Author: Théophile Niyitegeka

{Researchers have found consuming four cans of energy drinks resulted in abnormal changes in blood pressure and heart rhythm within two hours according to Daily Mail.}

The researchers revealed 32 fluid ounces (just under a litre) of a commercially-available energy drink was found to contain about 108g of sugar (roughly 27 teaspoons), and 320mg of caffeine, close to the daily recommended daily limit, along with other substances such as taurine, ginseng and carnitine.

“We decided to study energy drinks’ potential heart health impact because previous research has shown 75 percent of the base’s military personnel have consumed an energy drink,” Dr Emily Fletcher, of the US Air Force Medical Centre in Travis, California, said.

The researchers found energy drinks made the heart pause for an extra 10 milliseconds between beats.

“It’s the pause from the end of the electrical impulse generating the heart to beat to the next impulse,” Dr Fletcher said.

“If this time interval, which is measured in milliseconds, is either too short or too long, it can cause the heart to beat abnormally. The resulting arrhythmia can be life threatening.”

According to Daily Mail, some medications increase this pause by 6 milliseconds and have warnings about the effect on product labels whereas energy drinks seem to have a bigger impact.

The finds of the research were published in the Journal of the American Heart Association.

Source:Elcrema

{Scientists from the University of Bristol have looked at all 14,500 participants in Children of the 90s and found that if a girl’s maternal grandmother smoked during pregnancy, the girl is 67% more likely to display certain traits linked to autism, such as poor social communication skills and repetitive behaviours.}

The team also found that if the maternal grandmother smoked, this increased by 53% the risk of her grandchildren having a diagnosed autism spectrum disorder (ASD).

These discoveries suggest that if a female is exposed to cigarette smoke while she is still in the womb, it could affect the developing eggs — causing changes that may eventually affect the development of her own children. Further research is now needed to find out what these molecular changes might be, and to see whether the same associations are present in other groups of people.

Unlike the analysis of autistic traits, which was based on over 7,000 participants, the 177 diagnosed with ASD were too few to analyse grandsons and granddaughters separately.

The discovery, published today in Scientific Reports, is part of an ongoing, long-term study of the effects of maternal and paternal grandmother’s smoking in pregnancy on the development of their grandchildren, who are all part of Children of the 90s. By using detailed information collected over many years on multiple factors that may affect children’s health and development, the researchers were able to rule out other potential explanations for their results.

The incidence of ASD has increased in recent years, and while some of this increase is undoubtedly down to improved diagnosis, changes in environment or lifestyle are also likely to play a role. The researchers also stress that many different factors, including genetic variation, are believed to affect an individual’s chances of developing ASD.

Past studies of maternal smoking in pregnancy and ASD in children have been inconclusive. Going back a generation has revealed an intergenerational effect, which interestingly is most clear cut when the mother herself did not smoke in pregnancy.

The reasons for this are not entirely clear but Professor Marcus Pembrey, one of the paper’s authors, says: ‘In terms of mechanisms, there are two broad possibilities. There is DNA damage that is transmitted to the grandchildren or there is some adaptive response to the smoking that leaves the grandchild more vulnerable to ASD. We have no explanation for the sex difference, although we have previously found that grand-maternal smoking is associated with different growth patterns in grandsons and granddaughters.

‘More specifically, we know smoking can damage the DNA of mitochondria — the numerous “power-packs” contained in every cell, and mitochondria are only transmitted to the next generation via the mother’s egg. The initial mitochondrial DNA mutations often have no overt effect in the mother herself, but the impact can increase when transmitted to her own children.’

Professor Jean Golding, another author, added: ‘We already know that protecting a baby from tobacco smoke is one of the best things a woman can do to give her child a healthy start in life. Now we’ve found that not smoking during pregnancy could also give their future grandchildren a better start too. We have started studying the next generation of participants (COCO90s), so eventually we will be able to see if the effect carries down from the great-grandparents to their great-grandchildren too.’

Dr Dheeraj Rai, another author, added: ‘We still do not know why many children develop autism and behaviours linked to it. The associations we observe raise intriguing issues on possible transgenerational influences in autism. Future research will help understand the meaning and mechanisms behind these findings. The National Autistic Society website contains a wealth of information about autism and details on how and where to seek advice.’

Alycia Halladay, PhD, chief science officer at the Autism Science Foundation (USA), said: ‘To date, research into the causes of autism has been limited to studying maternal or paternal exposures during pregnancy. By utilizing a birth cohort in the United Kingdom [Children of the 90s], scientists are able to go back a generation to examine the role of grandparental exposures, presumably through germ line mutations and epigenetic modifications. Hopefully, grandparental exposures will continue to be investigated to better understand this mechanism.’

Source:Science Daily

{First-of-its-kind, personalized glucose forecasting tool may make meal planning simpler for type 2 diabetes patients}

Columbia University researchers have developed a personalized algorithm that predicts the impact of particular foods on an individual’s blood sugar levels. The algorithm has been integrated into an app, Glucoracle, that will allow individuals with type 2 diabetes to keep a tighter rein on their glucose levels — the key to preventing or controlling the major complications of a disease that affects 8 percent of Americans.

The findings were published online today in PLOS Computational Biology.

Medications are often prescribed to help patients with type 2 diabetes manage their blood sugar levels, but exercise and diet also play an important role.

“While we know the general effect of different types of food on blood glucose, the detailed effects can vary widely from one person to another and for the same person over time,” said lead author David Albers, PhD, associate research scientist in Biomedical Informatics at Columbia University Medical Center (CUMC). “Even with expert guidance, it’s difficult for people to understand the true impact of their dietary choices, particularly on a meal-to-meal basis. Our algorithm, integrated into an easy-to-use app, predicts the consequences of eating a specific meal before the food is eaten, allowing individuals to make better nutritional choices during mealtime.”

The algorithm uses a technique called data assimilation, in which a mathematical model of a person’s response to glucose is regularly updated with observational data — blood sugar measurements and nutritional information — to improve the model’s predictions, explained co-study leader George Hripcsak, MD, MS, the Vivian Beaumont Allen Professor and chair of Biomedical Informatics at CUMC. Data assimilation is used in a variety of applications, notably weather forecasting.

“The data assimilator is continually updated with the user’s food intake and blood glucose measurements, personalizing the model for that individual,” said co-study leader Lena Mamykina, PhD, assistant professor of biomedical informatics at CUMC, whose team has designed and developed the Glucoracle app.

Glucoracle allows the user to upload fingerstick blood measurements and a photo of a particular meal to the app, along with a rough estimate of the nutritional content of the meal. This estimate provides the user with an immediate prediction of post-meal blood sugar levels. The estimate and forecast are then adjusted for accuracy. The app begins generating predictions after it has been used for a week, allowing the data assimilator has learned how the user responds to different foods.

The researchers initially tested the data assimilator on five individuals using the app, including three with type 2 diabetes and two without the disease. The app’s predictions were compared with actual post-meal blood glucose measurements and with the predictions of certified diabetes educators.

For the two non-diabetic individuals, the app’s predictions were comparable to the actual glucose measurements. For the three subjects with diabetes, the app’s forecasts were slightly less accurate, possibly due to fluctuations in the physiology of patients with diabetes or parameter error, but were still comparable to the predictions of the diabetes educators.

“There’s certainly room for improvement,” said Dr. Albers. “This evaluation was designed to prove that it’s possible, using routine self-monitoring data, to generate real-time glucose forecasts that people could use to make better nutritional choices. We have been able to make an aspect of diabetes self-management that has been nearly impossible for people with type 2 diabetes more manageable. Now our task is to make the data assimilation tool powering the app even better.”

Encouraged by these early results, the research team is preparing for a larger clinical trial. The researchers estimate that the app could be ready for widespread use within two years.

Source:Science Daily