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In this paper, well-defined vaterite hollow spheres and amorphous barium carbonate microrods are synthesized in Proteus mirabilis/urea solution. The urease-generated bacterium Proteus mirabilis is able to convert urea to ammonia and CO2, thereby leading to the precipitation of metal carbonate in Proteus mirabilis/urea solution containing Ca2+ or Ba2+ ions. It is found that the vaterite hollow spheres are so-called mesocrystals because they have identified primary particles and single-crystalline nature. Crystallization of CaCO3 using Proteus mirabilis and other two bacteria Bacillus subtilis and Aerobacter aerogenes in dilute ammonia aqueous solutions (pH 8.5) is also investigated, suggesting that the products are all CaCO3 mesocrystals. Therefore, we speculate that bacteria promoting formation of CaCO3 mesocrystals may be a common phenomenon. In addition, marked morphological changes and structural transition in the CaCO3 particles from amorphous calcium carbonate irregular aggregates to vaterite hollow spheres to a mixture of calcite and vaterite hollow discs and polyhedrons in Proteus mirabilis/urea solution are observed depending on the reaction time. BaCO3 particles change from oval to rod in morphology within 7 days of reaction, but the structure of them is still amorphous even after a month. The biomolecules mainly proteins secreted by the bacteria are probably responsible for the morphologies and structures of metal carbonate minerals by first stabilizing their nanosized precursors, which then transform into mesocrystals or amorphous aggregates via oriented or nonoriented aggregation of nanoparticles. This provides a novel and facile way for the study of biomineralization mechanisms and crystal growth modification.

A substantial cost of granular iron permeable reactive barriers is that of the granular iron itself. Cutting the iron with sand can reduce costs, but several performance issues arise. In particular, reaction rates are expected to decline as the percentage of iron in the blend is diminished. This might occur simply as a function of iron content, or mass transfer effects may play a role in a much less predictable fashion. Column experiments were conducted to investigate the performance consequences of mixing Connelly granular iron with sand using the reduction kinetics of trichloroethylene (TCE) to quantify the changes. Five mixing ratios (i.e., 100%, 85%, 75%, 50%, and 25% of iron by weight) were studied. The experimental data showed that there is a noticeable decrease in the reaction rate when the content of sand is 25% by weight (iron mass to pore volume ratio, Fe/Vp = 3548 g/L) or greater. An analysis of the reaction kinetics, using the Langmuir‐Hinshelwood rate equation, indicated that mass transfer became an apparent cause of rate loss when the iron content fell below 50% by weight (Fe/Vp = 2223 g/L). Paradoxically, there were tentative indications that TCE removal rates were higher in a 15% sand + 85% iron mixture (Fe/Vp = 4416 g/L) than they were in 100% iron (Fe/Vp = 4577 g/L). This subtle improvement in performance might be due to an increase of iron surface available for contact with TCE, due to grain packing in the sand‐iron mixture.

BackgroundPseudouridylation is the most prevalent type of posttranscriptional modification in various stable RNAs of all organisms, which significantly affects many cellular processes that are regulated by RNA. Thus, accurate identification of pseudouridine (Ψ) sites in RNA will be of great benefit for understanding these cellular processes. Due to the low efficiency and high cost of current available experimental methods, it is highly desirable to develop computational methods for accurately and efficiently detecting Ψ sites in RNA sequences. However, the predictive accuracy of existing computational methods is not satisfactory and still needs improvement.ResultsIn this study, we developed a new model, PseUI, for Ψ sites identification in three species, which are H. sapiens, S. cerevisiae, and M. musculus. Firstly, five different kinds of features including nucleotide composition (NC), dinucleotide composition (DC), pseudo dinucleotide composition (pseDNC), position-specific nucleotide propensity (PSNP), and position-specific dinucleotide propensity (PSDP) were generated based on RNA segments. Then, a sequential forward feature selection strategy was used to gain an effective feature subset with a compact representation but discriminative prediction power. Based on the selected feature subsets, we built our model by using a support vector machine (SVM). Finally, the generalization of our model was validated by both the jackknife test and independent validation tests on the benchmark datasets. The experimental results showed that our model is more accurate and stable than the previously published models. We have also provided a user-friendly web server for our model at http://zhulab.ahu.edu.cn/PseUI, and a brief instruction for the web server is provided in this paper. By using this instruction, the academic users can conveniently get their desired results without complicated calculations.ConclusionIn this study, we proposed a new predictor, PseUI, to detect Ψ sites in RNA sequences. It is shown that our model outperformed the existing state-of-art models. It is expected that our model, PseUI, will become a useful tool for accurate identification of RNA Ψ sites.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2321-0) contains supplementary material, which is available to authorized users.

5-methylcytosine (m5C) is one of the most common and abundant post-transcriptional modifications (PTCMs) in RNA. Recent studies showed that m5C plays important roles in many biological functions such as RNA metabolism and cell fate decision. Because most experimental methods that determine m5C sites across the transcriptome are time-consuming and expensive, it is urgent to develop accurate computational methods to identify m5C sites effectively. A benchmark dataset is important for developing and evaluating computational methods. In this work, we constructed four different datasets according to the data redundancy and imbalance. Based on these datasets, we generated three different kinds of features, i.e., KNFs (K-nucleotide frequencies), KSNPFs (K-spaced nucleotide pair frequencies), and pseDNC (pseudo-dinucleotide composition), and then used a support vector machine (SVM) to build our models. Based on the imbalanced and nonredundant dataset, Met935, we extensively studied the three kinds of features and determined an optimal combination of the features. Based on the feature combination, we built models on the three different datasets and compared them with state-of-the-art models. According to the predictive results of the stringent jackknife test, the models based on the three features, 4NF, 1SNPF, and pseDNC, are superior or comparable to other methods. To determine the best model between the models based on the imbalanced dataset Met935 and the balanced dataset Met240, we further evaluated the two models on an independent test set Test1157. Our results demonstrate that the model based on the balanced dataset Met240 achieved the highest recall (68.79%) and the highest Matthews correlation coefficient (MCC) (0.154). In addition, the model is also superior to other state-of-the-art methods according to the integrated parameter MCC on the independent test set. Thus, we selected the model based on Met240 as our final model, which was named RNAm5CPred. In addition, a web server for RNAm5CPred (http://zhulab.ahu.edu.cn/RNAm5CPred/) has been provided to facilitate experimental research.

Aim: To study the expression of proline-rich Akt-substrate PRAS40 in the cell survival pathway and tumor progression. Methods: The effects of three key kinase inhibitors on PRAS40 activity in the cell survival pathway, serum withdrawal, H 2 O 2 and overexpression of Akt were tested. The expression of PRAS40, Akt, Raf and 14-3-3 in normal cells and cancer cell lines was determined by Western blot. Results: The PI3K inhibitors worthmannin and Ly294002, but not rapamycin, completely inhibited the phosphorylation of Akt and PRAS40. The phosphorylation level of Akt decreased after serum withdrawal and treatment with the MEK inhibitor Uo126, but increased after treatment with H 2 O 2 at low concentration, whereas none of these treatments changed PRAS40 activity. 14-3-3 is a PRAS40 binding protein, and the expression of 14-3-3, like that of PRAS40, was higher in HeLa cells than in HEK293 cells; PRAS40 had a stronger phosphorylation activity in A549 and HeLa cancer cells than in HEK293 normal cells. In the breast cancer model (MCF10A/MCF7) and lung cancer model (BEAS/H1198/H1170) we also found the same result: PRAS40 was constitutively active in H1198/H1170 and MCF7 premalignant and malignant cancer cells, but weakly expressed in MCF10A and BEAS normal cell. We also discussed PRAS40 activity in other NSCLC cell lines. Conclusion: The PI3K-Akt survival pathway is the main pathway that PRAS40 is involved in; PRAS40 is a substrate for Akt, but can also be activated by an Aktindependent mechanisms. PRAS40 activation is an early event during breast and lung carcinogenesis.

Cell-cell adhesion molecule cadherin-11(CDH11) is preferentially expressed in basal-like breast cancer cells and facilitates breast cancer cell migration by promoting small GTPase Rac activity. However, how the expression of CDH11 is regulated in breast cancer cells is not understood. Here, we show that CDH11 is transcriptionally controlled by homeobox C8 (HOXC8) in human breast cancer cells. HOXC8 serves as a CDH11-specific transcription factor and binds to the site of nucleotides −196 to −191 in the CDH11 promoter. Depletion of HOXC8 leads to the decrease in anchorage-independent cell growth, cell migration/invasion and spontaneous metastasis of breast cancer cells; however, suppressed tumorigenic events were fully rescued by ectopic CDH11 expression in HOXC8-knockdown cells. These results indicate that HOXC8 impacts breast tumorigenesis through CDH11. The analysis of publically available human breast tumor microarray gene expression database demonstrates a strong positive linear association between HOXC8 and CDH11 expression (ρ = 0.801, p < 0.001). Survival analysis (Kaplan-Meier method, log-rank test) shows that both high HOXC8 and CDH11 expression correlate with poor recurrence-free survival rate of patients. Together, our study suggests that HOXC8 promotes breast tumorigenesis by maintaining high level of CDH11 expression in breast cancer cells.

We fabricate and experimentally characterize a broadband fractal acoustic metamaterial that can serve to attenuate the low-frequency sounds at selective frequencies ranging from 225 to 1175 Hz. The proposed metamaterials are constructed by the periodic Hilbert fractal elements made of photosensitive resin via 3D printing. In analogy to electromagnetic fractal structures, it is shown that multiple resonances can also be excited in the acoustic counterpart due to their self-similar properties, which help to attenuate the acoustic energy in a wide spectrum. The confinement of sound waves in such subwavelength element is evidenced by both numerical and experimental results. The proposed metamaterial may provide possible alternative for various applications such as the noise attenuation and the anechoic materials.