Miracle-dz/UniFAR-FTUs huggingface dataset:
Droplet digital PCR is an accurate method to assess methylation status on FFPE samples

ABSTRACT Most tissue samples available for cancer research are archived as formalin-fixed paraffin-embedded (FFPE) samples. However, the fixation process and the long storage duration lead to DNA fragmentation and hinder epigenome analysis. The use of droplet digital PCR (ddPCR) to detect DNA methylation has recently emerged. In this study, we compare an optimized ddPCR assay with a conventional qPCR assay by targeting a dilution series of control DNA. In addition, we compare the ddPCR technology with results from Infinium arrays targeting two separate CpG sites on a set of colon adenoma FFPE samples. Our data demonstrate that qPCR and ddPCR assess methylation status equally well on dilution controls with a high DNA input. However, the methylation detection on low-input samples is more accurate using ddPCR. The proposed primer design (methylation-independent primers with amplification of solely the converted DNA target) will allow for methylation detection, independent of bisulfite conversion efficiency. Those data show that ddPCR can be used for methylation analysis on FFPE samples with a wide range of DNA input and that the precision of the assay depends largely on the total amount of amplifiable DNA fragments. Due to accessibility of the ddPCR technology and its accuracy on high- as well as low-DNA input samples, we propose the use of this approach for studies involving degraded FFPE samples.
Recognizing Biomedical Named Entities Using Skip-Chain Conditional Random Fields

Linear-chain Conditional Random Fields (CRF) has been applied to perform the Named Entity Recognition (NER) task in many biomedical text mining and information extraction systems. However, the linear-chain CRF cannot capture long distance dependency, which is very common in the biomedical literature. In this paper, we propose a novel study of capturing such long distance dependency by defining two principles of constructing skip-edges for a skip-chain CRF: linking similar words and linking words having typed dependencies. The approach is applied to recognize gene/protein mentions in the literature. When tested on the BioCreAtIvE II Gene Mention dataset and GENIA corpus, the approach contributes significant improvements over the linear-chain CRF. We also present in-depth error analysis on inconsistent labeling and study the influence of the quality of skip edges on the labeling performance.
Structure and Dynamics of the Functionalized MOF Type UiO-66(Zr): NMR and Dielectric Relaxation Spectroscopies Coupled with DFT Calculations

Advanced one- and two-dimensional high-field and ultrafast MAS NMR measurements have been conducted in tandem with DFT calculations for the NMR parameters to deeply characterize the local environment and the long-range structure order of the porous metal–organic framework (MOF) type UiO-66(Zr) (UiO for University of Oslo) functionalized by a series of polar −Br, −2OH, and −NH2 groups. Such an innovative combining approach applied to the complex architecture of MOFs has been revealed successful not only to unambiguously assign all the NMR signals to the corresponding crystallographic sites but also to validate the crystal structures for each functionalized material that were only predicted so far. A further step consisted of probing the impact of the grafted functions on the ligand dynamics of these MOFs by means of dielectric relaxation spectroscopy measurements. It has been evidenced that the rotational motion of the organic linker requires overpassing an energy barrier that strongly depends on the funct.
Classification of EEG-based attention for brain computer interface

This paper reports on an EEG-based brain computer interface (BCI) development, which recognizes four levels of attention. In order to measure the levels of subject's attention, many types of biological signals can be recorded such as electroencephalogram (EEG), electrocardiogram(ECG), electrooculo-gram(EOG), and electromyogram (EMG). Among these methods EEG generally is used as the most effective one for assessing subject's cognitive functions. Recognizing attention levels can be used in a wide variety of applications such as students' attention level, clinical application in detecting Attention Deficit Hyperactivity Disorder (ADHD), and driver fatigue detecting system. Highlighting the four levels of attention is proposed here, in which the acquired signals from subjects are modeled in a designed task so that attention levels vary from non-attention conditions (closed eyes and reading task) to full attention conditions (mathematics task and vigilance). While the previous studies only worked on two levels of attention (low and high levels), the novelty of proposed method is in using four levels of attention. After proving the effectiveness of proposed system, the results reveal appropriate signal processing and classification methods for discriminating the levels of attention which can be used for boosting the BCI performance.
The Evolution of a Female Genital Trait Widely Distributed in the Lepidoptera: Comparative Evidence for an Effect of Sexual Coevolution

Background Sexual coevolution is considered responsible for the evolution of many male genital traits, but its effect on female genital morphology is poorly understood. In many lepidopterans, females become temporarily unreceptive after mating and the length of this refractory period is inversely related to the amount of spermatophore remaining in their genital tracts. Sperm competition can select for males that delay female remating by transferring spermatophores with thick spermatophore envelopes that take more time to be broken. These envelopes could select for signa, sclerotized sharp structures located within the female genital tract, that are used for breaking spermatophores. Thus, this hypothesis predicts that thick spermatophore envelopes and signa evolve in polyandrous species, and that these adaptations are lost when monandry evolves subsequently. Here we test the expected associations between female mating pattern and presence/absence of signa, and review the scant information available on the thickness of spermatophore envelopes. Methodology/Principal Findings We made a literature review and found information on female mating pattern (monandry/polyandry), presence/absence of signa and phylogenetic position for 37 taxa. We built a phylogenetic supertree for these taxa, mapped both traits on it, and tested for the predicted association by using Pagel's test for correlated evolution. We found that, as predicted by our hypothesis, monandry evolved eight times and in five of them signa were lost; preliminary evidence suggests that at least in two of the three exceptions males imposed monandry on females by means of specially thick spermatophore envelopes. Previously published data on six genera of Papilionidae is in agreement with the predicted associations between mating pattern and the characteristics of spermatophore envelopes and signa. Conclusions/Significance Our results support the hypothesis that signa are a product of sexually antagonistic coevolution with spermatophore envelopes.
Lethal and Pre-Lethal Effects of a Fungal Biopesticide Contribute to Substantial and Rapid Control of Malaria Vectors

Rapidly emerging insecticide resistance is creating an urgent need for new active ingredients to control the adult mosquitoes that vector malaria. Biopesticides based on the spores of entomopathogenic fungi have shown considerable promise by causing very substantial mortality within 7–14 days of exposure. This mortality will generate excellent malaria control if there is a high likelihood that mosquitoes contact fungi early in their adult lives. However, where contact rates are lower, as might result from poor pesticide coverage, some mosquitoes will contact fungi one or more feeding cycles after they acquire malaria, and so risk transmitting malaria before the fungus kills them. Critics have argued that ‘slow acting’ fungal biopesticides are, therefore, incapable of delivering malaria control in real-world contexts. Here, utilizing standard WHO laboratory protocols, we demonstrate effective action of a biopesticide much faster than previously reported. Specifically, we show that transient exposure to clay tiles sprayed with a candidate biopesticide comprising spores of a natural isolate of Beauveria bassiana, could reduce malaria transmission potential to zero within a feeding cycle. The effect resulted from a combination of high mortality and rapid fungal-induced reduction in feeding and flight capacity. Additionally, multiple insecticide-resistant lines from three key African malaria vector species were completely susceptible to fungus. Thus, fungal biopesticides can block transmission on a par with chemical insecticides, and can achieve this where chemical insecticides have little impact. These results support broadening the current vector control paradigm beyond fast-acting chemical toxins.
Reducing distress and improving social functioning in daily life in people with auditory verbal hallucinations: study protocol for the ‘Temstem’ randomised controlled trial

Introduction Auditory verbal hallucinations (AVH) are prevalent experiences that can induce distress and impede social functioning. While most voice hearers benefit from antipsychotic medication or cognitive–behavioural therapy, additional effective interventions are needed to reduce the burden of experiencing AVH. ‘Temstem’ is an easily accessible and useable smartphone application that was developed by designers in close cooperation with voice hearers and experts. By using language games, Temstem aims to reduce distress and improve social functioning. Methods This is a single-blind multicentre randomised controlled trial with two arms: ‘Temstem+AVH monitoring’ versus ‘AVH monitoring’ (total n=100). Participants are adult patients who suffer daily from AVH and will be recruited in outpatient units. Primary assessment in daily life is made by the Experience Sampling Method (ESM) and daily monitoring with the PsyMate app. During an ESM period of 6 days, participants assess their mental state (including AVH and context) several times a day by filling in short questionnaires. There are three 6-day ESM periods: at baseline (week 0–1), post-treatment (weeks 5–6) and follow-up (weeks 9–10). In addition, during the entire 10-week study period, all participants monitor their AVH two times a day with a short assessment via the PsyMate app. Participants in the Temstem+AVH monitoring condition are provided with the Temstem app from week 1 to 6. Other assessments made at baseline, post-treatment and follow-up are based on questionnaires and a clinical interview. Ethics and dissemination The results from this study will provide an evaluation of the effectiveness of Temstem, a non-invasive and easily accessible app for voice hearers, and insight into the determinants of optimal use. Results will be disseminated unreservedly, irrespective of the magnitude or direction of the effects. This study protocol was approved by the Medical Ethics Committee of the VU University Medical Centre (METC number: 2015.435/NL53684.029.15). Trial registration number ISRCTN75717636; Pre-results.
Linking hydrolysis performance to Trichoderma reesei cellulolytic enzyme profile

Trichoderma reesei expresses a large number of enzymes involved in lignocellulose hydrolysis and the mechanism of how these enzymes work together is too complex to study by traditional methods, for example, by spiking with single enzymes and monitoring hydrolysis performance. In this study, a multivariate approach, partial least squares regression, was used to see whether it could help explain the correlation between enzyme profile and hydrolysis performance. Diverse enzyme mixtures were produced by T. reesei Rut‐C30 by exploiting various fermentation conditions and used for hydrolysis of washed pretreated corn stover as a measure of enzyme performance. In addition, the enzyme mixtures were analyzed by liquid chromatography–tandem mass spectrometry to identify and quantify the different proteins. A multivariate model was applied for the prediction of enzyme performance based on the combination of different proteins present in an enzyme mixture. The multivariate model was used for identification of candidate proteins that are correlated to enzyme performance on pretreated corn stover. A very large variation in hydrolysis performance was observed and this was clearly caused by the difference in fermentation conditions. Besides β‐glucosidase, the multivariate model identified several xylanases, Cip1 and Cip2, as relevant proteins to study further. Biotechnol. Bioeng. 2016;113: 1001–1010. © 2015 Wiley Periodicals, Inc.
Navigating the Interface Between Landscape Genetics and Landscape Genomics

As next-generation sequencing data become increasingly available for non-model organisms, a shift has occurred in the focus of studies of the geographic distribution of genetic variation. Whereas landscape genetics studies primarily focus on testing the effects of landscape variables on gene flow and genetic population structure, landscape genomics studies focus on detecting candidate genes under selection that indicate possible local adaptation. Navigating the transition between landscape genomics and landscape genetics can be challenging. The number of molecular markers analyzed has shifted from what used to be a few dozen loci to thousands of loci and even full genomes. Although genome scale data can be separated into sets of neutral loci for analyses of gene flow and population structure and putative loci under selection for inference of local adaptation, there are inherent differences in the questions that are addressed in the two study frameworks. We discuss these differences and their implications for study design, marker choice and downstream analysis methods. Similar to the rapid proliferation of analysis methods in the early development of landscape genetics, new analytical methods for detection of selection in landscape genomics studies are burgeoning. We focus on genome scan methods for detection of selection, and in particular, outlier differentiation methods and genetic-environment association tests because they are the most widely used. Use of genome scan methods requires an understanding of the potential mismatches between the biology of a species and assumptions inherent in analytical methods used, which can lead to high false positive rates of detected loci under selection. Key to choosing appropriate genome scan methods is an understanding of the underlying demographic structure of study populations, and such data can be obtained using neutral loci from the generated genome-wide data or prior knowledge of a species' phylogeographic history. To this end, we summarize recent simulation studies that test the power and accuracy of genome scan methods under a variety of demographic scenarios and sampling designs. We conclude with a discussion of additional considerations for future method development, and a summary of methods that show promise for landscape genomics studies but are not yet widely used.
Determination of gluten consumption in celiac disease patients on a gluten-free diet.

Background Celiac disease (CD) patients adhering to a gluten-free diet (GFD) are exposed frequently to low levels of gluten that contribute to symptoms and persistent intestinal histologic damage. Objective We analyzed prior clinical data to determine how much gluten is accidentally consumed while on a GFD. The aim was to understand the range of gluten consumption for a wide distribution of CD patients. Design A meta-analysis was conducted on data from 2 different clinical programs: 1) measurements of gluten in stool and urine in CD and non-CD populations; and 2) analysis of data from trials for the investigational therapeutic latiglutenase. The stool and urine studies included controlled gluten challenges. A calibration factor was applied that allowed normal ingestion of gluten to be computed from the urine and stool measurements. From the latiglutenase trial data, a determination of gluten consumption was made by estimating how much gluten was eliminated from patients' diets due to a trial effect that led to improved histology even in the placebo group. Results The average inadvertent exposure to gluten by CD individuals on a GFD was estimated to be ∼150-400 (mean) and ∼100-150 (median) mg/d using the stool test and ∼300-400 (mean) and ∼150 (median) mg/d using the urine test. The analyses of the latiglutenase data for CD individuals with moderate to severe symptoms indicate that patients ingested significantly >200 mg/d of gluten. Conclusions These surrogate biomarkers of gluten ingestion indicate that many individuals following a GFD regularly consume sufficient gluten to trigger symptoms and perpetuate intestinal histologic damage.
Desmoglein-2 interaction is crucial for cardiomyocyte cohesion and function.

AIMS We determined the contribution of the desmosomal cadherin desmoglein-2 to cell-cell cohesion in cardiomyocytes. In the intercalated disc, providing mechanical strength and electrical communication between adjacent cardiomyocytes, desmoglein-2 is closely associated with N-cadherin and gap junctions. METHODS AND RESULTS We studied intercalated discs of HL-1 cardiomyocytes by immunostaining of desmoglein-2 and N-cadherin. Cohesion was measured using a liberase-based dissociation-assay and compared with cell-free single-molecule atomic force microscopy measurements. L-tryptophan caused irregular desmoglein-2 condensation, weakened cell-cell cohesion and impaired both homophilic desmoglein-2 and N-cadherin trans-interaction, whereas l-phenylalanine had no effect. L-tryptophan did not affect N-cadherin localization and its inhibitory effect on cell-cohesion and desmoglein-2 binding, but not on N-cadherin interaction, was blocked by a desmoglein-specific tandem peptide. Moreover, Ca(2+)-depletion, desmoglein-2 knockdown, a desmoglein-specific single peptide and certain desmoglein-2 mutations associated with arrhythmogenic cardiomyopathy reduced cell-cell cohesion, whereas cell adhesion was strengthened by desmoglein-2 overexpression. Since single peptide did not interfere with N-cadherin trans-interaction, these data indicate that (i) desmoglein-2 binding is crucial for cardiomyocyte cohesion and (ii) L-tryptophan reduced both desmoglein-2 and N-cadherin binding, whereas single and tandem peptide can be used to specifically target desmoglein-2-mediated adhesion. L-tryptophan and single peptide also induced ultrastructural alterations of areae compositae. Functional analyses at the organ level revealed reduced cardiomyocyte function and inefficient response to adrenergic stimulation in both L-tryptophan- and single peptide-challenged murine Langendorff hearts paralleled by redistribution of connexin 43 in L-tryptophan-treated heart slices. CONCLUSION Our data demonstrate that desmoglein-2 plays a critical role in cardiomyocyte cohesion and function.
Molecular Identification of Forensically Important Blow Fly Species (Diptera: Calliphoridae) in Taiwan

Abstract Forensic entomology is a discipline that mainly uses insects collected in and around corpses to estimate the post-mortem interval in medicocriminal investigations. Among all scavenger and necrophagous insect groups that are related to corpses, blow flies (Diptera: Calliphoridae) are probably most important, not only because they occur in abundant numbers but also because they are one of the earliest groups to find corpses. However, most entomological evidence is strongly dependent on accurate species identification. Because identification allows the proper developmental data and distribution ranges to be applied in criminal investigations, species in Taiwan were surveyed from early 2000 and were identified using molecular data. Currently, eight species have been identified: Chrysomya megacephala (Fabricius), Chrysomya pinguis (Walker), Chrysomya rufifacies (Macquart), Hemipyrellia ligurriens (Wiedemann), Lucilia bazini Séguy, Lucilia cuprina (Wiedemann), Lucilia hainanensis Fan, and Lucilia prophyrina (Walker). We focused on classifying these blow fly species to establish a knowledge basis for further forensic entomological research in Taiwan. Because molecular data are helpful in identifying insect specimens, especially when no specimen of suitable condition for morphological identification is obtained, we extracted mitochondrial cytochrome oxidase subunit I (COI) DNA of the preceding blow fly species to study its application value for their differentiation. The cloning and sequencing of the COI gene (≈1,588 base pairs) of these eight species were completed, and the data were analyzed. Preliminary results revealed the high support of congeneric groupings of species by using COI data; these sequences were also shown to be highly conserved within the same species. To actually use the database of COI sequences under various specimen conditions, specific primers were also applied for different insect stages, different segments of adults, and specimens preserved for various times. A molecular primer key was ultimately constructed for the purpose of rapid and accurate species identification at the molecular level regardless of which stage or which part of a blow fly specimen is collected.
Clustering Arabic Tweets for Sentiment Analysis

The focus of this study is to evaluate the impact of linguistic preprocessing and similarity functions for clustering Arabic Twitter tweets. The experiments apply an optimized version of the standard K-Means algorithm to assign tweets into positive and negative categories. The results show that root-based stemming has a significant advantage over light stemming in all settings. The Averaged Kullback-Leibler Divergence similarity function clearly outperforms the Cosine, Pearson Correlation, Jaccard Coefficient and Euclidean functions. The combination of the Averaged Kullback-Leibler Divergence and root-based stemming achieved the highest purity of 0.764 while the second-best purity was 0.719. These results are of importance as it is contrary to normal-sized documents where, in many information retrieval applications, light stemming performs better than root-based stemming and the Cosine function is commonly used.
Resource aware design of a deep convolutional-recurrent neural network for speech recognition through audio-visual sensor fusion

Today's Automatic Speech Recognition systems only rely on acoustic signals and often don't perform well under noisy conditions. Performing multi-modal speech recognition - processing acoustic speech signals and lip-reading video simultaneously - significantly enhances the performance of such systems, especially in noisy environments. This work presents the design of such an audio-visual system for Automated Speech Recognition, taking memory and computation requirements into account. First, a Long-Short-Term-Memory neural network for acoustic speech recognition is designed. Second, Convolutional Neural Networks are used to model lip-reading features. These are combined with an LSTM network to model temporal dependencies and perform automatic lip-reading on video. Finally, acoustic-speech and visual lip-reading networks are combined to process acoustic and visual features simultaneously. An attention mechanism ensures performance of the model in noisy environments. This system is evaluated on the TCD-TIMIT 'lipspeaker' dataset for audio-visual phoneme recognition with clean audio and with additive white noise at an SNR of 0dB. It achieves 75.70% and 58.55% phoneme accuracy respectively, over 14 percentage points better than the state-of-the-art for all noise levels.