Sunday, January 27, 2019

Mouth and Gut Bacteria May Aid in Overweight And Obesity Treatment

Studies done at The Washington University St. Louis Medical School have shown that trillions of bacteria live in our gut. These bacteria perform specific activities such as extracting calories from food we eat and managing nutrients. These bacteria are common to all of us, however, each individual has a unique set of the bacteria.  Studies at Washington University have shown that the composition of the bacteria plays an important role in weight control. A more recent study done at Penn State University is suggesting that mouth bacteria in infants may predict obesity later in life.
The researchers at Washington University studied mice, and concluded that obese mice had more of the bacteria called Firmicutes in their gut, and fewer of  the bacteria called Bacteroidetes.  Firmicutes are associated  with obesity and Bacteroidetes are associated with leanness. These same bacteria were found in the mouths of participants in the Penn State University study. The researchers indicated that an imbalance in these two sets of bacteria could lead to obesity.
The researchers concluded that “the children who had rapid weight gain as infants, which is a strong risk factor for childhood obesity, had fewer groups of bacteria or less diversity in their mouth bacteria. These children also had a higher ratio of Firmicutes to Bacteroidetes, two of the most common bacteria groups of the human microbiota.”
One of the study’s researchers indicated that “There's … a certain balance of these two common bacteria groups, Firmicutes and Bacteroidetes, that tends to work best under normal healthy conditions, and disruptions to that balance could lead to dysregulation in digestion,”
Of course researchers will need to determine the full effect of these two types of bacteria in the creation of fat tissue, and the value of the bacteria in the mouth for predicting obesity. And researchers need to determine what diets lead to the optimal composition of these bacteria. However, gaining knowledge about these bacteria may enable us to better fight, predict, and avoid obesity. 


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Sunday, January 20, 2019

Using Artificial Intelligence to Treat Prediabetes

Prediabetes is a chronic disease that afflicts 84% of the adults in the U.S., and having prediabetes raises the risk for diabetes heart disease stroke and other problems. The  Centers for Disease Control and Prevention (CDC) established the Diabetes Prevention Program (DPP) to address prediabetes. That program is based on a study, funded by the National Institutes of Diabetes and Digestive and Kidney Disease (NIDDK). The study was done and reported on between 1996 and 2002. The services delivered in the DPP can potentially be replicated with the help of artificial intelligence.

The original DPP study indicated that for those with prediabetes, lifestyle modification plus diet and increased physical activity could reduce the risk of diabetes by 58%. The study was done using highly trained individuals -- registered dietitians, for example -- to deliver the one-on-one counseling. The one-on-one program was later translated into a group based program. This group based program was less costly than the original one-on-one program. Still, additional efforts are underway to reduce the cost of the program. One of these programs uses artificial intelligence and telemedicine to deliver the counseling.

The program is called the Lark Weight Loss Health Coach AI (HCAI). In a study, HCAI was used to determine the effectiveness of conversational artificial intelligence (AI) when used as a mobile app for smart phones. The study also measured the user acceptability of the methodology.

There were 70 participants in the study, and the study's standards met the CDC’s criteria for the CDC’s diabetes prevention program. The criteria were those used for the original DPP trials. Although more research needs to be done, the results were quite promising.

The investigators concluded that “the use of an AI health Coach is associated with weight loss comparable to in-person lifestyle interventions. It can also encourage behavior changes and have higher user acceptability. Research into AI and its application in telemedicine should be pursued, with clinical trials investigating effects on weight, health behaviors, and user engagement and acceptability.”

If this approach proves beneficial, it could increase the number of people with prediabetes who can get treatment while lowering the cost. Healthcare providers should keep abreast of this type of research, because it can be quite important in the future.
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