Posted on Multiple Sclerosis

Machine learning model predicts the health conditions of people with Multiple Sclerosis during stay-at-home periods.

Smartphone and watch


New CMU-led research has developed a model that can predict how stay-at-home orders affect the mental health of people with chronic neurological disorders. CREDIT Irina Shatilova

Research led by Carnegie Mellon University has developed a model that can accurately predict how stay-at-home orders like those put in place during the COVID-19 pandemic affect the mental health of people with chronic neurological disorders such as multiple sclerosis.

Researchers from CMU, the University of Pittsburgh and the University of Washington gathered data from the smartphones and fitness trackers of people with MS both before and during the early wave of the pandemic. Specifically, they used the passively collected sensor data to build machine learning models to predict depression, fatigue, poor sleep quality and worsening MS symptoms during the unprecedented stay-at-home period.

Before the pandemic began, the original research question was whether digital data from the smartphones and fitness trackers of people with MS could predict clinical outcomes. By March 2020, as study participants were required to stay at home, their daily behavior patterns were significantly altered. The research team realized the data being collected could inform the effect of the stay-at-home orders on people with MS.

“It presented us with an exciting opportunity,” said Mayank Goel, head of the Smart Sensing for Humans (SMASH) Lab at CMU. “If we look at the data points before and during the stay-at-home period, can we identify factors that signal changes in the health of people with MS?”

The team gathered data passively over three to six months, collecting information such as the number of calls on the participants’ smartphones and the duration of those calls; the number of missed calls; and the participants’ location and screen activity data. The team also collected heart rate, sleep information and step count data from their fitness trackers. The research, “Predicting Multiple Sclerosis Outcomes During the COVID-19 Stay-at-Home Period: Observational Study Using Passively Sensed Behaviors and Digital Phenotyping,” was recently published in the Journal of Medical Internet Research Mental Health. Goel, an associate professor in the School of Computer Science’s Software and Societal Systems Department (S3D) and Human-Computer Interaction Institute (HCII), collaborated with Prerna Chikersal, a Ph.D. student in the HCII; Dr. Zongqi Xia, an associate professor of Neurology and director of the Translational and Computational Neuroimmunology Research Program at the University of Pittsburgh; and Anind Dey, a professor and dean of the University of Washington’s Information School.

The work was based on previous studies from Goel’s and Dey’s research groups. In 2020, a CMU team published research that presented a machine learning model that could identify depression in college students at the end of the semester using smartphone and fitness tracker data. Participants in the earlier study, specifically 138 first-year CMU students, were relatively similar to each other when compared to the larger population beyond the university. The researchers set out to test whether their modeling approach could accurately predict clinically relevant health outcomes in a real-world patient population with greater demographic and clinical diversity, leading them to collaborate with Xia’s MS research program.

People with MS can experience several chronic comorbidities, which gave the team a chance to test if their model could predict adverse health outcomes such as severe fatigue, poor sleep quality and worsening of MS symptoms in addition to depression. Building on this study, the team hopes to advance precision medicine for people with MS by improving early detection of disease progression and implementing targeted interventions based on digital phenotyping.

The work could also help inform policymakers tasked with issuing future stay-at-home orders or other similar responses during pandemics or natural disasters. When the original COVID-19 stay-at-home orders were issued, there were early concerns about its economic impacts but only a belated appreciation for the toll on peoples’ mental and physical health — particularly among vulnerable populations such as those with chronic neurological conditions.

“We were able to capture the change in people’s behaviors and accurately predict clinical outcomes when they are forced to stay at home for prolonged periods,” Goel said. “Now that we have a working model, we could evaluate who is at risk for worsening mental health or physical health, inform clinical triage decisions, or shape future public health policies.”

Posted on Lupus

Gene associated with Lupus may protect against severe COVID-19 infection

Gene associated with Lupus may protect against severe COVID-19 infection


The balance between the risk of autoimmune disease and the risk of infection credit Dr David Lester Morris, Robert Lester Morris, Dr Deborah Cunninghame Graham, and Professor Timothy Vyse (CC-BY 4.0, https://creativecommons.org/licenses/by/4.0/)

Some genetic variants may put people at risk of autoimmune diseases while conferring protection against the outcome of viral infection. A study published November 3rd in the open access journal PLOS Genetics by David Morris and Timothy Vyse at King’s College London, UK and colleagues suggest that genetic predisposition for systemic lupus erythematosus (SLE) may be protective against severe COVID-19 infection.

Scientists have observed a correlation between the genes associated with severe COVID-19 and those with SLE. To locate associated genes and gain insight into the shared genetic effects, researchers compared the genetics of severe COVID-19 with those of SLE using multiple analyses, including an approach that can focus on specific areas of the genome. The authors then accessed data on genes and the genome structure obtained from several biomedical databases to understand the biology of shared genetics.

The researchers found that TYK2, a gene associated with both SLE and severe COVID-19 provides protection against viral infection, but increases risk for autoimmune disease. Future studies will be needed to fully understand the genetic relationships between COVID-19 and other diseases. The study has its limitations, such as the overrepresentation of European ancestry in the datasets used to perform the analyses.

According to the authors, “Our results indicate that there are shared genetic effects between the autoimmune disease SLE and the clinical consequences of COVID-19. The locus with the most evidence of shared association (TYK2) is involved in interferon production, a process that is important in response to viral infection and known to be dysregulated in SLE patients. In seeking to uncover the mechanisms underlying these relationships it was apparent that the functional effects of the risk and protective genotypes are complex.”

Dr. David Morris and Professor Timothy Vyse, who led the study, add that “this is an exciting result made possible by the large genetic studies in COVID-19 and Lupus, and opens the door to our understanding of how the biology of the immune system is calibrated to protect us against infection from viruses and other infectious agents, but at the risk of developing autoimmune disease.”

Posted on Rheumatoid arthritis

One in five patients with rheumatoid arthritis was undiagnosed during the pandemic.


The number of new diagnoses of rheumatoid arthritis fell by 20% in the first year of the COVID-19 pandemic, new research suggests.

The study, published today in The Lancet Rheumatology journal by researchers from King’s College London, shows there could be as many as a fifth of new cases that have gone undiagnosed, with cases not jumping up above pre-2020 levels. This suggests many of these patients have not been seen by their GP or been reviewed by a hospital specialist. However, for patients who were diagnosed during the pandemic, there did not appear to be more delays in starting treatment.

The study evaluated the diagnosis and treatment of different types of arthritis in England during the first two years of the pandemic.

Rheumatoid arthritis, psoriatic arthritis and ankylosing spondylitis are autoimmune diseases that primarily affect the joints and spine. People with these conditions experience chronic pain which can limit their mobility. If diagnosis and treatment is delayed, these conditions can lead to chronic disability due to joint damage, impaired function, work absence, and reduced quality of life. Early diagnosis and treatment of these types of arthritis improves outcomes for patients. Once diagnosed, patients can start highly effective treatments to control symptoms and prevent irreversible damage.

Each year, the quality of care for people with rheumatoid arthritis is benchmarked through a process of national audit. These audits were paused during the pandemic, however, making comparisons of care challenging.

Researchers from King’s College London used OpenSAFELY, a highly secure health data platform, to determine how the diagnosis and management of arthritis was affected by the pandemic. From a study population of over 17 million people in England, they were able to evaluate care for 31,000 people with new diagnoses of arthritis between April 2019 and March 2022.

The results showed that the number of newly recorded arthritis diagnoses fell by 20% in the year after the first COVID-19 lockdown, relative to the year before the pandemic. Arthritis diagnoses fell again as COVID-19 cases rose, before returning to pre-pandemic levels by April 2022. Researchers did not see a rebound in diagnoses after restrictions were lifted, suggesting that there is likely to be a substantial burden of undiagnosed patients.

Importantly, the study also showed that, for people who were diagnosed during the pandemic, the time to assessment by a hospital specialist was shorter than before the pandemic. This may be due to fewer hospital referrals overall and increased utilisation of virtual appointments during the pandemic.

Additionally, the proportion of patients who were started on treatment was similar before and during the pandemic. However, medications perceived to be safer, but less effective, were prescribed more frequently during the pandemic. This could relate to clinicians’ concerns about the effects of stronger medications on COVID-19 infections.

Lead author Dr Mark Russell, from King’s College London, said: “This study highlights that there are likely to be people with joint pain and swelling who remain undiagnosed as a consequence of the pandemic. It is important to speak to a doctor if you have these symptoms, as early diagnosis and treatment of conditions such as rheumatoid arthritis greatly improves outcomes for patients and increases the likelihood of disease remission.

“An important message of this study is that it is possible to assess the quality of care for patients with long-term health conditions using routinely collected health data. This approach could be applied to many other chronic health conditions and be used to provide feedback to NHS organisations and clinicians, with the aim of optimising care for patients.”

Posted on Women's Health

Yoga and Meditation Poses for Period Cramps

Image source 


Every woman experiences cramps at some point in her life. For some, it’s mild discomfort, while for others, it can be debilitating. The pain often makes it hard for them to get through the day, let alone participate in activities they enjoy. 

In addition, many women also find that their moods are affected by cramps, making them more irritable and prone to anxiety or depression.



Cramps are caused by the uterus contracting to shed the uterine lining. This process is called menstruation or a period that is integral to women’s sexual and reproductive health. The contractions can be quite strong, and they can cause pain in the lower abdomen, back, and thighs. Aside from that, symptoms may include nausea, vomiting, diarrhea, fatigue, and cramps.

While there are several ways to ease the pain of cramps, such as taking over-the-counter medication and using a heating pad, some women are looking for more natural solutions.  If you’re one of them, yoga and meditation may be worth a try.

YOGA AND MEDITATION POSES 

Yoga is a low-impact form of exercise that relieves all sorts of pain, including menstrual cramps. It involves stretching and holding certain positions for a period of time to relax the muscles and ease the pain.

On the other hand, meditation is a form of mindfulness that allows you to focus on your breath and be in the present moment to help you take your mind off the pain you are feeling and relax.

There are several different yoga and meditation poses that can help to ease period cramps. Some of the most effective ones are listed below: 

Child’s Pose

The child’s pose is excellent for stretching out your lower back and relieving pain in your spine. It also helps to relax the muscles in your hips, thighs, and calves.

To do this pose, start on your hands and knees with your palms flat on the ground and your knees hip-width apart. As you exhale, bow forward, lowering your forehead to the ground. Then, allow your hips to sink back towards your heels and your arms to extend out in front of you. Hold this position for at least 30 seconds to a minute.

Modified Cobra Pose

For your breathing and relaxation, try this modified version of Cobra Pose. It can help to open up your chest and shoulders while strengthening your back.

To get into the pose, lie on your stomach with your legs straight out behind you and your palms flat on the ground next to your shoulders. As you inhale, lift your chest off the ground, keeping your pelvis and thighs firmly planted. Stay in this position for a few seconds before slowly lowering back to the ground.

Pelvic Tilts

Pelvic Tilts is an excellent exercise if you’re feeling bloated or constipated. It’s a gentle way to massage the internal organs and improve circulation in your lower body. Plus, it’s a great technique to burn calories during your period. 

Start by lying on your back with your knees bent and your feet flat on the ground. As you exhale, press down into your feet and tilt your pelvis toward the sky. Take a few seconds to keep this position before going back to the starting position. Repeat ten times.

Supported Bridge Pose

Another great pose for getting rid of period cramps is the Supported Bridge Pose. This pose eases the pain by opening up the chest and shoulders to relieve the tension built up in these areas during your period.

For this pose, you’ll need a yoga block and a blanket. Then, lay on your back with your knees bent and your feet flat on the ground. Place the yoga block under your lower back, and put the blanket over your pelvis. As you inhale, press your feet into the ground and lift your hips off of the ground. Hold this pose for 30 seconds to a minute, then release it back to the ground.

Cat-Cow Pose

If you’re feeling nauseous or have headaches in addition to your cramps, the Cat-Cow pose can help, as it stretches out your back and neck muscles.

First, put your hands and knees on the ground with your palms flat and your knees hip-width apart. Then, as you inhale, arch your back and look up towards the ceiling. Then, as you exhale, round your back and tuck your chin towards your chest. Repeat this sequence ten times.

MEDITATION TIPS

Besides these yoga poses, meditation can be a helpful tool for managing period cramps. Here are a few tips to get started:

1. Focus on your breath: One of the simplest ways to meditate is to focus on your breath. First, find a comfortable position to sit or lie in and close your eyes. Then, focus on taking deep, slow breaths. For instance, inhale through your nose for a count of four, then exhale through your mouth for a count of eight. Repeat this for 5-10 minutes.

2. Count your breaths: Another way to focus on your breath is to count each inhale and exhale. Begin by inhaling for a count of four, then exhaling for a count of eight. On the next inhale, count to three, then exhale for a count of eight. Continue counting down on the inhales until you reach one. Then, start back at four and repeat the cycle.

3. Focus on a mantra: A mantra is a short, repeated phrase or word that can help to focus and calm the mind. Choose a mantra that is simple and easy to remember. Once you have chosen your mantra, repeat it aloud or silently to yourself as you breathe. For example, you could repeat the word “relax” or “let go” with each inhale and exhale.

4. Visualize a peaceful scene: Another way to calm the mind is to visualize a peaceful scene. Close your eyes and imagine yourself in a calming place like a beach or meadow. Then, focus on the details of the scene-the sounds, smells, and colors. Stay in this peaceful place for 5 minutes or longer.

Conclusion

While there’s no one-size-fits-all solution for managing period cramps, yoga and meditation can be helpful for many people. If you’re new to these practices, start with simple poses and meditations. Then, as you become more comfortable, you can try more advanced techniques. 

Lastly, remember to listen to your body and stop if you feel any pain. With regular practice, you’ll likely find relief from your cramps.

Posted on Multiple Sclerosis

New method for measuring brain activity could help multiple sclerosis patients

Spatial structure tractography and temporal structure showing connection between edges


Spatial structure tractography and temporal structure showing connection between edge credit Sorrentino et Al

Researchers of the Human Brain Project have developed a new methodology to calculate the delay of signal propagations in brains of patients suffering from multiple sclerosis, a chronic inflammatory disease that affects more than 2 million people worldwide. The results have been published in the Journal of Neuroscience by researchers at the Institut de Neurosciences des Systèmes, Marseille, France and of the University of Naples Parthenope and the University of Campania, Caserta in Italy.

In multiple sclerosis, the immune cells of the body attack the myelin, an insulating sheath that covers all the neurons. Myelin serves a similar purpose to the plastic that insulates electric cables, making electricity travel faster. Damage to the myelin layer in the brain causes the electrical signals to slow down, translating into delayed communications between brain areas and reduced or compromised abilities. Measuring the precise effect of the myelinic damage can help doctors in providing a personalized approach to patients.

This is harder than it looks for multiple sclerosis: “This illness is a diagnostic paradox,” explains Pierpaolo Sorrentino, lead author of the study. “There are patients whose MRI scans show extensive degradation of myelin but do not experience a corresponding impairment, and others that show little evident damage but still experience considerable issues. Often we are not able to tell by simply looking at the scans.” Stimulating the brain to measure real-time delay between areas is also not effective when attempting to estimate the delays of many brain connections and not just one: the signal ends up being too muddled up to be a reliable indicator of propagation. 

Instead, the researchers have developed a method to measure the delay that does not involve direct stimulation, but uses the neuronal avalanches (bursts of activity happening in cascades) that spontaneously travel across the brain. “These spontaneous bursts of activity can be used to measure the time it takes a signal to travel across the white-matter bundles connecting any two brain areas and then compare it with healthy controls without any myelinic damage,” says Sorrentino. “By not interfering directly with the signal, we can in a few minutes estimate the delay between most pairs of brain regions and then integrate it with what the MRI scans are showing us.”

In addition to informing the treatment, the method can also be used to refine virtual brain models of patients to further increase the level of personalization. Large-scale brain modelling typically assumes constant velocity of signal across the edges, but this isn’t exactly true even in a healthy brain. “We are now able to add the time delay factor to these simulations, improving the diagnostic and predictive tools available to doctors and their patients,” Sorrentino concludes.