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Three out of nine patients (33%) were ES free after two months of treatment. Parents reported subjective improvements in cognitive and behavioral domains. Side effects, primarily drowsiness, were seen in 89% of patients (n = 8). Eight of the nine (89%) patients had electroencephalographic (EEG) studies prior to and after initiation of CBD. Three out of five patients (60%) had resolution in their hypsarrhythmia pattern. SIGNIFICANCE Purified pharmaceutical CBD may be an effective and safe adjunctive therapy in refractory ES and may also be associated with improvements in electrographic findings. OBJECTIVES The main aim of this study was to assess the effectiveness of cognitive behavior therapy (CBT) for comorbid dissociative seizures (DS) in patients with epilepsy. METHODS We conducted a retrospective case note review of 14 patients with epilepsy who underwent outpatient CBT for DS in a tertiary neuropsychiatry service. The diagnosis of DS was confirmed by neurologists clinically and/or following video-telemetry electroencephalogram (EEG). We evaluated the outcome of the CBT treatment with respect to frequency of DS, measures of depression, anxiety, and social functioning. RESULTS Measures of depression and anxiety significantly reduced following CBT treatment. Overall, frequency of DS reduced following CBT treatment but did not reach statistical significance. SIGNIFICANCE This study provides evidence that CBT can be effective in reducing depression and anxiety in patients with both epilepsy and DS. Anxiety and depression are likely to be associated with DS. Further research in larger samples and longitudinal studies are recommended to evaluate the long-term efficacy of CBT in this patient group. BACKGROUND Little is known about the association of metabolic syndrome (MetS) and quality of life (QoL) in people with epilepsy (PWE). We evaluate the trends of MetS in PWE across various age groups. We also evaluate the association of MetS and QoL in PWE. METHODS Clinical and seizure data were collected in 173 people with controlled epilepsy. Physical fitness was assessed by using the six-minute walk test and one-minute step test. Self-reported SF-12 questionnaire, was used to derive physical (PCS) and mental (MCS) component scores. RESULTS The average age of the study population was 25.85 ± 9.62 years, and MetS was observed in 91 (52.6%). Obesity was seen in 153 (88.4%). Average distance walked in the six-minute walk test was 385.55 ± 71.52 m. Mean PCS and MCS were 45.95 ± 7.92 and 45.72 ± 10.40, respectively. More number of women had MetS (47.6% vs. 62.6%; p = 0.049) and women in the study population had lower high-density lipoprotein (HDL)-C (44.34 ± 11.60 vs. 38.65 ± 10.13 mm Hg; p 40 years. CONCLUSION Metabolic syndrome is seen in more than half of PWE, and this increased prevalence is not associated with the number of antiepileptic medicines. While prevalence of MetS was stable at 50.0% across all age groups, components of MetS have varying prevalence across age groups hence, suggesting their varied contribution across age groups. OBJECTIVE To evaluate the performance of machine learning (ML) algorithms and to compare them to logistic regression for the prediction of risk of cardiovascular diseases (CVD), chronic kidney disease (CKD), diabetes (DM), and hypertension (HTN) and in a prospective cohort study using simple clinical predictors. STUDY DESIGN AND SETTING We conducted analyses in a population-based cohort study in Asian adults (n=6,762). Five different ML models were considered single-hidden-layer neural network, support vector machine, random forest, gradient boosting machine and k-nearest neighbour, and were compared to standard logistic regression. RESULTS The incidences at 6-year of CVD, CKD, DM, and HTN cases were 4.0%, 7.0%, 9.2%, and 34.6%, respectively. Logistic regression reached the highest AUC for CKD (0.905 [0.88, 0.93]) and DM (0.768 [0.73, 0.81]) predictions. For CVD and HTN, the best models were neural network (0.753 [0.70, 0.81]) and support vector machine (0.780 [0.747, 0.812]), respectively. However, the differences with logistic regression were small (less than 1%) and non-significant. Logistic regression, gradient boosting machine and neural network were systematically ranked among the best models. CONCLUSION Logistic regression yields as good performance as ML models to predict the risk of major chronic diseases with low incidence and simple clinical predictors. OBJECTIVE Help educators address misconceptions about P-values and provide a tool that can be used to teach a more contemporary interpretation. DESIGN and Setting A scripted tutorial utilizing problem-based learning and a diagnostic test analogy to deconstruct the misunderstandings about P-values and develop a more Bayesian approach to study interpretation. RESULTS A diagnostic test analogy is an effective teaching tool. Learners' understanding of Bayes' theorem in diagnostic testing can be used as a bridge to the realization that the pre-study probability of a true difference is crucial for study interpretation. The analogy has several caveats and shortcomings. The limitations of this analogy and the conceptual difficulties with the Bayesian study analyses are addressed. CONCLUSIONS P-values do not provide the information many assume they do - they are not equivalent to a probability of a chance finding. This tutorial helps move learners from these incorrect notions to new insights. Product packaging is an important instrument for marketers to draw consumer attention to specific product information and influence product perceptions. ALLN supplier The purpose of this research is to investigate whether exposure to a product's packaging can also activate specific mindsets that, once activated, alter consumers' food perceptions. The results of three experiments demonstrate that elongated containers activate a health mindset that influences both consumers' perception of the packaged food product but also their health perceptions of subsequently encountered food. Specifically, foods in elongated containers lead consumers to think of concepts related to healthiness, which have differentiable effects on subsequent healthy and unhealthy food products. Vegetables are an important but under consumed part of a healthy diet. There is growing interest in promoting vegetable acceptance and consumption among infants to help establish life-long healthy eating patterns. A recent survey of commercial baby food products in the United States by Moding and colleagues revealed a lack of variety in the types of vegetables offered. Most notably, there were no commercially available single, dark green vegetable products. Instead, dark green vegetables were often mixed with fruits or red/orange vegetables (e.g., squash) that provide additional sweetness. In order for liking for vegetables to be learned, the flavors from the vegetables must still be perceptible within the mixture. Thus, the objective of the research reported here was to understand the sensory profiles of vegetable-containing Stage 2 infant products commercially available in the United States and how ingredient composition affects flavor profiles. We performed descriptive analysis to quantitatively profile the sensory properties of 21 commercial vegetable-containing infant foods and one prepared in our laboratory. Eleven experienced panelists participated in 14.5 h of lexicon generation and training prior to rating all 22 products (in triplicate) for 14 taste, flavor, and texture attributes. Products that contained fruit were not only sweeter than products that did not contain fruit but were also higher in fruit flavors and lower in vegetable flavors. In general, sensory profiles were driven by the first ingredient in the product. Because few products had dark green vegetables as a first ingredient, dark green vegetable flavor was not prevalent in this category. This suggests the sensory profiles of commercially available infant vegetables foods may not be adequate to facilitate increased acceptance of green vegetables. Based on structure analyses of butyrylcholinesterase (BChE), a series of 21 acridone glycosides were designed, synthesized and evaluated in vitro for their BChE and acetylcholinesterase (AChE) inhibitory activities. d-ribose derivative 6f exhibited the greatest inhibitory activity on BChE (IC50 = 6.95 μM), and was the most selective inhibitor of BChE with the IC50 ratio of AChE/BChE was 20.59. d-glucose and d-galactose derivatives 6a and 6b showed inhibitory activities against both AChE and BChE. Moreover, compounds 6a, 6b, 6f and 5t were found nontoxic on SHSY5Y neuroblastoma and HepG2 cell and exhibited remarkable neuroprotective activity. Besides, compound 6f showed mixed-type inhibition against BChE (Ki = 1.76 μM), which renders 6f a potential agent for the treatment of Alzheimer's disease. These novel acridone hybrids might be used as efficient probes to reveal the relationship between ligands and BChE and pave the way for developing selective BChE inhibitors to further study the pathogenesis of alzheimer's disease. Membrane proteins exist in lipid bilayers and mediate solute transport, signal transduction, cell-cell communication and energy conversion. Their activities are fundamental for life, which make them prominent subjects of study, but access to only a limited number of high-resolution structures complicates their mechanistic understanding. The absence of such structures relates mainly to difficulties in expressing and purifying high quality membrane protein samples in large quantities. An additional layer of complexity stems from the presence of intra- and/or extra-cellular domains constituted by unstructured intrinsically disordered regions (IDR), which can be hundreds of residues long. Although IDRs form key interaction hubs that facilitate biological processes, these are regularly removed to enable structural studies. To advance mechanistic insight into intact intrinsically disordered membrane proteins, we have developed a protocol for their purification. Using engineered yeast cells for optimized expression and purification, we have purified to homogeneity two very different human membrane proteins each with >300 residues long IDRs; the sodium proton exchanger 1 and the growth hormone receptor. Subsequent to their purification we have further explored their incorporation into membrane scaffolding protein nanodiscs, which will enable future structural studies. Pyroptosis, a form of programmed cell death, has garnered increasing attentions as it relates to innate immunity and diseases. The discovery of caspase-1/3/4/5/8/11 function in sensing various challenges expands the spectrum of pyroptosis mediators and also reveals that pyroptosis is not cell type specific. Recent studies identified that pyroptosis could be chemically mediated cancer development. In this mini-review, we provided a primer on pyroptosis and discussed the induction of pyroptosis in cancer and its implications in cancer management. Moreover, its two important executioners, the gasdermin D (GSDMD) and gasdermin E (GSDME), and the functions and mechanisms of them in the regulation in cancer therapy were focused on. Small molecules-mediated pyroptosis were found to effectively inhibit various tumor cells. In brief, the findings of pyroptosis-dependent cancer progression, new drugs and therapeutic target may lead to a promising, novel therapeutic approach for cancer patients. V.

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