Miracle-dz/UniFAR-FTUs huggingface dataset:
Environment, rather than Hematodinium parasitization, determines collateral disease contraction in a crustacean host

Host, pathogen, and environment are determinants of the disease triangle, the latter being a key driver of disease outcomes and persistence within a community. The dinoflagellate genus Hematodinium is detrimental to crustaceans globally – considered to suppress the innate defences of hosts, making them more susceptible to co-infections. Evidence supporting immune-suppression is largely anecdotal and sourced from diffuse accounts of compromised decapods. We used a population of shore crabs (Carcinus maenas), where Hematodinium sp. is endemic, to determine the extent of collateral infections across two distinct environments (open water, semi- closed dock). Using a multi-resource approach (PCR, histology, haematology, population genetics, eDNA), we identified 162 Hematodinium-positive crabs and size/sex-matched these to 162 Hematodinium-free crabs out of 1,191 analysed. Crabs were interrogated for additional disease-causing agents; haplosporidians, microsporidians, mikrocytids, Vibrio spp. , fungi, Sacculina, trematodes, and haemolymph bacterial loads. We found no significant differences in occurrence, severity or composition of collateral infections between Hematodinium-positive and Hematodinium-free crabs at either site, but crucially, we recorded site-restricted blends of pathogens. We found no gross signs of host cell immune reactivity toward Hematodinium in the presence or absence of other pathogens. We contend Hematodinium sp. is an immune-evader rather than immune-suppressor, which suggests an evolutionary drive toward latency in this environmentally plastic host.
Automatic consistency assurance for literature-based gene ontology annotation

Literature-based gene ontology (GO) annotation is a process where expert curators use uniform expressions to describe gene functions reported in research papers, creating computable representations of information about biological systems. Manual assurance of consistency between GO annotations and the associated evidence texts identified by expert curators is reliable but time-consuming, and is infeasible in the context of rapidly growing biological literature. A key challenge is maintaining consistency of existing GO annotations as new studies are published and the GO vocabulary is updated. In this work, we introduce a formalisation of biological database annotation inconsistencies, identifying four distinct types of inconsistency. We propose a novel and efficient method using state-of-the-art text mining models to automatically distinguish between consistent GO annotation and the different types of inconsistent GO annotation. We evaluate this method using a synthetic dataset generated by directed manipulation of instances in an existing corpus, BC4GO. We provide detailed error analysis for demonstrating that the method achieves high precision on more confident predictions. Two models built using our method for distinct annotation consistency identification tasks achieved high precision and were robust to updates in the GO vocabulary. Our approach demonstrates clear value for human-in-the-loop curation scenarios.
Confounds of using the unc-58 selection marker highlights the importance of genotyping co-CRISPR genes

Multiple advances have been made to increase the efficiency of CRISPR/Cas9 editing using the model genetic organism Caenorhabditis elegans (C. elegans). Here we report on the use of co-CRISPR ‘marker’ genes: worms in which co-CRISPR events have occurred have overt, visible phenotypes which facilitates the selection of worms that harbour CRISPR events in the target gene. Mutation in the co-CRISPR gene is then removed by outcrossing to wild type but this can be challenging if the CRISPR and co-CRISPR gene are hard to segregate. However, outcrossing can be avoided by selecting worms of wild type appearance from a ‘jackpot’ brood. These are broods in which a high proportion of the progeny of a single injected worm display the co-CRISPR phenotype suggesting high CRISPR efficiency. This can deliver worms that harbour the desired mutation in the target gene locus without the co-CRISPR mutation. We have successfully generated a discrete mutation in the C. elegans nlg-1 gene using this method. However, in the process of sequencing to authenticate editing in the nlg-1 gene we discovered genomic rearrangements that arise at the co-CRISPR gene unc-58 that by visual observation were phenotypically silent but nonetheless resulted in a significant reduction in motility scored by thrashing behaviour. This highlights that careful consideration of the hidden consequences of co-CRISPR mediated genetic changes should be taken before downstream analysis of gene function. Given this, we suggest sequencing of co-CRISPR genes following CRISPR procedures that utilise phenotypic selection as part of the pipeline.
TCAB1 is necessary for telomerase assembly

Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, U.S.A. College of Osteopathic Medicine, Michigan State University, East Lansing, MI, U.S.A. Cellular and Molecular Biology Graduate Program, College of Natural Sciences, Michigan State University, East Lansing, MI, U.S.A. Children’s Medical Research Institute and University of Sydney, Westmead, NSW 2145, Australia. Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, U.S.A. Department of Obstetrics, Gynecology, and Reproductive Biology, Michigan State University, East Lansing MI, U.S.A.
Performance Comparison between U-Net Variant Models in Spine Segmentation

Spine Magnetic resonance imaging (MRI) is a crucial diagnostic technique for illnesses of the spinal cord. The UNET network, the most prominent neural network model for segmenting medical images has opened up new opportunities for spin MRI segmentation as a result of the rapid development of deep-learning algorithms. In this study, we compared the difference between UNet and five other variants (Unet++, Unet+++, Attention-UNet, Dense-UNet, and R2UNet) in performance and efficiency by training and testing them on the same Spine MRI image dataset that contained 200 patients. The results showed that Attention-UNet performed best on the Miou (83.33 percent) and Average dice(89.15 percent) metrics; R2UNet performed best on the Accuracy (97.12 percent) metric. Attention-UNet has the slightest difference between the basic segmentation and the baseline value in terms of segmentation performance. This study could provide a better understanding of different networks on the Spine MRI Segmentation task.
Mechanosensitive Osteogenesis on Native Cellulose Scaffolds for Bone Tissue Engineering

In recent years, plant-derived cellulosic biomaterials have become a popular way to create scaffolds for a variety of tissue engineering applications. Moreover, such scaffolds possess similar physical properties (porosity, stiffness) that resemble bone tissues and have been explored as potential biomaterials for tissue engineering applications. Here, plant-derived cellulose scaffolds were seeded with MC3T3-E1 pre-osteoblast cells. Moreover, to assess the potential of these biomaterials, we also applied cyclic hydrostatic pressure (HP) to the cells and scaffolds over time to mimic a bone-like environment more closely. After one week of proliferation, cell-seeded scaffolds were exposed to HP up to 270 KPa at a frequency of 1Hz, once per day, for up to two weeks. Scaffolds were incubated in osteogenic inducing media (OM) or regular culture media (CM). The effect of cyclic HP combined with OM on cell-seeded scaffolds resulted in an increase of differentiated cells. This corresponded to an upregulation of alkaline phosphatase activity and scaffold mineralization. Importantly, the results reveal that well known mechanosensitive pathways cells which regulate osteogenesis appear to remain functional even on novel plant-derived cellulosic biomaterials.
The parasitic nematode Strongyloides ratti exists as populations of long-lived asexual lineages

Nematodes are important parasites of people and animals and in natural ecosystems they are a major ecological force. Strongyloides ratti is a common parasitic nematode of wild rats and we have investigated its population genetics using single worm, whole genome sequencing. We find that S. ratti populations in the UK consist of mixtures of asexual lineages that are widely dispersed across a host population. These parasite lineages are likely very old and may have originated in Asia from where rats originated. Genes that underly the parasitic phase of the parasite’s life cycle are hyperdiverse, compared with the rest of the genome, and this may allow the parasites to maximise their fitness in a diverse host population. These patterns of parasitic nematode population genetics have not been found before and may also apply to Strongyloides spp. that infect people, which will affect how we should approach their control.
de novo variant calling identifies cancer mutation profiles in the 1000 Genomes Project

Detection of de novo variants (DNVs) is critical for studies of disease-related variation and mutation rates. We developed a GPU-based workflow to rapidly call DNVs (HAT) and demonstrated its effectiveness by applying it to 4,216 Simons Simplex Collection (SSC) whole-genome sequenced parent-child trios from DNA derived from blood. In our SSC DNV data, we identified 78 ± 15 DNVs per individual, 18% ± 5% at CpG sites, 75% ± 9% phased to the paternal chromosome of origin, and an average allele balance of 0.49. These calculations are all in line with DNV expectations. We sought to build a control DNV dataset by running HAT on 602 whole-genome sequenced parent-child trios from DNA derived from lymphoblastoid cell lines (LCLs) from the publicly available 1000 Genomes Project (1000G). In our 1000G DNV data, we identified 740 ± 967 DNVs per individual, 14% ± 4% at CpG sites, 61% ± 11% phased to the paternal chromosome of origin, and an average allele balance of 0.41. Of the 602 trios, 80% had > 100 DNVs and we hypothesized the excess DNVs were cell line artifacts. Several lines of evidence in our data suggest that this is true and that 1000G does not appear to be a static reference. By mutation profile analysis, we tested whether these cell line artifacts were random and found that 40% of individuals in 1000G did not have random DNV profiles; rather they had DNV profiles matching B-cell lymphoma. Furthermore, we saw significant excess of protein-coding DNVs in 1000G in the gene IGLL5 that has already been implicated in this cancer. As a result of cell line artifacts, 1000G has variants present in DNA repair genes and at Clinvar pathogenic or likely-pathogenic sites. Our study elucidates important implications of the use of sequencing data from LCLs for both reference building projects as well as disease-related projects whereby these data are used in variant filtering steps.
Bibliometric Analysis on Applications of Digital Twins in Autonomous Vehicles

This paper presents a bibliometric analysis of the research literature on potential applications of digital twins in autonomous vehicles, aiming to identify its main features, the current research trends and their evolution and potential gaps for future studies. The set of publications under study is collected through the most popular scientific databases by performing targeted queries and after removing erroneous entries. Different types of analysis (trend analysis, co-occurrence analysis and citation analysis) are performed and the results obtained are presented through graphs and tables, discussed to extract useful conclusions and widened to propose future extensions and suggestions for the involved stakeholders.
Structural, elastic, and electronic properties of recently discovered ternary silicide superconductor Li2IrSi3: An ab-initio study

The structural, elastic, and electronic properties of the very recently discovered ternary silicide superconductor, Li2IrSi3, are calculated using an ab-initio technique. We adopt the plane-wave pseudopotential approach within the framework of the first-principles density functional theory (DFT) implemented by the CASTEP code. The calculated structural parameters show reasonable agreement with the experimental results. The elastic moduli of this interesting material are calculated for the first time. The electronic band structure and electronic energy density of states indicate the strong covalent Ir–Si and Si–Si bonding, which leads to the formation of the rigid structure of Li2IrSi3. Strong covalency gives rise to a high Debye temperature in this system. We discuss the theoretical results in detail in this paper.
Standard methods for Apis mellifera venom research

Honey bees have a sting which allows them to inject venomous substances into the body of an opponent or attacker. As the sting originates from a modified ovipositor, it only occurs in the female insect, and this is a defining feature of the bee species that belong to a subclade of the Hymenoptera called Aculeata. There is considerable interest in bee venom research, primarily because of an important subset of the human population who will develop a sometimes life threatening allergic response after a bee sting. However, the use of honey bee venom goes much further, with alleged healing properties in ancient therapies and recent research. The present paper aims to standardize selected methods for honey bee venom research. It covers different methods of venom collection, characterization and storage. Much attention was also addressed to the determination of the biological activity of the venom and its use in the context of biomedical research, more specifically venom allergy. Finally, the procedure for the assignment of new venom allergens has been presented. Métodos estándar para la investigación del veneno de Apis mellifera Las abejas melíferas tienen un aguijón que les permite inyectar sustancias venenosas en el cuerpo de un oponente o atacante. El aguijón es un ovipositor modificado que solo se manifiesta en el insecto hembra, siendo este una característica que define a las especies de abejas que pertenecen al subclado de himenópteros llamada Aculeata. Hay un interés considerable en la investigación del veneno de abeja, principalmente debido a que un porcentaje importante de la población humana desarrollará una respuesta alérgica - a veces mortal - a la picadura de abeja. Sin embargo, el uso del veneno de la abeja melífera abarca mucho más, con presuntas propiedades curativas en terapias antiguas e investigaciones recientes. El presente trabajo tiene como objetivo estandarizar métodos seleccionados para la investigación del veneno de las abejas melíferas. Cubre diferentes métodos de recolección, caracterización y almacenamiento de veneno. También se prestó mucha atención a la determinación de la actividad biológica del veneno y su uso en el contexto de la investigación biomédica, más específicamente la alergia al veneno. Finalmente, se ha presentado el procedimiento para la asignación de nuevos alérgenos de veneno.
Gender gap evolution: evidence from Europe during the Great Recession

This paper examines the evolution of labor market gender gaps during the Great Recession in Europe. We have focused on participation and unemployment gender gaps, and estimated fixed effects models that incorporate social, economic and institutional features of the fifteen European Union member states from 2003 to 2013. Our results indicate that gender gaps have decreased during this time span, and particularly so during the recession years. Generally speaking, economic growth seems to foster gender inequalities while labor market institutions, such as unionization and employment protection legislation, tend to favor convergence for female and male workforce participation as well as for unemployment rates. * LED and Paris 8 University, carole.brunet@univ-paris8.fr ** IDHE and Paris 8 University, esther.jeffers@univ-paris8.fr
Status of 4D BIM Implementation in Indian Construction

Enhanced visualisation is one of the low hanging fruits of BIM implementation. It helps in improving clarity in communications and fosters collaboration & coordination of construction projects for efficient delivery. 4D BIM combines the proposed sequence of work in a project with the 3D parametric digital model of the facility to be built. 4D BIM is highly beneficial both for managing people and materials. It can revolutionise the way facilities are designed, managed and developed. Significant benefits of 4D BIM have been reported in planning & project programming/scheduling, monitoring, progress conflict prevention & resolution, data security and construction safety. 4D BIM also adds value to business by facilitating marketing and sales. BIM has been primarily used by design & management consultants and some large contractors in India for design optimisation and construction project management. While 4D BIM has the potential to contribute for the efficient project delivery, there is limited literature on the extent of 4D BIM implementation in India. An attempt has been made to investigate the status of 4D BIM implementation in India and study the perceived benefits, barriers and drivers by key stakeholders in the construction sector using a questionnaire survey among clients and contractors. The results revealed high levels of awareness of 4D BIM, but the usage is low. Plan for usage in the short term is also found to be low. There is no significant difference in perception between the clients and contractors on benefits, barriers & drivers of 4D BIM. Visualizing the construction flow, Validating the time schedules by simulations and Communicating the construction plan are found to be the most perceived benefits. Lack of 4D BIM knowledge within internal workforce, Traditional project delivery methods/contract and Lack of 4D BIM expertise in the market have been reported as the critical barriers. The key drivers of 4D BIM are Government Mandate for 4D BIM and Awareness of 4D BIM benefits and ROI.
Simulations of Fast Shear Flows of PS Oligomers Confirm Monomeric Friction Reduction in Fast Elongational Flows of Monodisperse PS Melts As Indicated by Rheooptical Data

It is known that polystyrene melts behave anomalously in fast elongational flows insofar as the steady-state elongational viscosity keeps decreasing with increasing stretching rate e, without showing the typical upturn at eτR ≈ 1, with τR the Rouse time. The authors have recently suggested that such an anomalous behavior might be due to a decrease of the monomeric friction coefficient brought about by alignment of the Kuhn segments of the polymer to the stretching direction. Here we perform a quantitative analysis of such a possibility by first determining from existing stress–optical data how such a reduction should correlate to the order parameter of the Kuhn segments and then by performing nonequilibrium molecular dynamics (NEMD) simulations over a sequence of styrene oligomers. We have used NEMD not only to obtain diffusion coefficients of those oligomers but also, for what seems to be the first time, friction coefficients. Indeed, it is well-known that the Einstein relationship linking friction to .
Evaluation of Semi-Elemental Formulae vs. Polymeric Formulae as Exclusive Enteral Nutrition in Active Pediatric Crohn???s Disease in India

Background and aim: Exclusive Enteral Nutrition (EEN) is an evidence-based therapy for pediatric Crohn’s Disease (CD). Various clinical studies are conducted to compare the efficacy of polymeric versus elemental formulae in CD. This is the first Indian prospective observational study comparing the therapeutic efficacy of Polymeric Formulae (PF) vs. Semi-Elemental Formulae (SEF) to maintain clinical remission in Pediatric CD. Method: Children with active CD, who commenced on EEN were enrolled. The cohorts were assessed nutritionally and their disease activity was measured using Pediatric Crohn’s disease activity Index. Data were recorded at baseline and after 8 weeks of post EEN. Result: Out of the 38 children recruited, 20 children were treated with SEF and 18 children with PF. 45% children and 50% children were well-nourished in the SEF and PF group respectively. One child relapsed from each of the cohorts within a year. Post therapy, 85% were well-nourished in the SEF group and 77.7% of children were wellnourished in the PF group. In both groups, significant weight gain (p<0.000) was noted at the end of EEN therapy. Conclusion: Polymeric formulae and Semi elemental formulae are effective in inducing clinical remission in active CD with no systemic side effects.
Confronting DDoS Attacks in Software-Defined Wireless Sensor Networks based on Evidence Theory

DDoS attacks aim at making the authorized users unable to access the network resources. In the present paper, an evidence theory based security method has been proposed to confront DDoS attacks in software-defined wireless sensor networks. The security model, as a security unit, is placed on the control plane of the software-defined wireless sensor network aiming at detecting the suspicious traffic. The main purpose of this paper is detection of the DDoS attack using the central controller of the software-defined network and entropy approach as an effective light-weight and quick solution in the early stages of the detection and, also, Dempster-Shafer theory in order to do a more exact detection with longer time. Evaluation of the attacks including integration of data from the evidence obtained using Dempster-Shafer and entropy modules has been done with the purpose of increasing the rate of detection of the DDoS attack, maximizing the true positive, decreasing the false negative, and confronting the attack. The results of the paper show that providing a security unit on the control plane in a software-defined wireless sensor network is an efficient method for detecting and evaluating the probability of DDoS attacks and increasing the rate of detection of an attacker.
DEEP LEARNING TECHNIQUES FOR IMAGE SEGMENTATION OF WHOLE BODY MRI

Recently, deep learning methods have achieved state of the art results across many fields of research. Deep learning has become prevalent in medical image analysis and plays an integral part of contemporary healthcare. In particular, contemporary image segmentation techniques make extensive use of deep artificial neural networks. This thesis presents two deep learning architectures for segmenting 3D multiparametric MRIs of patients with limb girdle muscular dystrophy. Muscular dystrophy is a genetic disease that causes muscle to be replaced by fatty tissue over time. Segmenting images of patients with muscular dystrophy has not been done prior to this work, and no labeled datasets of muscular dystrophy images are openly available. Image segmentations provide quantitative metrics, such as the fraction of muscle voxels out of all non-background voxels, that can help clinical researchers track the progression of the disease in a patient. The fact that a labeled dataset does not exist poses a challenge. A relatively small, manually labeled dataset of tissue signatures is created to train convolutional neural networks and stacked sparse autoencoders. The success of