scholarly journals A hydrogel beads based platform for single-cell phenotypic analysis and digital molecular detection

2019 ◽  
Author(s):  
Yanzhe Zhu ◽  
Jing Li ◽  
Xingyu Lin ◽  
Xiao Huang ◽  
Michael R. Hoffmann
Keyword(s):  
Single Cell ◽  
Molecular Detection ◽  
Basic Research ◽  
Genotypic Differences ◽  
Phenotypic Analysis ◽  
Hydrogel Beads ◽  
Research Areas ◽  
Hydrogel Network ◽  
Digital Polymerase Chain Reaction ◽  
Environment Evolution

AbstractMicrofluidic platforms integrating phenotyping and genotyping approaches have the potential to advance the understanding of single cell genotype-to-phenotype correlations. These correlations can play a key role in tackling antibiotic heteroresistance, cancer cell heterogeneity, and other related fundamental problems. Herein, we report a novel platform that enables both high-throughput digital molecular detection and single-cell phenotypic analysis, utilizing nanoliter-sized biocompatible polyethylene glycol hydrogel beads produced by a convenient and disposable centrifugal droplet generation device. The hydrogel beads have been demonstrated enhanced thermal stability, and achieved uncompromised efficiencies in digital polymerase chain reaction, digital loop-mediated isothermal amplification, and single cell phenotyping. The crosslinked hydrogel network highlights the prospective linkage of various subsequent molecular analyses to address the genotypic differences between cellular subpopulations exhibiting distinct phenotypes. Our platform shows great potential for applications in clinical practice and medical research, and promises new perspectives in mechanism elucidation of environment-evolution interaction and other basic research areas.

scholarly journals Single-cell analysis for drug development using convex lens-induced confinement imaging

BioTechniques ◽  
2019 ◽  
Vol 67 (5) ◽  
pp. 210-217 ◽  
Author(s):  
Ndeye Khady Thiombane ◽  
Nicolas Coutin ◽  
Daniel Berard ◽  
Radin Tahvildari ◽  
Sabrina Leslie ◽  
...  
Keyword(s):  
Single Cell ◽  
Drug Response ◽  
Drug Exposure ◽  
Cellular Proliferation ◽  
New Technologies ◽  
Detection Sensitivity ◽  
Yeast Cells ◽  
Sample Population ◽  
Phenotypic Analysis ◽  
Convex Lens

New technologies have powered rapid advances in cellular imaging, genomics and phenotypic analysis in life sciences. However, most of these methods operate at sample population levels and provide statistical averages of aggregated data that fail to capture single-cell heterogeneity, complicating drug discovery and development. Here we demonstrate a new single-cell approach based on convex lens-induced confinement (CLiC) microscopy. We validated CLiC on yeast cells, demonstrating subcellular localization with an enhanced signal-to-noise and fluorescent signal detection sensitivity compared with traditional imaging. In the live-cell CLiC assay, cellular proliferation times were consistent with flask culture. Using methotrexate, we provide drug response data showing a fivefold cell size increase following drug exposure. Taken together, CLiC enables high-quality imaging of single-cell drug response and proliferation for extended observation periods.

Preface

2012 ◽  
Vol 84 (12) ◽  
pp. iv
Author(s):  
Yuping Wu ◽  
Shiyou Guan ◽  
Guoxiu Wang
Keyword(s):  
Basic Research ◽  
Ceramic Materials ◽  
The Sustainable Development ◽  
Biobased Materials ◽  
Novel Materials ◽  
Research Areas ◽  
Academic Exchange ◽  
Fine Chemistry ◽  
Innovative Materials ◽  
High Level

In 2005 at the centennial anniversary of Fudan University, Shanghai, China, a new conference venue began [1]. This venue, the International Conference on Novel Materials and Synthesis (NMS) together with the International Symposium on Fine Chemistry and Functional Polymers (FCFP), is targeted to provide high-level academic exchange for both local and international chemists, materialists, physicists, engineers, and technologists in the fields of materials and synthesis. The year 2011 was the International Year of Chemistry, and it is well known that chemistry is an essential creative science for the sustainable development of humankind. As a result, the joint NMSVII/ FCFP-XXI event (www.nms-iupac.org), held in Shanghai, China, 16-21 October 2011, was more important than ever. The Conference received much support from IUPAC, The National Natural Science Foundation of China, Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, the Science and Technology Commission of the Shanghai Municipality, and the National Basic Research Program of China (2007CB209700), and was carried out under the auspices of IUPAC. The Conference was attended by 430 participants from 40 countries and areas. The scientific program comprised 10 plenary lectures, 56 keynote lectures, 206 invited lectures, and 94 posters. Detailed, active, and lively discussions were covered by the following themes: - innovative chiral and achiral compounds - innovative bio- and biobased materials and composites - innovative polymers such as conducting, semiconducting ones, supramolecular (supermolecular, dynamers) - innovative energy systems including fuel cells, solar cells, lithium batteries, and supercapacitors - innovative nanomaterials such as 1D, 2D, and 3D nanomaterials - new ceramic materials such as superconductors, electronic, diaelectronic, ferroelectric, piezoelectric, optoelectric, and magnetic materials - new metallic materials including alloys - other novel materials including drugs, perfumes, agricultural chemicals, and photosensitive materials, displaying materials and fine ceramics; and - neutron scattering and its application in fundamental and applied research on new materials. The program served to emphasize that novel materials and their preparation are dynamic research areas that are attracting growing interest from researchers, engineers, industries, and policy-makers. Furthermore, novel materials continue to find applications that serve the needs and interests of producers and consumers. A selection of 13 papers based on specially invited presentations at NMSVII/ FCFP-XXI is published in this issue to demonstrate the quality and scope of the themes of this Conference. During the Conference, the role and contributions of this high-level academic platform to novel materials and their synthesis are well realized by the participants, sponsors, and exhibitors. In addition, the organization committee established the Distinguished Award 2011 for Novel Materials and their Synthesis along with IUPAC; Prof. Guoxiu Wang (Australia), Dr. Dr. Fusayoshi Masuda (Japan), Prof. Dr. André-Jean Attias (France), and Prof. Bao-Lian Su (Belgium) received the award for their excellent work. The IUPAC Prof. Jiang Novel Materials Youth Prize was awarded to two winners, Prof. Zhibo Li (China) and Dr. Jr-Hau He (Taiwan, China), for the first time. This will next be awarded in 2013. Three winners for the IUPAC Poster Prize were also awarded. Yuping Wu, Shiyou Guan, and Guoxiu Wang Conference Editors [1] Y. P. Wu. Pure Appl. Chem. 78 (10), iii (2006).

Quantitative Single-Cell mRNA Analysis in Hydrogel Beads

2016 ◽  
Vol 55 (23) ◽  
pp. 6698-6701 ◽  
Author(s):  
Agata Rakszewska ◽  
Rosa J. Stolper ◽  
Anna B. Kolasa ◽  
Aigars Piruska ◽  
Wilhelm T. S. Huck
Keyword(s):  
Single Cell ◽  
Hydrogel Beads ◽  
Mrna Analysis

scholarly journals Periods of development of department of tourism at Ivan Franko National University of Lviv

2012 ◽  
Vol 1 (40) ◽  
pp. 86-100
Author(s):  
M. Malska ◽  
M. Rutynskyi
Keyword(s):  
Key Words ◽  
Staff Member ◽  
Basic Research ◽  
Research Areas ◽  
National University

The article describes the process of formation and main stages of the Tourism Chair of the Ivan Franko Lviv National University. The authors described the basic research areas of the Tourism Chair in detail. The contribution each of the staff member is evaluated. The attention is drawn to basic scientific monographs, textbooks and books prepared by the staff of the Chair during last nine years. Key words: Department of Tourism, periods of development, scientific specialisation.

scholarly journals Quality Assurance can be applied to fundamental research: Supporting Excellence in the Science Base

2004 ◽  
Vol 26 (6) ◽  
pp. 49-53 ◽  
Author(s):  
Margaret M. Robins
Keyword(s):  
Quality Assurance ◽  
Formal System ◽  
Basic Research ◽  
Research Areas ◽  
Science Base ◽  
Fundamental Research

Quality Assurance (QA) has a bad press in research circles. Fundamental researchers tend to consider that experienced scientists do not need any controls beyond their own integrity. This article attempts to show how QA can be applied even to the most original and basic research areas, and that there are benefits to the introduction of a formal system, provided all personnel are involved in the aspects that affect them.

scholarly journals Dice-XMBD: Deep Learning-Based Cell Segmentation for Imaging Mass Cytometry

2021 ◽  
Vol 12 ◽  
Author(s):  
Xu Xiao ◽  
Ying Qiao ◽  
Yudi Jiao ◽  
Na Fu ◽  
Wenxian Yang ◽  
...  
Keyword(s):  
Deep Learning ◽  
High Resolution ◽  
Single Cell ◽  
Image Data ◽  
Basic Research ◽  
Cell Segmentation ◽  
Imaging Method ◽  
Imaging Data ◽  
Mass Cytometry ◽  
Multiplexed Imaging

Highly multiplexed imaging technology is a powerful tool to facilitate understanding the composition and interactions of cells in tumor microenvironments at subcellular resolution, which is crucial for both basic research and clinical applications. Imaging mass cytometry (IMC), a multiplex imaging method recently introduced, can measure up to 100 markers simultaneously in one tissue section by using a high-resolution laser with a mass cytometer. However, due to its high resolution and large number of channels, how to process and interpret the image data from IMC remains a key challenge to its further applications. Accurate and reliable single cell segmentation is the first and a critical step to process IMC image data. Unfortunately, existing segmentation pipelines either produce inaccurate cell segmentation results or require manual annotation, which is very time consuming. Here, we developed Dice-XMBD1, a Deep learnIng-based Cell sEgmentation algorithm for tissue multiplexed imaging data. In comparison with other state-of-the-art cell segmentation methods currently used for IMC images, Dice-XMBD generates more accurate single cell masks efficiently on IMC images produced with different nuclear, membrane, and cytoplasm markers. All codes and datasets are available at https://github.com/xmuyulab/Dice-XMBD.

scholarly journals Publication Landscape on Cushing's Disease: From the Past 40 Years to Future Directions

2021 ◽  
Author(s):  
Ming-Jie Luo ◽  
Kelei Du ◽  
Xiaopeng Guo ◽  
Zihao Wang ◽  
Bing Xing
Keyword(s):  
Clinical Trials ◽  
Cushing’S Disease ◽  
Latent Dirichlet Allocation ◽  
Basic Research ◽  
Research Topic ◽  
Cushing's Disease ◽  
International Studies ◽  
Future Directions ◽  
Country Level ◽  
Research Areas

Abstract PurposeThough literature related to Cushing's disease (CD) has grown significantly, previous reviews exclusively focused on specific research areas and were biased towards highly cited articles. This study aims to systemically analyze the research landscapes and trends using unbiased methods. MethodsWe queried all the CD-related publications in PubMed and clinical trials registered on clinicaltrials.gov. Latent Dirichlet allocation (LDA), a machine learning method, was used to derive research hotspots from article texts. The research topic clusters and country-level collaboration were revealed by network analysis.Results5015 articles were published since 1981, currently growing at 155 per year, with more retrospective studies but fewer prospective studies. Interestingly, the most popular LDA research topics were complications and comorbidities, endocrine hormone tests and surgical therapy, and they formed a remarkable triangle relationship in the research topic network. These topics had numerous international studies and were supported by most funding. In addition, many topics in the basic research domain were proliferating, including mutation, biomarkers, endopeptidases, and other molecular genetics and pathology of CD. Out of 63 registered clinical trials, over 25% were withdrawn due to inadequate patient recruitment or lack of funding.ConclusionsThis publication landscape analysis provided a systemic representation of CD literature regarding the history, current challenges, and future directions, enabling clinicians a rapid and comprehensive insight into the disease.

scholarly journals Cellsnp-lite: an efficient tool for genotyping single cells

2021 ◽  
Author(s):  
Xianjie Huang ◽  
Yuanhua Huang
Keyword(s):  
Single Cell ◽  
Single Cells ◽  
Basic Research ◽  
Substantial Improvement ◽  
Data Sets ◽  
Sequencing Data ◽  
Single Cell Sequencing ◽  
Memory Efficiency ◽  
Computational Speed ◽  
Cell Data

AbstractSummarySingle-cell sequencing is an increasingly used technology and has promising applications in basic research and clinical translations. However, genotyping methods developed for bulk sequencing data have not been well adapted for single-cell data, in terms of both computational parallelization and simplified user interface. Here we introduce a software, cellsnp-lite, implemented in C/C++ and based on well supported package htslib, for genotyping in single-cell sequencing data for both droplet and well based platforms. On various experimental data sets, it shows substantial improvement in computational speed and memory efficiency with retaining highly concordant results compared to existing methods. Cellsnp-lite therefore lightens the genetic analysis for increasingly large single-cell data.AvailabilityThe source code is freely available at https://github.com/single-cell-genetics/[email protected]

scholarly journals High-Content Image-Based Single-Cell Phenotypic Analysis for the Testicular Toxicity Prediction Induced by Bisphenol A and Its Analogs Bisphenol S, Bisphenol AF, and Tetrabromobisphenol A in a Three-Dimensional Testicular Cell Co-culture Model

2019 ◽  
Vol 173 (2) ◽  
pp. 313-335 ◽  
Author(s):  
Lei Yin ◽  
Jacob Steven Siracusa ◽  
Emily Measel ◽  
Xueling Guan ◽  
Clayton Edenfield ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Three Dimensional ◽  
Testicular Cell ◽  
Phenotypic Analysis ◽  
Bisphenol S ◽  
Cytoskeletal Structure ◽  
Culture Model ◽  
Bisphenol Af

Abstract Emerging data indicate that structural analogs of bisphenol A (BPA) such as bisphenol S (BPS), tetrabromobisphenol A (TBBPA), and bisphenol AF (BPAF) have been introduced into the market as substitutes for BPA. Our previous study compared in vitro testicular toxicity using murine C18-4 spermatogonial cells and found that BPAF and TBBPA exhibited higher spermatogonial toxicities as compared with BPA and BPS. Recently, we developed a novel in vitro three-dimensional (3D) testicular cell co-culture model, enabling the classification of reproductive toxic substances. In this study, we applied the testicular cell co-culture model and employed a high-content image (HCA)-based single-cell analysis to further compare the testicular toxicities of BPA and its analogs. We also developed a machine learning (ML)-based HCA pipeline to examine the complex phenotypic changes associated with testicular toxicities. We found dose- and time-dependent changes in a wide spectrum of adverse endpoints, including nuclear morphology, DNA synthesis, DNA damage, and cytoskeletal structure in a single-cell-based analysis. The co-cultured testicular cells were more sensitive than the C18 spermatogonial cells in response to BPA and its analogs. Unlike conventional population-averaged assays, single-cell-based assays not only showed the levels of the averaged population, but also revealed changes in the sub-population. Machine learning-based phenotypic analysis revealed that treatment of BPA and its analogs resulted in the loss of spatial cytoskeletal structure, and an accumulation of M phase cells in a dose- and time-dependent manner. Furthermore, treatment of BPAF-induced multinucleated cells, which were associated with altered DNA damage response and impaired cellular F-actin filaments. Overall, we demonstrated a new and effective means to evaluate multiple toxic endpoints in the testicular co-culture model through the combination of ML and high-content image-based single-cell analysis. This approach provided an in-depth analysis of the multi-dimensional HCA data and provided an unbiased quantitative analysis of the phenotypes of interest.

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