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Toronto, Jul 10: Pasteurising breast milk at 62.5 degrees Celsius for 30 minutes inactivates the SARS-CoV-2 virus that causes Covid-19, making it safe for consumption by babies, a study claims.

According to the research published in the Canadian Medical Association Journal, current advice for women with Covid-19 is to continue to breastfeed their own infants.

In Canada, it is standard care to provide pasteurised breast milk to very-low-birth-weight babies in hospital until their own mother's milk supply is adequate, the researchers said.

"In the event that a woman who is Covid-19-positive donates human milk that contains SARS-CoV-2, whether by transmission through the mammary gland or by contamination through respiratory droplets, skin, breast pumps and milk containers, this method of pasteurisation renders milk safe for consumption," said Sharon Unger, a professor at the University of Toronto in Canada.

The Holder method, a technique used to pasteurise milk in all Canadian milk banks at 62.5 degrees Celsius for 30 minutes, is effective at neutralising viruses such as HIV, hepatitis and others that are known to be transmitted through human milk, the researchers said.

In the latest study, the researchers spiked human breast milk with a viral load of SARS-CoV-2 and tested samples that either sat at room temperature for 30 minutes or were warmed to 62.5 degrees Celsius for 30 minutes.

They then measured for active virus, finding that the virus in the pasteurised milk was inactivated after heating.

More than 650 human breast milk banks around the world use the Holder method to ensure a safe supply of milk for vulnerable infants, the researchers said.

Feb 22: The subjective feeling of well-being experienced by many people with the practice of meditation is associated with specific changes in the brain, according to a study which may lead to better clinical recommendations of the practice.

The study, published in the journal Brain and Cognition, examined the effects of the technique known as Transcendental Meditation (TM), which consists of the silent repetition of a meaningless sound.

In the study, the researchers from the IMT School for Advanced Studies Lucca in Italy, enrolled 34 healthy young volunteers and divided them in two groups.

They said the first group practised TM 40 minutes per day in two sessions of 20 minutes each, one in the morning and the other in the evening.

The second group, the scientists said, did not change its daily routine.

Using questionnaires, they also measured the anxiety and stress levels of all the participants at the beginning of the study, as well as the subjects' ability to manage stressful situations.

According to the researchers, the participants were also subjected to a functional magnetic resonance imaging (fMRI) brain scan, in order to measure the organ's activity at rest, and changes in the excitation among different cerebral areas.

They repeated the tests after three months, at the end of the study.

According to the study, the levels of anxiety and stress perceived by the subjects who followed the meditation program were significantly reduced in comparison with those of the volunteers who did not practice TM.

"Magnetic resonance imaging also shows that the reduction of anxiety levels is associated with specific changes in the connectivity between different cerebral areas, such as precuneus, left parietal lobe and insula, which all have an important role in the modulation of emotions and inner states," said study co-author Giulia Avvenuti from the IMT School for Advanced Studies Lucca.

"In the control group, instead, none of these changes was observed. The fact that Transcendental Meditation has measurable effects on the 'dialogue' between brain structures involved in the modulation of affective states opens new perspectives for the understanding of brain-mind relationships," said Pietro Pietrini, IMT School's Director, and co-author of the study.

"It also extends the results of recent research suggesting that drugs therapies and psychotherapy leverage on the same biological mechanism," Pietrini said.

According to the researchers, even a few months of practice of TM can have positive effects which can be correlated with measurable changes in the brain.

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.