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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. [ABSTRACT FROM AUTHOR]

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 [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Theobroma grandiflorum (Malvaceae), known as cupuassu, is a tree indigenous to the Amazon basin, valued for its large fruits and seed pulp, contributing notably to the Amazonian bioeconomy. The seed pulp is utilized in desserts and beverages, and its seed butter is used in cosmetics. Here, we present the sequenced telomere-to-telomere genome of cupuassu, disclosing its genomic structure, evolutionary features, and phylogenetic relationships within the Malvaceae family., Findings: The cupuassu genome spans 423 Mb, encodes 31,381 genes distributed in 10 chromosomes, and exhibits approximately 65% gene synteny with the Theobroma cacao genome, reflecting a conserved evolutionary history, albeit punctuated with unique genomic variations. The main changes are pronounced by bursts of long-terminal repeat retrotransposons at postspecies divergence, retrocopied and singleton genes, and gene families displaying distinctive patterns of expansion and contraction. Furthermore, positively selected genes are evident, particularly among retained and dispersed tandem and proximal duplicated genes associated with general fruit and seed traits and defense mechanisms, supporting the hypothesis of potential episodes of subfunctionalization and neofunctionalization following duplication, as well as impact from distinct domestication process. These genomic variations may underpin the differences observed in fruit and seed morphology, ripening, and disease resistance between cupuassu and the other Malvaceae species., Conclusions: The cupuassu genome offers a foundational resource for both breeding improvement and conservation biology, yielding insights into the evolution and diversity within the genus Theobroma., (© The Author(s) 2024. Published by Oxford University Press GigaScience.)

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., (© 2022. Springer Science+Business Media, LLC, part of Springer Nature.)