Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Heat Processing on DNA Degradation and PCR-Based Detection of Wild-Type and Transgenic Maize

Reliable detection of genetically modified (GM) maize is significant for food authenticity, labelling, quality, and safety assessment. This study aims to evaluate the factors influencing degradation and polymerase chain reaction (PCR) amplification of DNA from the wild type and transgenic maize (events Bt-176 and MON810) during thermal treatment at 100°C and 121°C. A new PCR method was developed targeting the Cry1Ab gene to detect insect-resistant GM plants. The yield of genomic DNAs extracted by the DNeasy plant mini kit dramatically decreased while DNAs obtained by cetyltrimethyl ammonium bromide- (CTAB-) based method did not show any visible changes in the yield by the time of processing. Treatment at 100°C did not significantly affect either genomic DNAs or amplicons. Heating at 121°C induced time-dependent degradation of genomic DNAs and exogenous Cry1Ab gene; however, it did not have any considerable influence on the exogenous 141 bp amplicons or endogenous amplicons in the range of 102 bp to 226 bp with the exception of the event MON810 extracted by the DNeasy plant mini kit. More yield was observed at 226 bp than 140 bp fragment of the invertase gene. The 141 bp fragment of the transgenic CaMV 35S promoter exhibited the highest thermal stability of all the examined amplicons. Analysis of foodstuffs demonstrated 102 bp amplicons specific for the zein gene as the effective marker to detect maize in the processed foods. The obtained results demonstrate that PCR-based detection of the wild type and transgenic maize is dependent on the combination of different parameters of crucial factors such as temperature and duration of exposure, transgenic event, DNA extraction method, DNA marker, and size and location of amplicons.
The Role of Threonyl-tRNA Synthetase in Regulating Autophagy in Ovarian Cancer

Autophagy is the process by which lysosomes degrade and recycle damaged proteins and organelles in order to promote cell survival under situations of nutrient deprivation and homeostatic stress. Studies in the Lounsbury Lab have identified threonyl-tRNA synthetase (TARS) as a potential regulator in the autophagy pathway. This study tests the hypotheses that TARS independently inhibits the process of autophagy within human ovarian cancer cells and that blocking TARS signaling increases markers of autophagy within tumors in a mouse model of ovarian cancer. Ovarian cancer cells were cultured and transfected with siRNA to reduce TARS levels and quantitative Western blotting was employed to test the effects of TARS knockdown during amino acid starvation or mTOR inhibition. Changes were detected using antibodies against TARS, the positive autophagy markers p-AMPK and p-ULK, and the protein p62. TARS knockdown by siRNA was successful (p<0.0001) and TARS inhibition resulted in increased levels of p-AMPK (p=0.0007) and p-ULK (p=0.003). To assess in vivo effects of TARS activity on autophagy, mice were injected subcutaneously with ID-8 ovarian cancer cells. After three weeks, the animals were treated three times per week with either vehicle control or the TARS inhibitor BC194. Tumor sections were analyzed by immunohistochemistry to detect TARS, autophagy, and inflammatory markers. Tumors treated with BC194 were larger and showed increased levels of TARS. The results of this study have strong implications for the potential to identify a novel therapeutic target in ovarian cancer treatment.
How linear distance and structural distance affect the processing of gap-filler dependencies in head-final relative clauses: An eye-tracking study on Mandarin Chinese

For sentences involving long-distance dependencies like relative clauses (RCs), there are two ways to view the distance between the head noun and the gap. One is the linear way and the other is the structural way. This study examines the respective roles of linear distance and structural distance and their interaction in processing long-distance dependencies in head-final RCs where the gap precedes the head noun. We measured Mandarin speakers’ eye-movements on reading sentences with subject-gap RCs in pseudo-cleft constructions. Overall, the findings suggest that structural distance affects the initial stage of processing and it interacts with linear distance, and that the factor of linear distance might need to be reconsidered in the processing of gap-filler dependencies in head-final RC structures.
Late Upper Palaeolithic hunter-gatherers in the Central Mediterranean: new archaeological and genetic data from the Late Epigravettian burial Oriente C (Favignana, Sicily)

Grotta d’Oriente, a small coastal cave located on the island of Favignana (Sicily, Italy) is a key site for the study of the early human colonization of Sicily. The individual known as Oriente C was found in the lower portion of an anthropogenic deposit containing typical local Late Upper Palaeolithic (Late Epigravettian) stone assemblages. Two radiocarbon dates on charcoal from the deposit containing the burial are consistent with the archaeological context and refer Oriente C to a period spanning about 14,200-13,800 cal. BP. Anatomical features are close to those of Late Upper Palaeolithic populations of the Mediterranean and show strong affinity with Palaeolithic individuals of San Teodoro. Here we present new ancient DNA data from Oriente C. Our results, confirming previous genetic analysis, suggest a substantial genetic homogeneity among Late Epigravettian hunter-gatherer populations of Central Mediterranean, presumably as a consequence of continuous gene flow among different groups, or a range expansion following the Last Glacial Maximum (LGM).
Factors influencing household participation in community forest management: evidence from Udon Thani Province, Thailand

ABSTRACT Rural communities in Thailand have long managed and used forest resources for their livelihoods. Using survey data collected from 400 households across two villages in northeastern Thailand, this study identifies the factors influencing household members’ participation in local community forest management (CFM) programs. Results of the logit regression models revealed that occupation, the number of years of residence in the community, household income and expense, the receipt of CFM information and training, CFM knowledge, decision process in CFM program, and the perceived social and institutional benefits of CFM positively influenced participation in the CF programs. Furthermore, self-efficiency was found to negatively influence participation. Overall, the findings indicate that local people who are less confidence or do not view participation goals as important but when they have been trained, have knowledge about the value of community forest. They are more likely to participate in CFM programs. These results improve our understanding of household participation in community forest management and highlight the need for context-specific approaches to community engagement in forest management programs for optimal policy solutions.
Research of Interval-based Cloud Similarity Comparison Algorithm

Uncertainty phenomenon includes fuzziness and randomness.Cloud model built an exchange model between quantities and qualities by integrating fuzziness and randomness.The present of both similar cloud and its measurement algorithm made cloud model had some theory value and real meanings.However,the characteristic of cloud made the algorithm with low precision and high consumption of calculation.Based on these,interval-based cloud similar comparability algorithm was brought forward in this paper,which improved original cloud similarity algorithm.The experimental results show that this algorithm optimizes the precision and consumption of calculation.
Volunteer Computing: Road to Efficient and Low-cost Scientific Research

resources that are loosely coupled, heterogeneous and geographically dispersed. In general a middleware determines how scalable and robust a grid can be. Volunteer computing is the act of using the unused computing resources from household computers as a part of the grid. Volunteer computing significantly helps several real time projects related to Climate study, Artificial Intelligence, Cryptography, space science, Chemistry and Biology. Volunteer computing is perceived by many research organizations that have less funding to buy computing resources. Volunteer computing demands a robust middleware that could provide a scalable communication framework and security. One of the most popular middleware for volunteer computing is BOINC (Berkeley Open Infrastructure for Network Computing). There are two major challenges in designing a robust volunteer computing architecture; One, the challenge of enhancing the communication framework and two, the challenge of saving the grid from attackers. This paper proposes efficient communication framework that will dynamically form smaller clusters of closely located computing nodes. In addition, the proposed communication framework is application specific; that is the communication framework switches its clustering algorithm specifically with respect to different applications. This paper aims at enhancing a commercially popular volunteer computing framework to eventually outstrip propriety grid computing frameworks.
The echiuran fauna of southern Africa (Class: Echiura, Phylum: Annelida)

This paper is a comprehensive report on the genera and species of Echiura previously recorded from southern Africa south of 23°30′ S. The echiuran fauna of this region currently comprises five genera and 22 species belonging to the single family Echiuridae. Three new species and six new records have been reported from the southern African region. The species of echiurans currently known from southern Africa have been reported from the east and south coasts and a very small part of the west coast extending northwards from Cape Town to Langebaan Lagoon. No records are as yet available from the coast of Namibia. Listriolobus capensis appears to be an endemic species, because it has not been recorded beyond the limits of southern Africa. Four species require additional investigation owing to their cosmopolitan status. A checklist of all the genera and species of echiurans recorded from southern Africa and a map showing their distribution along the coastline are given. A key for the identification of all the genera and species is provided. The museum accession numbers of all the species recorded from southern Africa are given.
The SUMO protease SENP3 regulates mitochondrial autophagy mediated by Fis1

Mitochondria are unavoidably subject to organellar stress resulting from exposure to a range of reactive molecular species. Consequently, cells operate a poorly understood quality control programme of mitophagy to facilitate elimination of dysfunctional mitochondria. Here we use a model stressor, deferiprone (DFP), to investigate the molecular basis for stress-induced mitophagy. We show that mitochondrial fission 1 protein (Fis1) is required for DFP-induced mitophagy and that Fis1 is SUMOylated at K149, an amino acid residue critical for Fis1 mitochondrial localization. We find that DFP treatment leads to the stabilisation of the SUMO protease SENP3, which is mediated by downregulation of the E3 ubiquitin (Ub) ligase CHIP. SENP3 is responsible for Fis1 deSUMOylation and depletion of SENP3 abolishes DFP-induced mitochondrial mitophagy. Furthermore, preventing Fis1 SUMOylation by conservative K149R mutation enhances Fis1 mitochondrial localization. Critically, expressing a Fis1 K149R mutant restores DFP-induced mitophagy in SENP3 depleted cells. Thus, we propose a model in which SENP3-mediated deSUMOylation facilitates Fis1 mitochondrial localization to underpin stress-induced mitophagy.
Personal recommendation algorithm in multidimensional and weighted social network

Personal recommendation is a crucial implementation to solve the problem of information overloading on the Internet.On the basis of researching personal recommendation skills and corresponding technologies,an application-driven personal recommendation algorithm in multidimensional and weighted social network was proposed.First,this algorithm built multidimensional and weighted social network between users,then applied the complex network clustering method—CPM(Clique Percolation Method) to find neighbor users,finally made recommendation on the grounds of the similarity between users.The experimental results show that the recommendation system of multidimensional network applying this algorithm can achieve higher recall and precision compared to content-based and collaborative filtering recommendation systems,and the quality of personal recommendation has been improved to some extent.
Cathelicidins In Humans And Animals

Abstract Cathelicidins are Important immunological peptides – HDPs (Host Defense Peptides) with high biological activity in mammals, including human and vertebrate animals. These evolutionary ancient molecules in these organisms are natural elements of antimicrobial, antiviral, antifungal and antiparasitic immunity against which germs and parasites have not developed immunity, which makes them alternatives to antibiotics. Catelicidins in human and vertebrates affect the germs and parasites directly and indirectly by activating the immune system. 1.What are immune peptides. 2. Cathelicidins. 2.1. Catelicidins in humans. 2.2. Cathelicidins in animals. 3. Summary
A Structured Virtual Space to Support Articulating and Sharing Rationales in Virtual Group Activities

Prior studies have shown that articulating and sharing group members’ rationales is beneficial in group activities. Yet there is limited understanding about design for sharing and organizing the rationales in virtual group activities. Addressing this research gap, this ongoing study explores design guidelines of a shared rationale space in a virtual group workspace. The user interface design of a work-in-progress rationale sharing groupware is presented. Résumé : Des études antérieures ont démontré que l’articulation et le partage du raisonnement des membres d’un groupe sont bénéfiques aux activités du groupe. Pourtant, on comprend mal comment concevoir le design d’un espace de partage et d’organisation du raisonnement lors d’activités de groupe virtuelles. Cette étude en cours cherche à combler cette lacune en explorant les normes de design d’un espace de partage du raisonnement d’un groupe de travail virtuel. Sera présenté le design d’une ébauche d’interface graphique d’un espace de partage du raisonnement.
Exploiting the Interconnected Lexicon: Bootstrapping English Language Learning in Young Spanish Speakers

This article reviews commonly accepted pedagogical practices for educating school-age English language learners, especially those whose first language is Spanish, and challenges these practices on the basis of results from psycholinguistics research that cast doubt on the assumptions underlying them. Policymakers and educators have different ideas about the best methods to teach these students; to a large extent, opinions from both sides are swayed by cultural beliefs, including the idea that children benefit more from language learning when they do not use their languages together in the same context (e.g., in a classroom setting; Petitto et al., 2001; Grosjean, 2006), or that they are delayed when they learn 2 languages simultaneously (Chiocca, 1998; Watson, 1996). But this assumption is undermined by experimental findings showing that second-language learners actually benefit when they use their first language to bootstrap learning of their target language (August, Carlo, Dressler, & Snow, 2005; Dressler, Carlo, Snow, August, & White, 2011; Proctor, August, Carlo, & Snow, 2006). Moreover, recent studies show that mixed-language settings, as compared to single-language settings, do not negatively impact learning outcomes in various academic subjects (Antón, Thierry, & Duñabeitia, 2015; Antón, Thierry, Goborov, Anasagasti, & Duñabeitia, 2016). We discuss evidence that bilinguals’ 2 language systems are frequently coactive via shared representations, and how such interconnectedness can bootstrap language learning without poorly affecting scholastic achievement. In addition, we propose research-based alternatives to common pedagogical practices that would exploit similarities between vocabulary in the first and second language.
Semantic Prioritization of Novel Causative Genomic Variants in Mendelian and Oligogenic Diseases

Semantic Prioritization of Novel Causative Genomic Variants in Mendelian and Oligogenic Diseases Imane Boudellioua Recent advances in Next Generation Sequencing (NGS) technologies have facilitated the generation of massive amounts of genomic data which in turn is bringing the promise that personalized medicine will soon become widely available. As a result, there is an increasing pressure to develop computational tools to analyze and interpret genomic data. In this dissertation, we present a systematic approach for interrogating patients’ genomes to identify candidate causal genomic variants of Mendelian and oligogenic diseases. To achieve that, we leverage the use of biomedical data available from extensive biological experiments along with machine learning techniques to build predictive models that rival the currently adopted approaches in the field. We integrate a collection of features representing molecular information about the genomic variants and information derived from biological networks. Furthermore, we incorporate genotype-phenotype relations by exploiting semantic technologies and automated reasoning inferred throughout a cross-species phenotypic ontology network obtained from human, mouse, and zebra fish studies. In our first developed method, named PhenomeNet Variant Predictor (PVP), we perform an extensive evaluation of a large set of synthetic exomes and genomes of diverse Mendelian diseases and phenotypes. Moreover, we evaluate PVP on a set of real patients’ exomes suffering from congenital hypothyroidism. We show that PVP successfully outperforms state-of-the-art methods, and provides a promising tool for accurate variant prioritization for Mendelian diseases. Next, we update the PVP method using a deep neural network architecture 5 as a backbone for learning and illustrate the enhanced performance of the new method, DeepPVP on synthetic exomes and genomes. Furthermore, we propose OligoPVP, an extension of DeepPVP that prioritizes candidate oligogenic combinations in personal exomes and genomes by integrating knowledge from protein-protein interaction networks and we evaluate the performance of OligoPVP on synthetic genomes created by known disease-causing digenic combinations. Finally, we discuss some limitations and future steps for extending the applicability of our proposed methods to identify the genetic underpinning for Mendelian and oligogenic diseases.
Machine learning para la selección de genes implicados en el desarrollo de Arabidopsis thaliana utilizando datos de expresión génica

in English, 250 words or less): Transcriptional programs are important in the development of the structures throughout the life cycle of plants. DNA microarray technology has provided a useful tool to discover relevant genes in the development of the reference plant Arabidopsis thaliana. However, previous studies use a reduced number samples to discover marker genes based on its specific expression along the tissues. In this work, a machine learning approach is presented to select relevant genes in the development of A. Thaliana. A database was built with more than 500 expression profiles corresponding to seeds, seedlings, roots, leaves and flowers. Gene selection was carried out with three different ML methods: FP-RF, RF-RFE, SVM-RFE. Furthermore, an autoencoder architecture was evaluated for dimensionality reduction of the data. The genes selected by ML techniques yield high classification performance in SVM, RF and ANN algorithms. Moreover, these genes are biologically relevant to plant development proccess. This work provides a new approach to study plant development from gene expression data.
Preweaning nutritional effects of supplements on performance of suckling beef calves grazing tropical pastures

vi RESUMO . viii GENERAL INTRODUCTION . 1 REFERENCES . 2 CHAPTER 1. Performance and metabolic responses of nursing beef calves fed supplements with increasing levels of rumen undegradable protein . 3 CHAPTER 2. A meta-analysis of the effects of creep feeding supplementation on performance and nutritional characteristics of beef calves grazing on tropical pastures.28
Computational studies of Glucocerebrosidase in complex with its facilitator protein Saposin-C

Gaucher’s Disease (GD) is a rare recessive disorder produced by the dysfunction of the lysosomal enzyme Glucocerebrosidase (GCase). GCase catalyses the cleavage of the glycolipid Glucosylceramide. The lack of functional GCase leads to the accumulation of its lipid substrate in lysosomes causing GD. GD presents a great phenotypic variation, symptoms ranging from asymptomatic adults to early childhood death due to neurological damage. More than 250 mutations in the protein GCase have been discovered that result in GD. Being able to link structural modifications of each mutation to the phenotypic variation of GD would enhance the understanding of the disease. The aim of this work is to understand the structural dynamics of wild type and mutant GCase. A model of the complex of the enzyme GCase with its facilitator protein, Saposin-C (Sap-C) was generated using Protein-Protein docking (PPD). In this work, a knowledge-based docking protocol that considers experimental data of protein- protein binding has been carried out. Here, a reliable model of the enzyme GCase with its facilitator protein is presented and is consistent with the experimental data. To understand the structural mechanism of function of the enzyme GCase, it was imperative to study its structural dynamics and conformational changes influenced by its interaction with other components including lipid bilayer, facilitator protein or substrate. Coarse-Grained MD (CG-MD) was employed to study lipid self-assembly and membrane insertion of the complex. Classical Atomistic MD (AT-MD) was used to study the dynamics of the interactions between different components of the simulation. Furthermore, the results of ten different AT-MD simulations sampling 9 s have been analysed. An activation method of GCase by Sap-C has been proposed, the change in conformation of GCase when its facilitator protein is present has been highlighted, through the stabilization of the loops at the entrance of the binding site. The differences in protein-protein binding when GCase is mutated have also been emphasised. Finally, Anharmonic Conformational Analysis and Markov State Models have been used to build a kinetic model of the system. This model supports our activation mechanism hyphothesis.