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BACKGROUND

A closed-loop system of insulin delivery (also called an artificial pancreas) may improve glycemic outcomes in children with type 1 diabetes.

METHODS

In a 16-week, multicenter, randomized, open-label, parallel-group trial, we assigned, in a 3:1 ratio, children 6 to 13 years of age who had type 1 diabetes to receive treatment with the use of either a closed-loop system of insulin delivery (closed-loop group) or a sensor-augmented insulin pump (control group). The primary outcome was the percentage of time that the glucose level was in the target range of 70 to 180 mg per deciliter, as measured by continuous glucose monitoring.

RESULTS

A total of 101 children underwent randomization (78 to the closed-loop group and 23 to the control group); the glycated hemoglobin levels at baseline ranged from 5.7 to 10.1%. The mean (±SD) percentage of time that the glucose level was in the target range of 70 to 180 mg per deciliter increased from 53±17% at baseline to 67±10% (the mean over 16 weeks of treatment) in the closed-loop group and from 51±16% to 55±13% in the control group (mean adjusted difference, 11 percentage points [equivalent to 2.6 hours per day]; 95% confidence interval, 7 to 14; P<0.001). In both groups, the median percentage of time that the glucose level was below 70 mg per deciliter was low (1.6% in the closed-loop group and 1.8% in the control group). In the closed-loop group, the median percentage of time that the system was in the closed-loop mode was 93% (interquartile range, 91 to 95). No episodes of diabetic ketoacidosis or severe hypoglycemia occurred in either group.


The number of reported Covid-19 cases across the globe has surpassed 25 million, with the U.S., Brazil and India leading the grim count, according to data from Johns Hopkins University.

The coronavirus has killed more than 843,000 people worldwide since it emerged from Wuhan, China, late last year, with the Americas reporting the bulk of fatalities. The U.S., Mexico and Brazil represent more than 40% of the global death toll, according to Johns Hopkins.

Reported Covid-19 cases first surpassed 10 million in late June, then reached 20 million just over six weeks later on Aug. 10, according to Johns Hopkins data.

The House will vote on legislation next month to remove cannabis from the Controlled Substances Act and erase some marijuana criminal records.

The bill would not legalize the drug, which would be left up to states, but the vote will still be a historic step in the effort to reduce legal penalties related to the drug. House Majority Whip James Clyburn (D-S.C.) said in an email to members that the vote will take place during the September work period.

BREAKING: The U.S. House will vote on a bill to remove cannabis from the Controlled Substances Act.

Summary: Transposable elements team up with evolutionary recent neurons to influence differentiation and physiological function of neurons in brain development.

Source: EPFL

The human genome contains over 4.5 million sequences of DNA called “transposable elements”, these virus-like entities that “jump” around and help regulate gene expression. They do this by binding transcription factors, which are proteins that regulate the rate of transcription of DNA to RNA, influencing gene expression in a broad range of biological events.

A striking new study has found young cancer survivors show high expression of a gene known to be an effective marker of aging. The researchers suggest this genetic biomarker could be used to identify cancer survivors most at risk of later-life frailty due to their treatment.

As we age, concentrations of a gene called p16INK4a gradually increase in our cells, making it a potentially useful molecular marker for aging. One of the gene’s roles is to slow cell division and reduce the proliferation of stem cells.

In a new study researchers set out to investigate p16INK4a levels in pediatric and young adult cancer survivors. The hypothesis was that increased p16INK4a levels could be an effective sign of frailty among young cancer survivors.

The news: IBM has built a new chemistry lab called RoboRXN in the cloud. It combines AI models, a cloud computing platform, and robots to help scientists design and synthesize new molecules while working from home.

How it works: The online lab platform allows scientists to log on through a web browser. On a blank canvas, they draw the skeletal structure of the molecular compounds they want to make, and the platform uses machine learning to predict the ingredients required and the order in which they should be mixed. It then sends the instructions to a robot in a remote lab to execute. Once the experiment is done, the platform sends a report to the scientists with the results.

Why it matters: New drugs and materials traditionally require an average of 10 years and $10 million to discover and bring to market. Much of that time is taken up by the laborious repetition of experiments to synthesize new compounds and learn from trial and error. IBM hopes that a platform like RoboRXN could dramatically speed up that process by predicting the recipes for compounds and automating experiments. In theory, it would lower the costs of drug development and allow scientists to react faster to health crises like the current pandemic, in which social distancing requirements have caused slowdowns in lab work.