When scientists analyze complex human diseases, such as cancer, a crucial step involves comparing the DNA sequence of a diseased individual to a reference genome from a healthy individual. This analysis helps identify genetic variations that may contribute to the disease, enabling researchers to accurately categorize the illness and understand its treatment responses.
Since the year 2000, the standard human reference genome has been incomplete, limiting researchers’ ability to access certain challenging genomic regions. This resulted in false positives, complicating the identification of true genetic variants responsible for tumor growth.
In 2022, the Society of Scientists announced a groundbreaking achievement: the first truly complete human genome, generated using advanced technology that minimizes fragmentation. This development has prompted extensive research into the benefits of utilizing new genomes in the study of complex genetic diseases, including cancer.
Researchers based in Canada and the United States proposed that employing the complete human genome could enhance the detection of structural variants, allowing for more accurate cancer diagnosis compared to traditional reference genomes. This analogy likens genomic mutations to missing or altered paragraphs in a textbook; structural mutations can lead to cancer by duplicating oncogenes, causing abnormal gene fusions, and inactivating tumor-suppressor genes.
To validate their hypothesis, researchers utilized established cancer cell models, specifically cancer cell lines alongside the cancer-free control known as COLO829. This particular cell line serves as a benchmark for evaluating new mutation detection methods. They analyzed multiple samples of the COLO829 cell line sequenced by different laboratories, as well as tumor samples from patients diagnosed with blood cancer, brain cancer, and ovarian cancer, thereby ensuring a real-world context for their findings.
The complete human reference genome incorporates approximately 200 million additional base pairs, effectively filling in gaps and rectifying missing regions from the previous standard. When the COLO829 sample was examined, the number of structural variants incorrectly identified using the outdated reference genome significantly decreased, from 225 to just 83 with the new genome. This advancement greatly enhances our capability to detect structural variations.
The research team noted that while the new human reference genome improves the precision of DNA change identification, it contains less labeled medical information compared to the older genome. To address this, they employed a tool called Levio SAM2 to align results from new and previous genomes, thereby combining the enhanced accuracy of new genomes with the extensive medical knowledge of older references, yielding optimal results.
The team applied this integrated approach to three patient samples and discovered that the number of cancer-specific mutation candidates needing manual clinical review was significantly reduced compared to using traditional reference genomes. This reduction streamlines the labor-intensive process of identifying true cancer-causing mutations, with one large variant, 609,000 base pairs in length, identified in a patient’s sample. This variant exhibited minimal signals in the old reference genome but displayed clear evidence in the new genome.
In conclusion, the researchers’ approach enhances structural mutation detection in cancer by minimizing false positives, allowing physicians to prioritize clinically significant mutations. They emphasized that lowering false positives is crucial in analyzing patient samples, and filtering out spurious mutations to isolate genuine cancer drivers requires considerable time and expertise. Although their liftover strategy increased analysis time by approximately 50% compared to solely using the old reference genome, researchers deemed this trade-off acceptable due to the considerable improvements in accuracy.
A recent analysis of archival data from NASA’s Galileo spacecraft’s Near Infrared Mapping Spectrometer (NIMS) has uncovered the first evidence of ammonia-containing compounds on Jupiter’s icy moon Europa. This groundbreaking discovery provides vital clues about Europa’s subsurface ocean and recent geological activity.
This composite image highlights red pixels indicating sites on Europa where ammonia compounds were detected; purple indicates areas without detection. Image credit: NASA/JPL-Caltech.
“The detection of ammonia (NH3) is significant for understanding not only the geology of icy bodies in our solar system but also their potential habitability and astrobiological relevance,” stated Dr. Al Emran, a researcher at NASA’s Jet Propulsion Laboratory.
“On Europa, the identification of ammonia or ammoniated species is crucial for revealing ocean chemistry, assessing habitability, and reconstructing the moon’s early atmosphere.”
Ammonia functions as an antifreeze agent, reducing the freezing point of liquid water by up to 100 K, which may help preserve underground oceans in icy celestial bodies.
Though it’s unclear if Europa’s underground ocean is directly linked to the surface, detecting ammonia compounds could imply such a connection, given that these materials are unstable under cosmic radiation.
In a new study published in Planetary Science Journal, Dr. Emran reported detecting a distinct ammonia absorption feature at 2.20 microns in Europa’s near-infrared spectrum.
This signal was confirmed through observations from Galileo’s NIMS instrument, which examined Europa during a flyby in the 1990s.
Ammonia hydrate and ammonium chloride are likely responsible for the detected spectral features.
The instability of ammonia under strong cosmic radiation highlights the importance of its presence on Europa’s surface.
The discovery of ammonia-containing materials suggests they may have originated from Europa’s subsurface ocean or shallow subsurface during the moon’s geologically recent past, possibly through cryovolcanism or similar processes.
This analysis also hints at significant implications for Europa’s internal structure.
The presence of ammoniated compounds aligns with a subsurface ocean characterized by a thinner, chemically reduced ice shell with a higher pH.
Ammonia’s antifreeze properties are essential, as they lower the freezing point of water ice, allowing for the maintenance of a liquid ocean beneath Europa’s icy shell.
“Faint signals of ammonia have been detected near fractures in the moon’s frozen surface, where liquid water, rich in dissolved ammonia compounds, is expected to ascend,” Emran noted.
“These compounds might have traversed the surface due to recent geologically active cryovolcanic events.”
Ammonia’s presence, which significantly lowers the freezing point of water, acts as a natural antifreeze.
Similar ammonia-bearing species have been identified on other icy objects in the outer solar system, including Pluto, Charon, certain moons of Uranus, and Saturn’s moon Enceladus. However, earlier attempts to confirm ammonia’s presence on Europa produced inconclusive results.
“The identification of ammonia-containing compounds in this research marks the first evidence of nitrogen-based species on Europa, a finding of considerable astrobiological importance due to nitrogen’s fundamental role in life’s molecular structure,” Emran concluded.
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A. Emran. 2026. NH3 detection at Europa’s 2.2 μm absorption band. Planetary Science Journal 6,255; doi: 10.3847/PSJ/ae1291
Molecular gas and X-ray emissions around Sagittarius A*, a black hole in the Milky Way.
Mark D. Golsky et al. (CC by 4.0)
Researchers have confirmed that hot winds are emanating from the supermassive black hole at the center of the Galaxy for the first time.
In contrast to many other supermassive black holes throughout the universe, Sagittarius A* (SGR A*) remains relatively subdued. Unlike its more active counterparts that emit vast jets, SGR A* does not produce such striking displays. While many supermassive black holes create winds, which are streams of hot gas that originate near the event horizon, these have never been definitively observed around SGR A*, despite theoretical predictions dating back to the 1970s.
Mark Golsky and Elena Marchikova from Northwestern University, Illinois, utilized the Atacama Large Millimeter/submillimeter Array (ALMA) in Chile to conduct a more detailed study of the cold gas in the innermost region of the Circumnuclear Disk (CND). Their observations revealed an unexpectedly large volume of cold gas and a distinct cone that penetrates through the hot gas.
“To find such a significant amount of cold gas so close to the black hole was surprising,” says Golsky. “Conventional understanding suggested it was unlikely to be there, which is why we hadn’t previously searched for it. When I shared this image, my colleague remarked, ‘We need to investigate this further, as it’s been a puzzle for over 50 years.’”
Golsky and Marchikova’s five years of observations provided a detailed analysis of the innermost part of the CND, mapping cold gases within a vicinity of SGR A* 100 times previous measurements. By simulating and subtracting the bright variability of SGR A*, they could isolate the dim light from the cold gas.
This approach revealed a pronounced cone region nearly devoid of cold gas, and when they overlaid X-ray emissions (produced by the hot gas), a striking correlation emerged. The energy required to propel the hot gas through this cone approximates that of 25,000 suns—far too substantial to originate from nearby stars or supernovae, indicating it likely derives from SGR A* itself. “The energy necessary comes directly from the black hole, confirming the presence of winds originating from it,” Golsky states.
<p>Prior observations have identified expansive gas bubbles, known as Fermi bubbles, situated above and below the galaxy. However, the possibility of these jets reforming remains uncertain. Understanding this wind phenomenon sheds light on why SGR A* shows lower activity and enhances our comprehension of black hole evolution.</p>
<p>The implications of the reduced wind activity surrounding SGR A* are exciting. If verified, findings by <a href="https://scholar.google.com/citations?user=1VNwK9gAAAAJ&hl=en">Ziri Younsi</a> from University College London could offer crucial insights into the nature of the black hole, including its rotational direction. Astronomers have postulated that SGR A* spins perpendicular to the Milky Way plane, implying a need for edge-on observation. However, the inaugural image of a black hole captured by the Event Horizon Telescope in 2022 produced inconclusive data, suggesting a possible in-person orientation.</p>
<p>“The mass of Sagittarius A* is well-defined by current observations, but its tilt angle relative to us remains largely unknown,” explains Younsi. “If these findings are robust, understanding the origins of these matter flows will be genuinely fascinating, as it will provide insights into how material spirals toward the black hole, contributing to our knowledge of galactic evolution.”</p>
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Teenager language may make online bullying difficult to detect
Vitapix/Getty Images
The terminology of Generation Alpha is evolving faster than educators, parents, and AI can keep up with.
Manisha Meta, a 14-year-old student from Warren E Hyde Middle School in Cupertino, California, alongside Fausto Giunchiglia from the University of Trent in Italy, examined 100 expressions popular among Generation Alpha, those born from 2010 to 2025, sourced from gaming, social media, and video platforms.
The researchers then asked 24 classmates of Mehta, aged between 11 and 14, to evaluate these phrases along with contextual screenshots. The volunteers assessed their understanding of the phrases, the contexts in which they were used, and if they carried potential safety risks or harmful interpretations. They also consulted their parents, professional moderators, and four AI models (GPT-4, Claude, Gemini, and Llama 3) for the same analysis.
“I’ve always been intrigued by Generation Alpha’s language because it’s so distinctive; relevance shifts rapidly, and trends become outdated just as quickly,” says Mehta.
Among the Alpha generation volunteers, 98% grasped the basic meaning of a given phrase, 96% understood the context of its use, and 92% recognized instances of harmful intent. In contrast, the AI model could identify harmful usage only around 40% of the time, with Claude stumbling from 32.5% to 42.3%. Parents and moderators also fell short, detecting harmful usages in just one-third of instances.
“We expected a broader comprehension than we observed,” Mehta reflects. “Much of the feedback from my parents was speculative.”
Common phrases from Generation Alpha often have double meanings based on context. For instance, “Let’s Cook His” can signify genuine praise in gaming but may also mockingly refer to someone rambling incoherently. “Kys,” once short for “know yourself,” has now been repurposed to mean “kill yourself.” Another phrase that could hide malicious intent is, “Is it acoustic?”
“Generation Alpha is exceedingly vulnerable online,” says Meta. “As AI increasingly dominates content moderation, understanding the language used by LLMs is crucial.”
“It’s evident that LLMs are transforming the landscape,” asserts Giunchiglia. “This presents fundamental questions that need addressing.”
The results were published this week at the Computing Machinery Conference Association on Equity, Accountability and Transparency in Athens, Greece.
“Empirical evidence from this research highlights significant shortcomings in content moderation systems, especially concerning the analysis and protection of young individuals,” notes Michael Veal from University College London. “Companies and regulators must heed this and adapt as regulations evolve in jurisdictions where platform laws are designed to safeguard the youth.”
The newly discovered radio jet is associated with J1601+3102, a highly radioloud kusar that spans an astounding 215,000 light years and exists just 1.2 billion years after the Big Bang. This structure was observed on a low-frequency array (LOFAR), Gemini North Telescope from the Gemini Near-Frared Spectrograph (GNIRS), and the hobby Eberly telescope, and the largest radio jet discovered early in the history of the universe. That's it.
“We were looking for a quasar with a powerful radio jet in the early universe, which helped us understand how the first jets were formed and how they influenced the evolution of the galaxy. ”
“Determining the properties of a quasar, such as its mass and the speed at which it consumes the problem, is necessary to understand its formation history.”
To measure these parameters, astronomers looked for specific wavelengths emitted by quasars known as the MGII (magnesium) wide emission lines.
This signal is usually displayed in the UV wavelength range. However, due to the expansion of the universe, which causes the light emitted by the quasar to “stretch” to a longer wavelength, the magnesium signal arrives at Earth in the near-infrared wavelength range that can be detected by the Gneal.
J1601+3102 Quasar was formed when the universe was less than 1.2 billion years. It's only 9% of my current age.
Quasars can have billions of times more mass than our Sun, but this is on the small side and weighs 450 million times the mass of the Sun.
The double-sided jets are asymmetric in both brightness and distance extending from the quasar, indicating that extreme environments may be affecting them.
“Interestingly, the quasars that run this large radio jet don't have any extreme black holes mass compared to other quasars,” Dr. Gloudemans said.
“This appears to indicate that generating such a powerful jet in early universes does not necessarily require very large black holes or accretion rates.”
The previous shortage of large radio jets in early space is attributed to noise from the microwave background of the universe. This is a constant fog of microwave radiation remaining from the Big Bang.
This permanent background radiation usually reduces the radio light of such distant objects.
“Because this object is so extreme, it can actually be seen from the Earth, even if it's far away,” Dr. Gloudemans said.
“This object shows us what we can discover by combining the forces of multiple telescopes operating at different wavelengths.”
result It will be displayed in Astrophysics Journal Letter.
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Anniek J. Gloudemans et al. 2025. Monster radio jet (>66 kpc) observed in quasars from z~5. apjl 980, L8; doi: 10.3847/2041-8213/AD9609
This article is based on a press release provided by NSF's Noirlab.
We are constantly detecting lies in our daily interactions. This could be a change in our partner’s tone of voice indicating hidden emotions, a child repeatedly looking at a forbidden present, or a colleague’s implausible story about missing petty cash at work.
Despite our ability to detect some lies, there are still instances where we fail to see through deception. Researchers have been investigating this phenomenon for over a century, with the latest studies offering new insights into the complexities of deception.
One recent significant study conducted by Associate Professor Timothy Luke and his team at the University of Gothenburg focused on analyzing the behaviors associated with lying. By delving into the nuances of deceit, they aimed to uncover the underlying processes of deception.
One key aspect highlighted by Luke is the distinction between “white” lies and deception, emphasizing that not all lies are equal. Deception involves deliberate attempts to mislead others, with various psychological factors influencing the complexity of deceit. Factors like communication style and length play crucial roles in distinguishing lies from truth.
While conventional beliefs suggest that liars exhibit behaviors like avoiding eye contact and nervousness, research findings from the Gothenburg study challenge these assumptions. Experts in the field of lie detection agree that gaze aversion and nervousness are not reliable indicators of deception.
Photo courtesy of Getty Images, Alamy. Image manipulation: Andy Potts.
Instead, experts suggest that the level of detail in the information provided can be a more reliable indicator of deception. People who lie tend to offer less detailed explanations compared to truth-tellers. Linguistic cues, such as inconsistencies in statements and evidence, also play a significant role in detecting deception.
When it comes to distinguishing truth from lies, researchers recommend employing a strategic approach that challenges inconsistencies in suspects’ narratives without direct accusations of lying. By presenting contradictory evidence and observing the suspect’s responses, investigators can uncover potential deception.
Photo courtesy of Getty Images, Alamy. Image manipulation: Andy Potts.
While traditional approaches to lie detection based on behavioral cues may be unreliable, focusing on individual characteristics and personal deceit patterns can offer more effective ways of uncovering lies. By examining linguistic patterns and analyzing personal deception models, researchers are improving their ability to detect deception effectively.
Ultimately, trust in one’s own investigative skills and evidence-based analysis is crucial in detecting lies. Fixed cues and generalizations may not always be accurate, emphasizing the importance of caution and critical thinking when assessing deceptive behaviors.
a While there has been widespread panic over drones and other unknown low-flying objects in New Jersey in recent days, many other parts of the country are still concerned about the very American nature of the skies, which has been resurgent in modern times. A mysterious person is happily captured by a UFO.
At the newly opened National UFO Historical Records Center – A cluster of beige buildings on the grounds of Martin Luther King Jr. Elementary School in Rio Rancho, New Mexico – Literally dozens of files detailing the unexplained flying object and the terror of those around it. It fills the cabinet.
For director David Marler, this first-of-its-kind public archive of UFO historical records is the culmination of a lifelong interest and investigation into UFOs, or UAPs, as the military now prefers to designate them, or unidentified anomalous phenomena.
It came at the perfect time. In recent years, Congressional and Senate hearings have brought the topic, which often rises and falls in public attention during times of national or political unrest, back into the spotlight.
Images taken last week showed what appeared to be several drones over New Jersey. Composite: TMX over AP
Mahler's collection of UFO books, magazines, magazines, newspapers, microfilms, audio recordings, and case files from the past 75 years is impressive, as well as files from early U.S. Air Force research (Project Sign, Project Grudge, and Project Blue Book). Included. by the National Commission on the Study of Aeronautical Phenomena, the Institute for the Study of Aeronautical Phenomena (formerly based in Alamogordo, three and a half hours away), and the UFO Research Committee of the United States. Akron, Ohio.
A September 13, 1959 military report details an object rotating seven times, marking four military radar stations in New Mexico traveling much faster than the Convair 106, the fastest fighter plane of the time. tracked by.
“The Air Force was interested in national defense in the same way it is today, not from a quote-unquote 'alien perspective,'” Mahler says. “For practical reasons, especially because qualified military and civilian pilots report these things.”
At a Congressional hearing last monthwitnesses claimed that the government was sitting on a trove of information about the UAP dating back decades. Two former Navy pilots said they witnessed first-hand unexplained objects that regularly violate U.S. airspace.
Retired Major David Gruesch, a former member of the Pentagon's UAP Task Force, said the U.S. government has been running a secret program for years to reverse engineer inhuman material taken from crash sites.
However, the United States Old Main Anomaly Resolution Officeor AARO, founded in 2022, said there is no single explanation that addresses the majority of UAP reports, namely “anomalous detections,” and that no evidence of extraterrestrial technology has been found.
David Gruesch stands at the Capitol building in Washington, DC, on July 26, 2023. Photo: Drew Angerer/Getty Images
AARO Director John Koslosky at Senate hearing said “Reports of unidentified anomalous phenomena, especially near national security locations, must be treated seriously by the U.S. government and investigated with scientific rigor.”
Marler, who has been following the issue relentlessly since he went looking for UFOs with his father when sightings were on the rise in Missouri, says he is neutral on the phenomenon.
“One has to be skeptical, look at the evidence objectively, and suspend conclusions and beliefs,” he says. “What I believe doesn't really matter unless there's data to support it.”
Earlier this year, the New York software company released Enigma, an app that collects sightings by uploading videos and photos with descriptions…
The probability that one word follows another can be used to create watermarks for AI-generated text.
Vikram Arun/Shutterstock
Google uses artificial intelligence watermarks to automatically identify text generated by its Gemini chatbot, making it easier to distinguish between AI-generated content and human-written posts. This watermarking system could help prevent AI chatbots from being exploited for misinformation and disinformation, as well as fraud in schools and business environments.
Now, the technology company says it is making available an open-source version of its technology so that other generative AI developers can similarly watermark output from their large-scale language models. I am. Pushmeet Kohli Google DeepMind is the company's AI research team, combining the former Google Brain and DeepMind labs. “SynthID is not a silver bullet for identifying AI-generated content, but it is an important building block for developing more reliable AI identification tools,” he says.
Independent researchers expressed similar optimism. “There is no known way to reliably watermark, but I really think this could help detect some things like AI-generated misinformation and academic fraud,” he said. I say. scott aaronson at the University of Texas at Austin, where he previously worked on AI safety at OpenAI. “We hope that other leading language modeling companies, such as OpenAI and Anthropic, will follow DeepMind’s lead in this regard.”
In May of this year, Google DeepMind announced Google announced that it has implemented the SynthID method for watermarking AI-generated text and video from Google's Gemini and Veo AI services, respectively. The company recently published a paper in the journal nature SynthID generally performs better than similar AI watermarking techniques for text. The comparison involved evaluating how easily the responses from different watermarked AI models were detectable.
In Google DeepMind's AI watermarking approach, as a model generates a sequence of text, a “tournament sampling” algorithm subtly moves it toward selecting “tokens” of specific words that are detectable by associated software. Create a statistical signature. This process randomly pairs candidate word tokens in tournament-style brackets. The winner of each pair is determined by which one gets the highest score according to the watermark function. Winners advance through successive tournament rounds until there is one round remaining. The “layered approach” “further complicates the potential for reverse engineering and attempts to remove watermarks,” it said. Yellow Furong at the University of Maryland.
It said a “determined adversary” with vast computational power could remove such AI watermarks. Hanlin Zhang at Harvard University. But he said SynthID's approach makes sense given the need for scalable watermarking in AI services.
Google DeepMind researchers tested two versions of SynthID that represent a trade-off between making watermark signatures easier to detect in exchange for distorting the text typically produced by AI models. They showed that the undistorted version of the AI watermark continued to work without noticeable impact on the quality of the 20 million text responses Gemini generated during live experiments.
However, the researchers also acknowledged that this watermarking works best on long chatbot responses that can be answered in a variety of ways, such as composing an essay or an email, as well as on math or coding questions. The response to this has not yet been tested.
Google DeepMind's team and others have stated the need for additional safeguards against misuse of AI chatbots, and Huang similarly recommended stronger regulation. “Requiring watermarks by law addresses both practicality and user adoption challenges and makes large language models more secure to use,” she says.
Researchers are experimenting with biosensors that can monitor workers’ vital signs and provide warnings if they show signs of heatstroke.
The four-year study involves more than 150 farmworkers in Florida who have been wearing sensors in the fields.
Agricultural workers are 35 times more likely to die from heatstroke than other workers.
People who work outdoors are at greatest risk from extreme heat, which can be fatal within minutes, so researchers have begun experimenting with wearable sensors that can monitor workers’ vital signs and warn them if they are starting to show the early symptoms of heatstroke.
In Pearson, Florida, where temperatures can soar to nearly 90 degrees just before and after noon, workers on a fern farm wear experimental biopatches as part of a study sponsored by the Environmental Protection Agency. National Institutes of HealthThe patch also measures a worker’s vital signs and skin hydration, and is equipped with a gyroscope to monitor continuous movement.
Scientists from Emory University and Georgia Tech are collecting data and feeding it into an artificial intelligence algorithm. The ultimate goal is for the AI to predict when workers are likely to suffer from heatstroke and send them a warning on their phone before that happens. But for now, the researchers are still analyzing the data and plan to publish a research paper next year.
“There’s a perception that field work is hot, and that’s the reality,” says Roxana Chicas, a nurse researcher at Emory University who has been overseeing Biopatch data collection. “I think with research and creativity, we can find ways to protect field workers.”
average 34 workers died of heatstroke According to the Environmental Protection Agency, farmworkers will be killed every year from 1992 to 2022. 35x odds Workers are more likely to die from heatstroke than other workers, but until now it has been left to states to decide how to protect workers from heatstroke. California, for example, requires employers to provide training, water, and shade when temperatures exceed 80 degrees Fahrenheit, but many states have no such rules.
Chicas and his team partnered with the Florida Farmworkers Association to recruit participants for the study, aiming to have 100 workers wear the biopatch over the four-year study, but were surprised by how many volunteered, ultimately enrolling 166.
Participating workers arrive at work before dawn, receive a patch, have their vital signs monitored, and then head out into the fields before the hottest, most dangerous parts of the day.
“We hope this study will help improve working conditions,” study participant Juan Pérez said in Spanish, adding that he has worked in the fern fields for 20 years and would like more breaks and higher wages.
Other farmworkers said they hoped the study would shed light on just how tough their jobs are.
Study participant Antonia Hernandez, who lives in Pearson, said she often worries about the heat hazards facing her and her daughter, who both work in fern fields.
“When you don’t have a family, the only thing you worry about is the house and the rent,” Hernandez said in Spanish. “But when you have children, the truth is, there’s a lot of pressure and you have to work.”
Chicas said he could see the heat-related fatigue showing on some of the workers’ faces.
“They look much older than their real age, some of them look much older than their real age, because it takes a toll on their body and their health,” she said.
Chikas has been researching ways to protect farmworkers from the heat for nearly a decade. In a project that began in 2015, workers were fitted with bulky sensors that measured skin temperature, skin hydration, blood oxygen levels, and vital signs. This latest study is the first to test a lightweight biopatch that looks like a large bandage and is placed in the center of the chest.
Overall, wearable sensors are much easier to use, and some are becoming more widely used. While the biosensors that Cikas’ team is experimenting with aren’t yet available to the public, a brand called SlateSafety sells a system (sponsored by the Occupational Safety and Health Administration) that is available to employers. The system includes an armband that transmits measurements of a worker’s core temperature to a monitoring system. If the temperature is too high, the employer can notify the worker to take a break.
A similar technology, called the Heat Stroke Prevention System, is used in the military. Developed by the U.S. Army Institute of Environmental Medicine, the system requires soldiers or Marines in a company to wear a chest strap that estimates core temperature, skin temperature and gait stability, allowing commanders to understand a soldier’s location and risk of heatstroke.
“The system is programmed to sense when a person is approaching higher than appropriate levels of heat exposure,” says Emma Atkinson, a biomedical researcher at the institute. stated in a news release “Our system allows us to provide warnings before heat stroke occurs, allowing us to intervene before someone collapses,” the report, released in February, added.
The system that Chicas and his team are developing differs from those systems in that it notifies workers directly, rather than in a larger system controlled by their employers. They haven’t finished collecting data from farmworkers yet, but the next step is for algorithms to start identifying patterns that might indicate risk of heatstroke.
“Outdoor workers need to spend time outdoors – otherwise food wouldn’t be harvested, ferns wouldn’t be cut, houses wouldn’t be built,” Chicas said. “With the growing threat of climate change, workers need something to better protect themselves.”
Utilizing artificial intelligence to analyze GP records for hidden patterns has significantly improved cancer detection rates for doctors.
The “C the Signs” AI tool used by general practitioner practices has increased cancer detection rates from 58.7% to 66.0%. This tool examines patients’ medical records, compiling past medical history, test results, prescriptions, treatments, and personal characteristics like age, postcode, and family history to indicate potential cancer risks.
Additionally, the tool prompts doctors to inquire about new symptoms and recommends tests or referrals for patients if it detects patterns suggesting a heightened risk of certain cancer types.
Currently in use in about 1,400 practices in England, “C the Signs” was tested in 35 practices in the East of England in May 2021, covering 420,000 patients.
Published in the Journal of Clinical Oncology, a study revealed that cancer detection rates rose from 58.7% to 66.0% by March 31, 2022, in clinics using the system, while remaining similar in those that did not utilize it.
Dr. Bea Bakshi, who developed “C the Signs” with colleague Miles Paling, emphasized the importance of early and quick cancer diagnosis through their system detecting over 50 types of cancer.
The tool was validated in a previous study analyzing 118,677 patients, where 7,295 were diagnosed with cancer and 7,056 were accurately identified by the algorithm.
Notably, the system’s ability to predict if a patient was unlikely to have cancer resulted in only 2.8% of these cases being confirmed with cancer diagnosis within six months.
Concerned by delays in cancer diagnosis, Bakshi developed the tool after witnessing a patient’s late pancreatic cancer diagnosis three weeks before their death, highlighting the importance of early detection.
“With two-thirds of deaths from untestable cancers, early diagnosis is crucial,” Bakshi emphasized.
In the UK, GPs follow National Institute for Health and Care Excellence guidelines to decide when to refer patients for cancer diagnosis, guided by tools like “C the Signs.”
The NHS’s long-term cancer plan aims to diagnose 75% of cancers at stage 1 or 2 by 2028, utilizing innovative technologies like the Garelli blood test for early cancer detection.
Decision support systems like “C the Signs,” improving patient awareness of cancer symptoms, and enhancing access to diagnostic technologies are essential for effective cancer detection, according to healthcare professionals.
NHS England’s national clinical director for cancer, Professor Peter Johnson, highlighted the progress in increasing early cancer diagnoses and access to timely treatments, emphasizing the importance of leveraging technology for improved cancer care.
As a human, you will play a crucial role in identifying whether a photo or video was created using artificial intelligence.
Various detection tools are available for assistance, either commercially or developed in research labs. By utilizing these deepfake detectors, you can upload or link to suspected fake media, and the detector will indicate the likelihood that it was generated by AI.
However, relying on your senses and key clues can also offer valuable insights when analyzing media to determine the authenticity of a deepfake.
Although the regulation of deepfakes, especially in elections, has been slow to catch up with AI advancements, efforts must be made to verify the authenticity of images, audio, and videos.
One such tool is the Deepfake Meter developed by Siwei Lyu at the University at Buffalo. This free and open-source tool combines algorithms from various labs to help users determine if media was generated by AI.
The DeepFake-o-meter demonstrates both the advantages and limitations of AI detection tools by rating the likelihood of a video, photo, or audio recording being AI-generated on a scale from 0% to 100%.
AI detection algorithms can exhibit biases based on their training, and while some tools like DeepFake-o-meter are transparent about their variability, commercial tools may have unclear limitations.
Lyu aims to empower users to verify the authenticity of media by continually improving detection algorithms and encouraging collaboration between humans and AI in identifying deepfakes.
audio
A notable instance of a deepfake in US elections was a robocall in New Hampshire using an AI-generated voice of President Joe Biden.
When subjected to various detection algorithms, the robocall clips showed varying probabilities of being AI-generated based on cues like the tone of the voice and presence of background noise.
Detecting audio deepfakes relies on anomalies like a lack of emotion or unnatural background noise.
photograph
Photos can reveal inconsistencies with reality and human features that indicate potential deepfakes, like irregularities in body parts and unnatural glossiness.
Analyzing AI-generated images can uncover visual clues such as misaligned features and exaggerated textures.
An AI-generated image purportedly showing Trump and black voters. Photo: @Trump_History45
Discerning the authenticity of AI-generated photos involves examining details like facial features and textures.
video
Video deepfakes can be particularly challenging due to the complexity of manipulating moving images, but visual cues like pixelated artifacts and irregularities in movements can indicate AI manipulation.
Detecting deepfake videos involves looking for inconsistencies in facial features, mouth movements, and overall visual quality.
The authenticity of videos can be determined by analyzing movement patterns, facial expressions, and other visual distortions that may indicate deepfake manipulation.
“Ash light” or AL is a faint mysterious glow or hue seen in the night hemisphere of Venus. It is often compared to Earthshine, the reflected light that illuminates the far side of the Moon.
First described by Italian astronomer Giovanni Riccioli in 1643, AL has been observed many times since then, but its faint, ephemeral, and elusive nature has prevented serious research. It’s here.
Even more problematic, AL has so far only been detected by the human eye, and no scientific instruments, either earth-based or space-based, have recorded this phenomenon.
Some authorities have declared this phenomenon to be an illusion, perhaps an eye contrast effect or even an “expectation bias.” Some have suggested that a defect in the equipment could explain the phenomenon. Light scattering, optical aberrations, background sky brightness, weather, etc.
But there are enough reliable reports about AL that some scientists can offer an explanation. These include reflected light from Earth, auroras, “airglow” radiation, lightning, and infrared (thermal) radiation from Venus’ atmosphere.
Most of these explanations are ignored for some reason. However, there is ample evidence that not only ultraviolet light from the sun, but also high-energy solar wind particles can excite oxygen atoms in Venus’ atmosphere.
This creates a pale green glow similar to that seen in the aurora borealis on Earth. However, the process is somewhat different because auroras on Earth are caused by Earth’s magnetic field interacting with solar particles, whereas Venus has no appreciable magnetic field.
It remains to be seen whether this explanation can explain all or some of the AL observations. Therefore, the long-standing mystery of AL may still turn out to be an illusion.
This article is an answer to the question (asked by Herman Townsend of Liverpool): “What is Ashen Light?”
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Scientists who study cancer have historically focused on understanding the various factors that contribute to cancer development and progression. They have looked at factors such as genes, lifestyle choices, and even bacteria. However, few researchers have investigated the role of fungi in the human body and how they affect cancer.
Researchers in Israel and the United States recently characterized the fungi that live inside human cancer tissue. Researchers took tumor, blood and plasma samples from more than 1,000 of her patients with various types of cancer and performed a type of “DNA sequencing.” ITS2 amplicon sequencing. They used this sequencing method to determine the presence of different fungal species within cancer tissue and measure the number of fungal cells living there.
Researchers found fragments of fungal DNA and cells in tissues from various human cancers. For example, they discovered several types of fungi associated with breast cancer. Cladosporium sphaerospermum, mainly affected patients over 50 years of age. they again, Malassezia globosaa skin fungus that affects pancreatic cancer patients, and Malassezia restriction bacterium, another skin fungus present in breast cancer tissue. Additionally, they discovered the following species: aspergillus and agar medium Found in lung cancer samples, especially those from smoking patients.
The researchers explained that their results were surprising. Skin fungi are not usually associated with breast cancer. Additionally, they suggested: Malassezia globosa DNA found in both breast and pancreatic cancer samples This suggests that it may play a broader role in cancer development.
The scientists then confirmed that the fungus was growing within the cancerous tumor using a method called . tissue staining. Histological staining is like adding color to a black and white photograph. In this case, the photos were of tissue taken from different types of cancer: melanoma, pancreatic cancer, breast cancer, lung cancer, and ovarian cancer. When we stained these tissues, we found that fungi often existed next to cancer cells.
The research team interpreted the results as indicating that fungi can influence cancer progression. They suggested that these fungi may have a commensal or even pathogenic relationship with cancer. In particular, they suggested that the fungus may function as follows. opportunistic pathogensIn other words, they were taking advantage of patients' weakened immune systems to cause infections that would not normally occur in healthy people.
Finally, the researchers used an advanced computational technique known as . machine learning, recognize and identify patterns in DNA data. They wanted to test whether certain types of fungi were present in different types of cancer. Scientists have determined that different types of cancer tissue are inhabited by different fungal communities.
The scientists concluded that understanding the relationship between fungi and cancer could help doctors develop new tools to diagnose and treat cancer patients. In particular, the researchers suggested that doctors could sort the fungal DNA in a patient's blood sample to detect which type of cancer they have. They suggested that fungi may provide a new non-invasive fingerprint for early detection of cancer.
We naturally detect lies all the time. It can be a drop in our partner's voice that alerts us to the fact that they are hiding their feelings. The eyes of a child return to the drawer containing the present they are not allowed to open. Or the incredible story told by a colleague trying to explain why the company's petty cash went missing.
However, we often cannot see through the lies. why? Researchers have been trying to answer this question for more than a century, but liars still slip through our hands. But the latest research may help shed light on where we went wrong.
But first they needed to determine exactly what a lie was. We might use the word “lie” to refer to someone who says they look good in clothes they don't know whether they fit, a partner who seems to be trying to hide an affair, or a murderer who claims to be innocent. yeah. But are they comparable? Surely some lies carry more weight than others? Luke likes to distinguish between “white” lies and what he calls deception.
“The structure of deception is more complex than many people think,” he says. “There may be a variety of psychological processes underlying it. We're not talking about the same thing. Even superficial things like the length and type of communication are important.”
Whether you're texting a lie or telling someone a lie to their face, Luke says the core of deception is a deliberate attempt to mislead another person. But determining what is a lie is another thing. Detecting it is another thing entirely. Is there really a surefire clue to someone else's deception?
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Can you spot a liar just by looking at their eyes?
A common belief is that people who lie are reluctant to meet the gaze of others. Still, in the Gothenburg study, 82 percent of experts agreed that people who lie are less likely to avoid eye contact or look away than people who tell the truth.
“Empirical research on deception detection is vast,” he says. Per Anders Grand Hug, professor of psychology at the University of Gothenburg and one of the co-authors of the study. “But the one issue most experts agree on is that gaze aversion is not a diagnostic clue for deception.”
Similarly, 70% of experts agreed that liars appear no more nervous than truth tellers. This may be surprising since nervousness and gaze aversion are two of her four main behaviors that a liar exhibits.
Photo courtesy of Getty Images, Alamy. Image manipulation: Andy Potts.
Other traditional indicators include that liars continually change their posture, touch their body frequently, and offer explanations that are less plausible, logical, or consistent than they would be if they were telling the truth. There are things to do.
These beliefs are also based on shaky empirical evidence. The researchers investigated deception and fidgeting (body movements), how long subjects took to answer questions (response latency), and whether subjects' explanations were consistent, meaningful, and easily expressed ( found that the relationship between fluency and fluency was not clear. cut. Some experts said liars do these things more, some less, and others said there was no difference.
read more:
words are important
Professor Aldert FreiThe University of Portsmouth expert on the psychology of deception, who was not involved in the Gothenburg study, said the most widespread misconception about deception was “the idea that nonverbal lie detection works”. ing.
He suggests that people who try to use nonverbal lie detection methods, even if those methods include polygraphs, video analysis, taking brain “fingerprints” using neuroimaging equipment, or using audio Even if it involves technologies such as change exploration, it means we need to proceed with caution. Pitch – These are all controversial areas in deception detection research.
is that so Any What is an effective way to spot a liar? According to Luke, he has one promising lead. It's the lack of detail. About 72% of experts agreed that people who lie provide less detailed information than people who tell the truth.
Vrij agreed, saying that instead of looking at how people behave, find out what they say. He said there are several linguistic indicators, such as the number of details or “complexity” that appear in the subjects' statements.
…
Despite problems associated with purported behavioral cues, such as gaze aversion, many practitioners are reluctant to replace them with more useful cues based on what the suspect says. , says Vrij. Old myths and methods slowly disappear.
“The most annoying thing is the assumptions that come from the TV programs that lead the general public.” [and] “Experts believe they can catch individual liars.” Professor Amina Memon He is a professor at the University of London, a leading expert on lie detection and interrogation, and one of the co-authors of the Gothenburg study.
Police who have a hunch about a suspect based on a typical profile of a liar may use coercive tactics such as getting innocent people to confess to crimes they did not commit. For this reason, Memon advocates interviewing with a neutral, fact-finding approach, rather than guessing whether someone is lying.
Photo courtesy of Getty Images, Alamy. Image manipulation: Andy Potts.
But behind all this lies a bigger problem. Perhaps the reason we haven't found universal clues to deception is because they simply don't exist.
Over the past century, researchers have almost exclusively adopted what is known as the non-theoretical approach. This means they are looking for the “laws” of deception, the clues that everyone shows. But perhaps the reason this kind of one-size-fits-all approach doesn't work is simply because everyone lies differently.
Poker players apply this logic when looking for other players' “tells,” actions that indicate whether that person is bluffing or not. Tellurium varies from person to person, so some people may scratch their nose when their hands are not feeling well, others may cough more, and others may seem calmer than usual.
Even if you throw these three people into a research setting, a theoretical approach will not work. These differences appear to be just noise.
Signs of lying
If we want to understand the cues, Luke argues, researchers need to take an “ideographic” approach and focus on what makes each individual unique. This involves creating a personal profile of how each person lies about the same types of things and in similar situations.
“Testing the same people under different conditions (a so-called 'repeated measures' experimental design) is the best approach,” Memon says.
It remains to be seen how researchers will overcome the logical hurdles, but it seems clear that the science of lie detection is changing. It's time to move away from what Luke calls “crude averages.” “People are a little too fascinated by cool tricks to spot someone's lies,” he says.
Importantly, researchers studying deception have repeatedly found that evidence from controlled environments shows that most people are bad at detecting lies. is. Liars are able to escape detection in part because they know and exploit stereotypes.
Photo courtesy of Getty Images, Alamy. Image manipulation: Andy Potts.
Our confirmation bias can also make us overconfident. We remember a disproportionate amount of the times when we caught a liar, and we don't notice the times when we didn't lie at all.
Even if we succeed, Luke is not convinced that the clues we think we used are really the keys we used to unlock the truth.
“Remember the last time you caught someone in a lie? How did you know?” he asks. “It probably wasn't because they were looking up and left. They probably had some kind of evidence, like receipts, text messages, witnesses. These are things that make people wonder if someone is offering the truth. That’s how we tend to actually judge whether or not.”
Even in the absence of concrete external evidence, it may be possible to assess situational factors. “In the real world, we can often understand to some extent why people would want to lie,” Luke says.
When someone we know is lying, we can better guess from subtle cues such as their gaze because we know them well. In these situations, Luke says it's best to read the situation better than the other person and try to understand their motives.
The key message is that behavioral cues to deception may exist, but they are likely to be highly personal. “It's better to trust your own detective work and check what people say against the evidence,” says Luke.
Fixed cues won't work. In fact, it can make it even harder to spot a liar. And what if no evidence is found? Luke's advice is simple. “Proceed with caution.”
Researchers have discovered a way to detect Parkinson’s disease up to 30 years before symptoms appear using biomarkers and PET scans. This breakthrough includes tracking neurodegeneration more sensitively than current methods and shows that rapid eye movement sleep behavior disorder (RBD) is an important early indicator of Parkinson’s disease. is identified. This discovery could lead to earlier diagnosis and treatment, potentially up to 10 years earlier than currently.
Researchers at The Florey and Austin Health in Melbourne, Australia, have demonstrated the potential to identify early indicators of Parkinson’s disease 20 to 30 years before the onset of symptoms. This breakthrough paves the way for early screening programs and intervention, potentially allowing treatment before significant damage occurs.
Researchers at the Florey Institute and Austin Health have demonstrated the possibility of identifying early indicators of Parkinson’s disease 20 to 30 years before the onset of symptoms. This breakthrough paves the way for early screening efforts and preventive treatment, long before permanent damage occurs.
Florey Professor Kevin Burnham said that although Parkinson’s disease, a debilitating neurodegenerative disease, is often thought of as a disease of the elderly, it actually begins in midlife and can last for decades. He said it may not be detected.
“Parkinson’s disease is very difficult to diagnose until symptoms become apparent, by which time up to 85 percent of the neurons in the brain that control motor coordination have been destroyed. At that point, many treatments are likely to be ineffective,” Professor Burnham said. “Our long-term goal is to find ways to detect diseases earlier and treat people before they cause harm.”
Advanced diagnostic technology
In a recently published study, neurologylead researcher Professor Burnham and colleagues explore how a known biomarker called F-AV-133 can be used in positron emission tomography (PET) scans to diagnose Parkinson’s disease and accurately track neurodegeneration. I’m explaining how it can be done.
In the Melbourne study, Austin Health’s Frawley Professor Chris Rowe and his team studied 26 patients with Parkinson’s disease, 12 controls, and 11 patients with rapid eye movement sleep behavior disorder (RBD), a strong indicator of Parkinson’s disease. I checked the name. .
Each person underwent two PET scans two years apart. Key findings include:
Currently available assessments of Parkinson’s disease showed no significant changes in clinical symptoms in any of the participants.
In contrast, PET scans showed “significant neuronal loss” in three key areas of the brains of people with the disease, making F-AV-133 more effective than what is currently available. also suggests that it is a sensitive means of monitoring neurodegeneration.
Further mathematical modeling yields the following calculation:
Slow nerve cell loss over a total of approximately 33 years in Parkinson’s disease
This loss takes about 10.5 years before the disease is detected on a PET scan.
Even if a PET scan detects the disease, it will take another six and a half years for motor symptoms to appear.
It takes about 3 years after physical symptoms appear until a clinical diagnosis is confirmed.
This corresponds to approximately 22.5 years of neuronal loss before clinical symptoms are sufficient for diagnosis.
Professor Burnham said the findings pave the way for the development of screening protocols to diagnose and treat Parkinson’s disease up to 10 years earlier than is currently possible. It may also help identify patients for clinical trials.
What is RBD?
RBD stands for Rapid Eye Movement Behavior Disorder.
Patients with RBD scream, thrash, and sometimes move violently during sleep, enacting vivid and disturbing dreams.
RBD is caused by a lack of muscle relaxation (sleep paralysis).
90% of RBD patients develop Parkinson’s disease.
Half of all Parkinson’s patients have RBD.
RBD is an important warning sign for early Parkinson’s disease.
If you have RBD, see a sleep specialist or neurologist.
Reference: “Use of 18F-AV-133 VMAT2 PET Imaging to Monitor Progressive Nigrostriatal Degeneration in Parkinson’s Disease”, Leah C. Beauchamp, Vincent Dore, Victor L. Villemagne, SanSan Xu, David Finkelstein, Kevin J. Barnham, Christopher Rowe, 28 November 2023 neurology. DOI: 10.1212/WNL.0000000000207748
Astronomers have detected a rare and extremely energetic particle falling to Earth.
Scientists say the ray, named after the Japanese sun goddess Amaterasu, is one of the most energetic cosmic rays ever detected.
The Amaterasu particle has an energy of more than 240 exaelectron volts (EeV), making it the second particle in recorded history, after another ultra-high-energy cosmic ray, the Oh My God particle (320 EeV), detected in 1991.
The origins of the particles are unknown, but experts believe that only the most powerful astronomical phenomena, larger than an exploding star, can produce them.
Toshihiro Fujii, associate professor at Osaka Metropolitan University, Japansaid that when he first discovered this particle, he thought, “There must have been a mistake.”
“We’ve seen energy levels unprecedented in the last 30 years,” he said.
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The particle seems to come out of nowhere, further deepening the mystery for scientists.
John Matthews, a research professor in the University of Utah’s Department of Physics and Astronomy, explains that there was nothing in the area high-energy enough to cause this phenomenon.
It appeared to emerge from the Local Void, the empty space adjacent to the Milky Way.
“We should be able to point to where in the sky they came from,” Professor Matthews says.
“But in the case of the Oh My God particle and this new particle, even if we trace its trajectory back to its source, there is nothing high enough energy to produce it.
“That’s the mystery – what the hell is going on?”
Typically, when ultra-high-energy cosmic rays hit Earth’s atmosphere, they create a cascade of secondary particles and electromagnetic radiation known as a massive air shower.
Some charged particles in air showers travel faster than the speed of light and produce a type of electromagnetic radiation that can be detected with special equipment.
One of those instruments is the Telescope Array Observatory in Utah, which discovered the Amaterasu particle.
image: Telescope Array Surface Detector in Utah.Photo: Associated Press
It is now hoped that this particle will pave the way for further research that will help uncover ultrahigh-energy cosmic rays and their origins.
Experts suggest this may indicate a much larger magnetic deflection than predicted, an unidentified source within the local void, or an incomplete understanding of high-energy particle physics.
Another Utah professor, John Beltz, said he was “throwing out crazy ideas” to try to explain the mystery.
“These events appear to be coming from completely different places in the sky. There is no one mysterious source,” he said. “It could be a flaw in the fabric of space-time, causing cosmic strings to collide.”
However, he added, “There is no conventional explanation.”
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