Retention of Root Canal Posts: Effect of Cement Film Thickness, Luting Cement, and Post Pretreatment.

The aim of this study was to investigate the effect of the cement film thickness of a zinc phosphate or a resin cement on retention of untreated and pretreated root canal posts. Prefabricated zirconia posts (CosmoPost: 1.4 mm) and two types of luting cements (a zinc phosphate cement [DeTrey Zinc] and a self-etch adhesive resin cement [Panavia F2.0]) were used. After removal of the crowns of 360 extracted premolars, canines, or incisors, the root canals were prepared with a parallel-sided drill system to three different final diameters. Half the posts did not receive any pretreatment. The other half received tribochemical silicate coating according to the manufacturer's instructions. Posts were then luted in the prepared root canals (n=30 per group). Following water storage at 37°C for seven days, retention of the posts was determined by the pull-out method. Irrespective of the luting cement, pretreatment with tribochemical silicate coating significantly increased retention of the posts. Increased cement film thickness resulted in decreased retention of untreated posts and of pretreated posts luted with zinc phosphate cement. Increased cement film thickness had no influence on retention of pretreated posts luted with resin cement. Thus, retention of the posts was influenced by the type of luting cement, by the cement film thickness, and by the post pretreatment.

Bond Strength of Resin Composite to Dentin with Different Adhesive Systems: Influence of Relative Humidity and Application Time.

PURPOSE To investigate the influence of relative humidity and application time on bond strength to dentin of different classes of adhesive systems. MATERIALS AND METHODS A total of 360 extracted human molars were ground to mid-coronal dentin. The dentin specimens were treated with one of six adhesive systems (Syntac Classic, OptiBond FL, Clearfil SE Bond, AdheSE, Xeno Select, or Scotchbond Universal), and resin composite (Filtek Z250) was applied to the treated dentin surface under four experimental conditions (45% relative humidity/application time according to manufacturers' instructions; 45% relative humidity/reduced application time; 85% relative humidity/application time according to manufacturers' instructions; 85% relative humidity/reduced application time). After storage (37°C, 100% humidity, 24 h), shear bond strength (SBS) was measured and data analyzed with nonparametric ANOVA followed by Kruskal-Wallis tests and Mann-Whitney U-tests with Bonferroni-Holm correction for multiple testing (level of significance: α = 0.05). RESULTS Increased relative humidity and reduced application time had no effect on SBS for Clearfil SE Bond and Scotchbond Universal (p = 1.00). For Syntac Classic, OptiBond FL, AdheSE, and Xeno Select there was no effect on SBS of reduced application time of the adhesive system (p ≥ 0.403). However, increased relative humidity significantly reduced SBS for Syntac Classic, OptiBond FL, and Xeno Select irrespective of application time (p ≤ 0.003), whereas for AdheSE, increased relative humidity significantly reduced SBS at recommended application time only (p = 0.002). CONCLUSION Generally, increased relative humidity had a detrimental effect on SBS to dentin, but reduced application time had no effect.

Prophylactic antibiotics or G(M)-CSF for the prevention of infections and improvement of survival in cancer patients receiving myelotoxic chemotherapy.

BACKGROUND Febrile neutropenia (FN) and other infectious complications are some of the most serious treatment-related toxicities of chemotherapy for cancer, with a mortality rate of 2% to 21%. The two main types of prophylactic regimens are granulocyte (macrophage) colony-stimulating factors (G(M)-CSF) and antibiotics, frequently quinolones or cotrimoxazole. Current guidelines recommend the use of colony-stimulating factors when the risk of febrile neutropenia is above 20%, but they do not mention the use of antibiotics. However, both regimens have been shown to reduce the incidence of infections. Since no systematic review has compared the two regimens, a systematic review was undertaken. OBJECTIVES To compare the efficacy and safety of G(M)-CSF compared to antibiotics in cancer patients receiving myelotoxic chemotherapy. SEARCH METHODS We searched The Cochrane Library, MEDLINE, EMBASE, databases of ongoing trials, and conference proceedings of the American Society of Clinical Oncology and the American Society of Hematology (1980 to December 2015). We planned to include both full-text and abstract publications. Two review authors independently screened search results. SELECTION CRITERIA We included randomised controlled trials (RCTs) comparing prophylaxis with G(M)-CSF versus antibiotics for the prevention of infection in cancer patients of all ages receiving chemotherapy. All study arms had to receive identical chemotherapy regimes and other supportive care. We included full-text, abstracts, and unpublished data if sufficient information on study design, participant characteristics, interventions and outcomes was available. We excluded cross-over trials, quasi-randomised trials and post-hoc retrospective trials. DATA COLLECTION AND ANALYSIS Two review authors independently screened the results of the search strategies, extracted data, assessed risk of bias, and analysed data according to standard Cochrane methods. We did final interpretation together with an experienced clinician. MAIN RESULTS In this updated review, we included no new randomised controlled trials. We included two trials in the review, one with 40 breast cancer patients receiving high-dose chemotherapy and G-CSF compared to antibiotics, a second one evaluating 155 patients with small-cell lung cancer receiving GM-CSF or antibiotics.We judge the overall risk of bias as high in the G-CSF trial, as neither patients nor physicians were blinded and not all included patients were analysed as randomised (7 out of 40 patients). We considered the overall risk of bias in the GM-CSF to be moderate, because of the risk of performance bias (neither patients nor personnel were blinded), but low risk of selection and attrition bias.For the trial comparing G-CSF to antibiotics, all cause mortality was not reported. There was no evidence of a difference for infection-related mortality, with zero events in each arm. Microbiologically or clinically documented infections, severe infections, quality of life, and adverse events were not reported. There was no evidence of a difference in frequency of febrile neutropenia (risk ratio (RR) 1.22; 95% confidence interval (CI) 0.53 to 2.84). The quality of the evidence for the two reported outcomes, infection-related mortality and frequency of febrile neutropenia, was very low, due to the low number of patients evaluated (high imprecision) and the high risk of bias.There was no evidence of a difference in terms of median survival time in the trial comparing GM-CSF and antibiotics. Two-year survival times were 6% (0 to 12%) in both arms (high imprecision, low quality of evidence). There were four toxic deaths in the GM-CSF arm and three in the antibiotics arm (3.8%), without evidence of a difference (RR 1.32; 95% CI 0.30 to 5.69; P = 0.71; low quality of evidence). There were 28% grade III or IV infections in the GM-CSF arm and 18% in the antibiotics arm, without any evidence of a difference (RR 1.55; 95% CI 0.86 to 2.80; P = 0.15, low quality of evidence). There were 5 episodes out of 360 cycles of grade IV infections in the GM-CSF arm and 3 episodes out of 334 cycles in the cotrimoxazole arm (0.8%), with no evidence of a difference (RR 1.55; 95% CI 0.37 to 6.42; P = 0.55; low quality of evidence). There was no significant difference between the two arms for non-haematological toxicities like diarrhoea, stomatitis, infections, neurologic, respiratory, or cardiac adverse events. Grade III and IV thrombopenia occurred significantly more frequently in the GM-CSF arm (60.8%) compared to the antibiotics arm (28.9%); (RR 2.10; 95% CI 1.41 to 3.12; P = 0.0002; low quality of evidence). Neither infection-related mortality, incidence of febrile neutropenia, nor quality of life were reported in this trial. AUTHORS' CONCLUSIONS As we only found two small trials with 195 patients altogether, no conclusion for clinical practice is possible. More trials are necessary to assess the benefits and harms of G(M)-CSF compared to antibiotics for infection prevention in cancer patients receiving chemotherapy.

Travellers returning ill from the tropics – a descriptive retrospective study

nternational travel continues to increase in frequency. Health care providers need a wide understanding of the spectrum of travel related diseases and their management. This retrospective study analyses the demographic and clinical data of 360 travellers returning from the tropics presenting to an outpatient clinic at a tertiary hospital between 2003 - 2007. The aim of this study was to analyse the frequency of presenting symptoms and diseases in ill returning travellers and to correlate them to the areas visited and the duration and purpose of travel. The main symptoms during travel were diarrhoea (n = 200, 56 %) and fever (n = 124, 34 %). Travellers not visiting friends and relatives but with close contact to the local population were at more than two-fold increased risk of diarrhoea (Odds Ratio [OR] 2.5; 95 % confidence interval [CI] 1.1-6.0, p = 0.03) and fever (OR 2.4; 95 % CI 1.1-5.3; p = 0.02) compared to tourist travellers. Travellers visiting friends and relatives (VFR) were not at increased risk for diarrhoea (OR 0.6; 95 % CI 0.3-1.3; p = 0.17), or fever (OR 1.5; 95 % CI 0.7-3.4; p = 0.28). Thirty-two percent of all travellers (n = 115) were diagnosed with a specific pathogen. Malaria (6 %), giardiasis (6 %) and amebiasis (4 %) were the most frequently detected pathogens. The odds of malaria as a cause of the presenting illness was lower among travellers reporting pre-travel advice. Specific antimicrobial treatment was required in around one third of the patients.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Generalized eMC implementation for Monte Carlo dose calculation of electron beams from different machine types

The electron Monte Carlo (eMC) dose calculation algorithm available in the Eclipse treatment planning system (Varian Medical Systems) is based on the macro MC method and uses a beam model applicable to Varian linear accelerators. This leads to limitations in accuracy if eMC is applied to non-Varian machines. In this work eMC is generalized to also allow accurate dose calculations for electron beams from Elekta and Siemens accelerators. First, changes made in the previous study to use eMC for low electron beam energies of Varian accelerators are applied. Then, a generalized beam model is developed using a main electron source and a main photon source representing electrons and photons from the scattering foil, respectively, an edge source of electrons, a transmission source of photons and a line source of electrons and photons representing the particles from the scrapers or inserts and head scatter radiation. Regarding the macro MC dose calculation algorithm, the transport code of the secondary particles is improved. The macro MC dose calculations are validated with corresponding dose calculations using EGSnrc in homogeneous and inhomogeneous phantoms. The validation of the generalized eMC is carried out by comparing calculated and measured dose distributions in water for Varian, Elekta and Siemens machines for a variety of beam energies, applicator sizes and SSDs. The comparisons are performed in units of cGy per MU. Overall, a general agreement between calculated and measured dose distributions for all machine types and all combinations of parameters investigated is found to be within 2% or 2 mm. The results of the dose comparisons suggest that the generalized eMC is now suitable to calculate dose distributions for Varian, Elekta and Siemens linear accelerators with sufficient accuracy in the range of the investigated combinations of beam energies, applicator sizes and SSDs.

Radiation metabolomics. 3. Biomarker discovery in the urine of gamma-irradiated rats using a simplified metabolomics protocol of gas chromatography-mass spectrometry combined with random forests machine learning algorithm

Abstract Radiation metabolomics employing mass spectral technologies represents a plausible means of high-throughput minimally invasive radiation biodosimetry. A simplified metabolomics protocol is described that employs ubiquitous gas chromatography-mass spectrometry and open source software including random forests machine learning algorithm to uncover latent biomarkers of 3 Gy gamma radiation in rats. Urine was collected from six male Wistar rats and six sham-irradiated controls for 7 days, 4 prior to irradiation and 3 after irradiation. Water and food consumption, urine volume, body weight, and sodium, potassium, calcium, chloride, phosphate and urea excretion showed major effects from exposure to gamma radiation. The metabolomics protocol uncovered several urinary metabolites that were significantly up-regulated (glyoxylate, threonate, thymine, uracil, p-cresol) and down-regulated (citrate, 2-oxoglutarate, adipate, pimelate, suberate, azelaate) as a result of radiation exposure. Thymine and uracil were shown to derive largely from thymidine and 2'-deoxyuridine, which are known radiation biomarkers in the mouse. The radiation metabolomic phenotype in rats appeared to derive from oxidative stress and effects on kidney function. Gas chromatography-mass spectrometry is a promising platform on which to develop the field of radiation metabolomics further and to assist in the design of instrumentation for use in detecting biological consequences of environmental radiation release.

Fast Prediction of Femoral Biomechanics Using Supervised Machine Learning and Statistical Shape Modeling

Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.