Na-TiNT Nanocrystals: Synthesis, Characterization, and Antibacterial Properties.

Titanium nanotubes have attractive morphological and physicochemical properties for several applications, such as high surface area, mesoporous structure, good stability, ion exchange capacity, and antibacterial property. Therefore, the field of nanotube applications is increasingly expanding, such as in solar cells sensitized by dye, photocatalysis, and antibacterial activity, among others. Therefore, a study of the antibacterial properties of sodium titanate nanotubes (Na-TiNTs) was carried out together with physicochemical characterizations, such as Raman spectroscopy which shows a peak characteristic of Na-O-Ti from nanotube-agglomerated regions. The XRD diffractogram confirmed the Raman spectra and evidenced the crystalline structure associated to Na-TiNT, which showed the characteristic peaks of the sodium trititanate crystal. SEM and TEM images showed the morphology of hollow nanotubes and forming semispherical particles. EDS shows the percentage values of each of the compounds in the Na-TiNT. The bacterial activity of the Na-TiNT was analyzed in Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa. Na-TiNT modified the activity of the gentamicin and norfloxacin antibiotics against multiresistant strains. Synergistic effects against Gram-positive S. aureus 10 and Gram-negative P. aeruginosa 15 bacteria were observed when the Na-TiNT was associated with gentamicin, reducing the concentration of this antibiotic that is required to inhibit bacterial growth. Another synergic effect was observed for S. aureus 10 with norfloxacin.

44 Current Challenges in miRNomics.

Mature microRNAs (miRNAs) are short RNA sequences about 18-24 nucleotide long, which provide the recognition key within RISC for the posttranscriptional regulation of target RNAs. Considering the canonical pathway, mature miRNAs are produced via a multistep process. Their transcription (pri-miRNAs) and first processing step via the microprocessor complex (pre-miRNAs) occur in the nucleus. Then they are exported into the cytosol, processed again by Dicer (dsRNA) and finally a single strand (mature miRNA) is incorporated into RISC (miRISC). The sequence of the incorporated miRNA provides the function of RNA target recognition via hybridization. Following binding of the target, the mRNA is either degraded or translation is inhibited, which ultimately leads to less protein production. Conversely, it has been shown that binding within the 5' UTR of the mRNA can lead to an increase in protein product. Regulation of homeostasis is very important for a cell; therefore, all steps in the miRNA-based regulation pathway, from transcription to the incorporation of the mature miRNA into RISC, are under tight control. While much research effort has been exerted in this area, the knowledgebase is not sufficient for accurately modelling miRNA regulation computationally. The computational prediction of miRNAs is, however, necessary because it is not feasible to investigate all possible pairs of a miRNA and its target, let alone miRNAs and their targets. We here point out open challenges important for computational modelling or for our general understanding of miRNA-based regulation and show how their investigation is beneficial. It is our hope that this collection of challenges will lead to their resolution in the near future.

Thermodynamics of Linear Carbon Chains.

Linear carbon chains (LCCs) are one-dimensional materials with unique properties, including high Debye temperatures and restricted selection rules for phonon interactions. Consequently, their Raman C-band frequency's temperature dependence is a probe to their thermal properties, which are well described within the Debye formalism even at room temperatures. Therefore, with the basis on a semiempirical approach we show how to use the C band to evaluate the LCCs' internal energy, heat capacity, coefficient of thermal expansion, thermal strain, and Grüneisen parameter, providing universal relations for these quantities in terms of the number of carbons atoms and the temperature.

Feature extraction approaches for biological sequences: a comparative study of mathematical features.

As consequence of the various genomic sequencing projects, an increasing volume of biological sequence data is being produced. Although machine learning algorithms have been successfully applied to a large number of genomic sequence-related problems, the results are largely affected by the type and number of features extracted. This effect has motivated new algorithms and pipeline proposals, mainly involving feature extraction problems, in which extracting significant discriminatory information from a biological set is challenging. Considering this, our work proposes a new study of feature extraction approaches based on mathematical features (numerical mapping with Fourier, entropy and complex networks). As a case study, we analyze long non-coding RNA sequences. Moreover, we separated this work into three studies. First, we assessed our proposal with the most addressed problem in our review, e.g. lncRNA and mRNA; second, we also validate the mathematical features in different classification problems, to predict the class of lncRNA, e.g. circular RNAs sequences; third, we analyze its robustness in scenarios with imbalanced data. The experimental results demonstrated three main contributions: first, an in-depth study of several mathematical features; second, a new feature extraction pipeline; and third, its high performance and robustness for distinct RNA sequence classification. Availability:https://github.com/Bonidia/FeatureExtraction_BiologicalSequences.

Genome-Wide Screening and Characterization of Non-Coding RNAs in Coffea canephora.

Coffea canephora grains are highly traded commodities worldwide. Non-coding RNAs (ncRNAs) are transcriptional products involved in genome regulation, environmental responses, and plant development. There is not an extensive genome-wide analysis that uncovers the ncRNA portion of the C. canephora genome. This study aimed to provide a curated characterization of six ncRNA classes in the Coffea canephora genome. For this purpose, we employed a combination of similarity-based and structural-based computational approaches with stringent curation. Candidate ncRNA loci had expression evidence analyzed using sRNA-seq libraries. We identified 7455 ncRNA loci (6976 with transcriptional evidence) in the C. canephora genome. This comprised of total 115 snRNAs, 1031 snoRNAs, 92 miRNA precursors, 602 tRNAs, 72 rRNAs, and 5064 lncRNAs. For miRNAs, we identified 159 putative high-confidence targets. This study was the most extensive genomic catalog of curated ncRNAs in the Coffea genus. This data might help elaborating more robust hypotheses in future comparative genomic studies as well as gene regulation and genome dynamics, helping to understand the molecular basis of domestication, environmental adaptation, resistance to pests and diseases, and coffee productivity.

The nuclear and mitochondrial genomes of Frieseomelitta varia - a highly eusocial stingless bee (Meliponini) with a permanently sterile worker caste.

BACKGROUND: Most of our understanding on the social behavior and genomics of bees and other social insects is centered on the Western honey bee, Apis mellifera. The genus Apis, however, is a highly derived branch comprising less than a dozen species, four of which genomically characterized. In contrast, for the equally highly eusocial, yet taxonomically and biologically more diverse Meliponini, a full genome sequence was so far available for a single Melipona species only. We present here the genome sequence of Frieseomelitta varia, a stingless bee that has, as a peculiarity, a completely sterile worker caste. RESULTS: The assembly of 243,974,526 high quality Illumina reads resulted in a predicted assembled genome size of 275 Mb composed of 2173 scaffolds. A BUSCO analysis for the 10,526 predicted genes showed that these represent 96.6% of the expected hymenopteran orthologs. We also predicted 169,371 repetitive genomic components, 2083 putative transposable elements, and 1946 genes for non-coding RNAs, largely long non-coding RNAs. The mitochondrial genome comprises 15,144 bp, encoding 13 proteins, 22 tRNAs and 2 rRNAs. We observed considerable rearrangement in the mitochondrial gene order compared to other bees. For an in-depth analysis of genes related to social biology, we manually checked the annotations for 533 automatically predicted gene models, including 127 genes related to reproductive processes, 104 to development, and 174 immunity-related genes. We also performed specific searches for genes containing transcription factor domains and genes related to neurogenesis and chemosensory communication. CONCLUSIONS: The total genome size for F. varia is similar to the sequenced genomes of other bees. Using specific prediction methods, we identified a large number of repetitive genome components and long non-coding RNAs, which could provide the molecular basis for gene regulatory plasticity, including worker reproduction. The remarkable reshuffling in gene order in the mitochondrial genome suggests that stingless bees may be a hotspot for mtDNA evolution. Hence, while being just the second stingless bee genome sequenced, we expect that subsequent targeting of a selected set of species from this diverse clade of highly eusocial bees will reveal relevant evolutionary signals and trends related to eusociality in these important pollinators.

An integrated analysis of mRNA and sRNA transcriptional profiles in Coffea arabica L. roots: insights on nitrogen starvation responses.

Coffea arabica L. is an important agricultural commodity, accounting for 60% of traded coffee worldwide. Nitrogen (N) is a macronutrient that is usually limiting to plant yield; however, molecular mechanisms of plant acclimation to N limitation remain largely unknown in tropical woody crops. In this study, we investigated the transcriptome of coffee roots under N starvation, analyzing poly-A+ libraries and small RNAs. We also evaluated the concentration of selected amino acids and N-source preferences in roots. Ammonium was preferentially taken up over nitrate, and asparagine and glutamate were the most abundant amino acids observed in coffee roots. We obtained 34,654 assembled contigs by mRNA sequencing, and validated the transcriptional profile of 12 genes by RT-qPCR. Illumina small RNA sequencing yielded 8,524,332 non-redundant reads, resulting in the identification of 86 microRNA families targeting 253 genes. The transcriptional pattern of eight miRNA families was also validated. To our knowledge, this is the first catalog of differentially regulated amino acids, N sources, mRNAs, and sRNAs in Arabica coffee roots.

An integrated analysis of mRNA and sRNA transcriptional profiles in Coffea arabica L. roots: insights on nitrogen starvation responses

Coffea arabica L. is an important agricultural commodity, accounting for 60% of traded coffee worldwide. Nitrogen (N) is a macronutrient that is usually limiting to plant yield; however, molecular mechanisms of plant acclimation to N limitation remain largely unknown in tropical woody crops. In this study, we investigated the transcriptome of coffee roots under N starvation, analyzing poly-A+ libraries and small RNAs. We also evaluated the concentration of selected amino acids and N-source preferences in roots. Ammonium was preferentially taken up over nitrate, and asparagine and glutamate were the most abundant amino acids observed in coffee roots. We obtained 34,654 assembled contigs by mRNA sequencing, and validated the transcriptional profile of 12 genes by RT-qPCR. Illumina small RNA sequencing yielded 8,524,332 non-redundant reads, resulting in the identification of 86 microRNA families targeting 253 genes. The transcriptional pattern of eight miRNA families was also validated. To our knowledge, this is the first catalog of differentially regulated amino acids, N sources, mRNAs, and sRNAs in Arabica coffee roots.

An integrated analysis of mRNA and sRNA transcriptional profiles in Coffea arabica L. roots: insights on nitrogen starvation responses

Coffea arabica L. is an important agricultural commodity, accounting for 60% of traded coffee worldwide. Nitrogen (N) is a macronutrient that is usually limiting to plant yield; however, molecular mechanisms of plant acclimation to N limitation remain largely unknown in tropical woody crops. In this study, we investigated the transcriptome of coffee roots under N starvation, analyzing poly-A+ libraries and small RNAs. We also evaluated the concentration of selected amino acids and N-source preferences in roots. Ammonium was preferentially taken up over nitrate, and asparagine and glutamate were the most abundant amino acids observed in coffee roots. We obtained 34,654 assembled contigs by mRNA sequencing, and validated the transcriptional profile of 12 genes by RT-qPCR. Illumina small RNA sequencing yielded 8,524,332 non-redundant reads, resulting in the identification of 86 microRNA families targeting 253 genes. The transcriptional pattern of eight miRNA families was also validated. To our knowledge, this is the first catalog of differentially regulated amino acids, N sources, mRNAs, and sRNAs in Arabica coffee roots.

Raman evidence for pressure-induced formation of diamondene.

Despite the advanced stage of diamond thin-film technology, with applications ranging from superconductivity to biosensing, the realization of a stable and atomically thick two-dimensional diamond material, named here as diamondene, is still forthcoming. Adding to the outstanding properties of its bulk and thin-film counterparts, diamondene is predicted to be a ferromagnetic semiconductor with spin polarized bands. Here, we provide spectroscopic evidence for the formation of diamondene by performing Raman spectroscopy of double-layer graphene under high pressure. The results are explained in terms of a breakdown in the Kohn anomaly associated with the finite size of the remaining graphene sites surrounded by the diamondene matrix. Ab initio calculations and molecular dynamics simulations are employed to clarify the mechanism of diamondene formation, which requires two or more layers of graphene subjected to high pressures in the presence of specific chemical groups such as hydroxyl groups or hydrogens.The synthesis of two-dimensional diamond is the ultimate goal of diamond thin-film technology. Here, the authors perform Raman spectroscopy of bilayer graphene under pressure, and obtain spectroscopic evidence of formation of diamondene, an atomically thin form of diamond.

PlanTE-MIR DB: a database for transposable element-related microRNAs in plant genomes.

Transposable elements (TEs) comprise a major fraction of many plant genomes and are known to drive their organization and evolution. Several studies show that these repetitive elements have a prominent role in shaping noncoding regions of the genome such as microRNA (miRNA) loci, which are components of post-transcriptional regulation mechanisms. Although some studies have reported initial formation of miRNA loci from TE sequences, especially in model plants, the approaches that were used did not employ systems that would allow results to be delivered by a user-friendly database. In this study, we identified 152 precursor miRNAs overlapping TEs in 10 plant species. PlanTE-MIR DB was designed to assemble this data and deliver it to the scientific community interested in miRNA origin, evolution, and regulation pathways. Users can browse the database through a web interface and search for entries using various parameters. This resource is cross-referenced with repetitive element (Repbase Update) and miRNA (miRBase) repositories, where sequences can be checked for further analysis. All data in PlanTE-MIR DB are publicly available for download in several file formats to facilitate their understanding and use. The database is hosted at http://bioinfo-tool.cp.utfpr.edu.br/plantemirdb/ .

A Comparative Study of the Photosensitizer Penetration into Artificial Caries Lesions in Dentin Measured by the Confocal Raman Microscopy.

This study utilized the confocal Raman microspectroscopy (CRM) technique for the first time to investigate the degree of the penetration of toluidine blue-orto (TBO) in artificial caries lesions produced by two distinct caries-inducing models. The dentin specimens (n = 10) were divided into three groups: control, in vitro and in situ. Thereafter, the lesion depth and the demineralization level were evaluated by cross-sectional microhardness (CSMH). CRM mapping across the dentin surface was assessed after the dye application. The CSMH and CRM data were analyzed by t-test and ANOVA, respectively (P < 0.05). The values of the lesion depth and the demineralization areas were higher for in situ samples (P < 0.05). The TBO penetration values (µm) for the control, in vitro and in situ groups were 44.8 ± 5.6, 46.1 ± 4.5 and 51.2 ± 8.5, respectively. There were no statistically significant differences among the groups (P > 0.05). The rate of TBO penetration was detected up to about <50 µm and the demineralization level did not influence the results. These results have showed promising parameters to develop new protocols for deep caries lesions management using photodynamic antimicrobial chemotherapy.