Miracle-dz/UniFAR-FTUs huggingface dataset:
The plover neurotranscriptome assembly: transcriptomic analysis in an ecological model species without a reference genome

We assembled a de novo transcriptome of short‐read Illumina RNA‐Seq data generated from telencephalon and diencephalon tissue samples from the Kentish plover, Charadrius alexandrinus. This is a species of considerable interest in behavioural ecology for its highly variable mating system and parental behaviour, but it lacks genomic resources and is evolutionarily distant from the few available avian draft genome sequences. We assembled and identified over 21 000 transcript contigs with significant expression in our samples, showing high homology to exonic sequences in avian draft genomes. From these, we identified >31 000 high‐quality SNPs and > 2500 simple sequence repeats (SSRs). We also analysed expression patterns in our data to identify potential candidate genes related to differences in male and female behaviour, identifying over 200 nonoverlapping putative autosomal transcripts that show significant expression differences between males and females. Gene ontology analysis revealed that female‐biased transcripts were significantly enriched for cerebral functions related to learning, cognition and memory, and male‐biased transcripts were mostly enriched for terms related to neural function such as neuron projection and synapses. This data set provides one of the first de novo transcriptome assemblies from non‐normalized short‐read next‐generation data and outlines an effective strategy for measuring sequence and expression variability simultaneously without the aid of a reference genome.
A pragmatic approach to the analysis of diets of generalist predators: the use of next‐generation sequencing with no blocking probes

Predicting whether a predator is capable of affecting the dynamics of a prey species in the field implies the analysis of the complete diet of the predator, not simply rates of predation on a target taxon. Here, we employed the Ion Torrent next‐generation sequencing technology to investigate the diet of a generalist arthropod predator. A complete dietary analysis requires the use of general primers, but these will also amplify the predator unless suppressed using a blocking probe. However, blocking probes can potentially block other species, particularly if they are phylogenetically close. Here, we aimed to demonstrate that enough prey sequence could be obtained without blocking probes. In communities with many predators, this approach obviates the need to design and test numerous blocking primers, thus making analysis of complex community food webs a viable proposition. We applied this approach to the analysis of predation by the linyphiid spider Oedothorax fuscus in an arable field. We obtained over two million raw reads. After discarding the low‐quality and predator reads, the libraries still contained over 61 000 prey reads (3% of the raw reads; 6% of reads passing quality control). The libraries were rich in Collembola, Lepidoptera, Diptera and Nematoda. They also contained sequences derived from several spider species and from horticultural pests (aphids). Oedothorax fuscus is common in UK cereal fields, and the results showed that it is exploiting a wide range of prey. Next‐generation sequencing using general primers but without blocking probes provided ample sequences for analysis of the prey range of this spider and proved to be a simple and inexpensive approach.
Towards I-centric business communication tools

The vision of I-centric communications is one of the important and well-known paradigms for future ubiquitous user-centric services. Following this vision, the goal of the research project 'I-centric business communication tools (ICBCT)' is to realize a seamless computing environment and supporting tools for mobile workers and users. Context awareness, personalization, adaptation as well as communication support are identified as key features of the envisioned platform. The tools were implemented using YACAN (yet-another context awareness), which is a context awareness framework developed by NTT DATA. During the course of the project, YACAN are enhanced with features derived from the I-centric communications approach. This paper introduces the functional building blocks as well as the logical architecture of the resulting ICBCT platform. Based on this architecture two service scenarios was shown.
Silica particles with encapsulated DNA as trophic tracers

Ecological networks such as food webs are extremely complex and can provide important information about the robustness and productivity of an ecosystem. In most cases, it is not feasible to observe trophic interactions between predators and prey directly and with the available methods, it is difficult to quantify the connections between them. Here, we show that submicron‐sized silica particles (100–150 nm) with encapsulated DNA (SPED) enable accurate food and organism labelling and quantification of specific animal‐to‐animal transfer over more than one trophic level. We found that SPED were readily transferable and quantifiable from the bottom to the top of a two‐level food chain of arthropods. SPED were taken up in the gut system and remained persistent in an animal over several days. When uniquely labelled SPED were applied at predefined ratios, we found that information about their relative abundance was reliably conserved after trophic level transfer and over time. SPED were also applied to investigate the flower preference of fly pollinators and proved to be a fast and accurate analysis method. SPED combine attributes of DNA barcoding and stable isotope analysis such as unique labelling, quantification via real‐time PCR and exact backtracking to the tracer source. This improves and simplifies the analysis and monitoring of ecological networks.
Performance of partial statistics in individual‐based landscape genetics

Individual‐based landscape genetic methods have become increasingly popular for quantifying fine‐scale landscape influences on gene flow. One complication for individual‐based methods is that gene flow and landscape variables are often correlated with geography. Partial statistics, particularly Mantel tests, are often employed to control for these inherent correlations by removing the effects of geography while simultaneously correlating measures of genetic differentiation and landscape variables of interest. Concerns about the reliability of Mantel tests prompted this study, in which we use simulated landscapes to evaluate the performance of partial Mantel tests and two ordination methods, distance‐based redundancy analysis (dbRDA) and redundancy analysis (RDA), for detecting isolation by distance (IBD) and isolation by landscape resistance (IBR). Specifically, we described the effects of suitable habitat amount, fragmentation and resistance strength on metrics of accuracy (frequency of correct results, type I/II errors and strength of IBR according to underlying landscape and resistance strength) for each test using realistic individual‐based gene flow simulations. Mantel tests were very effective for detecting IBD, but exhibited higher error rates when detecting IBR. Ordination methods were overall more accurate in detecting IBR, but had high type I errors compared to partial Mantel tests. Thus, no one test outperformed another completely. A combination of statistical tests, for example partial Mantel tests to detect IBD paired with appropriate ordination techniques for IBR detection, provides the best characterization of fine‐scale landscape genetic structure. Realistic simulations of empirical data sets will further increase power to distinguish among putative mechanisms of differentiation.
A microsatellite‐based linkage map for song sparrows (Melospiza melodia)

Although linkage maps are important tools in evolutionary biology, their availability for wild populations is limited. The population of song sparrows (Melospiza melodia) on Mandarte Island, Canada, is among the more intensively studied wild animal populations. Its long‐term pedigree data, together with extensive genetic sampling, have allowed the study of a range of questions in evolutionary biology and ecology. However, the availability of genetic markers has been limited. We here describe 191 new microsatellite loci, including 160 high‐quality polymorphic autosomal, 7 Z‐linked and 1 W‐linked markers. We used these markers to construct a linkage map for song sparrows with a total sex‐averaged map length of 1731 cM and covering 35 linkage groups, and hence, these markers cover most of the 38–40 chromosomes. Female and male map lengths did not differ significantly. We then bioinformatically mapped these loci to the zebra finch (Taeniopygia guttata) genome and found that linkage groups were conserved between song sparrows and zebra finches. Compared to the zebra finch, marker order within small linkage groups was well conserved, whereas the larger linkage groups showed some intrachromosomal rearrangements. Finally, we show that as expected, recombination frequency between linked loci explained the majority of variation in gametic phase disequilibrium. Yet, there was substantial overlap in gametic phase disequilibrium between pairs of linked and unlinked loci. Given that the microsatellites described here lie on 35 of the 38–40 chromosomes, these markers will be useful for studies in this species, as well as for comparative genomics studies with other species.
Gastro-oesophageal reflux symptoms, oesophagitis and Barrett’s oesophagus in the general population: the Loiano–Monghidoro study

Objective: Existing endoscopy-based data on gastro-oesophageal reflux disease (GORD) in the general population are scarce. This study aimed to evaluate typical symptoms and complications of GORD, and their associated risk factors, in a representative sample of the Italian population. Methods: 1533 adults from two Italian villages were approached to undergo symptom assessment using a validated questionnaire and upper gastrointestinal endoscopy. Data were obtained from 1033 individuals (67.4% response rate). Results: The prevalence of reflux symptoms was 44.3%; 23.7% of the population experienced such symptoms on at least 2 days per week (frequent symptoms). The prevalence rates of oesophagitis and Barrett’s oesophagus in the population were 11.8% and 1.3%, respectively. Both frequent (relative risk (RR) 2.6; 95% confidence interval (CI) 1.7 to 3.9) and infrequent (RR 1.9; 95% CI 1.2 to 3.0) reflux symptoms were associated with the presence of oesophagitis. No reflux symptoms were reported by 32.8% of individuals with oesophagitis and 46.2% of those with Barrett’s oesophagus. Hiatus hernia was associated with frequent reflux symptoms and oesophagitis, and was present in 76.9% of those with Barrett’s oesophagus. We found no association between body mass index and reflux symptoms or oesophagitis. Conclusions: GORD is common in Italy, but the prevalence of Barrett’s oesophagus in the community is lower than has been reported in selected populations. Both frequent and infrequent reflux symptoms are associated with an increased risk of oesophagitis. Individuals with oesophagitis and Barrett’s oesophagus often have no reflux symptoms.
Individual identification from genetic marker data: developments and accuracy comparisons of methods

Genetic marker‐based identification of distinct individuals and recognition of duplicated individuals has important applications in many research areas in ecology, evolutionary biology, conservation biology and forensics. The widely applied genotype mismatch (MM) method, however, is inaccurate because it relies on a fixed and suboptimal threshold number (TM) of mismatches, and often yields self‐inconsistent pairwise inferences. In this study, I improved MM method by calculating an optimal TM to accommodate the number, mistyping rates, missing data and allele frequencies of the markers. I also developed a pairwise likelihood relationship (LR) method and a likelihood clustering (LC) method for individual identification, using poor‐quality data that may have high and variable rates of allelic dropouts and false alleles at genotyped loci. The 3 methods together with the relatedness (RL) method were then compared in accuracy by analysing an empirical frog data set and many simulated data sets generated under different parameter combinations. The analysis results showed that LC is generally one or two orders more accurate for individual identification than the other methods. Its accuracy is especially superior when the sampled multilocus genotypes have poor quality (i.e. teemed with genotyping errors and missing data) and highly replicated, a situation typical of noninvasive sampling used in estimating population size. Importantly, LC is the only method that guarantees to produce self‐consistent results by partitioning the entire set of multilocus genotypes into distinct clusters, each cluster containing one or more genotypes that all represent the same individual. The LC and LR methods were implemented in a computer program COLONY for free download from the Internet.
Development of a stereo video see-through HMD for AR systems

Geometrical studies and experiments were carried out in order to specify requirements for the imaging and display systems of a stereo video see-through head-mounted display (HMD) for augmented reality (AR) systems. It was found that it was necessary to set the left and right optical axes of the stereoscopic imaging system to be parallel to one another, and likewise for the display system. It was also found that, for AR applications handling real spaces at short distances, it was necessary to align the optical axes of the imaging system with the optical axes of the display system in order to avoid spatial perception errors. We refer to this as a 'parallax-free' system. Based on these studies and experiments, a parallax-free stereo video see-through HMD with a wide field of view was developed. It was also confirmed experimentally that a small displacement of the entrance pupils of the imaging system along the axes to the exit pupils of the display system does not cause serious spatial perception errors. By displacing the position of the entrance pupils of the imaging system by 30 mm, we have downsized the HMD to a thickness of 36 mm and lightened it to 340 g. The HMD was then applied to an actual AR system and its usefulness was verified.
Optimization of AFLP for extremely large genomes over 70 Gb

Here, we present an improved amplified fragment length polymorphism (AFLP) protocol using restriction enzymes (AscI and SbfI) that recognize 8‐base pair sequences to provide alternative optimization suitable for species with a genome size over 70 Gb. This cost‐effective optimization massively reduces the number of amplified fragments using only +3 selective bases per primer during selective amplification. We demonstrate the effects of the number of fragments and genome size on the appearance of nonidentical comigrating fragments (size homoplasy), which has a negative impact on the informative value of AFLP genotypes. We also present various reaction conditions and their effects on reproducibility and the band intensity of the extremely large genome of Viscum album. The reproducibility of this octo‐cutter protocol was calculated using several species with genome sizes ranging from 1 Gb (Carex panicea) to 76 Gb (V. album). The improved protocol also succeeded in detecting high intraspecific variability in species with large genomes (V. album, Galanthus nivalis and Pinus pumila).
Hedgehog inhibition prolongs survival in a genetically engineered mouse model of pancreatic cancer

Background and aims: Pancreatic cancer is among the most dismal of human malignancies. Current therapeutic strategies are virtually ineffective in controlling advanced, metastatic disease. Recent evidence suggests that the Hedgehog signalling pathway is aberrantly reactivated in the majority of pancreatic cancers, and that Hedgehog blockade has the potential to prevent disease progression and metastatic spread. Methods: Here it is shown that the Hedgehog pathway is activated in the Pdx1-Cre;LsL-KrasG12D;Ink4a/Arflox/lox transgenic mouse model of pancreatic cancer. The effect of Hedgehog pathway inhibition on survival was determined by continuous application of the small molecule cyclopamine, a smoothened antagonist. Microarray analysis was performed on non-malignant human pancreatic ductal cells overexpressing Gli1 in order to screen for downstream Hedgehog target genes likely to be involved in pancreatic cancer progression. Results: Hedgehog inhibition with cyclopamine significantly prolonged median survival in the transgenic mouse model used here (67 vs 61 days; p = 0.026). In vitro data indicated that Hedgehog activation might at least in part be ascribed to oncogenic Kras signalling. Microarray analysis identified 26 potential Hedgehog target genes that had previously been found to be overexpressed in pancreatic cancer. Five of them, BIRC3, COL11A1, NNMT, PLAU and TGM2, had been described as upregulated in more than one global gene expression analysis before. Conclusion: This study provides another line of evidence that Hedgehog signalling is a valid target for the development of novel therapeutics for pancreatic cancer that might be worth evaluating soon in a clinical setting.
Identification of oncogenic genes for colon adenocarcinoma from genomics data

Identification of oncogenic genes from comprehensive genomics data with large sample size is of challenge. Here, we apply a well-established computational model, Bayesian factor and regression model (BFRM), to predict unknown colon cancer genes from colon adenocarcinoma genomic data. The BFRM takes advantages of its latent factors to characterize the underlying association between genes and the large number of colon cancer patients. Based on the known cancer genes in Online Mendelian Inheritance in Man (OMIM), we addressed three important latent factors focusing on characterization of heterogeneity of expression patterns related to specific oncogenic genes from the microarray data of 174 colon cancer patients. We found that the three latent factors can be employed to predict unknown colon cancer genes using the known oncogenic genes. These predicted unknown cancer genes were extensively validated by using the new somatic genes identified in the same patients from DNA sequencing data.
TEMPLE: analysing population genetic variation at transcription factor binding sites

Genetic variation occurring at the level of regulatory sequences can affect phenotypes and fitness in natural populations. This variation can be analysed in a population genetic framework to study how genetic drift and selection affect the evolution of these functional elements. However, doing this requires a good understanding of the location and nature of regulatory regions and has long been a major hurdle. The current proliferation of genomewide profiling experiments of transcription factor occupancies greatly improves our ability to identify genomic regions involved in specific DNA–protein interactions. Although software exists for predicting transcription factor binding sites (TFBS), and the effects of genetic variants on TFBS specificity, there are no tools currently available for inferring this information jointly with the genetic variation at TFBS in natural populations. We developed the software Transcription Elements Mapping at the Population LEvel (TEMPLE), which predicts TFBS, evaluates the effects of genetic variants on TFBS specificity and summarizes the genetic variation occurring at TFBS in intraspecific sequence alignments. We demonstrate that TEMPLE's TFBS prediction algorithms gives identical results to PATSER, a software distribution commonly used in the field. We also illustrate the unique features of TEMPLE by analysing TFBS diversity for the TF Senseless (SENS) in one ancestral and one cosmopolitan population of the fruit fly Drosophila melanogaster. TEMPLE can be used to localize TFBS that are characterized by strong genetic differentiation across natural populations. This will be particularly useful for studies aiming to identify adaptive mutations. TEMPLE is a java‐based cross‐platform software that easily maps the genetic diversity at predicted TFBSs using a graphical interface, or from the Unix command line.
Partial genotyping at polymorphic markers can improve heritability estimates in sibling groups

Accurate estimates of heritability ( h2 ) are necessary to assess adaptive responses of populations and evolution of fitness‐related traits in changing environments. For plants, h2 estimates generally rely on maternal progeny designs, assuming that offspring are either half‐sibs or unrelated. However, plant mating systems often depart from half‐sib assumptions, this can bias h2 estimates. Here, we investigate how to accurately estimate h2 in nonmodel species through the analysis of sibling designs with a moderate genotyping effort. We performed simulations to investigate how microsatellite marker information available for only a subset of offspring can improve h2 estimates based on maternal progeny designs in the presence of nonrandom mating, inbreeding in the parental population or maternal effects. We compared the basic family method, considering or not adjustments based on average relatedness coefficients, and methods based on the animal model. The animal model was used with average relatedness information, or with hybrid relatedness information: associating one‐generation pedigree and family assumptions, or associating one‐generation pedigree and average relatedness coefficients. Our results highlighted that methods using marker‐based relatedness coefficients performed as well as pedigree‐based methods in the presence of nonrandom mating (i.e. unequal male reproductive contributions, selfing), offering promising prospects to investigate in situ heritabilities in natural populations. In the presence of maternal effects, only the use of pairwise relatednesses through pedigree information improved the accuracy of h2 estimates. In that case, the amount of father‐related offspring in the sibling design is the most critical. Overall, we showed that the method using both one‐generation pedigree and average relatedness coefficients was the most robust to various ecological scenarios.
Twitch-Obtaining Intramuscular Stimulation: Observations in the Management of Radiculopathic Chronic Low Back Pain

Objectives: To display the effect of twitch-obtaining intramuscular stimulation [TOIMS] in chronic lower back pain management and to identify characteristics of patients who respond best to TOIMS.Methods: Retrospective analysis included 32 consecutive patients who failed conventional treatment for low back and/or lower extremity pain. All patients referred for TOIMS received such treatment. Analysis included TOIMS patients treated between January, 1992 through June, 1995. Treatments occurred weekly or every two weeks. The controls were patients with similar symptoms referred for electrodiagnosis and received only standard treatment [StdRx, not including TOIMS] for lower back pain management. Assessment of outcomes occurred at a mean of 30.9 ± 10.8 months. The main outcome measures studied were pain reduction and return to work.Results: Patients who received TOIMS had significantly longer symptom duration, and there were more patients with fibromyalgia, spinal stenosis, and failed lumbar surgeries. At foll.