Miracle-dz/UniFAR-FTUs huggingface dataset:
PKMYT1 is a computationally predicted target for kidney cancer

Protein Kinase Membrane Associated Tyrosine/Threonine 1 (PKMYT1) is an understudied member of the serine/threonine protein kinase family. PKMYT1 is listed as a dark kinase according to the Illuminating the Druggable Genome (IDG) target development level classification. Using a combination of bioinformatics tools that we developed, we predict that targeting PKMYT1 is potentially beneficial for treating kidney cancer.
Reliability and Reproducibility of T1-weighted images: comparing MPRAGE and Prospective Motion Correction with Volumetric Navigators

New large neuroimaging studies, such as the ABCD and HCP Development studies are adopting a new T1-weighted imaging sequence with volumetric navigators (vNav) in favor of the more traditional 3-Dimensional Magnetization-Prepared Rapid Gradient-Echo Imaging (MPRAGE) sequence. In this study, we used a dataset of children (ages 5-21, N=366) from the Healthy Brian Network Initiative and directly compared the MPRAGE and vNav sequences to determine if the morphometric measurements obtained from both protocols are equivalent. Reliability and reproducibility were assessed with a subset of subjects (N=61) that performed two MPRAGE and two vNav sequences within the same imaging session. With morphometric measurements such as volume and cortical thickness, Intraclass correlation coefficients (ICC) scores show that reliability is the highest within the vNav sequences and lowest within the MPRAGE sequences. ICC scores were also higher for the MPRAGE-vNav pair then the MPRAGE-MPRAGE pair, possibly due to the higher motion in one of the MPRAGE runs. Results also show that the vNav sequence is robust to a high head motion population, such as children. In conclusion, morphometric measurements obtained for the MPRAGE and vNav sequences can be directly compared.
Interplay of ERα binding and DNA methylation in the intron-2 determines the expression and estrogen regulation of cystatin A in breast cancer cells

Despite advances in early detection and treatment, invasion and metastasis of breast tumors remains a major hurdle. Cystatin A (CSTA, also called stefin A), an estrogen-regulated gene in breast cancer cells, is an inhibitor of cysteine cathepsins, and a purported tumor suppressor. Loss of CSTA expression in breast tumors evidently shifts the balance in favor of cysteine cathepsins, thereby promoting extracellular matrix remodeling, tumor invasion and metastasis. However, the underlying mechanism behind the loss of CSTA expression in breast tumors is not known. Here, we have analyzed CSTA expression, and methylation of upstream and intron-2 CpG sites within the CSTA locus in human breast cancer cell lines and breast tumors of the TCGA cohort. Results showed an inverse relationship between expression and methylation. Sequence analysis revealed a potential estrogen response element (ERE) in the intron-2. Analysis of ChIP-seq data (ERP000380) and our own ChIP experiments showed that 17β-estradiol (E2) enhanced ERα binding to this ERE in MCF-7 cells. This ERE was located amidst the differentially methylated intron-2 CpG sites, which provoked us to examine the possible conflict between estrogen-regulation of CSTA and DNA methylation in the intron-2. We analyzed the expression of CSTA and its regulation by estrogen in MDA-MB-231 and T47D cells subjected to global demethylation by 5-azacytidine (5-aza). 5-aza, not only enhanced CSTA expression in these cell lines but also restored estrogen-regulation of CSTA in these cells. Taken together, our results indicate that DNA methylation-dependent silencing could play a significant role in the loss of CSTA expression in breast tumors. The potential of DNA methylation as an indicator of CSTA expression or as a marker of tumor progression can be explored in future investigations. Furthermore, our results indicate the convergence of ERα-mediated estrogen regulation and DNA methylation in the intron-2, thereby offering a novel context to understand the role of estrogen-ERα signaling axis in breast tumor invasion and metastasis.
Leaf spot of Hydrangea macrophylla caused by Corynespora cassiicola in China

Abstract Hydrangea macrophylla, also known as big leaf hydrangea, is an economically valuable ornamental garden plant. From 2016 to 2018, a high incidence of leaf spot disease of hydrangea occurred in Hunan Province of China. Symptoms consisted of irregular to circular lesions, dark brown in color with gray-white centers and delimited by dark brown borders. The lesions further coalesced to form irregularly shaped necrotic areas and extended to the leaf apex resulting in leaf wilt. A fungus was consistently isolated from the symptomatic plants and identified as Corynespora cassiicola by morphological characters and phylogenetic analyses. Pathogenicity was confirmed by fulfilling Koch’s postulates. This is the first report of C. cassiicola causing leaf spot on H. macrophylla in China.
Influence of Genetic Interactions on Polygenic Prediction

Prediction of phenotypes from genotypes is an important objective to fulfill the promises of genomics, precision medicine and agriculture. Although it’s now possible to account for the majority of genetic variation through model fitting, prediction of phenotypes remains a challenge, especially across populations that have diverged in the past. In this study, we designed simulation experiments to specifically investigate the role of genetic interactions in failure of polygenic prediction. We found that non-additive genetic interactions can significantly reduce the accuracy of polygenic prediction. Our study demonstrated the importance of considering genetic interactions in genetic prediction.
07. Female-biased sexual size dimorphism is driven by phenotypic selection on females in the Omei treefrog

Sexual size dimorphism (SSD) is a widespread phenomenon commonly attributed to sex-specific patterns of selection on body size. Using data from Dengchigou population of the Omei treefrog (Rhacophorus omeimontis) in Fengtongzhai National Nature Reserve, southwestern China, we evaluated the hypothesis that direct phenotypic selection on both males and females can produce SSD. Female biased-SSD was generally driven by selection on females due to fecundity advantage of large body size rather than sexual selection favouring large male body size. Furthermore, differences in life-history traits (i.e. growth rate and/or time available for growth) between the sexes also resulted in female biased-SSD. Our findings suggest that the relationship between female size and fecundity supports the prediction that selection for fecundity drives female biased-SSD.
Molecular Characterization and Comparative Pathogenicity of Goose Parvovirus Isolated from Jilin Province, Northeast China

SUMMARY. Goose parvovirus (GPV) is a highly contagious disease caused by GPV in goslings and young Muscovy ducklings. In recent years, frequent GPV outbreaks have occurred in many regions of Jilin Province, China. In this study, to understand the immune-related characteristics of the currently prevailing GPV strains in some regions of Jilin Province, six GPV strains were isolated from six different regions of Jilin Province in 2016–2018. The results of phylogenetic analysis, clinical signs, and histopathologic analysis showed that four strains were virulent and two strains were attenuated. Specifically, we found that the two attenuated strains have the same amino acid mutation at the same position in the virus protein 3 (VP3) gene, and the virulent strains have more mutation sites than the attenuated strains. This finding suggests that changes in these sites may result in GPV replication or reduction in the immune response in goslings, thereby producing strong pathogenicity, and that attenuated strains are more conservative than virulent strains.
MetaPrism: A Toolkit for Joint Taxa/Gene Analysis of Metagenomic Sequencing Data

Background In microbiome research, metagenomic sequencing generates enormous amounts of data. These data are typically classified into taxa for taxonomy analysis, or into genes for functional analysis. However, a joint analysis where the reads are classified into taxa-specific genes is often overlooked. Result To enable the analysis of this biologically meaningful feature, we developed a novel bioinformatic toolkit, MetaPrism, which can analyze sequence reads for a set of joint taxa/gene analyses: 1) classify sequence reads and estimate the abundances for taxa-specific genes; 2) tabularize and visualize taxa-specific gene abundances; 3) compare the abundances between groups, and 4) build prediction models for clinical outcome. We illustrated these functions using a published microbiome metagenomics dataset from patients treated with immune checkpoint inhibitor therapy and showed the joint features can serve as potential biomarkers to predict therapeutic responses. Conclusions MetaPrism is a toolkit for joint taxa and gene analysis. It offers biological insights on the taxa-specific genes on top of the taxa-alone or gene-alone analysis. MetaPrism is open source software and freely available at https://github.com/jiwoongbio/MetaPrism. The example script to reproduce the manuscript is also provided in the above code repository.
Comparison of root-matching techniques for electromagnetic transient simulation

Electromagnetic transient simulation has become a very important tool in the design of electrical power systems. Dommel's trapezoidal integrator substitution, the standard method for electromagnetic transient simulations, often causes numerical oscillations due to truncation errors, particularly if some small time constants exist in the network. An alternative exponential form of the difference equation has been developed and demonstrated, using root-matching techniques. This exponential form of difference equation results in highly efficient and accurate time domain simulation with no tendency for numerical oscillation regardless of the time step used. In applying the root-matching techniques, an assumption is made as to the variation of the input between time steps. This paper looks at the performance of the various exponential forms of difference equation.
Markov Prediction based on Semi-supervised Kernel Fuzzy Clustering

This paper proposes an improved Markov prediction, according to the temperature control problem of hot blast stove alternate supply air in the operation of blast furnace operation, namely, implement clustering for waiting to be processed data, used kernel fuzzy c-means clustering based on the pairwise constraints. The supply air temperature of hot blast stove is seen as without aftereffect things in this method, introduce semi-supervised learning mechanism in traditional fuzzy clustering to deal with the basic data, and using the kernel effectiveness index improved the FCM algorithm. Experiments show that the improved clustering algorithm is superior to other algorithms in accuracy and performance, at the same time, the improved prediction model comparison with the traditional values of temperature prediction, which has obvious advantages in defined temperature range and the fit of the temperature value, the guiding significance was significantly enhanced in industrial field.
Occurrence and growth inhibitory activity of Striga hermonthica (delile) benth on Sorghum bicolor (L.) moench in Lafia, Nigeria

The incidence of Striga hermonthica was investigated on some Sorghum bicolor farms in Lafia, Nigeria. The quadrant sampling technique was used and a total of six plots of size 10m x 10m each were sampled randomly in three locations namely; Shabu, Shendam Road and Makurdi Road, encompassing Lafia North, East and Central respectively. Incidence parameters such as the number of Striga and Sorghum, the height of Striga, distance of Striga to infected Sorghum and height of Sorghum were documented. A total of 572 stands of Striga were counted in all sampled locations. Sorghum farms in Shabu had the highest mean population of Striga (261), followed by both Shendam and Makurdi Road with mean populations of 13 Striga each. Negative correlations were observed between height of Striga and height of infected Sorghum, as well as between number of Striga and number of Sorghum plants. Distance of Striga to infected Sorghum correlated positively with height of infected Sorghum. Positive correlation was also observed between number of Striga and height of infected Sorghum. Growth reduction and consequent loss of Sorghum yield due to activity of Striga require integrated management approaches for sustainable Sorghum production and yield improvement in the study area.
Reading in a foreign language: Strategic variation between readers of differing proficiency

For university language students who are required to deal with literary texts for linguistic or literary purposes, there is hardly any transitional stage between short adapted expository texts, read in the early stages of language learning, and complex literary texts, encountered at university in the literature class. Language readers must then make a substantial mental effort to understand texts intended for a native readership. In challenging reading mode, the quality of reading depends on the efficiency of problem-solving operations, including evaluative and executive strategies, put into place in order to attempt to fill in the comprehension gaps present in complex texts. Although reading strategies used by foreign language learners have been identified and categorised by research, the conditions of their use and their relationships are still unclear. Moreover, to my knowledge, no empirical investigation has focused specifically on comprehension monitoring in the context of foreign language literary texts. Literature instruction would benefit from such a study. Using verbal reports to elicit data, this study proposes to examine how proficient and less proficient university students of French, at intermediate level of instruction, implement problem-solving strategies when reading literary texts. Strategies such as guessing at words, consulting a dictionary, and translating mentally, are studied in relation to their contribution to the overall monitoring cycle. The results obtained indicate that proficient and less proficient readers tend to use the same strategies but with different purposes. The study demonstrates that the major difference between the two groups of respondents resides in ability some readers have to integrate meaning and construct text in a cohesive and synthetic fashion.
A data-driven approach to optimising the encoding for multi-shell diffusion MRI with application to neonatal imaging

Diffusion MRI has the potential to provide important information about the connectivity and microstructure of the human brain during normal and abnormal development, non-invasively and in vivo. Recent developments in MRI hardware and reconstruction methods now permit the acquisition of large amounts of data within relatively short scan times. This makes it possible to acquire more informative multi-shell data, with diffusion-sensitisation applied along many directions over multiple b-value shells. Such schemes are characterised by the number of shells acquired, and the specific b-value and number of directions sampled for each shell. However, there is currently no clear consensus as to how to optimise these parameters. In this work, we propose a means of optimising multi-shell acquisition schemes by estimating the information content of the diffusion MRI signal, and optimising the acquisition parameters for sensitivity to the observed effects, in a manner agnostic to any particular diffusion analysis method that might subsequently be applied to the data. This method was used to design the acquisition scheme for the neonatal diffusion MRI sequence used in the developing Human Connectome Project, which aims to acquire high quality data and make it freely available to the research community. The final protocol selected by the algorithm, and currently in use within the dHCP, consists of b = 0, 400, 1000, 2600 s/mm2 with 20, 64, 88 & 128 DW directions per shell respectively. Highlights A data driven method is presented to design multi-shell diffusion MRI acquisition schemes (b-values and no. directions). This method optimises the multi-shell scheme for maximum sensitivity to the information content in the signal. When applied in neonates, the data suggest that a b=0 + 3 shell strategy is appropriate
Space-variant optical character recognition

An active vision system with a multiresolution sensor has the advantages of a wide visual field, high central resolution and low data rate. The authors use a special space-variant sensor based on complex log mapping to do character recognition in real scenes. The authors describe experiments with feature designs based on several statistical OCR methods: characteristic loci, partition and projection. The authors also examine several rotation-invariant feature designs based on the partition and projection methods. After studying the problem of recognizing strings in real scenes. The authors derive a rule based approach to solve the attention problem in the context of pattern recognition. Finally the authors describe an active vision system which successfully recognizes characters on a license plate in a real scene. <<ETX>>
A New Fast and High Performance Intrusion Detection System

The cyber-attacks represent one of the most dangerous secret weapons. Intrusion detection system is an important tool to protect our systems and networks against the various forms of attacks. The purpose of this paper is to build a fast and high performance hybrid hierarchical intrusion detection system called NFPHIDS that possesses the following characteristics: have a short training time, detect the low frequent attacks, give a high detection rate for frequent attacks, and give a low false alarm rate. NFPHIDS contains two levels. The first one includes four fast classifiers Random Forest, Simple Cart, Best first decision tree, Naive Bayes used for their excellent performance on the detection of respectively Normal behavior and DOS, Probe, R2L, and U2R. Only five outputs of the first level are selected, and used as inputs of the second level that contains Naive Bayes as final classifier. The experimentation on KDD99 shows the high performance of our model compared to the results obtained by some wellknown classifiers.
AN EVALUATIVE CASE STUDY ON PROFESSIONAL COMPETENCY OF PRESERVICE INFORMATION TECHNOLOGY TEACHERS

The purpose of this study is to evaluate preservice Information Technology (IT) teachers’ professional competency in the teaching process. The study was designed on the basis of evaluative case study. The participants of the study consisted of seven preservice IT teachers attending the department of Computer Education and Instructional Technologies (CEIT) at the College of Education of the higher education institution in Turkey in the spring semester of the 2008-2009 academic year, one participant researcher and one mentor teacher. In the study, the qualitative research data collection methods such as small-group interviews, observations and field notes were used, while the evaluation forms of the participant researcher and mentor teacher, the reflections of mentor teachers, and the researcher's journals were used as supplementary data sources. Inductive data analysis methods were employed in this study. The findings of the study indicated that the preservice IT teachers were competent in the preparation of instructional materials, in the use of instructional materials and technological tools and in the implementation of assessment and evaluation activities. However, the preservice IT teachers had a low level of competency in the use of technological concepts and in the observation of students’ development. The findings of the study were discussed based on the handbook that was published by the MoNE. The research also has implications for future research, IT teachers and IT preservice teachers.
Analysis of DNA Polymorphisms in Arabic Camel (Camelus dromedarius) Using Random Amplified Polymorphic DNA Polymerase Chain Reaction Technique

Camel populations in Iraq are facing a severe decline which demands immediate actions to ensure its conservation. This study was carried out at molecular genetics laboratory, college of agriculture, university of Basrah. Twenty four blood samples were analyzed by random amplified polymorphic DNA (RAPD) to investigate genetic similarity and diversity among and within three Arabic camel flocks (Camelus dromedarius) represented in Basrah, Thy Qar and Muthanna provinces. Ten random primers were used to amplify DNA fragments in these three flocks. Among ten tested RAPD primers, 6 primers generated novel and polymorphic DNA fragments in all tested samples. A total of 381 bands were obtained, 168 of them were polymorphic. The number of polymorphic bands in each population was found to be different and was higher in the Muthanna than in Thy Qar and Basrah provinces (76, 50 and 42) bands, respectively. Number of polymorphic bands in Muthanna province population was approximately 1.5 times as diverse as that in Basrah and Thy Qar provinces populations. Comparison of banding patterns in Muthanna, Basrah and Thy Qar populations revealed substantial differences that the populations may have been subjected to a long period of geographical isolation from each other. Relationship was determined on the base of polymorphic products analysis and presented in the form of dendrogram (UPGMA percent method). There is a significant correlation between geographical distance and genetic distance between populations. RAPD analysis confirmed the presence of genetic variation within tested Arabic camel. The obtained data will help build conservation strategies to avoid the extinction of animals from their natural habitats in the future. RAPD technique makes it ideal for genetic mapping, plant and animal breeding programs and DNA fingerprinting, with particular utility in the field of population genetics. This study compared, for the first time, variation in DNA fingerprinting of Arabic camels in Iraq.