The cancer angiogenesis co-culture assay:In vitro quantification of the angiogenic potential of tumoroids

The treatment response to anti-angiogenic agents varies among cancer patients and predictive biomarkers are needed to identify patients with resistant cancer or guide the choice of anti-angiogenic treatment. We present “the Cancer Angiogenesis Co-Culture (CACC) assay”, an in vitro Functional Precision Medicine assay which enables the study of tumouroid induced angiogenesis. This assay can quantify the ability of a patient-derived tumouroid to induce vascularization by measuring the induction of tube formation in a co-culture of vascular cells and tumoroids established from the primary colorectal tumour or a metastasis. Furthermore, the assay can quantify the sensitivity of patient-derived tumoroids to anti-angiogenic therapies. We observed that tube formation increased in a dose-dependent manner upon treatment with the pro-angiogenic factor vascular endothelial growth factor A (VEGF-A). When investigating the angiogenic potential of tumoroids from 12 patients we found that 9 tumoroid cultures induced a significant increase in tube formation compared to controls without tumoroids. In these 9 angiogenic tumoroid cultures the tube formation could be abolished by treatment with one or more of the investigated anti-angiogenic agents. The 3 non-angiogenic tumoroid cultures secreted VEGF-A but we observed no correlation between the amount of tube formation and tumoroid-secreted VEGF-A. Our data suggests that the CACC assay recapitulates the complexity of tumour angiogenesis, and when clinically verified, could prove a valuable tool to quantify sensitivity towards different anti-angiogenic agents

Automated image analysis for quantification of filamentous bacteria

BACKGROUND: Antibiotics of the β-lactam group are able to alter the shape of the bacterial cell wall, e.g. filamentation or a spheroplast formation. Early determination of antimicrobial susceptibility may be complicated by filamentation of bacteria as this can be falsely interpreted as growth in systems relying on colorimetry or turbidometry (such as Vitek-2, Phoenix, MicroScan WalkAway). The objective was to examine an automated image analysis algorithm for quantification of filamentous bacteria using the 3D digital microscopy imaging system, oCelloScope. RESULTS: Three E. coli strains displaying different resistant profiles and differences in filamentation kinetics were used to study a novel image analysis algorithm to quantify length of bacteria and bacterial filamentation. A total of 12 β-lactam antibiotics or β-lactam–β-lactamase inhibitor combinations were analyzed for their ability to induce filamentation. Filamentation peaked at approximately 120 min with an average cell length of 30 μm. CONCLUSION: The automated image analysis algorithm showed a clear ability to rapidly detect and quantify β-lactam-induced filamentation in E. coli. This rapid determination of β-lactam-mediated morphological alterations may facilitate future development of fast and accurate AST systems, which in turn will enable early targeted antimicrobial therapy. Therefore, rapid detection of β-lactam-mediated morphological changes may have important clinical implications. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12866-015-0583-5) contains supplementary material, which is available to authorized users

A survey of the antidote preparedness in Norwegian hospitals

Objectives Antidotes are an important part of the emergency preparedness in hospitals. In the case of a major chemical accident or a fire, large quantities of antidotes may be needed within a short period of time. For time-critical antidotes it is therefore necessary that they be immediately available. We wanted to evaluate the antidote preparedness in Norwegian hospitals as regards the national recommendations and compare this with other international guidelines. Methods A digital survey was sent to the 50 hospitals in Norway that treat acute poisonings. Of these, four hospitals are categorised as regional hospitals, 15 as large hospitals and 31 as small hospitals. Each hospital was asked which antidotes they stockpiled from a list of 35 antidotes. The financial costs (low, moderate, high) were added to an established efficacy scale to illustrate the cost-effectiveness of the different antidotes. Results The response rate was 100%. Eleven of fifty (22%) hospitals stockpiled all antidotes recommended for their hospital size. All four regional hospitals had all the recommended antidotes. Large hospitals which were not regional hospitals had the least availability of antidotes, and only one large hospital stockpiled all antidotes recommended for this hospital size. Conclusions We found varying compliance with the national recommendations for antidote storage in hospitals. To strengthen antidote preparedness, we recommend standardised European guidelines to support national guidelines

Additional file 1: of Automated image analysis for quantification of filamentous bacteria

Piperacillin-induced filamentation in E. coli . The time-lapse movies show E. coli treated with piperacillin (PIP, 64 mg/L) and without (Positive control), respectively; as well as graphs showing growth and average length of the bacteria. (MOV 4671 kb

Additional file 1: of Automated image analysis for quantification of filamentous bacteria

Piperacillin-induced filamentation in E. coli . The time-lapse movies show E. coli treated with piperacillin (PIP, 64 mg/L) and without (Positive control), respectively; as well as graphs showing growth and average length of the bacteria. (MOV 4671 kb

Automated image analysis for quantification of filamentous bacteria

Abstract Background Antibiotics of the β-lactam group are able to alter the shape of the bacterial cell wall, e.g. filamentation or a spheroplast formation. Early determination of antimicrobial susceptibility may be complicated by filamentation of bacteria as this can be falsely interpreted as growth in systems relying on colorimetry or turbidometry (such as Vitek-2, Phoenix, MicroScan WalkAway). The objective was to examine an automated image analysis algorithm for quantification of filamentous bacteria using the 3D digital microscopy imaging system, oCelloScope. Results Three E. coli strains displaying different resistant profiles and differences in filamentation kinetics were used to study a novel image analysis algorithm to quantify length of bacteria and bacterial filamentation. A total of 12 β-lactam antibiotics or β-lactam–β-lactamase inhibitor combinations were analyzed for their ability to induce filamentation. Filamentation peaked at approximately 120 min with an average cell length of 30 μm. Conclusion The automated image analysis algorithm showed a clear ability to rapidly detect and quantify β-lactam-induced filamentation in E. coli. This rapid determination of β-lactam-mediated morphological alterations may facilitate future development of fast and accurate AST systems, which in turn will enable early targeted antimicrobial therapy. Therefore, rapid detection of β-lactam-mediated morphological changes may have important clinical implications

Automated image analysis for quantification of filamentous bacteria

Abstract Background Antibiotics of the β-lactam group are able to alter the shape of the bacterial cell wall, e.g. filamentation or a spheroplast formation. Early determination of antimicrobial susceptibility may be complicated by filamentation of bacteria as this can be falsely interpreted as growth in systems relying on colorimetry or turbidometry (such as Vitek-2, Phoenix, MicroScan WalkAway). The objective was to examine an automated image analysis algorithm for quantification of filamentous bacteria using the 3D digital microscopy imaging system, oCelloScope. Results Three E. coli strains displaying different resistant profiles and differences in filamentation kinetics were used to study a novel image analysis algorithm to quantify length of bacteria and bacterial filamentation. A total of 12 β-lactam antibiotics or β-lactam–β-lactamase inhibitor combinations were analyzed for their ability to induce filamentation. Filamentation peaked at approximately 120 min with an average cell length of 30 μm. Conclusion The automated image analysis algorithm showed a clear ability to rapidly detect and quantify β-lactam-induced filamentation in E. coli. This rapid determination of β-lactam-mediated morphological alterations may facilitate future development of fast and accurate AST systems, which in turn will enable early targeted antimicrobial therapy. Therefore, rapid detection of β-lactam-mediated morphological changes may have important clinical implications