Eggs may not be good after all: New study

COVID-19 mostly kills through an overreaction of the immune system, whose function is precisely to fight infections, say scientists who have decoded the mechanisms, symptoms, and diagnosis of the disease caused by the SARS-Cov-2 coronavirus.

In a study published in the journal Frontiers in Public Health, the researchers explained step-by-step how the virus infects the airways, multiplies inside cells, and in severe cases causes the immune defences to overshoot with a "cytokine storm".

This storm is an over-activation of white blood cells, which release too-great amounts of cytokines -- inflammation-stimulating molecules --into the blood, they said.

"Similar to what happens after infection with SARS and MERS, data show that patients with severe COVID-19 may have a cytokine storm syndrome," said study author Daishun Liu, Professor at Zunyi Medical University in China.

"The rapidly increased cytokines attract an excess of immune cells such as lymphocytes and neutrophils, resulting in an infiltration of these cells into lung tissue and thus cause lung injury," Liu said.

The researchers explained that the cytokine storm ultimately causes high fever, excessive leakiness of blood vessels, and blood clotting inside the body.

It also causes extremely low blood pressure, lack of oxygen and excess acidity of the blood, and build-up of fluids in the lungs, they said.

The researchers noted that white blood cells are misdirected to attack and inflame even healthy tissue, leading to failure of the lungs, heart, liver, intestines, kidneys, and genitals.

This multiple organ dysfunction syndrome (MODS) may worsen and shutdown the lungs, a condition called acute respiratory distress syndrome, (ARDS), they said.

This, the researchers explained, happens due to the formation of a so-called hyaline membrane -- composed of debris of proteins and dead cells -- lining the lungs, which makes absorption of oxygen difficult.

Most deaths due to COVID-19 are therefore due to respiratory failure, they said.

The researchers explained that in the absence of a specific antiviral cure for COVID-19, the goal of treatment must be to the fight the symptoms, and lowering the mortality rate through intensive maintenance of organ function.

For example, an artificial liver blood purification system or renal replacement therapy can be used to filter the blood through mechanical means, they said.

The team noted that especially important are methods to supplement or replace lung function, for example with non-invasive mechanical ventilation through a mask, ventilation through a tube into the windpipe, the administration of heated and humidified oxygen via a tube in the nose, or a heart-lung bypass.

The researchers stressed the importance of preventing secondary infections.

They noted that SARS-Cov-2 also invades the intestines, where it causes inflammation and leakiness of the gut lining, allowing the opportunistic entry of other disease-causing microorganisms.

The researchers advocate that this should be prevented with nutritional support, for example with probiotics -- beneficial bacteria that protect against the establishment of harmful ones -- and nutrients and amino acids to improve the immune defences and function of the intestine.

"Because treatment for now relies on aggressive treatment of symptoms, preventative protection against secondary infections, such as bacteria and fungi, is particularly important to support organ function, especially in the heart, kidneys, and liver, to try and avoid further deterioration of their condition," Liu added.

Boston, Feb 4: Practising yoga may increase levels of a messenger molecule involved in regulating brain activity, and completing one yoga class per week may maintain elevated levels of this chemical, according to a study which may lead to better ways of mitigating depressive symptoms.

The study, published in the Journal of Alternative and Complementary Medicine, assessed a group of 30 clinically depressed patients who were randomly divided into two groups.

According to the researchers, including those from Boston University in the US, both groups engaged in coherent breathing, and Iyengar yoga -- a form of hatha yoga, developed by B. K. S. Iyengar, emphasising on detail, precision, and alignment in the performance of yoga postures.

The only difference between the groups, the scientists said, was the number of 90 minute yoga sessions, and home sessions in which each group participated.

Over three months, they said, the high-dose group (HDG) was assigned three sessions per week, while the low-intensity group (LIG) engaged in two sessions per week.

The participants underwent magnetic resonance imaging (MRI) scans of their brain before the first and after the last yoga session, and also completed a clinical depression scale to monitor their symptoms, the study noted.

Results of the study revealed that both groups had improvement in depressive symptoms after three months.

Their MRI analysis showed that levels of the brain messenger molecule GABA were elevated after three months of yoga, as compared to the levels before starting yoga.

According to the study, this increase was found for approximately four days after the last yoga session, but the rise was no longer observed after about eight days.

"The study suggests that the associated increase in GABA levels after a yoga session are 'time-limited' similar to that of pharmacologic treatments such that completing one session of yoga per week may maintain elevated levels of GABA," explained study co-author Chris Streeter from Boston University.

Providing evidence-based data may help in getting more individuals to try yoga as a strategy for improving their health and well-being, the scientists said.

"A unique strength of this study is that pairing the yoga intervention with brain imaging provides important neurobiological insight as to the 'how' yoga may help to alleviate depression and anxiety," said study co-author Marisa Silveri from Harvard University.

In this study, we found that an important neurochemical, GABA, which is related to mood, anxiety, and sleep, is significantly increased in association with a yoga intervention," Silveri said.

New York, Feb 26:  A new wearable sensor that works in conjunction with artificial intelligence (AI) technology could help doctors remotely detect critical changes in heart failure patients days before a health crisis occurs, says a study.

The researchers said the system could eventually help avert up to one in three heart failure readmissions in the weeks following initial discharge from the hospital and help patients sustain a better quality of life.

"This study shows that we can accurately predict the likelihood of hospitalisation for heart failure deterioration well before doctors and patients know that something is wrong," says the study's lead author Josef Stehlik from University of Utah in the US.

"Being able to readily detect changes in the heart sufficiently early will allow physicians to initiate prompt interventions that could prevent rehospitalisation and stave off worsening heart failure," Stehlik added.

According to the researchers, even if patients survive, they have poor functional capacity, poor exercise tolerance and low quality of life after hospitalisations.

"This patch, this new diagnostic tool, could potentially help us prevent hospitalizations and decline in patient status," Stehlik said.

For the findings, published in the journal Circulation: Heart Failure, the researchers followed 100 heart failure patients, average age 68, who were diagnosed and treated at four veterans administration (VA) hospitals in Utah, Texas, California, and Florida.

After discharge, participants wore an adhesive sensor patch on their chests 24 hours a day for up to three months.

The sensor monitored continuous electrocardiogram (ECG) and motion of each subject.

This information was transmitted from the sensor via Bluetooth to a smartphone and then passed on to an analytics platform, developed by PhysIQ, on a secure server, which derived heart rate, heart rhythm, respiratory rate, walking, sleep, body posture and other normal activities.

Using artificial intelligence, the analytics established a normal baseline for each patient. When the data deviated from normal, the platform generated an indication that the patient's heart failure was getting worse.

Overall, the system accurately predicted the impending need for hospitalization more than 80 per cent of the time.

On average, this prediction occurred 10.4 days before a readmission took place (median 6.5 days), the study said.