jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Velma T. E. Aho | Laure‐Alix Clerbaux | Anne Kupczok | Bree J. Tillett | Neha Garg | Jannie G. E. Henderickx
Source: PROTEOMICS (article, 2025-04-27)
Field: Chemistry — Spectroscopy

A Non‐Metaproteomics Researchers’ View on Metaproteomics in Microbiome Research Metaproteomics, an emerging field among the omic techniques, holds great promise for unraveling the function of microbiomes in host health and our environment. Metaproteomics can also be a valuable addition to multiomics studies of the microbiome, complementing genome-resolved metagenomics, metatranscriptomics, and metabolomics. The potential advancements from metaproteomics and multiomics research touch a breadth of disciplines, including ecology, biochemistry, immunology, medical microbiology, cell physiology, and medicine, and could lead to both fundamental and applied discoveries. However, there are significant roadblocks to widespread adoption of metaproteomics among microbiome researchers. In this Viewpoint article, we highlight the pivotal role of metaproteomics in microbiome research by showcasing its advantages, exploring opportunities to overcome challenges, and paving the way for its broader adoption as a mainstream technique. We hope that the recommendations provided in this Viewpoint article will inspire new, beneficial collaborations between proteomics experts, algorithm and infrastructure developers, biochemists, cell biologists, and microbiologists, enabling the construction of a knowledge base of microbiome function that can have an immediate and direct impact on host health and the environment. Metaproteomics ; Microbiome ; Metagenomics ; Function (biology) ; Data science ; Computational biology ; Proteomics ; Gut microbiome ; Biology ; Bioinformatics ; Computer science ; Evolutionary biology Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Microbial Community Ecology and Physiology
Authors: Andrew M. Frey | Frances R. Sidgwick | Andrew Porter | Paweł Palmowski | Matthias Trost
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-09-22)
Field: Chemistry — Spectroscopy

Recommendations for Quantitative Data-Independent Acquisition (DIA) Proteomics using Controlled Quantitative Experiments (CQEs) Abstract Advances in mass spectrometry and associated computational tools have resulted in the wide-spread adoption of Data-Independent Acquisition (DIA) for proteomics. Experiments using state-of-the-art instrumentation and specialised modes of acquisition report ever increasing throughput and protein identification rates. However, experiments to test the efficacy of protein quantitation in these novel methods is surprisingly rare -especially in novel methods where low sample input or high-throughput is considered. Here, we performed a series of controlled quantitative experiments (CQEs) on two commonly used mass spectrometry platforms (Exploris480 and timsTOF HT), using defined mixtures of human, yeast, and bacterial proteomes. Peptide spectrum matching and initial quantification was performed using DIA-NN, with a series of post-processing options also compared. Overall, we identified &gt;10,000 unique proteins and &gt;160,000 precursors across samples with excellent accuracy and precision. Additional post-processing was found to have drastic impacts on ID rates, quantitative precision and accuracy, and false quantitative rate (FQR). These impacts were particularly notable in experiments using low amounts of sample. In optimal loading conditions, data processing could reduce FQR from ∼0.1 to 0 % with minimal losses in ID rates. Ultimately, we present a series of recommendations for proteomics data processing, and advice on the use of CQEs and resulting metrics when assessing quantitative efficacy in novel modes of acquisition. Quantitative proteomics ; Mass spectrometry ; Proteomics ; Instrumentation (computer programming) ; Quantitative analysis (chemistry) ; Quantitative assessment ; Label-free quantification ; Matching (statistics) Advanced Proteomics Techniques and Applications
Authors: Akihiro Inoue | Hideaki Watanabe | K Kusakabe | Masahiro Nishikawa | S Ohtsuka | Yasuhiro Shiraishi | Mashio Taniwaki | Yoshihiro Takimoto | Masaki Matsumoto | Mitsuharu Miyoshi | Seiji Shigekawa | Riko Kitazawa | Teruhito Kido | Takanori Ohnishi | Hisaaki Takahashi | Takeharu Kunieda
Source: Acta Neurochirurgica (article, 2025-02-19)
Field: Materials Science — Materials Chemistry

Three-dimensional amide proton transfer (APT) imaging appliable to navigation surgery can present comparable metabolic activity of glioblastoma to 11C-Methionine PET The area of tumor invasion could be evaluated by 3D FSE-APT in a similar way to <sup>11</sup>C-Met-PET, and the cut-off value for deciding the borderline between the area including infiltrating tumor cells and that with almost no tumor cells was 12.8%. In addition, 3D FSE-APT could be applied to navigation systems and may have great potential as an imaging modality replacing <sup>11</sup>C-Met-PET in GBM surgery. Medicine ; Glioma ; Neuroradiology ; Nuclear medicine ; Positron emission tomography ; Magnetic resonance imaging ; Brain tumor ; Radiology ; Neurology ; Pathology ; Cancer research Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; MRI in cancer diagnosis
Authors: Si Ran Wang | Zhan Ye Chen | Shao Nan Chen | Jun Yan Dai | J. Zhang | Zhen Jie Qi | Li Jie Wu | Meng Sun | Qun Yan Zhou | Huidong Li | Zhangjie Luo | Qiang Cheng | Tie Jun Cui
Source: Nature Communications (article, 2025-07-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Simplified radar architecture based on information metasurface Modern radar typically employs a chain radio-frequency (RF)-digital architecture, imposing high costs, substantial hardware burdens, and integration challenges. Here, we propose a simplified radar architecture based on space-time-coding (STC) information metasurfaces. With the capabilities to generate multiple frequencies and customize their phases, the STC metasurfaces play crucial roles in both transmission and reception: they enable chirp signal generation and radiation at the transmitter while facilitating echo reception and dechirp processing at the receiver. Remarkably, dechirp processing is performed at the RF level, removing the need for high-speed digitization and potentially enabling more efficient signal processing than conventional digital methods. As a proof of concept, experiments demonstrate that the proposed metasurface radar achieves target detection and range/speed measurement performance comparable to that of conventional systems. This study presents an innovative radar system paradigm that integrates RF front ends and signal processors onto an information metasurface platform, achieving essential sensing functions with reduced system complexity and cost. Computer science ; Architecture ; Radar ; Computational biology ; Biology ; Telecommunications ; Geography Metamaterials and Metasurfaces Applications ; Radar Systems and Signal Processing ; Advanced Wireless Communication Technologies
Authors: Alexia Jolicoeur‐Martineau
Source: Research Square (preprint, 2025-12-18)
Field: Chemistry — Organic Chemistry

Less is More: Recursive Reasoning with Tiny Networks Argument (complex analysis) ; Benchmark (surveying) ; Artificial neural network ; Scaling ; Deep neural networks ; Recurrent neural network Wood and Agarwood Research ; Multimodal Machine Learning Applications ; Big Data and Digital Economy
Authors: Witold Wolski | Jonas Grossmann | Leonardo Schwarz | Peter Leary | Can Türker | Paolo Nanni | Ralph Schlapbach | Christian Panse
Source: Journal of Proteome Research (article, 2025-01-24)
Field: Chemistry — Spectroscopy

<i>prolfquapp</i> ─ A User-Friendly Command-Line Tool Simplifying Differential Expression Analysis in Quantitative Proteomics Mass spectrometry is a cornerstone of quantitative proteomics, enabling relative protein quantification and differential expression analysis (<i>DEA</i>) of proteins. As experiments grow in complexity, involving more samples, groups, and identified proteins, interactive differential expression analysis tools become impractical. The <i>prolfquapp</i> addresses this challenge by providing a command-line interface that simplifies <i>DEA</i>, making it accessible to nonprogrammers and seamlessly integrating it into workflow management systems. <i>Prolfquapp</i> streamlines data processing and result visualization by generating dynamic HTML reports that facilitate the exploration of differential expression results. These reports allow for investigating complex experiments, such as those involving repeated measurements or multiple explanatory variables. Additionally, <i>prolfquapp</i> supports various output formats, including XLSX files, <i>SummarizedExperiment</i> objects and rank files, for further interactive analysis using spreadsheet software, the <i>exploreDE</i> Shiny application, or gene set enrichment analysis software, respectively. By leveraging advanced statistical models from the <i>prolfqua</i> R package, <i>prolfquapp</i> offers a user-friendly, integrated solution for large-scale quantitative proteomics studies, combining efficient data processing with insightful, publication-ready outputs. Proteomics ; Computer science ; Expression (computer science) ; Computational biology ; Protein expression ; Differential (mechanical device) ; User Friendly ; Biology ; Operating system ; Engineering ; Programming language ; Genetics Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Gene expression and cancer classification
Authors: Mohammadreza Ashrafian | Leila Yousefi
Source: Scientific Reports (article, 2025-07-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Subwavelength imaging using orbital angular momentum waves generated by metasurfaces Using conventional imaging techniques, the maximum obtainable resolution of an object is limited to about half the wavelength of the incident light, a phenomenon known as the diffraction limit. This limitation poses significant challenges in fields requiring high-resolution imaging, such as microscopy and nanotechnology. In this paper, we address this challenge by designing a dielectric metasurface to generate an optical Laguerre-Gaussian (LG) orbital angular momentum (OAM) beam. This innovative approach leverages the unique properties of OAM beams to achieve imaging beyond the diffraction limit. The dielectric metasurface is meticulously engineered to control both the phase and amplitude of the output wave, enabling the generation of high-quality LG OAM beams. Unlike traditional near-field and far-field imaging techniques, our proposed method does not necessitate a restricted distance between the imaging system components, offering greater flexibility and practicality in various applications. To validate the performance of our method, we conducted comprehensive numerical simulations. The results demonstrate that the generated OAM beam can achieve a resolution of 0.29 times the incident wavelength, surpassing the conventional diffraction limit. Diffraction ; Optics ; Angular momentum ; Angular spectrum method ; Physics ; Wavelength ; Gaussian beam ; Beam (structure) ; Limit (mathematics) ; Angular resolution (graph drawing) ; Computer science Metamaterials and Metasurfaces Applications ; Orbital Angular Momentum in Optics ; Advanced Antenna and Metasurface Technologies
Authors: Anjana J. Atapattu | Tharindu D. Nuwarapaksha
Source: Preprints.org (preprint, 2025-02-08)
Field: Chemistry — Inorganic Chemistry

Integrating Organic Fertilizers in Coconut Farming: Best Practices and Application Techniques Organic fertilizers are a revolutionary concept in coconut farming as they provide a pack-age for sustainable coconut production. This chapter looks at the multiple advantages of organic fertilization methods and types of organic fertilizers which include compost, ver-micompost, livestock manure, green manure, crop residues, and biofertilizers. Chapter fo-cuses on the best practices, application methods, time of application, frequency and rate of application of nutrients for coconut palm at various developmental stages. The chapter provides a detailed and systematic review of the environmental, economic and social im-pacts of organic fertilization. Benefits include enhanced soil health, biodiversity promo-tion, carbon sequestration, cost effectiveness, quality improvement of the yield, food secu-rity and possibilities of creating rural income. Issues including resource accessibility difficulties, nutrient deficiencies, and intensive labor requirement are explored in detail, as well as future trends that focus on advanced technologies, new research areas, and policy approaches. Thus, the chapter on organic fertilization as a coherent concept that can be applied to coconut production and other goals of environmental protection, food security, and sustainable development of agriculture. Organic farming ; Agriculture ; Agricultural science ; Business ; Environmental science ; Agroforestry ; Agricultural engineering ; Geography ; Engineering Coconut Research and Applications
Authors: Abdullah Maher | Mohamed A. Swillam
Source: Scientific Reports (article, 2025-01-15)
Field: Materials Science — Surfaces, Coatings and Films

Highly Efficient and achromatic mid-infrared silicon nitride meta-lenses Inverse design with topology optimization considers a promising methodology for discovering new optimized photonic structure that enables to break the limitations of the forward or the traditional design especially for the meta-structure. This work presents a high efficiency mid infra-red imaging photonics element along mid infra-red wavelengths band starts from 2 to 5 µm based on silicon nitride optimized material structures. The first two designs are broadband focusing and reflective meta-lens under very high numerical aperture condition (NA = 0.9). The two designs are modeled by inverse design with topology optimization problem with Kreisselmeier-Steinhauser (k-s) aggregation objective function, while the final design is depended on novel inverse design optimization problem with double aggregation objective function that can target bifocal points along the wavelength band producing high efficiency achromatic broadband multi-focal meta-lens under very high numerical apertures ([Formula: see text]). Achromatic lens ; Infrared ; Silicon nitride ; Computer science ; Optoelectronics ; Materials science ; Optics ; Silicon ; Physics Optical Coatings and Gratings ; Metamaterials and Metasurfaces Applications ; Photonic and Optical Devices
Authors: Anjana J. Atapattu | Tharindu D. Nuwarapaksha | Shashi S. Udumann | Nuwandhya S. Dissanayaka
Source: Crops (article, 2025-04-03)
Field: Chemistry — Inorganic Chemistry

Integrating Organic Fertilizers in Coconut Farming: Best Practices and Application Techniques Organic fertilizers are a revolutionary concept in coconut farming as they provide a package for sustainable coconut production. This review examines the multiple advantages of organic fertilization methods and types of organic fertilizers, which include compost, vermicompost, livestock manure, green manure, crop residues, and biofertilizers. The review focuses on the best practices, application methods, time of application, frequency and rate of application of nutrients for coconut palm at various developmental stages. The study provides a detailed and systematic review of the environmental, economic and social impacts of organic fertilization. Benefits include enhanced soil health, biodiversity promotion, carbon sequestration, cost effectiveness, quality improvement of the yield, food security and possibilities of creating rural income. Issues including resource accessibility difficulties, nutrient deficiencies, and intensive labor requirements are explored in detail, as well as future trends that focus on advanced technologies, new research areas, and policy approaches. Thus, the study reviews organic fertilization as a coherent concept that can be applied to coconut production and other goals of environmental protection, food security, and sustainable development of agriculture. Agricultural science ; Agriculture ; Organic farming ; Agroforestry ; Business ; Environmental science ; Agricultural engineering ; Engineering ; Biology ; Ecology Coconut Research and Applications
Authors: Douwe Schulte | Rien Leuvenink | S. Jäger | Albert J. R. Heck | Joost Snijder
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-01-22)
Field: Chemistry — Spectroscopy

A universal spectrum annotator for complex peptidoforms in mass spectrometry-based proteomics Abstract Accurate and comprehensive peptide spectrum annotation is a crucial step to interpret mass spectrometry-based proteomics data. While peak assignment in peptide fragmentation spectra is central to a broad range of proteomics applications, current tools tend to be specialized to a specific task. Here we present a more comprehensive tool, the Annotator, which unifies spectrum annotation for bottom-up, middle-down, top-down, cross-linked, and glycopeptide fragmentation mass spectra, from all fragmentation methods, including all ion types: a/b/c, x/y/z, d/v/w, and immonium ions. The Annotator integrates all known post-translational modifications from common databases and additionally allows for the definition of custom fragmentation models and modifications. Modifications allow for diagnostic fragment ions, site specific neutral losses, and multiple breakage sites for cross-linkers. The underlying library used for the theoretical fragmentation and matching is based on the unified peptidoform notation ProForma 2.0 and made available as a Rust library (rustyms) with Python bindings. This enables spectrum annotation of diverse and complex peptidoforms across the broad range of mass spectrometry-based proteomics applications. Mass spectrometry ; Proteomics ; Computer science ; Chemistry ; Chromatography ; Biochemistry Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics
Authors: Raven L. Buckman Johnson | Hark Karkee | Alexander Gundlach‐Graham
Source: Journal of Analytical Atomic Spectrometry (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Two-stage semi-supervised machine learning for classification of Ti-rich nanoparticles and microparticles measured by spICP-TOFMS An application of two-stage SSML model to classify individual Ti-containing particles via spICP-TOFMS analysis. With two-stage SSML, we demonstrate low false-positive rates (≤5%) and moderate particle recoveries for all measured particle types. Stage (stratigraphy) ; Nanoparticle ; Materials science ; Artificial intelligence ; Chromatography ; Computer science ; Nanotechnology ; Chemistry ; Geology Machine Learning in Materials Science ; Computational Drug Discovery Methods
Authors: Zakiah I. Kalantan | Lujain Alharbi | Maryam H. Al-Zahrani | Sulafah M. Saleh Binhimd
Source: Contemporary Mathematics (article, 2025-01-25)
Field: Chemistry — Analytical Chemistry

Robust Dimensionality Reduction: A Bootstrap-Based Evaluation of PCA with Applications in Nutritional and Environmental Sciences The complex structures of vast amounts of data provide a considerable challenge to researchers. Dimensional reduction methods are reliable and transform high-dimensional data into lower-dimensional representations while preserving most original information. Principal Component Analysis (PCA) is a commonly used approach for dimensionality reduction that transforms data into a lower-dimensional space while preserving important information. The variability within the sample may affect the stability and reliability of PCA results. The constraint of existing approaches compromises the accuracy of PCA stability assessments in practical data scenarios. These methodologies frequently depend on linear assumptions and encounter difficulties when addressing high-dimensional data. This study used the bootstrap method to assess the stability of PCA by assessing the variability of eigenvalues and principal components over several bootstrap iterations. We evaluate how stability metrics, particularly confidence intervals for eigenvalues and the proportion of variance clarified, can assist in determining the optimal number of principal components. The results indicate that the bootstrap provides a helpful framework for evaluating the robustness of PCA and guiding informed decisions on dimensionality reduction in many applications, including data compression, visualization, and classification. Moreover, the results illustrate the efficacy of this method in enhancing the reliability and interpretability of PCA findings among distinct data-driven research endeavors. This study enhances understanding of how principal component analysis (PCA) tackles data unpredictability while delivering valuable insights for professionals in several disciplines. Dimensionality reduction ; Mathematics ; Reduction (mathematics) ; Curse of dimensionality ; Statistics ; Econometrics ; Artificial intelligence ; Computer science Spectroscopy and Chemometric Analyses
Authors: Maik Pietzner | Alice Williamson | Karen A. Hunt | Mine Koprulu | Leonhard Kohleick | Kamil Demircan | Sarah Finer | Julia Carrasco-Zanini | David A. van Heel | Claudia Langenberg
Source: medRxiv (preprint, 2025-08-13)
Field: Chemistry — Spectroscopy

Nanoparticle enriched mass spectrometry proteomics in British South Asians identifies novel variant-protein-disease mechanisms ABSTRACT Understanding genetic variation underlying differences in plasma protein levels can elucidate human disease mechanisms, but prior evidence was almost entirely derived from white Europeans using protein-preselected affinity reagents. Here, we integrate exome sequencing and common non-coding variation with untargeted nanoparticle enriched mass spectrometry (MS)-based plasma proteomics (Seer Proteograph XT: n=8067 protein groups) in &gt;1,400 British-Bangladeshi and British-Pakistani individuals. We gain quantitatively and qualitatively different insights compared to two affinity-based assays in the same samples (SomaLogic 11k: n=9685 and Olink HT: n=5416 proteins), both in terms of proteins covered, and new proteogenomic insights into disease biology. Considering both additive and non-additive genetic effects, we identify &gt;1,200 significant variant-protein associations (n=895 cis -protein quantitative trait loci (pQTL)), half of which are novel. Cross-platform comparison demonstrated that inconsistencies in pQTL discovery are mostly explained by technical variation, and that multiple platforms are required to capture the full spectrum of pQTLs of blood proteins. We integrate proteogenomic evidence with orthogonal human genetic, experimental, and single cell expression data to consolidate a potential role of 21 proteins in the pathology of 44 diseases: e.g., a novel role of high IGLV3-21 in the development of Grave’s disease elucidating B-cell mediated autoimmunity. Our results demonstrate the potential of MS-based blood proteomics in diverse ancestries for pQTL discovery, including functional characterization of missense variants, and the need to consolidate evidence from multiple biological domains to confidently assign proteins to disease pathology to guide drug target identification and drug repurposing. Proteomics ; Mass spectrometry ; Computational biology ; Disease ; Chemistry ; Biology ; Medicine ; Chromatography ; Biochemistry ; Gene ; Internal medicine Advanced Proteomics Techniques and Applications