jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Alejandro Fernández-Vega | Federica Farabegoli | María M. Alonso-Martínez | Ignacio Ortea
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-11-30)
Field: Chemistry — Spectroscopy

Comparison of TIMS-PASEF quantitative proteomics data-analysis workflows using FragPipe, DIA-NN, and Spectronaut from a user’s perspective Abstract Data-independent acquisition (DIA) methods have gained great popularity in bottom-up quantitative proteomics, as they overcome the irreproducibility and under-sampling limitations of data-dependent acquisition (DDA). diaPASEF, recently developed for the timsTOF Pro mass spectrometers, has brought improvements to DIA, providing additional ion separation (in the ion mobility dimension) and increasing sensitivity. Several studies have benchmarked different workflows for DIA quantitative proteomics, but mostly using instruments from Sciex and Thermo, and therefore, the results are not extrapolable to diaPASEF data. In this work, using a real-life sample set like the one that can be found in any proteomics experiment, we compared the results of analyzing PASEF data with different combinations of library-based and library-free analysis, combining the tools of the FragPipe suite, DIA-NN and including MS1-level LFQ with DDA-PASEF data, and also comparing with the workflows possible in Spectronaut. We verified that library-independent workflows, not so efficient not so long ago, have greatly improved in the recent versions of the software tools, and now perform as well or even better than librarybased ones. We report here information so that the user who is going to conduct a relative quantitative proteomics study using a timsTOF Pro mass spectrometer can make an informed decision on how to acquire (diaPASEF for DIA analysis, or DDA-PASEF for MS1-level LFQ) the samples, and what can be expected depending on the data analysis tool used, among the different alternatives offered by the recently optimized tools for TIMS-PASEF data analysis. Computer science ; Workflow ; Software ; Proteomics ; Sample (material) ; Data acquisition ; Perspective (graphical) ; Data mining ; Set (abstract data type) ; Data science ; Database ; Artificial intelligence ; Chemistry ; Chromatography Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Analytical chemistry methods development
Authors: Oliver M. Crook | Colin Davies | Lisa M. Breckels | Josie A. Christopher | Laurent Gatto | Paul Kirk | Kathryn S. Lilley
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-01-05)
Field: Chemistry — Spectroscopy

Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE Abstract The steady-state localisation of proteins provides vital insight into their function. These localisations are context specific with proteins translocating between different sub-cellular niches upon perturbation of the subcellular environment. Differential localisation , that is a change in the steady-state subcellular location of a protein, provides a step towards mechanistic insight of subcellular protein dynamics. Aberrant localisation has been implicated in a number of pathologies, thus differential localisation may help characterise disease states and facilitate rational drug discovery by suggesting novel targets. High-accuracy high-throughput mass spectrometry-based methods now exist to map the steady-state localisation and re-localisation of proteins. Here, we propose a principled Bayesian approach, BANDLE, that uses these data to compute the probability that a protein differentially localises upon cellular perturbation, as well quantifying the uncertainty in these estimates. Furthermore, BANDLE allows information to be shared across spatial proteomics datasets to improve statistical power. Extensive simulation studies demonstrate that BANDLE reduces the number of both type I and type II errors compared to existing approaches. Application of BANDLE to datasets studying EGF stimulation and AP-4 dependent localisation recovers well studied translocations, using only two-thirds of the provided data. Moreover, we potentially implicate TMEM199 with AP-4 dependent localisation. In an application to cytomegalovirus infection, we obtain novel insights into the rewiring of the host proteome. Integration of high-throughput transcriptomic and proteomic data, along with degradation assays, acetylation experiments and a cytomegalovirus intcractome allows us to provide the functional context of these data. Proteomics ; Computational biology ; Proteome ; Context (archaeology) ; Biology ; Quantitative proteomics ; Computer science ; Subcellular localization ; Bioinformatics ; Cell biology ; Genetics ; Cytoplasm ; Gene Advanced Proteomics Techniques and Applications ; Biosensors and Analytical Detection
Authors: Junqiu Zhang | Liwei Xu | Hongtao Jiang | Chuanlai Xu | Wenjing Liu | Ting Wu | Hua Kuang
Source: Biosensors (article, 2021-07-13)
Field: Chemistry — Analytical Chemistry

Development of an Immunoassay for the Detection of Copper Residues in Pork Tissues The presence of high concentrations of copper (Cu) residues in pork is highly concerning and therefore, this study was designed to develop a high-throughput immunoassay for the detection of such residues in edible pork tissues. The Cu content in the pork samples after digestion with HNO3 and H2O2 was measured using a monoclonal antibody (mAb) against a Cu (II)–ethylenediaminetetraacetic acid (EDTA) complex. The resulting solution was neutralized using NaOH at pH 7 and the free metal ions in the solution were chelated with EDTA for the immunoassay detection. An indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) method was developed for Cu ion analysis. The half maximal inhibitory concentration of the mAb against Cu (II)–EDTA was 5.36 ng/mL, the linear detection range varied between 1.30 and 27.0 ng/mL, the limit of detection (LOD) was 0.43 μg/kg, and the limit of quantification (LOQ) was 1.42 μg/kg. The performances of the immunoassay were evaluated using fortified pig serum, liver, and pork samples and had a recovery rate of 94.53–102.24%. Importantly, the proposed immunoassay was compared with inductively coupled plasma mass spectroscopy (ICP-MS) to measure its performance. The detection correlation coefficients of the three types of samples (serum, pork, and liver) were 0.967, 0.976, and 0.983, respectively. Thirty pork samples and six pig liver samples were collected from local markets and Cu was detected with the proposed ic-ELISA. The Cu content was found to be 37.31~85.36 μg/kg in pork samples and 1.04–1.9 mg/kg in liver samples. Furthermore, we detected the Cu content in pigs with feed supplemented with tribasic copper chloride (TBCC) and copper sulfate (CS) (60, 110, and 210 mg/kg in feed). There was no significant difference in Cu accumulation in pork tissues between the TBCC and CS groups, while a remarkable Cu accumulation was found for the CS group in liver at 210 mg/kg, representing more than a two-fold higher level than seen in the TBCC group. Therefore, the proposed immunoassay was found to be robust and sensitive for the detection of Cu, providing a cost effective and practical tool for its detection in food and other complicated samples. Detection limit ; Immunoassay ; Chemistry ; Ethylenediaminetetraacetic acid ; Chromatography ; Copper ; Inductively coupled plasma mass spectrometry ; Linear range ; Chelation ; Monoclonal antibody ; Mass spectrometry ; Antibody Analytical chemistry methods development ; Trace Elements in Health ; Electrochemical Analysis and Applications
Authors: Lucas Etourneau | Nelle Varoquaux | Thomas Bürger
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-08-20)
Field: Chemistry — Spectroscopy

Unveiling the links between peptide identification and differential analysis FDR controls by means of a practical introduction to knockoff filters Abstract In proteomic differential analysis, FDR control is often performed through a multiple test correction ( i . e ., the adjustment of the original p-values). In this protocol, we apply a recent and alternative method, based on so-called knockoff filters. It shares interesting conceptual similarities with the target-decoy competition procedure, classically used in proteomics for FDR control at peptide identification. To provide practitioners with a unified understanding of FDR control in proteomics, we apply the knockoff procedure on real and simulated quantitative datasets. Leveraging these comparisons, we propose to adapt the knockoff procedure to better fit the specificities of quantitive proteomic data (mainly very few samples). Performances of knockoff procedure are compared with those of the classical Benjamini-Hochberg procedure, hereby shedding a new light on the strengths and weaknesses of target-decoy competition. False discovery rate ; Identification (biology) ; Decoy ; Computational biology ; Proteomics ; Computer science ; Biology ; Genetics ; Gene Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Receptor Mechanisms and Signaling
Authors: Daisha Van Der Watt | Hannah Boekweg | Thy Truong | Amanda J. Guise | Edward D. Plowey | Ryan Kelly | Samuel Payne
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-08-18)
Field: Chemistry — Spectroscopy

Benchmarking PSM identification tools for single cell proteomics Abstract Single cell proteomics is an emerging sub-field within proteomics with the potential to revolutionize our understanding of cellular heterogeneity and interactions. Recent efforts have largely focused on technological advancements in sample preparation, chromatography and instrumentation to enable measuring proteins present in these ultra-limited samples. Although advancements in data acquisition have rapidly improved our ability to analyze single cells, the software pipelines used in data analysis were originally written for traditional bulk samples and their performance on single cell data has not been investigated. We benchmarked five popular peptide identification tools on single cell proteomics data. We found that MetaMorpheus achieved the greatest number of peptide spectrum matches at a 1% false discovery rate. Depending on the tool, we also find that post processing machine learning can improve spectrum identification results by up to ∼40%. Although rescoring leads to a greater number of peptide spectrum matches, these new results typically are generated by 3rd party tools and have no way of being utilized by the primary pipeline for quantification. Exploration of novel metrics for machine learning algorithms will continue to improve performance. Pipeline (software) ; Computer science ; Proteomics ; Identification (biology) ; Benchmarking ; Software ; Instrumentation (computer programming) ; Machine learning ; Artificial intelligence ; Field (mathematics) ; Data science ; Data mining ; Chemistry ; Biology Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Advanced Biosensing Techniques and Applications
Authors: Nicholas Dwork | Jeremy W. Gordon | Shuyu Tang | Daniel O’Connor | Esben Søvsø Szocska Hansen | Christoffer Laustsen | Peder E. Z. Larson
Source: Magnetic Resonance Materials in Physics Biology and Medicine (article, 2021-01-27)
Field: Chemistry — Spectroscopy

Di-chromatic interpolation of magnetic resonance metabolic images Results are shown with images of hyperpolarized pyruvate, lactate, and bicarbonate using data of the heart and brain from healthy human volunteers, a healthy porcine heart, and a human with prostate cancer. Interpolation (computer graphics) ; Magnetic resonance imaging ; Human brain ; Magnetic resonance spectroscopic imaging ; Biomagnetism Advanced NMR Techniques and Applications ; Advanced MRI Techniques and Applications ; Optical Polarization and Ellipsometry
Authors: Bennett Elizabeth Barr | Charles R. Hurburgh | Gretchen A. Mosher
Source: Applied Engineering in Agriculture (article, 2021-01-01)
Field: Chemistry — Analytical Chemistry

Maximizing Processing Value with Selective Handling Strategies: An Analysis of Soybeans Received at Iowa Elevators Highlights Levels of protein and oil influence the marketability of soybeans Geographic differences in soybeans have economic implications for grain elevators Random errors in the receiving and analysis process mask these differences For soybeans to be marketed on protein and oil levels, errors in handling and analysis must be addressed Abstract . A better ability to understand and use geographic variations in protein and oil is one way to maximize the value potential of soybeans for handlers and processors. An Iowa cooperative had been sourcing soybeans for processing from nearby elevator locations and wanted to know whether this strategy was maximizing the net processing value of the soybeans. Random and systematic errors from testing and measurement instruments also impact marketing decisions and were investigated as part of this project. During the Fall 2018 soybean harvest, soybean samples were collected from 32 country elevator locations belonging to one Iowa-based cooperative which has its own soybean processing plant. Samples were analyzed using near-infrared spectroscopy (NIR), and protein and oil content data were entered into an Estimated Processing Value (EPV) model to determine value differences of soybeans among elevator locations. Results showed substantial variability among locations that represented a $0.23/bushel EPV spread. No significant variation was found in soybean quality over the harvest season, suggesting that marketing decisions can be made at the beginning of the season. To determine the incidence of random errors, a simulated Excel-based model was used with three test cases. The introduction of random error lowered value gaps between locations, which made the discrimination of high-value locations from average or low-value locations difficult. Although protein and oil measurement with the NIR instrument was feasible even on busy harvest season days, the validity of marketing decisions using these data depended highly on the error involved in sample analysis. Future studies should identify specific sources of error and attempt to eliminate them. Specifically, one of the largest sources of error in a commodity-based market system is in the measuring units. The ability to isolate and quantify measurement error will improve the capability of the commodity-based soybean market system to focus trade decisions on end use traits, maximizing soybean value and providing incentive for improvement. Keywords: Error analysis, Grain elevators, Selective handling, Soybean processing, Soybean value. Bushel ; Elevator ; Statistics ; Quality (philosophy) ; Mathematics ; Agricultural science ; Agricultural engineering ; Environmental science ; Geography ; Engineering Spectroscopy and Chemometric Analyses ; Food composition and properties ; Animal Nutrition and Physiology
Authors: Tunan Chen | Kang Li | Fengxiang Ma | Xinjie Qiu | Zongjia Qiu | Zhenghai Liao | Guoqiang Zhang
Source: Sensors (article, 2021-12-07)
Field: Chemistry — Spectroscopy

Application of Excimer Lamp in Quantitative Detection of SF6 Decomposition Component SO2 Accurate quantitative detection for trace gas has long been the center of failure diagnosis for gas-insulated equipment. An absorption spectroscopy-based detection system was developed for trace SF<sub>6</sub> decomposition SO<sub>2</sub> detection in this paper. In order to reduce interference from other decomposition, ultraviolet spectrum of SO<sub>2</sub> was selected for detection. Firstly, an excimer lamp was developed in this paper as the excitation of the absorption spectroscopy compared with regular light sources with electrodes, such as electrodeless lamps that are more suitable for long-term monitoring. Then, based on the developed excimer lamp, a detection system for trace SO<sub>2</sub> was established. Next, a proper absorption peak was selected by calculating spectral derivative for further analysis. Experimental results indicated that good linearity existed between the absorbance and concentration of SO<sub>2</sub> at the chosen absorption peak. Moreover, the detection limit of the proposed detection system could reach the level of 10<sup>-7</sup>. The results of this paper could serve as a guide for the application of excimer lamp in online monitoring for SF<sub>6</sub>-insulated equipment. Detection limit ; Absorbance ; Absorption spectroscopy ; Absorption (acoustics) ; Materials science ; Analytical Chemistry (journal) ; Excimer ; Spectroscopy ; Decomposition ; Ultraviolet ; Chemistry ; Optics ; Optoelectronics ; Fluorescence ; Chromatography Spectroscopy and Laser Applications ; Air Quality Monitoring and Forecasting ; Gas Sensing Nanomaterials and Sensors
Authors: Ananth Prakash | David García‐Seisdedos | Shengbo Wang | Deepti J Kundu | Andrew Collins | Nancy George | Pablo Moreno | Irene Papatheodorou | Andrew R. Jones | Juan Antonio Vizcaíno
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-09-11)
Field: Chemistry — Spectroscopy

An integrated view of baseline protein expression in human tissues Abstract The availability of proteomics datasets in the public domain, and in the PRIDE database in particular, has increased dramatically in recent years. This unprecedented large-scale availability of data provides an opportunity for combined analyses of datasets to get organism-wide protein abundance data in a consistent manner. We have reanalysed 24 public proteomics datasets from healthy human individuals, to assess baseline protein abundance in 31 organs. We defined tissue as a distinct functional or structural region within an organ. Overall, the aggregated dataset contains 67 healthy tissues, corresponding to 3,119 mass spectrometry runs covering 498 samples, coming from 489 individuals. We compared protein abundances between the different organs and studied the distribution of proteins across organs. We also compared the results with data generated in analogous studies. We also performed gene ontology and pathway enrichment analyses to identify organ-specific enriched biological processes and pathways. As a key point, we have integrated the protein abundance results into the resource Expression Atlas, where it can be accessed and visualised either individually or together with gene expression data coming from transcriptomics datasets. We believe this is a good mechanism to make proteomics data more accessible for life scientists. Proteomics ; Human Protein Atlas ; Computational biology ; Gene ontology ; Biology ; Transcriptome ; Protein expression ; Baseline (sea) ; Ontology ; Bioinformatics ; Gene expression ; Computer science ; Gene ; Genetics Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Metabolomics and Mass Spectrometry Studies
Authors: Chloe A. N. Gerak | Sophia Y. Cho | Maxim Kolesnikov | Mark Okon | M.E.P. Murphy | Richard B. Sessions | Michel Roberge | Lawrence P. McIntosh
Source: Journal of Biological Chemistry (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Biophysical characterization of the ETV6 PNT domain polymerization interfaces ETV6 is an E26 transformation specific family transcriptional repressor that self-associates by its PNT domain to facilitate cooperative DNA binding. Chromosomal translocations frequently generate constitutively active oncoproteins with the ETV6 PNT domain fused to the kinase domain of one of many protein tyrosine kinases. Although an attractive target for therapeutic intervention, the propensity of the ETV6 PNT domain to polymerize via the tight head-to-tail association of two relatively flat interfaces makes it challenging to identify suitable small molecule inhibitors of this protein-protein interaction. Herein, we provide a comprehensive biophysical characterization of the ETV6 PNT domain interaction interfaces to aid future drug discovery efforts and help define the mechanisms by which its self-association mediates transcriptional repression. Using NMR spectroscopy, X-ray crystallography, and molecular dynamics simulations, along with amide hydrogen exchange measurements, we demonstrate that monomeric PNT domain variants adopt very stable helical bundle folds that do not change in conformation upon self-association into heterodimer models of the ETV6 polymer. Surface plasmon resonance-monitored alanine scanning mutagenesis studies identified hot spot regions within the self-association interfaces. These regions include both central hydrophobic residues and flanking salt-bridging residues. Collectively, these studies indicate that small molecules targeted to these hydrophobic or charged regions within the relatively rigid interfaces could potentially serve as orthosteric inhibitors of ETV6 PNT domain polymerization. Alanine scanning ; Repressor ; Chemistry ; Mutagenesis ; Biology ; Biophysics ; Biochemistry ; Cell biology ; Transcription factor ; Mutation ; Gene Enzyme Structure and Function ; Genomics and Chromatin Dynamics ; Monoclonal and Polyclonal Antibodies Research
Authors: Mehrdad Yaghoobi | Tudor Grecu | Stephanie Brookes | Colin J. Campbell
Source: Analytical Chemistry (article, 2021-10-22)
Field: Chemistry — Physical and Theoretical Chemistry

Automatic Cocrystal Detection by Raman Spectral Deconvolution-Based Novelty Analysis Cocrystals are important molecular adducts that have many advantages as a means of modifying the physicochemical properties of active pharmaceutical ingredients, including taste masking and improved solubility, bioavailability, and stability. As a result, the discovery of new cocrystals is of great interest to commercial drug discovery programs. Time-consuming manual analysis of the large volumes of data that emerge from large-scale cocrystal screening programs of up to 1000s of preparations poses a challenge. Raman spectroscopy has been shown to discriminate between cocrystals and physical mixtures and is easy to automate, allowing rapid screening of large numbers of potential cocrystals, but the spectral features that encode the information are often subtle (e.g., slight changes in peak positions or intensities). We have employed an automated signal processing routine based on a sparse decomposition algorithm to speed up the data processing steps while maintaining the accuracy of a trained spectroscopist. We used our algorithm to screen 31 potential cocrystal preparations and found that through the use of a computationally generated threshold, we could achieve a clear classification of cocrystals and physical mixtures in less than a minute, compared to several hours manually. Cocrystal ; Chemistry ; Drug discovery ; Biological system ; Pattern recognition (psychology) ; Artificial intelligence ; Computer science ; Molecule ; Organic chemistry Crystallography and molecular interactions ; Crystallization and Solubility Studies ; Computational Drug Discovery Methods