Pub Date : 2021-03-25DOI: 10.2174/1574362416666210325112850
Y. Yap, E. Chowdhury, R. Koh, S. Chye, Kenny Gah Leong Voon, Iekhsan Othman, K. Ng
PARK9 familial Parkinson’s disease (PD) is caused by loss-of-function mutation in ATP13A2 gene in which the mutation impairs autophagic-lysosomal degradation pathway and induces intraneuronal accumulation of alpha-synuclein. RNA interference has been a useful tool to generate in vitro knockdown model to study the physiological role of gene. However, availability of validated ATP13A2-deficient in vitro model is limited. Hence, we developed the ATP13A2-deficient PD model by delivering ATP13A2 siRNA into neuroblastoma cells using carbonate apatite nanoparticles (CA NPs). CA NPs were fabricated using different concentrations of calcium chloride and characterised, in the presence or absence of ATP13A2 siRNA. Time-dependent stabilities of CA NPs and CA NPs-associated siRNA (CA-siRNA) complex were evaluated by pH, turbidity, size, and zeta potential measurements. The dissolution abilities at acidic condition of both complexes were investigated. Following that, green fluorescence protein (GFP) and four different siRNAs targeting ATP13A2 (siRNA_5, 6, 7 and 8) were transfected to cells with the fabricated CA NPs. Western blot was performed to determine the knockdown effect of the four siRNAs. It was found that 4 mM calcium chloride was ideal for CA NP formation while incubation time of 48 hours is required to maintain the stability of nanoparticles. Successful transfection was confirmed by detection of fluorescence signal from the GFP plasmid and subsequent silencing of this signal by transfecting GFP siRNA. Western blot analysis revealed that ATP13A2 protein expression was significantly reduced to 20% upon transfection with 20 nM of siRNA_5. ATP13A2-deficient PD model was successfully developed.
{"title":"Development of ATP13A2-deficient in vitro Model for PARK9 Parkinson’s Disease","authors":"Y. Yap, E. Chowdhury, R. Koh, S. Chye, Kenny Gah Leong Voon, Iekhsan Othman, K. Ng","doi":"10.2174/1574362416666210325112850","DOIUrl":"https://doi.org/10.2174/1574362416666210325112850","url":null,"abstract":"\u0000\u0000PARK9 familial Parkinson’s disease (PD) is caused by loss-of-function mutation in ATP13A2 gene in which the mutation impairs autophagic-lysosomal degradation pathway and induces intraneuronal accumulation of alpha-synuclein. RNA interference has been a useful tool to generate in vitro knockdown model to study the physiological role of gene. However, availability of validated ATP13A2-deficient in vitro model is limited. \u0000\u0000\u0000\u0000\u0000Hence, we developed the ATP13A2-deficient PD model by delivering ATP13A2 siRNA into neuroblastoma cells using carbonate apatite nanoparticles (CA NPs). \u0000\u0000\u0000\u0000CA NPs were fabricated using different concentrations of calcium chloride and characterised, in the presence or absence of ATP13A2 siRNA. Time-dependent stabilities of CA NPs and CA NPs-associated siRNA (CA-siRNA) complex were evaluated by pH, turbidity, size, and zeta potential measurements. The dissolution abilities at acidic condition of both complexes were investigated. Following that, green fluorescence protein (GFP) and four different siRNAs targeting ATP13A2 (siRNA_5, 6, 7 and 8) were transfected to cells with the fabricated CA NPs. Western blot was performed to determine the knockdown effect of the four siRNAs.\u0000\u0000\u0000\u0000It was found that 4 mM calcium chloride was ideal for CA NP formation while incubation time of 48 hours is required to maintain the stability of nanoparticles. Successful transfection was confirmed by detection of fluorescence signal from the GFP plasmid and subsequent silencing of this signal by transfecting GFP siRNA. Western blot analysis revealed that ATP13A2 protein expression was significantly reduced to 20% upon transfection with 20 nM of siRNA_5. \u0000\u0000\u0000\u0000ATP13A2-deficient PD model was successfully developed.\u0000\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49230310","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 : 2021-03-09DOI: 10.2174/1574362416666210309154336
Sakshi Gupta, K. Veer
An infectious disease enumerated in Wuhan, China in December 2019, and then exported in many countries across world called Coronavirus disease 2019. It is also named by COVID-19. COVID-19 is an ongoing pandemic 60.2 Million confirmed cases, which is a leading health concern for public across the world, where mainly middle and old age people are hospitalized and dead across the affected countries. Where more than 1.42 Million people have deceased and More than 41.5 Million people have been recovered. Almost all the countries are fighting against the transmission of the virus by restricting transportation and other daily life activities. Coronavirus outbreak causes many psychological disorders, such as, fear of infection and dying. On the other hand, COVID-19 results some positive consequences on environment due to restricted human activities. Environmental conditions including air quality, global warming, water quality, change of biodiversity and ecosystem and many more parameters are shows a significant improvement in meteorological graph. Overall environmental pollution is reduced and earth is healing itself.
{"title":"Lesson From Covid19 Outbreak And Its Impact: A Generalized Study","authors":"Sakshi Gupta, K. Veer","doi":"10.2174/1574362416666210309154336","DOIUrl":"https://doi.org/10.2174/1574362416666210309154336","url":null,"abstract":"\u0000\u0000An infectious disease enumerated in Wuhan, China in December 2019, and then exported in many countries across world called Coronavirus disease 2019. It is also named by COVID-19. COVID-19 is an ongoing pandemic 60.2 Million confirmed cases, which is a leading health concern for public across the world, where mainly middle and old age people are hospitalized and dead across the affected countries. Where more than 1.42 Million people have deceased and More than 41.5 Million people have been recovered. Almost all the countries are fighting against the transmission of the virus by restricting transportation and other daily life activities. Coronavirus outbreak causes many psychological disorders, such as, fear of infection and dying. On the other hand, COVID-19 results some positive consequences on environment due to restricted human activities. Environmental conditions including air quality, global warming, water quality, change of biodiversity and ecosystem and many more parameters are shows a significant improvement in meteorological graph. Overall environmental pollution is reduced and earth is healing itself.\u0000\u0000\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47292107","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 : 2021-01-20DOI: 10.2174/1574362416666210120104636
P. Mosaddeghi, F. Shahabinezhad, Z. Dehghani, Mitra Farahmandnejad, M. Taghipour, M. Moghadami, Navid Nezafat, S. Masoompour, M. Negahdaripour
As the outbreak of COVID-19 has accelerated, an urgent need for finding strategies to combat the virus is growing. Thus, gaining more knowledge on the pathogenicity mechanism of SARS-CoV-2, the causing agent of COVID-19, and its interaction with the immune system is of utmost importance. Although this novel virus is not well known yet, its structural and genetic similarity with SARS-CoV as well as the comparable pattern of age-mortality relations suggest that some previous findings on SARS could be applicable for COVID-19. The aim of this study was to investigate the most important signaling pathways activated by coronaviruses to better understand the viral pathogenesis and host immune responses. Here, a systems biology study was conducted on a SARS database. It was followed by a literature review on the cognate subject. It was proved that interferons may possess a crucial role in the defense against coronavirus diseases. The literature supported the validity of the employed approach and the notion that interferon induction could play a key role in the body defense against coronavirus infections. Altogether, administration of interferons or interferon-inducing agents in a prophylactic manner or at early stages of the disease, could mimic the effective antiviral responses against SARS-CoV-2 and reduce the disease severity. At later stages of the disease, however, the balance of the immune reactions would be disrupted and the responses would shift toward immunopathogenic over-reactions, which could be exacerbated by interferon usage. Moderating the activity of the immune system by anti-inflammatory agents, might be the optimum approach in such conditions.
{"title":"Therapeutic Approaches for COVID-19 Based on the Interferon-mediated Immune Responses","authors":"P. Mosaddeghi, F. Shahabinezhad, Z. Dehghani, Mitra Farahmandnejad, M. Taghipour, M. Moghadami, Navid Nezafat, S. Masoompour, M. Negahdaripour","doi":"10.2174/1574362416666210120104636","DOIUrl":"https://doi.org/10.2174/1574362416666210120104636","url":null,"abstract":"\u0000\u0000 As the outbreak of COVID-19 has accelerated, an urgent need for finding strategies to combat the\u0000virus is growing. Thus, gaining more knowledge on the pathogenicity mechanism of SARS-CoV-2, the causing agent of\u0000COVID-19, and its interaction with the immune system is of utmost importance. Although this novel virus is not well known\u0000yet, its structural and genetic similarity with SARS-CoV as well as the comparable pattern of age-mortality relations suggest\u0000that some previous findings on SARS could be applicable for COVID-19.\u0000\u0000\u0000\u0000 The aim of this study was to investigate the most important signaling pathways activated by coronaviruses to\u0000better understand the viral pathogenesis and host immune responses.\u0000\u0000\u0000\u0000 Here, a systems biology study was conducted on a SARS database. It was followed by a literature review on the\u0000cognate subject.\u0000\u0000\u0000\u0000 It was proved that interferons may possess a crucial role in the defense against coronavirus diseases. The literature\u0000supported the validity of the employed approach and the notion that interferon induction could play a key role in the body\u0000defense against coronavirus infections.\u0000\u0000\u0000\u0000 Altogether, administration of interferons or interferon-inducing agents in a prophylactic manner or at early\u0000stages of the disease, could mimic the effective antiviral responses against SARS-CoV-2 and reduce the disease severity.\u0000At later stages of the disease, however, the balance of the immune reactions would be disrupted and the responses would\u0000shift toward immunopathogenic over-reactions, which could be exacerbated by interferon usage. Moderating the activity of\u0000the immune system by anti-inflammatory agents, might be the optimum approach in such conditions.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46519555","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 : 2021-01-20DOI: 10.2174/1574362416666210120103124
Nikita Jatai, Tanu Sharma, K. Veer
All over the world, there is a new target of public health emergency looming the world along with an appearance and distribution of the novel coronavirus disease (2019-nCoV) also known as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). This Virus initially generated in bats and then after transferred to a human being over unknown animal playing the role of mediator in Wuhan, China in December 2019. This virus is passed by breathing or in contact with an infected person’s droplets. The Incubation period is between 2 to 14 days for COVID-19, that is the time between exposure of the virus (person becoming infected) and symptom on that person, is on an average of 5-6 days, however it can goes up to 14 days. Throughout this period, which can be also known as “pre-symptomatic” period, some of the infected patients or persons can be contagious. That is why, transferal from a pre-symptomatic case can happen before the symptoms onset. Where there is few number of case studies and reports, pre-symptomatic transferal has been documented via contact with someone who is diagnosed with virus and increase investigation of that particular clusters of total confirmed cases. The main problem is that the symptoms are just like the regular flu that are cough, fever, sore throat, fatigue and breathlessness. This virus is moderate or mild in most of the people, but in elder ones, it may proceed to pneumonia, multi-organ dysfunction and Acute Respiratory Distress Syndrome (ARDS). Coronavirus has significant consequences on the Health system, mainly on cardiovascular diseases and on the environment.
{"title":"Impact of Corona virus Outbreak on Climate and air Quality","authors":"Nikita Jatai, Tanu Sharma, K. Veer","doi":"10.2174/1574362416666210120103124","DOIUrl":"https://doi.org/10.2174/1574362416666210120103124","url":null,"abstract":"\u0000\u0000All over the world, there is a new target of public health emergency looming the world along with an appearance and distribution of the novel coronavirus disease (2019-nCoV) also known as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). This Virus initially generated in bats and then after transferred to a human being over unknown animal playing the role of mediator in Wuhan, China in December 2019. This virus is passed by breathing or in contact with an infected person’s droplets. The Incubation period is between 2 to 14 days for COVID-19, that is the time between exposure of the virus (person becoming infected) and symptom on that person, is on an average of 5-6 days, however it can goes up to 14 days. Throughout this period, which can be also known as “pre-symptomatic” period, some of the infected patients or persons can be contagious. That is why, transferal from a pre-symptomatic case can happen before the symptoms onset. Where there is few number of case studies and reports, pre-symptomatic transferal has been documented via contact with someone who is diagnosed with virus and increase investigation of that particular clusters of total confirmed cases. The main problem is that the symptoms are just like the regular flu that are cough, fever, sore throat, fatigue and breathlessness. This virus is moderate or mild in most of the people, but in elder ones, it may proceed to pneumonia, multi-organ dysfunction and Acute Respiratory Distress Syndrome (ARDS). Coronavirus has significant consequences on the Health system, mainly on cardiovascular diseases and on the environment.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44226300","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 : 2021-01-15DOI: 10.2174/1574362414666190619092910
Iyappan Murugesan and Karpagam Sathish
This paper presents electrical power system comprises many complex and interrelating elements that are susceptible to the disturbance or electrical fault. The faults in electrical power system transmission line (TL) are detected and classified. But, the existing techniques like Artificial Neural Network (ANN) failed to improve the Fault Detection (FD) performance during transmission and distribution. In order to reduce the Power Loss Rate (PLR), Daubechies Wavelet Transform based Gradient Ascent Deep Neural Learning (DWT-GADNL) Technique is introduced for FDin electrical power sub-station. DWT-GADNL Technique comprises three step, normalization, feature extraction and FD through optimization. Initially sample power TL signal is taken. After that in first step, min-max normalization process is carried out to estimate the various rated values of transmission lines. Then in second step, Daubechies Wavelet Transform (DWT) is employed for decomposition of normalized TL signal to different components for feature extraction with higher accuracy. Finally in third step, Gradient Ascent Deep Neural Learning is an optimization process for detecting the local maximum (i.e., fault) from the extracted values with help of error function and weight value. When maximum error with low weight value is identified, the fault is detected with lesser time consumption. DWT-GADNL Technique is measured with PLR, Feature Extraction Accuracy (FEA), and Fault Detection Time (FDT). The simulation result shows that DWT-GADNL Technique is able to improve the performance of FEA and reduces FDT and PLR during the transmission and distribution when compared to state-ofthe- art works. An electric power system incorporates production, broadcast and distribution of electric energy. To send the electric power to massive load centers, transmission lines are exploited. The fast growth of electric power systems results in huge number of lines in operation and total length. TL are susceptible to faults in case of lightning, short circuits, mis-operation, human errors, overload, etc. Faults resulted in tiny to long power outages for customers. To protect the reliable power system operations, Fault identification, isolation and localization are imperative. The voltage lessened to minimal value, when fault occurs on TL. FD is an essential problem in power system engineering to minimize the PLR. DWT-GADNL Technique is introduced for FD in TL during transmission and distribution. Power Loss due to the fault occurrence during the transmission and distribution is a common problem in electrical power system. To lessen the PLR, the fault is detected in earlier stage. From the sample transmission line, the features are extracted and the values are calculated. When the observed value is lesser than the actual value, the fault is detected through performing the gradient ascent optimization process in transmission line. In this optimization process, the local maxima are identified to reduce th
{"title":"Gradient Ascent Optimization for Fault Detection in Electrical Power Systems based on Wavelet Transformation","authors":"Iyappan Murugesan and Karpagam Sathish","doi":"10.2174/1574362414666190619092910","DOIUrl":"https://doi.org/10.2174/1574362414666190619092910","url":null,"abstract":"\u0000\u0000This paper presents electrical power system comprises many complex and interrelating\u0000elements that are susceptible to the disturbance or electrical fault. The faults in electrical\u0000power system transmission line (TL) are detected and classified. But, the existing techniques like Artificial\u0000Neural Network (ANN) failed to improve the Fault Detection (FD) performance during transmission\u0000and distribution. In order to reduce the Power Loss Rate (PLR), Daubechies Wavelet Transform\u0000based Gradient Ascent Deep Neural Learning (DWT-GADNL) Technique is introduced for FDin electrical\u0000power sub-station. DWT-GADNL Technique comprises three step, normalization, feature extraction\u0000and FD through optimization. Initially sample power TL signal is taken. After that in first step,\u0000min-max normalization process is carried out to estimate the various rated values of transmission lines.\u0000Then in second step, Daubechies Wavelet Transform (DWT) is employed for decomposition of normalized\u0000TL signal to different components for feature extraction with higher accuracy. Finally in third step,\u0000Gradient Ascent Deep Neural Learning is an optimization process for detecting the local maximum (i.e.,\u0000fault) from the extracted values with help of error function and weight value. When maximum error\u0000with low weight value is identified, the fault is detected with lesser time consumption. DWT-GADNL\u0000Technique is measured with PLR, Feature Extraction Accuracy (FEA), and Fault Detection Time\u0000(FDT). The simulation result shows that DWT-GADNL Technique is able to improve the performance\u0000of FEA and reduces FDT and PLR during the transmission and distribution when compared to state-ofthe-\u0000art works.\u0000\u0000\u0000\u0000An electric power system incorporates production, broadcast and distribution\u0000of electric energy. To send the electric power to massive load centers, transmission lines are exploited.\u0000The fast growth of electric power systems results in huge number of lines in operation and total length.\u0000TL are susceptible to faults in case of lightning, short circuits, mis-operation, human errors, overload, etc.\u0000Faults resulted in tiny to long power outages for customers. To protect the reliable power system operations,\u0000Fault identification, isolation and localization are imperative. The voltage lessened to minimal value,\u0000when fault occurs on TL. FD is an essential problem in power system engineering to minimize the PLR.\u0000DWT-GADNL Technique is introduced for FD in TL during transmission and distribution.\u0000\u0000\u0000\u0000Power Loss due to the fault occurrence during the transmission and distribution is a common\u0000problem in electrical power system. To lessen the PLR, the fault is detected in earlier stage. From the\u0000sample transmission line, the features are extracted and the values are calculated. When the observed\u0000value is lesser than the actual value, the fault is detected through performing the gradient ascent optimization\u0000process in transmission line. In this optimization process, the local maxima are identified to reduce\u0000th","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43615749","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 : 2021-01-15DOI: 10.2174/1574362414666181226154935
J. Senbagamalar
A topological index of a graph G is a numerical parameter related to G which characterizes its molecular topology. In the field of QSAR and QSPR research, theoretical properties of the chemical compounds and their molecular topological indices such as distance connectivity indices and degree connectivity indices are used to predict the bioactivity of different molecular compounds. Such an approach is different from the traditional QSAR methodology, where one employs selected simpler physico-chemical properties to predict biological activities of molecules. In order to obtain the structure-activity relationships in which theoretical and computational methods are necessary to find appropriate representations of the molecular structure of chemical compounds. These representations are realized through the molecular descriptors. Molecular descriptors are numbers containing structural information derived from the structural representation used for molecules under study. A topological index defined on molecular structure G can be considered as a real valued function f :G→ R+ which maps each durg molecular structure to certain real numbers. Graphene sheets are composed of carbon atoms linked in hexagonal shapes with each carbon atom covalently bonded to three other carbon atoms. Each sheet of graphene is only one atom thick and each graphene sheet is considered a single molecule. Graphene has the same structure of carbon atoms linked in hexagonal shapes to form carbon nanotubes, but graphene is flat rather than cylindrical.. This paper addresses the problem of computing the Wiener , First Zagreb index and Forgotten index of Complementary graphs of graphene sheets, triangular benzenoid graph, circumcoronene molecular graph and nanostar dendrimers. The line graphs were used for modeling amino acid sequences of proteins and of the genetic code. The connected graphs are isomorphic to self complementary graphs. Recently, molecular graphs have proved to be highly useful for drugs activity. Non empirical parameters of chemical structures derived from graph theoretic formalisms are being widely used by many researchers in studies pertaining to molecular design, pharmaceutical drug-design, and environmental hazard assessment of chemicals.
{"title":"On Graph theoretic index of Complementary Benzenoids And Macromolecules","authors":"J. Senbagamalar","doi":"10.2174/1574362414666181226154935","DOIUrl":"https://doi.org/10.2174/1574362414666181226154935","url":null,"abstract":"\u0000\u0000A topological index of a graph G is a numerical parameter related to G\u0000which characterizes its molecular topology. In the field of QSAR and QSPR research, theoretical\u0000properties of the chemical compounds and their molecular topological indices such as distance\u0000connectivity indices and degree connectivity indices are used to predict the bioactivity of different\u0000molecular compounds.\u0000\u0000\u0000\u0000Such an approach is different from the traditional QSAR methodology,\u0000where one employs selected simpler physico-chemical properties to predict biological activities of\u0000molecules. In order to obtain the structure-activity relationships in which theoretical and computational\u0000methods are necessary to find appropriate representations of the molecular structure of\u0000chemical compounds. These representations are realized through the molecular descriptors. Molecular\u0000descriptors are numbers containing structural information derived from the structural representation\u0000used for molecules under study.\u0000\u0000\u0000\u0000A topological index defined on molecular structure G can be considered as a real valued\u0000function\u0000f :G→ R+ which maps each durg molecular structure to certain real numbers. Graphene\u0000sheets are composed of carbon atoms linked in hexagonal shapes with each carbon atom covalently\u0000bonded to three other carbon atoms. Each sheet of graphene is only one atom thick and each\u0000graphene sheet is considered a single molecule. Graphene has the same structure of carbon atoms\u0000linked in hexagonal shapes to form carbon nanotubes, but graphene is flat rather than cylindrical..\u0000This paper addresses the problem of computing the Wiener , First Zagreb index and Forgotten index\u0000of Complementary graphs of graphene sheets, triangular benzenoid graph, circumcoronene\u0000molecular graph and nanostar dendrimers.\u0000\u0000\u0000\u0000The line graphs were used for modeling amino acid sequences of proteins and of the\u0000genetic code. The connected graphs are isomorphic to self complementary graphs. Recently, molecular\u0000graphs have proved to be highly useful for drugs activity. Non empirical parameters of\u0000chemical structures derived from graph theoretic formalisms are being widely used by many researchers\u0000in studies pertaining to molecular design, pharmaceutical drug-design, and environmental\u0000hazard assessment of chemicals.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2174/1574362414666181226154935","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67973433","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 : 2021-01-04DOI: 10.2174/1574362415999210104223820
Imen Saidi, A. Hammami
In this paper, a robust sliding mode controller is developed to control an orthosis used for rehabilitation of lower limb. The orthosis is defined as a mechanical device intended to physically assist a human subject for the realization of his movements. It should be adapted to the human morphology, interacting in harmony with its movements, and providing the necessary efforts along the limbs to which it is attached. The application of the sliding mode control to the Shank-orthosis system shows satisfactory dynamic response and tracking performances. In fact, position tracking and speed tracking errors are very small. The sliding mode controller effectively absorbs disturbance and parametric variations, hence the efficiency and robustness of our applied control.
{"title":"Sliding Mode Control of an Actuated Knee Joint Orthosis","authors":"Imen Saidi, A. Hammami","doi":"10.2174/1574362415999210104223820","DOIUrl":"https://doi.org/10.2174/1574362415999210104223820","url":null,"abstract":"\u0000\u0000In this paper, a robust sliding mode controller is developed to control an orthosis used for rehabilitation of lower limb.\u0000\u0000\u0000\u0000The orthosis is defined as a mechanical device intended to physically assist a human subject for the realization of his movements. It should be adapted to the human morphology, interacting in harmony with its movements, and providing the necessary efforts along the limbs to which it is attached.\u0000\u0000\u0000\u0000The application of the sliding mode control to the Shank-orthosis system shows satisfactory dynamic response and tracking performances.\u0000\u0000\u0000\u0000In fact, position tracking and speed tracking errors are very small. The sliding mode controller effectively absorbs disturbance and parametric variations, hence the efficiency and robustness of our applied control.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45897524","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 : 2020-12-23DOI: 10.2174/1574362415999201223090332
K. Veer, Tanu Sharma
Till now, across from a few basic data, nothing is well clear regarding its exact origin, incubation period, seriousness and what makes it transmissible is not recommended for COVID19 anywhere in the world. It was on 28 January that the World Health Organisation released a paper relating to medical data and recommendations from the management of previous HCoV epidemics. The present paper outlines steps for the identification and assessment of patients with extreme acute respiratory disease; monitoring and infection prevention strategies; tracking and early intervention therapy; treatment of respiratory arrest and ARDS; clinical diagnosis; recommendations for septic shock management; therapies; and concerns for pregnant women.
{"title":"Impact of Covid19 and its Treatment: a Report","authors":"K. Veer, Tanu Sharma","doi":"10.2174/1574362415999201223090332","DOIUrl":"https://doi.org/10.2174/1574362415999201223090332","url":null,"abstract":"\u0000\u0000Till now, across from a few basic data, nothing is well clear regarding its exact origin, incubation period,\u0000seriousness and what makes it transmissible is not recommended for COVID19 anywhere in the world. It was on 28\u0000January that the World Health Organisation released a paper relating to medical data and recommendations from the\u0000management of previous HCoV epidemics. The present paper outlines steps for the identification and assessment of\u0000patients with extreme acute respiratory disease; monitoring and infection prevention strategies; tracking and early\u0000intervention therapy; treatment of respiratory arrest and ARDS; clinical diagnosis; recommendations for septic shock\u0000management; therapies; and concerns for pregnant women.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43043095","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 : 2020-12-01DOI: 10.2174/1574362414666190320163953
O. Akbarzadeh, M. Khosravi, Mehdi Shadloo-Jahromi
Achieving the best possible classification accuracy is the main purpose of each pattern recognition scheme. An interesting area of classifier design is to design for biomedical signal and image processing. In the current work, in order to increase recognition accuracy, a theoretical frame for combination of classifiers is developed. This method uses different pattern representations to show that a wide range of existing algorithms could be incorporated as the particular cases of compound classification where all the pattern representations are used jointly to make an accurate decision. The results show that the combination rules developed under the Naive Bayes and Fuzzy integral method outperforms other classifier combination schemes. The performance of different combination schemes has been studied through an experimental comparison of different classifier combination plans. The dataset used in the article has been obtained from biological signals.
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