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Category: biotech/medical – Page 1,611

For the first time, a team of scientists has created a synthetic single-celled organism that can divide and grow like a regular living cell. This breakthrough could lead to designer cells that can produce useful chemicals on demand or treat disease from inside the body.

This new study, by scientists from the J. Craig Venter Institute (JCVI), the National Institute of Standards and Technology (NIST) and MIT, builds on over a decade’s work in creating synthetic lifeforms. In 2010 a JCVI team created the world’s first cell with a synthetic genome, which they dubbed JCVI-syn1.0.

In 2016, the researchers followed that up with JCVI-syn3.0, a version where the goal was to make the organism as simple as possible. With only 473 genes, it was the simplest living cell ever known – by comparison, an E. coli bacterium has well over 4000 genes. But perhaps it was too simple, because the cells weren’t all that effective at dividing. Rather than uniform shapes and sizes, some of them would form filaments and others wouldn’t fully separate.

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Ambi Robotics has two flagship products. AmbiSort is a robotic putwall that sorts boxes, polybags, and envelopes from bulk input flow (chutes, totes, and bins) into destination containers (mail sacks, totes). Ambi Robotics claims the system works “over 50% faster than manual labor.” AmbiKit is a robotic system that builds unique kits from any item set. The company said it can be used with subscription boxes, medical kits, gift sets and sample sets for a variety of industries, including cosmetics, food and beverage, consumer goods, medical devices, aerospace and automotive.

The company’s robots are modular, but they do use suction-based gripping. Here’s how AmbiSort works. A depth-sensing camera first looks into a bin of items and analyzes the objects. After determining how to best grasp the item, the robot picks up the item with its suction gripper, holds it up to a barcode scanner, then places the item into a bin. The system then alerts a human operator when a bin is full and ready to be packed.

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Japan is becoming the latest country to issue digital vaccine passports, according to a report, allowing citizens to use proof of inoculation to travel internationally once again.

The digital passport will be available through a mobile app and will be linked to the government’s vaccination program, Japanese news outlet Nikkei Asia reported. Vaccinated citizens currently receive a certificate in paper format.

The passport is in talks to be added to an app that is expected to debut next month as a means to show negative test results.

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New concept delivers continuous electricity with an approach that reduces cost and risk

San Diego, March 29, 2021 – Fusion energy is heating up. In the past few months, both the U.S. Department of Energy’s (DOE) Fusion Energy Sciences Advisory Committee (FESAC) and the National Academies of Sciences, Engineering, and Medicine (NASEM) released reports calling for aggressive development of fusion energy in the U.S.

Now, scientists at the DIII-D National Fusion Facility have released a new design for a compact fusion reactor that can generate electricity and help define the technology necessary for commercial fusion power. The approach is based on the “Advanced Tokamak” concept pioneered by the DIII-D program, which enables a higher-performance, self-sustaining configuration that holds energy more efficiently than in typical pulsed configurations, allowing it to be built at a reduced scale and cost.

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UC scientists and physicians hope to permanently cure patients of sickle cell disease by using CRISPR-Cas9 to replace a defective gene with the normal version.

In 2014, two years after her Nobel Prize-winning invention of CRISPR-Cas9 genome editing, Jennifer Doudna thought the technology was mature enough to tackle a cure for a devastating hereditary disorder, sickle cell disease, that afflicts millions of people around the world, most of them of African descent. Some 100000 Black people in the U.S. are afflicted with the disease.

Mobilizing colleagues in the then-new Innovative Genome Institute (IGI) — a joint research collaboration between the University of California, Berkeley, and UC San Francisco — they sought to repair the single mutation that makes red blood cells warp and clog arteries, causing excruciating pain and often death. Available treatments today typically involve regular transfusions, though bone marrow transplants can cure those who can find a matched donor.

After six years of work, that experimental treatment has now been approved for clinical trials by the U.S. Food and Drug Administration, enabling the first tests in humans of a CRISPR-based therapy to directly correct the mutation in the beta-globin gene responsible for sickle cell disease. Beta-globin is one of the proteins in the hemoglobin complex responsible for carrying oxygen throughout the body.

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Univ. of Toronto Researcher: “I did not realize quite how bad [the lack of reproducibility and poor quality in research papers] was.”

Many areas of science have been facing a reproducibility crisis over the past two years, and machine learning and AI are no exception. That has been highlighted by recent efforts to identify papers with results that are reproducible and those that are not.

Two new analyses put the spotlight on machine learning in health research, where lack of reproducibility and poor quality is especially alarming. “If a doctor is using machine learning or an artificial intelligence tool to aid in patient care, and that tool does not perform up to the standards reported during the research process, then that could risk harm to the patient, and it could generally lower the quality of care,” says Marzyeh Ghassemi of the University of Toronto.

In a paper describing her team’s analysis of 511 other papers, Ghassemi’s team reported that machine learning papers in healthcare were reproducible far less often than in other machine learning subfields. The group’s findings were published this week in the journal Science Translational Medicine. And in a systematic review published in Nature Machine Intelligence, 85 percent of studies using machine learning to detect COVID-19 in chest scans failed a reproducibility and quality check, and none of the models was near ready for use in clinics, the authors say.

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Didn’t watch the video.

Prof David R. Liu, Professor at Harvard University, the Broad Institute, and HHMI was interviewed by the Sheeky Science Show. In the interview, they discussed how to make precise genome editing safe & efficient using the latest CRISPR tech advances in base editing and prime editing and taking it to the clinic (e.g Beam Therapeutics). They talked about the next frontier, epigenome editing.

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