792 research outputs found
Methyl methanesulfonate (MMS) produces heat-labile DNA damage but no detectable in vivo DNA double-strand breaks
Homologous recombination (HR) deficient cells are sensitive to methyl methanesulfonate (MMS). HR is usually involved in the repair of DNA double-strand breaks (DSBs) in Saccharomyces cerevisiae implying that MMS somehow induces DSBs in vivo. Indeed there is evidence, based on pulsed-field gel electrophoresis (PFGE), that MMS causes DNA fragmentation. However, the mechanism through which MMS induces DSBs has not been demonstrated. Here, we show that DNA fragmentation following MMS treatment, and detected by PFGE is not the consequence of production of cellular DSBs. Instead, DSBs seen following MMS treatment are produced during sample preparation where heat-labile methylated DNA is converted into DSBs. Furthermore, we show that the repair of MMS-induced heat-labile damage requires the base excision repair protein XRCC1, and is independent of HR in both S.cerevisiae and mammalian cells. We speculate that the reason for recombination-deficient cells being sensitive to MMS is due to the role of HR in repair of MMS-induced stalled replication forks, rather than for repair of cellular DSBs or heat-labile damage
The association of early post-transplant glucose levels with long-term mortality
Aims/objective: We aimed to assess the long-term effects of post-transplant glycaemia on long-term survival after renal transplantation.
Methods: Study participants were 1,410 consecutive transplant recipients without known diabetes who underwent an OGTT 10 weeks post-transplant and were observed for a median of 6.7 years (range 0.3–13.8 years). The HRs adjusted for age, sex, traditional risk factors and transplant-related risk factors were estimated.
Results: Each 1 mmol/l increase in fasting plasma glucose (fPG) or 2 h plasma glucose (2hPG) was associated with 11% (95% CI −1%, 24%) and 5% (1%, 9%) increments in all-cause mortality risk and 19% (1%, 39%) and 6% (1%, 12%) increments in cardiovascular (CV) mortality risk, respectively. Including both fPG and 2hPG in the multi-adjusted model the HR for 2hPG remained unchanged, while the HR for fPG was attenuated (1.05 [1.00, 1.11] and 0.97 [0.84, 1.14]). Compared with recipients with normal glucose tolerance, patients with post-transplant diabetes mellitus had higher all-cause and CV mortality (1.54 [1.09, 2.17] and 1.80 [1.10, 2.96]), while patients with impaired glucose tolerance (IGT) had higher all-cause, but not CV mortality (1.39 [1.01, 1.91] and 1.04 [0.62, 1.74]). Conversely, impaired fasting glucose was not associated with increased all-cause or CV mortality (0.79 [0.52, 1.23] and 0.76 [0.39, 1.49]). Post-challenge hyperglycaemia predicted death from any cause and infectious disease in the multivariable analyses (1.49 [1.15, 1.95] and 1.91 [1.09, 3.33]).
Conclusions/interpretation: For predicting all-cause and CV mortality, 2hPG is superior to fPG after renal transplantation. Also, early post-transplant diabetes, IGT and post-challenge hyperglycaemia were significant predictors of death. Future studies should determine whether an OGTT helps identify renal transplant recipients at increased risk of premature death.
© The Author(s) 2011. This article is published with open access at Springerlink.co
Beta cell function after weight loss: a clinical trial comparing gastric bypass surgery and intensive lifestyle intervention
The effects of various weight loss strategies on pancreatic beta cell function remain unclear. We aimed to compare the effect of intensive lifestyle intervention (ILI) and Roux-en-Y gastric bypass surgery (RYGB) on beta cell function. Design One year controlled clinical trial (ClinicalTrials.gov identifier NCT00273104). One hundred and nineteen morbidly obese participants without known diabetes from the MOBIL study (mean (s.d.) age 43.6 (10.8) years, body mass index (BMI) 45.5 (5.6) kg/m2, 84 women) were allocated to RYGB (n=64) or ILI (n=55). The patients underwent repeated oral glucose tolerance tests (OGTTs) and were categorised as having either normal (NGT) or abnormal glucose tolerance (AGT). Twenty-nine normal-weight subjects with NGT (age 42.6 (8.7) years, BMI 22.6 (1.5) kg/m2, 19 women) served as controls. OGTT-based indices of beta cell function were calculated. One year weight reduction was 30 % (8) after RYGB and 9 % (10) after ILI (P<0.001). Disposition index (DI) increased in all treatment groups (all P<0.05), although more in the surgery groups (both P<0.001). Stimulated proinsulin-to-insulin (PI/I) ratio decreased in both surgery groups (both P<0.001), but to a greater extent in the surgery group with AGT at baseline (P<0.001). Post surgery, patients with NGT at baseline had higher DI and lower stimulated PI/I ratio than controls (both P<0.027). Gastric bypass surgery improved beta cell function to a significantly greater extent than ILI. Supra-physiological insulin secretion and proinsulin processing may indicate excessive beta cell function after gastric bypass surgery
Der Anstieg von Cholecystokinin im Plasma während eines durch Escherichia-coli-Endotoxin induzierten Schocks beim Schwein
Investigation of diode-pumped 2.8-µm laser performance in Er:BaY2F8
Laser operation at 2.8 mm in BaY2F8 with erbium concentrations of 7.5% and 20% is investigated under laser-diode pumping at 967 nm. Output powers as high as 250 mW and slope efficiencies as high as 24% are obtained. Results are comparable with those of Er3+:LiYF4 under the same pump conditions. Slope efficiencies above 30% are predicted for optimized erbium concentrations
Parathyroid hormone, but not vitamin D, is associated with the metabolic syndrome in morbidly obese women and men: a cross-sectional study
<p>Abstract</p> <p>Background</p> <p>The prevalence of vitamin D insufficiency and secondary hyperparathyroidism is high among morbidly obese subjects. Further, low serum levels of 25-hydroxyvitamin D (25 [OH]D) and magnesium have been associated with increased risk of the metabolic syndrome (MS), and recently, a possible link between PTH and MS has been reported. Although it is well known that the synthesis and secretion of PTH is regulated by serum levels of calcium, phosphate, magnesium and 25(OH)D, less is known about the possible clustered affiliation of these parameters with MS. We aimed to explore whether MS is associated with abnormal serum levels of PTH, 25(OH)D and magnesium in a population of morbidly obese patients.</p> <p>Methods</p> <p>Fasting serum levels of 25(OH)D, PTH and magnesium were assessed in a cross-sectional cohort study of 1,017 consecutive morbidly obese patients (68% women). Multiple logistic regression analyses were used to assess the independent effect of PTH, 25(OH)D and magnesium on the odds for MS (National Cholesterol Education Program [NCEP]) after adjustment for confounding factors.</p> <p>Results</p> <p>Sixty-eight percent of the patients had MS. Patients with MS had lower mean serum magnesium (P < 0.001) and higher mean PTH (P = 0.067) than patients without MS, whereas mean 25(OH)D did not differ significantly. Patients with PTH levels in the second to fourth quartiles had higher odds of prevalent MS (odds ratio 1.47 [95% CI 0.92–2.35], 2.33 [95% CI 1.40–3.87] and 2.09 [95% CI 1.23–3.56], respectively), after adjustment for 25(OH)D, magnesium, calcium, phosphate, creatinine, age, gender, season of serum sampling, BMI, current smoking, albuminuria, CRP, insulin resistance and type 2 diabetes. Further, PTH was significantly correlated with systolic and diastolic pressure (both P < 0.001), but not with the other components of MS. The levels of 25(OH)D and magnesium were not associated with MS in the multivariate model.</p> <p>Conclusion</p> <p>The PTH level, but not the vitamin D level, is an independent predictor of MS in treatment seeking morbidly obese Caucasian women and men. Randomized controlled clinical trials, including different therapeutic strategies to lower PTH, e.g. calcium/vitamin D supplementation and weight reduction, are necessary to explore any cause-and-effect relationship.</p
Deep Image Translation with an Affinity-Based Change Prior for Unsupervised Multimodal Change Detection
Image translation with convolutional neural networks has recently been used as an approach to multimodal change detection. Existing approaches train the networks by exploiting supervised information of the change areas, which, however, is not always available. A main challenge in the unsupervised problem setting is to avoid that change pixels affect the learning of the translation function. We propose two new network architectures trained with loss functions weighted by priors that reduce the impact of change pixels on the learning objective. The change prior is derived in an unsupervised fashion from relational pixel information captured by domain-specific affinity matrices. Specifically, we use the vertex degrees associated with an absolute affinity difference matrix and demonstrate their utility in combination with cycle consistency and adversarial training. The proposed neural networks are compared with the state-of-the-art algorithms. Experiments conducted on three real data sets show the effectiveness of our methodology
Code-Aligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images
Image translation with convolutional autoencoders has recently been used as an approach to multimodal change detection (CD) in bitemporal satellite images. A main challenge is the alignment of the code spaces by reducing the contribution of change pixels to the learning of the translation function. Many existing approaches train the networks by exploiting supervised information of the change areas, which, however, is not always available. We propose to extract relational pixel information captured by domain-specific affinity matrices at the input and use this to enforce alignment of the code spaces and reduce the impact of change pixels on the learning objective. A change prior is derived in an unsupervised fashion from pixel pair affinities that are comparable across domains. To achieve code space alignment, we enforce pixels with similar affinity relations in the input domains to be correlated also in code space. We demonstrate the utility of this procedure in combination with cycle consistency. The proposed approach is compared with the state-of-the-art machine learning and deep learning algorithms. Experiments conducted on four real and representative datasets show the effectiveness of our methodology
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