Immune cells battle an infection.
Measuring immune resilience
The researchers measured immune resilience in two ways. The first is based on the relative quantities of two types of immune cells, CD4+ T cells and CD8+ T cells. CD4+ T cells coordinate the immune system’s response to pathogens and are often used to measure immune health (with higher levels typically suggesting a stronger immune system). However, in 2021, the researchers found that a low level of CD8+ T cells (which are responsible for killing damaged or infected cells) is also an important indicator of immune health. In fact, patients with high levels of CD4+ T cells and low levels of CD8+ T cells during SARS-CoV-2 and HIV infection were the least likely to develop severe COVID and AIDS.
Individuals with optimal levels of immune resilience were more likely to live longer.
In the same 2021 study, the researchers identified a second measure of immune resilience that involves two gene expression signatures correlated with an infected person’s risk of death. One of the signatures was linked to a higher risk of death; it includes genes related to inflammation — an essential process for jumpstarting the immune system but one that can cause considerable damage if left unbridled. The other signature was linked to a greater chance of survival; it includes genes related to keeping inflammation in check. These genes help the immune system mount a balanced immune response during infection and taper down the response after the threat is gone. The researchers found that participants who expressed the optimal combination of genes lived longer.
Immune resilience and longevity
The researchers assessed levels of immune resilience in nearly 50,000 participants of different ages and with various types of challenges to their immune systems, including acute infections, chronic diseases, and cancers. Their evaluation demonstrated that individuals with optimal levels of immune resilience were more likely to live longer, resist HIV and influenza infections, resist recurrence of skin cancer after kidney transplant, survive COVID infection, and survive sepsis.
However, a person’s immune resilience fluctuates all the time. Study participants who had optimal immune resilience before common symptomatic viral infections like a cold or the flu experienced a shift in their gene expression to poor immune resilience within 48 hours of symptom onset. As these people recovered from their infection, many gradually returned to the more favorable gene expression levels they had before. However, nearly 30% who once had optimal immune resilience did not fully regain that survival-associated profile by the end of the cold and flu season, even though they had recovered from their illness.
Intriguingly, some people who are 90+ years old still have optimal immune resilience, suggesting that these individuals’ immune systems have an exceptional capacity to control inflammation and rapidly restore proper immune balance.
This could suggest that the recovery phase varies among people and diseases. For example, young female sex workers who had many clients and did not use condoms — and thus were repeatedly exposed to sexually transmitted pathogens — had very low immune resilience. However, most of the sex workers who began reducing their exposure to sexually transmitted pathogens by using condoms and decreasing their number of sex partners experienced an improvement in immune resilience over the next 10 years.
Immune resilience and aging
The researchers found that the proportion of people with optimal immune resilience tended to be highest among the young and lowest among the elderly. The researchers suggest that, as people age, they are exposed to increasingly more health conditions (acute infections, chronic diseases, cancers, etc.) which challenge their immune systems to undergo a “respond-and-recover” cycle. During the response phase, CD8+ T cells and inflammatory gene expression increase, and during the recovery phase, they go back down.
However, over a lifetime of repeated challenges, the immune system is slower to recover, altering a person’s immune resilience. Intriguingly, some people who are 90+ years old still have optimal immune resilience, suggesting that these individuals’ immune systems have an exceptional capacity to control inflammation and rapidly restore proper immune balance despite the many respond-and-recover cycles that their immune systems have faced.
Public health ramifications could be significant. Immune cell and gene expression profile assessments are relatively simple to conduct, and being able to determine a person’s immune resilience can help identify whether someone is at greater risk for developing diseases, how they will respond to treatment, and whether, as well as to what extent, they will recover.
Avalanche rescue dogs train to find and dig out people buried in snow slides
By the time he is three, Lume, like Huckleberry, will be a fully trained avy pup and will join seven other avy dogs on Breckenridge ski patrol team. Some of the team members, both human and canine, are also certified to work with Colorado Rapid Avalanche Deployment, a coordinated response team that works with the Summit County Sheriff’s office for avalanche emergencies outside of the ski slopes’ boundaries.
There have been 19 avalanche deaths in the U.S. this season, according to avalanche.org, which tracks slides; eight in Colorado. During the entirety of last season there were 17. Avalanche season runs from November through June, but avalanches can occur year-round.
High tech and high stakes
Complementing avy dogs’ ability to smell people buried in a slide, avalanche detection, rescue and recovery is becoming increasingly high tech. There are transceivers, signal locators, ground scanners and drones, which are considered “games changers” by many in avalanche rescue and recovery
For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
A drone can provide thermal imaging of objects caught in a slide; what looks like a rock from far away might be a human with a heat signature. Transceivers, also known as beacons, send a signal from an avalanche victim to a companion. Signal locators, like RECCO reflectors which are often sewn directly into gear, can echo back a radar signal sent by a detector; most ski resorts have RECCO detector units.
Research suggests that Ground Penetrating Radar (GPR), an electromagnetic tool used by geophysicists to pull images from inside the ground, could be used to locate an avalanche victim. A new study from the Department of Energy’s Sandia National Laboratories suggests that a computer program developed to pinpoint the source of a chemical or biological terrorist attack could also be used to find someone submerged in an avalanche. The search algorithm allows for small robots (described as cockroach-sized) to “swarm” a search area. Researchers say that this distributed optimization algorithm can help find avalanche victims four times faster than current search mechanisms. For a person buried in an avalanche, the chance of survival plummets after 20 minutes, so every moment counts.
An avy dog in training is picking up scent
Sarah McLear
While rescue gear has been evolving, predicting when a slab will fall remains an emerging science — kind of where weather forecasting science was in the 1980s. Avalanche forecasting still relies on documenting avalanches by going out and looking,” says Ethan Greene, director of the Colorado Avalanche Information Center (CAIC). “So if there's a big snowstorm, and as you might remember, most avalanches happened during snowstorms, we could have 10,000 avalanches that release and we document 50,” says Greene. “Avalanche forecasting is essentially pattern recognition,” he adds--and understanding the layering structure of snow.
However, determining where the hazards lie can be tricky. While a dense layer of snow over a softer, weaker layer may be a recipe for an avalanche, there’s so much variability in snowpack that no one formula can predict the trigger. Further, observing and measuring snow at a single point may not be representative of all nearby slopes. Finally, there’s not enough historical data to help avalanche scientists create better prediction models.
That, however, may be changing.
Last year, an international group of researchers created computer simulations of snow cover using 16 years of meteorological data to forecast avalanche hazards, publishing their research in Cold Regions Science and Technology. They believe their models, which categorize different kinds of avalanches, can support forecasting and determine whether the avalanche is natural (caused by temperature changes, wind, additional snowfall) or artificial (triggered by a human or animal).
With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides.
With data from two sites in British Columbia and one in Switzerland, researchers built computer simulations of five different avalanche types. “In terms of real time avalanche forecasting, this has potential to fill in a lot of data gaps, where we don't have field observations of what the snow looks like,” says Simon Horton, a postdoctoral fellow with the Simon Fraser University Centre for Natural Hazards Research and a forecaster with Avalanche Canada, who participated in the study. While complex models that simulate snowpack layers have been around for a few decades, they weren’t easy to apply until recently. “It's been difficult to find out how to apply that to actual decision-making and improving safety,” says Horton. If you can derive avalanche problem types from simulated snowpack properties, he says, you’ll learn “a lot about how you want to manage that risk.”
The five categories include “new snow,” which is unstable and slides down the slope, “wet snow,” when rain or heat makes it liquidly, as well as “wind-drifted snow,” “persistent weak layers” and “old snow.” “That's when there's some type of deeply buried weak layer in the snow that releases without any real change in the weather,” Horton explains. “These ones tend to cause the most accidents.” One step by a person on that structurally weak layer of snow will cause a slide. Horton is hopeful that computer simulations of avalanche types can be used by scientists in different snow climates to help predict hazard levels.
Greene is doubtful. “If you have six slopes that are lined up next to each other, and you're going to try to predict which one avalanches and the exact dimensions and what time, that's going to be really hard to do. And I think it's going to be a long time before we're able to do that,” says Greene.
What both researchers do agree on, though, is that what avalanche prediction really needs is better imagery through satellite detection. “Just being able to count the number of avalanches that are out there will have a huge impact on what we do,” Greene says. “[Satellites] will change what we do, dramatically.” In a 2022 paper, scientists at the University of Aberdeen in England used satellites to study two deadly Himalayan avalanches. The imaging helped them determine that sediment from a 2016 ice avalanche plus subsequent snow avalanches contributed to the 2021 avalanche that caused a flash flood, killing over 200 people. The researchers say that understanding the avalanches characteristics through satellite imagery can inform them how one such event increases the magnitude of another in the same area.
Avy dogs trainers hide in dug-out holes in the snow, teaching the dogs to find buried victims
Sarah McLear
Lifesaving combo: human tech and Mother Nature’s gear
Even as avalanche forecasting evolves, dogs with their built-in rescue mechanisms will remain invaluable. With smell receptors ranging from 800 million for an average dog, to 4 billion for scent hounds, canines remain key to finding people caught in slides. (Humans in comparison, have a meager 12 million.) A new study published in the Journal of Neuroscience revealed that in dogs smell and vision are connected in the brain, which has not been found in other animals. “They can detect the smell of their owner's fingerprints on a glass slide six weeks after they touched it,” says Nicholas Dodman, professor emeritus at Cummings School of Veterinary Medicine at Tufts University. “And they can track from a boat where a box filled with meat was buried in the water, 100 feet below,” says Dodman, who is also co-founder and president of the Center for Canine Behavior Studies.
Another recent study from Queens College in Belfast, United Kingdom, further confirms that dogs can smell when humans are stressed. They can also detect the smell of a person’s breath and the smell of the skin cells of a deceased person.
The emerging avalanche-predicting human-made tech and the incredible nature-made tech of dogs’ olfactory talents is the lifesaving “equipment” that Leffler believes in. Even when human-made technology develops further, it will be most efficient when used together with the millions of dogs’ smell receptors, Leffler believes. “It is a combination of technology and the avalanche dog that will always be effective in finding an avalanche victim.”