Acetylene Fuels TCE Reductive Dechlorination by Defined Dehalococcoides/Pelobacter Consortia.

Acetylene (C2H2) can be generated in contaminated groundwater sites as a consequence of chemical degradation of trichloroethene (TCE) by in situ minerals, and C2H2 is known to inhibit bacterial dechlorination. In this study, we show that while high C2H2 (1.3 mM) concentrations reversibly inhibit reductive dechlorination of TCE by Dehalococcoides mccartyi isolates as well as enrichment cultures containing D. mccartyi sp., low C2H2 (0.4 mM) concentrations do not inhibit growth or metabolism of D. mccartyi. Cocultures of Pelobacter SFB93, a C2H2-fermenting bacterium, with D. mccartyi strain 195 or with D. mccartyi strain BAV1 were actively sustained by providing acetylene as the electron donor and carbon source while TCE or cis-DCE served as the electron acceptor. Inhibition by acetylene of reductive dechlorination and methanogenesis in the enrichment culture ANAS was observed, and the inhibition was removed by adding Pelobacter SFB93 into the consortium. Transcriptomic analysis of D. mccartyi strain 195 showed genes encoding for reductive dehalogenases (e.g., tceA) were not affected during the C2H2-inhibition, while genes encoding for ATP synthase, biosynthesis, and Hym hydrogenase were down-regulated during C2H2 inhibition, consistent with the physiological observation of lower cell yields and reduced dechlorination rates in strain 195. These results will help facilitate the optimization of TCE-bioremediation at contaminated sites containing both TCE and C2H2

Exploring customer concerns on service quality under the COVID-19 crisis: a social media analytics study from the retail industry

The COVID-19 pandemic has triggered a set of government policies and supermarket regulations, which affects customers' grocery shopping behaviours. However, the specific impact of COVID-19 on retailers at the customer end has not yet been addressed. Using text-mining techniques (i.e., sentiment analysis, topic modelling) and time series analysis, we analyse 161,921 tweets from leading UK supermarkets during the first COVID-19 lockdown. The results show the causes of sentiment change in each time series and how customer perception changes according to supermarkets’ response actions. Drawing on the social media crisis communication framework and Situational Crisis Communication theory, this study investigates whether responding to a crisis helps retail managers better understand their customers. The results uncover that customers experiencing certain social media interactions may evaluate attributes differently, resulting in varying levels of customer information collection, and grocery companies could benefit from engaging in social media crisis communication with customers. As new variants of COVID-19 keep appearing, emerging managerial problems put businesses at risk for the next crisis. Based on the results of text-mining analysis of consumer perceptions, this study identifies emerging topics in the UK grocery sector in the context of COVID-19 crisis communication and develop the sub-dimensions of service quality assessment into four categories: physical aspects, reliability, personal interaction, and policies. This study reveals how supermarkets could use social media data to better analyse customer behaviour during a pandemic and sustain competitiveness by upgrading their crisis strategies and service provision. It also sheds light on how future researchers can leverage the power of social media data with multiple text-mining methodologies

Exploring customer concerns on service quality under the COVID-19 crisis: A social media analytics study from the retail industry

The COVID-19 pandemic has triggered a set of government policies and supermarket regulations, which affects customers' grocery shopping behaviours. However, the specific impact of COVID-19 on retailers at the customer end has not yet been addressed. Using text-mining techniques (i.e., sentiment analysis, topic modelling) and time series analysis, we analyse 161,921 tweets from leading UK supermarkets during the first COVID-19 lockdown. The results show the causes of sentiment change in each time series and how customer perception changes according to supermarkets’ response actions. Drawing on the social media crisis communication framework and Situational Crisis Communication theory, this study investigates whether responding to a crisis helps retail managers better understand their customers. The results uncover that customers experiencing certain social media interactions may evaluate attributes differently, resulting in varying levels of customer information collection, and grocery companies could benefit from engaging in social media crisis communication with customers. As new variants of COVID-19 keep appearing, emerging managerial problems put businesses at risk for the next crisis. Based on the results of text-mining analysis of consumer perceptions, this study identifies emerging topics in the UK grocery sector in the context of COVID-19 crisis communication and develop the sub-dimensions of service quality assessment into four categories: physical aspects, reliability, personal interaction, and policies. This study reveals how supermarkets could use social media data to better analyse customer behaviour during a pandemic and sustain competitiveness by upgrading their crisis strategies and service provision. It also sheds light on how future researchers can leverage the power of social media data with multiple text-mining methodologies

Pedestrian Crossing Action Recognition and Trajectory Prediction with 3D Human Keypoints

Accurate understanding and prediction of human behaviors are critical prerequisites for autonomous vehicles, especially in highly dynamic and interactive scenarios such as intersections in dense urban areas. In this work, we aim at identifying crossing pedestrians and predicting their future trajectories. To achieve these goals, we not only need the context information of road geometry and other traffic participants but also need fine-grained information of the human pose, motion and activity, which can be inferred from human keypoints. In this paper, we propose a novel multi-task learning framework for pedestrian crossing action recognition and trajectory prediction, which utilizes 3D human keypoints extracted from raw sensor data to capture rich information on human pose and activity. Moreover, we propose to apply two auxiliary tasks and contrastive learning to enable auxiliary supervisions to improve the learned keypoints representation, which further enhances the performance of major tasks. We validate our approach on a large-scale in-house dataset, as well as a public benchmark dataset, and show that our approach achieves state-of-the-art performance on a wide range of evaluation metrics. The effectiveness of each model component is validated in a detailed ablation study.Comment: ICRA 202

Soyasaponins Can Blunt Inflammation by Inhibiting the Reactive Oxygen Species-Mediated Activation of PI3K/Akt/NF-kB Pathway

We and others have recently shown that soyasaponins abundant in soybeans can decrease inflammation by suppressing the nuclear factor kappa B (NF-kB)-mediated inflammation. However, the exact molecular mechanisms by which soyasaponins inhibit the NF-kB pathway have not been established. In this study in macrophages, soyasaponins (A1, A2 and I) inhibited the lipopolysaccharide (LPS)-induced release of inflammatory marker prostaglandin E2 (PGE2) to a similar extent as the NF-kB inhibitor (BAY117082). Soyasaponins (A1, A2 and I) also suppressed the LPS-induced expression of cyclooxygenase 2 (COX-2), another inflammatory marker, in a dose-dependent manner by inhibiting NF-kB activation. In defining the associated mechanisms, we found that soyasaponins (A1, A2 and I) blunted the LPS-induced IKKα/β phosphorylation, IkB phosphorylation and degradation, and NF-kB p65 phosphorylation and nuclear translocation. In studying the upstream targets of soyasaponins on the NF-kB pathway, we found that soyasaponins (A1, A2 and I) suppressed the LPS-induced activation of PI3K/Akt similarly as the PI3K inhibitor LY294002, which alone blocked the LPS-induced activation of NF-kB. Additionally, soyasaponins (A1, A2 and I) reduced the LPS-induced production of reactive oxygen species (ROS) to the same extent as the anti-oxidant N-acetyl-L-cysteine, which alone inhibited the LPS-induced phosphorylation of Akt, IKKα/β, IkBα, and p65, transactivity of NF-kB, PGE2 production, and malondialdehyde production. Finally, our results show that soyasaponins (A1, A2 and I) elevated SOD activity and the GSH/GSSG ratio. Together, these results show that soyasaponins (A1, A2 and I) can blunt inflammation by inhibiting the ROS-mediated activation of the PI3K/Akt/NF-kB pathway

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Surgical site infection after gastrointestinal surgery in high-income, middle-income, and low-income countries: a prospective, international, multicentre cohort study

Background: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. Methods: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country. Countries with participating centres were stratified into high-income, middle-income, and low-income groups according to the UN's Human Development Index (HDI). Data variables from the GlobalSurg 1 study and other studies that have been found to affect the likelihood of SSI were entered into risk adjustment models. The primary outcome measure was the 30-day SSI incidence (defined by US Centers for Disease Control and Prevention criteria for superficial and deep incisional SSI). Relationships with explanatory variables were examined using Bayesian multilevel logistic regression models. This trial is registered with ClinicalTrials.gov, number NCT02662231. Findings: Between Jan 4, 2016, and July 31, 2016, 13 265 records were submitted for analysis. 12 539 patients from 343 hospitals in 66 countries were included. 7339 (58·5%) patient were from high-HDI countries (193 hospitals in 30 countries), 3918 (31·2%) patients were from middle-HDI countries (82 hospitals in 18 countries), and 1282 (10·2%) patients were from low-HDI countries (68 hospitals in 18 countries). In total, 1538 (12·3%) patients had SSI within 30 days of surgery. The incidence of SSI varied between countries with high (691 [9·4%] of 7339 patients), middle (549 [14·0%] of 3918 patients), and low (298 [23·2%] of 1282) HDI (p < 0·001). The highest SSI incidence in each HDI group was after dirty surgery (102 [17·8%] of 574 patients in high-HDI countries; 74 [31·4%] of 236 patients in middle-HDI countries; 72 [39·8%] of 181 patients in low-HDI countries). Following risk factor adjustment, patients in low-HDI countries were at greatest risk of SSI (adjusted odds ratio 1·60, 95% credible interval 1·05–2·37; p=0·030). 132 (21·6%) of 610 patients with an SSI and a microbiology culture result had an infection that was resistant to the prophylactic antibiotic used. Resistant infections were detected in 49 (16·6%) of 295 patients in high-HDI countries, in 37 (19·8%) of 187 patients in middle-HDI countries, and in 46 (35·9%) of 128 patients in low-HDI countries (p < 0·001). Interpretation: Countries with a low HDI carry a disproportionately greater burden of SSI than countries with a middle or high HDI and might have higher rates of antibiotic resistance. In view of WHO recommendations on SSI prevention that highlight the absence of high-quality interventional research, urgent, pragmatic, randomised trials based in LMICs are needed to assess measures aiming to reduce this preventable complication

A systems-level understanding of electron flow in TCE-dechlorinating microbial communities using modeling and molecular biology tools

Groundwater and soils have been frequently contaminated by trichloroethene (TCE), perchloroethene (PCE) and other chlorinated compounds in the U.S. and worldwide, in spite of their established toxicity and mutagenicity towards many organisms, including humans. In order to protect public health, bioremediation using Dehalococcoides-containing microbial communities is a promising approach to reach ecotoxicological-safety endpoints. The overall goal of this research is to understand electron flows in complex dechlorinating microbial communities, and to develop mathematical models to predict the performance of the microbial communities in different environmental conditions. To accomplish these goals, we first studied the electron flow and material exchange of constructed TCE-dechlorinating consortia. We also applied emerging molecular techniques to study TCE-dechlorinating microbial communities under different remediation conditions. Furthermore, we developed integrated thermodynamic and kinetic models to predict the dechlorination performance and microbial growth of syntrophic consortia under batch and continuous-flow conditions, and the suite of models were further validated using enrichment cultures. The first objective of this research was to understand the material and energy exchange between Dehalococcoides and its supporting syntrophic bacteria. We investigated dechlorination activity, cell growth, cell aggregate formation, and global gene expression of D. mccartyi strain 195 (strain 195) grown with Syntrophomonas wolfei in co-cultures amended with butyrate and TCE. By applying thermodynamically consistent rate laws to study the electrons flows in the co-culture, we found that the growth rates of the two species were strictly coupled by H2 transfer, and that the growth yield of syntrophic bacteria and the ratio maintained in the co-cultures were mainly controlled by thermodynamics. We demonstrated, for the first time, that D. mccartyi could form cell aggregates with its supporting fermenter S. wolfei on butyrate. Furthermore, we found carbon monoxide (CO) may serve as a supplemental energy source for S. wolfei during syntrophic fermentation with strain 195, and that the observed increased cell yields of strain 195 is likely due to the continuous removal of CO in the co-culture. In order to understand the microbial community structure shift from "feast-and-famine" condition (semi-batch) to the continuous feeding of low nutrients condition (completely-mixed flow reactor (CMFR)), molecular techniques based on 16S I-tags and metagenomic sequencing were applied to investigate the dechlorinating community structural shift after transition from semi-batch to a long-term steady-state CMFR condition. A Dehalococcoides genus-wide microarray was also applied to study the transcriptional dynamics of D. mccartyi strains within the CMFR community that was grown in the continuous-flowing diluted, nutrient poor environment. I-tags and metagenomic sequencing analysis revealed that dominant species in the CMFR shifted significantly from the semi-batch culture condition while the ratio of D. mccartyi was maintained at relatively stable levels. Transcriptional analysis identified tceA and vcrA to be among the most expressed genes in the CMFR, hup and vhu were more critical hydrogenases utilized by Dehalococcoides sp. in the continuous-flowing system. In contrast, corrinoid-related uptake and modification genes were expressed at lower levels in the CMFR than in the semi-batch culture during active dechlorination. A systems-level approach was applied to determine accurate kinetic parameters involved in reductive dechlorination from simple constructed syntrophic consoria to complex microbial communities. The results demonstrated that the kinetic parameters involved in reductive dechlorination were in similar ranges for simple and complex Dehalococcoides-containing cultures. Cell growth calculations showed H2 was the most sensitive factor limiting the growth of H2-utilizing microorganisms involved in dechlorinating communities. High concentrations of acetate resulted in slower dechlorination rates by inhibiting the growth of specific fermenting bacteria. High sulfate concentrations also hindered dechlorination performance due to either sulfide inhibition or competition with sulfate reduction. The mechanism for observed slower dechlorination rates with lower bicarbonate concentrations was not clear and further experiments need to be conducted to evaluate the role of bicarbonate in reductive dechlorination communities. Based on the knowledge obtained in the previous studies, an integrated thermodynamic and kinetic model was developed to predict reductive dechlorination and cell growth under batch growth conditions. The model parameters calculated to fit the experimental data were at the same levels as those determined experimentally. The resultant model accurately captured the dechlorination kinetics in two Dehalococcoides-containing syntrphic co-cultures using different fermenting substrates. The model was validated at different donor to acceptor ratios in syntrophic co-cultures and in syntrophic tri-cultures and enrichment cultures performing hydrogenotrophic methanogenesis. The sensitivity of kinetic parameters on model stability was tested. Half velocity constants and inhibition coefficients were found to be the most sensitive factors affecting model predictions.The significance of this research is to provide a more fundamental understanding of the metabolic exchange and energy transfer among the key players of TCE-dechlorinating communities, as well as the physiology of dechlorinating microbial communities experiencing different environmental stresses. The integrated thermodynamic and kinetic models developed in this study could be used as a platform to incorporate more biological processes under different experimental conditions. The knowledge developed in this research will aid practitioners to better design, monitor and optimize future in situ bioremediation systems