Background Plants are naturally associated with root microbiota, which are microbial communities influential to host fitness. Thus, it is important to understand how plants control root microbiota. Epigenetic factors regulate the readouts of genetic information and consequently many essential biological processes. However, it has been elusive whether RNA-directed DNA methylation (RdDM) affects root microbiota assembly. Results By applying 16S rRNA gene sequencing, we investigated root microbiota of Arabidopsis mutants defective in the canonical RdDM pathway, including dcl234 that harbors triple mutation in the Dicer-like proteins DCL3, DCL2, and DCL4, which produce small RNAs for RdDM. Alpha diversity analysis showed reductions in microbe richness from the soil to roots, reflecting the selectivity of plants on root-associated bacteria. The dcl234 triple mutation significantly decreases the levels of Aeromonadaceae and Pseudomonadaceae, while it increases the abundance of many other bacteria families in the root microbiota. However, mutants of the other examined key players in the canonical RdDM pathway showed similar microbiota as Col-0, indicating that the DCL proteins affect root microbiota in an RdDM-independent manner. Subsequently gene analysis by shotgun sequencing of root microbiome indicated a selective pressure on microbial resistance to plant defense in the dcl234 mutant. Consistent with the altered plant-microbe interactions, dcl234 displayed altered characters, including the mRNA and sRNA transcriptomes that jointly highlighted altered cell wall organization and up-regulated defense, the decreased cellulose and callose deposition in root xylem, and the restructured profile of root exudates that supported the alterations in gene expression and cell wall modifications. Conclusion Our findings demonstrate an important role of the DCL proteins in influencing root microbiota through integrated regulation of plant defense, cell wall compositions, and root exudates. Our results also demonstrate that the canonical RdDM is dispensable for Arabidopsis root microbiota. These findings not only establish a connection between root microbiota and plant epigenetic factors but also highlight the complexity of plant regulation of root microbiota.
Many contemporary neuroscience experiments utilize high-throughput approaches to simultaneously collect behavioural data from many animals. The resulting data are often complex in structure and are subjected to systematic biases, which require new approaches for analysis and normalization. This study addressed the normalization need by establishing an approach based on linear-regression modeling. The model was established using a dataset of visual motor response (VMR) obtained from several strains of wild-type (WT) zebrafish collected at multiple stages of development. The VMR is a locomotor response triggered by drastic light change, and is commonly measured repeatedly from multiple larvae arrayed in 96-well plates. This assay is subjected to several systematic variations. For example, the light emitted by the machine varies slightly from well to well. In addition to the light-intensity variation, biological replication also created batch-batch variation. These systematic variations may result in differences in the VMR and must be normalized. Our normalization approach explicitly modeled the effect of these systematic variations on VMR. It also normalized the activity profiles of different conditions to a common baseline. Our approach is versatile, as it can incorporate different normalization needs as separate factors. The versatility was demonstrated by an integrated normalization of three factors: light-intensity variation, batch-batch variation and baseline. After normalization, new biological insights were revealed from the data. For example, we found larvae of TL strain at 6 days post-fertilization (dpf) responded to light onset much stronger than the 9-dpf larvae, whereas previous analysis without normalization shows that their responses were relatively comparable. By removing systematic variations, our model-based normalization can facilitate downstream statistical comparisons and aid detecting true biological differences in high-throughput studies of neurobehaviour.
Retinitis Pigmentosa (RP) is a mostly incurable inherited retinal degeneration affecting approximately 1 in 4000 individuals globally. The goal of this work was to identify drugs that can help patients suffering from the disease. To accomplish this, we screened drugs on a zebrafish autosomal dominant RP model. This model expresses a truncated human rhodopsin transgene (Q344X) causing significant rod degeneration by 7 days post-fertilization (dpf). Consequently, the larvae displayed a deficit in visual motor response (VMR) under scotopic condition. The diminished VMR was leveraged to screen an ENZO SCREEN-WELL REDOX library since oxidative stress is postulated to play a role in RP progression. Our screening identified a beta-blocker, carvedilol, that ameliorated the deficient VMR of the RP larvae and increased their rod number. Carvedilol may directly on rods as it affected the adrenergic pathway in the photoreceptor-like human Y79 cell line. Since carvedilol is an FDA-approved drug, our findings suggest that carvedilol can potentially be repurposed to treat autosomal dominant RP patients.
BackgroundHPV vaccine can block the infection of high-risk human papillomavirus and is an important measure to effectively reduce the incidence of cervical cancer and precancerous lesions. However, the HPV vaccination rate is still low in China. There are many factors. Therefore, it is important to study the influencing factors to provide basis for promoting the formulation of vaccination strategies.MethodsThis study used a multi-stage sampling method to conduct a face-to-face questionnaire survey on women in different regions of China. The new general self-efficacy scale was used to measure the self-efficacy of the respondents. The short form of family health scale measured their family health. The t-test and binary Logistic regression analysis were used to screen the influencing factors of HPV vaccination. Restricted cubic spline model was used to analyze the influence trend of self-efficacy and family health on HPV vaccination rate.Results(1) The HPV vaccination rate was low, especially in the ≤18 group. The place of residence, capita household income/month, individual self-efficacy and family health had a significant impact on HPV vaccination. (2) The restricted cubic spline model showed that self-efficacy positively promoted HPV vaccination, the correlation strength was statistically significant (χ2 =27.64, P<0.001) and non-linear (χ2 = 12.49, P = 0.0004); The poor family health hindered HPV vaccination, and the association strength was statistically significant (χ2 = 47.81, P < 0.001) and non-linear (χ2 = 9.96, P = 0.0016).ConclusionIt is necessary to strengthen the health education of HPV vaccination knowledge in the population to eliminate the hesitancy of vaccination. Free HPV vaccination strategies should be developed and encourage people of appropriate age to receive as early as possible. Self-efficacy and family health should be enhanced to increase HPV vaccination rate, so as to achieve the goal of reducing the incidence of cervical cancer and protecting women's health.
A robust tuning method based on an artificial neural network for model predictive control (MPC) of industrial systems with parametric uncertainties is put forward in this work. Firstly, an efficient approach to characterize the mapping relationship between the controller parameters and the robust performance indices is established. As there are normally multiple conflicted robust performance indices to be considered in MPC tuning, the neural network is further used to fuse the indices to produce a simple label representing the acceptable level of the robust performance. Finally, an automated algorithm is proposed to tune the MPC parameters for the considered uncertain system to achieve the desired robust performance. In addition, the regulation of the pH value of the sewage treatment system is used to verify the effectiveness of the robust tuning algorithm which is described in this paper.
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