Scientists develop robust blood test that can detect liver damage in minutes

Agencies

May 28, 2018

London, May 28: Scientists have developed a quick and robust blood test that can detect liver damage before the symptoms appear. The test developed by researchers from the University College London in the UK could address a huge need for early detection of liver disease. It distinguishes between samples taken from healthy individuals and those with varying degrees of liver damage, researchers said. The study, published in the journal Advanced Materials, describes the new method of detecting liver fibrosis, the first stage of liver scarring that leads to fatal liver disease if left unchecked, from a blood sample in 30-45 minutes.

“We hope that our new test could be used on a routine basis in GP surgeries and hospital clinics to screen people who face an elevated risk of liver disease, but don’t yet show signs of liver damage to identify those with serious fibrosis, so that they can access treatment before it’s too late,” said William Rosenberg, a professor at UCL. “This may open the door to a cost-effective regular screening programme thanks to its simplicity, low cost and robustness,” he said.

Researchers at the University of Massachusetts in the US designed a sensor that uses large molecules called polymers, coated with fluorescent dyes that bind to blood proteins based on their chemical properties. The fluorescent dyes change in brightness and colour, yielding a different pattern of fluorescence depending on the protein composition of the blood sample.

The team at UCL tested the sensor by comparing results from small blood samples (equivalent to finger-prick checks) from 65 people, in three balanced groups of healthy patients and those with early-stage and late-stage fibrosis. They found that the sensor could identify different patterns of protein levels in the blood serum of people in the three groups.

“By comparing the different samples, the sensor array identified a ‘fingerprint’ of liver damage,” said William Peveler, who completed the research at UCL. “This method is known as a chemical nose, as it can recognise the difference between healthy and unhealthy blood samples without relying on known disease markers,” said Peveler.

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Excess smartphone use linked to mental distress, suicidality

Agencies

February 11,2020

Using smartphone for long hours every day may do you more harm than you can probably think of. Researchers have found that spending a lot of time with the device and on social media may lead to mental distress and suicidality among adolescents.

The findings, published in the journal CMAJ (Canadian Medical Association Journal) contains guidance for physicians, parents and teachers on how to help teenagers manage smartphone and social media use for a healthy balance between sleep, academic work, social activity, interpersonal relationships and online activity.

"Physicians, teachers and families need to work together with youth to decrease possible harmful effects of smartphones and social media on their relationships, sense of self, sleep, academic performance, and emotional well-being," said lead author of the study Elia Abi-Jaoude from Toronto Western Hospital in Canada.

This review of evidence, led by the Hospital for Sick Children (SickKids), focuses on smartphone use and does not consider online gaming.

"For adolescents today, who have not known a world without social media, digital interactions are the norm, and the potential benefits of online access to productive mental health information -- including media literacy, creativity, self-expression, sense of belonging and civic engagement -- as well as low barriers to resources such as crisis lines and Internet-based talking therapies cannot be discounted," the authors wrote.

The researchers recommend that doctors should ask teenagers to reduce social media use rather than eradicate it completely and encourage parents to be part of the conversations.

Parents should discuss appropriate smartphone use with teenagers to determine together how to reduce risks and set boundaries.

A recent poll from the US indicates that 54 per cent of teenagers think they spend too much time on their smartphones and about half said they were cutting back on usage.

"Encouragingly, youth are increasingly recognising the negative impact of social media on their lives and starting to take steps to mitigate it," the authors wrote.

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Wearable sensor to predict worsening heart failure

News Network

February 26,2020

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.

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