Nucleic acid quantification and disease outcome prediction in colorectal cancer

SenseHunger: Machine Learning Approach to Hunger Detection Using Wearable Sensors

The perception of hunger and satiety is of great importance to maintaining a healthy body weight and avoiding chronic diseases such as obesity, underweight, or deficiency syndromes due to malnutrition. There are a number of disease patterns, characterized by a chronic loss of this perception. To our best knowledge, hunger and satiety cannot be classified using non-invasive measurements. Aiming to develop an objective classification system, this paper presents a multimodal sensory system using associated signal processing and pattern recognition methods for hunger and satiety detection based on non-invasive monitoring. We used an Empatica E4 smartwatch, a RespiBan wearable device, and JINS MEME smart glasses to capture physiological signals from five healthy normal weight subjects inactively sitting on a chair in a state of hunger and satiety. After pre-processing the signals, we compared different feature extraction approaches, either based on manual feature engineering or deep feature learning. Comparative experiments were carried out to determine the most appropriate sensor channel, device, and classifier to reliably discriminate between hunger and satiety states. Our experiments showed that the most discriminative features come from three specific sensor modalities: Electrodermal Activity (EDA), infrared Thermopile (Tmp), and Blood Volume Pulse (BVP).

Reliability of real-time reverse-transcription PCR in clinical diagnostics: gold standard or substandard?

Molecular diagnostics is one of the major growth areas of modern medicine, with real-time PCR established as a qualitative and quantitative technology that is rapid, accurate and sensitive. The sequencing of the human genome, comprehensive genomic, mRNA and miRNA expression profiling of numerous cancer types, the ongoing identification of disease-associated polymorphisms and the expanding availability of genomic sequence information for human pathogens has opened the door to a wide range of translational applications for this technology. Consequently, novel real-time PCR assays have been developed for diagnosis and prognosis, treatment monitoring, transplant biology and pathogen detection, as well as more controversial uses such as lifestyle genotyping. However, this technology is still troubled by significant technical deficiencies. Hence its often-improper use as a clinical tool has important public health implications, most recently demonstrated through its association with the measles, mumps and rubella vaccine/autism controversy. This serves as a timely reminder of the indispensable requirement for careful experimental design, validation and analysis.