Women wearing heavy makeup less likely to be perceived as leaders: study

A team of scientists has produced first open source all-atom models of full-length COVID-19 Spike protein that facilitates viral entry into host cells – a discovery that can facilitate a faster vaccine and antiviral drug development.

The group from Seoul National University in South Korea, University of Cambridge in the UK and Lehigh University in the US produced the first open-source all-atom models of a full-length S protein.

The researchers say this is of particular importance because the S protein plays a central role in viral entry into cells, making it a main target for vaccine and antiviral drug development.

"Our models are the first full-length SARS-CoV-2 spike (S) protein models that are available to other scientists," said Wonpil Im, a professor in Lehigh University.

"Our team spent days and nights to build these models very carefully from the known cryo-EM structure portions. Modeling was very challenging because there were many regions where simple modeling failed to provide high-quality models," he wrote in a paper published in The Journal of Physical Chemistry B.

Scientists can use the models to conduct innovative and novel simulation research for the prevention and treatment of Covid-19.

Though the coronavirus uses many different proteins to replicate and invade cells, the Spike protein is the major surface protein that it uses to bind to a receptor.

The total number of global COVID-19 cases was nearing 9 million, while the deaths have increased to over 467,000, according to the Johns Hopkins University.

With 2,279,306 cases and 119,967 deaths, the US continues with the world's highest number of COVID-19 infections and fatalities, according to the CSSE.

Brazil comes in the second place with 1,083,341 infections and 50,591 deaths.

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.

Washington D.C, Feb 10: Children's vulnerability towards depression, anxiety, impulsive behaviour, and poor cognitive performance could be determined by considering the hours of sleep they manage to get.

Sleep states are active processes that support the reorganisation of brain circuitry. This makes sleep especially important for children, whose brains are developing and reorganising rapidly.

In a study by researchers from the University of Warwick -- recently published in the journal Molecular Psychiatry -- cases of 11,000 children aged between 9 and 11 years from the Adolescent Brain Cognitive Development dataset were analyzed to find out the relationship between sleep duration and brain structure.

The study was carried out by researchers Professor Jianfeng Feng, Professor Edmund Rolls, Dr. Wei Cheng and colleagues from the University of Warwick's Department of Computer Science and Fudan University.

Measures of depression, anxiety, impulsive behaviour and poor cognitive performance in the children were associated with shorter sleep duration. Moreover, the depressive problems were associated with short sleep duration one year later.

The reduced brain volume of areas such as orbitofrontal cortex, prefrontal, and temporal cortex, precuneus, and supramarginal gyrus was found to be associated with the shorter sleep duration.

Professor Jianfeng Feng, from the University of Warwick's Department of Computer Science, comments: "The recommended amount of sleep for children 6 to 12 years of age is 9-12 hours. However, sleep disturbances are common among children and adolescents around the world due to the increasing demand on their time from school, increased screen time use, and sports and social activities."

A previous study showed that about 60 per cent of adolescents in the United States receive less than eight hours of sleep on school nights.

Professor Jianfeng Feng further added: "Our findings showed that the total score for behavior problems in children with less than 7 hours sleep was 53 per cent higher on average and the cognitive total score was 7.8 per cent lower on average than for children with 9-11 hours of sleep. It highlights the importance of enough sleep in both cognition and mental health in children."

Professor Edmund Rolls from the University of Warwick's Department of Computer Science also commented: "These are important associations that have been identified between sleep duration in children, brain structure, and cognitive and mental health measures, but further research is needed to discover the underlying reasons for these relationships."