TY - JOUR A1 - Monavari, M. A1 - Medhekar, R. A1 - Nawaz, Q. A1 - Monavari, Mehran A1 - Fuentes‐Chandía, M. A1 - Homaeigohar, S. A1 - Boccaccini, A. R. T1 - A 3D printed bone tissue engineering scaffold composed of alginate dialdehyde-gelatine reinforced by lysozyme loaded cerium doped mesoporous silica-calcia nanoparticles N2 - A novel biomaterial comprising alginate dialdehyde-gelatine (ADA-GEL) hydrogel augmented by lysozyme loaded mesoporous cerium doped silica-calcia nanoparticles (Lys-Ce-MSNs) is 3D printed to create bioactive scaffolds. Lys-Ce-MSNs raise the mechanical stiffness of the hydrogel composite scaffold and induce surface apatite mineralization, when the scaffold is immersed in simulated body fluid (SBF). Moreover, the scaffolds can co-deliver bone healing (Ca and Si) and antioxidant ions (Ce), and Lys to achieve antibacterial (and potentially anticancer) properties. The nanocomposite hydrogel scaffolds can hold and deliver Lys steadily. Based on the in vitro results, the hydrogel nanocomposite containing Lys assured improved pre-osteoblast cell (MC3T3-E1) proliferation, adhesion, and differentiation, thanks to the biocompatibility of ADA-GEL, bioactivity of Ce-MSNs, and the stabilizing effect of Lys on the scaffold structure. On the other hand, the proliferation level of MG63 osteosarcoma cells decreased, likely due to the effect of Lys. Last but not least, cooperatively, alongside gentamicin (GEN), Lys brought about a proper antibacterial efficiency to the hydrogel nanocomposite scaffold against gram-positive and gram-negative bacteria. Taken together, ADA-GEL/Lys-Ce-MSN nanocomposite holds great promise for 3D printing of multifunctional hydrogel bone tissue engineering (BTE) scaffolds, able to induce bone regeneration, address infection, and potentially inhibit tumor formation and growth. KW - Materials chemistry KW - Polymers and plastics KW - Biomaterials KW - Bioengineering KW - Biotechnology KW - 3D printing KW - Bone tissue engineering KW - Drug delivery KW - Lysozyme KW - Mesoporous SiO2-CaO nanoparticles PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-581238 DO - https://doi.org/10.1002/mabi.202200113 SN - 1616-5195 VL - 22 IS - 9 SP - 1 EP - 15 PB - Wiley-VCH CY - Weinheim AN - OPUS4-58123 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Monavari, Mahshid A1 - Homaeigohar, Shahin A1 - Medhekar, Rucha A1 - Nawaz, Qaisar A1 - Monavari, Mehran A1 - Zheng, Kai A1 - Boccaccini, Aldo R. T1 - A 3D-Printed Wound-Healing Material Composed of Alginate Dialdehyde–Gelatin Incorporating Astaxanthin and Borate Bioactive Glass Microparticles N2 - In this study, a wound dressing composed of an alginate dialdehyde−gelatin (ADA-GEL) hydrogel incorporated by astaxanthin (ASX) and 70B (70:30 B2O3/CaO in mol %) borate bioactive glass (BBG) microparticles was developed through 3D printing. ASX and BBG particles sti.ened the composite hydrogel construct and delayed its in vitro degradation compared to the pristine hydrogel construct, mainly due to their cross-linking role, likely arising from hydrogen bonding between the ASX/BBG particles and ADA-GEL chains. Additionally, the composite hydrogel construct could hold and deliver ASX steadily. The composite hydrogel constructs codelivered biologically active ions (Ca and B) and ASX, which should lead to a faster, more e.ective wound-healing process. As shown through in vitro tests, the ASX-containing composite hydrogel promoted fibroblast (NIH 3T3) cell adhesion, proliferation, and vascular endothelial growth factor expression, as well as keratinocyte (HaCaT) migration, thanks to the antioxidant activity of ASX, the release of cell-supportive Ca2+ and B3+ ions, and the biocompatibility of ADA-GEL. Taken together, the results show that the ADA-GEL/BBG/ASX composite is an attractive biomaterial to develop multipurposed wound-healing constructs through 3D printing. KW - General Materials Science PY - 2023 DO - https://doi.org/10.1021/acsami.2c23252 SP - 1 EP - 12 PB - American Chemical Society (ACS) AN - OPUS4-58548 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Monavari, M. A1 - Homaeigohar, S. A1 - Fuentes-Chandía, M. A1 - Nawaz, Q. A1 - Monavari, Mehran A1 - Venkatraman, A. A1 - Boccaccini, A. T1 - 3D printing of alginate dialdehyde-gelatin (ADA-GEL) hydrogels incorporating phytotherapeutic icariin loaded mesoporous SiO2-CaO nanoparticles for bone tissue engineering N2 - 3D printing enables a better control over the microstructure of bone restoring constructs, addresses the challenges seen in the preparation of patient-specific bone scaffolds, and overcomes the bottlenecks that can appear in delivering drugs/growth factors promoting bone regeneration. Here, 3D printing is employed for the fabrication of an osteogenic construct made of hydrogel nanocomposites. Alginate dialdehyde-gelatin (ADA-GEL) hydrogel is reinforced by the incorporation of bioactive glass nanoparticles, i.e. mesoporous silica-calcia nanoparticles (MSNs), in two types of drug (icariin) loading. The composites hydrogel is printed as superhydrated composite constructs in a grid structure. The MSNs not only improve the mechanical stiffness of the constructs but also induce formation of an apatite layer when the construct is immersed in simulated body fluid (SBF), thereby promoting cell adhesion and proliferation. The nanocomposite constructs can hold and deliver icariin efficiently, regardless of its incorporation mode, either as loaded into the MSNs or freely distributed within the hydrogel. Biocompatibility tests showed that the hydrogel nanocomposites assure enhanced osteoblast proliferation, adhesion, and differentiation. Such optimum biological properties stem from the superior biocompatibility of ADA-GEL, the bioactivity of the MSNs, and the supportive effect of icariin in relation to cell Proliferation and differentiation. Taken together, given the achieved structural and biological properties and effective drug delivery capability, the hydrogel nanocomposites show promising potential for bone tissue engineering. KW - 3D printed hydrogel KW - ADA-GEL KW - Drug delivery KW - Mesoporous SiO2-CaO nanoparticles KW - Bone tissue engineering PY - 2021 DO - https://doi.org/10.1016/j.msec.2021.112470 VL - 131 SP - 1 EP - 11 PB - Elsevier B.V. AN - OPUS4-53848 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Gleim, Tobias A1 - Monavari, Mehran A1 - Bertovic, Marija A1 - Wille, Frank T1 - AI-driven Documentation Analysis for Safety Assessment of Packages with Hazardous Goods N2 - Transport packages for radioactive material require, dependent on type und quantity of the radioactive material, a regulatory approval. Safety assessments shall be conducted in compliance with the IAEA regulations and documented in a comprehensive package design safety report to obtain approval from authority. This comprehensive safety report evaluates a broad range of requirements from the regulations, including physical specifications, control measures, and testing assessments. Additionally, it encompasses supporting documents such as specifications, plans in a variety of complex documents. Safety and manufacturing reports contain multiple interconnected sub-reports covering various topics. Changes, such as component modifications, material property updates, standards, or regulatory revisions, often impact multiple sections of the safety analysis reports, making even minor adjustments complex and time-consuming. Each transport package has unique constraints, making every safety report distinct, despite following the same regulatory framework. This project aims to enhance data analysis and processing through AI-based approaches [4]. Automated methods for analysing and interlinking documentation will improve efficiency, accuracy, and consistency while reducing human error in safety assessments. A key challenge is that pre-trained Large Language Models (LLMs) lack domain-specific data on packaging safety, potentially leading to inaccurate results. To mitigate this, the project applies Retrieval-Augmented Generation (RAG) in conjunction with LLMs. This approach integrates the strengths of pre-trained models with expert knowledge from databases and document repositories, ensuring accurate, well-founded, and transparent assessments. Beyond technical challenges, human factors must be considered early. New technologies often trigger resistance, if not introduced properly. Furthermore, long-term AI-reliance may lead to loss of expertise needed to solve complex problems. User-centred approach ensures effective implementation and lasting viability. This study evaluates the feasibility of using LLMs [2] and RAG [1, 3] for regulatory compliance in radioactive material transport. By analysing current documentation workflows, we assess how AI-driven tools can interpret complex safety reports and identify critical dependencies. Furthermore, we highlight the necessity of robust data governance, confidentiality measures, and AI reliability in this highly regulated domain. T2 - KONTEC 2025 CY - Dresden, Germany DA - 17.09.2025 KW - AI-driven KW - QI-Digital KW - Retrieval-Augmented Generation KW - Large Language Model PY - 2025 SP - 1 EP - 9 PB - Kontec Gesellschaft für technische Kommunikation GmbH CY - Dresden AN - OPUS4-64154 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Nourinejhad Zarghani, Shaheen A1 - Ehlers, Jens A1 - Monavari, Mehran A1 - von Bargen, Susanne A1 - Hamacher, Joachim A1 - Büttner, Carmen A1 - Bandte, Martina T1 - Applicability of Different Methods for Quantifying Virucidal Efficacy Using MENNO Florades and Tomato Brown Rugose Fruit Virus as an Example N2 - After entry of a quarantine/regulated pathogen, infected plants shall be destroyed, and the cultivated area (e.g., greenhouse) shall be disinfected. Therefore, the selection of an effective disinfectant plays an important role. With the availability of different methods for virus quantification, we investigated the application of quantitative ELISA (qELISA), RT-qPCR (reverse transcription-quantitative polymerase chain reaction), and bioassays for the quantification of disinfectant efficacy. Therefore, we estimated the titer reduction in tomato brown rugose fruit virus (ToBRFV), a regulated pathogen, in plant sap and on germ carriers after treatment with MENNO Florades 4% for 16 h. The virus load before and after the treatment was measured with the mentioned methods. The RT-qPCR and qELISA methods showed very low efficacy in the presence of the disinfectant. Although bioassays are time-consuming, need purified particles for establishing the quantification models, and are less sensitive than RT-qPCR, they were able to quantify the differences in virus titer in the presence/absence of disinfectant. Interestingly, the bioassays reached at least the lower limit sensitivity of a qELISA. By being less sensitive to the presence of the disinfectant, bioassays proved to be the only technique for the determination of the disinfectant efficacy against ToBRFV on different germ carriers as well as on virus-infected plant sap. KW - Plant Science KW - Ecology KW - Evolution KW - Behavior and Systematics PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-585497 DO - https://doi.org/10.3390/plants12040894 VL - 12 IS - 4 SP - 1 EP - 18 PB - MDPI AG AN - OPUS4-58549 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Nourinejhad Zarghani, Shaheen A1 - Monavari, Mehran A1 - Ehlers, Jens A1 - Hamacher, Joachim A1 - Büttner, Carmen A1 - Bandte, Martina T1 - Comparison of Models for Quantification of Tomato Brown Rugose Fruit Virus Based on a Bioassay Using a Local Lesion Host N2 - Considering the availability of serological and molecular biological methods, the bioassay has been paled into insignificance, although it is the only experimental method that can be used to demonstrate the infectivity of a virus. We compared goodness-of-fit and predictability power of five models for the quantification of tomato brown rugose fruit virus (ToBRFV) based on local lesion assays: the Kleczkowski model, Furumoto and Mickey models I and II, the Gokhale and Bald model (growth curve model), and the modified Poisson model. For this purpose, mechanical inoculations onto Nicotiana tabacum L. cv. Xanthi nc and N. glutionosa L. with defined virus concentrations were first performed with half-leaf randomization in a Latin square design. Subsequently, models were implemented using Python software and fitted to the number of local lesions. All models could fit to the data for quantifying ToBRFV based on local lesions, among which the modified Poisson model had the best prediction of virus concentration in spike samples based on local lesions, although data of individual indicator plants showed variations. More accurate modeling was obtained from the test plant N. glutinosa than from N. tabacum cv. Xanthi nc. The position of the half-leaves on the test plants had no significant effect on the number of local lesions. KW - Plant Science KW - Ecology KW - Evolution KW - Behavior and Systematics PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-585506 DO - https://doi.org/10.3390/plants11243443 VL - 11 IS - 24 SP - 1 EP - 16 PB - MDPI AN - OPUS4-58550 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Nourinejhad Zarghani, S. A1 - Monavari, Mehran A1 - Nourinejhad Zarghani, A. A1 - Nouri, S. A1 - Ehlers, J. A1 - Hamacher, J. A1 - Bandte, M. A1 - Büttner, C. T1 - Quantifying plant viruses: Evolution from bioassay to infectivity dilution curves along the model of tobamoviruses N2 - This review describes the development of the bioassay as a means of quantifying plant viruses, with particular attention to tobamovirus. It delves into various models used to establish a correlation between virus particle concentration and the number of induced local lesions (the infectivity dilution curve), including the Poisson, Furumoto and Mickey, Kleczkowski, Growth curve, and modified Poisson models. The parameters of each model are described, and their application or performance in the context of the tobacco mosaic virus is explored. This overview highlights the enduring value of the infectivity dilution curve in tobamovirus quantification, providing valuable insights for researchers or practitioners of bioassays and theoreticians of modeling. KW - Local lesion KW - qRT-PCR KW - Nicotiana KW - ToBRFV KW - TMV KW - CGMMV KW - Disinfection KW - Modeling PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-630142 DO - https://doi.org/10.3390/v16030440 SN - 1999-4915 VL - 16 IS - 3 SP - 1 EP - 14 PB - MDPI CY - Basel AN - OPUS4-63014 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Monavari, Mehran A1 - Albakri, Bashar T1 - Retrieval-Augmented Generation (RAG) for Digitalization of Quality Infrastructure Assets. Use case: Digital Reference Material Documents N2 - This poster presents a novel approach to digitalizing quality infrastructure (QI) assets using Retrieval-Augmented Generation (RAG). QI assets, such as standards, certificates, and product passports, are typically available only in human-readable formats like PDFs. Converting these documents into machine-readable formats (e.g., XML) is labor-intensive, requiring the definition of ontologies and manual data entry. The proposed method leverages RAG, an advanced technique combining information retrieval and text generation, to automate this process. Specifically, the approach involves: * Retrieval Model: Extracting relevant text chunks from large document collections based on semantic similarity. * Generation Model: Generating machine-readable formats (e.g., XML) from the retrieved text using predefined ontologies. The poster demonstrates this method by converting BAM Certificates of Reference Materials into a Digital Reference Material Document (DRMD) schema. Future work aims to further automate ontology creation using machine learning and large language models (LLMs), reducing manual effort and accelerating the generation of digital assets essential for Q-X Dataspace and machine-readability. N2 - In diesem Poster wird ein neuartiger Ansatz zur Digitalisierung von Qualitätsinfrastrukturen (QI) unter Verwendung der Retrieval-Augmented Generation (RAG) vorgestellt. QI-Assets, wie z.B. Normen, Zertifikate und Produktpässe, sind in der Regel nur in menschenlesbaren Formaten wie PDFs verfügbar. Die Konvertierung dieser Dokumente in maschinenlesbare Formate (z. B. XML) ist arbeitsintensiv und erfordert die Definition von Ontologien und die manuelle Dateneingabe. Die vorgeschlagene Methode nutzt RAG, eine fortschrittliche Technik, die Information Retrieval und Textgenerierung kombiniert, um diesen Prozess zu automatisieren. Der Ansatz umfasst im Einzelnen: * Retrieval-Modell: Extraktion relevanter Textabschnitte aus großen Dokumentensammlungen auf der Grundlage semantischer Ähnlichkeit. * Generierungsmodell: Generierung maschinenlesbarer Formate (z.B. XML) aus dem abgerufenen Text unter Verwendung vordefinierter Ontologien. Das Poster demonstriert diese Methode anhand der Konvertierung von BAM-Zertifikaten für Referenzmaterialien in ein Schema für digitale Referenzmaterialdokumente (DRMD). Zukünftige Arbeiten zielen darauf ab, die Ontologieerstellung mit Hilfe von maschinellem Lernen und großen Sprachmodellen (LLMs) weiter zu automatisieren, um den manuellen Aufwand zu reduzieren und die Generierung digitaler Assets zu beschleunigen, die für den Q-X Datenraum und Maschinenlesbarkeit unerlässlich sind. T2 - QI-Digital Forum 2024 CY - Berlin, Germany DA - 09.10.2024 KW - Digitalization KW - Quality Infrastructure KW - Retrieval-Augmented Generation KW - Digitalisierung KW - Qualtitätsinfrastruktur KW - Large Language Models KW - XML PY - 2024 AN - OPUS4-61733 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Monavari, Mehran A1 - Prellwitz, Matthias A1 - Muth, Thilo A1 - Eichstädt, Sascha A1 - Koch, Claudia T1 - Quality-X: A Federated Digital Ecosystem for the Future Quality Infrastructure N2 - Harmonized and interoperable national Quality Infrastructure (QI) systems are essential for fostering cooperation, promoting mutual trust, and facilitating trade. The true potential of the QI is realized when its elements and actors are seamlessly integrated into a cohesive digital QI ecosystem. Recent developments towards industrial international data spaces enable such an ecosystem but require the integration of QI principles. Recognizing the lack of such a platform, Quality-X aims at setting the stage for the implementation of a QI ecosystem in international data spaces (IDS), GAIA-X and related German and European projects dedicated to secure data sharing. Quality-X is not about the construction of a platform; it is the creation of an inclusive QI ecosystem with harmonized interfaces. Instead of imposing rigid data structures, it prioritizes interoperability. Through the utilization of Decentralized Identifiers (DIDs), Verifiable Credentials, and Identity Hubs, Quality-X seeks seamless interactions across diverse service provider systems. This white paper introduces the concept and vision of Quality-X and discusses the general prerequisites for integrating QI processes within data spaces. Further on, we introduce existing testbeds, which will serve as an experimental proving ground for exploring various use cases related to the implementation of the vision of a QI-Digital. +++ Harmonisierte und interoperable nationale Qualitätsinfrastrukturen (QI) sind für die Förderung der Zusammenarbeit, des gegenseitigen Vertrauens und der Erleichterung des Handels unerlässlich. Das wahre Potenzial der QI kommt zum Tragen, wenn ihre Elemente und Akteure nahtlos in ein kohärentes digitales QI-Ökosystem integriert werden. Die jüngsten Entwicklungen hin zu industriellen internationalen Datenräumen ermöglichen ein solches Ökosystem, erfordern jedoch die Integration von QI-Prinzipien. Angesichts des Fehlens einer solchen Plattform zielt Quality-X darauf ab, die Voraussetzungen für die Umsetzung eines QI-Ökosystems in internationalen Datenräumen (IDS), GAIA-X und verwandten deutschen und europäischen Projekten zum sicheren Datenaustausch zu schaffen. Bei Quality-X geht es nicht um den Aufbau einer Plattform, sondern um die Schaffung eines umfassenden QI-Ökosystems mit harmonisierten Schnittstellen. Anstatt starre Datenstrukturen aufzuerlegen, steht die Interoperabilität im Vordergrund. Durch die Verwendung von dezentralen Identifikatoren (DIDs), überprüfbaren Berechtigungsnachweisen und Identitäts-Hubs strebt Quality-X eine nahtlose Interaktion zwischen verschiedenen Systemen von Dienstleistern an. Dieses Whitepaper stellt das Konzept und die Vision von Quality-X vor und erörtert die allgemeinen Voraussetzungen für die Integration von QI-Prozessen in Datenräumen. Darüber hinaus stellen wir bestehende Testbeds vor, die als experimentelles Versuchsfeld für die Erforschung verschiedener Anwendungsfälle im Zusammenhang mit der Umsetzung der Vision einer QI-Digital dienen sollen. KW - Quality Assurance KW - Quality Infrastructure KW - Data Spaces KW - Digitalization KW - Quality Management KW - Interoperability KW - Verification KW - Identification KW - Certificate KW - Datenräume KW - Qualitätsinfrastruktur KW - Gaia-X KW - Manufacturing-X KW - Catena-X KW - Datenökosystem KW - Qualitätssicherung KW - Qualitätsmanagement PY - 2023 UR - https://www.qi-digital.de/fileadmin/user_upload/website/publikationen/1022_Brosch%C3%BCre_Quality-X_v4.pdf SP - 1 CY - Berlin AN - OPUS4-59354 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Monavari, Mehran A1 - Prellwitz, Matthias A1 - Koch, Claudia A1 - van de Kreeke, Johannes A1 - Melzer, Michael A1 - Richter, Silke T1 - The Digital Reference Material Document: From Paper Certificates to Interoperable Data Objects in Digital Quality Infrastructure N2 - Reference materials (RMs) are essential for traceable and reliable measurements in science and industry, yet their certificate/document remain largely paper-based. The Digital Reference Material Document (DRMD) project at BAM introduces a transformative approach by converting traditional RM certificates/documents into machine-interpretable, XML-based digital assets. Building on the Digital Calibration Certificate framework, DRMDs encode ISO 33401 requirements and integrate semantic standards like D-SI and material identifiers. These digital documents support automated data exchange, integration into laboratory systems, and interoperability e.g. via asset administration shells and data spaces. The paper presents the DRMD schema concept, and outlines the path toward international harmonization and large-scale deployment, positioning DRMDs as a cornerstone of a digital quality infrastructure. T2 - IMEKO TC-6 International Conference on Metrology and Digital Transformation - M4DConf 2025 DA - 03.09.2025 KW - Digital Reference Material Document KW - Quality Infrastructure KW - Reference Material Certificate KW - DRMD PY - 2025 UR - https://www.m4dconf.org/ UR - https://www.sciencedirect.com/journal/measurement-digitalization SP - 1 EP - 6 AN - OPUS4-64269 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -