scholarly journals Current advances in prognostic and diagnostic biomarkers for solid cancers: Detection techniques and future challenges

2022 ◽  
Vol 146 ◽  
pp. 112488
Author(s):  
Mintu Pal ◽  
Thingreila Muinao ◽  
Hari Prasanna Deka Boruah ◽  
Neeraj Mahindroo
Keyword(s):  
Diagnostic Biomarkers ◽  
Detection Techniques ◽  
Future Challenges

Facial Image Processing in Computer Vision

2013 ◽  
pp. 1111-1123
Author(s):  
Moi Hoon Yap ◽  
Hassan Ugail
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Computer Animation ◽  
Feature Detection ◽  
Research Field ◽  
Future Research ◽  
Expression Recognition ◽  
Facial Image ◽  
Detection Techniques ◽  
Future Challenges

The application of computer vision in face processing remains an important research field. The aim of this chapter is to provide an up-to-date review of research efforts of computer vision scientist in facial image processing, especially in the areas of entertainment industry, surveillance, and other human computer interaction applications. To be more specific, this chapter reviews and demonstrates the techniques of visible facial analysis, regardless of specific application areas. First, the chapter makes a thorough survey and comparison of face detection techniques. It provides some demonstrations on the effect of computer vision algorithms and colour segmentation on face images. Then, it reviews the facial expression recognition from the psychological aspect (Facial Action Coding System, FACS) and from the computer animation aspect (MPEG-4 Standard). The chapter also discusses two popular existing facial feature detection techniques: Gabor feature based boosted classifiers and Active Appearance Models, and demonstrate the performance on our in-house dataset. Finally, the chapter concludes with the future challenges and future research direction of facial image processing.

scholarly journals Precision Detection Technology: Equipping Precision Oncology with Wings

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Rilan Bai ◽  
Zheng Lv ◽  
Xiao Chen ◽  
Hanfei Guo ◽  
Ling Bai ◽  
...  
Keyword(s):  
Liquid Biopsy ◽  
New Drugs ◽  
Therapeutic Effects ◽  
Precision Oncology ◽  
Detection Techniques ◽  
Detection Technology ◽  
Future Challenges ◽  
Rare Gene ◽  
The Many

In recent years, precision medical detection techniques experienced a rapid transformation from low-throughput to high-throughput genomic sequencing, from multicell promiscuous detection to single-cell precision sequencing. The emergence of liquid biopsy technology has compensated for the many limitations of tissue biopsy, leading to a tremendous transformation in precision detection. Precision detection techniques contribute to monitoring disease development more closely, evaluating therapeutic effects more scientifically, and developing new targets and new drugs. In the future, the role of precision detection and the joint detection in epigenetics, rare gene detection, individualized targeted therapy, and multigene targeted drug combination therapy should be extensively explored. This article reviews the changes in precision medical detection technology in the era of precision medicine, as well as the development, clinical application, and future challenges of liquid biopsy.

Facial Image Processing in Computer Vision

2011 ◽  
pp. 179-190
Author(s):  
Moi Hoon Yap ◽  
Hassan Ugail
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Computer Animation ◽  
Feature Detection ◽  
Research Field ◽  
Future Research ◽  
Expression Recognition ◽  
Facial Image ◽  
Detection Techniques ◽  
Future Challenges

The application of computer vision in face processing remains an important research field. The aim of this chapter is to provide an up-to-date review of research efforts of computer vision scientist in facial image processing, especially in the areas of entertainment industry, surveillance, and other human computer interaction applications. To be more specific, this chapter reviews and demonstrates the techniques of visible facial analysis, regardless of specific application areas. First, the chapter makes a thorough survey and comparison of face detection techniques. It provides some demonstrations on the effect of computer vision algorithms and colour segmentation on face images. Then, it reviews the facial expression recognition from the psychological aspect (Facial Action Coding System, FACS) and from the computer animation aspect (MPEG-4 Standard). The chapter also discusses two popular existing facial feature detection techniques: Gabor feature based boosted classifiers and Active Appearance Models, and demonstrate the performance on our in-house dataset. Finally, the chapter concludes with the future challenges and future research direction of facial image processing.

scholarly journals Nanomedicine-based technologies and novel biomarkers for the diagnosis and treatment of Alzheimer’s disease: from current to future challenges

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Amanda Cano ◽  
Patric Turowski ◽  
Miren Ettcheto ◽  
Jason Thomas Duskey ◽  
Giovanni Tosi ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Disease Progression ◽  
State Of The Art ◽  
Diagnostic Tools ◽  
Diagnostic Biomarkers ◽  
Future Challenges ◽  
Novel Biomarkers ◽  
New Treatments ◽  
The Brain

AbstractIncreasing life expectancy has led to an aging population, which has consequently increased the prevalence of dementia. Alzheimer's disease (AD), the most common form of dementia worldwide, is estimated to make up 50–80% of all cases. AD cases are expected to reach 131 million by 2050, and this increasing prevalence will critically burden economies and health systems in the next decades. There is currently no treatment that can stop or reverse disease progression. In addition, the late diagnosis of AD constitutes a major obstacle to effective disease management. Therefore, improved diagnostic tools and new treatments for AD are urgently needed. In this review, we investigate and describe both well-established and recently discovered AD biomarkers that could potentially be used to detect AD at early stages and allow the monitoring of disease progression. Proteins such as NfL, MMPs, p-tau217, YKL-40, SNAP-25, VCAM-1, and Ng / BACE are some of the most promising biomarkers because of their successful use as diagnostic tools. In addition, we explore the most recent molecular strategies for an AD therapeutic approach and nanomedicine-based technologies, used to both target drugs to the brain and serve as devices for tracking disease progression diagnostic biomarkers. State-of-the-art nanoparticles, such as polymeric, lipid, and metal-based, are being widely investigated for their potential to improve the effectiveness of both conventional drugs and novel compounds for treating AD. The most recent studies on these nanodevices are deeply explained and discussed in this review. Graphic Abstract

ACE2 as therapeutic agent

2020 ◽  
Vol 134 (19) ◽  
pp. 2581-2595
Author(s):  
Qiuhong Li ◽  
Maria B. Grant ◽  
Elaine M. Richards ◽  
Mohan K. Raizada
Keyword(s):  
Therapeutic Agent ◽  
Renin Angiotensin System ◽  
Peptide Hormone ◽  
Experimental Models ◽  
Electrolyte Balance ◽  
Ang Ii ◽  
Angiotensin Converting Enzyme 2 ◽  
Beneficial Effects ◽  
Overwhelming Evidence ◽  
Future Challenges

Abstract The angiotensin-converting enzyme 2 (ACE2) has emerged as a critical regulator of the renin–angiotensin system (RAS), which plays important roles in cardiovascular homeostasis by regulating vascular tone, fluid and electrolyte balance. ACE2 functions as a carboxymonopeptidase hydrolyzing the cleavage of a single C-terminal residue from Angiotensin-II (Ang-II), the key peptide hormone of RAS, to form Angiotensin-(1-7) (Ang-(1-7)), which binds to the G-protein–coupled Mas receptor and activates signaling pathways that counteract the pathways activated by Ang-II. ACE2 is expressed in a variety of tissues and overwhelming evidence substantiates the beneficial effects of enhancing ACE2/Ang-(1-7)/Mas axis under many pathological conditions in these tissues in experimental models. This review will provide a succinct overview on current strategies to enhance ACE2 as therapeutic agent, and discuss limitations and future challenges. ACE2 also has other functions, such as acting as a co-factor for amino acid transport and being exploited by the severe acute respiratory syndrome coronaviruses (SARS-CoVs) as cellular entry receptor, the implications of these functions in development of ACE2-based therapeutics will also be discussed.

Articles Published in EJPA 2009–2010

2011 ◽  
Vol 27 (4) ◽  
pp. 290-298 ◽  
Author(s):  
Tuulia M. Ortner ◽  
Isabella Vormittag
Keyword(s):  
Psychological Assessment ◽  
Rating Scales ◽  
Self Report ◽  
Related Field ◽  
Broad Scope ◽  
Future Challenges ◽  
Health Related ◽  
Report Data ◽  
Self Report Data

With reference to EJPA’s unique and broad scope, the current study analyzed the characteristics of the authors as well as the topics and research aims of the 69 empirical articles published in the years 2009–2010. Results revealed that more than one third of the articles were written by authors affiliated with more than one country. With reference to their research aims, an almost comparable number of articles (1) presented a new measure, (2) dealt with adaptations of measures, or (3) dealt with further research on existing measures. Analyses also revealed that most articles did not address any particular field of application. The second largest group was comprised of articles related to the clinical field, followed by the health-related field of application. The majority of all articles put their focus on investigating questionnaires or rating scales, and only a small number of articles investigated procedures classified as tests or properties of interviews. As to further characteristics of the method(s) used, a majority of EJPA contributions addressed self-report data. Results are discussed with reference to publication demands as well as the current and future challenges and demands of psychological assessment.

Facet Theory

1998 ◽  
Vol 3 (1) ◽  
pp. 13-36 ◽  
Author(s):  
Ruth Guttman ◽  
Charles W. Greenbaum
Keyword(s):  
Data Analysis ◽  
Animal Behavior ◽  
Infant Development ◽  
Facet Theory ◽  
Structural Relationships ◽  
Future Challenges ◽  
Spatial Configurations ◽  
Multidimensional Methods ◽  
Definition Of ◽  
Scalogram Analysis

This article gives an overview of Facet Theory, a systematic approach to facilitating theory construction, research design, and data analysis for complex studies, that is particularly appropriate to the behavioral and social sciences. Facet Theory is based on (1) a definitional framework for a universe of observations in the area of study; (2) empirical structures of observations within this framework; (3) a search for correspondence between the definitional system and aspects of the empirical structure for the observations. The development of Facet Theory and Facet Design is reviewed from early scale analysis and the Guttman Scale, leading to the concepts of “mapping sentence,” “universe of content,” “common range,” “content facets,” and nonmetric multidimensional methods of data analysis. In Facet Theory, the definition of the behavioral domain provides a rationale for hypothesizing structural relationships among variables employed in a study. Examples are presented from various areas of research (intelligence, infant development, animal behavior, etc.) to illustrate the methods and results of structural analysis with Smallest Space Analysis (SSA), Multidimensional Scalogram Analysis (MSA), and Partial Order Scalogram Analysis (POSA). The “radex” and “cylindrex” of intelligence tests are shown to be outstanding examples of predicted spatial configurations that have demonstrated the ubiquitous emergence of the same empirical structures in different studies. Further examples are given from studies of spatial abilities, infant development, animal behavior, and others. The use of Facet Theory, with careful construction of theory and design, is shown to provide new insights into existing data; it allows for the diagnosis and discrimination of behavioral traits and makes the generalizability and replication of findings possible, which in turn makes possible the discovery of lawfulness. Achievements, issues, and future challenges of Facet Theory are discussed.

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