Background Alzheimer’s disease (AD) is associated with metabolic abnormalities linked to critical elements of neurodegeneration. We recently administrated Combined Metabolic Activators (CMA) to the AD rat model and observed that administration of CMA activated the mitochondrial functions and eventually improved the AD-associated histological parameters in the animals. CMA consists of NAD + and glutathione precursors and includes L-serine, nicotinamide riboside, N-acetyl-L-cysteine, and L-carnitine tartrate. Methods Here, we designed a randomised, double-blinded, placebo-controlled phase-II trial and studied the effect of CMA administration on the global metabolism of AD patients. The primary endpoint was on the difference in cognitive and daily living activity scores between the placebo and the treatment arms. The secondary aim of this study was to evaluate the safety and tolerability of CMA. We also performed a comprehensive human plasma metabolome and proteome analysis. Results Based on our analysis, we showed a significant decrease of ADAS-Cog scores on Day 84 vs Day 0 (p = 0.00001, 29% improvement) in the CMA group. Moreover, there was a significant enhancement (p = 0.0073) in ADAS-Cog scores between CMA and placebo groups in patients with higher ADAS-Cog scores. Improved cognitive functions were endorsed with relevant hippocampal volumes and cortical thickness alterations. Moreover, the plasma levels of proteins and metabolites associated with NAD + and glutathione metabolism are significantly improved after treatment. Conclusion In conclusion, our results show that treating AD patients with CMA leads to enhanced cognitive functions associated with the improved metabolome, proteome and structural neuroimaging parameters, suggesting a role for such a therapeutic regimen in treating patients, especially with severe AD. Trial registration: ClinicalTrials.gov NCT04044131 Registered 17 July 2019, https://clinicaltrials.gov/ct2/show/NCT04044131

Binary similarity detection determines whether two given binary code snippets are similar or not, usually on function granularity. This task is challenging due to different compilation optimizations and CPU architectures. Recently, deep-learning methods have made great achievements in this field, although most of them use artificially selected features or ignore some important semantic information like code literals or function signatures during feature processing. In addition, random samples and pair loss function are used in similarity training, which only covers limited similarity relations between functions. In this paper, a new framework MFEN-Sim is proposed to detect similar binary functions. The framework contains three stages: feature extraction and normalization, mutli-feature based function feature embedding network (MFEN) and similarity learning network. Multiple features including assembly instructions, CFG structures and function code literals are extracted from binary functions. Then these features are fed into MFEN composed of three modules: function semantic and structure embedding module, function signature prediction module, and function code literal embedding module. The three modules generate embeddings representing the function semantic and structural features, the function signature prediction features and the function code literal features. Finally, MFEN-Sim utilizes a similarity training network based on contrastive learning to make MFEN recognize more similarity relations between functions. MFEN-Sim is evaluated on 281,601 functions in 144 binaries and 17 CVEs in real-world software. Experimental results show that our work outperforms state-of-the-art systems ( i.e., Gemini, FIT and SAFE) by 7.1%, 9.9% and 8.2% on AUC metric in cross-architecture, optimization-level similarity detection, and achieves higher recall than baselines in searching vulnerabilities in real-world applications.

In this paper, ammonium phosphate polymer (APP), guanidinium phosphate urea (GUP), phosphonic acid, and a small number of additives that confer flame retardant properties were prepared as a new composite flame retardant. Cedar (Cryptomeria japonica) and hinoki (Chamaecyparis obtuse) penetrate and absorb the solution into the inner wall of the wood by vacuum pressurization, thus obtaining fire-retardant woods. The flame retardant effectsat different absorption amounts were investigated by thermogravimetric analysis and cone calorimetry.The absorption amounts of both kinds of wood above 0.095 g.cm-3and 0.085g.cm-3respectively, met the flame retardant standard ISO-5660-1: 2015. Thermogravimetric analysis showed that the fire-retardant-treated wood increased thermal stability, accelerated carbonization, and lower the decomposition temperature to below 300°C.

Background: Alzheimer’s disease (AD) is associated with metabolic abnormalities linked to critical elements of neurodegeneration. We recently administrated Combined Metabolic Activators (CMA) to the AD rat model and observed that administration of CMA activated the mitochondrial functions and eventually improved the AD-associated histological parameters in the animals. CMA consists of NAD+ and glutathione precursors and includes L-serine, nicotinamide riboside, N-acetyl-L-cysteine, and L-carnitine tartrate. Methods: Here, we designed a randomised, double-blinded, placebo-controlled phase-II trial and studied the effect of CMA administration on the global metabolism of AD patients. The primary endpoint was on the difference in cognitive and daily living activity scores between the placebo and the treatment arms. The secondary aim of this study was to evaluate the safety and tolerability of CMA. We also performed a comprehensive human plasma metabolome and proteome analysis. Results: Based on our analysis, we showed a significant decrease of ADAS-Cog scores on Day 84 vs Day 0 (p=0.00001, 29% improvement) in the CMA group. Moreover, there was a significant enhancement (p=0.0073) in ADAS-Cog scores between CMA and placebo groups in patients with higher ADAS-Cog scores. Improved cognitive functions were endorsed with relevant hippocampal volumes and cortical thickness alterations. Moreover, the plasma levels of proteins and metabolites associated with NAD+ and glutathione metabolism are significantly improved after treatment. Conclusion: In conclusion, our results show that treating AD patients with CMA leads to enhanced cognitive functions associated with the improved metabolome, proteome and structural neuroimaging parameters, suggesting a role for such a therapeutic regimen in treating patients, especially with severe AD.Trial registration: ClinicalTrials.gov NCT04044131 Registered 17 July 2019, https://clinicaltrials.gov/ct2/show/NCT04044131

An epitome of a sustainable city, Masdar City in the United Arab Emirates, boasts of its integrated land use and multi-modal transportation network. When developed as planned, it could be an example for designing future cities. However, little is known of how accessible it could be in spite of its unique design. Conversely, accessibility, as a conceptual and operational definition, has gone through several iterations. However, it still remains an often misunderstood and poorly defined and measured construct. Masdar City, as planned, consists of several types of sustainable transportation options including walking, biking, personal rapid transit (PRT), group rapid transit (GRT), bus/light rapid transit, and metro. The hierarchical additive approach (considering both spatial analysis and the time-based analysis), reports that majority of Masdar City has low accessibility to the regional metro station. Also, the result indicates that more than half of the city will need between 13.1 to 25 minutes, with an average of 15 minutes, to reach the metro station. In all, the city has medium accessibility to the metro station with opportunities to enhance the overall accessibility. Elimination of transit stops that are redundant can reduce the headway and stalling time and hence the total travel time. Also, by locating new transit stops (bus, PRT or LRT) in grids where access to closest public transit is more than 400 m by walking can help balance the capital cost of infrastructure (public transit) while improving the accessibility to the regional metro for its residents. The follow-up analysis reported that the medium accessibility increased from 20% to 24%. Evaluation of accessibility in planned areas (city or neighbourhood) can provide insights on efficiency of a sustainable city such as Masdar City.