Confronting Challenges to the Uptake of Digital Healthcare | Paola Mattei

Confronting Challenges to the Uptake of Digital Healthcare | Paola Mattei

Digital healthcare promises a wealth of benefits for current healthcare systems, yet its uptake has been remarkably slow across Europe. Taking the example of the UK in particular, Paola Mattei, Associate Professor in Political Science at the University of Milan, Italy, has recently considered the explanations for the slow uptake of digital healthcare and provides a commentary on why this is the case and what challenges now need to be faced to ensure success.

Do Maternal Influences on Birthweight Influence Future Cardiometabolic Risk? | Dr Gunn-Helen Moen

Do Maternal Influences on Birthweight Influence Future Cardiometabolic Risk? | Dr Gunn-Helen Moen

Adverse environmental factors in the mother’s womb and/or during the first years of life have traditionally been thought to be responsible for an increased risk of cardiometabolic disease for children later in life. Dr Gunn-Helen Moen [MO-en] at the University of Oslo in Norway and her collaborators used sophisticated statistical and genetic techniques to identify whether there is a causal effect of environmental factors that influence intrauterine growth on future cardiometabolic risk in the child. Their results were surprising but important.

Using Machine Learning to Predict Bacterial Growth According to the Media Components | Dr Bei-Wen Ying

Using Machine Learning to Predict Bacterial Growth According to the Media Components | Dr Bei-Wen Ying

Bacterial growth depends on the complex interactions of a multitude of chemical components. Microbiologists have long attempted to predict bacterial growth according to culture media components, and have employed a variety of mathematical and computational models to this end. Dr Bei-Wen Ying and her colleagues at the University of Tsukuba, Japan, successfully applied machine learning to understand the contribution of media culture components to bacterial growth. Their work makes a significant contribution to growth prediction and demonstrates that machine learning can be employed in the exploration of the complex dynamics that regulate living systems.

How Cancer Cells Overcome the Obstacle of Senescence | Sebastian Igelmann

How Cancer Cells Overcome the Obstacle of Senescence | Sebastian Igelmann

Cellular senescence [suh-NEH-Sns] is the process by which cells age and permanently stop dividing but do not die. While the process of senescence creates a barrier to tumour formation, it can still be overcome by cancer cells. Sebastian Igelmann, a PhD student supervised by group leader Dr Gerardo Ferbeyre at the University of Montreal, has identified a group of enzymes that work together to reprogramme cellular metabolism. This work provides important insight into how tumour cells may initiate proliferation and circumvent senescence. Critically, this specialist group of enzymes provides a potential therapeutic target for human cancer treatment.

The Holy Grail of Safer Opioids: Targeting Mu Opioid Receptor Splice Variants | Dr Ying-Xian Pan

The Holy Grail of Safer Opioids: Targeting Mu Opioid Receptor Splice Variants | Dr Ying-Xian Pan

Despite their numerous side effects, opioid drugs and morphine-like agents have remained a pillar in the medical management of pain. Most clinically used opioid drugs act through mu opioid receptors. Dr Ying-Xian Pan and his team from the Rutgers New Jersey Medical School, USA, studies the molecular and cellular mechanisms of mu opioid receptors and aim to develop novel strategies and opioid analgesics for better treating pain without side effects associated with traditional opiates. Efforts to find substitutes for traditional opioid drugs are helping address the opiate abuse crisis that affects many countries around the globe.

Using Genetics to Diagnose Rare Metabolic Diseases | Dr Michael Wanger

Using Genetics to Diagnose Rare Metabolic Diseases | Dr Michael Wanger

Identifying the cause of an illness in a sick baby or child is not always easy, particularly if the disease is rare. Throughout his career, Dr Michael Wangler, at the Baylor College of Medicine and Jan and Dan Duncan Neurological Research Institute, has investigated rare childhood diseases. Combining his expertise in paediatrics and genetics, Dr Wangler utilises genomics, metabolomics and the humble fruit fly to identify the genes responsible for rare and undiagnosed diseases to improve both diagnosis and treatment.