Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches

The ubiquity of smartphones have opened up the possibility of widespread use of the Experience Sampling Method (ESM). The method is used to collect longitudinal data of participants' daily life experiences and is ideal to capture fluctuations in emotions (momentary mental states) as an indicator for later mental ill-health. In this study, ESM data of patients with psychosis spectrum disorder and controls were used to examine daily life emotions and higher order patterns thereof. We attempted to determine whether aggregated ESM data, in which statistical measures represent the distribution and dynamics of the original data, were able to distinguish patients from controls in a predictive modelling framework. Variable importance, recursive feature elimination, and ReliefF methods were used for feature selection. Model training, tuning, and testing were performed in nested cross-validation, based on algorithms such as Random Forests, Support Vector Machines, Gaussian Processes, Logistic Regression and Neural Networks. ROC analysis was used to post-process these models. Stability of model performance was studied using Monte Carlo simulations. The results provide evidence that patterns in emotion changes can be captured by applying a combination of these techniques. Acceleration in the variables anxious and insecure was particularly successful in adding further predictive power to the models. The best results were achieved by Support Vector Machines with radial kernel (accuracy=82% and sensitivity=82%). This proof-of-concept work demonstrates that synergistic machine learning and statistical modeling may be used to harness the power of ESM data in the future

Alternative splicing downstream of EMT enhances phenotypic plasticity and malignant behavior in colon cancer

Phenotypic plasticity allows carcinoma cells to transiently acquire the quasi-mesenchymal features necessary to detach from the primary mass and proceed along the invasion-metastasis cascade. A broad spectrum of epigenetic mechanisms is likely to cause the epithelial-to-mesenchymal (EMT) and mesenchymal-to-epithelial (MET) transitions necessary to allow local dissemination and distant metastasis. Here, we report on the role played by alternative splicing (AS) in eliciting phenotypic plasticity in epithelial malignancies with focus on colon cancer. By taking advantage of the coexistence of subpopulations of fully epithelial (EpCAM(hi)) and quasi-mesenchymal and highly metastatic (EpCAM(lo)) cells in conventional human cancer cell lines, we here show that the differential expression of ESRP1 and other RNA-binding proteins (RBPs) downstream of the EMT master regulator ZEB1 alters the AS pattern of a broad spectrum of targets including CD44 and NUMB, thus resulting in the generation of specific isoforms functionally associated with increased invasion and metastasis. Additional functional and clinical validation studies indicate that both the newly identified RBPs and the CD44s and NUMB2/4 splicing isoforms promote local invasion and distant metastasis and are associated with poor survival in colon cancer. The systematic elucidation of the spectrum of EMT-related RBPs and AS targets in epithelial cancers, apart from the insights in the mechanisms underlying phenotypic plasticity, will lead to the identification of novel and tumor-specific therapeutic targets

Technical pitfalls and proposed modifications of instructions for use for endovascular aortic aneurysm repair using the Gore Excluder conformable device in angulated and short landing zones

We describe a case of an abdominal aortic aneurysm (AAA) and angulated proximal neck treated with a Gore Excluder conformable endoprosthesis and show relevant technical pitfalls in the deployment of the graft main body. An 82-year-old man presented with a 71-mm asymptomatic AAA with an angulated infrarenal proximal neck (75°) and was referred to our unit. The patient was treated with a 26-mm Gore Excluder conformable device, which was deployed slightly above the renal arteries after precatheterization of the lowest renal artery. The graft was then repositioned with support of the introducer sheath and a stiff guide wire. The proximal sealing zone was ballooned before the endograft delivery system was retrieved to avoid distal migration. Technical success was achieved. The patient was discharged with no complications. No type Ia endoleak was present on the 6-month computed tomography scan. Endovascular treatment of an AAA with a severe angulated proximal neck can be effective with a conformable stent graft if technical measures are used during deployment of the main body to optimize the seal.</p

Integrated nano-opto-electro-mechanical sensor for spectrometry and nanometrology

Spectrometry is widely used for the characterization of materials, tissues, and gases, and the need for size and cost scaling is driving the development of mini and microspectrometers. While nanophotonic devices provide narrowband filtering that can be used for spectrometry, their practical application has been hampered by the difficulty of integrating tuning and read-out structures. Here, a nano-opto-electro-mechanical system is presented where the three functionalities of transduction, actuation, and detection are integrated, resulting in a high-resolution spectrometer with a micrometer-scale footprint. The system consists of an electromechanically tunable double-membrane photonic crystal cavity with an integrated quantum dot photodiode. Using this structure, we demonstrate a resonance modulation spectroscopy technique that provides subpicometer wavelength resolution. We show its application in the measurement of narrow gas absorption lines and in the interrogation of fiber Bragg gratings. We also explore its operation as displacement-to-photocurrent transducer, demonstrating optomechanical displacement sensing with integrated photocurrent read-out