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group, SSQ improvements were significantly associated with improvements in QOLIE-31 Total Score (TS; P  less then  0.0001) and the Seizure Worry (SW; P  less then  0.0001) and Social Functioning (SF; P = 0.0030) subscales. In the ESL 1200 mg subgroup, SSQ improvements were significantly associated with improvements in QOLIE-31 TS (P  less then  0.0001) and the SW (P  less then  0.0001) and Energy/Fatigue (EF; P = 0.0007) subscales. In the ESL 800 mg subgroup, improvements in the SSQ were significantly associated with improvements in QOLIE-31 TS (P = 0.0362) and the SW (P = 0.0241) subscale. There was no significant association between changes in the SSQ and changes in the MADRS in patients treated with ESL. These findings demonstrated that in this clinical trial population, adding ESL to baseline AED therapy had utility for decreasing seizure severity and improving HRQoL. There were no significant associations between changes in seizure severity and changes in depressive symptoms in patients with FS.Methods that use directed acoustic [14,128] and electric fields [104,115] have shown a promise in oil recovery in the past. These methods are great candidates to not only facilitate oil recovery, but also reduce CO2 emissions to a minimum. However, they have not found big commercial success due to poor understanding of the underlying mechanisms that facilitate the recovery. This paper is focused on breaching this gap by summarizing the main theories and experimental work done in the fields of acoustic and electric wave propagation though liquids, their interfaces and saturated porous media. The main theories of the acoustic and electric wave propagation through liquid and saturated porous media are outlined and discussed here. Key physical mechanisms that occur in the reservoir oil and water phases and at their interface during acoustic and electric wave propagation are identified. The development of the Maxwell stress theory of the liquid-liquid interface under the influence of the electric field by Melcher, Smith, Taylor and Lin et al. is shown to be a useful tool to estimate the critical voltage that disturbs a liquid-liquid interface [78,112,120]. Important aspects in wellbore acoustic transducer design and its selection to fit into the reservoir conditions are covered and scrutinized [66,101]. Characteristics of the magnetostrictive devices are shown to fit reservoir conditions the best.Seattle's Sweetened Beverage Tax is an excise tax of 1.75 cents per ounce on sugar-sweetened beverages and is one of the highest beverage taxes in the U.S. This study examined the impact of Seattle's tax on the prices of beverages. We conducted audits of 407 retail food stores and eating places (quick service restaurants and coffee shops) before and 6 months after the tax was implemented in Seattle and in a comparison area. Ordinary least squares difference-in-differences models with store fixed effects were used to estimate the effect of the tax on prices, stratified by beverage type and store type. In secondary analyses, we assessed the effect of the tax on the price of non-taxed beverages and foods. Results from the adjusted difference-in-differences models indicated the tax was associated with an average increase of 1.58 cents per ounce among Seattle retailers, representing 90 % of the price of the tax. By store type, price increases were highest in smaller grocery stores and drug stores. By beverage type, price increases were highest for energy beverages and soda and lowest for bottled coffee and juice drinks. Prices of some non-taxed beverages also increased while the prices of select healthy foods generally did not. The sweetened beverage tax in Seattle is higher than beverage taxes in most other cities, and nearly the full cost of the tax is being passed through to consumers for many beverage types and stores types.A series of Pt(II) complexes of the type [Pt(1,10-phenanthroline)(SArFn)2] (SArFn = SC6H3-3,4-F2(1); SC6F4-4-H (2); SC6F5(3)) were synthesized from [Pt(1,10-phenanthroline)(Cl)2] and [Pb(SArFn)2] via metathesis reactions. The complexes were fully characterized including the unambiguous determination of their molecular structures by single-crystal X-ray diffraction techniques, showing the metal centers to be into a slightly distorted square-planar environments. The in vitro cytotoxic activity of the complexes was evaluated on six cancerous cell lines, i.e glial cells of nervous central system (U-251), prostate (PC-3), leukemia (K-562), colon (HCT-15), breast (MCF-7) and lung (SKLU-1); we also included a healthy cell line of COS-7 (African green monkey kidney) for comparative purposes. We found that complex 2 was selective for PC-3. In addition, the IC50 values for the series of complexes were determined using the U-251, HCT-15 and SKLU-1 cancerous cell lines, as well as in the healthy cell line (COS-7), where complex 1 exhibited the best activity, with IC50 values going from 4.56 to 4.78 μM. These studies where further complemented with DNA docking theoretical calculations and DNA affinity experiments.Lysyl oxidase-like 2 (LOXL2) is a copper-dependent amine oxidase that catalyzes the oxidative deamination of the ε-amino group of lysines/hydroxylysines on substrate proteins (collagen and elastin) to form aldehyde groups. The generated aldehyde groups are of significance in crosslinking with the adjacent aldehyde or ε-amino group on proteins in extracellular matrix. In this paper, we have studied the reaction mechanism of LOXL2 by means of quantum mechanics (QM) and combined QM and molecular mechanics (QM/MM) methods. This study is divided into two parts, i.e. the biosynthesis of lysine tyrosylquinone (LTQ) cofactor and oxidative deamination of ε-amino group of lysine by LTQ. For the former part, the reaction is driven by a large exothermicity of about 284 kJ/mol. Dopaquinone radical (DPQr) is suggested to be an intermediate state in this reaction. In addition, His652 residue is predicted to serve as proton acceptor. The rate-determining step for the biosynthesis of LTQ is found to be hydrogen-atom abstraction from the benzene ring on substrate by Cu2+-hydroxide, which is a proton-coupled electron transfer (PCET) process with an energy barrier of 84 kJ/mol. For the latter part, the reaction is exothermic by about 145 kJ/mol, and the copper ion is proposed to play a role of redox catalyst in the last step to generate the product of aldehyde. However, the copper ion might not be indispensable for the latter part, which is consistent with the previous study.At present, the majority of the proposed Deep Learning (DL) methods provide point predictions without quantifying the model's uncertainty. However, a quantification of the reliability of automated image analysis is essential, in particular in medicine when physicians rely on the results for making critical treatment decisions. In this work, we provide an entire framework to diagnose ischemic stroke patients incorporating Bayesian uncertainty into the analysis procedure. We present a Bayesian Convolutional Neural Network (CNN) yielding a probability for a stroke lesion on 2D Magnetic Resonance (MR) images with corresponding uncertainty information about the reliability of the prediction. For patient-level diagnoses, different aggregation methods are proposed and evaluated, which combine the individual image-level predictions. Those methods take advantage of the uncertainty in the image predictions and report model uncertainty at the patient-level. In a cohort of 511 patients, our Bayesian CNN achieved an accuracy of 95.33% at the image-level representing a significant improvement of 2% over a non-Bayesian counterpart. The best patient aggregation method yielded 95.89% of accuracy. Integrating uncertainty information about image predictions in aggregation models resulted in higher uncertainty measures to false patient classifications, which enabled to filter critical patient diagnoses that are supposed to be closer examined by a medical doctor. We therefore recommend using Bayesian approaches not only for improved image-level prediction and uncertainty estimation but also for the detection of uncertain aggregations at the patient-level.

A routinely collected big data set was analyzed to determine the effectiveness of naturalistic inpatient treatment and to identify predictors of treatment outcome and discontinuation.

The sample included 878 patients with borderline personality disorder who received non-manualized dialectic behavioral therapy in a psychosomatic clinic. Effect sizes (Hedge's g) were calculated to determine effectiveness. A bootstrap-enhanced regularized regression with 91 potential predictors was used to identify stable predictors of residualized symptom- and functional change and treatment discontinuation. learn more Results were validated in a holdout sample and repeated cross validation.

Effect sizes were small to medium (g=0.28-0.51). Positive symptom-related outcome was predicted by low affect regulation skills and no previous outpatient psychotherapy. Lower age, absence of work disability, high emotional and physical role limitations and low bodily pain were associated with greater improvement in functional outcome. Higher education and comorbid recurrent depressive disorder were the main predictors of treatment completion. The predictive quality of the models varied, with the best being found for symptom-related outcome (R

=18%).

While the exploratory process of variable selection replicates previous findings, the validation results suggest that tailoring treatment to the individual patient might not be based solely on sociodemographic, clinical and psychological baseline data.

While the exploratory process of variable selection replicates previous findings, the validation results suggest that tailoring treatment to the individual patient might not be based solely on sociodemographic, clinical and psychological baseline data.To maximize desired products in engineered cellular factories it is often necessary to optimize metabolic flux. While a number of works have focused on metabolic pathway enhancement through genetic regulators and synthetic scaffolds, these approaches require time-intensive design and optimization with limited versatility and capacity for scale-up. Recently, nucleic-acid nanotechnology has emerged as an encouraging approach to overcome these limitations and create systems for modular programmable control of metabolic flux. Using toehold-mediated strand displacement (TMSD), nucleic acid constructs can be made into dynamic devices that recognize specific biomolecular triggers for conditional control of gene regulation as well as design of dynamic synthetic scaffolds. This review will consider the various approaches that have been used thus far to control metabolic flux using toehold-gated devices.

This study examined the association between changing family relationships (marital relationships and parent-child relationships) and adolescents' mental health in transitional China. It further explored the potential moderating role of living arrangements in the abovementioned associations.

The study design used in the study is a longitudinal study.

Data were derived from wave 1 (academic year 2013-2014, grade 7) and wave 2 (academic year 2014-2015, grade 8) of the China Education Panel Survey (CEPS). We used fixed-effects models in the longitudinal data analysis (N=7237).

Descriptive analysis indicated significant changes in both adolescents' mental health and self-reported family relationships during the transition from grade 7 to grade 8. The fixed-effects models showed that high marital quality and close parent-child relationships improved the mental health of adolescents. Interaction analysis suggested that paternal living arrangements significantly moderated the association between the father-child relationships and adolescents' mental health effects of the father-child relationships were weaker among those living away from their biological fathers than among those living with their biological fathers.