Multiparametric magnetic resonance imaging-based assessment of the effect of adenomyosis on determining the depth of myometrial invasion in endometrial cancer.

Background: Accurate preoperative diagnosis of endometrial cancer (EC) with deep myometrial invasion (DMI) is critical to deciding whether to perform lymphadenectomy. However, the presence of adenomyosis makes distinguishing DMI from superficial myometrial invasion (SMI) on magnetic resonance imaging (MRI) challenging. We aimed to evaluate the accuracy of multiparametric MRI (mpMRI) in diagnosing DMI in EC coexisting with adenomyosis (EC-A) compared with EC without coexisting adenomyosis and to evaluate the effect of different adenomyosis subtypes on myometrial invasion (MI) depth in EC. Methods: Patients with histologically confirmed International Federation of Gynecology and Obstetrics (FIGO) stage I EC who underwent preoperative MRI were consecutively included in this 2-center retrospective study. Institution 1 was searched from January 2017 to November 2022 and institution 2 was searched from June 2017 to March 2021. Patients were divided into 2 groups: group A, patients with EC-A; group B, EC patients without coexisting adenomyosis, matched 1:2 according to age ±5 years and tumor grade. A senior radiologist assessed the MRI adenomyosis classification in group A. Then, 2 radiologists (R1/R2) independently interpreted T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), T1-weighted contrast-enhanced (T1CE), and a combination of all images (mpMRI) respectively, and then assessed MI depth. Accuracy, sensitivity, specificity, and the areas under the receiver operating curve (AUC) were calculated. The chi-square test was used to compare the accuracy of diagnosing DMI. Interobserver agreement was evaluated using the Kappa test. Results: A total of 70 cases in group A and 140 cases in group B were included. The accuracy, sensitivity, and specificity of consensus were 94.3% [95% confidence interval (CI): 88.9-99.7%] vs. 92.1% (95% CI: 87.7-96.6%), 60.0% (95% CI: 17-92.7%) vs. 86.7% (95% CI: 68.4-95.6%), and 96.9% (95% CI: 88.4-95.5%) vs. 93.6% (95% CI: 86.8-97.2%) (group A vs. group B, respectively). There was no significant difference in the diagnostic accuracy of DMI on each sequence between the groups (Reviewer 1/Reviewer 2): PT2WI=0.14/0.17, PDWI=0.50/0.33, PT1CE=0.90/0.18, PmpMRI=0.50/0.37. The AUC for T2WI, DWI, T1CE, and mpMRI (Reviewer 1/Reviewer 2), respectively, were 0.54 (95% CI: 0.42-0.66)/0.78 (95% CI: 0.67-0.87), 0.63 (95% CI: 0.50-0.74)/0.77 (95% CI: 0.65-0.86), 0.69 (95% CI: 0.57-0.80)/0.79 (95% CI: 0.68-0.88), and 0.91 (95% CI: 0.82-0.97)/0.89 (95% CI: 0.79-0.95) (group A) and 0.83 (95% CI: 0.76-0.89)/0.85 (95% CI: 0.78-0.90), 0.83 (95% CI: 0.76-0.89)/0.86 (95% CI: 0.79-0.91), 0.88 (95% CI: 0.82-0.93)/0.86 (95% CI: 0.80-0.92), and 0.91 (95% CI: 0.85-0.95)/0.87 (95% CI: 0.80-0.92) (group B). Interobserver agreement was highest with mpMRI [κ=0.387/0.695 (case/control)]. The consensus results of MRI categorization of adenomyosis revealed no significant difference in the accuracy of diagnosing DMI by adenomyosis subtype (Pspatial relationship>0.99, Paffected area=0.52, Paffected pattern=0.58, Paffected size>0.99). Conclusions: The presence of adenomyosis or adenomyosis subtype had no significant effect on the interpretation of the depth of MI. T1CE can increase the contrast between adenomyosis and cancer foci; therefore, the information provided by T1CE should be valued.

Warming Leads to Changes in Soil Organic Carbon Molecules Due to Decreased Mineral Protection.

Climate change affects the content and composition of soil organic carbon (SOC). However, warming-induced changes in the SOC compounds remain unknown. Using nuclear magnetic resonance spectroscopy, molecular mixing models, and Fourier transform ion cyclotron resonance mass spectrometry, we analyzed the variations and relationships in molecular compounds in Mollisol with 10-56 g C kg-1 soil-1 by translocating soils under six climate regimes. We found that increased temperature and precipitation were negatively correlated with carbohydrate versus lipid and lignin versus protein. The former was consistent across soils with varying SOC contents, but the latter decreased as the SOC content increased. The carbohydrate-lipid correlations were related to dithionite-citrate-extractable Fe, while the lignin-protein correlations were linked to changes in moisture and pyrophosphate-extractable Fe/Al. Our findings indicate that the reduction in the mineral protection of SOC is associated with molecular alterations in SOC under warming conditions.

Nitrogen-fixing cyanobacteria enhance microbial carbon utilization by modulating the microbial community composition in paddy soils of the Mollisols region.

Nitrogen-fixing cyanobacteria (NFC) are photosynthetic prokaryotic microorganisms capable of nitrogen fixation. They can be used as biofertilizers in paddy fields, thereby improving the rice tillering capacity and yield. To reveal the microbiological mechanisms by which nitrogen-fixing cyanobacteria alter soil carbon storage, we conducted a field experiment using NFC as a partial substitute for nitrogen fertilizer in paddy fields in the Sanjiang Plain of Northeast China's Mollisols region. Using metagenomic sequencing technology and Biolog Ecoplate™ carbon matrix metabolism measurements, we explored the changes in the soil microbial community structure and carbon utilization in paddy fields. The results indicated that the replacement of nitrogen fertilizer with NFC predisposed the soil microbial community to host a great number of copiotrophic bacterial taxa, and Proteobacteria and Actinobacteria were closely associated with the metabolism of soil carbon sources. Moreover, through co-occurrence network analysis, we found that copiotrophic bacteria clustered in modules that were positively correlated with the metabolic level of carbon sources. The addition of NFC promoted the growth of copiotrophic bacteria, which increased the carbon utilization level of soil microorganisms, improved the diversity of the microbial communities, and had a potential impact on the soil carbon stock. The findings of this study are helpful for assessing the impact of NFC on the ecological function of soil microbial communities in paddy fields in the black soil area of Northeast China, which is highly important for promoting sustainable agricultural development and providing scientific reference for promoting the use of algal-derived nitrogen fertilizers.

Identification of glycosyltransferase-related genes signature and integrative analyses in patients with ovarian cancer.

BACKGROUND: Glycosyltransferases (GT) play a crucial role in glycosylation reactions, and aberrant expression of glycosyltransferase-related genes (GTs) leads to abnormal glycosylation, which is associated with tumor progression. However, the prognostic value of aberrant expression of GTs in ovarian cancer (OC) and the correlation between GTs and tumor microenvironment (TME) remain unknown. METHODS: TCGA and GSE53963 databases were used to obtain data on OC patient samples. The association of GTs with OC was analyzed. Molecular subtypes were identified by consensus unsupervised clustering, followed by immune infiltration and functional enrichment analyses. Survival analysis was performed using Kaplan-Meier curves and log-rank tests. Least Absolute Shrinkage and Selection Operator (LASSO) and multifactorial cox regression were used to screen for signature genes associated with OC and used to establish prognostic models. RESULT: OC patients were categorized into 5 GTs clusters using consensus unsupervised cluster analysis. Clusters D and E showed significant differences between survival, signaling pathways and immune infiltration. Then, a risk model was developed based on the 12 signature genes, which provides a more accurate evaluation of the prognosis of OC patients. We categorized patients into high-risk and low-risk groups based on the risk score and found that the survival of patients in the high-risk group was significantly lower than that in the low-risk group. Moreover, the risk score was significantly correlated with tumor microenvironment, immune infiltration, and chemotherapy sensitivity. CONCLUSION: Overall, we performed a comprehensive analysis of GTs in OC patients and developed a risk model for OC. Our findings will provide a new insight to OC prognosis and treatment.

Exploring the role of NAA40 in immune infiltrates and prognostic prediction in hepatocellular carcinoma.

NAA40 belongs to the N-terminal acetyltransferase (NATs) family, responsible for protein N-terminal modification, and it exerts crucial roles across various cancers. However, its impact on patient prognosis and immune infiltration in hepatocellular carcinoma (HCC) remains elusive. To address this, our study delved into the comprehensive analysis of NAA40 in the context of cancer. Our pan-cancer analysis unveiled elevated NAA40 expression in multiple tumor types, including BLCA, BRCA, CHOL, COAD, ESCA, HNSC, LIHC, LUAD, LUSC, STAD, and THCA. Additionally, through a comprehensive examination across various cancer types within TCGA, we discovered that high NAA40 gene expression correlated with poor prognosis in HCC, pointing toward its role in promoting oncogenesis. Further investigation illuminated the association of increased NAA40 expression with T stage, pathologic stage, tumor status, and histologic grade. Interestingly, we noted a significant inverse correlation between NAA40 expression and the infiltration levels of immune cells, such as DC cells, neutrophils, NK cells, and T cells, in liver cancer. This observation underpins the hypothesis that NAA40 influences HCC development by modulating immune cell infiltration. Functional enrichment analysis provided valuable insights into the pathways influenced by NAA40. Enriched pathways encompassed oxidative phosphorylation, xenobiotic metabolism, bile acid metabolism, fatty acid metabolism, G2M checkpoint, and E2F targets. These findings collectively position NAA40 as a potential biomarker for prognostic prediction and monitoring the effects of immunotherapy in HCC.

Effect of interaction between dissolved organic matter and iron/manganese (hydrogen) oxides on the degradation of organic pollutants by in-situ advanced oxidation techniques.

Iron and manganese (hydrogen) oxides (IMHOs) exhibit excellent redox capabilities for environmental pollutants and are commonly used in situ chemical oxidation (ISCO) technologies for the degradation of organic pollutants. However, the coexisting dissolved organic matter (DOMs) in surface environments would influence the degradation behavior and fate of organic pollutants in IMHOs-based ISCO. This review has summarized the interactions and mechanisms between DOMs and IMHOs, as well as the properties of DOM-IMHOs complexes. Importantly, the promotion or inhibition impact of DOM was discussed from three perspectives. First, the presence of DOMs may hinder the accessibility of active sites on IMHOs, thus reducing their efficiency in degrading organic pollutants. The formation of compounds between DOMs and IMHOs alters their stability and activity in the degradation process. Second, the presence of DOMs may also affect the generation and transport of active species, thereby influencing the oxidative degradation process of organic pollutants. Third, specific components within DOMs also participate and affect the degradation pathways and rates. A comprehensive understanding of the interaction between DOMs and IMHOs helps to better understand and predict the degradation process of organic pollutants mediated by IMHOs in real environmental conditions and contributes to the further development and application of IMHO-mediated ISCO technology.

Multiple spatial scales of bacterial and fungal structural and functional traits affect carbon mineralization.

Studying the functional heterogeneity of soil microorganisms at different spatial scales and linking it to soil carbon mineralization is crucial for predicting the response of soil carbon stability to environmental changes and human disturbance. Here, a total of 429 soil samples were collected from typical paddy fields in China, and the bacterial and fungal communities as well as functional genes related to carbon mineralization in the soil were analysed using MiSeq sequencing and GeoChip gene microarray technology. We postulate that CO2 emissions resulting from bacterial and fungal carbon mineralization are contingent upon their respective carbon consumption strategies, which rely on the regulation of interactions between biodiversity and functional genes. Our results showed that the spatial turnover of the fungal community was 2-4 times that of the bacterial community from hundreds of meters to thousands of kilometres. The effect of spatial scale exerted a greater impact on the composition rather than the functional characteristics of the microbial community. Furthermore, based on the establishment of functional networks at different spatial scales, we observed that both bacteria and fungi within the top 10 taxa associated with carbon mineralization exhibited a prevalence of generalist species at the regional scale. This study emphasizes the significance of spatial scaling patterns in soil bacterial and fungal carbon degradation functions, deepening our understanding of how the relationship between microbial decomposers and soil heterogeneity impacts carbon mineralization and subsequent greenhouse gas emissions.

Deciphering microbiomes dozens of meters under our feet and their edaphoclimatic and spatial drivers.

Microbes inhabiting deep soil layers are known to be different from their counterpart in topsoil yet remain under investigation in terms of their structure, function, and how their diversity is shaped. The microbiome of deep soils (>1 m) is expected to be relatively stable and highly independent from climatic conditions. Much less is known, however, on how these microbial communities vary along climate gradients. Here, we used amplicon sequencing to investigate bacteria, archaea, and fungi along fifteen 18-m depth profiles at 20-50-cm intervals across contrasting aridity conditions in semi-arid forest ecosystems of China's Loess Plateau. Our results showed that bacterial and fungal α diversity and bacterial and archaeal community similarity declined dramatically in topsoil and remained relatively stable in deep soil. Nevertheless, deep soil microbiome still showed the functional potential of N cycling, plant-derived organic matter degradation, resource exchange, and water coordination. The deep soil microbiome had closer taxa-taxa and bacteria-fungi associations and more influence of dispersal limitation than topsoil microbiome. Geographic distance was more influential in deep soil bacteria and archaea than in topsoil. We further showed that aridity was negatively correlated with deep-soil archaeal and fungal richness, archaeal community similarity, relative abundance of plant saprotroph, and bacteria-fungi associations, but increased the relative abundance of aerobic ammonia oxidation, manganese oxidation, and arbuscular mycorrhizal in the deep soils. Root depth, complexity, soil volumetric moisture, and clay play bridging roles in the indirect effects of aridity on microbes in deep soils. Our work indicates that, even microbial communities and nutrient cycling in deep soil are susceptible to changes in water availability, with consequences for understanding the sustainability of dryland ecosystems and the whole-soil in response to aridification. Moreover, we propose that neglecting soil depth may underestimate the role of soil moisture in dryland ecosystems under future climate scenarios.

[Functional Genomics Analysis of Nitrogen and Phosphorus Transformation in Maize Rhizosphere Microorganisms].

Fertilizer reduction and efficiency improvement is an important basis for ensuring the safety of the agricultural ecological environment. Microorganisms are the key driving force for regulating the soil nitrogen and phosphorus cycle. Studying the nitrogen and phosphorus transformation function of rhizosphere microorganisms can provide a microbiological regulation approach for further improving the use efficiency of soil nitrogen and phosphorus. Based on the field micro-plot experiments of three typical farmland soils(phaeozem, cambisol, and acrisol), metagenomic sequencing technology was used to study the differences in functional genes and regulatory factors of maize rhizosphere microorganisms during soil nitrogen and phosphorus transformation. The results showed that the functional diversity of maize rhizosphere microorganisms was affected by soil type. The functional diversity of rhizosphere microorganisms in phaeozem and cambisol was mainly affected by water content and nutrient content, and that in acrisol was affected by total phosphorus(TP) and available phosphorus(AP). For soil nitrogen transformation, the gene abundance of related enzymes in the pathway of nitrogen transformation was the highest in the urease gene(ureC) and glucose dehydrogenase gene(gdh), which were 7.25×10-5-12.88×10-5 and 4.47×10-5-7.49×10-5, respectively. The total abundance of assimilatory nitrate reduction functional genes in acrisol was higher than that in phaeozem and cambisol, and the total abundance of functional genes related to other processes was the highest in cambisol. The abundance of functional genes encoding enzymes related to nitrogen metabolism was mainly driven by soil bacterial richness, total potassium(TK), and TP. For soil phosphorus transformation, the number of alkaline phosphatase genes(phoD) catalyzing organic phosphorus mineralization was 1093, and the number of acid phosphatase genes(PHO) was 42. The abundance of phoD was two orders of magnitude higher than that of PHO. In addition, fertilization had no significant effect on the abundance of phoD and PHO in the same soil type. Random forest analysis showed that the abundances of phoD and PHO were significantly affected by soil moisture, organic matter(OM), and total nitrogen(TN), but AP content had the greatest impact on PHO abundance. These results clarified the nitrogen and phosphorus transformation characteristics of maize rhizosphere microorganisms at the functional genomic level and enriched the molecular biological mechanism of the microbial nitrogen and phosphorus transformation function.

Deciphering Biotic and Abiotic Mechanisms Underlying Straw Decomposition and Soil Organic Carbon Priming in Agriculture Soils Receiving Long-Term Fertilizers.

Straw-related carbon (C) dynamics are central for C accrual in agro-ecosystems and should be assessed by investigating their decomposition and soil organic carbon (SOC) priming effects. Our understanding of biotic and abiotic mechanisms underpinning these two C processes, however, is still not sufficiently profound. Soils that had received organic and mineral fertilizers for 26 years were sampled for a 28 day incubation experiment to assess 13C-labeled straw decomposition and SOC priming effects. On the basis of analyzing physicochemical properties, fungal taxonomic (MiSeq sequencing) and functional (metagenomics) guilds, we quantified the contributions of biotic and abiotic attributes to straw decomposition and SOC priming. Here, we propose two distinct mechanisms underlying straw decomposition and SOC priming in agriculture soils: (i) accelerated straw mineralization in manure-treated soils was mainly driven by biotic forces, while (ii) larger SOC priming in NPK-amended soils was through abiotic regulation.

Root microbiota confers rice resistance to aluminium toxicity and phosphorus deficiency in acidic soils.

Aluminium (Al) toxicity impedes crop growth in acidic soils and is considered the second largest abiotic stress after drought for crops worldwide. Despite remarkable progress in understanding Al resistance in plants, it is still unknown whether and how the soil microbiota confers Al resistance to crops. Here we found that a synthetic community composed of highly Al-resistant bacterial strains isolated from the rice rhizosphere increased rice yield by 26.36% in acidic fields. The synthetic community harvested rhizodeposited carbon for successful proliferation and mitigated soil acidification and Al toxicity through extracellular protonation. The functional coordination between plants and microbes offers a promising way to increase the usage of legacy phosphorus in topsoil. These findings highlight the potential of microbial tools for advancing sustainable agriculture in acidic soils.

Transcriptome profiling and ceRNA network of small extracellular vesicles from resting and degranulated mast cells.

Aim: This study aimed to investigate the transcriptomic characteristics and interactions between competitive endogenous RNAs (ceRNAs) within small extracellular vesicles (sEVs) derived from mast cells (MCs). Methods: Transcriptome sequencing analyzed lncRNA, circRNA and mRNA expression in resting and degranulated MC-derived sEVs. Constructed ceRNA regulatory network through correlation analysis and target gene prediction. Results: Differentially expressed 1673 mRNAs, 173 lncRNAs and 531 circRNAs were observed between resting and degranulated MCs-derived sEVs. Enrichment analysis revealed involvement of neurodegeneration, infection and tumor pathways. CeRNA networks included interactions between lncRNA-miRNA, circRNA-miRNA and miRNA-mRNA, targeting genes in the hippo and wnt signaling pathways linked to tumor immune regulation. Conclusion: This study provides valuable insights into MC-sEV molecular mechanisms, offering significant data resources for further investigations.

Mast cells (MCs) are important for various health conditions, including allergies, infections, tumors and brain disorders. MCs release tiny structures called small extracellular vesicles (sEVs) that carry different molecules, such as genetic material, to communicate with other cells in the body's immune system. However, we still do not know much about how these sEVs work. In this study, we examined the sEVs from MCs and found specific genetic molecules that change when MCs become activated. We discovered that these molecules are involved in important processes related to diseases like neurodegeneration and infection. We also identified networks of molecules that interact with each other, influencing immune regulation of tumor. By studying this, we gain new knowledge about how MCs use sEVs to communicate with other cells in our body during immune responses.

Knowledge diffusion of Geodetector: A perspective of the literature review and Geotree.

Spatial heterogeneity is a fundamental research topic in the field of geography, and Geodetector is a widely used tool for studying this phenomenon. To understand the research advancements and knowledge diffusion trends surrounding Geodetector, we constructed an author evolutionary tree structure fusing its 847 core citations in the Web of Science database and Geotree model for the first time. The results of our literature statistics indicated that Geodetector has garnered the attention of 3123 authors from 48 countries since its publication in the Ecological Indicators journal in 2010, who have published core papers concerning ten important topics. The majority of these studies focused on spatial heterogeneity and its influencing factors. Our analysis of Geotree data revealed a significant correlation between the publication rate of scholars in large teams and their academic activities. Our analysis of the knowledge diffusion chain shown that only 2% of the total number of authors have contributed to over 20% of the scientific collaborations and knowledge diffusion, and they were recognized as experts in Geodetector research. To provide a comprehensive reference for future scholars, we have summarized the citing countries, five classical articles, main scientific domains, and core teams of Geodetector research.

Drivers of microbially and plant-derived carbon in topsoil and subsoil.

Plant- and microbially derived carbon (C) are the two major sources of soil organic matter (SOM), and their ratio impacts SOM composition, accumulation, stability, and turnover. The contributions of and the key factors defining the plant and microbial C in SOM along the soil profile are not well known. By leveraging nuclear magnetic resonance spectroscopy and biomarker analysis, we analyzed the plant and microbial C in three soil types using regional-scale sampling and combined these results with a meta-analysis. Topsoil (0-40 cm) was rich in carbohydrates and lignin (38%-50%), whereas subsoil (40-100 cm) contained more proteins and lipids (26%-60%). The proportion of plant C increases, while microbial C decreases with SOM content. The decrease rate of the ratio of the microbially derived C to plant-derived C (CM:P ) with SOM content was 23%-30% faster in the topsoil than in the subsoil in the regional study and meta-analysis. The topsoil had high potential to stabilize plant-derived C through intensive microbial transformations and microbial necromass formation. Plant C input and mean annual soil temperature were the main factors defining CM:P in topsoil, whereas the fungi-to-bacteria ratio and clay content were the main factors influencing subsoil CM:P . Combining a regional study and meta-analysis, we highlighted the contribution of plant litter to microbial necromass to organic matter up to 1-m soil depth and elucidated the main factors regulating their long-term preservation.

IL18R1-Related Molecules as Biomarkers for Asthma Severity and Prognostic Markers for Idiopathic Pulmonary Fibrosis.

To determine the role of inflammation-related proteins in predicting asthma severity and outcome, 92 inflammation-related proteins were measured in the asthmatic serum using Olink analysis. Different bioinformatics algorithms were developed to cross analyze with the single-cell or transcriptome data sets from the Gene Expression Omnibus database to explore the role of IL18R1 and related genes in asthma and idiopathic pulmonary fibrosis (IPF). Olink identified 52 differentially expressed proteins in asthma. They were strongly linked to the cytokine-cytokine receptor interaction, TNF, and NF-κB signaling pathway. Seven proteins were found in both single-cell RNA and Olink analyses. Among them, IL18R1 was predominantly expressed in mast cells, and the results suggested enhanced communication between mast cells and CD 8+ T cells. IL18R1 was upregulated in serum and induced sputum and bronchoalveolar lavage fluid of patients with uncontrolled or severe asthma. IL18R1 was positively correlated with TNFSF1 and OSM and S100A12. The diagnostic efficacy of these serum IL18R1-related molecules for asthma ranged from 0.839 to 0.921. Moreover, high levels of IL18R1, TNFSF1, OSM, and S100A12 were significantly associated with shorter survival times and worse lung function. IL18R1-related molecules may serve as biomarkers for monitoring uncontrolled or severe asthma and as prognostic markers for IPF.

Analyzing the Material Basis of Anti-RSV Efficacy of Lonicerae japonicae Flos Based on the PK-PD Model.

Lonicerae japonicae Flos (LJF) possesses a good anti-respiratory syncytial virus (RSV) effect. However, the material basis of LJF in treating RSV is still unclear. In this study, a sensitive and accurate quantitative method based on UHPLC-QQQ MS was established and validated for the simultaneous determination of the 15 ingredients from LJF in RSV-infected mice plasma. Multiple reaction monitoring was performed for quantification of the standards and of the internal standard in plasma. All the calibration curves show good linear regression within the linear range (r2 > 0.9918). The method validation results, including specificity, linearity, accuracy, precision, extraction recovery, matrix effect, and stability of 15 ingredients, are all within the current acceptance criteria. This established method was successfully applied to the pharmacokinetic study of 15 compounds from LJF. Furthermore, the repair rate of lung index and the improvement rate of IFN-γ and IL-6 improved after administration of the LJF, indicating that LJF possessed a positive effect on the treatment of RSV infection. Finally, by combining Spearman and Grey relation analysis, isochlorogenic acid B, isochlorogenic acid C, secoxyloganin, chlorogenic acid, and loganic acid are speculated to be the main effective ingredients of LJF in treating RSV. This study lays the foundation for attempts to reveal the mechanisms of the anti-RSV effect of LJF.

Manual correction of genome annotation improved alternative splicing identification of Artemisia annua.

Gene annotation is essential for genome-based studies. However, algorithm-based genome annotation is difficult to fully and correctly reveal genomic information, especially for species with complex genomes. Artemisia annua L. is the only commercial resource of artemisinin production though the content of artemisinin is still to be improved. Genome-based genetic modification and breeding are useful strategies to boost artemisinin content and therefore, ensure the supply of artemisinin and reduce costs, but better gene annotation is urgently needed. In this study, we manually corrected the newly released genome annotation of A. annua using second- and third-generation transcriptome data. We found that incorrect gene information may lead to differences in structural, functional, and expression levels compared to the original expectations. We also identified alternative splicing events and found that genome annotation information impacted identifying alternative splicing genes. We further demonstrated that genome annotation information and alternative splicing could affect gene expression estimation and gene function prediction. Finally, we provided a valuable version of A. annua genome annotation and demonstrated the importance of gene annotation in future research.

Catalytic degradation of benzene over non-thermal plasma coupled Co-Ni binary metal oxide nanosheet catalysts.

Non-thermal plasma (NTP) has been demonstrated as one of the promising technologies that can degrade volatile organic compounds (VOCs) under ambient condition. However, one of the key challenges of VOCs degradation in NTP is its relatively low mineralization rate, which needs to be addressed by introducing catalysts. Therefore, the design and optimization of catalysts have become the focus of NTP coupling catalysis research. In this work, a series of two-dimensional nanosheet Co-Ni metal oxides were synthesized by microwave method and investigated for the catalytic oxidation of benzene in an NTP-catalysis coupling system. Among them, Co2Ni1Ox achieves 60% carbon dioxide (CO2) selectivity (SCO2) when the benzene removal efficiency (REbenzene) reaches more than 99%, which is a significant enhancement compared with the CO2 selectivity obtained without any catalysts (38%) under the same input power. More intriguingly, this SCO2 is also significantly higher than that of single metal oxides, NiO or Co3O4, which is only around 40%. Such improved performance of this binary metal oxide catalyst is uniquely attributed to the synergistic effects of Co and Ni in Co2Ni1Ox catalyst. The introduction of Co2Ni1Ox was found to promote the generation of acrolein significantly, one of the key intermediates found in NTP alone system reported previously, suggest the benzene ring open reaction is promoted. Compared with monometallic oxides NiO and Co3O4, Co2Ni1Ox also shows higher active oxygen proportion, better oxygen mobility, and stronger low-temperature redox capability. The above factors result in the improved catalytic performance of Co2Ni1Ox in the NTP coupling removal of benzene.

A Novel Strategy for Accelerating Pumpable Ice Slurry Production with Ozone Micro-Nano Bubbles and Extending the Shelf Life of Larimichthys polyactis.

In this study, a novel strategy for accelerating the production of pumpable ice slurry (PIS) by using ozone micro-nano bubbles (O3-MNBs) was proposed. The effect of PIS containing sodium alginate (SA) and O3-MNBs on the preservation of small yellow croaker (Larimichthys polyactis) was investigated. The results indicate that using SA solution containing O3-MNBs instead of only SA solution resulted in quicker production of PIS by promoting ice nucleation and eliminating supercooling. The distribution and positive effect of O3-MNBs as a nucleation agent on freezing characteristics were discussed. Microbial concentrations, pH, total volatile basic nitrogen, and thiobarbituric acid reactive substance content were also examined. Storage in novel PIS (containing O3-MNBs) had higher performance than storage in flake ice or conventional PIS due to the strong bacteriostatic ability of O3. Therefore, O3-MNBs injection can be used as a novel method for PIS production and the preservation of fresh marine products.

Home-based microbial solution to boost crop growth in low-fertility soil.

Soil microbial inoculants are expected to boost crop productivity under climate change and soil degradation. However, the efficiency of native vs commercialized microbial inoculants in soils with different fertility and impacts on resident microbial communities remain unclear. We investigated the differential plant growth responses to native synthetic microbial community (SynCom) and commercial plant growth-promoting rhizobacteria (PGPR). We quantified the microbial colonization and dynamic of niche structure to emphasize the home-field advantages for native microbial inoculants. A native SynCom of 21 bacterial strains, originating from three typical agricultural soils, conferred a special advantage in promoting maize growth under low-fertility conditions. The root : shoot ratio of fresh weight increased by 78-121% with SynCom but only 23-86% with PGPRs. This phenotype correlated with the potential robust colonization of SynCom and positive interactions with the resident community. Niche breadth analysis revealed that SynCom inoculation induced a neutral disturbance to the niche structure. However, even PGPRs failed to colonize the natural soil, they decreased niche breadth and increased niche overlap by 59.2-62.4%, exacerbating competition. These results suggest that the home-field advantage of native microbes may serve as a basis for engineering crop microbiomes to support food production in widely distributed poor soils.