Falls among older adults often begin with changes too subtle to be noticed during an ordinary walk. A person may still appear steady while moving through a familiar environment, yet struggle when asked to divide attention between walking and another task. A new study by researchers Dong, Hu, Guo and colleagues examines whether machine-learning techniques can identify this hidden vulnerability in community-dwelling older adults by analyzing how gait changes during dual-task walking. Published in BMC Geriatrics in 2026, the research focuses on a potentially powerful combination of digital movement measurement and artificial intelligence: spatiotemporal gait parameters recorded while people walk and perform a second mental or motor activity.
Walking is not a single, automatic action. It requires continuous coordination between the brain, muscles, sensory systems and balance mechanisms. When a person walks while counting backward, answering questions or carrying an object, the nervous system must distribute attention between locomotion and the competing task. This is known as dual-task walking. Older adults who have limited cognitive or physical reserve may respond by slowing down, shortening their steps, widening their base of support or becoming more irregular in their timing. These adaptations can provide clues about fall susceptibility that may remain invisible during conventional clinical walking tests.
The study’s central idea is that gait should be evaluated under realistic cognitive pressure rather than only in ideal, distraction-free conditions. Spatiotemporal gait parameters describe measurable features of movement across time and space, including walking speed, stride length, step time, cadence, stance duration and the variability between consecutive steps. In a dual-task setting, researchers can also examine the degree to which these variables change compared with normal walking. This difference, often called dual-task cost, can reveal how much a person’s mobility is affected when attention is divided. A larger cost may indicate reduced ability to manage competing demands while remaining stable.
Machine learning offers a way to analyze these patterns simultaneously. Traditional clinical assessment may focus on one or two measurements, such as walking speed or the number of previous falls. A machine-learning model can process many variables at once and search for combinations associated with elevated risk. Depending on the model design, the system may learn from labeled examples, in which participants’ gait data are linked to fall-related outcomes, and then estimate risk for new individuals. Algorithms can detect nonlinear relationships that are difficult to capture with conventional statistical methods, although their usefulness depends heavily on the quality, size and representativeness of the data used for training.
The community setting is especially important. Many studies of balance and falls are conducted in hospitals or specialist laboratories, where participants may be healthier, more closely supervised or less representative of the broader older population. Community-dwelling adults live independently and encounter the complex conditions that make falls more likely: distractions, uneven surfaces, hurried movement, household obstacles and the need to perform several tasks at once. By focusing on this group, the research addresses a practical question for preventive medicine: can accessible gait testing identify people who appear independent but may require additional support before a serious fall occurs?
A potential advantage of this approach is its ability to move fall-risk assessment toward objective, repeatable measurement. Gait sensors, pressure-sensitive walkways, wearable devices or camera-based systems can convert movement into numerical data. Those data may be more sensitive than a brief visual observation, particularly when they capture step-to-step variability and changes induced by a secondary task. In the future, similar measurements could potentially be collected in clinics, rehabilitation centers or even at home. However, a prediction tool would need to be tested across different ages, health conditions, walking environments and technology platforms before it could be trusted for widespread use.
The research also highlights the technical challenges behind apparently simple predictions. Falls are influenced by numerous factors, including muscle strength, vision, medication use, reaction time, fear of falling, neurological disease and environmental hazards. Gait features alone cannot explain every incident. A machine-learning model may also perform impressively on the data used to develop it but less reliably on people from another population, a problem known as limited generalizability or overfitting. For clinical adoption, researchers must therefore evaluate calibration, sensitivity and specificity, test the model on independent datasets and make its decisions understandable to health professionals and patients.
Although the citation identifies the study’s objective and methodology, it does not provide detailed numerical findings such as sample size, predictive accuracy or the specific algorithm used. Those results will determine how close this technology is to practical deployment. Even so, the study reflects a broader shift in geriatric care: fall prevention is increasingly being treated as a problem of measurable, dynamic performance rather than a simple checklist of past incidents. By combining dual-task gait analysis with machine learning, the researchers are investigating whether the body’s response to distraction can serve as an early warning signal—one that could eventually help clinicians intervene before a dangerous fall changes an older person’s independence.
Subject of Research: Fall-risk prediction in community-dwelling older adults using machine learning and dual-task spatiotemporal gait parameters.
Article Title: Machine learning-based fall risk prediction in community-dwelling older adults using dual-task spatiotemporal gait parameters.
Article References: Dong, G., Hu, H., Guo, Y. et al. “Machine learning-based fall risk prediction in community-dwelling older adults using dual-task spatiotemporal gait parameters.” BMC Geriatrics (2026). https://doi.org/10.1186/s12877-026-07998-3
Image Credits: AI Generated
DOI: 10.1186/s12877-026-07998-3
Keywords: machine learning, fall risk prediction, older adults, community-dwelling older adults, dual-task walking, gait analysis, spatiotemporal gait parameters, geriatric medicine, balance, mobility.
As populations age, scientists are looking more closely at a hidden biological process that may help explain why some older adults remain mobile and independent while others experience a rapid decline in strength, balance, and endurance. A systematic review by A. Boshnjaku, R. Obërtinca, M. Hoxha, and colleagues examines whether five inflammation-related biomarkers—CRP, high-sensitivity CRP, interleukin-6, interleukin-10, and tumor necrosis factor-alpha—are linked to physical performance in older adults living in the community. Published in BMC Geriatrics, the review focuses on a question with major implications for healthy aging: can signals circulating in the blood reveal who is at greater risk of losing physical function?
The study centers on chronic, low-grade inflammation, a biological condition often associated with aging and commonly described as “inflammaging.” Unlike the intense inflammation triggered by an infection or injury, inflammaging can persist quietly over years. It may be influenced by immune-system changes, excess body fat, physical inactivity, chronic disease, and cellular stress. Although inflammation is essential for repairing tissue and fighting pathogens, prolonged activation can affect muscle metabolism, blood-vessel function, nervous-system signaling, and energy production. These changes could, in theory, make everyday movements such as walking, rising from a chair, or climbing stairs increasingly difficult.
C-reactive protein, or CRP, is one of the most widely used indicators of systemic inflammation. It is produced primarily by the liver in response to inflammatory signals, especially interleukin-6. Standard CRP testing is useful for detecting relatively pronounced inflammatory activity, while high-sensitivity CRP, known as hs-CRP, can measure much lower concentrations. That distinction matters in research on older adults, where subtle inflammatory differences may exist even when there is no obvious acute illness. However, neither CRP nor hs-CRP identifies a single disease or proves that inflammation itself caused a decline in physical ability.
The review also considers three signaling proteins known as cytokines. Interleukin-6, or IL-6, can promote inflammation but also participates in muscle adaptation and energy regulation, making its effects highly dependent on timing, tissue, and physiological context. Tumor necrosis factor-alpha, or TNF-α, is a potent inflammatory mediator that can influence muscle protein breakdown and interfere with insulin signaling. Interleukin-10, or IL-10, generally acts as an anti-inflammatory regulator, helping restrain excessive immune activation. Examining these markers together offers a more nuanced picture than relying on a single laboratory value.
Physical performance is a crucial measure of aging because it reflects how effectively multiple systems work together. Muscle strength alone does not determine whether a person can remain independent. Walking speed, repeated chair stands, balance, grip strength, endurance, and composite tests such as the Short Physical Performance Battery can reveal the combined effects of the muscular, cardiovascular, neurological, and skeletal systems. For people living outside hospitals and care facilities, these measures may also provide a practical snapshot of resilience in everyday life. A small difference in performance can translate into a major difference in fall risk, mobility, and the ability to manage daily activities.
By bringing together evidence from studies of community-dwelling older adults, the authors address an important gap between laboratory research and real-world aging. Older people living independently are not a uniform group: some have multiple chronic conditions, while others remain highly active; some take anti-inflammatory medications, and others do not. Diet, smoking, obesity, socioeconomic conditions, sleep, recent infections, and exercise can all alter cytokine levels and physical performance. A systematic review can help determine whether associations between biomarkers and function appear consistently across this complex population or whether they vary substantially from one study to another.
The review’s importance lies not only in asking whether inflammatory markers are associated with poorer performance, but also in highlighting the limitations of interpreting such relationships. A high biomarker level may be a consequence of frailty, reduced activity, obesity, or an undiagnosed illness rather than the original cause of decline. Conversely, a single blood sample may fail to capture fluctuations in inflammation over time. Differences in laboratory methods, cutoff values, participant health, medication use, and performance tests can make studies difficult to compare. These issues are central when translating population-level associations into decisions about an individual patient.
The findings may ultimately support a broader approach to healthy aging in which inflammation is considered alongside strength, nutrition, cardiovascular health, cognition, and social environment. The biomarkers discussed in the review are not presented as standalone tests that can predict the future with certainty. Instead, they may help researchers understand why physical function changes and identify biological pathways that could be targeted through exercise, weight management, treatment of chronic disease, or other interventions. The study also underscores the need for longitudinal research capable of separating cause from consequence and for standardized testing that can connect laboratory signals with meaningful improvements in daily life.
For now, the review places a spotlight on the immune system as a possible contributor to the physical changes associated with later life. Its focus on CRP, hs-CRP, IL-6, IL-10, and TNF-α reflects the growing recognition that aging is not simply the result of muscles becoming weaker, but of interconnected changes across the body. Understanding how these inflammatory signals relate to mobility could help scientists develop more precise strategies for preserving independence—while reminding clinicians and the public that a blood test is most informative when interpreted together with a person’s functional ability, medical history, and lived environment.
Subject of Research: The relationship between inflammatory biomarkers and physical performance in community-dwelling older adults.
Article Title: What is the impact of CRP, hs-CRP, IL-6, IL-10, and TNFα in physical performance in community-dwelling older adults: a systematic review.
Article References: Boshnjaku, A., Obërtinca, R., Hoxha, M. et al. What is the impact of CRP, hs-CRP, IL-6, IL-10, and TNFα in physical performance in community-dwelling older adults: a systematic review. BMC Geriatrics (2026). https://doi.org/10.1186/s12877-026-08080-8
Image Credits: AI Generated
DOI: 10.1186/s12877-026-08080-8
Keywords: aging, older adults, inflammation, CRP, hs-CRP, IL-6, IL-10, TNF-α, physical performance, inflammaging, systematic review
Most people know that the kidneys clean the blood, but far fewer realise they also help protect the brain. Growing research shows that chronic kidney disease can damage memory, thinking and concentration, making brain health another major concern for millions of patients around the world. Researchers summarised evidence showing that kidney disease affects much more […]
The post The Hidden Link Between Kidney Disease and Memory Loss appeared first on Knowridge Science Report.
Chronic pain is often treated as a medical problem that can be measured with scales, prescriptions, and clinical guidelines. For older adults, however, the experience of pain is also shaped by mobility, memory, sleep, mood, independence, and the ability to communicate with health professionals. A new study published in BMC Geriatrics places that lived experience at the center of the discussion, examining how older adults perceive chronic pain management in primary care settings.
The article, authored by P. Gopal, A. Kagarmanova, E. Staab and colleagues, focuses on a point where many long-term health decisions are made: the primary care clinic. Primary care clinicians are often the first professionals to evaluate persistent pain and the people most likely to coordinate treatment over months or years. This makes the setting especially important for older patients, who may be managing several chronic diseases and taking multiple medications at the same time.
Chronic pain is generally defined as pain that persists or recurs for longer than the expected period of tissue healing, commonly described as three months or more. It may arise from osteoarthritis, neuropathy, spinal disorders, previous injuries, cancer, or several conditions acting together. Unlike acute pain, which can serve as a warning signal, chronic pain involves complex changes in the nervous system. Repeated signals can increase the sensitivity of pain pathways, a process known as central sensitization, meaning that pain may continue even after the original injury has stabilized.
For older adults, treating this type of pain is rarely a matter of simply choosing a stronger drug. Age-related changes in kidney and liver function can alter how medicines are absorbed, processed, and eliminated. This can increase the risk of side effects from opioids, sedatives, anti-inflammatory drugs, and other treatments. At the same time, many older patients live with hypertension, heart disease, diabetes, dementia, or depression, conditions that can influence both the perception of pain and the safety of available therapies.
The study’s focus on perceptions is scientifically significant because clinical success cannot be judged only by changes in a numerical pain score. Two people who report the same intensity on a ten-point scale may have very different levels of disability, fear, sleep disruption, or confidence in their treatment. Older adults may value the ability to walk to the shops, sleep through the night, remain socially active, or avoid dependence on family members more than achieving complete elimination of pain. Understanding these priorities can help clinicians define treatment goals that are meaningful in everyday life.
Primary care also presents a distinctive communication challenge. Appointments may be brief, while chronic pain is influenced by physical, psychological, and social factors that require time to explain. Some patients may hesitate to report pain because they fear being dismissed, appearing demanding, or being prescribed medications they do not want. Others may assume that pain is an unavoidable part of aging. When these assumptions remain unspoken, clinicians can underestimate the burden of pain or recommend plans that patients cannot realistically follow.
A patient-centered approach attempts to address this gap by combining clinical evidence with the individual’s preferences, circumstances, and goals. In practice, that may involve medication review, physical therapy, exercise adapted to ability, occupational strategies, psychological support, sleep interventions, and education about pain biology. The technical principle is multimodal care: different treatments target different mechanisms and consequences of pain, potentially reducing reliance on any single intervention. For older adults, coordinated care can also help identify harmful drug interactions and prevent avoidable loss of function.
The research is arriving as health systems confront a rapidly aging population and growing demand for long-term pain care. Chronic pain affects quality of life, physical activity, and healthcare use, yet treatment remains inconsistent across communities. Access to physiotherapy, behavioral health services, specialist pain clinics, and transportation can vary sharply. These structural factors matter because a treatment plan may be clinically sound but ineffective if a patient cannot afford it, reach appointments, understand the instructions, or obtain help at home.
By examining older adults’ views, the paper contributes to a broader shift in pain research: away from treating patients as passive recipients of medical decisions and toward recognizing them as experts in their own daily experience. Their perspectives can reveal whether treatment goals are understandable, whether risks are being communicated clearly, and whether care plans fit real lives. Such information may help primary care teams design more responsive conversations about benefits, harms, uncertainty, and acceptable trade-offs.
The publication does not make the patient’s voice a decorative addition to pain medicine; it treats that voice as evidence relevant to clinical quality. As the medical community searches for safer and more individualized ways to manage chronic pain, the central question is increasingly practical: does the treatment help an older person live better, function more safely, and retain control over daily life? The study by Gopal, Kagarmanova, Staab and colleagues brings that question into primary care, where many of the most important decisions about persistent pain are made.
Subject of Research: Older adults’ perceptions of chronic pain management in primary care settings
Article Title: Perceptions of older adults on chronic pain management in primary care settings
Article References: Gopal, P., Kagarmanova, A., Staab, E. et al. “Perceptions of older adults on chronic pain management in primary care settings.” BMC Geriatrics (2026). https://doi.org/10.1186/s12877-026-08000-w
Image Credits: AI Generated
DOI: 10.1186/s12877-026-08000-w
Keywords: Older adults, chronic pain, pain management, primary care, patient perspectives, geriatrics
Long-term care residents moving from a nursing facility to an emergency department enter one of the most complex transitions in modern healthcare. The journey may begin with a sudden change in consciousness, breathing, mobility, pain, or behavior, but it quickly becomes a transfer of information, responsibility, and risk between institutions. A new qualitative study published in BMC Geriatrics examines how this cross-setting transition is experienced by the people involved, highlighting a vulnerable point in the healthcare system that is often treated as a routine logistical event.
The study, led by PC Hsu, LY.A. Chen, and YC Chen and colleagues, focuses on residents of long-term care facilities who are transferred to emergency departments. Unlike quantitative research, which typically measures outcomes such as admission rates, waiting times, or mortality, qualitative research investigates how individuals interpret and experience a process. Through this approach, researchers can identify communication breakdowns, conflicting expectations, emotional pressures, and practical barriers that may not appear in hospital databases.
For older adults living in long-term care, an emergency transfer can be medically necessary but physically and psychologically destabilizing. Many residents live with multiple chronic conditions, frailty, dementia, sensory impairment, or limited ability to communicate. These characteristics can make it difficult for them to describe symptoms, understand unfamiliar surroundings, or participate directly in decisions. The emergency department, meanwhile, is designed for rapid assessment and acute treatment, not always for the slower, highly individualized care needs of frail older people.
The transition also creates a handover challenge. Clinical information must travel with the resident, including medication lists, allergies, advance-care preferences, baseline cognitive and functional status, recent symptoms, and the reason for transfer. If any of this information is incomplete, delayed, or misunderstood, clinicians may have to reconstruct the patient’s history under intense time pressure. This can lead to duplicated tests, inappropriate medication decisions, delays in treatment, or care plans that fail to reflect the resident’s usual condition.
A central technical issue is the difference between a patient’s baseline and an acute change. A resident with dementia may appear confused in the emergency department even when their behavior is consistent with their usual state. Conversely, a subtle change in alertness or mobility may indicate infection, dehydration, stroke, or another serious condition. Without reliable baseline information from long-term care staff or family members, emergency clinicians may struggle to distinguish chronic impairment from delirium, a sudden disturbance in attention and cognition associated with substantial risks in older adults.
By examining experiences across care settings, the research addresses the concept of continuity of care. Continuity is not simply the transfer of documents; it includes consistency in clinical goals, communication, decision-making, and personal knowledge of the resident. A successful transition requires coordination among long-term care workers, emergency medical services, hospital clinicians, residents, and families. Each group may possess only part of the relevant information, making the quality of interaction between them as important as the technology used to transmit records.
The study’s qualitative design is particularly valuable because transitions are shaped by human factors. Staff may face time constraints, staffing shortages, unclear responsibilities, or different documentation systems. Families may experience anxiety when they are asked to make urgent decisions without a complete explanation of the resident’s condition. Residents may feel disoriented or powerless as they move between unfamiliar environments. Capturing these perspectives can reveal why formal protocols sometimes fail in practice, even when they appear comprehensive on paper.
The findings are relevant to a wider healthcare challenge: populations are aging while medical care is becoming increasingly fragmented. Long-term care facilities and hospitals often operate under separate administrative structures, with different workflows, electronic records, professional cultures, and performance measures. Emergency departments may focus on rapid diagnosis and disposition, whereas long-term care teams emphasize daily function, prevention, and quality of life. The transition between these systems can therefore become a vulnerable interface where important context is lost.
Improving that interface could involve standardized transfer forms, interoperable electronic records, direct clinician-to-clinician communication, clearer escalation pathways, and explicit documentation of a resident’s baseline function and care preferences. Yet the study’s focus on lived experience suggests that technical solutions alone may not be sufficient. Better transitions also depend on mutual understanding, shared accountability, and recognition that a transfer is not an isolated event but a continuum extending from the long-term care facility to the emergency department and back again.
As healthcare systems search for ways to reduce preventable harm among older adults, the experience of cross-setting transitions deserves greater attention. The study by Hsu, Chen, Chen, and colleagues places this often-overlooked process at the center of inquiry. Its subject is not merely how residents are transported, but how information, clinical judgment, dignity, and responsibility move with them. That perspective may help health services design emergency transfers that are safer, more coordinated, and more responsive to the realities of long-term care.
Subject of Research: Cross-setting care transitions of long-term care residents to the emergency department.
Article Title: The experience of cross-setting care transitions of long-term care residents to the emergency department: a qualitative study
Article References: Hsu, PC., Chen, LY.A., Chen, YC. et al. “The experience of cross-setting care transitions of long-term care residents to the emergency department: a qualitative study.” BMC Geriatrics (2026). https://doi.org/10.1186/s12877-026-08059-5
Image Credits: AI Generated
DOI: 10.1186/s12877-026-08059-5
Just over a week ago, Health and Human Services secretary Robert F. Kennedy Jr declared that the ongoing outbreak of the explosive diarrhea-causing parasite was “under control.”
But the reality is that cases are climbing into the thousands across 45 states, as USA Today reports, meaning his reassurances appear to have been a gross overstatement. According to the Centers for Disease Control and Prevention, the number of cases increased by an additional 2,500 cases between July 21 and July 28 alone.
As of this week, the CDC has confirmed over 6,700 cases since May 1 and is “aware of more than 11,500 additional cases that are not laboratory confirmed or require further investigation and analysis.”
There is a bright side: while the symptoms are gross, there have been no known fatalities. There have been 423 hospitalizations so far, but no deaths have been recorded, according to the agency.
Health officials are still racing to nail down the source of the outbreak of the microscopic parasite Cyclospora cayetanensis, which is known to cause frequent — and often explosive — watery diarrhea. The top suspect so far has been Taylor Farms, one of Taco Bell’s lead suppliers, whose bagged shredded lettuce was initially found by the Food and Drug Administration to contain the parasite.
While the FDA has since gone back on that claim, saying the results were a “false positive,” Taylor Farms has nonetheless agreed to lead a “voluntary” recall of the allegedly tainted lettuce.
The true count of cyclosporiasis cases in the US remains extremely difficult to tally. As the CDC notes, “surveillance updates do not include probable cases.” Many people who fall ill “recover without medical care and are not tested for Cyclospora.”
According to a map issued by the agency, the two hotspots are Michigan and Ohio. Michigan alone passed the 10,000 cases mark today, according to the state’s Department of Health and Human Services.
The only states that have yet to report or confirm a single case, per the CDC’s map, are Montana, New Mexico, Maine, South Carolina, and Hawaii.
Fortunately, it’s easy to protect oneself from the parasite. Public health experts recommend thoroughly washing fruits and vegetables or simply cooking them, which kills the tiny critters.
More on the outbreak: Trump Is Having a Major Problem With Diarrhea
The post Almost the Entire Country Is Drowning in Cases of Explosive Diarrhea appeared first on Futurism.
Glowy oils, tinted creams, misty sprays, chalky sticks, lightweight gels. Like many people, my pool bag is filled with many types of sunscreen. But all use the same sun-shielding chemicals. In fact, the allowed ingredient list for U.S. sunscreens hasn’t changed in 20 years — until now.
This June, the U.S. Food and Drug Administration (FDA) added bemotrizinol (Beh-moh-TRIZ-eh-nol) to its approved list.
“I think we should all be super excited,” says Tanya Hathaway. She’s a dermatologist who specializes in treating high-risk skin-cancer patients. Hathaway works at the Fred Hutchinson Cancer Center in Seattle, Wash.
Bemotrizinol has many benefits. It lasts longer than other sunscreen ingredients. It won’t get quickly absorbed into the bloodstream. And it’s very good at blocking those rays of the sun that age skin.
Sunscreens in Europe have used the chemical for more than 25 years, Hathaway notes. More recently, it’s been approved in Japan, Canada, Australia and many other places.
There are some sunscreen ingredients used elsewhere that still are not allowed in U.S. products. Bemotrizinol’s approval could open U.S. doors for some of these. It’s “a great first step,” Hathaway says.
Sunscreens use a few tricks to protect our skin from the sun’s rays. Physical sunscreens rely on minerals such as titanium dioxide and zinc oxide. These create a coating that reflects sunlight, like a mirror. But they can leave a white sheen on the skin. Just think of a lifeguard’s nose, says Jennifer Stein. She’s a dermatologist at NYU Langone Health in New York City.
Those zinc and titanium products also “don’t rub in so well,” she notes. “And if people don’t like the way their sunscreen smells or feels, they’re not going to use it.”
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Non-mineral sunscreens often rub in a bit better. They often use chemicals such as avobenzone (Ay-vah-BEN-zoan) and oxybenzone to absorb the sun’s rays. But these molecules are not very stable. They start to break down when hit by sunlight, Stein says. That’s not ideal for something that’s designed for use in the sun.
Because bemotrizinol is more stable, people may not need to apply sunscreens with it as often. This new ingredient also is good at blocking ultraviolet A1 (UVA1) radiation. That’s a type that gets deep into the skin. Over time, UVA1 can make skin wrinkly, loose and spotted, Hathaway says.
Current U.S. sunscreens do a good job of blocking UVB, which causes sunburns. But U.S. sunscreens had fewer options for blocking UVA, she says. Bemotrizinol “really expands that UVA spectrum of coverage.”
You might have seen influencers on TikTok or Instagram making DIY sunscreens. Often, they will call the ingredients in commercial brands “toxic.” Sunscreen skepticism on social media is nothing new, Stein says. Patients who avoid sunscreen often worry about chemicals passing through the skin.
That can happen with things like avobenzone and oxybenzone. They may even get into your blood, Stein says — but only if “you apply them to large areas of the body repeatedly throughout the day.” Even so, people shouldn’t fear them. Hathaway says no studies have shown that U.S. sunscreen ingredients are unsafe when used at current levels.
Bemotrizinol, which is a big molecule, is less likely to pass through skin than these other chemicals. It’s “too big to squeeze through the skin cells to get down into your bloodstream,” Stein says.
FDA classifies bemotrizinol as GRASE (short for generally recognized as safe and effective). Titanium dioxide and zinc oxide are the only other U.S. sunscreen ingredients with this rating.
Bemotrizinol’s U.S. approval goes into effect on August 9. So sunscreens using it could hit shelves later this summer. But a new sunscreen is not the only way to stay safe from the sun. There are plenty of low-tech options, too: long sleeves, hats, sunglasses and staying in the shade. “The more clothing you’re wearing,” Stein emphasizes, “the less you have to depend on sunscreen.”
For only the second time in its history, the American Red Cross has declared a “national blood supply crisis,” after donations fell to a four-year summer low.
The hotter summer months conventionally trigger blood shortages because people are more likely to injure themselves while spending time outdoors.
And this summer has been particularly extreme. According to the Red Cross, extreme heat, poor air quality, and widespread foodborne illnesses have compounded into blood donations dropping precipitously, causing supply levels to plummet to a historic low.
The news comes amidst record-breaking temperatures this summer, devastating heatwaves that have killed at least 25 people in the US. Public health officials are also battling an outbreak of an explosive diarrhea-causing parasite that’s has spread to 45 states.
As a result of plummeting donations, the Red Cross, which is the largest single provider of blood products, has “less than a one-day national supply of type O positive blood.” Type O positive is the most commonly transfused blood type, and highly valued because can safely be used to treat over 80 percent of the population.
The Red Cross declared its first-ever national blood crisis in January 2022, triggered by a previous low in donor turnout due to ongoing COVID-19 surge disruptions.
“Every donation has the potential to help save lives, and we urgently need everyone who is eligible to make an appointment to give blood as soon as possible,” said Red Cross Biomedical Services president Chris Hrouda in a statement.
The risks of an extremely limited blood supply are considerable.
“There’s always the possibility, when the blood supply dips like it has, that patients won’t be able to get the blood products they need, when they need,” Red Cross spokesperson Matt Trotter told NPR affiliate KOSU.
By mid-July, the Red Cross was already ringing the alarm bells, warning that donations had fallen by about 25 percent in June.
To get back on track doesn’t require drastic action, either. The organization says that just “three more donors at each blood drive this summer can end this crisis and stabilize the blood supply.”
“One donation can help save multiple lives, so if you’ve got an hour you can spare, you can do a lot of good with it,” Trotter told KOSU. “Many people who think they are ineligible actually can donate blood.”
If you or a loved one wants to donate blood, this site run by the Red Cross can help find a blood drive nearby.
Updated to correctly identify blood types.
More on blood: Immortality-Obsessed Tech Guy Trying New Technique That Involves Removing “All Blood From Body”
The post The United States Is Rapidly Running Out of Blood appeared first on Futurism.
A large British study spanning more than 70 years has found that people who experience chronic money struggles over their working lives show measurable declines in memory and processing speed by their 50s, along with signs of accelerated brain shrinkage decades later.
The post Decades of Financial Hardship Linked to Faster Brain Aging appeared first on Sci.News: Breaking Science News.
Adding breakfast back into the daily routine of teens around age 18 who habitually skip the meal can meaningfully improve their nutrition, with the biggest gains seen among those given protein-rich morning meals, according to a six-month clinical trial.
The post New Study Finds Eating Breakfast Boosts Diet Quality in Teens Who Usually Skip It appeared first on Sci.News: Breaking Science News.
The tech overlords pushing the AI boom are quickly wearing out what little welcome they had.
You may have noticed big-name AI labs pushing new commercials lately. Meta’s new 60-second ad spot insists that the “future is for everyone,” even as CEO Mark Zuckerberg’s personal net worth eclipses the GDP of Hungary. Anthropic’s new commercial for Claude assures viewers that there’s “hope in hard questions,” seemingly embracing the discomfort that comes when your software is used to bomb elementary schools in Iran.
For as magnanimous as these new PR stunts appear on the surface, a vast swathe of the public they’re meant to sway are rejecting the industry’s faux-populism messaging out of hand, as the cost of AI — born out in inflation, data center pollution, fears of job loss and mental health concerns — becomes too much to bear.
According to data compiled by Pew Research, 40 percent of US adults predict AI will have a negative impact on society writ large, compared to just 16 percent who say it’ll have a positive effect. A whole 31 percent of those surveyed think AI will have negative consequences for themselves, personally, over the next 20 years.
As disgust with AI itself grows, so too does resistance to the hardware embodying its rise.
Per a separate poll by Gallup, flagged by Business Insider, an astonishing three-quarters of US adults are now resolutely opposed to hyperscale data centers popping up near their home. City councils are increasingly forced to reconcile with landowners hostile to any AI data center appearing in their district, putting significant strain on developers hoping to gorge themselves on the fruits of the AI boom. Protests against AI companies are flaring up across the country, with Time reporting 142 protests across 42 states in one day alone.
Beyond data centers, a decentralized but highly-motivated movement is growing around the chopping, hacking, and outright sabotage of AI-integrated surveillance cameras. A parallel struggle is being waged around AI-integrated surveillance drones, with organizers in cities like Minneapolis beating back ambitious police dragnets.
So if you’re a tech executive trying to win back the masses to the AI revolution, take note: it’s gonna take a lot more than a few smarmy commercials to solve your PR problem.
More on AI: Google’s Profits Look a Little Terrifying Under the Hood
The post The AI Industry Has Acted So Badly That It’s Now Dealing With a Huge Wave of Hatred appeared first on Futurism.
Over the past year or so, a puzzling idea has taken hold among billionaires ranging from Elon Musk to Jeff Bezos: that instead of trying to force data centers on communities that don’t want them down on Earth, it would be much easier just to launch them into space.
The economics and logistics of the scheme, many experts have pointed out, are absolutely absurd. And even beyond those practical concerns, if corporations actually did somehow manage to fill the planet’s orbit with the facilities, scientists are now warning that the environmental cost would be devastating.
A new petition organized by the group EarthJustice, first reported by the Guardian, is warning of “catastrophic” consequences for the planet if the billionaire-backed dream ever came to pass. The 29-page petition calls on the US Federal Communications Commission to investigate current orbital data center licensing requests as potentially in violation of “federal law,” joining the chorus of experts warning that it’s a horrible idea for just about everybody.
“The FCC is currently considering multiple requests for licensing extraordinary numbers of satellite-based data centers to be placed into low-earth orbit over the next decade,” the petition begins. “The proponents of these proposals describe their plans in grandiose, civilization-changing terms. But these same proponents have refused to embrace any inquiry into the impacts of their self claimed epochal technology on the environment, science, economy, or other values. This is not just poor planning and a missed opportunity: it violates federal law.”
The filing does double duty. On top of formally petitioning the FCC to prepare an environmental assessment, it’s also a “petition to deny,” which is a legal mechanism that requires the petitioner to back up their claims with verified facts. That requirement turns the document into a de facto review article — with 113 footnote citations, it’s easily one of the most detailed public accounts yet of what orbital data centers could actually cost the planet.
“The operation of more than a million data center satellites threatens potentially catastrophic forms and quantities of atmospheric pollution, risking damage to the climate, to the ozone layer, to human health, and to the chemistry of the stratosphere itself,” the petition reads.
In particular, the petition warns that giving free rein to tech billionaires to clutter our skies with experimental data centers would accelerate our contamination of the stratosphere, which is currently facing an unprecedented rise in heavy metals, noxious gasses, and carbon particles thanks to record satellite launches.
Satellite companies run by tech and aerospace tycoons are already facing scrutiny for their lack of transparency around this type of pollution, a situation the petition warns would make significantly worse. As the petition authors write, they are “concerned that no [company] has yet provided more than a token acknowledgment of environmental risks.”
“Moreover,” the authors continue, “no [company] has provided satisfactory detail to explain how it will mitigate the cumulative environmental harms flowing from the foreseeable operation of more than a million satellites [emphasis in original], orbiting our planet, colliding and disintegrating and plummeting back to Earth.”
More on data centers: Climate Activists Pelt Microsoft Data Center With Balloons Full of Acid
The post The Type of Orbital Data Centers That Billionaires Want to Launch Into Space Would Wreak Ecological Catastrophe, Scientists Warn appeared first on Futurism.
Have you ever wondered how researchers use artificial intelligence (AI) in environmental science? Certain AI computer models can learn from scientific data and operate without manual programming, in a process called machine learning. Machine learning models can identify patterns in environmental datasets and help scientists assess public health risks linked to environmental conditions.
One well-known public health risk is the rise in antibiotic-resistant bacteria. These bacteria carry genes called antibiotic resistance genes that protect them from antibiotic medicines. As the number of these genes increases, the medicines become less effective, and diseases spread faster.
Agricultural soils are the largest reservoirs of antibiotic resistance genes, because manure from livestock like cows and pigs often contains leftover antibiotics fed to them. When used as fertilizer, this manure transfers antibiotics into the agricultural soil, where bacteria develop antibiotic resistance genes.
To better understand how antibiotic-resistant bacteria will affect global health in the future, scientists want to develop faster ways to detect antibiotic resistance genes. However, current methods of detection are slow and fail to predict future trends. To address this problem, a group of scientists from Algeria used machine learning models to predict the prevalence of antibiotic resistance genes in soil microbes under future climate scenarios, and to identify the key environmental drivers and high-risk areas.
The team compiled existing microbial data from 3 public databases: the National Center for Biotechnology Information’s Sequence Read Archive, the Metagenomic Rapid Annotations using Subsystems Technology database, and the Joint Genome Institute’s Integrated Microbial Genomes & Microbiomes database. Their final dataset contained about 2,000 agricultural soil samples from 67 countries across 6 continents. These samples represented a wide range of soil characteristics, climate conditions, and different types of antibiotic resistance genes.
They integrated the microbial dataset with climate data, including global temperature and precipitation measurements from WorldClim, and land use data, including crop types, irrigation systems, and livestock density from the European Space Agency Climate Change Initiative Land Cover maps. The researchers also included data on future climate projections for 2050 and 2070 from the World Climate Research Programme based on low, medium, and high global greenhouse gas emission scenarios.
After preparing the datasets, the team set up 6 machine learning models that differ in terms of their data size, model complexity, analytical speed, and customization. These models included Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), Deep Neural Network (DNN), and Logistic Regression (LR).
They ran each model using different combinations of variables from their datasets, including soil properties, microbial community metrics, climate variables, and land use characteristics. To validate the models, the team separated the full dataset into 10 random subsets. They trained the models on 9 of the subsets, then recorded the result of the 10th subset. Each model repeated this process 10 times in a different order so that each subset was evaluated once in the results, using a technique known as stratified 10-fold cross-validation. The researchers scored each model on 5 performance metrics, including precision, sensitivity, and predictive power. Based on these results, they determined that LightGBM was the most accurate model.
They found that the LightGBM model identified soil temperature as the strongest environmental predictor of antibiotic resistance genes. At soil temperatures above 18°C (about 64°F), the number of antibiotic resistance genes increased dramatically. The model also identified soil acidity, organic carbon content, moisture, and annual precipitation as influential variables, accounting for 71% of the increase in antibiotic resistance genes under future climate scenarios. Likewise, the LightGBM model predicted that the number of high-risk areas would increase by 35% under the high-emissions scenario, with South Asia, Sub-Saharan Africa, and Mediterranean Europe as the most vulnerable regions.
Based on the LightGBM model output, the team concluded that soil conditions will change to favor antibiotic resistance genes under all future climate scenarios. They also suggested that LightGBM is a fast and effective model for environmental predictions that could be used to assess other climate change risks such as natural disasters. They recommended that future researchers explore how to apply machine learning methods to early warning systems and utilize machine learning results in environmental management decisions.
The post Predicting microbial antibiotic resistance with AI appeared first on Sciworthy.
Zillionaire eccentric Bryan Johnson, fresh off of being diagnosed with an incurable disease, says he just “cloned” himself “as a newborn.” Yep, you heard that right.
The immortality influencer shared in an X update that he has a “baby” version of himself growing in a petri dish that he says will allow him to become his “own blood boy” — doesn’t he already have a son who does that for him? — and potentially even “grow organs for transplantation.”
“This may be scary to some people… a dystopian future,” Johnson wrote. “But, for others, they will see it as the inevitable future of health.”
In case this is all starting to sound like the grim sci-fi plot of a certain Michael Bay movie or Kazuo Ishiguro novel, it’s not a literal, living breathing clone. (Although by posting an infamous picture of himself edited to look like a baby, Johnson’s certainly playing into that impression.)
Instead, Johnson’s created his own pluripotent stem cells. These stem cells can self-renew and develop into any type of cell in the body, making them invaluable for repairing damaged tissue.
Where Johnson’s claims of cloning himself as a “newborn” come in is the fact that these highly versatile stem cells normally only exist when we’re still an embryo. But in recent decades scientists have developed techniques to reprogram regular adult cells into an embryonic pluripotent state, which are called induced pluripotent stem cells.
Johnson is confident that by having his own store of stem cells on hand he can “rebuild” his body, repairing everything from damaged lungs to eyesight.
“This technology gives us a path to reverse aging,” he declares.
His optimism is admirable, but many of these stem cell applications he’s touting haven’t been proven yet. Johnson claims his baby clone will let him grow organs, for example, but scientists still haven’t developed a reliable technique for creating organs derived from someone’s own stem cells. One promising technique involves growing an organ in the body of another animal like a pig before transplanting it into a human, but these attempts have stopped when the organ was still in an embryo, and no transplantation has been attempted.
An alternative that doesn’t involve stem cells, xenotransplantation, harvests organs from a genetically modified animal pig, but has only been demonstrated in human recipients who were braindead, with the transplanted organ slowly rejected over the course of several days.
All that’s to say is that we should be skeptical about Johnson’s longevity advice, though we will certainly keep rubbernecking to see how his quixotic quest is going.
More on health: Trump Is Having a Major Problem With Diarrhea
The post Bryan Johnson Says He’s Cloned Himself “As a Newborn” to “Grow Organs for Transplantation,” Which Is a Preposterous Exaggeration appeared first on Futurism.
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