V-ELMpiRNAPred: Identification of human piRNAs by the voting-based extreme learning machine (V-ELM) with a new hybrid feature.

Piwi-interacting RNAs (piRNAs) were recently discovered as endogenous small noncoding RNAs. Some recent research suggests that piRNAs may play an important role in cancer. So the precise identification of human piRNAs is a significant work. In this paper, we introduce a series of new features with 80 dimension called short sequence motifs (SSM). A hybrid feature vector with 1444 dimension can be formed by combining 1364 features of [Formula: see text]-mer strings and 80 features of SSM features. We optimize the 1444 dimension features using the feature score criterion (FSC) and list them in descending order according to the scores. The first 462 are selected as the input feature vector in the classifier. Moreover, eight of 80 SSM features appear in the top 20. This indicates that these eight SSM features play an important part in the identification of piRNAs. Since five of the above eight SSM features are associated with nucleotide A and G ('A*G', 'A**G', 'A***G', 'A****G', 'A*****G'). So, we guess there may exist some biological significance. We also use a neural network algorithm called voting-based extreme learning machine (V-ELM) to identify real piRNAs. The Specificity (Sp) and Sensitivity (Sn) of our method are 95.48% and 94.61%, respectively in human species. This result shows that our method is more effective compared with those of the piRPred, piRNApredictor, Asym-Pibomd, Piano and McRUMs. The web service of V-ELMpiRNAPred is available for free at http://mm20132014.wicp.net:38601/velmprepiRNA/Main.jsp .

OP-Triplet-ELM: Identification of real and pseudo microRNA precursors using extreme learning machine with optimal features.

MicroRNAs (miRNAs) are a set of short (21-24 nt) non-coding RNAs that play significant regulatory roles in the cells. Triplet-SVM-classifier and MiPred (random forest, RF) can identify the real pre-miRNAs from other hairpin sequences with similar stem-loop (pseudo pre-miRNAs). However, the 32-dimensional local contiguous structure-sequence can induce a great information redundancy. Therefore, it is essential to develop a method to reduce the dimension of feature space. In this paper, we propose optimal features of local contiguous structure-sequences (OP-Triplet). These features can avoid the information redundancy effectively and decrease the dimension of the feature vector from 32 to 8. Meanwhile, a hybrid feature can be formed by combining minimum free energy (MFE) and structural diversity. We also introduce a neural network algorithm called extreme learning machine (ELM). The results show that the specificity ([Formula: see text])and sensitivity ([Formula: see text]) of our method are 92.4% and 91.0%, respectively. Compared with Triplet-SVM-classifier, the total accuracy (ACC) of our ELM method increases by 5%. Compared with MiPred (RF) and miRANN, the total accuracy (ACC) of our ELM method increases nearly by 2%. What is more, our method commendably reduces the dimension of the feature space and the training time.

Promoter recognition based on the maximum entropy hidden Markov model.

Since the fast development of genome sequencing has produced large scale data, the current work uses the bioinformatics methods to recognize different gene regions, such as exon, intron and promoter, which play an important role in gene regulations. In this paper, we introduce a new method based on the maximum entropy Markov model (MEMM) to recognize the promoter, which utilizes the biological features of the promoter for the condition. However, it leads to a high false positive rate (FPR). In order to reduce the FPR, we provide another new method based on the maximum entropy hidden Markov model (ME-HMM) without the independence assumption, which could also accommodate the biological features effectively. To demonstrate the precision, the new methods are implemented by R language and the hidden Markov model (HMM) is introduced for comparison. The experimental results show that the new methods may not only overcome the shortcomings of HMM, but also have their own advantages. The results indicate that, MEMM is excellent for identifying the conserved signals, and ME-HMM can demonstrably improve the true positive rate.

[Variation of Cd, Zn and Se contents of polished rice and the potential health risk for subsistence-diet farmers from typical areas of South China].

In this study, a total of 70 polished rice samples were randomly collected at agro-product markets from some typical regions of South China. Their contents of Cd, Zn and Se were determined by atomic adsorption spectrophotometers (AAS) and atomic fluorescence spectrometry (AES) respectively. The variation of the contents with rice areas was described in terms of soil conditions and the potential health risk by food exposure to these rice rains for subsistence-diet fanners is discussed. Over 70% of the total samples have Cd contents exceeding the State Food Security Standards (0.2 mg x kg(-1)) with Cd/Zn ratios exceeding the suggested critical threshold of 0.015. Widest variation was found for Cd and smallest for Zn, showing rice Cd prone to environmental stress. The extent to which the contents of the analyzed elements varied with rice areas was rater for Cd and Se than for Zn, though the contents followed in the same order: polluted area > acid paddy area and neutral paddy area. This further evidenced a determinacy of chemical availability in rice Cd uptake. Taking the reference dose values by WHO and USEPA, the health risk by Cd exposure to the rice diet from different areas was estimated. The consumption of rice from polluted area and acid paddy area may impose serious health risks for subsistence diet farmers though those from neutral paddy area may be still safe under the WHO guideline. It is demanded that the problem of the rice rains high in Cd and low in Zn and Se, and serious potential risk should be taken into account while developing high-yielding rice in acid and polluted rice ares of South China. Technology for depressing Cd uptake and low-Cd cultivar breeding should he pursued in rice production sector in the future.

[Effects of heavy metals pollution on paddy soil aggregates composition and heavy metals distribution].

Topsoil samples were collected from a polluted and an adjacent non-polluted paddy field in the Taihu Lake region of China. Different particle size fractions of soil aggregates were separated by low-energy dispersion procedure, and their mass composition and Pb, Cd, Hg, and As concentrations were determined. Under heavy metals pollution, the mass composition of sand-sized fractions reduced, while that of clay-sized fractions increased. The concentrations of test metals in different particle size fractions differed, with the highest in < 0.002 mm fraction, followed by in 2-0.2 mm fraction. In 0.02-0.002 mm and 0.2-0.02 mm fractions, all the test metals were relatively deficient, with an enrichment index of 0.56-0.96. The present study showed that the aggregation of fine particles could be depressed by heavy metals pollution, which in turn, led to a relative increase in the mass composition of fine particles and the associated allocation of heavy metals in weakly aggregated silt particles, and further, increased the risks of heavy metals translocation from polluted farmland into water and atmosphere. Further studies should be made on the impacts of heavy metals pollution on soil biophysical and biochemical processes and related mechanisms.

Erk is involved in the differentiation induced by diallyl disulfide in the human gastric cancer cell line MGC803.

Diallyl disulfide (DADS) is a major constituent of garlic. Previously, we found that DADS both inhibited proliferation in human gastric cancer cells in vitro and in vivo, and induced G2/M arrest. In this study, we investigated whether this differentiation effect was induced by DADS in human gastric cancer MGC803 cells, and whether it was related to an alteration in ERK activity. The results showed that the growth of MGC803 cells was inhibited by DADS. Cells treated with DADS displayed a lower nucleocytoplasmic ratio and tended to form gland and intercellular conjunction structures. The ConA-mediated cell agglutination ratio and cells' ALP specific activity decreased. In MGC803 cells, dye transfer was limited to a few cells neighbouring the dye-injected cell and to a depth of 1-2 layers beneath the scrape site. However, after treatment with DADS, the LY (Lucifer Yellow) was transferred to several cells immediately neighbouring the microinjected cell and to a depth of 2-4 cell layers from the scrape site. This indicated that DADS induced differentiation in MGC803 cells. Western blot analysis revealed that although DADS did not influence the quantity of ERK1/2 protein expressed, it did decrease its phosphorylation in a concentration-dependent manner, compared with the controls. At 30 mg x L(-1), DADS inhibited the activation of ERK1/2 in 15-30 min. These results suggested that the DADS-induced differentiation of MGC803 cells involved an alteration of the ERK1/2 signaling pathway.