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The physicochemical properties of synthetically produced bone substitute materials (BSM) have a major impact on biocompatibility. This affects bony tissue integration, osteoconduction, as well as the degradation pattern and the correlated inflammatory tissue responses including macrophages and multinucleated giant cells (MNGCs). Thus, influencing factors such as size, special surface morphologies, porosity, and interconnectivity have been the subject of extensive research. In the present publication, the influence of the granule size of three identically manufactured bone substitute granules based on the technology of hydroxyapatite (HA)-forming calcium phosphate cements were investigated, which includes the inflammatory response in the surrounding tissue and especially the induction of MNGCs (as a parameter of the material degradation). For the in vivo study, granules of three different size ranges (small = 0.355–0.5 mm; medium = 0.5–1 mm; big = 1–2 mm) were implanted in the subcutaneous connective tissue of 45 male BALB/c mice. At 10, 30, and 60 days post implantationem, the materials were explanted and histologically processed. The defect areas were initially examined histopathologically. Furthermore, pro- and anti-inflammatory macrophages were quantified histomorphometrically after their immunohistochemical detection. The number of MNGCs was quantified as well using a histomorphometrical approach. The results showed a granule size-dependent integration behavior. The surrounding granulation tissue has passivated in the groups of the two bigger granules at 60 days post implantationem including a fibrotic encapsulation, while a granulation tissue was still present in the group of the small granules indicating an ongoing cell-based degradation process. The histomorphometrical analysis showed that the number of proinflammatory macrophages was significantly increased in the small granules at 60 days post implantationem. Similarly, a significant increase of MNGCs was detected in this group at 30 and 60 days post implantationem. Based on these data, it can be concluded that the integration and/or degradation behavior of synthetic bone substitutes can be influenced by granule size.
Implementation of product-service systems (PSS) requires structural changes in the way that business in manufacturing industries is traditionally conducted. Literature frequently mentions the importance of human resource management (HRM), since people are involved in the entire process of PSS development and employees are the primary link to customers. However, to this day, no study has provided empirical evidence whether and in what way HRM of firms that implement PSS differs from HRM of firms that solely run a traditional manufacturing based business model. The aim of this study is to contribute to closing this gap by investigating the particular HR components of manufacturing firms that implement PSS and compare it with the HRM of firms that do not. The context of this study is the fashion industry, which is an ideal setting since it is a mature and highly competitive industry that is well-documented for causing significant environmental impact. PSS present a promising opportunity for fashion firms to differentiate and mitigate the industry’s ecological footprint. Analysis of variance (ANOVA) was conducted to analyze data of 102 international fashion firms. Findings reveal a significant higher focus on nearly the entire spectrum of HRM components of firms that implement PSS compared with firms that do not. Empirical findings and their interpretation are utilized to propose a general framework of the role of HRM for PSS implementation. This serves as a departure point for both scholars and practitioners for further research, and fosters the understanding of the role of HRM for managing PSS implementation.
Hyperspectral imaging and reflectance spectroscopy in the range from 200–380 nm were used to rapidly detect and characterize copper oxidation states and their layer thicknesses on direct bonded copper in a non-destructive way. Single-point UV reflectance spectroscopy, as a well-established method, was utilized to compare the quality of the hyperspectral imaging results. For the laterally resolved measurements of the copper surfaces an UV hyperspectral imaging setup based on a pushbroom imager was used. Six different types of direct bonded copper were studied. Each type had a different oxide layer thickness and was analyzed by depth profiling using X-ray photoelectron spectroscopy. In total, 28 samples were measured to develop multivariate models to characterize and predict the oxide layer thicknesses. The principal component analysis models (PCA) enabled a general differentiation between the sample types on the first two PCs with 100.0% and 96% explained variance for UV spectroscopy and hyperspectral imaging, respectively. Partial least squares regression (PLS-R) models showed reliable performance with R2c = 0.94 and 0.94 and RMSEC = 1.64 nm and 1.76 nm, respectively. The developed in-line prototype system combined with multivariate data modeling shows high potential for further development of this technique towards real large-scale processes.
UV hyperspectral imaging (225 nm–410 nm) was used to identify and quantify the honey- dew content of real cotton samples. Honeydew contamination causes losses of millions of dollars annually. This study presents the implementation and application of UV hyperspectral imaging as a non-destructive, high-resolution, and fast imaging modality. For this novel approach, a reference sample set, which consists of sugar and protein solutions that were adapted to honeydew, was set-up. In total, 21 samples with different amounts of added sugars/proteins were measured to calculate multivariate models at each pixel of a hyperspectral image to predict and classify the amount of sugar and honeydew. The principal component analysis models (PCA) enabled a general differentiation between different concentrations of sugar and honeydew. A partial least squares regression (PLS-R) model was built based on the cotton samples soaked in different sugar and protein concentrations. The result showed a reliable performance with R2cv = 0.80 and low RMSECV = 0.01 g for the valida- tion. The PLS-R reference model was able to predict the honeydew content laterally resolved in grams on real cotton samples for each pixel with light, strong, and very strong honeydew contaminations. Therefore, inline UV hyperspectral imaging combined with chemometric models can be an effective tool in the future for the quality control of industrial processing of cotton fibers.
Due to its wide-ranging endocrine functions, adipose tissue influences the whole body’s metabolism. Engineering long-term stable and functional human adipose tissue is still challenging due to the limited availability of suitable biomaterials and adequate cell maturation. We used gellan gum (GG) to create manual and bioprinted adipose tissue models because of its similarities to the native extracellular matrix and its easily tunable properties. Gellan gum itself was neither toxic nor monocyte activating. The resulting hydrogels exhibited suitable viscoelastic properties for soft tissues and were stable for 98 days in vitro. Encapsulated human primary adipose-derived stem cells (ASCs) were adipogenically differentiated for 14 days and matured for an additional 84 days. Live-dead staining showed that encapsulated cells stayed viable until day 98, while intracellular lipid staining showed an increase over time and a differentiation rate of 76% between days 28 and 56. After 4 weeks of culture, adipocytes had a univacuolar morphology, expressed perilipin A, and secreted up to 73% more leptin. After bioprinting establishment, we demonstrated that the cells in printed hydrogels had high cell viability and exhibited an adipogenic phenotype and function. In summary, GG-based adipose tissue models show long-term stability and allow ASCs maturation into functional, univacuolar adipocytes.
Adipose tissue is related to the development and manifestation of multiple diseases, demonstrating the importance of suitable in vitro models for research purposes. In this study, adipose tissue lobuli were explanted, cultured, and used as an adipose tissue control to evaluate in vitro generated adipose tissue models. During culture, lobule exhibited a stable weight, lactate dehydrogenase, and glycerol release over 15 days. For building up in vitro adipose tissue models, we adapted the biomaterial gelatin methacryloyl (GelMA) composition and handling to homogeneously mix and bioprint human primary mature adipocytes (MA) and adipose-derived stem cells (ASCs), respectively. Accelerated cooling of the bioink turned out to be essential for the homogeneous distribution of lipid-filled MAs in the hydrogel. Last, we compared manual and bioprinted GelMA hydrogels with MA or ASCs and the explanted lobules to evaluate the impact of the printing process and rate the models concerning the physiological reference. The viability analyses demonstrated no significant difference between the groups due to additive manufacturing. The staining of intracellular lipids and perilipin A suggest that GelMA is well suited for ASCs and MA. Therefore, we successfully constructed physiological in vitro models by bioprinting MA-containing GelMA bioinks.
The chemical recycling of used motor oil via catalytic cracking to convert it into secondary diesel-like fuels is a sustainable and technically attractive solution for managing environmental concerns associated with traditional disposal. In this context, this study was conducted to screen basic and acidic-aluminum silicate catalysts doped with different metals, including Mg, Zn, Cu, and Ni. The catalysts were thoroughly characterized using various techniques such as N2 adsorption–desorption isotherms, FT-IR spectroscopy, and TG analysis. The liquid and gaseous products were identified using GC, and their characteristics were compared with acceptable ranges from ASTM characterization methods for diesel fuel. The results showed that metal doping improved the performance of the catalysts, resulting in higher conversion rates of up to 65%, compared to thermal (15%) and aluminum silicates (≈20%). Among all catalysts, basic aluminum silicates doped with Ni showed the best catalytic performance, with conversions and yields three times higher than aluminum silicate catalysts. These findings significantly contribute to developing efficient and eco-friendly processes for the chemical recycling of used motor oil. This study highlights the potential of basic aluminum silicates doped with Ni as a promising catalyst for catalytic cracking and encourages further research in this area.
The present publication reports the purification effort of two natural bone blocks, that is, an allogeneic bone block (maxgraft®, botiss biomaterials GmbH, Zossen, Germany) and a xenogeneic block (SMARTBONE®, IBI S.A., Mezzovico Vira, Switzerland) in addition to previously published results based on histology. Furthermore, specialized scanning electron microscopy (SEM) and in vitro analyses (XTT, BrdU, LDH) for testing of the cytocompatibility based on ISO 10993-5/-12 have been conducted. The microscopic analyses showed that both bone blocks possess a trabecular structure with a lamellar subarrangement. In the case of the xenogeneic bone block, only minor remnants of collagenous structures were found, while in contrast high amounts of collagen were found associated with the allogeneic bone matrix. Furthermore, only island-like remnants of the polymer coating in case of the xenogeneic bone substitute seemed to be detectable. Finally, no remaining cells or cellular remnants were found in both bone blocks. The in vitro analyses showed that both bone blocks are biocompatible. Altogether, the purification level of both bone blocks seems to be favorable for bone tissue regeneration without the risk for inflammatory responses or graft rejection. Moreover, the analysis of the maxgraft® bone block showed that the underlying purification process allows for preserving not only the calcified bone matrix but also high amounts of the intertrabecular collagen matrix.
Introduction: Bioresorbable collagenous barrier membranes are used to prevent premature soft tissue ingrowth and to allow bone regeneration. For volume stable indications, only non-absorbable synthetic materials are available. This study investigates a new bioresorbable hydrofluoric acid (HF)-treated magnesium (Mg) mesh in a native collagen membrane for volume stable situations. Materials and Methods: HF-treated and untreated Mg were compared in direct and indirect cytocompatibility assays. In vivo, 18 New Zealand White Rabbits received each four 8 mm calvarial defects and were divided into four groups: (a) HF-treated Mg mesh/collagen membrane, (b) untreated Mg mesh/collagen membrane (c) collagen membrane and (d) sham operation. After 6, 12 and 18 weeks, Mg degradation and bone regeneration was measured using radiological and histological methods. Results: In vitro, HF-treated Mg showed higher cytocompatibility. Histopathologically, HF-Mg prevented gas cavities and was degraded by mononuclear cells via phagocytosis up to 12 weeks. Untreated Mg showed partially significant more gas cavities and a fibrous tissue reaction. Bone regeneration was not significantly different between all groups. Discussion and Conclusions: HF-Mg meshes embedded in native collagen membranes represent a volume stable and biocompatible alternative to the non-absorbable synthetic materials. HF-Mg shows less corrosion and is degraded by phagocytosis. However, the application of membranes did not result in higher bone regeneration.
Salivary gland tumors (SGTs) are a relevant, highly diverse subgroup of head and neck tumors whose entity determination can be difficult. Confocal Raman imaging in combination with multivariate data analysis may possibly support their correct classification. For the analysis of the translational potential of Raman imaging in SGT determination, a multi-stage evaluation process is necessary. By measuring a sample set of Warthin tumor, pleomorphic adenoma and non-tumor salivary gland tissue, Raman data were obtained and a thorough Raman band analysis was performed. This evaluation revealed highly overlapping Raman patterns with only minor spectral differences. Consequently, a principal component analysis (PCA) was calculated and further combined with a discriminant analysis (DA) to enable the best possible distinction. The PCA-DA model was characterized by accuracy, sensitivity, selectivity and precision values above 90% and validated by predicting model-unknown Raman spectra, of which 93% were classified correctly. Thus, we state our PCA-DA to be suitable for parotid tumor and non-salivary salivary gland tissue discrimination and prediction. For evaluation of the translational potential, further validation steps are necessary.
This article studies the effects of reverse factoring in a supply chain when the buyer company facilitates its lower short-term borrowing rates to the supplier corporation in return for extended payment terms. We explore the role of interest rate changes, rating changes, and the business cycle position on the cost and benefit trade-off from a supplier perspective. We utilize a combined empirical approach consisting of an event study in Step 1 and a simulation model in Step 2. The event study identifies the quantitative magnitude of central bank decisions and rating changes on the interest rate differential. The simulation computes with a rolling-window methodology the daily cost and benefits of reverse factoring from 2010 to 2018 under the assumption of the efficient market hypothesis. Our major finding is that changes of crucial financial variables such as interest rates, ratings, or news alerts will turn former win-win into win-lose situations for the supplier contingent to the business cycle. Overall, our results exhibit sophisticated trade-offs under reverse factoring and consequently require a careful evaluation in managerial decisions.
Sleep is extremely important for physical and mental health. Although polysomnography is an established approach in sleep analysis, it is quite intrusive and expensive. Consequently, developing a non-invasive and non-intrusive home sleep monitoring system with minimal influence on patients, that can reliably and accurately measure cardiorespiratory parameters, is of great interest. The aim of this study is to validate a non-invasive and unobtrusive cardiorespiratory parameter monitoring system based on an accelerometer sensor. This system includes a special holder to install the system under the bed mattress. The additional aim is to determine the optimum relative system position (in relation to the subject) at which the most accurate and precise values of measured parameters could be achieved. The data were collected from 23 subjects (13 males and 10 females). The obtained ballistocardiogram signal was sequentially processed using a sixth-order Butterworth bandpass filter and a moving average filter. As a result, an average error (compared to reference values) of 2.24 beats per minute for heart rate and 1.52 breaths per minute for respiratory rate was achieved, regardless of the subject’s sleep position. For males and females, the errors were 2.28 bpm and 2.19 bpm for heart rate and 1.41 rpm and 1.30 rpm for respiratory rate. We determined that placing the sensor and system at chest level is the preferred configuration for cardiorespiratory measurement. Further studies of the system’s performance in larger groups of subjects are required, despite the promising results of the current tests in healthy subjects.
Sleep is essential to physical and mental health. However, the traditional approach to sleep analysis—polysomnography (PSG)—is intrusive and expensive. Therefore, there is great interest in the development of non-contact, non-invasive, and non-intrusive sleep monitoring systems and technologies that can reliably and accurately measure cardiorespiratory parameters with minimal impact on the patient. This has led to the development of other relevant approaches, which are characterised, for example, by the fact that they allow greater freedom of movement and do not require direct contact with the body, i.e., they are non-contact. This systematic review discusses the relevant methods and technologies for non-contact monitoring of cardiorespiratory activity during sleep. Taking into account the current state of the art in non-intrusive technologies, we can identify the methods of non-intrusive monitoring of cardiac and respiratory activity, the technologies and types of sensors used, and the possible physiological parameters available for analysis. To do this, we conducted a literature review and summarised current research on the use of non-contact technologies for non-intrusive monitoring of cardiac and respiratory activity. The inclusion and exclusion criteria for the selection of publications were established prior to the start of the search. Publications were assessed using one main question and several specific questions. We obtained 3774 unique articles from four literature databases (Web of Science, IEEE Xplore, PubMed, and Scopus) and checked them for relevance, resulting in 54 articles that were analysed in a structured way using terminology. The result was 15 different types of sensors and devices (e.g., radar, temperature sensors, motion sensors, cameras) that can be installed in hospital wards and departments or in the environment. The ability to detect heart rate, respiratory rate, and sleep disorders such as apnoea was among the characteristics examined to investigate the overall effectiveness of the systems and technologies considered for cardiorespiratory monitoring. In addition, the advantages and disadvantages of the considered systems and technologies were identified by answering the identified research questions. The results obtained allow us to determine the current trends and the vector of development of medical technologies in sleep medicine for future researchers and research.
In order to decouple economic growth from global material consumption it is necessary to implement material efficiency strategies at the level of single enterprises and their supply chains, and to implement circular economy aspects. Manufacturing firms face multiple implementation challenges like cost limitations, competition, innovation and stakeholder pressure, and supplier and customer relationships, among others. Taking as an example a case of a medium-sized manufacturing company, opportunities to realise material efficiency improvements within the company borders - on the supply chain and by using circular economy measures - are assessed. Deterministic calculations and simulations, performed for the supply chain of this company, show that measures to increase material efficiency in the supply chain are important. However, they need to be complemented by efforts to return waste and used products to the economic cycle, which requires rethinking the traditional linear economic system.
A laboratory prototype for hyperspectral imaging in ultra-violet (UV) region from 225 to 400 nm was developed and used to rapidly characterize active pharmaceutical ingredients (API) in tablets. The APIs are ibuprofen (IBU), acetylsalicylic acid (ASA) and paracetamol (PAR). Two sample sets were used for a comparison purpose. Sample set one comprises tablets of 100% API and sample set two consists of commercially available painkiller tablets. Reference measurements were performed on the pure APIs in liquid solutions (transmission) and in solid phase (reflection) using a commercial UV spectrometer. The spectroscopic part of the prototype is based on a pushbroom imager that contains a spectrograph and charge-coupled device (CCD) camera. The tablets were scanned on a conveyor belt that is positioned inside a tunnel made of polytetrafluoroethylene (PTFE) in order to increase the homogeneity of illumination at the sample position. Principal component analysis (PCA) was used to differentiate the hyperspectral data of the drug samples. The first two PCs are sufficient to completely separate all samples. The rugged design of the prototype opens new possibilities for further development of this technique towards real large-scale application.
From the perspective of manufacturing companies, the political, media and economic discourse on decarbonisation in the recent years manifests itself as an increasing social expectation of action. In Germany, in particular, this discourse is also being driven forward by powerful companies, respectively sectors, most notably the automotive industry. Against this background, the present paper examines how German manufacturing companies react to rising societal pressure and emerging policies. It examines which measures the companies have taken or plan to take to reduce their carbon footprint, which aspirations are associated with this and the structural characteristics (company size, energy intensity, and sector) by which these are influenced. A mix methods approach is applied, utilising data gathered from approx. 900 companies in context of the Energy Efficiency Index of German Industry (EEI), along with media research focusing on the announced decarbonisation plans and initiatives. We demonstrate that one-size-serves-all approaches are not suitable to decarbonise industry, as the situation and ambitions differ considerably depending on size, energy intensity and sector. Even though the levels of ambition and urgency are high, micro and energy intensive companies, in particular, are challenged. The present research uncovers a series of questions that call for attention to materialise the ambitions and address the challenges outlined.
Globalization has increased the number of road trips and vehicles. The result has been an intensification of traffic accidents, which are becoming one of the most important causes of death worldwide. Traffic accidents are often due to human error, the probability of which increases when the cognitive ability of the driver decreases. Cognitive capacity is closely related to the driver’s mental state, as well as other external factors such as the CO2 concentration inside the vehicle. The objective of this work is to analyze how these elements affect driving. We have conducted an experiment with 50 drivers who have driven for 25 min using a driving simulator. These drivers completed a survey at the start and end of the experiment to obtain information about their mental state. In addition, during the test, their stress level was monitored using biometric sensors and the state of the environment (temperature, humidity and CO2 level) was recorded. The results of the experiment show that the initial level of stress and tiredness of the driver can have a strong impact on stress, driving behavior and fatigue produced by the driving test. Other elements such as sadness and the conditions of the interior of the vehicle also cause impaired driving and affect compliance with traffic regulations.
Highly viscous bioinks offer great advantages for the three-dimensional fabrication of cell-laden constructs by microextrusion printing. However, no standardised method of mixing a high viscosity biomaterial ink and a cell suspension has been established so far, leading to non-reproducible printing results. A novel method for the homogeneous and reproducible mixing of the two components using a mixing unit connecting two syringes is developed and investigated. Several static mixing units, based on established mixing designs, were adapted and their functionality was determined by analysing specific features of the resulting bioink. As a model system, we selected a highly viscous ink consisting of fresh frozen human blood plasma, alginate, and methylcellulose, and a cell suspension containing immortalized human mesenchymal stem cells. This bioink is crosslinked after fabrication. A pre-crosslinked gellan gum-based bioink providing a different extrusion behaviour was introduced to validate the conclusions drawn from the model system. For characterisation, bioink from different zones within the mixing device was analysed by measurement of its viscosity, shape fidelity after printing and visual homogeneity. When taking all three parameters into account, a comprehensive and reliable comparison of the mixing quality was possible. In comparison to the established method of manual mixing inside a beaker using a spatula, a significantly higher proportion of viable cells was detected directly after mixing and plotting for both bioinks when the mixing unit was used. A screw-like mixing unit, termed “HighVisc”, was found to result in a homogenous bioink after a low number of mixing cycles while achieving high cell viability rates.
Appropriate mechanical properties and fast endothelialization of synthetic grafts are key to ensure long-term functionality of implants. We used a newly developed biostable polyurethane elastomer (TPCU) to engineer electrospun vascular scaffolds with promising mechanical properties (E-modulus: 4.8 ± 0.6 MPa, burst pressure: 3326 ± 78 mmHg), which were biofunctionalized with fibronectin (FN) and decorin (DCN). Neither uncoated nor biofunctionalized TPCU scaffolds induced major adverse immune responses except for minor signs of polymorph nuclear cell activation. The in vivo endothelial progenitor cell homing potential of the biofunctionalized scaffolds was simulated in vitro by attracting endothelial colony-forming cells (ECFCs). Although DCN coating did attract ECFCs in combination with FN (FN + DCN), DCN-coated TPCU scaffolds showed a cell-repellent effect in the absence of FN. In a tissue-engineering approach, the electrospun and biofunctionalized tubular grafts were cultured with primary-isolated vascular endothelial cells in a custom-made bioreactor under dynamic conditions with the aim to engineer an advanced therapy medicinal product. Both FN and FN + DCN functionalization supported the formation of a confluent and functional endothelial layer.
Supply chains have evolved into dynamic, interconnected supply networks, which increases the complexity of achieving end-to-end traceability of object flows and their experienced events. With its capability of ensuring a secure, transparent, and immutable environment without relying on a trusted third party, the emerging blockchain technology shows strong potential to enable end-to-end traceability in such complex multitiered supply networks. This paper aims to overcome the limitations of existing blockchain-based traceability architectures regarding their object-related event mapping ability, which involves mapping the creation and deletion of objects, their aggregation and disaggregation, transformation, and transaction, in one holistic architecture. Therefore, this paper proposes a novel ‘blueprint-based’ token concept, which allows clients to group tokens into different types, where tokens of the same type are non-fungible. Furthermore, blueprints can include minting conditions, which, for example, are necessary when mapping assembly processes. In addition, the token concept contains logic for reflecting all conducted object-related events in an integrated token history. Finally, for validation purposes, this article implements the architecture’s components in code and proves its applicability based on the Ethereum blockchain. As a result, the proposed blockchain-based traceability architecture covers all object-related supply chain events and proves its general-purpose end-to-end traceability capabilities of object flows.