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Hall thrusters are electric propulsion devices that are widely used in modern spaceflight. To obtain the critical corrosion data effectively and accurately during long-life tests of Hall thrusters, this paper proposes an automated corrosion measurement method based on three-dimensional point cloud technology. This method uses binocular structured light scanning method to obtain surface point cloud data. The point cloud topology relationship of these disordered data is also established by KD-tree and radius filtering. The base plane is determined according to the average of the outer circle plane in the discharge chamber, and the original point cloud data is sliced transversely and longitudinally. The point cloud of section data is extracted and the corrosion width data is obtained according to the round hole feature extraction and center of circle calculation. The corrosion angle is calculated according to the angle between the straight line and the normal of the section. The proposed method has been verified and the results show that the overall error accuracy is within 60 μm, which meets the requirements for automatic measurement of Hall thruster corrosion. It is a real and effective method to obtain the critical corrosion data during long-life tests of Hall thrusters. [ABSTRACT FROM AUTHOR]

Fatty acids not only form phospholipids that contribute to the formation of cell membranes but also participate in many metabolic activities, such as energy storage and cell signal transduction. The liver plays a key role in the synthesis and metabolism of fatty acids. The composition and contents of fatty acids in the liver are closely related to body health. Most fatty acid-detection methods require a large sample size and can detect only a small number of fatty acids. Therefore, a sensitive and efficient method to determine fatty acids in the liver is urgently required. Herein, a method based on gas chromatography-mass spectrometry (GC-MS) was established for the simultaneous determination of 39 fatty acids in 1.1 mg of liver tissue. Different extraction methods and derivatization conditions were compared to develop an optimal sample-treatment method. The performance of two different columns in separating the target fatty acids were also compared. A total of 10 mg of liver was added to 450 μL of normal saline and ground at -35 ℃ to obtain a homogenate. Next, 50 μL of the homogenate (equivalent to 1.1 mg of liver) was added with 750 μL of chloroform-methanol (1∶2, v/v) to extract total fatty acids. The fatty acid extracts were dried under nitrogen, and then derivatized at 100 ℃ for 90 min after being added with methanol containing 5% sulfuric acid. The fatty acid methyl esters were extracted with hexane and then separated on an SP-2560 capillary column (100 m×0.25 mm×0.2 μm; Supelco, USA) via GC-MS. The results revealed that all 39 fatty acid methyl esters detected had good linearities in the certain mass concentration ranges with correlation coefficients ( R 2 ) greater than 0.9940. The limits of detection (LOD) and quantification (LOQ) of these methyl esters in the liver were 2-272 ng/mg and 7-906 ng/mg, respectively. The accuracy and precision of the method were evaluated by spiking the liver homogenate with tridecylic acid and eicosanoic acid at low (0.09 μg/mg), moderate (0.90 μg/mg), and high (5.40 μg/mg) concentration levels. The recoveries ranged from 82.4% to 101.0% with an intraday relative standard deviations (RSDs) ( n =5) of 3.2%-12.0% and interday RSDs ( n =3) of 5.4%-13.4%. The method was successfully applied to detect fatty acids in the livers of four healthy male Sprague-Dawley (SD) rats and four male SD rats with abnormal liver function induced by perfluorooctane sulfonate (PFOS). PFOS is a persistent organic pollutant. Twenty-six fatty acids were detected in the livers of both groups. Among the fatty acids investigated, pentadecanoic acid (C15∶0), γ -linolenic acid (C18∶3n6), and elaidic acid (C18∶1n9t) cannot be detected by the methods reported in the literature. By contrast, the method developed in this study could separate the isomers of oleic acid (elaidic acid, C18∶1n9t; oleic acid, C18∶1n9c) and linolenic acid (linolelaidic acid, C18∶2n6t; linoleic acid, C18∶2n6c). In conclusion, the developed method is simple and can detect a large number of fatty acids using small sample amounts and few reagents. More importantly, it could successfully separate fatty acid isomers. These findings indicate that the developed method is suitable for the detection of fatty acid composition and contents in the liver in clinical and experimental research.

Sleep disorders are common in patients with Alzheimer's disease, and can even occur in patients with amnestic mild cognitive impairment, which appears before Alzheimer's disease. Sleep disorders further impair cognitive function and accelerate the accumulation of amyloid-β and tau in patients with Alzheimer's disease. At present, sleep disorders are considered as a risk factor for, and may be a predictor of, Alzheimer's disease development. Given that sleep disorders are encountered in other types of dementia and psychiatric conditions, sleep-related biomarkers to predict Alzheimer's disease need to have high specificity and sensitivity. Here, we summarize the major Alzheimer's disease-specific sleep changes, including abnormal non-rapid eye movement sleep, sleep fragmentation, and sleep-disordered breathing, and describe their ability to predict the onset of Alzheimer's disease at its earliest stages. Understanding the mechanisms underlying these sleep changes is also crucial if we are to clarify the role of sleep in Alzheimer's disease. This paper therefore explores some potential mechanisms that may contribute to sleep disorders, including dysregulation of the orexinergic, glutamatergic, and γ-aminobutyric acid systems and the circadian rhythm, together with amyloid-β accumulation. This review could provide a theoretical basis for the development of drugs to treat Alzheimer's disease based on sleep disorders in future work., Competing Interests: None