Lifeboat Foundation: Safeguarding Humanity
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Category: biotech/medical – Page 2,240

Bioengineers at Boston Children’s Hospital report the first demonstration of a robot able to navigate autonomously inside the body. In an animal model of cardiac valve repair, the team programmed a robotic catheter to find its way along the walls of a beating, blood-filled heart to a leaky valve—without a surgeon’s guidance. They report their work today in Science Robotics.

Surgeons have used robots operated by joysticks for more than a decade, and teams have shown that tiny robots can be steered through the body by external forces such as magnetism. However, senior investigator Pierre Dupont, Ph.D., chief of Pediatric Cardiac Bioengineering at Boston Children’s, says that to his knowledge, this is the first report of the equivalent of a self-driving car navigating to a desired destination inside the body.

Dupont envisions assisting surgeons in complex operations, reducing fatigue and freeing surgeons to focus on the most difficult maneuvers, improving outcomes.

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A special focus on rogue proteins may hold future promise in stopping the progression of nerve cell destruction in people who have amyotrophic lateral sclerosis (ALS) or frontotemporal dementia.

ALS, a rare but devastating disorder that’s also known as Lou Gehrig’s disease, attacks the body’s , resulting in progressive muscle weakness as the neurons degenerate over time. There is no cure. People with ALS eventually lose their strength and the ability to move their arms, legs and body.

About a third of those with ALS also develop frontotemporal dementia (FTD), a destruction of neurons in the brain that causes profound personality changes and disability. The two diseases are similar in both pathology and genetics. FTD tends to affect people earlier than Alzheimer’s disease, the most common type of dementia.

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Using human cancer cells, tumor and blood samples from cancer patients, researchers at Johns Hopkins Medicine have uncovered the role of a neurotransmitter in the spread of aggressive cancers. Neurotransmitters are chemical “messengers” that transmit impulses from neurons to other target cells.

The work, described in the April 9 issue of the journal Cell Reports, found that this neurotransmitter, called N-acetyl-aspartyl-glutamate (NAAG) NAAG is more abundant in cancers with a tendency to grow and spread rapidly—or so-called higher grade cancers—than in lower grade tumors, making it a potential marker for tumor progression or regression during cancer therapy, the researchers say. The experiments also demonstrated that NAAG is a source of glutamate, a chemical that cancer cells use as building blocks to survive, in tumors that express an enzyme called glutamate carboxypeptidase II (GCPII). The group also discovered that stopping the GCPII from being active by using a drug called 2-PMPA to treat human ovarian tumors implanted in ovaries of mice, reduced tumor weights and glutamate concentrations.

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Researchers at Rady Children’s Institute for Genomic Medicine (RCIGM) have utilized a machine-learning process and clinical natural language processing (CNLP) to diagnose rare genetic diseases in record time. This new method is speeding answers to physicians caring for infants in intensive care and opening the door to increased use of genome sequencing as a first-line diagnostic test for babies with cryptic conditions.

“Some people call this , we call it augmented intelligence,” said Stephen Kingsmore, MD, DSc, President and CEO of RCIGM. “Patient care will always begin and end with the doctor. By harnessing the power of technology, we can quickly and accurately determine the root cause of genetic diseases. We rapidly provide this critical information to physicians so they can focus on personalizing care for babies who are struggling to survive.”

A new study documenting the process was published today in the journal Science Translational Medicine. The workflow and research were led by the RCIGM team in collaboration with leading technology and data-science developers —Alexion, Clinithink, Diploid, Fabric Genomics and Illumina.

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Scientists on Tuesday unveiled a battery-free pacemaker that generates its energy from the heartbeats of pigs in what could pave the way for an “implant for life” in humans suffering from heart defects.

Millions of patients rely on pacemakers —small electrical implants in the chest of abdomen—to help regulate their heartbeats after chronic or acute illness.

Even with recent technological advances, pacemaker batteries can be rigid or bulky, and may need replacing several times over the lifespan of a .

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Scientists from Tomsk Polytechnic University (TPU), together with colleagues from the United States and Germany, have found a way to obtain inexpensive catalysts from hexagonal boron nitride or “white graphene.” The technology can be used in the production of environmentally friendly hydrogen fuel.

The researchers have found a new way to functionalize a dielectric, otherwise known as white graphene, i.e. (hBN), without destroying it or changing its properties. Thanks to the new method, the researchers synthesized a polymer nano carpet with strong covalent bond on the samples.

Prof Raul Rodriguez from the TPU Research School of Chemistry & Applied Biomedical Sciences explains:

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BYU electrical engineering students have stumbled upon a very unconventional method that could speed up lab-on-a-chip disease diagnosis.

When someone goes to the hospital for a serious illness, if a bacterial infection is suspected, it can take up to three days to get results from a bacteria culture test. By then, it is often too late to adequately treat the infection, especially if the bacteria are resistant to common antibiotics.

BYU students are working on a project to diagnose antibiotic resistant bacteria, or superbugs, in less than an hour. Their method relies on extracting bacteria from a blood sample and then pulling DNA from that . If specific genetic codes indicating antibiotic resistance are present in the DNA, fluorescent molecules can be attached to these sites. Laser light can then be shined on the DNA samples and the molecules will light up.

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For years, post traumatic stress disorder (PTSD) has been one of the most challenging disorders to diagnose. Traditional methods, like one-on-one clinical interviews, can be inaccurate due to the clinician’s subjectivity, or if the patient is holding back their symptoms.

Now, researchers at New York University say they’ve taken the guesswork out of diagnosing PTSD in veterans by using artificial intelligence to objectively detect PTSD by listening to the sound of someone’s voice. Their research, conducted alongside SRI International — the research institute responsible for bringing Siri to iPhones— was published Monday in the journal Depression and Anxiety.

According to The New York Times, SRI and NYU spent five years developing a voice analysis program that understands human speech, but also can detect PTSD signifiers and emotions. As the NYT reports, this is the same process that teaches automated customer service programs how to deal with angry callers: By listening for minor variables and auditory markers that would be imperceptible to the human ear, the researchers say the algorithm can diagnose PTSD with 89% accuracy.

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After 20 years of dedicated research, scientists have cracked the chemical code of an incredibly complex ‘anti-tumour antibiotic’ known to be highly effective against cancer cells as well as drug-resistant bacteria, and have reproduced it synthetically in the lab for the first time.

This major breakthrough and world-first could hail a new era in the design and production of new antibiotics and anticancer agents.

The ‘super substance’—kedarcidin—was discovered in its natural form by a pharmaceutical company when they extracted it from a soil sample in India almost 30-years-ago. Soil is the natural source of all antibiotics developed since the 1940s but in order for them to be developed as potential drug treatments they must be produced via .

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Researchers from Osaka University have developed a technique for improving accuracy of laser beam shaping and wavefront obtained by conventional methods with no additional cost by optimizing virtual phase grating. The results of their research were published in Scientific Reports.

A high quality square flattop is in demand for various fields, such as uniform laser processing and medicine, as well as ultrahigh intensity laser applications for accelerators and nuclear fusion. Beam is key to realizing the laser’s potential abilities and effects. However, since beam shape and wavefront vary by laser, beam shaping is essential for producing the desired shapes to respond to various needs.

Static and adaptive beam shaping methods have been developed for various applications. With Diffractive Optical Element (DOE) as a static method, edge steepness and flatness are low and wavefront becomes deformed after shaping. (Figure 1 (a)) In addition, computer-generated hologram (CGH) as a typical adaptive method has the same difficulties.

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