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opencc-zeroAug 2020View details →

Datasets related to the paper 'Identifying priority areas for restoring mountain ungulates in the Caucasus ecoregion'

Three datasets are contained here: 1. The final habitat suitability map for bezoar goats (Capra aegagrus aegagrus) for the Caucasus ecoregion (in TIFF format) 2. The table of occurence location used for generating this map (in CSV format) 3. The habitat patches derived from the habitat suitability map and their priority ranking according to three conservation scenarios (in SHP format)

opencc-zeroSep 2020View details →

Data from: Standardization and validation of a panel of cross-species microsatellites to individually identify the Asiatic wild dog (Cuon alpinus)

The Asiatic wild dog or dhole (Cuon alpinus) is a highly elusive, monophyletic, forest dwelling, social canid distributed across south and Southeast Asia. Severe pressures from habitat loss, prey depletion, disease, human persecution and interspecific competition resulted in global population decline in dholes. Despite a declining population trend, detailed information on population size, ecology, demography and genetics is lacking. Generating reliable information at landscape level for dholes is challenging due to their secretive behaviour and monomorphic physical features. Recent advances in non-invasive DNA-based tools can be used to monitor populations and individuals across large landscapes. In this paper, we describe standardization and validation of faecal DNA-based methods for individual identification of dholes. We tested this method on 249 field-collected dhole faeces from five protected areas of the central Indian landscape in the state of Maharashtra, India. Results We tested a total of 18 cross-species markers and developed a panel of 12 markers for unambiguous individual identification of dholes. This marker panel identified 101 unique individuals from faecal samples collected across our pilot field study area. These loci showed varied level of amplification success (57-88%), polymorphism (3-9 alleles), heterozygosity (0.23-0.63) and produced a cumulative misidentification rate or PID(unbiased) and PID(sibs) value of 4.7x10-10 and 1.5x10-4, respectively, indicating a high statistical power in individual discrimination from poor quality samples. Conclusion Our results demonstrated that the selected panel of 12 microsatellite loci can conclusively identify dholes from poor quality, non-invasive biological samples and help in exploring various population parameters. This genetic approach would be useful in dhole population estimation across its range and will help in assessing population trends and other genetic parameters for this elusive, social carnivore.

opencc-zeroSep 2020View details →

Parentage analyses identify local dispersal events and sibling aggregations in a natural population of Millepora hydrocorals, a free-spawning marine invertebrate

Dispersal is a critical process for the persistence and productivity of marine populations. For many reef species, there is increasing evidence that local demography and self-recruitment have major consequences on their genetic diversity and adaptation to environmental change. Yet empirical data of dispersal patterns in reef-building species remain scarce. Here, we document the first genetic estimates of self-recruitment and dispersal distances in a free-spawning marine invertebrate, the hydrocoral Millepora platyphylla. Using twelve microsatellite markers, we gathered genotypic information from 3,160 georeferenced colonies collected over 9,000 m2 of a single reef in three adjacent habitats in Moorea, French Polynesia; the mid slope, upper slope, and back reef. Although the adult population was predominantly clonal (85% were clones), our parentage analysis revealed a moderate self-recruitment rate with 8 to 37% of sexual propagules produced locally. Assigned offspring often settled at less than 10 meters from their parents and dispersal events decrease with increasing geographic distance. There were no discrepancies between the dispersal distances of offspring assigned to parents belonging to clonal versus non-clonal genotypes. Inter-habitat dispersal events via cross-reef transport were also detected for sexual and asexual propagules. Sibship analysis showed that full siblings recruit together on the reef (more than 40% settled at < 30 m), resulting in sibling aggregations. Our findings highlight the importance of self-recruitment together with clonality in stabilizing population dynamics, which may ultimately enhance local sustainability and resilience to disturbance.

opencc-by-4.0Oct 2020View details →

PIBAC: Extensive cultivation of the pig gut microbiome identifies novel bacterial diversity and functions and enables tailored functional studies

In-depth cultivation of the pig gut microbiome towards novel bacterial diversity and tailored functional studies: <ul> <li>780 MAGs from all-in-one assembly of 295 pig gut metagenomic samples (Xiao, 2016)</li> <li>38 isolates representing novel species (single draft genomes)</li> <li>representing in total 617 species (hqMAGs-dereplicated_genomes, comp>90%, con<5%</li> </ul> More information you can find here: https://github.com/tillrobin/PIBAC https://www.dsmz.de/pibac   External study providing data: Xiao, Liang, et al. "A reference gene catalogue of the pig gut microbiome." Nature microbiology 1.12 (2016): 16161. <a href="https://doi.org/10.1038/nmicrobiol.2016.161">https://doi.org/10.1038/nmicrobiol.2016.161</a>

opencc-by-4.0Oct 2020View details →

LCCSS: A Similarity Metric for Identifying Similar Test Code

Apresentação do artigo "LCCSS: A Similarity Metric for Identifying Similar Test Code" para o SBCARS 2020.

opencc-zeroOct 2020View details →

Supplementary material 1 from: Datta A, Kumschick S, Geerts S, Wilson JRU (2020) Identifying safe cultivars of invasive plants: six questions for risk assessment, management, and communication. In: Wilson JR, Bacher S, Daehler CC, Groom QJ, Kumschick S, Lockwood JL, Robinson TB, Zengeya TA, Richardson DM. NeoBiota 62: 81-97. https://doi.org/10.3897/neobiota.62.51635

Table S1. Plant taxa listed under South African regulations for which certain sub-specific entities are listed differently from other entities

Data from: Natural disturbances can produce misleading bioassessment results: identifying metrics to detect anthropogenic impacts in intermittent rivers

Ecosystems experience natural disturbances and anthropogenic impacts that affect biological communities and ecological processes. When natural disturbance modifies anthropogenic impacts, current widely used bioassessment metrics can prevent accurate assessment of biological quality. Our aim was to assess the ability of biomonitoring metrics to detect anthropogenic impacts at both perennial and intermittent sites, and in the latter including both flowing and disconnected pool aquatic phases. Specifically, aquatic macroinvertebrates from 20 rivers were sampled along gradients of natural flow intermittence (natural disturbance) and anthropogenic impacts to investigate their combined effects on widely used river biomonitoring metrics (i.e. taxonomic richness and standard biological indices) and novel functional metrics, including functional redundancy (i.e. the number of taxa contributing similarly to an ecosystem function, here a trophic function) and response diversity (i.e. how functionally similar taxa respond to natural disturbance and anthropogenic impacts). Our results showed that natural flow intermittence can confound river bioassessment, and that a set of new functional metrics could be used as effective alternatives to standard metrics in naturally disturbed intermittent rivers.

opencc-by-4.0Nov 2020View details →

Failed Total Hip Arthroplasty: Diagnostic Performance of Conventional MRI Features and Locoregional Lymphadenopathy to Identify Infected Implants

Background: Very little has been published about the diagnostic performance of MRI in total hip arthroplasty (THA) infection. Purpose: To determine the diagnostic performance of conventional MRI features and of new lymph nodal indices to identify infection in patients with failed THA. Study type: Retrospective. Population: In all, 119 patients (66 females; age 66.9 ± 12.4 years) with failed THA. Field strength/sequences: Metal artifact reduction sequence (MARS) protocol including short tau inversion recovery and turbo spin-echo T1 - and T2 -weighted sequences at 1.5T. Assessment: Patients underwent pelvis MRI prior to failed THA revision. MRIs were reviewed to identify periprosthetic bone destruction, soft-tissue mass, effusion, synovitis, lamellated synovitis, extracapsular edema, fibrous periprosthetic membrane, bone edema, and extracapsular collection/sinus tract. The number and maximum diameter of inguinal, obturator and iliac lymph nodes of the affected hip were assessed and normalized to those of the unaffected hip to calculate the ratio of nodal size (RNS), ratio of node number (RNN), difference of nodal size (DNS), and difference of node number (DNN). Statistical tests: The Mann-Whitney U-and chi-square test were used. Diagnostic performance of indices and odds ratios (OR) were calculated. Results: RNS, RNN, DNS, and DNN indices were significantly different (P = 0.000) between infected and noninfected THA, with accuracies ranging from 84.8% (RNS) and 93.1% (RNN). All other MRI features were significantly more prevalent in infected THA (P ≤ 0.002), except bone destruction, periarticular soft-tissue mass, and fibrous membrane (P ≥ 0.031). Sensitivities ranged from 7.9% (soft-tissue mass) to 76.3% (effusion/bone edema), specificity from 45.7% (bone destruction) to 97.5% (synovitis/lamellated synovitis), accuracy from 49.6% (bone destruction) to 81.5% (synovitis), OR from 0.261 (soft-tissue mass) to 35.550 (synovitis). Data conclusion: Conventional MRI features have limited accuracy to differentiate septic and aseptic THA failure. Lymph nodal indices, particularly those related to nodal number, may represent biomarkers of THA infection.

opencc-by-4.0Nov 2020View details →

Utilizing Social Media for Identifying Drug Addiction and Recovery Intervention

This dataset is for the paper "Utilizing Social Media for Identifying Drug Addiction and Recovery Intervention" published in Data Analytics for Smart Health (DASH) workshop (<a href="https://sites.google.com/view/ieee-dash-2020">https://sites.google.com/view/ieee-dash-2020</a>) co-located with the IEEE BigData 2020 conference. Overview of the Paper Topic-specific social media forums such as Reddit have become popular platforms for users discussing health-related information as well as for scientific analysis of that information. Such discussions among users have been found to be effective in providing useful insights and assistance in many healthcare applications. This study focuses on one such application, where we utilize Reddit posts related to drug addiction/substance abuse, in order to help the addicted persons. We observe some linguistic differences in the posts as users gradually move from the addicted stage to more and more advanced recovery stages. We then classify user-posts on Reddit as to be indicative of drug addiction or of different stages of recovery of the user.  By annotating Reddit posts with the help of standard social and health psychology literature, we develop a Machine Learning classifier based on linguistic features, to classify the posts among different classes related to addiction and recovery. Finally, we identify users having an intention to recover and perform a personalized mentor recommendation by referring them to users who are already in their advanced stage of recovery based on the usage of drugs. To our knowledge, this work is the first attempt to utilize social media for helping addicted users having the intention to recover with personalized mentor recommendations to facilitate their process of recovery. Overview of the dataset  The dataset contains posts from drug addiction-related Subreddits which are topic-specific communities within the Reddit OSM (Online Social Media). We considered 100 distinct Subreddits related to drug addiction and recovery, which are listed in the Wiki page of the Subreddit `Drugs' (<a href="https://www.reddit.com/r/Drugs/wiki/subreddits">https://www.reddit.com/r/Drugs/wiki/subreddits</a>). We annotated 3151 posts out of all the posts collected as one of the 5 classes: 'Addicted', ' E(early)-Recovery',  ' M(maintaining)-Recovery',  ' A(advanced)-Recovery', 'Others'.  The dataset has the following 8 fields,  * id: A unique identifier for each post * username: The username for each post * title: Each post is associated with a title * body: The main descriptive part of the post is identified by its 'body' * #comments: This field represents the number of comments the post has received * score: This field represents the number of upvotes received by each post * label_classification: The label given to a post for the classification task (one of the 5 classes stated above) * label_recommendation: The label given to a post for the recommendation task where the 'Addicted' class of classification task was further divided into 'Addicted with intention to recover', and 'Addicted without intention to recover' Note that the dataset has been anonymized by replacing all personally identifiable information (PII) such as usernames, email-ids, phone numbers, SSNs, etc. by using the tool available at <a href="https://github.com/mns-llc/bitsnarf">https://github.com/mns-llc/bitsnarf</a>  as well as using some standard dictionary-based methods.

Utilizing next-generation sequencing to identify prey DNA in western North Atlantic grey seal (Halichoerus grypus) diet

Increasing grey seal (Halichoerus grypus) abundance in coastal New England is leading to social, political, economic, and ecological controversies. We studied grey seal feeding habits through next-generation sequencing of prey DNA using 16S amplicons from seal scat (N = 74) collected from a breeding colony on Monomoy Island in Massachusetts, U.S. and report frequency of occurrence and relative read abundance. We also assigned seal sex to scat samples using a revised PCR assay. In contrast to current understanding of grey seal diet from hard parts and fatty acid analysis, we found no significant difference between male and female diet measured by alpha and beta diversity. Overall, we detected 24 prey groups, 18 of which resolved to species. Sand lance (Ammodytes spp.) was the most frequently consumed prey group, with a frequency of occurrence (FO) of 97.3%, consistent with previous studies, but Atlantic menhaden (Brevoortia tyrannus), the second most frequently consumed species (FO = 60.8%), has not been documented in U.S. grey seal diet previously. Our results suggest that a metabarcoding approach to seal food habits can yield important new ecological insights, but that traditional hard parts analysis does not underestimate consumption of Atlantic cod (Gadus morhua; FO = 6.7% Gadidae spp.) and salmon (Salmo salar; FO = 0%), two particularly valuable species of concern.

Near-complete sequence of a novel reovirus genome identified from Callinectes sapidus

The Atlantic blue crab, Callinectes sapidus, is an estuarine keystone species that functions as both predator and prey in food webs and supports a multi-million dollar fishery along the western Atlantic coast from the US mid-Atlantic to southern Brazil. Throughout their range, blue crabs are host to viral, bacterial, fungal, protozoan, and metazoan pathogens. Reoviruses are non-enveloped icosahedral viruses with genomes comprised of 9 to 12 segments of linear double-stranded RNA (dsRNA). They have been found in diverse host species including brachyuran crustaceans. This work describes the sequence of a novel reovirus genome, discovered in Callinectes sapidus. The double-stranded RNA genome of CsRV2 consists of 12 segments that encode 13 putative proteins. High nucleotide sequence identity with Eriocheir sinensis Reovirus 905 revealed this virus belongs to Cardoreovirus within the Reoviridae family.

An integrated genomic approach identifies HOXC8 as an upstream regulator in ovarian endometrioma

Purpose: To identify the upstream regulators (URs) involved in the onset and pathogenesis of ovarian endometrioma. Methods: Recently, a method called SMITE that uses transcriptome data in combination with publicly available data for identifying URs of cellular processes has been developed. Here, we used SMITE with transcriptome data from ovarian endometrioma stromal cells (ovESCs) and eutopic endometrium stromal cells (euESCs) in combination with publicly available gene regulatory network data. To confirm the URs identified by SMITE, we developed a Boolean network simulation to see if correcting aberrant expressions of the identified genes could restore the entire gene expression profile of ovESCs to a profile similar to that of euESCs. We then established euESCs overexpressing the identified gene and characterized them by cell function assays and transcriptome analysis. Results: SMITE identified 12 potential URs in ovarian endometrioma that were confirmed by the Boolean simulation. One of the URs, HOXC8, was confirmed to be overexpressed in ovESCs. HOXC8 overexpression significantly enhanced cell proliferation, migration, adhesion, and fibrotic activities, and altered expression statuses of the genes involved in TGF-ß signaling. HOXC8 overexpression also increased the expression levels of phosphorylated SMAD2/SMAD3. The increased adhesion and fibrosis activities by HOXC8 were significantly inhibited by E-616452, a selective inhibitor of TGF-ß receptor type I kinases. Main Conclusions: Integrated genomic approaches identified HOXC8 as an UR in ovarian endometrioma. The pathological features of ovarian endometrioma including cell proliferation, adhesion, and fibrosis were induced by HOXC8 and its subsequent activation of TGF-ß signaling.

opencc-zeroDec 2020View details →

Supplementary information for: Using networks to identify structure in phylogenetic tree sets

Modern phylogenomic studies produce large sets of trees that can represent variation in inferred phylogenies across genes, uncertainty in estimated phylogenies for a given gene, or both. Standard practice is to condense this variation down to a small set of point estimates or consensus trees in order to facilitate display and interpretation. However, doing so results in the loss of enormous amounts of information about the structure of the underlying tree set. Here, we propose new approaches to explore and detect structure in the tree set itself. These approaches rely on the well-developed mathematical foundations of community detection in networks and leverage two different network types. The first type uses nodes to represent trees and connects these nodes with edges whose weights are determined by the similarity (affinity) of the trees. The second type uses nodes to represent bipartitions and connects nodes with edges whose weights represent the covariance in bipartition presence/absence across trees in the set. These two network types carry information that is complementary, but not identical. A variety of methods may be applied to both networks in order to identify interesting community structure. These community detection approaches provide a rich view of the information contained in phylogenomic data sets and facilitate investigation into the forces driving inferred phylogenetic variation across genomes.

opencc-by-4.0Dec 2020View details →

Single-cell profiling identifies pre-existing CD19-negative subclones in a B-ALL patient with CD19-negative relapse after CAR-T therapy

This repository contains necessary files for reproducing the analysis in Rabilloud, Potier et al. (2020). The instructions for reproducing the analysis are given in github (https://github.com/Delphine-Potier/B-ALL-CAR-T) and extra files are available in GEO/SRA (GSE153697 ; SRP269742).

opencc-zeroDec 2020View details →

Data from: Identifying 'useful' fitness models: balancing the benefits of added complexity with realistic data requirements in models of individual plant fitness

Direct species interactions are commonly included in individual fitness models used for coexistence and local-diversity modeling. Though widely considered important for such models, direct interactions alone are often insufficient for accurately predicting fitness, coexistence or diversity outcomes. Incorporating higher-order interactions (HOIs) can lead to more accurate individual fitness models, but also adds many model terms, which can quickly result in model over-fitting. We explore approaches for balancing the trade-off between tractability and model accuracy that occurs when HOIs are added to individual fitness models. To do this, we compare models parameterized with data from annual plant communities in Australia and Spain, varying in the extent of information included about the focal and neighbor species. The best performing models for both datasets were those that grouped neighbors based on origin status and life form, a grouping approach that reduced the number of model parameters substantially while retaining important ecological information about direct interactions and HOIs. Results suggest that specific focal- or neighbor-species identity is not necessary for building well-performing fitness models that include HOIs. In fact, grouping neighbors by even basic functional information seems sufficient to maximize model accuracy, an important outcome for the practical use of HOI-inclusive fitness models.

opencc-zeroDec 2020View details →

Data from: In search of an optimal DNA diagnosis for taxonomic descriptions with MOLD, a novel tool to identify diagnostic nucleotide characters

While DNA characters are increasingly used for phylogenetic inference, taxa delimitation and identification, their use for formal description of taxa remains scarce and inconsistent. The major impediments until recently was a lack of a suitable algorithm to identify signature DNA characters. The 2019-2020 however were marked by an almost simultaneous release of three softwares, simple to run and designed specifically for taxonomists. There is, nevertheless, a major concern, whether taxonomy will benefit from wide application of these, or any of the previously available tools. The reluctance of using DNA data in taxonomy is partly due to concerns of insufficient reliability of DNA characters, as robustness of DNA based diagnoses, depending on the sampled fraction of the species diversity has not thus far been assessed. We propose a novel program, named MOLD that recovers diagnostic nucleotide combinations (DNCs) for selected taxa with DNA sequences available. We carried our random iterated haplotype subsampling on species in six published DNA data sets of varying complexity, providing a diagnosis to each subsample to evaluate how the robustness of DNA based diagnosis changes depending on the sampled fraction of the taxon's diversity. We demonstrate that the currently used diagnostic DNA characters, or combinations thereof (DNCs) often do not exist for a particular species in a particular data set, or are not sufficiently reliable. We propose a new type of DNA diagnosis, termed herein rDNCs, which is compiled to suit pre-defined criteria of reliability, and is implemented in MOLD. We demonstrate that rDNCs can be successfully identified even in data sets comprising hundreds of species, and allow for notably more reliable diagnoses, than the currently used diagnostic DNA characters. MOLD recovers reliable and reproducible diagnoses in traditionally problematic cases, such as cryptic species or species with pronounced genetic structure, and shows unparalleled efficiency in large DNA data sets, making a valuable complement to the currently existing toolkit.

opennotspecifiedAug 2020View details →

FIGURE 2. Caecid growth stages. Roman numerals identify and arrows delimit each stage. A in A Rosetta Stone for eastern Pacific Caecidae (Gastropoda: Caenogastropoda)

FIGURE 2. Caecid growth stages. Roman numerals identify and arrows delimit each stage. A. Arrow pointing to an incised line. B. Arrow pointing to a suture. C. Arrow pointing to area with pronounced increase in diameter. D. Arrow pointing to change in sculpture. E. Arrow pointing to a varix.

opencc-by-4.0Jan 2021View details →

A systems biology approach to identify essential epigenetic regulators for specific biological processes in plants

Supplemental Files for McCoy et al "A systems biology approach to identify essential epigenetic regulators for specific biological processes in plants"

opencc-zeroJan 2021View details →

High spatial resolution mapping identifies habitat characteristics of the invasive vine Antigonon leptopus on St. Eustatius (Lesser Antilles)

On the Caribbean island of St. Eustatius, Coralita (Antigonon leptopus) is an aggressive invasive vine posing major biodiversity conservation concerns. The generation of distribution maps can address these conservation concerns by helping to elucidate the drivers of invasion. We test the use of support vector machines to map the distribution of Coralita on St. Eustatius at high spatial resolution and use this map to identify potential landscape and geomorphological factors associated with Coralita presence. This latter step was performed by comparing the actual distribution of Coralita patches to a random distribution of patches. To train the support vector machine algorithm, we used three vegetation indices and seven texture metrics derived from a 2014 WorldView-2 image. The resulting map shows that Coralita covered 3.18% of the island in 2014, corresponding to an area of 64 ha. The mapped distribution was highly accurate, with 93.2% overall accuracy (Coralita class producer's accuracy: 76.4%, user's accuracy: 86.2%). Using this classification map, we found that Coralita is not randomly distributed across the landscape, occurring significantly closer to roads and drainage channels, in areas with higher accumulated moisture, and on flatter slopes. Coralita was found more often than expected in grasslands, disturbed forest and urban areas, but was relatively rare in natural forest. These results highlight the ability of high spatial resolution data from sensors such as WorldView-2 to produce accurate invasive species, providing valuable information for predicting current and future spread risks and for early detection and removal plans.