important physicochemical parameter which describes the behavior of organic compounds. In this work, the apparent <i>n</i>-octanol/water partition coefficients (log<i>D</i>) of basic compounds were determined using ion-suppression reversed-phase liquid chromatography (IS-RPLC) on a silica-based C18 column. The quantitative structure-retention relationship (QSRR) models between log<i>D</i> and log<i>k</i><sub>w</sub> (logarithm of retention factor corresponding to 100% aqueous fraction of mobile phase) were established at pH 7.0-10.0. It was found that log<i>D</i> had a poor linear correlation with log<i>k</i><sub>w</sub> at pH 7.0 and pH 8.0 when strongly ionized compounds were included in the model compounds. However, the linearity of the QSRR model was significantly improved, especially at pH 7.0, when molecular structure parameters such as electrostatic charge <i>n</i><sub>e</sub> and hydrogen bonding parameters A and B were introduced. External validation experiments further confirmed that the multi-parameter models could accurately predict the log<i>D</i> value of basic compounds not only under strong alkaline conditions, but also under weak alkaline and even neutral conditions. The log<i>D</i> values of basic sample compounds were predicted based on the multi-parameter QSRR models. Compared with previous work, the findings of this study extended the pH range for the determination of the log<i>D</i> values of basic compounds, providing an optional mild pH for IS-RPLC experiments. Chemistry ; Partition coefficient ; Octanol ; Chromatography ; Aqueous solution ; Capacity factor ; Reversed-phase chromatography ; Analytical Chemistry (journal) ; High-performance liquid chromatography ; Organic chemistry Analytical Chemistry and Chromatography ; Chromatography in Natural Products ; Chemical and Physical Properties in Aqueous Solutions
Authors: Oliver M. Crook | Nathan Gittens | Chun‐wa Chung | Charlotte M. Deane
Source: Journal of Proteome Research (article, 2023-08-15)
Field: Chemistry — Spectroscopy

A Functional Bayesian Model for Hydrogen–Deuterium Exchange Mass Spectrometry Proteins often undergo structural perturbations upon binding to other proteins or ligands or when they are subjected to environmental changes. Hydrogen-deuterium exchange mass spectrometry (HDX-MS) can be used to explore conformational changes in proteins by examining differences in the rate of deuterium incorporation in different contexts. To determine deuterium incorporation rates, HDX-MS measurements are typically made over a time course. Recently introduced methods show that incorporating the temporal dimension into the statistical analysis improves power and interpretation. However, these approaches have technical assumptions that hinder their flexibility. Here, we propose a more flexible methodology by reframing these methods in a Bayesian framework. Our proposed framework has improved algorithmic stability, allows us to perform uncertainty quantification, and can calculate statistical quantities that are inaccessible to other approaches. We demonstrate the general applicability of the method by showing it can perform rigorous model selection on a spike-in HDX-MS experiment, improved interpretation in an epitope mapping experiment, and increased sensitivity in a small molecule case-study. Bayesian analysis of an HDX experiment with an antibody dimer bound to an E3 ubiquitin ligase identifies at least two interaction interfaces where previous methods obtained confounding results due to the complexities of conformational changes on binding. Our findings are consistent with the cocrystal structure of these proteins, demonstrating a bayesian approach can identify important binding epitopes from HDX data. We also generate HDX-MS data of the bromodomain-containing protein BRD4 in complex with GSK1210151A to demonstrate the increased sensitivity of adopting a Bayesian approach. Mass spectrometry ; Hydrogen–deuterium exchange ; Deuterium ; Chemistry ; Bayesian probability ; Hydrogen ; Computer science ; Physics ; Chromatography ; Nuclear physics ; Artificial intelligence Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography ; DNA and Nucleic Acid Chemistry
Authors: Romy Cools | Kobe Kerkhofs | Renan C.F. Leitao | Guy Bormans
Source: Seminars in Nuclear Medicine (review, 2023-05-05)
Field: Chemistry — Organic Chemistry

Preclinical Evaluation of Novel PET Probes for Dementia Medicine ; Dementia ; Pet imaging ; Preclinical research ; Neuroscience ; Positron emission tomography ; Bioinformatics ; Medical physics ; Pathology ; Nuclear medicine ; Disease ; Biology Click Chemistry and Applications ; Neuroscience and Neuropharmacology Research ; Computational Drug Discovery Methods
Authors: Jingjing Zhang | Luya Li | Jintuo Yin | Xidong Zhang | Ying Zheng | Rui Feng
Source: BMC Pharmacology and Toxicology (article, 2023-03-01)
Field: Materials Science — Biomaterials

Study on the thermal stability of nab-paclitaxel during hyperthermic intraperitoneal chemotherapy Overall, albumin-bound paclitaxel is relatively stable to different temperatures (25 °C, 37 °C, 41 °C, 42 °C and 43 °C). This study will lay a foundation for further studies on the albumin-bound paclitaxel during hyperthermic intraperitoneal chemotherapy. Taxane ; Paclitaxel ; Albumin ; Chemotherapy ; Human serum albumin ; Hyperthermic intraperitoneal chemotherapy ; Medicine ; Serum albumin ; Pharmacology ; Hyperthermia ; In vitro ; Chemistry ; Internal medicine ; Chromatography ; Cancer ; Biochemistry ; Cytoreductive surgery ; Ovarian cancer Nanoparticle-Based Drug Delivery ; Intraperitoneal and Appendiceal Malignancies ; Hepatocellular Carcinoma Treatment and Prognosis
Authors: Krishnaja Tikkisetty | Taylor Filewood | Jeffrey Yan | Honoria Kwok | Pamela Brunswick | Robert B. Cody | Dayue Shang
Source: Analytical Methods (article, 2023-01-01)
Field: Chemistry — Spectroscopy

Method development for forensic oil identification by direct analysis in real time time-of-flight mass spectrometry The current well-established chromatography and mass spectrometry based oil spill identification procedures, such as those outlined by the European Committee for Standardization, are highly reliable as methods, highly defensible in the court of law, and widely applicable to the majority of oil spill situations. Nevertheless, the methodology is time consuming and labour intensive, which may not be ideal when dealing with an emergency oil spill situation. In this study, direct analysis in real time time-of-flight mass spectrometry (DART/TOFMS) was used to successfully develop an efficient oil identification method. To confirm the accuracy of this method spilled oil samples were tested from five previous years of blind round robin testing organized by the oil spill identification network of experts (OSINET) under the Bonn Agreement. Heatmap inspection, principal component analysis and finally discriminant analysis of principal components were used to arrive at final predictions regarding the identities of the spilled oil samples. The results were compared with the results of previous gas chromatography flame ionization detection (GC/FID) and gas chromatography triple quadrupole mass spectrometry (GC/MS/MS) analyses of the same oils. While taking only about a tenth of the time, the DART/TOFMS analysis produced results similar to those of classical GC/FID and GC/MS/MS (EI<sup>+</sup>) procedures. The ability of DART/TOFMS to display this level of validity exemplifies its potential to be a new tool for supplementing classical analyses for oil spill forensics. Identification (biology) ; Mass spectrometry ; Time-of-flight mass spectrometry ; Chromatography ; Chemistry ; Forensic identification ; Quadrupole time of flight ; Tandem mass spectrometry ; Biology Mass Spectrometry Techniques and Applications ; Oil Spill Detection and Mitigation ; Isotope Analysis in Ecology
Authors: Wei Guo | Heguang Sun | Hongbo Qiao | Hui Zhang | Lin Zhou | Ping Dong | Xiaoyu Song
Source: Agriculture (article, 2023-07-27)
Field: Chemistry — Analytical Chemistry

Spectral Detection of Peanut Southern Blight Severity Based on Continuous Wavelet Transform and Machine Learning Peanut southern blight has a severe impact on peanut production and is one of the most devastating soil-borne fungal diseases. We conducted a hyperspectral analysis of the spectral responses of plants to peanut southern blight to provide theoretical support for detecting the severity of the disease via remote sensing. In this study, we collected leaf-level spectral data during the winter of 2021 and the spring of 2022 in a greenhouse laboratory. We explored the spectral response mechanisms of diseased peanut leaves and developed a method for assessing the severity of peanut southern blight disease by comparing the continuous wavelet transform (CWT) with traditional spectral indices and incorporating machine learning techniques. The results showed that the SVM model performed best and was able to effectively detect the severity of peanut southern blight when using CWT (WF770~780, 5) as an input feature. The overall accuracy (OA) of the modeling dataset was 91.8% and the kappa coefficient was 0.88. For the validation dataset, the OA was 90.5% and the kappa coefficient was 0.87. These findings highlight the potential of this CWT-based method for accurately assessing the severity of peanut southern blight. Blight ; Hyperspectral imaging ; Kappa ; Continuous wavelet transform ; Wavelet transform ; Wavelet ; Artificial intelligence ; Pattern recognition (psychology) ; Mathematics ; Agronomy ; Biology ; Computer science ; Discrete wavelet transform Spectroscopy and Chemometric Analyses ; Peanut Plant Research Studies ; Remote Sensing in Agriculture
Authors: Yue Xu | Xiangyang Zhou | Wenjuan Lei
Source: Foods (article, 2023-09-28)
Field: Chemistry — Analytical Chemistry

Identifying the Producer and Grade of Matcha Tea through Three-Dimensional Fluorescence Spectroscopy Analysis and Distance Discrimination The three-dimensional fluorescence spectroscopy features the advantage of obtaining emission spectra at different excitation wavelengths and providing more detailed information. This study established a simple method to discriminate both the producer and grade of matcha tea by coupling three-dimensional fluorescence spectroscopy analysis and distance discrimination. The matcha tea was extracted three times and three-dimensional fluorescence spectroscopies of these tea infusions were scanned; then, the dimension of three-dimensional fluorescence spectroscopies was reduced by the integration at three specific areas showing local peaks of fluorescence intensity, and a series of vectors were constructed based on a combination of integrated vectors of the three tea infusions; finally, four distances were used to discriminate the producer and grade of matcha tea, and two discriminative patterns were compared. The results indicated that proper vector construction, appropriate discriminative distance, and correct steps are three key factors to ensure the high accuracy of the discrimination. The vector based on the three-dimensional fluorescence spectroscopy of all three tea infusions resulted in a higher accuracy than those only based on spectroscopy of one or two tea infusions, and the first tea infusion was more sensitive than the other tea infusion. The Mahalanobis distance had a higher accuracy that was up to 100% when the vector is appropriate, while the other three distances were about 60-90%. The two-step discriminative pattern, identifying the producer first and the grade second, showed a higher accuracy and a smaller uncertainty than the one-step pattern of identifying both directly. These key conclusions above help discriminate the producer and grade of matcha in a quick, accurate, and green method through three-dimensional fluorescence spectroscopy, as well as in quality inspections and identifying the critical parameters of the producing process. Mahalanobis distance ; Fluorescence spectroscopy ; Fluorescence ; Spectroscopy ; Chemistry ; Discriminative model ; Pattern recognition (psychology) ; Biological system ; Analytical Chemistry (journal) ; Artificial intelligence ; Mathematics ; Computer science ; Chromatography ; Optics ; Physics ; Biology Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Tea Polyphenols and Effects
Authors: Dea Gogishvili | Eva Illes‐Toth | Matthew J. Harris | Christopher Hopley | Charlotte E. Teunissen | Sanne Abeln
Source: Proteins Structure Function and Bioinformatics (article, 2023-12-27)
Field: Materials Science — Materials Chemistry

Structural flexibility and heterogeneity of recombinant human glial fibrillary acidic protein (GFAP) Glial fibrillary acidic protein (GFAP) is a promising biomarker for brain and spinal cord disorders. Recent studies have highlighted the differences in the reliability of GFAP measurements in different biological matrices. The reason for these discrepancies is poorly understood as our knowledge of the protein's 3-dimensional conformation, proteoforms, and aggregation remains limited. Here, we investigate the structural properties of GFAP under different conditions. For this, we characterized recombinant GFAP proteins from various suppliers and applied hydrogen-deuterium exchange mass spectrometry (HDX-MS) to provide a snapshot of the conformational dynamics of GFAP in artificial cerebrospinal fluid (aCSF) compared to the phosphate buffer. Our findings indicate that recombinant GFAP exists in various conformational species. Furthermore, we show that GFAP dimers remained intact under denaturing conditions. HDX-MS experiments show an overall decrease in H-bonding and an increase in solvent accessibility of GFAP in aCSF compared to the phosphate buffer, with clear indications of mixed EX2 and EX1 kinetics. To understand possible structural interface regions and the evolutionary conservation profiles, we combined HDX-MS results with the predicted GFAP-dimer structure by AlphaFold-Multimer. We found that deprotected regions with high structural flexibility in aCSF overlap with predicted conserved dimeric 1B and 2B domain interfaces. Structural property predictions combined with the HDX data show an overall deprotection and signatures of aggregation in aCSF. We anticipate that the outcomes of this research will contribute to a deeper understanding of the structural flexibility of GFAP and ultimately shed light on its behavior in different biological matrices. Glial fibrillary acidic protein ; Chemistry ; Dimer ; Recombinant DNA ; Biophysics ; GFAP stain ; Protein structure ; Deamidation ; Biochemistry ; Biology ; Enzyme Enzyme Structure and Function ; Metabolomics and Mass Spectrometry Studies ; Protein Structure and Dynamics