Antimicrobial photodynamic therapy compared to systemic antibiotic therapy in non-surgical treatment of periodontitis: Systematic review and meta-analysis.

BACKGROUND: Periodontitis is one of the most prevalent inflammatory diseases in humans. It is associated with the presence of bacteria and is mediated by the host's immune response This study represents a systematic review and meta-analysis trying to answer the following question: "What is the effect of antimicrobial photodynamic therapy (aPDT) as an adjunct to scaling and root planing (SRP) compared to systemic antibiotic therapy with amoxicillin plus metronidazole (AMX+MTZ) on the non-surgical treatment of periodontitis?". METHODS: Clinical studies comparing aPDT with systemic use of AMX+MTZ were searched until January of 2020 using the databases: PubMed, MEDLINE, SCOPUS, EMBASE, Cochrane Central, Web of Science and Scielo, as well manual searches in related journals. Periodontal clinical parameters such as probing depth (PD), clinical attachment level (CAL) and bleeding on probing (BOP) were statistically analyzed. RESULTS: Five randomized clinical studies (RCTs) were included within the eligibility criteria, and served as a basis for qualitative and quantitative analyzes. All the studies reported an improvement in the clinical parameters with both therapies, although in a direct comparison, our analyzes did not find statistical differences that indicate the superiority of one supporting treatment in relation to the other. CONCLUSION: Although the limited number of RCTs and the great heterogeneity between them, it can conclude that aPDT presents similar clinical results compared to antibiotic therapy with AMX+MTZ as adjuvants in the non-surgical treatment of periodontitis

Secular evolution versus hierarchical merging: galaxy evolution along the Hubble sequence, in the field and rich environments

In the current galaxy formation scenarios, two physical phenomena are invoked to build disk galaxies: hierarchical mergers and more quiescent external gas accretion, coming from intergalactic filaments. Although both are thought to play a role, their relative importance is not known precisely. Here we consider the constraints on these scenarios brought by the observation-deduced star formation history on the one hand, and observed dynamics of galaxies on the other hand: the high frequency of bars and spirals, the high frequency of perturbations such as lopsidedness, warps, or polar rings. All these observations are not easily reproduced in simulations without important gas accretion. N-body simulations taking into account the mass exchange between stars and gas through star formation and feedback, can reproduce the data, only if galaxies double their mass in about 10 Gyr through gas accretion. Warped and polar ring systems are good tracers of this accretion, which occurs from cold gas which has not been virialised in the system's potential. The relative importance of these phenomena are compared between the field and rich clusters. The respective role of mergers and gas accretion vary considerably with environment.Comment: 18 pages, 8 figures, review paper to "Penetrating Bars through Masks of Cosmic Dust: the Hubble Tuning Fork Strikes a New Note", Pilanesberg, ed. D. Block et al., Kluwe

Allosteric Analysis of Glucocorticoid Receptor-DNA Interface Induced by Cyclic Py-Im Polyamide: A Molecular Dynamics Simulation Study

Background: It has been extensively developed in recent years that cell-permeable small molecules, such as polyamide, can be programmed to disrupt transcription factor-DNA interfaces and can silence aberrant gene expression. For example, cyclic pyrrole-imidazole polyamide that competes with glucocorticoid receptor (GR) for binding to glucocorticoid response elements could be expected to affect the DNA dependent binding by interfering with the protein-DNA interface. However, how such small molecules affect the transcription factor-DNA interfaces and gene regulatory pathways through DNA structure distortion is not fully understood so far. Methodology/Principal Findings: In the present work, we have constructed some models, especially the ternary model of polyamides+DNA+GR DNA-binding domain (GRDBD) dimer, and carried out molecular dynamics simulations and free energy calculations for them to address how polyamide molecules disrupt the GRDBD and DNA interface when polyamide and protein bind at the same sites on opposite grooves of DNA. Conclusions/Significance: We found that the cyclic polyamide binding in minor groove of DNA can induce a large structural perturbation of DNA, i.e. a.4 A ˚ widening of the DNA minor groove and a compression of the major groove by more than 4A ˚ as compared with the DNA molecule in the GRDBD dimer+DNA complex. Further investigations for the ternary system of polyamides+DNA+GRDBD dimer and the binary system of allosteric DNA+GRDBD dimer revealed that the compression o

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Detecting Network Communities: An Application to Phylogenetic Analysis

This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis

The neuroscience of suicidal behaviors: what can we expect from endophenotype strategies?

Vulnerability to suicidal behavior (SB) is likely mediated by an underlying genetic predisposition interacting with environmental and probable epigenetic factors throughout the lifespan to modify the function of neuronal circuits, thus rendering an individual more likely to engage in a suicidal act. Improving our understanding of the neuroscience underlying SBs, both attempts and completions, at all developmental stages is crucial for more effective preventive treatments and for better identification of vulnerable individuals. Recent studies have characterized SB using an endophenotype strategy, which aims to identify quantitative measures that reflect genetically influenced stable changes in brain function. In addition to aiding in the functional characterization of susceptibility genes, endophenotypic research strategies may have a wider impact in determining vulnerability to SB, as well as the translation of human findings to animal models, and vice versa. Endophenotypes associated with vulnerability to SB include impulsive/aggressive personality traits and disadvantageous decision making. Deficits in realistic risk evaluation represent key processes in vulnerability to SB. Serotonin dysfunction, indicated by neuroendocrine responses and neuroimaging, is also strongly implicated as a potential endophenotype and is linked with impulsive aggression and disadvantageous decision making. Specific endophenotypes may represent heritable markers for the identification of vulnerable patients and may be relevant targets for successful suicide prevention and treatments