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Abstract Advancements in genomic and proteomic technologies have powered the creation of large gene and protein networks (“interactomes”) for understanding biological systems. However, the proliferation of interactomes complicates the selection of networks for specific applications. Here, we present a comprehensive evaluation of 45 current human interactomes, encompassing protein-protein interactions as well as gene regulatory, signaling, colocalization, and genetic interaction networks. Our analysis shows that large composite networks such as HumanNet, STRING, and FunCoup are most effective for identifying disease genes, while smaller networks such as DIP, Reactome, and SIGNOR demonstrate stronger performance in interaction prediction. Our study provides a benchmark for interactomes across diverse biological applications and clarifies factors that influence network performance. Furthermore, our evaluation pipeline paves the way for continued assessment of emerging and updated interaction networks in the future.

IntroductionTime-and dose-dependent adverse effects of amiodarone have not been described in cats. The primary aim of this retrospective multicenter cohort study was to report the type and frequency of clinical adverse effects and biochemical changes in cats receiving amiodarone chronically. The secondary aim was to report survival outcomes in this population of cats.MethodsMedical records were reviewed for signalment, arrhythmia diagnosis, presence of structural heart disease, systemic comorbidities and congestive heart failure at presentation, amiodarone dose, serial bloodwork results, adverse events, and survival outcome.ResultsThe study population included 27 client-owned cats (2016–2022). All cats had structural cardiac disease, and many were in congestive heart failure (17/27; 63%) at presentation. Amiodarone was most commonly prescribed for ventricular tachycardia (19/27, 70%), and it was administered once daily with a median [range] dose of 8.8 [4.515.2] mg/kg/day. There was a decrease in serum concentration of alanine transaminase between pretreatment values and values measured during the early amiodarone treatment window, 1–90 days (n = 16; p = 0.034). No statistical difference in serum concentration of alanine transaminase (n = 10; p = 0.799) was noted after 90 days of treatment compared to pretreatment. There was no change in hematocrit, neutrophil count, and serum concentration of alkaline phosphatase and total thyroxine during treatment in assessed cats. Ten cats (37%) had at least one episode of hyporexia or vomiting while receiving amiodarone. The median survival time for all-cause mortality was 441 days (95% confidence interval, 126–929 days); cats in which the primary therapeutic target was both supraventricular and concomitant ventricular tachyarrhythmias had at least a two-fold risk of dying compared to cats with supraventricular tachyarrhythmias alone (hazard ratio 12.9, 95% CI 1.86–89.8; p = 0.010).DiscussionAmiodarone was primarily used to treat ventricular arrhythmias. Transient gastrointestinal signs were reported in approximately one-third of the cats studied, but no clinically significant laboratory abnormalities were found in cats receiving amiodarone.

Abstract The demand for open data and open science is on the rise, fueled by expectations from the scientific community, calls to increase transparency and reproducibility in research findings, and developments such as the Final Data Management and Sharing Policy from the U.S. National Institutes of Health and a memorandum on increasing public access to federally funded research, issued by the U.S. Office of Science and Technology Policy. This paper explores the pivotal role of data repositories in biomedical research and open science, emphasizing their importance in managing, preserving, and sharing research data. Our objective is to familiarize readers with the functions of data repositories, set expectations for their services, and provide an overview of methods to evaluate their capabilities. The paper serves to introduce fundamental concepts and community-based guiding principles and aims to equip researchers, repository operators, funders, and policymakers with the knowledge to select appropriate repositories for their data management and sharing needs and foster a foundation for the open sharing and preservation of research data.

The R package innsight offers a general toolbox for revealing variable-wise interpretations of deep neural networks' predictions with so-called feature attribution methods. Aside from the unified and user-friendly framework, the package stands out in three ways: It is generally the first R package implementing feature attribution methods for neural networks. Secondly, it operates independently of the deep learning library, allowing the interpretation of neural networks from any R package, including keras, torch, neuralnet, and even custom models. Despite its flexibility, innsight benefits internally from the torch package's fast and efficient array calculations, which builds on LibTorch - PyTorch's C++ backend - without a Python dependency. Finally, it offers a variety of visualization tools for tabular, signal, image data, or a combination of these. Additionally, the plots can be rendered interactively using the plotly package.

IntroductionPharmacovigilance is vital for drug safety. The process typically involves two key steps: initial signal generation from spontaneous reporting systems (SRSs) and subsequent expert review to assess the signals’ (potential) causality and decide on the appropriate action.MethodsWe propose a novel discovery and verification approach to pharmacovigilance based on electronic healthcare data. We enhance the signal detection phase by introducing an ensemble of methods which generated signals are combined using Borda count ranking; a method designed to emphasize consensus. Ensemble methods tend to perform better when data is noisy and leverage the strengths of individual classifiers, while trying to mitigate some of their limitations. Additionally, we offer the committee of medical experts with the option to perform an in-depth investigation of selected signals through tailored pharmacoepidemiological studies to evaluate their plausibility or spuriousness. To illustrate our approach, we utilize data from the German Pharmacoepidemiological Research Database, focusing on drug reactions to the direct oral anticoagulant rivaroxaban.ResultsIn this example, the ensemble method is built upon the Bayesian confidence propagation neural network, longitudinal Gamma Poisson shrinker, penalized regression and random forests. We also conduct a pharmacoepidemiological verification study in the form of a nested active comparator case-control study, involving patients diagnosed with atrial fibrillation who initiated anticoagulant treatment between 2011 and 2017.DiscussionThe case study reveals our ability to detect known adverse drug reactions and discover new signals. Importantly, the ensemble method is computationally efficient. Hasty false conclusions can be avoided by a verification study, which is, however, time-consuming to carry out. We provide an online tool for easy application: https://borda.bips.eu.

Abstract Background Type 2 diabetes in young people is an aggressive disease with a greater risk of complications leading to increased morbidity and mortality during the most productive years of life. Prevalence in the UK and globally is rising yet experience in managing this condition is limited. There are no consensus guidelines in the UK for the assessment and management of paediatric type 2 diabetes. Methods Multidisciplinary professionals from The Association of Children’s Diabetes Clinicians (ACDC) and the National Type 2 Diabetes Working Group reviewed the evidence base and made recommendations using the Grading Of Recommendations, Assessment, Development and Evaluation (GRADE) methodology. Results and discussion Young people with type 2 diabetes should be managed within a paediatric diabetes team with close working with adult diabetes specialists, primary care and other paediatric specialties. Diagnosis of diabetes type can be challenging with many overlapping features. Diabetes antibodies may be needed to aid diagnosis. Co-morbidities and complications are frequently present at diagnosis and should be managed holistically. Lifestyle change and metformin are the mainstay of early treatment, with some needing additional basal insulin. GLP1 agonists should be used as second-line agents once early ketosis and symptoms are controlled. Glycaemic control improves microvascular but not cardiovascular risk. Reduction in excess adiposity, smoking prevention, increased physical activity and reduction of hypertension and dyslipidaemia are essential to reduce major adverse cardiovascular events. Conclusions This evidence-based guideline aims to provide a practical approach in managing this condition in the UK.

Abstract Field Line Resonances (FLRs) are a critical component in Earth's magnetospheric dynamics, associated with the transfer of energy between Ultra Low Frequency waves and local plasma populations. In this study we investigate how the polarisation of FLRs are impacted by cold plasma density distributions during geomagnetic storms. We present an analysis of Van Allen Probe A observations, where the spacecraft traversed a storm time plasmaspheric plume. We show that the polarisation of the FLR is significantly altered at the sharp azimuthal density gradient of the plume boundary, where the polarisation is intermediate with significant poloidal and toroidal components. These signatures are consistent with magnetohydrodynamic modeling results, providing the first observational evidence of a 3D FLR associated with a plume in Earth's magnetosphere. These results demonstrate the importance of cold plasma in controlling wave dynamics in the magnetosphere, and have important implications for wave‐particle interactions at a range of energies.

Intra-arterial chemotherapy (IAC) represents a mainstay in the treatment of retinoblastoma. In a minority of cases, the external carotid artery (ECA) serves as the dominant supply to the central retinal artery and is associated with prolonged fluoroscopy times and higher intraprocedural radiation doses. The aim of this study was to evaluate the utility of time-of-flight (TOF) magnetic resonance angiography (MRA) for prospective determination of internal (ICA) versus ECA dominance for procedural planning. Between April 2017 and December 2020 (44 months), staging MR prior to IAC for retinoblastoma included variant spatial saturation band position TOF angiography. Exams were then retrospectively reviewed for concordance of ICA versus ECA dominance between the two modalities. Eight consecutive patients were included in the study. Mean patient age at time of diagnosis was 20.3 ± 10.7 months (range: 2.7–33.2 months). Ten affected eyes were included (2 cases of bilateral disease), with stage D disease in eight eyes and stage B disease in two eyes. MRA techniques demonstrated antegrade ophthalmic artery (OA) flow in 9/10 (90%) of affected eyes. Subsequent catheter angiography confirmed ICA dominant supply in 9/9 (100%). For a single affected eye (10%), the OA was demonstrated as orthotopic by T2 flow void, nonvisualized on anterior saturation TOF sequences, and faintly visualized on posterior saturation TOF sequences. Aggregate MRA to catheter angiographic concordance was 10/10 (100%). Variant saturation TOF MRA predicts ICA versus ECA dominant supply to the central retinal artery in retinoblastoma.

Preparing faculty to conduct quality teaching is critical to maximize student learning and the educational experience. As increased attention to faculty effectiveness and effect of their teaching program is observed, the more important it becomes for faculty to engage in the scholarship of teaching and learning (SoTL). The workshop “Developing a scholarship of teaching and learning portfolio in applied horticulture” was conducted at the 2022 American Society for Horticultural Science conference in Chicago, IL, USA, and featured a panel of teaching scholars who provided insight and guidance for developing, enhancing, evaluating, and promoting SoTL for both traditional classroom teachers and extension educators.

Abstract A 2D Cartesian simulation is presented and used to solve the ideal, low‐beta, linear magnetohydrodynamics equations. A simulation is used to investigate the propagation of Alfvén waves through inhomogeneities in Alfvén speed and density. In particular, the loss of Alfvén wave energy through coupling to the fast wave, and also the form of the Alfvén wave as it emerges from the inhomogeneous region is studied. Potential applications of this include the magnetospheres of both Jupiter and the Earth. The results show that Alfvén waves can be significantly distorted by a nonuniformity and still propagate through the region efficiently, with relatively small amounts of Alfvén wave energy lost through mode conversion and reflection.

This paper introduces arfpy, a python implementation of Adversarial Random Forests, which is a lightweight procedure for synthesizing new data that resembles some given data. The software arfpy equips practitioners with straightforward functionalities for both density estimation and generative modeling. The method is particularly useful for tabular data and its competitive performance is demonstrated in previous literature. As a major advantage over the mostly deep learning based alternatives, arfpy combines the method’s reduced requirements in tuning efforts and computational resources with a user-friendly python interface. This supplies audiences across scientific fields with software to generate data effortlessly. https://github.com/bips-hb/arfpy.

Summary: A vexing observation in genome-wide association studies (GWASs) is that parallel analyses in different species may not identify orthologous genes. Here, we demonstrate that cross-species translation of GWASs can be greatly improved by an analysis of co-localization within molecular networks. Using body mass index (BMI) as an example, we show that the genes associated with BMI in humans lack significant agreement with those identified in rats. However, the networks interconnecting these genes show substantial overlap, highlighting common mechanisms including synaptic signaling, epigenetic modification, and hormonal regulation. Genetic perturbations within these networks cause abnormal BMI phenotypes in mice, too, supporting their broad conservation across mammals. Other mechanisms appear species specific, including carbohydrate biosynthesis (humans) and glycerolipid metabolism (rodents). Finally, network co-localization also identifies cross-species convergence for height/body length. This study advances a general paradigm for determining whether and how phenotypes measured in model species recapitulate human biology.

Background: The Weill Cornell Medicine, Samuel J. Wood Library’s Systematic Review (SR) service began in 2011, with 2021 marking a decade of service. This paper will describe how the service policies have grown and will break down our service quantitatively over the past 11 years to examine SR timelines and trends. Case Presentation: We evaluated 11 years (2011-2021) of SR request data from our in-house documentation. In the years assessed, there have been 319 SR requests from 20 clinical departments, leading to 101 publications with at least one librarian collaborator listed as co-author. The average review took 642 days to publication, with the longest at 1408 days, and the shortest at 94 days. On average, librarians spent 14.7 hours in total on each review. SR projects were most likely to be abandoned at the title/abstract screening phase. Several policies have been put into place over the years in order to accommodate workflows and demand for our service. Discussion: The SR service has seen several changes since its inception in 2011. Based on the findings and emerging trends discussed here, our service will inevitably evolve further to adapt to these changes, such as machine learning-assisted technology.

Sustainable flood risk management (SFRM) has become popular since the 1980s. Many governmental and non-governmental organisations have been keen on implementing the SFRM strategies by integrating social, ecological, and economic themes into their flood risk management (FRM) practices. However, the justifications for SFRM are still somewhat embryonic, and it is not yet clear whether this concept is influencing current policies in different countries. This paper reviews the past and current flood management experiences from flood defence to SFRM in four developed countries to highlight lessons for coastal megacities in development. The paper explores recent strategies such as “Making Space for Water”, Planning Policy Statement 25 (PPS25), and the National Planning Policy Framework (NPPF) in the UK and “Room for the River” in the Netherlands, which were implemented to mitigate flooding, integrate FRM with sustainability concepts, and deliver sound FRM practice for future generations. In this context, the United States has also established a National Flood Insurance Program (NFIP), and in a different approach, Japan has developed an advanced flood warning and evacuation contingency system to prepare for climatic extremes. These case studies give good lessons in achieving long-term SFRM to deliver sound flood management practices considering socio-economic and environmental concerns. Most developing coastal megacities especially in Asia are still heavily reliant on a traditional hard-engineering approach, which may not be enough to mitigate substantial risks due to human factors (e.g. large population, rapid socio-economic growth, subsidence from excessive groundwater extraction) and natural factors (e.g. climate change including sea-level rise and land subsidence). It is clear that different countries and cities have their interpretation of SFRM, but this paper explores how policymakers can adopt “mixed options” to move towards long-term thinking about sustainability with social, economic, and environmental considerations.

Abstract Primary challenges for current and future precision neutrino experiments using liquid argon time projection chambers (LArTPCs) include understanding detector effects and quantifying the associated systematic uncertainties. This paper presents a novel technique for assessing and propagating LArTPC detector-related systematic uncertainties. The technique makes modifications to simulation waveforms based on a parameterization of observed differences in ionization signals from the TPC between data and simulation, while remaining insensitive to the details of the detector model. The modifications are then used to quantify the systematic differences in low- and high-level reconstructed quantities. This approach could be applied to future LArTPC detectors, such as those used in SBN and DUNE.

Abstract In 1977, a sample of diseased adult honeybees (Apis mellifera) from Egypt was found to contain large amounts of a previously unknown virus, Egypt bee virus, which was subsequently shown to be serologically related to deformed wing virus (DWV). By sequencing the original isolate, we demonstrate that Egypt bee virus is in fact a fourth unique, major variant of DWV (DWV-D): more closely related to DWV-C than to either DWV-A or DWV-B. DWV-A and DWV-B are the most common DWV variants worldwide due to their close relationship and transmission by Varroa destructor. However, we could not find any trace of DWV-D in several hundred RNA sequencing libraries from a worldwide selection of honeybee, varroa and bumblebee samples. This means that DWV-D has either become extinct, been replaced by other DWV variants better adapted to varroa-mediated transmission, or persists only in a narrow geographic or host range, isolated from common bee and beekeeping trade routes.

Abstract The MicroBooNE liquid argon time projection chamber located at Fermilab is a neutrino experiment dedicated to the study of short-baseline oscillations, the measurements of neutrino cross sections in liquid argon, and to the research and development of this novel detector technology. Accurate and precise measurements of calorimetry are essential to the event reconstruction and are achieved by leveraging the TPC to measure deposited energy per unit length along the particle trajectory, with mm resolution. We describe the non-uniform calorimetric reconstruction performance in the detector, showing dependence on the angle of the particle trajectory. Such non-uniform reconstruction directly affects the performance of the particle identification algorithms which infer particle type from calorimetric measurements. This work presents a new particle identification method which accounts for and effectively addresses such non-uniformity. The newly developed method shows improved performance compared to previous algorithms, illustrated by a 93.7% proton selection efficiency and a 10% muon mis-identification rate, with a fairly loose selection of tracks performed on beam data. The performance is further demonstrated by identifying exclusive final states in ν μ CC interactions. While developed using MicroBooNE data and simulation, this method is easily applicable to future LArTPC experiments, such as SBND, ICARUS, and DUNE.

Rotavirus is the most common pathogen causing pediatric diarrhea and an important cause of morbidity and mortality in low- and middle-income countries. Previous evidence suggests that the introduction of rotavirus vaccines in national immunization schedules resulted in dramatic declines in disease burden but may also be changing the rotavirus genetic landscape and driving the emergence of new genotypes. We report genotype data of more than 16,000 rotavirus isolates from 40 countries participating in the Global Rotavirus Surveillance Network. Data from a convenience sample of children under five years of age hospitalized with acute watery diarrhea who tested positive for rotavirus were included. Country results were weighted by their estimated rotavirus disease burden to estimate regional genotype distributions. Globally, the most frequent genotypes identified after weighting were G1P[8] (31%), G1P[6] (8%) and G3P[8] (8%). Genotypes varied across WHO Regions and between countries that had and had not introduced rotavirus vaccine. G1P[8] was less frequent among African (36 vs 20%) and European (33 vs 8%) countries that had introduced rotavirus vaccines as compared to countries that had not introduced. Our results describe differences in the distribution of the most common rotavirus genotypes in children with diarrhea in low- and middle-income countries. G1P[8] was less frequent in countries that had introduced the rotavirus vaccine while different strains are emerging or re-emerging in different regions.

Abstract Background Transgender women in the United States (U.S.) experience a disproportionate burden of HIV infection and challenges to engagement in HIV prevention and care. This excess burden is driven by structural and economic inequities. Microeconomic interventions may be effective strategies for reducing HIV inequities for this population. However, few studies have explored transgender women’s preferences for microeconomic interventions to address structural determinants of HIV vulnerability. Methods We conducted individual interviews with 19 adult transgender women in 2 U.S. cities (Richmond, VA and St. Louis, MO) who reported one or more sexual risk behaviors and recent economic hardship related to employment/income, housing, or food security. Interviews were recorded, transcribed, and analyzed using thematic content analysis. Results The majority (74%) of transgender women were racial/ethnic minorities with mean age of 26.3 years. 89% were currently economically vulnerable; and 23% were employed full-time. 37% reported living with HIV. Participants expressed strong support for unrestricted vouchers, with many expressing the need for funds to support gender-affirming interventions. Assistance with how to budget and save and support for job acquisition, career planning, and employment sustainment were also preferred, including access to non-stigmatizing employment. Visible transgender leadership, group empowerment, and small (rather than large) numbers of participants were considered important aspects of intervention design for transgender women, including outreach through existing transgender networks to facilitate inclusion. Incorporating HIV counseling and testing to reduce vulnerability to HIV was acceptable. However, transgender women enrolled in the study preferred that HIV not be the focus of an intervention. Conclusions Flexible microeconomic interventions that support gender affirming interventions, improve financial literacy, and provide living-wage non-stigmatizing employment are desired by economically vulnerable transgender women. While not focused on HIV, such interventions have the potential to reduce the structural drivers of HIV vulnerability among transgender women.

Objectives Spin is a reporting practice in which study results are misrepresented by overestimating efficacy or underestimating harm. Prevalence of spin varies between clinical specialties, and estimates are based almost entirely on clinical trials. Little is known about spin in systematic reviews.Design We performed a cross-sectional analysis searching MEDLINE and Embase for systematic reviews and meta-analyses pertaining to antiplatelet therapies following acute coronary syndrome on 2 June 2020. Data were extracted evaluating the presence of spin and study characteristics, including methodological quality as rated by A MeaSurement Tool to Assess systematic Reviews (AMSTAR-2). All data extraction was conducted in a masked, duplicate manner from 2 June 2020 to 26 June 2020.Participants and setting Not applicable.Primary and secondary outcome measures We assessed abstracts of systematic reviews on antiplatelet therapy following acute coronary syndrome and evaluated the prevalence of the nine most severe types of spin. We additionally explored associations between spin and certain study characteristics, including quality.Results Our searches returned 15 263 articles, and 185 systematic reviews met inclusion criteria. Of these 185 reviews, 31.9% (59/185) contained some form of spin in the abstract. Seven forms of spin (1, 2, 3, 4, 5, 7 and 9) among the nine most severe were identified. No instances of types 6 or 8 were found. There were no statistically significant relationships between spin and the evaluated study characteristics or AMSTAR-2 appraisals.Conclusions Spin was present in abstracts for systematic reviews and meta-analyses; subsequent studies are needed to identify correlations between spin and specific study characteristics. There were no statistically significant associations between spin and study characteristics or AMSTAR-2 ratings; however, implementing changes will ensure that spin is reduced in the field of cardiology as well as other fields of medicine.

This article describes a data-driven framework based on spatiotemporal machine learning to produce distribution maps for 16 tree species (Abies alba Mill., Castanea sativa Mill., Corylus avellana L., Fagus sylvatica L., Olea europaea L., Picea abies L. H. Karst., Pinus halepensis Mill., Pinus nigra J. F. Arnold, Pinus pinea L., Pinus sylvestris L., Prunus avium L., Quercus cerris L., Quercus ilex L., Quercus robur L., Quercus suber L. and Salix caprea L.) at high spatial resolution (30 m). Tree occurrence data for a total of three million of points was used to train different algorithms: random forest, gradient-boosted trees, generalized linear models, k-nearest neighbors, CART and an artificial neural network. A stack of 305 coarse and high resolution covariates representing spectral reflectance, different biophysical conditions and biotic competition was used as predictors for realized distributions, while potential distribution was modelled with environmental predictors only. Logloss and computing time were used to select the three best algorithms to tune and train an ensemble model based on stacking with a logistic regressor as a meta-learner. An ensemble model was trained for each species: probability and model uncertainty maps of realized distribution were produced for each species using a time window of 4 years for a total of six distribution maps per species, while for potential distributions only one map per species was produced. Results of spatial cross validation show that the ensemble model consistently outperformed or performed as good as the best individual model in both potential and realized distribution tasks, with potential distribution models achieving higher predictive performances (TSS = 0.898, R2logloss = 0.857) than realized distribution ones on average (TSS = 0.874, R2logloss = 0.839). Ensemble models for Q. suber achieved the best performances in both potential (TSS = 0.968, R2logloss = 0.952) and realized (TSS = 0.959, R2logloss = 0.949) distribution, while P. sylvestris (TSS = 0.731, 0.785, R2logloss = 0.585, 0.670, respectively, for potential and realized distribution) and P. nigra (TSS = 0.658, 0.686, R2logloss = 0.623, 0.664) achieved the worst. Importance of predictor variables differed across species and models, with the green band for summer and the Normalized Difference Vegetation Index (NDVI) for fall for realized distribution and the diffuse irradiation and precipitation of the driest quarter (BIO17) being the most frequent and important for potential distribution. On average, fine-resolution models outperformed coarse resolution models (250 m) for realized distribution (TSS = +6.5%, R2logloss = +7.5%). The framework shows how combining continuous and consistent Earth Observation time series data with state of the art machine learning can be used to derive dynamic distribution maps. The produced predictions can be used to quantify temporal trends of potential forest degradation and species composition change.

Introduction Studies regarding environmental contributions on callous-unemotional (CU) traits in children have informed about the protective role of positive parenting. However, it has not been explored whether findings from these studies -mostly conducted in High-Income Countries- can be generalised to Low-Middle-Income Countries (LMICs). Exposure to community violence is common in LMICs and is associated with emotional and behavioural problems in children. Therefore, it may represent an environmental risk factor for CU traits. Objectives This prospective study explores whether positive parenting has a protective role in relation to CU traits in young Colombian children whose families have been exposed to community violence. Methods We assessed 235 families with children at age 3.5 years, from three contrasting regions of Colombia, using observations of mother-child interactions and maternal reports of community violence at ages 3.5 and 5.0 years. Results Hierarchical multiple linear regression models indicated that maternal positivity at 3.5 years was associated with lower CU traits at age 5.0 years only in children of families exposed to community violence (interaction term p= .001). In the exposed group maternal positivity explained 10% of the variance (β= -.34, p= .001) with low positivity associated with elevated CU traits and high positivity with low CU traits. Maternal praise was not associated with CU traits. However, maternal negativity during play was associated with elevated CU traits as a main effect. Conclusions Based on these findings, whether or not exposure to community violence is associated with elevated CU traits depends on maternal positivity, with low positivity creating vulnerability, and high positivity, resilience. Disclosure No significant relationships.

The University of Victoria Earth System Climate Model (UVic ESCM) of intermediate complexity has been a useful tool in recent assessments of long-term climate changes, including both paleo-climate modelling and uncertainty assessments of future warming. Since the last official release of the UVic ESCM 2.9 and the two official updates during the last decade, considerable model development has taken place among multiple research groups. The new version 2.10 of the University of Victoria Earth System Climate Model presented here will be part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). More precisely it will be used in the intercomparison of Earth system models of intermediate complexity (EMIC), such as the C4MIP, the Carbon Dioxide Removal and Zero Emissions Commitment model intercomparison projects (CDR-MIP and ZECMIP, respectively). It now brings together and combines multiple model developments and new components that have come about since the last official release of the model. The main additions to the base model are (i) an improved biogeochemistry module for the ocean, (ii) a vertically resolved soil model including dynamic hydrology and soil carbon processes, and (iii) a representation of permafrost carbon. To set the foundation of its use, we here describe the UVic ESCM 2.10 and evaluate results from transient historical simulations against observational data. We find that the UVic ESCM 2.10 is capable of reproducing changes in historical temperature and carbon fluxes well. The spatial distribution of many ocean tracers, including temperature, salinity, phosphate and nitrate, also agree well with observed tracer profiles. The good performance in the ocean tracers is connected to an improved representation of ocean physical properties. For the moment, the main biases that remain are a vegetation carbon density that is too high in the tropics, a higher than observed change in the ocean heat content (OHC) and an oxygen utilization in the Southern Ocean that is too low. All of these biases will be addressed in the next updates to the model.

Abstract Background The objective of this study was to assess the overall quality of study-level meta-analyses in high-ranking journals using commonly employed guidelines and standards for systematic reviews and meta-analyses. Methods 100 randomly selected study-level meta-analyses published in ten highest-ranking clinical journals in 2016–2017 were evaluated by medical librarians against 4 assessments using a scale of 0–100: the Peer Review of Electronic Search Strategies (PRESS), Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), Institute of Medicine’s (IOM) Standards for Systematic Reviews, and quality items from the Cochrane Handbook. Multiple regression was performed to assess meta-analyses characteristics’ associated with quality scores. Results The overall median (interquartile range) scores were: PRESS 62.5(45.8–75.0), PRISMA 92.6(88.9–96.3), IOM 81.3(76.6–85.9), and Cochrane 66.7(50.0–83.3). Involvement of librarians was associated with higher PRESS and IOM scores on multiple regression. Compliance with journal guidelines was associated with higher PRISMA and IOM scores. Conclusion This study raises concerns regarding the reporting and methodological quality of published MAs in high impact journals Early involvement of information specialists, stipulation of detailed author guidelines, and strict adherence to them may improve quality of published meta-analyses.