[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.

Androgen receptor isoforms in human prostatic cancer tissue and LNCaP cell line.

AIM: To investigate the androgen receptor (AR) isoform expressions in human prostatic cancer tissue and LNCaP cell line. METHODS: With high resolution isoelectric focusing (IEF) method we demonstrated the different expressions of AR isoforms in human prostatic cancer tissues and LNCaP cell line. RESULTS: Data were obtained from three prostatic cancer specimens and the LNCaP cell line. Three types of AR isoforms were detected with pI values at 6.5, 6.0, and 5.3. For the 3 prostatic cancer specimens, 1 sample showed all the three types of AR isoforms, the second specimen expressed at 6.5 and 6.0, and the third failed to show any type of isoforms. The LNCaP cell line expressed all the three AR isoforms. Binding of 3H-dihydrotestosterone (3H-DHT) to these three isoforms was inhibited by the addition of 100-fold excess of DHT or testosterone, while not by progesterone, oestradiol and diethylstilboestrol. CONCLUSION: The expression of AR isoforms is different in different prostate cancer tissues, which may be related to the difference in the effect of anti-androgen therapy in different patients.