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10.1134/S0006350921020160 http://scihub22266oqcxt.onion/10.1134/S0006350921020160 34230672!8252696!34230672     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biophysics+(Oxf) 2021 ; 66 (2): 327-348 Nephropedia Template TP {{tp|p=34230672|t=2021. A Continuous Model of Three Scenarios of the Infection Process with Delayed Immune Response Factors |pdf=|usr=}}{{34230672}} gab.com Text A Continuous Model of Three Scenarios of the Infection Process with Delayed Immune Response Factors JO: Biophysics (Oxf) http://www.kidney.de/pget.php?&tw=1&pmid=34230672 #FOAvip The course of an infection was modeled as a controlled nonlinear process. Understanding the substantial differences observed in the trajectory of the disease caused by the new coronavirus SARS-CoV-2 is of critical importance at the moment. Numerous factors have been considered to explain the fact that symptoms vary highly among different people and the infection transmission rate varies among local populations. Virus replication within the host cell and the development of an immune response to virus antigens in the body are two interdependent processes, which have aftereffects and depend on the preexisting states of the cell and virus populations. Different scenarios with the same input parameters are necessary to consider for modeling the properties of the states. The efficiency of the immune response is the most important factor, including the time it takes to develop defense responses from three levels of the immune system, which is a complex system of the body. A computational description of infection scenarios was proposed on the basis of a delay differential equation with two values of the time lag. In the new model, transitions between phases of infectious disease depend on the initial virus dose and the delayed immune response to infection. A variation in the dose of the virus and response time can lead to a transition from an acute phase of the disease with overt symptoms to a chronic phase or fatal outcome. Asymptomatic transmission of viral infection was calculated and described in the model as a situation where the virus is rapidly and efficiently suppressed after a short replication phase, while still persisting in the body in minor amounts. An analysis of the model behavior is consistent with the theory that the initial number of virions can affect the quality of the immune response. The reasons that high individual differences are observed in the trajectory of COVID-19 disease and the formation of types of the immune response to coronavirus are still poorly understood. Known trajectories of hepatitis C virus (HCV) infection were used as a basis for model scenarios. Twit Text FOAVip A Continuous Model of Three Scenarios of the Infection Process with Delayed Immune Response Factors ????Biophysics (Oxf) http://www.kidney.de/pget.php?&tw=1&pmid=34230672 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34230672 #FOAvip English Wikipedia <ref>{{Cite pmid|34230672}}</ref> A Continuous Model of Three Scenarios of the Infection Process with Delayed Immune Response Factors #MMPMID34230672 Perevaryukha AY Biophysics (Oxf) 2021[]; 66 (2): 327-348 PMID34230672show ga The course of an infection was modeled as a controlled nonlinear process. Understanding the substantial differences observed in the trajectory of the disease caused by the new coronavirus SARS-CoV-2 is of critical importance at the moment. Numerous factors have been considered to explain the fact that symptoms vary highly among different people and the infection transmission rate varies among local populations. Virus replication within the host cell and the development of an immune response to virus antigens in the body are two interdependent processes, which have aftereffects and depend on the preexisting states of the cell and virus populations. Different scenarios with the same input parameters are necessary to consider for modeling the properties of the states. The efficiency of the immune response is the most important factor, including the time it takes to develop defense responses from three levels of the immune system, which is a complex system of the body. A computational description of infection scenarios was proposed on the basis of a delay differential equation with two values of the time lag. In the new model, transitions between phases of infectious disease depend on the initial virus dose and the delayed immune response to infection. A variation in the dose of the virus and response time can lead to a transition from an acute phase of the disease with overt symptoms to a chronic phase or fatal outcome. Asymptomatic transmission of viral infection was calculated and described in the model as a situation where the virus is rapidly and efficiently suppressed after a short replication phase, while still persisting in the body in minor amounts. An analysis of the model behavior is consistent with the theory that the initial number of virions can affect the quality of the immune response. The reasons that high individual differences are observed in the trajectory of COVID-19 disease and the formation of types of the immune response to coronavirus are still poorly understood. Known trajectories of hepatitis C virus (HCV) infection were used as a basis for model scenarios. äA Continuous Model of Three Scenarios of the Infection Process with De(epmc).pdf DeepDyve Pubget Overpricing