The impact of the temperature and exploitation time on the tensile properties and plain strain fracture toughness, KIc in characteristic areas of welded joint

This paper presents the analysis of the temperature and exploitation time impact on the resistant measure to brittle fracture of welded joint constituents of the new and exploited low-alloyed Cr-Mo steel A-387 Gr. B from the aspect of application of the parameters obtained by tensile testing and parameters obtained by fracture mechanics testing. The exploited parent metal is a part of the reactor mantle which has working for over 40 years and is in the damage repair stage, wherein it is being replaced with a new material. Basic characteristics of the material strength, as well as the stress-elongation curves required for stress analysis are obtained by tensile testing. The testing of plane strain fracture toughness is conducted in order to determine the critical stress intensity factor, KIc, that is, assessment of behavior of the new and exploited parent metal, welded metal and heat affected zone from the side of the new parent metal and from the side of the exploited parent metal in the presence of the crack type error. Based on the research results, the analysis of the resistance to brittle fracture was performed in order to compare the obtained values for characteristic areas of welded joint and justify the selection of welding technology

A comparison of methods for studying the tumor microenvironment's spatial heterogeneity in digital pathology specimens

This study was supported by Lothian University Hospitals, Medical Research Scotland and Indica Labs, Inc. Indica Labs, Inc. also provided in-kind resource.Background: The tumor microenvironment is highly heterogeneous, and it is understood to affect tumor progression and patient outcome. A number of studies have reported the prognostic significance of tumor-infiltrating lymphocytes and tumor budding in colorectal cancer. However, the significance of the intra-tumoral heterogeneity present in the spatial distribution of these features within the tumor immune microenvironment (TIME) has not been previously reported. Evaluating this intra-tumoral heterogeneity may aid the understanding of the TIME’s effect on patient prognosis as well as identify novel aggressive phenotypes which can be further investigated as potential targets for new treatment. Methods: In this study we propose and apply two spatial statistical methodologies for the evaluation of the intra-tumor heterogeneity present in the distribution of CD3+ and CD8+ lymphocytes and tumor buds in 232 stage II colorectal cancer cases. Getis-Ord hotspot analysis was applied to quantify the cold and hotspots, defined as regions with a significantly low or high number of each feature of interest, respectively. A novel spatial heatmap methodology for the quantification of the cold and hotspots of each feature of interest, which took into account both the inter-patient heterogeneity and the intra-tumor heterogeneity, was further developed. Results: Resultant data from each analysis, characterizing the spatial intra-tumor heterogeneity of lymphocytes and tumor buds, were used for the development of two new highly prognostic risk models. Conclusions: Our results highlight the value of applying spatial statistics for the assessment of the intra-tumor heterogeneity. Both Getis-Ord hotspot and our proposed Spatial Heatmap analysis are broadly applicable across other tissue types as well as other features of interest.Publisher PDFPeer reviewe

A comparison of methods for studying the tumor microenvironment's spatial heterogeneity in digital pathology specimens

Background: The tumor microenvironment is highly heterogeneous, and it is understood to affect tumor progression and patient outcome. A number of studies have reported the prognostic significance of tumor-infiltrating lymphocytes and tumor budding in colorectal cancer. However, the significance of the intra-tumoral heterogeneity present in the spatial distribution of these features within the tumor immune microenvironment (TIME) has not been previously reported. Evaluating this intra-tumoral heterogeneity may aid the understanding of the TIME’s effect on patient prognosis as well as identify novel aggressive phenotypes which can be further investigated as potential targets for new treatment.Methods: In this study we propose and apply two spatial statistical methodologies for the evaluation of the intra-tumor heterogeneity present in the distribution of CD3+ and CD8+ lymphocytes and tumor buds in 232 stage II colorectal cancer cases. Getis-Ord hotspot analysis was applied to quantify the cold and hotspots, defined as regions with a significantly low or high number of each feature of interest, respectively. A novel spatial heatmap methodology for the quantification of the cold and hotspots of each feature of interest, which took into account both the inter-patient heterogeneity and the intra-tumor heterogeneity, was further developed. Results: Resultant data from each analysis, characterizing the spatial intra-tumor heterogeneity of lymphocytes and tumor buds, were used for the development of two new highly prognostic risk models.Conclusions: Our results highlight the value of applying spatial statistics for the assessment of the intra-tumor heterogeneity. Both Getis-Ord hotspot and our proposed Spatial Heatmap analysis are broadly applicable across other tissue types as well as other features of interest

Abstract LB-368: Applications of automated image analysis, machine learning and spatial statistics for the improvement of stage II colorectal cancer prognosis

Background and Objectives: The tumor microenvironment (TME) plays an important role on tumor progression and patient survival outcome. The TME varies significantly amongst patients as well as within individual tumors. Although a number of studies have reported the prognostic significance of the various TME components, only a very small number of those address the issue of intra-tumor heterogeneity. In this study, we evaluate the densities and interactions of tumor infiltrating lymphocytes, macrophages and tumor buds (TBs) in order to create a more personalized prognosis for patients with stage II colorectal cancer (CRC). This was achieved through the use of multiplexed immunofluorescence, automated image analysis and machine learning approaches. In addition, we developed an objective methodology for studying the intra-tumor heterogeneity and assess its impact on patient survival outcome. Methods: Multiplexed immunofluorescence and automated image analysis using HALO® software were applied for the quantification of CD3+, CD8+ T cells, CD68+, CD163+ macrophages and TBs, across 2 sequential whole slide images (WSI). This was performed on 230 stage II CRC patient samples from Scotland and Japan. Density and spatial relationships between the cellular subpopulations were averaged across the WSI to form input for a prognostic model. To evaluate the intra-patient heterogeneity a further analysis method was developed which divided the WSI into grids with a fixed tile area of 0.785mm2. Tiles with significantly small or large numbers of the feature of interest were considered hot or coldspots respectively. The number of each objects' hot or coldspots within each patient were then calculated. Two machine learning algorithms were employed for the analysis of the data from each analysis method, which lead to the development of two new prognostic risk models. Results: The first combinatorial prognostic model, utilizing the averaged data, consisted of lymphocyte infiltration, the number of lymphocytes within 50µm of TBs and CD68+ /CD163+ macrophage cell ratio. This model was shown to identify a subpopulation of patients who exhibit 100% survival over a 5-year follow-up period. This finding was confirmed in an independent and international validation cohort. The second prognostic model using the results from the spatial heatmap analysis, included the number of TB hotspots as well as the number of hotspots for the proximity of lymphocytes to TBs. This model was shown to be of high prognostic significance. Conclusion: This work demonstrates how by applying digital pathology and machine learning approaches it is possible to identify stage II CRC patients for whom surgical resection alone may be curative. Furthermore, we report a new methodology to evaluate the intra-tumor heterogeneity which was found to improve stage II CRC patient stratification when compared to the current clinical gold standards

A risky business or a safe BET? A Fuzzy Set Event Tree for estimating hazard in biotelemetry studies

The use of biotelemetry methods can provide information on animal behaviour, movement ecology and energetics. However, deployment of biotelemetry equipment on free-living animals incurs risk of damage or loss, which can result in high cost and low sample sizes. To facilitate the uptake of these methods, we have recognized the need for a prescribed procedure for assessing failure risk in biotelemetry studies. Here, we have adapted a commonly used technique in industry and engineering, Event Tree analysis, to facilitate risk estimation and deployment procedure critique. This method can incorporate the use of fuzzy logic to accommodate the uncertainty and scarcity of technical data that are often associated with animal biotelemetry equipment and techniques. Alternatively, probabilistic data may be used for procedures where appropriate models have been established. To encourage the adoption of this method by the scientific community, we have developed a freeware program, Biotelemetry Event Tree (BET). We advocate the use of this method, in the interests of scientific robustness and animal welfare.Fil: Bidder, O. R.. Swansea University; Reino UnidoFil: Arandjelovi, O.. Swansea University; Reino UnidoFil: Almutairi, F.. Swansea University; Reino UnidoFil: Shepard, E. L. C.. Swansea University; Reino UnidoFil: Lambertucci, Sergio Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Patagonia Norte. Instituto de Investigación en Biodiversidad y Medioambiente; Argentina. Universidad Nacional del Comahue; ArgentinaFil: Qasem, L. A. . Swansea University; Reino UnidoFil: Wilson, R. P. . Swansea University; Reino Unid

Publication trends on population medicine programs in Primary Health Care: a bibliometric study

Background In the last two decades there has been a growing attention towards the necessity to switch from an individual care to a population-based approach for long term conditions in Primary Health Care in order to assess the population health needs and to guarantee system sustainability. In this context, various programs such as the ‘‘Disease Management Programs’’ or the ‘‘Medical Home’’ have been developed. The aim of this study is to evaluate publication output related to this issue and trends in the USA and in the European Countries. Methods This study consists of a bibliometric analysis of publications over the period 1988–2014. A systematic review was performed by searching MEDLINE database using specific keywords. The records were categorized according to the year of publication and the Country of first author’s affiliation. The descriptive and inferential statistics were performed. Inferential analysis was performed trough a linear regression, the number of articles per year was considered as the dependent variable in a logarithmic scale, being the regression nonlinear in the parameters. Three different regressions were done, one referred to total of Countries, one to the USA and one to the European Countries. Results Out of 1387 records 1257 were included in the analysis. The distribution of the articles among Countries vary from 0,1% of the Ireland to 73% of the USA. The time trend analysis showed an increase by 24% of the number of publications per year (CI 95% 22%-27%) in the total of Countries, by 23% per year (CI95% 20%-25%) in the USA and of 10% per year (CI95% 7%-13%) in the European Countries. 8th European Public Health Conference: Poster Displays 475 Conclusion The present study showed that there has been a growing interest in scientific research regarding to the population medicine approach in Primary Health Care both in the USA and European Countries. Further studies are necessary to assess the impact of these programs according to the Triple Aim perspective (effectiveness, patient experience, sustainability). Key messages This is a contribution to the evidence of the relevance of population medicine for long term conditions in Primary Health Care European Healthcare Systems welfare oriented can implement population medicine programs in Primary Health Care supported by this evidenc

Urban-rural differences in hospitalisation rates among elderly patients in two long-term care settings in Tuscany, Italy

Context Patients who are in nursing homes or homes in community-based settings that belongs to the category of elderly in long-term care (LTC) often have complex needs that require different kinds of support because of their functional and cognitive limitations, as well as their need for medical care for acute and chronic conditions. Our aim was to see if there are any differences between hospitalizations in high and low density areas for the patients who are in an LTC program, in nursing homes or in home care. Methods This study is an ecological study using data sources from the Tuscany region during the period 2012-2013. In our study we measured the percentage of hospitalization. We measured the use of hospitalization by the dependent elderly in home care and nursing homes, taking into account that they have complex needs. Our analysis has drawn on administrative health data for those aged 65 and over with complex needs who are in an individual planning program in Tuscany, Italy. Hospital discharge data were obtained from the Agenzia regionale di sanita della Toscana (ARS).The denominator was the elderly in home care and residential care, during the given period (1000 personyears). Levels of rurality were measured using OECD REGIONAL TYPOLOGY, 2010, which is based on the criteria of population density and size of the urban centres located within a region. Descriptive and inferential statistics were performed. Results Our sample size was 13,869 patients in the Tuscany region who were in the LTC program during the period 20122013. The median rate of hospitalization in low density areas was 49.33% (per 100 person-years) for the elderly in home care, and 51.08% (per 100 person-years) from more densely populated districts. For elderly people in residential care, the median rate of hospitalization was 42.48% (per 100 person-years) in low density areas and 47.36% (per 100 person-years) in high density districts. The p-values for low vs high density areas are 0.120 for the first indicator, and 0.358 for the second indicator. Discussion Our findings show that there are not significant differences of health disparities between elderly in Long term care program in rural and urban areas, which may derive from free access to care and more healthcare programs in rural areas. Although certain disparities still exit, like a higher hospitalization rate in more densely population districts, especially in home care, the health care system has effectively reduced rural-urban disparities when it comes to the elderly with complex needs. Further steps are needed to be performed in order to delve this preliminary evidence