Pub Date : 2020-05-02DOI: 10.2174/1574362415999200502030632
A. Shojaeian, Ameneh Mehri-Ghahfarrokhi, M. Safaei
The circular RNAs (circRNAs) are defined as single-stranded RNA molecules with a length of 100 bp up to 4 kb, resulting from head-to-tail junctions at splice sites of spliced transcripts. Moreover, they are stable and abundant conserved RNA molecules, which often have tissue-specific expression and developmental stages. Dysregulation of circRNAs has been identified in many types of malignancies that mainly affect the progression of human cancers. This review was prepared via searching of the databases of Science Direct, Directory of Open Access Journals (DOAJ), Google Scholar, Pub-Med (NLM), Scopus, Web of Science, and hand searching using relative keywords. The selected papers were fully reviewed and required information for the review was extracted and summarized. In recent decades, the prevalence of thyroid cancer, especially papillary thyroid cancer (PTC), is the most common endocrine cancer increasingly among all cancers, thereby attracting worldwide attention. The global rate of death from thyroid cancer is approximately 0.2 -0.6 per 100,000 people. Some of the known axes involved in PTC include circ-0025033/miR-1304/miR1231, circPVT1/miR-126, circBACH2/miR-139-5p/LMO4, circ-ITCH/miR-22-3p/CBL/βcatenin, circZFR/miR1261/C8orf4, circRAPGEF5/miR-198/FGFR1, circNUP214/miR145/ZEB2. In this article, we review briefly the most important signaling axes involved in thyroid cancer. The expression level of microRNA (miRNAs) is regulated by circRNAs. Thus, circRNAs play an important role in the oncogenic and malignant behavior of cancer. The fact that circRNAs have been found in abundance in saliva, exosomes and standard blood samples makes circRNAs a diagnostic marker for diseases, especially cancer screening.
环状RNA（circRNA）被定义为长度为100bp至4kb的单链RNA分子，由剪接转录物剪接位点的头尾连接产生。此外，它们是稳定且丰富的保守RNA分子，通常具有组织特异性表达和发育阶段。circRNA的失调已在许多类型的恶性肿瘤中被发现，这些恶性肿瘤主要影响人类癌症的进展。这篇综述是通过搜索Science Direct、开放获取期刊目录（DOAJ）、Google Scholar、Pub Med（NLM）、Scopus、Web of Science的数据库以及使用相关关键词进行手动搜索而编写的。对所选论文进行了全面审查，并提取和总结了审查所需的信息。近几十年来，甲状腺癌症，特别是癌症（PTC）的患病率，日益成为所有癌症中最常见的内分泌癌症，引起了全世界的关注。全球癌症死亡率约为每10万人0.2至0.6人。参与PTC的一些已知轴包括circ-0025033/miR-1304/miR1231、circPVT1/miR-126、circBACH2/miR-139-5p/LMO4、circITCH/miR-22-3p/CBL/β连环蛋白、circZFR/miR1261/C8orf4、circRAPGEF5/miR-198/FGFR1、circNUP214/miR145/ZEB2。在这篇文章中，我们简要回顾了与甲状腺癌症有关的最重要的信号轴。微小RNA（miRNAs）的表达水平受circRNAs的调控。因此，circRNA在癌症的致癌和恶性行为中发挥着重要作用。在唾液、外泌体和标准血液样本中发现了大量circRNA，这一事实使circRNA成为疾病的诊断标志物，尤其是癌症筛查。
{"title":"CircRNAs and Axes Involved in Thyroid Cancer based on PTC: A Biomarker for Prognosis, Diagnosis and Treatment","authors":"A. Shojaeian, Ameneh Mehri-Ghahfarrokhi, M. Safaei","doi":"10.2174/1574362415999200502030632","DOIUrl":"https://doi.org/10.2174/1574362415999200502030632","url":null,"abstract":"\u0000\u0000The circular RNAs (circRNAs) are defined as single-stranded RNA\u0000molecules with a length of 100 bp up to 4 kb, resulting from head-to-tail junctions at splice sites\u0000of spliced transcripts. Moreover, they are stable and abundant conserved RNA molecules, which\u0000often have tissue-specific expression and developmental stages. Dysregulation of circRNAs has\u0000been identified in many types of malignancies that mainly affect the progression of human\u0000cancers.\u0000\u0000\u0000\u0000 This review was prepared via searching of the databases of Science Direct, Directory\u0000of Open Access Journals (DOAJ), Google Scholar, Pub-Med (NLM), Scopus, Web of Science,\u0000and hand searching using relative keywords. The selected papers were fully reviewed and\u0000required information for the review was extracted and summarized.\u0000\u0000\u0000\u0000 In recent decades, the prevalence of thyroid cancer, especially papillary thyroid cancer\u0000(PTC), is the most common endocrine cancer increasingly among all cancers, thereby attracting\u0000worldwide attention. The global rate of death from thyroid cancer is approximately 0.2 -0.6 per\u0000100,000 people. Some of the known axes involved in PTC include circ-0025033/miR-1304/miR1231, circPVT1/miR-126, circBACH2/miR-139-5p/LMO4, circ-ITCH/miR-22-3p/CBL/βcatenin, circZFR/miR1261/C8orf4, circRAPGEF5/miR-198/FGFR1, circNUP214/miR145/ZEB2. In this article, we review briefly the most important signaling axes involved in\u0000thyroid cancer. The expression level of microRNA (miRNAs) is regulated by circRNAs.\u0000\u0000\u0000\u0000Thus, circRNAs play an important role in the oncogenic and malignant behavior of\u0000cancer. The fact that circRNAs have been found in abundance in saliva, exosomes and standard\u0000blood samples makes circRNAs a diagnostic marker for diseases, especially cancer screening.\u0000\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44411843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-02-26DOI: 10.2174/1574362415666200226103116
T. Tirupal, B. Mohan, S. Kumar
The main objective of image fusion for multimodal medical images is to retrieve valuable information by combining multiple images obtained from various sources into a single image suitable for better diagnosis. In this paper, a detailed survey on various existing medical image fusion algorithms, with a comparative discussion is presented. Image fusion algorithms available in the current literature are categorized into various methods known as (1) morphological methods, (2) human value system operator based methods, (3) sub-band decomposition methods, (4) neural network based methods, and (5) fuzzy logic based methods. This research concludes that even though there exists a few open-ended creative and logical difficulties, the fusion of medical images in many combinations assists in utilizing medical image fusion for medicinal diagnostics and examination. There is tremendous progress in the fields of deep learning, artificial intelligence and bio-inspired optimization techniques. Effective utilization of these techniques can be used to further improve the efficiency of image fusion algorithms.
{"title":"Multimodal Medical Image Fusion Techniques – A Review","authors":"T. Tirupal, B. Mohan, S. Kumar","doi":"10.2174/1574362415666200226103116","DOIUrl":"https://doi.org/10.2174/1574362415666200226103116","url":null,"abstract":"\u0000\u0000The main objective of image fusion for multimodal medical images is to retrieve valuable information by combining multiple images obtained from various sources into a single image suitable for better diagnosis. In this paper, a detailed survey on various existing medical image fusion algorithms, with a comparative discussion is presented. Image fusion algorithms available in the current literature are categorized into various methods known as (1) morphological methods, (2) human value system operator based methods, (3) sub-band decomposition methods, (4) neural network based methods, and (5) fuzzy logic based methods. This research concludes that even though there exists a few open-ended creative and logical difficulties, the fusion of medical images in many combinations assists in utilizing medical image fusion for medicinal diagnostics and examination. There is tremendous progress in the fields of deep learning, artificial intelligence and bio-inspired optimization techniques. Effective utilization of these techniques can be used to further improve the efficiency of image fusion algorithms.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":"15 1","pages":"1-22"},"PeriodicalIF":0.0,"publicationDate":"2020-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41587322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-02-24DOI: 10.2174/1574362415666200224094706
Hani H. Attar, M. Khosravi, Shmatkov Sergiy Igorovich, Kuchuk Nina Georgievan, Mohammad Alhihi
Multi-Service Streams Network (MSSN) has become such a popular technique in modern applications including, medical fields for E-health applications, such as medical systems and patient monitoring network systems. Recent E-health researches intend to compare MSSN data communications with traditional methods such as on the internet. Based on the above-mentioned fact, the proposed work in this paper is directed to obtain detailed analysis of the MSSN applied over E-health, using the G/G/1 analysis method, including traffic probabilistic-time characteristics to establish its self-similar processes. Moreover, the paper proposes the purpose of estimating the queue service efficiency and overload management by the essential criterion, which takes into account the time delay, time jitter, and the packet loss probability expected in the E-health applications. Based on the necessary standard for the proposed uses, the results of queue operations and also relevant buffer space algorithms are evaluated. Moreover, the estimated qualitative measurement of the network development for the proposed model is obtained and compared with the most common techniques adapted in E-health applications. The collected results show that MSSN is an applicable technique to be applied over the E-health applications mainly on its excellent time delay, jitter, packet losses probability and others. The main aim of this paper is to obtain a full detailed analysis on the MSSN that is applied over E-health applications, using the mass service capacity for the mathematical model class G/G/1 in the most general case of a single-channel system.
{"title":"E-Health Communication System with Multiservice Data Traffic Evaluation Based on a G/G/1 Analysis Method","authors":"Hani H. Attar, M. Khosravi, Shmatkov Sergiy Igorovich, Kuchuk Nina Georgievan, Mohammad Alhihi","doi":"10.2174/1574362415666200224094706","DOIUrl":"https://doi.org/10.2174/1574362415666200224094706","url":null,"abstract":"\u0000\u0000 Multi-Service Streams Network (MSSN) has become such a popular technique in modern applications including, medical fields for E-health applications, such as medical systems and patient monitoring network systems. Recent E-health researches intend to compare MSSN data communications with traditional methods such as on the internet.\u0000\u0000\u0000\u0000\u0000 Based on the above-mentioned fact, the proposed work in this paper is directed to obtain detailed analysis of the MSSN applied over E-health, using the G/G/1 analysis method, including traffic probabilistic-time characteristics to establish its self-similar processes. Moreover, the paper proposes the purpose of estimating the queue service efficiency and overload management by the essential criterion, which takes into account the time delay, time jitter, and the packet loss probability expected in the E-health applications. Based on the necessary standard for the proposed uses, the results of queue operations and also relevant buffer space algorithms are evaluated. Moreover, the estimated qualitative measurement of the network development for the proposed model is obtained and compared with the most common techniques adapted in E-health applications.\u0000\u0000\u0000\u0000\u0000The collected results show that MSSN is an applicable technique to be applied over the E-health applications mainly on its excellent time delay, jitter, packet losses probability and others.\u0000\u0000\u0000\u0000\u0000 The main aim of this paper is to obtain a full detailed analysis on the MSSN that is applied over E-health applications, using the mass service capacity for the mathematical model class G/G/1 in the most general case of a single-channel system. \u0000\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48414069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-02-11DOI: 10.2174/1574362415666200211104406
M. Safaei, Ameneh Mehri-Ghahfarrokhi, A. Shojaeian
Long non-coding ribonucleic acid (lncRNA) is known as similar transcripts of messenger RNA (mRNA) whose size discrepancy is between 100 and 200 nucleotides. Recent studies in this area have revealed that lncRNAs are involved in cancer tumorogenesis and progression. Such molecules are transcribed from genome regions that lack open reading frame (ORF) and fail to encode any protein. LncRNAs are characterized by tumorigenic behaviors which can be considered as new biomarkers. Among all types of thyroid cancer (TC), papillary thyroid carcinoma (PTC) is the most common one. This review was prepared via searching of the databases of Science Direct, Directory of Open Access Journals (DOAJ), Google Scholar, Pub-Med (NLM), Scopus, Web of Science, and hand searching using relative keywords. The selected papers were fully reviewed and required information for the review was extracted and summarized. Pervious studies indicated that BRAF-activated non-protein coding RNA (BANCR) expression had been increased in thyroid tumors compared with adjacent normal tissues. Additionally, BANCR had mediated epithelial-mesenchymal transition (EMT) through regulating the expression of epithelial (E)-cadherin, vimentin, and neuronal (N)-cadherin. Moreover, H19 was an example of an lncRNA that could function either as a tumor promoter or suppressor. An important part of this study was dedicated to reviewing signaling pathways involved in TC including extracellular-signal-regulated kinase (ERK) pathway and mitogen-activated protein kinase (ERK/MAPK), transforming growth factor-β/ (TGF-ß)/Smads, the Janus kinase/signal transducers and activators of transcription (JAK/STAT), P53, as well as other pathways. Briefly, this study provided an overview on current understanding of the function of lncRNA and micro RNAs (miRNAs) along with their interactions in TC.
长非编码核糖核酸（lncRNA）被称为信使RNA（mRNA）的类似转录物，其大小差异在100到200个核苷酸之间。该领域的最新研究表明lncRNA参与了癌症的肿瘤发生和发展。这些分子是从缺乏开放阅读框（ORF）且不能编码任何蛋白质的基因组区域转录而来的。lncRNA具有致瘤行为的特点，可作为新的生物标志物。在所有类型的甲状腺癌症（TC）中，乳头状甲状腺癌（PTC）是最常见的。这篇综述是通过搜索Science Direct、开放获取期刊目录（DOAJ）、Google Scholar、Pub Med（NLM）、Scopus、Web of Science的数据库以及使用相关关键词进行手动搜索而编写的。对选定的论文进行了全面审查，并提取和总结了审查所需的信息。普遍的研究表明，与邻近的正常组织相比，BRAF激活的非蛋白编码RNA（BANCR）在甲状腺肿瘤中的表达增加。此外，BANCR通过调节上皮（E）-钙粘蛋白、波形蛋白和神经元（N）-钙粘着蛋白的表达，介导了上皮-间质转化（EMT）。此外，H19是lncRNA的一个例子，它可以作为肿瘤启动子或抑制剂发挥作用。本研究的一个重要部分致力于综述TC涉及的信号通路，包括细胞外信号调节激酶（ERK）通路和丝裂原活化蛋白激酶（ERK/MAPK）、转化生长因子-β/（TGF-ß）/Smads、Janus激酶/信号转导子和转录激活子（JAK/STAT）、P53以及其他通路。简言之，本研究概述了目前对lncRNA和微小RNA（miRNA）的功能及其在TC中的相互作用的理解。
{"title":"Trace of Long non-coding RNAs in Signaling Pathways Relative to Thyroid Cancer","authors":"M. Safaei, Ameneh Mehri-Ghahfarrokhi, A. Shojaeian","doi":"10.2174/1574362415666200211104406","DOIUrl":"https://doi.org/10.2174/1574362415666200211104406","url":null,"abstract":"\u0000\u0000Long non-coding ribonucleic acid (lncRNA) is known as similar transcripts of messenger RNA (mRNA) whose size discrepancy is between 100 and 200 nucleotides. Recent studies in this area have revealed that lncRNAs are involved in cancer tumorogenesis and progression. Such molecules are transcribed from genome regions that lack open reading frame (ORF) and fail to encode any protein. LncRNAs are characterized by tumorigenic behaviors which can be considered as new biomarkers. Among all types of thyroid cancer (TC), papillary thyroid carcinoma (PTC) is the most common one. \u0000\u0000\u0000\u0000\u0000This review was prepared via searching of the databases of Science Direct, Directory of Open Access Journals (DOAJ), Google Scholar, Pub-Med (NLM), Scopus, Web of Science, and hand searching using relative keywords. The selected papers were fully reviewed and required information for the review was extracted and summarized. \u0000\u0000\u0000\u0000\u0000 Pervious studies indicated that BRAF-activated non-protein coding RNA (BANCR) expression had been increased in thyroid tumors compared with adjacent normal tissues. Additionally, BANCR had mediated epithelial-mesenchymal transition (EMT) through regulating the expression of epithelial (E)-cadherin, vimentin, and neuronal (N)-cadherin. Moreover, H19 was an example of an lncRNA that could function either as a tumor promoter or suppressor. An important part of this study was dedicated to reviewing signaling pathways involved in TC including extracellular-signal-regulated kinase (ERK) pathway and mitogen-activated protein kinase (ERK/MAPK), transforming growth factor-β/ (TGF-ß)/Smads, the Janus kinase/signal transducers and activators of transcription (JAK/STAT), P53, as well as other pathways. \u0000\u0000\u0000\u0000\u0000 Briefly, this study provided an overview on current understanding of the function of lncRNA and micro RNAs (miRNAs) along with their interactions in TC.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42391954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-02-11DOI: 10.2174/1574362415666200211105355
Drishti Yadav and Karan Veer
With the enhancement in manageability and robustness, ultrasound discovers growing usage in an eclectic variety of applications. The capability to accomplish and construe an outsized variability of ultrasound investigations is marvelously revealed by Physicians, nurses and medical officers, and the use of ultrasound in the developing world is unequivocally supported by a growing body of literature. This paper delivers a general idea of the technological and engineering developments that succor in the progression of ultrasonic applications. This paper reviews the prevailing literature in aid of ultrasound use in the emerging biosphere. It also endorses imminent guidelines for ultrasound usage and exploration in order to develop the investigative capability and patient care in the utmost far-flung regions of the world. A well-thought-out examination of bibliographic records in quest of peer-reviewed research accomplishments by means of an intensive assessment interrogation was carried out. Good quality papers were included in the review based on their features. With the intention of analyzing the verdicts of the considered investigations, we employed an inferential scrutiny approach centered on the quality of the content. A total of 152 papers were included in this review including a massive volume of literature works on various ultrasonic applications. These ultrasonic applications included food processing, cleaning, and nanostructured material synthesis along with a variety of therapeutic and clinical applications. This review identified the captivating improvements and ground-breaking applications of ultrasound worldwide together with a few of its prospective applications. The utilization of ultrasound in processing crafts innovative and attention-grabbing approaches which have an eclectic scope for further research both from industrial and academic perspectives. Various areas, for instance: crystallization, degassing, drying, extraction, filtration, freezing, homogenization, meat tenderization, sterilization, etc.; have been acknowledged with prodigious potential for forthcoming improvements in food processing and preservation. Enriched extraction of heat sensitive bioactive and food constituents at lower processing temperatures can be carried out using UAE. There is also a prospective for attaining concurrent extrication and encapsulation of extracted constituents via ultrasonic. Nevertheless, its utilization in the diagnosis of certain syndromes still remains controversial. In the near future, tumor ablation would necessitate the most important use of high intensity focused ultrasound in medicine. These applications, predominantly the treatment of uterine fibroids, are projected to encounter stretched out usage globally. With the proliferation of additional ablation techniques, a number of electrifying enhancements and innovative applications lie on the vista; together with application for targeted drug delivery and gene thera
{"title":"A comprehensive review on applications of Ultrasound in various industries","authors":"Drishti Yadav and Karan Veer","doi":"10.2174/1574362415666200211105355","DOIUrl":"https://doi.org/10.2174/1574362415666200211105355","url":null,"abstract":"\u0000\u0000 With the enhancement in manageability and robustness, ultrasound discovers growing usage in an eclectic variety of applications. The capability to accomplish and construe an outsized variability of ultrasound investigations is marvelously revealed by Physicians, nurses and medical officers, and the use of ultrasound in the developing world is unequivocally supported by a growing body of literature. This paper delivers a general idea of the technological and engineering developments that succor in the progression of ultrasonic applications. This paper reviews the prevailing literature in aid of ultrasound use in the emerging biosphere. It also endorses imminent guidelines for ultrasound usage and exploration in order to develop the investigative capability and patient care in the utmost far-flung regions of the world.\u0000\u0000\u0000\u0000\u0000A well-thought-out examination of bibliographic records in quest of peer-reviewed research accomplishments by means of an intensive assessment interrogation was carried out. Good quality papers were included in the review based on their features. With the intention of analyzing the verdicts of the considered investigations, we employed an inferential scrutiny approach centered on the quality of the content.\u0000\u0000\u0000\u0000\u0000 A total of 152 papers were included in this review including a massive volume of literature works on various ultrasonic applications. These ultrasonic applications included food processing, cleaning, and nanostructured material synthesis along with a variety of therapeutic and clinical applications. This review identified the captivating improvements and ground-breaking applications of ultrasound worldwide together with a few of its prospective applications.\u0000\u0000\u0000\u0000\u0000The utilization of ultrasound in processing crafts innovative and attention-grabbing approaches which have an eclectic scope for further research both from industrial and academic perspectives. Various areas, for instance: crystallization, degassing, drying, extraction, filtration, freezing, homogenization, meat tenderization, sterilization, etc.; have been acknowledged with prodigious potential for forthcoming improvements in food processing and preservation. Enriched extraction of heat sensitive bioactive and food constituents at lower processing temperatures can be carried out using UAE. There is also a prospective for attaining concurrent extrication and encapsulation of extracted constituents via ultrasonic. Nevertheless, its utilization in the diagnosis of certain syndromes still remains controversial. In the near future, tumor ablation would necessitate the most important use of high intensity focused ultrasound in medicine. These applications, predominantly the treatment of uterine fibroids, are projected to encounter stretched out usage globally. With the proliferation of additional ablation techniques, a number of electrifying enhancements and innovative applications lie on the vista; together with application for targeted drug delivery and gene thera","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":"15 1","pages":"1-13"},"PeriodicalIF":0.0,"publicationDate":"2020-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48410241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-02-03DOI: 10.2174/1574362415666200203122829
Rajesh Basnet
The serum and glucocorticoid inducible protein kinase (SGK) family signals downstream of phosphoinositide-3-kinase (PI3K) and is made up of three isoforms: SGK1, 2, and 3. respectively, and their activity is dependent on growth factor activation. Among these SGK family one such potential target and less explored enzyme is SGK3. SGK3 regulate a range of basic cellular processes, such as cell proliferation, migration and survival. Thus play an important role in cancer development. These kinase-signaling pathways present both opportunities and challenges for cancer therapy. In this paper, we reviewed the status of SGK3 regulation and its role in normal cell physiology and transformation. In addition, the potential roles of SGK3 signal transduction in breast cancer and prostate cancer are discussed.
{"title":"Mechanisms of activation and key roles of SGK3 under physiological conditions and in prostate and breast cancer.","authors":"Rajesh Basnet","doi":"10.2174/1574362415666200203122829","DOIUrl":"https://doi.org/10.2174/1574362415666200203122829","url":null,"abstract":"\u0000\u0000The serum and glucocorticoid inducible protein kinase (SGK) family signals downstream of phosphoinositide-3-kinase (PI3K) and is made up of three isoforms: SGK1, 2, and 3. respectively, and their activity is dependent on growth factor activation. Among these SGK family one such potential target and less explored enzyme is SGK3. SGK3 regulate a range of basic cellular processes, such as cell proliferation, migration and survival. Thus play an important role in cancer development. These kinase-signaling pathways present both opportunities and challenges for cancer therapy. In this paper, we reviewed the status of SGK3 regulation and its role in normal cell physiology and transformation. In addition, the potential roles of SGK3 signal transduction in breast cancer and prostate cancer are discussed.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":"15 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2020-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2174/1574362415666200203122829","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46996789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-27DOI: 10.2174/1574362415666191227154656
S. Manju, Helenprabha K
In recent days, the remote sensing algorithms are used in the medical field for improving the visualization of the medical images. Because, the medical images are generally in the gray scale image format for better visualization the colour Doppler or spectrograms are used but they are expensive. To overcome this drawback the remote sensing algorithm is applied to the medical images to group the pixels and visualize in different colours. The image processing techniques is used to classify the vegetation region into 16 samples. The image pre-processing is done by Wiener filter to remove the noise. Feature extraction is carried out by Grey Level Co-occurrence Matrix (GLCM) and the spectral bands are optimized by Particle Swarm Optimization (PSO) .The classification of vegetation region is classified by Extreme Learning Machine. In this, the comparisons of the remote sensing algorithms like IRVM-MFO, ELM-DF and ELM-PSO for the Indian pines and Salinas Dataset. Among these the ELM- Dragon Fly algorithm produced the best results for both the sets. Hence, this ELM-DF is applied to the Brain tissue region segmentation. In this paper the analysis is performed to find the efficient method for vegetation classification by comparing with other methods. Simulations are carried out on two datasets such as Indian Pine and Salinas scene. Performance metrics such as accuracy, specificity, and sensitivity have been evaluated that show the efficiency of the proposed classifier.
{"title":"Analysis Of Vegetation Classification Algorithms On Satellite Images And Medical Images","authors":"S. Manju, Helenprabha K","doi":"10.2174/1574362415666191227154656","DOIUrl":"https://doi.org/10.2174/1574362415666191227154656","url":null,"abstract":"\u0000\u0000In recent days, the remote sensing algorithms are used in the medical field for improving the visualization of the medical images. Because, the medical images are generally in the gray scale image format for better visualization the colour Doppler or spectrograms are used but they are expensive. To overcome this drawback the remote sensing algorithm is applied to the medical images to group the pixels and visualize in different colours. The image processing techniques is used to classify the vegetation region into 16 samples. The image pre-processing is done by Wiener filter to remove the noise. Feature extraction is carried out by Grey Level Co-occurrence Matrix (GLCM) and the spectral bands are optimized by Particle Swarm Optimization (PSO) .The classification of vegetation region is classified by Extreme Learning Machine. In this, the comparisons of the remote sensing algorithms like IRVM-MFO, ELM-DF and ELM-PSO for the Indian pines and Salinas Dataset. Among these the ELM- Dragon Fly algorithm produced the best results for both the sets. Hence, this ELM-DF is applied to the Brain tissue region segmentation. In this paper the analysis is performed to find the efficient method for vegetation classification by comparing with other methods. Simulations are carried out on two datasets such as Indian Pine and Salinas scene. Performance metrics such as accuracy, specificity, and sensitivity have been evaluated that show the efficiency of the proposed classifier.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46822033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-13DOI: 10.2174/1574362415666191213145321
Yinglei Song, Mohammad N.A. Rana, Junfeng Qu, Chunmei Liu
Recently, deep learning based methods have become an important approach to the accurate analysis of medical images. This paper provides a comprehensive survey of the most important deep learning based methods that have been developed for medical image processing. A number of important contributions made in last five years are summarized and surveyed. Specifically, deep learning based algorithms developed for image segmentation, image classification, registration, object detection and other important problems are reviewed. In addition, an overview of challenges that currently exist in the field and potential directions for future research is provided in the end of the survey.
{"title":"A Survey of Deep Learning Based Methods in Medical Image Processing","authors":"Yinglei Song, Mohammad N.A. Rana, Junfeng Qu, Chunmei Liu","doi":"10.2174/1574362415666191213145321","DOIUrl":"https://doi.org/10.2174/1574362415666191213145321","url":null,"abstract":"\u0000\u0000Recently, deep learning based methods have become an important approach to the accurate analysis of medical images. \u0000\u0000\u0000\u0000\u0000 This paper provides a comprehensive survey of the most important deep learning based methods that have been developed for medical image processing. A number of important contributions made in last five years are summarized and surveyed. \u0000\u0000\u0000\u0000\u0000 Specifically, deep learning based algorithms developed for image segmentation, image classification, registration, object detection and other important problems are reviewed. In addition, an overview of challenges that currently exist in the field and potential directions for future research is provided in the end of the survey.\u0000\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":"15 1","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2019-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41828187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-02DOI: 10.2174/1574362414666191202100807
Teresa V.V, A. B
In this research work presents an efficient way Carry Select Adder (CSLA) performance and estimation. The CSLA is utilized in several system to mitigate the issue of carry propagation delay that is happens by severally generating various carries and to get the sum, select a carry because of the uses of various pairs of RCA to provide the sum of the partial section also carry by consisting carry input but the CSLA isn't time economical, then by the multiplexers extreme total and carry is chosen in the selected section. The fundamental plan of this work is to attain maximum speed and minimum power consumption by using Binary to Excess-1. Convertor rather than RCA within the regular CSLA. Here RCA denotes the Ripple Carry Adder section. At the span to more cut back the facility consumption, a method of CSLA with D LATCH is implemented during this research work. The look of Updated Efficient Area -Carry Select Adder (UEA-CSLA) is evaluated and intended in XILINX ISE design suite 14. 5 tools. This VLSI arrangement is utilized in picture preparing application by concluding the cerebrum tumor discovery. In this study, medicinal pictures estimation, investigation districts in the multi phantom picture isn't that much proficient to defeat this disadvantage here utilized hyper spectral picture method is presented a sifting procedure in VLSI innovation restriction of cerebrum tumor is performed Updated Efficient Area - Carry Select Adder propagation result dependent on Matrix Laboratory in the adaptation of R2018b.
{"title":"Updated Efficient Area -Carry Select Adder for Low Complexity D LATCH Configuration by disease identification in brain tumor hyper spectral image","authors":"Teresa V.V, A. B","doi":"10.2174/1574362414666191202100807","DOIUrl":"https://doi.org/10.2174/1574362414666191202100807","url":null,"abstract":"\u0000\u0000 In this research work presents an efficient way Carry Select Adder (CSLA) performance and estimation. The CSLA is utilized in several system to mitigate the issue of carry propagation delay that is happens by severally generating various carries and to get the sum, select a carry because of the uses of various pairs of RCA to provide the sum of the partial section also carry by consisting carry input but the CSLA isn't time economical, then by the multiplexers extreme total and carry is chosen in the selected section. \u0000\u0000\u0000\u0000\u0000 The fundamental plan of this work is to attain maximum speed and minimum power consumption by using Binary to Excess-1. Convertor rather than RCA within the regular CSLA. Here RCA denotes the Ripple Carry Adder section. At the span to more cut back the facility consumption, a method of CSLA with D LATCH is implemented during this research work. The look of Updated Efficient Area -Carry Select Adder (UEA-CSLA) is evaluated and intended in XILINX ISE design suite 14. 5 tools. This VLSI arrangement is utilized in picture preparing application by concluding the cerebrum tumor discovery. \u0000\u0000\u0000\u0000\u0000 In this study, medicinal pictures estimation, investigation districts in the multi phantom picture isn't that much proficient to defeat this disadvantage here utilized hyper spectral picture method is presented a sifting procedure in VLSI innovation restriction of cerebrum tumor is performed Updated Efficient Area - Carry Select Adder propagation result dependent on Matrix Laboratory in the adaptation of R2018b. \u0000\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45454694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-12-02DOI: 10.2174/1574362414666191202144116
N. Shahparian, M. Yazdi, M. Khosravi
In recent years, resting-state functional magnetic resonance imaging (rs-fMRI) has been increasingly used as a noninvasive and practical method in different areas of neuroscience and psychology for recognizing brain’s mechanism as well as diagnosing neurological diseases. In this work, we use rs-fMRI data for diagnosing Alzheimer disease. To do that, by using the rs-fMRI of a patient, we computed the time series of some anatomical regions and then applied the Latent Low Rank Representation method to extract suitable features. Next, based on the extracted features we apply a Support Vector Machine (SVM) classifier to determine whether the patient belongs to healthy category, mild stage of the disease or Alzheimer stage. The obtained classification accuracy for the proposed method is more than 97.5%. We performed different experiments on a database of rs-fMRI data containing the images of 43 healthy subjects, 36 mild cognitive impairment patients and 32 Alzheimer patients and the obtained results demonstrated that the best performance is achieved when the SVM with Gaussian kernel and the features of only 7 regions were used.
{"title":"Alzheimer Disease Diagnosis from fMRI images Based on Latent Low Rank Features and Support Vector Machine (SVM)","authors":"N. Shahparian, M. Yazdi, M. Khosravi","doi":"10.2174/1574362414666191202144116","DOIUrl":"https://doi.org/10.2174/1574362414666191202144116","url":null,"abstract":"\u0000\u0000In recent years, resting-state functional magnetic resonance imaging (rs-fMRI) has been increasingly used as a noninvasive and practical method in different areas of neuroscience and psychology for recognizing brain’s mechanism as well as diagnosing neurological diseases. In this work, we use rs-fMRI data for diagnosing Alzheimer disease.\u0000\u0000\u0000\u0000To do that, by using the rs-fMRI of a patient, we computed the time series of some anatomical regions and then applied the Latent Low Rank Representation method to extract suitable features. Next, based on the extracted features we apply a Support Vector Machine (SVM) classifier to determine whether the patient belongs to healthy category, mild stage of the disease or Alzheimer stage.\u0000\u0000\u0000\u0000The obtained classification accuracy for the proposed method is more than 97.5%.\u0000\u0000\u0000\u0000We performed different experiments on a database of rs-fMRI data containing the images of 43 healthy subjects, 36 mild cognitive impairment patients and 32 Alzheimer patients and the obtained results demonstrated that the best performance is achieved when the SVM with Gaussian kernel and the features of only 7 regions were used.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":"15 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2019-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48196580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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