Diversity of Xenorhabdus and Photorhabdus spp. and their symbiotic entomopathogenic nematodes from Thailand

Xenorhabdus and Photorhabdus spp. are bacterial symbionts of entomopathogenic nematodes (EPNs). In this study, we isolated and characterized Xenorhabdus and Photorhabdus spp. from across Thailand together with their associated nematode symbionts, and characterized their phylogenetic diversity. EPNs were isolated from soil samples using a Galleria-baiting technique. Bacteria from EPNs were cultured and genotyped based on recA sequence. The nematodes were identified based on sequences of 28S rDNA and internal transcribed spacer regions. A total of 795 soil samples were collected from 159 sites in 13 provinces across Thailand. A total of 126 EPNs isolated from samples taken from 10 provinces were positive for Xenorhabdus (n = 69) or Photorhabdus spp. (n = 57). Phylogenetic analysis separated the 69 Xenorhabdus isolates into 4 groups. Groups 1, 2 and 3 consisting of 52, 13 and 1 isolates related to X. stockiae, and group 4 consisting of 3 isolates related to X. miraniensis. The EPN host for isolates related to X. stockiae was S. websteri, and for X. miraniensis was S. khoisanae. The Photorhabdus species were identified as P. luminescens (n = 56) and P. asymbiotica (n = 1). Phylogenenic analysis divided P. luminescens into five groups. Groups 1 and 2 consisted of 45 and 8 isolates defined as subspecies hainanensis and akhurstii, respectively. One isolate was related to hainanensis and akhurstii, two isolates were related to laumondii, and one isolate was the pathogenic species P. asymbiotica subsp. australis. H. indica was the major EPN host for Photorhabdus. This study reveals the genetic diversity of Xenorhabdus and Photorhabdus spp. and describes new associations between EPNs and their bacterial symbionts in Thailand

Impact of the ‘Contributing Factors in Construction Accidents’ (ConCA) model

In 2005 the ‘Contributing factors in Construction Accidents’ framework (ConCA) introduced a sociotechnical systems approach to risk management in construction. ConCA demonstrated the value of exploring distal factors and identifying underlying or latent causes: It promoted an understanding of construction accidents as systemic accidents and challenged an industry-wide culture of blaming frontline workers. A decade later the original article has been cited by research from 37 countries, shaping inquiries and initiatives to improve safety in both the UK and Australia. But to what extent has systems thinking infiltrated practitioners and policy-makers’ views? Despite broader views of contributing factors, many practitioners still view workers in a negative light, holding them responsible for accidents because of complacency, cynicism about safety, or a high-tolerance for risk. This paper evaluates the impact of the ConCA framework, updates it, and develops our understanding of the relationships between immediate circumstances and distal factors, as seen by an expert panel of participants (n = 32). A more in-depth ‘ConCA+’ framework is proposed. It challenges the negative perceptions of workers, and supports shifting the emphasis of risk management away from worker behaviors and towards resolving wider systemic issues. New directions are proposed which show how knowledge management, job design, technological innovation, empowerment and collaboration should be the focus of future work

Isolation and Characterization of Mutant Sinorhizobium meliloti NodD1 Proteins with Altered Responses to Luteolin

NodD1, a member of the NodD family of LysR-type transcriptional regulators (LTTRs), mediates nodulation (nod) gene expression in the soil bacterium Sinorhizobium meliloti in response to the plant-secreted flavonoid luteolin. We used genetic screens and targeted approaches to identify NodD1 residues that show altered responses to luteolin during the activation of nod gene transcription. Here we report four types of NodD1 mutants. Type I (NodD1 L69F, S104L, D134N, and M193I mutants) displays reduced or no activation of nod gene expression. Type II (NodD1 K205N) is constitutively active but repressed by luteolin. Type III (NodD1 L280F) demonstrates enhanced activity with luteolin compared to that of wild-type NodD1. Type IV (NodD1 D284N) shows moderate constitutive activity yet can still be induced by luteolin. In the absence of luteolin, many mutants display a low binding affinity for nod gene promoter DNA in vitro. Several mutants also show, as does wild-type NodD1, increased affinity for nod gene promoters with added luteolin. All of the NodD1 mutant proteins can homodimerize and heterodimerize with wild-type NodD1. Based on these data and the crystal structures of several LTTRs, we present a structural model of wild-type NodD1, identifying residues important for inducer binding, protein multimerization, and interaction with RNA polymerase at nod gene promoters

A Mobile App For Delirium Screening

Objective: The objective of this study is to describe the algorithm and technical implementation of a mobile app that uses adaptive testing to assess an efficient mobile app for the diagnosis of delirium. Materials and Methods: The app was used as part of a NIH-funded project to assess the feasibility, effectiveness, administration time, and costs of the 2-step delirium identification protocol when performed by physicians and nurses, and certified nursing assistants (CNA). The cohort included 535 hospitalized patients aged 79.7 (SD¼6.6) years enrolled at 2 different sites. Each patient was assessed on 2 consecutive days by the research associate who performed the reference delirium assessment. Thereafter, physicians, nurses, and CNAs performed adaptive delirium assessments using the app. Qualitative data to assess the experience of administering the 2-step protocol, and the app usability were also collected and analyzed from 50 physicians, 189 nurses, and 83 CNAs. We used extensible hypertext markup language (XHTML) and JavaScript to develop the app for the iOS–based iPad. The App was linked to Research Electronic Data Capture (REDCap), a relational database system, via a REDCap application programming interface (API) that sent and received data from/to the app. The data from REDCap were sent to the Statistical Analysis System for statistical analysis. Results: The app graphical interface was successfully implemented by XHTML and JavaScript. The API facilitated the instant updating and retrieval of delirium status data between REDCap and the app. Clinicians performed 881 delirium assessments using the app for 535 patients. The transmission of data between the app and the REDCap system showed no errors. Qualitative data indicated that the users were enthusiastic about using the app with no negative comments, 82% positive comments, and 18% suggestions of improvement. Delirium administration time for the 2-step protocol showed similar total time between nurses and physicians (103.9 vs 106.5 seconds). Weekly enrollment reports of the app data were generated for study tracking purposes, and the data are being used for statistical analyses for publications. Discussion: The app developed using iOS could be easily converted to other operating systems such as Android and could be linked to other relational databases beside REDCap, such as electronic health records to facilitate better data retrieval and updating of patient’s delirium status

Higher C-reactive Protein Levels Predict Postoperative Delirium in Older Patients Undergoing Major Elective Surgery: A Longitudinal Nested Case-Control Study

Background—Delirium is a common, morbid, and costly postoperative complication.. We aimed to identify blood-based postoperative delirium markers in a nested case control study of older surgical patients using a proteomics approach followed by enzyme-linked immunosorbent assay (ELISA) validation. Methods and Materials—The Successful Aging after Elective Surgery Study enrolled dementia-free adults age ≥70 undergoing major scheduled non-cardiac surgery (N=566; 24% delirium). Plasma was collected at 4 timepoints: preoperatively (PREOP), post-anesthesia care unit (PACU), postoperative day 2 (POD2) and 1 month follow-up (PO1MO). Matched pairs were selected for the independent discovery (39 pairs) and replication cohorts (36 pairs), which were subsequently combined into the pooled cohort (75 pairs). iTRAQ-based relative quantitation mass spectrometry proteomics was performed to identify the strongest delirium-related protein, which was selected for ELISA validation. Using the ELISA results, statistical analyses using non-parametric signed-rank tests were performed in all cohorts examining the association between the identified protein and delirium. Results—C-reactive protein (CRP) emerged from the proteomics analysis as the strongest delirium-related protein. ELISA validation confirmed that compared to controls, cases had significantly higher CRP levels (*p\u3c.05, **p\u3c.01) in the discovery, replication, and pooled cohorts at PREOP (median paired difference [mg/L] 1.97*, 0.29, 1.56**, respectively), PACU (2.83, 2.22*, 2.53**, respectively) and POD2 (71.97**, 35.18*, 63.76**, respectively), but not PO1MO (2.72, −0.66, 1.10, respectively). Discussion—Elevated pre- and postoperative plasma levels of CRP were associated with delirium, suggesting that a pre-inflammatory state and heightened inflammatory response to surgery are potential pathophysiological mechanisms of delirium

Vegetation‐hydrology dynamics in complex terrain of semiarid areas: 2. Energy‐water controls of vegetation spatiotemporal dynamics and topographic niches of favorability

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95632/1/wrcr11124.pd

Lectin-like bacteriocins from pseudomonas spp. utilise D-rhamnose containing lipopolysaccharide as a cellular receptor

Lectin-like bacteriocins consist of tandem monocot mannose-binding domains and display a genus-specific killing activity. Here we show that pyocin L1, a novel member of this family from Pseudomonas aeruginosa, targets susceptible strains of this species through recognition of the common polysaccharide antigen (CPA) of P. aeruginosa lipopolysaccharide that is predominantly a homopolymer of d-rhamnose. Structural and biophysical analyses show that recognition of CPA occurs through the C-terminal carbohydrate-binding domain of pyocin L1 and that this interaction is a prerequisite for bactericidal activity. Further to this, we show that the previously described lectin-like bacteriocin putidacin L1 shows a similar carbohydrate-binding specificity, indicating that oligosaccharides containing d-rhamnose and not d-mannose, as was previously thought, are the physiologically relevant ligands for this group of bacteriocins. The widespread inclusion of d-rhamnose in the lipopolysaccharide of members of the genus Pseudomonas explains the unusual genus-specific activity of the lectin-like bacteriocins

Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer’s disease

Alzheimer’s disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in 18F-flortaucipir vs. 18F-fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (NM) in 289 symptomatic patients from the Alzheimer’s Disease Neuroimaging Initiative. We identified six T/NM clusters with differing limbic and cortical patterns. The canonical group was defined as the T/NM pattern with lowest regression residuals. Groups resilient to T had less hypometabolism than expected relative to T and displayed better cognition than the canonical group. Groups susceptible to T had more hypometabolism than expected given T and exhibited worse cognitive decline, with imaging and clinical measures concordant with non-AD copathologies. Together, T/NM mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD

Dissociation of tau pathology and neuronal hypometabolism within the ATN framework of Alzheimer’s disease

Alzheimer’s disease (AD) is defined by amyloid (A) and tau (T) pathologies, with T better correlated to neurodegeneration (N). However, T and N have complex regional relationships in part related to non-AD factors that influence N. With machine learning, we assessed heterogeneity in 18F-flortaucipir vs. 18F-fluorodeoxyglucose positron emission tomography as markers of T and neuronal hypometabolism (NM) in 289 symptomatic patients from the Alzheimer’s Disease Neuroimaging Initiative. We identified six T/NM clusters with differing limbic and cortical patterns. The canonical group was defined as the T/NM pattern with lowest regression residuals. Groups resilient to T had less hypometabolism than expected relative to T and displayed better cognition than the canonical group. Groups susceptible to T had more hypometabolism than expected given T and exhibited worse cognitive decline, with imaging and clinical measures concordant with non-AD copathologies. Together, T/NM mismatch reveals distinct imaging signatures with pathobiological and prognostic implications for AD