scholarly journals Diketopyrrolopyrrole Fluorescent Probes, Photophysical and Biological Applications

Chemosensors ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 44
Author(s):  
Muhammad Aminu Auwalu ◽  
Shanshan Cheng

Biological applications of fluorescent probes are rapidly increasing in the supramolecular chemistry research field. Several organic dyes are being utilized currently in developing and advancing this attractive research area, of which diketopyrrolopyrrole (DPP) organic dyes show an exceptional photophysical features (high-fluorescence quantum yield (FQY), good photochemical and thermal stability) that are essential properties for biological applications. Great efforts have been made in recent years towards developing novel fluorescent DPPs by different chemists for such applications, and some positive results have been reported. As a result, this review article gives an account of the progress that has so far been made very recently, mainly within the last decade, in that we selectively focus on and discuss more from 2015 to present on some recent scholarly achievements of fluorescent DPPs: quantum yield, aggregation-induced emission (AIE), solid-state emission, bio-imaging, cancer/tumor therapy, mitochondria staining and some polymeric fluorescent DPPs. Finally, this review article highlights researchers working on luminescent DPPs and the future prospects in some key areas towards designing DPP-based fluorescent probes in order to boost their photophysical and biological applications more effectively.

2019 ◽  
Vol 26 (21) ◽  
pp. 3958-4002 ◽  
Author(s):  
Caixia Yin ◽  
Jiawei Li ◽  
Fangjun Huo

In recent years, fluorescent probes have recently attracted attention from researchers. As a vital trace metal element, Cu2+ has an important role in the human body and environment. Therefore, the development and design of Cu2+ small-molecular fluorescent probes has been an active research area. This review focuses on the developments in the area of small-molecular fluorescent probes for Cu2+ in biological applications according to different sensing mechanisms including charge transfer (CT), electron transfer, energy transfer, excited-state intramolecular proton transfer (ESIPT).


2020 ◽  
Vol 39 (1) ◽  
pp. 209-221
Author(s):  
Jiafeng Wan ◽  
Xiaoyuan Zhang ◽  
Kai Zhang ◽  
Zhiqiang Su

Abstract In recent years, nanomaterials have attracted lots of attention from researchers due to their unique properties. Nanometer fluorescent materials, such as organic dyes, semiconductor quantum dots (QDs), metal nano-clusters (MNCs), carbon dots (CDs), etc., are widely used in biological imaging due to their high sensitivity, short response time, and excellent accuracy. Nanometer fluorescent probes can not only perform in vitro imaging of organisms but also achieve in vivo imaging. This provides medical staff with great convenience in cancer treatment. Combined with contemporary medical methods, faster and more effective treatment of cancer is achievable. This article explains the response mechanism of three-nanometer fluorescent probes: the principle of induced electron transfer (PET), the principle of fluorescence resonance energy transfer (FRET), and the principle of intramolecular charge transfer (ICT), showing the semiconductor QDs, precious MNCs, and CDs. The excellent performance of the three kinds of nano fluorescent materials in biological imaging is highlighted, and the application of these three kinds of nano fluorescent probes in targeted biological imaging is also introduced. Nanometer fluorescent materials will show their significance in the field of biomedicine.


2015 ◽  
Vol 137 (2) ◽  
pp. 757-769 ◽  
Author(s):  
Baoxin Zhang ◽  
Chunpo Ge ◽  
Juan Yao ◽  
Yaping Liu ◽  
Huichen Xie ◽  
...  

Author(s):  
Subham Jain N ◽  
Preeti S ◽  
Amit B Patil

Background: The nanotechnology which has vast growth in the research field and the outcome product of nanotechnology is nanoparticles. Quantum dots with a size range of 2-10nm represents a new form in nanotechnology materials. It has showed widespread attention in recent years in the field of science and its application in drug delivery. Quantum dots are semiconductor nanocrystals which possess interesting properties and characteristics such as unique optical properties, quantum confinement effect and emit fluorescence on excitation with a light source which makes them a potential candidate for nano-probes and for carriers for biological application. Objective: The objective of the article is to explain the role and application of Quantum dots in drug delivery and its future application in pharmaceutical science and research. This review focuses on drug delivery through Quantum dots and Quantum dots helping nanocarriers for drug delivery. The development of QD nano-carriers for drugs has become a hotspot in the fields of nano-drug research. The Quantum Dot labelled nano-carrier can able to deliver the drugs with fewer side effects and it can able to trace the drug location in the body. Results: The Fluorescent emission of Quantum dots is better than other organic dyes which leads to better drug delivery for cancer or acting as a tag for other drug carriers. Conclusion: Because of emission property of Quantum Dots, it can be said used with other drug carriers and later it can be traced with the help of Quantum Dots. Quantum dots can be said as smart Drug delivery.


10.2196/19072 ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. e19072
Author(s):  
Susanne Grødem Johnson ◽  
Thomas Potrebny ◽  
Lillebeth Larun ◽  
Donna Ciliska ◽  
Nina Rydland Olsen

Background E-learning technologies, including mobile apps, are used to a large extent in health care education. Mobile apps can provide extendable learning environments and motivate students for adaptive and collaborative learning outside the classroom context. Developers should design practical, effective, and easy-to-use mobile apps. Usability testing is an important part of app development in order to understand if apps meet the needs of users. Objective The aim of this study is to perform a scoping review of usability methods and attributes reported in usability studies of mobile apps for health care education. Methods The scoping review is guided by the methodological framework developed by Arksey & O’Malley and further developed by Levac et al and Kahlil et al. The stages we will follow are as follows: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies; (4) charting the data; and (5) summarizing and reporting the results. We have developed two research questions to meet the aim of the study, which are as follows: (1) What usability methods are used to evaluate the usability of mobile apps for health care education? and (2) What usability attributes are reported in the usability studies of mobile apps for health care education? We will apply a comprehensive search of the literature, including 10 databases, a reference search, and a search for grey literature. Two review authors will independently screen articles for eligibility. Results The initial electronic database searches were completed in March 2019. The literature search identified 14,297 unique references. Following title and abstract screening, the full texts of 369 records were obtained. The scoping review is expected to be completed in spring 2021. Conclusions We expect the overview of usability methods and attributes reported in usability studies of mobile apps for health care education to contribute to the knowledge base for researchers and developers. It will give an overview of the research field and provide researchers and developers with relevant and important information on the usability research area, including highlighting possible research gaps. International Registered Report Identifier (IRRID) DERR1-10.2196/19072


2021 ◽  
Vol 9 ◽  
Author(s):  
Udisha Singh ◽  
Vinod Morya ◽  
Bhaskar Datta ◽  
Chinmay Ghoroi ◽  
Dhiraj Bhatia

Of the multiple areas of applications of DNA nanotechnology, stimuli-responsive nanodevices have emerged as an elite branch of research owing to the advantages of molecular programmability of DNA structures and stimuli-responsiveness of motifs and DNA itself. These classes of devices present multiples areas to explore for basic and applied science using dynamic DNA nanotechnology. Herein, we take the stake in the recent progress of this fast-growing sub-area of DNA nanotechnology. We discuss different stimuli, motifs, scaffolds, and mechanisms of stimuli-responsive behaviours of DNA nanodevices with appropriate examples. Similarly, we present a multitude of biological applications that have been explored using DNA nanodevices, such as biosensing, in vivo pH-mapping, drug delivery, and therapy. We conclude by discussing the challenges and opportunities as well as future prospects of this emerging research area within DNA nanotechnology.


2021 ◽  
Author(s):  
Ricardo Ribeiro ◽  
Alina Trifan ◽  
António J. R. Neves

BACKGROUND The wide availability and small size, together with the decrease in pricing of different types of sensors, has made it possible, over the last decade, to acquire a huge amount of data about a person's life in real time. These sensors can be incorporated into personal electronic devices available at reasonable cost, such as smartphones and small wearable devices. They allow the acquisition of images, audio, location, physical activity and physiological signals, among other data. With these data, usually denoted as lifelog data, we can then analyze and understand personal experiences and behaviors. This process is called lifelogging. OBJECTIVE The goal of this article is to review the literature in the research area of lifelogging over the past decade and provide an historical overview on this research topic. To this purpose, we analyze lifelogging applications that monitor and assist people with memory problems. METHODS We follow a narrative review methodology to conduct a comprehensive search of relevant publications in Google Scholar and Scopus databases. In order to find these relevant publication, topic-related keywords were identified and combined based on different lifelogging type of data and applications. RESULTS A total of 124 publications were selected and included in this narrative review. 411 publications were retrieved and screened from the two scholar databases. Out of these, 114 publications were fully reviewed. In addition, 32 more publications were manually included based on our bibliographical knowledge in this research field. CONCLUSIONS The use of personal lifelogs can be beneficial to improve the life quality of people suffering from memory problems, such as dementia. Through the acquisition and analysis of lifelog data, lifelogging systems can create digital memories to be used as surrogate memory. Through this narrative we understand that contextual information can be extracted from the lifelogs and it provides significant information for understanding the daily life of people suffering from memory issues based on events, experiences and behaviors.


Author(s):  
Bin Guo ◽  
Yunji Liang ◽  
Zhu Wang ◽  
Zhiwen Yu ◽  
Daqing Zhang ◽  
...  

In the past decades, numerous research efforts have been made to model and extract the contexts of users in pervasive computing environments. The recent explosion of sensor-equipped mobile phone market and the phenomenal growth of geo-tagged data (Twitter messages, Foursquare check-ins, etc.) have enabled the analysis of new dimensions of contexts that involve the social and urban context. The technology trend towards pervasive sensing and large-scale social and community computing is making “Social and Community Intelligence (SCI)” a new research area that aims at investigating individual/group behavior patterns, community and urban dynamics based on the “digital footprints.” It is believed that the SCI technology has the potential to revolutionize the field of context-aware computing. The aim of this chapter is to identify this emerging research area, present the research background, define the general system framework, characterize its unique properties, discuss the open research challenges, and present this emerging research field.


Author(s):  
Imad Rahal ◽  
Baoying Wang ◽  
James Schnepf

Since the invention of the printing press, text has been the predominate mode for collecting, storing and disseminating a vast, rich range of information. With the unprecedented increase of electronic storage and dissemination, document collections have grown rapidly, increasing the need to manage and analyze this form of data in spite of its unstructured or semistructured form. Text-data analysis (Hearst, 1999) has emerged as an interdisciplinary research area forming a junction of a number of older fields like machine learning, natural language processing, and information retrieval (Grobelnik, Mladenic, & Milic-Frayling, 2000). It is sometimes viewed as an adapted form of a very similar research field that has also emerged recently, namely, data mining, which focuses primarily on structured data mostly represented in relational tables or multidimensional cubes. This article provides an overview of the various research directions in text-data analysis. After the “Introduction,” the “Background” section provides a description of a ubiquitous text-data representation model along with preprocessing steps employed for achieving better text-data representations and applications. The focal section, “Text-Data Analysis,” presents a detailed treatment of various text-data analysis subprocesses such as information extraction, information retrieval and information filtering, document clustering and document categorization. The article closes with a “Future Trends” section followed by a “Conclusion” section.


Genes ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1264
Author(s):  
Stavros Makrodimitris ◽  
Roeland C. H. J. van Ham ◽  
Marcel J. T. Reinders

The current rate at which new DNA and protein sequences are being generated is too fast to experimentally discover the functions of those sequences, emphasizing the need for accurate Automatic Function Prediction (AFP) methods. AFP has been an active and growing research field for decades and has made considerable progress in that time. However, it is certainly not solved. In this paper, we describe challenges that the AFP field still has to overcome in the future to increase its applicability. The challenges we consider are how to: (1) include condition-specific functional annotation, (2) predict functions for non-model species, (3) include new informative data sources, (4) deal with the biases of Gene Ontology (GO) annotations, and (5) maximally exploit the GO to obtain performance gains. We also provide recommendations for addressing those challenges, by adapting (1) the way we represent proteins and genes, (2) the way we represent gene functions, and (3) the algorithms that perform the prediction from gene to function. Together, we show that AFP is still a vibrant research area that can benefit from continuing advances in machine learning with which AFP in the 2020s can again take a large step forward reinforcing the power of computational biology.


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