Breakdown of Protein Production May Contribute to Brain Aging

Ribosome (center) responsible for synthesizing protein (red) from mRNA. Dark purple strands illustrate transfer RNAs involved in protein production.

The underlying factors contributing to cellular senescence may have been uncovered, revealing insights into various aging processes at the cellular level.

Studies on the brains of a type of freshwater fish known as Killifish reveal that as these fish age, their internal protein factories begin to malfunction, leading to critical protein classes being synthesized abnormally and creating a damaging feedback loop.

This revelation could pave the path for innovative approaches to addressing cognitive decline in aging; Alessandro Cellerino from the Leibniz Institute on Aging in Germany states, “Our focus is more on enhancing cognitive function and preventing cognitive impairment, rather than merely extending life span.”

Within cells, the templates for protein synthesis are encoded in DNA. When proteins are required, these instructions are transcribed into mRNA molecules.

This mRNA is then processed and transported to ribosomes, the cellular factories responsible for protein assembly. Ribosomes attach to and traverse mRNA strands, interpreting the three-letter codons and translating them into amino acid sequences, ultimately forming proteins.

Typically, a greater quantity of mRNA leads to increased protein synthesis. However, numerous studies indicate that this relationship falters in aging human cells, suggesting that protein output may diminish even if mRNA levels remain unchanged.

Through their investigation of aging ribosomes in the brains of Killifish, Cellerino and his team may have identified the cause of this phenomenon. Employing advanced imaging techniques, the researchers captured dynamic movements of ribosomes on constrained mRNA.

The findings revealed that, as the Killifish brain aged, an unexpected buildup of ribosomes occurred, particularly at codons for the amino acids arginine and lysine, leading to stalled ribosome activity and incomplete protein synthesis.

Arginine and lysine are crucial for numerous biomolecules associated with DNA and RNA, and their charged nature suggests that these stallings could significantly disrupt RNA and DNA-binding proteins.

These protein malfunctions pose a serious issue, as they are integral to crucial cellular processes such as RNA synthesis, splicing, and DNA repair.

“Aging is associated with increased DNA damage, reduced RNA production, decreased splicing efficiency, and diminished protein synthesis,” explains Cellerino. “We propose that this ribosome stalling binds these diverse senescence phenomena together.”

Moreover, Cellerino notes that ribosomes themselves harbor RNA-binding proteins, creating a detrimental cycle of stalling that further reduces ribosome availability and, accordingly, protein production.

The pressing question remains whether ribosomal stalling is also present in the human brain. Recent work by Jean Yeo at UC San Diego indicates that RNA-binding proteins diminish in aging human neurons, echoing Cellerino’s findings, although the underlying causes are still uncertain. “This change in RNA-binding proteins could explain their declining levels,” Yeo states.

If these observations hold true for humans, it could herald new strategies for treating age-associated cognitive disorders. Additionally, in Killifish, ribosomal stalling triggers stress signals that instigate inflammatory responses. “The persistent activation of this pathway leads to chronic inflammation,” warns Cellerino. “Chronic inflammation is a significant factor in brain aging.”

Experimental drugs that may mitigate this condition by blocking the associated signaling pathways are on the horizon, according to Cellerino.

“However, it is premature to draw definitive conclusions regarding their potential impact on longevity,” he cautions. This uncertainty arises from the lack of understanding regarding the initiation of ribosomal stalling at specific amino acids, as well as whether the same stalling mechanism exists across all organs.

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Source: www.newscientist.com

Advanced AI Experiences “Total Accuracy Breakdown” When Confronted with Complex Issues, Research Finds

Researchers at Apple have identified “fundamental limitations” in state-of-the-art artificial intelligence models, prompting concerns about the competitive landscape in the tech industry for developing more robust systems.

In a study, Apple noted that the advanced AI model, known as the large-scale inference model (LRMS), experienced a “complete collapse in accuracy” when faced with complex challenges.

Standard AI models outperformed LRMS on tasks of lower complexity, yet both encountered “complete collapse” on highly complex tasks. LRMS attempts to handle intricate queries by creating detailed reasoning processes to break down issues into manageable steps.


The research, which evaluated the models’ puzzle-solving capabilities, revealed that LRMS began to “reduce inference efforts” as it neared performance breakdowns—something researchers labeled as “particularly concerning.”

Gary Marcus, a noted academic voice on AI capabilities, characterized the Apple paper as “quite devastating” and highlighted that these findings raise pivotal concerns regarding the race towards achieving artificial general intelligence (AGI), which would enable systems to emulate human-level cognitive tasks.

Referencing large language models (LLMs), Marcus remarked: “[of] AGIs, who can fundamentally change society, are joking about themselves.”

Moreover, the paper indicated that early in the “thinking” process, the inference model often squandered computational resources seeking solutions for simpler problems. However, as complexity increased, the model initially considered incorrect answers before ultimately arriving at correct ones.

When confronted with complex issues, the model experienced “collapse” and failed to generate accurate solutions. In one instance, it could not succeed even with an algorithm provided to assist.

The findings illustrated that “as problem difficulty rises, models begin to intuitively diminish inference efforts as they approach critical thresholds that closely align with the accuracy collapse point.”

According to Apple experts, these findings highlight “fundamental scaling limitations” in the reasoning capabilities of current inference models.

The study involved LRMS-based assignments like the Tower of Hanoi and River Crossing puzzle. The researchers acknowledged that their focus on puzzles signifies a boundary to their work.

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The study concluded that current AI methodologies may have hit fundamental limitations. Models tested included OpenAI’s O3, Google’s Gemini Thinking, Anthropic’s Claude 3.7 Sonnet-Thinking, and Deepseek-R1. Google and Deepseek will be approached for comments, while OpenAI, the organization behind ChatGPT, opted not to provide a statement.

Discussing AI models’ capacity for “generalizable reasoning” or broader conclusions, the paper observes:

Andrew Rogoiski from the People-centered AI Institute at Surrey University remarked that Apple’s findings illustrate the industry remains grappling with AGI, suggesting that the current methods may have hit a “dead end.”

He added, “The revelation that the large model underperforms on complex tasks while faring well in simpler or medium-complexity contexts indicates we may be approaching a profound impasse.”

Source: www.theguardian.com

Metamoderator Opens Up About Breakdown Following Exposure to Beheading and Child Abuse: ‘I Couldn’t Eat or Sleep’

When Solomon* entered the gleaming Octagon Tower in Accra, Ghana, he was embarking on his journey as a meta content moderator. Tasked with removing harmful content from social media, he faced a challenging yet rewarding role.

However, just two weeks into his training, he encountered a much darker side of the job than he had anticipated.

“I initially didn’t encounter graphic content, but eventually, it escalated to images of beheadings, child abuse, bestiality, and more. The first time I saw that content, I was completely taken aback.”




Octagon Building in Accra. Photo: foxglove

“Eventually, I became desensitized and began to normalize what I was seeing. It was disturbing to find myself watching beheadings and child abuse.”

“I’ll never forget that day,” Solomon recounted, having arrived from East Africa in late 2023. “The system doesn’t allow you to skip. You must view it for a minimum of 15 seconds.”

In one particular video, a woman from his homeland cried for help as several assailants attacked her.

He noted that this exposure was increasingly unsettling. One day there were no graphic videos, but as a trend emerged, suddenly around 70-80% of the content became graphic. He gradually felt “disconnected from humanity.”

In the evenings, he returned to shared accommodations provided by his employer, the outsourcing firm Telepelforming, where he faced issues related to privacy, water, and electricity.

When Solomon learned of his childhood friend’s death, it shattered his already fragile mental state. He was Broken, feeling trapped in his thoughts, and turned to Telepelforming for a temporary escape until he could regain his composure.

Isolating himself for two weeks, he admitted, “I began to spiral into depression. I stopped eating and sleeping, smoking day in and day out. I was never this way before.”

Solomon tried to take his own life and was hospitalized, where he was diagnosed with major depressive disorder and suicidal ideation. He was discharged eight days later, towards the end of 2024.

Telepelforming offered him a lower-paying position, but he feared it would not suffice to live in Accra. He sought compensation for his distress and long-term psychological care, but instead, Telepelforming sent him back to his hometown amid unrest.

“I feel used and discarded. They treated me like a disposable water bottle,” Solomon expressed after his termination.

He reflected on his past professional life in his home country, saying, “I was content and at peace before coming here.”

Another moderator, Abel*, defended Solomon and shared how he ended his contract in solidarity with fellow employees.

He confronted Telepelforming: “You’re not treating him fairly.”

“They isolated him at home. He felt unsafe being alone, which caused him severe stress, prompting him to return to work.”

Abel also faced mental health struggles stemming from the content. “I was unaware of the nature of the job and the reality of viewing explicit material for work… The first time I encountered blood, I was left numbed.”

He mentioned that colleagues often gathered to sip coffee and discuss disturbing material, even sharing their discomfort.

He hesitated to discuss these issues with wellbeing coaches due to a fear of how his concerns would be perceived by his team leader. He faced challenges when he declined to utilize a wellness service he believed was merely for “research purposes.”

A spokesman for Telepelforming stated: Recognizing his depression following his friend’s death, we conducted a psychological evaluation and found he was unfit to continue in a moderation role.

“We offered a different non-moderating position, which he declined, expressing a desire to remain in his current role. With that not being a viable option, his employment ended, and he was provided compensation per our contractual agreement.

“Throughout his tenure and afterward, we ensured ongoing psychological support. He consistently declined assistance. At the suggestion of his family, help was arranged for him, and upon medical approval, arrangements for a flight to Ethiopia were made.

“We have maintained support for him in Ethiopia, but he has avoided it, instead attempting to pressure Telepelforming for monetary compensation under the threat of public exposure.”

*The name has been changed to protect their identity

Source: www.theguardian.com

ARC-AGI-2: Breakdown of Leading AI Model in Latest Artificial General Information Evaluation

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The ARC-AGI-2 benchmark is designed to be a difficult test for AI models

Just_Super/Getty Images

The most sophisticated AI models present today are inadequate scores on new benchmarks designed to measure progress towards artificial general information (AGI), and brute-force computing power is not sufficient to improve as evaluators consider the cost of running the model.

There are many competing definitions of AGI, but it is generally thought to refer to AI capable of performing cognitive tasks that humans can do. To measure this, the ARC Awards Foundation previously began a test of reasoning ability called ARC-AGI-1. Last December, Openai announced that the O3 model scored highly in tests, with some asking if the company is approaching AGI achievement.

But now the new test, the ARC-AGI-2, has raised the bar. Although current AI systems on the market are difficult enough to not achieve a score of over 100 digits of 100 in tests, all questions have been answered by at least two people on less than two attempts.

in Blog post Introducing the ARC-AGI-2, ARC president Greg Kamradt said a new benchmark is needed to test skills that differ from previous iterations. “To beat it, you need to demonstrate both high levels of adaptability and high efficiency,” he writes.

The ARC-AGI-2 benchmark differs from other AI benchmark tests in that it focuses on the ability to match the world’s leading PHD performance, but on the ability to complete simple tasks, such as replicating new image changes based on past examples of iconic interpretations. The current model is superior to “deep learning” measured by ARC-AGI-1, but not so good for seemingly simple tasks that require more challenging thinking and interaction with ARC-AGI-2. For example, Openai’s O3-low model won 75.7% on the ARC-AGI-1, but only 4% on the ARC-AGI-2.

This benchmark also adds a new dimension to measure AI capabilities by examining the efficiency of problem solving, as measured at the cost required to complete the task. For example, ARC paid a human tester $17 per task, while O3-low estimates that it would cost $200 for the same task.

“I think ARC-AGI’s new iteration, which now focuses on balancing performance and efficiency, is a major step towards a more realistic evaluation of the AI ​​model,” he says. Joseph Imperial At the University of Bath, UK. “This is a sign that we are moving from a one-dimensional evaluation test that is not only focusing on performance, but also considering a decline in computing power.”

Models that can pass the ARC-AGI-2 should not only be very capable, but also be smaller and lighter, Imperial says. Model efficiency is a key component of the new benchmark. This helps address concerns that AI models are becoming more energy-intensive Sometimes to the point of waste – to achieve much better results.

However, not everyone is convinced that the new measure will be beneficial. “The whole framing of this to test intelligence is not the correct framing.” Catherine Frick At Staffordshire University, UK. Instead, these benchmarks are extrapolated to imply general functionality across a set of tasks, simply by assessing the ability of AI to properly complete a single task or a set of tasks.

Working well with these benchmarks should not be seen as a major moment for AGI, Flick said:

And another question is what will happen if ARC-AGI-2 is given, or when it is given. Do you need yet another benchmark? “If they develop ARC-AGI-3, I guess they’ll add another axis to the graph [the] The minimum number of humans – whether expert or not, it will take a task to solve, in addition to performance and efficiency,” says Imperial. In other words, discussions about AGI rarely resolve immediately.

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Source: www.newscientist.com

How tractor beams could soon become a reality: A breakdown of how they’ll work

A beam is a stream of particles moving from a source to a target, exerting a pushing force rather than a pulling force on the target.

On Earth, we can use a vacuum cleaner to pull something towards us, but in reality, we are creating a pressure difference that causes the remaining air molecules to push the object.

This method is not considered a beam and would not work in space where there are no molecules in a vacuum.


However, in space, objects can be moved without using beams. The “gravity tractor” is a concept for a spacecraft that would maneuver near an asteroid and utilize mutual gravity to alter its trajectory.

The spacecraft uses ion thrusters to counteract the gravitational pull of the asteroid, effectively pulling it forward at a controlled pace.

Although gravity is a universal force present between all objects with mass, it is relatively weak.

As an alternative, the European Space Agency (ESA) has explored the possibility of utilizing electrostatic attraction as a stronger force. However, this force can be neutralized due to the canceling of positive and negative charges on objects.

The ESA study discussed methods to charge an asteroid, such as bombarding it with electrons to create a charged object that can be influenced by the spacecraft charged to around 20,000 volts, acting as a type of tractor beam.

While this method is slower than a science fiction tractor beam, it demonstrates a potential approach to manipulating objects in space.

This article was written in response to a question from Alexandra Rowland about the feasibility of a Star Trek-style tractor beam.

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Source: www.sciencefocus.com

Breakdown products of Vitamin B3 in excess may increase the risk of cardiovascular disease

Despite intensive efforts to prevent cardiovascular disease (CVD), substantial residual CVD risk remains, even in people who receive all guideline-recommended interventions. Niacin (vitamin B3) is an essential micronutrient fortified in staple foods, but its role in CVD is poorly understood. Excessive amounts of niacin's breakdown products may be associated with an increased risk of death, heart attack, and stroke, according to a new study.

Niacin is an essential micronutrient that is fortified in staple foods beyond dietary requirements. Image credit: Ferrell other., doi: 10.1038/s41591-023-02793-8.

Although CVD is a major cause of morbidity and mortality worldwide, only a portion of the attributable risk is explained by established risk factors.

Despite significant advances in treatment, the risk of residual cardiovascular disease remains high, and it has been suggested that additional, as yet unrecognized factors contribute to cardiovascular disease.

Research has previously shown that niacin (vitamin B3) reduces levels of low-density lipoprotein cholesterol.

However, this vitamin does not seem to have the expected effect in reducing CVD risk, the so-called “niacin paradox”.

“Our study shows that niacin breakdown products can promote vascular inflammation, providing a potential explanation for this discrepancy,” said Cleveland Clinic researcher Stanley Hazen, Ph.D. said.

In the study, the authors analyzed plasma samples from 4,325 people in three patient cohorts, including men and women from the United States and Europe.

They found that two breakdown products of niacin, the metabolites N1-methyl-2-pyridone-5-carboxamide (2PY) and N1-methyl-4-pyridone-3-carboxamide (4PY), are associated with increased CVD risk. I discovered that

In subsequent human genetic studies and mouse studies, the research team found that this increased risk is due to these breakdown products increasing the abundance of the pro-inflammatory protein VCAM-1 within the endothelial cells lining the blood. showed that it may be mediated by the ability of one of the (4PY). ship.

“Further studies are needed in large-scale studies to investigate the association between niacin and its degradation products and CVD,” the researchers said.

their findings It was published in the magazine natural medicine.

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M. Ferrell other. 2024. End metabolites of niacin promote vascular inflammation and contribute to cardiovascular disease risk. Nat Med 30, 424-434; doi: 10.1038/s41591-023-02793-8

Source: www.sci.news