ABSTRACT
ObjectiveTo investigate the disease progression and immunoprotective characteristics in mice re-infected with homogeneous/heterogeneous Plasmodium strains following cure of Plasmodium infections with chloroquine at the peak of parasitemia. MethodsC57BL/6 mice were infected with the non-lethal P. yoelii 17XNL strain, and half of mice were given treatment with chloroquine at the peak of parasitemia (9 days post-infection), while the other mice were self-cured naturally. Then, all cured mice were re-infected with the equivalent lethal P. yoelii 17XL or P. berghei ANKA strain 90 days following primary Plasmodium infections. The parasitemia levels during primary infections and reinfections were measured by microscopic examinations of Giemsa-stained thin blood films, and the levels of the IgG antibody in sera and the percentages of memory T cell subsets in spleen cells were detected in mice using ELISA and flow cytometry before and after parasite reinfections, respectively. Results Following primary infections with the P. yoelii 17XNL strain, the serum IgG antibody levels were (5.047 ± 0.924) pg/mL in the selfcured mice and (4.429 ± 0.624) pg/mL in the chloroquine-treated mice, respectively (t = 0.437, P > 0.05), which were both significantly higher than that in the uninfected mice (1.624 pg/mL ± 0.280 pg/mL) (F = 22.522, P < 0.01). There was no significant difference in the serum IgG antibody level among self-cured and chloroquine-treated mice re-infected with the P. yoelii 17XL strain or the P. berghei ANKA strain (F = 0.542, P > 0.05); however, the serum IgG antibody levels were all significantly higher in selfcured and chloroquine-treated mice re-infected with the P. yoelii 17XLstrain[(15.487±1.173)pg/mLand(15.965±1.150)pg/mL] or the P. berghei ANKA strain [(14.644 ± 1.523) pg/mL and (15.185 ± 1.333) pg/mL] relative to primary infections (F = 67.383, P < 0.01). There was no significant difference in the proportion of CD4+ [(34.208 ± 2.106), (32.820 ± 1.930), (34.023 ± 2.289), (35.608 ± 1.779) pg/mL] or CD8+ T memory cells [(17.935 ± 2.092), (18.918 ± 2.823), (17.103 ± 1.627), (17.873 ± 1.425) pg/mL] in self-cured and chloroquine-treated mice with primary infections with the P. yoelii 17XNL strain followed by re-infections with the P. yoelii 17XL strain or the P. berghei ANKA strain (F = 0.944 and 0.390, both P > 0.05); however, the proportions of the CD4+ or CD8+ T memory cells were significantly greater in self-cured and chloroquine-treated mice with primary infections with the P. yoelii 17XNL strain followed by re-infections with the P. yoelii 17XL strain or the P. berghei ANKA strain than in mice with primary infections (F = 50.532 and 21.751, both P < 0.01). Conclusions The cure of murine Plasmodium infections with chloroquine does not affect the production of effective immune protections in mice during parasite re-infections. Following a primary infection, mice show a protection against re-infections with either homogeneous or heterogeneous Plasmodium strains, and a higher-level resistance to re-infections with homogeneous parasite strains is found than with heterogeneous strains.
ABSTRACT
<p><b>OBJECTIVE</b>To construct a breast cancer gene-drug network model for extracting and predicting the correlations between breast cancer-related genes and drugs.</p><p><b>METHODS</b>We developed an algorithm based on the ABC principle and the association rules to obtain the correlations between the biological entities. For breast cancer, we constructed 3 different correlations (gene-gene, drug-drug and gene-drug) and used the R language to implement the associated network model. The reliability of the algorithm was verified by ROC curve.</p><p><b>RESULTS</b>We identified 185 breast cancer-associated genes and 98 associations between them, 97 drugs and 170 associations between them. The breast cancer genes-drugs network contained 127 genes and 77 drugs with 384 associations between them.</p><p><b>CONCLUSIONS</b>We identified a large number of different correlations between the breast cancer-related genes and drugs and close correlations between some biological entity pairs that have not yet been reported, which may provide a new strategy for experimental design for testing personalized breast cancer treatment.</p>