Development and application of a hybrid MHD-kinetic model in JOREK

Energetic particle (EP) driven instabilities will be of strongly increased relevance in future burning plasmas as the EP pressure will be very large compared to the thermal plasma. Understanding the interaction of EPs and bulk plasma is crucial for developing next-generation fusion devices. In this work, the JOREK MHD code is extended to allow for the simulation of EP instabilities at high EP pressures using realistic plasma and EP parameter in a full-f formulation with anisotropic pressure coupling to the bluid background. The code is first benchmarked linearly for the ITPA-TAE as well as the experiment based AUG-NLED cases, obtaining good agreement to other codes. Then, it is applied to a high energetic particle pressure discharge in the ASDEX Upgrade tokamak using a realistic non-Maxwellian distribution of EPs, reproducing aspects of the experimentally observed instabilities. Non-linear applications are possible based on the implentation, but will require dedicated verification and validation left for future work

Quantitative EEG (QEEG) Measures Differentiate Parkinson`s Disease Patients from Healthy Controls

Objectives: To find out which Quantitative EEG (QEEG) parameters could best distinguish patients with Parkinson's disease (PD) with and without Mild Cognitive Impairment from healthy individuals and to find an optimal method for feature selection. Background: Certain QEEG parameters have been seen to be associated with dementia in Parkinson's and Alzheimer's disease. Studies have also shown some parameters to be dependent on the stage of the disease. We wanted to investigate the differences in high-resolution QEEG measures between groups of PD patients and healthy individuals, and come up with a small subset of features that could accurately distinguish between the two groups. Methods: High-resolution 256-channel EEG were recorded in 50 PD patients (age 68.8 ± 7.0 year; female/male 17/33) and 41 healthy controls (age 71.1 ± 7.7 year; female/male 20/22). Data was processed to calculate the relative power in alpha, theta, delta, beta frequency bands across the different regions of the brain. Median, peak frequencies were also obtained and alpha1/theta ratios were calculated. Machine learning methods were applied to the data and compared. Additionally, penalized Logistic regression using LASSO was applied to the data in R and a subset of best-performing features was obtained. Results: Random Forest and LASSO were found to be optimal methods for feature selection. A group of six measures selected by LASSO was seen to have the most effect in differentiating healthy individuals from PD patients. The most important variables were the theta power in temporal left region and the alpha1/theta ratio in the central left region. Conclusion: The penalized regression method applied was helpful in selecting a small group of features from a dataset that had high multicollinearity. Keywords: Parkinson's disease, QEEG, cognitive decline, Parkinson's disease dementia, neurodegenerative disorders, machine learnin

Stage III Non-Small Cell Lung Cancer in the elderly: Patient characteristics predictive for tolerance and survival of chemoradiation in daily clinical practice

Background: In unselected elderly with stage III Non-Small Cell Lung Cancer (NSCLC), evidence is scarce regarding motives and effects of treatment modalities. Methods: Hospital-based multicenter retrospective study including unresectable stage III NSCLC patients aged >= 70 and diagnosed between 2009 and 2013 (N = 216). Treatment motives and tolerance (no unplanned hospitalizations and completion of treatment), and survival were derived from medical records and the Netherlands Cancer Registry. Results: Patients received concurrent chemoradiation (cCHRT, 33%), sequential chemoradiation (sCHRT, 24%), radical radiotherapy (RT, 16%) or no curative treatment (27%). Comorbidity, performance status (58%) and patient refusal (15%) were the most common motives for omitting cCHRT. Treatment tolerance for cCHRT and sCHRT was worse in case of severe comorbidity (OR 6.2 (95%Cl 1.6-24) and OR 6.4 (95%CI 1.8-22), respectively). One-year survival was 57%, 50%, 49% and 26% for cCHRT, sCHRT, RT and no curative treatment, respectively. Compared to cCHRT, survival was worse for no curative treatment (P = 0.000), but not significantly worse for sCHRT and RT (P = 0.38). Conclusion: Although relatively fit elderly were assigned to cCHRT, treatment tolerance was worse, especially for those with severe comorbidity. Survival seemed not significantly better as compared to sCHRT or RT. Prospective studies in this vital and understudied area are needed

Chemotherapy and Tyrosine Kinase Inhibitors in the last month of life in patients with metastatic lung cancer: A patient file study in the Netherlands

Objective: Chemotherapy in the last month of life for patients with metastatic lung cancer is often considered as aggressive end-of-life care. Targeted therapy with Tyrosine Kinase Inhibitors (TKIs) is a relatively new treatment of which not much is known yet about use in the last month of life. We examined what percentage of patients received chemotherapy or TKIs in the last month of life in the Netherlands. Methods: Patient files were drawn from 10 hospitals across the Netherlands. Patients had to meet the following eligibility criteria: metastatic lung cancer; died between June 1, 2013 and July 31, 2015. Results: From the included 1,322 patients, 39% received no treatment for metastatic lung cancer, 52% received chemotherapy and 9% received TKIs. A total of 232 patients (18%) received treatment in the last month of life (11% chemotherapy, 7% TKIs). From the patients who received chemotherapy, 145 (21%) received this in the last month of life and 79 (11%) started this treatment in the last month of life. TKIs were given and started more often in the last month of life: from the patients who received TKIs, 87 (72%) received this treatment in the last month of life and 15 (12%) started

Development and Validation of a Novel and Rapid Molecular Detection Method for High-Risk Human Papillomavirus in Formalin-Fixed, Paraffin-Embedded Tumor Tissue

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