scholarly journals Comparative Study of Contact Repulsion in Control and Mutant Macrophages Using a Novel Interaction Detection

2020 ◽  
Vol 6 (5) ◽  
pp. 36
Author(s):  
José Alonso Solís-Lemus ◽  
Besaiz J Sánchez-Sánchez ◽  
Stefania Marcotti ◽  
Mubarik Burki ◽  
Brian Stramer ◽  
...  
Keyword(s):  
Computational Analysis ◽  
Statistical Significance ◽  
Contact Dynamics ◽  
Drosophila Embryo ◽  
Interaction Detection ◽  
Future Developments ◽  
Novel Method ◽  
Candidate Protein ◽  
Motion Characteristics ◽  
Mutant Cells

In this paper, a novel method for interaction detection is presented to compare the contact dynamics of macrophages in the Drosophila embryo. The study is carried out by a framework called macrosight, which analyses the movement and interaction of migrating macrophages. The framework incorporates a segmentation and tracking algorithm into analysing the motion characteristics of cells after contact. In this particular study, the interactions between cells is characterised in the case of control embryos and Shot mutants, a candidate protein that is hypothesised to regulate contact dynamics between migrating cells. Statistical significance between control and mutant cells was found when comparing the direction of motion after contact in specific conditions. Such discoveries provide insights for future developments in combining biological experiments with computational analysis.

scholarly journals Comparative study of contact repulsion in control and mutant macrophages using a novel interaction detection

2020 ◽  
Author(s):  
JA Solís-Lemus ◽  
BJ Sánchez-Sánchez ◽  
S Marcotti ◽  
M Burki ◽  
B Stramer ◽  
...  
Keyword(s):  
Cell Shape ◽  
Cell Tracking ◽  
Statistical Significance ◽  
Specific Protein ◽  
Cell Segmentation ◽  
Wild Type ◽  
Detection Mechanism ◽  
Interaction Detection ◽  
Motion Characteristics ◽  
Mutant Cells

AbstractThis paper compares the contact-repulsion movement of mutant and wild-type macrophages using a novel interaction detection mechanism. The migrating macrophages are observed in Drosophila embryos. The study is carried out by a framework called macrosight, which analyses the movement and interaction of migrating macrophages. The framework incorporates a segmentation and tracking algorithm into analysing motion characteristics of cells after contact. In this particular study, the interactions between cells is characterised in the case of control embryos and Shot3 mutants, where the cells have been altered to suppress a specific protein, looking to understand what drives the movement. Statistical significance between control and mutant cells was found when comparing the direction of motion after contact in specific conditions. Such discoveries provide insights for future developments in combining biological experiments to computational analysis. Cell Segmentation, Cell Tracking, Macrophages, Cell Shape, Contact Analysis

scholarly journals Diselenides and Benzisoselenazolones as Antiproliferative Agents and Glutathione-S-Transferase Inhibitors

Molecules ◽  
2019 ◽  
Vol 24 (16) ◽  
pp. 2914 ◽  
Author(s):  
Dorota Krasowska ◽  
Nunzio Iraci ◽  
Claudio Santi ◽  
Józef Drabowicz ◽  
Marcin Cieslak ◽  
...  
Keyword(s):  
Cell Lines ◽  
Cancer Cell ◽  
Computational Analysis ◽  
Binding Mode ◽  
Amino Derivative ◽  
Lead Compound ◽  
Glutathione S Transferase ◽  
Mcf7 Cells ◽  
Antiproliferative Agents ◽  
Future Developments

A series of variously functionalized selenium-containing compounds were purposely synthesized and evaluated against a panel of cancer cell lines. Most of the compounds showed an interesting cytotoxicity profile with compound 5 showing a potent activity on MCF7 cells. The ethyl amino derivative 5 acts synergistically with cis-platin and inhibits the GST enzyme with a potency that well correlates with the cytotoxicity observed in MCF7 cells. A computational analysis suggests a possible binding mode on the GST enzyme. As the main outcome of the present study, the ethyl amino derivative 5 emerged as a valid lead compound for further, future developments.

scholarly journals Manipulation of Miniature and Microminiature Bodies on a Harmonically Oscillating Platform by Controlling Dry Friction

Micromachines ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1087
Author(s):  
Sigitas Kilikevičius ◽  
Algimantas Fedaravičius ◽  
Virginija Daukantienė ◽  
Kristina Liutkauskienė ◽  
Linas Paukštaitis
Keyword(s):  
Dry Friction ◽  
The Body ◽  
Control Parameters ◽  
Friction Control ◽  
Vibrating Plates ◽  
Directional Motion ◽  
Novel Method ◽  
Nonprehensile Manipulation ◽  
Motion Characteristics ◽  
And Control

Currently used nonprehensile manipulation systems that are based on vibrational techniques employ temporal (vibrational) asymmetry, spatial asymmetry, or force asymmetry to provide and control a directional motion of a body. This paper presents a novel method of nonprehensile manipulation of miniature and microminiature bodies on a harmonically oscillating platform by creating a frictional asymmetry through dynamic dry friction control. To theoretically verify the feasibility of the method and to determine the control parameters that define the motion characteristics, a mathematical model was developed, and modeling was carried out. Experimental setups for miniature and microminiature bodies were developed for nonprehensile manipulation by dry friction control, and manipulation experiments were carried out to experimentally verify the feasibility of the proposed method and theoretical findings. By revealing how characteristic control parameters influence the direction and velocity, the modeling results theoretically verified the feasibility of the proposed method. The experimental investigation verified that the proposed method is technically feasible and can be applied in practice, as well as confirmed the theoretical findings that the velocity and direction of the body can be controlled by changing the parameters of the function for dynamic dry friction control. The presented research enriches the classical theories of manipulation methods on vibrating plates and platforms, as well as the presented results, are relevant for industries dealing with feeding, assembling, or manipulation of miniature and microminiature bodies.

scholarly journals Immune-Complexome Analysis Identifies Immunoglobulin-Bound Biomarkers That Predict the Response to Chemotherapy of Pancreatic Cancer Patients

Cancers ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 746
Author(s):  
Giorgia Mandili ◽  
Laura Follia ◽  
Giulio Ferrero ◽  
Hiroyuki Katayama ◽  
Wang Hong ◽  
...  
Keyword(s):  
Computational Analysis ◽  
Prognostic Biomarkers ◽  
Ductal Adenocarcinoma ◽  
Orbitrap Mass Spectrometer ◽  
Response To Chemotherapy ◽  
Before And After ◽  
Tumor Immunogenicity ◽  
Novel Method ◽  
Poor Efficacy ◽  
Induce Antibody

Pancreatic Ductal Adenocarcinoma (PDA) is an aggressive malignancy with a very poor outcome. Although chemotherapy (CT) treatment has poor efficacy, it can enhance tumor immunogenicity. Tumor-Associated Antigens (TAA) are self-proteins that are overexpressed in tumors that may induce antibody production and can be PDA theranostic targets. However, the prognostic value of TAA-antibody association as Circulating Immune Complexes (CIC) has not yet been elucidated, mainly due to the lack of techniques that lead to their identification. In this study, we show a novel method to separate IgG, IgM, and IgA CIC from sera to use them as prognostic biomarkers of CT response. The PDA Immune-Complexome (IC) was identified using a LTQ-Orbitrap mass spectrometer followed by computational analysis. The analysis of the IC of 37 PDA patients before and after CT revealed differential associated antigens (DAA) for each immunoglobulin class. Our method identified different PDA-specific CIC in patients that were associated with poor prognosis patients. Finally, CIC levels were significantly modified by CT suggesting that they can be used as effective prognostic biomarkers to follow CT response in PDA patients.

scholarly journals A cell cycle-independent, conditional gene inactivation strategy for differentially tagging wild-type and mutant cells

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Sonal Nagarkar-Jaiswal ◽  
Sathiya N Manivannan ◽  
Zhongyuan Zuo ◽  
Hugo J Bellen
Keyword(s):  
Cell Cycle ◽  
Gene Inactivation ◽  
Inversion Method ◽  
Wild Type ◽  
Flip Flop ◽  
Temporal Cues ◽  
A Cell ◽  
Novel Method ◽  
Mutant Cells

Here, we describe a novel method based on intronic MiMIC insertions described in Nagarkar-Jaiswal et al. (2015) to perform conditional gene inactivation in Drosophila. Mosaic analysis in Drosophila cannot be easily performed in post-mitotic cells. We therefore, therefore, developed Flip-Flop, a flippase-dependent in vivo cassette-inversion method that marks wild-type cells with the endogenous EGFP-tagged protein, whereas mutant cells are marked with mCherry upon inversion. We document the ease and usefulness of this strategy in differential tagging of wild-type and mutant cells in mosaics. We use this approach to phenotypically characterize the loss of SNF4Aγ, encoding the γ subunit of the AMP Kinase complex. The Flip-Flop method is efficient and reliable, and permits conditional gene inactivation based on both spatial and temporal cues, in a cell cycle-, and developmental stage-independent fashion, creating a platform for systematic screens of gene function in developing and adult flies with unprecedented detail.

A Novel Method for $\gamma - \text{photons}$ Depth-of-Interaction Detection in Monolithic Scintillation Crystals

2016 ◽  
Vol 63 (5) ◽  
pp. 2487-2495 ◽  
Author(s):  
Roberto Pani ◽  
Marco Bettiol ◽  
Enrico Preziosi ◽  
Cristian Borrazzo ◽  
Rosanna Pellegrini ◽  
...  
Keyword(s):  
Depth Of Interaction ◽  
Interaction Detection ◽  
Scintillation Crystals ◽  
Novel Method

scholarly journals Novel method for hurricane trajectory prediction based on data mining

2013 ◽  
Vol 1 (5) ◽  
pp. 4681-4712
Author(s):  
X. Dong ◽  
D. C. Pi
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
Prediction Accuracy ◽  
Trajectory Prediction ◽  
Motion Patterns ◽  
Novel Method ◽  
Motion Characteristics ◽  
Trajectory Database ◽  
Current Movement

Abstract. This paper describes a novel method for hurricane trajectory prediction based on data mining (HTPDM) according to the hurricane's motion characteristics. Firstly, all frequent trajectories in the historical hurricane trajectory database are mined by using association analysis technology and their corresponding association rules are generated as motion patterns. Then, the current hurricane trajectories are matched with the motion patterns for predicting. If no association rule is found for matching, a predicted result according to the hurricane current movement trend would be returned. All experiments are conducted with the Atlantic weather Hurricane/Tropical Data from 1900 to 2008. The experimental results show that if the matching failure part is contained, the prediction accuracy is 57.5%. Whereas, the valve would be to 65% provided all matches are successful.

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