Modified Galacto- or Fuco-Clusters Exploiting the Siderophore Pathway to Inhibit the LecA- or LecB-Associated Virulence of Pseudomonas aeruginosa

Galacto- and fuco-clusters conjugated with one to three catechol or hydroxamate motifs were synthesised to target LecA and LecB lectins of Pseudomonas aeruginosa (PA) localised in the outer membrane and inside the bacterium. The resulting glycocluster–pseudosiderophore conjugates were evaluated as Trojan horses to cross the outer membrane of PA by iron transport. The data suggest that glycoclusters with catechol moieties are able to hijack the iron transport, whereas those with hydroxamates showed strong nonspecific interactions. Mono- and tricatechol galactoclusters ( G1C and G3C ) were evaluated as inhibitors of infection by PA in comparison with the free galactocluster ( G0 ). All of them exhibited an inhibitory effect between 46 to 75 % at 100 μM, with a higher potency than G0 . This result shows that LecA localised in the outer membrane of PA is involved in the infection mechanism.     

R2D2: A scalable deep learning toolkit for medical imaging segmentation

Deep learning has gained a significant popularity in recent years thanks to its tremendous success across a wide range of relevant fields of applications, including medical image analysis domain in particular. Although convolutional neural networks (CNNs) based medical applications have been providing powerful solutions and revolutionizing medicine, efficiently training of CNNs models is a tedious and challenging task. It is a computationally intensive process taking long time and rare system resources, which represents a significant hindrance to scientific research progress. In order to address this challenge, we propose in this article, R2D2, a scalable intuitive deep learning toolkit for medical imaging semantic segmentation. To the best of our knowledge, the present work is the first that aims to tackle this issue by offering a novel distributed versions of two well-known and widely used CNN segmentation architectures [ie, fully convolutional network (FCN) and U-Net]. We introduce the design and the core building blocks of R2D2. We further present and analyze its experimental evaluation results on two different concrete medical imaging segmentation use cases. R2D2 achieves up to 17.5× and 10.4× speedup than single-node based training of U-Net and FCN, respectively, with a negligible, though still unexpected segmentation accuracy loss. R2D2 offers not only an empirical evidence and investigates in-depth the latest published works but also it facilitates and significantly reduces the effort required by researchers to quickly prototype and easily discover cutting-edge CNN configurations and architectures.     

Forest governance and REDD+ in Central Africa: towards a participatory model to increase stakeholder involvement in carbon markets

Forests play a significant role in the global carbon budget, and can help to mitigate climate change impacts. Tropical forests which experience high rates of deforestation and forest degradation are particularly important, as they are the most active in winter. Based on academic research into global environmental policies in Central Africa, this study finds that REDD+ policies can succeed when there is a carbon market mechanism that increases participation by developing countries, with better integration of forest management and community forestry. Incentives should be based on an appropriate baseline, accurate carbon stocks and fluxes estimation, a suitable silvicultural system and regular monitoring.     

Solidification microstructure-dependent hydrogen generation behavior of Al–Sn and Al–Fe alloys in alkaline medium

This work deals with the development of quantitative correlations of hydrogen evolution performance with solidification microstructural and thermal parameters in Al–1Sn, Al–2Sn, Al–1Fe, and Al-1.5Fe [wt.%] alloys. The cellular growth as a function of growth and cooling rates is evaluated using power type experimental laws, which allow determining representative intervals of microstructure length scale for comparison purposes with the results of immersion tests in 5 wt%NaOH solution. For both Al alloys systems, hydrogen evolution becomes slower as the alloy solute content increased. However, for a given alloy composition, whereas a more homogeneous distribution of Sn-rich particles promotes faster hydrogen generation using Al–Sn alloys, coarsening of Al₆Fe IMCs (intermetallic compounds) fibers favors hydrogen production using Al–Fe alloys. When solidification conditions that result in a range of cellular spacings within 16 and 19 μm are considered, the specific hydrogen production of the Al-1wt.%Fe alloy is higher than that of the other studied alloys.     

3D Radiation Therapy Boost Improves the Outcome of Whole Brain Radiation Therapy Treated RPA II Patients with One or Two Brain Metastases

Purpose

to evaluate the role of whole brain radiotherapy (WBRT) and radiation boost (RB) for 208 patients recursive partitioning analysis (RPA) II with 1 or 2 brain metastases (BM) at a single institution.

Methods and Materials

the dose of WBRT was 30 Gy (10 fractions of 3 Gy). One hundred thirty-two patients (63.5%) benefited from RB of 9 Gy in 3 fractions of 3 Gy at the metastatic site. Patients had 1 or 2 BM in 122 (58.7%) and 86 cases (41.3%), respectively.

Results

patients with one or two metastases had similar survival (4.6 and 5.1 months, respectively) (p = 0.4). Median overall survival (OS) for patients treated with WBRT and RB, and with WBRT alone was 5.9 and 3.7 months, respectively (p = 0.03). The 6-, 12- and 24-month OS rates after WBRT and RB were 48.5%, 25% and 10.6%, respectively, while WBRT alone resulted in OS rates of 34%, 22.4% and 3.2%, respectively (p = 0.03). After WBRT and RB, the 6-, 12- and 24-month local control rates were 92%, 82% and 67%, respectively, while they were 81.2%, 75% and 37.5%, respectively, after WBRT alone (p = 0.03). The 6-, 12- and 24-month brain control rates after WBRT and RB were 88.7%, 75.8% and 62%, respectively, and after WBRT alone they were 78.5%, 59% and 37.7%, respectively (p = 0.03).

Conclusion

additional boost delivered with 3D conformal radiotherapy improves local and brain control rates significantly as well as overall survival for RPA II patients with 1 or 2 unresectable BM.     

高速冷镦机的动平衡研究

本文探讨了高速冷镦机的振动力、振动力矩、输入扭矩波动的合理平衡途径,首次提出了利用平衡机构与配重进行动平衡的综合方法,并在凹模回转高速冷镦机上进行了验证。     

轻烃燃气输配系统技术分析

轻烃燃气是由轻烃燃料和空气混合而成,由于其性质与液化石油气混空气相近,相对价格较低,不失为将来与天然气接轨的一种过渡燃气。作者通过对轻烃燃气输配系统的技术分析后认为,轻烃燃气只适合于小规模、低热值燃气供气。若供气规模过大,则经济性会变差;为使热值稳定,冬季和夏季的燃气出厂压力差异极大,将对输配系统带来较大的问题;冬季供应压力低,有碍于燃气管网的安全。     

Understanding the binder chemistry,microstructure, and physical properties of volcanic ash phosphate geopolymer binder

This work aims to assess the influence of the chemical composition of the binder resulting from the reaction of phosphoric acid and volcanic ash on its final characteristics. Six initial compositions of volcanic ash phosphate geopolymer with molar ratios Fe/P of 0.27, 0.5, 0.54, 0.81, 1, and 1.5 were designed by adding various dosages of phosphoric acid to volcanic ash. The results show that the hardening time increases with the decrease of molar ratios Fe/P. An excess of phosphoric acid leads to an unstable binder that is partially destroyed with the aging of the binder. The volcanic ash phosphate geopolymer with molar ratios of Fe/P = 0.5–0.54 has the optimum compressive strength (49–53 MPa at 90 days), the lowest water absorption (8.8-9.5 wt.%) as well as porosity (18–19.6 vol.%). The main binder is a porous phase of ferro-silico-aluminophosphate. Secondary phases were also identified in some mixes including ferro-aluminophosphate and magnesium phosphate.