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‘Mini liver’ will grow in person’s own lymph node in bold new trial

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A person has received an experimental treatment for the first time that, if successful, will lead them to grow an additional, ‘miniature liver’. The procedure, developed by the biotechnology firm LyGenesis, marks the beginning of a clinical trial designed for people whose livers are failing, but who have not received an organ transplant.

The approach is unusual: researchers injected healthy liver cells from a donor into a lymph node in the upper abdomen of the person with liver failure. The idea is that in several months, the cells will multiply and take over the lymph node to form a structure that can perform the blood-filtering duties of the person’s failing liver.

“It’s a very bold and incredibly innovative idea,” says Valerie Gouon-Evans, a liver-regeneration specialist at Boston University in Massachusetts, who is not involved with the company.

The person who received the treatment, on 25 March, is recovering well from the procedure and was discharged from the clinic, says Michael Hufford, chief executive of LyGenesis, which is based in Pittsburgh, Pennsylvania. But physicians will need to closely monitor them for infection because the person needs to take immunosuppressive drugs so that their body doesn’t reject the donor cells, says Stuart Forbes, a hepatologist at the University of Edinburgh, UK, who is not affiliated with LyGenesis.

Organ crisis

More than 50,000 people in the United States die each year with liver disease. In the end stage of the disease, scar tissue that has accumulated prevents the organ from filtering toxic substances in the blood, and can lead to infection or liver cancer.

A liver transplant can help, but there is a shortage of organs: about 1,000 people in the United States die every year waiting for a transplant. Thousands more aren’t eligible because they are too ill to undergo the procedure.

Gloved hands holding up a fluid bag of the donor liver cells in a lab.

A person received donor liver cells on 25 March that were injected into one of their lymph nodes.Credit: LyGenesis

LyGenesis has been trialling an approach that could help people in this situation — and make use of donated livers that would otherwise go to waste because a person on the transplant waiting list with a compatible health profile hasn’t materialized in time. The company’s strategy delivers the donor cells through a tube in the throat, injecting them into a lymph node near the liver. Lymph nodes, which also filter waste in the body and are an important part of the immune system, are ideal for growing mini livers, Hufford says, because they receive a large supply of blood and there are hundreds of them throughout the body, so if a few are used to generate mini livers, plenty of others can continue to function as lymph nodes.

The treatment has so far worked in mice1, dogs and pigs2. To test the therapy in pigs, researchers restricted blood flow to the animals’ livers, causing the organs to fail, and injected donor cells into lymph nodes. Miniature livers formed within two months and had a cellular architecture resembling a healthy liver. Researchers even found cells that transport bile, a digestive fluid produced by the liver, in the mini livers of the pigs. In this case, they saw no build-up of bile acid, suggesting that the mini organs were processing the fluid.

Hufford says there’s reason to think that the organs won’t grow indefinitely in the lymph nodes. The mini organs rely on chemical distress signals from the failing liver to grow; once the new organs have stabilized blood filtering, they will stop growing because that distress signal disappears, he says. But it’s not yet clear precisely how large the mini-livers will become in humans, he adds.

The company aims to enrol 12 people into the phase II trial by mid-2025 and publish results the following year, Hufford says. The trial, which was approved by US regulators in 2020, will not only measure participant safety, survival time and quality of life post-treatment, but will also help to establish the ideal number of mini livers to stabilize someone’s health. The clinicians running the trial will inject liver cells in up to five of a person’s lymph nodes to determine whether the extra organs can boost the procedure’s success rate.

A stop-gap measure

However, mini livers might not relieve all of the complications of end-stage liver disease, says Forbes, who has formed his own company to tackle liver disease using genetically modified immune cells that stimulate repair. One of the most serious of these is portal hypertension, in which the build-up of scar tissue compresses blood vessels in the liver and can cause internal bleeding.

Hufford acknowledges that the mini livers are not expected to address portal hypertension, but the hope is that they can provide a stopgap until a liver becomes available for transplant, or make people healthy enough to undergo a transplant. “That would be amazing, because these patients currently have no other treatment options,” Gouon-Evans says.

LyGenesis has ambitions beyond mini livers, too. The company is now testing similar approaches to grow kidney and pancreas cells in the lymph nodes of animals, Hufford says.

If the liver trial is successful, Gouon-Evans says, it would be worth investigating whether a person’s own stem cells could be used to generate the cells that seed the lymph nodes. This technique could create personalized cells that capture the diversity of cells in the liver and don’t require immunosuppressive drugs, she says.

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Google AI could soon use a person’s cough to diagnose disease

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Person coughing into their elbow while in bed.

The field of audiomics combines artificial intelligence tools with human sounds, such as a coughs, to evaluate health.Credit: Getty

A team led by Google scientists has developed a machine-learning tool that can help to detect and monitor health conditions by evaluating noises such as coughing and breathing. The artificial intelligence (AI) system1, trained on millions of audio clips of human sounds, might one day be used by physicians to diagnose diseases including COVID-19 and tuberculosis and to assess how well a person’s lungs are functioning.

This is not the first time a research group has explored using sound as a biomarker for disease. The concept gained traction during the COVID-19 pandemic, when scientists discovered that it was possible to detect the respiratory disease through a person’s cough2.

What’s new about the Google system — called Health Acoustic Representations (HeAR) — is the massive data set that it was trained on, and the fact that it can be fine-tuned to perform multiple tasks.

The researchers, who reported the tool earlier this month in a preprint1 that has not yet been peer reviewed, say it’s too early to tell whether HeAR will become a commercial product. For now, the plan is to give interested researchers access to the model so that they can use it in their own investigations. “Our goal as part of Google Research is to spur innovation in this nascent field,” says Sujay Kakarmath, a product manager at Google in New York City who worked on the project.

How to train your model

Most AI tools being developed in this space are trained on audio recordings — for example, of coughs — that are paired with health information about the person who made the sounds. For example, the clips might be labelled to indicate that the person had bronchitis at the time of the recording. The tool comes to associate features of the sounds with the data label, in a training process called supervised learning.

“In medicine, traditionally, we have been using a lot of supervised learning, which is great because you have a clinical validation,” says Yael Bensoussan, a laryngologist at the University of South Florida in Tampa. “The downside is that it really limits the data sets that you can use, because there is a lack of annotated data sets out there.”

Instead, the Google researchers used self-supervised learning, which relies on unlabelled data. Through an automated process, they extracted more than 300 million short sound clips of coughing, breathing, throat clearing and other human sounds from publicly available YouTube videos.

Each clip was converted into a visual representation of sound called a spectrogram. Then the researchers blocked segments of the spectrograms to help the model learn to predict the missing portions. This is similar to how the large language model that underlies chatbot ChatGPT was taught to predict the next word in a sentence after being trained on myriad examples of human text. Using this method, the researchers created what they call a foundation model, which they say can be adapted for many tasks.

An efficient learner

In the case of HeAR, the Google team adapted it to detect COVID-19, tuberculosis and characteristics such as whether a person smokes. Because the model was trained on such a broad range of human sounds, to fine-tune it, the researchers only had to feed it very limited data sets labelled with these diseases and characteristics.

On a scale where 0.5 represents a model that performs no better than a random prediction and 1 represents a model that makes an accurate prediction each time, HeAR scored 0.645 and 0.710 for COVID-19 detection, depending on which data set it was tested on — a better performance than existing models trained on speech data or general audio. For tuberculosis, the score was 0.739.

The fact that the original training data were so diverse — with varying sound quality and human sources — also means that the results are generalizable, Kakarmath says.

Ali Imran, an engineer at the University of Oklahoma in Tulsa, says that the sheer volume of data used by Google lends significance to the research. “It gives us the confidence that this is a reliable tool,” he says.

Imran leads the development of an app named AI4COVID-19, which has shown promise at distinguishing COVID-19 coughs from other types of cough3. His team plans to apply for approval from the US Food and Drug Administration (FDA) so that the app can eventually move to market; he is currently seeking funding to conduct the necessary clinical trials. So far, no FDA-approved tool provides diagnosis through sounds.

The field of health acoustics, or ‘audiomics’, is promising, Bensoussan says. “Acoustic science has existed for decades. What’s different is that now, with AI and machine learning, we have the means to collect and analyse a lot of data at the same time.” She co-leads a research consortium focused on exploring voice as a biomarker to track health.

“There’s an immense potential not only for diagnosis, but also for screening” and monitoring, she says. “We can’t repeat scans or biopsies every week. So that’s why voice becomes a really important biomarker for disease monitoring,” she adds. “It’s not invasive, and it’s low resource.”

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The Lazy Person’s Guide to ChatGPT

Lazy Person's Guide to ChatGPT

Let’s face it, sometimes laziness isn’t a vice, it’s a survival strategy. In our hyper-connected world, constantly striving for peak productivity can be as exhausting as it is unrealistic. But what if there was a way to embrace your inner sloth while still getting things done? Enter ChatGPT, the AI-powered language model that’s like a personal assistant for the chronically low-energy.

This guide is for the time-strapped, the easily distracted, and the champions of the nap. We’ll show you how to leverage ChatGPT’s superpowers to automate your life, conquer tedious tasks, and maybe even squeeze in an extra Netflix binge without guilt.

The world of artificial intelligence (AI) has witnessed remarkable advancements, and at the forefront is ChatGPT, a versatile AI developed by OpenAI. This tool, with its conversational abilities, has opened up new avenues for automating various tasks. The appeal of ChatGPT lies in its simplicity and accessibility, making it an ideal candidate for enhancing productivity, especially for those who prefer a more laid-back approach to technology.

Understanding ChatGPT

Before diving into the ways to use ChatGPT, it’s essential to understand what it is and how it works. ChatGPT is a variant of the GPT (Generative Pretrained Transformer) model, designed to understand and generate human-like text based on the input it receives. This makes it an excellent tool for conversation, content creation, and information retrieval.

Setting Up for Success

To get started, users need access to ChatGPT. It’s available on various platforms, including a web interface provided by OpenAI. Setting up involves creating an account and possibly choosing a subscription plan, depending on the level of usage anticipated.

Automating Daily Tasks

ChatGPT can handle a wide range of tasks. Here are some key areas where it can be particularly helpful:

  1. Email and Communication: ChatGPT can draft emails, create responses, and even manage basic communication needs. By inputting context or specific instructions, users can get a ready-to-send email draft in seconds.
  2. Scheduling and Reminders: For those who struggle with organization, ChatGPT can be a lifesaver. It can help structure daily schedules, set reminders, and even provide prompts for upcoming meetings or events.
  3. Content Creation: Whether it’s drafting a blog post, creating social media content, or even generating ideas for creative projects, ChatGPT is adept at understanding and producing various forms of content.
  4. Learning and Research: Need quick summaries of articles, or assistance with understanding complex topics? ChatGPT can break down information into digestible formats, making learning and research less daunting.
  5. Entertainment and Leisure: From generating personalized reading lists to suggesting movie recommendations, ChatGPT can enhance leisure time as well.

Advanced Automation

For individuals inclined to explore beyond the basics, ChatGPT’s capabilities can be significantly enhanced through integration with other tools and services, unlocking a new realm of possibilities. This expansion often involves utilizing Application Programming Interfaces (APIs), which are sets of protocols and tools for building software applications. By leveraging these APIs, users can seamlessly connect ChatGPT with various other software platforms and systems. This connectivity enables a wide array of functionalities, from streamlining complex workflows to enhancing data analysis processes.

Furthermore, for those with specific needs or unique challenges, ChatGPT can be customized to create tailored chatbots. These custom chatbots can be designed to cater to particular industries, such as customer service, healthcare, or education, providing targeted responses and interactions based on the unique requirements of these sectors. For instance, a custom chatbot in a customer service scenario can handle frequent inquiries, schedule appointments, and provide instant support, thereby increasing efficiency and customer satisfaction.

Ethical and Responsible Usage

While ChatGPT is a powerful tool, it’s important to use it ethically and responsibly. This means being aware of its limitations, respecting privacy, and not using it for deceptive or harmful purposes.

Conclusion

For the “lazy” person looking to boost productivity, ChatGPT offers a unique blend of ease and efficiency. It’s a testament to how AI can be harnessed to not just automate tasks but also to enhance daily life in a meaningful way. As AI continues to evolve, the potential for even more sophisticated forms of automation looks promising, paving the way for a future where technology and convenience coexist harmoniously.

This guide provides a starting point for those looking to integrate ChatGPT into their routine. It shows that you don’t have to be tech-savvy or deeply involved in the workings of AI to benefit from this incredible technology. ChatGPT stands as a bridge between advanced AI capabilities and the everyday user, offering a glimpse into a future where AI assists us in more ways than we could have imagined.

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