New Trends for the Processing of Poly(Methyl Methacrylate) Biomaterial for Dental Prosthodontics

Rehabilitation of masticatory function in patients with absent teeth with removable dentures is an established form of treating partial or complete dentition in edentulous patients. The developments in recent decades with dental implants dominate current dental research. However, medical contraindications, a negative attitude toward implants, or financial limitations on the part of the patients limit their universal applicability, so the rehabilitation with dental prostheses still makes up a significant portion of everyday clinical practice. Conversely, removable dentures are used in the critical conditions of the oral cavity. There are about 500 strains of microorganisms in the mouth, which form the biofilm in an acidic environment causing several issues, such as denture stomatitis, deterioration of the periodontal status of the remaining teeth, or carious lesions in the supporting teeth. Therefore, it is very important to choose a suitable material for the prosthesis. Poly(methyl methacrylate) (PMMA) is an acrylic resin usually used with a long tradition for prosthetic purposes. The aim of this chapter is to present the trends for the processing of PMMA. It includes the chemical synthesis, conventional thermal processing of this acrylic resin, the new processing technique assisted with ultrasound, the antibacterial effect on PMMA with nanoparticles, and the cytotoxicity, genotoxicity, and mutagenesis of this material

A population-based controlled experiment assessing the epidemiological impact of digital contact tracing

While Digital contact tracing (DCT) has been argued to be a valuable complement to manual tracing in the containment of COVID-19, no empirical evidence of its effectiveness is available to date. Here, we report the results of a 4-week population-based controlled experiment that took place in La Gomera (Canary Islands, Spain) between June and July 2020, where we assessed the epidemiological impact of the Spanish DCT app Radar Covid. After a substantial communication campaign, we estimate that at least 33% of the population adopted the technology and further showed relatively high adherence and compliance as well as a quick turnaround time. The app detects about 6.3 close-contacts per primary simulated infection, a significant percentage being contacts with strangers, although the spontaneous follow-up rate of these notified cases is low. Overall, these results provide experimental evidence of the potential usefulness of DCT during an epidemic outbreak in a real population

Daptomycin plus Fosfomycin versus Daptomycin Alone for Methicillin-Resistant Staphylococcus 2 aureus Bacteremia and Endocarditis. A Randomized Clinical Trial

Background We aimed to determine whether daptomycin plus fosfomycin provides higher treatment success than daptomycin alone for methicillin-resistant Staphylococcus aureus (MRSA) bacteremia and endocarditis. Methods A randomized (1:1) phase 3 superiority, open-label, and parallel group clinical trial of adult inpatients with MRSA bacteremia was conducted at 18 Spanish hospitals. Patients were randomly assigned to receive either 10 mg/kg of daptomycin intravenously daily plus 2 g of fosfomycin intravenously every 6 hours, or 10 mg/kg of daptomycin intravenously daily. Primary endpoint was treatment success 6 weeks after the end of therapy. Results Of 167 patients randomized, 155 completed the trial and were assessed for the primary endpoint. Treatment success at 6 weeks after the end of therapy was achieved in 40 of 74 patients who received daptomycin plus fosfomycin and in 34 of 81 patients who were given daptomycin alone (54.1% vs 42.0%; relative risk, 1.29 [95% confidence interval, .93-1.8]; P = .135). At 6 weeks, daptomycin plus fosfomycin was associated with lower microbiologic failure (0 vs 9 patients; P = .003) and lower complicated bacteremia (16.2% vs 32.1%; P = .022). Adverse events leading to treatment discontinuation occurred in 13 of 74 patients (17.6%) receiving daptomycin plus fosfomycin, and in 4 of 81 patients (4.9%) receiving daptomycin alone (P = .018). Conclusions Daptomycin plus fosfomycin provided 12% higher rate of treatment success than daptomycin alone, but this difference did not reach statistical significance. This antibiotic combination prevented microbiological failure and complicated bacteremia, but it was more often associated with adverse events

Inherent directionality explains the lack of feedback loops in empirical networks

We explore the hypothesis that the relative abundance of feedback loops in many empirical complex networks is severely reduced owing to the presence of an inherent global directionality. Aimed at quantifying this idea, we propose a simple probabilistic model in which a free parameter γ controls the degree of inherent directionality. Upon strengthening such directionality, the model predicts a drastic reduction in the fraction of loops which are also feedback loops. To test this prediction, we extensively enumerated loops and feedback loops in many empirical biological, ecological and socio-technological directed networks. We show that, in almost all cases, empirical networks have a much smaller fraction of feedback loops than network randomizations. Quite remarkably, this empirical finding is quantitatively reproduced, for all loop lengths, by our model by fitting its only parameter γ. Moreover, the fitted value of γ correlates quite well with another direct measurement of network directionality, performed by means of a novel algorithm. We conclude that the existence of an inherent network directionality provides a parsimonious quantitative explanation for the observed lack of feedback loops in empirical networks

Comparing the Invasibility of Experimental “Reefs” with Field Observations of Natural Reefs and Artificial Structures

Natural systems are increasingly being modified by the addition of artificial habitats which may facilitate invasion. Where invaders are able to disperse from artificial habitats, their impact may spread to surrounding natural communities and therefore it is important to investigate potential factors that reduce or enhance invasibility. We surveyed the distribution of non-indigenous and native invertebrates and algae between artificial habitats and natural reefs in a marine subtidal system. We also deployed sandstone plates as experimental ‘reefs’ and manipulated the orientation, starting assemblage and degree of shading. Invertebrates (non-indigenous and native) appeared to be responding to similar environmental factors (e.g. orientation) and occupied most space on artificial structures and to a lesser extent reef walls. Non-indigenous invertebrates are less successful than native invertebrates on horizontal reefs despite functional similarities. Manipulative experiments revealed that even when non-indigenous invertebrates invade vertical “reefs”, they are unlikely to gain a foothold and never exceed covers of native invertebrates (regardless of space availability). Community ecology suggests that invertebrates will dominate reef walls and algae horizontal reefs due to functional differences, however our surveys revealed that native algae dominate both vertical and horizontal reefs in shallow estuarine systems. Few non-indigenous algae were sampled in the study, however where invasive algal species are present in a system, they may present a threat to reef communities. Our findings suggest that non-indigenous species are less successful at occupying space on reef compared to artificial structures, and manipulations of biotic and abiotic conditions (primarily orientation and to a lesser extent biotic resistance) on experimental “reefs” explained a large portion of this variation, however they could not fully explain the magnitude of differences

An RNAi in silico approach to find an optimal shRNA cocktail against HIV-1

<p>Abstract</p> <p>Background</p> <p>HIV-1 can be inhibited by RNA interference <it>in vitro </it>through the expression of short hairpin RNAs (shRNAs) that target conserved genome sequences. <it>In silico </it>shRNA design for HIV has lacked a detailed study of virus variability constituting a possible breaking point in a clinical setting. We designed shRNAs against HIV-1 considering the variability observed in naïve and drug-resistant isolates available at public databases.</p> <p>Methods</p> <p>A Bioperl-based algorithm was developed to automatically scan multiple sequence alignments of HIV, while evaluating the possibility of identifying dominant and subdominant viral variants that could be used as efficient silencing molecules. Student t-test and Bonferroni Dunn correction test were used to assess statistical significance of our findings.</p> <p>Results</p> <p>Our <it>in silico </it>approach identified the most common viral variants within highly conserved genome regions, with a calculated free energy of ≥ -6.6 kcal/mol. This is crucial for strand loading to RISC complex and for a predicted silencing efficiency score, which could be used in combination for achieving over 90% silencing. Resistant and naïve isolate variability revealed that the most frequent shRNA per region targets a maximum of 85% of viral sequences. Adding more divergent sequences maintained this percentage. Specific sequence features that have been found to be related with higher silencing efficiency were hardly accomplished in conserved regions, even when lower entropy values correlated with better scores. We identified a conserved region among most HIV-1 genomes, which meets as many sequence features for efficient silencing.</p> <p>Conclusions</p> <p>HIV-1 variability is an obstacle to achieving absolute silencing using shRNAs designed against a consensus sequence, mainly because there are many functional viral variants. Our shRNA cocktail could be truly effective at silencing dominant and subdominant naïve viral variants. Additionally, resistant isolates might be targeted under specific antiretroviral selective pressure, but in both cases these should be tested exhaustively prior to clinical use.</p

Modularity in Protein Complex and Drug Interactions Reveals New Polypharmacological Properties

Recent studies have highlighted the importance of interconnectivity in a large range of molecular and human disease-related systems. Network medicine has emerged as a new paradigm to deal with complex diseases. Connections between protein complexes and key diseases have been suggested for decades. However, it was not until recently that protein complexes were identified and classified in sufficient amounts to carry out a large-scale analysis of the human protein complex system. We here present the first systematic and comprehensive set of relationships between protein complexes and associated drugs and analyzed their topological features. The network structure is characterized by a high modularity, both in the bipartite graph and in its projections, indicating that its topology is highly distinct from a random network and that it contains a rich and heterogeneous internal modular structure. To unravel the relationships between modules of protein complexes, drugs and diseases, we investigated in depth the origins of this modular structure in examples of particular diseases. This analysis unveils new associations between diseases and protein complexes and highlights the potential role of polypharmacological drugs, which target multiple cellular functions to combat complex diseases driven by gain-of-function mutations

Identification of Plasmodium vivax Proteins with Potential Role in Invasion Using Sequence Redundancy Reduction and Profile Hidden Markov Models

BACKGROUND: This study describes a bioinformatics approach designed to identify Plasmodium vivax proteins potentially involved in reticulocyte invasion. Specifically, different protein training sets were built and tuned based on different biological parameters, such as experimental evidence of secretion and/or involvement in invasion-related processes. A profile-based sequence method supported by hidden Markov models (HMMs) was then used to build classifiers to search for biologically-related proteins. The transcriptional profile of the P. vivax intra-erythrocyte developmental cycle was then screened using these classifiers. RESULTS: A bioinformatics methodology for identifying potentially secreted P. vivax proteins was designed using sequence redundancy reduction and probabilistic profiles. This methodology led to identifying a set of 45 proteins that are potentially secreted during the P. vivax intra-erythrocyte development cycle and could be involved in cell invasion. Thirteen of the 45 proteins have already been described as vaccine candidates; there is experimental evidence of protein expression for 7 of the 32 remaining ones, while no previous studies of expression, function or immunology have been carried out for the additional 25. CONCLUSIONS: The results support the idea that probabilistic techniques like profile HMMs improve similarity searches. Also, different adjustments such as sequence redundancy reduction using Pisces or Cd-Hit allowed data clustering based on rational reproducible measurements. This kind of approach for selecting proteins with specific functions is highly important for supporting large-scale analyses that could aid in the identification of genes encoding potential new target antigens for vaccine development and drug design. The present study has led to targeting 32 proteins for further testing regarding their ability to induce protective immune responses against P. vivax malaria