Pub Date : 2022-12-02DOI: 10.2174/1574362418666221202152035
Yinglong Hou, Shenzhou Ma, Ximin Wang, Zhan Li
Heart failure was induced by MI in rats. Two weeks after MI surgery, rats with large infarcts (40%) were randomized into control (untreated MI group, n=10) and IMDtreated (n=10) groups. The MI group and Sham group received saline injections. Rats in the IMD group received IMD1-53, 10nmol/kg/day, intraperitoneally, for four weeks. The AF inducibility and atrial effective refractory period (AERP) were assessed with the electrophysiology test. Additionally, the left atrial diameter and heart function and hemodynamic test were performed. We detected the area changes of myocardial fibrosis in the left atrium by using Masson staining. To detect the protein expression and mRNA expression of transforming growth factor-β1 (TGF-β1), αSMA, collagen Ⅰ, collagen Ⅲ and NADPH oxidase (Nox4) in myocardial fibroblasts and left atrial, we used the Western blot method and the SYBR Green I real-time quantitative polymerase chain reaction (PCR) assay Compared with the MI group, IMD1-53 treatment decreased left atrial diameter and improved cardiac function, and it also improved the left ventricle end-diastolic pressure (LVEDP). IMD1-53 treatment attenuated AERP prolongation and reduced atrial fibrillation inducibility in the IMD group. In vivo, IMD1-53 reduced the left atrial fibrosis content in the heart of MI rats and inhibited mRNA and protein expression of collagen type Ⅰ and Ⅲ. IMD1-53 also inhibited the expression of TGF-β1, α-SMA and Nox4 both in mRNA and protein. In vivo, we found that IMD1-53 inhibited the phosphorylation of Smad3. In vitro, we found that the down-regulation of the expression of Nox4 was partly dependent on the TGF-β1/ALK5 pathway. IMD1-53 reduced the inducibility and duration of AF and atrial fibrosis in the rats after the MI operation. The possible mechanisms are associated with the inhibition of TGFβ1/Smad3-related fibrosis and TGF-β1/Nox4 activity. Therefore, IMD1-53 may be a promising agent as upstream therapy for the prevention of AF. Compared with the MI group, IMD1-53 treatment decreased left atrial diameter and improved cardiac function, it also improved the left ventrical end diastolic pressure (LVEDP). IMD1-53 treatment attenuated AERP prolongation and reduced atrial fibrillation inducibility in the IMD group. In vivo, the results showed that IMD1-53 reduced the left atrial fibrosis content on the heart of MI rats and inhibited the expression of collagen type Ⅰ and Ⅲ both in mRNA and protein. IMD1-53 also inhibited the expression of TGF-β1, α-SMA and Nox4 both in mRNA and protein. In vivo, the study also showed that IMD1-53 inhibited the phosphorylation of Smad3. In vitro, we found that the down-regulated the expression of Nox4 was partly dependent on TGF-β1/ALK5 pathway. none.
心肌梗死引起大鼠心力衰竭。心肌梗死术后2周，大面积梗死(40%)大鼠随机分为对照组(未治疗心肌梗死组，n=10)和imd治疗组(n=10)。心肌梗死组和假手术组均给予生理盐水注射。imd组大鼠给予IMD1-53, 10nmol/kg/天，腹腔注射，连续4周。电生理试验评估心房颤动诱导能力和心房有效不应期(AERP)。同时进行左房内径、心功能及血流动力学检查。用马松染色法检测左心房心肌纤维化面积变化。为了检测心肌成纤维细胞和左心房中转化生长因子-β1 (TGF-β1)、αSMA、胶原Ⅰ、胶原Ⅲ和NADPH氧化酶(Nox4)的蛋白表达和mRNA表达，我们采用Western blot法和SYBR Green I实时定量聚合酶链反应(PCR)检测。与MI组比较，IMD1-53治疗可降低左心房内径，改善心功能，改善左心室舒张末压(LVEDP)。IMD1-53治疗减少了imd组的AERP延长和降低了心房颤动的诱发性。体内IMD1-53降低心肌梗死大鼠心脏左心房纤维化含量，抑制胶原型Ⅰ和ⅢmRNA和蛋白表达。IMD1-53对TGF-β1、α-SMA和Nox4的mRNA和蛋白表达均有抑制作用。在体内，我们发现imd1 -53抑制Smad3的磷酸化。在体外，我们发现Nox4表达的下调部分依赖于TGF-β1/ALK5通路。IMD1-53降低心肌梗死术后大鼠房颤和心房纤维化的诱发性和持续时间。其可能机制与抑制TGF-β1/ smad3相关纤维化和TGF-β1/Nox4活性有关。因此，IMD1-53可能是预防房颤上游治疗的有希望的药物。与MI组相比，IMD1-53治疗可减小左房内径，改善心功能，并改善左室舒张末期压(LVEDP)。IMD1-53治疗减少了IMD组的AERP延长，降低了心房颤动的诱发性。体内实验结果显示，IMD1-53降低心肌梗死大鼠心脏左心房纤维化含量，抑制胶原型Ⅰ和ⅢmRNA和蛋白的表达。IMD1-53对TGF-β1、α-SMA和Nox4的mRNA和蛋白表达均有抑制作用。在体内，该研究还表明IMD1-53抑制Smad3的磷酸化。在体外，我们发现Nox4的表达下调部分依赖于TGF-β1/ALK5通路。
{"title":"Intermedin 1-53 Ameliorates Atrial Fibrosis and Reduces Inducibility of\u0000Atrial Fibrillation via TGF-β1/pSmad3 and Nox4 Pathways in a Rat Model\u0000of Heart Failure","authors":"Yinglong Hou, Shenzhou Ma, Ximin Wang, Zhan Li","doi":"10.2174/1574362418666221202152035","DOIUrl":"https://doi.org/10.2174/1574362418666221202152035","url":null,"abstract":"\u0000\u0000Heart failure was induced by MI in rats. Two weeks after MI surgery, rats\u0000with large infarcts (40%) were randomized into control (untreated MI group, n=10) and IMDtreated (n=10) groups. The MI group and Sham group received saline injections. Rats in the IMD\u0000group received IMD1-53, 10nmol/kg/day, intraperitoneally, for four weeks. The AF inducibility\u0000and atrial effective refractory period (AERP) were assessed with the electrophysiology test. Additionally, the left atrial diameter and heart function and hemodynamic test were performed. We detected the area changes of myocardial fibrosis in the left atrium by using Masson staining. To detect the protein expression and mRNA expression of transforming growth factor-β1 (TGF-β1), αSMA, collagen Ⅰ, collagen Ⅲ and NADPH oxidase (Nox4) in myocardial fibroblasts and left atrial,\u0000we used the Western blot method and the SYBR Green I real-time quantitative polymerase chain\u0000reaction (PCR) assay\u0000\u0000\u0000\u0000Compared with the MI group, IMD1-53 treatment decreased left atrial diameter and improved cardiac function, and it also improved the left ventricle end-diastolic pressure (LVEDP).\u0000IMD1-53 treatment attenuated AERP prolongation and reduced atrial fibrillation inducibility in the\u0000IMD group. In vivo, IMD1-53 reduced the left atrial fibrosis content in the heart of MI rats and inhibited mRNA and protein expression of collagen type Ⅰ and Ⅲ. IMD1-53 also inhibited the expression of TGF-β1, α-SMA and Nox4 both in mRNA and protein. In vivo, we found that IMD1-53\u0000inhibited the phosphorylation of Smad3. In vitro, we found that the down-regulation of the expression of Nox4 was partly dependent on the TGF-β1/ALK5 pathway.\u0000\u0000\u0000\u0000IMD1-53 reduced the inducibility and duration of AF and atrial fibrosis in the rats\u0000after the MI operation. The possible mechanisms are associated with the inhibition of TGFβ1/Smad3-related fibrosis and TGF-β1/Nox4 activity. Therefore, IMD1-53 may be a promising\u0000agent as upstream therapy for the prevention of AF.\u0000\u0000\u0000\u0000Compared with the MI group, IMD1-53 treatment decreased left atrial diameter and improved cardiac function, it also improved the left ventrical end diastolic pressure (LVEDP). IMD1-53 treatment attenuated AERP prolongation and reduced atrial fibrillation inducibility in the IMD group. In vivo, the results showed that IMD1-53 reduced the left atrial fibrosis content on the heart of MI rats and inhibited the expression of collagen type Ⅰ and Ⅲ both in mRNA and protein. IMD1-53 also inhibited the expression of TGF-β1, α-SMA and Nox4 both in mRNA and protein. In vivo, the study also showed that IMD1-53 inhibited the phosphorylation of Smad3. In vitro, we found that the down-regulated the expression of Nox4 was partly dependent on TGF-β1/ALK5 pathway.\u0000\u0000\u0000\u0000none.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42431913","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 : 2022-11-30DOI: 10.2174/1574362418666221130164014
S. Kashaw, Chaitali Mallick, Mitali Mishra, Vivek Asati, Varsha Kashaw, R. Das
The prolonged antimalarial therapy with the marketed drug has developed multi-resistant strains of Plasmodium parasites that emerge as a consequential global problem. Therefore, designing new antimalarial agents is an exclusive solution to overcome the alarming situation. The integrated computational perspectives, such as pharmacophore mapping, 3D-QSAR and docking studies have been applied to improve the activity of the imidazo-quinoline scaffold. The best hypothesis AARRR_1 (Survival score 5.4609) obtained through pharmacophore mapping revealed that imidazo-quinoline scaffold is found to be vital for antimalarial activity. The significant CoMFA (q2 = 0.728, r2 = 0.909) and CoMSIA (q2 = 0.633, r2 = 0.729) models, developed by using molecular field analysis with the PLS method, showed good predictive ability with r2pred values of 0.9127 and 0.7726, respectively. Docking studies were performed using Schrodinger and GOLD software with the Plasmodium falciparum purine nucleoside phosphorylase enzyme (PDB ID-5ZNC) and results indicated that the imidazo-quinoline moiety facilitates the interaction with Tyr 160. In addition, some compounds are screened from the ZINC database based on structural requirements to verify the relevance of the research. Finally, designed molecules and ZINC database compounds were screened through the ADMET tool to evaluate pharmacokinetic and drug-likeness parameters. Thus, these exhaustive studies suggested that established models have good predictability and would help in the optimization of newly designed molecules that may lead to potent antimalarial activity for getting rid of resistance issues. Significant results have been obtained
{"title":"In Silico-Based Structural Prediction, Molecular Docking and ADMET Analysis of Novel Imidazo-Quinoline Derivatives as pf Purine Nucleoside Phosphorylase Inhibitors","authors":"S. Kashaw, Chaitali Mallick, Mitali Mishra, Vivek Asati, Varsha Kashaw, R. Das","doi":"10.2174/1574362418666221130164014","DOIUrl":"https://doi.org/10.2174/1574362418666221130164014","url":null,"abstract":"\u0000\u0000The prolonged antimalarial therapy with the marketed drug has developed multi-resistant strains of Plasmodium parasites that emerge as a consequential global problem. Therefore, designing new antimalarial agents is an exclusive solution to overcome the alarming situation.\u0000\u0000\u0000\u0000The integrated computational perspectives, such as pharmacophore mapping, 3D-QSAR and docking studies have been applied to improve the activity of the imidazo-quinoline scaffold. The best hypothesis AARRR_1 (Survival score 5.4609) obtained through pharmacophore mapping revealed that imidazo-quinoline scaffold is found to be vital for antimalarial activity. The significant CoMFA (q2 = 0.728, r2 = 0.909) and CoMSIA (q2 = 0.633, r2 = 0.729) models, developed by using molecular field analysis with the PLS method, showed good predictive ability with r2pred values of 0.9127 and 0.7726, respectively. Docking studies were performed using Schrodinger and GOLD software with the Plasmodium falciparum purine nucleoside phosphorylase enzyme (PDB ID-5ZNC) and results indicated that the imidazo-quinoline moiety facilitates the interaction with Tyr 160.\u0000\u0000\u0000\u0000In addition, some compounds are screened from the ZINC database based on structural requirements to verify the relevance of the research. Finally, designed molecules and ZINC database compounds were screened through the ADMET tool to evaluate pharmacokinetic and drug-likeness parameters.\u0000\u0000\u0000\u0000Thus, these exhaustive studies suggested that established models have good predictability and would help in the optimization of newly designed molecules that may lead to potent antimalarial activity for getting rid of resistance issues.\u0000\u0000\u0000\u0000Significant results have been obtained\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41470224","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 : 2022-08-27DOI: 10.2174/1574362417666220827114844
D. Sekar, Auxzilia Preethi K, S. Selvakumar
Hypertension is a global public health issue that is becoming more prevalent. It is a non-communicable disease and is a great public health problem affecting almost half of the world’s adult population. Being multifactorial, hypertension is a key risk factor for stroke, coronary artery disease, heart failure, and chronic renal failure. However, the cellular and molecular mechanisms that enable it remains mostly unknown. According to numerous studies, microRNAs (miRNAs) have been implicated in a range of cellular processes in the development of illnesses. The current study aims in identifying miRNAs in hypertension from genome sequences found in public genomic databases. In this study, we have used bioinformatic approaches to identify miR-26a-1 for hypertension using NCBI database, miRbase and target scan. Finally, RNA fold was used to create the secondary structure of miR-260-1. Careful evaluation of secondary structure result showed that hsa-miR-26a-1 has a minimum free energy of - 37.30 kcal. The correlation between miR-26a-1 and hypertension genome sequence was identified. These computational approaches have concluded that miR-26a-1 can be used as a diagnosis, prognosis and effective therapeutic target for treating hypertension. Thus, further research could enlighten the role of miR-26a-1 in hypertension.
{"title":"In Silico Identification of Human miR-26a-1 from Hypertension Genome Sequence","authors":"D. Sekar, Auxzilia Preethi K, S. Selvakumar","doi":"10.2174/1574362417666220827114844","DOIUrl":"https://doi.org/10.2174/1574362417666220827114844","url":null,"abstract":"\u0000\u0000Hypertension is a global public health issue that is becoming more prevalent. It is a non-communicable disease and is a great public health problem affecting almost half of the world’s adult population. Being multifactorial, hypertension is a key risk factor for stroke, coronary artery disease, heart failure, and chronic renal failure. However, the cellular and molecular mechanisms that enable it remains mostly unknown. According to numerous studies, microRNAs (miRNAs) have been implicated in a range of cellular processes in the development of illnesses. The current study aims in identifying miRNAs in hypertension from genome sequences found in public genomic databases.\u0000\u0000\u0000\u0000In this study, we have used bioinformatic approaches to identify miR-26a-1 for hypertension using NCBI database, miRbase and target scan. Finally, RNA fold was used to create the secondary structure of miR-260-1.\u0000\u0000\u0000\u0000Careful evaluation of secondary structure result showed that hsa-miR-26a-1 has a minimum free energy of - 37.30 kcal. The correlation between miR-26a-1 and hypertension genome sequence was identified.\u0000\u0000\u0000\u0000These computational approaches have concluded that miR-26a-1 can be used as a diagnosis, prognosis and effective therapeutic target for treating hypertension. Thus, further research could enlighten the role of miR-26a-1 in hypertension.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42746357","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 : 2022-07-15DOI: 10.2174/1574362417666220715105527
Sushovan Chaudhury, Nilesh Shelke, Zahraa M. Rashid, K. Sau
The study of breast cancer detection begins with the WBCD dataset for most researchers, as it is a very well-known dataset. We use this dataset as a benchmark in this paper to study ML algorithms like SVM, DT, RF, KNN, NB classifiers, Logistic Regression, Extra Trees, Bagging Classifiers with hard and soft voting, Ensemble techniques and Extreme Gradient Boosting classifiers like XG Boost and 2 deep learning models with regularization and without regularization. The primary objective is to revisit how the existing classifiers fare with the WBCD dataset and suggest a method with Grid search and Randomized search by selecting the best hyper-parameters to apply with and without PCA and check if WBCD dataset can be classified in lesser time without compromising accuracy. We explore PCA as a feature extraction technique in this dataset and use techniques like Feature Scaling K Fold stratified cross-validation technique, K best etc. We implement Grid search CV along with PCA in the pipeline to tune the hyper parameters across various classifiers and reduce the training and prediction time without compromising accuracy. Last but not the least, this paper also compares the accuracy, precision and recall of various ML techniques for manually selected features by observing the feature importance score and the correlation matrix. In our experiment with all features, we get an accuracy of 97.9 per cent for Extra trees and Ensemble techniques with RF, KNN and Extra Trees with soft voting strategy and using feature selection with PCA and grid search we get an accuracy of 99.1 per cent with SVM (kernel trick). We also demonstrate that the running time of training and prediction also reduces if hyper parameters of classifiers are tuned appropriately which is taken care of by Grid and Randomized Hyper Parameter Grids. It is shown in this paper that Feature subset selection or feature ranking may not be the best way and not the only way to be applied on WBCD dataset along with PCA. In datasets where features are closely correlated , a method for hyper parameter tuning using either Grid or Randomized Search can be accompanied with PCA to extract the best feature combinations and then fed into the classifiers to get good accuracy scores and can be executed in a much quicker time.
{"title":"Effect of Grid Search and Hyper Parameter Tuned Pipeline with Various Classifiers and PCA for Breast Cancer Detection","authors":"Sushovan Chaudhury, Nilesh Shelke, Zahraa M. Rashid, K. Sau","doi":"10.2174/1574362417666220715105527","DOIUrl":"https://doi.org/10.2174/1574362417666220715105527","url":null,"abstract":"\u0000\u0000The study of breast cancer detection begins with the WBCD dataset for most researchers, as it is a very well-known dataset. We use this dataset as a benchmark in this paper to study ML algorithms like SVM, DT, RF, KNN, NB classifiers, Logistic Regression, Extra Trees, Bagging Classifiers with hard and soft voting, Ensemble techniques and Extreme Gradient Boosting classifiers like XG Boost and 2 deep learning models with regularization and without regularization.\u0000\u0000\u0000\u0000The primary objective is to revisit how the existing classifiers fare with the WBCD dataset and suggest a method with Grid search and Randomized search by selecting the best hyper-parameters to apply with and without PCA and check if WBCD dataset can be classified in lesser time without compromising accuracy.\u0000\u0000\u0000\u0000We explore PCA as a feature extraction technique in this dataset and use techniques like Feature Scaling K Fold stratified cross-validation technique, K best etc. We implement Grid search CV along with PCA in the pipeline to tune the hyper parameters across various classifiers and reduce the training and prediction time without compromising accuracy. Last but not the least, this paper also compares the accuracy, precision and recall of various ML techniques for manually selected features by observing the feature importance score and the correlation matrix.\u0000\u0000\u0000\u0000In our experiment with all features, we get an accuracy of 97.9 per cent for Extra trees and Ensemble techniques with RF, KNN and Extra Trees with soft voting strategy and using feature selection with PCA and grid search we get an accuracy of 99.1 per cent with SVM (kernel trick). We also demonstrate that the running time of training and prediction also reduces if hyper parameters of classifiers are tuned appropriately which is taken care of by Grid and Randomized Hyper Parameter Grids.\u0000\u0000\u0000\u0000It is shown in this paper that Feature subset selection or feature ranking may not be the best way and not the only way to be applied on WBCD dataset along with PCA. In datasets where features are closely correlated , a method for hyper parameter tuning using either Grid or Randomized Search can be accompanied with PCA to extract the best feature combinations and then fed into the classifiers to get good accuracy scores and can be executed in a much quicker time.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46280414","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 : 2022-06-10DOI: 10.2174/1574362417666220610153540
Tamanna Ahmed, Rishita Dey, Jhumpa Mukherjee, A. Samadder, S. Nandi
Osteoarthritis (OA) is one of the common chronic inflammatory neurodegenerative joint disorders that cause disability among the geriatric population. It involves loss of the articular cartilage that covers the end of a long bone thereby failing to prevent the friction between the joint. The literature on the prevalence of OA and different risk factors like physical inactivity, obesity, and joint injury was searched through Google scholar, PubMed, research gate, Wikipedia, etc for the review. OA has affected around 303 million people globally. It affects the knee, hip, hands, and spine joints owing to common symptoms like pain, swelling, and disability. Further, OA-associated disability causes depression leading to economic and social burden with physical isolation; thus making it more severe for older people in their day-to-day lifestyle. Presently, no permanent cure has been developed for OA. Although, there are many risk factors of OA among them the most prominent one is considered to be “aging”. Most people crossing the age of 65–70 years have been associated with changes in the joints (one or more) about the development of OA. Several theories related to cellular aging and cell senescence with OA development. However, aging alone does not cause this condition; it is accelerated by the abnormal signal transduction followed by the progression of OA. The blueprint of possible management of OA by the different approaches has been the prime concern of this review work. An outline of the risk factors of abnormal signal transduction and different treatment approaches including regenerative therapy, synthetic drugs, and naturopathy manipulating them concerning OA are discussed in this review which might be an answer to the age-old issue of geriatrics.
{"title":"Age Related Osteoarthritis: Regenerative therapy, Synthetic Drugs, and Naturopathy to Combat Abnormal Signal Transduction","authors":"Tamanna Ahmed, Rishita Dey, Jhumpa Mukherjee, A. Samadder, S. Nandi","doi":"10.2174/1574362417666220610153540","DOIUrl":"https://doi.org/10.2174/1574362417666220610153540","url":null,"abstract":"\u0000\u0000Osteoarthritis (OA) is one of the common chronic inflammatory neurodegenerative joint disorders that cause disability among the geriatric population. It involves loss of the articular cartilage that covers the end of a long bone thereby failing to prevent the friction between the joint.\u0000\u0000\u0000\u0000The literature on the prevalence of OA and different risk factors like physical inactivity, obesity, and joint injury was searched through Google scholar, PubMed, research gate, Wikipedia, etc for the review.\u0000\u0000\u0000\u0000OA has affected around 303 million people globally. It affects the knee, hip, hands, and spine joints owing to common symptoms like pain, swelling, and disability. Further, OA-associated disability causes depression leading to economic and social burden with physical isolation; thus making it more severe for older people in their day-to-day lifestyle. Presently, no permanent cure has been developed for OA. Although, there are many risk factors of OA among them the most prominent one is considered to be “aging”. Most people crossing the age of 65–70 years have been associated with changes in the joints (one or more) about the development of OA. Several theories related to cellular aging and cell senescence with OA development. However, aging alone does not cause this condition; it is accelerated by the abnormal signal transduction followed by the progression of OA. The blueprint of possible management of OA by the different approaches has been the prime concern of this review work.\u0000\u0000\u0000\u0000An outline of the risk factors of abnormal signal transduction and different treatment approaches including regenerative therapy, synthetic drugs, and naturopathy manipulating them concerning OA are discussed in this review which might be an answer to the age-old issue of geriatrics.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44800459","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 : 2022-06-01DOI: 10.2174/1574362417666220601162839
Golla Mahalaxmi, T. Tirupal, Syed Shanawaz, Sandip Swarnakar, S. Krishna
Despite enormous advances in medical technology, the prognosis of Brain Tumour (BT) remains an extremely time-consuming and troublesome assignment for physicians. Early and precise brain tumour identification gives an effective results and leads to increased survival rate. Within this paper, an examination of various techniques in order of priority to classify clinical images is presented to analyse various research gaps and highlights their costs and benefits. Human mortality can be reduced by using an automatic classification scheme. The automatic classification of brain tumours is a difficult task due to the large spatial and structural variability of the brain tumor’s surrounding region. The latest developments have been investigated in image characterization strategies for diagnosing human body disease and addressing the classification of nuclear medical imaging identification techniques like Convolution Neural Network (CNN), Support Vector Machine (SVM), Histogram technique, K-Means Clustering (K-MC) etc., just as the respective parameters like the image modalities employed, the dataset and the trade-offs have been compared for each technique. Among these techniques, CNN model accomplished the highest accuracy of 99% for two sets of data: Brain Tumour Segmentation (BTS) and BD-brain tumour and a high average susceptibility of 0.99 for all datasets. Finally, the review demonstrated that improving image order strategies with regarding accuracy, sensitivity value, and feasibility for Computer-Aided Diagnosis (CAD) is a significant challenge as well as an open research area.
{"title":"A Comparison and Survey on Brain Tumour Detection Techniques Using MRI Images","authors":"Golla Mahalaxmi, T. Tirupal, Syed Shanawaz, Sandip Swarnakar, S. Krishna","doi":"10.2174/1574362417666220601162839","DOIUrl":"https://doi.org/10.2174/1574362417666220601162839","url":null,"abstract":"\u0000\u0000Despite enormous advances in medical technology, the prognosis of Brain Tumour (BT) remains an extremely time-consuming and troublesome assignment for physicians. Early and precise brain tumour identification gives an effective results and leads to increased survival rate. Within this paper, an examination of various techniques in order of priority to classify clinical images is presented to analyse various research gaps and highlights their costs and benefits. Human mortality can be reduced by using an automatic classification scheme. The automatic classification of brain tumours is a difficult task due to the large spatial and structural variability of the brain tumor’s surrounding region. The latest developments have been investigated in image characterization strategies for diagnosing human body disease and addressing the classification of nuclear medical imaging identification techniques like Convolution Neural Network (CNN), Support Vector Machine (SVM), Histogram technique, K-Means Clustering (K-MC) etc., just as the respective parameters like the image modalities employed, the dataset and the trade-offs have been compared for each technique. Among these techniques, CNN model accomplished the highest accuracy of 99% for two sets of data: Brain Tumour Segmentation (BTS) and BD-brain tumour and a high average susceptibility of 0.99 for all datasets. Finally, the review demonstrated that improving image order strategies with regarding accuracy, sensitivity value, and feasibility for Computer-Aided Diagnosis (CAD) is a significant challenge as well as an open research area.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47471921","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 : 2022-05-27DOI: 10.2174/1574362417666220527091755
Shruti Jain
In this paper, the authors have predicted Forkhead box O (FOXO) using the Ensemble learning algorithm. When FOXO is in excess in the human body it leads to LNCap prostate cancer cells leads and if deficit leads to neurodegenerative diseases. Neurodegenerative diseases like Alzheimer's and Parkinson's are neurological illnesses that are caused by damaged brain cells. For prediction of FOXO protein, Gradient Boosted Machine (GBM) and Random forest (RF) techniques are used. The main idea of using GBM is its non-linear nature but it is difficult for any single decision tree to fit all training. To overcome this, an RF algorithm is used. RF combines the results at the end of the process by average or majority rules, while the GBM algorithm combines the results along the way. 29.16% improvement has been observed by RF over GBM. Average square error is also evaluated to check the testing and training of data for 100 trees on 100 tree sizes. In this paper, a computational model for the prediction of FOXO protein using Ensemble learning techniques (Random Forest and GBM) has been proposed. If the dataset has many variable features and the prediction accuracy is not as important then RF can be considered. On the other hand, GBMs are better suited for datasets that have very few or fewer input features and where high accuracy predictions are required. However, there are instances when either GBM or RF can perform equally well depending on how they are tuned.
{"title":"Computational Model for Prediction of Foxo Protein Employing Ensemble Learning Algorithm","authors":"Shruti Jain","doi":"10.2174/1574362417666220527091755","DOIUrl":"https://doi.org/10.2174/1574362417666220527091755","url":null,"abstract":"\u0000\u0000In this paper, the authors have predicted Forkhead box O (FOXO) using the Ensemble learning algorithm. When FOXO is in excess in the human body it leads to LNCap prostate cancer cells leads and if deficit leads to neurodegenerative diseases.\u0000\u0000\u0000\u0000Neurodegenerative diseases like Alzheimer's and Parkinson's are neurological illnesses that are caused by damaged brain cells. For prediction of FOXO protein, Gradient Boosted Machine (GBM) and Random forest (RF) techniques are used.\u0000\u0000\u0000\u0000The main idea of using GBM is its non-linear nature but it is difficult for any single decision tree to fit all training. To overcome this, an RF algorithm is used. RF combines the results at the end of the process by average or majority rules, while the GBM algorithm combines the results along the way.\u0000\u0000\u0000\u000029.16% improvement has been observed by RF over GBM. Average square error is also evaluated to check the testing and training of data for 100 trees on 100 tree sizes.\u0000\u0000\u0000\u0000In this paper, a computational model for the prediction of FOXO protein using Ensemble learning techniques (Random Forest and GBM) has been proposed. If the dataset has many variable features and the prediction accuracy is not as important then RF can be considered. On the other hand, GBMs are better suited for datasets that have very few or fewer input features and where high accuracy predictions are required. However, there are instances when either GBM or RF can perform equally well depending on how they are tuned.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47063289","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}
Diabetes is one of the most common diseases which are major public health problem worldwide. It is also the leading high risk causes of death and disability in the world. To avoid further complications due to diabetes, regular monitoring of blood glucose levels is very important. All the current method used to measure blood glucose is the invasive way, which requires finger piercing, and this invasive method is more painful and more likely to cause infection. However, patients need to be directed towards the development of non-invasive techniques to relieve pain. In this project we use non-invasive techniques that use Near Infrared sensor for glucose level determination from fingertip without requiring needles and test strips. Near Infrared (NIR) optical signal is transmitted through one side of the fingertip and then received from its other side through which blood glucose’s molecular count is predicted by analyzing the variation in the received signal’s intensity after its reflection. And then the signal was filtered and amplified before going into the microcontroller to be displayed on an LCD display. The glucose readings were also sent to a phone via Wi-Fi and displayed through an Android application use of IoT. The designed hardware calibrated with regression analysis by a pre calibrated conventional blood sugar machine and the derived equation is being set with respect to voltage vs Blood sugar measurement and set in the microcontroller. Finally the device is being tested with the 5 individual subjects with 10 reading each. The device is being designed to measure the Blood Glucose in noninvasive way and it is successfully doing the same beside that the incorporation of IoT in the device give us the freedom of measuring the Blood glucose from the distance and available through the internet.
{"title":"A Non-Invasive IoT-Based Glucose Level Monitoring System","authors":"Sudip Paul, Shruti Jain, Bikram Majhi, Karobi Pegu, Vinayak Majhi","doi":"10.2174/1574362417666220524085231","DOIUrl":"https://doi.org/10.2174/1574362417666220524085231","url":null,"abstract":"\u0000\u0000Diabetes is one of the most common diseases which are major public health problem worldwide. It is also the leading high risk causes of death and disability in the world. To avoid further complications due to diabetes, regular monitoring of blood glucose levels is very important. All the current method used to measure blood glucose is the invasive way, which requires finger piercing, and this invasive method is more painful and more likely to cause infection. However, patients need to be directed towards the development of non-invasive techniques to relieve pain.\u0000\u0000\u0000\u0000In this project we use non-invasive techniques that use Near Infrared sensor for glucose level determination from fingertip without requiring needles and test strips.\u0000\u0000\u0000\u0000Near Infrared (NIR) optical signal is transmitted through one side of the fingertip and then received from its other side through which blood glucose’s molecular count is predicted by analyzing the variation in the received signal’s intensity after its reflection. And then the signal was filtered and amplified before going into the microcontroller to be displayed on an LCD display. The glucose readings were also sent to a phone via Wi-Fi and displayed through an Android application use of IoT.\u0000\u0000\u0000\u0000The designed hardware calibrated with regression analysis by a pre calibrated conventional blood sugar machine and the derived equation is being set with respect to voltage vs Blood sugar measurement and set in the microcontroller. Finally the device is being tested with the 5 individual subjects with 10 reading each.\u0000\u0000\u0000\u0000The device is being designed to measure the Blood Glucose in noninvasive way and it is successfully doing the same beside that the incorporation of IoT in the device give us the freedom of measuring the Blood glucose from the distance and available through the internet.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42851141","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 : 2022-05-18DOI: 10.2174/1574362417666220518120229
P. Mathur, Tanu Sharma, K. Veer
Electrocardiogram (ECG) is widely used in the healthcare domain because of its usage as a diagnostics tool for several cardiovascular diseases. It becomes essential to study and analyse the ECG data with the help of classification techniques. In this review paper, a brief overview of ECG signal information is presented. Various approaches for diagnosing cardiovascular diseases have been discussed, along with the need for accurate ECG signal analysis. These approaches are mainly based on the principles of machine learning and deep learning. The advantages and limitations of these techniques in the detection of cardiovascular diseases are presented within the scope of future work. This study can be helpful for researchers in bridging the gap between current approaches and future techniques for the detection of arrhythmia conditions.
{"title":"ECG Diagnosis for Cardiovascular Diseases Using Soft Computing Algorithms","authors":"P. Mathur, Tanu Sharma, K. Veer","doi":"10.2174/1574362417666220518120229","DOIUrl":"https://doi.org/10.2174/1574362417666220518120229","url":null,"abstract":"\u0000\u0000Electrocardiogram (ECG) is widely used in the healthcare domain because of its usage as a diagnostics tool for several cardiovascular diseases. It becomes essential to study and analyse the ECG data with the help of classification techniques. In this review paper, a brief overview of ECG signal information is presented. Various approaches for diagnosing cardiovascular diseases have been discussed, along with the need for accurate ECG signal analysis. These approaches are mainly based on the principles of machine learning and deep learning. The advantages and limitations of these techniques in the detection of cardiovascular diseases are presented within the scope of future work. This study can be helpful for researchers in bridging the gap between current approaches and future techniques for the detection of arrhythmia conditions.\u0000","PeriodicalId":10868,"journal":{"name":"Current Signal Transduction Therapy","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43049401","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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