COMPARISON OF BRAIN METABOLITE CHANGES IN MANGANESE-EXPOSED WELDERS AND SMELTERS

poster abstractExcessive manganese (Mn) exposure is known to cause cognitive, psychiatric and motor deficits. Mn overexposure occurs in different occupational settings, where the type and level of exposure may vary. Magnetic resonance imaging (MRI) and spectroscopy (MRS) can be used to evaluate brain Mn accumulation and to measure Mn-induced metabolite changes non-invasively. The aim of this study was to compare metabolite changes among different brain regions of welders and smelters following occupational Mn exposure. Nine Mn-exposed smelters, 14 Mn-exposed welders and 23 male matched controls were recruited from a cohort of workers from two factories in China (mean airborne Mn level: 0.227 and 0.025 mg/m3 for smelters and welders, respectively). Short-echo-time 1H MRS spectra were acquired in each subject from four volumes of interest: the frontal cortex, posterior cingulate cortex, hippocampus, and thalamus. We found that 1) in the frontal cortex, significantly decreased creatine (Cr), glutamate (Glu) and glutathione (GSH) were found in welders, whereas decreased Glu was found in smelters as compared to controls. 2) In the thalamus, reduced myo-inositol was found in both smelters and welders, while Glu and GSH were decreased in welders. These results suggest that Mn-induced brain metabolite changes may be regional in nature and more extensive in welders than in smelters. The frontal cortex seems to show a more profound change than the other brain areas tested among Mn exposed subjects. Further studies are needed to investigate the effects of exposure type and length on the mechanism of Mn neurotoxicity. (Supported by NIH/NIEHS R21 ES-017498, National Science Foundation of China Grant #81072320 and 30760210)

Application of Flux Diverters in High Temperature Superconducting Transformer Windings for AC Loss Reduction

Flux diverters (FDs) are used in High Temperature Superconducting (HTS) transformers for AC loss reduction and flux optimization. In this paper, a 2D axial symmetric superconducting winding model is proposed and two designs of flux diverters are applied to the windings. A homogenization approach is used to analyze the windings with large turn numbers. The key parameters including the number, width, height and the spatial positions of the FDs are adjusted for AC loss and magnetic flux analysis. The means of obtaining optimum designs of the FDs is provided and can be used to develop new winding designs with FDs, which contributes to better electromagnetic performance and higher efficiency of HTS transformers

Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark

Purpose: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase the safety of the operation through context-sensitive warnings and semi-autonomous robotic assistance or improve training of surgeons via data-driven feedback. In surgical workflow analysis up to 91% average precision has been reported for phase recognition on an open data single-center video dataset. In this work we investigated the generalizability of phase recognition algorithms in a multicenter setting including more difficult recognition tasks such as surgical action and surgical skill. Methods: To achieve this goal, a dataset with 33 laparoscopic cholecystectomy videos from three surgical centers with a total operation time of 22 h was created. Labels included framewise annotation of seven surgical phases with 250 phase transitions, 5514 occurences of four surgical actions, 6980 occurences of 21 surgical instruments from seven instrument categories and 495 skill classifications in five skill dimensions. The dataset was used in the 2019 international Endoscopic Vision challenge, sub-challenge for surgical workflow and skill analysis. Here, 12 research teams trained and submitted their machine learning algorithms for recognition of phase, action, instrument and/or skill assessment. Results: F1-scores were achieved for phase recognition between 23.9% and 67.7% (n = 9 teams), for instrument presence detection between 38.5% and 63.8% (n = 8 teams), but for action recognition only between 21.8% and 23.3% (n = 5 teams). The average absolute error for skill assessment was 0.78 (n = 1 team). Conclusion: Surgical workflow and skill analysis are promising technologies to support the surgical team, but there is still room for improvement, as shown by our comparison of machine learning algorithms. This novel HeiChole benchmark can be used for comparable evaluation and validation of future work. In future studies, it is of utmost importance to create more open, high-quality datasets in order to allow the development of artificial intelligence and cognitive robotics in surgery

Nitroaromatic Antibiotics as Nitrogen Oxide Sources

Nitroaromatic antibiotics show activity against anaerobic bacteria and parasites, finding use in the treatment of Heliobacter pylori infections, tuberculosis, trichomoniasis, human African trypanosomiasis, Chagas disease and leishmaniasis. Despite this activity and a clear need for the development of new treatments for these conditions, the associated toxicity and lack of clear mechanisms of action have limited their therapeutic development. Nitroaromatic antibiotics require reductive bioactivation for activity and this reductive metabolism can convert the nitro group to nitric oxide (NO) or a related reactive nitrogen species (RNS). As nitric oxide plays important roles in the defensive immune response to bacterial infection through both signaling and redox-mediated pathways, defining controlled NO generation pathways from these antibiotics would allow the design of new therapeutics. This review focuses on the release of nitrogen oxide species from various nitroaromatic antibiotics to portend the increased ability for these compounds to positively impact infectious disease treatment

N-doped TiO2 Nanotubes as an Effective Additive to Improve the Catalytic Capability of Methanol Oxidation for Pt/Graphene Nanocomposites

N-doped TiO2 nanotubes have been prepared as additives to improve the catalytic capability of Pt/graphene composites in methanol oxidation reactions. Electrochemical experiments show that the catalytic performance of Pt/graphene composites has been greatly improved by the introduction of N-doped TiO2 nanotubes

NEDD4 and NEDD4L: Ubiquitin Ligases Closely Related to Digestive Diseases

Protein ubiquitination is an enzymatic cascade reaction and serves as an important protein post-translational modification (PTM) that is involved in the vast majority of cellular life activities. The key enzyme in the ubiquitination process is E3 ubiquitin ligase (E3), which catalyzes the binding of ubiquitin (Ub) to the protein substrate and influences substrate specificity. In recent years, the relationship between the subfamily of neuron-expressed developmental downregulation 4 (NEDD4), which belongs to the E3 ligase system, and digestive diseases has drawn widespread attention. Numerous studies have shown that NEDD4 and NEDD4L of the NEDD4 family can regulate the digestive function, as well as a series of related physiological and pathological processes, by controlling the subsequent degradation of proteins such as PTEN, c-Myc, and P21, along with substrate ubiquitination. In this article, we reviewed the appropriate functions of NEDD4 and NEDD4L in digestive diseases including cell proliferation, invasion, metastasis, chemotherapeutic drug resistance, and multiple signaling pathways, based on the currently available research evidence for the purpose of providing new ideas for the prevention and treatment of digestive diseases

Para-Substituted O-Benzyl Sulfohydroxamic Acid Derivatives as Redox-Triggered Nitroxyl (HNO) Sources

Nitroxyl shows a unique biological profile compared to the gasotransmitters nitric oxide and hydrogen sulfide. Nitroxyl reacts with thiols as an electrophile, and this redox chemistry mediates much of its biological chemistry. This reactivity necessitates the use of donors to study nitroxyl’s chemistry and biology. The preparation and evaluation of a small library of new redox-triggered nitroxyl sources is described. The condensation of sulfonyl chlorides and properly substituted O-benzyl hydroxylamines produced O-benzyl-substituted sulfohydroxamic acid derivatives with a 27–79% yield and with good purity. These compounds were designed to produce nitroxyl through a 1, 6 elimination upon oxidation or reduction via a Piloty’s acid derivative. Gas chromatographic headspace analysis of nitrous oxide, the dimerization and dehydration product of nitroxyl, provides evidence for nitroxyl formation. The reduction of derivatives containing nitro and azide groups generated nitrous oxide with a 25–92% yield, providing evidence of nitroxyl formation. The oxidation of a boronate-containing derivative produced nitrous oxide with a 23% yield. These results support the proposed mechanism of nitroxyl formation upon reduction/oxidation via a 1, 6 elimination and Piloty’s acid. These compounds hold promise as tools for understanding nitroxyl’s role in redox biology

Analysis of the Effectiveness of Urban Land-Use-Change Models Based on the Measurement of Spatio-Temporal, Dynamic Urban Growth: A Cellular Automata Case Study

Developing countries have been undergoing dramatic urban growth over the past three decades. It is essential to understand and simulate the urban growth process for smart urban planning and sustainable development purposes. Cellular automata (CA) modeling is an efficient approach to simulating urban land use/cover change; however, the traditional CA method has limitations in simulating the various urban growth patterns and processes. This study aims to analyze the influences of different urban growth characteristics on the effectiveness of CA modeling by conducting a case study over the area in the Pearl River Delta of Southern China. We used the growth rate, landscape expansion index, and spatial dependency to quantify the urban growth characteristics. The effectiveness of CA modeling was measured through a comparison of the simulation results with the reference data. The simulation results and validation analyses reveal that the traditional CA is not applicable for the following three situations: (1) the urban growth pattern characterized by less growth area or a higher ratio of outlying expansion; (2) the urban region that includes several subregions with disparate growth characteristics; and (3) the existence of temporal differences in growth characteristics over a long period