Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization

Thermodynamic processes with free energy parameters are often used in algorithms that solve the free energy minimization problem to predict secondary structures of single RNA sequences. While results from these algorithms are promising, an observation is that single sequence-based methods have moderate accuracy and more information is needed to improve on RNA secondary structure prediction, such as covariance scores obtained from multiple sequence alignments. We present in this paper a new approach to predicting the consensus secondary structure of a set of aligned RNA sequences via pseudo-energy minimization. Our tool, called RSpredict, takes into account sequence covariation and employs effective heuristics for accuracy improvement. RSpredict accepts, as input data, a multiple sequence alignment in FASTA or ClustalW format and outputs the consensus secondary structure of the input sequences in both the Vienna style Dot Bracket format and the Connectivity Table format. Our method was compared with some widely used tools including KNetFold, Pfold and RNAalifold. A comprehensive test on different datasets including Rfam sequence alignments and a multiple sequence alignment obtained from our study on the Drosophila X chromosome reveals that RSpredict is competitive with the existing tools on the tested datasets. RSpredict is freely available online as a web server and also as a jar file for download at http://datalab.njit.edu/biology/RSpredict

Relationship between sleep and obesity among U.S. and South Korean college students

Background Little is known about the relationship between sleep and obesity in young adults, particularly college students. This study examined the relationship between sleep (i.e., sleep duration and quality) and obesity in a large and diverse binational sample of college students. Methods Analyses were based on a 40-item paper survey from 2016/2017 to 2017/2018 academic years, with a 72% response rate. The samples were 1578 college students aged 18–25 years from five universities (two in the U.S. and three in South Korea). Weight and height were measured objectively; other measures (e.g., health behaviors) were self-reported. Multinomial logistic regression was used to assess the association between sleep duration and independent variables (race/nationality, gender, and BMI). Poisson regression was used to examine the relationship between sleep quality and independent variables. Results Overall, blacks had a higher adjusted odds ratio (AOR) of short sleep (\u3c 7 h/night) than whites (AOR = 1.74, P \u3c .01); overweight participants had a higher AOR of short sleep than normal weight participants (AOR = 1.52, P \u3c .01); and obese participants had a higher AORs of both short and long sleep (\u3e 9 h/night) (AOR = 1.67, P \u3c .01; AOR = 1.79, P \u3c .05, respectively). Among men, being black, overweight, and obesity were associated with short sleep (P \u3c .05), whereas only obesity was related to short sleep among women (P \u3c .05). In analyses stratified by race and nationality, overweight and obesity were related to short sleep among blacks only (P \u3c .05). Overall, sleep quality (getting enough sleep to feel rested in the morning in the past 7 days) was worse in blacks and South Koreans than whites (P \u3c .05), worse in women than men (P \u3c .05), and worse in participants with obesity than normal weight participants (P \u3c .05). Conclusions Obesity was associated with both short (\u3c 7 h/night) and long sleep duration (\u3e 9 h/night) and poor sleep quality among all participants. In comparison with whites, blacks were more like to have short sleep, and blacks and South Koreans had worse sleep quality. Further investigations using a larger sample of college students in multiple countries may be helpful to identify target populations who are at a greater risk of obesity and sleep problems

Relationship between sleep and obesity among U.S. and South Korean college students

Background Little is known about the relationship between sleep and obesity in young adults, particularly college students. This study examined the relationship between sleep (i.e., sleep duration and quality) and obesity in a large and diverse binational sample of college students. Methods Analyses were based on a 40-item paper survey from 2016/2017 to 2017/2018 academic years, with a 72% response rate. The samples were 1578 college students aged 18–25 years from five universities (two in the U.S. and three in South Korea). Weight and height were measured objectively; other measures (e.g., health behaviors) were self-reported. Multinomial logistic regression was used to assess the association between sleep duration and independent variables (race/nationality, gender, and BMI). Poisson regression was used to examine the relationship between sleep quality and independent variables. Results Overall, blacks had a higher adjusted odds ratio (AOR) of short sleep ( 9 h/night) (AOR = 1.67, P < .01; AOR = 1.79, P < .05, respectively). Among men, being black, overweight, and obesity were associated with short sleep (P < .05), whereas only obesity was related to short sleep among women (P < .05). In analyses stratified by race and nationality, overweight and obesity were related to short sleep among blacks only (P < .05). Overall, sleep quality (getting enough sleep to feel rested in the morning in the past 7 days) was worse in blacks and South Koreans than whites (P < .05), worse in women than men (P < .05), and worse in participants with obesity than normal weight participants (P < .05). Conclusions Obesity was associated with both short ( 9 h/night) and poor sleep quality among all participants. In comparison with whites, blacks were more like to have short sleep, and blacks and South Koreans had worse sleep quality. Further investigations using a larger sample of college students in multiple countries may be helpful to identify target populations who are at a greater risk of obesity and sleep problems

Effect of RF Magnetron Sputtered Nickel Oxide Thin Films as an Anode Buffer Layer in a P 3

Bulk heterojunction solar cells were investigated using poly(3-hexylthiophene) (P₃HT):[6,6]-phenyl-C₆₁ butyric acid methyl ester (PCBM) with a nickel oxide (NiO) anode buffer layer between the photoactive layer and an indium tin oxide (ITO) anode layer. The NiO anode buffer layer was deposited using radio frequency magnetron sputtering on an ITO electrode layer for effective hole transport and electron blocking. The NiO film is a p-type semiconductor with resistivity of 0.35 Ω cm. The power conversion efficiency was improved substantially by the NiO anode buffer layer compared to a solar cell with an anode buffer layer made from poly(3,4-ethylenedioxythiophene) (PEDOT):poly(styrene sulfonate) (PSS). The solar cell with a 10 nm thick NiO anode buffer layer had a power conversion efficiency of 4.71%. These results are explained by the improved charge transport across the interface between the active layer and ITO electrode

Effect of RF Magnetron Sputtered Nickel Oxide Thin Films as an Anode Buffer Layer in a P₃HT:PCBM Bulk Hetero-Junction Solar Cells

Bulk heterojunction solar cells were investigated using poly(3-hexylthiophene) (P₃HT):[6,6]-phenyl-C₆₁ butyric acid methyl ester (PCBM) with a nickel oxide (NiO) anode buffer layer between the photoactive layer and an indium tin oxide (ITO) anode layer. The NiO anode buffer layer was deposited using radio frequency magnetron sputtering on an ITO electrode layer for effective hole transport and electron blocking. The NiO film is a p-type semiconductor with resistivity of 0.35 Ω cm. The power conversion efficiency was improved substantially by the NiO anode buffer layer compared to a solar cell with an anode buffer layer made from poly(3,4-ethylenedioxythiophene) (PEDOT):poly(styrene sulfonate) (PSS). The solar cell with a 10 nm thick NiO anode buffer layer had a power conversion efficiency of 4.71%. These results are explained by the improved charge transport across the interface between the active layer and ITO electrode

Local spreading of MSL complexes from roX genes on the Drosophila X chromosome

MSL proteins and noncoding roX RNAs form complexes to up-regulate hundreds of genes on the Drosophila male X chromosome, and make X-linked gene expression equal in males and females. Altering the ratio of MSL proteins to roX RNA dramatically changes X-chromosome morphology. In protein excess, the MSL complex concentrates near sites of roX transcription and is depleted elsewhere. These results support a model for distribution of MSL complexes, in which local spreading in cis from roX genes is balanced with diffusion of soluble complexes in trans. When overexpressed, MSL proteins can recognize the X chromosome, modify histones, and partially restore male viability even in the absence of roX RNAs. Thus, the protein components can carry out all essential functions of dosage compensation, but roX RNAs facilitate the correct targeting of MSL complexes, in part by nucleation of spreading from their sites of synthesis

Regulation of Histone H4 Lys16 Acetylation by Predicted Alternative Secondary Structures in roX Noncoding RNAs▿ †

Despite differences in size and sequence, the two noncoding roX1 and roX2 RNAs are functionally redundant for dosage compensation of the Drosophila melanogaster male X chromosome. Consistent with functional conservation, we found that roX RNAs of distant Drosophila species could complement D. melanogaster roX mutants despite low homology. Deletion of a conserved predicted stem-loop structure in roX2, containing a short GUb (GUUNUACG box) in its 3′ stem, resulted in a defect in histone H4K16 acetylation on the X chromosome in spite of apparently normal localization of the MSL complex. Two copies of the GUb sequence, newly termed the “roX box,” were functionally redundant in roX2, as mutants in a single roX box had no phenotype, but double mutants showed reduced H4K16 acetylation. Interestingly, mutation of two of three roX boxes in the 3′ end of roX1 RNA also reduced H4K16 acetylation. Finally, fusion of roX1 sequences containing a roX box restored function to a roX2 deletion RNA lacking its cognate roX box. These results support a model in which the functional redundancy between roX1 and roX2 RNAs is based, at least in part, on short GUUNUACG sequences that regulate the activity of the MSL complex

Evaluation of Hyperparameter Combinations of the U-Net Model for Land Cover Classification

The aim of this study was to select the optimal deep learning model for land cover classification through hyperparameter adjustment. A U-Net model with encoder and decoder structures was used as the deep learning model, and RapidEye satellite images and a sub-divided land cover map provided by the Ministry of Environment were used as the training dataset and label images, respectively. According to different combinations of hyperparameters, including the size of the input image, the configuration of convolutional layers, the kernel size, and the number of pooling and up-convolutional layers, 90 deep learning models were built, and the model performance was evaluated through the training accuracy and loss, as well as the validation accuracy and loss values. The evaluation results showed that the accuracy was higher with a smaller image size and a smaller kernel size, and was more dependent on the convolutional layer configuration and number of layers than the kernel size. The loss tended to be lower as the convolutional layer composition and number of layers increased, regardless of the image size or kernel size. The deep learning model with the best performance recorded a validation loss of 0.11 with an image size of 64 &times; 64, a convolutional layer configuration of C&rarr;C&rarr;C&rarr;P, a kernel size of 5 &times; 5, and five layers. Regarding the classification accuracy of the land cover map constructed using this model, the overall accuracy and kappa coefficient for three study cities showed high agreement at approximately 82.9% and 66.3%, respectively