Credits: Freepik
For the first time in a quarter-century, the United States is seeing more cases of measles during a single year than at any point since the disease was last declared eliminated in 2000. A startling 1,277 cases were reported as of mid‑2025—already more than the former yearly record of 1,274, which was set in 2019. Adding to alarms, three lives—two kids in Texas and an adult in New Mexico—have already been lost this year, equaling the number of U.S. measles deaths since elimination.
This comeback highlights both the vulnerability of public health gains and the lethal effects of waning vaccination levels.
In 2000, when the U.S. marked measles elimination, it meant zero sustained domestic transmission for over a year—a feat achieved due to successful vaccination and disease surveillance. A strong two-dose schedule of the measles-mumps-rubella (MMR) vaccine, accessible since the 1970s, fueled that achievement.
But since 2021, national school-age MMR coverage has slipped below the all-important 95% herd immunity bar that experts say is critical to widespread protection. More than 125,000 kindergartners alone had exemptions from one or more mandatory vaccines during the 2023–24 school year. That set the stage for contagion to spread—particularly in clusters of unvaccinated communities.
In West Texas, an undervaccinated area in late January sparked a huge outbreak. Over 750 cases have been traced to the region, spreading to Oklahoma and New Mexico and prompting an early vaccination campaign. Counties reacted by administering early doses of MMR as young as six months old, and in Texas, early infant vaccination jumped—the rate was eight times higher than in 2019, according to Truveta health data.
Communities rallied with pop-up vaccination sites, state-level policy interventions, and an increased uptake of MMR. Nevertheless, smaller outbreaks in 38 states and 27 discrete clusters indicate a more pervasive susceptibility.
Waning MMR Coverage: Sustained vaccine skepticism and exemptions have eroded herd immunity in communities.
Highly Infectious Virus: Measles spreads more quickly and widely than many respiratory diseases—up to 90% infection of susceptible close contacts. It only takes one contagious person to initiate large outbreaks.
Global Spread: Measles is endemic throughout the world. Imported cases in countries where the virus is circulating continuously are the lifeblood of ongoing outbreaks.
Local Susceptibility: With an unvaccinated cluster present, the virus circulates nearly unimpeded.
In 2019, misinformation-driven outbreaks infected Orthodox Jewish communities in New York. Now, the epicenter is Texas, but the virus is spreading extensively—eliciting extensive alarm.
While the epicenter is still West Texas, the virus has now spread in several states:
New Mexico & Oklahoma: Connected to initial outbreak, with overlapping transmission chains.
Kansas: 83 cases, all but one related to primary Texas outbreak.
Wyoming: Expressed a measles case for the first time since 2010—an unvaccinated kid in rural Casper.
Utah, Michigan, Florida: New instances of travel-associated cases have surfaced, emphasizing the national risk.
Public health authorities are cautioning that if transmission persists after January 2026, the U.S. will forfeit its measles elimination status, which is reversing a big public health achievement.
The Reuters Health update is a reflection of the U.S. crisis. Pan American Health Organization (PAHO) indicates a 29-fold increase in measles in the Americas compared to last year. There have been 3,170 cases in Canada since 1998 and Mexico had 2,597 cases in 2025—with 10 related deaths. Mennonites and other isolated communities' vaccine skepticism is driving the comeback.
The CDC has estimated a mere 8% of the 2025 cases in fully or partially vaccinated persons. In other words, more than 90% infected were unvaccinated. Hospitalizations have been glaringly high: 155 patients, including numerous young children. Specifically, 28% of these cases are in children under age 5—the exact age group that the MMR vaccine is supposed to protect.
MMR vaccine is one of the most effective medical tools ever—93% effective after one dose, and as much as 97% after two. Yet its effectiveness hinges on widespread coverage, not simple use. There are several forces at play:
Vaccine Hesitancy & Misinformation: Sustained disinformation efforts—across social media and conspiracy networks—chips away at confidence in vaccines.
Policy Vacuum: The U.S. lacks a permanent CDC director. HHS Secretary Robert F. Kennedy Jr. surprised with a pro-vaccine public statement this spring, but his past record of vaccine skepticism and disregarding CDC advisory panels erodes faith.
Educational Shifts: Additional states have broadened vaccine exemption policies, granting greater refusal under medical, religious, or philosophical reasons.
At levels of community coverage below 95%, outbreaks become nearly inevitable.
Others suggest 2025 represents a systemic public health collapse. The pathogen's general return is a reflection not of biology but policy abandonment and frayed solidarity. Vaccination is not just individual defense—it's a social compact.
Others notice a silver lining: almost universal alarm, rapid policy response, and vaccination catch-up campaigns are proving the system responsive—if communities reassert collective responsibility.
This isn't about erecting barriers, but about renewing the networks of trust that allow vaccines to protect whole communities.
We stand at a crossroads, The resurgence of measles illustrates how progress can vanish when vigilance does. Yet while 2025 has set new records, it also sparked renewed urgency—and rare moments of collective action.
We can't risk losing what was once seen as core public health. At the center of this battle is a simple, evidence-based fact: Vaccination saves lives—not only individuals, but communities. America has to choose: is this the time we repair the fissures in public trust and systems—or do we allow measles take back territory?
Source and in photos L to R: Minor, structural muscle injury (type 3a), source: SEMS Journal; player Choclo (source: LDU Quito); diagram of the muscle fiber, source: SEMS Journal
Liga Deportiva Univerrsitaria (LDU) has confirmed a new injury to its roster this Sunday. Defender José "Choclo" Quintero has a grade 3A muscle injury. This has been confirmed by team's official statement which has come from the club's medical department.
The player is currently undergoing rehabilitation and will begin strength training and physical therapy sessions. The official statement says that "Choclo" will have a reasonable amount of time before he returns to the field. He has so far played 19 matches and his return will depend on his progress.
He had earlier suffered a skull fracture from August 30 2021 to October 4 2021 and as a result had missed three games in the season 21/22. Previously too in the season 16/17, he was in rehabilitation for 173 days due to a knew medial ligament tear, as a result of which he missed 31 games.
Also Read: Inner Child: Being Left Out And Rejected In Childhood Becomes A Social Seed For Deeper Connections
As per the 2014 study published in Translational Medicine @ UniSa, Official Journal of the Medical School of the University of Salerno, a 3A muscle injury is part of the structural injuries, which are divided into 3 sub-groups as per the "entity of the lesion within the muscle".
A type 3A lesion is a minor partial lesion, which involves one or more primary fascicles within a secondary bundle.
It usually is characterized by sharp pain, especially during a specific movement. The pain is, however, localized, and is easy to "appreciate on palpation and, at times, preceded by a snap sensation. On palpitation, it is not possible to detect the structural defect as it is too small and the contraction against manual resistance is painful," notes the study.
Another study from 2016, published in the journal Joints, a 3A involves a minor partial muscle tear with small maximum diameter and could be detected through MRI that shows fiber disruption.
A 2019 study published in the journal Sport and Exercise Medicine Switzerland, notes that Type 3A are of less than 5mm in size. Thus, it includes 1-5 primary muscle bundles. The study also notes that such injuries usually heal without defect, however, injury to the perimysium and the aponeurosis is found in type 3b injuries (> 5 mm), which is the cause for intermuscular hematoma formation.
Also Read: What Is Innotox? The ‘Korean Botox’ People Are Injecting At Home—And Why Doctors Are Worried
Type 3B injuries are moderate partial lesion, which involves at least a secondary bundle, with less than 50% of breakage surface. A Type 4 lesion is a sub-total tear with more than 50% of breakage surface or even a complete tear of the muscle. It also involves the muscle belly or the musculotendinous junction.
While these comprise structural injuries, Type 1 and Type 2 comprise the non-structural injuries.
It is the non-structural injuries, which are the most common and accounts for 70% of all muscle injuries in football players, mentions the 2014 study.
While the lesion may not be readily recognized in these injuries, they cause more than 50% of days of absence away from sport matches and training, the study notes. When they are ignored, they could turn into structural injuries.
Non-structural muscle injuries are classified into different types based on their underlying causes. Here's a breakdown of common types and what triggers them:
These injuries are often the result of fatigue or sudden changes in training routines, running surfaces, or high-intensity activities. The muscle strain occurs due to the body not being fully adapted to new or excessive demands.
This type of injury is linked to prolonged and excessive eccentric muscle contractions — when the muscle lengthens while under tension. This repeated strain can lead to overuse and damage.
Type 2A injuries are typically associated with spinal issues. Often misdiagnosed, they stem from minor intervertebral disorders that irritate spinal nerves. This nerve irritation disrupts the normal control of muscle tone in specific “target” muscles. In such cases, treating the underlying spinal disorder becomes the main focus of care.
These injuries are caused by a breakdown in the balance of the neuro-musculoskeletal system, particularly the mutual inhibition mechanism controlled by muscle spindles. When this balance is disrupted, the regulation of muscle tone suffers. Specifically, when the inhibition of agonist muscles is reduced, those muscles may become overly contracted to compensate — leading to dysfunction and injury.
Credits: Canva
For decades, lung cancer has been synonymous with smoking. But the data is shifting—and fast. Today, 10–20% of lung cancer cases in the U.S. are found in people who have never smoked a single cigarette. A new large-scale international study has now unearthed some of the strongest evidence yet that air pollution may be a major culprit—and it’s leaving a genetic trail behind.
Researchers have discovered that fine particulate matter in polluted air, commonly from traffic, industrial emissions, and smog, is strongly associated with DNA mutations that are also found in smokers’ lung tumors. These mutations may be key drivers of lung cancer development in never-smokers.
The research, involving whole-genome sequencing of lung tumors from 871 never-smokers across 28 regions in four continents, found that individuals living in highly polluted environments had significantly more driver mutations—the kind that directly trigger cancer.
The investigators matched tumor samples with long-term air pollution exposure estimates, using ground and satellite data for fine particulate matter (PM2.5). They found that non-smokers exposed to high levels of pollution were nearly four times more likely to exhibit the SBS4 mutational signature—a genetic fingerprint commonly linked to tobacco smoke.
Additionally, they identified a 76% increase in a separate signature associated with accelerated biological aging. This is alarming, considering these were individuals with no direct tobacco exposure.
What makes this finding even more significant is that researchers discovered TP53 and EGFR mutations—both known to be aggressive lung cancer markers—more frequently in people living in polluted areas. These genetic changes are typically hallmarks of cancers in smokers.
This implies that air pollution could be triggering similar molecular pathways to those activated by cigarette smoke.
But there was a twist: a new mutational signature, SBS40a, was found in 28% of never-smokers but not in smokers. The origin of this marker remains unclear, but it suggests that pollution may not be the only hidden risk.
The study adds to a growing body of evidence that air pollution is not just an irritant—it’s a carcinogen. Fine particles can be inhaled deep into the lungs, where they may damage DNA directly or trigger chronic inflammation that promotes tumor growth.
Even more surprising, another carcinogen showed up in the data: aristolochic acid, found in some traditional Chinese herbal remedies. This compound was associated with a distinct mutational signature in patients from Taiwan, hinting at a possible secondary environmental risk factor for lung cancer in never-smokers.
The rise of lung cancer in non-smokers is especially noticeable in East Asia, where rates remain disproportionately high—particularly among women. While genetic predisposition may play a role, this new evidence points clearly to environmental exposures as a key contributor.
And it’s not just an Asian problem. In Western countries, urban dwellers are also exposed to dangerously high levels of air pollution. The World Health Organization estimates that 99% of the world’s population breathes air that exceeds safe pollution thresholds. This means the risk is truly global.
The power of this new research lies in its use of whole-genome sequencing to link pollution to DNA changes. These mutational signatures act as a kind of molecular journal, recording every environmental insult a cell has endured.
The ability to map those changes and match them to known pollutants gives researchers a more precise way to trace cancer origins—not just infer them from epidemiological studies.
While this study can’t definitively prove causation, the strong correlation between pollution exposure and cancer-driving mutations makes it clear that dirty air is more than just a nuisance—it's a potential trigger for deadly disease.
Researchers acknowledge some limitations. Pollution estimates were regional, not personal, meaning it’s unclear how much exposure each participant had. Self-reported smoking histories can also be unreliable.
Still, the pattern is unmistakable. Air pollution behaves like a mutagen, leaving behind signatures that align with known cancer mechanisms. And it appears to affect never-smokers in a strikingly similar fashion to tobacco users—down to the very DNA damage.
This study raises serious public health questions: If environmental exposure to polluted air can cause DNA mutations tied to cancer, what safeguards are in place to protect those most vulnerable?
Governments and public health agencies may need to reconsider air quality regulations, urban zoning, and access to clean air—especially in densely populated cities where pollution levels remain dangerously high.
Healthcare systems might also need to adapt. Traditional lung cancer screenings focus on long-time smokers, but this research could shift how we think about early detection in non-smokers, especially those living in high-risk environments.
Lung cancer has long been viewed through the lens of personal responsibility: if you smoked, you knew the risks. But this research changes that narrative. The air we breathe—something no one can fully avoid—is now emerging as a significant threat.
For non-smokers around the world, especially women and urban residents, this is a wake-up call. Your lungs may be at risk not because of personal choices, but because of public ones—decisions about pollution control, urban planning, and clean energy.
The future of lung cancer prevention may lie not just in quitting cigarettes, but in cleaning up the air we all share.
Credits: Canva
Every year, thousands of seemingly healthy people—often young, active, and without obvious warning signs—die suddenly due to cardiac arrest. For decades, doctors have struggled to reliably identify which patients with heart conditions are at high risk and who might be unnecessarily undergoing invasive interventions. That may be about to change.
In a breakthrough that could transform how we predict—and prevent—sudden cardiac death, scientists at Johns Hopkins University have developed an artificial intelligence model that vastly outperforms current clinical standards in identifying people most at risk. Their new system, known as MAARS (Multimodal AI for Arrhythmia Risk Stratification), not only forecasts risk with up to 93% accuracy in vulnerable age groups, but also explains why someone is high risk—something most algorithms fail to do.
The focus of the study is hypertrophic cardiomyopathy (HCM), one of the most common inherited heart conditions. It affects around 1 in 200 to 500 people globally and is a leading cause of sudden cardiac death in athletes and young adults. While most individuals with HCM live normal lives, a subset is at high risk for lethal arrhythmias—heart rhythm disturbances that can cause the heart to stop without warning. And here’s the catch: right now, doctors only have a 50-50 shot at predicting who will be affected.
“Currently we have patients dying in the prime of their life because they aren’t protected,” said Dr. Natalia Trayanova, senior author of the study and a leading figure in AI cardiology research. “And others are putting up with defibrillators for the rest of their lives with no benefit.”
Trayanova is referring to implantable cardioverter defibrillators (ICDs)—tiny devices inserted into the chest that deliver electric shocks to correct abnormal heart rhythms. They save lives in the right patients but come with physical, emotional, and financial burdens when used unnecessarily.
The need for a more precise, personalized tool has never been greater.
Published in Nature Cardiovascular Research, the new model represents a significant departure from traditional clinical guidelines used across the US and Europe.
MAARS doesn’t rely on a single data source. Instead, it analyzes a multimodal spectrum of information—ranging from electronic health records and patient histories to contrast-enhanced cardiac MRI images that reveal scarring, or fibrosis, within the heart.
Scarring is a key factor in determining sudden death risk in HCM. But interpreting these raw images is extremely challenging for even seasoned cardiologists. That’s where AI has the edge.
“People have not used deep learning on those images,” Trayanova explained. “We are able to extract this hidden information in the images that is not usually accounted for.”
The AI essentially spots dangerous patterns in the heart’s scar tissue that the human eye—and even conventional software—can’t see.
In clinical tests involving real-world patients from Johns Hopkins Hospital and Sanger Heart & Vascular Institute in North Carolina, the results were staggering:
What makes this even more valuable is its ability to provide explanations. The system doesn't just say "this patient is high risk"—it breaks down the why, giving cardiologists critical information to tailor treatment plans.
“This significantly enhances our ability to predict those at highest risk compared to our current algorithms,” said co-author Dr. Jonathan Crispin, a Johns Hopkins cardiologist. “It has the power to transform clinical care.”
MAARS isn't the first AI model from Trayanova’s lab. In 2022, her team built another tool that provided survival predictions for patients with prior heart attacks, known as infarcts. But this latest model breaks new ground by tackling one of the most elusive forms of cardiac risk—arrhythmias caused by scarring in inherited heart conditions. The potential benefits are wide-ranging:
Importantly, the model was trained and validated across diverse demographics, showing consistent performance regardless of age, gender, or ethnicity.
The researchers aren’t stopping here. They plan to expand MAARS to include other forms of arrhythmia-related heart diseases, such as cardiac sarcoidosis and arrhythmogenic right ventricular cardiomyopathy—conditions that also carry a high risk of sudden death but suffer from diagnostic ambiguity.
They’re also working to test the model in larger, more varied populations to move it closer to clinical adoption.
Artificial intelligence has long been hyped as the future of medicine. But MAARS is more than hype—it’s a working proof of concept that shows how deep learning can complement medical expertise, not replace it.
AI may soon become your cardiologist’s most powerful diagnostic tool—one that sees what even the best-trained human eyes might miss. And when lives are on the line, that kind of clarity could mean everything.
© 2024 Bennett, Coleman & Company Limited