Pub Date : 2021-01-01DOI: 10.33545/26646536.2021.v3.i2a.28
S. Revathi, G. Deepa, K. Deepika, T. Gopika
{"title":"Biodiesel production from canola oil with KOH by transesterification process","authors":"S. Revathi, G. Deepa, K. Deepika, T. Gopika","doi":"10.33545/26646536.2021.v3.i2a.28","DOIUrl":"https://doi.org/10.33545/26646536.2021.v3.i2a.28","url":null,"abstract":"","PeriodicalId":13816,"journal":{"name":"International Journal of Bioscience, Biochemistry and Bioinformatics","volume":"1266 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91519072","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 : 2020-07-01DOI: 10.17706/IJBBB.2020.10.3.137-143
J. Hayano, Atsushi Yamada, Y. Yoshida, N. Ueda, E. Yuda
The spread of continuous indwelling sensors in the subcutaneous tissue has enabled continuous monitoring of interstitial fluid glucose concentration (ISFG) under daily activities. This technology is considered to enable the development of a method for evaluating glycemic control function by analyzing not only the detailed state of diabetes and other pathological conditions but also the characteristics of glycemic dynamics. To clarify the basic fluctuation characteristics of long-term ISFG, the spectral structure and nonlinear dynamics properties of ISFG obtained by continuous monitoring for 11 days were analyzed in healthy and diabetic subjects.
{"title":"Spectral Structure and Nonlinear Dynamics Properties of Long-Term Interstitial Fluid Glucose","authors":"J. Hayano, Atsushi Yamada, Y. Yoshida, N. Ueda, E. Yuda","doi":"10.17706/IJBBB.2020.10.3.137-143","DOIUrl":"https://doi.org/10.17706/IJBBB.2020.10.3.137-143","url":null,"abstract":"The spread of continuous indwelling sensors in the subcutaneous tissue has enabled continuous monitoring of interstitial fluid glucose concentration (ISFG) under daily activities. This technology is considered to enable the development of a method for evaluating glycemic control function by analyzing not only the detailed state of diabetes and other pathological conditions but also the characteristics of glycemic dynamics. To clarify the basic fluctuation characteristics of long-term ISFG, the spectral structure and nonlinear dynamics properties of ISFG obtained by continuous monitoring for 11 days were analyzed in healthy and diabetic subjects.","PeriodicalId":13816,"journal":{"name":"International Journal of Bioscience, Biochemistry and Bioinformatics","volume":"21 1","pages":"137-143"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82414218","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}
Machine learn methods have been widely used for classification and diagnosis of diseases for increasing its accuracy and efficiency. The kernel extreme learning machine is being increasingly used algorithm to training single layer forward neural network as that this network is given the weights between input and hidden layers, and the bias parameter of each hidden node. In order to obtain more stable and accurate model, an artificial bee colony algorithm is used to pre-train parameters of kernel parameter and penalty parameter. weight and bias. In this paper, an artificial bee colony based kernel extreme learning machine is proposed to classify medical datasets. This proposed method is called ABC-KELM. In experiments, we use two benchmark datasets that are Breast cancer and Parkinson disease from the UCI repository to evaluate the effectiveness and classification accuracy. The experimental results reveal that the ABC-KELM can obtain satisfactory classification results.
{"title":"Parameter Optimization of Kernel Extreme Learning Machine Using Artificial Bee Colony Algorithm and Its Application for Disease Classification","authors":"M. Horng, Jian-Ying Cheng, Yu-Lun Hung, Yu-Cheng Hung, Yung-Nien Sun, Pongpon Nilaphruek","doi":"10.17706/IJBBB.2020.10.3.127-136","DOIUrl":"https://doi.org/10.17706/IJBBB.2020.10.3.127-136","url":null,"abstract":"Machine learn methods have been widely used for classification and diagnosis of diseases for increasing its accuracy and efficiency. The kernel extreme learning machine is being increasingly used algorithm to training single layer forward neural network as that this network is given the weights between input and hidden layers, and the bias parameter of each hidden node. In order to obtain more stable and accurate model, an artificial bee colony algorithm is used to pre-train parameters of kernel parameter and penalty parameter. weight and bias. In this paper, an artificial bee colony based kernel extreme learning machine is proposed to classify medical datasets. This proposed method is called ABC-KELM. In experiments, we use two benchmark datasets that are Breast cancer and Parkinson disease from the UCI repository to evaluate the effectiveness and classification accuracy. The experimental results reveal that the ABC-KELM can obtain satisfactory classification results.","PeriodicalId":13816,"journal":{"name":"International Journal of Bioscience, Biochemistry and Bioinformatics","volume":"1 1","pages":"127-136"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84146603","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}
Currently, many people wear a wristband type device while sleeping to automatically record how many hours they sleep. Even a system without a wearing device, such as a smartphone application, needs to be set in advance. Therefore, automatic recording of sleep time cannot be realized without advanced measurement preparation. In this study, we propose a method to estimate sleep time without advanced preparation based on a simple measurement of biological information after awakening. We extracted 97 types of features from sensor data that were measured using wearable devices. We analyzed whether significant differences between each feature appear according to the previous sleep time. Furthermore, we evaluated the accuracy when the sleep time is estimated by machine learning using features with a significant difference. We adopted Support Vector Machine (SVM) as a machine learning algorithm and Leave-One-Session-Out Cross Validation (LOSO-CV) as an evaluation method. Consequently, there were seven features with significant differences when the biological information was measured one hour after awakening. By using machine learning, the accuracy of the previous sleep time (three sleep time categories: short, medium, or long) was estimated to be 62.5%.
{"title":"Feature Analysis to Estimate Sleep Time Based on Simple Measurement of Biological Information after Awakening","authors":"Mahiro Imabeppu, Ren Katsurada, Tatsuhito Hasegawa","doi":"10.17706/IJBBB.2020.10.3.144-153","DOIUrl":"https://doi.org/10.17706/IJBBB.2020.10.3.144-153","url":null,"abstract":"Currently, many people wear a wristband type device while sleeping to automatically record how many hours they sleep. Even a system without a wearing device, such as a smartphone application, needs to be set in advance. Therefore, automatic recording of sleep time cannot be realized without advanced measurement preparation. In this study, we propose a method to estimate sleep time without advanced preparation based on a simple measurement of biological information after awakening. We extracted 97 types of features from sensor data that were measured using wearable devices. We analyzed whether significant differences between each feature appear according to the previous sleep time. Furthermore, we evaluated the accuracy when the sleep time is estimated by machine learning using features with a significant difference. We adopted Support Vector Machine (SVM) as a machine learning algorithm and Leave-One-Session-Out Cross Validation (LOSO-CV) as an evaluation method. Consequently, there were seven features with significant differences when the biological information was measured one hour after awakening. By using machine learning, the accuracy of the previous sleep time (three sleep time categories: short, medium, or long) was estimated to be 62.5%.","PeriodicalId":13816,"journal":{"name":"International Journal of Bioscience, Biochemistry and Bioinformatics","volume":"40 1","pages":"144-153"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82207401","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: 10.33545/26646536.2020.v2.i1a.13
Karunakaran Kalaiselvan, Chinnavenkataraman Govindasamy, N. Vasanth
{"title":"Synthesis by silver nanoparticle activity of Larvicidal Useing leaf extracts of Andrographis alata against Culex quinquefasciatus","authors":"Karunakaran Kalaiselvan, Chinnavenkataraman Govindasamy, N. Vasanth","doi":"10.33545/26646536.2020.v2.i1a.13","DOIUrl":"https://doi.org/10.33545/26646536.2020.v2.i1a.13","url":null,"abstract":"","PeriodicalId":13816,"journal":{"name":"International Journal of Bioscience, Biochemistry and Bioinformatics","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75371483","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: 10.17706/ijbbb.2020.10.1.26-33
Patthanasak Rungsirivanich, N. Thongwai
Sixteen Bacillus isolates were obtained from leaves of Miang plant (Camellia sinensis (L.) Kuntze var. assamica (J.W. Mast.) Kitam.) collected from Miang gardens in Chiang Mai and Phrae provinces of Thailand. All bacterial isolates were identified within 3 species including B. licheniformis, B. siamensis and B. tequilensis based on 16S rRNA gene sequence. The culture broth of B. siamensis ML122-2, ML123-1 and ML124-1 could inhibit growth of Staphylococcus aureus ATCC 25923 and methicillin resistant S. aureus DMST 20625 while B. licheniformis ML071-1, ML073-1, ML075-1 and ML076-2 could inhibit growth of B. cereus TISTR 687 and S. aureus ATCC 25923 with the inhibitory value ranging between 242.4 363.6 and 265.2 340.9 AU/ml, respectively. Moreover, B. siamensis ML122-2 could tolerate tannin, 1% (w/v). Accordingly, B. siamensis ML122-2, ML123-1 and ML124-1 and B. licheniformis ML071-1, ML073-1, ML075-1 and ML076-2 may involve in biological control of Miang fermentation process.
{"title":"Antibacterial Activity and Tannin Tolerance of Bacillus spp. Isolated from Leaves of Miang (Camellia sinensis (L.) Kuntze var. assamica (J.W. Mast.) Kitam.)","authors":"Patthanasak Rungsirivanich, N. Thongwai","doi":"10.17706/ijbbb.2020.10.1.26-33","DOIUrl":"https://doi.org/10.17706/ijbbb.2020.10.1.26-33","url":null,"abstract":"Sixteen Bacillus isolates were obtained from leaves of Miang plant (Camellia sinensis (L.) Kuntze var. assamica (J.W. Mast.) Kitam.) collected from Miang gardens in Chiang Mai and Phrae provinces of Thailand. All bacterial isolates were identified within 3 species including B. licheniformis, B. siamensis and B. tequilensis based on 16S rRNA gene sequence. The culture broth of B. siamensis ML122-2, ML123-1 and ML124-1 could inhibit growth of Staphylococcus aureus ATCC 25923 and methicillin resistant S. aureus DMST 20625 while B. licheniformis ML071-1, ML073-1, ML075-1 and ML076-2 could inhibit growth of B. cereus TISTR 687 and S. aureus ATCC 25923 with the inhibitory value ranging between 242.4 363.6 and 265.2 340.9 AU/ml, respectively. Moreover, B. siamensis ML122-2 could tolerate tannin, 1% (w/v). Accordingly, B. siamensis ML122-2, ML123-1 and ML124-1 and B. licheniformis ML071-1, ML073-1, ML075-1 and ML076-2 may involve in biological control of Miang fermentation process.","PeriodicalId":13816,"journal":{"name":"International Journal of Bioscience, Biochemistry and Bioinformatics","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":"88902947","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: 10.33545/26646536.2020.v2.i1a.14
A. Hossain, Abdelmuhsin Abdelgadir
{"title":"Effects of indole acetic acid (IAA) hormone and bitter apple extract on growth development and nutrient content of mung bean plant in vitro","authors":"A. Hossain, Abdelmuhsin Abdelgadir","doi":"10.33545/26646536.2020.v2.i1a.14","DOIUrl":"https://doi.org/10.33545/26646536.2020.v2.i1a.14","url":null,"abstract":"","PeriodicalId":13816,"journal":{"name":"International Journal of Bioscience, Biochemistry and Bioinformatics","volume":"116 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75000070","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: 10.33545/26646536.2020.v2.i1a.16
Olusola Ao, Ogunsina Oi, Adekahunsi Aj, A. Fakoya
Malaria is a mosquito-borne disease that has plagued mankind for ages and continues to be most common and deadly parasitic disease in the world. The search for novel antimalarial compounds has been required by Plasmodium falciparum resistance to standard antimalarial drugs. Plants derivative are significant sources of biologically active metabolites which have potentials for new antimalarial drugs’ discovery. Meanwhile a number of alkaloids have been successfully used for the treatment of malaria. In this study, alkaloid-rich fraction of stem bark extract of Lannea acida was evaluated for possible antiplasmodial activity, against Plasmodium berghei, a chloroquine-sensitive protozoan. Suppressive activity of the fraction was examined for five consecutive days with the extract doses and chloroquine as the control drug, curative experimental groups were infected for five days prior to extract treatment, while the prophylactic groups were pretreated daily for five days before inoculation with 1×10 chloroquine-sensitive Plasmodium berghei intraperitoneally. The control group was administered with 10 ml distilled water/kg; 200 and 400 mg extract/kg weight were administered to the experimental groups, and chloroquine 5 mg/kg body weight respectively. All doses of the fraction produced significant, dose-dependent, chemo suppressive activity against the parasite in the suppressive, curative and prophylactic tests compared with chloroquine treated mice. The extract treatment also casused an elongation in the mean survival time of treated mice compared to the untreated mice.
疟疾是一种蚊子传播的疾病，多年来一直困扰着人类，并且仍然是世界上最常见和最致命的寄生虫病。恶性疟原虫对标准抗疟药物的耐药性要求寻找新的抗疟化合物。植物衍生物是生物活性代谢物的重要来源，具有开发抗疟新药的潜力。与此同时，一些生物碱已被成功地用于治疗疟疾。在本研究中，研究了Lannea acid茎皮提取物中富含生物碱的部分对伯氏疟原虫(一种对氯喹敏感的原生动物)的抗疟原虫活性。以提取液剂量和对照药物氯喹为对照，连续5天检测该组分的抑制活性，治疗组在提取液治疗前5天感染，预防组在接种1×10氯喹敏感伯氏疟原虫前5天每天进行预处理。对照组给予蒸馏水10 ml /kg;试验组分别给予提取物200、400 mg/kg体重，氯喹5 mg/kg体重。与氯喹处理的小鼠相比，所有剂量的部分在抑制、治疗和预防试验中对寄生虫产生显著的、剂量依赖的化学抑制活性。与未处理的小鼠相比，提取物处理也导致治疗小鼠的平均生存时间延长。
{"title":"Antimalarial activities of alkaloid-rich fraction of stem bark extract of Lannea acida in mice infected with Plasmodium berghei","authors":"Olusola Ao, Ogunsina Oi, Adekahunsi Aj, A. Fakoya","doi":"10.33545/26646536.2020.v2.i1a.16","DOIUrl":"https://doi.org/10.33545/26646536.2020.v2.i1a.16","url":null,"abstract":"Malaria is a mosquito-borne disease that has plagued mankind for ages and continues to be most common and deadly parasitic disease in the world. The search for novel antimalarial compounds has been required by Plasmodium falciparum resistance to standard antimalarial drugs. Plants derivative are significant sources of biologically active metabolites which have potentials for new antimalarial drugs’ discovery. Meanwhile a number of alkaloids have been successfully used for the treatment of malaria. In this study, alkaloid-rich fraction of stem bark extract of Lannea acida was evaluated for possible antiplasmodial activity, against Plasmodium berghei, a chloroquine-sensitive protozoan. Suppressive activity of the fraction was examined for five consecutive days with the extract doses and chloroquine as the control drug, curative experimental groups were infected for five days prior to extract treatment, while the prophylactic groups were pretreated daily for five days before inoculation with 1×10 chloroquine-sensitive Plasmodium berghei intraperitoneally. The control group was administered with 10 ml distilled water/kg; 200 and 400 mg extract/kg weight were administered to the experimental groups, and chloroquine 5 mg/kg body weight respectively. All doses of the fraction produced significant, dose-dependent, chemo suppressive activity against the parasite in the suppressive, curative and prophylactic tests compared with chloroquine treated mice. The extract treatment also casused an elongation in the mean survival time of treated mice compared to the untreated mice.","PeriodicalId":13816,"journal":{"name":"International Journal of Bioscience, Biochemistry and Bioinformatics","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75106652","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: 10.33545/26646536.2020.v2.i1a.15
O. Okojokwu, I. A. Onaji, Bashiru Shafa Abubakar, M. Adebayo, Nanman Ladul Mwankat, I. Yusuf, Francis Ofuowoicho Ukah, E. E. Entonu, M. Ali, A. Ogaji, J. Anejo-Okopi
{"title":"Genital Chlamydia trachomatis infection among pregnant women in Jos north, Jos, Nigeria: A hospital-based cross-sectional study","authors":"O. Okojokwu, I. A. Onaji, Bashiru Shafa Abubakar, M. Adebayo, Nanman Ladul Mwankat, I. Yusuf, Francis Ofuowoicho Ukah, E. E. Entonu, M. Ali, A. Ogaji, J. Anejo-Okopi","doi":"10.33545/26646536.2020.v2.i1a.15","DOIUrl":"https://doi.org/10.33545/26646536.2020.v2.i1a.15","url":null,"abstract":"","PeriodicalId":13816,"journal":{"name":"International Journal of Bioscience, Biochemistry and Bioinformatics","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82915745","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: 10.17706/ijbbb.2020.10.2.94-109
K. Fujimoto, S. Seno, Hironori Shigeta, T. Mashita, M. Ishii, H. Matsuda
FUCCI (fluorescent ubiquitination-based cell cycle indicator) is a fluorescent probe used to visualize the cell cycle progression of individual cells using fluorescent proteins of different colors. Because the cell cycle is related to biological processes such as proliferation of cancer cells, analysis of imaging data visualized using FUCCI is extremely important. This paper proposes a method for spatiotemporal tracking and analysis of FUCCI-labeled cells from time-lapse videos. To address the color transition of the FUCCI-labeled cell with the cell cycle progression, the proposed method simultaneously estimates the location and the cell cycle phase of the target cell. Furthermore, to analyze the cell phase transition, this paper proposes to apply multistate time-to-event analysis to the information obtained through our tracking method. This paper demonstrates the usefulness of our method with application to FUCCI-labeled HuH7 cells (human hepatocellular carcinoma cell line).
{"title":"Tracking and Analysis of FUCCI-Labeled Cells Based on Particle Filters and Time-to-Event Analysis","authors":"K. Fujimoto, S. Seno, Hironori Shigeta, T. Mashita, M. Ishii, H. Matsuda","doi":"10.17706/ijbbb.2020.10.2.94-109","DOIUrl":"https://doi.org/10.17706/ijbbb.2020.10.2.94-109","url":null,"abstract":"FUCCI (fluorescent ubiquitination-based cell cycle indicator) is a fluorescent probe used to visualize the cell cycle progression of individual cells using fluorescent proteins of different colors. Because the cell cycle is related to biological processes such as proliferation of cancer cells, analysis of imaging data visualized using FUCCI is extremely important. This paper proposes a method for spatiotemporal tracking and analysis of FUCCI-labeled cells from time-lapse videos. To address the color transition of the FUCCI-labeled cell with the cell cycle progression, the proposed method simultaneously estimates the location and the cell cycle phase of the target cell. Furthermore, to analyze the cell phase transition, this paper proposes to apply multistate time-to-event analysis to the information obtained through our tracking method. This paper demonstrates the usefulness of our method with application to FUCCI-labeled HuH7 cells (human hepatocellular carcinoma cell line).","PeriodicalId":13816,"journal":{"name":"International Journal of Bioscience, Biochemistry and Bioinformatics","volume":"323 1","pages":"94-109"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80302069","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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