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Root-associated bacteria play a vital role in the growth and adaptation of host plants to drought stress. These bacteria can be classified as rhizoplane and rhizosphere bacteria based on their distance from the root surface. Tomato plants are often exposed to periodic drought and nitrogen (N) addition throughout their life cycle, but the impacts of these factors on the plant and root-associated bacteria are not well understood. To gain insight into this relationship, we conducted an experiment to monitor the effects of periodic drought and N addition on rhizoplane and rhizosphere bacteria of tomato plants. Drought and N addition had interactive effects on plant and soil properties, which varied with the timing of drought. There were clear divergences in community traits such as alpha diversity, beta diversity, and network topological features between the two types of bacteria. The rhizoplane bacteria showed lower alpha diversity but higher beta diversity and were more sensitive to drought and N addition than the rhizosphere bacteria. Nitrogen addition could downsize the effects of drought on rhizoplane bacterial community compositions. The higher proximity to the root might induce a community to develop more cooperation between different members to cope with plant metabolites, as revealed by the more connected and modularized community network of the rhizoplane bacteria. Drought at the seedling stage had great legacy effects on plant and soil properties. It may enhance selection, cause the dominance of deterministic processes in the assembly of rhizoplane bacteria, and reduce bacterial community network complexity. In conclusion, N addition could interact with drought in affecting tomato plants and their root-associated bacteria, depending on the timing of drought and the fineness of root niches. The higher sensitivity of rhizoplane bacteria to drought and N addition calls for more research due to their higher proximity and importance to plants in future environmental changes.

Glucose, a critical source of energy, directly determines the homeostasis of the human body. However, due to the lack of robust imaging probes, the mechanism underlying the changes of glucose homeostasis in the human body remains unclear. Herein, diboronic acid probes with good biocompatibility and high sensitivity were synthesized based on an ortho-aminomethylphenylboronic acid probe, phenyl(di)boronic acid (PDBA). Significantly, by introducing the water-solubilizing group −CN directly opposite the boronic acid group and −COOCH3or −COOH groups to the β site of the anthracene in PDBA, we obtained the water-soluble probe Mc-CDBAwith sensitive response (F/F0= 47.8, detection limit (LOD) = 1.37 μM) and Ca-CDBAwith the highest affinity for glucose (Ka= 4.5 × 103M–1). On this basis, Mc-CDBAwas used to identify glucose heterogeneity between normal and tumor cells. Finally, Mc-CDBAand Ca-CDBAwere used for imaging glucose in zebrafish. Our research provides a new strategy for designing efficient boronic acid glucose probes and powerful new tools for the evaluation of glucose-related diseases.

In crowdsourcing scenarios, we can obtain each instance’s multiple noisy labels from different crowd workers and then infer its integrated label via label aggregation. In spite of the effectiveness of label aggregation methods, there still remains a certain level of noise in the integrated labels. Thus, some noise correction methods have been proposed to reduce the impact of noise in recent years. However, to the best of our knowledge, existing methods rarely consider an instance’s information from both its features and multiple noisy labels simultaneously when identifying a noise instance. In this study, we argue that the more distinguishable an instance’s features but the noisier its multiple noisy labels, the more likely it is a noise instance. Based on this premise, we propose a label distribution similarity-based noise correction (LDSNC) method. To measure whether an instance’s features are distinguishable, we obtain each instance’s predicted label distribution by building multiple classifiers using instances’ features and their integrated labels. To measure whether an instance’s multiple noisy labels are noisy, we obtain each instance’s multiple noisy label distribution using its multiple noisy labels. Then, we use the Kullback-Leibler (KL) divergence to calculate the similarity between the predicted label distribution and multiple noisy label distribution and define the instance with the lower similarity as a noise instance. The extensive experimental results on 34 simulated and four real-world crowdsourced datasets validate the effectiveness of our method.

ABSTRACTAnimal manure is the main source of bioenergy production by anaerobic digestion (AD). However, the pathogenic bacteria in manure may pose a high risk to human health by contaminating the environment if not effectively inactivated during AD. Worldwide, more than 20,000 biogas plants are running for the treatment of animal manure. AD has been playing the important role in establishing a circular economy in the agricultural sector and may contribute to the United Nations sustainable development goal (UN SDG). Nevertheless, whether AD is a reliable approach for pathogens inactivation has been challenged. A comprehensive understanding of the coping mechanisms of pathogens with adverse conditions and the challenges of establishing the AD process to inactivate effectively pathogens are yet to be analyzed. In this review, the diversity and resistance of pathogens in animal manure are summarized. The efficiencies and the difficulties of their inactivations in AD are also analyzed. In particular, three forms of pathogens i.e. sporing-forming pathogens, viable but non-culturable (VBNC) pathogens, and persistent pathogens are discussed. The factors influencing the pathogens’ inactivation and AD efficiencies are analyzed. The trade-off between energy production and pathogens inactivation in an AD system was consequently pointed out. This review concluded that the development of anaerobic processes should meet the goals of high efficient bioenergy production and deep hygienization.

Shallow lakes, the most numerous waterbodies on Earth, are susceptible to climate warming and nutrient enrichment whose effects on the microbial functional potentials are not yet fully understood, however. Here, we applied a microarray‐based technology termed GeoChip 5.0 to investigate microbial functional genes at the beginning of April in shallow lake ecosystems simulated in mesocosms that have been undergoing nutrient enrichment and warming for 9 yr. Our results showed that warming exacerbated the impact of nutrient enrichment on microbial metabolic potentials and significantly elevated the microbial autotrophy potentials, carbon degradation potentials (e.g., starch, hemicellulose, cellulose, and chitin), and polyphosphate mobilization potentials. We also observed that warming enhanced the impacts of nutrient enrichment on microbial functional gene structure. The combination of warming and nutrient enrichment increased the deterministic effect from phytoplankton, causing higher interlinking of microbial functional genes involved in the carbon, nitrogen, phosphorus, and sulfur cycling in correlation‐based networks. Overall, we propose that the joint effect of warming and nutrient enrichment promoted the autotrophic carbon supply and the heterotrophic carbon demand and changed the carbon fluxes in the experimental mesocosms.

Accurate material removal modeling is the basis for optimizing the surface quality and improving the performance of equipment components. In this study, a multi-sensor fusion method of vision and sound is used to monitor in-process grinding material removal rate (MRR). First, belt grinding experiments are conducted using different grinding parameters, and vision and sound signals are captured by industrial CCD cameras and an omnidirectional condenser microphone, respectively. Second, the features of the captured grinding spark images are extracted based on two aspects: color and texture, and those of the grinding sound are investigated in the time, frequency, and time–frequency domains. Moreover, the complementarity between the vision and sound signals and their sensitivity to different grinding parameters are discussed. Finally, based on feature-level fusion strategies, the Pearson correlation coefficient and the sequential backward selection algorithms are jointly used to select the optimal feature subsets. MRR prediction models are established using the selected feature subsets and an improved light gradient boosting machine (LightGBM) algorithm. The test results show that the error in the MRR prediction model of same-specification abrasive belts is less than 3 %, and the coefficient, R2, is as high as 99.2 %. The proposed method can be used to predict the MRR resulting from a single grinding parameter and multiple ones, using the same-specification abrasive belts. Compared to other prediction models, the improved LightGBM model is superior in terms of the time factor without reduction in the accuracy of the model.

Acidic coal mining lakes (AMLs) are characterized by low pH, low biodiversity, and high concentrations of sulfate and metals. However, to date, knowledge is inadequate on the involvement of the aquatic microbial functions in biogeochemical processes of an AML. Here, we use a natural weakly alkaline lake (WAL) as a reference to investigate the functional gene structure of microbial communities in the aerobic surface waters of an AML by using a metagenomic approach with GeoChip‐based functional gene arrays (GeoChip 5.0). We found significant differences in the compositions of the microbial functional genes between the two lake types. The AML had significantly lower gene diversity than the WAL, and the functional genes detected in the AML were almost a subset of those in the WAL. We also found significant differences in the microbial metabolic potentials between the two lake types. In the AML, the microbial communities had higher functional capacities in phosphorus‐utilization, sulfur oxidation, and metal‐detoxification and had lower metabolic potentials of carbon and nitrogen fixation, and the degradation of starch, hemicellulose, cellulose, chitin, and lignin than those in the WAL. By performing null model and network analyses, we observed stronger deterministic effects of the functional gene assemblages and greater clustering among the co‐occurring functional genes in the AML than those in the WAL. Altogether, we demonstrated contrasting patterns of freshwater microbial metabolic potentials and functional gene interactions between an AML and a WAL, which may advance the understanding of microbial functional response to acidification in freshwater lakes.

Bacterial communities comprise large numbers of species and normally include a few abundant taxa and many rare taxa. These two subcommunities may have fundamentally different ecological roles, and it is not clear whether their diversity patterns along elevation gradients vary. In this study, we investigated the diversity of bacterioplankton and their subcommunities, i.e., abundant and rare bacterioplankton, in lakes across gradual elevations from 525 m to 4652 m at Siguniang Mountain in western China via the high‐throughput sequencing of bacterial 16S rRNA genes. Elevation showed strong influence on bacterioplankton community composition (BCC) and that the dissimilarity of BCC increased with increasing differences in elevation. However, the elevational distance‐decay rate of abundant bacterioplankton was higher than that of rare bacterioplankton. Abundant bacterioplankton were more sensitive to changes of environmental factors than rare bacterioplankton. We observed a marginal increase in alpha diversity, estimated as operational taxonomic unit richness and phylogenetic diversity, of overall bacterioplankton with increasing elevation. The alpha diversity of abundant bacterioplankton decreased monotonically with elevation; in contrast, the alpha diversity of rare bacterioplankton increased monotonically with elevation. Null model tests indicated that environmental filtering played a dominant role in overall bacterioplankton community assembly along the elevation gradient, while there was decreased contribution of environmental selection to rare bacterioplankton in smaller lakes at higher elevation. Our results revealed that abundant bacterioplankton followed the general elevation diversity theory commonly found for plants and animals in freshwater lakes, whereas rare bacterioplankton did not follow this tenet.

The current climate warming and eutrophication are known to interactively threaten freshwater biodiversity; however, the interactive effects on lacustrine bacterioplankton diversity remain to be determined. Here, we analyzed the spring bacterioplankton community composition (BCC) in 24 outdoor, flow-through mesocosms (mimicking shallow lake environments) under 3 temperature scenarios and 2 nutrient regimes. Our results revealed that neither long-term warming (8.5 years) nor nutrient enrichment had significant effects on bacterioplankton alpha diversity, whereas long-term enhanced warming (elevated 50% above the IPCC A2 climate scenario) and nutrient enrichment in combination increased bacterioplankton beta diversity. We also found that BCC shifted significantly under enhanced warming and nutrient-enriched conditions towards decreased relative abundances of Actinobacteria, Bacteroidetesand Betaproteobacteria, whereas the percentages of Cyanobacteria, total rare phyla and unclassified phyla significantly increased. Null-model tests indicated that deterministic processes played a more important role than stochastic processes in determining BCC. However, the relative importance of stochasticity, primarily ecological drift, was enhanced and contributed to the increased beta diversity of BCC under enhanced warming and nutrient-enriched conditions. Overall, our study suggests that the synergetic effects of warming and nutrient enrichment may result in high variability in the composition of bacterioplankton communities in lacustrine water bodies.

The current climate warming and eutrophication are known to interactively threaten freshwater biodiversity; however, the interactive effects on lacustrine bacterioplankton diversity remain to be determined. Here, we analyzed the spring bacterioplankton community composition (BCC) in 24 outdoor, flow-through mesocosms (mimicking shallow lake environments) under 3 temperature scenarios and 2 nutrient regimes. Our results revealed that neither long-term warming (8.5 years) nor nutrient enrichment had significant effects on bacterioplankton alpha diversity, whereas long-term enhanced warming (elevated 50% above the IPCC A2 climate scenario) and nutrient enrichment in combination increased bacterioplankton beta diversity. We also found that BCC shifted significantly under enhanced warming and nutrient-enriched conditions towards decreased relative abundances of Actinobacteria, Bacteroidetes and Betaproteobacteria, whereas the percentages of Cyanobacteria, total rare phyla and unclassified phyla significantly increased. Null-model tests indicated that deterministic processes played a more important role than stochastic processes in determining BCC. However, the relative importance of stochasticity, primarily ecological drift, was enhanced and contributed to the increased beta diversity of BCC under enhanced warming and nutrient-enriched conditions. Overall, our study suggests that the synergetic effects of warming and nutrient enrichment may result in high variability in the composition of bacterioplankton communities in lacustrine water bodies.

Current guidelines recommend adjuvant chemotherapy (ACT) for stage II colorectal cancer (CRC) patients by using clinical high risk factors, with which circulating tumor cells (CTCs) were not considered. Here, an assessment to detect CTCs based on subtraction enrichment mediated by magnetic beads conjugated with CD45, immunofluorescence staining of CK, and fluorescence in situ hybridization of CEP8 is established. Both CEP8- and CK-positive CTCs have the potential to improve the risk stratification of stage II CRC patients. Patients with preoperative CTCs of ≥4 had a significantly higher recurrence risk than those with preoperative CTCs of <4 in two external validation cohorts (P< 0.0001). In the subgroup with clinical high risk, when preoperative CTCs were <4, patients did not benefit from ACT (P= 0.5764); however, when preoperative CTCs were ≥4, patients received benefit from ACT (P= 0.0064). Additionally, regardless of clinical risk status and preoperative CTC levels, if postoperative CTC levels were ≥4 for more than three consecutive time points (monitoring time interval, 2–6 months), the recurrence rate was 100%. Our findings suggested that the subtraction enrichment of CTCs could provide a reliable method to stratify the recurrence risk and make therapeutic decisions after surgery in stage II CRC patients.

Wheat Fusarium head blight (FHB) may cause serious losses in grain yield and quality in China. More than 7 million hectares which approximately accounts for 25% of the total areas in China is infected by the disease. The cultivation of wheat varieties with resistance to Fusarium head blight is recognized as one of the most important components to diminish losses due to this disease. Chinese wheat breeders have commenced the research on FHB since 1950s. Wheat cultivars with improved FHB resistance were developed through conventional breeding. Some famous resistant varieties such as Sumai 3, Yangmai 158 and Ning 7840 were released from Jiangsu Academy of Agricultural Sciences, these varieties were widely applied in wheat production and breeding programs. Significant achievements concerning molecular mapping and marker assisted selection have been made in the past decade. The major QTL on chromosome 3BS was identified and located in the same region on chromosome 3BS in Sumai 3, Ning 894037, Wangshuibai, and Chinese Spring. Using SSR marker in this QTL region for assisted selection, some lines with the same resistance to FHB were obtained. New STS markers and SSCP markers were developed and will be tested for the efficiency of MAS. However, further achievements are still hindered by a number of constraints. More FHB resistance genetic resources from landrace in middle to lower reaches of Yangtze River are necessary to be used for improving FHB resistant. The genetic mechanism of the varieties contributing the resistance to improved cultivars is needed to be understood. Development of functional markers for FHB is discussed.