34 research outputs found
Formulation of a mmaA4 Gene Deletion Mutant of Mycobacterium bovis BCG in Cationic Liposomes Significantly Enhances Protection against Tuberculosis
A new vaccination strategy is urgently needed for improved control of the global tuberculosis (TB) epidemic. Using a mouse aerosol Mycobacterium tuberculosis challenge model, we investigated the protective efficacy of a mmaA4 gene deletion mutant of Mycobacterium bovis BCG (ΔmmaA4BCG) formulated in dimethyl dioctadecyl ammonium bromide (DDA) – D(+) trehalose 6,6 dibenenate (TDB) (DDA/TDB) adjuvant. In previous studies, deletion of the mmaA4 gene was shown to reduce the suppression of IL-12 production often seen after mycobacterial infections. While the non-adjuvanted ΔmmaA4BCG strain did not protect mice substantially better than conventional BCG against a tuberculous challenge in four protection experiments, the protective responses induced by the ΔmmaA4BCG vaccine formulated in DDA/TDB adjuvant was consistently increased relative to nonadjuvanted BCG controls. Furthermore, the ΔmmaA4BCG-DDA/TDB vaccine induced significantly higher frequencies of multifunctional (MFT) CD4 T cells expressing both IFNγ and TNFα (double positive) or IFNγ, TNFα and IL-2 (triple positive) than CD4 T cells derived from mice vaccinated with BCG. These MFT cells were characterized by having higher IFNγ and TNFα median fluorescence intensity (MFI) values than monofunctional CD4 T cells. Interestingly, both BCG/adjuvant and ΔmmaA4BCG/adjuvant formulations induced significantly higher frequencies of CD4 T cells expressing TNFα and IL-2 than nonadjuvanted BCG or ΔmmaA4BCG vaccines indicating that BCG/adjuvant mixtures may be more effective at inducing central memory T cells. Importantly, when either conventional BCG or the mutant were formulated in adjuvant and administered to SCID mice or immunocompromised mice depleted of IFNγ, significantly lower vaccine-derived mycobacterial CFU were detected relative to immunodeficient mice injected with non-adjuvanted BCG. Overall, these data suggest that immunization with the ΔmmaA4BCG/adjuvant formulation may be an effective, safe, and relatively inexpensive alternative to vaccination with conventional BCG
Orographic Effects of the Tibetan Plateau on the East Asian Summer Monsoon: An Energetic Perspective
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
Median fluorescence intensity (MFI) of (A) IFNγ or (B) TNFα in monofunctional or multifunctional CD8 T cells.
<p>The data are presented as the mean of individual MFI values for 4–5 mice per vaccine group. *Statistical significance relative to monofunctional cytokine expressing cells, <i>p</i><0.05. <sup>#</sup> Significant differences relative to BCG in the same T cell subset, p<0.05.</p
Muliparameter flow cytometry was used to determine the frequency (%) of (A) monofunctional CD4 T cells producing only IFNγ, TNFα, or IL-2 or (B) CD4 MFT cells producing both IFNγ and TNFα, IFNγ and IL-2, TNFα and IL-2 or all three cytokines from naïve or vaccinated mice.
<p>Splenocytes from three to five unchallenged mice per group were analyzed separately for these experiments. * Significant differences relative to naïve controls (<i>p</i><0.05). <sup>#</sup> Significant differences compared to BCG-vaccinated mice (<i>p</i><0.05).</p
Protection in C57BL/6 mice against a <i>M. tuberculsosis</i> Erdman aerosol challenge after vaccination with either BCG or the <i>ΔmmaA4</i>BCG/adjuvant formulation.
<p>Mice were challenged with <i>M. tuberculosis</i> 8 weeks after a single s.c. immunization and then were sacrificed 1, 2 or 4 months after the challenge for enumeration of CFU's in the lung. Significant CFU reduction relative to * naïve mice (<i>p</i><0.05) or <sup>#</sup> BCG-vaccinated controls (<i>p</i><0.05).</p
Median fluorescence intensity (MFI) of (A) IFNγ or (B) TNFα in monofunctional or multifunctional CD4 T cells.
<p>The data are presented as the mean of individual MFI values for 4–5 mice per vaccine group. * Significant differences relative to monofunctional cytokine expressing cells, <i>p</i><0.05. <sup>#</sup> Significant differences relative to BCG in the same T cell subset, p<0.05.</p