This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Consuming high amounts of red meat is commonly linked to an increased risk of developing cancer, especially colorectal cancer. At the same time, antibodies against Neu5Gc , a carbohydrate derived from red meat, have been observed to worsen cancer in “human-like” mice. While these antibodies and red meat consumption are each believed to increase cancer risk, it remains unknown how diet affects the antibodies. Now, research suggests that consuming Neu5Gc from red meat and dairy can modulate the amounts and properties of anti-Neu5Gc antibodies in humans, providing clues to how the carbohydrate might be linked to cancer. The team behind the study calculated daily intake of Neu5Gc for more than 19,000 subjects aged 18 years or older. These participants provided regular logs of food consumed over 24-hour periods as part of the NutriNet-Santé study, which was designed to investigate relationships between nutrition and health status..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

This course teaches the design of contemporary information systems for biological and medical data. Examples are chosen from biology and medicine to illustrate complete life cycle information systems, beginning with data acquisition, following to data storage and finally to retrieval and analysis. Design of appropriate databases, client-server strategies, data interchange protocols, and computational modeling architectures. Students are expected to have some familiarity with scientific application software and a basic understanding of at least one contemporary programming language (e.g. C, C++, Java, Lisp, Perl, Python). A major term project is required of all students. This subject is open to motivated seniors having a strong interest in biomedical engineering and information system design with the ability to carry out a significant independent project.
This course was offered as part of the Singapore-MIT Alliance (SMA) program as course number SMA 5304.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"The immunosuppressive tumor microenvironment (TME) plays essential roles in cancer development and progression. Exosomes mediate crosstalk between tumor cells and other stromal or immune cells in the TME, but how tumor-derived exosomes promote the progression of bladder cancer, one of the most common types of cancer, remains unclear. To find out, researchers recently examined the effects of exosomes extracted from the conditioned medium (CM) of MB49 bladder cancer cells. The researchers found that the cancer-derived exosomes were ingested by mouse macrophages both in vitro and in vivo and that they induced macrophage polarization toward the immunosuppressive M2 phenotype. Exosome-secreting MB49 cells induced tumor growth in mice, but the exosome inhibitor GW4869 reduced tumor growth, macrophage M2 polarization and immunosuppression, confirming the pro-tumor effects of the cancer-derived exosomes..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

The course focuses on casting contemporary problems in systems biology and functional genomics in computational terms and providing appropriate tools and methods to solve them. Topics include genome structure and function, transcriptional regulation, and stem cell biology in particular; measurement technologies such as microarrays (expression, protein-DNA interactions, chromatin structure); statistical data analysis, predictive and causal inference, and experiment design. The emphasis is on coupling problem structures (biological questions) with appropriate computational approaches.

This course reviews the key genomic technologies and computational approaches that are driving advances in prognostics, diagnostics, and treatment. Throughout the semester, emphasis will return to issues surrounding the context of genomics in medicine including: what does a physician need to know? what sorts of questions will s/he likely encounter from patients? how should s/he respond? Lecturers will guide the student through real world patient-doctor interactions. Outcome considerations and socioeconomic implications of personalized medicine are also discussed. The first part of the course introduces key basic concepts of molecular biology, computational biology, and genomics. Continuing in the informatics applications portion of the course, lecturers begin each lecture block with a scenario, in order to set the stage and engage the student by showing: why is this important to know? how will the information presented be brought to bear on medical practice? The final section presents the ethical, legal, and social issues surrounding genomic medicine. A vision of how genomic medicine relates to preventative care and public health is presented in a discussion forum with the students where the following questions are explored: what is your level of preparedness now? what challenges must be met by the healthcare industry to get to where it needs to be?
Lecturers
Dr. Atul J. Butte
Dr. Steven A. Greenberg
Dr. Alvin Thong-Juak Kho
Dr. Peter Park
Dr. Marco F. Ramoni
Dr. Alberto A. Riva
Dr. Zoltan Szallasi
Dr. Jeffrey Mark Drazen
Dr. Todd Golub
Dr. Joel Hirschhorn
Dr. Greg Tucker-Kellogg
Dr. Scott Weiss

In this activity, learners explore the "nuts and bolts" of gene chips. Learners construct a simple model of a DNA microarray (also known as gene chips) and learn how microarrays can be used to identify and treat disease--including cancer. This resource includes references and an explanation of microarrays.