Why Some COVID-19 Infections May Be Free of Symptoms But Not Free of Harm

Scientists are studying the potential consequences of asymptomatic COVID-19 and how many people may suffer long term health problems. Eric Topol was worried when he first saw images of the lungs of people who had been infected with COVID-19 aboard the Diamond Princess, a cruise ship that was quarantined off the coast of Japan in the earliest weeks of the pandemic.

A study of 104 passengers found that 76 of them had COVID but were asymptomatic. Of that group, CT scans showed that 54 percent had lung abnormalities—patchy grey spots known as ground glass opacities that signal fluid build-up in the lungs.

These CT scans were “disturbing,” wrote Topol, founder and director of the Scripps Research Translational Institute, with co-author Daniel Oran in a narrative review of asymptomatic disease published in the Annals of Internal Medicine. “If confirmed, this finding suggests that the absence of symptoms might not necessarily mean the absence of harm.”

One recent study estimated that a staggering 35 percent of all COVID-19 infections are asymptomatic. “That’s why it’s important to know if this is a vulnerability,” Topol says.

But Topol says he hasn’t seen any further studies investigating lung abnormalities in asymptomatic people in the more than a year and a half since the Diamond Princess cases were first documented. “It’s like we just gave up on it.”

He argues that asymptomatic disease hasn’t gotten the attention it should amid the race to treat severe disease and develop vaccines to prevent it. As a result, scientists are still largely in the dark about the potential consequences of asymptomatic infections—or how many people are suffering those consequences.

One stumbling block that scientists worry could keep them from truly understanding the scope of the problem is that it’s incredibly challenging to pinpoint how many people had asymptomatic infections. “There’s probably a pool of people out there who had asymptomatic disease but were never tested so they don’t know they had COVID at that time,” says Ann Parker, assistant professor of medicine at Johns Hopkins and a specialist in post-acute COVID-19 care.

Still, there is some evidence that asymptomatic disease can cause serious harm among some people—including blood clots, heart damage, a mysterious inflammatory disorder, and long COVID, the syndrome marked by a range of symptoms from breathing difficulties to brain fog that linger after an infection. Here’s a look at what scientists know so far about the effects of asymptomatic COVID-19 and what they’re still trying to figure out.

Heart inflammation and blood clots

Just as imaging scans have revealed damage to the lungs of asymptomatic individuals, chest scans have also shown abnormalities in the hearts and blood of people with asymptomatic infections—including blood clots and inflammation.

Thrombosis Journal and other publications have described several cases of blood clots in the kidneys, lungs, and brains of people who hadn’t had any symptoms. When these gel-like clumps get stuck in a vein, they prevent an organ from getting the blood it needs to function—which can lead to seizures, strokes, heart attacks, and death.

There have been relatively few of these case reports—and it’s unclear whether some patients might have had other underlying issues that could have caused a clot. But the Washington State researchers who reported on one case of renal blood clot write that it “suggests that unexplained thrombus in otherwise asymptomatic patients can be a direct result of COVID-19 infection, and serves as a call to action for emergency department clinicians to treat unexplained thrombotic events as evidence of COVID-19.”

Meanwhile, studies also suggest that asymptomatic infections could be causing harm to the heart. In May, cardiac MRI scans of 1,600 college athletes who had tested positive for COVID-19 revealed evidence of myocarditis, or inflammation of the heart muscle, in 37 people—28 of whom hadn’t had any symptoms, says Saurabh Rajpal, a cardiovascular disease specialist at the Ohio State University and lead author on the study.

Myocarditis can cause symptoms such as chest pain, palpitations, and fainting—but sometimes it doesn’t produce any symptoms at all. Rajpal says that while the athletes in the study were asymptomatic, “the changes on the MRI were similar to or almost the same as those who had clinical or symptomatic myocarditis.”

Although these chest scans are worrisome, Rajpal says that scientists don’t know yet what they ultimately mean for the health of asymptomatic patients. It’s possible that myocarditis might resolve over time—perhaps even before patients know they had it—or it could develop into a more serious long-term health issue. Long-term studies are necessary to suss that out.

The athletes’ heart inflammation might also be completely unrelated to their COVID-19 infection. Scientists would need to compare the scans with a set taken just before an individual was infected with COVID-19. So that, Rajpal says, will still need to be teased out.

Long COVID

Additionally, people with asymptomatic infections are at risk of becoming so-called COVID-19 long-haulers, a syndrome whose definition has been hard to pin down as it can include any combination of diverse and often overlapping symptoms such as pain, breathing difficulties, fatigue, brain fog, dizziness, sleep disturbance, and hypertension.

“There’s a myth out there that it only occurs with severe COVID, and obviously it occurs far more frequently in mild COVID,” Topol says.

Linda Geng, co-director of Stanford Health Care’s Post-Acute COVID-19 Syndrome Clinic in the U.S., agrees. “There is actually not a great predictive factor about the severity of your illness in the acute phase and whether you will get long COVID,” she says. “And long COVID can be quite debilitating, and we don’t know the endpoint for those who are suffering from it.”

Studies attempting to assess how many asymptomatic infections account for long COVID symptoms have varied. FAIR Health, a healthcare nonprofit in the U.S., found from an analysis of healthcare claims that about a fifth of asymptomatic patients went on to become long-haulers. Another study, which is under peer review, used data from the University of California’s electronic health records and estimated that number could be as high as 32 percent.

Melissa Pinto, a co-author of the latter study and associate professor in the Sue & Bill Gross School of Nursing at University of California Irvine, says the researchers examined healthcare records of people who tested positive for COVID-19 but hadn’t reported symptoms at the time of infection—only to come in later with symptoms associated with long COVID-19. To ensure they were identifying long-haulers, the researchers screened out anyone with a preexisting illness that could explain their later symptoms.

“This is not from another chronic disease,” she says. “These are new symptoms.”

But it’s unclear how accurate any of these estimates might be. Pinto says that some long-haulers are wary of seeking care after having their symptoms dismissed by physicians who weren’t familiar with long COVID-19 syndrome. That’s why she believes that the rates of asymptomatic infections among long-haulers are an underestimate.

Anecdotally, Geng and Parker both say that while they’ve seen plenty of patients with mild symptoms that initially went unrecognised, they’ve had little experience treating patients who were truly asymptomatic.

“We saw many patients who didn’t think they had symptoms except in retrospect because they found out that they had tested positive,” Geng says. “Because they’ve had these long unexplained symptoms of what’s presumed to be long COVID, they think, well, maybe that wasn’t allergies.”

But she thinks that most people who were truly asymptomatic are unlikely to have gotten tested and therefore wouldn’t think to consult a specialist in post-COVID-19 care if they started experiencing unexplained symptoms like brain fog and dizziness.

Parker says that ultimately physicians are still trying to understand the broad symptoms seen in long-haulers. “When a patient comes to see us, we do a very thorough evaluation because we still don’t know exactly what to attribute to COVID and what might be a pre-existing underlying syndrome,” she says. “The last thing I want to have happen is to say to a patient, yes, this is because you had COVID and miss something else that we could have addressed.”

Mysterious inflammation in children

Physicians have also seen troubling clinical manifestations of asymptomatic COVID-19 in children. Early in the pandemic, reports emerged of a rare and mysterious inflammatory syndrome similar to Kawasaki disease that typically sets in weeks after an initial infection.

“Six weeks down the line these people, especially children, will develop inflammation throughout their body,” Rajpal says.

The condition—now called multisystem inflammatory syndrome in children, or MIS-C—typically causes fever, rash, abdominal pain, vomiting, and diarrhoea. It can have harmful effects on multiple organs, from hearts that have trouble pumping blood to lungs that are scarred. It is typically seen among children under 14, although adults have also been diagnosed with this syndrome.

MIS-C is incredibly rare. Kanwal Farooqi, assistant professor of paediatrics at Columbia University Vagelos College of Physicians and Surgeons, says that less than one percent of paediatric COVID-19 patients present with some type of critical disease—and MIS-C is just one of them. However, asymptomatic infections do play a role in the syndrome: A recent study of 1,075 children who had been diagnosed with MIS-C showed that three-quarters had originally been asymptomatic.

But there’s reason to hope that this syndrome might not cause long-term effects in patients, symptomatic or otherwise. Farooqi was the lead author on a recent study of 45 paediatric patients showing that their heart problems—which ranged from leaky valves to enlarged coronary arteries—mostly resolved within six months.

“That is reassuring,” Farooqi says. Still, she recommends administering follow-up MRI scans even to patients whose heart troubles seem to have resolved to make sure there’s no longer-term damage, such as scarring. She also says that it’s “really reasonable” to be cautious about asymptomatic infections and encourages parents to have their child evaluated if they have any persistent symptoms even if the original infection was mild or asymptomatic.

“What’s important is that we can’t right now say that there are no consequences,” she says.

Calls for more studies

Scientists caution that there’s still so much we don’t know about the potential harm of asymptomatic infections. Many have called for more rigorous studies to get to the bottom of the long-term effects of asymptomatic disease, why those effects occur, and how to treat them.

Rajpal points out that his study was only possible because the Big 10 athletic conference requires athletes to get tested every few days. Regular testing is key for uncovering asymptomatic cases, he says, which means that most data on asymptomatic disease is likely to come from healthcare workers, athletes, and other workplaces with strict testing protocols.

It’s also unclear what could be causing these lingering side effects. Scientists hypothesise that it could be an inflammatory response of the body’s immune system that persists long after an infection has been cleared. Others suggest there could be remnants of the virus lingering in the body that continue to trigger an immune reaction months after the COVID-19 infection peaked.

“This is all unchartered, unproven, just a lot of theories,” Topol says.

Yet even if asymptomatic infections aren’t linked in high rates to death and hospitalisation, Pinto and others say it’s important to keep in mind that long COVID-19 symptoms can be debilitating to a patient’s quality of life.

“Even if people survive, we don’t want them to be having a lifelong chronic disease,” Pinto says. “We don’t know what this does to the body, so it’s not something that I would want to take my chances with.”

The bottom line

With so much we don’t know about the long-term effects of asymptomatic COVID-19, scientists insist it’s better to err on the side of caution.

“The full impact can take years to show,” Rajpal says. Although the chances are slim that an individual with asymptomatic infection will have a really bad outcome, he points out that the continuing high rate of infections means that more people are going to suffer.

“Even rare things can affect a lot of people,” he says. “From a public health perspective if you can reduce the number of people that get this infection, you will reduce the number of people who get severe outcomes.”

Parker agrees, adding that it’s particularly important to prevent infection now as the more transmissible Delta variant drives surges in cases and hospitalisations across the country.

“We have had an amazing breakthrough in terms of the rapid development of effective and safe vaccines,” she says. Although Parker and other scientists remain uncertain of the health effects of asymptomatic COVID-19, “we do know that vaccinations are safe and effective and available.”

By Amy McKeever

Source: Why some COVID-19 infections may be free of symptoms but not free of harm | National Geographic

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How To Support Kids Who Are Anxious About Returning School

Back-to-school jitters are normal every fall. But as families prepare for the beginning of the 2021–22 school year, these run-of-the-mill worries are colliding with fresh uncertainties about the ongoing COVID-19 pandemic, leaving kids and parents more anxious than usual.

Parents can use many strategies to help their children handle this challenging situation, according to Elizabeth Reichert, clinical associate professor of psychiatry and behavioral sciences at the Stanford University School of Medicine.

“I often talk to parents about being the lighthouse in their child’s storm, the light that shines steadily in a predictable rhythm and doesn’t waver no matter how big the storm is,” Reichert said. “Their job is to be that lighthouse.”

Reichert spoke with science writer Erin Digitale about how parents can help ensure that budding students of any age—from preschool to high school—are ready to handle anxieties as the school year begins.

Erin Digitale: What are some concerns kids may have?

Elizabeth Reichert: Lots of things come to mind. Many kids are going to a new school for the first time: Maybe they’re starting middle school, preschool, or kindergarten. Those are big transitions in nonpandemic times. With the pandemic, we might see more stress in kids of all ages.

Children may have concerns specific to the pandemic, such as the mandate that California students must wear masks while indoors at school. Kids who are more anxious may ask a lot of questions: “How am I going to keep my mask on all day? What if I want to take it off? What are the rules around it?” They may have increased fear of getting sick, too.

For some children and teens, it will be the first time they’ve been in close proximity to groups of people in a very long time, which brings up concerns about social interactions. For kids in middle and high school, social dynamics are especially important. They’ve just had a year and a half of navigating their social lives in the virtual world, and now they’re re-navigating how to manage social dynamics in person. Social interactions may feel more emotionally draining.

Also, not all kids are the same. With virtual learning, some children really struggled to stay engaged and motivated, grasp the material, and remain connected with friends and teachers. But there were other children, often those who were shyer or had difficulties in large-group settings, who thrived. For those more introverted kiddos, if they’ve been in a comfort zone at home, going back to large groups may be a more difficult transition.

ED: What signs might parents see that children are feeling anxious or otherwise struggling emotionally?

ER: This depends on the age of the child. Among little ones, parents may see increased tearfulness about going to preschool or day care, clingy behavior, or regression in milestones such as potty training. With school-aged children, parents may see resistance to going to school, oppositional behavior, and somatic complaints such as stomachaches or headaches.

That’s going to be really tricky to navigate because schools now have strict guidelines about not coming to school sick. For teens, there may also be school refusal and withdrawn behavior, such as staying isolated in their rooms, or more irritability and moodiness. Risky behavior such as substance abuse may also increase.

Parents can expect some distress and worry during the first few weeks after any transition—especially now, when children are being asked to do many new things all at once. That can affect energy levels and emotional reserves. But if there is a major change from a child’s or teen’s baseline behavior that doesn’t dissipate after a couple of weeks—such as a teenager who is withdrawing more and more and refusing to engage in typical activities, or a child who is progressively more distressed—that is a red flag. Parents may want to consider seeking help at that point.

ED: What proactive steps can parents take before school begins?

ER: Parents can start talking about going back, listening to what’s on their child’s mind, and engaging kids in the fun components of returning to school, such as picking out school supplies or a new T-shirt—something they can get excited about. They can also walk or drive by the school or visit its playground to build excitement. It may also be helpful to start practicing saying goodbye and leaving the house, encouraging independent play, and helping children adjust to being away from their parents.

If bedtimes have drifted later during summer vacation, parents can shift the family schedule during the week or two before school starts to get back in the habit of going to bed and waking up earlier. They can also reestablish other pre-pandemic routines that worked well for the family.

ED: If a child still feels distressed, what should parents do to help?

ER: If a child remains anxious, there are key steps parents can take. When our children are upset, our natural is instinct to remove the distress they’re experiencing. But the first step is not jumping straight to problem solving.

The first step is to listen, to create space to hear the kid’s concerns. Acknowledge what they’re feeling even if you don’t agree with it. The child should feel that they’re being heard, that it is OK to feel what they are feeling, and that they have space to talk to Mom or Dad.

Once parents have a better sense of what’s going on, they should try to work collaboratively with the child to figure out a plan. They can ask: What does the child feel like they’re capable of doing? What can Mom or Dad do to help? Who else could help—a friend, sibling, another family member? If, for example, a child refuses to go to school, parents can say, “How can we make it feel easier?” while also communicating to the child that, ultimately, it’s their job to go to school.

By creating small opportunities for getting through difficult situations and coping with their worries, children will build the confidence and the independence they need to feel more in control and less afraid. It’s important to remember that children are resilient and adaptable, and, for many, after a period of transition, they will find their groove.

Parents can also elicit the help of the school and teacher. Teachers know this is a big transition for kids, and they are gearing up to help.

ED: Parents feel anxiety about this transition, too. What healthy coping strategies can they use to make sure they manage their own stress instead of expressing it in ways that may increase their child’s distress?

ER: Parents are the biggest models for our kids. If our kids see us really anxious about something, they’re going to feed off that. Parents need to be mindful of their own emotions so they can self-regulate and become present for their child.

We want to be steady sources of support for our children. It’s also fine to say we feel worried or we don’t know the answer, because that shows it’s OK to feel those things. The problem is when our worries get too big, when we’re no longer calm, or we are saying and doing things we don’t want to model for our children.

It’s essential to find moments for self-care. Taking even just a couple of deep breaths in the moment, taking a bathroom break, getting a drink of water, or doing other things that create a brief transition for yourself, a moment to regulate your feelings, is helpful. Think back to what worked for you before the pandemic, and try getting even a small inkling of that back, such as five minutes a day of moving your body if exercise helps you. This is not only important for you as a parent, but it also shows your child that you have strategies to take care of yourself.

We can also invite our children into healthy coping activities with us: A parent can say to a school-aged or older child, “I’m feeling pretty stressed about this, and for me, going for a walk helps me clear my head. Do you want to go for a walk with me?” Parents and young kids can blow bubbles together—small kids enjoy it, and you can talk about how big breaths for bubbles help everyone feel better.

If they need more help, parents can seek resources from the teachers and support staff at their child’s school, from their pediatrician, and from online resources at the Stanford Parenting Center at Stanford Children’s Health.

Source: How to Support Kids Who Are Anxious About Returning…

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Moderna Vaccine Creates Twice as Many Antibodies as Pfizer, Study Shows

Coronavirus: Modern vaccine generated more than double antibodies than Pfizer shot. Moderna Inc.’s Covid vaccine generated more than double the antibodies from a similar shot made by Pfizer Inc. and BioNTech SE in research that directly compared immune responses with inoculations.

A study of nearly 2,500 workers at a major hospital in Belgium found antibody levels among people who had not been infected with coronavirus before receiving two doses of the Moderna vaccine averaged 2,888 units per day. Milliliters, compared to 1,108 units / ml in a similar group that received two shots of the Pfizer shot.

The results, published Monday in a letter to the Journal of the American Medical Association, suggested that the differences could be explained by:

– larger amount of active ingredient in the Moderna vaccine – 100 micrograms versus 30 micrograms in Pfizer-BioNTech. Longer interval between doses of the Moderna vaccine – four weeks versus three weeks for Pfizer-BioNTech

Moderna’s vaccine was associated with a double risk reduction against breakthrough SARS-CoV-2 infections compared to Pfizers in a review of humans in the Mayo Clinic Health System in the United States from January to July. The results were reported in a separate study released prior to publication and peer review on 9 August.

The Moderna COVID‑19 vaccine (pINN: elasomeran), codenamed mRNA-1273 and sold under the brand name Spikevax, is a COVID-19 vaccine developed by Moderna, the United States National Institute of Allergy and Infectious Diseases (NIAID) and the Biomedical Advanced Research and Development Authority (BARDA).

It is authorized for use in people aged twelve years and older in some jurisdictions and for people eighteen years and older in other jurisdictions to provide protection against COVID-19 which is caused by infection by the SARS-CoV-2 virus. It is designed to be administered as two or three 0.5 mL doses given by intramuscular injection at an interval of at least 28 days apart.

It is an RNA vaccine composed of nucleoside-modified mRNA (modRNA) encoding a spike protein of SARS-CoV-2, which is encapsulated in lipid nanoparticles

By:

Source: Covid: Moderna Vaccine Creates Twice as Many Antibodies as Pfizer, Study Shows – Bloomberg

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Non-Negotiable Diet, Sleep and Exercise Routines For a Longer Life

Thanks to today’s advanced research and new innovations, it’s more than possible for us to live longer, stronger and healthier lives. While life expectancy in the U.S. dropped one full year during the first half of 2020, according to a CDC report, much of that was attributed to the pandemic. Prior to Covid, however, life expectancy in the U.S. was 78.8 years in 2019, up a tenth of a year over 2018.

As a longevity researcher, I’ve spent the bulk of my career gathering insights from world-leading health experts, doctors, scientists and nutritionists from all over the world. Here’s what I tell people when they ask about the non-negotiable rules I live by for a longer life:

1. Get regular checkups

Early diagnosis is critical for the prevention of disease and age-related decline, so it’s important to get yourself checked regularly, and as comprehensively as possible.

At the very least, I make it a point to have a complete annual physical exam that includes blood count and metabolic blood chemistry panels, a thyroid panel and testing to reveal potential deficiencies in vitamin D, vitamin B, iron and magnesium (all nutrients that our body needs to perform a variety of essential functions).

2. Let food be thy medicine

Poor diet is the top driver of noncommunicable diseases worldwide, killing at least 11 million people every year.

Here are some of my diet rules for a longer life:

  • Eat more plants: To reduce your risk of cardiovascular disease and diabetes, try to have every meal include at least one plant-based dish. I typically have broccoli, cauliflower, asparagus or zucchini as a side for lunch and dinner. When I snack, I opt for berries, nuts or fresh veggies.
  • Avoid processed foods: Many products you find in grocery stores today are loaded with salt, sugar, saturated fats and chemical preservatives. A 2019 study of 20,000 men and women aged 21 to 90 found that a diet high in processed foods resulted in an 18% increased risk of death by all causes.
  • Drink more water: Most of us drink far too little water for our optimal health. I keep a bottle of water with lemon slices at hand wherever I spent most of my day.
  • Include healthy fats: Not all fats are bad. High-density lipids (HDL), including monounsaturated and polyunsaturated fats, are considered “good fats,” and are essential to a healthy heart, blood flow and blood pressure.

3. Get moving (yes, walking counts)

Just 15 to 25 minutes of moderate exercise a day can prolong your life by up to three years if you are obese, and seven years if you are in good shape, one study found.

I try not to focus on the specific type of exercise you do. Anything that gets you up out of the chair, moving and breathing more intensely on a regular basis is going to help.

That’s why the method I practice and recommend the most is extremely simple: Walking. Brisk walking can improve cardiovascular health and reduce risk of obesity, diabetes and high blood pressure. It can even ease symptoms of depression and anxiety.

4. Eat early, and less often

Clinical data shows that intermittent fasting — an eating pattern where you cycle between periods of eating and fasting — can improve insulin stability, cholesterol levels, blood pressure, mental alertness and energy.

To ease into the “eat early, and less often” diet, I started with a 16:8-hour intermittent fasting regimen. This is where you eat all of your meals within one eight-hour period — for instance, between 8 a.m. and 4 p.m., or between 10 a.m. and 6 p.m.

But keep in mind that a fasting or caloric-restricted diet isn’t for everyone; always talk to your doctor before making any drastic changes to your diet and eating routine.

5. Constantly work on quitting bad habits

One of the biggest toxic habits is excessive use of alcohol. Studies show that high and regular use can contribute to damages your liver and pancreas, high blood pressure and the immune system.

Large amounts of sugar consumption is another bad habit. Sure, in the right doses, sugars from fruits, vegetables and even grains play an important role in a healthy diet. I eat fruits and treat myself to some ice cream once in a while. But make no mistake: Excess sugar in all its forms is poison. To lessen my intake, I avoid processed foods and sugary drinks.

Lastly, I don’t smoke — but for anyone who does, I recommend quitting as soon as possible. According to the CDC, cigarette smoking is behind 480,000 deaths per year in the U.S.

6. Make sleep your superpower

A handful of studies of millions of sleepers show that less sleep can lead to a shorter life. Newer studies are strengthening known and suspected relationships between inadequate sleep and a wide range of disorders, including hypertensionobesity and diabetes and impaired immune functioning.

I aim for at least seven hours of sleep per night. For me, an essential ingredient for getting quality sleep is darkness; I make sure there’s no light and no electronic devices in my room before bedtime.

 

By: Sergey Young, Contributor

Sergey Young is a longevity researcher, investor and the founder of Longevity Vision Fund. He is also the author of “The Science and Technology of Growing Young: An Insider’s Guide to the Breakthroughs That Will Dramatically Extend Our Lifespan.” Sergey is on the Board of Directors of the American Federation of Aging Research and the Development Sponsor of Age Reversal XPRIZE global competition, designed to cure aging. Follow him on Twitter @SergeyYoung200.

Source: ‘Non-negotiable’ diet, sleep and exercise routines for a longer life

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What’s The Difference Between Sympathy & Empathy? Psychologists Explain

The suffix -pathy comes from the Greek word for “suffering,” pathos. The U.S. medical system is built around pathology, which simply means diagnosing suffering and treating disease. Similarly, mental health professionals find social connections critically important to the ways that people cope with and overcome suffering, grief, and trauma. Words like sympathy, empathy, and even apathy describe the nuanced differences between the very complex social connections and reactions humans display when we are suffering or when we witness others in pain.

While subtle behavioral differences might seem obvious to therapists, counselors, and psychologists, it’s not so easy for everyone else. So we spoke to Atlanta-based therapist Habiba Zaman, LPC, NCC, Pepperdine University professor of psychology Steven M. Sultanoff, Ph.D., and licensed clinical psychologist Bruce L. Thiessen, Ph.D., about simple ways to define sympathy and empathy—and their relationship to compassion.

Defining sympathy.

“Sympathy is when you understand someone else’s suffering and feel sorrow or pity for the experience they are facing,” Zaman explains. “It involves having a value judgment on someone else’s experience.”

While often well intentioned, this value-judgment-centered response often creates a palpable distance between the person in pain and the person who is listening. So, Zaman says, sympathy is often extended when a person doesn’t necessarily relate to, fully comprehend, or appreciate the circumstances of suffering facing someone they know or love.

“The emotion of sympathy is my experience of (reaction to) your situation. Sympathy lacks understanding,” Sultanoff adds. “When you are sympathetic, you get caught up in your own emotional reaction to how you are experiencing the world. This, for the most part, does not demonstrate any understanding of the person in distress.”

He notes that sympathy can create a barrier to understanding that can be activated because a sympathetic person may shift focus away from the person in distress to focus on themselves instead. Sympathy is the emotional reaction of the listener, who might say things like “I feel so sorry that this is happening to you,” or “I get so angry just listening to your story.” Other common ways it can show up are as pity (e.g., “I feel so bad for you”) or even as envy (e.g., “I’m sorry for your loss, but I sure wish I had as much time with my loved ones as you did”).

Defining empathy.

“When one expresses empathy, one draws upon personal experience, in relating to another person in the midst of a similar experience or hardship,” Thiessen explains. “An example of an empathetic statement might be, ‘I also have recently lost a loved one and know what it feels like to experience that deep sense of sorrow and grief.”

He says that this sense of commonality is a key differentiator between empathy and sympathy.

“Empathy is the ability to feel intimately and see the other person’s perspective. It is not just to understand what they are going through but rather, being able to walk in the other person’s shoes,” Zaman explains. “It is being able to say, ‘I am here to feel with you’ and let you know you are not alone.”

She adds that empathy is best defined by how the listener connects with the person in pain. Without judgment, an empathetic person would try to create and hold space for a person’s feelings and experiences. Empathy, which can be taught and honed over time, involves honoring how a person in pain sees their own situation, even if that is not how others might view it.

Understanding the key differences.

When it comes to understanding the key differences between empathy and sympathy, there are both internal and external factors to keep in mind. Sympathy and empathy are largely distinguished by external behavioral and performative aspects, which most people believe are a reflection of how the listener internally feels about the person who is suffering. Instead, the experts say that the difference is more about the relationship between the listener and the sufferer.

On the outside, sympathy often appears socially distant, like a one-off message of condolences, with no follow-up. Zaman says this is because sympathy lacks intimacy, but there may be situational reasons why that might be the case. In certain corporate settings or power structures, it might be appropriate to emotionally withhold to maintain decorum or to preserve group dynamics that extend beyond just the listener and the person in pain. Social dynamics and the appropriateness of displaying curiosity toward a person in pain might make a listener moderate their naturally emotive behavior.

“Sympathy is used in social situations where there isn’t an intimate connection between two people. It would be perfectly appropriate in a corporate environment to experience sympathy from coworkers or a boss. A card or flowers that share in acknowledging grief is perfectly acceptable and is expected in those environments because anything more could be perceived as inauthentic, unless that initial and genuine connection is there,” Zaman says.

Meanwhile, she says, that very same gesture of sending a card and flowers might be wholly inadequate for lifelong friends. Thus, the relationship and social context between the people involved is very important.

Also, no matter how close or distant the relationship, Sultanoff says that empathy is an internal experience of feeling caring, concern, and understanding toward another human being or living creature that is best shown through active and reflective listening.

“Responding by repeating back (but not parroting) what you heard from the other person, while especially attending to their feelings, demonstrates focus on the person and letting go of your own internal distractions,” he says.

In an attempt to be empathetic, a person who genuinely wants to help might share problem-solving advice, but Sultanoff says that this behavior does not necessarily show empathy for the other person’s immediate emotional state. In many ways, the difference between sympathy and empathy is the desire to understand the experience of a person who is suffering, not necessarily the drive to stop their suffering.

What about compassion?

“Both empathy and sympathy, when coming from a place of sincerity, are sensations and open expressions of compassion,” Thiessen says. After all, compassion, which simply means “to suffer together,” is an expression of caring and warmth.

He says that compassion from empathy typically comes from sharing similar experiences with another person, but compassion from sympathy can be just as useful. “For example, the act of researching the types of suffering experienced by an abused child might increase a person’s sympathy for abused children, regardless of whether or not the researching party had ever been a victim of child abuse,” offers Thiessen.

And this ability to extend emotions beyond one’s own personal experience is good because compassion allows humans to be motivated to alleviate harms they, personally, have never experienced.

“Expressions of compassion, be they in the form of empathy, or sympathy, or some palpable act of kindness, can be experienced as a healing balm on the psyche and the soul,” Thiessen says.

Moreover, that emotional inspiration can spark activism, philanthropy, or public advocacy in the service of moral causes that are far-reaching and socially impactful. In this way, actively cultivating compassion can allow an observer in one situation to be a force for change in many others.

The bottom line.

In the simplest of terms, empathy is an internal emotion that is directed outward toward another person, Sultanoff says. It demonstrates a true understanding of the other person, without any personal biases interfering with that understanding. Sympathy, however, is internally directed.

If you are watching someone in mourning or grief, empathy is focused on understanding the person in pain, while sympathy is focused on your reaction to watching that person deal with their pain. “From a mental health perspective, empathy is very healing, and sympathy is not,” Sultanoff says.

“Generally, it feels better to be the recipient of empathy than simply sympathy, because it allows for a point of connection and intimacy. Also, an expression of sympathy may be more difficult to trust unless it is coming from a genuine relationship and a place of genuine concern,” Thiessen summarizes.

All that said, both feelings can serve socially positivity purposes when tied with compassion and action.

Nafeesah Allen, Ph.D.

By :  Nafeesah Allen, Ph.D.

Nafeesah Allen, Ph.D., is an American writer and independent researcher with a particular interest in migration, literature, gender identity, and diaspora studies within the global

Source: Sympathy vs. Empathy: The Key Differences & Social Uses

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U.S. Set To Recommend Booster Covid-19 Vaccine Dose For Most People, Reports Say

U.S health officials are expected to recommend Covid-19 vaccine booster doses for Americans across all eligible age groups eight months after they received their second vaccine dose, to ensure lasting protection against the coronavirus as the more infectious delta variant spreads across the country partially blunting the efficacy of existing vaccine regimens.

According to the Associated Press, health officials could announce the booster recommendation as soon as this week, just a few days after an additional vaccine dose was recommended for people with weakened immune systems.

The Biden administration could then begin rolling out the third shots as early as mid-to-late September, the New York Times reported, citing unnamed officials.

The first booster shots will likely be administered to nursing home residents, health care workers and elderly Americans who were among the first people in the country to be inoculated.

The Associated Press notes that the formal deployment of the booster doses can only take place after the vaccines have been fully approved by the Food and Drug Administration—an action that is expected for the Pfizer jab in the next few weeks.

The Food and Drug Administration is expected to fully approve the Pfizer vaccine in the coming weeks which will formally open the door for it to be offered as a booster to millions of Americans who have already received two vaccine doses.

Big Number

59.4%. That’s the percentage of the eligible U.S. popuplation (12 years of age and older) that has been fully vaccinated against Covid-19, with 70% receiving at least one dose, according to the CDC’s tracker.

Surprising Fact

An estimated 1.1 million people have already received an unauthorized booster dose of the Moderna or Pfizer vaccine, ABC News reported last week, citing an internal CDC document reviewed by the broadcaster. The number is likely an undercount as it only accounts for people who received a third dose of an mRNA vaccine but does not count those who may have received a dose of the one-shot Johnson & Johnson vaccine and then received a second dose of either the Moderna or Pfizer vaccines.

Key Background

Last week, the U.S. Food and Drug Administration approved a booster dose of the Covid-19 vaccines made by Pfizer and Moderna for people with compromised immune systems. The targeted move was aimed at providing better protection for people who have undergone solid organ transplants or those diagnosed with conditions that are considered to be immunocompromised.

Unlike the eight-month gap being proposed for booster doses for the general population, immunocompromised patients can receive their third dose as early as 28 days after their second shot. The FDA’s decision followed similar moves undertaken by Israel, France and Germany who began administering an additional dose to vulnerable populations amid the threat of the more infectious delta variant of the virus.

Contra

As the more infectious delta variant of the coronavirus takes hold across the U.S. questions about the effectiveness or even the necessity of a booster dose remain unanswered. While some vaccines are slightly less effective against the variant, it is still unclear if protection against more severe disease and hospitalizations have been impacted significantly as well.

This makes any decision to authorize booster doses remains a controversial one in the global context as critics decry the fact that developed nations are administering an additional dose at a time when several poorer nations have limited access to vaccines. Earlier this month, the World Health Organization (WHO) called for a moratorium on Covid-19 vaccine booster shots until at least the end of September.

Further Reading

U.S. to Advise Boosters for Most Americans 8 Months After Vaccination (New York Times)

US to recommend COVID vaccine boosters at 8 months (Associated Press)

More Than 1 Million Have Received Unauthorized Third Dose (WebMD)

FDA Authorizes Extra Covid-19 Vaccine Dose For Those With Weakened Immune Systems (Forbes)

How Good Are Covid-19 Vaccines At Protecting Against The Delta Variant? (Forbes)

I am a Breaking News Reporter at Forbes, with a focus on covering important tech policy and business news. Graduated from Columbia University with an MA in Business and Economics Journalism in 2019. Worked as a journalist in New Delhi, India from 2014 to 2018. Have a news tip? DMs are open on Twitter @SiladityaRay or drop me an email at siladitya@protonmail.com.

Source: U.S. Set To Recommend Booster Covid-19 Vaccine Dose For Most People, Reports Say

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Why Vaccinated People Are Getting ‘Breakthrough’ Infections

A wedding in Oklahoma leads to 15 vaccinated guests becoming infected with the coronavirus. Raucous Fourth of July celebrations disperse the virus from Provincetown, Mass., to dozens of places across the country, sometimes carried by fully vaccinated celebrants.

As the Delta variant surges across the nation, reports of infections in vaccinated people have become increasingly frequent — including, most recently, among at least six Texas Democrats, a White House aide and an aide to Speaker Nancy Pelosi.

The highly contagious variant, combined with a lagging vaccination campaign and the near absence of preventive restrictions, is fueling a rapid rise in cases in all states, and hospitalizations in nearly all of them. It now accounts for about 83 percent of infections diagnosed in the United States.

But as worrying as the trend may seem, breakthrough infections — those occurring in vaccinated people — are still relatively uncommon, experts said, and those that cause serious illness, hospitalization or death even more so. More than 97 percent of people hospitalized for Covid-19 are unvaccinated.

“The takeaway message remains, if you’re vaccinated, you are protected,” said Dr. Celine Gounder, an infectious disease specialist at Bellevue Hospital Center in New York. “You are not going to end up with severe disease, hospitalization or death.”

Reports of breakthrough infections should not be taken to mean that the vaccines do not work, Dr. Anthony S. Fauci, the Biden administration’s top pandemic adviser, said on Thursday at a news briefing.

“By no means does that mean that you’re dealing with an unsuccessful vaccine,” he said. “The success of the vaccine is based on the prevention of illness.”

Still, vaccinated people can come down with infections, overwhelmingly asymptomatic or mild. That may come as a surprise to many vaccinated Americans, who often assume that they are completely shielded from the virus. And breakthrough infections raise the possibility, as yet unresolved, that vaccinated people may spread the virus to others.

Given the upwelling of virus across much of the country, some scientists say it is time for vaccinated people to consider wearing masks indoors and in crowded spaces like shopping malls or concert halls — a recommendation that goes beyond current guidelines from the Centers for Disease Control and Prevention, which recommends masking only for unvaccinated people.

The agency does not plan to change its guidelines unless there is a significant change in the science, said a federal official speaking on condition of anonymity because he was not authorized to speak on the matter.

The agency’s guidance already gives local leaders latitude to adjust their policies based on rates of transmission in their communities, he added. Citing the rise of the Delta variant, health officials in several California jurisdictions are already urging a return to indoor masking; Los Angeles County is requiring it.

“Seatbelts reduce risk, but we still need to drive carefully,” said Dr. Scott Dryden-Peterson, an infectious disease physician and epidemiologist at Brigham & Women’s Hospital in Boston. “We’re still trying to figure out what is ‘drive carefully’ in the Delta era, and what we should be doing.”

The uncertainty about Delta results in part from how it differs from previous versions of the coronavirus. Although its mode of transmission is the same — it is inhaled, usually in indoor spaces — Delta is thought to be about twice as contagious as the original virus.

Significantly, early evidence also suggests that people infected with the Delta variant may carry roughly a thousandfold more virus than those infected with the original virus. While that does not seem to mean that they get sicker, it does probably mean that they are more contagious and for longer.

Dose also matters: A vaccinated person exposed to a low dose of the coronavirus may never become infected, or not noticeably so. A vaccinated person exposed to extremely high viral loads of the Delta variant is more likely to find his or her immune defenses overwhelmed.

The problem grows worse as community transmission rates rise, because exposures in dose and number will increase. Vaccination rates in the country have stalled, with less than half of Americans fully immunized, giving the virus plenty of room to spread.

Unvaccinated people “are not, for the most part, taking precautions, and that’s what’s driving it for everybody,” said Dr. Eric J. Rubin, the editor in chief of the New England Journal of Medicine. “We’re all susceptible to whatever anyone’s behavior is in this epidemic.”

Dr. Gounder likened the amount of protection offered by the vaccines to a golf umbrella that keeps people dry in a rainstorm. “But if you’re out in a hurricane, you’re still going to get wet,” she said. “That’s kind of the situation that the Delta variant has created, where there’s still a lot of community spread.”

For the average vaccinated person, a breakthrough infection is likely to be inconsequential, causing few to no symptoms. But there is concern among scientists that a few vaccinated people who become infected may go on to develop long Covid, a poorly understood constellation of symptoms that persists after the active infection is resolved.

Much has been made of Delta’s ability to sidestep immune defenses. In fact, all of the existing vaccines seem able to prevent serious illness and death from the variant. In laboratory studies, Delta actually has proved to be a milder threat than Beta, the variant first identified in South Africa.

Whether a vaccinated person ever becomes infected may depend on how high antibodies spiked after vaccination, how potent those antibodies are against the variant, and whether the level of antibodies in the person’s blood has waned since immunization.

In any case, immune defenses primed by the vaccines should recognize the virus soon after infection and destroy it before significant damage occurs.

“That is what explains why people do get infected and why people don’t get seriously ill,” said Michel C. Nussenzweig, an immunologist at Rockefeller University in New York. “It’s nearly unavoidable, unless you’re going to give people very frequent boosters.”

There is limited evidence beyond anecdotal reports to indicate whether breakthrough infections with the Delta variant are more common or more likely to fan out to other people. The C.D.C. has recorded about 5,500 hospitalizations and deaths in vaccinated people, but it is not tracking milder breakthrough infections.

Additional data is emerging from the Covid-19 Sports and Society Workgroup, a coalition of professional sports leagues that is working closely with the C.D.C. Sports teams in the group are testing more than 10,000 people at least daily and sequencing all infections, according to Dr. Robby Sikka, a physician who worked with the N.B.A.’s Minnesota Timberwolves.

Breakthrough infections in the leagues seem to be more common with the Delta variant than with Alpha, the variant first identified in Britain, he said. As would be predicted, the vaccines cut down the severity and duration of illness significantly, with players returning less than two weeks after becoming infected, compared with nearly three weeks earlier in the pandemic.

But while they are infected, the players carry very high amounts of virus for seven to 10 days, compared with two or three days in those infected with Alpha, Dr. Sikka said. Infected players are required to quarantine, so the project has not been able to track whether they spread the virus to others — but it’s likely that they would, he added.

“If they’re put just willy-nilly back into society, I think you’re going to have spread from vaccinated individuals,” he added. “They don’t even recognize they have Covid because they think they’re vaccinated.”

Elyse Freitas was shocked to discover that 15 vaccinated people became infected at her wedding. Dr. Freitas, 34, a biologist at the University of Oklahoma, said she had been very cautious throughout the pandemic, and had already postponed her wedding once. But after much deliberation, she celebrated the wedding indoors on July 10.

Based on the symptoms, Dr. Freitas believes that the initial infection was at a bachelorette party two days before the wedding, when a dozen vaccinated people went unmasked to bars in downtown Oklahoma City; seven of them later tested positive. Eventually, 17 guests at the wedding became infected, nearly all with mild symptoms.

“In hindsight, I should have paid more attention to the vaccination rates in Oklahoma and the emergence of the Delta variant and adjusted my plans accordingly,” she said.

An outbreak in Provincetown, Mass., illustrates how quickly a cluster can grow, given the right conditions. During its famed Fourth of July celebrations, the small town hosted more than 60,000 unmasked revelers, dancing and mingling in crowded bars and house parties.

The crowds this year were much larger than usual, said Adam Hunt, 55, an advertising executive who has lived in Provincetown part time for about 20 years. But the bars and clubs didn’t open until they were allowed to, Mr. Hunt noted: “We thought we were doing the right thing. We thought we were OK.”

Mr. Hunt did not become infected with the virus, but several of his vaccinated friends who had flown in from places as far as Hawaii and Alabama tested positive after their return. In all, the cluster has grown to at least 256 cases — including 66 visitors from other states — about two-thirds in vaccinated people.

“I did not expect that people who were vaccinated would be becoming positive at the rate that they were,” said Steve Katsurinis, chair of the Provincetown Board of Health. Provincetown has moved swiftly to contain the outbreak, reinstating a mask advisory and stepping up testing. It is conducting 250 tests a day, compared with about eight a day before July 1, Mr. Katsurinis said.

Health officials should also help the public understand that vaccines are doing what they are supposed to — preventing people from getting seriously ill, said Kristen Panthagani, a geneticist at Baylor College of Medicine who runs a blog explaining complex scientific concepts.

“Vaccine efficacy isn’t 100 percent — it never is,” she said. “We shouldn’t expect Covid vaccines to be perfect, either. That’s too high an expectation.”

By:

Source: Why Vaccinated People Are Getting ‘Breakthrough’ Infections – The New York Times

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Scientists Predict Early Covid-19 Symptoms Using AI (And An App)

Combining self-reported symptoms with Artificial Intelligence can predict the early symptoms of Covid-19, according to research led by scientists at Kings College London. Previous studies have predicted whether people will develop Covid using symptoms from the peak of viral infection, which can be less relevant over time — fever is common during later phases, for instance.

The new study reveals which symptoms of infection can be used for early detection of the disease. Published in the journal The Lancet Digital Health, the research used data collected via the ZOE COVID Symptom Study smartphone app. Each app user logged any symptoms that they experienced over the first 3 days, plus the result of a subsequent PCR test for Coronavirus and personal information like age and sex.

Researchers used those self-reported data from the app to assess three models for predicting Covid in advance, which involved using one dataset to train a given model before its performance was tested on another set. The training set included almost 183,000 people who reported symptoms from 16 October to 30 November 2020, while the test dataset consisted of more than 15,000 participants with data between 16 October and 30 November.

The three models were: 1) a statistical method called logical regression; 2) a National Health Service (NHS) algorithm, and; 3) an Artificial Intelligence (AI) approach known as a ‘hierarchical Gaussian process’. Of the three prediction models, the AI approach performed the best, so it was then used to identify patterns in the data. The AI prediction model was sensitive enough to find which symptoms were most relevant in various groups of people.

The subgroups were occupation (healthcare professional versus non-healthcare), age group (16-39, 40-59, 60-79, 80+ years old), sex (male or female), Body-Mass Index (BMI as underweight, normal, overweight/obese) and several well-known health conditions. According to results produced by the AI model, loss of smell was the most relevant early symptom among both healthcare and non-healthcare workers, and the two groups also reported chest pain and a persistent cough.

The symptoms varied among age groups: loss of smell had less relevance to people over 60 years old, for instance, and seemed irrelevant to those over 80 — highlighting age as a key factor in early Covid detection. There was no big difference between sexes for their reported symptoms, but shortness of breath, fatigue and chills/shivers were more relevant signs for men than for women.

No particular patterns were found in BMI subgroups either and, in terms of health conditions, heart disease was most relevant for predicting Covid. As the study’s symptoms were from 2020, its results might only apply to the original strain of the SARS-CoV-2 virus and Alpha variant – the two variants with highest prevalence in the UK that year.

The predictions wouldn’t have been possible without the self-reported data from the ZOE COVID Symptom Study project, a non-profit collaboration between scientists and personalized health company ZOE, which was co-founded by genetic epidemiologist Tim Spector of Kings College London.

The project’s website keeps an up-to-date ranking of the top 5 Covid symptoms reported by British people who are now fully vaccinated (with a Pfizer or AstraZeneca vaccine), have so far received one of the two doses, or are still unvaccinated. Those top 5 symptoms provide a useful resource if you want to know which signs are common for the most prevalent variant circulating in a population — currently Delta – as distinct variants can be associated with different symptoms.

When a new variant emerges in future, you could pass some personal information (such as age) to the AI prediction model so it shows the early symptoms most relevant to you — and, if you developed those symptoms, take a Covid test and perhaps self-isolate before you transmit the virus to other people. As the new study concludes, such steps would help alleviate stress on public health services:

“Early detection of SARS-CoV-2-infected individuals is crucial to contain the spread of the COVID-19 pandemic and efficiently allocate medical resources.” Follow me on Twitter or LinkedIn. Check out my website or some of my other work here.

I’m a science communicator and award-winning journalist with a PhD in evolutionary biology. I specialize in explaining scientific concepts that appear in popular culture and mainly write about health, nature and technology. I spent several years at BBC Science Focus magazine, running the features section and writing about everything from gay genes and internet memes to the science of death and origin of life. I’ve also contributed to Scientific American and Men’s Health. My latest book is ’50 Biology Ideas You Really Need to Know’.

Source: Scientists Predict Early Covid-19 Symptoms Using AI (And An App)

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Critics:

Healthcare providers and researchers are faced with an exponentially increasing volume of information about COVID-19, which makes it difficult to derive insights that can inform treatment. In response, AWS launched CORD-19 Search, a new search website powered by machine learning, that can help researchers quickly and easily search for research papers and documents and answer questions like “When is the salivary viral load highest for COVID-19?”

Built on the Allen Institute for AI’s CORD-19 open research dataset of more than 128,000 research papers and other materials, this machine learning solution can extract relevant medical information from unstructured text and delivers robust natural-language query capabilities, helping to accelerate the pace of discovery.

In the field of medical imaging, meanwhile, researchers are using machine learning to help recognize patterns in images, enhancing the ability of radiologists to indicate the probability of disease and diagnose it earlier.

UC San Diego Health has engineered a new method to diagnose pneumonia earlier, a condition associated with severe COVID-19. This early detection helps doctors quickly triage patients to the appropriate level of care even before a COVID-19 diagnosis is confirmed. Trained with 22,000 notations by human radiologists, the machine learning algorithm overlays x-rays with colour-coded maps that indicate pneumonia probability. With credits donated from the AWS Diagnostic Development Initiative, these methods have now been deployed to every chest x-ray and CT scan throughout UC San Diego Health in a clinical research study.

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Coalition for Epidemic Preparedness Innovations

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Survey: How US employees feel about a full return to the workplace

What Happens To Our Brains When We Get Depressed

In the ’90s, when he was a doctoral student at the University of Lausanne, in Switzerland, neuroscientist Sean Hill spent five years studying how cat brains respond to noise. At the time, researchers knew that two regions—the cerebral cortex, which is the outer layer of the brain, and the thalamus, a nut-like structure near the centre—did most of the work. But, when an auditory signal entered the brain through the ear, what happened, specifically?

Which parts of the cortex and thalamus did the signal travel to? And in what order? The answers to such questions could help doctors treat hearing loss in humans. So, to learn more, Hill, along with his supervisor and a group of lab techs, anaesthetized cats and inserted electrodes into their brains to monitor what happened when the animals were exposed to sounds, which were piped into their ears via miniature headphones. Hill’s probe then captured the brain signals the noises generated.

The last step was to euthanize the cats and dissect their brains, which was the only way for Hill to verify where he’d put his probes. It was not a part of the study he enjoyed. He’d grown up on a family farm in Maine and had developed a reverence for all sentient life. As an undergraduate student in New Hampshire, he’d experimented on pond snails, but only after ensuring that each was properly anaesthetized. “I particularly loved cats,” he says, “but I also deeply believed in the need for animal data.” (For obvious reasons, neuroscientists cannot euthanize and dissect human subjects.)

Over time, Hill came to wonder if his data was being put to the best possible use. In his cat experiments, he generated reels of magnetic tape—printouts that resembled player piano scrolls. Once he had finished analyzing the tapes, he would pack them up and store them in a basement. “It was just so tangible,” he says. “You’d see all these data coming from the animals, but then what would happen with it? There were boxes and boxes that, in all likelihood, would never be looked at again.” Most researchers wouldn’t even know where to find them.

Hill was coming up against two interrelated problems in neuroscience: data scarcity and data wastage. Over the past five decades, brain research has advanced rapidly—we’ve developed treatments for Parkinson’s and epilepsy and have figured out, if only in the roughest terms, which parts of the brain produce arousal, anger, sadness, and pain—but we’re still at the beginning of the journey.

Scientists are still some way, for instance, from knowing the size and shape of each type of neuron (i.e., brain cell), the RNA sequences that govern their behavior, or the strength and frequency of the electrical signals that pass between them. The human brain has 86 billion neurons. That’s a lot of data to collect and record.

But, while brain data is a precious resource, scientists tend to lock it away, like secretive art collectors. Labs the world over are conducting brain experiments using increasingly sophisticated technology, from hulking magnetic-imaging devices to microscopic probes. These experiments generate results, which then get published in journals. Once each new data set has served this limited purpose, it goes . . . somewhere, typically onto a secure hard drive only a few people can access.

Hill’s graduate work in Lausanne was at times demoralizing. He reasoned that, for his research to be worth the costs to both the lab that conducted it and the cats who were its subjects, the resulting data—perhaps even all brain data—should live in the public domain. But scientists generally prefer not to share. Data, after all, is a kind of currency: it helps generate findings, which lead to jobs, money, and professional recognition. Researchers are loath to simply give away a commodity they worked hard to acquire. “There’s an old joke,” says Hill, “that neuroscientists would rather share toothbrushes than data.”

He believes that, if they don’t get over this aversion—and if they continue to stash data in basements and on encrypted hard drives—many profound questions about the brain will remain unanswered. This is not just a matter of academic curiosity: if we improve our understanding of the brain, we could develop treatments that have long eluded us for major mental illnesses.

In 2019, Hill became director of Toronto’s Krembil Centre for Neuroinformatics (KCNI), an organization working at the intersection of neuroscience, information management, brain modelling, and psychiatry. The basic premise of neuroinformatics is this: the brain is big, and if humans are going to have a shot at understanding it, brain science must become big too. The KCNI’s goal is to aggregate brain data and use it to build computerized models that, over time, become ever more complex—all to aid them in understanding the intricacy of a real brain.

There are about thirty labs worldwide explicitly dedicated to such work, and they’re governed by a central regulatory body, the International Neuroinformatics Coordinating Facility, in Sweden. But the KCNI stands out because it’s embedded in a medical institution: the Centre for Addiction and Mental Health (CAMH), Canada’s largest psychiatric hospital. While many other neuroinformatics labs study genetics or cognitive processing, the KCNI seeks to demystify conditions like schizophrenia, anxiety, and dementia. Its first area of focus is depression.

Fundamentally, we don’t have a biological understanding of depression.

The disease affects more than 260 million people around the world, but we barely understand it. We know that the balance between the prefrontal cortex (at the front of the brain) and the anterior cingulate cortex (tucked just behind it) plays some role in regulating mood, as does the chemical serotonin. But what actually causes depression? Is there a tiny but important area of the brain that researchers should focus on?

And does there even exist a singular disorder called depression, or is the label a catch-all denoting a bunch of distinct disorders with similar symptoms but different brain mechanisms? “Fundamentally,” says Hill, “we don’t have a biological understanding of depression or any other mental illness.”

The problem, for Hill, requires an ambitious, participatory approach. If neuroscientists are to someday understand the biological mechanisms behind mental illness—that is, if they are to figure out what literally happens in the brain when a person is depressed, manic, or delusional—they will need to pool their resources. “There’s not going to be a single person who figures it all out,” he says. “There’s never going to be an Einstein who solves a set of equations and shouts, ‘I’ve got it!’ The brain is not that kind of beast.”

The KCNI lab has the feeling of a tech firm. It’s an open-concept space with temporary workstations in lieu of offices, and its glassed-in meeting rooms have inspirational names, like “Tranquility” and “Perception.” The KCNI is a “dry centre”: it works with information and software rather than with biological tissue.

To obtain data, researchers forge relationships with other scientists and try to convince them to share what they’ve got. The interior design choices are a tactical part of this effort. “The space has to look nice,” says Dan Felsky, a researcher at the centre. “Colleagues from elsewhere must want to come in and collaborate with us.”

Yet it’s hard to forget about the larger surroundings. During one interview in the “Clarity” room, Hill and I heard a code-blue alarm, broadcast across CAMH, to indicate a medical emergency elsewhere in the hospital. Hill’s job doesn’t involve front line care, so he doesn’t personally work with patients, but these disruptions reinforce his sense of urgency. “I come from a discipline where scientists focus on theoretical subjects,” he says. “It’s important to be reminded that people are suffering and we have a responsibility to help them.”

Today, the science of mental illness is based primarily on the study of symptoms. Patients receive a diagnosis when they report or exhibit maladaptive behaviours—despair, anxiety, disordered thinking—associated with a given condition. If a significant number of patients respond positively to a treatment, that treatment is deemed effective. But such data reveals nothing about what physically goes on within the brain.

“When it comes to the various diseases of the brain,” says Helena Ledmyr, co-director of the International Neuroinformatics Coordinating Facility, “we know astonishingly little.” Shreejoy Tripathy, a KCNI researcher, gives modern civilization a bit more credit: “The ancient Egyptians would remove the brain when embalming people because they thought it was useless. In theory, we’ve learned a few things since then. In relation to how much we have left to learn, though, we’re not that much further along.”

Joe Herbert, a Cambridge University neuroscientist, offers a revealing comparison between the way mental versus physical maladies are diagnosed. If, in the nineteenth century, you walked into a doctor’s office complaining of shortness of breath, the doctor would likely diagnose you with dyspnea, a word that basically means . . . shortness of breath.

Today, of course, the doctor wouldn’t stop there: they would take a blood sample to see if you were anemic, do an X-ray to search for a collapsed lung, or subject you to an echocardiogram to spot signs of heart disease. Instead of applying a Greek label to your symptoms, they’d run tests to figure out what was causing them.

Herbert argues that the way we currently diagnose depression is similar to how we once diagnosed shortness of breath. The term depression is likely as useful now as dyspnea was 150 years ago: it probably denotes a range of wildly different maladies that just happen to have similar effects. “Psychiatrists recognize two types of depression—or three, if you count bipolar—but that’s simply on the basis of symptoms,” says Herbert. “Our history of medicine tells us that defining a disease by its symptoms is highly simplistic and inaccurate.”

The advantage of working with models, as the KCNI researchers do, is that scientists can experiment in ways not possible with human subjects. They can shut off parts of the model brain or alter the electrical circuitry. The disadvantage is that models are not brains. A model is, ultimately, a kind of hypothesis—an illustration, analogy, or computer simulation that attempts to explain or replicate how a certain brain process works.

Over the centuries, researchers have created brain models based on pianos, telephones, and computers. Each has some validity—the brain has multiple components working in concert, like the keys of a piano; it has different nodes that communicate with one another, like a telephone network; and it encodes and stores information, like a computer—but none perfectly describes how a real brain works. Models may be useful abstractions, but they are abstractions nevertheless.

Yet, because the brain is vast and mysterious and hidden beneath the skull, we have no choice but to model it if we are to study it. Debates over how best to model it, and whether such modelling should be done at the micro or macro scale, are hotly contested in neuroscience. But Hill has spent most of his life preparing to answer these questions.

Hill grew up in the ’70s and ’80s, in an environment entirely unlike the one in which he works. His parents were adherents of the back-to-the-land movement, and his father was an occasional artisanal toymaker. On their farm, near the coast of Maine, the family grew vegetables and raised livestock using techniques not too different from those of nineteenth-century homesteaders. They pulled their plough with oxen and, to fuel their wood-burning stove, felled trees with a manual saw.

When Hill and his older brother found out that the local public school had acquired a TRS-80, an early desktop computer, they became obsessed. The math teacher, sensing their passion, decided to loan the machine to the family for Christmas. Over the holidays, the boys became amateur programmers. Their favourite application was Dancing Demon, in which a devilish figure taps its feet to an old swing tune. Pretty soon, the boys had hacked the program and turned the demon into a monster resembling Boris Karloff in Frankenstein. “In the dark winter of Maine,” says Hill, “what else were we going to do?”

The experiments spurred conversation among the brothers, much of it the fevered speculation of young people who’ve read too much science fiction. They fantasized about the spaceships they would someday design. They also discussed the possibility of building a computerized brain. “I was probably ten or eleven years old,” Hill recalls, “saying to my brother, ‘Will we be able to simulate a neuron? Maybe that’s what we need to get artificial intelligence.’”

Roughly a decade later, as an undergraduate at the quirky liberal arts university Hampshire College, Hill was drawn to computational neuroscience, a field whose practitioners were doing what he and his brother had talked about: building mathematical, and sometimes even computerized, brain models.

In 2006, after completing his PhD, along with postgraduate studies in San Diego and Wisconsin, Hill returned to Lausanne to co-direct the Blue Brain Project, a radical brain-modelling lab in the Swiss Alps. The initiative had been founded a year earlier by Henry Markram, a South African Israeli neuroscientist whose outsize ambitions had made him a revered and controversial figure.

In neuroscience today, there are robust debates as to how complex a brain model should be. Some researchers seek to design clean, elegant models. That’s a fitting description of the Nobel Prize–winning work of Alan Hodgkin and Andrew Huxley, who, in 1952, drew handwritten equations and rudimentary illustrations—with lines, symbols, and arrows—describing how electrical signals exit a neuron and travel along a branch-like cable called an axon.

Other practitioners seek to make computer-generated maps that incorporate hundreds of neurons and tens of thousands of connections, image fields so complicated that Michelangelo’s Sistine Chapel ceiling looks minimalist by comparison. The clean, simple models demystify brain processes, making them understandable to humans. The complex models are impossible to comprehend: they offer too much information to take in, attempting to approximate the complexity of an actual brain.

Markram’s inclinations are maximalist. In a 2009 TED Talk, he said that he aimed to build a computer model so comprehensive and biologically accurate that it would account for the location and activity of every human neuron. He likened this endeavour to mapping out a rainforest tree by tree. Skeptics wondered whether such a project was feasible. The problem isn’t merely that there are numerous trees in a rainforest: it’s also that each tree has its own configuration of boughs and limbs. The same is true of neurons.

Each is a microscopic, blob-like structure with dense networks of protruding branches called axons and dendrites. Neurons use these branches to communicate. Electrical signals run along the axons of one neuron and then jump, over a space called a synapse, to the dendrites of another. The 86 billion neurons in the human brain each have an average of 10,000 synaptic connections. Surely, skeptics argued, it was impossible, using available technology, to make a realistic model from such a complicated, dynamic system.

In 2006, Markram and Hill got to work. The initial goal was to build a hyper-detailed, biologically faithful model of a “microcircuit” (i.e., a cluster of 31,000 neurons) found within the brain of a rat. With a glass probe called a patch clamp, technicians at the lab penetrated a slice of rat brain, connected to each individual neuron, and recorded the electrical signals it sent out.

By injecting dye into the neurons, the team could visualize their shape and structure. Step by step, neuron by neuron, they mapped out the entire communication network. They then fed the data into a model so complex that it required Blue Gene, the IBM supercomputer, to run.

In 2015, they completed their rat microcircuit. If they gave their computerized model certain inputs (say, a virtual spark in one part of the circuit), it would predict an output (for instance, an electrical spark elsewhere) that corresponded to biological reality. The model wasn’t doing any actual cognitive processing: it wasn’t a virtual brain, and it certainly wasn’t thinking.

But, the researchers argued, it was predicting how electrical signals would move through a real circuit inside a real rat brain. “The digital brain tissue naturally behaves like the real brain tissue,” reads a statement on the Blue Brain Project’s website. “This means one can now study this digital tissue almost like one would study real brain tissue.”

The breakthrough, however, drew fresh criticisms. Some neuroscientists questioned the expense of the undertaking. The team had built a multimillion-dollar computer program to simulate an already existing biological phenomenon, but so what? “The question of ‘What are you trying to explain?’ hadn’t been answered,” says Grace Lindsay, a computational neuroscientist and author of the book Models of the Mind. “A lot of money went into the Blue Brain Project, but without some guiding goal, the whole thing seemed too open ended to be worth the resources.”

Others argued that the experiment was not just profligate but needlessly convoluted. “There are ways to reduce a big system down to a smaller system,” says Adrienne Fairhall, a computational neuroscientist at the University of Washington. “When Boeing was designing airplanes, they didn’t build an entire plane just to figure out how air flows around the wings. They scaled things down because they understood that a small simulation could tell them what they needed to know.” Why seek complexity, she argues, at the expense of clarity and elegance?

The harshest critics questioned whether the model even did what it was supposed to do. When building it, the team had used detailed information about the shape and electrical signals of each neuron. But, when designing the synaptic connections—that is, the specific locations where the branches communicate with one another—they didn’t exactly mimic biological reality, since the technology for such detailed brain mapping didn’t yet exist. (It does now, but it’s a very recent development.)

Instead, the team built an algorithm to predict, based on the structure of the neurons and the configuration of the branches, where the synaptic connections were likely to be. If you know the location and shape of the trees, they reasoned, you don’t need to perfectly replicate how the branches intersect.

But Moritz Helmstaedter—a director at the Max Planck Institute for Brain Research, in Frankfurt, Germany, and an outspoken critic of the project—questions whether this supposition is true. “The Blue Brain model includes all kinds of assumptions about synaptic connectivity, but what if those assumptions are wrong?” he asks. The problem, for Helmstaedter, isn’t just that the model could be inaccurate: it’s that there’s no way to fully assess its accuracy given how little we know about brain biology.

If a living rat encounters a cat, its brain will generate a flight signal. But, if you present a virtual input representing a cat’s fur to the Blue Brain model, will the model generate a virtual flight signal too? We can’t tell, Helmstaedter argues, in part because we don’t know, in sufficient detail, what a flight signal looks like inside a real rat brain.

Hill takes these comments in stride. To criticisms that the project was too open-ended, he responds that the goal wasn’t to demystify a specific brain process but to develop a new kind of brain modelling based in granular biological detail.

The objective, in other words, was to demonstrate—to the world and to funders—that such an undertaking was possible. To criticisms that the model may not work, Hill contends that it has successfully reproduced thousands of experiments on actual rats. Those experiments hardly prove that the simulation is 100 percent accurate—no brain model is—but surely they give it credibility.

And, to criticisms that the model is needlessly complicated, he counters that the brain is complicated too. “We’d been hearing for decades that the brain is too complex to be modelled comprehensively,” says Hill. “Markram put a flag in the ground and said, ‘This is achievable in a finite amount of time.

The specific length of time is a matter of some speculation. In his TED Talk, Markram implied that he might build a detailed human brain model by 2019, and he began raising money toward a new initiative, the Human Brain Project, meant to realize this goal. But funding dried up, and Markram’s predictions came nowhere close to
panning out.

The Blue Brain Project, however, remains ongoing. (The focus, now, is on modelling a full mouse brain.) For Hill, it offers proof of concept for the broader mission of neuroinformatics. It has demonstrated, he argues, that when you systemize huge amounts of data, you can build platforms that generate reliable insights about the brain. “We showed that you can do incredibly complex data integration,” says Hill, “and the model will give rise to biologically realistic responses.”

When Hill was approached by recruiters on behalf of CAMH to ask if he might consider leaving the Blue Brain Project to start a neuroinformatics lab in Toronto, he demurred. “I’d just become a Swiss citizen,” he says, “and I didn’t want to go.” But the hospital gave him a rare opportunity: to practice cutting-edge neuroscience in a clinical setting. CAMH was formed, in 1998, through a merger of four health care and research institutions.

It treats over 34,000 psychiatric patients each year and employs more than 140 scientists, many of whom study the brain. Its mission, therefore, is both psychiatric and neuroscientific—a combination that appealed to Hill. “I’ve spoken to psychiatrists who’ve told me, ‘Neuroscience doesn’t matter,’” he says. “In their work, they don’t think about brain biology. They think about treating the patient in front of them.” Such biases, he argues, reveal a profound gap between brain research and the illnesses that clinicians see daily. At the KCNI, he’d have a chance to bridge that gap.

The business of data-gathering and brain-modelling may seem dauntingly abstract, but the goal, ultimately, is to figure out what makes us human. The brain, after all, is the place where our emotional, sensory, and imaginative selves reside. To better understand how the modelling process works, I decided to shadow a researcher and trace an individual data point from its origins in a brain to its incorporation in a KCNI model.

Last February, I met Homeira Moradi, a neuroscientist at Toronto Western Hospital’s Krembil Research Institute who shares data with the KCNI. Because of where she works, she has access to the rarest and most valuable resource in her field: human brain tissue. I joined her at 9 a.m., in her lab on the seventh floor. Below us, on the ground level, Taufik Valiante, a neurosurgeon, was operating on an epileptic patient. To treat epilepsy and brain cancer, surgeons sometimes cut out small portions of the brain. But, to access the damaged regions, they must also remove healthy tissue in the neocortex, the high-functioning outer layer of the brain.

Moradi gets her tissue samples from Valiante’s operating room, and when I met her, she was hard at work weighing and mixing chemicals. The solution in which her tissue would sit would have to mimic, as closely as possible, the temperature and composition of an actual brain. “We have to trick the neurons into thinking they’re still at home,” she said.

She moved at the frenetic pace of a line cook during a dinner rush. At some point that morning, Valiante’s assistant would text her from the OR to indicate that the tissue was about to be extracted. When the message came through, she had to be ready. Once the brain sample had been removed from the patient’s head, the neurons within it would begin to die. At best, Moradi would have twelve hours to study the sample before it expired.

The text arrived at noon, by which point we’d been sitting idly for an hour. Suddenly, we sprang into action. To comply with hospital policy, which forbids Moradi from using public hallways where a visitor may spot her carrying a beaker of brains, we approached the OR indirectly, via a warren of underground tunnels.

The passages were lined with gurneys and illuminated, like catacombs in an Edgar Allan Poe story, by dim, inconsistent lighting. I hadn’t received permission to witness the operation, so I waited for Moradi outside the OR and was able to see our chunk of brain only once we’d returned to the lab. It didn’t look like much—a marble-size blob, gelatinous and slightly bloody, like gristle on a steak.

Under a microscope, though, the tissue was like nothing I’d ever seen. Moradi chopped the sample into thin pieces, like almond slices, which went into a small chemical bath called a recording chamber. She then brought the chamber into another room, where she kept her “rig”: an infrared microscope attached to a manual arm.

She put the bath beneath the lens and used the controls on either side of the rig to operate the arm, which held her patch clamp—a glass pipette with a microscopic tip. On a TV monitor above us, we watched the pipette as it moved through layers of brain tissue resembling an ancient root system—tangled, fibrous, and impossibly dense.

Moradi needed to bring the clamp right up against the wall of a cell. The glass had to fuse with the neuron without puncturing the membrane. Positioning the clamp was maddeningly difficult, like threading the world’s smallest needle. It took her the better part of an hour to connect to a pyramidal neuron, one of the largest and most common cell types in our brain sample.

Once we’d made the connection, a filament inside the probe transmitted the electrical signals the neuron sent out. They went first into an amplifier and then into a software application that graphed the currents—strong pulses with intermittent weaker spikes between them—on an adjacent computer screen. “Is that coming from the neuron?” I asked, staring at the screen. “Yes,” Moradi replied. “It’s talking to us.”

A depressive brain is a noisy one. What if scientists could locate the neurons causing the problem?

It had taken us most of the day, but we’d successfully produced a tiny data set—information that may be relevant to the study of mental illness. When neurons receive electrical signals, they often amplify or dampen them before passing them along to adjacent neurons. This function, called gating, enables the brain to select which stimuli to pay attention to. If successive neurons dampen a signal, the signal fades away.

If they amplify it, the brain attends more closely. A popular theory of depression holds that the illness has something to do with gating. In depressive patients, neurons may be failing to dampen specific signals, thereby inducing the brain to ruminate unnecessarily on negative thoughts. A depressive brain, according to this theory, is a noisy one. It is failing to properly distinguish between salient and irrelevant stimuli. But what if scientists could locate and analyze a specific cluster of neurons (i.e., a circuit) that was causing the problem?

Etay Hay, an Israeli neuroscientist and one of Hill’s early hires at the KCNI, is attempting to do just that. Using Moradi’s data, he’s building a model of a “canonical” circuit—that is, a circuit that appears thousands of times, with some variations, in the outer layer of the brain. He believes a malfunction in this circuit may underlie some types of treatment-resistant depression.

The circuit contains pyramidal neurons, like the one Moradi recorded from, that communicate with smaller cells, called interneurons. The interneurons dampen the signals the pyramidal neurons send them. It’s as if the interneurons are turning down the volume on unwanted thoughts. In a depressive brain, however, the interneurons may be failing to properly reduce the signals, causing the patient to get stuck in negative-thought loops.

Etienne Sibille, another CAMH neuroscientist, has designed a drug that increases communication between the interneurons and the pyramidal neurons in Hay’s circuit. In theory, this drug should enable the interneurons to better do their job, tamp down on negative thoughts, and improve cognitive function.

This direct intervention, which occurs at the cellular level, could be more effective than the current class of antidepressants, called SSRIs, which are much cruder. “They take a shotgun approach to depression,” says Sibille, “by flooding the entire brain with serotonin.” (That chemical, for reasons we don’t fully understand, can reduce depressive symptoms, albeit only in some people.)

Sibille’s drug, however, is more targeted. When he gives it to mice who seem listless or fearful, they perk up considerably. Before testing it on humans, Sibille hopes to further verify its efficacy. That’s where Hay comes in. He has finished his virtual circuit and is now preparing to simulate Sibille’s treatment. If the simulation reduces the overall amount of noise in the circuit, the drug can likely proceed to human trials, a potentially game-changing breakthrough.

Hill’s other hires at the KCNI have different specialties from Hay’s but similar goals. Shreejoy Tripathy is building computer models to predict how genes affect the shape and behaviour of neurons. Andreea Diaconescu is using video games to collect data that will allow her to better model early stage psychosis.

This can be used to predict symptom severity and provide more effective treatment plans. Joanna Yu is building the BrainHealth Databank, a digital repository for anonymized data—on symptoms, metabolism, medications, and side effects—from over 1,000 CAMH patients with depression. Yu’s team will employ AI to analyze the information and predict which treatment may offer the best outcome for each individual.

Similarly, Dan Felsky is helping to run a five-year study on over 300 youth patients at CAMH, incorporating data from brain scans, cognitive tests, and doctors’ assessments. “The purpose,” he says, “is to identify signs that a young person may go on to develop early adult psychosis, one of the most severe manifestations of mental illness.”

All of these researchers are trained scientists, but their work can feel more like engineering: they’re each helping to build the digital infrastructure necessary to interpret the data they bring in.

Sibille’s work, for instance, wouldn’t have been possible without Hay’s computer model, which in turn depends on Moradi’s brain-tissue lab, in Toronto, and on data from hundreds of neuron recordings conducted in Seattle and Amsterdam. This collaborative approach, which is based in data-sharing agreements and trust-based relationships, is incredibly efficient. With a team of three trainees, Hay built his model in a mere twelve months. “If just one lab was generating my data,” he says, “I’d have kept it busy for twenty years.” Read more……

Simon Lewsen, a Toronto-based writer, contributes to Azure, Precedent, enRoute, the Globe and Mail, and The Atlantic. In 2020, he won a National Magazine Award.

Source: What Happens to Our Brains When We Get Depressed? | The Walrus

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A Link Between The Gut and Diet May Mean a Cure For an Incurable Disease

Your gut is a thriving universe unto itself. This tiny cosmos is inhabited by thousands on thousands of microorganisms, which together make up your gut microbiome. Among other things, this internal ecosystem contains bacteria that we rely on to help us break down and process the foods that we’re not readily equipped to digest. But a slew of recent scientific studies shows that our gut also connects more broadly to our holistic health, even to things that are seemingly unrelated, like our brains.

The science is preliminary, but there is compelling evidence that what you eat — and in turn, that changes the gut microbiome — has an outsized influence on your health. But not in the way you’d think. What’s new — A new study published on Friday in the journal Science Advances looks at how diet could alter multiple sclerosis (MS) symptoms via the gut microbiome. By feeding mice with an MS-like condition a specific diet, scientists were able to reprogram their gut bacteria — and reduce their symptoms.

The study started with the observation that the gut microbiomes of people with MS lack a kind of bacteria that, in most folks’ gut, breakdowns a nutrient called isoflavones. This nutrient is commonly found in everyday staple foods, like soy and beans. So, the team hypothesized that MS might be related to the absence of these bacteria — and in turn, eating more foods with isoflavones in them could alleviate the symptoms.

From there, they were able to demonstrate the critical difference that the bacteria’s presence or absence can make in this disease. Why it matters — This study is so intriguing because it identifies a clear relationship between the gut, the food we eat, and our brain and body health.

In the new study, the researchers go further than past work by not only establishing a clear link between gut bacteria and diet, but also the mechanisms driving the relationship — and how to potentially game it to our advantage. “The hypothesis has always been that bacterial composition is tightly linked to diet,” says Sergio Baranzini, a neurology professor at the University of California, San Francisco who was not involved in the research.

While other studies have investigated this relationship, “what those studies fell short of is showing what could be the potential mechanism.” MS is rare, but it also occupies a place in the public consciousness, in part because of its insidious effects on the body. TV personality Jack Osbourne and actress Selma Blair have both been diagnosed with the disease.

MS essentially wreaks its havoc by putting the central nervous system out of business. Over time, people with MS will slowly lose their sensory, motor, and cognitive abilities. There is no cure — but this study hints at the promise of dietary interventions to quell some of its effects. Baranzini was impressed with the revelation. “I was surprised to see that everything was working,” he says. “It felt like, ‘Can this be too good to be true?’ ”

Digging into the details — First, it’s key to learn about isoflavones, a nutrient present in many common foods, and what it does in the body.

Foods rich in isoflavones include:

  • Soybeans
  • Lentils
  • Pistachios
  • Chickpeas
  • Peanuts
  • Other beans and legumes.

Our guts can’t naturally break down isoflavones, so we host a strain of bacteria that do the hard work of metabolizing them. While beans and legumes offer myriad benefits, it’s not the isoflavone itself that is the secret ingredient to health. Rather, it’s the type of bacteria in our gut microbiome that metabolize the isoflavone. If you introduce isoflavone by eating lots of beans and peanuts, then the bacteria will flourish.

How they did it — In this study, the researchers fed a group of mice infected with an experimental version of MS an isoflavone-rich diet and also fed another group of infected mice an isoflavone-free diet. The mice that ate the isoflavone-free diet deteriorated far more rapidly over the course of three weeks, while the mice that ate the isoflavones deteriorated at a much slower rate.

The reason for this effect has to do with how the different elements of the microbiome work together to safeguard our body’s health, according to Ashutosh Mangalam, the study’s corresponding author and a pathology professor at the University of Iowa’s Carver College of Medicine. He likens the gut microbiome to a town. The town doctor is one of the most crucial elements, and if you remove the doctor, then the town as a whole suffers. But, if the doctor comes back, then the town can recover.

But if you are worried about MS, there is no reason to start eating a bean-rich diet just yet (although beans are great). “In science we have learned that everything is a Goldilocks system,” says Mangalam. Everything is good in moderation.

What’s next — This study is a first step on the road to treatments that are cheap, effective, and simple. There’s currently no cure for MS, but more broadly, the effect seen here of a bean-rich diet hints at the influence of both isoflavones and the gut on other conditions to do with aging and neurodegeneration, like ALS, or Lou Gherig’s Disease, something Mangalam is confident will bear out.

Testing this idea in humans is on the horizon, though any human participants will follow a slightly different diet regimen — more beans. Baranzini also cautions that making the jump from mice to humans carries new challenges. While it may be possible to treat experimentally induced MS with a nutrient found in beans, MS in humans is another beast entirely.

Mangalam plans to seek out how the microbiome influences MS in other ways, too. “I am well aware that MS is not a singular disease,” he says. “We might have to divide MS patients into certain categories based on microbiome function.” “That’s what my dream research is for the next five to 10 years, to try to identify what [other bacteria are] lacking.”

Abstract: The gut microbiota is a potential environmental factor that influences the development of multiple sclerosis (MS). We and others have demonstrated that patients with MS and healthy individuals have distinct gut microbiomes. However, the pathogenic relevance of these differences remains unclear. Previously, we showed that bacteria that metabolize isoflavones are less abundant in patients with MS, suggesting that isoflavone-metabolizing bacteria might provide protection against MS. Here, using a mouse model of MS, we report that an isoflavone diet provides protection against disease, which is dependent on the presence of isoflavone-metabolizing bacteria and their metabolite equol. Notably, the composition of the gut microbiome in mice fed an isoflavone diet exhibited parallels to healthy human donors, whereas the composition in those fed an isoflavone-free diet exhibited parallels to patients with MS. Collectively, our study provides evidence that dietary-induced gut microbial changes alleviate disease severity and may contribute to MS pathogenesis.

Source: A link between the gut and diet may mean a cure for an incurable disease

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Critics:

While it’s important to understand that there’s a place for all foods to fit into a healthy lifestyle, some should be minimized where possible to help optimize gut health,” explains Turnbull. When it comes to eating for a healthy gut, these foods aren’t on the roster:

Refined grains. Refined carbs (i.e. white pasta, white bread) basically feed the “bad” bacteria in your digestive system, according to an article in the journal Nutrients,. This can “decrease the ratio of good bacteria found in the gut, which may lead to inflammation,” says Turnbull. Moreover, processed carbs are “harder for your gut to break down and are more likely to cause unpleasant gastrointestinal symptoms,” says Bryan Curtin, M.D., MHSc, board-certified gastroenterologist at the Institute for Digestive Health and Liver Disease at Mercy Medical Center. (See also: Is Fasting Good for Your Gut Bacteria?)

Processed foods. While you’re at it, cut back on processed foods (think: fast food, packaged snacks) in general. These items lack the nutrients found in produce that normally feed good bacteria, says Turnbull, and, ya know, benefit tons of other parts of your body. In fact, research suggests that processed foods create the ideal environment for inflammation-causing microbes, aka inflammation that can pave the way for IBD and IBS. Also, many processed, frozen, and canned foods are sneaky sources of gluten, so you’ll want to steer clear if you have celiac disease.

High-fat foods. Though fat is an essential macronutrient, eating too many high-fat foods (i.e. fried foods) can cause your gut to work extra hard, which can hinder microbial diversity, she explains. And research agrees: foods high in fat — mainly saturated and trans-fat — can reduce Lactobacillus and Akkermansia muciniphila, two microbes linked to good health. In turn, high-fat foods may exacerbate symptoms such as bloating, nausea, gas, and diarrhea, so it’s worth limiting them if you have a digestive disorder, says Turnbull. (Related: 7 Ways to Bolster Good Gut Bacteria, Besides Eating Yogurt)

Dairy products. When it comes to dairy, moderation may be the way to go. In fact, a diet low in dairy (i.e. the Mediterranean diet) can increase friendly bacteria — Lactobacillus and Bifidobacterium — and decrease the bad guys — Clostridium — according to a 2017 review. You may also want to avoid high-lactose dairy if you have a digestive disorder or lactose intolerance, a condition that affects 68 percent of people worldwide, according to the National Institute of Diabetes and Digestive and Kidney Diseases. This includes “cow’s milk, buttermilk, low-fat yogurt, evaporated and condensed milk,” says Turnbull.

Red meat. To protect your gut, limit red meat like pork, beef, and lamb, especially if it’s processed. (Sorry, bacon.) Not only is it high in saturated fats, but red meat also reduces levels of good bacteria, according to the aforementioned 2017 review. Another 2020 review in Advances in Nutrition shares that red meat *also* increases numbers of the bad guys, like Proteobacteria. Talk about double trouble.

“While it’s important to understand that there’s a place for all foods to fit into a healthy lifestyle, some should be minimized where possible to help optimize gut health,” explains Turnbull. When it comes to eating for a healthy gut, these foods aren’t on the roster:

Refined grains. Refined carbs (i.e. white pasta, white bread) basically feed the “bad” bacteria in your digestive system, according to an article in the journal Nutrients,. This can “decrease the ratio of good bacteria found in the gut, which may lead to inflammation,” says Turnbull. Moreover, processed carbs are “harder for your gut to break down and are more likely to cause unpleasant gastrointestinal symptoms,” says Bryan Curtin, M.D., MHSc, board-certified gastroenterologist at the Institute for Digestive Health and Liver Disease at Mercy Medical Center. (See also: Is Fasting Good for Your Gut Bacteria?)

Processed foods. While you’re at it, cut back on processed foods (think: fast food, packaged snacks) in general. These items lack the nutrients found in produce that normally feed good bacteria, says Turnbull, and, ya know, benefit tons of other parts of your body. In fact, research suggests that processed foods create the ideal environment for inflammation-causing microbes, aka inflammation that can pave the way for IBD and IBS. Also, many processed, frozen, and canned foods are sneaky sources of gluten, so you’ll want to steer clear if you have celiac disease.

High-fat foods. Though fat is an essential macronutrient, eating too many high-fat foods (i.e. fried foods) can cause your gut to work extra hard, which can hinder microbial diversity, she explains. And research agrees: foods high in fat — mainly saturated and trans-fat — can reduce Lactobacillus and Akkermansia muciniphila, two microbes linked to good health. In turn, high-fat foods may exacerbate symptoms such as bloating, nausea, gas, and diarrhea, so it’s worth limiting them if you have a digestive disorder, says Turnbull. (Related: 7 Ways to Bolster Good Gut Bacteria, Besides Eating Yogurt)

Dairy products. When it comes to dairy, moderation may be the way to go. In fact, a diet low in dairy (i.e. the Mediterranean diet) can increase friendly bacteria — Lactobacillus and Bifidobacterium — and decrease the bad guys — Clostridium — according to a 2017 review. You may also want to avoid high-lactose dairy if you have a digestive disorder or lactose intolerance, a condition that affects 68 percent of people worldwide, according to the National Institute of Diabetes and Digestive and Kidney Diseases. This includes “cow’s milk, buttermilk, low-fat yogurt, evaporated and condensed milk,” says Turnbull.

Red meat. To protect your gut, limit red meat like pork, beef, and lamb, especially if it’s processed. (Sorry, bacon.) Not only is it high in saturated fats, but red meat also reduces levels of good bacteria, according to the aforementioned 2017 review. Another 2020 review in Advances in Nutrition shares that red meat *also* increases numbers of the bad guys, like Proteobacteria. Talk about double trouble.

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