Greece is just one example of a population where the share of older people is expanding, and with it the incidences of neurodegenerative diseases. Among these, Alzheimer’s disease is the most prevalent, accounting for 70% of neurodegenerative disease cases in Greece. According to estimates published by the Alzheimer Society of Greece, 197,000 people are suffering from the disease at present. This number is expected to rise to 354,000 by 2050.
Dr. Andreas Papadopoulos1, a physician and scientific coordinator at Iatropolis Medical Group, a leading diagnostic provider near Athens, Greece, explains the key role of early diagnosis: “The likelihood of developing Alzheimer’s may be only 1% to 2% at age 65. But then it doubles every five years. Existing drugs cannot reverse the course of the degeneration; they can only slow it down. This is why it’s crucial to make the right diagnosis in the preliminary stages—when the first mild cognitive disorder appears—and to filter out Alzheimer’s patients2.”
Diseases like Alzheimer’s or other neurodegenerative pathologies characteristically have a very slow progression, which makes is difficult to recognize and quantify pathological changes on brain MRI images at an early stage. In evaluating scans, some radiologists describe the process as one of “guesstimation,” as visual changes in the highly complex anatomy of the brain are not always possible to observe well with the human eye. This is where technical innovations such as artificial intelligence can offer support in interpreting clinical images.
One such tool is the AI-Rad Companion Brain MR3. Part of a family of AI-based, decision-support solutions for imaging, AI-Rad Companion Brain MR is a brain volumetry software that provides automatic volumetric quantification of different brain segments. “It is able to segment them from each other: it isolates the hippocampi and the lobes of the brain and quantifies white matter and gray matter volumes for each segment individually.” says Dr. Papadopoulos. In total, it has the capacity to segment, measure volumes, and highlight more than 40 regions of the brain.
Calculating volumetric properties manually can be an extremely laborious and time-consuming task. “More importantly, it also involves a degree of precise observation that humans are simply not able to achieve.” says Dr. Papadopoulos. Papadopoulos has always been an early adopter and welcomed technological innovations in imaging throughout his career. This AI-powered tool means that he can now also compare the quantifications with normative data from a healthy population. And it’s not all about the automation: the software displays the data in a structured report and generates a highlighted deviation map based on user settings. This allows the user to also monitor volumetric changes manually with all the key data prepared automatically in advance.
Opportunities for more accurate observation and evaluation of volumetric changes in the brain encourages Papadopoulos when he considers how important the early detection of neurodegenerative diseases is. He explains: “In the early stages, the volumetric changes are small. In the hippocampus, for example, there is a volume reduction of 10% to 15%, which is very difficult for the eye to detect. But the objective calculations provided by the system could prove a big help.”
The aim of AI is to relieve physicians of a considerable burden and, ultimately, to save time when optimally embedded in the workflow. An extremely valuable role for this particular AI-powered postprocessing tool is that it can visualize a deviation of the different structures that might be hard to identify with the naked eye. Papadopoulos already recognizes that the greatest advantage in his work is “the objective framework that AI-Rad Companion Brain MR provides on which he can base his subjective assessment during an examination.”
AI-Rad Companion4 from Siemens Healthineers supports clinicians in their daily routine of diagnostic decision-making. To maintain a continuous value stream, our AI-powered tools include regular software updates and upgrades that are deployed to the customers via the cloud. Customers can decide whether they want to integrate a fully cloud-based approach into their working environment leveraging all the benefits of the cloud or a hybrid approach that allows them to process imaging data within their own hospital IT setup.
The upcoming software version of AI-Rad Companion Brain MR will contain new algorithms that are capable of segmenting, quantifying, and visualizing white matter hyperintensities (WMH). Along with the McDonald criteria, reporting WHM aids in multiple sclerosis (MS) evaluation.
The EU wants to put companies on the hook for harmful AI
The new bill, called the AI Liability Directive, will add teeth to the EU’s AI Act, which is set to become EU law around the same time. The AI Act would require extra checks for “high risk” uses of AI that have the most potential to harm people, including systems for policing, recruitment, or health care.
The new liability bill would give people and companies the right to sue for damages after being harmed by an AI system. The goal is to hold developers, producers, and users of the technologies accountable, and require them to explain how their AI systems were built and trained. Tech companies that fail to follow the rules risk EU-wide class actions.
For example, job seekers who can prove that an AI system for screening résumés discriminated against them can ask a court to force the AI company to grant them access to information about the system so they can identify those responsible and find out what went wrong. Armed with this information, they can sue.
The proposal still needs to snake its way through the EU’s legislative process, which will take a couple of years at least. It will be amended by members of the European Parliament and EU governments and will likely face intense lobbying from tech companies, which claim that such rules could have a “chilling” effect on innovation.
In particular, the bill could have an adverse impact on software development, says Mathilde Adjutor, Europe’s policy manager for the tech lobbying group CCIA, which represents companies including Google, Amazon, and Uber.
Under the new rules, “developers not only risk becoming liable for software bugs, but also for software’s potential impact on the mental health of users,” she says.
Imogen Parker, associate director of policy at the Ada Lovelace Institute, an AI research institute, says the bill will shift power away from companies and back toward consumers—a correction she sees as particularly important given AI’s potential to discriminate. And the bill will ensure that when an AI system does cause harm, there’s a common way to seek compensation across the EU, says Thomas Boué, head of European policy for tech lobby BSA, whose members include Microsoft and IBM.
However, some consumer rights organizations and activists say the proposals don’t go far enough and will set the bar too high for consumers who want to bring claims.
China is betting big on another gas engine alternative: methanol cars
Today, the leading company making methanol from carbon dioxide is Carbon Recycling International, an Icelandic company. Geely invested in CRI in 2015, and they have partnered to build the world’s largest CO2-to-fuel factory in China. When it’s running, it could recycle 160,000 tons of CO2 emissions from steel plants every year.
The potential for clean production is what makes methanol desirable as a fuel. It’s not just a more efficient way to use energy, but also a way to remove existing CO2 from the air. To reach carbon neutrality by 2060, as China has promised, the country can’t put all its eggs in one basket, like EVs. Popularizing the use of methanol fuel and the clean production of methanol may enable China to hit its target sooner.
Can methanol move beyond its dirty roots?
But the future is not all bright and green. Currently, the majority of methanol in China is still made by burning coal. In fact, the ability to power cars with coal instead of oil, which China doesn’t have much of, was a major reason the country pursued methanol in the first place. Today, the Chinese provinces that lead in methanol-car experiments are also the ones that have abundant coal resources.
But as Bromberg says, unlike gas and diesel, at least methanol has the potential to be green. The production of methanol may still have a high carbon footprint today, just as most EVs in China are still powered by electricity generated from coal. But there is a path to transition from coal-produced methanol to renewables-produced methanol.
“If that is not an intention—if people are not going to pursue low-carbon methanol—you really don’t want to implement methanol at all,” Bromberg says.
Methanol fuel also has other potential drawbacks. It has a lower energy density than gasoline or diesel, requiring bigger, heavier fuel tanks—or drivers may need to refuel more often. This also effectively prevents methanol from being used as an airplane fuel.
What’s more, methanol is severely toxic when ingested and moderately so when inhaled or when people are exposed to it in large amounts. The potential harm was a big concern during the pilot program, though the researchers concluded that methanol proved no more toxic to participants than gas.
Beyond China, some other countries, like Germany and Denmark, are also exploring the potential of methanol fuels. China, though, is at least one step ahead of the rest—even if it remains a big question whether it will replicate its success in developing EVs or follow the path of another country with a major auto industry.
In 1982, California offered subsidies for car manufacturers to make over 900 methanol cars in a pilot program. The Reagan administration even pushed for the Alternative Motor Fuels Act to promote the use of methanol. But a lack of advocacy and the falling price of gasoline prevented further research of methanol fuel, and pilot drivers, while generally satisfied with their cars’ performance, complained about the availability of methanol fuel and the smaller range compared with gas cars. California officially ended the use of methanol cars in 2005, and there’s been no such experimentation in the US since.
Can we find ways to live beyond 100? Millionaires are betting on it.
But to test the same treatments in people, we’d need to run clinical trials for decades, which would be very difficult and extremely expensive. So the hunt is on for chemical clues in the blood or cells that might reveal how quickly a person is aging. Quite a few “aging clocks,” which purport to give a person’s biological age rather than their chronological age, have been developed. But none are reliable enough to test anti-aging drugs—yet.
As I leave to head back to my own slightly less posh but still beautiful hotel, I’m handed a gift bag. It’s loaded up with anti-aging supplements, a box with a note saying it contains an AI longevity assistant, and even a regenerative toothpaste. At first glance, I have absolutely no idea if any of them are based on solid science. They might be nothing more than placebos.
Ultimately, of all the supplements, drugs and various treatments being promoted here, the workout is the one that’s most likely to work, judging from the evidence we have so far. It’s obvious, but regular exercise is key to gaining healthy years of life. Workouts designed to strengthen our muscles seem to be particularly beneficial for keeping us healthy, especially in later life. They can even help keep our brains young.
I’ll be penning a proper write up of the conference when I’m back home, so if your curiosity has been piqued, keep an eye out for that next week! In the meantime, here’s some related reading:
- I wrote about what aging clocks can and can’t tell us about our biological age earlier this year.
- Anti-aging drugs are being tested as a way to treat covid. The idea is that, by rejuvenating the immune system, we might be able to protect vulnerable older people from severe disease.
- Longevity scientists are working to extend the lifespan of pet dogs. There’ll be benefits for the animals and their owners, but the eventual goal is to extend human lifespan, as I wrote in August.
- The Saudi royal family could become one of the most significant investors in anti-aging research, according to this piece by my colleague Antonio Regalado. The family’s Hevolution Foundation plans to spend a billion dollars a year on understanding how aging works, and how to extend healthy lifespan.
- While we’re on the subject of funding, most of the investment in the field has been poured into Altos Labs—a company focusing on ways to tackle aging by reprogramming cells to a more youthful state. The company has received financial backing from some of the wealthiest people in the world, including Jeff Bezos and Yuri Milner, Antonio explains.
From around the web
An experimental Alzheimer’s drug appears to slow cognitive decline. It’s huge news, given the decades of failed attempts to treat the disease. But the full details of the study have not yet been published, and it is difficult to know how much of an impact the drug might have on the lives of people with the disease. (STAT)
Bionic pancreases could successfully treat type 1 diabetes, according to the results of a clinical trial. The credit card-sized device, worn on the abdomen, can constantly monitor a person’s blood sugar levels, and deliver insulin when needed. (MIT Technology Review)
We’re headed for a dementia epidemic in US prisons. There’s a growing number of older inmates, and the US penal system doesn’t have the resources to look after them. (Scientific American)
Unvaccinated people are 14 times more likely to develop monkeypox disease than those who receive the Jynneos vaccine are, according to the US Centers for Disease Control and Prevention. But the organization doesn’t yet know how the vaccine affects the severity of disease in those who do become unwell, or if there is any difference in protection for people who are given fractional doses. (The New York Times $)
Don’t call them minibrains! In last week’s Checkup, I covered organoids—tiny clumps of cells meant to mimic full-grown organs. They’ve mainly been used for research, but we’ve started to implant them into animals to treat disease, and humans are next. Arguably the best-known organoids are those made from brain cells, which have been referred to as minibrains. A group of leading scientists in the field say this wrongly implies that the cells are capable of complex mental functions, like the ability to think or feel pain. They ask that we use the less-catchy but more accurate term “neural organoid” instead. (Nature)
That’s it for this week. Thanks for reading!