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\"Hana is at school, high on the hill, when her village is devastated by a powerful tsunami. When she is finally reunited with her family, she learns that the wave has taken more than she could have ever imagined. To cope with her grief, Hana begins to paint chidori (a thousand birds), to honor those that are lost.\"-- Provided by publisher.

Objectives. To determine how community-based organizations (CBOs) define priorities for bolstering community resilience, challenges in addressing these priorities, and strategies to address challenges. Methods. The Community Resilience Learning Collaborative and Research Network (C-LEARN) is a multiphase study examining opportunities to improve community resilience to the threats of disaster and climate change in South Louisiana. Phase I of C-LEARN involved using the National Health Security Strategy and Implementation Plan for directed content analysis of key informant interviews with CBO representatives from 47 agencies within South Louisiana between February and May 2018. Results. CBO interviewees highlighted the importance of forging relationships and building trust through diverse cross-sector collaborations and partnerships before disasters. Such collaborations and partnerships were shown to tailor disaster response to the needs of particular communities and populations as well as address key challenges such as gaps in information, services, and resources. Conclusions. Our results encourage a culture of community resilience and community preparedness through partnerships and community-engaged strategies. C-LEARN will utilize the results of our interviews in the design of phase II of our agency-level coalition-building intervention.

This manuscript presents the protocol and participatory planning process for implementing the Community Resilience Learning Collaborative and Research Network (C-LEARN) study. C-LEARN is designed to determine how to build a service program and individual client capacity to improve mental health-related quality of life among individuals at risk for depression, with exposure to social risk factors or concerns about environmental hazards in areas of Southern Louisiana at risk for events such as hurricanes and storms. The study uses a Community Partnered Participatory Research (CPPR) framework to incorporate community priorities into study design and implementation. The first phase of C-LEARN is assessment of community priorities, assets, and opportunities for building resilience through key informant interviews and community agency outreach. Findings from this phase will inform the implementation of a two-level (program-level and individual client level) randomized study in up to four South Louisiana communities. Within communities, health and social-community service programs will be randomized to Community Engagement and Planning (CEP) for multi-sector coalition support or Technical Assistance (TA) for individual program support to implement evidence-based and community-prioritized intervention toolkits, including an expanded version of depression collaborative care and resources (referrals, manuals) to address social risk factors such as financial or housing instability and for a community resilience approach to disaster preparedness and response. Within each arm, the study will randomize individual adult clients to one of two mobile applications that provide informational resources on services for depression, social risk factors, and disaster response or also provide psychoeducation on Cognitive Behavioral Therapy to enhance coping with stress and mood. Planned data collection includes baseline, six-month and brief monthly surveys for clients, and baseline and 12-month surveys for administrators and staff.

Serum antibodies directed against myelin oligodendrocyte glycoprotein (MOG) are found in patients with acquired CNS demyelinating syndromes that are distinct from multiple sclerosis and aquaporin-4-seropositive neuromyelitis optica spectrum disorder. Based on an extensive literature review and a structured consensus process, we propose diagnostic criteria for MOG antibody-associated disease (MOGAD) in which the presence of MOG-IgG is a core criterion. According to our proposed criteria, MOGAD is typically associated with acute disseminated encephalomyelitis, optic neuritis, or transverse myelitis, and is less commonly associated with cerebral cortical encephalitis, brainstem presentations, or cerebellar presentations. MOGAD can present as either a monophasic or relapsing disease course, and MOG-IgG cell-based assays are important for diagnostic accuracy. Diagnoses such as multiple sclerosis need to be excluded, but not all patients with multiple sclerosis should undergo screening for MOG-IgG. These proposed diagnostic criteria require validation but have the potential to improve identification of individuals with MOGAD, which is essential to define long-term clinical outcomes, refine inclusion criteria for clinical trials, and identify predictors of a relapsing versus a monophasic disease course.

Predicting impacts of global environmental change is challenging due to the complex life cycles that characterize many terrestrial and aquatic taxa. Different life stages often interact with the physical environment in distinct ways, and a growing body of work suggests that stresses experienced during one life stage can \"carry over\" to influence subsequent stages. Assessments of population responses to environmental perturbation must therefore consider how effects might propagate across life-history transitions. We investigated consequences of ocean acidification (decreased pH and carbonate saturation) for early life stages of the Olympia oyster ( Ostrea lurida ), a foundation species in estuaries along the Pacific coast of North America. We reared oysters at three levels of seawater pH, including a control (8.0) and two additional levels (7.9 and 7.8). Oysters were cultured through their planktonic larval period to metamorphosis and into early juvenile life. Larvae reared under pH 7.8 exhibited a 15% decrease in larval shell growth rate, and a 7% decrease in shell area at settlement, compared to larvae reared under control conditions. Impacts were even more pronounced a week after settlement, with juveniles that had been reared as larvae under reduced pH exhibiting a 41% decrease in shell growth rate. Importantly, the latter effect arose regardless of the pH level the oysters experienced as juveniles, indicating a strong carry-over effect from the larval phase. Adverse impacts of early exposure to low pH persisted for at least 1.5 months after juveniles were transferred to a common environment. Overall, our results suggest that a stringent focus on a single phase of the life cycle (e.g., one perceived as the \"weakest link\") may neglect critical impacts that can be transferred across life stages in taxa with complex life histories.

AbstractObjectiveTo determine the efficacy and safety of low carbohydrate diets (LCDs) and very low carbohydrate diets (VLCDs) for people with type 2 diabetes.DesignSystematic review and meta-analysis.Data sourcesSearches of CENTRAL, Medline, Embase, CINAHL, CAB, and grey literature sources from inception to 25 August 2020.Study selectionRandomized clinical trials evaluating LCDs (<130 g/day or <26% of a 2000 kcal/day diet) and VLCDs (<10% calories from carbohydrates) for at least 12 weeks in adults with type 2 diabetes were eligible.Data extractionPrimary outcomes were remission of diabetes (HbA1c <6.5% or fasting glucose <7.0 mmol/L, with or without the use of diabetes medication), weight loss, HbA1c, fasting glucose, and adverse events. Secondary outcomes included health related quality of life and biochemical laboratory data. All articles and outcomes were independently screened, extracted, and assessed for risk of bias and GRADE certainty of evidence at six and 12 month follow-up. Risk estimates and 95% confidence intervals were calculated using random effects meta-analysis. Outcomes were assessed according to a priori determined minimal important differences to determine clinical importance, and heterogeneity was investigated on the basis of risk of bias and seven a priori subgroups. Any subgroup effects with a statistically significant test of interaction were subjected to a five point credibility checklist.ResultsSearches identified 14 759 citations yielding 23 trials (1357 participants), and 40.6% of outcomes were judged to be at low risk of bias. At six months, compared with control diets, LCDs achieved higher rates of diabetes remission (defined as HbA1c <6.5%) (76/133 (57%) v 41/131 (31%); risk difference 0.32, 95% confidence interval 0.17 to 0.47; 8 studies, n=264, I2=58%). Conversely, smaller, non-significant effect sizes occurred when a remission definition of HbA1c <6.5% without medication was used. Subgroup assessments determined as meeting credibility criteria indicated that remission with LCDs markedly decreased in studies that included patients using insulin. At 12 months, data on remission were sparse, ranging from a small effect to a trivial increased risk of diabetes. Large clinically important improvements were seen in weight loss, triglycerides, and insulin sensitivity at six months, which diminished at 12 months. On the basis of subgroup assessments deemed credible, VLCDs were less effective than less restrictive LCDs for weight loss at six months. However, this effect was explained by diet adherence. That is, among highly adherent patients on VLCDs, a clinically important reduction in weight was seen compared with studies with less adherent patients on VLCDs. Participants experienced no significant difference in quality of life at six months but did experience clinically important, but not statistically significant, worsening of quality of life and low density lipoprotein cholesterol at 12 months. Otherwise, no significant or clinically important between group differences were found in terms of adverse events or blood lipids at six and 12 months.ConclusionsOn the basis of moderate to low certainty evidence, patients adhering to an LCD for six months may experience remission of diabetes without adverse consequences. Limitations include continued debate around what constitutes remission of diabetes, as well as the efficacy, safety, and dietary satisfaction of longer term LCDs.Systematic review registrationPROSPERO CRD42020161795.

Background Heart failure is one of the leading causes of hospitalization in the United States. Advances in big data solutions allow for storage, management, and mining of large volumes of structured and semi-structured data, such as complex healthcare data. Applying these advances to complex healthcare data has led to the development of risk prediction models to help identify patients who would benefit most from disease management programs in an effort to reduce readmissions and healthcare cost, but the results of these efforts have been varied. The primary aim of this study was to develop a 30-day readmission risk prediction model for heart failure patients discharged from a hospital admission. Methods We used longitudinal electronic medical record data of heart failure patients admitted within a large healthcare system. Feature vectors included structured demographic, utilization, and clinical data, as well as selected extracts of un-structured data from clinician-authored notes. The risk prediction model was developed using deep unified networks (DUNs), a new mesh-like network structure of deep learning designed to avoid over-fitting. The model was validated with 10-fold cross-validation and results compared to models based on logistic regression, gradient boosting, and maxout networks. Overall model performance was assessed using concordance statistic. We also selected a discrimination threshold based on maximum projected cost saving to the Partners Healthcare system. Results Data from 11,510 patients with 27,334 admissions and 6369 30-day readmissions were used to train the model. After data processing, the final model included 3512 variables. The DUNs model had the best performance after 10-fold cross-validation. AUCs for prediction models were 0.664 ± 0.015, 0.650 ± 0.011, 0.695 ± 0.016 and 0.705 ± 0.015 for logistic regression, gradient boosting, maxout networks, and DUNs respectively. The DUNs model had an accuracy of 76.4% at the classification threshold that corresponded with maximum cost saving to the hospital. Conclusions Deep learning techniques performed better than other traditional techniques in developing this EMR-based prediction model for 30-day readmissions in heart failure patients. Such models can be used to identify heart failure patients with impending hospitalization, enabling care teams to target interventions at their most high-risk patients and improving overall clinical outcomes.

Background Dietary modifications are considered a first-line intervention for chronic disease management, yet graduating doctors still report not feeling competent to counsel patients on their diet. Research has focused on methods to address this shortfall in physician competency, including culinary medicine. Culinary medicine is an approach to education that involves hands-on food and cooking learning experiences to equip participants with tools for improving the nutrition behaviour and health of their future patients. Despite positive findings in the efficacy of these interventions, they differ markedly in approach and target, which therefore fails to provide adequate evidence that could serve to guide future culinary medicine interventions. Objective A scoping review to synthesize the existing literature on culinary medicine interventions that are offered during medical training. Methods Online databases were used to identify literature published prior to April 2022 that involve a hands-on culinary medicine component to nutrition and examine academic impact, feasibility and acceptability. Results Twenty-four studies met the eligibility criteria. Despite promising gains in nutrition knowledge, confidence and high acceptability of the programs, large variations exist in delivery method, setting, and course content between programs. There is a lack of program cost reporting and long-term follow up of participants, inconsistent evidence for improved nutrition attitudes amongst participants, as well as geographically limited adoption of such programs. Conclusions The findings of this research demonstrate a clear increase in interest in the use of hands-on culinary medicine programs as educational tools, evidence of feasibility in implementation, and improved student nutritional knowledge, skill and counseling compared to a traditional didactic curriculum. The quality of culinary medicine research studies is increasing and the aims of research are narrowing to focus on how culinary medicine can positively impact medical education. The findings from this review will aid in legitimising culinary medicine as an effective delivery method of nutritional education in medical programs.

Genetic diversity is key to crop improvement. Owing to pervasive genomic structural variation, a single reference genome assembly cannot capture the full complement of sequence diversity of a crop species (known as the ‘pan-genome’ 1 ). Multiple high-quality sequence assemblies are an indispensable component of a pan-genome infrastructure. Barley ( Hordeum vulgare L.) is an important cereal crop with a long history of cultivation that is adapted to a wide range of agro-climatic conditions 2 . Here we report the construction of chromosome-scale sequence assemblies for the genotypes of 20 varieties of barley—comprising landraces, cultivars and a wild barley—that were selected as representatives of global barley diversity. We catalogued genomic presence/absence variants and explored the use of structural variants for quantitative genetic analysis through whole-genome shotgun sequencing of 300 gene bank accessions. We discovered abundant large inversion polymorphisms and analysed in detail two inversions that are frequently found in current elite barley germplasm; one is probably the product of mutation breeding and the other is tightly linked to a locus that is involved in the expansion of geographical range. This first-generation barley pan-genome makes previously hidden genetic variation accessible to genetic studies and breeding. Chromosome-scale sequence assemblies of 20 diverse varieties of barley are used to construct a first-generation pan-genome, revealing previously hidden genetic variation that can be used by studies aimed at crop improvement

Viral infection of mammalian host results in the activation of innate immune responses. Toll-like receptors (TLRs) have been shown to mediate the recognition of many types of pathogens, including viruses. The genomes of viruses possess unique characteristics that are not found in mammalian genomes, such as high CpG content and double-stranded RNA. These genomic nucleic acids serve as molecular signatures associated with viral infections. Here we show that TLR7 recognizes the single-stranded RNA viruses, vesicular stomatitis virus and influenza virus. The recognition of these viruses by plasmacytoid dendritic cells and B cells through TLR7 results in their activation of costimulatory molecules and production of cytokines. Moreover, this recognition required intact endocytic pathways. Mice deficient in either the TLR7 or the TLR adaptor protein MyD88 demonstrated reduced responses to in vivo infection with vesicular stomatitis virus. These results demonstrate microbial ligand recognition by TLR7 and provide insights into the pathways used by the innate immune cells in the recognition of viral pathogens.