Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
9,302
datasets available to search
ShareScore release 0.9.0
Dataset results
9,302 results for “DETECT”
Data from: Landscape history confounds the ability of the NDVI to detect fine-scale variation in grassland communities
1. The NDVI is a remotely-sensed vegetation index that is frequently used in ecological studies. There is, however, a lack of studies that evaluate the ability of the NDVI to detect fine-scale variation in grassland plant community composition and species richness. Ellenberg indicators characterize the environmental preferences of plant species – and community-mean Ellenberg values have been used to explore the environmental drivers of community assembly. 2. We used variation partitioning to test the ability of satellite-based NDVI to explain community-mean Ellenberg nutrient (mN) and moisture (mF) indices, and the richness of habitat-specialist species in dry grasslands of different ages. The grasslands represent a gradient of decreasing soil nutrient status. 3. If community composition is determined by the responses of individual species to the underlying environmental conditions and if, at the same time, community composition determines the optical characteristics of the vegetation canopy, then positive relationships between the NDVI and mN and mF are expected. Many grassland specialists are intolerant of nutrient-rich soils. If specialist richness is negatively related to soil-nutrient levels, then a negative association between the NDVI and specialist richness is expected. However, because grassland community composition is not only influenced by abiotic variables but also by other spatial and temporal drivers, we included spatial variables and grassland age in the statistical analyses. 4. The NDVI explained the majority of the variation in mF, and also contributed to a substantial proportion of the variation in mN. However, variation in specialist richness and the lowest values of mN were explained by grassland age and spatial variables – but were poorly explained by the NDVI. 5. Synthesis and applications. The NDVI showed a good ability to detect variation in plant community composition, and should provide a valuable tool for assessing fine-scale environmental variation in grasslands or for monitoring changes in grassland habitat properties. However, because the concentration of grassland specialists not only depends on environmental variables but also on the age and spatial context of the grasslands, the NDVI is unlikely to allow the identification of grasslands with high numbers of specialist species.
Data from: D quantification of tumor vasculature in lymphoma xenografts in NOD/SCID mice allows to detect differences among vascular-targeted therapies
Quantitative characterization of the in vivo effects of vascular-targeted therapies on tumor vessels is hampered by the absence of useful 3D vascular network descriptors aside from microvessel density. In this study, we extended the quantification of planar vessel distribution to the analysis of vascular volumes by studying the effects of antiangiogenic (sorafenib and sunitinib) or antivascular (combretastatin A4 phosphate) treatments on the quantity and spatial distributions of thin microvessels. These observations were restricted to perinecrotic areas of treated human multiple myeloma tumors xenografted in immunodeficient mice and to microvessels with an approximate cross-sectional area lower than 75 µm2. Finally, vessel skeletonization minimized artifacts due to possible differential wall staining and allowed a comparison of the various treatment effects. Antiangiogenic drug treatment reduced the number of vessels of every caliber (at least 2-fold fewer vessels vs. controls; p<0.001, n = 8) and caused a heterogeneous distribution of the remaining vessels. In contrast, the effects of combretastatin A4 phosphate mainly appeared to be restricted to a homogeneous reduction in the number of thin microvessels (not more than 2-fold less vs. controls; p<0.001, n = 8) with marginal effects on spatial distribution. Unexpectedly, these results also highlighted a strict relationship between microvessel quantity, distribution and cross-sectional area. Treatment-specific changes in the curves describing this relationship were consistent with the effects ascribed to the different drugs. This finding suggests that our results can highlight differences among vascular-targeted therapies, providing hints on the processes underlying sample vascularization together with the detailed characterization of a pathological vascular tree.
Data from: Using ABC and microsatellite data to detect multiple introductions of invasive species from a single source
The introduction of invasive species to new locations (that is, biological invasions) can have major impact on biodiversity, agriculture and public health. As such, determining the routes and modality of introductions with genetic data has become a fundamental goal in molecular ecology. To assist with this goal, new statistical methods and frameworks have been developed, such as approximate Bayesian computation (ABC) for inferring invasion history. Here, we present a model of invasion accounting for multiple introductions from a single source (MISS), a heretofore largely unexplored model. We simulate microsatellite data to evaluate the power of ABC to distinguish between single and multiple introductions from the same source, under a range of demographic parameters. We also apply ABC to microsatellite data from three invasions of bumblebee in New Zealand. In addition, we assess the performance of several methods of summary statistics selection. Our simulated results suggested good ability to distinguish between one- and two-wave models over much but not all of the parameter space tested, independent of summary statistics used. Globally, parameter estimation was good except for bottleneck timing. For one of the bumblebee species, we clearly rejected the MISS model, while for the other two we found inconclusive results. Since a second wave may provide genetic reinforcement to initial colonists, help relieve inbreeding among founders, or increase the hazard of the invasion, its detection may be crucial for managing invasions; we suggest that the MISS model could be considered as a potential model in future theoretical and empirical studies of invasions.
Data from: Genome-wide scans detect adaptation to aridity in a widespread forest tree species.
Patterns of adaptive variation within plant species are best studied through common garden experiments, but these are costly and time-consuming, especially for trees that have long generation times. We explored whether genome-wide scanning technology combined with outlier marker detection could be used to detect adaptation to climate and provide an alternative to common garden experiments. As a case study, we sampled nine provenances of the widespread forest tree species, Eucalyptus tricarpa, across an aridity gradient in southeastern Australia. Using a Bayesian analysis we identified a suite of 94 putatively adaptive (outlying) sequence-tagged markers across the genome. Population-level allele frequencies of these outlier markers were strongly correlated with temperature and moisture availability at the site of origin, and with population differences in functional traits measured in two common gardens. Using the output from a canonical analysis of principal coordinates we devised a metric that provides a holistic measure of genomic adaptation to aridity that could be used to guide assisted migration or genetic augmentation.
Data from: Detecting genes for variation in parasite burden and immunological traits in a wild population: testing the candidate gene approach
Identifying the genes underlying phenotypic variation in natural populations can provide novel insight into the evolutionary process. Here we test the candidate gene approach to identifying loci involved in variation in gastrointestinal parasite burden, in a wild population of Soay sheep. A comprehensive literature review, Gene Ontology databases, and comparative genomics resources were used to generate a list of candidate genes. In a pilot study these candidates, along with 50 random genes, were then sequenced in pools of Soay sheep with low and high gastrointestinal nematode burden. Further candidates were identified from SNPs that were highly differentiated between high and low resistance sheep breeds. A panel of 192 candidate and control SNPs were then typed in 960 individual Soay sheep to examine whether they individually explained variation in parasite burden, as measured as faecal egg count (FEC), as well as two immune measures. The cumulative effect of the candidate and control SNPs were estimated by fitting genetic relationship matrices (GRMs) as random effects in animal models of the three traits. No more significant SNPs were identified in the pilot sequencing experiment and association study than expected by chance. Furthermore, no significant difference was found between the proportions of candidate or control SNPs that were found to be significantly associated with parasite burden/immune measures. No significant effect of the candidate or control gene GRMs was found. There is thus little support for the candidate gene approach to the identification of loci explaining variation in parasitological and immunological traits in this population.
Automated detection of lameness in sheep using machine learning approaches: novel insights into behavioural differences among lame and non-lame sheep
Lameness in sheep is the biggest cause of concern regarding poor health and welfare among sheep producing countries. Best practice for lameness relies on rapid treatment, yet there are no objective measures of lameness detection. Use of accelerometers and gyroscopes have been widely used in human activity studies and their use is becoming increasingly common in livestock. In this study, we used 23 datasets (10 non-lame and 13 lame sheep) from an accelerometer and gyroscope-based ear sensor with a sampling frequency of 16 Hz to develop and compare algorithms that can differentiate lameness within three different activities (walking, standing and lying). We show for the first time that features extracted from accelerometer and gyroscope signals can differentiate between lame and non-lame sheep while standing, walking and lying. The random forest algorithm performed best for classifying lameness with accuracy of 84.91% within lying, 81.15% within standing and 76.83% within walking and overall correctly classified over 80% sheep within activities. Both accelerometer and gyroscope-based features ranked among the top 10 features for classification. Our results suggest that novel behavioural differences between lame and non-lame sheep across all three activities could be used to develop an automated system for lameness detection.
Data from: Molecular detection of trophic links in a complex insect host-parasitoid food web
Previously, host-parasitoid links have been unveiled almost exclusively by time-intensive rearing, while molecular methods were used only in simple agricultural host-parasitoid systems in the form of species specific primers. Here we present a general method for molecular detection of these links applied to a complex caterpillar-parasitoid food web from tropical rainforest of Papua New Guinea. We DNA barcoded hosts, parasitoids and their tissue remnants and matched the sequences to our extensive library of local species. We were thus able to match 87% of host sequences and 36% of parasitoid sequences to species, and infer subfamily or family in almost all cases. Our analysis affirmed 93 hitherto unknown trophic links between 37 host species from a wide range of Lepidoptera families and 46 parasitoid species from Hymenoptera and Diptera by identifying DNA sequences for both the host and the parasitoid involved in the interaction. Molecular detection proved especially useful in cases where distinguishing host species in caterpillar stage was difficult morphologically, or when the caterpillar died during rearing. We have even detected a case of extreme parasitoid specialization in a pair of Choreutis species which do not differ in caterpillar morphology and ecology. Using the molecular approach outlined here leads to better understanding of parasitoid host specificity, opens new possibilities for rapid surveys of food web structure and allows inference of species associations not already anticipated.
Data from: Reliability assessment of null allele detection: inconsistencies between and within different methods
Microsatellite loci are widely used in population genetic studies, but the presence of null alleles may lead to biased results. Here, we assessed five methods that indirectly detect null alleles and found large inconsistencies among them. Our analysis was based on 20 microsatellite loci genotyped in a natural population of Microtus oeconomus sampled during 8 years, together with 1200 simulated populations without null alleles, but experiencing bottlenecks of varying duration and intensity, and 120 simulated populations with known null alleles. In the natural population, 29% of positive results were consistent between the methods in pairwise comparisons, and in the simulated data set, this proportion was 14%. The positive results were also inconsistent between different years in the natural population. In the null-allele-free simulated data set, the number of false positives increased with increased bottleneck intensity and duration. We also found a low concordance in null allele detection between the original simulated populations and their 20% random subsets. In the populations simulated to include null alleles, between 22% and 42% of true null alleles remained undetected, which highlighted that detection errors are not restricted to false positives. None of the evaluated methods clearly outperformed the others when both false-positive and false-negative rates were considered. Accepting only the positive results consistent between at least two methods should considerably reduce the false-positive rate, but this approach may increase the false-negative rate. Our study demonstrates the need for novel null allele detection methods that could be reliably applied to natural populations.
Data from: Identification of migratory bird flyways in North America using community detection on biological networks
Migratory behavior of waterfowl populations in North America has traditionally been broadly characterized by four north-south flyways, and these flyways have been central to the management of waterfowl populations for more than 80 years. However, previous flyway characterizations are not easily updated with current bird movement data and fail to provide assessments of the importance of specific geographical regions to the identification of flyways. Here, we developed a network model of migratory movement for four waterfowl species —mallard (Anas platyrhnchos), northern pintail (A. acuta), American green-winged teal (A. carolinensis), and Canada goose (Branta canadensis) — in North America using bird band and recovery data. We then identified migratory flyways using a community detection algorithm and characterize the importance of smaller geographic regions in identifying flyways using a novel metric, the consolidation factor. We identified four main flyways for mallards, northern pintails, and American green-winged teal with the flyway identification in Canada geese exhibiting higher complexity. For mallards, flyways were relatively consistent through time. However, consolidation factors revealed that for mallards and green-winged teal the presumptive Mississippi flyway was potentially a zone of high mixing between other flyways. Our results demonstrate that the network approach provides a robust method for flyway identification that is widely applicable given the relatively minimal data requirements and is easily updated with future movement data to reflect changes in flyway definitions and management goals.
Data from: Detection of tephra layers in Antarctic sediment cores with hyperspectral imaging
Tephrochronology uses recognizable volcanic ash layers (from airborne pyroclastic deposits, or tephras) in geological strata to set unique time references for paleoenvironmental events across wide geographic areas. This involves the detection of tephra layers which sometimes are not evident to the naked eye, including the so-called cryptotephras. Tests that are expensive, time-consuming, and/or destructive are often required. Destructive testing for tephra layers of cores from difficult regions, such as Antarctica, which are useful sources of other kinds of information beyond tephras, is always undesirable. Here we propose hyperspectral imaging of cores, Self-Organizing Map (SOM) clustering of the preprocessed spectral signatures, and spatial analysis of the classified images as a convenient, fast, non-destructive method for tephra detection. We test the method in five sediment cores from three Antarctic lakes, and show its potential for detection of tephras and cryptotephras.
Data from: Echolocation detections and digital video surveys provide reliable estimates of the relative density of harbour porpoises
1. Robust estimates of the density or abundance of cetaceans are required to support a wide range of ecological studies and inform management decisions. Considerable effort has been put into the development of line-transect sampling techniques to obtain estimates of absolute density from aerial and boat-based visual surveys. Surveys of cetaceans using acoustic loggers or digital cameras provide alternative methods to estimate relative density that have the potential to reduce cost and provide a verifiable record of all detections. However the ability of these methods to provide reliable estimates of relative density has yet to be established. 2. These methodologies were compared by conducting aerial visual line-transect surveys (n=10 days) and digital video strip-transect surveys (n=4 days) in the Moray Firth, Scotland. Simultaneous acoustic data were collected from moored echolocation detectors (C-PODs) at 58 locations across the study site. Density surface modelling (DSM) of visual survey data was used to estimate spatial variation in relative harbour porpoise density on a 4x4 km grid. DSM was also performed on the digital survey data, and the resulting model output compared to that from visual survey data. Estimates of relative density from visual surveys around acoustic monitoring sites were compared with several metrics previously used to characterise variation in acoustic detections of echolocation clicks. 3. There was a strong correlation between estimates of relative density from visual surveys and digital video surveys (Spearman's ρ=0.85). A correction to account for animals missed on the transect line (previously calculated for visual aerial surveys of harbour porpoise in the North Sea (Hammond et al. 2013)) was used to convert relative density from the visual surveys to absolute density. This allowed calculation of the first estimate of a proxy for detection probability in digital video surveys, suggesting that 61% (CV=0.53) of harbour porpoises were detected. There was also a strong correlation between acoustic detections and density with a Spearman's ρ=0.73 for detection positive hours. 4. These results provide confidence in the emerging use of digital video and acoustic surveys for studying the density of small cetaceans and their responses to environmental and anthropogenic change.
Data from: Modifiable patient-related barriers and their association with breast cancer detection practices among Ugandan women without a diagnosis of breast cancer
Most women with breast cancer in sub-Saharan Africa (SSA) are diagnosed with late-staged disease. The current study assesses patient-related barriers among women from a general SSA population to better understand how patient-related barriers contribute to diagnostic delays. Using convenience-based sampling, 401 Ugandan women without breast cancer were surveyed to determine how prior participation in cancer detection practices correlate with patient-related barriers to prompt diagnosis. In a predominantly poor (76%) and rural population (75%), the median age of the participants was 38. Of the women surveyed, 155 (46%) had prior exposure to breast cancer education, 92 (27%) performed breast self-examination (BSE) and 68 (20%) had undergone a recent clinical breast examination (CBE), breast ultrasound or breast biopsy. The most commonly identified barriers to prompt diagnosis were knowledge deficits regarding early diagnosis (79%), economic barriers to accessing care (68%), fear (37%) and poor social support (24%). However, only women who reported knowledge deficits – a modifiable barrier – were less likely to participate in cancer detection practices (p<0.05). Women in urban and rural areas were similarly likely to report economic barriers, knowledge deficits and/or poor social support, but rural women were less likely than urban women to have received breast cancer education and/or perform BSE (p<0.001). Women who have had prior breast cancer education (p<0.001) and/or who perform BSE (p=0.02) were more likely to know where she can go to receive a diagnostic breast evaluation. These findings suggest that SSA countries developing early breast cancer detection programs should specifically address modifiable knowledge deficits among women less likely to achieve a diagnostic work-up to reduce diagnostic delays and improve breast cancer outcomes.
Data from: Using human vision to detect variation in avian coloration: How bad is it?
Assessing variation in animal coloration is difficult as animals differ in their visual system properties. This has led some to propose that human vision can never be used to evaluate coloration, yet many studies have a long history of relying on human vision. To reconcile these views, we compared the reflectance spectra of preserved avian plumage elements with two measures that are humans biased: RGB values from digital photographs and the corresponding reflectance spectra from a field guide. We measured 73 plumage elements across 14 bird species. The field guide reflectance spectra were drastically different from that of the actual birds, particularly for blue elements. However, principal components analyses on all three data sets indicated remarkably similar data structure. We conclude that human vision can detect much of the variation in coloration in the visible range, providing fodder for subsequent studies in ecology, evolution, behavior, and visual ecology.
Data from: Environmental DNA (eDNA) detects the invasive rusty crayfish (Orconectes rusticus) at low abundances
Early detection is invaluable for the cost-effective control and eradication of invasive species, yet many traditional sampling techniques are ineffective at the low population abundances found at the onset of the invasion process. Environmental DNA (eDNA) is a promising and sensitive tool for early detection of some invasive species, but its efficacy has not yet been evaluated for many taxonomic groups and habitat types. We evaluated the ability of eDNA to detect the invasive rusty crayfish Orconectes rusticus, and to reflect patterns of its relative abundance, in upper Midwest, USA inland lakes. We paired conventional baited trapping as a measure of crayfish relative abundance with water samples for eDNA, which were analysed in the laboratory with a qPCR assay. We modelled detection probability for O. rusticus eDNA using relative abundance and site characteristics as covariates, and also tested the relationship between eDNA copy number and O. rusticus relative abundance. We detected O. rusticus eDNA in all lakes where this species was collected by trapping, down to low relative abundances, as well as in two lakes where trap catch was zero. Detection probability of O. rusticus eDNA was well-predicted by relative abundance of this species and lake water clarity. However there was poor correspondence between eDNA copy number and O. rusticus relative abundance estimated by trap catches. Synthesis and applications. Our study demonstrates a field and laboratory protocol for eDNA monitoring of crayfish invasions, with results of statistical models that provide guidance of sampling effort and detection probabilities for researchers in other regions and systems. We propose eDNA be included as a tool in surveillance for invasive or imperilled crayfishes and other benthic arthropods.
Data from: Detection of somatic epigenetic variation in Norway spruce via targeted bisulfite sequencing
Epigenetic mechanisms represent a possible mechanism for achieving a rapid response of long‐lived trees to changing environmental conditions. However, our knowledge on plant epigenetics is largely limited to a few model species. With increasing availability of genomic resources for many tree species, it is now possible to adopt approaches from model species that permit to obtain single‐base pair resolution data on methylation at a reasonable cost. Here, we used targeted bisulfite sequencing (TBS) to study methylation patterns in the conifer species Norway spruce (Picea abies). To circumvent the challenge of disentangling epigenetic and genetic differences, we focused on four clone pairs, where clone members were growing in different climatic conditions for 24 years. We targeted >26.000 genes using TBS and determined the performance and reproducibility of this approach. We characterized gene body methylation and compared methylation patterns between environments. We found highly comparable capture efficiency and coverage across libraries. Methylation levels were relatively constant across gene bodies, with 21.3 ± 0.3%, 11.0 ± 0.4% and 1.3 ± 0.2% in the CG, CHG, and CHH context, respectively. The variance in methylation profiles did not reveal consistent changes between environments, yet we could identify 334 differentially methylated positions (DMPs) between environments. This supports that changes in methylation patterns are a possible pathway for a plant to respond to environmental change. After this successful application of TBS in Norway spruce, we are confident that this approach can contribute to broaden our knowledge of methylation patterns in natural tree populations.
Data from: Proboscis profiler: a tool for detecting acanthocephalan morphotypes
Molecular studies conducted over the past 25 years have revealed previously unrecognised diversity in the phylum Acanthocephala. Several nominal species have been shown to represent complexes of morphologically cryptic biological species, a situation potentially confounding the analysis of ecological data. A software tool, 'Proboscis profiler', was developed to detect morphological heterogeneity in collections of superficially similar acanthocephalan worms based on the multivariate statistical analysis of proboscis hook dimensions. Proboscis profiler identifies objective, natural groups in a collection of acanthocephalans which may correspond to distinct biological species or populations. Initial trials demonstrate that Proboscis profiler can discriminate biological acanthocephalan species of the Echinorhynchus gadi Zoega in Müller, 1776 complex and differentiate between dorsal and ventral hook rows from the proboscis of E. salmonis Müller, 1784. Proboscis profiler is free software and can be downloaded from http://acanthocephala.sourceforge.net.
Data from: Direct detection of male quality can facilitate the evolution of female choosiness and indicators of good genes: evolution across a continuum of indicator mechanisms
The evolution of mating displays as indicators of male quality has been the subject of extensive theoretical and empirical research for over four decades. Research has also addressed the evolution of female mate choice favoring such indicators. Yet, much debate still exists about whether displays can evolve through the indirect benefits of female mate choice. Here, we use a population genetic model to investigate how the extent to which females can directly detect male quality influences the evolution of female choosiness and male displays. We use a continuum framework that incorporates indicator mechanisms that are traditionally modelled separately. Counter to intuition, we find that intermediate levels of direct detection of male quality can facilitate, rather than impede, the evolution of female choosiness and male displays in broad regions of this continuum. We examine how this evolution is driven by selective forces on genetic quality and on the display, and find that direct detection of male quality results in stronger indirect selection favoring female choosiness. Our results imply that displays maybe more likely to evolve when female choosiness has already evolved to discriminate perceptible forms of male quality. They also highlight the importance of considering general female choosiness, as well as preference, in studies of "good genes".
Data from: Application of ancient DNA to the reconstruction of past microbial assemblages and for the detection of toxic cyanobacteria in subtropical freshwater ecosystems
Ancient DNA (aDNA) analysis of lake sediments is a promising tool for detecting shifts in past microbial assemblages in response to changing environmental conditions. We examined sediment core samples from subtropical, freshwater Laguna Blanca (Uruguay), which has been severely affected by cultural eutrophication since 1960 and where cyanobacterial blooms, particularly those of the saxitoxin-producer Cylindrospermopsis raciborskii, have been reported since the 1990s. Samples corresponding to ~1846, 1852, 2000 and 2007 A.D. were selected to perform Denaturing Gradient Gel Electrophoresis (DGGE) analysis of the 16S-23S rRNA intergenic transcribed spacer (ribosomal ITS) to compare their prokaryotic assemblage composition. Each stratum showed different ITS patterns, but the composition of 21st Century samples was clearly different than those of mid-19th Century. This compositional change was correlated to shifts in sediment organic matter and chlorophyll a content, which were significantly higher in recent samples. The presence of saxitoxin-producing cyanobacteria was addressed by quantitative real time PCR of the sxtU gene involved in toxin biosynthesis. This gene was present only in recent samples, for which clone libraries and ITS sequencing indicated the presence of Cyanobacteria. Phylogenetic analyses identified C. raciborskii only in the 2000 sample, shortly after several years when blooms were recorded in the lake. These data suggest the utility of aDNA for the reconstruction of microbial assemblage shifts in subtropical lakes, at least on centennial scales. The application of aDNA analysis to genes involved in cyanotoxin synthesis extends the applicability of molecular techniques in paleolimnological studies to include key microbial community characteristics of great scientific and social interest.
Data from: Detecting small-scale genotype-environment interactions in apomictic dandelion (Taraxacum officinale) populations
Studies of genotype × environment interactions (G×E) and local adaptation provide critical tests of natural selection's ability to counter opposing forces such as gene flow. Such studies may be greatly facilitated in asexual species, given the possibility for experimental replication at the level of true genotypes (rather than populations) and the possibility of using molecular markers to assess genotype-environment associations in the field (neither of which is possible for most sexual species). Here we tested for G×E in asexual dandelions (Taraxacum officinale) by subjecting six genotypes to experimental drought, mown, and benign (control) conditions, and subsequently using microsatellites to assess genotype-environment associations in the field. We found strong G×E, with genotypes that performed poorly under benign conditions showing the highest performance under stressful conditions (drought or mown). Our six focal genotypes comprise >80% of plants in local populations. The most common genotype in the field showed its highest relative performance under mown conditions (the most common habitat in our study area), and almost all plants of this genotype in the field were found growing in mowed lawns. Genotypes performing best under benign experimental conditions were found most frequently in unmown conditions in the field. These results are strongly indicative of local adaptation at a very small scale, with unmown microsites of only a few square meters typically embedded within larger mown lawns. By studying an asexual species we were able to map genotypes with known ecological characteristics to environments with high spatial precision.
Data from: Detection and initial management of gestational diabetes through primary health care services in Morocco: an effectiveness-implementation trial
Background: Gestational Diabetes Mellitus (GDM) testing and management in Morocco is associated with delays resulting in late commencement of treatment. To reduce delays and to increase access of women to GDM care, a country-adapted intervention targeting primary health care providers was designed to test the hypothesis that detection and initial management of GDM at the primary level of care improves newborn outcomes in terms of lower birthweights and less cases of macrosomia and impacts on maternal weight gain, glucose balance and pregnancy outcomes. Materials and methods: We conducted a cluster randomized controlled trial in two districts of Morocco. In each district, 10 health centers were randomly selected to serve either as intervention or control sites. Pregnant women attending antenatal care in the study facilities were eligible to participate. At the intervention sites, women were offered GDM screening by capillary glucose testing following International Association of Diabetes in Pregnancy Study Groups/WHO criteria. Women diagnosed with GDM received counselling on nutrition and exercise and were followed up through their health center whereas at control facilities routine practice was applied. Primary outcome was birthweight and secondary outcomes maternal weight gain, glucose control and pregnancy complications. We further assessed GDM prevalence in the intervention arm. Statistical analysis was performed on 210 recruited women. Continuous variables were reported using means while categorical variables using frequencies with tests of independence applying chi-squared tests. Differences of outcome variables between the two groups were estimated by mixed-effects regression models and effect sizes adjusted for confounders. The trial is registered under NCT02979756 at ClinicalTrials.gov. Results: GDM prevalence reached 23.7% in Marrakech. Birthweight in the intervention group was 147grams lower than in the control group (p = 0.08) as was the proportion of macrosomes (3.5% versus 18.4%; p< 0.001). In the intervention arm, women did two times more follow-ups than at control sites (p = 0.001) and mean follow-up intervals were shorter (11.3 days versus 18.7 days; p < 0.001). Overall, 30% more fasting blood sugar values were balanced (p = 0.005) and mean weekly maternal weight gain 49 grams lower (p = 0.032) in the intervention group. More women from control facilities had a delivery complication whereas more newborn complications were observed in women from intervention facilities. No difference between the two groups existed regarding mode of delivery and mean gestational age at delivery. One of the main limitations of the study was the Hawthorn-effect at control sites that might have led to an underestimation of the effect size. Conclusion: A high GDM prevalence in Morocco calls for a context-adapted screening and management approach to enable early interventions. GDM detection and care through antenatal care at primary health facilities may have positively impacted on newborn birthweight but findings are inconclusive. Results of this study will contribute to the decision on a potential upscaling of the intervention in Morocco. Future research could examine long term metabolic changes including diabetes type 2 in the cohort of women and their children.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.