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4 percentage point reduced risk of relapse [95% confidence interval (CI)=-12.0, 5.3] comparing XR-NTX to BUP-NX (explaining 21% of the total effect). For the non-homeless subgroup, the indirect path contributed a 9.4 percentage point increased risk of relapse (95% CI=3.1, 15.7) comparing XR-NTX to BUP-NX (explaining 57% of the total effect).

A novel approach to mediation analysis shows that much of the difference in medication effectiveness (extended-release naltrexone versus buprenorphine-naloxone) on opioid relapse among non-homeless adults with opioid use disorder appears to be explained by mediators of adherence, illicit opioid use, depressive symptoms and pain.

A novel approach to mediation analysis shows that much of the difference in medication effectiveness (extended-release naltrexone versus buprenorphine-naloxone) on opioid relapse among non-homeless adults with opioid use disorder appears to be explained by mediators of adherence, illicit opioid use, depressive symptoms and pain.The deviation between chronological age and age predicted using brain MRI is a putative marker of overall brain health. Age prediction based on structural MRI data shows high accuracy in common brain disorders. However, brain aging is complex and heterogenous, both in terms of individual differences and the underlying biological processes. Here, we implemented a multimodal model to estimate brain age using different combinations of cortical area, thickness and sub-cortical volumes, cortical and subcortical T1/T2-weighted ratios, and cerebral blood flow (CBF) based on arterial spin labeling. For each of the 11 models we assessed the age prediction accuracy in healthy controls (HC, n = 750) and compared the obtained brain age gaps (BAGs) between age-matched subsets of HC and patients with Alzheimer's disease (AD, n = 54), mild (MCI, n = 90) and subjective (SCI, n = 56) cognitive impairment, schizophrenia spectrum (SZ, n = 159) and bipolar disorder (BD, n = 135). We found highest age prediction accuracy in HC when integrating all modalities. Furthermore, two-group case-control classifications revealed highest accuracy for AD using global T1-weighted BAG, while MCI, SCI, BD and SZ showed strongest effects in CBF-based BAGs. Combining multiple MRI modalities improves brain age prediction and reveals distinct deviations in patients with psychiatric and neurological disorders. The multimodal BAG was most accurate in predicting age in HC, while group differences between patients and HC were often larger for BAGs based on single modalities. These findings indicate that multidimensional neuroimaging of patients may provide a brain-based mapping of overlapping and distinct pathophysiology in common disorders.Root Cause Analysis and Action (RCA2 ) guidelines offer fundamental improvements to traditional RCA. Yet, these guidelines lack robust methods to support a human factors analysis of patient harm events and development of systems-level interventions. We recently integrated a complement of human factors tools into the RCA2 process to address this gap. These tools include the Human Factors Analysis and Classification System (HFACS), the Human Factors Intervention Matrix (HFIX), and a multiple-criterion decision tool called FACES, for selecting effective HFIX solutions. We describe each of these tools and illustrate how they can be integrated into RCA2 to create a robust human factors RCA process called HFACS-RCA2 . We also present qualitative results from an 18-month implementation study within a large academic health center. Results demonstrate how HFACS-RCA2 can foster a more comprehensive, human factors analysis of serious patient harm events and the identification of broader system interventions. Following HFACS-RCA2 implementation, RCA team members (risk managers and quality improvement advisors) also experienced greater satisfaction in their work, leadership gained more trust in RCA findings and recommendations, and the transparency of the RCA process increased. Effective strategies for overcoming implementation barriers, including changes in roles, responsibilities and workload will also be presented.The present study focuses on the quantitative phase imaging of erythrocytes with the aim to compare the morphological differences between epilepsy patients under antiepileptic treatment, who have no other disease which may affect the erythrocyte morphology, and the healthy control group. The white light diffraction phase microscopy (WDPM) has been used to obtain the interferogram of the erythrocyte surfaces. The continuous wavelet transform with Paul wavelet has been chosen to calculate the surface profiles from this interferogram image. For the determination of alteration in morphology, besides WDPM, erythrocyte surfaces have been investigated by light microscope and scanning electron microscope. In this way, it has been possible to see the difference in terms of precision and implementation between the most commonly used methods with regard to the quantitative phase imaging. Erythrocytes from all the samples have been examined and displayed in both two- and three-dimensional way. We have observed that erythrocytes of patients with effective antiepileptic blood levels were more affected in morphology than healthy subjects. When we compared the erythrocyte morphological changes of patients who received monotherapy or polytherapy, no difference was observed. In conclusion, antiepileptic drugs (AEDs) cause red blood cell (RBC) morphological changes and a combined usage of WDPM with Paul wavelet and light microscopy methods are very convenient for studying the erythrocyte morphologies on multiple patients.Cancer metabolism is influenced by availability of nutrients in the microenvironment and can to some extent be manipulated by dietary modifications that target oncogenic metabolism. Epigenetic high throughput screening As yet, few dietary interventions have been scientifically proven to mitigate disease progression or enhance any other kind of therapy in human cancer. However, recent advances in the understanding of cancer metabolism enable us to predict or devise effective dietary interventions that might antagonize tumor growth. In fact, evidence emerging from preclinical models suggests that appropriate combinations of specific cancer therapies with dietary interventions could critically impact therapeutic efficacy. Here, we review the potential benefits of precision nutrition approaches in augmenting the efficacy of cancer treatment.