Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure and Functional Diversity of Surface Bacterioplankton Communities in an Overwintering Habitat for Large Yellow Croaker, Pseudosciaena crocea, of the Southern East China Sea

Given the biogeochemical functions of marine microbes, the structure and functional diversity of bacterioplankton communities could be regarded as bioindicators that reflect environmental quality. The habitat of the large yellow croaker (Pseudosciaena crocea) is suffering from widespread degradation, but the study of the croaker habitat is still insufficient. Here, we used 16S rRNA gene sequencing and functional prediction to investigate the surface bacterioplankton communities in an overwintering ground of P. crocea during the overwintering period (November 2018 to April 2019). Our results showed that the taxa and functions of the environmental bacterioplankton community exhibited obvious seasonality. Specifically, the bacterioplankton communities in autumn were characterized by animal parasites or symbionts, such as Acinetobacter baumannii and Moraxella, while organic substance–degrading bacteria, such as Rhodococcus, Stenotrophomonas, and Alcanivorax, dominated in spring. Moreover, phylogenetic-based mean nearest taxon distance (MNTD) analyses indicated that dispersal limitation was the most important process governing the spatiotemporal assembly of the bacterioplankton communities. The distance decay of similarity also suggested the impact of dispersal limitation on the generation of biogeographical patterns. Furthermore, variation partitioning analysis (VPA) and a partial Mantel test revealed that environmental filters, such as nutrients, temperature, and salinity, had relatively weak deterministic effects on the bacterioplankton community assembly. Overall, these findings provide a basis for understanding the theory of surface microbial community assembly in the overwintering habitat of the large yellow croaker.
The effect of enzymatic modification and genetic background on wheat gliadin immunological properties

Abstract The immune response to gliadins extracted from 35 wheat cultivars, strains and species was investigated. With the use of a non-competitive ELISA method, we sought to examine if immune reaction occurs between wheat proteins and sera from patients sensitive to gluten, as well as between wheat proteins and rabbit antibodies against pentapeptide QQQPP. Results showed considerable differences among cultivars. Breeding strains STH 183, STH 650, STH 2804, Triticum aethiopicum and Triticum durum showed the lowest immunoreactivity of the native samples. Seventeen of selected wheat flour samples were subjected to enzymatic modifications by subtilisin and transglutaminase. Samples modified by subtilisin exhibited the most extensive change in the level of immunoreactivity of gliadin proteins. The lowest immunoreactivity was reported for the breeding strains STH 1596, STH 2804 and cultivars Tonacja and Zyta. One wheat cultivar (Tonacja), known for its high native gliadin immunoreactivity, was shown to be very susceptible to enzymatic digestion, which resulted in a reduction of its initial immunoreactivity level to low values. Immunoreactivity analysis was also conducted on extracted gliadin fractions from winter wheat strain Ostka strzelecka. The highest level of immunoreactivity to both types of antibodies we used was indicated for ω5-gliadins. It was, however, abrogated in the aftermath of enzymatic modifications.
Seeding strategies for multi-objective test case selection: an application on simulation-based testing

The time it takes software systems to be tested is usually long. This is often caused by the time it takes the entire test suite to be executed. To optimize this, regression test selection approaches have allowed for improvements to the cost-effectiveness of verification and validation activities in the software industry. In this area, multi-objective algorithms have played a key role in selecting the appropriate subset of test cases from the entire test suite. In this paper, we propose a set of seeding strategies for the test case selection problem that generate the initial population of multi-objective algorithms. We integrated these seeding strategies with an NSGA-II algorithm for solving the test case selection problem in the context of simulation-based testing. We evaluated the strategies with six case studies and a total of 21 fitness combinations for each case study (i.e., a total of 126 problems). Our evaluation suggests that these strategies are indeed helpful for solving the multi-objective test case selection problem. In fact, two of the proposed seeding strategies outperformed the NSGA-II algorithm without seeding population with statistical significance for 92.8 and 96% of the problems.
Impact of Age on tDCS Effects on Pain Threshold and Working Memory: Results of a Proof of Concept Cross-Over Randomized Controlled Study

Background: Age is an important factor that impacts the variability of tDCS effects. Objective/Hypothesis: To compare effects of anodal (a)-tDCS over the left dorsolateral prefrontal cortex (DLPFC), and primary motor cortex (M1) in adolescents, adults, and elderly on heat pain threshold (HPT; primary outcome) and the working memory (WM; secondary outcome). We hypothesized that the effect of tDCS on HPT and WM performance would be the largest in adolescents because their pre-frontal cortex is more prone to neuroplasticity. Methods: We included 30 healthy women within the age ranges of 15–16 (adolescents, n = 10), 30–40 (adults, n = 10), and 60–70 (elderly, n = 10) years. In this crossover single-blinded study, participants received three interventions applied over the DLPF and M1. The active stimulation intensity was two mA for 30 min. From 20 min of stimulation onset, the tDCS session was coupled with an online n-back task. The a-tDCS and sham were applied in a random sequence, with a washout time of a minimum 7 days between each trial. HPT was evaluated before and after stimulation. The WM performance with an n-back task was assessed after the tDCS session. Results: A Generalized Estimating Equation (GEE) model revealed a significant effect of the a-tDCS over the left DLPFC to reduce the HPT in adolescents compared with sham. It increased the pain perception significantly [a large effect size (ES) of 1.09)]. In the adults, a-tDCS over M1 enhanced the HPT significantly (a large ES of 1.25) compared to sham. No significant effect for HPT was found in the elderly. Response time for hits was reduced for a-tDCS over the DLPFC in adolescents, as compared to the other two age groups. Conclusions: These findings suggest that a-tDCS modulates pain perception and WM differentially according to age and target area of stimulation. In adolescents, anodal stimulation over the DLPFC increased the pain perception, while in adults, the stimulation over the M1 increased the pain threshold. Thus, they elucidate the impact of tDCS for different age groups and can help to define what is the appropriate intervention according to age in further clinical trials. Clinical Trial Registration: www.ClinicalTrials. gov, Identifier: NCT04328545.
A comparative study of text entry performance of low-profile versus high-profile keyboards

Users' perceptions on what makes a good computer keyboard varies. Laptop computers are often equipped with low-profile keyboards for improved mobility, while desktop computers often are equipped with traditional high-profile keyboards with longer displacement ranges. This work set out to explore if the keyboard height profile influence text entry performance. A controlled experiment was set up with N = 15 participants. The results show that the low-profile keyboard yielded on average 12% faster text entry rates than the high-profile keyboards. No significant effects could be observed on error rates.
How does the strength of selection influence genetic correlations?

Genetic correlations between traits can strongly impact evolutionary responses to selection, and may thus impose constraints on adaptation. Theoretical and empirical work has made it clear that, without strong linkage, genetic correlations at evolutionary equilibrium result from an interplay of correlated pleiotropic effects of mutations, and correlational selection favoring combinations of trait values. However, it is not entirely clear how the strength of stabilizing selection influences this compromise between mutation and selection effects on genetic correlations. Here, we show that the answer to this question crucially depends on the intensity of genetic drift. In large, effectively infinite populations, genetic correlations are unaffected by the strength of selection, regardless of whether the genetic architecture involves common small-effect mutations (Gaussian regime), or rare large-effect mutations (House-of-Cards regime). In contrast in finite populations, the strength of selection does affect genetic correlations, by shifting the balance from drift-dominated to selection-dominated evolutionary dynamics. The transition between these domains depends on mutation parameters to some extent, but with a similar dependence of genetic correlation on the strength of selection. Our results are particularly relevant for understanding how senescence shapes patterns of genetic correlations across ages, and genetic constraints on adaptation during colonization of novel habitats.
Macroscale network feedback structure of transcriptome during cell fate transition

Organogenesis is a biological process of cell fate transition. Underlying this process are complex changes in the transcriptome. Although these changes have been described extensively in terms of individual genes or pathways, a mcroscale description of gene regulatory network dynamics is lacking. Leveraging time-series data from single-cell transcriptome profiling of developing mouse embryos, we present a novel analytic framework to aggregate dynamic gene expressions across the transcriptome into state changes in 14 core biological processes, and to construct an ordinary differential equation-based mathematical model of the macroscale network capturing its feedback structure. We determine the polarity and magnitude of direct pairwise causal relationships between biological processes and identify higher-order feedback interactions that dominate system behaviour. Despite heterogenous expressions at the gene level, we find that the transcriptome at the macroscale level has a feedback structure that is intrinsically stable and robust. We show the pivotal role of signaling in driving systemic changes and uncover the importance of homeostatic process and establishment of localization in regulating network dynamics. Localized regulatory structures represent domain-specific regulations that are essential to cell fate transition, especially lipid metabolic process. Altogether, this study not only provides a holistic picture of macroscale transcriptome dynamics during mouse organogenesis, but also offers insight into key aspects of information flow in the transcriptome that control cell fate transition.
The identification of corn leaf diseases based on transfer learning and data augmentation

Corn is one of the most important food crops in the world, but there are many kinds of corn diseases, and it is difficult to diagnose by planting personnel based on experience. However, the misdiagnosis reduces production efficiency. With the development of computer technology, the use of deep learning and image recognition technology for plant disease detection has become an important research direction. We propose a convolutional neural network based on data augmentation combined with transfer learning to identify corn leaf disease models. The algorithm first increases the data by means of data augmentation to improve the generalization and accuracy of the model, and builds a convolutional neural network model based on transfer learning. Then, it uses the model for training, accelerates the training process of the convolutional neural network, and uses test dataset feedback network training results. In this study, the corn leaf images in PlantVillage were used as the dataset of our experiment to classify the four categories which consists of Corn Gray leaf spot, Corn Common rust, Corn Northern Leaf Blight and healthy leaves. We first obtained our optimization model by fine-tuning the GoogLeNet pre-training network, adjusting parameters such as optimizer and learning rate. Then we trained the optimization model, like the original GoogLeNet network, ResNet18, Vgg16, and Vgg19 networks based on transfer learning and compare the results. The results show that by using our optimized model, the average recognition accuracy of corn disease which consists of corn common leaf rust, Corn Common rust, Corn Northern Leaf Blight and healthy leaves reached 97.6%, and the recognition accuracy of each category was greater than 95%. Compared with the original GoogLeNet model, the highest accuracy rate is improved by 5.9%. Also, the effect is better when compared with other networks based on transfer learning. Our model provides new ideas for the identification of diseases, insect pests of corn and other crops.
Modified Vaccinia Ankara Based SARS-CoV-2 Vaccine Expressing Full-Length Spike Induces Strong Neutralizing Antibody Response

There is a great need for the development of vaccines for preventing SARS-CoV-2 infection and mitigating the COVID-19 pandemic. Here, we developed two modified vaccinia Ankara (MVA) based vaccines which express either a membrane anchored full-length spike protein (MVA/S) stabilized in a prefusion state or the S1 region of the spike (MVA/S1) which forms trimers and is secreted. Both immunogens contained the receptor-binding domain (RBD) which is a known target of antibody-mediated neutralization. Following immunizations with MVA/S or MVA/S1, both spike protein recombinants induced strong IgG antibodies to purified full-length SARS-CoV-2 spike protein. The MVA/S induced a robust antibody response to purified RBD, S1 and S2 whereas MVA/S1 induced an antibody response to the S1 region outside of the RBD region. Both vaccines induced an antibody response in the lung and that was associated with induction of bronchus-associated lymphoid tissue. MVA/S but not MVA/S1 vaccinated mice generated robust neutralizing antibody responses against SARS-CoV-2 that strongly correlated with RBD antibody binding titers. Mechanistically, S1 binding to ACE-2 was strong but reduced following prolonged pre-incubation at room temperature suggesting confirmation changes in RBD with time. These results demonstrate MVA/S is a potential vaccine candidate against SARS-CoV-2 infection.
Collapse of South Africa's penguins in the early 21st century

The number of African penguins Spheniscus demersus breeding in South Africa collapsed from about 56 000 pairs in 2001 to some 21 000 pairs in 2009, a loss of 35 000 pairs (>60%) in eight years. This reduced the global population to 26 000 pairs, when including Namibian breeders, and led to classification of the species as Endangered. In South Africa, penguins breed in two regions, the Western Cape and Algoa Bay (Eastern Cape), their breeding localities in these regions being separated by c. 600 km. Their main food is anchovy Engraulis encrasicolus and sardine Sardinops sagax, which are also the target of purse-seine fisheries. In Algoa Bay, numbers of African penguins halved from 21 000 pairs in 2001 to 10 000 pairs in 2003. In the Western Cape, numbers decreased from a mean of 35 000 pairs in 2001–2005 to 11 000 pairs in 2009. At Dassen Island, the annual survival rate of adult penguins decreased from 0.70 in 2002/2003 to 0.46 in 2006/2007; at Robben Island it decreased from 0.77 to 0.55 in the same period. In both the Western and Eastern Cape provinces, long-term trends in numbers of penguins breeding were significantly related to the combined biomass of anchovy and sardine off South Africa. However, recent decreases in the Western Cape were greater than expected given a continuing high abundance of anchovy. In this province, there was a south-east displacement of prey around 2000, which led to a mismatch in the distributions of prey and the western breeding localities of penguins.
Identification of protein-protected mRNA fragments and structured excised intron RNAs in human plasma by TGIRT-seq peak calling

Human plasma contains >40,000 different coding and non-coding RNAs that are potential biomarkers for human diseases. Here, we used thermostable group II intron reverse transcriptase sequencing (TGIRT-seq) combined with peak calling to simultaneously profile all RNA biotypes in apheresis-prepared human plasma pooled from healthy individuals. Extending previous TGIRT-seq analysis, we found that human plasma contains largely fragmented mRNAs from >19,000 protein-coding genes, abundant full-length, mature tRNAs and other structured small non-coding RNAs, and less abundant tRNA fragments and mature and pre-miRNAs. Many of the mRNA fragments identified by peak calling correspond to annotated protein-binding sites and/or have stable predicted secondary structures that could afford protection from plasma nucleases. Peak calling also identified novel repeat RNAs, miRNA-sized RNAs, and putatively structured intron RNAs of potential biological, evolutionary, and biomarker significance, including a family of full-length excised introns RNAs, subsets of which correspond to mirtron pre-miRNAs or agotrons.
Family-wide evaluation of RALF peptides in Arabidopsis thaliana

Plant peptide hormones are important players controlling various aspects of plants’ lives. RAPID ALKALINIZATION FACTOR (RALF) peptides have recently emerged as important players in multiple physiological processes. Numerous studies on RALF peptides focused on broad phylogenetic analysis including multiple species. Thus, progress has been made in understanding the evolutionary processes that shaped this family. Nevertheless, to date, there is no comprehensive, family-wide functional study on RALF peptides. Here, we analysed the phylogeny and function of the proposed multigenic RALF peptide family in the model plant Arabidopsis thaliana, ecotype Col-0. Our phylogenetic analysis reveals that two of the previously proposed RALF peptides are not genuine RALF peptides, which leads us to propose a new consensus AtRALF peptide family annotation. Moreover, we show that the majority of AtRALF peptides are able to induce seedling or root growth inhibition in A. thaliana seedlings when applied exogenously as synthetic peptides. Additionally, we show that most of these responses are dependent on the Catharanthus roseus RLK1-LIKE receptor kinase FERONIA, suggesting a pivotal role in the perception of multiple RALF peptides. One sentence summary The majority of A. thaliana RALF peptides inhibit growth in a FERONIA-dependent manner
Efficient Cas9 multiplex editing using unspaced sgRNA arrays engineering in a Potato virus X vector

Systems based on the clustered, regularly interspaced, short palindromic repeat (CRISPR) and CRISPR associated proteins (Cas) have revolutionized genome editing in many organisms, including plants. Most CRISPR-Cas strategies in plants rely on genetic transformation using Agrobacterium tumefaciens to supply the gene editing reagents, such as the Cas nucleases or the guide RNA (gRNA). While the Cas nucleases are constant elements in editing approaches, gRNAs are target-specific and a screening process is usually required to identify those most effective. Plant virus-derived vectors are an alternative for the fast and efficient delivery of gRNAs into adult plants, due to the virus capacity for genome amplification and systemic movement, a strategy known as virus-induced genome editing (VIGE). In this work, we engineered Potato virus X (PVX) to build a vector able to easily express one or more gRNAs in adult solanaceous plants. Using the PVX-based vector, Nicotiana benthamiana genes were efficiently targeted, producing nearly 80% indels in a transformed line that constitutively expressed Streptococcus pyogenes Cas9. Interestingly, results showed that the PVX vector allows expression of arrays of unspaced gRNAs achieving highly efficient multiplex editing in a few days in adult plant tissues. We also demonstrate that genome modifications are inherited in plants regenerated from infected tissues. In sum, the new PVX VIGE vector allows easy, fast and efficient expression of gRNAs arrays for multiplex CRISPR-Cas genome editing and will be a useful tool for functional gene analysis and precision breeding across diverse plant species, particularly in important crops of the family Solanaceae.
A novel ensemble and composite approach for classifying proteins based on Chou’s pseudo amino acid composition

For the fact that the location of proteins gave some details about the function of a protein whose location was uncertain, protein classification was regarded as a very important task in the field of biological data mining. However, the success of a human genome project led to a protein sequence explosion. There is a great need to develop a computational method for fast and reliable prediction of the locations of proteins according to their primary sequences. In this paper, we used the composite classifier system that was formed by a set of k-nearest neighbor (K-NN) classifiers, each of which was defined in a different pseudo amino composition vector. In the pseudo amino composition vector space, protein can be presented by Pseudo amino acid composition. The location of a queried protein is determined by the outcome of choice made among these constituent individual classifiers. It is shown through the outcome that the classifier outperformed the single classifier widely used in biological literature. So the composite classifier can be employed as a robust method to predict protein location in the field of biological data mining. Key words: Composite classifier system, biological data mining, atomic classifiers, pseudo amino acid composition.
CRISPR-induced indels and base editing using the Staphylococcus aureus Cas9 in potato

Genome editing is now widely used in plant science for both fundamental research and molecular crop breeding. The clustered regularly interspaced short palindromic repeats (CRISPR) technology, through its precision, high efficiency and versatility, allows to edit many sites in plant genomes. This system has been highly successful to produce of knock-out mutants through the introduction of frameshift mutations due to error-prone repair pathways. Nevertheless, recent new CRISPR-based technologies such as base editing and prime editing can generate precise and on request nucleotide conversion, allowing to fine-tune protein function and generate gain-of-function mutants. However, genome editing through CRISPR systems still have some drawbacks and limitations, such as the PAM restriction and the need for more diversity in CRISPR tools to simultaneously mediate different catalytic activities. In this study, we successfully used the CRISPR-Cas9 system from Staphylococcus aureus (SaCas9) for the introduction of frameshift mutations in the tetraploid genome of the cultivated potato (Solanum tuberosum). We also developed a S. aureus-cytosine base editor that mediate nucleotide conversions, allowing to precisely modify specific residues or regulatory elements in potato. Our proof-of-concept results in potato expand the plant dicot CRISPR toolbox for biotechnology and precision breeding applications.