Team:CPU CHINA/ModelII
Abstract:
In this section, we build ODEs to model the growth of Mtb in vitro and in vivo. We firstly model the natural growth of Mtb in vitro and the growth of Mtb exposed to several antibacterial agents in vitro. We screen out Granulysin as the desirable candidate. Secondly we build an in vivo model, considering the dynamic infection and immune response of non-infected macrophages, infected macrophages , T cells and Mtb. Then we integrated experiment results into our model and evaluated the efficacy of our system.
Part I Modeling in vitro growth of Mtb
Here we build a simple growth model of Mtb in vitro at natural state and we model the growth of Mtb in vitro exposed to different anti-bacteria agents. We generate the candidate antibacterial agents set according to the feedback of HP that PI suggested us to use antimicrobial peptide. We collect Granulysin[1], Human Beta Defensins(HBD)[2],Protegrin1(PG-1)[2],D-V13K(D1-D5)[3] as candidate antibacterial peptide set.
We firstly build a simple in vitro growth model of Mtb at natural state, assuming that the growth of Mtb follows sigmoid growth curve, and we use following equation to model the growth of Mtb
,where N then equals
following literature[1-3], we set the the carrying capacity Nmax of Mtb to 10^8. Based on the fact that the CFU of Mtb double in every around 18hs, we calculate and set the intrinsic reproduction rate r=0.92 by set N to N2. We then simulate the natural in vivo growth of Mtb, shown in Figure.1
We found that the Mtb reached the carrying capacity in around 20 days without control. Next we consider the effect of antibacterial agents, assuming that the efficacy of an antibacterial agent at a certain amount is a constant, we extract the bacteria-killing constant of each candidate agent from literature and scale the coefficient (summarized in table 1).We found out that D-V13K(D2-D4) show no obvious antimicrobial effect and thus are removed before the simulation. In all, considering the effect of an antibacterial agent, the growth of Mtb N then equals the natural growth M minus the killed Mtb D.
See in Table 1 for coefficients
Figure.2 shows the living bacteria number Ni under the treatment of Granulysin, Human Beta Defensins(HBD) and Protegrin1(PG-1) with a dose of 10μg/ml. We found that the total number of Mtb treated with Granulysin was reduced the fastest and could be well controlled (less than 5%) in around 5 days while HBD takes around 7 days and PG-1 take even more time. Although the dose could be different, the relative bacteria-killing trend among these agents would stay the same, thus Granulysin is predicted to be the most efficient one. And we decide to choose Granulysin to be expressed.
Part II Modeling in vivo growth of Mtb
The Mtb bacteria usually develop pulmonary TB. After the entrance of the bacilli into the lung, phagocytosis of the bacteria by alveolar macrophages takes place and leads to the activation and recruitment of other immune cell mediated response. The specific immune response at the site of bacteria implantation results in the formation of local granulomas,an spherical structure composed of bacteria, macrophages, and other immune cells. Bacilli contained in the granuloma can remain or be reactivated later after increasing to a limit in which the macrophages burst,releasing more bacteria.
Here we propose a system of ordinary differential equations to model the interaction among non-infected macrophages, infected macrophages, T cells and Mtb bacilli.Model is based on previous work[5,6] and we improved the previous model dividing the bacteria population into intracellular bacteria and extracellular bacteria two parts due to the biological characteristic of Mtb. Cinical latency and active TB are characterized by the number of intracellular and extracellular bacteria, respectively. We try to minimum the number of variables describing the principal features of the cellular immunology against TB as much as possible in this model.
We assume that uninfected macrophages reproduce at constant rate αu , and die at a per capita constant rate µU.Uninfected macrophages get infected at a rate proportional to the product of MU and Bt, with constant of proportionality β, and once infected naturally die at per capita constant rate µI , where µI ≥ µU and get eliminated by T cells at a rate proportional to the product of Mi and Tc , with constant of proportionality ωT.
Mtb bacteria multiply inside an infected macrophage up to a limit at which the macrophage bursts, and releases bacteria. For this reason, the growth rate of Mtb bacteria is set as rextra and rintra ,where rintra is the average number of bacteria produced inside an infected macrophage and rextra is the growth rate of extracellular bacteria. The releasing bacteria become temporarily extracellular, and they infect macrophages, or are ingested and killed by uninfected macrophages at a rate proportional to the product of MU and Bi with constant of proportionality ωU . Mtb die at per capita rate µB.
In the presence of bacteria and infected macrophages, the supply of specific Tc is given by following formula
where rt is the growth rate of T cells, and Tmax is the maximum T cell population level. Finally, the T-cells die at per capita rate µT .
See parameters in Table.2
We explored the initial impact using the initial value Mu=100, Mi=0, B=100, Tc=1, Be=99, Bi=1,see results shown in following Figure5.1
And the recruited T cells number are shown in following Figure 5.2
In this step,we found out that while the growth rate, and death rate of Mtb bacteria play dominant role on the dynamics of the Mtb,the T cell recruit rate rt also interested us. In human body, this constant represents the effectiveness of the main body immunity.
We set different rt values and observed the corresponding responses, shown in following figures:
1)rt=0.008
A low T cell recruit rate constant represents a low effectiveness of the body immunity. And this lead the body lose control of Mtb with the characteristic of a crazily increasing amount of infected macrophages Mi and Mtb, which would finally result in an obvious symptom of active tuberculosis.
In this step,we found out that while the growth rate, and death rate of Mtb bacteria play dominant role on the dynamics of the Mtb,the T cell recruit rate rtis also one of the top sensitive parameters which interested us.
2)rt=0.08
Here,a certain amount of T cells have been recruited and the number of infected macrophages became stable one month after infection.However,the recruited T cells are not enough to eliminate most of infected macrophages,as well as Mtb.
3)rt=0.8
Here the simulation shows that the numbers of infected macrophages and T cells
reached a stable state around one month after infection. This means that the growth of in vitro Mtb is well controlled,while there did be a small amount of Mtb remained.
In this situation, individual could show no obvious symptom of tuberculosis, but rather be a carrier of mycobacterium tuberculosis, which is a latency disease mode.
In clinic, individuals infected with Mtb could exhibit a suppression response able to control infection (not clear it) and settle into a latent state,or a response that fails to suppress infection leading to acute, primary disease. Our modeling have revealed these two modes separated by the effectiveness of body immunity, to be specific, the T cell recruit rate in our model. This helped us gain insight on the dynamic process that how the Mtb grow inside human body and how immune system fight against it.
PartⅢ Modeling in vivo growth of Mtb under treatment
We then consider the granulysin effect by integrating following formula into our previous model
Where the constant μp is estimated from wet-lab granulysin time-kill experiment.
We then track the dynamic infection process with a initial situation of 100 Mtb infecting an individual with low T cell recruit rate(rt=0.008) . We simulated the infection at natural state(Fig.9) and state treated with our system(Fig.10).
Here,we found that while Mtb keep increasing during the infection without treatment, the number of Mtb under the treatment of our system rise only around the first 4 days, after which there would be a obvious decrease. This indicate us that our system is able to control in vivo growth of Mtb within a week. This convince us the effectiveness of our system and help us understand how our system effect the dynamic infection process focusing on in vivo growth of Mtb. Also our modeling has the potential to provide guidance on future clinical use of our immune-like cells, for instance giving suggestions on interval time.
Conclusion
Our in vivo model (PartⅡ) tried to balance between practicability and complexity. Comparing to existing published models, Christopher Kribs Zaleta et al[5] modeled cellular immunology in granuloma area, considering the population of uninfected macrophages, infected macrophages, Mtb bacteria, and T cells. In their model, in-vivo Mtb was only released by the burst of infected macrophages. While Abba Gumel et al[6] further considered the growth of Mtb outside macrophages based on their work, however, in their model the growth of two kinds of Mtb is not separated. In our model both intracellular and exracellular growth of Mtb are taken into consideration, thus our model(PartⅡ) meets the biological regulation better.
Plus Part Modeling in vivo growth of Mtb Advanced
# Note : This part is just for fun
Here we aim to describe the biological process of dynamic infection and immune response via a model that suits biological better,we use a model reported in literature[7],comparing to our previous model, this complex model further consider the differential of T helper cells, and update uninfected macrophages into resting macrophage and activated macrophages. The dynamic of cytokines is also considered.
Macrophages
Resting macrophages (MR) are less efficient in presenting Ag, phagocytizing and killing bacteria, and secreting cytokiness than activated macrophages. Resting macrophages can become activated in response to IFN-γ together with exposure to bacterial Ag. Resting macrophages can also become chronically infected.
Activated macrophages (MA)are effective at killing M.tuberculosis because they are more efficient at phagosome-lysosome fusion than resting macrophages. A macrophage is considered to be activated if it is in a state in which it can efficiently phagocytize and kill mycobacteria. The main cytokine that down-regulates activated macrophages is IL-10.It overrides the antimycobacterial effects of IFN-γ on macrophages. Activated macrophages deactivate over time when they are not given sufficient stimuli.
Infected macrophages(MI) contain a large a number of bacteria but have not received adequate stimuli for activation (facilitated by bacterial factors). Such macrophages eventually lose the capacity to become activated and thus are unable to clear their bacterial load and thus to be the key reservoir for M. tuberculosis. The relationships are shown in Figure.11,and formulas are shown in
Cytokines
IL-10,IL-12,IL-4,IFN-γ are four key cytokines that play a key role in the course of human TB, principally effecting cellular activation, deactivation, and differentiation.
For details:
IL-10 is produced primarily by macrophages and Th2 lymphocytesin. IL-10 plays essential roles in down-regulating an active immune response in TB, including deactivation of macrophages , inhibition of T cell proliferation , and suppression of cytokine production by T lymphocytes.
IL-12 is a key Th1-type cytokine produced by activated and infected macrophages in response to Mtb stimulation,IL-12 can induce the differentiation of Th0 lymphocytes to Th1 lymphocytes, also by enhance the production of IFN-γ. Macrophage production of IL-12 is considerably enhanced when the macrophage is primed with IFN-γ ; however, production is simultaneously inhibited by IL-10 .
IL-4 governs the differentiation of Th0 cells to Th2 cells. The role of IL-4 in the immune response to TB is controversial. It is involved in down-regulating and opposing the development of a Th1-type cell response by inhibitingTh0 to Th1 differentiation .
IFN-γ is key to the development of an effective cell-mediated response to M. tuberculosis.IFN-γ activates resting macrophages, enhancing their ability to effectively clear pathogens and also to release cytokines . IFN-γ is also involved in the process of T cell differentiation by enhancing the rate of Th0 to Th1 differentiation and by overriding opposition by IL-4 to this process .
.
T helper cells
CD41 T lymphocytes is considered to produce cytokines that govern the cell-mediated immune response and eliminat the infected macrophages via apoptosis.
Mtb
Mtb is divided into extracellular or intracellular status.
All the coefficients are shown in following table
In the highly complex cytokine feedback system, some cytokines oppose each other.Three general types of parameters are estimated for each: a maximum rate;a half-saturation constant; and a relative effect parameter.Maximal rates (k6, k7, k3) describe the limiting rate of a process when given maximal stimulation. They are equivalent to the standard Vmax from Michaelis-Menten kinetics.Half-saturation constants (s1–s6) are equivalent to the standard km in Michaelis-Menten kinetics. These values are equal to the concentration of the stimulatory cytokine where the associated rate is halfmaximal .Relative effect parameters (f1–f6) adjust for these difference in values,and are scaled for the inhibitory cytokine in each case. Ratios are estimated from cytokine assays of pleural or BAL fluid.
We found that this model at the given initial value is unstable shown in Figure15.1 and Figure15.2,the reason could be a sudden rise of IFN-γ. Still, this is a simple exploration following published models.
This virtual model could simulate general human cell-mediated immune response to infection.
References
[1] Stenger, & S. (1998). An antimicrobial activity of cytolytic t cells mediated by granulysin. Science, 282(5386), 121-125.
[2] Fattorini, L. , Gennaro, R. , Zanetti, M. , Tan, D. , Brunori, L. , & Giannoni, F. , et al. (2004). in vitro activity of protegrin-1 and beta-defensin-1, alone and in combination with isoniazid, against mycobacterium tuberculosis. Peptides (New York),25(7), 0-1077.
[3] Jiang, Z., Higgins, M. P., Whitehurst, J., Kisich, K. O., Voskuil, M. I., & Hodges, R. S. (2011). Anti-tuberculosis activity of α-helical antimicrobial peptides: de novo designed L- and D-enantiomers versus L- and D-LL-37. Protein and peptide letters, 18(3), 241–252. doi:10.2174/092986611794578288
[4] T. Ulrischs and S. Kaufmann, Cell mediated immune response in Tuberculosis, first edition,
[5] Lippincott Williams and Wilkins, New York, 2004 Ibarguen-Mondragon, E. , Esteva, L. , & Chávez-Galán, Leslie. (2011). A mathematical model for cellular immunology of tuberculosis. MATHEMATICAL BIOSCIENCES AND ENGINEERING, 8(4), 973-986.
[6] Burbano-Rosero, E. M. , Esteva, L. , & Eduardo Ibargüen-Mondragón. (2017). Mathematical model for the growth of mycobacterium tuberculosis in the granuloma. Mathematical Biosciences and Engineering, 15(2), 407-428.
[7] Wigginton, J. E. , & Kirschner, D. . (2001). A model to predict cell-mediated immune regulatory mechanisms during human infection with mycobacterium tuberculosis. The Journal of Immunology, 166(3), 1951-1967.
[8] Koppensteiner, H. , Brack-Werner, R. , & Schindler, M. . (2012). Macrophages and their relevance in human immunodeficiency virus type i infection. Retrovirology, 9(1).
[9] Murphy, J. , Summer, R. , Wilson, A. A. , Kotton, D. N. , & Fine, A. . (2008). The prolonged life-span of alveolar macrophages. American Journal of Respiratory Cell and Molecular Biology, 38(4), 380-385.
[10] Sud, D. , Bigbee, C. , Flynn, J. L. , & Kirschner, D. E. . (2006). Contribution of cd8+ t cells to control of mycobacterium tuberculosis infection. The Journal of Immunology, 177(8), 5747-5747.
[11] Ibarguen-Mondragon, E. , Esteva, L. , & Chávez-Galán, Leslie. (2011). A mathematical model for cellular immunology of tuberculosis. MATHEMATICAL BIOSCIENCES AND ENGINEERING, 8(4), 973-986.
[12] Marino, S. , & Kirschner, D. E. . (2004). The human immune response to mycobacterium tuberculosis in lung and lymph node. Journal of Theoretical Biology, 227(4), 463-486.
[13] Wigginton, J. E. , & Kirschner, D. . (2001). A model to predict cell-mediated immune regulatory mechanisms during human infection with mycobacterium tuberculosis. The Journal of Immunology, 166(3), 851-867.
[14] Li, Q. , Whalen, C. C. , Albert, J. M. , Larkin, R. , Zukowski, L. , & Cave, M. D. , et al. (2002). Differences in rate and variability of intracellular growth of a panel of mycobacterium tuberculosis clinical isolates within a human monocyte model. Infection & Immunity, 70(11), 6489.
[15] Zhang, M. , Gong, J. , Yang, Z. , Samten, B. , Cave, M. ?. , & Barnes, P. . (899). Enhanced capacity of a widespread strain of\r, mycobacterium tuberculosis\r, to grow in human macrophages. The Journal of Infectious Diseases, 179(5), 1211-1217.
[16] Zhang, Y. , Dhandayuthapani, S. , & Deretic, V. . (896). Molecular basis for the exquisite sensitivity of mycobacterium tuberculosis to isoniazid. Proceedings of the National Academy of Sciences, 93(9), 11212-11216.
[17] Cooper, & Andrea, M. . (1409). Cell-mediated immune responses in tuberculosis. Annual Review of Immunology, 27(1), 163-412.
Plus Part References
[103] Cheong, Y. C., & Ledger, W. L. (2003). Cytokines in health and disease. Obstetrician & Gynaecologist, 5(3), 155-159.
[101]Huhn, R. D. , Radwanski, E. , O'Connell, S. M. , Sturgill, M. G. , & Cutler, D. L. . (1996). Pharmacokinetics and immunomodulatory properties of intravenously administered recombinant human interleukin-10 in healthy volunteers. Blood, 87(2), 699-705.
[102] Huhn, R. D. , Radwanski, E. , Gallo, J. , Affrime, M. B. , Sabo, R. , & Gonyo, G. , et al. (1997). Pharmacodynamics of subcutaneous recombinant human interleukin‐10 in healthy volunteers. Clinical Pharmacology & Therapeutics, 62.
[127] Kurzrock, R. , Rosenblum, M. G. , Sherwin, S. A. , Rios, A. , Talpaz, M. , & Quesada, J. R. , et al. (2009). Pharmacokinetics, single-dose tolerance, and biological activity of recombinant gamma-interferon in cancer patients. Oncology, 42(1), 41-50.
[104] Silver, R. F., Li, Q., & Ellner, J. J. (1998). Expression of virulence of mycobacterium tuberculosiswithin human monocytes: virulence correlates with intracellular growth and induction of tumor necrosis factor alpha but not with evasion of lymphocyte-dependent monocyte effector functions. Infection & Immunity, 66(3), 1190-9.
[105] Silver, R. F. , Li, Q. , Boom, W. H. , & Ellner, J. J. . (1998). Lymphocyte-dependent inhibition of growth of virulent mycobacterium tuberculosis h37rv within human monocytes: requirement for cd4+ t cells in purified protein derivative-positive, but not in purified protein derivative-negative subjects. Journal of Immunology, 160(5), 2408.
[107] Manca, C. , Tsenova, L. , & Barry, C. . (1999). mycobacterium tuberculosis cdc1551 induces a more vigorous host response in vivo and in vitro, but is not more virulent than other clinical isolates. Journal of Immunology, 162(11), 6740-6746.
[108] Paul, S. , Laochumroonvorapong, P. , & Kaplan, G. . (1996). Comparable growth of virulent and avirulent mycobacterium tuberculosis in human macrophages in vitro. Journal of Infectious Diseases, 174(1), 105-112.
[128] Zhang, M. , Gong, J. , Yang, Z. , Samten, B. , Cave, M. ?. , & Barnes, P. . (1999). Enhanced capacity of a widespread strain of\r, mycobacterium tuberculosis\r, to grow in human macrophages. The Journal of Infectious Diseases, 179(5), 1213-1217.
[109] North, & R., J. . (1993). Mycobacterial virulence. virulent strains of mycobacteria tuberculosis have faster in vivo doubling times and are better equipped to resist growth-inhibiting functions of macrophages in the presence and absence of specific immunity. Journal of Experimental Medicine, 177(6), 1723-1733.
[50]Barnes, P. F. , Lu, S. , Abrams, J. S. , Wang, E. , Yamamura, M. , & Modlin, R. L. . (1993). Cytokine production at the site of disease in human tuberculosis. Infection & Immunity, 61(8), 3482-9.
[51]Tsukaguchi, K. , Lange, B. D. , & Boom, W. H. . (1999). Differential regulation of ifn-gamma, tnf-alpha, and il-10 production by cd4(+) alphabetatcr+ t cells and vdelta2(+) gammadelta t cells in response to monocytes infected with mycobacterium tuberculosis-h37ra. Cellular Immunology, 194(1), 12.
[56] Fulton, S. A. , Cross, J. V. , Toossi, Z. T. , & Boom, W. H. . (1998). Regulation of interleukin-12 by interleukin-10, transforming growth factor-beta, tumor necrosis factor-alpha, and interferon-gamma in human monocytes infected with mycobacterium tuberculosis h37ra. Journal of Infectious Diseases, 178(4), 1105-1114.
[60] Chensue, S. W. , Ruth, J. H. , Warmington, K. , Lincoln, P. , & Kunkel, S. L. . (1995). in vivo regulation of macrophage il-12 production during type 1 and type 2 cytokine-mediated granuloma formation. The Journal of Immunology, 155(7), 3546-3551.
[79] Zhang, M. , Lin, Y. G. , Iyer, D. V. , Gong, J. H. , & Barnes, P. F. . (1995). T-cell cytokine responses in human infection with mycobacterium tuberculosis. Infection and Immunity, 63(8), 3231-3234.
[111] Zhang, M. ,., Gately, M. K., Wang, E. ,., Gong, J. ,., Wolf, S. F., & Lu, S. ,., et al. (1994). Interleukin 12 at the site of disease in tuberculosis. Journal of Clinical Investigation, 93(4), 1733-9.
[16] Tsukaguchi, K. , Balaji, K. N. , & Boom, W. H. . (1995). Cd4+ alpha beta t cell and gamma delta t cell responses to mycobacterium tuberculosis. similarities and differences in ag recognition, cytotoxic effector function, and cytokine production. Journal of Immunology, 154(4), 1786-1796.
[53] Meyaard, L. , Hovenkamp, E. , Otto, S. A. , & Miedema, F. . (1996). Il-12-induced il-10 production by human t cells as a negative feedback for il-12-induced immune responses. The Journal of Immunology, 156(8), 2776-2782.
[55] Yssel, H. , {De Waal Malefyt, R, Roncarolo, M. G. , Abrams, J. S. , Lahesmaa, R. , & Spits, H. , et al. (1992). Il-10 is produced by subsets of human cd4+ t cell clones and peripheral blood t cells. Journal of immunology (Baltimore, Md. : 1950), 149(7), 2378-2384.
[59] Isler, P. , de Rochemonteix, B. G. , Songeon, F. , Boehringer, N. , & Nicod, L. P. . (1999). Interleukin-12 production by human alveolar macrophages is controlled by the autocrine production of interleukin-10. American Journal of Respiratory Cell & Molecular Biology, 20(2), 270.
[16] Tsukaguchi, K. , Balaji, K. N. , & Boom, W. H. . (1995). Cd4+ alpha beta t cell and gamma delta t cell responses to mycobacterium tuberculosis. similarities and differences in ag recognition, cytotoxic effector function, and cytokine production. Journal of Immunology, 154(4), 1786-1796.
[129] Westermann, J. , & Pabst, R. . (1992). Distribution of lymphocyte subsets and natural killer cells in the human body. The Clinical Investigator, 70(7), 539-544.
[64] O'Donnell, M. A. , Luo, Y. , Chen, X. H. , Szilvasi, A. , & Clinton, S. K. . (1999). Role of il-12 in the induction and potentiation of ifn-γ in response to bacillus calmette-guerin. The Journal of Immunology, 163(8), 4246-4252.
[112] D"Andrea, & A. (1993). Interleukin 10 (il-10) inhibits human lymphocyte interferon gamma- production by suppressing natural killer cell stimulatory factor/il-12 synthesis in accessory cells. Journal of Experimental Medicine, 178(3), 1041-1048.
[130] Chomarat, & P. (1993). Interferon gamma inhibits interleukin 10 production by monocytes. Journal of Experimental Medicine, 177(2), 523-527.
[37] Flesch, I. E. A. , & Kaufmann, S. H. E. . (1990). Activation of tuberculostatic macrophage functions by gamma interferon, interleukin-4, and tumor necrosis factor. Infection and Immunity, 58(8), 2675-2677.
[58] Fulton, S. A. , Johnsen, J. M. , Wolf, S. F. , Sieburth, D. S. , & Boom, W. H. . (1996). Interleukin-12 production by human monocytes infected with mycobacterium tuberculosis: role of phagocytosis. Infection and Immunity, 64(7), 2523-2531.
[131] Sadek, M. I. , Sada, E. , Toossi, Z. , Schwander, S. K. , & Rich, E. A. . (1998). Chemokines induced by infection of mononuclear phagocytes with mycobacteria and present in lung alveoli during active pulmonary tuberculosis. American Journal of Respiratory Cell and Molecular Biology, 19(3), 513-521.
[67]Law, K. , Weiden, M. , Harkin, T. , Tchouwong, K. , Chi, C. , & Rom, W. N. . (1996). Increased release of interleukin-1 beta, interleukin-6, and tumor necrosis factor-alpha by bronchoalveolar cells lavaged from involved sites in pulmonary tuberculosis. Am J Respir Crit Care Med, 153(2), 799-804.
[68]Condos, R. , Rom, W. , Liu, Y. , & Schluger, N. . (1998). Local immune responses correlate with presentation and outcome in tuberculosis. American Journal of Respiratory and Critical Care Medicine, 157(3), 729-735.
[69]Antony, V. B. , Godbey, S. W. , Kunkel, S. L. , Hott, J. W. , Hartman, D. L. , & Burdick, M. D. , et al. (1993). Recruitment of inflammatory cells to the pleural space. chemotactic cytokines, il-8, and monocyte chemotactic peptide-1 in human pleural fluids. Journal of Immunology, 151(12), 7216-7223.
[70]Stephan K. Schwander, Torres, M. , Sada, E. , Carranza, C. , & Rich, E. A. . (1998). Enhanced responses to mycobacterium tuberculosis antigens by human alveolar lymphocytes during active pulmonary tuberculosis. The Journal of Infectious Diseases, 178(5), 1434-1445.
[117]Meddowstaylor, S. , Martin, D. J. , & Tiemessen, C. T. . (1999). Dysregulated Production of Interleukin-8 in Individuals Infected with Human Immunodeficiency Virus Type 1 and. University of Indianapolis. Betascript Publishing.
[132]Furth, V. , & R. (1973). Quantitative study on the production and kinetics of mononuclear phagocytes during an acute inflammatory reaction. Journal of Experimental Medicine, 138(6), 1314-1330.
[114]Sprent, J. , & Basten, A. . (1973). Circulating t and b lymphocytes of the mouse: ii. lifespan. Cellular Immunology, 7(1), 0-59.
[8]Assenmacher, M. , M Löhning, Scheffold, A. , Richter, A. , Miltenyi, S. , & Schmitz, J. , et al. (1998). Commitment of individual th1-like lymphocytes to expression of ifn-gamma versus il-4 and il-10: selective induction of il-10 by sequential stimulation of naive th cells with il-12 and il-4. Journal of Immunology, 161(6), 2825-2832.
[62]Sornasse, T. , Larenas, P. V. , Davis, K. A. , Vries, J. E. D. , & Yssel, H. . (1996). Differentiation and stability of t helper 1 and 2 cells derived from naive human neonatal cd4+ t cells, analyzed at the single-cell level. Journal of Experimental Medicine, 184(2), 473-483.
[20]Rojas, M. , Olivier, M. , Gros, P. , Barrera, L. F. , & Luis F. García. (1999). Tnf-α and il-10 modulate the induction of apoptosis by virulent mycobacterium tuberculosis in murine macrophages. Journal of Immunology, 162(10), 6122.
[13]Oddo, M. , Renno, T. , Attinger, A. , Bakker, T. , & Meylan, P. R. A. . (1998). Fas ligand induced apoptosis of infected human macrophages reduces the viability of intracellular mycobacterium tuberculosis. The Journal of Immunology, 160(11), 5448-5454.
[14]Lewinsohn, D. M. , Bement, T. T. , Xu, J. , Lynch, D. H. , Grabstein, K. H. , & Reed, S. G. , et al. (1998). Human purified protein derivative-specific cd4+ t cells use both cd95-dependent and cd95-independent cytolytic mechanisms. Journal of Immunology, 160(5), 2374-9.
[15]Tan, J. S. , Canaday, D. H. , Boom, W. H. , Balaji, K. N. , Schwander, S. K. , & Rich, E. A. . (1997). Human alveolar t lymphocyte responses to mycobacterium tuberculosis antigens: role for cd4+ and cd8+ cytotoxic t cells and relative resistance of alveolar macrophages to lysis. Journal of Immunology, 159(1), 290-7.
[16]Tsukaguchi, K. , Balaji, K. N. , & Boom, W. H. . (1995). Cd4+ alpha beta t cell and gamma delta t cell responses to mycobacterium tuberculosis. similarities and differences in ag recognition, cytotoxic effector function, and cytokine production. Journal of Immunology, 154(4), 1786-1796.
[120]Rojas, M. , Barrera, L. F. , Puzo, G. , & Garcia, L. F. . (1997). Differential induction of apoptosis by virulent mycobacterium tuberculosis in resistant and susceptible murine macrophages: role of nitric oxide and mycobacterial products. Journal of immunology (Baltimore, Md. : 1950), 159(3), 1352-1361.
[126]Balcewicz-Sablinska, M. K. , & Remold, H. X. G. G. . (1999). Interleukin 10 produced by macrophages inoculated with mycobacterium avium attenuates mycobacteria-induced apoptosis by reduction of tnf-α activity. The Journal of Infectious Diseases, 180(4), 1230-1237.
[106]Zhang, M. , Gong, J. , Lin, Y. , & Barnes, P. F. . (1998). Growth of virulent and avirulent mycobacterium tuberculosis strains in human macrophages. Infection and Immunity, 66(2).
[125]Hirsch, C. S. , Ellner, J. J. , Russell, D. G. , & Rich, E. A. . (1994). Complement receptor-mediated uptake and tumor necrosis factor-alpha-mediated growth inhibition of mycobacterium tuberculosis by human alveolar macrophages. Journal of Immunology, 152(2), 743.