Hybrid Product Cost Calculation Model as a Decision Support Tool

Cost calculation is of huge importance both for determining a rational and competitive price of the product and preparation of offers according to customer\u27s demand, where deadlines for sending offers are limited. In individual and small batch production, which is characterised by a wide product range, reduced quantities, and short delivery times, cost calculation in forming the price of the product according to customer requirements is of essential importance. Traditional methods of calculating the cost of products in these cases are inefficient, considering the number of offers that need to be made, timing, as well as their competitiveness in the market. For product cost calculation in individual and small batch production, it is necessary to apply modern, efficient methods and models based on the application of artificial intelligence. A wide range of products, which is characteristic of individual and small batch production in some companies, enables the development of modern costing models with the use of basic principles of group technology. The constructional and technological similarity of products enables the formation of groups of similar parts and appropriate group technological processes. Combining that with artificial intelligence, it is possible to develop appropriate cost calculation models. This paper presents a developed model for production cost calculation, based on the principles of group technology and adaptive neuralfuzzy networks (ANFIS)

Novel phylogenetic algorithm to monitor human tropism in Egyptian H5N1-HPAIV reveals evolution toward efficient human-to-human transmission

Years of endemic infections with highly pathogenic avian influenza (HPAI) A subtype H5N1 virus in poultry and high numbers of infections in humans provide ample opportunity in Egypt for H5N1-HPAIV to develop pandemic potential. In an effort to better understand the viral determinants that facilitate human infections of the Egyptian H5N1-HPAIVvirus, we developed a new phylogenetic algorithm based on a new distance measure derived from the informational spectrum method (ISM). This new approach, which describes functional aspects of the evolution of the hemagglutinin subunit 1 (HA1), revealed a growing group G2 of H5N1-HPAIV in Egypt after 2009 that acquired new informational spectrum (IS) properties suggestive of an increased human tropism and pandemic potential. While in 2006 all viruses in Egypt belonged to the G1 group, by 2011 these viruses were virtually replaced by G2 viruses. All of the G2 viruses displayed four characteristic mutations (D43N, S120(D,N), (S,L)129Δ and I151T), three of which were previously reported to increase binding to the human receptor. Already in 2006–2008 G2 viruses were significantly (p<0.02) more often found in humans than expected from their overall prevalence and this further increased in 2009–2011 (p<0.007). Our approach also identified viruses that acquired additional mutations that we predict to further enhance their human tropism. The extensive evolution of Egyptian H5N1-HPAIV towards a preferential human tropism underlines an urgent need to closely monitor these viruses with respect to molecular determinants of virulence

Characterization of conserved properties of hemagglutinin of H5N1 and human influenza viruses: possible consequences for therapy and infection control

<p>Abstract</p> <p>Background</p> <p>Epidemics caused by highly pathogenic avian influenza virus (HPAIV) are a continuing threat to human health and to the world's economy. The development of approaches, which help to understand the significance of structural changes resulting from the alarming mutational propensity for human-to-human transmission of HPAIV, is of particularly interest. Here we compare informational and structural properties of the hemagglutinin (HA) of H5N1 virus and human influenza virus subtypes, which are important for the receptor/virus interaction.</p> <p>Results</p> <p>Presented results revealed that HA proteins encode highly conserved information that differ between influenza virus subtypes H5N1, H1N1, H3N2, H7N7 and defined an HA domain which may modulate interaction with receptor. We also found that about one third of H5N1 viruses which are isolated during the 2006/07 influenza outbreak in Egypt possibly evolve towards receptor usage similar to that of seasonal H1N1.</p> <p>Conclusion</p> <p>The presented results may help to better understand the interaction of influenza virus with its receptor(s) and to identify new therapeutic targets for drug development.</p

Predicted enhanced human propensity of current avian-like H1N1 swine influenza virus from China

Influenza A virus (IAV) subtypes against which little or no pre-existing immunity exists in humans represent a serious threat to global public health. Monitoring of IAV in animal hosts is essential for early and rapid detection of potential pandemic IAV strains to prevent their spread. Recently, the increased pandemic potential of the avian-like swine H1N1 IAV A/swine/Guangdong/104/2013 has been suggested. The virus is infectious in humans and the general population seems to lack neutralizing antibodies against this virus. Here we present an in silico analysis that shows a strong human propensity of this swine virus further confirming its pandemic potential. We suggest mutations which would further enhance its human propensity. We also propose conserved antigenic determinants which could serve as a component of a prepandemic vaccine. The bioinformatics tool, which can be used to further monitor the evolution of swine influenza viruses towards a pandemic virus, are described here and are made publically available (http://www.vin.bg.ac.rs/180/tools/iav-mon.php; http://www.biomedprotection.com/iav-mon.php)

IDPpi:Protein-protein interaction analyses of human intrinsically disordered proteins

Intrinsically disordered proteins (IDPs) are characterized by the lack of a fixed tertiary structure and are involved in the regulation of key biological processes via binding to multiple protein partners. IDPs are malleable, adapting to structurally different partners, and this flexibility stems from features encoded in the primary structure. The assumption that universal sequence information will facilitate coverage of the sparse zones of the human interactome motivated us to explore the possibility of predicting protein-protein interactions (PPIs) that involve IDPs based on sequence characteristics. We developed a method that relies on features of the interacting and non-interacting protein pairs and utilizes machine learning to classify and predict IDP PPIs. Consideration of both sequence determinants specific for conformational organizations and the multiplicity of IDP interactions in the training phase ensured a reliable approach that is superior to current state-of-the-art methods. By applying a strict evaluation procedure, we confirm that our method predicts interactions of the IDP of interest even on the proteome-scale. This service is provided as a web tool to expedite the discovery of new interactions and IDP functions with enhanced efficiency. © 2018 The Author(s)

In Silico and In Vitro Inhibition of SARS-CoV-2 PLpro with Gramicidin D

Finding an effective drug to prevent or treat COVID-19 is of utmost importance in tcurrent pandemic. Since developing a new treatment takes a significant amount of time, drug repurposing can be an effective option for achieving a rapid response. This study used a combined in silico virtual screening protocol for candidate SARS-CoV-2 PLpro inhibitors. The Drugbank database was searched first, using the Informational Spectrum Method for Small Molecules, followed by molecular docking. Gramicidin D was selected as a peptide drug, showing the best in silico interaction profile with PLpro. After the expression and purification of PLpro, gramicidin D was screened for protease inhibition in vitro and was found to be active against PLpro. The current study’s findings are significant because it is critical to identify COVID-19 therapies that are efficient, affordable, and have a favorable safety profil

Could Inelastic Interactions Induce Quantum Probabilistic Transitions?

What are quantum entities? Is the quantum domain deterministic or probabilistic? Orthodox quantum theory (OQT) fails to answer these two fundamental questions. As a result of failing to answer the first question, OQT is very seriously defective: it is imprecise, ambiguous, ad hoc, non-explanatory, inapplicable to the early universe, inapplicable to the cosmos as a whole, and such that it is inherently incapable of being unified with general relativity. It is argued that probabilism provides a very natural solution to the quantum wave/particle dilemma and promises to lead to a fully micro-realistic, testable version of quantum theory that is free of the defects of OQT. It is suggested that inelastic interactions may induce quantum probabilistic transitions

Practice patterns in chronic graft-versus-host disease patient management and patient reported outcome measures across the EBMT allogeneic transplantation network

Background Chronic graft-versus-host disease (cGvHD) is one of the most common life-threatening complications following allogeneic haematopoietic stem cell transplantation (alloHSCT). Understanding outcome after alloHSCT requires a full evaluation of the patient’s health status, including cGvHD and patient reported outcomes (PROs). In an effort to better understand practice patterns across European countries, a survey was initiated by the Integrated European Network on cGvHD (an EU-funded COST Action CA17138 EUROGRAFT, www.gvhd.eu) and the Transplant Complications Working Party of the European Society for Blood and Marrow Transplantation (EBMT). This report shares results of the survey, offering a snapshot view of current practice patterns in the context of long-term care of cGvHD patients. Methods Our self-designed 38-item online survey (Supplementary Material) was intended to collect data regarding transplant center characteristics, data registration practices, the use of NIH criteria in clinical routine, biopsies/biomarkers for clinical assessment, cGvHD cell-based therapies, and PROs. The survey used computer adapted testing methods and took ~10 min to complete. All centers participating in the COST Action EUROGRAFT and all EBMT centers performing alloHSCT were invited by email for participation in the survey. Data were collected between July 2019 and July 2020. Appropriate descriptive statistics were used. In case of multiple entries for a single center (n = 4), only the entry from the most senior staff member was included for the analysis. Missing data was reported as such. Findings Center characteristics Survey results are summarized in Table 1. A total of 72 centers out of 424 invited centers from 24 countries responded to the survey, representing ~17% of all alloHSCT centers and 19.6% of all transplanted patients within the EBMT network [1]. The majority of participating alloHSCT centers were from Europe with exception of three centers based in Asia and one in Latin America. Survey responses were mainly submitted by physicians and data managers. Of note, the size of the transplant programs differed between responding (mean ± SD, n = 47 ± 40 transplants/year) vs. non-responding (mean ± SD, n = 39 ± 31 transplants/year) centers (Supplementary Material)

B7-H1 Blockade Increases Survival of Dysfunctional CD8+ T Cells and Confers Protection against Leishmania donovani Infections

Experimental visceral leishmaniasis (VL) represents an exquisite model to study CD8+ T cell responses in a context of chronic inflammation and antigen persistence, since it is characterized by chronic infection in the spleen and CD8+ T cells are required for the development of protective immunity. However, antigen-specific CD8+ T cell responses in VL have so far not been studied, due to the absence of any defined Leishmania-specific CD8+ T cell epitopes. In this study, transgenic Leishmania donovani parasites expressing ovalbumin were used to characterize the development, function, and fate of Leishmania-specific CD8+ T cell responses. Here we show that L. donovani parasites evade CD8+ T cell responses by limiting their expansion and inducing functional exhaustion and cell death. Dysfunctional CD8+ T cells could be partially rescued by in vivo B7-H1 blockade, which increased CD8+ T cell survival but failed to restore cytokine production. Nevertheless, B7-H1 blockade significantly reduced the splenic parasite burden. These findings could be exploited for the design of new strategies for immunotherapeutic interventions against VL

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. Conclusion We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.Peer reviewe