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BACKGROUND: Incorporating genomic data into risk prediction has become an increasingly popular approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. METHODS: Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. RESULTS: The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p=0.006), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p

Abstract Climate change is currently one of humanity’s greatest threats. To help scholars understand the psychology of climate change, we conducted an online quasi-experimental survey on 59,508 participants from 63 countries (collected between July 2022 and July 2023). In a between-subjects design, we tested 11 interventions designed to promote climate change mitigation across four outcomes: climate change belief, support for climate policies, willingness to share information on social media, and performance on an effortful pro-environmental behavioural task. Participants also reported their demographic information (e.g., age, gender) and several other independent variables (e.g., political orientation, perceptions about the scientific consensus). In the no-intervention control group, we also measured important additional variables, such as environmentalist identity and trust in climate science. We report the collaboration procedure, study design, raw and cleaned data, all survey materials, relevant analysis scripts, and data visualisations. This dataset can be used to further the understanding of psychological, demographic, and national-level factors related to individual-level climate action and how these differ across countries.

The common bean (Phaseolus vulgaris L.) is a globally cultivated leguminous crop. Fusarium wilt (FW), caused by Fusarium oxysporum f. sp. phaseoli (Fop), is a significant disease leading to substantial yield loss in common beans. Disease-resistant cultivars are recommended to counteract this. The objective of this investigation was to identify single nucleotide polymorphism (SNP) markers associated with FW resistance and to pinpoint potential resistant common bean accessions within a core collection, utilizing a panel of 157 accessions through the Genome-wide association study (GWAS) approach with TASSEL 5 and GAPIT 3. Phenotypes for Fop race 1 and race 4 were matched with genotypic data from 4740 SNPs of BARCBean6K_3 Infinium Bea Chips. After ranking the 157-accession panel and revealing 21 Fusarium wilt-resistant accessions, the GWAS pinpointed 16 SNPs on chromosomes Pv04, Pv05, Pv07, Pv8, and Pv09 linked to Fop race 1 resistance, 23 SNPs on chromosomes Pv03, Pv04, Pv05, Pv07, Pv09, Pv10, and Pv11 associated with Fop race 4 resistance, and 7 SNPs on chromosomes Pv04 and Pv09 correlated with both Fop race 1 and race 4 resistances. Furthermore, within a 30 kb flanking region of these associated SNPs, a total of 17 candidate genes were identified. Some of these genes were annotated as classical disease resistance protein/enzymes, including NB-ARC domain proteins, Leucine-rich repeat protein kinase family proteins, zinc finger family proteins, P-loopcontaining nucleoside triphosphate hydrolase superfamily, etc. Genomic prediction (GP) accuracy for Fop race resistances ranged from 0.26 to 0.55. This study advanced common bean genetic enhancement through marker-assisted selection (MAS) and genomic selection (GS) strategies, paving the way for improved Fop resistance.

Abstract This paper describes an approach for developing strategic cycle network planning tools. Based on our experience developing and deploying the Cycle Route Uptake and Scenario Estimation (CRUSE) Tool for Ireland, we outline the underlying methods, including disaggregation of origin–destination data with the open source ‘odjitter’ software, incorporation of additional trip purposes, routing, scenario generation, and development of an intuitive user interface that is tested and used by practitioners. Commissioned by the national infrastructure agency Transport Infrastructure Ireland, CRUSE provides estimates of current and potential future cycling levels under ‘snapshot’ scenarios to inform investment decisions. The publicly available results at https://cruse.bike/ enable planners, engineers, and other stakeholders to make more evidence-based decisions. CRUSE goes beyond previous work by: modeling networks at high spatial resolution; simulating multiple trip purposes (social, shopping, personal utility, recreational, and cycle touring), supplementing official origin–destination datasets on travel for work and education; and providing estimates of ‘quietness’ (a proxy for cyclist comfort and route preference) at the route segment level. Three network types—‘Fastest’, ‘Balanced’, and ‘Quietest’—help plan both arterial and residential cycle networks. Workshops with stakeholders were used to inform the development of the tool. Feedback shows that the tool has a wide range of uses and is already being used in practice to inform urban, inter-urban, and rural cycle network designs. The approach is flexible and open source, allowing the underlying ideas and code to be adapted, supporting more evidence-based and effective cycling policies and interventions internationally.

There is a growing movement in Canada towards youth homelessness prevention. One such response, called shelter diversion aims to move young people into safe and supportive housing as quickly as possible. The objective of this project is to assess how, and in what ways, shelter diversion operates and whether this intervention permanently or temporarily diverts youth from homelessness. Our project is grounded in principles of community-based participatory research including community/university partnerships and an advisory committee of lived-experience experts. Our team is utilizing mixed methods to capture the outcomes of diversion programs. Data collection began in September 2022 and ended in May 2024. Quantitative and qualitative data analysis is underway. Preliminary results show differences in how diversion is defined and implemented across organizations. There are also differences in staffing models and program budgets. The findings from this study will contribute to a recommendation for a national definition and adaptable program model for shelter diversion, easily accessible to support the expansion of diversion programs into youth-serving organizations across Canada. This study is the first in Canada to examine the effectiveness of shelter diversion as an early intervention strategy to prevent youth homelessness on a national scale.

Abstract Background Incorporating genomic data into risk prediction has become an increasingly popular approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. Methods Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. Results The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p=0.006), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p

Abstract Background Despite continuing advancements in treatments for opioid use disorder (OUD), continued high rates of relapse indicate the need for more effective approaches, including novel pharmacological interventions. Glucagon-like peptide 1 receptor agonists (GLP-1RA) provide a promising avenue as a non-opioid medication for the treatment of OUD. Whereas GLP-1RAs have shown promise as a treatment for alcohol and nicotine use disorders, to date, no controlled clinical trials have been conducted to determine if a GLP-1RA can reduce craving in individuals with OUD. The purpose of the current protocol was to evaluate the potential for a GLP-1RA, liraglutide, to safely and effectively reduce craving in an OUD population in residential treatment. Method This preliminary study was a randomized, double-blinded, placebo-controlled clinical trial designed to test the safety and efficacy of the GLP-1RA, liraglutide, in 40 participants in residential treatment for OUD. Along with taking a range of safety measures, efficacy for cue-induced craving was evaluated prior to (Day 1) and following (Day 19) treatment using a Visual Analogue Scale (VAS) in response to a cue reactivity task during functional near-infrared spectroscopy (fNIRS) and for craving. Efficacy of treatment for ambient craving was assessed using Ecological Momentary Assessment (EMA) prior to (Study Day 1), across (Study Days 2–19), and following (Study Days 20–21) residential treatment. Discussion This manuscript describes a protocol to collect clinical data on the safety and efficacy of a GLP-1RA, liraglutide, during residential treatment of persons with OUD, laying the groundwork for further evaluation in a larger, outpatient OUD population. Improved understanding of innovative, non-opioid based treatments for OUD will have the potential to inform community-based interventions and health policy, assist physicians and health care professionals in the treatment of persons with OUD, and to support individuals with OUD in their effort to live a healthy life. Trial registration: ClinicalTrials.gov: NCT04199728. Registered 16 December 2019, https://clinicaltrials.gov/study/NCT04199728?term=NCT04199728 . Protocol Version 10 May 2023

Abstract Importance Large-scale estimates of bronchopulmonary dysplasia (BPD) are warranted for adequate prevention and treatment. However, systematic approaches to ascertain rates of BPD are lacking. Objective To conduct a systematic review and meta-analysis to assess the prevalence of BPD in very low birth weight (≤ 1,500 g) or very low gestational age (

Abstract Background Despite wide scale assessments, it remains unclear how large-scale severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination affected the wastewater concentration of the virus or the overall disease burden as measured by hospitalization rates. Methods We used weekly SARS-CoV-2 wastewater concentration with a stratified random sampling of seroprevalence, and linked vaccination and hospitalization data, from April 2021–August 2021 in Jefferson County, Kentucky (USA). Our susceptible ( $$S$$ S ), vaccinated ( $$V$$ V ), variant-specific infected ( $${I}_{1}$$ I 1 and $${I}_{2}$$ I 2 ), recovered ( $$R$$ R ), and seropositive ( $$T$$ T ) model ( $${SV}{I}_{2}{RT}$$ S V I 2 R T ) tracked prevalence longitudinally. This was related to wastewater concentration. Results Here we show the 64% county vaccination rate translate into about a 61% decrease in SARS-CoV-2 incidence. The estimated effect of SARS-CoV-2 Delta variant emergence is a 24-fold increase of infection counts, which correspond to an over 9-fold increase in wastewater concentration. Hospitalization burden and wastewater concentration have the strongest correlation (r = 0.95) at 1 week lag. Conclusions Our study underscores the importance of continuing environmental surveillance post-vaccine and provides a proof-of-concept for environmental epidemiology monitoring of infectious disease for future pandemic preparedness.

This pilot randomized controlled trial protocol aims to (1) assess the impact on the wellbeing of Syrian refugee young adults (18–24 years) of being a community mental health worker (CMHW) implementing WHO's evidence-based psychosocial intervention - Problem Management Plus (PM+) - with adults in their community, and (2) identify the mechanisms associated with the outcomes of enhanced wellbeing and coping, and reduced stress among these CMHWs. Over 108 million people have been forcibly displaced as of the end of 2022. Mental health consequences of these displacements are significant, yet human resources for health are not sufficient to meet the needs. A large proportion of refugee populations are youth and young adults (YA). Evidence indicates their engagement in supporting their communities leads to their own enhanced wellbeing and that of their community. This trial trains Syrian refugees to serve their communities as CMHW (n=19) or tutors (n=19) and compare wellbeing, stress and coping outcomes between these two groups and a control group (n = 40). We will also assess 7 mechanisms as potential pathways for the interventions to influence outcomes. Surveys will assess outcomes and mechanisms, hair samples will measure stress cortisol. The primary analysis will use a Bayesian Hierarchical Model approach to model the trajectories of the mechanisms and primary study endpoints over time for individuals in each of the arms. Our results will elucidate critical mechanisms in which engagement of young adults to support their community enhances their own wellbeing. Trial registration: National Institutes of Mental Health, NCT05265611, Registered prospectively in 2021. Lebanon clinical trials registry #: LBCTR2023015206, Registered in 2023.

OBJECTIVE: Although family-based treatment (FBT) is considered a first-line treatment for adolescent anorexia nervosa (AN), it is underutilized in community settings and is unavailable to many families for a multitude of practical reasons (e.g., costs of treatment, transportation constraints). Adapting FBT interventions for delivery in home-based and community-based settings may reduce pragmatic barriers to treatment uptake and engagement. METHODS: This pilot effectiveness-implementation trial will assess outcomes, implementation, and mechanisms of FBT adapted for the home setting (FBT-HB), delivered in the context of community-based behavioral health agencies. Adolescents with AN-spectrum disorders (n = 50) and their caregivers will be randomly assigned to either FBT-HB or home-based treatment as usual (TAU; integrated family therapy approach). Caregivers and adolescents will provide data on weight, eating, and putative treatment mechanisms, including caregiver self-efficacy and adolescent eating-related and weight-related distress. Implementation constructs of feasibility, acceptability, and appropriateness will be measured among providers and participating families. HYPOTHESES: We expect that FBT-HB will be feasible, acceptable, and appropriate, and will outperform TAU in terms of improvements in adolescent weight and eating-related psychopathology. We further expect that caregiver self-efficacy and adolescent eating-related and weight-related distress, but not general distress, will show greater improvements in FBT-HB relative to TAU and will be associated with better adolescent weight and eating outcomes in FBT-HB. POTENTIAL IMPLICATIONS: The proposed study has clear potential to advance scientific and clinical understanding of the real-world effectiveness of FBT for AN, including whether adapting it for the home setting improves its accessibility and effects on treatment outcome.

A educação digital tem se feito presente de forma cada vez mais diversa e consistente, desde o ensino formal até a produção de conteúdos educacionais em redes sociais. Nessas práticas, ganham destaque materiais de ensino-aprendizagem, dentre os quais destacamos os recursos educacionais digitais – ou recursos educacionais abertos (REAs). Por outro lado, a discussão acerca dos gêneros do discurso tem ganhado cada vez mais relevância e experimentado novos desdobramentos. Assim, considerando a importância que os REAs têm contemporaneamente na educação e a sua complexidade textual e discursiva, este trabalho tem como objetivo geral discutir a sua caracterização no quadro dos gêneros do discurso, mais especificamente sua constituição como gênero ou como hipergênero. Para isso, são mobilizados conceitos teóricos acerca do campo da educação e tecnologia, a exemplo de Castro Filho et al (2008), Santos (2013) Santana, Rossini e Pretto (2012), e dos estudos do texto e do discurso, como Marcuschi (2008), Távora (2008), Bonini (2011) e Bakhtin (2011). Os exemplares usados para análise são REAs produzidos no âmbito do Projeto EPTrilhas, desenvolvido pela Universidade Federal de Santa Catarina em parceria com a Secretaria de Educação Profissional e Tecnológica (SETEC) do Ministério da Educação. Essa análise evidenciou, pelas características do gênero, mídia e suporte, que os REAs multimodais em suporte virtual possuem características que os identificam como hipergêneros.

BackgroundLytic or malpositioned tunnels may require bone grafting during revision anterior cruciate ligament reconstruction (rACLR) surgery. Patient characteristics and effects of grafting on outcomes after rACLR are not well described.PurposeTo describe preoperative characteristics, intraoperative findings, and 2-year outcomes for patients with rACLR undergoing bone grafting procedures compared with patients with rACLR without grafting.Study designCohort study; Level of evidence, 3.MethodsA total of 1234 patients who underwent rACLR were prospectively enrolled between 2006 and 2011. Baseline revision and 2-year characteristics, surgical technique, pathology, treatment, and patient-reported outcome instruments (International Knee Documentation Committee [IKDC], Knee injury and Osteoarthritis Outcome Score [KOOS], Western Ontario and McMaster Universities Osteoarthritis Index, and Marx Activity Rating Scale [Marx]) were collected, as well as subsequent surgery information, if applicable. The chi-square and analysis of variance tests were used to compare group characteristics.ResultsA total of 159 patients (13%) underwent tunnel grafting-64 (5%) patients underwent 1-stage and 95 (8%) underwent 2-stage grafting. Grafting was isolated to the femur in 31 (2.5%) patients, the tibia in 40 (3%) patients, and combined in 88 patients (7%). Baseline KOOS Quality of Life (QoL) and Marx activity scores were significantly lower in the 2-stage group compared with the no bone grafting group (P≤ .001). Patients who required 2-stage grafting had more previous ACLRs (P < .001) and were less likely to have received a bone-patellar tendon-bone or a soft tissue autograft at primary ACLR procedure (P≤ .021) compared with the no bone grafting group. For current rACLR, patients undergoing either 1-stage or 2-stage bone grafting were more likely to receive a bone-patellar tendon-bone allograft (P≤ .008) and less likely to receive a soft tissue autograft (P≤ .003) compared with the no bone grafting group. At 2-year follow-up of 1052 (85%) patients, we found inferior outcomes in the 2-stage bone grafting group (IKDC score = 68; KOOS QoL score = 44; KOOS Sport/Recreation score = 65; and Marx activity score = 3) compared with the no bone grafting group (IKDC score = 77; KOOS QoL score = 63; KOOS Sport/Recreation score = 75; and Marx activity score = 7) (P≤ .01). The 1-stage bone graft group did not significantly differ compared with the no bone grafting group.ConclusionTunnel bone grafting was performed in 13% of our rACLR cohort, with 8% undergoing 2-stage surgery. Patients treated with 2-stage grafting had inferior baseline and 2-year patient-reported outcomes and activity levels compared with patients not undergoing bone grafting. Patients treated with 1-stage grafting had similar baseline and 2-year patient-reported outcomes and activity levels compared with patients not undergoing bone grafting.

Plausible competing developmental models show similar or identical structural equation modeling model fit indices, despite making very different causal predictions. One way to help address this problem is incorporating outside information into selecting among models. This study attempted to select among developmental models of children's early mathematical skills by incorporating information about the extent to which models forecast the longitudinal pattern of causal impacts of early math interventions. We tested for the usefulness and validity of the approach by applying it to data from three randomized controlled trials of early math interventions with longitudinal follow-up assessments in the United States (Ns = 1,375, 591, 744; baseline age 4.3, 6.5, 4.4; 17%-69% Black). We found that, across data sets, (a) some models consistently outperformed other models at forecasting later experimental impacts, (b) traditional statistical fit indices were not strongly related to causal fit as indexed by models' accuracy at forecasting later experimental impacts, and (c) models showed consistent patterns of similarity and discrepancy between statistical fit and models' effectiveness at forecasting experimental impacts. We highlight the importance of triangulation and call for more comparisons of experimental and nonexperimental estimates for choosing among developmental models.

IntroductionVolunteering in the community is thought to provide unique benefits to people who experience limited engagement in society. In the global South, volunteer programs are often framed as empowering women and benefiting the poor, without empirical evidence or systematic investigation of what this means from a local perspective. For this reason, it is critical to represent stakeholder knowledge, understand how change happens systemically, and reduce cultural bias in scientific inquiry and public policy. As such, efforts to respect diverse narratives and problem-solving approaches are key to science diplomacy – they help us understand cultural relevance, program efficacy, and for whom a program is considered transformative.Methods and resultsThis study shows how Syrian refugee and Jordanian women, living in resource-poor families, articulated (i) concepts of empowerment and life satisfaction and (ii) the benefits of engaging in community-based volunteering programs. Through engaging in a participatory methodology known as Fuzzy Cognitive Mapping, women generated visual representations of these constructs and cause-and-effect reasoning. They identified several dimensions of empowerment (e.g., cultural, financial, and psychological empowerment) and several meanings of life satisfaction (e.g. adaptation, acceptance, and contentment). They also mapped connections between variables, identifying those that might catalyze change. We were specifically interested in evaluating understandings of We Love Reading, a program that trains volunteers to become changemakers in their local community. In simulations, we modelled how employment, education, money, and volunteering would drive system change, with notable results on cultural empowerment.DiscussionThrough visual maps and scenarios of change, the study demonstrates a participatory approach to localizing knowledge and evaluating programs. This is key to improving scientific enquiry and public policy.

The 2019 London Extinction Rebellion was the first attempt by environmental protesters to create prolonged large-scale disruption in a Western capital city. The effects on public opinion were difficult to predict because protests seen as extreme can reduce support, but protests seen as justified can increase support. We studied longitudinal opinion changes in a nationally representative sample (n = 832) before, during, and after the rebellion, in conjunction with experimental analysis of the causal effects of media reports (n = 1441). The rebellion was longitudinally associated with national increases in environmental concern, and activist media increased dissatisfaction with current government action. Reports from different media sources caused activism intentions and support to move in different directions, contributing to longitudinally increased polarisation in attitudes to activism. The rebellion had minimal effects on belief in whether ordinary people can produce relevant change (based on collective efficacy and support for a Citizens’ Assembly). The rebellion thus apparently succeeded in strengthening general environmental attitudes without polarising them, and probably somewhat grew the pool of engaged activists, but did not lead to major growth in collective mobilisation or improved environmental policy.

Abstract Background and Aim C‐reactive protein (CRP)‐to‐albumin ratio (CAR) is a novel score with prognostic value in inflammatory conditions. This study assessed the performance of CAR as an objective marker of disease activity and prediction of subtherapeutic infliximab trough levels in patients with inflammatory bowel disease (IBD). Methods A retrospective study was conducted on three different patient cohorts with IBD: patients who had (i) fecal calprotectin (FC) measurements; (ii) Mayo Endoscopic Scores; and (iii) infliximab trough levels available. The relative performances of CAR, albumin, and CRP were compared in predicting disease activity (based on FC or Mayo Endoscopic Score) and infliximab trough levels. Results In both the FC (n = 289) and endoscopy (n = 65) cohorts, albumin and CAR correlated with objective disease activity. CAR (area under the curve [AUC] 0.70) was only marginally better at detecting active disease, measured by FC, compared to CRP (AUC 0.68). A CAR >0.15 was able to detect Mayo 3 disease (AUC 0.83, sensitivity 81%, specificity 89%). Albumin (r = 0.38) and CAR (r = −0.42) correlated with infliximab trough levels (n = 204). The optimal CAR for detecting subtherapeutic infliximab trough levels was >0.08 (AUC 0.70, sensitivity 66%, specificity 64%). Both albumin and CAR were independent predictors of subtherapeutic infliximab trough levels but correlated poorly with infliximab trough levels longitudinally in the same patient. Conclusion CAR was only a modest discriminator of subtherapeutic infliximab levels and offers little more than CRP in detecting active disease. CAR has potential to detect severe Mayo 3 disease and could be calculated in patients admitted with suspected acute severe ulcerative colitis.

Asthma is a heterogeneous disease, with multiple underlying inflammatory pathways and structural airway abnormalities that impact disease persistence and severity. Recent progress has been made in developing targeted asthma therapeutics, especially for subjects with eosinophilic asthma. However, there is an unmet need for new approaches to treat patients with severe and exacerbation-prone asthma, who contribute disproportionately to disease burden. Extensive deep phenotyping has revealed the heterogeneous nature of severe asthma and identified distinct disease subtypes. A current challenge in the field is to translate new and emerging knowledge about different pathobiologic mechanisms in asthma into patient-specific therapies, with the ultimate goal of modifying the natural history of disease. Here, we describe the Precision Interventions for Severe and/or Exacerbation-Prone Asthma (PrecISE) Network, a groundbreaking collaborative effort of asthma researchers and biostatisticians from around the United States. The PrecISE Network was designed to conduct phase II/proof-of-concept clinical trials of precision interventions in the population with severe asthma, and is supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health. Using an innovative adaptive platform trial design, the PrecISE Network will evaluate up to 6 interventions simultaneously in biomarker-defined subgroups of subjects. We review the development and organizational structure of the PrecISE Network, and choice of interventions being studied. We hope that the PrecISE Network will enhance our understanding of asthma subtypes and accelerate the development of therapeutics for severe asthma.

Common bean (Phaseolus vulgaris) is one of the major legume crops cultivated worldwide. Bacterial wilt (BW) of common bean (Curtobacterium flaccumfaciens pv. flaccumfaciens), being a seed-borne disease, has been a challenge in common bean producing regions. A genome-wide association study (GWAS) was conducted to identify SNP markers associated with BW resistance in the USDA common bean core collection. A total of 168 accessions were evaluated for resistance against three different isolates of BW. Our study identified a total of 14 single nucleotide polymorphism (SNP) markers associated with the resistance to BW isolates 528, 557, and 597 using mixed linear models (MLMs) in BLINK, FarmCPU, GAPIT, and TASSEL 5. These SNPs were located on chromosomes Phaseolus vulgaris [Pv]02, Pv04, Pv08, and Pv09 for isolate 528; Pv07, Pv10, and Pv11 for isolate 557; and Pv04, Pv08, and Pv10 for isolate 597. The genomic prediction accuracy was assessed by utilizing seven GP models with 1) all the 4,568 SNPs and 2) the 14 SNP markers. The overall prediction accuracy (PA) ranged from 0.30 to 0.56 for resistance against the three BW isolates. A total of 14 candidate genes were discovered for BW resistance located on chromosomes Pv02, Pv04, Pv07, Pv08, and Pv09. This study revealed vital information for developing genetic resistance against the BW pathogen in common bean. Accordingly, the identified SNP markers and candidate genes can be utilized in common bean molecular breeding programs to develop novel resistant cultivars.

In psychological science, replicability—repeating a study with a new sample achieving consistent results (Parsons et al., 2022)—is critical for affirming the validity of scientific findings. Despite its importance, replication efforts are few and far between in psychological science with many attempts failing to corroborate past findings. This scarcity, compounded by the difficulty in accessing replication data, jeopardizes the efficient allocation of research resources and impedes scientific advancement. Addressing this crucial gap, we present the Replication Database (https://forrt-replications.shinyapps.io/fred_explorer), a novel platform hosting 1,239 original findings paired with replication findings. The infrastructure of this database allows researchers to submit, access, and engage with replication findings. The database makes replications visible, easily findable via a graphical user interface, and tracks replication rates across various factors, such as publication year or journal. This will facilitate future efforts to evaluate the robustness of psychological research.