Using a Comprehensive Model to Test and Predict the Factors of Online Learning Effectiveness

As online learning is an important part of higher education, the effectiveness of online learning has been tested with different methods. Although the literature regarding online learning effectiveness has been related to various factors, a more comprehensive review of the factors may result in broader understanding of online learning effectiveness. Therefore the purpose of this study was to investigate the relationship among online learning effectiveness, interactivity, collaboration, communication media, and group trust. A student survey based on online learning effectiveness, interactivity, collaboration, communication media, group trust, and demographic information was used in this study. All these variables were used as predictor variables. A total of 401 responses were received during summer 2013 from a southeastern university. Different models were compared by using multiple linear regression. Results of the best predicting model showed interactivity was the strongest predictor of online learning effectiveness, followed by previous online grades, age, employment status, number of online courses taken, and ethnicity. These predictors explained 38% of the variances in online learning effectiveness. Findings of this study provide valuable information for online instructors and university administrators

Identification of the role of immune-related genes in the diagnosis of bipolar disorder with metabolic syndrome through machine learning and comprehensive bioinformatics analysis

BackgroundBipolar disorder and metabolic syndrome are both associated with the expression of immune disorders. The current study aims to find the effective diagnostic candidate genes for bipolar affective disorder with metabolic syndrome.MethodsA validation data set of bipolar disorder and metabolic syndrome was provided by the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were found utilizing the Limma package, followed by weighted gene co-expression network analysis (WGCNA). Further analyses were performed to identify the key immune-related center genes through function enrichment analysis, followed by machine learning-based techniques for the construction of protein–protein interaction (PPI) network and identification of the Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest (RF). The receiver operating characteristic (ROC) curve was plotted to diagnose bipolar affective disorder with metabolic syndrome. To investigate the immune cell imbalance in bipolar disorder, the infiltration of the immune cells was developed.ResultsThere were 2,289 DEGs in bipolar disorder, and 691 module genes in metabolic syndrome were identified. The DEGs of bipolar disorder and metabolic syndrome module genes crossed into 129 genes, so a total of 5 candidate genes were finally selected through machine learning. The ROC curve results-based assessment of the diagnostic value was done. These results suggest that these candidate genes have high diagnostic value.ConclusionPotential candidate genes for bipolar disorder with metabolic syndrome were found in 5 candidate genes (AP1G2, C1orf54, DMAC2L, RABEPK and ZFAND5), all of which have diagnostic significance

GWAS and WGCNA uncover hub genes controlling salt tolerance in maize (Zea mays L.) seedlings

Salt stress influences maize growth and development. To decode the genetic basis and hub genes controlling salt tolerance is a meaningful exploration for cultivating salt-tolerant maize varieties. Herein, we used an association panel consisting of 305 lines to identify the genetic loci responsible for Na+- and K+-related traits in maize seedlings. Under the salt stress, seven significant single nucleotide polymorphisms were identified using a genome-wide association study, and 120 genes were obtained by scanning the linkage disequilibrium regions of these loci. According to the transcriptome data of the above 120 genes under salinity treatment, we conducted a weighted gene co-expression network analysis. Combined the gene annotations, two SNaC/SKC (shoot Na+ content/shoot K+ content)-associated genes GRMZM2G075104 and GRMZM2G333183 were finally identified as the hub genes involved in salt tolerance. Subsequently, these two genes were verified to affect salt tolerance of maize seedlings by candidate gene association analysis. Haplotypes TTGTCCG-CT and CTT were determined as favorable/salt-tolerance haplotypes for GRMZM2G075104 and GRMZM2G333183, respectively. These findings provide novel insights into genetic architectures underlying maize salt tolerance and contribute to the cultivation of salt-tolerant varieties in maize

Characterization and genomic analysis of chromate resistant and reducing Bacillus cereus strain SJ1

<p>Abstract</p> <p>Background</p> <p>Chromium is a toxic heavy metal, which primarily exists in two inorganic forms, Cr(VI) and Cr(III). Chromate [Cr(VI)] is carcinogenic, mutational, and teratogenic due to its strong oxidizing nature. Biotransformation of Cr(VI) to less-toxic Cr(III) by chromate-resistant and reducing bacteria has offered an ecological and economical option for chromate detoxification and bioremediation. However, knowledge of the genetic determinants for chromate resistance and reduction has been limited so far. Our main aim was to investigate chromate resistance and reduction by <it>Bacillus cereus </it>SJ1, and to further study the underlying mechanisms at the molecular level using the obtained genome sequence.</p> <p>Results</p> <p><it>Bacillus cereus </it>SJ1 isolated from chromium-contaminated wastewater of a metal electroplating factory displayed high Cr(VI) resistance with a minimal inhibitory concentration (MIC) of 30 mM when induced with Cr(VI). A complete bacterial reduction of 1 mM Cr(VI) was achieved within 57 h. By genome sequence analysis, a putative chromate transport operon, <it>chrIA</it>1, and two additional <it>chrA </it>genes encoding putative chromate transporters that likely confer chromate resistance were identified. Furthermore, we also found an azoreductase gene <it>azoR </it>and four nitroreductase genes <it>nitR </it>possibly involved in chromate reduction. Using reverse transcription PCR (RT-PCR) technology, it was shown that expression of adjacent genes <it>chrA</it>1 and <it>chrI </it>was induced in response to Cr(VI) but expression of the other two chromate transporter genes <it>chrA</it>2 and <it>chrA</it>3 was constitutive. In contrast, chromate reduction was constitutive in both phenotypic and gene expression analyses. The presence of a resolvase gene upstream of <it>chrIA</it>1, an arsenic resistance operon and a gene encoding Tn7-like transposition proteins ABBCCCD downstream of <it>chrIA</it>1 in <it>B. cereus </it>SJ1 implied the possibility of recent horizontal gene transfer.</p> <p>Conclusion</p> <p>Our results indicate that expression of the chromate transporter gene <it>chrA</it>1 was inducible by Cr(VI) and most likely regulated by the putative transcriptional regulator ChrI. The bacterial Cr(VI)-resistant level was also inducible. The presence of an adjacent arsenic resistance gene cluster nearby the <it>chrIA</it>1 suggested that strong selective pressure by chromium and arsenic could cause bacterial horizontal gene transfer. Such events may favor the survival and increase the resistance level of <it>B. cereus </it>SJ1.</p

Differences in interactions of aboveground and belowground herbivores on the invasive plant Alternanthera philoxeroides and native host A-sessilis

Plant invasions may result in novel plant-herbivore interactions. However, we know little about whether and how invasive plants can mediate native above- and belowground herbivore interactions. In this study, we conducted greenhouse experiments to examine the interaction between a native defoliating beetle, Cassida piperata, and a native root-knot nematode, Meloidogyne incognita, on the invasive alligator weed, Alternanthera philoxeroides. We also included their native host A. sessilis in the experiments to examine whether the patterns of above- and belowground herbivore interaction vary with host plants (invasive vs. native). We analyzed total carbon and nitrogen in leaves and roots attacked by M. incognita and C. piperata. M. incognita slightly negatively affected feeding by C. piperata on A. philoxeroides, and the leaf area damaged decreased as the number of M. incognita increased. M. incognita had a negative impact on total leaf nitrogen, but had no impact on total leaf carbon. M. incognita egg production on A. philoxeroides roots decreased as the amount of damage caused by C. piperata increased. Herbivory by C. piperata did not affect total root carbon or nitrogen. M. incognita and C. piperata did not affect each other on the native plant A. sessilis. These results suggest that invasive plants can mediate native above- and belowground herbivore interactions. The knowledge of how invasive plants affect those interactions is crucial for better understanding the impacts of biological invasions on native above- and belowground organisms

Advances of Non-Ionic Surfactant Vesicles (Niosomes) and Their Application in Drug Delivery

Non-Ionic surfactant based vesicles, also known as niosomes, have attracted much attention in pharmaceutical fields due to their excellent behavior in encapsulating both hydrophilic and hydrophobic agents. In recent years, it has been discovered that these vesicles can improve the bioavailability of drugs, and may function as a new strategy for delivering several typical of therapeutic agents, such as chemical drugs, protein drugs and gene materials with low toxicity and desired targeting efficiency. Compared with liposomes, niosomes are much more stable during the formulation process and storage. The required pharmacokinetic properties can be achieved by optimizing components or by surface modification. This novel delivery system is also easy to prepare and scale up with low production costs. In this paper, we summarize the structure, components, formulation methods, quality control of niosome and its applications in chemical drugs, protein drugs and gene delivery

Climate warming increases biological control agent impact on a non-target species

Climate change may shift interactions of invasive plants, herbivorous insects and native plants, potentially affecting biological control efficacy and non-target effects on native species. Here, we show how climate warming affects impacts of a multivoltine introduced biocontrol beetle on the non-target native plant Alternanthera sessilis in China. In field surveys across a latitudinal gradient covering their full distributions, we found beetle damage on A. sessilis increased with rising temperature and plant life history changed from perennial to annual. Experiments showed that elevated temperature changed plant life history and increased insect overwintering, damage and impacts on seedling recruitment. These results suggest that warming can shift phenologies, increase non-target effect magnitude and increase non-target effect occurrence by beetle range expansion to additional areas where A. sessilis occurs. This study highlights the importance of understanding how climate change affects species interactions for future biological control of invasive species and conservation of native species