I am sleeping, u r there.
I try 2 work, u r there.
I try 2 shower, u r there
i eat, u demand ur share.
When i call u , u r nowhere!
If i fall, u just mew and stare.
If i laugh, u just glare.
NOW, BMDCs and platelet generation in vitro (?) is near. AIDS risk cut down by 50%? TRANSFUSIONS WILL BE LESS RISKY AND INEXPENSIVE.
Rejection will be overcome easily due to a custom created set.
microRNA called miR-142 involved in the process by which the immature cells in the bone marrow give rise to all the types of blood cells, including immune cells and the oxygen-bearing red blood cells
Reporter: Aviva Lev-Ari, PhD, RN
Dr. Elik Chapnik, Natali Rivkin and Dr. Eran Hornstein
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Cancer Driver Mutations
Larry H. Bernstein, MD, FCAP, LPBI
Big Data Screen Uncovers New Cancer Driver Genes
Using publicly available information from genomic and proteomic databases, a team of scientists lead by researchers at Sanford Burnham Prebys Medical Discovery Institute (SBP) have created a new and more comprehensive catalog of driver mutations for cancer. Driver mutations are genes that handle the progression of cancerous growths. The researchers used cancer mutation and protein structure databases to identify mutations in patient tumors that alter normal protein-protein interaction (PPI) interfaces—identifying more than 100 novel cancer driver genes that may help explain how tumors that are driven by the same gene often lead to vastly different clinical outcomes.
“This is the first time that three-dimensional protein features, such as PPIs, have been used to identify driver genes across large cancer datasets,” explained lead author Eduard Porta-Pardo, Ph.D., postdoctoral fellow at SBP. “We…
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I have always wanted to investigate
Murine , primate , cell line and human blood tumors!
Larry H. Bernstein, MD, FCAP, Curator
Tumor Models Bridge Mouse-Human Gap
Revamped Allograft and Innovative Xenograft Models Can Reduce the Risks of Late-Stage Clinical Trials and Increase the Odds of Translational Success
CRISPR-Cas9 sgRNA in vitro screens can be used to look for genes that when lost induce resistance to a drug (positive screen) or increase sensitivity to a drug (negative screen). The technology might also be a powerful tool for target ID screens in vivo, and looks set to aid in our understanding of tumor development and progression in animal models. [Horizon Discovery]
Precision medicine is all about the two T’s—targets and treatments—targets that emerge from analyses of patient-specific information, and treatments that hit these targets. Both T’s, however, pose difficulties. All too often, insights and drug candidates originating in precision medicine fail to translate into clinical practice.
This reality prompted sober comments…
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I have had some interesting feedback from my colleagues about protecting their work.
Its not just a play or poems that are plagiarized. My posts have pointed out that the academia is the hotbed of plagiarism.
You teach a course and you create a curriculum that arms the student with skills that can immediately be used in the real world.You made them see the importance of using certain calculations or tools or methods.
You then teach a different course. The management does not own the curriculum you developed.
The next person who comes in to teach needs to be given an advance notice of at least 45 days to get a textbook in place and develop his own curriculum. Or you can work out a deal for a royalty. this is unheard of but you should be able to do that with any kind of training or educational institute.My point…
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You must have heard the term ‘kernel’ floating around quite a few times. People from many different backgrounds use it in different contexts. The thing is that this term has been applied to different things in different domains. When we talk about operating systems, we talk about which kernel is being used. Kernel is also used extensively in parallel computing and in the GPU domain, where it is the function which is called repetitively on a computing grid. It has a few other meanings in different hardware related programming fields. But in this post, I will discuss kernels as applied to machine learning. Kernels are used in machine learning to transform the data so that the classification becomes easier. One common thing in all these different definitions of the term ‘kernel’ is that it is being used as a bridge between two things. In operating systems, it is the bridge…
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Over-fitting.. takes me back.. TY
Let’s say you are given a small set of data points. These data points can take any form like weight distribution of people, location of people who buy your products, types of smartphones, etc. Now your job is to estimate the underlying model. As in, if an unknown point comes in, you should to be able to fit it into your model. Typical supervised learning stuff! But the problem is that you have very few datapoints to begin with. So how do we accurately estimate that model? Should you really tighten your model to satisfy every single point you have?
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