New recessive compound heterozygous variants of RP1L1 in RP1L1 maculopathy.

AIM: To identify a maculopathy patient caused by new recessive compound heterozygous variants in RP1L1. METHODS: Comprehensive retinal morphological and functional examinations were evaluated for the patient with RP1L1 maculopathy. Targeted sequence capture array technique was used to screen potential pathologic variants. Polymerase chain reaction and Sanger sequencing were used to confirm the screening results. RESULTS: Fundus examination showed round macular lesions appeared in both eyes. Optical coherence tomography showed that the inner segment/outer segment continuity was disorganized and disruptive in the left eye, but it was uneven and slightly elevated in the right eye. Fundus autofluorescence showed patchy hyper-autofluorescence in the macula. Visual field examination indicates central defects in both eyes. Electroretinogram (ERG) and multifocal ERG showed no obvious abnormalities. Fundus fluorescein angiography in the macula showed obviously irregular hyper-fluorescence in the right eye and slightly hyper-fluorescence in the left eye. We found that the proband carried a missense variant (c.1972C>T) and a deletion variant (c.4717_4718del) of RP1L1, which were originated from the parents and formed compound heterozygous variants. Both variants are likely pathogenic according to the ACMG criteria. Multimodal imaging, ERG and detailed medical history are important diagnostic tools for differentiating between acquired and inherited retinal disorders. CONCLUSION: A maculopathy case with detailed retinal phenotype and new recessive compound heterozygous variants of RP1L1 is identified in a Chinese family, which expands the understanding of phenotype and genotype in RP1L1 maculopathy.

Exploration and validation of related hub gene expression during SARS-CoV-2 infection of human bronchial organoids.

BACKGROUND: In the novel coronavirus pandemic, the high infection rate and high mortality have seriously affected people's health and social order. To better explore the infection mechanism and treatment, the three-dimensional structure of human bronchus has been employed in a better in-depth study on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We downloaded a separate microarray from the Integrated Gene Expression System (GEO) on a human bronchial organoids sample to identify differentially expressed genes (DEGS) and analyzed it with R software. After processing with R software, Gene Ontology (GO) and Kyoto PBMCs of Genes and Genomes (KEGG) were analyzed, while a protein-protein interaction (PPI) network was constructed to show the interactions and influence relationships between these differential genes. Finally, the selected highly connected genes, which are called hub genes, were verified in CytoHubba plug-in. RESULTS: In this study, a total of 966 differentially expressed genes, including 490 upregulated genes and 476 downregulated genes were used. Analysis of GO and KEGG revealed that these differentially expressed genes were significantly enriched in pathways related to immune response and cytokines. We construct protein-protein interaction network and identify 10 hub genes, including IL6, MMP9, IL1B, CXCL8, ICAM1, FGF2, EGF, CXCL10, CCL2, CCL5, CXCL1, and FN1. Finally, with the help of GSE150728, we verified that CXCl1, CXCL8, CXCL10, CCL5, EGF differently expressed before and after SARS-CoV-2 infection in clinical patients. CONCLUSIONS: In this study, we used mRNA expression data from GSE150819 to preliminarily confirm the feasibility of hBO as an in vitro model to further study the pathogenesis and potential treatment of COVID-19. Moreover, based on the mRNA differentiated expression of this model, we found that CXCL8, CXCL10, and EGF are hub genes in the process of SARS-COV-2 infection, and we emphasized their key roles in SARS-CoV-2 infection. And we also suggested that further study of these hub genes may be beneficial to treatment, prognostic prediction of COVID-19.

[Nitrous Oxide Production in Response to Oxygen in a Solar Greenhouse Vegetable Soil].

To explore the sources of peak nitrous oxide (N2O) flushes in solar greenhouse vegetable field, an experiment was conducted with two conventional vegetable soils under different initial volume fractions of oxygen (O2) (0%, 1%, 3%, 5%, and 10%). A robotized incubation system was employed to analyze the gas kinetics[O2, N2O, nitric oxide (NO), nitrogen (N2), and carbon dioxide (CO2)] every 6 or 8 h and calculate the N2O/(NO+N2O+N2) index. Sodium chlorate (NaClO3) was used to inhibit the oxidation of NO2- to further explore the relationship between N2O and nitrite (NO2-). A parallel off-line incubation in triplicates was conducted under similar conditions to measure the dynamic changes in inorganic nitrogen content[ammonia (NH4+), nitrate (NO3-), and NO2-]. The results showed that N2O production under anaerobic condition was significantly higher than that under aerobic condition. The peak value of N2O in the soil collected from a straw-added plot (DIS) was significantly higher than that in the soil from non-straw added plot (DI) (P<0.01) when the volume fraction of oxygen was ≤ 1%. Oxygen can directly affect N2O production by delaying or inhibiting N2O reduction, with significant increase in N2O production rate under oxygen-depleted condition. However, the N2production rate decreased significantly with increase in initial oxygen volume fraction (P<0.01). When the initial volume fraction of oxygen was between 1% and 5%, a continuous accumulation of NO2- was observed during the incubation period, resulting in the significantly higher N2O/(NO+N2O+N2) index than that in either anaerobic or 10% of oxygen treatments. Furthermore, a linear correlation was observed between NO2- and N2O at 5% and 10% of oxygen with the addition of NaClO3 (R2 ≥ 0.85). Incomplete denitrification and nitrifier denitrification from NO2- induction co-occurred in the range of 1% and 5% volume fractions of oxygen, significantly increasing the soil N2O production and N2O/(NO+N2O+N2) index. In addition, N2O production under anaerobic condition was significantly higher than that under aerobic condition (P<0.01).