J Transl Med
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High-dose interferon-alpha 2b (IFN-alpha 2b) is the only approved systemic therapy in the United States for the adjuvant treatment of melanoma. The study objective was to explore the immunomodulatory mechanism of action for IFN-alpha 2b by measuring serum regulatory T cell (Treg), serum transforming growth factor-beta (TGF-beta), interleukin (IL)-10, and autoantibody levels in patients with melanoma treated with the induction phase of the high-dose IFN-alpha 2b regimen. ⋯ Patients with melanoma in this study showed increased basal levels of Treg that may be relevant to their disease and its progression. Treg levels shifted in patients with melanoma treated with IFN-alpha 2b, although no firm conclusions regarding the role of Tregs as a marker of treatment response or outcome can be made at present.
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Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams.
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Americans see clinical research as important, with over 15 million American residents participating in NIH-sponsored studies in 2008 and growing yearly. ⋯ This finding most likely has occurred for several reasons. One reason is that the physician lacks an infrastructure for designing and carrying out trials. This lack is because of an absence of a coordinated effort to train clinical trialists. It is clear that the Nation needs a more purposeful approach to developing and maintaining the infrastructure for designing and conducting clinical trials. Building it de novo trial by trial is profoundly inefficient, to say nothing about time consuming and error prone.
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Vitamin D insufficiency is common in hospitalized patients. Recent evidence suggests that vitamin D may enhance the innate immune response by induction of cathelicidin (LL-37), an endogenous antimicrobial peptide produced by macrophages and neutrophils. Thus, the relationship between vitamin D status and LL-37 production may be of importance for host immunity, but little data is available on this subject, especially in the setting of human sepsis syndrome and other critical illness. ⋯ This study demonstrates an association between critical illness and lower 25(OH)D and DBP levels in critically ill patients as compared to healthy controls. It also establishes a positive association between vitamin D status and plasma LL-37, which suggests that systemic LL-37 levels may be regulated by vitamin D status. Optimal vitamin D status may be important for innate immunity especially in the setting of sepsis. Further invention studies to examine this association are warranted.
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Mass spectrometric analysis of the blood proteome is an emerging method of clinical proteomics. The approach exploiting multi-protein/peptide sets (fingerprints) detected by mass spectrometry that reflect overall features of a specimen's proteome, termed proteome pattern analysis, have been already shown in several studies to have applicability in cancer diagnostics. We aimed to identify serum proteome patterns specific for early stage breast cancer patients using MALDI-ToF mass spectrometry. ⋯ MALDI-ToF spectrometry of serum has an obvious potential to differentiate samples between early breast cancer patients and healthy controls. Importantly, a classifier built on MS-based serum proteome patterns outperforms available protein biomarkers analyzed in blood by immunoassays.