Role of Surface Energy and Nano-Roughness in the Removal Efficiency of Bacterial Contamination by Nonwoven Wipes from Frequently Touched Surfaces

Healthcare associated infections (HCAIs) are responsible for substantial patient morbidity, mortality and economic cost. Infection control strategies for reducing rates of transmission include the use of nonwoven wipes to remove pathogenic bacteria from frequently touched surfaces. Wiping is a dynamic process that involves physicochemical mechanisms to detach and transfer bacteria to fibre surfaces within the wipe. The purpose of this study was to determine the extent to which systematic changes in fibre surface energy and nano-roughness influence removal of bacteria from an abiotic polymer surface in dry wiping conditions, without liquid detergents or disinfectants. Nonwoven wipe substrates composed of two commonly used fibre types, lyocell (cellulosic) and polypropylene, with different surface energies and nano-roughnesses, were manufactured using pilot-scale nonwoven facilities to produce samples of comparable structure and dimensional properties. The surface energy and nano-roughness of some lyocell substrates were further adjusted by either oxygen (O2) or hexafluoroethane (C2F6) gas plasma treatment. Static adpression wiping of an inoculated surface under dry conditions produced removal efficiencies of between 9.4% and 15.7%, with no significant difference (p < 0.05) in the relative removal efficiencies of Escherichia coli, Staphylococcus aureus or Enterococcus faecalis. However, dynamic wiping markedly increased peak wiping efficiencies to over 50%, with a minimum increase in removal efficiency of 12.5% and a maximum increase in removal efficiency of 37.9% (all significant at p < 0.05) compared with static wiping, depending on fibre type and bacterium. In dry, dynamic wiping conditions, nonwoven wipe substrates with a surface energy closest to that of the contaminated surface produced the highest E. coli removal efficiency, while the associated increase in fibre nano-roughness abrogated this trend with S. aureus and E. faecalis. Plasma modification of the nano-roughness and surface energy of fibres in nonwoven wipes was found to influence the relative removal efficiencies of common bacterial pathogens from model healthcare surfaces under dynamic wiping conditions

How and When Socially Entrepreneurial Nonprofit Organizations Benefit From Adopting Social Alliance Management Routines to Manage Social Alliances?

Social alliance is defined as the collaboration between for-profit and nonprofit organizations. Building on the insights derived from the resource-based theory, we develop a conceptual framework to explain how socially entrepreneurial nonprofit organizations (SENPOs) can improve their social alliance performance by adopting strategic alliance management routines. We test our framework using the data collected from 203 UK-based SENPOs in the context of cause-related marketing campaign-derived social alliances. Our results confirm a positive relationship between social alliance management routines and social alliance performance. We also find that relational mechanisms, such as mutual trust, relational embeddedness, and relational commitment, mediate the relationship between social alliance management routines and social alliance performance. Moreover, our findings suggest that different types of social alliance motivation can influence the impact of social alliance management routines on different types of the relational mechanisms. In general, we demonstrate that SENPOs can benefit from adopting social alliance management routines and, in addition, highlight how and when the social alliance management routines–social alliance performance relationship might be shaped. Our study offers important academic and managerial implications, and points out future research directions

Comparison of RCAS1 and metallothionein expression and the presence and activity of immune cells in human ovarian and abdominal wall endometriomas

BACKGROUND: The coexistence of endometrial and immune cells during decidualization is preserved by the ability of endometrial cells to regulate the cytotoxic immune activity and their capability to be resistant to immune-mediated apoptosis. These phenomena enable the survival of endometrial ectopic cells. RCAS1 is responsible for regulation of cytotoxic activity. Metallothionein expression seems to protect endometrial cells against apoptosis. The aim of the present study was to evaluate RCAS1 and metallothionein expression in human ovarian and scar endometriomas in relation to the presence of immune cells and their activity. METHODS: Metallothionein, RCAS1, CD25, CD69, CD56, CD16, CD68 antigen expression was assessed by immunohistochemistry in ovarian and scar endometriomas tissue samples which were obtained from 33 patients. The secretory endometrium was used as a control group (15 patients). RESULTS: The lowest metallothionein expression was revealed in ovarian endometriomas in comparison to scar endometriomas and to the control group. RCAS1 expression was at the highest level in the secretory endometrium and it was at comparable levels in ovarian and scar endometriomas. Similarly, the number of CD56-positive cells was lower in scar and ovarian endometriomas than in the secretory endometrium. The highest number of macrophages was found in ovarian endometriomas. RCAS1-positive macrophages were observed only in ovarian endometriomas. CD25 and CD69 antigen expression was higher in scar and ovarian endometriomas than in the control group. CONCLUSION: The expression of RCAS1 and metallothionein by endometrial cells may favor the persistence of these cells in ectopic localization both in scar following cesarean section and in ovarian endometriosis

Computational Prediction and Molecular Characterization of an Oomycete Effector and the Cognate Arabidopsis Resistance Gene

Hyaloperonospora arabidopsidis (Hpa) is an obligate biotroph oomycete pathogen of the model plant Arabidopsis thaliana and contains a large set of effector proteins that are translocated to the host to exert virulence functions or trigger immune responses. These effectors are characterized by conserved amino-terminal translocation sequences and highly divergent carboxyl-terminal functional domains. The availability of the Hpa genome sequence allowed the computational prediction of effectors and the development of effector delivery systems enabled validation of the predicted effectors in Arabidopsis. In this study, we identified a novel effector ATR39-1 by computational methods, which was found to trigger a resistance response in the Arabidopsis ecotype Weiningen (Wei-0). The allelic variant of this effector, ATR39-2, is not recognized, and two amino acid residues were identified and shown to be critical for this loss of recognition. The resistance protein responsible for recognition of the ATR39-1 effector in Arabidopsis is RPP39 and was identified by map-based cloning. RPP39 is a member of the CC-NBS-LRR family of resistance proteins and requires the signaling gene NDR1 for full activity. Recognition of ATR39-1 in Wei-0 does not inhibit growth of Hpa strains expressing the effector, suggesting complex mechanisms of pathogen evasion of recognition, and is similar to what has been shown in several other cases of plant-oomycete interactions. Identification of this resistance gene/effector pair adds to our knowledge of plant resistance mechanisms and provides the basis for further functional analyses

Identification of B Cell Epitopes of Alcohol Dehydrogenase Allergen of Curvularia lunata

BACKGROUND/OBJECTIVE: Epitope identification assists in developing molecules for clinical applications and is useful in defining molecular features of allergens for understanding structure/function relationship. The present study was aimed to identify the B cell epitopes of alcohol dehydrogenase (ADH) allergen from Curvularia lunata using in-silico methods and immunoassay. METHOD: B cell epitopes of ADH were predicted by sequence and structure based methods and protein-protein interaction tools while T cell epitopes by inhibitory concentration and binding score methods. The epitopes were superimposed on a three dimensional model of ADH generated by homology modeling and analyzed for antigenic characteristics. Peptides corresponding to predicted epitopes were synthesized and immunoreactivity assessed by ELISA using individual and pooled patients' sera. RESULT: The homology model showed GroES like catalytic domain joined to Rossmann superfamily domain by an alpha helix. Stereochemical quality was confirmed by Procheck which showed 90% residues in most favorable region of Ramachandran plot while Errat gave a quality score of 92.733%. Six B cell (P1-P6) and four T cell (P7-P10) epitopes were predicted by a combination of methods. Peptide P2 (epitope P2) showed E(X)(2)GGP(X)(3)KKI conserved pattern among allergens of pathogenesis related family. It was predicted as high affinity binder based on electronegativity and low hydrophobicity. The computational methods employed were validated using Bet v 1 and Der p 2 allergens where 67% and 60% of the epitope residues were predicted correctly. Among B cell epitopes, Peptide P2 showed maximum IgE binding with individual and pooled patients' sera (mean OD 0.604±0.059 and 0.506±0.0035, respectively) followed by P1, P4 and P3 epitopes. All T cell epitopes showed lower IgE binding. CONCLUSION: Four B cell epitopes of C. lunata ADH were identified. Peptide P2 can serve as a potential candidate for diagnosis of allergic diseases

Analysis of the Expression, Secretion and Translocation of the Salmonella enterica Type III Secretion System Effector SteA

Many Gram-negative pathogens possess virulence-related type III secretion systems. Salmonella enterica uses two of these systems, encoded on the pathogenicity islands SPI-1 and SPI-2, respectively, to translocate more than 30 effector proteins into eukaryotic host cells. SteA is one of the few effectors that can be translocated by both systems. We investigated the conditions affecting the synthesis of this effector, its secretion to culture media and its translocation into host cells. Whereas steA was expressed under a wide range of conditions, some factors, including low and high osmolarity, and presence of butyrate, decreased expression. SteA was efficiently secreted to the culture media under both SPI-1 and SPI-2 inducing conditions. The kinetics of translocation into murine macrophages and human epithelial cells was studied using fusions with the 3xFLAG tag, and fusions with CyaA from Bordetella pertussis. Translocation into macrophages under non-invasive conditions was mainly dependent on the SPI-2-encoded type III secretion system but some participation of the SPI-1 system was also detected 6 hours post-infection. Interestingly, both type III secretion systems had a relevant role in the translocation of SteA into epithelial cells. Finally, a deletion approach allowed the identification of the N-terminal signal necessary for translocation of this effector. The amino acid residues 1–10 were sufficient to direct translocation into host cells through both type III secretion systems. Our results provide new examples of functional overlapping between the two type III secretion systems of Salmonella

Use of twitter data for waste minimisation in beef supply chain

Approximately one third of the food produced is discarded or lost, which accounts for 1.3 billion tons per annum. The waste is being generated throughout the supply chain viz. farmers, wholesalers/processors, logistics, retailers and consumers. The majority of waste occurs at the interface of retailers and consumers. Many global retailers are making efforts to extract intelligence from customer’s complaints left at retail store to backtrack their supply chain to mitigate the waste. However, majority of the customers don’t leave the complaints in the store because of various reasons like inconvenience, lack of time, distance, ignorance etc. In current digital world, consumers are active on social media and express their sentiments, thoughts, and opinions about a particular product freely. For example, on an average, 45,000 tweets are tweeted daily related to beef products to express their likes and dislikes. These tweets are large in volume, scattered and unstructured in nature. In this study, twitter data is utilised to develop waste minimization strategies by backtracking the supply chain. The execution process of proposed framework is demonstrated for beef supply chain. The proposed model is generic enough and can be applied to other domains as well

Identification of Hyaloperonospora arabidopsidis Transcript Sequences Expressed during Infection Reveals Isolate-Specific Effectors

Biotrophic plant pathogens secrete effector proteins that are important for infection of the host. The aim of this study was to identify effectors of the downy mildew pathogen Hyaloperonospora arabidopsidis (Hpa) that are expressed during infection of its natural host Arabidopsis thaliana. Infection-related transcripts were identified from Expressed Sequence Tags (ESTs) derived from leaves of the susceptible Arabidopsis Ws eds1-1 mutant inoculated with the highly virulent Hpa isolate Waco9. Assembly of 6364 ESTs yielded 3729 unigenes, of which 2164 were Hpa-derived. From the translated Hpa unigenes, 198 predicted secreted proteins were identified. Of these, 75 were found to be Hpa-specific and six isolate Waco9-specific. Among 42 putative effectors identified there were three Elicitin-like proteins, 16 Cysteine-rich proteins and 18 host-translocated RXLR effectors. Sequencing of alleles in different Hpa isolates revealed that five RXLR genes show signatures of diversifying selection. Thus, EST analysis of Hpa-infected Arabidopsis is proving to be a powerful method for identifying pathogen effector candidates expressed during infection. Delivery of the Waco9-specific protein RXLR29 in planta revealed that this effector can suppress PAMP-triggered immunity and enhance disease susceptibility. We propose that differences in host colonization can be conditioned by isolate-specific effectors

25th Annual Computational Neuroscience Meeting: CNS-2016

Abstracts of the 25th Annual Computational Neuroscience Meeting: CNS-2016 Seogwipo City, Jeju-do, South Korea. 2–7 July 201