Transcriptomic technologies are evolving to diagnose cancer earlier and more accurately to provide greater predictive and prognostic utility to oncologists and patients. Digital techniques such as RNA sequencing are replacing still-imaging techniques to provide more detailed analysis of the transcriptome and aberrant expression that causes oncogenesis, while companion diagnostics are developing to determine the likely effectiveness of targeted treatments. This article examines recent advancements in molecular profiling research and technology as applied to cancer diagnosis, clinical applications and predictions for the future of personalized medicine in oncology.
The Ball State University Center for Peace and Conflict Studies in the United States has compiled altruistic stories from different countries such as India, Australia, the United States, and England since the onset of the COVID‐19 pandemic. We examined those stories to understand (1) who receives the most support, (2) what type of support is provided, (3) who those supporters are, and (4) why people support each other during the pandemic. Conducting a qualitative content analysis of 104 altruistic stories, we first identified that (a) older individuals , (b) people with sensitive health conditions, and disabilities, (c) frontline workers, and (d) working class and marginalized communities received the primary support. Second, we identified three types of support: (a) material, (b) social/emotional, and (c) psychological. Third, we found that support was coming from (a) different organizations, (b) advantaged groups, and (c) volunteers. Last, (a) sharing a community/humanity identity, (b) allyship, and (c) showing gratitude were the reasons behind altruistic and prosocial behavior. Our findings contribute to the literature by providing some possible reasons and ways that allies have supported disadvantaged communities via sharing the available resources and how showing gratitude can be a reason for altruism and prosocial behavior in a pandemic.
In the last two decades, advances in genomic, transcriptomic and proteomic methods have enabled us to identify and classify cancers by their molecular profiles. Many anticipate that a molecular taxonomy of cancer will not only lead to more effective subtyping of cancers but also earlier diagnoses, more informative prognoses and more targeted treatments. This article reviews recent technological developments in the field of proteomics, recent discoveries in proteomic cancer biomarker research and trends in clinical use. Readers are also informed of examples of successful commercialization, and the future of proteomics in cancer diagnostics.
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