Redundancy in microbiota-mediated suppression of the soybean cyst nematode.

BACKGROUND: Soybean cyst nematodes (SCN) as animal parasites of plants are not usually interested in killing the host but are rather focused on completing their life cycle to increase population, resulting in substantial yield losses. Remarkably, some agricultural soils after long-term crop monoculture show a significant decline in SCN densities and suppress disease in a sustainable and viable manner. However, relatively little is known about the microbes and mechanisms operating against SCN in such disease-suppressive soils. RESULTS: Greenhouse experiments showed that suppressive soils (S) collected from two provinces of China and transplantation soils (CS, created by mixing 10% S with 90% conducive soils) suppressed SCN. However, SCN suppressiveness was partially lost or completely abolished when S soils were treated with heat (80 °C) and formalin. Bacterial community analysis revealed that the specific suppression in S and CS was mainly associated with the bacterial phylum Bacteroidetes, specifically due to the enrichment of Chitinophaga spp. and Dyadobacter sp., in the cysts. SCN cysts colonized by Chitinophaga spp. showed dramatically reduced egg hatching, with unrecognizable internal body organization of juveniles inside the eggshell due to chitinase activity. Whereas, Dyadobacter sp. cells attached to the surface coat of J2s increased soybean resistance against SCN by triggering the expression of defence-associated genes. The disease-suppressive potential of these bacteria was validated by inoculating them into conducive soil. The Dyadobacter strain alone or in combination with Chitinophaga strains significantly decreased egg densities after one growing cycle of soybeans. In contrast, Chitinophaga strains alone required more than one growing cycle to significantly reduce SCN egg hatching and population density. CONCLUSION: This study revealed how soybean monoculture for decades induced microbiota homeostasis, leading to the formation of SCN-suppressive soil. The high relative abundance of antagonistic bacteria in the cyst suppressed the SCN population both directly and indirectly. Because uncontrolled proliferation will likely lead to quick demise due to host population collapse, obligate parasites like SCN may have evolved to modulate virulence/proliferation to balance these conflicting needs. Video Abstract.

A recent insight of applications of gold nanoparticles in glioblastoma multiforme therapy.

The application of gold nanoparticles (AuNPs) in cancer therapy, particularly targeted therapy of glioblastoma multiforme (GBM), is an up-and-coming field of research that has gained much interest in recent years. GBM is a life-threatening malignant tumour of the brain that currently has a 95 % death rate with an average of 15 months of survival. AuNPs have proven to have wide clinical implications and compelling therapeutic potential in many researches, specifically in GBM treatment. It was found that the reason why AuNPs were highly desired for GBM treatment was due to their unique properties that diversified the applications of AuNPs further to include imaging, diagnosis, and photothermal therapy. These properties include easy synthesis, biocompatibility, and surface functionalization. Various studies also underscored the ability of AuNPs to cross the blood-brain-barrier and selectively target tumour cells while displaying no major safety concerns which resulted in better therapy results. We attempt to bring together some of these studies in this review and provide a comprehensive overview of safety evaluations and current and potential applications of AuNPs in GBM therapy that may result in AuNP-mediated therapy to be the new gold standard for GBM treatment.

Preparation and application of hydroxypropyl methylcellulose blended with beeswax and essential oil edible coating to enhance the shelf life of sweet cherries.

The study involved preparing and applying edible nano-emulsion coatings containing hydroxypropyl methylcellulose (HPMC), beeswax (BW), and essential oils (thyme, cinnamon, clove, and peppermint) onto sweet cherries. The application was conducted at 4 °C, and the coated cherries were stored for 36 days. This research examines synthesized nano-emulsions physicochemical properties and antibacterial and antifungal activities (C1, C2, and C3). Additionally, it evaluates the quality parameters of control and coated sweet cherry samples. The features of the three edible coatings were assessed, and the findings from the zeta sizer, zeta potential, FTIR, and SEM analyses were deemed satisfactory. It was observed that the application of nano-emulsion coating C1 yielded positive results in maintaining quality attributes such as total suspended solids (TSS), total solids (TS), color, weight loss, respiration rate, firmness, total phenolic contents, and sensory evaluations. Nano-emulsion coating C1 demonstrated efficacy as an antibacterial and antifungal agent against foodborne pathogens E. coli and A. niger, respectively. The current research results are promising and applicable in food industries. The implications suggest that composite nano-emulsion, specifically nano-emulsion edible coatings, can be extensively and effectively used to preserve the quality and shelf life of fruits and vegetables. Furthermore, the environmental waste from conventional food packaging will be minimized using edible packaging applications.

Estrogens in plants and emerging risks to human health.

Steroid estrogens (SEs) accumulate in agro-food systems through wastewater treatment and dairy manure, but very little is known about their potential impact on plants and dietary risk to human health. We conducted a meta-analysis to address key questions including, how plants respond to SEs under different environmental conditions, what is the accumulation potential of SEs in distinct plant families, and associated daily dietary intake risks to humans. Based on 517 endpoints, we revealed that various crop species show a heterogeneous response to SEs types (n = 140), SEs concentrations (n = 141), and exposure medium (n = 166). A subsidy-stress response was observed in terms of SEs accumulation for plant growth. The bioaccumulation of SE in plants was shown to be greatest in sand, followed by soil, and hydroponic media. Plants exposed to SEs exhibit considerable changes in physiological and biochemical characteristics. Surprisingly, food crops such as carrot and potato were found as major source of SEs daily intake in food chain but their consequences remains largely unknown. Further field-oriented research is needed to unveil the threshold levels for SEs in soil-plant systems as it may pose a global threat to human health. The state of knowledge presented here may guide towards urgently needed future investigations in this field for reducing the risk in SEs in agro-food systems.

Bone Age Assessment Empowered with Deep Learning: A Survey, Open Research Challenges and Future Directions.

Deep learning is a quite useful and proliferating technique of machine learning. Various applications, such as medical images analysis, medical images processing, text understanding, and speech recognition, have been using deep learning, and it has been providing rather promising results. Both supervised and unsupervised approaches are being used to extract and learn features as well as for the multi-level representation of pattern recognition and classification. Hence, the way of prediction, recognition, and diagnosis in various domains of healthcare including the abdomen, lung cancer, brain tumor, skeletal bone age assessment, and so on, have been transformed and improved significantly by deep learning. By considering a wide range of deep-learning applications, the main aim of this paper is to present a detailed survey on emerging research of deep-learning models for bone age assessment (e.g., segmentation, prediction, and classification). An enormous number of scientific research publications related to bone age assessment using deep learning are explored, studied, and presented in this survey. Furthermore, the emerging trends of this research domain have been analyzed and discussed. Finally, a critical discussion section on the limitations of deep-learning models has been presented. Open research challenges and future directions in this promising area have been included as well.

Brain Tumor Analysis Empowered with Deep Learning: A Review, Taxonomy, and Future Challenges.

Deep Learning (DL) algorithms enabled computational models consist of multiple processing layers that represent data with multiple levels of abstraction. In recent years, usage of deep learning is rapidly proliferating in almost every domain, especially in medical image processing, medical image analysis, and bioinformatics. Consequently, deep learning has dramatically changed and improved the means of recognition, prediction, and diagnosis effectively in numerous areas of healthcare such as pathology, brain tumor, lung cancer, abdomen, cardiac, and retina. Considering the wide range of applications of deep learning, the objective of this article is to review major deep learning concepts pertinent to brain tumor analysis (e.g., segmentation, classification, prediction, evaluation.). A review conducted by summarizing a large number of scientific contributions to the field (i.e., deep learning in brain tumor analysis) is presented in this study. A coherent taxonomy of research landscape from the literature has also been mapped, and the major aspects of this emerging field have been discussed and analyzed. A critical discussion section to show the limitations of deep learning techniques has been included at the end to elaborate open research challenges and directions for future work in this emergent area.

Bacterial community assemblages in the rhizosphere soil, root endosphere and cyst of soybean cyst nematode-suppressive soil challenged with nematodes.

In disease-suppressive soil, plants rely upon mutualistic associations between roots and specific microbes for nutrient acquisition and disease suppression. Notably, the transmission of suppressiveness by the cysts of sugar beet cyst nematode from suppressive to conducive soils has been previously observed in greenhouse trials. However, our current understanding of the bacterial assemblages in the cyst, root endosphere and rhizosphere soil is still limited. To obtain insights into these bacterial microbiota assemblages, the bacterial communities inhabiting the plant-associated microhabitats and cysts in soybean cyst nematode (SCN)-suppressive soil were characterized by deep sequencing, using soybean grown under growth room conditions with additional SCN challenge. Clustering analysis revealed that the cyst bacterial community was closer to the root endosphere community than to the rhizosphere and bulk soil communities. Interestingly, the cyst bacterial community was initially established by the consecutive selection of bacterial taxa from the soybean root endosphere. We found a set of potential microbial consortia, such as Pasteuria, Pseudomonas, Rhizobium, and other taxa, that were consistently enriched in the rhizocompartments under SCN challenge, and more abundant in the cysts than in the bulk soil. Our results suggest that the soybean root-associated and cyst microbiota may cause the suppressiveness of SCN in suppressive soil.

Successive soybean-monoculture cropping assembles rhizosphere microbial communities for the soil suppression of soybean cyst nematode.

One of the mechanisms of disease suppressiveness in soils is long-term monoculture (LTM) cropping to dissuade pathogen infestation. However, the linkage between monoculturing and microbial community assemblage in the rhizosphere for disease suppression remains unclear. To decipher this potential relationship, soil samples were collected from seven locations in northeastern China, where LTM (6-38 yr) and short-term monoculture (STM ≤ 5 yr) cropping of soybean showed varying degrees of soil suppressiveness to the soybean cyst nematode (SCN; Heterodera glycines). Using high-throughput pyrosequencing to examine bacterial 16S rRNA and fungal ITS1 genes, we observed substantial variation in the species richness and relative abundance of taxa in the rhizosphere across different sampling sites. At the genus level, the genera Pseudomonas, Purpureocillium and Pochonia, which have been documented to suppress SCN in earlier studies, were much more abundant in LTM soils than in STM soils. Moreover, the relative abundance of several bacterial and fungal genera with metabolic, biocidal and parasitic activities was also monitored in the rhizosphere. In this study, we provide additional evidence that plants shift the structural and functional composition of the rhizosphere microbiota to suppress pathogen infection in LTM cropping soils.

Population Genetics of Hirsutella rhossiliensis, a Dominant Parasite of Cyst Nematode Juveniles on a Continental Scale.

Hirsutella rhossiliensis is a parasite of juvenile nematodes, effective against a diversity of plant-parasitic nematodes. Its global distribution on various nematode hosts and its genetic variation for several geographic regions have been reported, while the global population genetic structure and factors underlying patterns of genetic variation of H. rhossiliensis are unclear. In this study, 87 H. rhossiliensis strains from five nematode species (Globodera sp., Criconemella xenoplax, Rotylenchus robustus, Heterodera schachtii, and Heterodera glycines) in Europe, the United States, and China were investigated by multilocus sequence analyses. A total of 280 variable sites (frequency, 0.6%) at eight loci and six clustering in high accordance with geographic populations or host nematode-associated populations were identified. Although H. rhossiliensis is currently recognized as an asexual fungus, recombination events were frequently detected. In addition, significant genetic isolation by geography and nematode hosts was revealed. Overall, our analyses showed that recombination, geographic isolation, and nematode host adaptation have played significant roles in the evolutionary history of H. rhossiliensis IMPORTANCE: H. rhossiliensis has great potential for use as a biocontrol agent to control nematodes in a sustainable manner as an endoparasitic fungus. Therefore, this study has important implications for the use of H. rhossiliensis as a biocontrol agent and provides interesting insights into the biology of this species.