Nitrogen, manganese, iron, and carbon resource acquisition are potential functions of the wild rice Oryza rufipogon core rhizomicrobiome

Background: The assembly of the rhizomicrobiome, i.e., the microbiome in the soil adhering to the root, is influenced by soil conditions. Here, we investigated the core rhizomicrobiome of a wild plant species transplanted to an identical soil type with small differences in chemical factors and the impact of these soil chemistry differences on the core microbiome after long-term cultivation. We sampled three natural reserve populations of wild rice (i.e., in situ) and three populations of transplanted in situ wild rice grown ex situ for more than 40 years to determine the core wild rice rhizomicrobiome. Results: Generalized joint attribute modeling (GJAM) identified a total of 44 amplicon sequence variants (ASVs) composing the core wild rice rhizomicrobiome, including 35 bacterial ASVs belonging to the phyla Actinobacteria, Chloroflexi, Firmicutes, and Nitrospirae and 9 fungal ASVs belonging to the phyla Ascomycota, Basidiomycota, and Rozellomycota. Nine core bacterial ASVs belonging to the genera Haliangium, Anaeromyxobacter, Bradyrhizobium, and Bacillus were more abundant in the rhizosphere of ex situ wild rice than in the rhizosphere of in situ wild rice. The main ecological functions of the core microbiome were nitrogen fixation, manganese oxidation, aerobic chemoheterotrophy, chemoheterotrophy, and iron respiration, suggesting roles of the core rhizomicrobiome in improving nutrient resource acquisition for rice growth. The function of the core rhizosphere bacterial community was significantly (p < 0.05) shaped by electrical conductivity, total nitrogen, and available phosphorus present in the soil adhering to the roots. Conclusion: We discovered that nitrogen, manganese, iron, and carbon resource acquisition are potential functions of the core rhizomicrobiome of the wild rice Oryza rufipogon. Our findings suggest that further potential utilization of the core rhizomicrobiome should consider the effects of soil properties on the abundances of different genera. [MediaObject not available: see fulltext.]

CT-Based Risk Factors for Mortality of Patients With COVID-19 Pneumonia in Wuhan, China: A Retrospective Study

Purpose: Computed tomography (CT) characteristics associated with critical outcomes of patients with coronavirus disease 2019 (COVID-19) have been reported. However, CT risk factors for mortality have not been directly reported. We aim to determine the CT-based quantitative predictors for COVID-19 mortality.Methods: In this retrospective study, laboratory-confirmed COVID-19 patients at Wuhan Central Hospital between December 9, 2019, and March 19, 2020, were included. A novel prognostic biomarker, V-HU score, depicting the volume (V) of total pneumonia infection and the average Hounsfield unit (HU) of consolidation areas was automatically quantified from CT by an artificial intelligence (AI) system. Cox proportional hazards models were used to investigate risk factors for mortality.Results: The study included 238 patients (women 136/238, 57%; median age, 65 years, IQR 51–74 years), 126 of whom were survivors. The V-HU score was an independent predictor (hazard ratio [HR] 2.78, 95% confidence interval [CI] 1.50–5.17; p = 0.001) after adjusting for several COVID-19 prognostic indicators significant in univariable analysis. The prognostic performance of the model containing clinical and outpatient laboratory factors was improved by integrating the V-HU score (c-index: 0.695 vs. 0.728; p &lt; 0.001). Older patients (age ≥ 65 years; HR 3.56, 95% CI 1.64–7.71; p &lt; 0.001) and younger patients (age &lt; 65 years; HR 4.60, 95% CI 1.92–10.99; p &lt; 0.001) could be further risk-stratified by the V-HU score.Conclusions: A combination of an increased volume of total pneumonia infection and high HU value of consolidation areas showed a strong correlation to COVID-19 mortality, as determined by AI quantified CT

Comparison of methane metabolism in the rhizomicrobiomes of wild and related cultivated rice accessions reveals a strong impact of crop domestication

Microbial communities from rhizosphere (rhizomicrobiomes) have been significantly impacted by domestication as evidenced by a comparison of the rhizomicrobiomes of wild and related cultivated rice accessions. While there have been many published studies focusing on the structure of the rhizomicrobiome, studies comparing the functional traits of the microbial communities in the rhizospheres of wild rice and cultivated rice accessions are not yet available. In this study, we used metagenomic data from experimental rice plots to analyze the potential functional traits of the microbial communities in the rhizospheres of wild rice accessions originated from Africa and Asia in comparison with their related cultivated rice accessions. The functional potential of rhizosphere microbial communities involved in alanine, aspartate and glutamate metabolism, methane metabolism, carbon fixation pathways, citrate cycle (TCA cycle), pyruvate metabolism and lipopolysaccharide biosynthesis pathways were found to be enriched in the rhizomicrobiomes of wild rice accessions. Notably, methane metabolism in the rhizomicrobiomes of wild and cultivated rice accessions clearly differed. Key enzymes involved in methane production and utilization were overrepresented in the rhizomicrobiome samples obtained from wild rice accessions, suggesting that the rhizomicrobiomes of wild rice maintain a different ecological balance for methane production and utilization compared with those of the related cultivated rice accessions. A novel assessment of the impact of rice domestication on the primary metabolic pathways associated with microbial taxa in the rhizomicrobiomes was performed. Results indicated a strong impact of rice domestication on methane metabolism; a process that represents a critical function of the rhizosphere microbial community of rice. The findings of this study provide important information for future breeding of rice varieties with reduced methane emission during cultivation for sustainable agriculture

Genome-Wide Identification of DUF26 Domain-Containing Genes in Dongxiang Wild Rice and Analysis of Their Expression Responses under Submergence

The DUF26 domain-containing protein is an extracellular structural protein, which plays an important role in signal transduction. Dongxiang wild rice (Oryza rufipogon Griff.) is the northern-most common wild rice in China. Using domain analysis, 85 DUF26 domain-containing genes were identified in Dongxiang wild rice (DXWR) and further divided into four categories. The DUF26 domain-containing genes were unevenly distributed on chromosomes, and there were 18 pairs of tandem repeats. Gene sequence analysis showed that there were significant differences in the gene structure and motif distribution of the DUF26 domain in different categories. Motifs 3, 8, 9, 13, 14, 16, and 18 were highly conserved in all categories. It was also found that there were eight plasmodesmata localization proteins (PDLPs) with a unique motif 19. Collinearity analysis showed that DXWR had a large number of orthologous genes with wheat, maize, sorghum and zizania, of which 17 DUF26 domain-containing genes were conserved in five gramineous crops. Under the stress of anaerobic germination and seedling submergence treatment, 33 DUF26 domain-containing genes were differentially expressed in varying degrees. Further correlation analysis with the expression of known submergence tolerance genes showed that these DUF26 domain-containing genes may jointly regulate the submergence tolerance process with these known submergence tolerance genes in DXWR

Combination of Genomics, Transcriptomics Identifies Candidate Loci Related to Cold Tolerance in Dongxiang Wild Rice

Rice, a cold-sensitive crop, is a staple food for more than 50% of the world’s population. Low temperature severely compromises the growth of rice and challenges China’s food safety. Dongxiang wild rice (DXWR) is the most northerly common wild rice in China and has strong cold tolerance, but the genetic basis of its cold tolerance is still unclear. Here, we report quantitative trait loci (QTLs) analysis for seedling cold tolerance (SCT) using a high-density single nucleotide polymorphism linkage map in the backcross recombinant inbred lines that were derived from a cross of DXWR, and an indica cultivar, GZX49. A total of 10 putative QTLs were identified for SCT under 4 °C cold treatment, each explaining 2.0–6.8% of the phenotypic variation in this population. Furthermore, transcriptome sequencing of DXWR seedlings before and after cold treatment was performed, and 898 and 3413 differentially expressed genes (DEGs) relative to 0 h in cold-tolerant for 4 h and 12 h were identified, respectively. Gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) analysis were performed on these DEGs. Using transcriptome data and genetic linkage analysis, combined with qRT-PCR, sequence comparison, and bioinformatics, LOC_Os08g04840 was putatively identified as a candidate gene for the major effect locus qSCT8. These findings provided insights into the genetic basis of SCT for the improvement of cold stress potential in rice breeding programs

Implementation Process Simulation and Performance Analysis for the Multi-Timescale Lookup-Table-Based Maximum Power Point Tracking under Variable Irregular Waves

The efficacy of the multi-timescale lookup-table-based maximum power point tracking (MLTB MPPT) in capturing energy at various fixed sea states has already been demonstrated. However, it remains imperative to conduct a more comprehensive evaluation of the MPPT tracking performance under varying sea states in practical scenarios. Additionally, it is crucial to engage in an in-depth analysis of the dynamic process and energy loss/consumption associated with MLTB MPPT implementations. This paper focuses on the implementation process simulation and performance analysis for the MLTB MPPT under variable irregular waves. Firstly, the structure of the wave power controller based on a MLTB MPPT algorithm is described in detail, as well as that of a controlled plant, known as a novel inverse-pendulum wave energy converter (NIPWEC). Secondly, mathematical models for the MLTB MPPT are developed, taking into account the efficiency of each link. In this paper, we present simplified modelling methods for both permanent magnet synchronous generator (PMSG) vector control and permanent magnet synchronous motor (PMSM) servo control. Finally, the tracking performance of the MLTB MPPT in the presence of variable irregular waves is comprehensively analyzed by simulating the implementation process and comparing it with two other MPPT algorithms, i.e., the frequency- and amplitude-control-based MPPT and the lookup-table-based internal mass position adjustment combined with the optimal fixed damping search. Results show that the MLTB MPPT (Method 2) is a competitive algorithm. Besides, a significant portion (>12%) of the time-averaged absorbed power is actually lost during the power generation process. On the other hand, the power required for a mass-position-adjusting mechanism is relatively small (approximately 0.2 kW, <1.5%). The research findings can offer theoretical guidance for optimizing the operation of NIPWEC engineering prototypes under actual sea conditions

Monitoring and Risk Assessment of Pesticide Residues in Tea Samples from China

<div><p>ABSTRACT</p><p>In the present study an effort was made to monitor the residue levels of 32 pesticides in tea samples collected from three representative tea districts of China during 2010 to 2012. A total of 223 samples of green tea, pu-erh tea, black tea, and oolong tea were determined using gas chromatography with mass spectrometry (GC-MS). Among 223 samples, 198 samples contained pesticide residues, and 39 samples had residue levels that were more than the European Union (EU) maximum residue limits (MRLs). The most positive and violated MLRs were observed in Oolong tea. The highest detection rates and the most often exceeding the MRLs were observed for the residues of bifenthrin. Ten pesticides were not found in the 223 tea samples. The potential health risks to consumers due to tea consumption in three representative cities were estimated. The results suggested that non-cancer hazards of organophosphorus, organochlorines, and pyrethroids and the cancer risks from exposure to hexachlorobenzene, heptachlor, chlordane, and pp’-DDT were clearly below the safe limit. Nevertheless, an investigation into continuous monitoring and tighter regulation of pesticide residues in tea samples are almost always desirable or even necessary for public health protection.</p></div

circ-Amotl1 in extracellular vesicles derived from ADSCs improves wound healing by upregulating SPARC translation

Aim: This study aims to explore the mechanism of circ- AMOT-like protein 1 (Amotl1) in extracellular vesicles (Evs) derived from adipose-derived stromal cells (ADSCs) regulating SPARC translation in wound healing process. Methods: The morphology, wound healing rate of the wounds and Ki67 positive rate in mouse wound healing models were assessed by H&E staining and immunohistochemistry (IHC). The binding of IGF2BP2 and SPARC was verified by RNA pull-down. Adipose-derived stromal cells (ADSCs) were isolated and verified. The Evs from ADSCs (ADSC-Evs) were analyzed. Results: Overexpression of SPARC can promote the wound healing process in mouse models. IGF2BP2 can elevate SPARC expression to promote the proliferation and migration of HSFs. circ-Amotl1 in ADSC-Evs can increase SPARC expression by binding IGF2BP2 to promote the proliferation and migration of HSFs. Conclusion: ADSC-Evs derived circ-Amotl1 can bind IGF2BP2 to increase SPARC expression and further promote wound healing process