scholarly journals Detecting and Correcting False Transients in Calcium Imaging

2018 ◽  
Author(s):  
Jeff L. Gauthier ◽  
Sue Ann Koay ◽  
Edward H. Nieh ◽  
David W. Tank ◽  
Jonathan W. Pillow ◽  
...  
Keyword(s):  
Calcium Imaging ◽  
Large Scale ◽  
Time Course ◽  
Robust Estimator ◽  
Neural Function ◽  
Visualization Tool ◽  
Large Dataset ◽  
Large Populations ◽  
Automated Methods ◽  
Insight Into

AbstractPopulation recordings of calcium activity are a major source of insight into neural function. Large dataset sizes often require automated methods, but automation can introduce errors that are difficult to detect. Here we show that automatic time course estimation can sometimes lead to significant misattribution errors, in which fluorescence is ascribed to the wrong cell. Misattribution arises when the shapes of overlapping cells are imperfectly defined, or when entire cells or processes are not identified, and misattribution can even be produced by methods specifically designed to handle overlap. To diagnose this problem, we develop a transient-by-transient metric and a visualization tool that allow users to quickly assess the degree of misattribution in large populations. To filter out misattribution, we also design a robust estimator that explicitly accounts for contaminating signals in a generative model. Our methods can be combined with essentially any cell finding technique, empowering users to diagnose and correct at large scale a problem that has the potential to significantly alter scientific conclusions.

scholarly journals CloneSifter: enrichment of rare clones from heterogeneous cell populations

BMC Biology ◽  
2020 ◽  
Vol 18 (1) ◽  
Author(s):  
David Feldman ◽  
FuNien Tsai ◽  
Anthony J. Garrity ◽  
Ryan O’Rourke ◽  
Lisa Brenan ◽  
...  
Keyword(s):  
Large Scale ◽  
Molecular Mechanisms ◽  
Cancer Metastasis ◽  
Population Level ◽  
Fitness Assessment ◽  
Large Populations ◽  
Organismal Development ◽  
Insight Into

Abstract Background Many biological processes, such as cancer metastasis, organismal development, and acquisition of resistance to cytotoxic therapy, rely on the emergence of rare sub-clones from a larger population. Understanding how the genetic and epigenetic features of diverse clones affect clonal fitness provides insight into molecular mechanisms underlying selective processes. While large-scale barcoding with NGS readout has facilitated cellular fitness assessment at the population level, this approach does not support characterization of clones prior to selection. Single-cell genomics methods provide high biological resolution, but are challenging to scale across large populations to probe rare clones and are destructive, limiting further functional analysis of important clones. Results Here, we develop CloneSifter, a methodology for tracking and enriching rare clones throughout their response to selection. CloneSifter utilizes a CRISPR sgRNA-barcode library that facilitates the isolation of viable cells from specific clones within the barcoded population using a sequence-specific retrieval reporter. We demonstrate that CloneSifter can measure clonal fitness of cancer cell models in vitro and retrieve targeted clones at abundance as low as 1 in 1883 in a heterogeneous cell population. Conclusions CloneSifter provides a means to track and access specific and rare clones of interest across dynamic changes in population structure to comprehensively explore the basis of these changes.

scholarly journals Large Scaled Topographic Mapping and Issues in Depicting VGI and Open Data

2021 ◽  
Vol 4 ◽  
pp. 1-6
Author(s):  
Benedikt Hajek ◽  
Karel Kriz
Keyword(s):  
Large Scale ◽  
Open Data ◽  
Quality Standard ◽  
Topographic Mapping ◽  
Quality Research ◽  
Contour Lines ◽  
New Challenges ◽  
New Processing ◽  
Automated Methods ◽  
Insight Into

Abstract. Open data and geospatial data collected by volunteers are nowadays easy to obtain and available with worldwide coverage through projects like OpenStreetMap. However, the use of these datasets leads to new challenges in depiction especially in the field of large scale topographic cartography. In addition to quality research, new processing and depiction methods for integrating these data are emerging. In the course of this work, specific problems of maps based on OpenStreetMap and Open Data elevation models are pointed out and possible solutions are introduced. In addition, a method for the preprocessing of contour lines is presented and the process flow is described in more detail. The goal of this work is to give insight into a toolbox of specially adapted and (semi-)automated methods. In this way, the quality standard of the depiction of topographic maps based on Open Data is to be increased, but also limitations are being shown.

The Use of Medical Record Linkage for Population and Genetic Studies

1969 ◽  
Vol 08 (01) ◽  
pp. 07-11 ◽  
Author(s):  
H. B. Newcombe
Keyword(s):  
Record Linkage ◽  
Large Scale ◽  
Medical Record Linkage ◽  
Canadian Province ◽  
Genetic Studies ◽  
Parental Characteristics ◽  
Family Histories ◽  
The Family ◽  
Large Populations ◽  
Machine Readable

Methods are described for deriving personal and family histories of birth, marriage, procreation, ill health and death, for large populations, from existing civil registrations of vital events and the routine records of ill health. Computers have been used to group together and »link« the separately derived records pertaining to successive events in the lives of the same individuals and families, rapidly and on a large scale. Most of the records employed are already available as machine readable punchcards and magnetic tapes, for statistical and administrative purposes, and only minor modifications have been made to the manner in which these are produced.As applied to the population of the Canadian province of British Columbia (currently about 2 million people) these methods have already yielded substantial information on the risks of disease: a) in the population, b) in relation to various parental characteristics, and c) as correlated with previous occurrences in the family histories.

scholarly journals Morphogenesis and evolution mechanisms of bacterially-induced struvite

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tian-Lei Zhao ◽  
Han Li ◽  
Hao-Fan Jiang ◽  
Qi-Zhi Yao ◽  
Ying Huang ◽  
...  
Keyword(s):  
Time Course ◽  
Carboxyl Groups ◽  
Precipitation Process ◽  
Phosphate Content ◽  
Biomimetic Mineralization ◽  
Struvite Precipitation ◽  
Growth Habits ◽  
Two Stages ◽  
Relevant Work ◽  
Insight Into

AbstractBacteria are able to induce struvite precipitation, and modify struvite morphology, leading to the mineral with various growth habits. However, the relevant work involving the morphogenesis is limited, thereby obstructing our understanding of bacterially mediated struvite mineralization. Here, an actinomycete Microbacterium marinum sp. nov. H207 was chosen to study its effect on struvite morphology. A combination of bacterial mineralization and biomimetic mineralization techniques was adopted. The bacterial mineralization results showed that strain H207 could induce the formation of struvite with grouping structure (i.e., a small coffin-like crystal grown on a large trapezoid-like substrate crystal), and the overgrowth structure gradually disappeared, while the substrate crystal further evolved into coffin-like, and quadrangular tabular morphology with time. The biomimetic experiments with different organic components confirmed that the soluble macromolecules rich in electronegative carboxyl groups secreted by strain H207 dominate the formation of the struvite grouping. The time-course biomimetic experiments with supernatant testified that the increase in pH and NH4+ content promoted the evolution of crystal habits. Moreover, the evolution process of substrate crystal can be divided into two stages. At the first stage, the crystal grew along the crystallographic b axis. At the later stage, coupled dissolution–precipitation process occurred, and the crystals grew along the corners (i.e., [110] and [1-10] directions). In the case of dissolution, it was also found that the (00-1) face of substrate crystal preferentially dissolved, which results from the low initial phosphate content and high PO43− density on this face. As a result, present work can provide a deeper insight into bio-struvite mineralization.

scholarly journals Time Course of Redox Biomarkers in COVID-19 Pneumonia: Relation with Inflammatory, Multiorgan Impairment Biomarkers and CT Findings

Antioxidants ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1126
Author(s):  
Tijana Kosanovic ◽  
Dragan Sagic ◽  
Vladimir Djukic ◽  
Marija Pljesa-Ercegovac ◽  
Ana Savic-Radojevic ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Time Course ◽  
Redox Homeostasis ◽  
Original Data ◽  
Advanced Oxidation Protein Products ◽  
Oxidative Stress Parameters ◽  
Systemic Oxidative Stress ◽  
Dependent Relation ◽  
Organ Tissue ◽  
Insight Into

Although the original data on systemic oxidative stress in COVID-19 patients have recently started to emerge, we are still far from a complete profile of changes in patients’ redox homeostasis. We aimed to assess the extent of oxidative damage of proteins, lipids and DNA during the course of acute disease, as well as their association with CT pulmonary patterns. In order to obtain more insight into the origin of the systemic oxidative stress, the observed parameters were correlated with inflammatory biomarkers and biomarkers of multiorgan impairment. In this prospective study, we included 58 patients admitted between July and October 2020 with COVID-19 pneumonia. Significant changes in malondialdehyde, 8-hydroxy-2’-deoxyguanosine and advanced oxidation protein products levels exist during the course of COVID-19. Special emphasis should be placed on the fact that the pattern of changes differs between non-hospitalized and hospitalized individuals. Our results point to the time-dependent relation of oxidative stress parameters with inflammatory and multiorgan impairment biomarkers, as well as pulmonary patterns in COVID-19 pneumonia patients. Correlation between redox biomarkers and immunological or multiorgan impairment biomarkers, as well as pulmonary CT pattern, confirms the suggested involvement of neutrophils networks, IL-6 production, along with different organ/tissue involvement in systemic oxidative stress in COVID-19.

scholarly journals Lipidomics Provides New Insight into Pathogenesis and Therapeutic Targets of the Ischemia—Reperfusion Injury

2021 ◽  
Vol 22 (6) ◽  
pp. 2798
Author(s):  
Zoran Todorović ◽  
Siniša Đurašević ◽  
Maja Stojković ◽  
Ilijana Grigorov ◽  
Slađan Pavlović ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Time Course ◽  
Membrane Lipids ◽  
Lipid Analysis ◽  
Cell Damage ◽  
Ischemia Reperfusion ◽  
Enzyme Inactivation ◽  
Critical Event ◽  
Tissue Ischemia ◽  
Insight Into

Lipids play an essential role in both tissue protection and damage. Tissue ischemia creates anaerobic conditions in which enzyme inactivation occurs, and reperfusion can initiate oxidative stress that leads to harmful changes in membrane lipids, the formation of aldehydes, and chain damage until cell death. The critical event in such a series of harmful events in the cell is the unwanted accumulation of fatty acids that leads to lipotoxicity. Lipid analysis provides additional insight into the pathogenesis of ischemia/reperfusion (I/R) disorders and reveals new targets for drug action. The profile of changes in the composition of fatty acids in the cell, as well as the time course of these changes, indicate both the mechanism of damage and new therapeutic possibilities. A therapeutic approach to reperfusion lipotoxicity involves attenuation of fatty acids overload, i.e., their transport to adipose tissue and/or inhibition of the adverse effects of fatty acids on cell damage and death. The latter option involves using PPAR agonists and drugs that modulate the transport of fatty acids via carnitine into the interior of the mitochondria or the redirection of long-chain fatty acids to peroxisomes.

scholarly journals The Effectiveness of Multi-Label Classification and Multi-Output Regression in Social Trait Recognition

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4127
Author(s):  
Will Farlessyost ◽  
Kelsey-Ryan Grant ◽  
Sara R. Davis ◽  
David Feil-Seifer ◽  
Emily M. Hand
Keyword(s):  
Social Interactions ◽  
First Impressions ◽  
Social Traits ◽  
Judicial Proceedings ◽  
Facial Attributes ◽  
Future Work ◽  
Automated Methods ◽  
Insight Into ◽  
Social Trait ◽  
Better Than

First impressions make up an integral part of our interactions with other humans by providing an instantaneous judgment of the trustworthiness, dominance and attractiveness of an individual prior to engaging in any other form of interaction. Unfortunately, this can lead to unintentional bias in situations that have serious consequences, whether it be in judicial proceedings, career advancement, or politics. The ability to automatically recognize social traits presents a number of highly useful applications: from minimizing bias in social interactions to providing insight into how our own facial attributes are interpreted by others. However, while first impressions are well-studied in the field of psychology, automated methods for predicting social traits are largely non-existent. In this work, we demonstrate the feasibility of two automated approaches—multi-label classification (MLC) and multi-output regression (MOR)—for first impression recognition from faces. We demonstrate that both approaches are able to predict social traits with better than chance accuracy, but there is still significant room for improvement. We evaluate ethical concerns and detail application areas for future work in this direction.

scholarly journals Geo-Spatial Analysis of Population Density and Annual Income to Identify Large-Scale Socio-Demographic Disparities

2021 ◽  
Vol 10 (7) ◽  
pp. 432
Author(s):  
Nicolai Moos ◽  
Carsten Juergens ◽  
Andreas P. Redecker
Keyword(s):  
Population Density ◽  
Large Scale ◽  
Methodological Approach ◽  
Spatial Relationship ◽  
Postal Code ◽  
Annual Income ◽  
Choropleth Maps ◽  
Clustering Approach ◽  
Relationship Of ◽  
Insight Into

This paper describes a methodological approach that is able to analyse socio-demographic and -economic data in large-scale spatial detail. Based on the two variables, population density and annual income, one investigates the spatial relationship of these variables to identify locations of imbalance or disparities assisted by bivariate choropleth maps. The aim is to gain a deeper insight into spatial components of socioeconomic nexuses, such as the relationships between the two variables, especially for high-resolution spatial units. The used methodology is able to assist political decision-making, target group advertising in the field of geo-marketing and for the site searches of new shop locations, as well as further socioeconomic research and urban planning. The developed methodology was tested in a national case study in Germany and is easily transferrable to other countries with comparable datasets. The analysis was carried out utilising data about population density and average annual income linked to spatially referenced polygons of postal codes. These were disaggregated initially via a readapted three-class dasymetric mapping approach and allocated to large-scale city block polygons. Univariate and bivariate choropleth maps generated from the resulting datasets were then used to identify and compare spatial economic disparities for a study area in North Rhine-Westphalia (NRW), Germany. Subsequently, based on these variables, a multivariate clustering approach was conducted for a demonstration area in Dortmund. In the result, it was obvious that the spatially disaggregated data allow more detailed insight into spatial patterns of socioeconomic attributes than the coarser data related to postal code polygons.

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