Pseudomonas aeruginosa biofilm formation and slime excretion on antibiotic-loaded bone cement

Background Infection is an infrequent but serious complication of prosthetic joint surgery. These infections will usually not clear until the implant is removed and re-implantation has a high failure rate, especially when Pseudomonas aeruginosa is involved. Material and methods We examined Pseudomonas aeruginosa biofilm formation on plain and gentamicin-loaded bone cement with confocal scanning laser microscopy (CSLM). Two different stains were applied in order to visualize and quantify the distribution of bacterial cells and extracellular polymeric substances (slime) from the bone cement surface to the top of the biofilm. Staining with LIVE/DEAD viability stain differentiated between live and dead bacteria within the biofilm, and slime production was evaluated after staining with Calcofluor white. Results CSLM showed that the biofilm was a nonuniform structure of variable thickness, with differences in local bacterial cell and slime densities. Incorporation of gentamicin in bone cement resulted in a 44% reduction in bacterial viability, while the slime density increased significantly. In addition, conventional plate counting showed the development of small-colony variants on gentamicin-loaded bone cement with a decreased sensitivity for gentamicin (MIC: 8 mg/L), as compared with normal-sized colonies taken from plain and gentamicin-loaded bone cement (MIC: 3 mg/L). The enhanced slime production on antibiotic-loaded bone cement, together with the formation of small-colony variants, resulted in decreased susceptibility to antibiotics-probably concomitant with the onset of persistent and relapsing infections. Interpretation In the clinical situation, our findings help to explain the frequent re-implantation failure of joint replacements infected with P. aeruginosa when the procedure has been performed using antibiotic-loaded bone cement

Treating natural disaster victims is dealing with shortages:An orthopaedics perspective

During natural disasters such as earthquakes or tsunamis, most of the casualties are known to suffer from musculoskeletal injuries. This leads to an enormous need of orthopaedic (surgical) implants such as osteosynthesis plates, which are difficult to provide in developing countries that rely on imported ones. One of the alternatives is utilization of local resources, but only after they have been proven safe to use, and meet the international standards set. Through this paper we would like to urge the international community to include locally produced biomedical products, like osteosynthesis plates in their scientific evaluations and communications. When the quality of local products is proven, the reluctance to use local products also by surgeons from developing countries will disappear and larger scale production can be initiated. This in its turn solves many problems that come after natural disasters and stimulates the national economy in an efficient and effective way

A genetic algorithm for the one-dimensional cutting stock problem with setups

This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the concepts of genetic algorithms is proposed to solve the problem. This heuristic is empirically analyzed by solving randomly generated instances and also practical instances from a chemical-fiber company. The computational results show that the method is efficient and obtains positive results when compared to other methods from the literature. © 2014 Brazilian Operations Research Society

Horizontal Transmission of Candida albicans and Evidence of a Vaccine Response in Mice Colonized with the Fungus

Disseminated candidiasis is the third leading nosocomial blood stream infection in the United States and is often fatal. We previously showed that disseminated candidiasis was preventable in normal mice by immunization with either a glycopeptide or a peptide synthetic vaccine, both of which were Candida albicans cell wall derived. A weakness of these studies is that, unlike humans, mice do not have a C. albicans GI flora and they lack Candida serum antibodies. We examined the influence of C. albicans GI tract colonization and serum antibodies on mouse vaccination responses to the peptide, Fba, derived from fructose bisphosphate aldolase which has cytosolic and cell wall distributions in the fungus. We evaluated the effect of live C. albicans in drinking water and antimicrobial agents on establishment of Candida colonization of the mouse GI tract. Body mass, C. albicans in feces, and fungal-specific serum antibodies were monitored longitudinally. Unexpectedly, C. albicans colonization occurred in mice that received only antibiotics in their drinking water, provided that the mice were housed in the same room as intentionally colonized mice. The fungal strain in unintentionally colonized mice appeared identical to the strain used for intentional GI-tract colonization. This is the first report of horizontal transmission and spontaneous C. albicans colonization in mice. Importantly, many Candida-colonized mice developed serum fungal-specific antibodies. Despite the GI-tract colonization and presence of serum antibodies, the animals made antibodies in response to the Fba immunogen. This mouse model has potential for elucidating C. albicans horizontal transmission and for exploring factors that induce host defense against disseminated candidiasis. Furthermore, a combined protracted GI-tract colonization with Candida and the possibility of serum antibody responses to the presence of the fungus makes this an attractive mouse model for testing the efficacy of vaccines designed to prevent human disseminated candidiasis

An organelle-specific protein landscape identifies novel diseases and molecular mechanisms

Contains fulltext : 158967.pdf (publisher's version ) (Open Access)Cellular organelles provide opportunities to relate biological mechanisms to disease. Here we use affinity proteomics, genetics and cell biology to interrogate cilia: poorly understood organelles, where defects cause genetic diseases. Two hundred and seventeen tagged human ciliary proteins create a final landscape of 1,319 proteins, 4,905 interactions and 52 complexes. Reverse tagging, repetition of purifications and statistical analyses, produce a high-resolution network that reveals organelle-specific interactions and complexes not apparent in larger studies, and links vesicle transport, the cytoskeleton, signalling and ubiquitination to ciliary signalling and proteostasis. We observe sub-complexes in exocyst and intraflagellar transport complexes, which we validate biochemically, and by probing structurally predicted, disruptive, genetic variants from ciliary disease patients. The landscape suggests other genetic diseases could be ciliary including 3M syndrome. We show that 3M genes are involved in ciliogenesis, and that patient fibroblasts lack cilia. Overall, this organelle-specific targeting strategy shows considerable promise for Systems Medicine

An integrated omics analysis reveals molecular mechanisms that are associated with differences in seed oil content between Glycine max and Brassica napus

Abstract Background: Rapeseed (Brassica napus L.) and soybean (Glycine max L.) seeds are rich in both protein and oil, which are major sources of biofuels and nutrition. Although the difference in seed oil content between soybean (~ 20%) and rapeseed (~ 40%) exists, little is known about its underlying molecular mechanism. Results: An integrated omics analysis was performed in soybean, rapeseed, Arabidopsis (Arabidopsis thaliana L. Heynh), and sesame (Sesamum indicum L.), based on Arabidopsis acyl-lipid metabolism- and carbon metabolism-related genes. As a result, candidate genes and their transcription factors and microRNAs, along with phylogenetic analysis and co-expression network analysis of the PEPC gene family, were found to be largely associated with the difference between the two species. First, three soybean genes (Glyma.13G148600, Glyma.13G207900 and Glyma.12G122900) co-expressed with GmPEPC1 are specifically enriched during seed storage protein accumulation stages, while the expression of BnPEPC1 is putatively inhibited by bna-miR169, and two genes BnSTKA and BnCKII are co-expressed with BnPEPC1 and are specifically associated with plant circadian rhythm, which are related to seed oil biosynthesis. Then, in de novo fatty acid synthesis there are rapeseed-specific genes encoding subunits β-CT (BnaC05g37990D) and BCCP1 (BnaA03g06000D) of heterogeneous ACCase, which could interfere with synthesis rate, and β-CT is positively regulated by four transcription factors (BnaA01g37250D, BnaA02g26190D, BnaC01g01040D and BnaC07g21470D). In triglyceride synthesis, GmLPAAT2 is putatively inhibited by three miRNAs (gma-miR171, gma-miR1516 and gma-miR5775). Finally, in rapeseed there was evidence for the expansion of gene families, CALO, OBO and STERO, related to lipid storage, and the contraction of gene families, LOX, LAH and HSI2, related to oil degradation. Conclusions: The molecular mechanisms associated with differences in seed oil content provide the basis for future breeding efforts to improve seed oil content

Correlated long-range mixed-harmonic fluctuations measured in pp, p+Pb and low-multiplicity Pb+Pb collisions with the ATLAS detector

For abstract see published article

Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC

The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at √s=13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1 fb −1 for the tt ¯ and γ+jet and 36.7 fb −1 −1 for the dijet event topologies

In situ calibration of large-radius jet energy and mass in 13 TeV proton–proton collisions with the ATLAS detector

The response of the ATLAS detector to largeradius jets is measured in situ using 36.2 fb−1 of √s = 13 TeV proton–proton collisions provided by the LHC and recorded by the ATLAS experiment during 2015 and 2016. The jet energy scale is measured in events where the jet recoils against a reference object, which can be either a calibrated photon, a reconstructed Z boson, or a system of well-measured small-radius jets. The jet energy resolution and a calibration of forward jets are derived using dijet balance measurements. The jet mass response is measured with two methods: using mass peaks formed by W bosons and top quarks with large transverse momenta and by comparing the jet mass measured using the energy deposited in the calorimeter with that using the momenta of charged-particle tracks. The transversemomentum and mass responses in simulations are found to be about 2–3% higher than in data. This difference is adjusted for with a correction factor. The results of the different methods are combined to yield a calibration over a large range of transverse momenta (pT). The precision of the relative jet energy scale is 1–2% for 200 GeV < pT < 2 TeV, while that of the mass scale is 2–10%. The ratio of the energy resolutions in data and simulation is measured to a precision of 10–15% over the same pT range