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The mechanisms of the bacterial response to biocides are poorly understood, despite their broad application. To identify the genetic basis and pathways implicated in the biocide stress response, we exposed Escherichia coli populations to 10 ubiquitous biocides. By comparing the transcriptional responses between a short-term exposure (30 min) and a long-term exposure (8 to 12 h) to biocide stress, we established the common gene and pathway clusters that are implicated in general and biocide-specific stress responses. Our analysis revealed a temporal choreography, starting from the upregulation of chaperones to the subsequent repression of motility and chemotaxis pathways and the induction of an anaerobic pool of enzymes and biofilm regulators. A systematic analysis of the transcriptional data identified a zur-regulated gene cluster to be highly active in the stress response against sodium hypochlorite and peracetic acid, presenting a link between the biocide stress response and zinc homeostasis. Susceptibility assays with knockout mutants further validated our findings and provide clear targets for downstream investigation of the implicated mechanisms of action.IMPORTANCE Antiseptics and disinfectant products are of great importance to control and eliminate pathogens, especially in settings such as hospitals and the food industry. Such products are widely distributed and frequently poorly regulated. Occasional outbreaks have been associated with microbes resistant to such compounds, and researchers have indicated potential cross-resistance with antibiotics. Despite that, there are many gaps in knowledge about the bacterial stress response and the mechanisms of microbial resistance to antiseptics and disinfectants. We investigated the stress response of the bacterium Escherichia coli to 10 common disinfectant and antiseptic chemicals to shed light on the potential mechanisms of tolerance to such compounds.

The mechanisms of the bacterial response to biocides are poorly understood, despite their broad application. To identify the genetic basis and pathways implicated in the biocide stress response, we exposed Escherichia coli populations to 10 ubiquitous biocides. By comparing the transcriptional responses between a short-term exposure (30 min) and a long-term exposure (8 to 12 h) to biocide stress, we established the common gene and pathway clusters that are implicated in general and biocide-specific stress responses. Our analysis revealed a temporal choreography, starting from the upregulation of chaperones to the subsequent repression of motility and chemotaxis pathways and the induction of an anaerobic pool of enzymes and biofilm regulators. A systematic analysis of the transcriptional data identified a zur-regulated gene cluster to be highly active in the stress response against sodium hypochlorite and peracetic acid, presenting a link between the biocide stress response and zinc homeostasis. Susceptibility assays with knockout mutants further validated our findings and provide clear targets for downstream investigation of the implicated mechanisms of action.IMPORTANCE Antiseptics and disinfectant products are of great importance to control and eliminate pathogens, especially in settings such as hospitals and the food industry. Such products are widely distributed and frequently poorly regulated. Occasional outbreaks have been associated with microbes resistant to such compounds, and researchers have indicated potential cross-resistance with antibiotics. Despite that, there are many gaps in knowledge about the bacterial stress response and the mechanisms of microbial resistance to antiseptics and disinfectants. We investigated the stress response of the bacterium Escherichia coli to 10 common disinfectant and antiseptic chemicals to shed light on the potential mechanisms of tolerance to such compounds.

ObjectiveStandardizationTo explore a novel special technique intensive mode (STIM) of teaching cardiac conduction system mapping skills. This method includes theoretical lecture, in vivo operation, 5-whys methods of analyses, intensive-problem oriented trainings, and assessments.MethodsTen post-graduates majoring in cardiology who have equivalent education backgrounds and technical levels were randomly divided into two groups (n=5 per group). All participants underwent a skill training on cardiac electrophysiology mapping, with one group training under the STIM and the other group under the traditional "theory-practice-test" (TPT) mode. The effect of these two educational techniques were evaluated at the end of the training.ResultsPostgraduates in the STIM group had a more solid grasp of the anatomical position and structure of the cardiac conduction system than those in the TPT group. During in-vivo operation, the students in the STIM group reconstructed and interpreted the electroanatomical maps, voltage maps, electric excitation maps, and electric conduction maps more accurately and quickly than those in the TPT group.ConclusionThe STIM teaching mode more effectively improved the basic surgical skills of postgraduates, stimulated the students' learning initiative, and improved the quality of education. STIM is a kind of intensive teaching mode of special skills, and is worth widely implementing in the education of postgraduates majoring in cardiovascular diseases.

A tantalizing question in evolutionary biology is whether evolution can be predicted from past experiences. To address this question, we created a coherent compendium of more than 15,000 mutation events for the bacterium Escherichia coli under 178 distinct environmental settings. Compendium analysis provides a comprehensive view of the explored environments, mutation hotspots and mutation co-occurrence. While the mutations shared across all replicates decrease with the number of replicates, our results argue that the pairwise overlapping ratio remains the same, regardless of the number of replicates. An ensemble of predictors trained on the mutation compendium and tested in forward validation over 35 evolution replicates achieves a 49.2 ± 5.8% (mean ± std) precision and 34.5 ± 5.7% recall in predicting mutation targets. This work demonstrates how integrated datasets can be harnessed to create predictive models of evolution at a gene level and elucidate the effect of evolutionary processes in well-defined environments.

The Industrial Internet of Things (IIoT) provides a foundation for the development of emerging digital servitization paradigm in smart manufacturing. The deep integration of massive heterogeneous IIOT data plays a critical role in realising manufacturing digital servitization. However, there is a knowledge gap between different manufacturing fields, which brings a challenge for efficient integration and leverage of industrial big data. For this purpose, a Framework of Manufacturing Knowledge Graph (FMKG) is proposed, which is used to extracts industry knowledge triples from multi-source heterogeneous data to integrate domain knowledge. Also, an attention-based graph embedding model (ABGE) is proposed to discover and complement the implicit missing relationships in the knowledge graph to obtain a complete industrial knowledge graph. The effectiveness of the ABGE model has been verified on several knowledge graph data sets. And an aerospace enterprise production process was taken as an example to establish a product quality knowledge graph, which proved the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

MgO carbonization is a green and low-carbon soil improvement technology. The use of MgO carbonization to solidify dredged sediment and transform it into road-building materials has significant environmental sustainability advantages. A series of microscopic characterization tests, including X-ray Diffraction (XRD), Scanning Electron Microscope–Energy Dispersive Spectrometer (SEM-EDS), and Mercury-in-Pressure (MIP) tests, were conducted to elucidate the evolution characteristics of mineral composition, microscopic morphology, and pore structure of sediment under carbonation. Based on the results, the mechanism of MgO carbonation–solidification of dredged sediment was explored. In order to verify the improvement of carbonation on the road performance of sediment, comparative tests were carried out on sediment, non-carbonated sediment, and carbonated sediment. The results indicate a significant improvement in the solidification of MgO-treated sediment through carbonation, with enhanced macroscopic strength and densified microscopic structure. This can be attributed to the encapsulation, cementation, and pore-filling effects of the hydration products and carbonation products of MgO on soil particles. The rebound modulus and splitting strength of carbonated sediment were 3.53 times and 2.16 times that of non-carbonated sediment, respectively. Additionally, the carbonated sediment showed improved saturated stability, resistance to salt solution wet–dry cycles, and resistance to freeze–thaw cycles. [ABSTRACT FROM AUTHOR]

The growing problems of soil erosion and sedimentation due to plantation and construction activities highlight the importance of reliable information on sediment sources with the objectives of designing and implementing targeted management practices. However, reliable information is unavailable for mountainous catchments in southern China. Accordingly, the fingerprinting approach was adopted to quantitatively identify sediment sources in a typical mountainous catchment disturbed by plantation and construction activities in the Dadingshan catchment, Guangdong Province, China. Sensitivity tests were conducted to evaluate the effect of correction factors on the modified model. The results indicated that geochemical elements could be applied for identifying sediment sources within the study catchment. However, the coarse sediment in the catchment posed challenges to the conservative behaviour of tracers. The findings suggested that the primary sediment source is exposed subsoil (51.5 ± 10.0%), followed by plantation topsoil (35.3 ± 16.2%) and wind farms (13.2 ± 10.2%). The mean goodness‐of‐fit value for all sediment samples was 87.1 ± 5.7%. The sediment contributions of various sources varied significantly due to differences in the extent and intensity of human intervention and the main erosion type of each source. Sensitivity analysis revealed that considering the assumption of source normality improved the source apportionment accuracy. However, particle size correction and tracer within‐source variability weighting in the modified mixing model resulted in unusual estimates of the source contributions. This contribution highlights the significance of considering uncertainties in key fingerprinting‐related aspects and emphasizes the need for implementing sediment control strategies in degraded forest environments. [ABSTRACT FROM AUTHOR]