Over the past decade, studies applying data-driven modeling approaches have demonstrated significant contributions toward the integrative understanding of multivariate cell regulatory system operation. Here we review applications of several of these approaches, including principal component analysis, partial least squares regression, partial least squares discriminant analysis, decision trees, and Bayesian networks, and describe the advances they have offered in systems-level understanding of immune cell signaling and communication. We show how these approaches generate novel insights from high-throughput proteomic data, from classification to association to influence to mechanisms. Looking forward, new experimental technologies involving single-cell measurements of cytokine expression beckon extension of these modeling techniques to inference of immune cell-cell communication networks, with a goal of aiding development of improved vaccine therapeutics.
[Show abstract][Hide abstract] ABSTRACT: Introduction: Interleukin-2 (IL-2) is multiple which functions during an inflammatory response.
Inflammation is a critical component of cancer progression. IL-10 is the most important cytokine
with anti-inflammatory properties. Cancer patients typically show depression of both cellular and
humoral immune functions. Aims: The objective of this experiment is to know the expression of
IL-2 and IL-10 in cervical cancer. Method: Paraffin block of the tissues frozen section cervical cancer
was cut in sharp and cleaned cryotome and place in glass plate that covered with poly-elysine.
The immunohistochemistry stains were done with monoclonal antibody anti IL-2 and IL-10 with
TSA-indirect method. The collected data were analyzed with T Test (SPSS for window 15). Result:
In this study the expression of IL-2 (35.9% = moderate) is less than the expression of IL-10 (45.3%
= moderate). From T Test analysis of p <= 0.153, it means that there is no significance in difference
between IL-2 and IL-10. Conclusion: We indicated that the immune response plays a role in balance
between cellular and humoral immunity.
[Show abstract][Hide abstract] ABSTRACT: Reliable in vitro human disease models that capture the complexity of in vivo tissue behaviors are crucial to gain mechanistic insights into human disease and enable the development of treatments that are effective across broad patient populations. The integration of stem cell technologies, tissue engineering, emerging biomaterials strategies and microfabrication processes, as well as computational and systems biology approaches, is enabling new tools to generate reliable in vitro systems to study the molecular basis of human disease and facilitate drug development. In this review, we discuss these recently developed tools and emphasize opportunities and challenges involved in combining these technologies toward regenerative science.
Drug discovery today 04/2014; 19(6). DOI:10.1016/j.drudis.2014.04.017 · 6.69 Impact Factor
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