Diet sodas might not raise diabetes risk

November 16, 2016

Nov 16: Drinking colas and other sugary drinks is tied to an increased risk of so-called pre-diabetes, a precursor to full-blown disease, but diet soda is not, a recent study suggests.

dietPrevious studies on the link between diet sodas and diabetes have been mixed; some research pointing to a potential connection has suggested this relationship may be explained at least in part by soda drinkers being overweight or obese.

In the current study, however, adults who routinely consumed at least one can of soda or other sugar-sweetened beverages a day were 46 percent more likely to develop elevated blood sugar levels than people who rarely or never drink cola.

“Emphasis should be placed on substituting sugar-sweetened beverages with water, unsweetened teas, or coffee,” said senior study author Nicola McKeown, a nutrition researcher at Tufts University in Boston.

“For daily consumers of sugary drinks, kicking the habit may be a difficult challenge, and incorporating an occasional diet soda, while increasing fluids from other sources, may be the best strategy to ultimately remove sugar-sweetened beverages from the diet,” McKeown added by email.

Globally, about one in nine adults have diabetes, and the disease will be the seventh leading cause of death by 2030, according to the World Health Organization. Most of these people have Type 2, or adult-onset, diabetes, which happens when the body can't properly use or make enough of the hormone insulin to convert blood sugar into energy.

People with blood sugar levels that are slightly elevated, but not high enough for a diabetes diagnosis, are sometimes described as having “pre-diabetes” because many will go on to develop diabetes. In the current study, researchers examined data collected on 1,685 middle-aged adults over about 14 years.

At the start of the study, none of the participants had diabetes or pre-diabetes. They were 52 years old on average and typically overweight.

Participants completed questionnaires detailing what they ate and drank during the study period. Sugar-sweetened beverages were defined as colas and other carbonated beverages, as well as drinks such as lemonade and fruit punch. This didn’t include fruit juice.

People who drank the most sodas – typically around six 12-ounce cans a week – had a much greater risk of developing elevated blood sugar levels than other participants after adjusting for factors such as age, gender and weight, researchers report in the Journal of Nutrition.

Higher consumption of soda and other sugar-sweetened beverages was also associated with insulin resistance, a reduced ability to respond to the hormone insulin that is another risk factor for developing diabetes.

Even after accounting for changes in weight and other aspects of diet, the relationships between sugar-sweetened beverages and these metabolic risk factors for diabetes persisted.

Diet soda intake—defined as low-calorie cola or other carbonated low-calorie beverages— was not associated with elevated blood sugar or insulin resistance.

The study doesn’t prove soda or sugary drinks cause diabetes.

Another limitation of the study is that participants may not be representative of a typical U.S. adult, the authors note. People in the study were mostly white, middle aged and more likely to be women. They also tended not to be as overweight or thick around the middle as many U.S. adults, the authors point out.

Because pre-diabetic elevated blood sugar can often be reversed before it advances to full-blown disease, the findings suggest it makes sense for people to avoid regular sodas to minimize their risk of developing diabetes, the researchers conclude.

“Sugar sweetened beverages have been shown to increase weight gain and risk of diabetes – including prediabetes,” Laura Rosella, a public health researcher at the University of Toronto who wasn’t involved in the study, said by email.

The current study findings add to a large body of evidence suggesting that the sugar and calories in soda can contribute to the risk of obesity and diabetes, noted Dr. Robert Cohen, a researcher at the University of Cincinnati College of Medicine who wasn’t involved in the study.

“I wouldn’t necessarily seek out diet drinks but the choice of non-calorie containing diet drinks is not associated with further insulin resistance or pre-diabetes in the way that calorie containing drinks are,” Cohen said by email.

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Agencies
July 2,2020

The American pharmaceutical giant Pfizer Inc. and the European biotechnology company BioNTech SE have conducted an experimental trial of a COVID-19 vaccine candidate and found it to be safe, well-tolerated, and capable of generating antibodies in the patients.

The study, which is yet to be peer-reviewed, describes the preliminary clinical data for the candidate vaccine -- nucleoside-modified messenger RNA (modRNA), BNT162b1.

It said the amount of antibodies produced in participants after they received two shots of the vaccine candidate was greater than that reported in patients receiving convalescent plasma from recovered COVID-19 patients.

"I was glad to see Pfizer put up their phase 1 trial data today. Virus neutralizing antibody titers achieved after two doses are greater than convalescent antibody titers," tweeted Peter Hotez, a vaccine scientist from Baylor College of Medicine in the US, who was unrelated to the study.

Researchers, including those from New York University in the US, who were involved in the study, said the candidate vaccine enables human cells to produce an optimised version of the receptor binding domain (RBD) antigen -- a part of the spike (S) protein of SARS-CoV-2 which it uses to gain entry into human cells.

"Robust immunogenicity was observed after vaccination with BNT162b1," the scientists noted in the study.

They said the program is evaluating at least four experimental vaccines, each of which represents a unique combination of mRNA format and target component of the novel coronavirus, SARS-CoV-2.

Based on the study's findings, they said BNT162b1 could be administered in a quantity that was well tolerated, potentially generating a dose dependent production of immune system molecules in the patients.

The research noted that patients treated with the vaccine candidate produced nearly 1.8 to 2.8 fold greater levels of RBD-binding antibodies that could neutralise SARS-CoV-2.

"We are encouraged by the clinical data of BNT162b1, one of four mRNA constructs we are evaluating clinically, and for which we have positive, preliminary, topline findings," said Kathrin U. Jansen, study co-author and Senior Vice President and Head of Vaccine Research & Development, Pfizer.

"We look forward to publishing our clinical data in a peer-reviewed journal as quickly as possible," Jansen said.

According to Ugur Sahin, CEO and Co-founder of BioNTech, and another co-author of the study, the preliminary data are encouraging as they provide an initial signal that BNT162b1 is able to produce neutralising antibody responses in humans.

He said the immune response observed in the patients treated with the experimental vaccine are at, or above, the levels observed from convalescent sera, adding that it does so at "relatively low dose levels."

"We look forward to providing further data updates on BNT162b1," Sahin said.

According to a statement from Pfizer, the initial part of the study included 45 healthy adults 18 to 55 years of age.

It said the priliminary data for BNT162b1 was evaluated in 24 subjects who received two injections of 10 microgrammes ( g) and 30 g -- 12 subjects who received a single injection of 100 g, and 9 subjects who received two doses of a dummy vaccine.

The study noted that participants received two doses, 21 days apart, of placebo, 10 g or 30 g of BNT162b1, or received a single dose of 100 g of the vaccine candidate.

According to the scientists, the highest neutralising concentrations of antibodies were observed seven days after the second dose of 10 g, or 30 g on day 28 after vaccination.

They said the neutralising concentrations were 1.8- and 2.8-times that observed in a panel of 38 blood samples from people who had contracted the virus.

In all 24 subjects who received two vaccinations at 10 g and 30 g dose levels, elevation of RBD-binding antibody concentrations was observed after the second injection, the study noted.

It said these concentrations are 8- and 46.3-times the concentration seen in a panel of 38 blood samples from those infected with the novel coronavirus.

At the 10 g or 30 g dose levels, the scientists said adverse reactions, including low grade fever, were more common after the second dose than the first dose.

According to Pfizer, local reactions and systemic events after injection with 10 g and 30 g of BNT162b1 were "dose-dependent, generally mild to moderate, and transient."

It said the most commonly reported local reaction was injection site pain, which was mild to moderate, except in one of 12 subjects who received a 100 g dose, which was severe.

The study noted that there was no serious adverse events reported by the patients.

Citing the limitations of the research, the scientists said the immunity generated in the participants in the form of the T cells and B cells of their immune system, and the level of immunity needed to protect one from COVID-19 are unknown.

With these preliminary data, along with additional data being generated, Pfizer noted in the statement that the two companies will determine a dose level, and select among multiple vaccine candidates to seek to progress to a large, global safety and efficacy trial, which may involve up to 30,000 healthy participants if regulatory approval to proceed is received.

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Agencies
April 15,2020

Dear parents, if you want your children to have proper sleep, read this carefully. Joining a growing list of studies that tell parents to shun devices at bed-time, researchers say that children who use devices and decide what time they go to sleep, achieve less sleep and feel more sleepier the following day than their peers.

The study of children in this age-group (aged 11 to 13 years), published in the New Zealand Medical Journal, found most (72 per cent) of the 163 students interviewed by University of Otago researchers achieved recommended guidelines of an average 9 to 11 hours sleep nightly over one week.

"But that also means that almost one in four students did not achieve sleep within these guidelines, which highlights an area for improvement," said study researcher Kate Ford.

However, consistent with previous research in 15 to 17-year-old New Zealanders, the study results show less sleep on the nights where devices are used in the hour before bed.

According to the researchers, students who used devices before going to sleep were also more likely to report that they felt sleepy the following morning. Watching television before bed had no significant effect on sleep length.

There were also some interesting observations over the weekends where students went to bed later but woke later achieving similar sleep length to the school days, the researchers said.

A small group of students (six per cent) who reported less than seven hours of sleep, including a small number reporting not sleeping at all, according to the study,

Therefore, while the average across the week of 72 per cent of students reporting adequate sleep is reassuring, it is far from the goal of every child achieving sleep within the recommended guidelines," Ford said.

Dr Paul Kelly, head of the Sleep Health Service at Canterbury District Health Board, supervised the study and explained that the foundations for good health are based on proper nutrition, regular exercise and good sleep quality.

Sleep quality is often overlooked as a contributory factor to poor health.

"The study findings suggest the need for parental guidance around bedtimings and moderation of the use and availability of electronic devices before bed," Kelly said.

"Respect and protect your sleep, as good daytime functioning is reliant on adequate sleep," Kelly added.

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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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