Pub Date : 2020-05-11DOI: 10.4236/jbise.2020.135007
R. Sakai, K. Uchiyama, N. Takahira, M. Kakeshita, Y. Otsu, Kazuhiro Yoshida, M. Ujihira
In total hip arthroplasty, judgment of the appropriateness of stem hammering is dependent on the experience and feelings of the surgeon and no objective evaluation method has been established. In this study, a frequency analysis of the hammering sounds in total hip arthroplasty was performed to investigate objective judgment criteria capable of preventing problems during surgery. Stem hammering was applied following the surgeon’s feelings as usual in an operating room. A directional microphone was placed at a distance about 2 m from the surgical field and the peak frequency reaching the maximum amplitude was determined by Fourier analysis. It was clarified that the same peak frequency repeats when appropriate fixation is acquired during surgery, suggesting that intraoperative fracture and postoperative loosening can be prevented by stopping hammering at the time the peak frequency converged. Investigation of changes in the hammering sound frequency may serve as objective judgment criteria capable of preventing problems during surgery.
{"title":"Usefulness of Hammering Sound Frequency Analysis as an Evaluation Method for the Prevention of Trouble during Hip Replacement","authors":"R. Sakai, K. Uchiyama, N. Takahira, M. Kakeshita, Y. Otsu, Kazuhiro Yoshida, M. Ujihira","doi":"10.4236/jbise.2020.135007","DOIUrl":"https://doi.org/10.4236/jbise.2020.135007","url":null,"abstract":"In total hip arthroplasty, judgment of the appropriateness of stem hammering is dependent on the experience and feelings of the surgeon and no objective evaluation method has been established. In this study, a frequency analysis of the hammering sounds in total hip arthroplasty was performed to investigate objective judgment criteria capable of preventing problems during surgery. Stem hammering was applied following the surgeon’s feelings as usual in an operating room. A directional microphone was placed at a distance about 2 m from the surgical field and the peak frequency reaching the maximum amplitude was determined by Fourier analysis. It was clarified that the same peak frequency repeats when appropriate fixation is acquired during surgery, suggesting that intraoperative fracture and postoperative loosening can be prevented by stopping hammering at the time the peak frequency converged. Investigation of changes in the hammering sound frequency may serve as objective judgment criteria capable of preventing problems during surgery.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42027538","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 : 2020-04-30DOI: 10.4236/jbise.2020.134004
Rafiqul Islam, S. Imran, M. Ashikuzzaman, Md. Munim Ali Khan
Magnetic Resonance Imaging (MRI) is an important diagnostic technique for early detection of brain Tumor and the classification of brain Tumor from MRI image is a challenging research work because of its different shapes, location and image intensities. For successful classification, the segmentation method is required to separate Tumor. Then important features are extracted from the segmented Tumor that is used to classify the Tumor. In this work, an efficient multilevel segmentation method is developed combining optimal thresholding and watershed segmentation technique followed by a morphological operation to separate the Tumor. Convolutional Neural Network (CNN) is then applied for feature extraction and finally, the Kernel Support Vector Machine (KSVM) is utilized for resultant classification that is justified by our experimental evaluation. Experimental results show that the proposed method effectively detect and classify the Tumor as cancerous or non-cancerous with promising accuracy.
{"title":"Detection and Classification of Brain Tumor Based on Multilevel Segmentation with Convolutional Neural Network","authors":"Rafiqul Islam, S. Imran, M. Ashikuzzaman, Md. Munim Ali Khan","doi":"10.4236/jbise.2020.134004","DOIUrl":"https://doi.org/10.4236/jbise.2020.134004","url":null,"abstract":"Magnetic Resonance Imaging (MRI) is an important diagnostic technique for early detection of brain Tumor and the classification of brain Tumor from MRI image is a challenging research work because of its different shapes, location and image intensities. For successful classification, the segmentation method is required to separate Tumor. Then important features are extracted from the segmented Tumor that is used to classify the Tumor. In this work, an efficient multilevel segmentation method is developed combining optimal thresholding and watershed segmentation technique followed by a morphological operation to separate the Tumor. Convolutional Neural Network (CNN) is then applied for feature extraction and finally, the Kernel Support Vector Machine (KSVM) is utilized for resultant classification that is justified by our experimental evaluation. Experimental results show that the proposed method effectively detect and classify the Tumor as cancerous or non-cancerous with promising accuracy.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"13 1","pages":"45-53"},"PeriodicalIF":0.0,"publicationDate":"2020-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43671919","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 : 2020-03-31DOI: 10.4236/jbise.2020.133003
R. Pidaparti, Divya Jakkam
The microtubule self-assembly process involves the basic building blocks, alpha and beta tubulins which spontaneously bind to one another through polymerization and under controlled intracellular conditions form protofilaments which in turn assemble into microtubules. The mechanical properties of the self-assembled protofilaments play an important role in formation of the microtubules. In this study, we investigate the mechanical properties of the experimentally self-assembled protofilaments (straight and curved) for under different loadings through 3D finite element analysis. Results of force-deformation and stiffness values obtained from the finite element analysis are presented. The results indicate that the stiffness and maximum stress properties change with varying protofilamant curvature. These force-deformation behaviors and stress distributions should help further understand the contribution of protofilaments mechanical properties in forming self-assembled microtubules.
{"title":"Mechanical Properties of Self-Assembled Microtubule Curved Protofilaments","authors":"R. Pidaparti, Divya Jakkam","doi":"10.4236/jbise.2020.133003","DOIUrl":"https://doi.org/10.4236/jbise.2020.133003","url":null,"abstract":"The microtubule self-assembly process involves the basic building blocks, alpha and beta tubulins which spontaneously bind to one another through polymerization and under controlled intracellular conditions form protofilaments which in turn assemble into microtubules. The mechanical properties of the self-assembled protofilaments play an important role in formation of the microtubules. In this study, we investigate the mechanical properties of the experimentally self-assembled protofilaments (straight and curved) for under different loadings through 3D finite element analysis. Results of force-deformation and stiffness values obtained from the finite element analysis are presented. The results indicate that the stiffness and maximum stress properties change with varying protofilamant curvature. These force-deformation behaviors and stress distributions should help further understand the contribution of protofilaments mechanical properties in forming self-assembled microtubules.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"17 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41260510","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 : 2020-02-28DOI: 10.4236/jbise.2020.132002
Shaomin Yan, Guang Wu
A large amount of transcriptomic data provides opportunities 1) to verify the gene regulatory mechanism, which is usually obtained from a single experiment, at population level; 2) to uncover the gene regulatory mechanism at population level; and 3) to build a quantitatively gene regulatory mechanism. One of the best studied regulatory mechanisms in bacteria is the quorum sensing (QS), which plays an important role in regulation of bacteria population behaviors such as antibiotic production, biofilm formation, bioluminescence, competence, conjugation, motility and sporulation. Pseudomonas aeruginosa is a Gram-negative bacterium causing diseases in plants, animals, humans, and its biofilm and drug-resistance become great concerns in clinics. P. aeruginosa has three QS systems including a specific one for Pseudomonas. In this study, the transcriptomic data of P. aeruginosa were combined from 104 publications and QS gene expressions were analyzed under different experimental conditions. The results demonstrate the quantitatively regulatory mechanisms of QS genes at population level including 1) to rank and group QS-related genes according to their activity; 2) to quantitatively define the role of a single global regulator; 3) to find out the probability that a global regulator impacts QS genes and the probability that a QS gene responds to global regulators; and 4) to search for overlapped genes under four types of experimental conditions. These results provide integrative information on understanding the regulation of QS genes at population level.
{"title":"Building Quantitative Gene Regulatory Mechanism in Quorum Sensing in Pseudomonas aeruginosa Using Transcriptomic Data","authors":"Shaomin Yan, Guang Wu","doi":"10.4236/jbise.2020.132002","DOIUrl":"https://doi.org/10.4236/jbise.2020.132002","url":null,"abstract":"A large amount of transcriptomic data provides opportunities 1) to verify the gene regulatory mechanism, which is usually obtained from a single experiment, at population level; 2) to uncover the gene regulatory mechanism at population level; and 3) to build a quantitatively gene regulatory mechanism. One of the best studied regulatory mechanisms in bacteria is the quorum sensing (QS), which plays an important role in regulation of bacteria population behaviors such as antibiotic production, biofilm formation, bioluminescence, competence, conjugation, motility and sporulation. Pseudomonas aeruginosa is a Gram-negative bacterium causing diseases in plants, animals, humans, and its biofilm and drug-resistance become great concerns in clinics. P. aeruginosa has three QS systems including a specific one for Pseudomonas. In this study, the transcriptomic data of P. aeruginosa were combined from 104 publications and QS gene expressions were analyzed under different experimental conditions. The results demonstrate the quantitatively regulatory mechanisms of QS genes at population level including 1) to rank and group QS-related genes according to their activity; 2) to quantitatively define the role of a single global regulator; 3) to find out the probability that a global regulator impacts QS genes and the probability that a QS gene responds to global regulators; and 4) to search for overlapped genes under four types of experimental conditions. These results provide integrative information on understanding the regulation of QS genes at population level.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"13 1","pages":"13-35"},"PeriodicalIF":0.0,"publicationDate":"2020-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49410507","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 : 2020-01-30DOI: 10.4236/jbise.2020.131001
Lucy Ly, R. Parsons, B. Austen
β-Secretase (BACE1 or β-site APP cleaving enzyme) is an acid protease that releases the neurotoxic 40 - 42 residue peptides (β-amyloid or A-β) from its glycoprotein precursor, (APP or amyloid precursor protein) which when released in brain is thought to give rise to cognitive decline in patients with Alzheimer’s Disease. Most structural studies on β-secretase have previously been performed with recombinant forms of the protease, in which the transmembrane coding region has been deleted. However, interactions with proteins of the same species are best studied using the full-length β-secretase as interactions are likely to be influenced by the hydrophobic nature and localization of its transmembrane regions. Here we develop a multi-step purification procedure that isolates a complex containing BACE1 from recombinant human cells using mild detergents in a procedure that retains other proteins within the complex and remains active in its β-site APP cleaving activity. Some of these proteins, eg reticulon 4, are identified by proteomics, and are known by previous studies performed by others to regulate the activity of BACE1 against APP. These interactions may aid the development of small proteins and peptides that could inhibit the release of aggregated forms of β-amyloid, and thus be useful therapeutically.
{"title":"Purification of Full-Length β-Secretase Involved in Alzheimer’s Disease, and Proteomic Identification of Binding Partners","authors":"Lucy Ly, R. Parsons, B. Austen","doi":"10.4236/jbise.2020.131001","DOIUrl":"https://doi.org/10.4236/jbise.2020.131001","url":null,"abstract":"β-Secretase (BACE1 or β-site APP cleaving enzyme) is an acid protease that releases the neurotoxic 40 - 42 residue peptides (β-amyloid or A-β) from its glycoprotein precursor, (APP or amyloid precursor protein) which when released in brain is thought to give rise to cognitive decline in patients with Alzheimer’s Disease. Most structural studies on β-secretase have previously been performed with recombinant forms of the protease, in which the transmembrane coding region has been deleted. However, interactions with proteins of the same species are best studied using the full-length β-secretase as interactions are likely to be influenced by the hydrophobic nature and localization of its transmembrane regions. Here we develop a multi-step purification procedure that isolates a complex containing BACE1 from recombinant human cells using mild detergents in a procedure that retains other proteins within the complex and remains active in its β-site APP cleaving activity. Some of these proteins, eg reticulon 4, are identified by proteomics, and are known by previous studies performed by others to regulate the activity of BACE1 against APP. These interactions may aid the development of small proteins and peptides that could inhibit the release of aggregated forms of β-amyloid, and thus be useful therapeutically.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45966074","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 : 2020-01-01DOI: 10.4236/jbise.2020.137013
Anlong Li, Xiaolan Wang, Yu Duan, Liuya Wei
The miscibility, stability and compressibility of L-α dioleoylphosphatidylcholine/rutin laurate mixed monolayer at the air/water were investigated by Langmuir film balance to reveal the characteristic of the molecular interaction. The two components of DOPC/RL mixed monolayer were miscible throughout the mixture composition range and at three experimental temperatures of 10°C, 25°C and 37°C. At all experimental conditions, RL increased the compressibility and elasticity of the DOPC monolayer. Both the temperature and the composition of the membrane affected the form of intermolecular forces in the mixed monolayer.
{"title":"The Dependence of the Miscibility, Stability and Compressibility of L-α Dioleoylphosphatidylcholine/Rutin Laurate Monolayer at the Air/Water on Temperature","authors":"Anlong Li, Xiaolan Wang, Yu Duan, Liuya Wei","doi":"10.4236/jbise.2020.137013","DOIUrl":"https://doi.org/10.4236/jbise.2020.137013","url":null,"abstract":"The miscibility, stability and compressibility of L-α dioleoylphosphatidylcholine/rutin laurate mixed monolayer at the air/water were investigated by Langmuir film balance to reveal the characteristic of the molecular interaction. The two components of DOPC/RL mixed monolayer were miscible throughout the mixture composition range and at three experimental temperatures of 10°C, 25°C and 37°C. At all experimental conditions, RL increased the compressibility and elasticity of the DOPC monolayer. Both the temperature and the composition of the membrane affected the form of intermolecular forces in the mixed monolayer.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70882667","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 : 2020-01-01DOI: 10.4236/jbise.2020.137014
E. Matsuyama
In this article, we propose a convolutional neural network (CNN)-based model, a ResNet-50 based model, for discriminating coronavirus disease 2019 (COVID-19) from Non-COVID-19 using chest CT. We adopted the use of wavelet coefficients of the entire image without cropping any parts of the image as input to the CNN model. One of the main contributions of this study is to implement an algorithm called gradient-weighted class activation mapping to produce a heat map for visually verifying where the CNN model is looking at the image, thereby, ensuring the model is performing correctly. In order to verify the effectiveness and usefulness of the proposed method, we compare the obtained results with that obtained by using pixel values of original images as input to the CNN model. The measures used for performance evaluation include accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and Matthews correlation coefficient (MCC). The overall classification accuracy, F1 score, and MCC for the proposed method (using wavelet coefficients as input) were 92.2%, 0.915%, and 0.839%, and those for the compared method (using pixel values of the original image as input) were 88.3%, 0.876%, and 0.766%, respectively. The experiment results demonstrate the superiority of the proposed method. Moreover, as a comprehensible classification model, the interpretability of classification results was introduced. The region of interest extracted by the proposed model was visualized using heat maps and the probability score was also shown. We believe that our proposed method could provide a promising computerized toolkit to help radiologists and serve as a second eye for them to classify COVID-19 in CT scan screening examination.
{"title":"A Deep Learning Interpretable Model for Novel Coronavirus Disease (COVID-19) Screening with Chest CT Images","authors":"E. Matsuyama","doi":"10.4236/jbise.2020.137014","DOIUrl":"https://doi.org/10.4236/jbise.2020.137014","url":null,"abstract":"In this article, we propose a convolutional neural network (CNN)-based model, a ResNet-50 based model, for discriminating coronavirus disease 2019 (COVID-19) from Non-COVID-19 using chest CT. We adopted the use of wavelet coefficients of the entire image without cropping any parts of the image as input to the CNN model. One of the main contributions of this study is to implement an algorithm called gradient-weighted class activation mapping to produce a heat map for visually verifying where the CNN model is looking at the image, thereby, ensuring the model is performing correctly. In order to verify the effectiveness and usefulness of the proposed method, we compare the obtained results with that obtained by using pixel values of original images as input to the CNN model. The measures used for performance evaluation include accuracy, sensitivity, specificity, positive predictive value, negative predictive value, F1 score, and Matthews correlation coefficient (MCC). The overall classification accuracy, F1 score, and MCC for the proposed method (using wavelet coefficients as input) were 92.2%, 0.915%, and 0.839%, and those for the compared method (using pixel values of the original image as input) were 88.3%, 0.876%, and 0.766%, respectively. The experiment results demonstrate the superiority of the proposed method. Moreover, as a comprehensible classification model, the interpretability of classification results was introduced. The region of interest extracted by the proposed model was visualized using heat maps and the probability score was also shown. We believe that our proposed method could provide a promising computerized toolkit to help radiologists and serve as a second eye for them to classify COVID-19 in CT scan screening examination.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70882813","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 : 2020-01-01DOI: 10.4236/jbise.2020.137016
B. Abapihi, M. Faisal, Ngoc Nguyen, Mera Kartika Delimayanti, Bedy Purnama, F. R. Lumbanraja, Dau Phan, Mamoru Kubo, K. Satou
Emergence of drug resistant bacteria is one of the serious problems in today’s public health. However, the relationship between genomic mutation of bacteria and the phenotypic difference of them is still unclear. In this paper, based on the mutation information in whole genome sequences of 96 MRSA strains, two kinds of phenotypes (pathogenicity and drug resistance) were learnt and predicted by machine learning algorithms. As a result of effective feature selection by cross entropy based sparse logistic regression, these phenotypes could be predicted in sufficiently high accuracy (100% and 97.87%, respectively) with less than 10 features. It means that we could develop a novel rapid test method in the future for checking MRSA phenotypes.
{"title":"Cross Entropy Based Sparse Logistic Regression to Identify Phenotype-Related Mutations in Methicillin-Resistant Staphylococcus aureus","authors":"B. Abapihi, M. Faisal, Ngoc Nguyen, Mera Kartika Delimayanti, Bedy Purnama, F. R. Lumbanraja, Dau Phan, Mamoru Kubo, K. Satou","doi":"10.4236/jbise.2020.137016","DOIUrl":"https://doi.org/10.4236/jbise.2020.137016","url":null,"abstract":"Emergence of drug resistant bacteria is one of the serious problems in today’s public health. However, the relationship between genomic mutation of bacteria and the phenotypic difference of them is still unclear. In this paper, based on the mutation information in whole genome sequences of 96 MRSA strains, two kinds of phenotypes (pathogenicity and drug resistance) were learnt and predicted by machine learning algorithms. As a result of effective feature selection by cross entropy based sparse logistic regression, these phenotypes could be predicted in sufficiently high accuracy (100% and 97.87%, respectively) with less than 10 features. It means that we could develop a novel rapid test method in the future for checking MRSA phenotypes.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70882921","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 : 2020-01-01DOI: 10.4236/jbise.2020.139019
Xian P. Jiang, C. Baucom, R. Elliott
It has been reported that transplantation of pheochromocytoma P12 and hepatoma cells’ mitochondria improve the locomotive activity and prevent disease progress in experimental Parkinson’s disease rats. To prepare for mitochondrial transplantation study in human neurodegenerative diseases, we select human fibroblasts as mitochondrial donor because that fibroblasts share many characteristics with mesenchymal stromal cells (MSCs). We isolate human primary fibroblasts and develop a mitochondrial DNA (mtDNA)-depleted mouse motor neuron NSC-34 cells (NSC-34 ρ° cells). Fibroblast and NSC-34 cell’s mitochondria are co-cultured with NSC-34 ρ° cells. Mitochondrial transplantation is observed by fluorescent microscopy. Gene expression is determined by polymerase chain reaction (PCR) and real time PCR (qPCR). Also, mitochondria are injected to mice bearing mammary adenocarcinoma 4T1 cells. We find results as following: 1) There are abundant mitochondria in fibroblasts (337 ± 80 mitochondria per fibroblast). 42.4% of viable mitochondria are obtained by using differential centrifugation. The isolated mitochondria actively transplant into NSC-34 ρ° cells after co-culture. 2) Fibroblasts transfer mitochondria to human mammary adenocarcinoma MCF-7 cells. 3) There is no expression of HLA-I antigen in fibroblast’s mitochondria indicating they can be used for allogeneic mitochondrial transplantation without HLA antigen match. 4) PCR and qPCR show that NSC-34 ρ° cells lose mitochondrially encoded cytochrome c oxidase I (MT-CO1) and mitochondrially encoded NADH dehydrogenase 1 (MT-ND1) and upregulate expression of glycolysis-associated genes hexokinase (HK2), glucose transporter 1 (SLC2A1) and lactate dehydrogenase A (LDHA). 5) Transplantation of NSC-34 mitochondria restores MT-CO1 and MT-ND1 and downregulates gene expression of HK2, SLC2A1 and LDHA. 6) Normal mammary epithelial mitochondria successfully enter to 4T1 cells in mice. Subcutaneous injection of mitochondria is safe for mice. In summary, mitochondrial transplantation replenishes mtDNA and rescues aerobic respiration of diseased cells with mitochondrial dysfunction. Human primary fibroblasts are potential mitochondrial donor for mitochondrial transplantation study in human neurodegenerative diseases.
{"title":"Mitochondria Dynamically Transplant into Cells in Vitro and in Mice and Rescue Aerobic Respiration of Mitochondrial DNA-Depleted Motor Neuron NSC-34","authors":"Xian P. Jiang, C. Baucom, R. Elliott","doi":"10.4236/jbise.2020.139019","DOIUrl":"https://doi.org/10.4236/jbise.2020.139019","url":null,"abstract":"It has been reported that transplantation of pheochromocytoma P12 and hepatoma cells’ mitochondria improve the locomotive activity and prevent disease progress in experimental Parkinson’s disease rats. To prepare for mitochondrial transplantation study in human neurodegenerative diseases, we select human fibroblasts as mitochondrial donor because that fibroblasts share many characteristics with mesenchymal stromal cells (MSCs). We isolate human primary fibroblasts and develop a mitochondrial DNA (mtDNA)-depleted mouse motor neuron NSC-34 cells (NSC-34 ρ° cells). Fibroblast and NSC-34 cell’s mitochondria are co-cultured with NSC-34 ρ° cells. Mitochondrial transplantation is observed by fluorescent microscopy. Gene expression is determined by polymerase chain reaction (PCR) and real time PCR (qPCR). Also, mitochondria are injected to mice bearing mammary adenocarcinoma 4T1 cells. We find results as following: 1) There are abundant mitochondria in fibroblasts (337 ± 80 mitochondria per fibroblast). 42.4% of viable mitochondria are obtained by using differential centrifugation. The isolated mitochondria actively transplant into NSC-34 ρ° cells after co-culture. 2) Fibroblasts transfer mitochondria to human mammary adenocarcinoma MCF-7 cells. 3) There is no expression of HLA-I antigen in fibroblast’s mitochondria indicating they can be used for allogeneic mitochondrial transplantation without HLA antigen match. 4) PCR and qPCR show that NSC-34 ρ° cells lose mitochondrially encoded cytochrome c oxidase I (MT-CO1) and mitochondrially encoded NADH dehydrogenase 1 (MT-ND1) and upregulate expression of glycolysis-associated genes hexokinase (HK2), glucose transporter 1 (SLC2A1) and lactate dehydrogenase A (LDHA). 5) Transplantation of NSC-34 mitochondria restores MT-CO1 and MT-ND1 and downregulates gene expression of HK2, SLC2A1 and LDHA. 6) Normal mammary epithelial mitochondria successfully enter to 4T1 cells in mice. Subcutaneous injection of mitochondria is safe for mice. In summary, mitochondrial transplantation replenishes mtDNA and rescues aerobic respiration of diseased cells with mitochondrial dysfunction. Human primary fibroblasts are potential mitochondrial donor for mitochondrial transplantation study in human neurodegenerative diseases.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70882624","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 : 2020-01-01DOI: 10.4236/jbise.2020.137015
Sakura Nishijima, T. Yada, T. Yamazaki, Y. Kuroiwa, M. Nakane, K. Fujino, T. Hirai, Y. Baba, S. M. Yamada, Sho Tsukiyama
Objective: To establish a practical method for discriminating dementia groups and healthy elderlies, by using scalp-recorded electroencephalograms (EEGs). Methods: 16-ch EEGs were recorded during resting state for 39 dementia groups and 11 healthy elderlies. The connectivity between any two electrodes was estimated by synchronization likelihood (SL). The brain networks were constructed by normalized SL values. The present leave-one-out cross validation (LOOCV) required the Euclidean distance between any two subjects having 120-dimensional vectors concerned with the SL values for six frequency bands. In order to investigate factors which would affect the LOOCV results, principal component analysis (PCA) was applied to all the subjects. Results: The accuracy for the upper alpha yielded more than 80% and 70% in the dementia groups and the healthy elderlies, respectively. The LOOCV result could be explained in terms of brain networks such as executive control network (ECN) and default mode network (DMN) characterized by factor loadings of principal components. Conclusions: Dementia groups and healthy elderlies could be characterized by principal components of SL values between all the electrode pairs, even less connections, which revealed disruption and preservation of DMN and ECN. Significance: This study will provide a simple and practical method for discriminating dementia groups from healthy elderlies by scalp-recorded EEGs.
{"title":"Discrimination between Dementia Groups and Healthy Elderlies Using Scalp-Recorded-EEG-Based Brain Functional Connectivity Networks","authors":"Sakura Nishijima, T. Yada, T. Yamazaki, Y. Kuroiwa, M. Nakane, K. Fujino, T. Hirai, Y. Baba, S. M. Yamada, Sho Tsukiyama","doi":"10.4236/jbise.2020.137015","DOIUrl":"https://doi.org/10.4236/jbise.2020.137015","url":null,"abstract":"Objective: To establish a practical method for discriminating dementia groups and healthy elderlies, by using scalp-recorded electroencephalograms (EEGs). Methods: 16-ch EEGs were recorded during resting state for 39 dementia groups and 11 healthy elderlies. The connectivity between any two electrodes was estimated by synchronization likelihood (SL). The brain networks were constructed by normalized SL values. The present leave-one-out cross validation (LOOCV) required the Euclidean distance between any two subjects having 120-dimensional vectors concerned with the SL values for six frequency bands. In order to investigate factors which would affect the LOOCV results, principal component analysis (PCA) was applied to all the subjects. Results: The accuracy for the upper alpha yielded more than 80% and 70% in the dementia groups and the healthy elderlies, respectively. The LOOCV result could be explained in terms of brain networks such as executive control network (ECN) and default mode network (DMN) characterized by factor loadings of principal components. Conclusions: Dementia groups and healthy elderlies could be characterized by principal components of SL values between all the electrode pairs, even less connections, which revealed disruption and preservation of DMN and ECN. Significance: This study will provide a simple and practical method for discriminating dementia groups from healthy elderlies by scalp-recorded EEGs.","PeriodicalId":64231,"journal":{"name":"生物医学工程(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70882975","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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