Survival of dental implants in patients with oral cancer treated by surgery and radiotherapy: a retrospective study

BACKGROUND: The aim of this retrospective study was to evaluate the survival of dental implants placed after ablative surgery, in patients affected by oral cancer treated with or without radiotherapy. METHODS: We collected data for 34 subjects (22 females, 12 males; mean age: 51 ± 19) with malignant oral tumors who had been treated with ablative surgery and received dental implant rehabilitation between 2007 and 2012. Postoperative radiation therapy (less than 50 Gy) was delivered before implant placement in 12 patients. A total of 144 titanium implants were placed, at a minimum interval of 12 months, in irradiated and non-irradiated residual bone. RESULTS: Implant loss was dependent on the position and location of the implants (P = 0.05-0.1). Moreover, implant survival was dependent on whether the patient had received radiotherapy. This result was highly statistically significant (P < 0.01). Whether the implant was loaded is another highly significant (P < 0.01) factor determinin

Structure of the TPR Domain of AIP: Lack of Client Protein Interaction with the C-Terminal alpha-7 Helix of the TPR Domain of AIP Is Sufficient for Pituitary Adenoma Predisposition

PMCID: PMC3534021This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Endomicroscopic and transcriptomic analysis of impaired barrier function and malabsorption in environmental enteropathy

Introduction: Environmental enteropathy (EE) is associated with growth failure, micronutrient malabsorption and impaired responses to oral vaccines. We set out to define cellular mechanisms of impaired barrier function in EE and explore protective mechanisms. Methods: We studied 49 adults with environmental enteropathy in Lusaka, Zambia using confocal laser endomicroscopy (CLE); histology, immunohistochemistry and mRNA sequencing of small intestinal biopsies; and correlated these with plasma lipopolysaccharide (LPS) and a zinc uptake test. Results: CLE images (median 134 for each study) showed virtually ubiquitous small intestinal damage. Epithelial defects, imaged by histology and claudin 4 immunostaining, were predominantly seen at the tips of villi and corresponded with leakage imaged in vivo by CLE. In multivariate analysis, circulating log-transformed LPS was correlated with cell shedding events (β = 0.83; P = 0.035) and with serum glucagon-like peptide-2 (β = -0.13; P = 0.007). Zinc uptake from a test dose of 25mg was attenuated in 30/47 (64%) individuals and in multivariate analysis was reduced by HIV, but positively correlated with GLP-2 (β = 2.72; P = 0.03). There was a U-shaped relationship between circulating LPS and villus surface area. Transcriptomic analysis identified 23 differentially expressed genes in severe enteropathy, including protective peptides and proteins. Conclusions: Confocal endomicroscopy, claudin 4 immunostaining and histology identify epithelial defects which are probably sites of bacterial translocation, in the presence of which increased epithelial surface area increases the burden of translocation. GLP 2 and other protective peptides may play an important role in mucosal protection in EE

Fate of Allochthonous Dissolved Organic Carbon in Lakes: A Quantitative Approach

Inputs of dissolved organic carbon (DOC) to lakes derived from the surrounding landscape can be stored, mineralized or passed to downstream ecosystems. The balance among these OC fates depends on a suite of physical, chemical, and biological processes within the lake, as well as the degree of recalcintrance of the allochthonous DOC load. The relative importance of these processes has not been well quantified due to the complex nature of lakes, as well as challenges in scaling DOC degradation experiments under controlled conditions to the whole lake scale. We used a coupled hydrodynamic-water quality model to simulate broad ranges in lake area and DOC, two characteristics important to processing allochthonous carbon through their influences on lake temperature, mixing depth and hydrology. We calibrated the model to four lakes from the North Temperate Lakes Long Term Ecological Research site, and simulated an additional 12 ‘hypothetical’ lakes to fill the gradients in lake size and DOC concentration. For each lake, we tested several mineralization rates (range: 0.001 d−1 to 0.010 d−1) representative of the range found in the literature. We found that mineralization rates at the ecosystem scale were roughly half the values from laboratory experiments, due to relatively cool water temperatures and other lake-specific factors that influence water temperature and hydrologic residence time. Results from simulations indicated that the fate of allochthonous DOC was controlled primarily by the mineralization rate and the hydrologic residence time. Lakes with residence times <1 year exported approximately 60% of the DOC, whereas lakes with residence times >6 years mineralized approximately 60% of the DOC. DOC fate in lakes can be determined with a few relatively easily measured factors, such as lake morphometry, residence time, and temperature, assuming we know the recalcitrance of the DOC

Access Rate to the Emergency Department for Venous Thromboembolism in Relationship with Coarse and Fine Particulate Matter Air Pollution

Particulate matter (PM) air pollution has been associated with cardiovascular and respiratory disease. Recent studies have proposed also a link with venous thromboembolism (VTE) risk. This study was aimed to evaluate the possible influence of air pollution-related changes on the daily flux of patients referring to the Emergency Department (ED) for VTE, dissecting the different effects of coarse and fine PM. From July 1st, 2007, to June 30th, 2009, data about ED accesses for VTE and about daily concentrations of PM air pollution in Verona district (Italy) were collected. Coarse PM (PM10-2.5) was calculated by subtracting the finest PM2.5 from the whole PM10. During the index period a total of 302 accesses for VTE were observed (135 males and 167 females; mean age 68.3±16.7 years). In multiple regression models adjusted for other atmospheric parameters PM10-2.5, but not PM2.5, concentrations were positively correlated with VTE (beta-coefficient = 0.237; P = 0.020). During the days with high levels of PM10-2.5 (≥75th percentile) there was an increased risk of ED accesses for VTE (OR 1.69 with 95%CI 1.13–2.53). By analysing days of exposure using distributed lag non-linear models, the increase of VTE risk was limited to PM10-2.5 peaks in the short-term period. Consistently with these results, in another cohort of subjects without active thrombosis (n = 102) an inverse correlation between PM10-2.5 and prothrombin time was found (R = −0.247; P = 0.012). Our results suggest that short-time exposure to high concentrations of PM10-2.5 may favour an increased rate of ED accesses for VTE through the induction of a prothrombotic state

Terrestrial support of lake food webs: Synthesis reveals controls over cross-ecosystem resource use

Widespread evidence that organic matter exported from terrestrial into aquatic ecosystems supports recipient food webs remains controversial. A pressing question is not only whether high terrestrial support is possible but also what the general conditions are under which it arises. We assemble the largest data set, to date, of the isotopic composition (δ$^{2}$H, δ$^{13}$C, and δ$^{15}$N) of lake zooplankton and the resources at the base of their associated food webs. In total, our data set spans 559 observations across 147 lakes from the boreal to subtropics. By predicting terrestrial resource support from within-lake and catchment-level characteristics, we found that half of all consumer observations that is, the median were composed of at least 42% terrestrially derived material. In general, terrestrial support of zooplankton was greatest in lakes with large physical and hydrological connections to catchments that were rich in aboveground and belowground organic matter. However, some consumers responded less strongly to terrestrial resources where within-lake production was elevated. Our study shows that multiple mechanisms drive widespread cross-ecosystem support of aquatic consumers across Northern Hemisphere lakes and suggests that changes in terrestrial landscapes will influence ecosystem processes well beyond their boundaries.Support to organize the working group that produced this manuscript came from Natural Environment Research Council grant NE/M005968/1. B.W.K. also received travel support from the Natural Sciences and Engineering Research Council of Canada Collaborative Research and Training Experiencein Biodiversity Research at the University of British Columbia. J.K. received funding from the Swedish Research Council (2012–2015, funding number 621-2011-3908). M.L.P. acknowledges funding from the NSF Division of Environmental Biology (grant number 1456151)

Platinum-(IV)-derivative satraplatin induced G2/M cell cycle perturbation via p53-p21(waf1/cip1)-independent pathway in human colorectal cancer cells

Platinum-(IV)-derivative satraplatin represents a new generation of orally available anti-cancer drugs that are under development for the treatment of several cancers. Understanding the mechanisms of cell cycle modulation and apoptosis is necessary to define the mode of action of satraplatin. In this study, we investigate the ability of satraplatin to induce cell cycle perturbation, clonogenicity loss and apoptosis in colorectal cancer (CRC) cells.Platinum-(IV)-derivative satraplatin represents a new generation of orally available anti-cancer drugs that are under development for the treatment of several cancers. Understanding the mechanisms of cell cycle modulation and apoptosis is necessary to define the mode of action of satraplatin. In this study, we investigate the ability of satraplatin to induce cell cycle perturbation, clonogenicity loss and apoptosis in colorectal cancer (CRC) cells

Citizen Science Reveals Unexpected Continental-Scale Evolutionary Change in a Model Organism

Organisms provide some of the most sensitive indicators of climate change and evolutionary responses are becoming apparent in species with short generation times. Large datasets on genetic polymorphism that can provide an historical benchmark against which to test for recent evolutionary responses are very rare, but an exception is found in the brown-lipped banded snail (Cepaea nemoralis). This species is sensitive to its thermal environment and exhibits several polymorphisms of shell colour and banding pattern affecting shell albedo in the majority of populations within its native range in Europe. We tested for evolutionary changes in shell albedo that might have been driven by the warming of the climate in Europe over the last half century by compiling an historical dataset for 6,515 native populations of C. nemoralis and comparing this with new data on nearly 3,000 populations. The new data were sampled mainly in 2009 through the Evolution MegaLab, a citizen science project that engaged thousands of volunteers in 15 countries throughout Europe in the biggest such exercise ever undertaken. A known geographic cline in the frequency of the colour phenotype with the highest albedo (yellow) was shown to have persisted and a difference in colour frequency between woodland and more open habitats was confirmed, but there was no general increase in the frequency of yellow shells. This may have been because snails adapted to a warming climate through behavioural thermoregulation. By contrast, we detected an unexpected decrease in the frequency of Unbanded shells and an increase in the Mid-banded morph. Neither of these evolutionary changes appears to be a direct response to climate change, indicating that the influence of other selective agents, possibly related to changing predation pressure and habitat change with effects on micro-climate

A machine learning pipeline for quantitative phenotype prediction from genotype data

<p>Abstract</p> <p>Background</p> <p>Quantitative phenotypes emerge everywhere in systems biology and biomedicine due to a direct interest for quantitative traits, or to high individual variability that makes hard or impossible to classify samples into distinct categories, often the case with complex common diseases. Machine learning approaches to genotype-phenotype mapping may significantly improve Genome-Wide Association Studies (GWAS) results by explicitly focusing on predictivity and optimal feature selection in a multivariate setting. It is however essential that stringent and well documented Data Analysis Protocols (DAP) are used to control sources of variability and ensure reproducibility of results. We present a genome-to-phenotype pipeline of machine learning modules for quantitative phenotype prediction. The pipeline can be applied for the direct use of whole-genome information in functional studies. As a realistic example, the problem of fitting complex phenotypic traits in heterogeneous stock mice from single nucleotide polymorphims (SNPs) is here considered.</p> <p>Methods</p> <p>The core element in the pipeline is the L1L2 regularization method based on the naïve elastic net. The method gives at the same time a regression model and a dimensionality reduction procedure suitable for correlated features. Model and SNP markers are selected through a DAP originally developed in the MAQC-II collaborative initiative of the U.S. FDA for the identification of clinical biomarkers from microarray data. The L1L2 approach is compared with standard Support Vector Regression (SVR) and with Recursive Jump Monte Carlo Markov Chain (MCMC). Algebraic indicators of stability of partial lists are used for model selection; the final panel of markers is obtained by a procedure at the chromosome scale, termed ’saturation’, to recover SNPs in Linkage Disequilibrium with those selected.</p> <p>Results</p> <p>With respect to both MCMC and SVR, comparable accuracies are obtained by the L1L2 pipeline. Good agreement is also found between SNPs selected by the L1L2 algorithms and candidate loci previously identified by a standard GWAS. The combination of L1L2-based feature selection with a saturation procedure tackles the issue of neglecting highly correlated features that affects many feature selection algorithms.</p> <p>Conclusions</p> <p>The L1L2 pipeline has proven effective in terms of marker selection and prediction accuracy. This study indicates that machine learning techniques may support quantitative phenotype prediction, provided that adequate DAPs are employed to control bias in model selection.</p

Estimated GFR reporting is not sufficient to allow detection of chronic kidney disease in an Italian regional hospital

<p>Abstract</p> <p>Background</p> <p>Chronic kidney disease (CKD) is an emerging worldwide problem. The lack of attention paid to kidney disease is well known and has been described in previous publications. However, little is known about the magnitude of the problem in highly specialized hospitals where serum creatinine values are used to estimate GFR values.</p> <p>Methods</p> <p>We performed a cross-sectional evaluation of hospitalized adult patients who were admitted to the medical or surgical department of Santa Maria della Misericordia Hospital in 2007. Information regarding admissions was derived from a database. Our goal was to assess the prevalence of CKD (defined as an estimated glomerular filtration rate [eGFR] < 60 mL/min/1.73 m²) and detection of CKD using diagnostic codes (Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM]). To reduce the impact of acute renal failure on the study, the last eGFR obtained during hospitalization was the value used for analysis, and intensive care and nephrology unit admissions were excluded. We also excluded patients who had ICD-9-CM codes for renal replacement therapy, acute renal failure, and contrast administration listed as discharge diagnoses.</p> <p>Results</p> <p>Of the 18,412 patients included in the study, 4,748 (25.8%) had reduced eGFRs, falling into the category of Kidney Disease Outcomes Quality Initiative (KDOQI) stage 3 (or higher) CKD. However, the diagnosis of CKD was only reported in 19% of these patients (904/4,748). It is therefore evident that there was a "gray area" corresponding to stage 3 CKD (eGFR 30-59 ml/min), in which most CKD diagnoses are missed. The ICD-9 code sensitivity for detecting CKD was significantly higher in patients with diabetes, hypertension, and cardiovascular disease (26.8%, 22.2%, and 23.7%, respectively) than in subjects without diabetes, hypertension, or cardiovascular disease (p < 0.001), but these values are low when the widely described relationship between such comorbidities and CKD is considered.</p> <p>Conclusion</p> <p>Although CKD was common in this patient population at a large inpatient regional hospital, the low rates of CKD detection emphasize the primary role nephrologists must play in continued medical education, and the need for ongoing efforts to train physicians (particularly primary care providers) regarding eGFR interpretation and systematic screening for CKD in high-risk patients (i.e., the elderly, diabetics, hypertensives, and patients with CV disease).</p