Abrasive Wear Resistance of the Iron- and WC-based Hardfaced Coatings Evaluated with Scratch Test Method

Abrasive wear is one of the most common types of wear, which makesabrasive wear resistance very important in many industries. Thehard facing is considered as useful and economical way to improve theperformance of components submitted to severe abrasive wear conditions, with wide range of applicable filler materials. The abrasive wear resistance of the three different hardfaced coatings (two iron‐based and one WC‐based), which were intended to be used for reparation of the impact plates of the ventilation mill, was investigated and compared. Abrasive wear tests were carried‐out by using the scratch tester under the dry conditions. Three normal loads of 10, 50 and 100 N and the constant sliding speed of 4 mm/s were used. Scratch test was chosen as a relatively easy and quick test method. Wear mechanism analysis showed significant influence of the hardfaced coatings structure, which, along with hardness, has determined coatings abrasive wear resistance

The tribological performance of hardfaced/ thermal sprayed coatings for increasing the wear resistance of ventilation mill working parts

During the coal pulverizing, the working parts of the ventilation mill are being worn by the sand particles. For this reason, the working parts are usually protected with materials resistant to wear (hardfaced/thermal sprayed coatings). The aim of this study was to evaluate the tribological performance of four different types of coatings as candidates for wear protection of the mill’s working parts. The coatings were produced by using the filler materials with the following nominal chemical composition: NiFeBSi-WC, NiCrBSiC, FeCrCTiSi, and FeCrNiCSiBMn, and by using the plasma arc welding and flame and electric arc spraying processes. The results showed that Ni-based coatings exhibited higher wear resistance than Fe-based coatings. The highest wear resistance showed coating produced by using the NiFeBSi-WC filler material and plasma transferred arc welding deposition process. The hardness was not the only characteristic that affected the wear resistance. In this context, the wear rate of NiFeBSi-WC coating was not in correlation with its hardness, in contrast to other coatings. The different wear performance of NiFeBSi-WC coating was attributed to the different type and morphological features of the reinforcing particles (WC)

Supplementary data for the article: Gligorijević, N.; Minić, S. L.; Robajac, D. B.; Nikolić, M.; Ćirković-Veličković, T.; Nedić, O. Characterisation and the Effects of Bilirubin Binding to Human Fibrinogen. International Journal of Biological Macromolecules 2019, 128, 74–79. https://doi.org/10.1016/j.ijbiomac.2019.01.124

Supplementary material for: [https://www.sciencedirect.com/science/article/pii/S014181301835880X?via%3Dihub]Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2824]Related to accepted version: [http://cherry.chem.bg.ac.rs/handle/123456789/2825

Supplementary data for the article: Gligorijević, N.; Minić, S. L.; Robajac, D. B.; Nikolić, M.; Ćirković-Veličković, T.; Nedić, O. Characterisation and the Effects of Bilirubin Binding to Human Fibrinogen. International Journal of Biological Macromolecules 2019, 128, 74–79. https://doi.org/10.1016/j.ijbiomac.2019.01.124

Supplementary material for: [https://www.sciencedirect.com/science/article/pii/S014181301835880X?via%3Dihub]Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/2824]Related to accepted version: [http://cherry.chem.bg.ac.rs/handle/123456789/2825

Proteomic insight into allergenic food corona on polyethylene terephthalate microplastics

Microplastics is abundant in the environment, food and beverages and get ingested by humans. Its complex interplay with proteins lead to formation of corona. Tightly bound proteins represent hard corona, while weaker binding partners are found in soft corona. Separation of hard and soft corona of allergenic proteins of shrimps, eggs and cow’s milk, tropomyosin (TPM), ovalbumin (OVA) and beta-lactoglobulin (BLG) and identification of binding partners by proteomics was aim of our study. Allergenic proteins were purified from egg white, shrimps and cow’s milk. Binding to polyethylene terephthalate microplastics (PET) (70-100 m) was probed at pH 7 for purified allergens and egg white proteins. After establishment of binding equilibrium, soft and hard corona were separated and analyzed by SDS PAGE, followed by identification of bound proteins by nanoLC-HRMS. Binding of all allergenic proteins was observed in both soft and hard corona. Soft corona contains exclusively intact, full length OVA, TPM and BLG. Hard corona is enriched for truncated OVA and oligomers of TPM. OVA fragments are partially or fully enfolded and have higher level of exposed hydrophobic patches resulting in higher affinity for PET microplastics. In comparison to OVA and TPM, hard corona of BLG is less abundant under similar conditions. BLG is compact globular protein with lower level of exposed hydrophobic patches in comparison to ovalbumin and tropomyosin. In hard corona, trace amounts of contaminating alfa-lactalbumin become enriched. In the presence of egg white protein extract OVA forms both SC and HC on microplastics, being the dominant protein of hard corona (with ovotransferrin). Lysozyme and ovomucin are present only in hard corona. Both proteins are known for their strong bioactivity and represent a small fraction of total egg white proteins. Our results show that allergenic proteins form hard corona on PET microplastics. Among egg white proteins, minor proteins such as lysozyme and ovomucin become enriched. Denaturing effect of strong binding to microplastics may change functional characteristics of allergens and bioactive proteins of foods and should be further investigated in functional assays.[https://itpa.it/index.php/past-events/xvii-itpa-hps-and-sepa-international-congress-rome-italy-november-29-december-1-2023/

The use of starch and β-lactoglobulin composite hydrogels as frameworks for preserving c-phycocyanin

Our study aimed to preserve the natural blue dye of C-phycocyanin (C-PC) phycobiliprotein from Spirulina microalgae due to its importance in the food industry. We incorporated C-PC into hydrogels formed by combining starch and β-lactoglobulin (BLG) using high-pressure (HP) processing to achieve this objective. Notably, thermal treatment resulted in the complete loss of colour derived from C-PC. We performed a comprehensive characterization of the resulting HP gels by rheology measurements, texture profile analysis (TPA), small-angle X-ray scattering (SAXS), and scanning electron microscopy (SEM). Different compositions of binary (BLG/C-PC) and ternary (starch/BLG/C-PC) systems were processed under high-pressure (HP) conditions reaching up to 4,500 bar. The C-PC pigment was effectively preserved by mixing BLG and starch with C-PC at pH 7, maintaining concentrations of 180, 5, and 10 mg/mL, respectively. The same concentrations of components were retained in the binary systems. Rheological properties of the gels were determined using a rheometer with plane/plane geometry, and texture analysis was conducted through TPA. These findings enabled the assessment of food gel's properties, such as hardness, springiness, chewiness, and cohesiveness. The structural characteristics of the gels were determined by SAXS, offering insights into the interactions between C-PC, BLG, and starch after HP processing. Adding CPC and starch formed solid gels with a larger mesh than the pure BLG gels. SEM scans of the gel surface revealed that all components influenced the overall morphology of gels. Even at low concentrations, the addition of starch notably influenced the gels' visual appearance and mechanical properties. Our investigation highlights the superior effectiveness of HP treatment in the preservation of C-PC compared to high-temperature treatment, evident in the sustained colour integrity of the C-PC blue dye

Effects of terminal substitution and iron coordination on antiproliferative activity of L-proline-salicylaldehyde-thiosemicarbazone hybrids

A series of five iron(III) complexes, namely [Fe(HL1)Cl2] (1), [Fe(HL2)Cl2]·1.6H2O (2·1.6H2O), [Fe(HL3)(MeOH)Cl2]·0.5H2O (3·0.5H2O), [Fe(HL4)(MeOH)Cl2]·0.5H2O (4·0.5H2O) and [Fe(HL4)(DMF)Cl2]·0.5Et2O·H2O (4′·0.5Et2O·H2O), where H2L1 = l‐proline‐salicylaldehyde–thiosemicarbazone (l‐Pro‐STSC), H2L2 = pyrrolidine‐substituted l‐Pro‐STSC, H2L3 = phenyl‐substituted l‐Pro‐STSC, and H2L4 = naphthyl‐substituted l‐Pro‐STSC, have been synthesized. The two ligand precursors (H2L3 and H2L4) and iron complexes were characterized by elemental analysis, spectroscopic methods (UV/Vis, IR, and NMR), ESI mass spectrometry, cyclic voltammetry, and single‐crystal X‐ray crystallography (1–3 and 4′). Magnetic properties of the five‐coordinate complex 2 and six‐coordinate complex 4 have also been investigated. The antiproliferative activity of the organic hybrids and their iron(III) complexes have been studied in vitro in five human cell lines and one murine cancer cell line, namely HeLa (cervical cancer), FemX (melanoma), A549 (alveolar basal adenocarcinoma), LS‐174 (colon cancer), MDA‐MB‐453 (breast cancer) and MS1 (transformed murine endothelial), as well as in human noncancerous fetal lung fibroblast cell line (MRC‐5). According to the structure–activity relationship, introduction of aromatic groups such as phenyl or naphthyl enhances the cytotoxic potency of the hybrids in the following order H2L1 < H2L2 < H2L3 < H2L4. Coordination of the hybrids to iron(III) improves their antiproliferative activity in the majority of investigated cell lines with exception of H2L3 in LS‐174, H2L4 in MS1, and both H2L3 and H2L4 in FemX cell lines, where an opposite effect was observed.This study was financially supported by the Austrian Science Fund (project number P28223 N34), Research and Development Agency of the Slovak Republic under the contracts No. APVV 15-0079 and APVV-15-0053, Scientific Grant Agency of the Slovak Republic (VEGA Project 1/0871/16) and Slovak University of Technology in Bratislava (Young Researcher Grant, M. Milunović, PhD) This work was also supported by Ministry of Education, Science, Research and Sport of the Slovak Republic withinhe Research and Development Operational Program for the project "University Science Park of STU Bratislava", ITMS 26240220084, cofunded by the European Regional Development Fund

Probabilistic Random Walk Models for Comparative Network Analysis

Graph-based systems and data analysis methods have become critical tools in many fields as they can provide an intuitive way of representing and analyzing interactions between variables. Due to the advances in measurement techniques, a massive amount of labeled data that can be represented as nodes on a graph (or network) have been archived in databases. Additionally, novel data without label information have been gradually generated and archived. Labeling and identifying characteristics of novel data is an important first step in utilizing the valuable data in an effective and meaningful way. Comparative network analysis is an effective computational means to identify and predict the properties of the unlabeled data by comparing the similarities and differences between well-studied and less-studied networks. Comparative network analysis aims to identify the matching nodes and conserved subnetworks across multiple networks to enable a prediction of the properties of the nodes in the less-studied networks based on the properties of the matching nodes in the well-studied networks (i.e., transferring knowledge between networks). One of the fundamental and important questions in comparative network analysis is how to accurately estimate node-to-node correspondence as it can be a critical clue in analyzing the similarities and differences between networks. Node correspondence is a comprehensive similarity that integrates various types of similarity measurements in a balanced manner. However, there are several challenges in accurately estimating the node correspondence for large-scale networks. First, the scale of the networks is a critical issue. As networks generally include a large number of nodes, we have to examine an extremely large space and it can pose a computational challenge due to the combinatorial nature of the problem. Furthermore, although there are matching nodes and conserved subnetworks in different networks, structural variations such as node insertions and deletions make it difficult to integrate a topological similarity. In this dissertation, novel probabilistic random walk models are proposed to accurately estimate node-to-node correspondence between networks. First, we propose a context-sensitive random walk (CSRW) model. In the CSRW model, the random walker analyzes the context of the current position of the random walker and it can switch the random movement to either a simultaneous walk on both networks or an individual walk on one of the networks. The context-sensitive nature of the random walker enables the method to effectively integrate different types of similarities by dealing with structural variations. Second, we propose the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) model. In the CUFID model, we construct an integrated network by inserting pseudo edges between potential matching nodes in different networks. Then, we design the random walk protocol to transit more frequently between potential matching nodes as their node similarity increases and they have more matching neighboring nodes. We apply the proposed random walk models to comparative network analysis problems: global network alignment and network querying. Through extensive performance evaluations, we demonstrate that the proposed random walk models can accurately estimate node correspondence and these can lead to improved and reliable network comparison results

Lymphatic marker podoplanin/D2-40 in human advanced cirrhotic liver- Re-evaluations of microlymphatic abnormalities

<p>Abstract</p> <p>Background</p> <p>From the morphological appearance, it was impossible to distinguish terminal portal venules from small lymphatic vessels in the portal tract even using histochemical microscopic techniques. Recently, D2-40 was found to be expressed at a high level in lymphatic endothelial cells (LECs). This study was undertaken to elucidate hepatic lymphatic vessels during progression of cirrhosis by examining the expression of D2-40 in LECs.</p> <p>Methods</p> <p>Surgical wedge biopsy specimens were obtained from non-cirrhotic portions of human livers (normal control) and from cirrhotic livers (LC) (Child A-LC and Child C-LC). Immunohistochemical (IHC), Western blot, and immunoelectron microscopic studies were conducted using D2-40 as markers for lymphatic vessels, as well as CD34 for capillary blood vessels.</p> <p>Results</p> <p>Imunostaining of D2-40 produced a strong reaction in lymphatic vessels only, especially in Child C-LC. It was possible to distinguish the portal venules from the small lymphatic vessels using D-40. Immunoelectron microscopy revealed strong D2-40 expression along the luminal and abluminal portions of the cell membrane of LECs in Child C-LC tissue.</p> <p>Conclusion</p> <p>It is possible to distinguish portal venules from small lymphatic vessels using D2-40 as marker. D2-40- labeling in lymphatic capillary endothelial cells is related to the degree of fibrosis in cirrhotic liver.</p

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