jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hengnian Qi | Hongyang Li | Liping Chen | Fengnong Chen | Jiahao Luo | Chu Zhang
Source: Foods (article, 2024-01-12)
Field: Chemistry — Analytical Chemistry

Hyperspectral Imaging Using a Convolutional Neural Network with Transformer for the Soluble Solid Content and pH Prediction of Cherry Tomatoes Cherry tomatoes are cultivated worldwide and favored by consumers of different ages. The soluble solid content (SSC) and pH are two of the most important quality attributes of cherry tomatoes. The rapid and non-destructive measurement of the SSC and pH of cherry tomatoes is of great significance to their production and consumption. In this research, hyperspectral imaging combined with a convolutional neural network with Transformer (CNN-Transformer) was utilized to analyze the SSC and pH of cherry tomatoes. Conventional machine learning and deep learning models were established for the determination of the SSC and pH. The findings demonstrated that CNN-Transformer yielded outstanding results in predicting the SSC, with the coefficient of determination of calibration (R<sup>2</sup><sub>C</sub>), validation (R<sup>2</sup><sub>V</sub>), and prediction (R<sup>2</sup><sub>P</sub>) for the SSC being 0.83, 0.87, and 0.83, respectively. Relatively worse results were obtained for the pH value prediction, with R<sup>2</sup><sub>C</sub>, R<sup>2</sup><sub>V</sub>, and R<sup>2</sup><sub>P</sub> values of 0.74, 0.68, and 0.60, respectively. Furthermore, the visualization of the CNN-Transformer model revealed the wavelength weight distributions, indicating that the 1380-1650 nm range served as the characteristic band for the SSC, while the spectral range at 945-1280 nm was the characteristic band for pH. In conclusion, integrating spectral information features with the attention mechanism of Transformer through a convolutional neural network can enhance the accuracy of predicting the SSC and pH for cherry tomatoes. Hyperspectral imaging ; Convolutional neural network ; Transformer ; Cherry tomato ; Deep learning ; Artificial intelligence ; Mathematics ; Horticulture ; Pattern recognition (psychology) ; Computer science ; Engineering ; Biology ; Electrical engineering Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Chemical Sensor Technologies
Authors: Ludwig Lautenbacher | Kevin Yang | Tobias Kockmann | Christian Panse | Matthew Chambers | Elias Kahl | Fengchao Yu | Wassim Gabriel | Del Bold | Tobias Schmidt | Kai Li | Brendan MacLean | Alexey I. Nesvizhskii | Mathias Wilhelm
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2024-06-03)
Field: Chemistry — Spectroscopy

Koina: Democratizing machine learning for proteomics research Recent developments in machine-learning (ML) and deep-learning (DL) have immense potential for applications in proteomics, such as generating spectral libraries, improving peptide identification, and optimizing targeted acquisition modes. Although new ML/DL models for various applications and peptide properties are frequently published, the rate at which these models are adopted by the community is slow, which is mostly due to technical challenges. We believe that, for the community to make better use of state-of-the-art models, more attention should be spent on making models easy to use and accessible by the community. To facilitate this, we developed Koina, an open-source containerized, decentralized and online-accessible high-performance prediction service that enables ML/DL model usage in any pipeline. Using the widely used FragPipe computational platform as example, we show how Koina can be easily integrated with existing proteomics software tools and how these integrations improve data analysis. Computer science ; Pipeline (software) ; Identification (biology) ; Artificial intelligence ; Proteomics ; Machine learning ; Software ; Data science ; Service (business) ; Deep learning ; Software engineering ; Operating system ; Chemistry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Machine Learning in Bioinformatics
Authors: Meera Gupta | Alex Johnson | Edward R. Cruz | Eli J. Costa | Randi L. Guest | Hsin‐Jung Li | Elizabeth M. Hart | Thao Nguyen | Michael Stadlmeier | Benjamin P. Bratton | Thomas J. Silhavy | Ned S. Wingreen | Zemer Gitai | Martin Wühr
Source: Nature Communications (article, 2024-07-13)
Field: Chemistry — Spectroscopy

Global protein turnover quantification in Escherichia coli reveals cytoplasmic recycling under nitrogen limitation Protein turnover is critical for proteostasis, but turnover quantification is challenging, and even in well-studied E. coli, proteome-wide measurements remain scarce. Here, we quantify the turnover rates of ~3200 E. coli proteins under 13 conditions by combining heavy isotope labeling with complement reporter ion quantification and find that cytoplasmic proteins are recycled when nitrogen is limited. We use knockout experiments to assign substrates to the known cytoplasmic ATP-dependent proteases. Surprisingly, none of these proteases are responsible for the observed cytoplasmic protein degradation in nitrogen limitation, suggesting that a major proteolysis pathway in E. coli remains to be discovered. Lastly, we show that protein degradation rates are generally independent of cell division rates. Thus, we present broadly applicable technology for protein turnover measurements and provide a rich resource for protein half-lives and protease substrates in E. coli, complementary to genomics data, that will allow researchers to study the control of proteostasis. Proteostasis ; Proteases ; Protein turnover ; Proteolysis ; Protein degradation ; Escherichia coli ; Cytoplasm ; Proteome ; Biology ; Biochemistry ; Protease ; Proteasome ; Cell biology ; Chemistry ; Protein biosynthesis ; Enzyme ; Gene Advanced Proteomics Techniques and Applications ; Enzyme Structure and Function ; Mass Spectrometry Techniques and Applications
Authors: Jonathan B. Boreyko
Source: Droplet (article, 2024-03-15)
Field: Materials Science — Surfaces, Coatings and Films

Jumping droplets Abstract When microdroplets with quasi‐spherical contact angles coalesce together on a low‐adhesion substrate, the capillary‐inertial expansion of the liquid bridge induces a dramatic out‐of‐plane jumping event due to symmetry breaking. From the onset of merging, droplet jumping initiates after a capillary‐inertial time scale of μs with characteristic jumping speeds of order m/s. This coalescence‐induced jumping‐droplet effect is most commonly observed among a population of growing dew droplets on a superhydrophobic condenser, but can also occur by colliding deposited droplets together or during droplet sliding on fog harvesters. In this review, we cover the historical development of capillary‐inertial jumping droplets, summarize the decade‐long effort to rationalize the ultra‐low energy conversion efficiency and critical droplet size of the phenomenon, and then present 15 variations on a theme of jumping. Capillary‐inertial jumping droplets are not only a visceral illustration of the surprising power of surface tension at the microscale but they also have the potential to enhance phase‐change heat transfer, enable self‐cleaning surfaces, combat frost formation, harvest energy, and govern the rate of disease spread for wheat crops. Jumping ; Microscale chemistry ; Capillary action ; Coalescence (physics) ; Mechanics ; Surface tension ; Materials science ; Composite material ; Physics ; Thermodynamics Surface Modification and Superhydrophobicity ; Fluid Dynamics and Heat Transfer ; Nanomaterials and Printing Technologies
Authors: Romain Tirole | Stefano Vezzoli | Dhruv Saxena | Shu Yang | T. V. Raziman | Emanuele Galiffi | Stefan A. Maier | J. B. Pendry | Riccardo Sapienza
Source: Nature Communications (article, 2024-09-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Second harmonic generation at a time-varying interface Time-varying metamaterials rely on large and fast changes of the linear permittivity. Beyond the linear terms, however, the effect of a non-perturbative modulation of the medium on harmonic generation remains largely unexplored. In this work, we study second harmonic generation at an optically pumped time-varying interface between air and a 310 nm Indium Tin Oxide film. We observe a modulation contrast at the second harmonic wavelength up to 93% for a pump intensity of 100 GW/cm<sup>2</sup>, leading to large frequency broadening and shift. We experimentally demonstrate that a significant contribution to the enhancement comes from the temporal modulation of the second order nonlinear susceptibility. Moreover, we show the frequency-modulated spectra resulting from single and double-slit time diffraction could be exploited for enhanced optical computing and sensing, enabling broadband time-varying effects on the harmonic signal and extending the application of Epsilon-Near-Zero materials to the visible range. Modulation (music) ; Second-harmonic generation ; Optics ; Harmonic ; High harmonic generation ; Physics ; Optoelectronics ; Indium tin oxide ; Nonlinear optics ; Materials science ; SIGNAL (programming language) ; Broadband ; Wavelength ; Acoustics ; Computer science ; Laser ; Nanotechnology ; Thin film Metamaterials and Metasurfaces Applications ; Photonic and Optical Devices ; Plasmonic and Surface Plasmon Research
Authors: Fan Zhang | Chaohui Wang | Weike Feng | Tong Liu | Zhengjie Wang | Yanzhao Wang | Mingzhao Wang | He‐Xiu Xu
Source: Nanophotonics (article, 2024-03-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Holographic communication using programmable coding metasurface With rapid development of holography, metasurface-based holographic communication scheme shows great potential in development of adaptive electromagnetic function. However, conventional passive metasurfaces are severely limited by poor reconfigurability, which makes it difficult to achieve wavefront manipulations in real time. Here, we propose a holographic communication strategy that on-demand target information is firstly acquired and encoded via a depth camera integrated with modified YOLOv5s target detection algorithm, then transmitted by software defined radio modules with long term evolution at 5 GHz, and finally reproduced in the form of holographic images by spin-decoupled programmable coding metasurfaces at 12 GHz after decoding through modified Gerchberg-Saxton algorithm. Experiments are conducted to demonstrate the brand-new concept of optical information conversion to electromagnetic one via above intelligent scheme. Our strategy may open a novel avenue toward applications of near-field communication based on adaptive variation of electric field patterns (i.e. holographic images). Reconfigurability ; Holography ; Computer science ; Coding (social sciences) ; Wavefront ; Decoding methods ; Field-programmable gate array ; Computer-generated holography ; Optics ; Computer vision ; Electronic engineering ; Physics ; Telecommunications ; Computer hardware ; Engineering ; Mathematics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Inès Metatla | Kévin Roger | Cérina Chhuon | Sara Ceccacci | Manuel Chapelle | Pierre-Olivier Schmit | Vadim Demichev | Ida Chiara Guerrera
Source: Clinical Proteomics (article, 2024-03-12)
Field: Chemistry — Spectroscopy

Neat plasma proteomics: getting the best out of the worst Plasma proteomics holds immense potential for clinical research and biomarker discovery, serving as a non-invasive "liquid biopsy" for tissue sampling. Mass spectrometry (MS)-based proteomics, thanks to improvement in speed and robustness, emerges as an ideal technology for exploring the plasma proteome for its unbiased and highly specific protein identification and quantification. Despite its potential, plasma proteomics is still a challenge due to the vast dynamic range of protein abundance, hindering the detection of less abundant proteins. Different approaches can help overcome this challenge. Conventional depletion methods face limitations in cost, throughput, accuracy, and off-target depletion. Nanoparticle-based enrichment shows promise in compressing dynamic range, but cost remains a constraint. Enrichment strategies for extracellular vesicles (EVs) can enhance plasma proteome coverage dramatically, but current methods are still too laborious for large series. Neat plasma remains popular for its cost-effectiveness, time efficiency, and low volume requirement. We used a test set of 33 plasma samples for all evaluations. Samples were digested using S-Trap and analyzed on Evosep One and nanoElute coupled to a timsTOF Pro using different elution gradients and ion mobility ranges. Data were mainly analyzed using library-free searches using DIA-NN. This study explores ways to improve proteome coverage in neat plasma both in MS data acquisition and MS data analysis. We demonstrate the value of sampling smaller hydrophilic peptides, increasing chromatographic separation, and using library-free searches. Additionally, we introduce the EV boost approach, that leverages on the extracellular vesicle fraction to enhance protein identification in neat plasma samples. Globally, our optimized analysis workflow allows the quantification of over 1000 proteins in neat plasma with a 24SPD throughput. We believe that these considerations can be of help independently of the LC-MS platform used. Proteome ; Proteomics ; Biomarker discovery ; Chemistry ; Extracellular vesicle ; Computer science ; Chromatography ; Robustness (evolution) ; Computational biology ; Nanotechnology ; Bioinformatics ; Materials science ; Biology ; Microvesicles ; Biochemistry Advanced Proteomics Techniques and Applications ; Extracellular vesicles in disease ; Advanced biosensing and bioanalysis techniques
Authors: Benjamin Geisler | Laura Fanfarillo | J. J. Hamlin | G. R. Stewart | Richard G. Hennig | P. J. Hirschfeld
Source: npj Quantum Materials (article, 2024-11-14)
Field: Materials Science — Materials Chemistry

Optical properties and electronic correlations in La3Ni2O7 bilayer nickelates under high pressure We explore the optical properties of La3Ni2O7 bilayer nickelates by using density functional theory including a Coulomb repulsion term. Convincing agreement with recent experimental ambient-pressure spectra is achieved for U ~ 3 eV, which permits tracing the microscopic origin of the characteristic features. Simultaneous consistency with angle-resolved photoemission spectroscopy and x-ray diffraction suggests the notion of rather moderate electronic correlations in this novel high-Tc superconductor. Oxygen vacancies form predominantly at the inner apical sites and renormalize the optical spectrum quantitatively, while the released electrons are largely accommodated by a defect state. We show that the structural transition occurring under high pressure coincides with a significant enhancement of the Drude weight and a reduction of the out-of-plane interband contribution that acts as a fingerprint of the emerging hole pocket. We further calculate the optical spectra for various possible magnetic phases including spin-density waves and discuss the results in the context of experiment. Finally, we investigate the role of the 2–2 versus 1–3 layer stacking and compare the bilayer nickelate to La4Ni3O10, La3Ni2O6, and NdNiO2, unveiling general trends in the optical spectrum as a function of the formal Ni valence in Ruddlesden–Popper versus reduced Ruddlesden–Popper nickelates. Bilayer ; Condensed matter physics ; High pressure ; Materials science ; Physics ; Engineering physics ; Chemistry ; Membrane Electronic and Structural Properties of Oxides ; Magnetic and transport properties of perovskites and related materials ; Luminescence Properties of Advanced Materials
Authors: Xia Li | Yue Jin | Jian Xue
Source: International Journal of General Medicine (article, 2024-05-01)
Field: Materials Science — Biomaterials

Unveiling Collagen’s Role in Breast Cancer: Insights into Expression Patterns, Functions and Clinical Implications Collagen, the predominant protein constituent of the mammalian extracellular matrix (ECM), comprises a diverse family of 28 members (I-XXVIII). Beyond its structural significance, collagen is implicated in various diseases or cancers, notably breast cancer, where it influences crucial cellular processes including proliferation, metastasis, apoptosis, and drug resistance, intricately shaping cancer progression and prognosis. In breast cancer, distinct collagens exhibit differential expression profiles, with some showing heightened or diminished levels in cancerous tissues or cells compared to normal counterparts, suggesting specific and pivotal biological functions. In this review, we meticulously analyze the expression of individual collagen members in breast cancer, utilizing Transcripts Per Million (TPM) data sourced from the GEPIA2 database. Through this analysis, we identify collagens that deviate from normal expression patterns in breast cancer, providing a comprehensive overview of their expression dynamics, functional roles, and underlying mechanisms. Our findings shed light on recent advancements in understanding the intricate interplay between these aberrantly expressed collagens and breast cancer. This exploration aims to offer valuable insights for the identification of potential biomarkers and therapeutic targets, thereby advancing the prospects of more effective interventions in breast cancer treatment. Medicine ; Breast cancer ; Cancer ; Expression (computer science) ; Computational biology ; Bioinformatics ; Cancer research ; Pathology ; Internal medicine ; Biology Collagen: Extraction and Characterization ; Bone and Dental Protein Studies ; Cancer Cells and Metastasis
Authors: Andrew Terhemen Tyowua | David Harbottle | Bernard P. Binks
Source: Advances in Colloid and Interface Science (review, 2024-08-06)
Field: Materials Science — Materials Chemistry

3D printing of Pickering emulsions, Pickering foams and capillary suspensions – A review of stabilization, rheology and applications Rheology ; Materials science ; Capillary action ; Pickering emulsion ; 3D printing ; Inkwell ; Suspension (topology) ; Nanotechnology ; Emulsion ; Composite material ; Chemical engineering ; Nanoparticle ; Engineering Pickering emulsions and particle stabilization ; Advanced Materials and Mechanics ; Micro and Nano Robotics
Authors: Anitta Jose | Tom Mathew | Nora Fernández‐Navas | Christine Joy Querebillo
Source: Micro (article, 2024-04-18)
Field: Materials Science — Materials Chemistry

Porous Inorganic Nanomaterials: Their Evolution towards Hierarchical Porous Nanostructures The advancement of both porous materials and nanomaterials has brought about porous nanomaterials. These new materials present advantages both due to their porosity and nano-size: small size apt for micro/nano device integration or in vivo transport, large surface area for guest/target molecule adsorption and interaction, porous channels providing accessibility to active/surface sites, and exposed reactive surface/active sites induced by uncoordinated bonds. These properties prove useful for the development of different porous composition types (metal oxides, silica, zeolites, amorphous oxides, nanoarrays, precious metals, non-precious metals, MOFs, carbon nanostructures, MXenes, and others) through different synthetic procedures—templating, colloidal synthesis, hydrothermal approach, sol-gel route, self-assembly, dealloying, galvanostatic replacement, and so—for different applications, such as catalysis (water-splitting, etc.), biosensing, energy storage (batteries, supercapacitors), actuators, SERS, and bio applications. Here, these are presented according to different material types showing the evolution of the structure design and development towards the formation of hierarchical porous structures, emphasizing that the formation of porous nanostructures came about out of the desire and need to form hierarchical porous nanostructures. Common trends observed across these different composition types include similar (aforementioned) applications and the use of porous nanomaterials as templates/precursors to create novel ones. Towards the end, a discussion on the link between technological advancements and the development of porous nanomaterials paves the way to present future perspectives on these nanomaterials and their hierarchical porous architectures. Together with a summary, these are given in the conclusion. Nanomaterials ; Porosity ; Materials science ; Nanotechnology ; Nanostructure ; Porous medium ; Chemical engineering ; Composite material ; Engineering Nanoporous metals and alloys ; Electrocatalysts for Energy Conversion ; Supercapacitor Materials and Fabrication
Authors: Fatma Fouad Hagar | Samar H. Abbas | Eman Atef | Dalia Abdelhamid | Mohamed Abdel‐Aziz
Source: Molecular Diversity (review, 2024-07-20)
Field: Chemistry — Organic Chemistry

Benzimidazole scaffold as a potent anticancer agent with different mechanisms of action (2016–2023) Benzimidazole scaffolds have potent anticancer activity due to their structure similarity to nucleoside. In addition, benzimidazoles could function as hydrogen donors or acceptors and bind to different drug targets that participate in cancer progression. The literature had many anticancer agents containing benzimidazole cores that gained much interest. Provoked by our endless interest in benzimidazoles as anticancer agents, we summarized the successful trials of the benzimidazole scaffolds in this concern. Moreover, we discuss the substantial opportunities in cancer treatment using benzimidazole-based drugs that may direct medicinal chemists for a compelling future design of more active chemotherapeutic agents with potential clinical applications. The uniqueness of this work lies in the highlighted benzimidazole scaffold hybridization with different molecules and benzimidazole-metal complexes, detailed mechanisms of action, and the IC<sub>50</sub> of the developed compounds determined by different laboratories after 2015. Benzimidazole ; Scaffold ; Chemistry ; Pharmacology ; Combinatorial chemistry ; Computational biology ; Nanotechnology ; Medicine ; Biology ; Materials science ; Biomedical engineering Click Chemistry and Applications ; Synthesis and Catalytic Reactions ; Synthesis and Biological Evaluation
Authors: Xiaofeng Zhou
Source: RSC Medicinal Chemistry (review, 2024-01-01)
Field: Chemistry — Organic Chemistry

Recent advances of tryptanthrin and its derivatives as potential anticancer agents Tryptanthrin is one of the well-known natural alkaloids with a broad spectrum of biological activities and can act as anti-inflammatory, anticancer, antibacterial, antifungal, antiviral, antitubercular, and other agents. Owing to its potent anticancer activity, tryptanthrin has been widely explored for the therapy of various cancers besides being effective against other diseases. Tryptanthrin with a pharmacological indoloquinazoline moiety can not only be modified by different functional groups to achieve various tryptanthrin derivatives, which may realize the improvement of anticancer activity, but also bind with different metal ions to obtain varied tryptanthrin metal complexes as potential anticancer agents, due to their higher anticancer activities in comparison with tryptanthrin (or its derivatives) and cisplatin. This review outlines the recent advances in the syntheses, structures, and anticancer activities of tryptanthrin derivatives and their metal complexes, trying to reveal their structure-activity relationships and to provide a helpful way for medicinal chemists in the development of new and effective tryptanthrin-based anticancer agents. Broad spectrum ; Chemistry ; Combinatorial chemistry Quinazolinone synthesis and applications ; Synthesis and Biological Evaluation ; Cancer therapeutics and mechanisms