The skin serves as our body’s first line of defense against external threats. As we age, however, the epidermis – the outermost layer of skin – gradually becomes thinner and loses its protective strength. Research has long emphasized the benefits of vitamin C (VC) in maintaining skin health and promoting antioxidant properties.

Recently, a team of researchers in Japan made an exciting discovery: VC helps thicken the skin by directly activating genes that control skin cell growth and development. Their findings, published online in the Journal of Investigative Dermatology, suggest that VC may restore skin function by reactivating genes essential for epidermal renewal.

Led by Dr. Akihito Ishigami, Vice President of the Division of Biology and Medical Sciences at Tokyo Metropolitan Institute for Geriatrics and Gerontology, the study used human epidermal equivalents – laboratory-grown models that closely mimic real human skin. In this model, skin cells are exposed to air on the surface while being nourished from underneath by a liquid nutrient medium.

The researchers applied VC at concentrations comparable to those typically transported from the bloodstream into the epidermis and found that VC-treated skin showed a thicker epidermal cell layer without significantly affecting the stratum corneum (the outer layer composed of dead cells) on day seven. By day 14, the inner layer was even thicker, and the outer layer was found to be thinner, suggesting that VC promotes the formation and division of keratinocytes.

Importantly, the study revealed that VC helps skin cells grow by reactivating genes associated with cell proliferation. This process occurs through DNA demethylation – a process in which methyl groups are removed from DNA, allowing for gene expression and promoting cell growth.

The researchers further identified over 10,138 hypomethylated differentially methylated regions in VC-treated skin and observed a 1.6- to 75.2-fold increase in the expression of 12 key proliferation-related genes. When a TET enzyme inhibitor was applied, these effects were reversed, confirming that VC functions through TET-mediated DNA demethylation.

These findings reveal how VC promotes skin renewal by triggering genetic pathways involved in growth and repair. This suggests that VC may be particularly helpful for older adults or those with damaged or thinning skin, boosting the skin’s natural capacity to regenerate and strengthen itself.

“We found that VC helps thicken the skin by encouraging keratinocyte proliferation through DNA demethylation, making it a promising treatment for thinning skin, especially in older adults,” concludes Dr. Ishigami.

This study was supported by grants from the Japan Society for the Promotion of Science (JSPS) KAKENHI: grant number 19K05902.

The article’s content has been rewritten to improve clarity, structure, and style while maintaining the core ideas.

For many, fitness trackers have become indispensable tools for monitoring how many calories they’ve burned in a day. However, these devices often inaccurately measure activity, particularly for those living with obesity. This is because current algorithms were built for people without obesity, and hip-worn trackers misread energy burn due to gait changes and device tilt. Wrist-worn models promise better comfort, adherence, and accuracy across body types, but no one has rigorously tested or calibrated them for this group.

A team of scientists at Northwestern University has developed a new algorithm that enables smartwatches to more accurately monitor the calories burned by people with obesity during various physical activities. The technology bridges a critical gap in fitness technology, making it easier for more people with obesity to track their daily activities and energy use.

The algorithm was tested against 11 state-of-the-art algorithms designed by researchers using research-grade devices and wearable cameras to catch every moment when wrist sensors missed the mark on calorie burn. The findings were published in Nature Scientific Reports.

The exercise class that motivated the research
Alshurafa was motivated to create the algorithm after attending an exercise class with his mother-in-law who has obesity. She worked harder than anyone else, yet when they glanced at the leaderboard, her numbers barely registered. This moment hit him: fitness shouldn’t feel like a trap for the people who need it most.

Algorithm rivals gold-standard methods
By using data from commercial fitness trackers, the new model rivals gold-standard methods of measuring energy burn and can estimate how much energy someone with obesity is using every minute, achieving over 95% accuracy in real-world situations. This advancement makes it easier for more people with obesity to track their daily activities and energy use.

How the study measured energy burn
In one group, 27 study participants wore a fitness tracker and metabolic cart – a mask that measures the volume of oxygen the wearer inhales and the volume of carbon dioxide the wearer exhales to calculate their energy burn (in kilocalories/kCals) and resting metabolic rate. The study participants went through a set of physical activities to measure their energy burn during each task. The scientists then looked at the fitness tracker results to see how they compared to the metabolic cart results.

In another group, 25 study participants wore a fitness tracker and body camera while just living their lives. The body camera allowed the scientists to visually confirm when the algorithm over- or under-estimated kCals.

At times, Alshurafa said he would challenge study participants to do as many pushups as they could in five minutes.
Many couldn’t drop to the floor, but each one crushed wall-pushups, their arms shaking with effort. We celebrate ‘standard’ workouts as the ultimate test, but those standards leave out so many people. These experiences showed me we must rethink how gyms, trackers, and exercise programs measure success – so no one’s hard work goes unseen.

The study is titled, “Developing and comparing a new BMI inclusive energy burn algorithm on wrist-worn wearables.”

Revolutionizing Forest Carbon Measurement with Space-Laser AI Technology

Forests are often referred to as the lungs of our planet, storing roughly 80 percent of the world’s terrestrial carbon and playing a critical role in regulating Earth’s climate. To understand this vital component of our ecosystem, researchers have been working tirelessly to develop more accurate and efficient methods for measuring forest carbon cycles.

A recent study by Hamdi Zurqani, an assistant professor of geospatial science at the University of Arkansas, has taken a significant leap forward in this endeavor. By integrating open-access satellite data with artificial intelligence algorithms on Google Earth Engine, researchers can now quickly and accurately map large-scale forest aboveground biomass, even in remote areas where accessibility is often an issue.

The study utilized information from NASA’s Global Ecosystem Dynamics Investigation LiDAR (GEDI), which features three lasers installed on the International Space Station. This system allows for precise measurements of three-dimensional forest canopy height, vertical structure, and surface elevation. Additionally, imagery data from the European Space Agency’s Copernicus Sentinel satellites – Sentinel-1 and Sentinel-2 – were combined with the 3D imagery from GEDI to improve the accuracy of biomass estimations.

The study tested four machine learning algorithms to analyze the data: Gradient tree boosting, random forest, classification and regression trees (CART), and support vector machine. Gradient tree boosting achieved the highest accuracy score and lowest error rates, while random forest came in second as a reliable but slightly less precise option. CART provided reasonable estimates but tended to focus on a smaller subset, highlighting that not all AI models are equally suited for estimating aboveground forest biomass.

The most accurate predictions came from combining Sentinel-2 optical data, vegetation indices, topographic features, and canopy height with the GEDI LiDAR dataset serving as the reference input for both training and testing the machine learning models. This demonstrates the importance of multi-source data integration in achieving reliable biomass mapping.

This breakthrough has significant implications for better accounting of carbon and improved forest management on a global scale. With more accurate assessments, governments and organizations can precisely track carbon sequestration and emissions from deforestation to inform policy decisions.

While there are still challenges remaining, such as the impact weather can have on satellite data and the lack of high-resolution LiDAR coverage in some regions, researchers like Zurqani are pushing forward with innovative solutions. Future research may explore deeper AI models, such as neural networks, to refine predictions further.

As climate change intensifies, technology like this will be indispensable in safeguarding our forests and the planet. The revolutionized forest carbon measurement technology is a beacon of hope for a more sustainable future, where we can harness the power of innovation to protect our environment and ensure a better tomorrow for generations to come.