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Protecting Lives: FDA Mandates Cybersecurity Guidelines for Medical Devices

To address growing concerns about cyber attacks and ransomware incidents, the Food and Drug Administration (FDA) has mandated new cybersecurity guidelines for medical devices. All new medical device applicants are now required to submit a cybersecurity plan outlining how they intend to “monitor, identify, and address” cybersecurity issues.

The FDA must also develop a process to ensure “reasonable assurance” that the device is secure from cyber threats. The FDA will require applicants to provide regular security updates and patches, as well as to disclose any open-source or other software used in their devices, according to CNN News.

In the past, the FDA has been chastised for not doing enough to address medical device cybersecurity concerns. FDA must now update its medical device cybersecurity guidance every two years, according to the bill.

According to a 2022 FBI report, more than half of digital medical devices and internet-connected products in hospitals had known vulnerabilities. Hackers could use these flaws to provide inaccurate readings, administer drug overdoses, or cause other risks to patient health.

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New RNA nanoparticles can perform gene editing in the lungs to treat lung diseases

Engineers at MIT and the University of Massachusetts Medical School have designed a new type of nanoparticle that can be administered to the lungs, where it can deliver messenger RNA for encoding useful proteins.

With further development, these particles could offer an inhalable treatment for cystic fibrosis and other diseases of the lung, the researchers say.

Treating or repairing a range of genetic diseases

“We are hopeful that [these particles] can be used to treat or repair a range of genetic diseases, including cystic fibrosis,” says Daniel Anderson, a professor in MIT’s Department of Chemical Engineering and a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science (IMES).

In a study of mice, Anderson and his colleagues used the particles to deliver mRNA encoding the machinery needed for CRISPR/Cas9 gene editing. That could open the door to designing therapeutic nanoparticles that can snip out and replace disease-causing genes.

Particle structure designed to be most likely to reach the lungs

The particles are made up of molecules that contain two parts: a positively charged headgroup and a long lipid tail. The positive charge of the headgroup helps the particles to interact with negatively charged mRNA, and it also help mRNA to escape from the cellular structures that engulf the particles once they enter cells.

The lipid tail structure, meanwhile, helps the particles to pass through the cell membrane. The researchers came up with 10 different chemical structures for the lipid tails, along with 72 different headgroups. By screening different combinations of these structures in mice, the researchers were able to identify those that were most likely to reach the lungs.

They are now working on making their nanoparticles more stable, so they could be aerosolized and inhaled using a nebulizer.

Promising therapeutic lung gene delivery applications

“This achievement paves the way for promising therapeutic lung gene delivery applications for various lung diseases,” says Dan Peer, director of the Laboratory of Precision NanoMedicine at Tel Aviv University, who was not involved in the study. “This platform holds several advantages compared to conventional vaccines and therapies, including that it’s cell-free, enables rapid manufacturing, and has high versatility and a favorable safety profile.”

The study appears March 30, 2023 in Nature Biotechnology.

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Should we pause development of AI systems smarter than GPT-4 for six months?

A “call for a pause” open letter sent out Wednesday warns of an “out-of-control race to develop and deploy ever-more-powerful AI systems.”

The letter, by Future of Life Institute, an organization focused on technological risks to humanity, warns that “AI systems with human-competitive intelligence can pose profound risks to society and humanity, as shown by extensive research.”        

The letter calls on “all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4.” As of early Thursday, the letter has been signed by verified AI experts at 1377 AI labs.

Overreach?

One AI expert not on that list: Dr. Ben Goertzel, CEO of SingularityNet and an AI scientist noted for his work in AGI (artificial general intelligence). “I don’t see how pausing training of bigger LLMs [large language models] for six months is going to suddenly cause the corporate honchos and tech bros to start pushing toward UBI for the poorest nations in the world, in anticipation of the difficulty pre-Singularity AI will cause to their economies,” he told Mindplex.

“I think the justification for pausing tech dev due to worries should need to be quite strong. Just like I think the justification for suspending freedom of speech should be quite strong. OK, you ban shouting fire in a crowded theater. But you don’t ban speech that seems like it might indirectly cause someone to do something illegal.

“Similarly, you take action against an LLM that demonstrably turns everyone who talks to it into murderous psychopaths, or a 3D printer whose express purpose is to cheaply 3D print bombs out of ordinary kitchen ingredients. But not against exciting new technologies with complex mixes of good and bad aspects and no immediate huge deadly threat associated with them.”

Other leading AI experts who have refused to sign include OpenAI CEO Sam Altman and Yann LeCun, Chief AI Scientist at Meta, who explained: “The year is 1440 and the Catholic Church has called for a 6 months moratorium on the use of the printing press and the movable type,” he said. “Imagine what could happen if commoners get access to books! They could read the Bible for themselves and society would be destroyed.”

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Coca-Cola and other major marketers enter ‘test and learn’ phase with generative AI

Coca-Cola and other major marketers are experimenting with generative AI to determine how to incorporate AI technologies into their marketing strategies.

But marketers are currently focused on using AI in the creative process. The potential legal ramifications of using generative AI platforms, which scrape data without the consent of publishers, artists, and others, could cause clients legal problems, according to consulting firm DigiDay.

Clients are cautious, according to marketers and agency executives, because of the potential legal issues, and are working with legal teams to ensure that generative AI platforms comply with data collection methods.

Despite the challenges, the potential of generative AI in marketing is very exciting. Christian Pierre, chief data intelligence officer at Gut Miami, believes that by 2024, the majority of the ideas in any major industry awards show’s Creative Data category will be some form of generative AI or inspired by it.

Marketers and agencies are currently in the early stages of testing and learning about how to use generative AI in meaningful ways to deliver on consumer expectations.

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The Shape of Your Heart May Predict Your Risk for Heart Disease and Atrial Fibrillation

Cedars-Smidt Sinai’s Heart Institute researchers have shown that the shape of your heart and certain genetic markers may indicate your risk of developing atrial fibrillation and heart muscle disease.

Patients with round hearts, similar in shape to a baseball, were found to be 31% more likely to develop atrial fibrillation and 24% more likely to develop cardiomyopathy than those with longer hearts shaped like a traditional Valentine’s heart.

Deep learning-enabled measurement of left ventricular sphericity index

The study, published in the peer-reviewed medical journal Med-Cell Press, examined cardiac MRI images from 38,897 healthy people to identify genetic markers linked to the risk of developing these cardiac conditions. Atrial fibrillation raises the risk of stroke, while cardiomyopathy can result in heart failure; both conditions affect millions of people worldwide, CBS News reports.

Cardiologists at Cedars-Sinai emphasize the potential for cardiac imaging and deep learning for diagnosing and preventing heart conditions before they become life-threatening diseases. They also stress the importance of understanding how a heart changes shape when sick and identifying genetic variations affecting the heart. The findings shed light on effective prevention methods for these conditions.

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Improve GPT-4’s Performance by 30% with This Self-Reflective Agent Technique!

Northeastern University and MIT researchers have created Reflexion, a self-reflective natural language agent that they claim can improve GPT-4 performance by an astounding 30%.

The agent can generate new prompts autonomously until it reaches the correct answer, by analyzing its mistakes and taking them into account. Reflexion was tested on two benchmarks, AlfWorld and HotPotQA, and achieved 97% success and a 17% improvement over the base agent, respectively.

Reflexion appears to be an important step toward natural language agents that can learn through trial and error, without constant human intervention. This approach enables agents, based on their experience history, to generate new ideas, explore previously unseen state spaces, and develop more precise action plans. It also allows agents to solve tasks and environments that were previously thought to be impossible.

Self-reflective agents such as Reflexion may play an important role in improving the performance of large-scale language models such as GPT-4, paving the way for more intelligent and autonomous AI systems.

Sources: MarkTechPost and arXiv
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11-Year-Old Creates AI-Based Eye Disease Detection App — a Testament to Young Minds’ Innovation

An 11-year-old Malayali-based girl in Dubai has created an AI-based app that uses an iPhone scanning technique to identify various eye ailments and illnesses. Leena Rafeeq, a self-taught coder, named the app “Ogler EyeScan” and shared her accomplishment on LinkedIn, where she received positive feedback from impressed users. Apple is currently reviewing the app.

Leena explained that her software analyzes characteristics such as light and color intensity, distance, and look-up locations to find eyeballs within the frame range, using computer vision and machine learning algorithms. The app can detect light-burst problems and whether the eyes are perfectly positioned inside the scanner frame, and can also diagnose illnesses such as Arcus, Melanoma, Pterygium, and Cataracts.

Leena, who began working on the software at the age of ten, spent six months developing it natively with Apple’s SwiftUI, without the use of any third-party libraries or packages. Leena’s accomplishment, along with that of her younger sister Hana, who made headlines for becoming the youngest iOS app developer, demonstrates the power of young minds’ innovation and their ability to positively impact society.

Source: Analytics Insight
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Cracking the Secret to Renaissance Art: Why Some Paintings were Egged

Researchers from Germany’s Karlsruhe Institute of Technology compared oil-egg recipes to plain oil paint and discovered that adding egg yolk to oil paint slowed oxidation and created strong links between pigment particles. The paint became stiffer, making it ideal for impasto techniques.

Adding egg yolk also reduced wrinkling, which can occur when oil paints dry at different rates. But too much egg yolk may cause the paint to take longer to dry, making it difficult for artists to add the next layer. One of many hidden secrets in Renaissance art that have yet to be discovered.

Understanding the scientific properties of Renaissance art materials can help with art preservation efforts. It can also allow people to appreciate the creative process and final product of these masterpieces.

Source: Science News
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New machine and deep learning method identifies Alzheimer’s disease biomarkers and potential targets

Alzheimer’s disease (AD), the most common cause of dementia and impaired cognitive function, still has no effective treatment, according to researchers. So research is centered on identifying AD biomarkers and targets.

Now, scientists at King Abdullah University of Science and Technology in Saudi Arabia have created a computational method that identifies AD biomarkers and targets. It combines multiple “hub gene” ranking methods and “feature selection” methods with machine learning and deep learning to identify hub genes and gene subsets, the researchers used three AD gene expression datasets using six ranking algorithms and two feature-selection methods.

The researchers then created machine learning and deep learning models to identify the gene subset that best distinguished Alzheimer’s disease samples from healthy controls. They found that feature selection methods outperformed hub gene sets in terms of prediction performance and that the five genes identified by both feature selection methods had an “AUC” of 0.979.

Based on a literature review, the researchers further showed that 70% of the upregulated hub genes (among the 28 overlapping hub genes) were AD targets, with six miRNA and one transcription factor associated with the upregulated hub genes. According to the researchers, overlapping upregulated hub genes can narrow the search space for potential novel targets.

Source: Nature Scientific Reports (open-access)
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How energy-generating synthetic organelles could sustain artificial cells — a powerhouse of the future

Energy production in nature is the responsibility of mitochondria and chloroplasts, and is crucial for fabricating sustainable, synthetic cells in the lab. Mitochondria are “the powerhouses of the cell,” but are also one of the most complex intracellular components to replicate artificially.

In Biophysics Reviews, by AIP Publishing, researchers from Sogang University in South Korea and the Harbin Institute of Technology in China identified the most promising advancements and greatest challenges of artificial mitochondria and chloroplasts.

“If scientists can create artificial mitochondria and chloroplasts, we could potentially develop synthetic cells that can generate energy and synthesize molecules autonomously. This would pave the way for the creation of entirely new organisms or biomaterials,” author Kwanwoo Shin said.

Key roles of chloroplasts, mitochondria and ATP

In plants, chloroplasts use sunlight to convert water and carbon dioxide into glucose. Mitochondria, found in plants and animals alike, produce energy by breaking down glucose. Once a cell produces energy, it often uses a molecule called adenosine triphosphate (ATP) to store and transfer that energy. When the cell breaks down the ATP, it releases energy that powers the cell’s functions.

“In other words, ATP acts as the main energy currency of the cell, and it is vital for the cell to perform most of the cellular functions,” said author Kwanwoo Shin.

One of the most significant challenges remaining in trying to reconstruct the energy production organelles is enabling self-adaptation in changing environments to maintain a stable supply of ATP. Future studies must investigate how to improve upon this limiting feature before synthetic cells are self-sustainable, the researchers say.

Energy efficiency

The team also described the components required to construct synthetic mitochondria and chloroplasts and they identified proteins as the most important aspects for molecular rotary machinery, proton transport and ATP production.

Previous studies have replicated components that make up energy-producing organelles. Some of the most promising work investigates the intermediate operations involved in the complex energy-generating process. By connecting the sequence of proteins and enzymes, researchers have improved energy efficiency.

The origin of life and cells

The researchers believe its important to create artificial cells with biologically realistic energy-generation methods that mimic natural processes. Replicating the entire cell could also lead to future biomaterials and lend insight into the past.

“This could be an important milestone in understanding the origin of life and the origin of cells,” Shin said.

The article, “Artificial organelles for sustainable chemical energy conversion and production: Artificial mitochondria and chloroplasts,” is authored by Hyun Park, Weichen Wang, Seo Hyeon Min, Yongshuo Ren, Xiaojun Han, and Kwanwoo Shin and is published in Biophysics Reviews on March 28, 2023, https://doi.org/10.1063/5.0131071.

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