[Analysis of nasal microbial characteristics in patients with allergic rhinitis and non-allergic rhinitis]

Objective: To investigate the characteristics of nasal flora and the pathogenic role of differential microbiome in patients with allergic rhinitis (AR) and non-allergic rhinitis (nAR). Methods: Thirty-five patients with AR who attended the rhinology outpatient clinic of the Second Hospital of Harbin Medical University from February to July 2022 were selected. A total of 35 nAR patients were selected as the test group, and 20 cases of healthy people with physical examination at the same period were selected as the control group, including 39 males and 51 females, aged 8 to 55 years. 16SrDNA High-throughput sequencing was used to analyze the relative abundance from nasal flora in the three groups of subjects. Alpha diversity index analysis was conducted with R software, and differences between groups were analyzed with LEfSe, Metastats, and t tests. At the same time, the role of microbiome and its relationship with environmental factors were analyzed with R software. Results: There was a significant difference in the bacterial composition of the samples from the three groups, with the relative abundance of Staphylococcus aureus (P=0.032) and Corynebacterium proinquum (P=0.032) within the AR group being significantly higher than that of the nAR group, and that of Lactobacillus murinus, Lactobacillus kunkeei, and Alcaligenes faecalis (P value was 0.016, 0.005, and 0.001, respectively) being significantly lower than that of the nAR group. The relative abundance of Ackermannia muciniphila within the nAR group was higher than that of the control group (P=0.009). Correlation analysis of environmental factors showed a negative correlation between Lactobacillus kunkeei and IgE (P=0.044), and a positive correlation between Lactobacillus murinus and age (P=0.019). AR and nAR random forest prediction models were constructed for the five genera, respectively, and the area under the curve (AUC) of the models of Streptococcus-SP-FF10, Pseudoalteromonas luteoviolacea, Pseudomonas parafulva, Acinetobacter ursingii, and Azotobacter chroococcum in the AR group was 100% (95%CI: 100% to 100%). The AUC for the Pseudomonas parafulva, Azotobacter chroococcum, Closoridium baratii, Turicibacter-SP-H121, and Streptococcus lutetiensis models in the nAR group was 98.4% (95%CI: 94.9% to 100%). Conclusions: The distribution of nasal flora in AR patients, nAR patients and healthy subjects is significantly different, and the changes of bacterial flora abundance are significantly related to the occurrence of AR and nAR. Combined detection of microbiota has the potential to diagnose AR and nAR patients.

Calibration of a 32 channel electron cyclotron emission radiometer on the HL-2A tokamak

A novel 32-channel electron cyclotron emission radiometer has been designed and tested for the measurement of electron temperature profiles on the HL-2A tokamak. This system is based on the intermediate frequency filter detection technique, and has the features of wide working frequency range and high spatial resolution. Two relative calibration methods have been investigated: sweeping the toroidal magnetic field and hopping the output frequency of the local oscillator. Preliminary results show that both methods can ensure reasonable profiles.

Development of electron cyclotron emission imaging system on the HL-2A tokamak

A 2D electron cyclotron emission imaging (ECEI) system has been developed for measurement of electron temperature fluctuations in the HL-2A tokamak. It is comprised of a front-end 24 channel heterodyne imaging array with a tunable RF range spanning 75-110 GHz, and a set of back-end ECEI electronics that together generate 24 × 8 = 192 channel images of the 2nd harmonic X-mode electron cyclotron emission from the HL-2A plasma. The simulated performance of the local oscillator (LO) optics and radio frequency (RF) optics is presented, together with the laboratory characterization results. The Gaussian beams from the LO optics are observed to properly cover the entire detector array. The ECE signals from the plasma are mixed with the LO signal in the array box, then delivered to the electronics system by low-loss microwave cables, and finally to the digitizers. The ECEI system can achieve temporal resolutions of ~μs, and spatial resolutions of 1 cm (radially) and 2 cm (poloidally).