No abstract

Data on inability to work from an observational study in patients treated with duloxetine for major depressive disorder in clinical practice in Germany were collected. Ability to work was compared between baseline and up to 6 months after initiation of duloxetine. All patients with a working status at baseline other than retired or retired early were included. 2,825 patients were analyzed, 54.8% were able to work at baseline increasing to 83.8% at 6 months. Of those patients unable to work at baseline, 72.7% were able to work after 6 months. A relevant reduction of inability to work was also found for patient subgroups with moderate to severe pain at baseline and those with and without MDD pretreatment. As inability to work is one of the main cost drivers for depressive patients in Germany, the reduction of inability to work could potentially result in considerable cost savings for health insurance companies and society.

Plankton is at the bottom of the food chain. Microscopic phytoplankton account for about 50% of all photosynthesis on Earth, corresponding to 50 billion tons of carbon each year, or about 125 billion tonnes of sugar [1]. Plankton is also the food for most species of fish, and therefore it represents the backbone of the aquatic environment. Thus, monitoring plankton is paramount to infer potential dangerous changes to the ecosystem. In this work we use a collection of plankton species extracted from a large dataset of images from the Woods Hole Oceanographic Institution (WHOI), to establish a basic set of morphological features for supporting the use of plankton as a biosensor. Using a perturbation detection approach, we show that it is possible to detect deviation from the average space of features for each species of plankton microorganisms, that we propose could be related to environmental threat or perturbations. Such an approach can open the way for the development of an automatic Artificial Intelligence (AI) based system for using plankton as biosensor.