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A Fruit and Vegetable Prescription program (12–16 weeks, 2018–2020) was implemented at community health centers serving rural communities in the northwestern United States. The impact of the program on type 2 diabetes control was evaluated. Reductions in mean hemoglobin A1C were statistically significant (P 9%) decreased from 76% (114/151) to 41% (62/151; P

Machine-learned coarse-grained (CG) models have the potential for simulating large molecular complexes beyond what is possible with atomistic molecular dynamics. However, training accurate CG models remains a challenge. A widely used methodology for learning CG force-fields maps forces from all-atom molecular dynamics to the CG representation and matches them with a CG force-field on average. We show that there is flexibility in how to map all-atom forces to the CG representation, and that the most commonly used mapping methods are statistically inefficient and potentially even incorrect in the presence of constraints in the all-atom simulation. We define an optimization statement for force mappings and demonstrate that substantially improved CG force-fields can be learned from the same simulation data when using optimized force maps. The method is demonstrated on the miniproteins Chignolin and Tryptophan Cage and published as open-source code., Comment: 44 pages, 19 figures

Jean Lachaine,1,2 Jean-Nicolas Charron,2 Jean C Gregoire,3 Robert A Hegele,4 Lawrence A Leiter5 1University of Montreal, Montreal, QC, Canada; 2PeriPharm Inc., Montreal, QC, Canada; 3Institut de cardiologie de Montréal, Montreal, QC, Canada; 4Robarts Research Institute, London, ON, Canada; 5Li Ka Shing Knowledge Institute, St. Michael’s Hospital, University of Toronto, Toronto, ON, CanadaCorrespondence: Jean Lachaine, Faculty of Pharmacy University of Montreal, 2900 Edouard-Montpetit Blvd, Montreal, Quebec, H3T 1J4, Canada, Email jean.lachaine@umontreal.caBackground: Despite the use of statins, many patients with cardiovascular disease (CVD) have persistent residual risk. In a large Phase III trial (REDUCE-IT), icosapent ethyl (IPE) was shown to reduce the first occurrence of the primary composite endpoint of cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, coronary revascularization, or hospitalization for unstable angina.Methods: We conducted a cost-utility analysis comparing IPE to placebo in statin-treated patients with elevated triglycerides, from a publicly funded, Canadian healthcare payer perspective, using a time-dependent Markov transition model over a 20-year time horizon. We obtained efficacy and safety data from REDUCE-IT, and costs and utilities from provincial formularies and databases, manufacturer sources, and Canadian literature sources.Results: In the probabilistic base-case analysis, IPE was associated with an incremental cost of $12,523 and an estimated 0.29 more quality-adjusted life years (QALYs), corresponding to an incremental cost-effectiveness ratio (ICER) of $42,797/QALY gained. At a willingness-to-pay of $50,000 and $100,000/QALY gained, there is a probability of 70.4% and 98.8%, respectively, that IPE is a cost-effective strategy over placebo. The deterministic model yielded similar results. In the deterministic sensitivity analyses, the ICER varied between $31,823-$70,427/QALY gained. Scenario analyses revealed that extending the timeframe of the model to a lifetime horizon resulted in an ICER of $32,925/QALY gained.Conclusion: IPE represents an important new treatment for the reduction of ischemic CV events in statin-treated patients with elevated triglycerides. Based on the clinical trial evidence, we found that IPE could be a cost-effective strategy for treating these patients in Canada.Keywords: cardiovascular diseases, icosapent ethyl, IPE, cost-effectiveness, cost per QALY

A leading cancer diagnosis in women worldwide is cervical cancer, with current treatments all posing a risk of serious side effects. Less toxic, but effective treatments are sought after. Aloe vera ( barbadensis miller), known for its beneficial properties, has been studied for cancer treatment. While aloe gel has been shown to exhibit anti-cancer activity, it cannot form a hydrogel alone. Therefore, an interpenetrating network comprising alginate blended with aloe was examined as a cervical cancer treatment. We hypothesized the antioxidant properties of aloe gel would decrease cancer cell viability while the alginate hydrogel would improve mucoadhesion. We further hypothesized the antioxidant activity of aloe gel would induce cancer cell death at levels similar to common chemotherapeutics, and aimed to determine if these chemotherapeutic behaviors are constructive or destructive. Material and adhesive properties, drug encapsulation, and cancer cell viability were investigated and validated. The effect of aloe-alginate hydrogels on cervical cancer cell viability was not significantly different compared to aloe-blends containing doxorubicin (DOX), indicating that the aloe alone decreased cancer cell viability rendering the additional cytotoxic therapeutic not impactful as an adjuvant therapy. This study provides insight into the potential of natural biopolymers for treating cervical cancer without systemic toxic compounds.

Ultra-high performance concrete (UHPC) is being increasingly used as a thin overlay for deficient normal strength concrete (NSC) structural elements. Compared to reinforced NSC elements, hybrid NSC-UHPC elements have two stages' structural behaviour under high shear load before failure: monolithic action followed by a composite mechanical action. The composite mechanical action gives to hybrid elements a structural hardening capability after the occurrence of a diagonal shear crack and is not yet considered by most design standards. Two analytical models for hybrid elements under shear load are thus proposed to predict the shear resistance V R of the monolithic action and to predict the structural hardening resistance V Rsh of the composite mechanical action. The shear resistance model integrates the UHPC contribution in the estimation of the tensile strain at mid-height cross-section according to the general method of the Canadian code. The structural hardening behaviour is reproduced with a strut-and-tie system with plastic hinges, where the failure is controlled by the crushing of a concrete strut. Predictions of the proposed models are in very good agreement with 31 hybrid elements experimental results retrieved from the literature.

The ability of a stochastically perturbed parameterization (SPP) approach to represent uncertainties in the model component of the Canadian Global Ensemble Prediction System was demonstrated in Part I of this investigation. The goal of this second step in SPP evaluation is to determine whether the scheme represents a viable alternative to the current operational combination of a multiphysics configuration and stochastically perturbed parameterization tendencies (SPPT). An assessment of the impact of each model uncertainty estimate in isolation reveals that, although the multiphysics configuration is highly effective at generating ensemble spread, it is often the result of differing biases rather than a reflection of flow-dependent error growth. Moreover, some of the members of the multiphysics ensemble suffer from large errors on regional scales as a result of suboptimal configurations. The SPP scheme generates a greater diversity of member solutions than the SPPT scheme in isolation, and it has an impact on forecast performance that is similar to that of current operational uncertainty estimates. When the SPP framework is combined with recent upgrades to the model physics suite that are only applicable in the stochastic perturbation context, the quality of global ensemble guidance is significantly improved. Significance Statement The stochastically perturbed parameterization (SPP) technique was introduced in Part I to represent model uncertainties in forecasts generated by an operational global ensemble prediction system. We focus here on the viability of this technique as a replacement for the system’s current uncertainty estimates: multiphysics and stochastic perturbations of physics tendencies. Despite the practical success of this combination, it suffers from physical inconsistencies and poor conservation properties. The adoption of SPP allows the ensemble to benefit from a recent set of model updates that couple with this new representation of model uncertainty to yield significant improvements in the quality of forecasts generated by the system.

Accurately representing model-based sources of uncertainty is essential for the development of reliable ensemble prediction systems for NWP applications. Uncertainties in discretizations, algorithmic approximations, and diabatic and unresolved processes combine to influence forecast skill in a flow-dependent way. An emerging approach designed to provide a process-level representation of these potential error sources, stochastically perturbed parameterizations (SPP), is introduced into the Canadian operational Global Ensemble Prediction System. This implementation extends the SPP technique beyond its typical application to free parameters in the physics suite by sampling uncertainty both within the dynamical core and at the formulation level using “error models” when multiple physical closures are available. Because SPP perturbs components within the model, internal consistency is ensured and conservation properties are not affected. The full SPP scheme is shown to increase ensemble spread to keep pace with error growth on a global scale. The sensitivity of the ensemble to each independently perturbed “element” is then assessed, with those responsible for the bulk of the response analyzed in more detail. Perturbations to surface exchange coefficients and the turbulent mixing length have a leading impact on near-surface statistics. Aloft, a tropically focused error model representing uncertainty in the advection scheme is found to initiate growing perturbations on the subtropical jet that lead to forecast improvements at higher latitudes. The results of Part I suggest that SPP has the potential to serve as a reliable representation of model uncertainty for ensemble NWP applications. Significance Statement Ensemble systems account for the negative impact that uncertainties in prediction models have on forecasts. Here, uncertain model parameters and algorithms are subjected to perturbations representing impact on forecast errors. By initiating error growth within the model calculations, the equally skillful members of the ensemble remain physically realistic and self-consistent, which is not guaranteed by other depictions of model error. This “stochastically perturbed parameterization” technique (SPP) comprises many small error sources, each analyzed in isolation. Each source is related to a limited set of processes, making it possible to determine how the individual perturbations affect the forecast. We conclude that SPP in the Canadian Global Ensemble Forecasting System produces realistic estimates of the impact of model uncertainties on forecast skill.

En 2016, la mission franco-suisse de Saqqarah a dégagé le péribole de la pyramide de la reine Ânkhnespépy II. Dans l’angle sud-ouest du monument, plus de dix mille ossements de bovidés ont été mis au jour. La découverte de deux momies et d’un naos a permis de comprendre que l’ensemble provient d’une nécropole pillée dans l’Antiquité et non encore repérée. Les momies ont révélé n’être composées que d’ossements, montrant qu’il s’agissait d’animaux sacralisés, peut-être en relation avec le taureau Apis.

© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited., Aims: The interaction between common cardiovascular risk factors (CVRF) and hypertrophic cardiomyopathy (HCM) is poorly studied. We sought to explore the relation between CVRF and the clinical characteristics of patients with HCM enrolled in the EURObservational Research Programme (EORP) Cardiomyopathy registry. Methods and results: 1739 patients with HCM were studied. The relation between hypertension (HT), diabetes (DM), body mass index (BMI) and clinical traits was analyzed. Analyses were stratified according to the presence or absence of a pathogenic variant in a sarcomere gene.The prevalence of HT, DM and obesity (Ob) was 37%, 10%, and 21%, respectively. HT, DM and Ob were associated with older age (p

The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.

Tests are shown to enhance learning: this is known as the "testing effect". The benefit of testing is theorized to be through "active retrieval", which is the effortful process of recalling stored knowledge. This differs from "passive studying", such as reading, which is a low effort process relying on recognition. The testing effect is commonly studied in random word list scenarios and is thought to disappear as complexity of material increases. Little is known about the testing effect in complex situations such as procedural learning. Therefore, we investigated if testing improves procedural learning of fracture fixation as compared to "passive studying".Fifty participants watched an instructional video of an open reduction internal fixation of a Sawbones™ femur. Participants then performed the procedure under guided supervision (pretest). After randomization, they either read the steps (passive studying group), or wrote down the steps from memory (active retrieval group) for a period of 15 minutes. After a washout period, all participants performed the procedure without guidance (posttest) and then once more, 1 week after the initial testing (retention test). The participants were assessed using the Objective Structured Assessment of Technical Skill. Each performance was video recorded for data analysis purposes.Participants in the passive studying group had significantly higher Objective Structured Assessment of Technical Skill scores during immediate assessment compared to the active retrieval group (p = 0.001), especially with respect to remembering the correct order of the steps (p = 0.002). The percentage of information forgotten was significantly less in the active retrieval group (p = 0.02) at the retention test.We demonstrated that, compared to passive studying, testing with active retrieval through writing resulted in better retention of fracture fixation knowledge (i.e., less forgetting). These findings can easily be applied and incorporated in existing curricula. Future studies are needed to determine the effects of different kinds of active retrieval methods such as verbal retrieval (e.g., dictating) in surgical practice.

This qualitative study examined how patient-related factors influence providers' contraceptive counseling for persons with substance use disorders (SUDs). Specifically, we explored individual behavior and social factors that contribute to providers modifying their contraceptive counseling approaches and described how providers alter their counseling recommendations and communication strategies in the presence of such factors.In 2019, we purposively recruited a national sample of contraceptive providers (N = 24) and conducted semistructured phone interviews to inquire about their contraceptive counseling practices for women with SUDs. Interviews were audio recorded, transcribed verbatim, and analyzed using thematic analysis with inductive codes.Participants included 10 medical doctors, 8 nurse practitioners, and 6 certified nurse-midwives. We found that providers modify their contraceptive counseling provision when their patients are actively using substances or have unstable living conditions, such as intimate partner violence or homelessness. With patients experiencing these instabilities, providers reported postponing contraceptive discussions until patients are stabilized in treatment, recommending long-active reversible contraceptive methods, and varying communication styles according to their own perceptions of patients' communication needs. Providers perceived that individuals in long-term recovery have increased stability and fewer barriers to contraceptive access and adherence and therefore reported increased willingness to provide greater autonomy during contraceptive decision making and shift the counseling focus to short-acting contraceptive methods.This study highlights that substance use and social "stability" of patients contributes to how providers approach their contraceptive counseling and make methods recommendations for their patients with SUDs. More research is needed to understand strategies that individuals with SUDs use to overcome barriers to contraceptive access and adherence in the context of active substance use and social instability.

The bacterium Serratia marcescens is an important opportunistic human pathogen that thrives in many environments, can become multidrug resistant, and is often involved in nosocomial outbreaks in neonatal intensive care units (NICU). We evaluated the role of sinks during five suspected S. marcescens outbreaks in a NICU.

This announcement reports the complete genome sequence of a non-Shiga toxin-producing Escherichia coli strain that was isolated from municipal biosolids collected from a Canadian wastewater treatment plant. This strain contains multiple metal, antimicrobial, and heat resistance genes, as determined by genome sequencing, and could be a useful bacterial model for future studies.

International audience; Purpose The prevalence of parental burnout, a condition that has severe consequences for both parents and children, varies dramatically across countries and is highest in Western countries characterized by high individualism.Method In this study, we examined the mediators of the relationship between individualism measured at the country level and parental burnout measured at the individual level in 36 countries (16,059 parents). Results The results revealed three mediating mechanisms, that is, self-discrepancies between socially prescribed and actual parental selves, high agency and self-directed socialization goals, and low parental task sharing, by which individualism leads to an increased risk of burnout among parents.Conclusion The results confirm that the three mediators under consideration are all involved, and that mediation was higher for self-discrepancies between socially prescribed and actual parental selves, then parental task sharing, and lastly selfdirected socialization goals. The results provide some important indications of how to prevent parental burnout at the societal level in Western countries.

Water temperature is an important environmental variable that has impacts on the physical, chemical, and biological processes in streamflows. Extreme river water temperatures affect the spawning, development and survival of several fish species, and are considered as important indicators of the health of a river and essential variables in all habitat models. Unfortunately, river water temperature data is characterised by its limited availability: measurement sites are often scarce, and records are regularly very short when available. It is hence crucial to develop regional thermal data estimation models for ungauged and partially gauged locations. Very few studies in the literature focused on the estimation of extreme water temperatures at sites where thermal data are limited or inexistent. A Temperature-Duration-Curve (TDC) model is proposed in this work to provide real-time estimates of river water temperature at ungauged locations during extreme events. The TDCs are estimated at the ungauged locations using a Generalised Additive Model and are then used to provide continuous estimates of river water temperature at these sites based on a spatial interpolation model. The model is developed based on a data base of 126 river thermal stations from Canada. The performance of the method is compared to a simpler approach and results indicate that the developed TDC model is robust and useful in practice.

As the number of satellite missions observing the ocean increases, reliable and cost-efficient tools are needed to accurately calibrate and validate the expanding network of space sensors. Traditionally, sea surface buoys have been used to measure various oceanic and atmospheric parameters; however, when it comes to subsatellite data related to processes occurring in the upper ocean layer, the use of traditional buoys is not always straightforward. The properties of different sensing bands, acquisition rates, sensor time and spatial resolution must be taken into account to properly match satellite remote signals with in-situ buoy measurements. This necessitates the creation of specialized sensors dedicated to measuring sea surface parameters, such as directional wave spectrum, sea surface current, and temperature, that have the most significant impact on remote sensing signal formation.The Miniaturized Electronics Lagrangian Oceanographic Drifter (MELODI) program has developed a specialized electronic platform that enables the rapid construction of miniaturized, cost-effective sea surface drifters for subsatellite calibration/validation tasks. The hardware can be configured with different set of onboard sensors, data preprocessing/compression modules, and satellite-enabled communication systems to allow for the real-time collection and transmission of data. Preference is given to the extensive use of environmental-friendly and biodegradable materials, as well as to the implementation of an industrial fabrication process to reduce the time and costs of mass buoy production.Our study addresses the specificity of measurements obtained from small-scale platforms, such as directional wave spectrum distortions due to intrinsic noise, reduction of wind impact on the buoy drift, oceanographic data preprocessing and compression for IOT small satellite messaging, etc. We present the first results of an in-situ validation campaign (7 day long) for a buoy created specifically for cal/val of the Surface Water and Ocean Topography (SWOT) mission. This miniaturized drifter (~15 cm in diameter) has onboard accelerometers, gyroscopes, magnetometer, GPS sensors and is dedicated to the systematical measurement of significant wave height, directional wave spectrum and sea surface current. The satellite-based communications allow real-time reporting every 15 min, with an expected autonomy of 2 months up to 1 year depending on the configuration and reporting frequency.We expect that the present results, electronic platform, and proposed algorithmic and technical solutions will allow enabling the development and implementation of a more robust network of observational drifting buoys for calibration and validation of ocean monitoring satellite missions. The work was supported by the project “Development of marine services using space data and IOT technologies by Kinéis” funded by IFREMER and Kinéis.

Mirror movements (MM) disorder is characterized by involuntary movements on one side of the body that mirror intentional movements on the opposite side. We performed genetic characterization of a family with autosomal dominant MM and identified ARHGEF7 , a RhoGEF, as a candidate MM gene. We found that Arhgef7 and its partner Git1 bind directly to Dcc. Dcc is the receptor for Netrin-1, an axon guidance cue that attracts commissural axons to the midline, promoting the midline crossing of axon tracts. We show that Arhgef7 and Git1 are required for Netrin-1–mediated axon guidance and act as a multifunctional effector complex. Arhgef7/Git1 activates Rac1 and Cdc42 and inhibits Arf1 downstream of Netrin-1. Furthermore, Arhgef7/Git1, via Arf1, mediates the Netrin-1–induced increase in cell surface Dcc. Mice heterozygous for Arhgef7 have defects in commissural axon trajectories and increased symmetrical paw placements during skilled walking, a MM-like phenotype. Thus, we have delineated how ARHGEF7 mutation causes MM.

Transposable elements (TEs) are major contributors to structural genomic variation by creating interspersed duplications of themselves. In return, structural variants (SVs) can affect the genomic distribution of TE copies and shape their load. One long-standing hypothesis states that hybridization could trigger TE mobilization and thus increase TE load in hybrids. We previously tested this hypothesis by performing a large-scale evolution experiment by mutation accumulation (MA) on multiple hybrid genotypes within and between wild populations of the yeastsSaccharomyces paradoxusandSaccharomyces cerevisiae. Using aggregate measures of TE load with short-read sequencing, we found no evidence for TE load increase in hybrid MA lines. Here, we resolve the genomes of the hybrid MA lines with long-read phasing and assembly to precisely characterize the role of SVs in shaping the TE landscape. Highly contiguous phased assemblies of 127 MA lines revealed that SV types like polyploidy, aneuploidy and loss of heterozygosity have large impacts on the TE load. We characterized 18 de novo TE insertions, indicating that transposition only has a minor role in shaping the TE landscape in MA lines. Because the scarcity of TE mobilization in MA lines provided insufficient resolution to confidently dissect transposition rate variation in hybrids, we adapted an in vivo assay to measure transposition rates in variousS. paradoxushybrid backgrounds. We found that transposition rates are not increased by hybridization, but are modulated by many genotype-specific factors including initial TE load, TE sequence variants and mitochondrial DNA inheritance. Our results show the multiple scales at which TE load is shaped in hybrid genomes, being highly impacted by SV dynamics and finely modulated by genotype-specific variation in transposition rates.

Siderophores are soluble or membrane-embedded molecules that bind the oxidized form of iron, Fe(III), and play roles in iron acquisition by microorganisms. Fe(III)-bound siderophores bind to specific receptors that allow microbes to acquire iron. However, certain soil microbes release a compound (pulcherriminic acid, PA) that, upon binding to Fe(III), forms a precipitate (pulcherrimin) that apparently functions by reducing iron availability rather than contributing to iron acquisition. Here, we use Bacillus subtilis (PA producer) and Pseudomonas protegens as a competition model to show that PA is involved in a peculiar iron-managing system. The presence of the competitor induces PA production, leading to precipitation of Fe(III) as pulcherrimin, which prevents oxidative stress in B. subtilis by restricting the Fenton reaction and deleterious ROS formation. In addition, B. subtilis uses its known siderophore bacillibactin to retrieve Fe(III) from pulcherrimin. Our findings indicate that PA plays multiple roles by modulating iron availability and conferring protection against oxidative stress during inter-species competition.

Due to their programmability via specific base pairing, self-assembled DNA origami structures have proven to be useful for a wide variety of applications, including diagnostics, molecular computation, drug delivery, and therapeutics. Measuring and characterizing these structures is therefore of great interest and an important part of quality control. Here, we show the extent to which DNA nanostructures can be characterized by a solid-state nanopore; a non-destructive, label-free, single-molecule sensor capable of electrically detecting and characterizing charged biomolecules. We demonstrate that in addition to geometrical dimensions, nanopore sensing can provide information on the mechanical properties, assembly yield, and stability of DNA nanostructures. For this work, we use a model structure consisting of a 3 helix-bundle (3HB), i.e. three interconnected DNA double helices using a M13 scaffold folded twice on itself by short DNA staple strands, and translocate it through solid-state nanopores fabricated by controlled breakdown. We present detailed analysis of the passage characteristics of 3HB structures through nanopores under different experimental conditions which suggest that segments of locally higher flexibility are present along the nanostructure contour that allow for the otherwise rigid 3HB to fold inside nanopores. By characterizing partially melted 3HB structures, we find that locally flexible segments are likely due to short staple oligomers missing from the fully assembled structure. The 3HB used herein is a prototypical example to establish nanopores as a sensitive, non-destructive, and label-free alternative to conventional techniques such as gel electrophoresis with which to characterize DNA nanostructures.

BackgroundWhile medications for opioid use disorder (MOUD) effectively treat OUD during pregnancy and the postpartum period, poor treatment retention is common. Digital phenotyping, or passive sensing data captured from personal mobile devices, namely smartphones, provides an opportunity to understand behaviors, psychological states, and social influences contributing to perinatal MOUD non-retention. Given this novel area of investigation, we conducted a qualitative study to determine the acceptability of digital phenotyping among pregnant and parenting people with opioid use disorder (PPP-OUD).MethodsThis study was guided by the Theoretical Framework of Acceptability (TFA). Within a clinical trial testing a behavioral health intervention for PPP-OUD, we used purposeful criterion sampling to recruit 11 participants who delivered a child in the past 12 months and received OUD treatment during pregnancy or the postpartum period. Data were collected through phone interviews using a structured interview guide based on four TFA constructs (affective attitude, burden, ethicality, self-efficacy). We used framework analysis to code, chart, and identify key patterns within the data.ResultsParticipants generally expressed positive attitudes about digital phenotyping and high self-efficacy and low anticipated burden to participate in studies that collect smartphone-based passive sensing data. Nonetheless, concerns were noted related to data privacy/security and sharing location information. Differences in participant assessments of burden were related to length of time required and level of remuneration to participate in a study. Interviewees voiced broad support for participating in a digital phenotyping study with known/trusted individuals but expressed concerns about third-party data sharing and government monitoring.ConclusionDigital phenotyping methods were acceptable to PPP-OUD. Enhancements in acceptability include allowing participants to maintain control over which data are shared, limiting frequency of research contacts, aligning compensation with participant burden, and outlining data privacy/security protections on study materials.

BackgroundDietary intake provides nutrients for humans and their gastrointestinal microorganisms, as some dietary constituents bypass human digestion. These undigested components affect the composition and function of the microorganisms present. Metagenomic analyses allow researchers to study functional capacity. As dietary components affect the composition and function of the gastrointestinal microbiome, there is potential for developing objective biomarkers of food intake using metagenomic data.ObjectiveWe aimed to utilize a computationally intensive, multivariate, machine learning approach to identify fecal Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology (KO) categories as biomarkers that accurately predict food intake.DesignData were aggregated from five controlled feeding studies in adults that studied the impact of specific foods (almonds, avocados, broccoli, walnuts, barley, and oats) on the gastrointestinal microbiota. DNA from pre- and post-intervention fecal samples underwent shotgun genomic sequencing. After pre-processing, sequences were aligned (DIAMONDv2.0.11.149) and functionally annotated (MEGANv6.12.2). After count normalization, the log of the fold change ratio for resulting features between pre- and post-intervention of the treatment group against its corresponding control was utilized to conduct differential KO abundance analysis. Differentially abundant KOs were used to train machine learning models examining potential biomarkers in both single-food and multi-food models.ResultsWe identified differentially abundant KOs for almond (n = 54), broccoli (n = 2,474), and walnut (n = 732) (q < 0.20). Using the differentially abundant KOs, prediction accuracies were 80%, 87%, and 86% prediction accuracies for the almond, broccoli, and walnut groups, respectively using a random forest model to classify food intake. The mixed-food random forest achieved 81% prediction accuracy.ConclusionsOur findings reveal promise in utilizing fecal metagenomics to objectively complement self-reported measures of food intake. Future research on various foods and dietary patterns will expand these exploratory analyses for eventual use in feeding study compliance and clinical settings.

Epidemiologic studies have shown an association between an adverse intrauterine environment (eg, exposure to malnutrition) and an increased risk of developing cardiometabolic disease in adulthood. These studies laid the foundation for the developmental origins of health and disease hypothesis, which states that limited nutrient supply to the fetus results in physiologic and metabolic adaptations that favor survival but result in unfavorable consequences in the offspring if there is excess nutrition after birth. This discrepancy in the pre- and postnatal milieus, perceived as stress by the offspring, may confer an increased risk of developing cardiometabolic disease later in life. Thus, early life exposures result in programming or changes in cellular memory that have effects on health throughout the life course. One of the mechanisms by which programming occurs is via epigenetic modifications of genes, processes that result in functionally relevant changes in genes (ie, gene expression) without an alteration in the genotype. In this review, we will describe how fetal exposures, including under- and overnutrition, affect neonatal and childhood growth and the future risk for cardiometabolic disease.

BackgroundThere remains a disproportionally high tobacco smoking rate in low-income populations. Multicomponent tobacco dependence interventions in theory are effective. However, which intervention components are necessary to include for low socioeconomic status (SES) populations is still unknown.ObjectiveTo assess the effectiveness of multicomponent tobacco dependence interventions for low SES and create a checklist tool examining multicomponent interventions.MethodsEMBASE and MEDLINE databases were searched to identify randomised controlled trials (RCTs) published with the primary outcome of tobacco smoking cessation measured at 6 months or post intervention. RCTs that evaluated tobacco dependence management interventions (for reduction or cessation) in low SES (experience of housing insecurity, poverty, low income, unemployment, mental health challenges, illicit substance use and/or food insecurity) were included. Two authors independently abstracted data. Random effects meta-analysis and post hoc sensitivity analysis were performed.ResultsOf the 33 included studies, the number of intervention components ranged from 1 to 6, with smoking quit rates varying between 1% and 36.6%. Meta-analysis revealed that both the 6-month and 12-month outcome timepoints, multicomponent interventions were successful in achieving higher smoking quit rates than the control (OR 1.64, 95% Cl 1.41 to 1.91; OR 1.74, 95% Cl 1.30 to 2.33). Evidence of low heterogeneity in the effect size was observed at 6-month (I2=26%) and moderate heterogeneity at 12-month (I2=56%) outcomes.ConclusionMulticomponent tobacco dependence interventions should focus on inclusion of social support, frequency and duration of components. Employing community-based participatory-action research approach is essential to addressing underlying psychosocioeconomic-structural factors, in addition to the proven combination pharmacotherapies.PROSPERO registration numberCRD42017076650.

BACKGROUND: Individuals with pain prescribed opioids experience high rates of comorbid depression. The aim of this study was to characterize pain, substance use, and health status as a function of depressive symptom level in individuals filling an opioid prescription at a community pharmacy. METHODS: Participants (N=1,268) filling an opioid prescription enrolled in a study validating a prescription drug monitoring metric completed an online survey assessing sociodemographics, depressive symptoms, substance use, prescription opioid misuse, overdose history, general health, and pain severity and interference. RESULTS: Approximately one-fifth (19.3%) had a positive depression screen. In covariate-adjusted logistic regression analyses, individuals with a positive depression screen were more likely to have moderate/high substance use risk scores for: prescription opioids (AOR=2.06; 95% CI: 1.51-2.79); street opioids (AOR=7.18; 95% CI: 2.57-20.01); cannabis (AOR=2.00; 95% CI: 1.34-3.00); cocaine (AOR=3.46; 95% CI: 1.46-8.22); tobacco (AOR=1.59; 95% CI: 1.18-2.15); methamphetamine (AOR=7.59; 95% CI: 2.58-22.35); prescription stimulants (AOR=2.95; 95% CI: 1.59-5.49); and sedatives (AOR=3.41; 95% CI: 2.43-4.79). Individuals with a positive depression screen were more likely to misuse prescription opioids (AOR=3.46; 95% CI: 2.33-5.15), experience a prior overdose (AOR=2.69; 95% CI: 1.76-4.11), report poorer general health (AOR=.25, 95% CI: .18-.35), and report moderate/severe pain severity (AOR=4.36, 95% CI: 2.80-6.77) and interference (AOR=6.47, 95% CI: 4.08-10.26). CONCLUSIONS: Individuals prescribed opioids with heightened depression were more likely to report other substance use, prescription opioid misuse, prior overdose, greater pain, and poorer health.

International audience; PURPOSE: Severely ill patients affected by coronavirus disease 2019 (COVID-19) develop circulatory failure. We aimed to report patterns of left and right ventricular dysfunction in the first echocardiography following admission to intensive care unit (ICU). METHODS: Retrospective, descriptive study that collected echocardiographic and clinical information from severely ill COVID-19 patients admitted to 14 ICUs in 8 countries. Patients admitted to ICU who received at least one echocardiography between 1st February 2020 and 30th June 2021 were included. Clinical and echocardiographic data were uploaded using a secured web-based electronic database (REDCap). RESULTS: Six hundred and seventy-seven patients were included and the first echo was performed 2 [1, 4] days after ICU admission. The median age was 65 [56, 73] years, and 71% were male. Left ventricle (LV) and/or right ventricle (RV) systolic dysfunction were found in 234 (34.5%) patients. 149 (22%) patients had LV systolic dysfunction (with or without RV dysfunction) without LV dilatation and no elevation in filling pressure. 152 (22.5%) had RV systolic dysfunction. In 517 patients with information on both paradoxical septal motion and quantitative RV size, 90 (17.4%) had acute cor pulmonale (ACP). ACP was associated with mechanical ventilation (OR\,>\,4), pulmonary embolism (OR\,>\,5) and increased PaCO(2). Exploratory analyses showed that patients with ACP and older age were more likely to die in hospital (including ICU). CONCLUSION: Almost one-third of this cohort of critically ill COVID-19 patients exhibited abnormal LV and/or RV systolic function in their first echocardiography assessment. While LV systolic dysfunction appears similar to septic cardiomyopathy, RV systolic dysfunction was related to pressure overload due to positive pressure ventilation, hypercapnia and pulmonary embolism. ACP and age seemed to be associated with mortality in this cohort.

International audience; We analysed the therapeutic outcomes of all consecutive patients with primary central nervous system lymphoma (PCNSL) registered in the prospective French database for PCNSL and treated with intensive chemotherapy (IC) followed by autologous stem cell transplantation (IC-ASCT) between 2011 and November 2019 (271 patients recruited, 266 analysed). In addition, treatment-related complications of thiotepa-based IC-ASCT were analysed from the source files of 85 patients from 3 centers. Patients had received IC-ASCT either in first-line treatment (n\,=\,147) or at relapse (n\,=\,119). The median age at IC-ASCT was 57 years (range: 22-74). IC consisted of thiotepa-BCNU (n\,=\,64), thiotepa-busulfan (n\,=\,24), BCNU-etoposide-cytarabine-melphalan (BEAM, n\,=\,36) and thiotepa-busulfan-cyclophosphamide (n\,=\,142). In multivariate analysis, BEAM and ASCT beyond the first relapse were adverse prognostic factors for relapse risk. The risk of treatment-related mortality was higher for ASCT performed beyond the first relapse and seemed higher for thiotepa-busulfan-cyclophosphamide. Thiotepa-BCNU tends to result in a higher relapse rate than thiotepa-busulfan-cyclophosphamide and thiotepa-busulfan. This study confirms the role of IC-ASCT in first-line treatment and at first-relapse PCNSL (5-year overall survival rates of 80 and 50%, respectively). The benefit/risk ratio of thiotepa-busulfan/thiotepa-busulfan-cyclophosphamide-ASCT could be improved by considering ASCT earlier in the course of the disease and dose adjustment of the IC.

Resistance to fibrinolysis, levels of procoagulant/antifibrinolytic neutrophil extracellular traps (NETs), and the severity of acute ischemic stroke (AIS) are increased by COVID-19. Whether NETs are components of AIS thrombi from COVID-19 patients and whether COVID-19 impacts the susceptibility of these thrombi to thrombolytic treatments remain unknown, however.We aimed to characterize AIS thrombi from COVID-19 patients by immunohistology and to compare their response to thrombolysis to that of AIS thrombi from non-COVID-19 patients.For this monocentric cohort study, 14 thrombi from COVID-19 AIS patients and 16 thrombi from non-COVID-19 patients, all recovered by endovascular therapy, were analyzed by immunohistology or subjected to ex vivo thrombolysis by tissue-type plasminogen (tPA)/plasminogen.COVID-19 AIS thrombi were rich in neutrophils and contained NETs, but not spike protein. Thrombolysis assays revealed a mean resistance profile to tPA/plasminogen of COVID-19 AIS thrombi similar to that of non-COVID-19 AIS thrombi. The addition of DNase 1 successfully improved thrombolysis by potentiating fibrinolysis irrespective of COVID-19 status. Levels of neutrophil, NETs, and platelet markers in lysis supernatants were comparable between AIS thrombi from non-COVID-19 and COVID-19 patients.These results show that COVID-19 does not impact NETs content or worsen fibrinolysis resistance of AIS thrombi, a therapeutic hurdle that could be overcome by DNase 1 even in the context of SARS-CoV-2 infection.

International audience; Background In acute ischemic stroke (AIS), fluid-attenuated inversion recovery (FLAIR) is used for treatment decisions when onset time is unknown. Synthetic FLAIR could be generated with deep learning from information embedded in diffusion-weighted imaging (DWI) and could replace acquired FLAIR sequence (real FLAIR) and shorten MRI duration. Purpose To compare performance of synthetic and real FLAIR for DWI-FLAIR mismatch estimation and identification of patients presenting within 4.5 hours from symptom onset. Materials and Methods In this retrospective study, all pretreatment and early follow-up ( .99). Conclusion Synthetic fluid-attenuated inversion recovery (FLAIR) had diagnostic performances similar to real FLAIR in depicting diffusion-weighted imaging-FLAIR mismatch and in helping to identify early acute ischemic stroke, and it may accelerate MRI protocols. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Carroll and Hurley in this issue.

Regional frequency analysis (RFA) aims to estimate quantiles of extreme hydrological variables (e.g. floods or low-flows) at sites where little or no hydrological data is available. This information is of interest for the optimal planning and management of water resources. A number of regional estimation models are evaluated and compared in this study and then used for regional estimation of flood quantiles at ungauged catchments located in the Montreal region in southern Quebec, Canada. In this study, two neighborhood approaches using canonical correlation analysis (CCA) and the region of influence (ROI) method are applied to delineate homogenous regions. Three regression methods namely log-linear regression model (LLRM), generalized additive models (GAM), and multivariate adaptive regression splines (MARS), recently introduced in the RFA context, are considered for regional estimation. These models are also applied considering all stations (ALL). The considered models, especially MARS, have never been used previously in a concrete application. Results indicate that MARS and GAM have comparable predictive performances, especially when applied with the whole dataset. Results also show that MARS used in combination with the CCA approach provide improved performances compared to all considered regional approaches. This may reflect the flexibility of the combination of these two approaches, their robustness, and their ability to better reproduce the hydrological phenomena, especially in real-world conditions when limited data are available.