Splicing factor hnRNPA1 regulates alternative splicing of LOXL2 to enhance production of LOXL2Δ13.

Lysyl oxidase-like 2 (LOXL2) is a member of the lysyl oxidase family and has the ability to catalyze the cross-linking of extracellular matrix collagen and elastin. High expression of LOXL2 is related to tumor cell proliferation, invasion and metastasis. LOXL2 contains 14 exons. Previous studies have found that LOXL2 has abnormal alternative splicing and exon skipping in a variety of tissues and cells, resulting in a new alternatively-spliced isoform denoted LOXL2Δ13. LOXL2Δ13 lacks LOXL2WT exon 13, but its encoded protein has greater ability to induce tumor cell proliferation, invasion and metastasis. However, the molecular events that produce LOXL2Δ13 are still unclear. In this study, we found that overexpression of the splicing factor hnRNPA1 in cells can regulate the alternative splicing of LOXL2 and increase the expression of LOXL2Δ13. The exonic splicing silencer (ESS) exists at the 3' splice site (3' SS) and 5' splice site (5' SS) of LOXL2 exon 13. HnRNPA1 can bind to the ESS and inhibit the inclusion of exon 13. The RRM domain of hnRNPA1 and phosphorylation of hnRNPA1 at S91 and S95 are important for the regulation of LOXL2 alternative splicing. These results show that hnRNPA1 is a splicing factor that enhances the production of LOXL2Δ13.

Minimally invasive endoscopic repair of rectovaginal fistula.

BACKGROUND: Surgical techniques for repair of rectovaginal fistula (RVF) have been continually developed, but the ideal procedure remains unclear. Endoscopic repair is a novel and minimally invasive technique for RVF repair with increasing reporting. AIM: To review the current applications and preliminary outcomes of this technique for RVF repair, aiming to give surgeons an alternative in clinical practice. METHODS: Available articles were searched according to the search strategy. And the sample size, fistula etiology, fistula type, endoscopic repair approaches, operative time and hospital stay, follow-up period, complication and life quality assessment were selected for recording and further analysis. RESULTS: A total of 11 articles were eventually identified, involving 71 patients with RVFs who had undergone endoscopic repair. The principal causes of RVFs were surgery (n = 51, 71.8%), followed by obstetrics (n = 7, 9.8%), inflammatory bowel disease (n = 5, 7.0%), congenital (n = 3, 4.2%), trauma (n = 2, 2.8%), radiation (n = 1, 1.4%), and in two patients, the cause was unclear. Most fistulas were in a mid or low position. Several endoscopic repair methods were included, namely transanal endoscopic microsurgery, endoscopic clipping, and endoscopic stenting. Most patients underwent > 1-year follow-up, and the success rate was 40%-93%, and all cases reported successful closure. Few complications were mentioned, while postoperative quality of life assessment was only mentioned in one study. CONCLUSION: In conclusion, endoscopic repair of RVF is novel, minimally invasive and promising with acceptable preliminary effectiveness. Given its unique advantages, endoscopic repair can be an alternative technique for surgeons.

Impacts of urea and 3,4-dimethylpyrazole phosphate on nitrification, targeted ammonia oxidizers, non-targeted nitrite oxidizers, and bacteria in two contrasting soils.

This study explored the effects of combined urea and 3,4-dimethylpyrazole phosphate (DMPP) on several components critical to the soil system: net nitrification rates; communities of targeted ammonia oxidizers [ammonia-oxidizing archaea (AOA) and bacteria (AOB) and complete ammonia-oxidizing bacteria (comammox)]; non-targeted nitrite-oxidizing bacteria (NOB) and bacteria. We conducted the study in two contrasting soils (acidic and neutral) over the course of 28 days. Our results indicated that DMPP had higher inhibitory efficacy in the acidic soil (30.7%) compared to the neutral soil (12.1%). The abundance of AOB and Nitrospira-like NOB were positively associated with nitrate content in acidic soil. In neutral soil, these communities were joined by the abundance of AOA and Nitrobacter-like NOB in being positively associated with nitrate content. By blocking the growth of AOB in acidic soil-and the growth of both AOB and comammox in neutral soil-DMPP supported higher rates of AOA growth. Amplicon sequencing of the 16S rRNA gene revealed that urea and urea + DMPP treatments significantly increased the diversity indices of bacteria, including Chao 1, ACE, Shannon, and Simpson in the acidic soil but did not do so in the neutral soil. However, both urea and urea + DMPP treatments obviously altered the community structure of bacteria in both soils relative to the control treatment. This experiment comprehensively analyzed the effects of urea and nitrification inhibitor on functional guilds involved in the nitrification process and non-targeted bacteria, not just focus on targeted ammonia oxidizers.

Effects of biochar and chemical fertilizer amendment on diazotrophic abundance and community structure in rhizosphere and bulk soils.

Diazotrophs carry out biological nitrogen (N) fixation process that replenishes available soil N; it is unclear how soil diazotrophic communities respond to biochar and chemical fertilizer amendment in agricultural ecosystem. Herein, we studied the impacts of biochar and chemical fertilizer amendment on diazotrophic communities in rhizosphere and bulk soils using nifH gene. The field experiment included four treatments: control (CK), biochar (B), chemical NPK fertilizer (CF), and biochar + chemical fertilizer (B + CF). nifH gene abundance in rhizosphere soils ranged from 9.00 × 107 to 2.57 × 108 copies g-1 dry soil among the different treatments, which was 1.42-2.68 times higher compared with the bulk soils ranging from 5.83 × 107 to 1.19 × 108 copies g-1 dry soil. Single application of biochar increased the abundance of nifH gene, whereas chemical fertilizer addition significantly decreased it in the bulk and rhizosphere soils. Single biochar addition affected diazotrophic community composition in rhizosphere soil, but not in the bulk soil. However, both CF and B + CF treatments obviously changed the community structure of diazotrophs in both soils. Moreover, rhizosphere effect enhanced nifH gene abundance and significantly altered the diazotrophic community structure compared to bulk soil. Phylogenetic analysis showed that all nifH sequences were affiliated to the cyanobacteria, α-, ß-, γ-, and δ- subclasses of the proteobacteria group. Soil nutrient availability rather than pH had significant impacts on diazotrophic community structure based on mantel test and redundancy analysis. Overall, biochar improves the diazotrophic abundance, while chemical fertilization negatively affects it by altering nutrient availability, and combined application of biochar and chemical fertilizer does not counteract the adverse influences of chemical fertilizer on nitrogen-fixing microorganisms.

Ammonia- and Nitrite-Oxidizing Bacteria are Dominant in Nitrification of Maize Rhizosphere Soil Following Combined Application of Biochar and Chemical Fertilizer.

Autotrophic nitrification is regulated by canonical ammonia-oxidizing archaea (AOA) and bacteria (AOB) and nitrite-oxidizing bacteria (NOB). To date, most studies have focused on the role of canonical ammonia oxidizers in nitrification while neglecting the NOB. In order to understand the impacts of combined biochar and chemical fertilizer addition on nitrification and associated nitrifiers in plant rhizosphere soil, we collected rhizosphere soil from a maize field under four different treatments: no fertilization (CK), biochar (B), chemical nitrogen (N) + phosphorus (P) + potassium (K) fertilizers (NPK), and biochar + NPK fertilizers (B + NPK). The potential nitrification rate (PNR), community abundances, and structures of AOA, AOB, complete ammonia-oxidizing bacteria (Comammox Nitrospira clade A), and Nitrobacter- and Nitrospira-like NOB were measured. Biochar and/or NPK additions increased soil pH and nutrient contents in rhizosphere soil. B, NPK, and B + NPK treatments significantly stimulated PNR and abundances of AOB, Comammox, and Nitrobacter- and Nitrospira-like NOB, with the highest values observed in the B + NPK treatment. Pearson correlation and random forest analyses predicted more importance of AOB, Comammox Nitrospira clade A, and Nitrobacter- and Nitrospira-like NOB abundances over AOA on PNR. Biochar and/or NPK additions strongly altered whole nitrifying community structures. Redundancy analysis (RDA) showed that nitrifying community structures were significantly affected by pH and nutrient contents. This research shows that combined application of biochar and NPK fertilizer has a positive effect on improving soil nitrification by affecting communities of AOB and NOB in rhizosphere soil. These new revelations, especially as they related to understudied NOB, can be used to increase efficiency of agricultural land and resource management.

Variable Selection from Image Texture Feature for Automatic Classification of Concrete Surface Voids.

Machine learning plays an important role in computational intelligence and has been widely used in many engineering fields. Surface voids or bugholes frequently appearing on concrete surface after the casting process make the corresponding manual inspection time consuming, costly, labor intensive, and inconsistent. In order to make a better inspection of the concrete surface, automatic classification of concrete bugholes is needed. In this paper, a variable selection strategy is proposed for pursuing feature interpretability, together with an automatic ensemble classification designed for getting a better accuracy of the bughole classification. A texture feature deriving from the Gabor filter and gray-level run lengths is extracted in concrete surface images. Interpretable variables, which are also the components of the feature, are selected according to a presented cumulative voting strategy. An ensemble classifier with its base classifier automatically assigned is provided to detect whether a surface void exists in an image or not. Experimental results on 1000 image samples indicate the effectiveness of our method with a comparable prediction accuracy and model explicable.