RESUMO
Zinc (Zn) is a vital element for plant growth and development, however, excessive Zn is toxic to plants. Common bermudagrass (Cynodon dactylon (L.) Pers.) and hybrid bermudagrass (C. dactylon (L.) Pers. × C. transvaalensis Burtt-Davy) are widely used turfgrass species with strong tolerance to diverse abiotic stresses, including excessive Zn2+ stress. However, the variation of zinc tolerance and accumulation in different bermudagrass cultivars remain unclear. In this study, we systematically analyzed the growth performance, physiological index and ion concentration in eight commercial cultivars of common and hybrid bermudagrass under different concentration of Zn2+ treatments using pot experiments. The results indicated that four cultivars of common bermudagrass could tolerate 20 mM Zn2+, whereas four cultivars of hybrid bermudagrass could only tolerate 10 mM Zn2+. Among the four common bermudagrass cultivars, cultivar Guanzhong and Common showed stronger Zn tolerance and accumulation abilities than other two cultivars. Further analyses of the expression of selected Zn homeostasis-related genes indicated that bermudagrass cultivars with stronger tolerance to excessive Zn have at least one expression-elevated gene involved in Zn homeostasis. These results not only expanded our understanding of Zn tolerance and accumulation in bermudagrass but also facilitated the application of commercial bermudagrass cultivars in phytoremediation of Zn pollution.
Assuntos
Cynodon , Zinco , Cynodon/genética , Cynodon/metabolismo , Zinco/metabolismo , Biodegradação AmbientalRESUMO
The structural integrity and esthetic appeal of concrete can be compromised by concrete cracks. Promise has been shown by microbe-induced calcium carbonate precipitation (MICP) as a solution for concrete cracking, with a focus on urease-producing microorganisms in research. Bacillus cereus was isolated from soil and employed for this purpose in this study due to its high urease activity. The strain exhibited strong tolerance for alkaline media and high salt levels, which grew at a pH of 13 and 4% salt concentration. The repair of concrete cracks with this strain was evaluated by assessing the effects of four different thickeners at varying concentrations. The most effective results were achieved with 10 g/L of sodium carboxymethyl cellulose (CMC-Na). The data showed that over 90% repair of cracks was achieved by this system with an initial water penetration time of 30 s. The study also assessed the quantity and sizes of crystals generated during the bacterial mineralization process over time to improve our understanding of the process. KEY POINTS: ⢠MICP using Bacillus cereus shows potential for repairing concrete cracks. ⢠Strain tolerates alkaline media and high salt levels, growing at pH 13 and 4% salt concentration. ⢠Sodium carboxymethyl cellulose (CMC-Na) at 10 g/L achieved over 90% repair of cracks.
Assuntos
Bacillus cereus , Bacillus , Urease , Carboximetilcelulose Sódica , Carbonato de Cálcio/química , Cloreto de Sódio , Sódio , Precipitação Química , Materiais de Construção/microbiologiaRESUMO
BACKGROUND: Bermudagrass (Cynodon dactylon L.) is an important warm-season turfgrass species with well-developed stolons, which lay the foundation for the fast propagation of bermudagrass plants through asexual clonal growth. However, the growth and development of bermudagrass stolons are still poorly understood at the molecular level. RESULTS: In this study, we comprehensively analyzed the acetylation and succinylation modifications of proteins in fast-growing stolons of the bermudagrass cultivar Yangjiang. A total of 4657 lysine acetylation sites on 1914 proteins and 226 lysine succinylation sites on 128 proteins were successfully identified using liquid chromatography coupled to tandem mass spectrometry, respectively. Furthermore, 78 proteins and 81 lysine sites were found to be both acetylated and succinylated. Functional enrichment analysis revealed that acetylated proteins regulate diverse reactions of carbohydrate metabolism and protein turnover, whereas succinylated proteins mainly regulate the citrate cycle. These results partly explained the different growth disturbances of bermudagrass stolons under treatment with sodium butyrate and sodium malonate, which interfere with protein acetylation and succinylation, respectively. Moreover, 140 acetylated proteins and 42 succinylated proteins were further characterized having similarly modified orthologs in other grass species. Site-specific mutations combined with enzymatic activity assays indicated that the conserved acetylation of catalase and succinylation of malate dehydrogenase both inhibited their activities, further implying important regulatory roles of the two modifications. CONCLUSION: In summary, our study implied that lysine acetylation and succinylation of proteins possibly play important regulatory roles in the fast growth of bermudagrass stolons. The results not only provide new insights into clonal growth of bermudagrass but also offer a rich resource for functional analyses of protein lysine acetylation and succinylation in plants.
Assuntos
Cynodon , Proteoma , Acetilação , Proteoma/metabolismo , Cynodon/genética , Lisina/metabolismo , Malato Desidrogenase/metabolismo , Catalase/metabolismo , Ácido Butírico/metabolismo , Processamento de Proteína Pós-Traducional , Malonatos/metabolismo , Sódio/metabolismo , Citratos/metabolismoRESUMO
Unfertilized duck eggs not removed prior to incubation will deteriorate quickly, posing a risk of contaminating the normally fertilized duck eggs. Thus, detecting the fertilization status of breeding duck eggs as early as possible is a meaningful and challenging task. Most existing work usually focus on the characteristics of chicken eggs during mid-term hatching. However, little attention has been paid to the detection for duck eggs prior to incubation. In this paper, we present a novel hybrid deep learning detection framework for the fertilization status of pre-incubation duck eggs, termed CVAE-DF, based on visible/near-infrared (VIS/NIR) transmittance spectroscopy. The framework comprises the encoder of a convolutional variational autoencoder (CVAE) and an improved deep forest (DF) model. More specifically, we first collected transmittance spectral data (400-1000 nm) of 255 duck eggs before hatching. The multiplicative scatter correction (MSC) method was then used to eliminate noise and extraneous information of the raw spectral data. Two efficient data augmentation methods were adopted to provide sufficient data. After that, CVAE was applied to extract representative features and reduce the feature dimension for the detection task. Finally, an improved DF model was employed to build the classification model on the enhanced feature set. The CVAE-DF model achieved an overall accuracy of 95.94 % on the test dataset. These experimental results in terms of four metrics demonstrate that our CVAE-DF method outperforms the traditional methods by a significant margin. Furthermore, the results also indicate that CVAE holds great promise as a novel feature extraction method for the VIS/NIR spectral analysis of other agricultural products. It is extremely beneficial to practical engineering.
Assuntos
Aprendizado Profundo , Patos , Fertilização , Espectroscopia de Luz Próxima ao Infravermelho , Animais , Espectroscopia de Luz Próxima ao Infravermelho/métodos , Fertilização/fisiologia , Óvulo/químicaRESUMO
Salt content is a crucial indicator of the maturity and internal quality of salted duck eggs (SDEs) during the pickling process. However, there is currently no valid and rapid method available for accurately detecting salt content. In the present study, we utilized hyperspectral imaging to no-destructively determine the salt content in egg yolks, egg whites, and whole eggs during the curing period. Firstly, principal component analysis was applied to explain the characteristics of egg yolk and white morphology transformation of SDEs with different maturities during curing. Secondly, sensitive spectral factors representative of changes in the salt content of SDEs were extracted by three spectral transformations (Savitzky-Golay SG, continuum removal CR, and first-order derivation FD) and three approaches of selecting characteristic wavelengths (successive projection algorithm SPA, uninformative variables elimination UVE and competitive adaptive reweighting sampling algorithm CARS). The results of the PLSR model suggested that the optimal models for predicting salt content in egg yolks, whites, and whole eggs were SG-UVE-PLSR (predicted coefficient of determination Rp2=0.912, predicted standard deviation SEp=0.151, residual prediction deviation RPD = 3.371), CR-CARS-PLSR (Rp2=0.873, SEp=0.862, RPD = 2.806), and CR-UVE-PLSR (Rp2=0.877, SEp=0.680, RPD = 2.851), respectively. Eventually, the optimal prediction model for the salt content of the whole egg was employed to a pixel spectral matrix to calculate the salt content values of pixel points on the hyperspectral image of SDEs. Additionally, pseudo-color techniques were employed to visualize the spatial distribution of predicted salt content. This work will provide a theoretical foundation for rapidly detecting maturity and enabling high-throughput quality sorting of SDEs.
Assuntos
Patos , Clara de Ovo , Animais , Imageamento Hiperespectral , Ovos , Gema de Ovo , Cloreto de SódioRESUMO
Background: Head and neck squamous cell carcinoma (HNSC) is the sixth most common cancer worldwide, and new cases are anticipated to reach 1.08 million in 2030. Our study aimed to identify the competing endogenous RNAs (ceRNAs) involved in HNSC tumorigenesis. Methods: First, a pan-cancer correlation analysis was conducted on the expression and survival conditions of sideroflexin (SFXN3) based on data downloaded from the Xena database. Second, the upstream regulatory microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) of SFXN3 were predicted using the Encyclopedia of RNA Interactomes (ENCORI) database. Expression and survival analyses were subsequently used to construct lncRNA-miRNA-mRNA ceRNA network that correlated with HNSC. Third, the proportion of various types of immune cells in HNSC was calculated using the CIBERSORT algorithm. Finally, a correlation analysis was performed on SFXN3, including immune cell infiltration (ICI), clinical stage, and immune checkpoints. Results: The pan-cancer analysis suggested that SFXN3 was up-regulated in HNSC, and it correlated with poor prognosis. The ceRNA regulatory network MIR193BHG-miR-29c-3p-SFXN3 was identified as one of the potential biological regulatory pathways of HNSC. The upstream lncRNA MIR193BHG was associated with a poor prognosis in HNSC, and its target gene SFXN3 was correlated with tumor ICI, immune cell biomarkers, and immune checkpoints. Conclusions: By performing ceRNA analysis, our study demonstrated that MIR193HG-miR-29c-3p-SFXN3 is significantly involved in HNSC, and this action axis markedly affect the therapeutic effect and prognosis.