3 research outputs found
Mathematical model of interactions immune system with Micobacterium tuberculosis
Tuberculosis (TB) remains a public health problem in the world, because of the increasing prevalence and treatment outcomes are less satisfactory. About 3 million people die each year and an estimated one third of the world's population infected with Mycobacterium Tuberculosis (M.tb) is latent. This is apparently related to incomplete understanding of the immune system in infection M.tb. When this has been known that immune responses that play a role in controlling the development of M.tb is Macrophages, T Lymphocytes and Cytokines as mediators. However, how the interaction between the two populations and a variety of cytokines in suppressing the growth of Mycobacterium tuberculosis germ is still unclear. To be able to better understand the dynamics of infection with M tuberculosis host immune response is required of a model.One interesting study on the interaction of the immune system with M.tb mulalui mathematical model approach. Mathematical model is a good tool in understanding the dynamic behavior of a system. With the mediation of mathematical models are expected to know what variables are most responsible for suppressing the growth of Mycobacterium tuberculosis germ that can be a more appropriate approach to treatment and prevention target is to develop a vaccine. This research aims to create dynamic models of interaction between macrophages (Macrophages resting, macrophages activated and macrophages infected), T lymphocytes (CD4 + T cells and T cells CD8 +) and cytokine (IL-2, IL-4, IL-10,IL-12,IFN-dan TNF-) on TB infection in the lung. To see the changes in each variable used parameter values derived from experimental literature. With the understanding that the variable most responsible for defense against Mycobacterium tuberculosis germs, it can be used as the basis for the development of a vaccine or drug delivery targeted so hopefully will improve the management of patients with tuberculosis. Mathematical models used in building Ordinary Differential Equations (ODE) in the form of differential equation systems Non-linear first order, the equation contains the functions used in biological systems such as the Hill function, Monod function, Menten- Kinetic Function. To validate the system used 4th order Runge Kutta method with the help of software in making the program Matlab or Maple to view the behavior and the quantity of cells of each population
Ultrasensitive detection of toxocara canis excretory-secretory antigens by a nanobody electrochemical magnetosensor assay.
peer reviewedHuman Toxocariasis (HT) is a zoonotic disease caused by the migration
of the larval stage of the roundworm Toxocara canis in the human host.
Despite of being the most cosmopolitan helminthiasis worldwide, its
diagnosis is elusive. Currently, the detection of specific immunoglobulins
IgG against the Toxocara Excretory-Secretory Antigens (TES), combined
with clinical and epidemiological criteria is the only strategy to diagnose
HT. Cross-reactivity with other parasites and the inability to distinguish
between past and active infections are the main limitations of this
approach. Here, we present a sensitive and specific novel strategy to
detect and quantify TES, aiming to identify active cases of HT. High
specificity is achieved by making use of nanobodies (Nbs), recombinant
single variable domain antibodies obtained from camelids, that due to
their small molecular size (15kDa) can recognize hidden epitopes not
accessible to conventional antibodies. High sensitivity is attained by the
design of an electrochemical magnetosensor with an amperometric readout
with all components of the assay mixed in one single step. Through
this strategy, 10-fold higher sensitivity than a conventional sandwich
ELISA was achieved. The assay reached a limit of detection of 2 and15
pg/ml in PBST20 0.05% or serum, spiked with TES, respectively. These
limits of detection are sufficient to detect clinically relevant toxocaral
infections. Furthermore, our nanobodies showed no cross-reactivity
with antigens from Ascaris lumbricoides or Ascaris suum. This is to our
knowledge, the most sensitive method to detect and quantify TES so far,
and has great potential to significantly improve diagnosis of HT. Moreover,
the characteristics of our electrochemical assay are promising for the
development of point of care diagnostic systems using nanobodies as a
versatile and innovative alternative to antibodies. The next step will be the
validation of the assay in clinical and epidemiological contexts