Mathematical modelling has been widely used in many fields, especially in recent years. The applications of mathematical modelling in infectious diseases have shown that situations such as isolation, quarantine, vaccination and treatment are often necessary to eliminate most infectious diseases. In this study, a mathematical model of COVID-19 disease involving susceptible (S), exposed (E), infected (I), quarantined (Q), vaccinated (V) and recovered (R) populations is considered. In order to show the biological significance of the system, the non-negative solution region and the boundedness of the relevant biological compartments are shown. The endemic and disease-free equilibrium points of the model are calculated, and local stability analyses of these equilibrium points are performed. The basic reproduction number is also calculated for the relevant model. Sensitivity analysis of this number is studied, and it has been pointed out which parameters affect this number and how they affect it. Moreover, using real data from Iraq, the model parameters are estimated using the least squares curve fitting method, and numerical simulations are performed by using these estimated values. For the solution of the model, the Adams-Bashforth type predictive-corrective numerical method is used, and with the help of numerical simulations, several predictions are achieved about the future course of COVID-19.
{"title":"A new mathematical modelling and parameter estimation of COVID-19: a case study in Iraq","authors":"M. Yavuz, Waled Yavız Ahmed Haydar","doi":"10.3934/bioeng.2022030","DOIUrl":"https://doi.org/10.3934/bioeng.2022030","url":null,"abstract":"Mathematical modelling has been widely used in many fields, especially in recent years. The applications of mathematical modelling in infectious diseases have shown that situations such as isolation, quarantine, vaccination and treatment are often necessary to eliminate most infectious diseases. In this study, a mathematical model of COVID-19 disease involving susceptible (S), exposed (E), infected (I), quarantined (Q), vaccinated (V) and recovered (R) populations is considered. In order to show the biological significance of the system, the non-negative solution region and the boundedness of the relevant biological compartments are shown. The endemic and disease-free equilibrium points of the model are calculated, and local stability analyses of these equilibrium points are performed. The basic reproduction number is also calculated for the relevant model. Sensitivity analysis of this number is studied, and it has been pointed out which parameters affect this number and how they affect it. Moreover, using real data from Iraq, the model parameters are estimated using the least squares curve fitting method, and numerical simulations are performed by using these estimated values. For the solution of the model, the Adams-Bashforth type predictive-corrective numerical method is used, and with the help of numerical simulations, several predictions are achieved about the future course of COVID-19.","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"22 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74191973","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}
M. Jelassi, K. Oshinubi, Mustapha Rachdi, J. Demongeot
The present paper aims to apply the mathematical ideas of the contagion networks in a discrete dynamic context to the modeling of two current pandemics, i.e., COVID-19 and obesity, that are identified as major risks by the World Health Organization. After providing a reminder of the main tools necessary to model epidemic propagation in a Boolean framework (Hopfield-type propagation equation, notion of centrality, existence of stationary states), we present two applications derived from the observation of real data and involving mathematical models for their interpretation. After a discussion of the obtained results of model simulations, multidisciplinary work perspectives (both on mathematical and biomedical sides) are proposed in order to increase the efficiency of the models currently used and improve both the comprehension of the contagion mechanism and the prediction of the dynamic behaviors of the pandemics' present and future states.
{"title":"Epidemic dynamics on social interaction networks","authors":"M. Jelassi, K. Oshinubi, Mustapha Rachdi, J. Demongeot","doi":"10.3934/bioeng.2022025","DOIUrl":"https://doi.org/10.3934/bioeng.2022025","url":null,"abstract":"The present paper aims to apply the mathematical ideas of the contagion networks in a discrete dynamic context to the modeling of two current pandemics, i.e., COVID-19 and obesity, that are identified as major risks by the World Health Organization. After providing a reminder of the main tools necessary to model epidemic propagation in a Boolean framework (Hopfield-type propagation equation, notion of centrality, existence of stationary states), we present two applications derived from the observation of real data and involving mathematical models for their interpretation. After a discussion of the obtained results of model simulations, multidisciplinary work perspectives (both on mathematical and biomedical sides) are proposed in order to increase the efficiency of the models currently used and improve both the comprehension of the contagion mechanism and the prediction of the dynamic behaviors of the pandemics' present and future states.","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"1 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83734213","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}
{"title":"Biotechnology – current achievements and future challenges","authors":"J. Zdarta, K. Jankowska","doi":"10.3934/bioeng.2022005","DOIUrl":"https://doi.org/10.3934/bioeng.2022005","url":null,"abstract":"<jats:p xml:lang=\"fr\" />","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"5 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81249338","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}
Soft matter encompasses multitude of systems like biomolecules, living cells, polymers, composites or blends. The increasing interest to better understand their physico-chemical properties has significantly favored the development of new techniques with unprecedented resolution. In this framework, atomic force microscopy (AFM) can act as one main actor to address multitude of intrinsic sample characteristics at the nanoscale level. AFM presents many advantages in comparison to other bulk techniques as the assessment of individual entities discharging thus, ensemble averaging phenomena. Moreover, AFM enables the visualization of singular events that eventually can provide response of some open questions that still remain unclear. The present manuscript aims to make the reader aware of the potential applications in the employment of this tool by providing recent examples of scientific studies where AFM has been employed with success. Several operational modes like AFM imaging, AFM based force spectroscopy (AFM-FS), nanoindentation, AFM-nanoscale infrared spectroscopy (AFM-nanoIR) or magnetic force microscopy (MFM) will be fully explained to detail the type of information that AFM is capable to gather. Finally, future prospects will be delivered to discern the following steps to be conducted in this field.
{"title":"Current and future perspectives of atomic force microscopy to elicit the intrinsic properties of soft matter at the single molecule level","authors":"C. Marcuello","doi":"10.3934/bioeng.2022020","DOIUrl":"https://doi.org/10.3934/bioeng.2022020","url":null,"abstract":"Soft matter encompasses multitude of systems like biomolecules, living cells, polymers, composites or blends. The increasing interest to better understand their physico-chemical properties has significantly favored the development of new techniques with unprecedented resolution. In this framework, atomic force microscopy (AFM) can act as one main actor to address multitude of intrinsic sample characteristics at the nanoscale level. AFM presents many advantages in comparison to other bulk techniques as the assessment of individual entities discharging thus, ensemble averaging phenomena. Moreover, AFM enables the visualization of singular events that eventually can provide response of some open questions that still remain unclear. The present manuscript aims to make the reader aware of the potential applications in the employment of this tool by providing recent examples of scientific studies where AFM has been employed with success. Several operational modes like AFM imaging, AFM based force spectroscopy (AFM-FS), nanoindentation, AFM-nanoscale infrared spectroscopy (AFM-nanoIR) or magnetic force microscopy (MFM) will be fully explained to detail the type of information that AFM is capable to gather. Finally, future prospects will be delivered to discern the following steps to be conducted in this field.","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"19 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78539746","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}
The lac operon in E. coli has been extensively studied by computational biologists. The bacterium uses it to survive in the absence of glucose, utilizing lactose for growth. This paper presents a novel modeling mechanism for the lac operon, transferring the process of lactose metabolism from the cell to a finite state machine (FSM). This FSM is implemented in field-programmable gate array (FPGA) and simulations are run in random conditions. A Markov chain is also proposed for the lac operon, which helps study its behavior in terms of probabilistic variables, validating the finite state machine at the same time. This work is focused towards conversion of biological processes into computing machines.
{"title":"Finite state machine and Markovian equivalents of the lac Operon in E. coli bacterium","authors":"Urooj Ainuddin, Maria Waqas","doi":"10.3934/bioeng.2022029","DOIUrl":"https://doi.org/10.3934/bioeng.2022029","url":null,"abstract":"<abstract> <p>The <italic>lac</italic> operon in <italic>E. coli</italic> has been extensively studied by computational biologists. The bacterium uses it to survive in the absence of glucose, utilizing lactose for growth. This paper presents a novel modeling mechanism for the <italic>lac</italic> operon, transferring the process of lactose metabolism from the cell to a finite state machine (FSM). This FSM is implemented in field-programmable gate array (FPGA) and simulations are run in random conditions. A Markov chain is also proposed for the <italic>lac</italic> operon, which helps study its behavior in terms of probabilistic variables, validating the finite state machine at the same time. This work is focused towards conversion of biological processes into computing machines.</p> </abstract>","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"1 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75317934","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}
Surgical site infections (SSI) are one of the most common hospital acquired infections and result in increased morbidity, mortality and financial burden on health services. The incidence of SSIs are not clearly defined and infection rates as varied as 20%–40% have been reported. The aim of this study was to systematically review the incidence and risk factors of SSI following HPB surgery.
Methods
The database of Medline (via PubMed) was systematically searched from 2013–2022. Articles were screened using the PRISMA statement and those that met the inclusion criteria were included in the study.
Results
Sixteen studies were eligible for inclusion in this systematic review. The average incidence of SSI was 29.8%. Key risk factors identified included male gender, open surgery, preoperative biliary stenting and obesity.
Conclusions
The incidence of SSI following HPB surgery varied, but it is generally high. A variety of pre-disposing patient factors can affect infection rates following HPB surgery. The results from this study suggest that perhaps laparoscopic surgery should be used where possible, and that there should be an awareness that gender, obesity and the use of stents may increase the incidence of SSIs following these operations.
{"title":"A systematic review on the incidence and risk factors of surgical site infections following hepatopancreatobiliary (HPB) surgery","authors":"Lucy Chambers, A. Sheen, K. Whitehead","doi":"10.3934/bioeng.2022010","DOIUrl":"https://doi.org/10.3934/bioeng.2022010","url":null,"abstract":"<abstract><sec> <title>Background</title> <p>Surgical site infections (SSI) are one of the most common hospital acquired infections and result in increased morbidity, mortality and financial burden on health services. The incidence of SSIs are not clearly defined and infection rates as varied as 20%–40% have been reported. The aim of this study was to systematically review the incidence and risk factors of SSI following HPB surgery.</p> </sec><sec> <title>Methods</title> <p>The database of Medline (via PubMed) was systematically searched from 2013–2022. Articles were screened using the PRISMA statement and those that met the inclusion criteria were included in the study.</p> </sec><sec> <title>Results</title> <p>Sixteen studies were eligible for inclusion in this systematic review. The average incidence of SSI was 29.8%. Key risk factors identified included male gender, open surgery, preoperative biliary stenting and obesity.</p> </sec><sec> <title>Conclusions</title> <p>The incidence of SSI following HPB surgery varied, but it is generally high. A variety of pre-disposing patient factors can affect infection rates following HPB surgery. The results from this study suggest that perhaps laparoscopic surgery should be used where possible, and that there should be an awareness that gender, obesity and the use of stents may increase the incidence of SSIs following these operations.</p> </sec></abstract>","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"4 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88353701","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}
T. Nakazawa, Sohei Tasaki, Kiyohiko Nakai, Takashi Suzuki
This paper presents a mathematical model governing the dynamics of a morphogenetic vascular endothelial cell (EC) during angiogenesis, and vascular growth formed by EC. Especially, we adopt a multiparticle system for modeling these cells. This model does not distinguish a tip cell from a stalk cell. A formed vessel is modeled using phase-field equation to prevent capillary expansion with time stepping in particular. Numerical simulation reveals that all cells are moving in the direction of high concentration of vascular endothelial growth factor (VEGF), and that they are mutually repellent in cases in which they are closer than some threshold.
{"title":"Multicellular model of angiogenesis","authors":"T. Nakazawa, Sohei Tasaki, Kiyohiko Nakai, Takashi Suzuki","doi":"10.3934/bioeng.2022004","DOIUrl":"https://doi.org/10.3934/bioeng.2022004","url":null,"abstract":"This paper presents a mathematical model governing the dynamics of a morphogenetic vascular endothelial cell (EC) during angiogenesis, and vascular growth formed by EC. Especially, we adopt a multiparticle system for modeling these cells. This model does not distinguish a tip cell from a stalk cell. A formed vessel is modeled using phase-field equation to prevent capillary expansion with time stepping in particular. Numerical simulation reveals that all cells are moving in the direction of high concentration of vascular endothelial growth factor (VEGF), and that they are mutually repellent in cases in which they are closer than some threshold.","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"112 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90384118","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}
In this research work, various machine learning models such as linear regression (LR), KNN and MLP were created to predict the optimized synthesis of biodiesel from pre-treated and non-treated Linseed oil in base transesterification reaction mode. Three input parameters were included for modelling, reaction time, catalyst concentrated ion, and methanol/oil-molar ratio. In biodiesel transesterification reaction 180 samples run with non-Pre-treated Linseed Methyl Ester (NPLME), Water Pre-treated Linseed Methyl Ester (WPLME) and Enzymatic Pre-treated Linseed Methyl Ester (EPLME) oil as feed stocks and optimized parameters are find out for maximum biodiesel yield to be 8:1 molar ratio, 0.4% weight catalyst, 60 °C reaction temperature.To test the technique, R2 and MAPE parameters were used. The average R2 values for linear regression, KNN, and MLP are 0.7030, 0.8554 and 0.7864 respectively. Moreover, the average MAPE values for these models are 11.1886, 6.0873 and 8.0669 respectively. Hence, it is observed that the KNN model outperforms other models with higher accuracy and low MAPE score.
{"title":"Computational approach using machine learning modelling for optimization of transesterification process for linseed biodiesel production","authors":"Sunil Gautam, Sangeeta Kanakraj, Azriel Henry","doi":"10.3934/bioeng.2022023","DOIUrl":"https://doi.org/10.3934/bioeng.2022023","url":null,"abstract":"In this research work, various machine learning models such as linear regression (LR), KNN and MLP were created to predict the optimized synthesis of biodiesel from pre-treated and non-treated Linseed oil in base transesterification reaction mode. Three input parameters were included for modelling, reaction time, catalyst concentrated ion, and methanol/oil-molar ratio. In biodiesel transesterification reaction 180 samples run with non-Pre-treated Linseed Methyl Ester (NPLME), Water Pre-treated Linseed Methyl Ester (WPLME) and Enzymatic Pre-treated Linseed Methyl Ester (EPLME) oil as feed stocks and optimized parameters are find out for maximum biodiesel yield to be 8:1 molar ratio, 0.4% weight catalyst, 60 °C reaction temperature.To test the technique, R2 and MAPE parameters were used. The average R2 values for linear regression, KNN, and MLP are 0.7030, 0.8554 and 0.7864 respectively. Moreover, the average MAPE values for these models are 11.1886, 6.0873 and 8.0669 respectively. Hence, it is observed that the KNN model outperforms other models with higher accuracy and low MAPE score.","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"68 1 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78050205","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}
Bashdar A. Salam, S. Khoshnaw, A. M. Adabar, Hedayat M. Sharifi, A. S. Mohammed
Spreading COVID-19 pandemic has been considered as a global issue. Many international efforts including mathematical approaches have been recently discussed to control this disease more effectively. In this study, we have developed our previous SIUWR model and some transmission parameters are added. Accordingly, the basic reproduction number and elasticity coefficients are calculated at the equilibrium points. Then, some key critical model parameters are identified based on local sensitivities. In addition, the validation of the suggested model is checked by comparing some collected real data in Iraq and France from January 1st, 2021 to December 25th, 2021. Interestingly, there are good agreements between the model results and the real confirmed data using computational simulations in MATLAB. Results provide some biological interpretations and they can be used to control this pandemic more effectively. The model results will be used for both countries in minimizing the impact of this virus on their communities.
{"title":"Model predictions and data fitting can effectively work in spreading COVID-19 pandemic","authors":"Bashdar A. Salam, S. Khoshnaw, A. M. Adabar, Hedayat M. Sharifi, A. S. Mohammed","doi":"10.3934/bioeng.2022014","DOIUrl":"https://doi.org/10.3934/bioeng.2022014","url":null,"abstract":"Spreading COVID-19 pandemic has been considered as a global issue. Many international efforts including mathematical approaches have been recently discussed to control this disease more effectively. In this study, we have developed our previous SIUWR model and some transmission parameters are added. Accordingly, the basic reproduction number and elasticity coefficients are calculated at the equilibrium points. Then, some key critical model parameters are identified based on local sensitivities. In addition, the validation of the suggested model is checked by comparing some collected real data in Iraq and France from January 1st, 2021 to December 25th, 2021. Interestingly, there are good agreements between the model results and the real confirmed data using computational simulations in MATLAB. Results provide some biological interpretations and they can be used to control this pandemic more effectively. The model results will be used for both countries in minimizing the impact of this virus on their communities.","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"2672 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84648816","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}
J. Calvo-Guirado, Nuria García Carrillo, Félix de Carlos-Villafranca, M. Garcés-Villalá, L. Mahesh, J. Ibáñez, F. Martínez-Martínez
The study's main objective was to evaluate the bone density and osseointegration around dental implants with two different implant surfaces with early loading, using a micro-CT device. Twenty-four Fixo® implants (Oxyimplant, Biomec Italy) 3.5 × 8.5 mm with Laser (test group) and acid-etched surface (control group) were placed in six young beagle dog's mandibles. MicroCT (Albira, Germay) evaluation with seven regions of interest was defined in each implant on two different surfaces. A total of 168 sites were studied, and four isocountours were also done in each implant at coronal, transversal, and sagittal scanned areas to evaluate bone density location. The effect on the bone evaluation of two different surfaces variables was evaluated at the mesial and distal positions, showing crestal, medial, and apical types of bone density. Implant positions (P2, P3, P4, and M1) were also analyzed to determine bone density areas. The results of hard tissue density indicated a statistical significance for laser surface at crestal ROIs level (p < 0.001) and position of implants (p = 0.032) related to P3 areas compared to the acid-etched surface in Fixo® implants. Density D4 was the most common type of bone surrounding Fixo® standard implants at three different positions and density D3 was the most found on Fixo® laser surfaces. Micro-CT evaluation was a powerful tool for measuring the type of bone quality and location surrounding dental implants. Micro-CT study revealed that the most common density type found around Fixo® laser surface (test) implants was density D3 at the mesial and distal coronal part and density D4 at the middle and apical part. Fixo® implant with acid-etched surface showed the type of density D4 bone in hole implant at 3 months follow-up. It is a complementary histologic and histomorphometric analysis method for implant surrounding bone density.
{"title":"A micro-CT evaluation of bone density around two different types of surfaces on one-piece fixo implants with early loading-an experimental study in dogs at 3 months","authors":"J. Calvo-Guirado, Nuria García Carrillo, Félix de Carlos-Villafranca, M. Garcés-Villalá, L. Mahesh, J. Ibáñez, F. Martínez-Martínez","doi":"10.3934/bioeng.2022028","DOIUrl":"https://doi.org/10.3934/bioeng.2022028","url":null,"abstract":"The study's main objective was to evaluate the bone density and osseointegration around dental implants with two different implant surfaces with early loading, using a micro-CT device. Twenty-four Fixo® implants (Oxyimplant, Biomec Italy) 3.5 × 8.5 mm with Laser (test group) and acid-etched surface (control group) were placed in six young beagle dog's mandibles. MicroCT (Albira, Germay) evaluation with seven regions of interest was defined in each implant on two different surfaces. A total of 168 sites were studied, and four isocountours were also done in each implant at coronal, transversal, and sagittal scanned areas to evaluate bone density location. The effect on the bone evaluation of two different surfaces variables was evaluated at the mesial and distal positions, showing crestal, medial, and apical types of bone density. Implant positions (P2, P3, P4, and M1) were also analyzed to determine bone density areas. The results of hard tissue density indicated a statistical significance for laser surface at crestal ROIs level (p < 0.001) and position of implants (p = 0.032) related to P3 areas compared to the acid-etched surface in Fixo® implants. Density D4 was the most common type of bone surrounding Fixo® standard implants at three different positions and density D3 was the most found on Fixo® laser surfaces. Micro-CT evaluation was a powerful tool for measuring the type of bone quality and location surrounding dental implants. Micro-CT study revealed that the most common density type found around Fixo® laser surface (test) implants was density D3 at the mesial and distal coronal part and density D4 at the middle and apical part. Fixo® implant with acid-etched surface showed the type of density D4 bone in hole implant at 3 months follow-up. It is a complementary histologic and histomorphometric analysis method for implant surrounding bone density.","PeriodicalId":45029,"journal":{"name":"AIMS Bioengineering","volume":"43 1","pages":""},"PeriodicalIF":2.3,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79884227","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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