A Reputational-Risk-Based Match Selection Framework for Collaborative Networks in the Logistics Sector

IPL/2021/ReEdIACollaborative networks in the logistics sector have proven to be a solution that both meets environmental footprint reduction goals and addresses the impact of rising fuel prices on logistics companies, especially for small-and medium-sized enterprises. Despite these benefits, these collaborative networks have not received the desired amount of participation due to reputational risk. This paper develops a framework for assessing and managing reputational risk to encourage logistics companies’ participation in collaborative networks. To this end, customer satisfaction factors were correlated with logistics operations, and this correlation was then modeled using the Bowtie method, fault trees, event trees, reliability theory, and the Monte Carlo model. The results show that it is possible to implement a structured model that can be easily put into practice. Using an illustrative case study, it is also possible to prioritize three companies according to their reputational risk as assessed by the proposed model. The developed model can promote the sustainability of collaborative networks in the logistics industry by assessing and consistently reducing reputational risk, thus supporting the strengthening of the relationship between suppliers, logistics service providers, and end customers.publishersversionpublishe

A Case Study of Aircraft Maintenance Repairs

and also by the Polytechnic Institute of Lisbon through the Projects for Research, Development, Innovation and Artistic Creation (IDI&CA), within the framework of the project ReEdIA—Risk Assessment and Management in Open Innovation, IPL/2021/ReEdIA/ISEL. Publisher Copyright: © 2022 by the authors.This paper proposes a qualitative model to overcome the limitations of conventional failure mode and effects analysis (FMEA), which does not consider risk mitigation capabilities when prioritizing risks. Failure to consider these capabilities can lead to unrealistic risk estimates, especially when the level of uncertainty is high. In the proposed model, the original applicability of conventional FMEA was retained along with the three conventional risk variables, namely, severity, occurrence, and detectability. In addition, a fourth variable was added to account for risk mitigation capabilities. A case study in the project selection of aircraft repairs was used to demonstrate the implementation of the model and its applicability. The results show that the inclusion of mitigation options leads to more realistic risk scenarios, suggesting that the original FMEA approach may lead to non-conservative risk estimates.publishersversionpublishe

Origin, phylogeny, variability and epitope conservation of SARS-CoV-2 worldwide

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses innumerous challenges, like understanding what triggered the emergence of this new human virus, how this RNA virus is evolving or how the variability of viral genome may impact the primary structure of proteins that are targets for vaccine. We analyzed 19471 SARS-CoV-2 genomes available at the GISAID database from all over the world and 3335 genomes of other Coronoviridae family members available at GenBank, collecting SARS-CoV-2 high-quality genomes and distinct Coronoviridae family genomes. Additionally, we analyzed 199,984 spike glycoprotein sequences. Here, we identify a SARS-CoV-2 emerging cluster containing 13 closely related genomes isolated from bat and pangolin that showed evidence of recombination, which may have contributed to the emergence of SARS-CoV-2. The analyzed SARS-CoV-2 genomes presented 9632 single nucleotide variants (SNVs) corresponding to a variant density of 0.3 over the genome, and a clear geographic distribution. SNVs are unevenly distributed throughout the genome and hotspots for mutations were found for the spike gene and ORF 1ab. We describe a set of predicted spike protein epitopes whose variability is negligible. Additionally, all predicted epitopes for the structural E, M and N proteins are highly conserved. The amino acid changes present in the spike glycoprotein of variables of concern (VOCs) comprise between 3.4% and 20.7% of the predicted epitopes of this protein. These results favors the continuous efficacy of the available vaccines targeting the spike protein, and other structural proteins. Multiple epitopes vaccines should sustain vaccine efficacy since at least some of the epitopes present in variability regions of VOCs are conserved and thus recognizable by antibodies.This work is based on SARS-CoV-2 genomes available in the GISAID database, so we would like to express our appreciation to all the researchers who contributed to the effort of sequencing and make genomes available. The authors would like to thank Francine Perler for valuable comments and suggestions. This work was funded by national funds from FCT – Fundação para a Ciência e a Tecnologia, I.P., projects UIDB/04138/2020 and UIDP/04138/2020. Filipa F. Vale is financed by FCT through Assistant Researcher grant CEECIND/03023/2017.info:eu-repo/semantics/publishedVersio

Liposomal Delivery of Newly Identified Prophage Lysins in a Pseudomonas aeruginosa Model

Pseudomonas aeruginosa is a Gram-negative opportunistic bacterium that presents resistance to several antibiotics, thus, representing a major threat to human and animal health. Phage-derived products, namely lysins, or peptidoglycan-hydrolyzing enzymes, can be an effective weapon against antibiotic-resistant bacteria. Whereas in Gram-positive bacteria, lysis from without is facilitated by the exposed peptidoglycan layer, this is not possible in the outer membrane-protected peptidoglycan of Gram-negative bacteria. Here, we suggest the encapsulation of lysins in liposomes as a delivery system against Gram-negative bacteria, using the model of P. aeruginosa. Bioinformatic analysis allowed for the identification of 38 distinct complete prophages within 66 P. aeruginosa genomes (16 of which newly sequenced) and led to the identification of 19 lysins of diverse sequence and function, 5 of which proceeded to wet lab analysis. The four purifiable lysins showed hydrolytic activity against Gram-positive bacterial lawns and, on zymogram assays, constituted of autoclaved P. aeruginosa cells. Additionally, lysins Pa7 and Pa119 combined with an outer membrane permeabilizer showed activity against P. aeruginosa cells. These two lysins were successfully encapsulated in DMPC:DOPE:CHEMS (molar ratio 4:4:2) liposomes with an average encapsulation efficiency of 33.33% and 32.30%, respectively. The application of the encapsulated lysins to the model P. aeruginosa led to a reduction in cell viability and resulted in cell lysis as observed in MTT cell viability assays and electron microscopy. In sum, we report here that prophages may be important sources of new enzybiotics, with prophage lysins showing high diversity and activity. In addition, these enzybiotics following their incorporation in liposomes were able to potentiate their antibacterial effect against the Gram-negative bacteria P. aeruginosa, used as the model.FFV is funded by Fundação para a Ciência e a Tecnologia (FCT) through an Assistant Researcher grant CEECIND/03023/2017, and a project grant (project PTDC/BTM-SAL/28978/2017) that supported this work. JSV holds a research fellowship within the scope of project PTDC/BTM-TEC/3238/2020 (FCT). The work has been partially supported by National funds from FCT, projects UIDB/04138/2020 and UIDP/04138/2020.info:eu-repo/semantics/publishedVersio