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Apicomplexan parasites are important pathogens of humans and domestic animals, including Plasmodium species (the agents of malaria) and Toxoplasma gondii, which is responsible for toxoplasmosis. They replicate within the cells of their animal hosts, to which they gain access using a unique parasite-driven invasion process. At the core of the invasion machine is a structure at the interface between the invading parasite and host cell called the moving junction (MJ)

To identify and analyze training programs in shared decision-making (SDM) for health professionals.We conducted an environmental scan looking for programs that train health professionals in SDM. Pairs of reviewers independently analyzed the programs identified using a standardized data extraction sheet. The developers of the programs validated the data extracted.We identified 54 programs conducted between 1996 and 2011 in 14 countries and 10 languages. Thirty-four programs targeted licensed health professionals, 10 targeted pre-licensure health professionals, and 10 targeted both. Most targeted only the medical profession (n=32); six targeted more than one health profession. The five most frequently mentioned teaching methods were case-based discussion, small group educational session, role play, printed educational material, and audit and feedback. Thirty-six programs reported having evaluated their impacts but evaluation data was available only for 17.Health professional training programs in SDM vary widely in how and what they deliver, and evidence of their effectiveness is sparse.This study suggests there is a need for international consensus on ways to address the variability in SDM training programs. We need agreed criteria for certifying the programs and for determining the most effective types of training.

The topographic features of the free energy landscapes that govern the thermodynamics and kinetics of conformational transitions in proteins, which in turn are integral for function, are not well understood. This reflects the experimental challenges associated with characterizing these multidimensional surfaces, even for small proteins. Here we focus on a 62-residue protein, gpW, that folds very rapidly into a native structure with an α/β topology in which α-helices are at the N- and C-terminal ends of the molecule with a central β-hairpin positioned orthogonally to the helices. Using relaxation dispersion NMR spectroscopy to probe the conformational fluctuations in gpW at 1 °C, we found that the native state interconverts with a transiently formed, sparsely populated second state with a lifetime of 250 μs, consistent with the global folding-unfolding rate under these conditions. In this low-populated state, the β-hairpin is unfolded whereas the α-helices remain predominantly formed. Our results argue for a hierarchical stability of secondary structural elements and demonstrate the existence of a complex free energy landscape even in this small, fast-folding single-domain protein.

While several risk stratification tools have been developed to predict the risk of recurrence in patients with an unprovoked venous thromboembolism (VTE), only 1 in 4 patients are categorized as low-risk. Rather than a one-time measure, serial D-dimer assessment holds promise to enhance the prediction of VTE recurrence after oral anticoagulant (OAC) cessation.Using the REVERSE cohort, we compared VTE recurrence among patients with normal D-dimer levels (490 ng/mL among males under age 70,500 ng/mL in others) at OAC cessation and 1-month follow-up, to those with an elevated D-dimer level at either timepoint. We also evaluated VTE recurrence based on absolute increase in D-dimer levels between the two timepoints (e.g., ∆D-dimer) according to quartiles.Among 214 patients with serial D-dimer levels measured at OAC cessation and 1-month follow-up, an elevated D-dimer level at either timepoint was associated with a numerically higher risk of recurrent VTE than patients with normal D-dimer levels at both timepoints (6.9 % vs. 4.2 % per year, hazard ratio 1.6; 95 % CI 0.9-2.7). Among women with2 HERDOO2 criteria, a normal D-dimer level at both timepoints predicted a very low risk of recurrent VTE during follow-up (0.8 % per year, 95 % CI 0.1-2.8). Irrespective of baseline value, recurrent VTE risk was only 3 % per year (95 % CI 1.4-5.6) among patients in the lowest ∆D-dimer quartile.Serial normal D-dimer levels have the potential to identify patients at a low risk of recurrent VTE. In addition, ∆D-dimer, irrespective of its elevation above cutoff threshold, may predict recurrent VTE.

OBJECTIVE The aim of this study was to determine an optimal follow-up imaging surveillance strategy in terms of cost-effectiveness after resection of nonfunctioning pituitary adenomas with curative intent. METHODS An individual-level state-transition microsimulation model was used to simulate costs and outcomes associated with three postoperative imaging strategies over a lifetime time horizon: 1) annual MRI surveillance, 2) tapered MRI surveillance (annual surveillance for 5 years followed by surveillance every 2 years), and 3) personalized surveillance (annual surveillance for 5 years followed by surveillance every 2 years when MRI shows remnant disease/postoperative changes, and surveillance at 7, 10, and 15 years for disease-free MRI). Transition probabilities, utilities, and costs were estimated from recent published data and discounted by 3% annually. Model outcomes included lifetime costs (2022 US dollars), quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs). RESULTS Under base case assumptions, annual surveillance yielded higher costs and lower health effects (QALYs) compared with the tapered and personalized surveillance strategies (dominated). Personalized surveillance demonstrated an additional 0.1 QALY at additional cost ($1298) compared with tapered surveillance (7.7 QALYs at a cost of $12,862). The ICER was $11,793/QALY. The optimal decision was most sensitive to the probability of postoperative changes on MRI after surgery and MRI cost. Accounting for parameter uncertainty, personalized surveillance had a higher probability of being a cost-effective surveillance option compared with the alternative strategies at 79%. CONCLUSIONS Using standard cost-effectiveness thresholds in the US ($100,000/QALY), personalized surveillance that accounted for remnant disease or postoperative changes on MRI was cost-effective compared with alternative surveillance strategies.

Warning labels are an important source of health information. This study examined awareness of health warnings on cannabis packages over time in Canada-where large rotating messages are mandated-versus US states with legal adult-use cannabis, which have less comprehensive regulations.Repeat cross-sectional data were collected from the International Cannabis Policy Study online surveys among past 12-month cannabis consumers in Canada and the US (Free recall of ≥1 warning increased to a greater extent in Canada from 2018 (5%; pre-legalization) to 2019 (13%; post-legalization) compared to US "legal" (AOR = 1.93,Cannabis legalization is associated with greater recall of health warning messages. Awareness of specific warning messages was higher in jurisdictions where the associated warning was mandated on packages, suggesting that warning labels may improve knowledge of cannabis-related health risks.Supplemental data for this article is available online at.

Alzheimer's disease (AD) is linked to the abnormal accumulation of amyloid β peptide (Aβ) aggregates in the brain. Silybin B, a natural compound extracted from milk thistle (

Machine learning (ML) methods are increasingly used in addition to conventional statistical modelling (CSM) for predicting readmission and mortality in patients with myocardial infarction (MI). However, the two approaches have not been systematically compared across studies of prognosis in patients with MI.Following PRISMA guidelines, we systematically reviewed the literature via Medline, EPub, Cochrane Central, Embase, Inspec, ACM Digital Library, and Web of Science. Eligible studies included primary research articles published from January 2000 to March 2020, comparing ML and CSM for prognostication after MI.Of 7,348 articles, 112 underwent full-text review, with the final set composed of 24 articles representing 374,365 patients. ML methods included artificial neural networks (n = 12 studies), random forests (n = 11), decision trees (n = 8), support vector machines (n = 8), and Bayesian techniques (n = 7). CSM included logistic regression (n = 19 studies), existing CSM-derived risk scores (n = 12), and Cox regression (n = 2). Thirteen of 19 studies examining mortality reported higher C-indexes with the use of ML compared with CSM. One study examined readmissions at 2 different time points, with C-indexes that were higher for ML than CSM. Across all studies, a total of 29 comparisons were performed, but the majority (n = 26, 90%) found small (0.05) absolute differences in the C-index between ML and CSM. With the use of a modified CHARMS checklist, sources of bias were identifiable in the majority of studies, and only 2 were externally validated.Although ML algorithms tended to have higher C-indexes than CSM for predicting death or readmission after MI, these studies exhibited threats to internal validity and were often unvalidated. Further comparisons are needed, with adherence to clinical quality standards for prognosis research. (Trial registration: PROSPERO CRD42019134896).