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High attrition-rates entailed by drug testing in 2D cell culture and animal models stress the need for improved modeling of human tumor tissues. In previous studies our 3D models on a decellularized tissue matrix have shown better predictivity and higher chemoresistance. A single porcine intestine yields material for 150 3D models of breast, lung, colorectal cancer (CRC) or leukemia. The uniquely preserved structure of the basement membrane enables physiological anchorage of endothelial cells and epithelial-derived carcinoma cells. The matrix provides different niches for cell growth: on top as monolayer, in crypts as aggregates and within deeper layers. Dynamic culture in bioreactors enhances cell growth. Comparing gene expression between 2D and 3D cultures, we observed changes related to proliferation, apoptosis and stemness. For drug target predictions, we utilize tumor-specific sequencing data in our in silico model finding an additive effect of metformin and gefitinib treatment for lung cancer in silico, validated in vitro. To analyze mode-of-action, immune therapies such as trispecific T-cell engagers in leukemia, as well as toxicity on non-cancer cells, the model can be modularly enriched with human endothelial cells (hECs), immune cells and fibroblasts. Upon addition of hECs, transmigration of immune cells through the endothelial barrier can be investigated. In an allogenic CRC model we observe a lower basic apoptosis rate after applying PBMCs in 3D compared to 2D, which offers new options to mirror antigen-specific immunotherapies in vitro. In conclusion, we present modular human 3D tumor models with tissue-like features for preclinical testing to reduce animal experiments.
Hintergrund
Die Fotodokumentation von offenen Frakturen, Wunden, Dekubitalulzera, Tumoren oder Infektionen ist ein wichtiger Bestandteil der digitalen Patientenakte. Bisher ist unklar, welchen Stellenwert diese Fotodokumentation bei der Abrechnungsprüfung durch den Medizinischen Dienst der Krankenkassen (MDK) hat.
Fragestellung
Kann eine Smartphone-basierte Fotodokumentation die Verteidigung von erlösrelevanten Diagnosen und Prozeduren sowie der Verweildauer verbessern?
Material und Methoden
Ausstattung der Mitarbeiter mit digitalen Endgeräten (Smartphone/Tablet) in den Bereichen Notaufnahme, Schockraum, OP, Sprechstunden sowie auf den Stationen. Retrospektive Auswertung der Abrechnungsprüfung im Jahr 2019 und Identifikation aller Fallbesprechungen, in denen die Fotodokumentation eine Erlösveränderung bewirkt hat.
Ergebnisse
Von insgesamt 372 Fallbesprechungen half die Fotodokumentation in 27 Fällen (7,2 %) zur Bestätigung eines Operationen- und Prozedurenschlüssels (OPS) (n = 5; 1,3 %), einer Hauptdiagnose (n = 10; 2,7 %), einer Nebendiagnose (n = 3; 0,8 %) oder der Krankenhausverweildauer (n = 9; 2,4 %). Pro oben genanntem Fall mit Fotodokumentation ergab sich eine durchschnittliche Erlössteigerung von 2119 €. Inklusive Aufwandpauschale für die Verhandlungen wurde somit ein Gesamtbetrag von 65.328 € verteidigt.
Diskussion
Der Einsatz einer Smartphone-basierten Fotodokumentation kann die Qualität der Dokumentation verbessern und Erlöseinbußen bei der Abrechnungsprüfung verhindern. Die Implementierung digitaler Endgeräte mit entsprechender Software ist ein wichtiger Teil des digitalen Strukturwandels in Kliniken.
The identification of biomarker signatures is important for cancer diagnosis and prognosis. However, the detection of clinical reliable signatures is influenced by limited data availability, which may restrict statistical power. Moreover, methods for integration of large sample cohorts and signature identification are limited. We present a step-by-step computational protocol for functional gene expression analysis and the identification of diagnostic and prognostic signatures by combining meta-analysis with machine learning and survival analysis. The novelty of the toolbox lies in its all-in-one functionality, generic design, and modularity. It is exemplified for lung cancer, including a comprehensive evaluation using different validation strategies. However, the protocol is not restricted to specific disease types and can therefore be used by a broad community. The accompanying R package vignette runs in ~1 h and describes the workflow in detail for use by researchers with limited bioinformatics training.
Purpose. Copal\(^®\) spacem is a new PMMA bone cement for fabricating spacers. This study compares elution of gentamicin, elution of vancomycin, and compressive strength of Copal\(^®\) spacem and of Palacos\(^®\) R+G at different vancomycin loadings in the powder of the cements. We hypothesized that antibiotic elution of Copal\(^®\) spacem is superior at comparable compressive strength. Methods. Compression test specimens were fabricated using Copal\(^®\) spacem manually loaded with 0.5 g gentamicin and additionally 2 g, 4 g, and 6 g of vancomycin per 40 g of cement powder (COP specimens) and using 0.5 g gentamicin premixed Palacos\(^®\) R+G manually loaded with 2 g, 4 g, and 6 g of vancomycin per 40 g of cement powder (PAL specimens). These specimens were used for determination of gentamicin and vancomycin elution (in fetal calf serum, at 22°C) and for determination of compressive strength both prior and following the elution tests. Results. Cumulative gentamicin concentrations (p < 0.005) and gentamicin concentration after 28 days (p ≤ 0.043) were significantly lower for COP specimens compared to PAL specimens. Cumulative vancomycin concentrations were significantly higher (p ≤ 0.043) for COP specimens after the second day. Vancomycin concentrations after 28 days were not significantly higher for the Copal specimens loaded with 2 g and 4 g of vancomycin. Compressive strength was not significantly different between COP specimens and PAL specimens before elution tests. Compressive strength after the elution tests was significantly lower (p = 0.005) for COP specimens loaded with 2 g of vancomycin. Conclusion. We could not demonstrate consistent superior antibiotic elution from Copal\(^®\) spacem compared to Palacos\(^®\) R+G for fabricating gentamicin and vancomycin loaded spacers. The results do not favor Copal\(^®\) spacem over Palacos\(^®\) R+G for the use as a gentamicin and vancomycin biantibiotic-loaded spacer.
The development of controlled biodegradable materials is of fundamental importance in immunodrug delivery to spatiotemporally controlled immune stimulation but avoid systemic inflammatory side effects. Based on this, polycarbonate nanogels are developed as degradable micellar carriers for transient immunoactivation of lymph nodes. An imidazoquinoline‐type TLR7/8 agonist is covalently conjugated via reactive ester chemistry to these nanocarriers. The nanogels not only provide access to complete disintegration by the hydrolysable polymer backbone, but also demonstrate a gradual disintegration within several days at physiological conditions (PBS, pH 6.4–7.4, 37 °C). These intrinsic properties limit the lifetime of the carriers but their payload can still be successfully leveraged for immunological studies in vitro on primary immune cells as well as in vivo. For the latter, a spatiotemporal control of immune cell activation in the draining lymph node is found after subcutaneous injection. Overall, these features render polycarbonate nanogels a promising delivery system for transient activation of the immune system in lymph nodes and may consequently become very attractive for further development toward vaccination or cancer immunotherapy. Due to the intrinsic biodegradability combined with the high chemical control during the manufacturing process, these polycarbonate‐based nanogels may also be of great importance for clinical translation.
The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors.