Science, Technology, and Current Futurism
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Science, Technology, and Current Futurism
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GM Approval Database | GMO Database | GM Crop Approvals - ISAAA.org

GM Approval Database | GMO Database | GM Crop Approvals - ISAAA.org | Science, Technology, and Current Futurism | Scoop.it
ISAAA presents an easy to use database of Biotech/GM crop approvals for various biotechnology stakeholders. It features the Biotech/GM crop events and traits that have been approved for commercialization and planting and/or for import for food and feed use with a short description of the crop and the trait.  Entries in the database were sourced principally from Biotechnology Clearing House of approving countries and from country regulatory websites. We invite corrections, additions/deletions, and suggestions for the improvement of the database. Contact us at gmapproval@isaaa.org or fill out our feedback form.
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CRISPR-CAS9 Reverses Disease Symptoms in Living Animals for First Time

CRISPR-CAS9 Reverses Disease Symptoms in Living Animals for First Time | Science, Technology, and Current Futurism | Scoop.it

MIT scientists report the use of a CRISPR methodology to cure mice of a rare liver disorder caused by a single genetic mutation. They say their study (“Genome editing with Cas9 in adult mice corrects a disease mutation and phenotype”), published in Nature Biotechnology, offers the first evidence that this gene-editing technique can reverse disease symptoms in living animals. CRISPR, which provides a way to snip out mutated DNA and replace it with the correct sequence, holds potential for treating many genetic disorders, according to the research team.

 

“What's exciting about this approach is that we can actually correct a defective gene in a living adult animal,” says Daniel Anderson, Ph.D., the Samuel A. Goldblith associate professor of chemical engineering at MIT, a member of the Koch Institute for Integrative Cancer Research, and the senior author of the paper.

 

The recently developed CRISPR system relies on cellular machinery that bacteria use to defend themselves from viral infection. Researchers have copied this cellular system to create gene-editing complexes that include a DNA-cutting enzyme called Cas9 bound to a short RNA guide strand that is programmed to bind to a specific genome sequence, telling Cas9 where to make its cut.

 

At the same time, the researchers also deliver a DNA template strand. When the cell repairs the damage produced by Cas9, it copies from the template, introducing new genetic material into the genome. Scientists envision that this kind of genome editing could one day help treat diseases such as hemophilia, and others that are caused by single mutations.

 

For this study, the researchers designed three guide RNA strands that target different DNA sequences near the mutation that causes type I tyrosinemia, in a gene that codes for an enzyme called FAH. Patients with this disease, which affects about 1 in 100,000 people, cannot break down the amino acid tyrosine, which accumulates and can lead to liver failure. Current treatments include a low-protein diet and a drug called NTCB, which disrupts tyrosine production.

 

In experiments with adult mice carrying the mutated form of the FAH enzyme, the researchers delivered RNA guide strands along with the gene for Cas9 and a 199-nucleotide DNA template that includes the correct sequence of the mutated FAH gene.

 

“Delivery of components of the CRISPR-Cas9 system by hydrodynamic injection resulted in initial expression of the wild-type Fah protein in ~1/250 liver cells,” wrote the investigators. “Expansion of Fah-positive hepatocytes rescued the body weight loss phenotype.”

 

While the team used a high pressure injection to deliver the CRISPR components, Dr. Anderson envisions that better delivery approaches are possible. His lab is now working on methods that may be safer and more efficient, including targeted nanoparticles. 


Via Dr. Stefan Gruenwald
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Bacteriograph: Photographs Printed with Bacterial Growth

Bacteriograph: Photographs Printed with Bacterial Growth | Science, Technology, and Current Futurism | Scoop.it

Microbiologist-turned-photographer Zachary Copfer has developed an amazing photo-printing technique that’s very different from any we’ve seen before. Rather than use photo-sensitive papers, chemicals, or ink, Copfer uses bacteria. The University of Cincinnati MFA photography student calls the technique “bacteriography”, which involves controlling bacteria growth to form desired images.

Here’s how Copfer’s method works: he first takes a supply of bacteria like E. coli, turns it into a fluorescent protein, and covers a plate with it. Next, he creates a “negative” of the photo he wants to print by covering the prepared plate with the photo and then exposing it to radiation. He then “develops” the image by having the bacterial grow, and finally “fixes” the image by coating the image with a layer of acrylic and resin.

 

Using this process, he creates images of things ranging from famous individuals to Hubble telescope photos of galaxies. Copfer writes that his project is intended to be a counterexample to the false dichotomy of art and science.


Via Dr. Stefan Gruenwald
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Machine Learning and Big Data Are Changing the Face of Biological Sciences

Until recently, the wet lab has been a crucial component of every biologist. Today's advances in the production of massive amounts of data and the creation of machine-learning algorithms for processing that data are changing the face of biological science—making it possible to do real science without a wet lab. David Heckerman shares several examples of how this transformation in the area of genomics is changing the pace of scientific breakthroughs.


Via Szabolcs Kósa, Dr. Stefan Gruenwald
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davidgibson's curator insight, May 28, 2013 11:05 PM

This 36 min video is well worth the time spent - to get an idea (hopefully a transferrable one) about Big Data and the frontiers of science. In this case both "wet lab" (test tubes microscopes) and "dry lab" (computer modeling with machine learning) and needed and so is content as well as computational literacy.

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Cusp 2011 Dr. Richard Satava

As Professor of Surgery at the University of Washington Medical Center and Senior Science Advisor at the US Army Medical Research and Materiel Command in Ft....
Sharrock's insight:

Robotic medicine and biotechnology advances are demonstrated in this video presentation dated 2011. Even back then, it is apparent that we can fix genetic mistakes, replace any organ (except the brain), perform surgery at almost any scale, and even clone ourselves. What SHOULDN"T we be able to do though? How should we limit these advances? How should students prepare for the biotech era and economy?

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Sharrock's curator insight, January 10, 2013 1:35 PM

This video from 2011 reveals successes in medicine already demonstrated. Every organ of the body can be transplanted and replaced except the brain, operations can be done by robots, operations can be done on specific cells. This surgeon can be found on the Internet. As the military implements some of the devices and systems seen here, civilians will eventually benefit from these advances as well. The video says a great deal about how far technology has come, but also explores, briefly, the ethical and moral implications. Considering the tech implications from another point of view, outside of medicine, I think of manufacturing. Right now, it seems that manufacturing and assembling by hand has not been automated yet. But imagine if one person assembled 10 devices at the same time as a  kind of sorcerer's apprentice. Imagine if the moves were "recorded" and performed by machine memory. The video is about 24 minutes long, but it is worth watching to realize the world is changing fast!

Sharrock's comment, January 10, 2013 3:11 PM
Robotic medicine and biotechnology advances are demonstrated in this video presentation dated 2011. Even back then, it is apparent that we can fix genetic mistakes, replace any organ (except the brain), perform surgery at almost any scale, and even clone ourselves. What SHOULDN"T we be able to do though? How should we limit these advances? How should students prepare for the biotech era and economy?
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Researchers engineer bacterium to hunt down and kill pathogens

Researchers engineer bacterium to hunt down and kill pathogens | Science, Technology, and Current Futurism | Scoop.it

Recent examples of new genetic circuits that enable cells to acquire biosynthetic capabilities, such as specific pathogen killing, present an attractive therapeutic application of synthetic biology. A team of researchers in Singapore has developed a technique for bioengineering a bacterium to seek out and kill targeted pathogens.

 

They demonstrate a novel genetic circuit that reprograms Escherichia coli to specifically recognize, migrate toward, and eradicate both dispersed and biofilm-encased pathogenic Pseudomonas aeruginosa cells. The reprogrammed E. coli degraded the mature biofilm matrix and killed the latent cells encapsulated within by expressing and secreting the antimicrobial peptide microcin S and the nuclease DNaseI upon the detection of quorum sensing molecules naturally secreted by P. aeruginosa. Furthermore, the reprogrammed E. coli exhibited directed motility toward the pathogen through regulated expression of CheZ in response to the quorum sensing molecules.

 

By integrating the pathogen-directed motility with the dual antimicrobial activity in E. coli, we achieved signifincantly improved killing activity against planktonic and mature biofilm cells due to target localization, thus creating an active pathogen seeking killer E. coli.


Via Dr. Stefan Gruenwald, NCPbiology
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NCPbiology's curator insight, June 27, 2014 6:26 AM

Interesting extra reading?

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Machine-learning algorithms could make chemical reactions intelligent leading to "smart drugs"

Machine-learning algorithms could make chemical reactions intelligent leading to "smart drugs" | Science, Technology, and Current Futurism | Scoop.it

Computer scientists at the Harvard School of Engineering and Applied Sciences (SEAS) and the Wyss Institute for Biologically Inspired Engineering at Harvard University have joined forces to put powerful probabilistic reasoning algorithms in the hands of bioengineers.

 

In a new paper presented at the Neural Information Processing Systems conference on December 7, Ryan P. Adams and Nils Napp have shown that an important class of artificial intelligence algorithms could be implemented using chemical reactions.

 

These algorithms, which use a technique called “message passing inference on factor graphs,” are a mathematical coupling of ideas from graph theory and probability. They represent the state of the art in machine learning and are already critical components of everyday tools ranging from search engines and fraud detection to error correction in mobile phones.

 

Adams’ and Napp’s work demonstrates that some aspects of artificial intelligence (AI) could be implemented at microscopic scales using molecules. In the long term, the researchers say, such theoretical developments could open the door for “smart drugs” that can automatically detect, diagnose, and treat a variety of diseases using a cocktail of chemicals that can perform AI-type reasoning.

 

“We understand a lot about building AI systems that can learn and adapt at macroscopic scales; these algorithms live behind the scenes in many of the devices we interact with every day,” says Adams, an assistant professor of computer science at SEAS whose Intelligent Probabilistic Systems group focuses on machine learning and computational statistics. “This work shows that it is possible to also build intelligent machines at tiny scales, without needing anything that looks like a regular computer. This kind of chemical-based AI will be necessary for constructing therapies that sense and adapt to their environment. The hope is to eventually have drugs that can specialize themselves to your personal chemistry and can diagnose or treat a range of pathologies.”

 

Adams and Napp designed a tool that can take probabilistic representations of unknowns in the world (probabilistic graphical models, in the language of machine learning) and compile them into a set of chemical reactions that estimate quantities that cannot be observed directly. The key insight is that the dynamics of chemical reactions map directly onto the two types of computational steps that computer scientists would normally perform in silico to achieve the same end.

 

This insight opens up interesting new questions for computer scientists working on statistical machine learning, such as how to develop novel algorithms and models that are specifically tailored to tackling the uncertainty molecular engineers typically face. In addition to the long-term possibilities for smart therapeutics, it could also open the door for analyzing natural biological reaction pathways and regulatory networks as mechanisms that are performing statistical inference. Just like robots, biological cells must estimate external environmental states and act on them; designing artificial systems that perform these tasks could give scientists a better understanding of how such problems might be solved on a molecular level inside living systems.


Via Dr. Stefan Gruenwald
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(HD) Dr. Michio Kaku: The Biotech Revolution - Vision of the Future - Full Documentary

(HD) Dr. Michio Kaku: The Biotech Revolution - Vision of the Future - Full Documentary ❶ HD Universe Channel: For all your Space, Universe and Science docume...

Via Gerd Moe-Behrens, Claudia, Jim Lerman, Lynnette Van Dyke
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Gerd Moe-Behrens's comment, October 22, 2013 4:17 PM
They recently changed it. Try this link http://www.youtube.com/watch?v=CG8TekgNEhA
malek's comment, October 22, 2013 5:25 PM
@socrates Logos: this link is active, thank you for sharing
Gerd Moe-Behrens's comment, October 22, 2013 5:27 PM
Great - you are welcome
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How could Biotechnology improve your life?

How could Biotechnology improve your life? | Science, Technology, and Current Futurism | Scoop.it
Experts on the World Economic Forum’s Council on Biotechnology have selected 10 developments which they believe could help not only meet the rapidly growing demand for energy, food and healthcare, but also increase productivity and create new jobs,...
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