A comparison of C/B ratios from studies using receiver operating characteristic curve analysis

Crystalline lens nuclear age prediction as a new biomarker of nucleus degeneration

BACKGROUND

The crystalline lens is a transparent structure of the eye to focus light on the retina. It becomes muddy, hard and dense with increasing age, which makes the crystalline lens gradually lose its function. We aim to develop a nuclear age predictor to reflect the degeneration of the crystalline lens nucleus.

METHODS

First we trained and internally validated the nuclear age predictor with a deep-learning algorithm, using 12 904 anterior segment optical coherence tomography (AS-OCT) images from four diverse Asian and American cohorts: Zhongshan Ophthalmic Center with Machine0 (ZOM0), Tomey Corporation (TOMEY), University of California San Francisco and the Chinese University of Hong Kong. External testing was done on three independent datasets: Tokyo University (TU), ZOM1 and Shenzhen People's Hospital (SPH). We also demonstrate the possibility of detecting nuclear cataracts (NCs) from the nuclear age gap.

FINDINGS

In the internal validation dataset, the nuclear age could be predicted with a mean absolute error (MAE) of 2.570 years (95% CI 1.886 to 2.863). Across the three external testing datasets, the algorithm achieved MAEs of 4.261 years (95% CI 3.391 to 5.094) in TU, 3.920 years (95% CI 3.332 to 4.637) in ZOM1-NonCata and 4.380 years (95% CI 3.730 to 5.061) in SPH-NonCata. The MAEs for NC eyes were 8.490 years (95% CI 7.219 to 9.766) in ZOM1-NC and 9.998 years (95% CI 5.673 to 14.642) in SPH-NC. The nuclear age gap outperformed both ophthalmologists in detecting NCs, with areas under the receiver operating characteristic curves of 0.853 years (95% CI 0.787 to 0.917) in ZOM1 and 0.909 years (95% CI 0.828 to 0.978) in SPH.

INTERPRETATION

The nuclear age predictor shows good performance, validating the feasibility of using AS-OCT images as an effective screening tool for nucleus degeneration. Our work also demonstrates the potential use of the nuclear age gap to detect NCs.

Northeast Atlantic elasmobranch community on the move: Functional reorganization in response to climate change

While spatial distribution shifts have been documented in many marine fishes under global change, the responses of elasmobranchs have rarely been studied, which may have led to an underestimation of their potential additional threats. Given their irreplaceable role in ecosystems and their high extinction risk, we used a 24-year time series (1997-2020) of scientific bottom trawl surveys to examine the effects of climate change on the spatial distribution of nine elasmobranch species within Northeast Atlantic waters. Using a hierarchical modeling of species communities, belonging to the joint species distribution models, we found that suitable habitats for four species increased on average by a factor of 1.6 and, for six species, shifted north-eastwards and/or to deeper waters over the past two decades. By integrating species traits, we showed changes in habitat suitability led to changes in the elasmobranchs trait composition. Moreover, communities shifted to deeper waters and their mean trophic level decreased. We also note an increase in the mean community size at maturity concurrent with a decrease in fecundity. Because skates and sharks are functionally unique and dangerously vulnerable to both climate change and fishing, we advocate for urgent considerations of species traits in management measures. Their use would make it better to identify species whose loss could have irreversible impacts in face of the myriad of anthropogenic threats.

Insights from the biogeographic approach for biocontrol of invasive alien pests: Estimating the ecological niche overlap of three egg parasitoids against Spodoptera frugiperda in China

Spodoptera frugiperda, the fall armyworm, causes major damage to maize and >80 other crops worldwide. Since S. frugiperda successfully invaded China in 2018 via long-distance migration from Myanmar, it has caused major maize yield losses and posed a severe threat to maize production and food security. The biocontrol approach for S. frugiperda using natural enemies is environmentally safe and effective. Estimating the potential suitable area (PSA) for S. frugiperda and its natural enemies can provide insights for its biocontrol and management. Therefore, based on the global distribution records and bioclimatic variables, we modeled the PSA of S. frugiperda and three egg parasitoids in China using an ensemble model (EM). We found that the prediction results of the EM were more reliable than those of a single model. The PSAs of S. frugiperda and its three egg parasitoids were mainly attributed to temperature variables. The PSA of S. frugiperda was divided into migratory and overwintering areas using the mean January 10 °C isotherm from 2018 to 2022. In the overwintering area, Trichogramma chilonis had the largest PSA overlap with S. frugiperda (94.57 %), followed by Telenomus remus (68.64 %) and Trichogramma dendrolimi (67.53 %). Telenomus remus and Tr. chilonis were the most effective egg parasitoids against S. frugiperda in the overwintering area. In the migratory area, Tr. chilonis had the largest PSA overlap with S. frugiperda (91.36 %), followed by Tr. dendrolimi (81.70 %) and Te. remus (15.23 %). Trichogramma dendrolimi would be the most effective egg parasitoid against S. frugiperda in the Yangtze River Basin and northeastern China. Trichogramma chilonis was the most effective egg parasitoid against S. frugiperda in central China. Our findings indicate that the three native egg parasitoids would be "good regulators" of S. frugiperda outbreaks in China.

Assessing risk from invasive alien plants in China: Reconstructing invasion history and estimating distribution patterns of Lolium temulentum and Aegilops tauschii

INTRODUCTION

The establishment of invasive alien plants (IAPs) is primarily driven by climate warming and human activities, and their populations have a negative impact on agricultural economics, ecological systems, and human health. Lolium temulentum and Aegilops tauschii are critical IAPs in China because they reduce the quality of cereal grains and decrease wheat yields. Lolium temulentum is a winter-temperate weed that spreads easily and is poisonous to humans and animals. Aegilops tauschii is resistant to herbicides, has a high reproductive rate, and frequently grows in wheat. Both species have been listed in the Ministry of Agriculture and Rural Affairs of the People's Republic of China's management catalog since 2006.

METHODS

In the present study, the historical occurrence and invasion of each species were collected and reconstructed, which showed that the population outbreak of L. temulentum began in 2010, whereas that of A. tauschii began in 2000. Using the optimal MaxEnt model, the geographical distributions of L. temulentum and A. tauschii were predicted based on screened species occurrences and environmental variables under the current and three future scenarios in the 2030s and 2050s (i.e., SSP1-2.6, SSP2-4.5, and SSP5-8.5).

RESULTS

The mean AUC values were 0.867 and 0.931 for L. temulentum and A. tauschii, respectively. Human influence index (HII), mean temperature of coldest quarter (bio11), and precipitation of coldest quarter (bio19) were the most significant variables for L. temulentum, whereas human influence index, temperature seasonality (standard deviation×100) (bio4), and annual mean temperature (bio1) were the critical environmental variables for A. tauschi. Suitable habitat areas in China for L. temulentum and A. tauschii currently covered total areas of 125 × 10⁴ and 235 × 10⁴ km², respectively. Future suitable areas of L. temulentum reached the maximum under SSP2-4.5, from 2021 to 2060, whereas for A. tauschii they reached the maximum under SSP5-8.5, from 2021 to 2060. Furthermore, the overlap area under the current climate conditions for L. temulentum and A. tauschii was approximately 90 × 10⁴ km², mainly located in Hubei, Anhui, Jiangsu, Shandong, Henan, Shaanxi, Shanxi, and Hebei. The overlap areas decreased in the 2030s, increased in the 2050s, and reached a maximum under SSP1-2.6 (or SSP2-4.5) with an approximate area of 104 × 10⁴ km². The centroid of L. temulentum in Henan was transferred to the southwest, whereas for A. tauschii it transferred to higher latitudes in the northeast.

DISCUSSION

Our findings provide a practical reference for the early warning, control, and management of these two destructive IAP populations in China.

Small-scale farming in drylands: New models for resilient practices of millet and sorghum cultivation

Finger millet, pearl millet and sorghum are amongst the most important drought-tolerant crops worldwide. They constitute primary staple crops in drylands, where their production is known to date back over 5000 years ago. Compared to other crops, millets and sorghum have received less attention until very recently, and their production has been progressively reduced in the last 50 years. Here, we present new models that focus on the ecological factors driving finger millet, pearl millet and sorghum traditional cultivation, with a global perspective. The interaction between environment and traditional agrosystems was investigated by Redundancy Analysis of published literature and tested against novel ethnographic data. Contrary to earlier beliefs, our models show that the total annual precipitation is not the most determinant factor in shaping millet and sorghum agriculture. Instead, our results point to the importance of other variables such as the duration of the plant growing cycle, soil water-holding capacity or soil nutrient availability. This highlights the potential of finger millet, pearl millet and sorghum traditional cultivation practices as a response to recent increase of aridity levels worldwide. Ultimately, these practices can play a pivotal role for resilience and sustainability of dryland agriculture.

Potential global geographical distribution of Lolium temulentum L. under climate change

Invasive alien plants posed a significant threat to natural ecosystems, biodiversity, agricultural production, as well as human and livestock health. Lolium temulentum, an annual invasive alien weed with fibrous roots, can reduce wheat production and cause economic losses. Moreover, the consumption of grains or cereal products mixed with darnel can cause dizziness, vomiting, and even death. Therefore, darnel is regarded as one of ″the worst weeds around the world″. In the present study, we predicted the potential global geographical distribution of L. temulentum using an optimal MaxEnt model, based on occurrence records and related environmental variables. The mean AUC, TSS, and KAPPA were 0.95, 0.778, and 0.75, indicating the MaxEnt model accuracy was excellent. The significant environmental variables, including the mean temperature of coldest quarter (bio 11), precipitation of coldest quarter (bio 19), temperature annual range (bio 7), and annual precipitation (bio 12), produced a great impact on the potential global geographical distribution of L. temulentum. Under the current climate, L. temulentum was primarily distributed in south-eastern Asia, Europe, and south-eastern North America. The widest total suitable habitat was distributed in Asia, covering nearly 796 × 10⁴ km². By the 2050s, the potential geographical distribution of L. temulentum was expected to decrease in the Northern Hemisphere, and shrink gradually in southern America, Africa, and Oceania. Moreover, the distribution center of L. temulentum was expected to shift from Asia to Europe. Based on these predictions, changes in the suitable habitats for L. temulentum between Europe and Asia warrant close attention to prevent further spread.

Error rates in SARS-CoV-2 testing examined with Bayes' theorem

The SARS-CoV-2 pandemic has created a demand for large scale testing, as part of the effort to understand and control transmission. It is important to quantify the error rates of test equipment under field conditions, which might differ significantly from those obtained in the laboratory. A literature review on SARS-CoV-2 reverse-transcription polymerase chain reaction (RT-PCR) is used to construct a clinical test confusion matrix. A simple correction method for bulk test results is then demonstrated with examples. The required sensitivity and specificity of a test are explored for societal needs and use cases, before a sequential analysis of common example scenarios is explored. The analysis suggests that many of the people with mild symptoms and positive test results are unlikely to be infected with SARS-CoV-2 in some regions. It is concluded that current and foreseen alternative tests can not be used to "clear" people as being non-infected. Recommendations are given that regional authorities must establish a programme to monitor operational test characteristics before launching large scale testing; and that large scale testing for tracing infection networks in some regions is not viable, but may be possible in a focused way that does not exceed the working capacity of the laboratories staffed by competent experts. RT-PCR tests can not be solely relied upon as the gold standard for SARS-CoV-2 diagnosis at scale, instead clinical assessment supported by a range of expert diagnostic tests should be used.

Implications of the 2019-2020 megafires for the biogeography and conservation of Australian vegetation

Australia’s 2019–2020 ‘Black Summer’ bushfires burnt more than 8 million hectares of vegetation across the south-east of the continent, an event unprecedented in the last 200 years. Here we report the impacts of these fires on vascular plant species and communities. Using a map of the fires generated from remotely sensed hotspot data we show that, across 11 Australian bioregions, 17 major native vegetation groups were severely burnt, and up to 67–83% of globally significant rainforests and eucalypt forests and woodlands. Based on geocoded species occurrence data we estimate that >50% of known populations or ranges of 816 native vascular plant species were burnt during the fires, including more than 100 species with geographic ranges more than 500 km across. Habitat and fire response data show that most affected species are resilient to fire. However, the massive biogeographic, demographic and taxonomic breadth of impacts of the 2019–2020 fires may leave some ecosystems, particularly relictual Gondwanan rainforests, susceptible to regeneration failure and landscape-scale decline.

Fires triggered by climate change threaten plant diversity in many biomes. Here the authors investigate how the catastrophic fires of 2019–2020 affected the vascular flora of SE Australia. They report that 816 species were highly impacted, including taxa of biogeographic and conservation interest.

SEASIM-NEAM: A Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics

In 2018 we published a spatially-explicit individual-based model (IBM) that uses satellite-derived maps of food availability and temperature to predict Northeast Atlantic mackerel (Scomber scombrus, NEAM) population dynamics. Since then, to address various ecological questions, we have extended the IBM to include additional processes and data. Throughout its development, technical documents have been provided in the form of e.g. supplementary information to published articles. However, we acknowledge that it would be difficult for potential users to collate information from separate supplementary documents and gain a full understanding of the current state of the IBM. Here, we provide a full technical specification of the latest version of our IBM. The technical specification is provided in the standard ODD (Overview, Design concepts and Details) format, and supplemented by a TRACE (TRAnsparent and Comprehensive model Evaludation) document. For the first time, we give our model the acronym SEASIM-NEAM: a Spatially-Explicit Agent-based SIMulator of North East Atlantic Mackerel population dynamics. This article supersedes previous documentation. Going forward we hope that this article will stimulate development of similar models.•This article collates improvements that have been made to SEASIM-NEAM over time.

Monitoring 2.0: Update on the Halyomorpha halys Invasion of Trentino

“BugMap” is a citizen science mobile application that provides a platform for amateur and expert scientists to report sightings of two invasive insect pests, the tiger mosquito Aedes albopictus Skuse (Diptera: Culicidae) and the brown marmorated stink bug, Halyomorpha halys Stål (Hemiptera: Pentatomidae). The latter is a notorious pest of fruit trees, vegetables, ornamentals, and row crops, inflicting severe agricultural and ecological disturbances in invaded areas. Our approach consists of coupling traditional monitoring with citizen science to uncover H. halys invasion in Trentino. The project was initiated in 2016 and the first results were reported in 2018. Here, we revisit our initiative four years after its adoption and unravel new information related to the invader dispersal and overwintering capacity. We found that our previous model predicted the current distribution of H. halys in Trentino with an accuracy of 72.5%. A new MaxEnt model was generated by pooling all reports received so far, providing a clearer perspective on areas at risk of stink bug establishment in this north Italian region. The information herein presented is of immediate importance for enhancing monitoring strategies of this pest and for refining its integrated management tactics.

Is Myotis lavali (Chiroptera, Vespertilionidae) endemic to the South American dry diagonal?

Myotis lavali was described from the M. nigricans complex based on museum specimens from the Caatinga of northeastern Brazil. Current records of the species from about 10 localities suggest that M. lavali seems to occur throughout the South American dry corridor, with peripheral records in the Atlantic Forest. Based on new distribution records, we assess if M. lavali is endemic to the South American dry diagonal corridor through species distribution modeling using an ensemble approach. We obtained 35 occurrences for the species and built a consensus scenario based on 12 algorithms to model its distribution. Even using different thresholds to assign presence and absence of M. lavali, 95–99% of its predicted distribution is within the dry corridor, with few areas in the boundary of the Atlantic Forest, especially in deciduous forests. Therefore, our results support that M. lavali is indeed very likely restricted to the dry diagonal and, although it occupies forested areas, the core of its distribution lies in the Caatinga and in the Cerrado regions of Brazil.

Impacts of climate change on infestations of Dubas bug (Ommatissus lybicus Bergevin) on date palms in Oman

Climate change has determined shifts in distributions of species and is likely to affect species in the future. Our study aimed to (i) demonstrate the linkage between spatial climatic variability and the current and historical Dubas bug (Ommatissus lybicus Bergevin) distribution in Oman and (ii) model areas becoming highly suitable for the pest in the future. The Dubas bug is a pest of date palm trees that can reduce the crop yield by 50% under future climate scenarios in Oman. Projections were made in three species distribution models; generalized linear model, maximum entropy, boosted regression tree using of four global circulation models (GCMs) (a) HadGEM2, (b) CCSM4, (c) MIROC5 and (d) HadGEM2-AO, under four representative concentration pathways (2.6, 4.5, 6.0 and 8.5) for the years 2050 and 2070. We utilized the most commonly used threshold of maximum sensitivity + specificity for classifying outputs. Results indicated that northern Oman is currently at great risk of Dubas bug infestations (highly suitable climatically) and the infestations level will remain high in 2050 and 2070. Other non-climatic integrated pest management methods may be greater value than climatic parameters for monitoring infestation levels, and may provide more effective strategies to manage Dubas bug infestations in Oman. This would ensure the continuing competitiveness of Oman in the global date fruit market and preserve national yields.

AUDIT and AUDIT-C as screening instruments for alcohol problem use in adolescents

BACKGROUND

The Alcohol Use Disorders Identification Test (AUDIT) is commonly used in adults to screen for harmful alcohol consumption but few studies exist on its use among adolescents. Our aim was to validate the AUDIT and its derivative consumption questionnaire (AUDIT-C) as screening instruments for the detection of problem use of alcohol in adolescents.

METHODS

621 adolescents (age-range, 12-19 years) were drawn from clinical and population samples who completed the AUDIT questionnaire. Psychiatric diagnoses were assessed using K-SADS-PL. A rating based on the K-SADS-PL was used to assess alcohol use habits, alcohol use disorders, screening and symptom criteria questions. Screening performance of the AUDIT and AUDIT-C sum scores and Receiver Operating Characteristic (ROC) curves were calculated. The diagnostic odds ratios (dOR) were calculated to express the overall discrimination between cut-offs.

RESULTS

Comparisons of ROC between the AUDIT and AUDIT-C pairs indicated a slightly better test performance by AUDIT for the whole sample and in a proportion of the subsamples. Optimal cut-off value for the AUDIT was ≥5 (sensitivity 0.931, specificity 0.772, dOR 45.22; 95% CI: 24.72-83.57) for detecting alcohol problem use. The corresponding optimal cut-off value for the AUDIT-C was ≥3 in detecting alcohol problem use (sensitivity 0.952, specificity 0.663, dOR 39.31; 95% CI: 19.46-78.97). Agreement between the AUDIT and AUDIT-C using these cut-off scores was high at 91.9%.

CONCLUSIONS

Our results for the cut-off scores for the early detection of alcohol problem use in adolescents are ≥5 for AUDIT, and ≥3 for AUDIT-C.

Flow Management to Control Excessive Growth of Macrophytes - An Assessment Based on Habitat Suitability Modeling

Mediterranean rivers in intensive agricultural watersheds usually display outgrowths of macrophytes - notably alien species - due to a combination of high concentrations of nutrients in the water runoff and low flows resulting from water abstraction for irrigation. Standard mechanical and chemical control is used to mitigate the problems associated with excessive growth of plant biomass: mainly less drainage capacity and higher flood risk. However, such control measures are cost and labor-intensive and do not present long-term efficiency. Although the high sensitivity of aquatic vegetation to instream hydraulic conditions is well known, management approaches based on flow management remain relatively unexplored. The aim of our study was therefore to apply physical habitat simulation techniques promoted by the Instream Flow Incremental Method (IFIM) to aquatic macrophytes - the first time it has been applied in this context - in order to model shifts in habitat suitability under different flow scenarios in the Sorraia river in central Portugal. We used this approach to test whether the risk of invasion and channel encroachment by nuisance species can be controlled by setting minimum annual flows. We used 960 randomly distributed survey points to analyze the habitat suitability for the most important aquatic species (including the invasive Brazilian milfoil Myriophyllum aquaticum, Sparganium erectum, and Potamogeton crispus) in regard to the physical parameters 'flow velocity,' 'water depth,' and 'substrate size'. We chose the lowest discharge period of the year in order to assess the hydraulic conditions while disturbances were at a low-point, thus allowing aquatic vegetation establishment and subsistence. We then used the two-dimensional hydraulic River2D software to model the potential habitat availability for different flow conditions based on the site-specific habitat suitability index for each physical parameter and species. Our results show that the growth and distribution of macrophytes in the hydrologically stable vegetation period is primarily a function of the local physical instream condition. Using site-specific preference curves and a two-dimensional hydraulic model, it was possible to determine minimum annual flows that might prevent the excessive growth and channel encroachment caused by Myriophyllum aquaticum.

Local, national, and regional viral haemorrhagic fever pandemic potential in Africa: a multistage analysis

BACKGROUND

Predicting when and where pathogens will emerge is difficult, yet, as shown by the recent Ebola and Zika epidemics, effective and timely responses are key. It is therefore crucial to transition from reactive to proactive responses for these pathogens. To better identify priorities for outbreak mitigation and prevention, we developed a cohesive framework combining disparate methods and data sources, and assessed subnational pandemic potential for four viral haemorrhagic fevers in Africa, Crimean-Congo haemorrhagic fever, Ebola virus disease, Lassa fever, and Marburg virus disease.

METHODS

In this multistage analysis, we quantified three stages underlying the potential of widespread viral haemorrhagic fever epidemics. Environmental suitability maps were used to define stage 1, index-case potential, which assesses populations at risk of infection due to spillover from zoonotic hosts or vectors, identifying where index cases could present. Stage 2, outbreak potential, iterates upon an existing framework, the Index for Risk Management, to measure potential for secondary spread in people within specific communities. For stage 3, epidemic potential, we combined local and international scale connectivity assessments with stage 2 to evaluate possible spread of local outbreaks nationally, regionally, and internationally.

FINDINGS

We found epidemic potential to vary within Africa, with regions where viral haemorrhagic fever outbreaks have previously occurred (eg, western Africa) and areas currently considered non-endemic (eg, Cameroon and Ethiopia) both ranking highly. Tracking transitions between stages showed how an index case can escalate into a widespread epidemic in the absence of intervention (eg, Nigeria and Guinea). Our analysis showed Chad, Somalia, and South Sudan to be highly susceptible to any outbreak at subnational levels.

INTERPRETATION

Our analysis provides a unified assessment of potential epidemic trajectories, with the aim of allowing national and international agencies to pre-emptively evaluate needs and target resources. Within each country, our framework identifies at-risk subnational locations in which to improve surveillance, diagnostic capabilities, and health systems in parallel with the design of policies for optimal responses at each stage. In conjunction with pandemic preparedness activities, assessments such as ours can identify regions where needs and provisions do not align, and thus should be targeted for future strengthening and support.

FUNDING

Paul G Allen Family Foundation, Bill & Melinda Gates Foundation, Wellcome Trust, UK Department for International Development.

Climate Shapes the Geographic Distribution of the Blowfly Sarconesia chlorogaster (Diptera: Calliphoridae): An Environmental Niche Modeling Approach

For all species, abiotic factors directly affect performance, survival and reproduction, and consequently, their geographic distribution. Species distribution models (SDMs) are important tools to predict the influence of abiotic factors in species distributions and has been more applied over the years. However, these models can be built under different algorithms and using different methods to select environmental predictors, which can lead to different results. Five different algorithms and two sets of environmental predictors were compared to predict the geographic distribution of the blowfly Sarconesia chlorogaster (Wiedemann) (Diptera: Calliphoridae). This species has several occurrence points and a considerable amount of biological data available, which makes S. chlorogaster a good model system to compare environmental predictors. Two sets of environmental predictors (mainly derived from temperature and humidity) were built, and the set based on the influence of abiotic variables on the ecophysiology of S. chlorogaster showed better results than the principal component analysis (PCA) approach using 19 climatic variables. We also employed five modeling algorithms-Envelope Score, Mahalanobis Distance, GARP, Support Vector Machines, and Maxent-and the latter two showed the best performances. The results indicate that temperature is the main factor shaping geographic distribution of S. chlorogaster through its effect on fitness. Furthermore, we showed that this species is mainly distributed in south, southeastern, and some northwestern and southwestern sites of South America. In addition, our results also predicted suitable areas in Ecuador and Colombia, countries without previous records.

Perspectives on invasive amphibians in Brazil

Introduced species have the potential to become invasive and jeopardize entire ecosystems. The success of species establishing viable populations outside their original extent depends primarily on favorable climatic conditions in the invasive ranges. Species distribution modeling (SDM) can thus be used to estimate potential habitat suitability for populations of invasive species. Here we review the status of six amphibian species with invasive populations in Brazil (four domestic species and two imported species). We (i) modeled the current habitat suitability and future potential distribution of these six focal species, (ii) reported on the disease status of Eleutherodactylus johnstonei and Phyllodytes luteolus, and (iii) quantified the acoustic overlap of P. luteolus and Leptodactylus labyrinthicus with three co-occurring native species. Our models indicated that all six invasive species could potentially expand their ranges in Brazil within the next few decades. In addition, our SDMs predicted important expansions in available habitat for 2 out of 6 invasive species under future (2100) climatic conditions. We detected high acoustic niche overlap between invasive and native amphibian species, underscoring that acoustic interference might reduce mating success in local frogs. Despite the American bullfrog Lithobates catesbeianus being recognized as a potential reservoir for the frog-killing fungus Batrachochytrium dendrobatidis (Bd) in Brazil, we did not detect Bd in the recently introduced population of E. johnstonei and P. luteolus in the State of São Paulo. We emphasize that the number of invasive amphibian species in Brazil is increasing exponentially, highlighting the urgent need to monitor and control these populations and decrease potential impacts on the locally biodiverse wildlife.

Lactate Elevation During and After Major Cardiac Surgery in Adults: A Review of Etiology, Prognostic Value, and Management

Elevated lactate is a common occurrence after cardiac surgery. This review summarizes the literature on the complex etiology of lactate elevation during and after cardiac surgery, including considerations of oxygen delivery, oxygen utilization, increased metabolism, lactate clearance, medications and fluids, and postoperative complications. Second, the association between lactate and a variety of outcomes are described, and the prognostic role of lactate is critically assessed. Despite the fact that elevated lactate is strongly associated with many important outcomes, including postoperative complications, length of stay, and mortality, little is known about the optimal management of postoperative patients with lactate elevations. This review ends with an assessment of the limited literature on this subject.

P300-Based Asynchronous Brain Computer Interface for Environmental Control System

An asynchronous brain computer interface (A-BCI) determines whether or not a subject is on control state, and produces control commands only in case of subject's being on control state. In this study, we propose a novel P300-based A-BCI algorithm that distinguishes control state and noncontrol state of users. Furthermore, A-BCI algorithm combined with a dynamic stopping function that enables users to select control command independent from a fixed number of intensification sequence. The proposed P300-based A-BCI algorithm uses classification patterns to determine control state and uses optimal operating point of receiver operating characteristics curve for dynamic stopping function. The proposed A-BCI algorithm is also combined with region-based paradigm (RBP) based stimulus interface. The A-BCI algorithm is tested on an internet-based environmental control system. A total of ten nondisabled subjects were participated voluntarily in the experiments. Two-level approach of the RBP-based stimulus interface improves noncontrol state detection accuracy up to 100%. Besides, ratio of incorrect command selection at control state is reduced significantly. At control state, ratio of correct selections, incorrect selections, and missed selections are 93.27%, 1.09%, and 5.63%, respectively. On the other hand, dynamic stopping function enables command selections at least two intensifications. Mean number of intensification sequences to complete the given tasks is 3.15. Thanks to dynamic stopping function, it provides a significant improvement on information transfer rate. The proposed A-BCI algorithm is important in terms of practical BCI systems.

Prevalence dependence in model goodness measures with special emphasis on true skill statistics

It has long been a concern that performance measures of species distribution models react to attributes of the modeled entity arising from the input data structure rather than to model performance. Thus, the study of Allouche et al. (Journal of Applied Ecology, 43, 1223, 2006) identifying the true skill statistics (TSS) as being independent of prevalence had a great impact. However, empirical experience questioned the validity of the statement. We searched for technical reasons behind these observations. We explored possible sources of prevalence dependence in TSS including sampling constraints and species characteristics, which influence the calculation of TSS. We also examined whether the widespread solution of using the maximum of TSS for comparison among species introduces a prevalence effect. We found that the design of Allouche et al. (Journal of Applied Ecology, 43, 1223, 2006) was flawed, but TSS is indeed independent of prevalence if model predictions are binary and under the strict set of assumptions methodological studies usually apply. However, if we take realistic sources of prevalence dependence, effects appear even in binary calculations. Furthermore, in the widespread approach of using maximum TSS for continuous predictions, the use of the maximum alone induces prevalence dependence for small, but realistic samples. Thus, prevalence differences need to be taken into account when model comparisons are carried out based on discrimination capacity. The sources we identified can serve as a checklist to safely control comparisons, so that true discrimination capacity is compared as opposed to artefacts arising from data structure, species characteristics, or the calculation of the comparison measure (here TSS).

The minimum area requirements (MAR) for giant panda: an empirical study

Habitat fragmentation can reduce population viability, especially for area-sensitive species. The Minimum Area Requirements (MAR) of a population is the area required for the population's long-term persistence. In this study, the response of occupancy probability of giant pandas against habitat patch size was studied in five of the six mountain ranges inhabited by giant panda, which cover over 78% of the global distribution of giant panda habitat. The probability of giant panda occurrence was positively associated with habitat patch area, and the observed increase in occupancy probability with patch size was higher than that due to passive sampling alone. These results suggest that the giant panda is an area-sensitive species. The MAR for giant panda was estimated to be 114.7 km² based on analysis of its occupancy probability. Giant panda habitats appear more fragmented in the three southern mountain ranges, while they are large and more continuous in the other two. Establishing corridors among habitat patches can mitigate habitat fragmentation, but expanding habitat patch sizes is necessary in mountain ranges where fragmentation is most intensive.

Optimal threshold estimator of a prognostic marker by maximizing a time-dependent expected utility function for a patient-centered stratified medicine

Defining thresholds of prognostic markers is essential for stratified medicine. Such thresholds are mostly estimated from purely statistical measures regardless of patient preferences potentially leading to unacceptable medical decisions. Quality-Adjusted Life-Years are a widely used preferences-based measure of health outcomes. We develop a time-dependent Quality-Adjusted Life-Years-based expected utility function for censored data that should be maximized to estimate an optimal threshold. We performed a simulation study to compare estimated thresholds when using the proposed expected utility approach and purely statistical estimators. Two applications illustrate the usefulness of the proposed methodology which was implemented in the R package ROCt ( www.divat.fr ). First, by reanalysing data of a randomized clinical trial comparing the efficacy of prednisone vs. placebo in patients with chronic liver cirrhosis, we demonstrate the utility of treating patients with a prothrombin level higher than 89%. Second, we reanalyze the data of an observational cohort of kidney transplant recipients: we conclude to the uselessness of the Kidney Transplant Failure Score to adapt the frequency of clinical visits. Applying such a patient-centered methodology may improve future transfer of novel prognostic scoring systems or markers in clinical practice.

Deciding on Interferon-Free Treatment for Chronic Hepatitis C: Updating Liver Stiffness Cut-Off Values to Maximize Benefit

Introduction

In a perspective of economic constraints the prioritizing of patients to IFN-free regimens is mainly based on the determination of liver stiffness by transient elastography (TE). Being a continuous variable the interpretation of TE results requires the identification of cut-off values, to date set to maximize diagnostic accuracy even if such values should be better based on more helpful outcome prediction endpoints.

Aim

To define the TE cut-off values in different clinical scenarios, including new IFN-free regimens, and to balance the clinical benefits versus harms in treated and untreated patients.

Methods

We assessed the accuracy of TE in staging 728 consecutive HCV patients and the distribution of TE values in 1,001 blood donors. Ten experts quantified the expected harm/benefit ratio for 6 scenarios resulting from 2 stages of liver disease (F≥2 or F≥3) and 3 treatment regimens: PEGIFN+ribavirin, PEGIFN+RBV+first-generation protease inhibitor, and IFN-free regimens. The optimal TE cut-off values were identified using the Metz equation.

Results

The estimated mean expected harm/benefit ratio for IFN-free regimens was 1/8.3 in patients with F≥2 and 1/10 in those with F≥3. The resulting optimal cut-off values were respectively 4.5 kPa with sensitivity at 99% and specificity at 12%, and 6.8 kPa with sensitivity at 94% and specificity at 41%. These cut-off values are lower than those maximizing accuracy and allow to reduce the number of false negative results.

Conclusions

The optimal TE cut-off values to prioritize patients for IFN-free regimens, are sensibly lower than those used to maximize diagnostic accuracy.

Absolute lactate value vs relative reduction as a predictor of mortality in severe sepsis and septic shock

PURPOSE

Lactate reduction, a common method of risk stratification, has been variably defined. Among patients with an initial lactate >4mmol/L, we compared mortality prediction between a subsequent lactate ≥4mmol/L to a <10% and <20% decrease between initial and subsequent lactate values.

MATERIALS AND METHODS

We performed a single-center retrospective study of patients presenting to the emergency department with an initial lactate ≥4mmol/L and suspected infection. Patients were stratified by lactate reduction using 3 previously identified definitions (subsequent lactate ≥4mmol/L, and <10% and <20% relative decrease in lactate) and compared using multivariable logistic regression. Sensitivity and specificity were compared using McNemar test.

RESULTS

A subsequent lactate ≥4mmol/L and a lactate reduction <20% were associated with increased in-hospital mortality (odds ratio [OR], 3.18; 95% confidence interval [CI], 1.24-8.16; P=.02 and OR, 3.11; 95% CI, 1.39-6.96; P=.006, respectively), whereas a lactate reduction <10% was not (OR, 1.13; 95% CI, 0.94-1.34; P=.11). A subsequent lactate ≥4mmol/L and a lactate reduction <20% were more sensitive than a lactate reduction <10% (72% vs 41%, P=.002 and 62% vs 41%, P=.008, respectively) but less specific (57% vs 76%, P<.001 and 67% vs 76%, P=.002, respectively).

CONCLUSIONS

A subsequent lactate ≥4mmol/L and lactate reduction <20% were associated with increased in-hospital mortality, whereas a lactate reduction <10% was not. Sensitivity and specificity are different between these parameters.

Accuracy of the Audio Computer Assisted Self Interview version of the Alcohol, Smoking and Substance Involvement Screening Test (ACASI ASSIST) for identifying unhealthy substance use and substance use disorders in primary care patients

BACKGROUND

An Audio Computer-assisted Self Interview (ACASI) version of the Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST) could reduce barriers to substance use screening and assessment in primary care settings. This study evaluated the diagnostic accuracy of an ACASI ASSIST for identification of unhealthy substance use and substance use disorders (SUD).

METHODS

399 adult patients were consecutively recruited from an urban safety-net primary care clinic. ACASI ASSIST scores for tobacco, alcohol, marijuana, and cocaine were compared against reference standard measures to assess the instrument's diagnostic accuracy for identifying unhealthy use and SUD, first using empirically-derived optimal cutoffs, and second using the currently recommended ASSIST cutoffs.

RESULTS

For identifying any unhealthy use, at the empirically-derived cutoffs the ACASI ASSIST had 93.6% sensitivity and 85.8% specificity (AUC=0.90) for tobacco, 85.9% sensitivity and 60.3% specificity (AUC=0.73), for alcohol in men, 100% sensitivity and 62.4% specificity (AUC=0.81) for alcohol in women, 94.6% sensitivity and 81.6% specificity (AUC=0.88) for marijuana, and 86.1% sensitivity, 84.0% specificity (AUC=0.85) for cocaine. For SUD, sensitivity ranged from 79% (for alcohol in males), to 100% (for tobacco), and specificity was 83% or higher (AUCs ranged 0.83-0.91). For substances other than tobacco, empirically-derived cutoff scores were lower than the standard cutoffs, and resulted in higher sensitivity and lower specificity for identifying unhealthy substance use.

CONCLUSIONS

The ACASI ASSIST is a valid measure of unhealthy use and SUD for substances that are commonly used by primary care patients, and could facilitate effective and efficient screening for substance use in medical settings.

The implementation of rare events logistic regression to predict the distribution of mesophotic hard corals across the main Hawaiian Islands

Predictive habitat suitability models are powerful tools for cost-effective, statistically robust assessment of the environmental drivers of species distributions. The aim of this study was to develop predictive habitat suitability models for two genera of scleractinian corals (Leptoserisand Montipora) found within the mesophotic zone across the main Hawaiian Islands. The mesophotic zone (30–180 m) is challenging to reach, and therefore historically understudied, because it falls between the maximum limit of SCUBA divers and the minimum typical working depth of submersible vehicles. Here, we implement a logistic regression with rare events corrections to account for the scarcity of presence observations within the dataset. These corrections reduced the coefficient error and improved overall prediction success (73.6% and 74.3%) for both original regression models. The final models included depth, rugosity, slope, mean current velocity, and wave height as the best environmental covariates for predicting the occurrence of the two genera in the mesophotic zone. Using an objectively selected theta (“presence”) threshold, the predicted presence probability values (average of 0.051 for Leptoseris and 0.040 for Montipora) were translated to spatially-explicit habitat suitability maps of the main Hawaiian Islands at 25 m grid cell resolution. Our maps are the first of their kind to use extant presence and absence data to examine the habitat preferences of these two dominant mesophotic coral genera across Hawai‘i.

Effectiveness of the Easy-Up Handle in acute rehabilitation

Objective: The ability to attain standing without assistance is important to independent functioning. The objectives of this study, therefore, were to: (1) determine the effectiveness of the Easy-Up Handle for enabling otherwise dependent patients to attain standing from an armless chair and (2) establish whether knee extension force played a role in such effectiveness.

Design: Cross-sectional descriptive study and explicatory experiment.

Setting: Acute rehabilitation unit.

Subjects: A subset ( n = 26) of 107 primarily elderly patients described in a previous study. The subjects were selected because of their inability to stand from an armless chair, even when using their upper limbs.

Main measures: The ability to stand from the same chair when using an Easy-Up Handle. Hand-held dynamometer measures of the combined strength of the lower extremities.

Results: Eight of 26 otherwise dependent patients were able to stand up independently with the Easy-Up Handle. Whether or not they were able to attain standing with the Easy-Up Handle was predicted by their combined knee extension force and by their combined force normalized against body weight. The Pearson correlations between stand-up independence (yes, no) and the forces were 0.496 and 0.543, respectively.

Conclusions: The Easy-Up Handle can facilitate independence in chair rise for some patients otherwise unable to stand from sitting. Even with the Easy-Up Handle, however, a threshold of knee extension force is required.

Feeding habitat quality and behavioral trade-offs in chimpanzees: a case for species distribution models

The distribution and abundance of food resources are among the most important factors that influence animal behavioral strategies. Yet, spatial variation in feeding habitat quality is often difficult to assess with traditional methods that rely on extrapolation from plot survey data or remote sensing. Here, we show that maximum entropy species distribution modeling can be used to successfully predict small-scale variation in the distribution of 24 important plant food species for chimpanzees at Gombe National Park, Tanzania. We combined model predictions with behavioral observations to quantify feeding habitat quality as the cumulative dietary proportion of the species predicted to occur in a given location. This measure exhibited considerable spatial heterogeneity with elevation and latitude, both within and across main habitat types. We used model results to assess individual variation in habitat selection among adult chimpanzees during a 10-year period, testing predictions about trade-offs between foraging and reproductive effort. We found that nonswollen females selected the highest-quality habitats compared with swollen females or males, in line with predictions based on their energetic needs. Swollen females appeared to compromise feeding in favor of mating opportunities, suggesting that females rather than males change their ranging patterns in search of mates. Males generally occupied feeding habitats of lower quality, which may exacerbate energetic challenges of aggression and territory defense. Finally, we documented an increase in feeding habitat quality with community residence time in both sexes during the dry season, suggesting an influence of familiarity on foraging decisions in a highly heterogeneous landscape.

Prediction of nonresponsiveness to medium-dose intravenous immunoglobulin (1 g/kg) treatment: an effective and safe schedule of acute treatment for Kawasaki disease

Purpose

Medium-dose (1 g/kg) intravenous immunoglobulin (IVIG) is effective in the majority of patients with Kawasaki disease (KD) but some patients who do not respond to medium-dose IVIG are at high risk for the development of coronary artery lesions (CALs). The purpose of this study was to identify the clinical predictors associated with unresponsiveness to medium-dose IVIG and the development of CALs.

Methods

A retrospective study was performed in 91 children with KD who were treated with medium-dose IVIG at our institution from January 2004 to December 2013. We classified the patients into responders (group 1; n=68) and nonresponders (group 2; n=23). We compared demographic, laboratory, and echocardiographic data between the 2 groups.

Results

Multivariate logistic regression analysis identified 6 variables as predictors for resistance to medium-dose IVIG. We generated a predictive scoring system assigning 1 point each for percentage of neutrophils ≥65%, C-reactive protein≥100 mg/L, aspartate aminotransferase≥100 IU/L, and alanine aminotransferase≥100 IU/L, as well as 2 points for less than 5 days of illness, and serum sodium level≤136 mmol/L. Using a cutoff point of ≥4 with this scoring system, we could predict nonresponsiveness to medium-dose IVIG with 74% sensitivity and 71% specificity.

Conclusion

If a patient has a low-risk score in this system, medium-dose IVIG can be recommended as the initial treatment. Through this process, we can minimize the adverse effects of high-dose IVIG and incidence of CALs.

Modelization of the Current and Future Habitat Suitability of Rhododendron ferrugineum Using Potential Snow Accumulation

Mountain areas are particularly sensitive to climate change. Species distribution models predict important extinctions in these areas whose magnitude will depend on a number of different factors. Here we examine the possible impact of climate change on the Rhododendron ferrugineum (alpenrose) niche in Andorra (Pyrenees). This species currently occupies 14.6 km2 of this country and relies on the protection afforded by snow cover in winter. We used high-resolution climatic data, potential snow accumulation and a combined forecasting method to obtain the realized niche model of this species. Subsequently, we used data from the high-resolution Scampei project climate change projection for the A2, A1B and B1 scenarios to model its future realized niche model. The modelization performed well when predicting the species's distribution, which improved when we considered the potential snow accumulation, the most important variable influencing its distribution. We thus obtained a potential extent of about 70.7 km(2) or 15.1% of the country. We observed an elevation lag distribution between the current and potential distribution of the species, probably due to its slow colonization rate and the small-scale survey of seedlings. Under the three climatic scenarios, the realized niche model of the species will be reduced by 37.9-70.1 km(2) by the end of the century and it will become confined to what are today screes and rocky hillside habitats. The particular effects of climate change on seedling establishment, as well as on the species' plasticity and sensitivity in the event of a reduction of the snow cover, could worsen these predictions.

New insights on postglacial colonization in western Europe: the phylogeography of the Leisler's bat (Nyctalus leisleri)

Despite recent advances in the understanding of the interplay between a dynamic physical environment and phylogeography in Europe, the origins of contemporary Irish biota remain uncertain. Current thinking is that Ireland was colonized post-glacially from southern European refugia, following the end of the last glacial maximum (LGM), some 20 000 years BP. The Leisler's bat (Nyctalus leisleri), one of the few native Irish mammal species, is widely distributed throughout Europe but, with the exception of Ireland, is generally rare and considered vulnerable. We investigate the origins and phylogeographic relationships of Irish populations in relation to those across Europe, including the closely related species N. azoreum. We use a combination of approaches, including mitochondrial and nuclear DNA markers, in addition to approximate Bayesian computation and palaeo-climatic species distribution modelling. Molecular analyses revealed two distinct and diverse European mitochondrial DNA lineages, which probably diverged in separate glacial refugia. A western lineage, restricted to Ireland, Britain and the Azores, comprises Irish and British N. leisleri and N. azoreum specimens; an eastern lineage is distributed throughout mainland Europe. Palaeo-climatic projections indicate suitable habitats during the LGM, including known glacial refugia, in addition to potential novel cryptic refugia along the western fringe of Europe. These results may be applicable to populations of many species.

The Influence of Data Resolution on Predicted Distribution and Estimates of Extent of Current Protection of Three 'Listed' Deep-Sea Habitats

Modelling approaches have the potential to significantly contribute to the spatial management of the deep-sea ecosystem in a cost effective manner. However, we currently have little understanding of the accuracy of such models, developed using limited data, of varying resolution. The aim of this study was to investigate the performance of predictive models constructed using non-simulated (real world) data of different resolution. Predicted distribution maps for three deep-sea habitats were constructed using MaxEnt modelling methods using high resolution multibeam bathymetric data and associated terrain derived variables as predictors. Model performance was evaluated using repeated 75/25 training/test data partitions using AUC and threshold-dependent assessment methods. The overall extent and distribution of each habitat, and the percentage contained within an existing MPA network were quantified and compared to results from low resolution GEBCO models. Predicted spatial extent for scleractinian coral reef and Syringammina fragilissima aggregations decreased with an increase in model resolution, whereas Pheronema carpenteri total suitable area increased. Distinct differences in predicted habitat distribution were observed for all three habitats. Estimates of habitat extent contained within the MPA network all increased when modelled at fine scale. High resolution models performed better than low resolution models according to threshold-dependent evaluation. We recommend the use of high resolution multibeam bathymetry data over low resolution bathymetry data for use in modelling approaches. We do not recommend the use of predictive models to produce absolute values of habitat extent, but likely areas of suitable habitat. Assessments of MPA network effectiveness based on calculations of percentage area protection (policy driven conservation targets) from low resolution models are likely to be fit for purpose.

Predicting potential ranges of primary malaria vectors and malaria in northern South America based on projected changes in climate, land cover and human population

Background

Changes in land use and land cover (LULC) as well as climate are likely to affect the geographic distribution of malaria vectors and parasites in the coming decades. At present, malaria transmission is concentrated mainly in the Amazon basin where extensive agriculture, mining, and logging activities have resulted in changes to local and regional hydrology, massive loss of forest cover, and increased contact between malaria vectors and hosts.

Methods

Employing presence-only records, bioclimatic, topographic, hydrologic, LULC and human population data, we modeled the distribution of malaria and two of its dominant vectors, Anopheles darlingi, and Anopheles nuneztovari s.l. in northern South America using the species distribution modeling platform Maxent.

Results

Results from our land change modeling indicate that about 70,000 km² of forest land would be lost by 2050 and 78,000 km² by 2070 compared to 2010. The Maxent model predicted zones of relatively high habitat suitability for malaria and the vectors mainly within the Amazon and along coastlines. While areas with malaria are expected to decrease in line with current downward trends, both vectors are predicted to experience range expansions in the future. Elevation, annual precipitation and temperature were influential in all models both current and future. Human population mostly affected An. darlingi distribution while LULC changes influenced An. nuneztovari s.l. distribution.

Conclusion

As the region tackles the challenge of malaria elimination, investigations such as this could be useful for planning and management purposes and aid in predicting and addressing potential impediments to elimination.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-015-1033-9) contains supplementary material, which is available to authorized users.