Simultaneous quantitative analysis of seven steroid hormones in human saliva: A novel method based on O-ethylhydroxylamine hydrochloride as derivatization reagent.

RATIONALE: Saliva has been widely accepted as a more convenient alternative to serum or plasma in the field of clinical diagnosis. However, the detection of trace components in saliva has been a bottleneck problem. The aim of this work was to develop a highly sensitive and reliable method for simultaneously determining the trace steroid hormones including some with poor ionization efficiency in human saliva by liquid chromatography/tandem mass spectrometry (LC/MS). METHODS: Saliva was deproteinated by acetonitrile containing mixed isotope internal standards and extracted with methyl tert-butyl ether. The extraction solution was dried under a stream of nitrogen and the residue was derivatized using 50 mM O-ethylhydroxylamine hydrochloride in 80% methanol/water solution (v/v). The processed sample was determined by LC/MS in multiple reaction monitoring (MRM) mode. RESULTS: The method was successfully established for the simultaneous quantification of seven steroid hormones in human saliva and showed excellent specificity and sensitivity. The limits of quantification (LOQs) of all steroid hormones were below 5 pg/mL, in particular, the LOQ of progesterone was as low as 0.15 pg/mL. The linear correlation coefficients (r) were greater than 0.9990 in the range of 2-200 pg/mL for T, DHEA, A4, P4, P5, and 17OHP4 and in the range of 5-500 pg/mL for 17OHP5. The intra-day and inter-day variability ranged from 1.86% to 7.83% and 1.95% to 10.4%, respectively. The recovery of the method ranged from 86.9% to 111.1% for all steroid hormones using three spiked concentrations. CONCLUSIONS: A novel LC/MS/MS method was developed for the simultaneous quantification of seven kinds of trace steroid hormones in human saliva. The results of the methodological study showed that the method exhibited excellent sensitivity and reliability for the evaluation of free steroid hormones in the human body. It is believed that this method could provide useful information of steroid hormone metabolism for auxiliary diagnosis of some endocrine disorders.

Improving Plasticity of Ferritic Stainless Steel Welded Joints via Laser Spot Control.

The plasticity of welded 441 ferritic stainless steel joints was controlled by varying the laser beam spot diameter during laser welding. A stainless steel plate thickness of 1.2 mm was used. The microstructures of the welded joints were analyzed for various spot diameters. The elongation of breaks and the reduced area of tensile specimens were analyzed to study the effects of spot diameter on plasticity of the welded joints. The results showed that the weld melt width and weld column crystal size increased with the spot diameter, but isometric crystals in the center of the weld were gradually reduced. Increasing spot diameter resulted in decreased tensile strength, elongation after breaks, and area reduction. So the parameter must be controlled during the laser welding.

Wild Geese Migration Optimization Algorithm: A New Meta-Heuristic Algorithm for Solving Inverse Kinematics of Robot.

This paper proposes a new meta-heuristic algorithm, named wild geese migration optimization (GMO) algorithm. It is inspired by the social behavior of wild geese swarming in nature. They maintain a special formation for long-distance migration in small groups for survival and reproduction. The mathematical model is established based on these social behaviors to solve optimization problems. Meanwhile, the performance of the GMO algorithm is tested on the stable benchmark function of CEC2017, and its potential for dealing with practical problems is studied in five engineering design problems and the inverse kinematics solution of robot. The test results show that the GMO algorithm has excellent computational performance compared to other algorithms. The practical application results show that the GMO algorithm has strong applicability, more accurate optimization results, and more competitiveness in challenging problems with unknown search space, compared with well-known algorithms in the literature. The proposal of GMO algorithm enriches the team of swarm intelligence optimization algorithms and also provides a new solution for solving engineering design problems and inverse kinematics of robots.