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Precision Medicine in Oncology

Authors: --- --- ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889457052 Year: Pages: 163 DOI: 10.3389/978-2-88945-705-2 Language: English
Publisher: Frontiers Media SA
Subject: Medicine (General) --- Oncology
Added to DOAB on : 2019-01-23 14:53:43
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The emerging precision medicine approach aims to tailor disease prevention and treatment to each patient on the basis of individual variability, environmental factors and lifestyle. Fundamental achievements in the last few decades have converged to offer nowadays the compelling opportunity to move towards this innovative approach: i) unprecedented improvements in disease modeling in silico, in vitro and in vivo; ii) acquisition of a wide range of biomedical information combined with the development of computational toolsets for flexible and integrative analyses of multi-assay datasets. Our deeper understanding of oncogenic mechanisms has finally begun to have a crucial impact on clinical decisions at several steps, from cancer prevention and diagnosis to therapeutic intervention. However, precision oncology still encounters several unresolved hurdles including tumour heterogeneity and recurrence as well as unexplained drug resistance and lack of effective ways to monitor response to therapeutic treatments. Notably, limitations in biomedical research regulation and governance represent additional debatable issues that need careful consideration.

Microlenses

ISBN: 9783038420507 9783038420507 Year: Pages: 160 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Added to DOAB on : 2015-10-22 08:40:45
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The study and application of microscale lenses and lens arrays enjoys a long history. Advances in microfabrication technologies in the past few decades have enabled the design and fabrication of microlenses and microlens arrays through many different approaches. In recent years, there has been notably a host of exciting developments in the microlenses and microlens arrays, including tunable-focus ones, those fabricated on non-planar substrates and surfaces, and microlens arrays mimicking natural compound eyes, to name just a few. The developments in microlenses and microlens arrays have found profound applications in many engineering and biomedical fields, including but not limited to optical coherence tomography (OCT), endoscopy, photolithography, 3-dimensional imaging, optical communications, and lab on chips. This Special Issue aims to highlight the state of the art in the development of microlenses and microlens arrays; examples being fabrication technologies and optical characterizations. It also focuses on their applications when implemented in microoptical systems.

Liquid Crystal on Silicon Devices: Modeling and Advanced Spatial Light Modulation Applications

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ISBN: 9783039218288 / 9783039218295 Year: Pages: 172 DOI: 10.3390/books978-3-03921-829-5 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:16
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Liquid Crystal on Silicon (LCoS) has become one of the most widespread technologies for spatial light modulation in optics and photonics applications. These reflective microdisplays are composed of a high-performance silicon complementary metal oxide semiconductor (CMOS) backplane, which controls the light-modulating properties of the liquid crystal layer. State-of-the-art LCoS microdisplays may exhibit a very small pixel pitch (below 4 ?m), a very large number of pixels (resolutions larger than 4K), and high fill factors (larger than 90%). They modulate illumination sources covering the UV, visible, and far IR. LCoS are used not only as displays but also as polarization, amplitude, and phase-only spatial light modulators, where they achieve full phase modulation. Due to their excellent modulating properties and high degree of flexibility, they are found in all sorts of spatial light modulation applications, such as in LCOS-based display systems for augmented and virtual reality, true holographic displays, digital holography, diffractive optical elements, superresolution optical systems, beam-steering devices, holographic optical traps, and quantum optical computing. In order to fulfil the requirements in this extensive range of applications, specific models and characterization techniques are proposed. These devices may exhibit a number of degradation effects such as interpixel cross-talk and fringing field, and time flicker, which may also depend on the analog or digital backplane of the corresponding LCoS device. The use of appropriate characterization and compensation techniques is then necessary.

Application of Bioinformatics in Cancers

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ISBN: 9783039217885 / 9783039217892 Year: Pages: 418 DOI: 10.3390/books978-3-03921-789-2 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Biotechnology
Added to DOAB on : 2019-12-09 11:49:16
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This collection of 25 research papers comprised of 22 original articles and 3 reviews is brought together from international leaders in bioinformatics and biostatistics. The collection highlights recent computational advances that improve the ability to analyze highly complex data sets to identify factors critical to cancer biology. Novel deep learning algorithms represent an emerging and highly valuable approach for collecting, characterizing and predicting clinical outcomes data. The collection highlights several of these approaches that are likely to become the foundation of research and clinical practice in the future. In fact, many of these technologies reveal new insights about basic cancer mechanisms by integrating data sets and structures that were previously immiscible.

Keywords

comorbidity score --- mortality --- locoregionally advanced --- HNSCC --- curative surgery --- traditional Chinese medicine --- health strengthening herb --- cancer treatment --- network pharmacology --- network target --- high-throughput analysis --- brain metastases --- colorectal cancer --- KRAS mutation --- PD-L1 --- tumor infiltrating lymphocytes --- drug resistance --- gefitinib --- erlotinib --- biostatistics --- bioinformatics --- Bufadienolide-like chemicals --- molecular mechanism --- anti-cancer --- bioinformatics --- cancer --- brain --- pathophysiology --- imaging --- machine learning --- extreme learning --- deep learning --- neurological disorders --- pancreatic cancer --- TCGA --- curation --- DNA --- RNA --- protein --- single-biomarkers --- multiple-biomarkers --- cancer-related pathways --- colorectal cancer --- DNA sequence profile --- Monte Carlo --- mixture of normal distributions --- somatic mutation --- tumor --- mutable motif --- activation induced deaminase --- AID/APOBEC --- transcriptional signatures --- copy number variation --- copy number aberration --- TCGA mining --- cancer CRISPR --- firehose --- gene signature extraction --- gene loss biomarkers --- gene inactivation biomarkers --- biomarker discovery --- chemotherapy --- microarray --- ovarian cancer --- predictive model --- machine learning --- overall survival --- observed survival interval --- skin cutaneous melanoma --- The Cancer Genome Atlas --- omics --- breast cancer prognosis --- artificial intelligence --- machine learning --- decision support systems --- cancer prognosis --- independent prognostic power --- omics profiles --- histopathological imaging features --- cancer --- intratumor heterogeneity --- genomic instability --- epigenetics --- mitochondrial metabolism --- miRNAs --- cancer biomarkers --- breast cancer detection --- machine learning --- feature selection --- classification --- denoising autoencoders --- breast cancer --- feature extraction and interpretation --- concatenated deep feature --- cancer modeling --- interaction --- histopathological imaging --- clinical/environmental factors --- oral cancer --- miRNA --- bioinformatics --- datasets --- biomarkers --- TCGA --- GEO DataSets --- hormone sensitive cancers --- breast cancer --- StAR --- estrogen --- steroidogenic enzymes --- hTERT --- telomerase --- telomeres --- alternative splicing --- network analysis --- hierarchical clustering analysis --- differential gene expression analysis --- cancer biomarker --- diseases genes --- variable selection --- false discovery rate --- knockoffs --- bioinformatics --- copy number variation --- cell-free DNA --- methylation --- mutation --- next generation sequencing --- self-organizing map --- head and neck cancer --- treatment de-escalation --- HP --- molecular subtypes --- tumor microenvironment --- Bioinformatics tool --- R package --- machine learning --- meta-analysis --- biomarker signature --- gene expression analysis --- survival analysis --- functional analysis --- bioinformatics --- machine learning --- artificial intelligence --- Network Analysis --- single-cell sequencing --- circulating tumor DNA (ctDNA) --- Neoantigen Prediction --- precision medicine --- Computational Immunology

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