A5073538531- Mass Spectrometry Techniques and Applications
- Nuclear Physics and Applications
- Cell Image Analysis Techniques
- Advanced Proteomics Techniques and Applications
- Metabolomics and Mass Spectrometry Studies
- Big Data and Business Intelligence
- Radiomics and Machine Learning in Medical Imaging
- Spectroscopy Techniques in Biomedical and Chemical Research
- CRISPR and Genetic Engineering
- Single-cell and spatial transcriptomics
- Ion-surface interactions and analysis
- Cholesterol and Lipid Metabolism
- COVID-19 diagnosis using AI
- Cardiac electrophysiology and arrhythmias
- Microbial Metabolic Engineering and Bioproduction
- Advanced biosensing and bioanalysis techniques
- Lipid metabolism and biosynthesis
- Cancer, Lipids, and Metabolism
- Generative Adversarial Networks and Image Synthesis
- Economic and Technological Developments in Russia
- Antimicrobial Peptides and Activities
- Brain Tumor Detection and Classification
- Advanced Chemical Sensor Technologies
- Transgenic Plants and Applications
- Analytical chemistry methods development
University of Illinois Urbana-Champaign
2020-2025
Center for Research in Molecular Medicine and Chronic Diseases
2017
Universidade de Santiago de Compostela
2017
Abstract Spatial omics technologies can reveal the molecular intricacy of brain. While mass spectrometry imaging (MSI) provides spatial localization compounds, comprehensive biochemical profiling at a brain-wide scale in three dimensions by MSI with single-cell resolution has not been achieved. We demonstrate complementary and mapping using MEISTER, an integrative experimental computational (MS) framework. Our framework integrates deep-learning-based reconstruction that accelerates...
Abstract Peptidergic dense-core vesicles are involved in packaging and releasing neuropeptides peptide hormones—critical processes underlying brain, endocrine exocrine function. Yet, the heterogeneity within these organelles, even for morphologically defined vesicle types, is not well characterized because of their small volumes. We present image-guided, high-throughput mass spectrometry-based protocols to chemically profile large populations both lucent lipid contents, allowing observation...
In this work we propose a new method for the rhythm classification of short single-lead ECG records, using set high-level and clinically meaningful features provided by abductive interpretation records.These include morphological rhythm-related that are used to build two classifiers: one evaluates record globally, aggregated values each feature; another as sequence, Recurrent Neural Network fed with individual detected heartbeat.The classifiers finally combined stacking technique, providing...
The brain consists of organized ensembles cells that exhibit distinct morphologies, cellular connectivity, and dynamic biochemistries control the executive functions an organism. However, relationships between chemical heterogeneity, cell function, phenotype are not always understood. Recent advancements in matrix-assisted laser desorption/ionization mass spectrometry have enabled high-throughput, multiplexed analysis single cells, capable resolving hundreds molecules each spectrum. We...
Abstract Plant bioengineering is a time-consuming and labor-intensive process with no guarantee of achieving desired traits. Here, we present fast, automated, scalable, high-throughput pipeline for plant (FAST-PB) in maize (Zea mays) Nicotiana benthamiana. FAST-PB enables genome editing product characterization by integrating automated biofoundry engineering callus protoplast cells single-cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We first demonstrated...
Mass spectrometry imaging (MSI) allows for untargeted mapping of the chemical composition tissues with attomole detection limits. MSI using Fourier transform (FT)-based mass spectrometers, such as FT-ion cyclotron resonance (FT-ICR), grants ability to examine space unmatched resolution and accuracy. However, direct large tissue samples FT-ICR is slow. In this work, we present an approach that combines subspace modeling ICR temporal signals compressed sensing accelerate high-resolution MSI. A...
The mammalian brain contains ∼20,000 distinct lipid species that contribute to its structural organization and function. profiles of cells change in response a variety cellular signals environmental conditions result modulation cell function through alteration phenotype. limited sample material combined with the vast chemical diversity lipids makes comprehensive profiling individual challenging. Here, we leverage resolving power 21 T Fourier-transform ion cyclotron resonance (FTICR) mass...
Improved throughput of analysis and lowered limits detection have allowed single-cell chemical to go beyond the a few molecules in such volume-limited samples, enabling researchers characterize different functional states individual cells. Image-guided mass spectrometry leverages optical fluorescence microscopy high-throughput cellular subcellular targets. In this work, we propose DATSIGMA (DAta-driven Tools for Single-cell using Image-Guided MAss spectrometry), workflow based on data-driven...
We present a subspace method that accelerates data acquisition using Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry imaging (MSI). For MSI of biological tissue samples, there is finite number heterogeneous types with distinct chemical profiles introduce redundancy in the high-dimensional measurements. Our model exploits measured from whole-slice samples by decomposing transient signals into linear combinations set basis transients desired spectral resolution. This...
Nasogastric tubes (NGTs) are feeding that inserted through the nose into stomach to deliver nutrition or medication. If not placed correctly, they can cause serious harm, even death patients. Recent AI developments demonstrate feasibility of robustly detecting NGT placement from Chest X-ray images reduce risks sub-optimally critically NGTs being missed delayed in their detection, but gaps remain clinical practice integration. In this study, we present a human-centered approach problem and...
Abstract Plant bioengineering is a time-consuming and labor-intensive process, with no guarantee of achieving the desired trait. Here we report fast, automated, scalable, high-throughput pipeline for plant (FAST-PB). FAST-PB achieves gene cloning, genome editing, product characterization by integrating automated biofoundry engineering callus protoplast cells single cell matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). We first demonstrate that can streamline Golden...
Elucidating the spatial-biochemical organization of brain across different scales produces invaluable insight into molecular intricacy brain. While mass spectrometry imaging (MSI) provides spatial localization compounds, comprehensive chemical profiling at a brain-wide scale in three dimensions by MSI with single-cell resolution has not been achieved. We demonstrate complementary and biochemical mapping via MEISTER, an integrative experimental computational framework. MEISTER integrates...
Biomedical imaging datasets are often small and biased, meaning that real-world performance of predictive models can be substantially lower than expected from internal testing. This work proposes using generative image editing to simulate dataset shifts diagnose failure modes biomedical vision models; this used in advance deployment assess readiness, potentially reducing cost patient harm. Existing methods produce undesirable changes, with spurious correlations learned due the co-occurrence...
Abstract Disclosure: C.P. Schane: None. A. Nelczyk: C. Chen: H. Vidana Gamage: M. Kadiri: M.T. McHenry: S. Bendre: N. Krawczynska: M.A. Henn: D.C. Castro: J. R.I. Tejeda: Hsiao: N.J. Engeseth: J.V. Sweedler: M.K. Wendt: T. Fan: W.G. Helferich: E.R. Nelson: One in eight women will develop breast cancer her lifetime, with metastasis being the leading cause of mortality. Once cells colonize metastatic site, they do not always immediately begin to proliferate, but remain dormant. These dormant...
Mass spectrometry imaging (MSI) allows for untargeted mapping of the chemical compositions tissues with attomole detection limits. MSI using Fourier transform-based mass spectrometers, such as FT-ion cyclotron resonance (FT-ICR), grants ability to examine space unmatched resolution and accuracy. However, direct large tissue samples on FT-ICR is restrictively slow. In this work, we present an approach that combines subspace modeling ICR temporal signals compressed sensing accelerate...
Mass spectrometry imaging (MSI) allows for untargeted mapping of the chemical compositions tissues with attomole detection limits. MSI using Fourier transform-based mass spectrometers, such as FT-ion cyclotron resonance (FT-ICR), grants ability to examine space unmatched resolution and accuracy. However, direct large tissue samples on FT-ICR is restrictively slow. In this work, we present an approach that combines subspace modeling ICR temporal signals compressed sensing accelerate...