High throughput calculation of local spatial autocorrelation length for label-free diagnosis of tissue biopsy

2018 ◽  
Author(s):  
Masanori Takabayashi ◽  
Hassaan Majeed ◽  
Andre Kajdacsy-Balla ◽  
Gabriel Popescu
Keyword(s):  
Spatial Autocorrelation ◽  
High Throughput ◽  
Label Free ◽  
Tissue Biopsy ◽  
Autocorrelation Length ◽  
Local Spatial Autocorrelation

scholarly journals Recognizing the Aggregation Characteristics of Extreme Precipitation Events Using Spatio-Temporal Scanning and the Local Spatial Autocorrelation Model

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 218
Author(s):  
Changjun Wan ◽  
Changxiu Cheng ◽  
Sijing Ye ◽  
Shi Shen ◽  
Ting Zhang
Keyword(s):  
Spatial Autocorrelation ◽  
Extreme Precipitation ◽  
Eastern China ◽  
Temporal Aggregation ◽  
Global Changes ◽  
Percentile Method ◽  
Extreme Precipitation Events ◽  
Spatio Temporal ◽  
Precipitation Events ◽  
Local Spatial Autocorrelation

Precipitation is an essential climate variable in the hydrologic cycle. Its abnormal change would have a serious impact on the social economy, ecological development and life safety. In recent decades, many studies about extreme precipitation have been performed on spatio-temporal variation patterns under global changes; little research has been conducted on the regionality and persistence, which tend to be more destructive. This study defines extreme precipitation events by percentile method, then applies the spatio-temporal scanning model (STSM) and the local spatial autocorrelation model (LSAM) to explore the spatio-temporal aggregation characteristics of extreme precipitation, taking China in July as a case. The study result showed that the STSM with the LSAM can effectively detect the spatio-temporal accumulation areas. The extreme precipitation events of China in July 2016 have a significant spatio-temporal aggregation characteristic. From the spatial perspective, China’s summer extreme precipitation spatio-temporal clusters are mainly distributed in eastern China and northern China, such as Dongting Lake plain, the Circum-Bohai Sea region, Gansu, and Xinjiang. From the temporal perspective, the spatio-temporal clusters of extreme precipitation are mainly distributed in July, and its occurrence was delayed with an increase in latitude, except for in Xinjiang, where extreme precipitation events often take place earlier and persist longer.

scholarly journals Development of a Robust High-Throughput Screening Platform for Inhibitors of the Striatal-Enriched Tyrosine Phosphatase (STEP)

2021 ◽  
Vol 22 (9) ◽  
pp. 4417
Author(s):  
Lester J Lambert ◽  
Stefan Grotegut ◽  
Maria Celeridad ◽  
Palak Gosalia ◽  
Laurent JS De Backer ◽  
...  
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
Tyrosine Kinases ◽  
High Throughput Screening ◽  
Kinase Inhibitors ◽  
Tyrosine Phosphatase ◽  
Protein Tyrosine Phosphatases ◽  
Synaptic Function ◽  
Label Free ◽  
Protein Tyrosine

Many human diseases are the result of abnormal expression or activation of protein tyrosine kinases (PTKs) and protein tyrosine phosphatases (PTPs). Not surprisingly, more than 30 tyrosine kinase inhibitors (TKIs) are currently in clinical use and provide unique treatment options for many patients. PTPs on the other hand have long been regarded as “undruggable” and only recently have gained increased attention in drug discovery. Striatal-enriched tyrosine phosphatase (STEP) is a neuron-specific PTP that is overactive in Alzheimer’s disease (AD) and other neurodegenerative and neuropsychiatric disorders, including Parkinson’s disease, schizophrenia, and fragile X syndrome. An emergent model suggests that the increase in STEP activity interferes with synaptic function and contributes to the characteristic cognitive and behavioral deficits present in these diseases. Prior efforts to generate STEP inhibitors with properties that warrant clinical development have largely failed. To identify novel STEP inhibitor scaffolds, we developed a biophysical, label-free high-throughput screening (HTS) platform based on the protein thermal shift (PTS) technology. In contrast to conventional HTS using STEP enzymatic assays, we found the PTS platform highly robust and capable of identifying true hits with confirmed STEP inhibitory activity and selectivity. This new platform promises to greatly advance STEP drug discovery and should be applicable to other PTP targets.

scholarly journals Development of a Novel Label-Free and High-Throughput Arginase-1 Assay Using Self-Assembled Monolayer Desorption Ionization Mass Spectrometry

2021 ◽  
pp. 247255522110006
Author(s):  
Michael D. Scholle ◽  
Zachary A. Gurard-Levin
Keyword(s):  
Mass Spectrometry ◽  
Drug Discovery ◽  
High Throughput ◽  
Ionization Mass Spectrometry ◽  
Ionization Mass ◽  
Label Free ◽  
Desorption Ionization ◽  
Arginase 1 ◽  
Self Assembled ◽  
High Throughput Assay

Arginase-1, an enzyme that catalyzes the reaction of L-arginine to L-ornithine, is implicated in the tumor immune response and represents an interesting therapeutic target in immuno-oncology. Initiating arginase drug discovery efforts remains a challenge due to a lack of suitable high-throughput assay methodologies. This report describes the combination of self-assembled monolayers and matrix-assisted laser desorption ionization mass spectrometry to enable the first label-free and high-throughput assay for arginase activity. The assay was optimized for kinetically balanced conditions and miniaturized, while achieving a robust assay (Z-factor > 0.8) and a significant assay window [signal-to-background ratio > 20] relative to fluorescent approaches. To validate the assay, the inhibition of the reference compound nor-NOHA (Nω-hydroxy-nor-L-arginine) was evaluated, and the IC50 measured to be in line with reported results (IC50 = 180 nM). The assay was then used to complete a screen of 175,000 compounds, demonstrating the high-throughput capacity of the approach. The label-free format also eliminates opportunities for false-positive results due to interference from library compounds and optical readouts. The assay methodology described here enables new opportunities for drug discovery for arginase and, due to the assay flexibility, can be more broadly applicable for measuring other amino acid–metabolizing enzymes.

Label free high throughput screening for apoptosis inducing chemicals using time-lapse microscopy signal processing

APOPTOSIS ◽  
2014 ◽  
Vol 19 (9) ◽  
pp. 1411-1418 ◽  
Author(s):  
Obaid Aftab ◽  
Madiha Nazir ◽  
Mårten Fryknäs ◽  
Ulf Hammerling ◽  
Rolf Larsson ◽  
...  
Keyword(s):  
Signal Processing ◽  
High Throughput ◽  
High Throughput Screening ◽  
Time Lapse ◽  
Label Free ◽  
Time Lapse Microscopy

Diffractive Protein Gratings as Optically Active Transducers for High-Throughput Label-free Immunosensing

2017 ◽  
Vol 89 (17) ◽  
pp. 9002-9008 ◽  
Author(s):  
Miquel Avella-Oliver ◽  
Javier Carrascosa ◽  
Rosa Puchades ◽  
Ángel Maquieira
Keyword(s):  
High Throughput ◽  
Optically Active ◽  
Label Free

scholarly journals Label-Free Whole Cell Biosensing for High-Throughput Discovery of Activators and Inhibitors Targeting G Protein-Activated Inwardly Rectifying Potassium Channels

ACS Omega ◽  
2018 ◽  
Vol 3 (11) ◽  
pp. 14814-14823 ◽  
Author(s):  
Katrin M. Krebs ◽  
Eva M. Pfeil ◽  
Katharina Simon ◽  
Manuel Grundmann ◽  
Felix Häberlein ◽  
...  
Keyword(s):  
Potassium Channels ◽  
G Protein ◽  
High Throughput ◽  
Label Free ◽  
Whole Cell ◽  
Inwardly Rectifying Potassium Channels ◽  
Inwardly Rectifying

The local spatial autocorrelation and the kernel method for identifying black zones

2003 ◽  
Vol 35 (6) ◽  
pp. 991-1004 ◽  
Author(s):  
Benoı̂t Flahaut ◽  
Michel Mouchart ◽  
Ernesto San Martin ◽  
Isabelle Thomas
Keyword(s):  
Spatial Autocorrelation ◽  
Kernel Method ◽  
Local Spatial Autocorrelation

scholarly journals Integration of an In Situ MALDI-Based High-Throughput Screening Process: A Case Study with Receptor Tyrosine Kinase c-MET

2017 ◽  
Vol 22 (10) ◽  
pp. 1203-1210 ◽  
Author(s):  
Katrin Beeman ◽  
Jens Baumgärtner ◽  
Manuel Laubenheimer ◽  
Karlheinz Hergesell ◽  
Martin Hoffmann ◽  
...  
Keyword(s):  
Drug Discovery ◽  
High Throughput ◽  
High Throughput Screening ◽  
Maldi Ms ◽  
Kinase Assay ◽  
Label Free ◽  
Screening Process ◽  
Label Free Detection ◽  
Ic50 Values

Mass spectrometry (MS) is known for its label-free detection of substrates and products from a variety of enzyme reactions. Recent hardware improvements have increased interest in the use of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS for high-throughput drug discovery. Despite interest in this technology, several challenges remain and must be overcome before MALDI-MS can be integrated as an automated “in-line reader” for high-throughput drug discovery. Two such hurdles include in situ sample processing and deposition, as well as integration of MALDI-MS for enzymatic screening assays that usually contain high levels of MS-incompatible components. Here we adapt our c-MET kinase assay to optimize for MALDI-MS compatibility and test its feasibility for compound screening. The pros and cons of the Echo (Labcyte) as a transfer system for in situ MALDI-MS sample preparation are discussed. We demonstrate that this method generates robust data in a 1536-grid format. We use the MALDI-MS to directly measure the ratio of c-MET substrate and phosphorylated product to acquire IC50 curves and demonstrate that the pharmacology is unaffected. The resulting IC50 values correlate well between the common label-based capillary electrophoresis and the label-free MALDI-MS detection method. We predict that label-free MALDI-MS-based high-throughput screening will become increasingly important and more widely used for drug discovery.

scholarly journals MALDIViz: A Comprehensive Informatics Tool for MALDI-MS Data Visualization and Analysis

2017 ◽  
Vol 22 (10) ◽  
pp. 1246-1252 ◽  
Author(s):  
Kishore Kumar Jagadeesan ◽  
Simon Ekström
Keyword(s):  
Mass Spectrometry ◽  
High Throughput ◽  
High Throughput Screening ◽  
Web Application ◽  
Low Cost ◽  
Maldi Ms ◽  
Ionization Mass ◽  
Label Free ◽  
Label Free Detection ◽  
R Shiny

Recently, mass spectrometry (MS) has emerged as an important tool for high-throughput screening (HTS) providing a direct and label-free detection method, complementing traditional fluorescent and colorimetric methodologies. Among the various MS techniques used for HTS, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) provides many of the characteristics required for high-throughput analyses, such as low cost, speed, and automation. However, visualization and analysis of the large datasets generated by HTS MALDI-MS can pose significant challenges, especially for multiparametric experiments. The datasets can be generated fast, and the complexity of the experimental data (e.g., screening many different sorbent phases, the sorbent mass, and the load, wash, and elution conditions) makes manual data analysis difficult. To address these challenges, a comprehensive informatics tool called MALDIViz was developed. This tool is an R-Shiny-based web application, accessible independently of the operating system and without the need to install any program locally. It has been designed to facilitate easy analysis and visualization of MALDI-MS datasets, comparison of multiplex experiments, and export of the analysis results to high-quality images.

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