This paper empirically analyzes the income effect of the nutrient intake structure of migrant workers based on the 2014 survey data on the employment and food demand of urban migrant workers in China. The results showed that after controlling for factors such as labor intensity, height and weight, the monthly average income significantly increased the calorie intake of migrant workers, and the income elasticity was 0.052. From the perspective of nutrient intake structure, the average monthly income had no significant effect on the carbohydrate intake of migrant workers, but significantly increased the fat and protein intake of migrant workers, and the income elasticity was 0.222 and 0.075, respectively. Nutrition has not linear relationship between demand and income. The effect of average income on caloric intake of migrant workers in low income group, middle income group and high income group decreases with the increase of income group, until it has no significant effect on high income group, and heat demand income elasticity of low-income as well as middle-income group of migrant workers was 0.182 and 0.092, respectively.
{"title":"Study on Income Effect of Nutrient Intake Structure of Migrant Workers: The Case of China","authors":"Zhiwei He, Kang Yu","doi":"10.31033/ijemr.10.4.27","DOIUrl":"https://doi.org/10.31033/ijemr.10.4.27","url":null,"abstract":"This paper empirically analyzes the income effect of the nutrient intake structure of migrant workers based on the 2014 survey data on the employment and food demand of urban migrant workers in China. The results showed that after controlling for factors such as labor intensity, height and weight, the monthly average income significantly increased the calorie intake of migrant workers, and the income elasticity was 0.052. From the perspective of nutrient intake structure, the average monthly income had no significant effect on the carbohydrate intake of migrant workers, but significantly increased the fat and protein intake of migrant workers, and the income elasticity was 0.222 and 0.075, respectively. Nutrition has not linear relationship between demand and income. The effect of average income on caloric intake of migrant workers in low income group, middle income group and high income group decreases with the increase of income group, until it has no significant effect on high income group, and heat demand income elasticity of low-income as well as middle-income group of migrant workers was 0.182 and 0.092, respectively.","PeriodicalId":8928,"journal":{"name":"Biomaterials eJournal","volume":"43 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89914319","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}
Six months after the first coronavirus case was identified in the United States, the virus continues to circulate across the country To what extent was the US
在美国发现首例冠状病毒病例六个月后，该病毒继续在全国范围内传播
{"title":"Was the United States Prepared to Confront Covid-19? According to Scientists, It Depends","authors":"Mattia Caldarulo","doi":"10.2139/ssrn.3643531","DOIUrl":"https://doi.org/10.2139/ssrn.3643531","url":null,"abstract":"Six months after the first coronavirus case was identified in the United States, the virus continues to circulate across the country To what extent was the US","PeriodicalId":8928,"journal":{"name":"Biomaterials eJournal","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81512841","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}
X. Kong, Lin Zhang, Quanda Zhang, Jiun Choong, Sicong Ma, X. Qin, Z. Qi, Ran Cheng, Yi Fang, Z. Ge, Yu Jiang, Jing Wang
Background: TAILORx data confirm that using a 21-gene expression assay known as Oncotype DX (ODX; Genomic Health, Redwood City, CA) to assess the risk of early-stage breast cancer recurrence can spare women unnecessary chemotherapy. However, high up-front costs (list price, $4175) could dissuade usage. Also, from a technical perspective, this test cannot be widely used in developing countries, especially in relatively poor areas. Methods: By analyzing the Surveillance, Epidemiology, and End-Results (SEER) database, Logistic Regression models were firstly used to identified significant variables that might be associated with breast cancer patients’ ODX recurrence scores (RS) and risk levels. Secondly, by adopting a series of machine leaning (ML) technologies, including random forest (RF), gradient boosting decision tree (GBDT), and XGBoost, we developed an assistant forecast system for the ODX recurrence risks [low-to-intermediate-risk (RS=2~25) and high-risk (RS=26~100)] based on individual’s sociodemographic information and clinicopathological information. This developed system was then validated in an independent validation data set via a training-test split method on the original data set. Findings: We identified 111,635 patients with breast cancer, among which, 86617 patients (77.59%) were not beyond 50 years old. There were 23,514 patients (21.1%) whose ODX RSs were within the low risk of recurrence group, 71,439 patients (64.0%) were at intermediate-risk level, and 16,682 patients (14.9%) were at high-risk level. Via the multinomial ordinal logit regression, the variables closely associated with the ODX recurrence scores included age, sex, race, tumor primary site, histopathological grade, tumor size, pathology, PR status, HER2 status, (all P<0.05). Through our developed assistant forecast system, as long as a breast cancer patient’s precise sociodemographic and clinicopathological information was input, the computer would be able to automatically forecast the patient’s ODX recurrence risk level with an accuracy probability. According to the validation results, the best overall accuracy of this forecast system was 87.02% (Ordered Logistic Regression), with 99.06% specificity (Ordered Logistic Regression), and 86.0% sensitivity (RF). Interpretation: Our developed assistant forecast system based on sociodemographic and clinicopathological data provided clinicians an alternative tool to estimate breast cancer patients’ ODX recurrence risk level, which could be used to help assist in making an adjuvant treatment decision. In the future, this tool is widely worthwhile to be retrospectively validated in clinical practice and applied in actual clinical scenarios.
{"title":"Construction of an Assistant Forecast System for Breast Cancer Oncotype Dx Recurrence Risk by Machine Learning","authors":"X. Kong, Lin Zhang, Quanda Zhang, Jiun Choong, Sicong Ma, X. Qin, Z. Qi, Ran Cheng, Yi Fang, Z. Ge, Yu Jiang, Jing Wang","doi":"10.2139/ssrn.3642585","DOIUrl":"https://doi.org/10.2139/ssrn.3642585","url":null,"abstract":"Background: \u0000TAILORx data confirm that using a 21-gene expression assay known as Oncotype DX (ODX; Genomic Health, Redwood City, CA) to assess the risk of early-stage breast cancer recurrence can spare women unnecessary chemotherapy. However, high up-front costs (list price, $4175) could dissuade usage. Also, from a technical perspective, this test cannot be widely used in developing countries, especially in relatively poor areas. \u0000 \u0000Methods: \u0000By analyzing the Surveillance, Epidemiology, and End-Results (SEER) database, Logistic Regression models were firstly used to identified significant variables that might be associated with breast cancer patients’ ODX recurrence scores (RS) and risk levels. Secondly, by adopting a series of machine leaning (ML) technologies, including random forest (RF), gradient boosting decision tree (GBDT), and XGBoost, we developed an assistant forecast system for the ODX recurrence risks [low-to-intermediate-risk (RS=2~25) and high-risk (RS=26~100)] based on individual’s sociodemographic information and clinicopathological information. This developed system was then validated in an independent validation data set via a training-test split method on the original data set. \u0000 \u0000Findings: \u0000We identified 111,635 patients with breast cancer, among which, 86617 patients (77.59%) were not beyond 50 years old. There were 23,514 patients (21.1%) whose ODX RSs were within the low risk of recurrence group, 71,439 patients (64.0%) were at intermediate-risk level, and 16,682 patients (14.9%) were at high-risk level. Via the multinomial ordinal logit regression, the variables closely associated with the ODX recurrence scores included age, sex, race, tumor primary site, histopathological grade, tumor size, pathology, PR status, HER2 status, (all P<0.05). Through our developed assistant forecast system, as long as a breast cancer patient’s precise sociodemographic and clinicopathological information was input, the computer would be able to automatically forecast the patient’s ODX recurrence risk level with an accuracy probability. According to the validation results, the best overall accuracy of this forecast system was 87.02% (Ordered Logistic Regression), with 99.06% specificity (Ordered Logistic Regression), and 86.0% sensitivity (RF). \u0000 \u0000Interpretation: \u0000Our developed assistant forecast system based on sociodemographic and clinicopathological data provided clinicians an alternative tool to estimate breast cancer patients’ ODX recurrence risk level, which could be used to help assist in making an adjuvant treatment decision. In the future, this tool is widely worthwhile to be retrospectively validated in clinical practice and applied in actual clinical scenarios.","PeriodicalId":8928,"journal":{"name":"Biomaterials eJournal","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73097078","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}
Aarti Chugh, P. Makkar, S. Aggarwal, Shriya Sharma, Yashwant Kumar Singh
The focus of this paper is to design and develop the Artificial Intelligence and Machine Learning based system which detects the fungal infection on a pet animal (especially Dog and Cat), and provide the treatment for it. It also provides the causes, Symptoms, Prevention for it. The proposed system integrates on Machine Learning algorithm trained on disease dataset, it first detects the species of pet animal by capturing the image of fungal infection of pet by using camera or by uploading the image in the system from the file explorer, and then provide the diagnosis about the fungal disease and its medication and treatment also. Although our system will verify the scan image for determining the diseases in canine. Diagnosing the Fungal Infection on pet animal quickly and accurately has the economic effectiveness.
{"title":"Approach of Image Processing in Diagnosis and Medication of Fungal Infections in Pet Animals","authors":"Aarti Chugh, P. Makkar, S. Aggarwal, Shriya Sharma, Yashwant Kumar Singh","doi":"10.2139/ssrn.3673124","DOIUrl":"https://doi.org/10.2139/ssrn.3673124","url":null,"abstract":"The focus of this paper is to design and develop the Artificial Intelligence and Machine Learning based system which detects the fungal infection on a pet animal (especially Dog and Cat), and provide the treatment for it. It also provides the causes, Symptoms, Prevention for it. The proposed system integrates on Machine Learning algorithm trained on disease dataset, it first detects the species of pet animal by capturing the image of fungal infection of pet by using camera or by uploading the image in the system from the file explorer, and then provide the diagnosis about the fungal disease and its medication and treatment also. Although our system will verify the scan image for determining the diseases in canine. Diagnosing the Fungal Infection on pet animal quickly and accurately has the economic effectiveness.","PeriodicalId":8928,"journal":{"name":"Biomaterials eJournal","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87003014","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 : 2020-06-08DOI: 10.34257/gjcstdvol20is1pg29
Satish Gajawada, H. Mustafa
John McCarthy (September 4, 1927 – October 24,2011) was an American computer scientist and cognitive scientist. The term “Artificial Intelligence” was coined by him(Wikipedia, 2020). Satish Gajawada (March 12, 1988 – Present) is an Indian Independent Inventor and Scientist. He coined the term “Artificial Satisfaction” in this article (Gajawada, S., and Hassan Mustafa, 2019a). A new field titled “Artificial Satisfaction” is introduced in this article. “Artificial Satisfaction” will be referred to as “The Brother of Artificial Intelligence” after the publication of this article. A new algorithm titled “Artificial Satisfaction Algorithm (ASA)” is designed and implemented in this work. For the sake of simplicity, Particle Swarm Optimization (PSO) Algorithm is modified with Artificial Satisfaction Concepts to create the“Artificial Satisfaction Algorithm (ASA).” PSO and AS Aalgorithms are applied on five benchmark functions. A comparision is made between the results obtained. The focus of this paper is more on defining and introducing “Artificial Satisfaction Field” to the rest of the world rather than on implementing complex algorithms from scratch.
{"title":"Artificial Satisfaction - The Brother of Artificial Intelligence","authors":"Satish Gajawada, H. Mustafa","doi":"10.34257/gjcstdvol20is1pg29","DOIUrl":"https://doi.org/10.34257/gjcstdvol20is1pg29","url":null,"abstract":"John McCarthy (September 4, 1927 – October 24,2011) was an American computer scientist and cognitive scientist. The term “Artificial Intelligence” was coined by him(Wikipedia, 2020). Satish Gajawada (March 12, 1988 – Present) is an Indian Independent Inventor and Scientist. He coined the term “Artificial Satisfaction” in this article (Gajawada, S., and Hassan Mustafa, 2019a). A new field titled “Artificial Satisfaction” is introduced in this article. “Artificial Satisfaction” will be referred to as “The Brother of Artificial Intelligence” after the publication of this article. A new algorithm titled “Artificial Satisfaction Algorithm (ASA)” is designed and implemented in this work. For the sake of simplicity, Particle Swarm Optimization (PSO) Algorithm is modified with Artificial Satisfaction Concepts to create the“Artificial Satisfaction Algorithm (ASA).” PSO and AS Aalgorithms are applied on five benchmark functions. A comparision is made between the results obtained. The focus of this paper is more on defining and introducing “Artificial Satisfaction Field” to the rest of the world rather than on implementing complex algorithms from scratch.","PeriodicalId":8928,"journal":{"name":"Biomaterials eJournal","volume":"373 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77428529","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}
R. Shaikh, E. Nippolainen, V. Virtanen, J. Torniainen, L. Rieppo, S. Saarakkala, I. Afara, J. Töyräs
In recent years, Raman spectroscopy has evolved as a promising in vivo tool in various biomedical applications. It has also shown potential for scoring the lesion severity of joint cartilage, which could be useful in determining the best treatment strategy during cartilage arthroscopic repair surgery. However, the effect of different cartilage injury types on Raman spectra is unknown. The study aims to show the potential of Raman spectroscopy to detect different cartilage injury types that mimic physiologically relevant damages. Different types of injuries were induced using established mechanical and enzymatic approaches. The mechanical damage—was induced through surface abrasion (ABR) (n = 12) or impact loading (IMP) (n = 12). Enzymatic damage—was induced using three different treatments: 30 minutes trypsin digestion (T-30)(n = 12), 90 minutes collagenase digestion (C-90)(n = 12), and 24 hours collagenase digestion (C-24)(n = 12). Raman spectra were obtained from all the specimens, and partial least squares discriminant analysis (PLS-DA) was applied to distinguish cartilage injury types from their respective controls. The PLS-DA cross-validation accuracies were higher for C-24 (88%) and IMP (79%) than for C-90 (67%), T-30 (63%), and ABR (58%) groups. This study indicates that Raman spectroscopy, combined with multivariate analysis, can identify different cartilage injury types.
{"title":"Raman Spectroscopy is Sensitive to Biochemical Changes Related to Various Cartilage Injuries","authors":"R. Shaikh, E. Nippolainen, V. Virtanen, J. Torniainen, L. Rieppo, S. Saarakkala, I. Afara, J. Töyräs","doi":"10.2139/ssrn.3606831","DOIUrl":"https://doi.org/10.2139/ssrn.3606831","url":null,"abstract":"In recent years, Raman spectroscopy has evolved as a promising in vivo tool in various biomedical applications. It has also shown potential for scoring the lesion severity of joint cartilage, which could be useful in determining the best treatment strategy during cartilage arthroscopic repair surgery. However, the effect of different cartilage injury types on Raman spectra is unknown. The study aims to show the potential of Raman spectroscopy to detect different cartilage injury types that mimic physiologically relevant damages. Different types of injuries were induced using established mechanical and enzymatic approaches. The mechanical damage—was induced through surface abrasion (ABR) (n = 12) or impact loading (IMP) (n = 12). Enzymatic damage—was induced using three different treatments: 30 minutes trypsin digestion (T-30)(n = 12), 90 minutes collagenase digestion (C-90)(n = 12), and 24 hours collagenase digestion (C-24)(n = 12). Raman spectra were obtained from all the specimens, and partial least squares discriminant analysis (PLS-DA) was applied to distinguish cartilage injury types from their respective controls. The PLS-DA cross-validation accuracies were higher for C-24 (88%) and IMP (79%) than for C-90 (67%), T-30 (63%), and ABR (58%) groups. This study indicates that Raman spectroscopy, combined with multivariate analysis, can identify different cartilage injury types.","PeriodicalId":8928,"journal":{"name":"Biomaterials eJournal","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86305259","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}
Robert L. Shuler, Theodore Koukouvitis, Dyske Suematsu
Like the trajectory of a rocket whose landing point is unpredictable unless it is steered, an epidemic takes a trajectory highly dependent on human behavior. To control the threat of a pandemic, a city or region must also be viewed as a system with certain capacities and constraints. The goal of this paper is to contribute the perspective of a systems engineer to the effort to fight pandemics. The availability of low latency case data and effectiveness of social distancing suggest sufficient control authority is for successful smoothing and targeting almost any desired level of low or high cases and immunity. We examine multi-step and intermittent-with-feedback partial unlock of social distancing for rapidly-spreading moderate-mortality epidemics and pandemics similar to COVID-19. Optimized scenarios reduce total cases and therefore deaths typically 8% and up to 30% by controlling overshoot as groups cross the herd immunity threshold, or lower thresholds to manage medical resources and provide economic relief. We analyze overshoot and provide guidance on how to damp it. An SIR model is used to evaluate scenarios that are intended to function over a wide variety of parameters. The end result is not a case trajectory prediction, but a prediction of which strategies produce near-optimal results over a wide range of epidemiological and social parameters.
{"title":"System Engineering and Overshoot Damping for Epidemics Such As COVID-19","authors":"Robert L. Shuler, Theodore Koukouvitis, Dyske Suematsu","doi":"10.2139/ssrn.3590869","DOIUrl":"https://doi.org/10.2139/ssrn.3590869","url":null,"abstract":"Like the trajectory of a rocket whose landing point is unpredictable unless it is steered, an epidemic takes a trajectory highly dependent on human behavior. To control the threat of a pandemic, a city or region must also be viewed as a system with certain capacities and constraints. The goal of this paper is to contribute the perspective of a systems engineer to the effort to fight pandemics. The availability of low latency case data and effectiveness of social distancing suggest sufficient control authority is for successful smoothing and targeting almost any desired level of low or high cases and immunity. We examine multi-step and intermittent-with-feedback partial unlock of social distancing for rapidly-spreading moderate-mortality epidemics and pandemics similar to COVID-19. Optimized scenarios reduce total cases and therefore deaths typically 8% and up to 30% by controlling overshoot as groups cross the herd immunity threshold, or lower thresholds to manage medical resources and provide economic relief. We analyze overshoot and provide guidance on how to damp it. An SIR model is used to evaluate scenarios that are intended to function over a wide variety of parameters. The end result is not a case trajectory prediction, but a prediction of which strategies produce near-optimal results over a wide range of epidemiological and social parameters.","PeriodicalId":8928,"journal":{"name":"Biomaterials eJournal","volume":"137 3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91098462","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}
Microbial proteases are useful in silk degumming, leather processing, detergent additives and waste water treatment. It is important to explore the cheap and easily available substrates for the growth and protease production by the microorganisms. A haloalkaliphilic actinobacterium, Nocardiopsis alba OM-4 was grown on solid waste materials and the media were optimized for the maximum protease production. The haloalkaliphilic actinobacterial culture was inoculated in house hold waste and agro-industrial waste products including wheat bran, lentil husk, green gram husk, corn cob, vegetables peels, fruit peels, agricultural waste, pulses flour, walnut shell, pista shell, ground nut been husk and gelatine. All the ingredients of the solid state media were in the range of 0.5-5.0 g/ml and the growth along with protease production was monitored for fifteen days. The aliquots of the grown culture were harvested each day and protease activity and growth were measured. Different combinations of medium components were assessed for the growth and protease production. The comparison of the protease activity revealed that pulse flour, corn cob, vegetable pills and green gram husk followed by agriculture waste supported the protease production. Walnut shell and Pista shell didn’t enhance the growth and protease production. Other ingredients were also useful for growth and protease production.
{"title":"Production of an Alkaline Protease From Nocardiopsis Alba Om-4, a Haloalkaliphilic Actinobacteria in Solid-State Fermentation Using Agricultural Waste Products","authors":"F. Thakrar, D. Goswami, Satya P. Singh","doi":"10.2139/ssrn.3586506","DOIUrl":"https://doi.org/10.2139/ssrn.3586506","url":null,"abstract":"Microbial proteases are useful in silk degumming, leather processing, detergent additives and waste water treatment. It is important to explore the cheap and easily available substrates for the growth and protease production by the microorganisms. A haloalkaliphilic actinobacterium, Nocardiopsis alba OM-4 was grown on solid waste materials and the media were optimized for the maximum protease production. The haloalkaliphilic actinobacterial culture was inoculated in house hold waste and agro-industrial waste products including wheat bran, lentil husk, green gram husk, corn cob, vegetables peels, fruit peels, agricultural waste, pulses flour, walnut shell, pista shell, ground nut been husk and gelatine. All the ingredients of the solid state media were in the range of 0.5-5.0 g/ml and the growth along with protease production was monitored for fifteen days. The aliquots of the grown culture were harvested each day and protease activity and growth were measured. Different combinations of medium components were assessed for the growth and protease production. The comparison of the protease activity revealed that pulse flour, corn cob, vegetable pills and green gram husk followed by agriculture waste supported the protease production. Walnut shell and Pista shell didn’t enhance the growth and protease production. Other ingredients were also useful for growth and protease production.","PeriodicalId":8928,"journal":{"name":"Biomaterials eJournal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75148103","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 : 2020-04-01DOI: 10.33472/afjbs.2.2.2020.58-69
Okoegwale E. E., Idialu J. E., Ehilen O. E., Ogie-Odia E. A.
This study was carried out to assess the vessel and fiber dimensions and characteristics of Blighia sapida Konig. and Lecaniodiscus cupanoides Planch ex Benth. growing in the rainforest and derived savanna regions of Edo state, Nigeria. In both taxa, rainforest species possessed wider and longer vessels than the derived savanna species. Also, significant variations were recorded in taxa vessel wall thickness between the two ecozones. The derived savanna plants had thicker vessel wall to counterbalance the water stress prevalent in that environment. In both species, vessel members lacked tails. Also, taxa fibers were of short and medium lengths. Significant variations between fiber lengths of species occurring in both habitats were not encountered. Fiber elements of taxa were of moderately thick wall while fiber/vessel length ratio was greater than 1 in both taxa. Although runkel ratios of both species studied were less than 1, they may however not be suitable for high grade pulp because of their low fiber length values. The study has revealed that the woods are suitable for various end uses because of the presence and distribution of vessels and fiber with thick walls.
本研究旨在研究白螺旋藻(Blighia sapida Konig)的血管和纤维尺寸及其特性。和Lecaniodiscus cupanoides Planch ex Benth。生长在尼日利亚埃多州的热带雨林和衍生稀树草原地区。在这两个分类群中，热带雨林物种比衍生的热带稀树草原物种具有更宽和更长的导管。此外，两个生态区的分类群血管壁厚度也存在显著差异。衍生的热带稀树草原植物具有较厚的血管壁，以抵消该环境中普遍存在的水分胁迫。在这两个物种中，导管成员都没有尾巴。分类群的纤维长度均为中短。在两种生境中，没有发现物种纤维长度的显著差异。两个类群的纤维成分均为中等厚壁，纤维/导管长度比均大于1。虽然所研究的两种植物的朗克尔比都小于1，但由于它们的纤维长度值较低，可能不适合用于优质纸浆。研究表明，由于厚壁容器和纤维的存在和分布，这些木材适用于各种最终用途。
{"title":"Assessment of Vessel and Fiber Characteristics of Blighia Sapida Konig. And Lecaniodiscus Cupanoides Planch Ex Benth. Growing in Rainforest and Derived Savanna Areas of Edo State, Nigeria","authors":"Okoegwale E. E., Idialu J. E., Ehilen O. E., Ogie-Odia E. A.","doi":"10.33472/afjbs.2.2.2020.58-69","DOIUrl":"https://doi.org/10.33472/afjbs.2.2.2020.58-69","url":null,"abstract":"This study was carried out to assess the vessel and fiber dimensions and characteristics of Blighia sapida Konig. and Lecaniodiscus cupanoides Planch ex Benth. growing in the rainforest and derived savanna regions of Edo state, Nigeria. In both taxa, rainforest species possessed wider and longer vessels than the derived savanna species. Also, significant variations were recorded in taxa vessel wall thickness between the two ecozones. The derived savanna plants had thicker vessel wall to counterbalance the water stress prevalent in that environment. In both species, vessel members lacked tails. Also, taxa fibers were of short and medium lengths. Significant variations between fiber lengths of species occurring in both habitats were not encountered. Fiber elements of taxa were of moderately thick wall while fiber/vessel length ratio was greater than 1 in both taxa. Although runkel ratios of both species studied were less than 1, they may however not be suitable for high grade pulp because of their low fiber length values. The study has revealed that the woods are suitable for various end uses because of the presence and distribution of vessels and fiber with thick walls.","PeriodicalId":8928,"journal":{"name":"Biomaterials eJournal","volume":"83 5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83556191","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}
Hisanobu Kamio, Shuehi Tsuchiya, K. Kuroda, M. Okido, Kazuto Okabe, H. Hibi
Successful osseointegration of a bone and implant directly must be achieved for treatment of a dental implant. However, the mechanism of osseointegration at the molecular level has yet to be fully elucidated. In this study, we focused on the proteoglycans (PGs)-rich layer between titanium dioxide (TiO2) and bone and chondroitin-4-sulfate transferase-1 (C4ST-1) that forms the sugar chain in PGs. Human bone marrow mesenchymal stem cells (hBMSCs) depleted of C4ST-1 were cultured on TiO2, and the interface between hBMSCs and TiO2 was analyzed by transmission electron microscopy. Further, the immunotolerance capacity, cell proliferation, initial attachment, and calcification were analyzed in vitro. At 14 days cultivation, a PGs-rich layer was observed between hBMSCs and TiO2. However, the PGs-rich layer was reduced in C4ST-1-depleted hBMSCs on TiO2. Further, real-time RT-PCR showed that conditioned media increased gene expression levels of M1-macrophage markers in human macrophages. However, C4ST-1 did not affect calcification, cell proliferation, and initial cell attachment on TiO2. These results suggested that C4ST-1 in hBMSCs affected the width of the PGs-rich layer on TiO2 and their immunotolerance capacity.
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