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During the operation of the reactor, a large amount of tritium is released into the surrounding air through the waste gas treatment system and the plant ventilation system. Tritium is very easy to replace hydrogen in water molecules, and can enter the human body through breathing, resulting in internal radiation hazards. Therefore, it is necessary to study the measurement of tritium in ambient air. At present, there is no national or industrial standard for the measurement of tritium in air. In this paper, the liquid scintillation counter was used to measure the activity concentration of tritium in air. It is found that the detection limit of the activity concentration of tritium in the air mainly depends on ambient temperature, relative humidity, sample amount, detection efficiency of the instrument, background count rate of the instrument, measurement time, etc. Among them, ambient temperature and relative humidity are inherent characteristics of air samples. Therefore, in order to reduce the detection limit and shorten the measurement time as much as possible, three aspects must be considered which is reducing the background count rate, improving the detection efficiency and increasing the sample volume. Possible approaches include selecting background water and scintillation fluid with the lowest possible counts, selecting the appropriate counting area, and optimizing the mixing ratio of sample and scintillation fluid. In order to reduce the effect of water and scintillation fluid on the background, 11 different sources of background water and 3 types of scintillation fluid were selected for testing. The samples were prepared according to the ratio of 8 mL of water to 12 mL of scintillation fluid, and the long-term counting measurement was carried out after being stored in the dark for 24 h. The measurement results show that the count rate range of the background water sample varies from 2.373 min-1 to 3.441 min-1, and the difference between the maximum value and the minimum value is 1.068 min-1, which also shows that the selection of the background water sample is very critical. For three scintillation fluids including Gold Star Quanta, OtpiPhase HiSafe 3 and UItima Gold LLT, there is no significant difference in background and detection efficiency.In order to further reduce the detection limit, a figure of merit (FOM) was introduced, which is the ratio of the square of the detection efficiency of the radionuclide of interest to the background count rate. To maximize FOM, it is necessary to reduce the sample background count rate while maintaining a high detection efficiency, which can be achieved by optimizing the count area. By changing the lower threshold (LL) and upper threshold (UL) of the pulse height discriminator, a series of counted regions and the corresponding FOM can be obtained. The optimal count interval is 0.35-4.35 keV, which maximizes FOM. For full spectrum counting, the sample detection efficiency is 29.27% and the background counting rate is 6.53 min-1, from which the FOM is calculated to be 131.2. After optimizing the counting area, although the detection efficiency is only 25.62%, the background is only 2.42 min-1, and the FOM reaches 271.2. The optimization of the counting interval reduces the detection efficiency from 29.27% to 25.62%, a decrease of 12.47%. But there is an even bigger reduction in background, at 170%. In terms of optimizing the combination of water and scintillation fluid, samples were prepared and measured with water contents of 35%, 40%, 45%, 50%, and 55%, respectively. The comparison results show that when the water content is 40% and 45%, the quality factor of the measurement system reaches the maximum, and the detection limit reaches the minimum. Tritium in air was measured under optimized conditions. The detection limit of typical samples is 20 mBq/m3, and the measurement time is 16 h, which is 1/2 shorter than that of full spectrum counting.

Although observational studies have suggested a link between hypothyroidism and myasthenia gravis (MG), a causal relationship has not been established. We aimed to investigate the causal association using a two-sample Mendelian randomization (MR) study. Using summary statistics from genome-wide association studies involving 494,577 and 38,243 individuals, single-nucleotide polymorphisms exhibiting no linkage disequilibrium (r2 ≤ 0.001) and displaying significant differences (p ≤ 5 × 10−8) were selected for hypothyroidism and MG. To assess the potential causality relationship between hypothyroidism and MG, MR analysis was conducted using inverse variance weighted (IVW), weighted median method, and MR-Egger. The MR-Egger regression, heterogeneity test, pleiotropy test, and leave-one-out sensitivity test were employed to examine sensitivity analyses. In addition, validation datasets were used to validate the relevant results. Genetic liability to hypothyroidism was positively associated with MG (IVW, OR: 1.36, 95% CI: 1.17–1.58, p = 7.53 × 10–05; weighted median, OR: 1.19, 95% CI: 0.70–2.02, p = 0.522; MR-Egger, OR: 1.19, 95% CI: 0.98–1.45, p = 0.080). Among the three MR methods, the correlation between hypothyroidism and MG genetic prediction was consistent. The independent validation set (IVW, OR: 466.47, 95% CI: 4.70 -46,285.95, p = 0.01) further supported this. Additionally, bidirectional studies showed that using IVW, there was no reverse causality (OR: 1.104, 95%CI: 0.96–1.27, p = 0.170). This MR study showed that hypothyroidism can increase the risk of MG. Further investigation into the underlying mechanisms of this potential causality is warranted to offer novel therapeutic options for MG in the future. [ABSTRACT FROM AUTHOR]