The Helicobacter pylori duodenal ulcer promoting gene, dupA in China

<p>Abstract</p> <p>Background</p> <p>The prevalence of <it>H. pylori </it>is as high as 60–70% in Chinese population. Although duodenal ulcer and gastric cancer are both caused by <it>H. pylori</it>, they are at opposite ends of the spectrum and as such are considered mutually exclusive. Duodenal ulcer promoting (<it>dupA</it>) gene was reported to be associated with duodenal ulcer development. The aim of this study was to determine the prevalence of <it>dupA </it>gene of <it>Helicobacter pylori </it>in patients with various gastroduodenal diseases and to explore the association between the gene and other virulence factors.</p> <p>Methods</p> <p><it>H. pylori </it>were isolated from gastric biopsies of patients with chronic gastritis, duodenal ulcer (DU), gastric ulcer (GU), or non-cardia gastric carcinoma. The <it>dupA</it>, <it>cagA</it>, <it>vacA</it>, <it>iceA </it>and <it>babA2 </it>genotypes were determined by polymerase chain reaction. Histological features of gastric mucosal biopsy specimens were graded based on the scoring system proposed by the updated Sydney system. IL-1β polymorphism was investigated using restriction fragment length polymorphism.</p> <p>Results</p> <p>Isolates from 360 patients including 133 with chronic gastritis, 101 with DU, 47 with GU, and 79 with non-cardia gastric carcinoma were examined. The <it>dupA </it>gene was detected in 35.3% (127/360) and the prevalence DU patients was significantly greater than that in gastric cancer or GU patients (45.5% vs. 24.1% and 23.4%, <it>P </it>< 0.05). Patients infected with <it>dupA</it>-positive strains had higher scores for chronic inflammation compared to those with <it>dupA</it>-negative strains (2.36 vs. 2.24, p = 0.058). The presence of <it>dupA </it>was not associated with the <it>cagA</it>, <it>vacA, iceA </it>and <it>babA 2 </it>genotypes or with IL-1β polymorphisms.</p> <p>Conclusion</p> <p>In China the prevalence of <it>dupA </it>gene was highest in DU and inversely related to GU and gastric cancer.</p

Oxidative Stress-Related Mechanisms and Antioxidant Therapy in Diabetic Retinopathy

Diabetic retinopathy (DR) is one of the most common microvascular complications of diabetes and is the leading cause of blindness in young adults. Oxidative stress has been implicated as a critical cause of DR. Metabolic abnormalities induced by high-glucose levels are involved in the development of DR and appear to be influenced by oxidative stress. The imbalance between reactive oxygen species (ROS) production and the antioxidant defense system activates several oxidative stress-related mechanisms that promote the pathogenesis of DR. The damage caused by oxidative stress persists for a considerable time, even after the blood glucose concentration has returned to a normal level. Animal experiments have proved that the use of antioxidants is a beneficial therapeutic strategy for the treatment of DR, but more data are required from clinical trials. The aims of this review are to highlight the improvements to our understanding of the oxidative stress-related mechanisms underlying the development of DR and provide a summary of the main antioxidant therapy strategies used to treat the disease

Intrinsic and Extrinsic Performance Limits of Graphene Devices on SiO2

The linear dispersion relation in graphene[1,2] gives rise to a surprising prediction: the resistivity due to isotropic scatterers (e.g. white-noise disorder[3] or phonons[4-8]) is independent of carrier density n. Here we show that acoustic phonon scattering[4-6] is indeed independent of n, and places an intrinsic limit on the resistivity in graphene of only 30 Ohm at room temperature (RT). At a technologically-relevant carrier density of 10^12 cm^-2, the mean free path for electron-acoustic phonon scattering is >2 microns, and the intrinsic mobility limit is 2x10^5 cm^2/Vs, exceeding the highest known inorganic semiconductor (InSb, ~7.7x10^4 cm^2/Vs[9]) and semiconducting carbon nanotubes (~1x10^5 cm^2/Vs[10]). We also show that extrinsic scattering by surface phonons of the SiO2 substrate[11,12] adds a strong temperature dependent resistivity above ~200 K[8], limiting the RT mobility to ~4x10^4 cm^2/Vs, pointing out the importance of substrate choice for graphene devices[13].Comment: 16 pages, 3 figure

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Effects of adsorbates on the electronic properties of graphene

Graphene, an atom-thick sheet of carbon, is a novel two-dimensional material in which the low-energy electrons behave as massless Dirac fermions. This thesis explores the effects of adsorbates on the electronic properties graphene by adsorption in controlled environment in ultra-high vacuum (UHV), coupled with in situ measurement of transport properties. Two types of adsorbates on graphene are investigated. First, the effects of charged impurity scattering are studied by controlled adsorption of potassium on bilayer graphene at low temperature in UHV. The results indicate that the magnitude of charged-impurity scattering in bilayer graphene is similar to that in single layer graphene, and in good agreement with theory. The widely observed lower mobility in bilayer graphene on SiO2 is likely due to another source of disorder. Second, the dielectric screening of bilayer graphene is modified by deposition of ice overlayers at low temperature in UHV. No screening effect is observed in pristine bilayer graphene. However, ice overlayers significantly increase the mobility of potassium-doped bilayer graphene through screening of potassium ions. Together, the ice deposition experiments demonstrate the existence of screening effect in bilayer graphene and support that charge impurities are not the dominant scatters in pristine bilayer graphene on SiO2. The screening of adsorbed potassium ions on single-layer graphene is also investigated both experimentally and theoretically. The increase in mobility upon ice deposition is much larger than expected assuming ice's bulk relative dielectric constant of 3.2. A simple model assuming stronger local screening near potassium ions is proposed which can explain the experimental observations. Temperature-dependent studies of electronic transport in the system of coadsorbed potassium and ice show that graphene's resistivity is sensitive to phase transitions in overlayers as well as desorption, opening new opportunities to study surface phases with electronic measurements

Side Scan Sonar Shipwreck Image Recognition Algorithm based on Transfer Learning and Deep Learning

Current underwater shipwreck side scan sonar samples are few and difficult to label. With small sample sizes, their image recognition accuracy with a convolutional neural network model is low. In this study, we proposed an image recognition method for shipwreck side scan sonar that combines transfer learning with deep learning. In the non-transfer learning, shipwreck sonar sample data were used to train the network, and the results were saved as the control group. The weakly correlated data were applied to train the network, then the network parameters were transferred to the new network, and then the shipwreck sonar data was used for training. These steps were repeated using strongly correlated data. Experiments were carried out on Lenet-5, AlexNet, GoogLeNet, ResNet and VGG networks. Without transfer learning, the highest accuracy was obtained on the ResNet network (86.27%). Using weakly correlated data for transfer training, the highest accuracy was on the VGG network (92.16%). Using strongly correlated data for transfer training, the highest accuracy was also on the VGG network (98.04%). In all network architectures, transfer learning improved the correct recognition rate of convolutional neural network models. Experiments show that transfer learning combined with deep learning improves the accuracy and generalization of the convolutional neural network in the case of small sample sizes

Predictive modeling based on tumor spectral CT parameters and clinical features for postoperative complications in patients undergoing colon resection for cancer

Abstract Background Colon cancer is a particularly prevalent malignancy that produces postoperative complications (POCs). However, limited imaging modality exists on the accurate diagnosis of POCs. The purpose of this study was therefore to construct a model combining tumor spectral CT parameters and clinical features to predict POCs before surgery in colon cancer. Methods This retrospective study included 85 patients who had preoperative abdominal spectral CT scans and underwent radical colon cancer resection at our institution. The patients were divided into two groups based on the absence (no complication/grade I) or presence (grades II–V) of POCs according to the Clavien-Dindo grading system. The visceral fat areas (VFA) of patients were semi-automatically outlined and calculated on L3-level CT images using ImageJ software. Clinical features and tumor spectral CT parameters were statistically compared between the two groups. A combined model of spectral CT parameters and clinical features was established by stepwise regression to predict POCs in colon cancer. The diagnostic performance of the model was evaluated using the receiver operating characteristic (ROC) curve, including area under the curve (AUC), sensitivity, and specificity. Results Twenty-seven patients with POCs and 58 patients without POCs were included in this study. MonoE40keV-VP and VFA were independent predictors of POCs. The combined model based on predictors yielded an AUC of 0.84 (95% CI: 0.74–0.91), with a sensitivity of 77.8% and specificity of 87.9%. Conclusions The model combining MonoE40keV-VP and VFA can predict POCs before surgery in colon cancer and provide a basis for individualized management plans. Critical relevance statement The model combining MonoE40keV-VP and visceral fat area can predict postoperative complications before surgery in colon cancer and provide a basis for individualized management plans. Key points • Visceral fat area and MonoE40keV-VP were independent predictors of postoperative complications in colon cancer. • The combined model yielded a high AUC, sensitivity, and specificity in predicting postoperative complications. • The combined model was superior to the single visceral fat area or MonoE40keV-VP in predicting postoperative complications. Graphical Abstrac