CD163 is a member of the group B scavenger receptor cysteine-rich (SRCR) superfamily. This study ... more CD163 is a member of the group B scavenger receptor cysteine-rich (SRCR) superfamily. This study describes aspects of the tissue distribution, the regulation of expression, and signal transduction after cross-linking of this receptor at the cell surface of macrophages. CD163 showed an exclusive expression on resident macrophages (e.g., red pulp macrophages, alveolar macrophages). The expression was inducible on monocyte-derived macrophages by glucocorticoids but not by interleukin-4 (IL-4), granulocyte-macrophage colony-stimulating factor (GM-CSF), and interferon-gamma. The combination of IL-4 or GM-CSF with glucocorticoids resulted in a further increase. Subcellular analysis of alveolar macrophages by immunoelectron microscopy showed a plasma membrane localization of the antigen. Cross-linking of CD163 with monoclonal antibody induced a protein tyrosine kinase-dependent signal that resulted in (1) slow-type calcium mobilization, (2) inositol triphosphate production, and (3) secreti...
CD163 is a member of the group B scavenger receptor cysteine-rich (SRCR) superfamily. This study ... more CD163 is a member of the group B scavenger receptor cysteine-rich (SRCR) superfamily. This study describes aspects of the tissue distribution, the regulation of expression, and signal transduction after cross-linking of this receptor at the cell surface of macrophages. CD163 showed an exclusive expression on resident macrophages (e.g., red pulp macrophages, alveolar macrophages). The expression was inducible on monocyte-derived macrophages by glucocorticoids but not by interleukin-4 (IL-4), granulocyte-macrophage colony-stimulating factor (GM-CSF), and interferon-gamma. The combination of IL-4 or GM-CSF with glucocorticoids resulted in a further increase. Subcellular analysis of alveolar macrophages by immunoelectron microscopy showed a plasma membrane localization of the antigen. Cross-linking of CD163 with monoclonal antibody induced a protein tyrosine kinase-dependent signal that resulted in (1) slow-type calcium mobilization, (2) inositol triphosphate production, and (3) secreti...
Background: There is a need to understand much more about the geographic variation of air polluta... more Background: There is a need to understand much more about the geographic variation of air pollutants. This requires the ability to extrapolate from monitoring stations to unsampled locations. The aim was to assess methods to develop accurate and high resolution maps of background air pollution across the EU. Methods: We compared the validity of ordinary kriging, universal kriging and regression mapping in developing EU-wide maps of air pollution on a 1 × 1 km resolution. Predictions were made for the year 2001 for nitrogen dioxide (NO 2 ), fine particles b 10 µm (PM 10 ), ozone (O 3 ), sulphur dioxide (SO 2 ) and carbon monoxide (CO) using routine monitoring data in Airbase. Predictor variables from EU-wide databases were land use, road traffic, population density, meteorology, altitude, topography and distance to sea. Models were developed for the global, rural and urban scale separately. The best method to model concentrations was selected on the basis of predefined performance measures (R 2 , Root Mean Square Error (RMSE)). Results: For NO 2 , PM 10 and O 3 universal kriging performed better than regression mapping and ordinary kriging. Validation of the final universal kriging estimates with results from all validation sites gave R 2 -values and RMSE-values of 0.61 and 6.73 µg/m 3 for NO 2 ; 0.45 and 5.19 µg/m 3 for PM 10 ; and 0.70 and 7.69 µg/m 3 for O 3 . For SO 2 and CO none of the three methods was able to provide a satisfactory prediction.
Land use regression (LUR) modelling is a popular method to estimate outdoor air pollution concent... more Land use regression (LUR) modelling is a popular method to estimate outdoor air pollution concentrations at the home and/or work addresses of individual subjects in epidemiological studies. Typically, such models are constructed using measurements from dedicated monitoring campaigns lasting up to 1 year. It is unknown to what extent such models can adequately predict concentrations in earlier or later time periods. We tested the stability of measured and modelled spatial contrasts in outdoor nitrogen dioxide (NO(2)) pollution across the Netherlands over 8 years. NO(2) measurements were conducted at 40 locations in the Netherlands in 1999-2000. In 2007, NO(2) was again measured at 144 locations, of which 35 were the same as in 1999-2000. This enabled us to compare measurements as well as model predictions between the two time periods. NO(2) measurements conducted in 2007 agreed well with NO(2) measurements taken in 1999-2000 at the same locations (R(2)=0.86). LUR models from 1999-2000 and 2007 explained 85% and 86% of observed spatial variance, respectively. The 2007 LUR model explained 77% of spatial variability in the 1999-2000 measurements and the 1999-2000 model explained 81% of variability in the 2007 measurements. We found good agreement between measured spatial contrasts in outdoor NO(2) in 1999-2000 and 2007. LUR models predicted spatial contrast 8 years in the past (2007 model) and 8 years in the future (1999-2000 model) well. This supports the use of LUR models in epidemiological studies with health data available for a later or earlier timepoint.
There are currently no epidemiological studies on health effects of long-term exposure to ultrafi... more There are currently no epidemiological studies on health effects of long-term exposure to ultrafine particles (UFP), largely because data on spatial exposure contrasts for UFP is lacking. The objective of this study was to develop a land use regression (LUR) model for UFP in the city of Amsterdam. Total particle number concentrations (PNC), PM10, PM2.5, and its soot content were measured directly outside 50 homes spread over the city of Amsterdam. Each home was measured during one week. Continuous measurements at a central urban background site were used to adjust the average concentration for temporal variation. Predictor variables (traffic, address density, land use) were obtained using geographic information systems. A model including the product of traffic intensity and the inverse distance to the nearest road squared, address density, and location near the port explained 67% of the variability in measured PNC. LUR models for PM2.5, soot, and coarse particles (PM10, PM2.5) explained 57%, 76%, and 37% of the variability in measured concentrations. Predictions from the PNC model correlated highly with predictions from LUR models for PM2.5, soot, and coarse particles. A LUR model for PNC has been developed, with similar validity as previous models for more commonly measured pollutants.
BACKGROUND: Several studies have found an effect on mortality of between-city contrasts in long-t... more BACKGROUND: Several studies have found an effect on mortality of between-city contrasts in long-term exposure to air pollution. The effect of within-city contrasts is still poorly understood. OBJECTIVES: We studied the association between long-term exposure to traffic-related air pollution and mortality in a Dutch cohort. METHODS: We used data from an ongoing cohort study on diet and cancer with 120,852 subjects who were followed from 1987 to 1996. Exposure to black smoke (BS), nitrogen dioxide, sulfur dioxide, and particulate matter ≤ 2.5 µm (PM 2.5 ), as well as various exposure variables related to traffic, were estimated at the home address. We conducted Cox analyses in the full cohort adjusting for age, sex, smoking, and area-level socioeconomic status. RESULTS: Traffic intensity on the nearest road was independently associated with mortality. Relative risks (95% confidence intervals) for a 10-µg/m 3 increase in BS concentrations (difference between 5th and 95th percentile) were 1.05 (1.00-1.11) for natural cause, 1.04 (0.95-1.13) for cardiovascular, 1.22 (0.99-1.50) for respiratory, 1.03 (0.88-1.20) for lung cancer, and 1.04 (0.97-1.12) for mortality other than cardiovascular, respiratory, or lung cancer. Results were similar for NO 2 and PM 2.5 , but no associations were found for SO 2 . CONCLUSIONS: Traffic-related air pollution and several traffic exposure variables were associated with mortality in the full cohort. Relative risks were generally small. Associations between natural-cause and respiratory mortality were statistically significant for NO 2 and BS. These results add to the evidence that long-term exposure to ambient air pollution is associated with increased mortality. Mean 34.5 μg/m 3 Min 14.6 μg/m 3 Max 52.8 μg/m 3 SD 7.3 μg/m 3 Mean 36.9 μg/m 3 Min 14.6 μg/m 3 Max 66.7 μg/m 3 SD 8.2 μg/m 3 Mean 13.9 μg/m 3 Min 8.7 μg/m 3 Max 19.5 μg/m 3 SD 2.2 μg/m 3 Mean 16.5 μg/m 3 Min 8.7 μg/m 3 Max 35.8 μg/m 3 SD 3.5 μg/m 3 Mean 13.7 μg/m 3 Min 4.2 μg/m 3 Max 33.8 μg/m 3 SD 5.1 μg/m 3 Mean 28.3 μg/m 3 Min 23.0 μg/m 3 Max 36.8 μg/m 3 SD 2.1 μg/m 3 Mean 2,284 mvh/24hr Min 1 mvh/24hr Max 104,275 mvh/24hr SD 3,767 mvh/24hr Mean 140,903 mvh/24hr Min 0 mvh/24hr Max 893,722 mvh/24hr SD 116,104 mvh/24hr
Background: There is evidence for adverse effects of outdoor air pollution on lung function of ch... more Background: There is evidence for adverse effects of outdoor air pollution on lung function of children. Quantitative summaries of the effects of air pollution on lung function, however, are lacking due to large differences among studies. oBjectives: We aimed to study the association between residential exposure to air pollution and lung function in five European birth cohorts with a standardized exposure assessment following a common protocol.
h i g h l i g h t s < LUR models were developed in 36 study areas in Europe using a standardized ... more h i g h l i g h t s < LUR models were developed in 36 study areas in Europe using a standardized approach. < NO 2 models explained a large fraction of concentration variability (median R 2 82%). < Local traffic intensity data were important predictors for LUR model development.
This article appeared in a journal published by Elsevier. The attached copy is furnished to the a... more This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright a b s t r a c t The immune system's efficacy in detecting and destroying cancer cells varies considerably throughout the stages of cancer development and its role may be critical particularly during the surgical period. Although surgery causes tumor cells to shed into the blood, immune cells have the capacity to destroy these tumor cells. However, surgery also suppresses cytotoxic capacity. It is particularly during this surgical period that psychological factors can have a significant dampening or strengthening impact on surgery-related immunomodulation response, thus exerting an effect on survival. This review describes the immune changes during the peri-surgical period and the influences psychological factors have on immune function, including the immune effects caused by psychological interventions in cancer patients. We recommend that future studies exploring the role of psychological factors on immune function and survival focus more on their influence during the peri-surgical period.
CD163 is a member of the group B scavenger receptor cysteine-rich (SRCR) superfamily. This study ... more CD163 is a member of the group B scavenger receptor cysteine-rich (SRCR) superfamily. This study describes aspects of the tissue distribution, the regulation of expression, and signal transduction after cross-linking of this receptor at the cell surface of macrophages. CD163 showed an exclusive expression on resident macrophages (e.g., red pulp macrophages, alveolar macrophages). The expression was inducible on monocyte-derived macrophages by glucocorticoids but not by interleukin-4 (IL-4), granulocyte-macrophage colony-stimulating factor (GM-CSF), and interferon-gamma. The combination of IL-4 or GM-CSF with glucocorticoids resulted in a further increase. Subcellular analysis of alveolar macrophages by immunoelectron microscopy showed a plasma membrane localization of the antigen. Cross-linking of CD163 with monoclonal antibody induced a protein tyrosine kinase-dependent signal that resulted in (1) slow-type calcium mobilization, (2) inositol triphosphate production, and (3) secreti...
CD163 is a member of the group B scavenger receptor cysteine-rich (SRCR) superfamily. This study ... more CD163 is a member of the group B scavenger receptor cysteine-rich (SRCR) superfamily. This study describes aspects of the tissue distribution, the regulation of expression, and signal transduction after cross-linking of this receptor at the cell surface of macrophages. CD163 showed an exclusive expression on resident macrophages (e.g., red pulp macrophages, alveolar macrophages). The expression was inducible on monocyte-derived macrophages by glucocorticoids but not by interleukin-4 (IL-4), granulocyte-macrophage colony-stimulating factor (GM-CSF), and interferon-gamma. The combination of IL-4 or GM-CSF with glucocorticoids resulted in a further increase. Subcellular analysis of alveolar macrophages by immunoelectron microscopy showed a plasma membrane localization of the antigen. Cross-linking of CD163 with monoclonal antibody induced a protein tyrosine kinase-dependent signal that resulted in (1) slow-type calcium mobilization, (2) inositol triphosphate production, and (3) secreti...
Background: There is a need to understand much more about the geographic variation of air polluta... more Background: There is a need to understand much more about the geographic variation of air pollutants. This requires the ability to extrapolate from monitoring stations to unsampled locations. The aim was to assess methods to develop accurate and high resolution maps of background air pollution across the EU. Methods: We compared the validity of ordinary kriging, universal kriging and regression mapping in developing EU-wide maps of air pollution on a 1 × 1 km resolution. Predictions were made for the year 2001 for nitrogen dioxide (NO 2 ), fine particles b 10 µm (PM 10 ), ozone (O 3 ), sulphur dioxide (SO 2 ) and carbon monoxide (CO) using routine monitoring data in Airbase. Predictor variables from EU-wide databases were land use, road traffic, population density, meteorology, altitude, topography and distance to sea. Models were developed for the global, rural and urban scale separately. The best method to model concentrations was selected on the basis of predefined performance measures (R 2 , Root Mean Square Error (RMSE)). Results: For NO 2 , PM 10 and O 3 universal kriging performed better than regression mapping and ordinary kriging. Validation of the final universal kriging estimates with results from all validation sites gave R 2 -values and RMSE-values of 0.61 and 6.73 µg/m 3 for NO 2 ; 0.45 and 5.19 µg/m 3 for PM 10 ; and 0.70 and 7.69 µg/m 3 for O 3 . For SO 2 and CO none of the three methods was able to provide a satisfactory prediction.
Land use regression (LUR) modelling is a popular method to estimate outdoor air pollution concent... more Land use regression (LUR) modelling is a popular method to estimate outdoor air pollution concentrations at the home and/or work addresses of individual subjects in epidemiological studies. Typically, such models are constructed using measurements from dedicated monitoring campaigns lasting up to 1 year. It is unknown to what extent such models can adequately predict concentrations in earlier or later time periods. We tested the stability of measured and modelled spatial contrasts in outdoor nitrogen dioxide (NO(2)) pollution across the Netherlands over 8 years. NO(2) measurements were conducted at 40 locations in the Netherlands in 1999-2000. In 2007, NO(2) was again measured at 144 locations, of which 35 were the same as in 1999-2000. This enabled us to compare measurements as well as model predictions between the two time periods. NO(2) measurements conducted in 2007 agreed well with NO(2) measurements taken in 1999-2000 at the same locations (R(2)=0.86). LUR models from 1999-2000 and 2007 explained 85% and 86% of observed spatial variance, respectively. The 2007 LUR model explained 77% of spatial variability in the 1999-2000 measurements and the 1999-2000 model explained 81% of variability in the 2007 measurements. We found good agreement between measured spatial contrasts in outdoor NO(2) in 1999-2000 and 2007. LUR models predicted spatial contrast 8 years in the past (2007 model) and 8 years in the future (1999-2000 model) well. This supports the use of LUR models in epidemiological studies with health data available for a later or earlier timepoint.
There are currently no epidemiological studies on health effects of long-term exposure to ultrafi... more There are currently no epidemiological studies on health effects of long-term exposure to ultrafine particles (UFP), largely because data on spatial exposure contrasts for UFP is lacking. The objective of this study was to develop a land use regression (LUR) model for UFP in the city of Amsterdam. Total particle number concentrations (PNC), PM10, PM2.5, and its soot content were measured directly outside 50 homes spread over the city of Amsterdam. Each home was measured during one week. Continuous measurements at a central urban background site were used to adjust the average concentration for temporal variation. Predictor variables (traffic, address density, land use) were obtained using geographic information systems. A model including the product of traffic intensity and the inverse distance to the nearest road squared, address density, and location near the port explained 67% of the variability in measured PNC. LUR models for PM2.5, soot, and coarse particles (PM10, PM2.5) explained 57%, 76%, and 37% of the variability in measured concentrations. Predictions from the PNC model correlated highly with predictions from LUR models for PM2.5, soot, and coarse particles. A LUR model for PNC has been developed, with similar validity as previous models for more commonly measured pollutants.
BACKGROUND: Several studies have found an effect on mortality of between-city contrasts in long-t... more BACKGROUND: Several studies have found an effect on mortality of between-city contrasts in long-term exposure to air pollution. The effect of within-city contrasts is still poorly understood. OBJECTIVES: We studied the association between long-term exposure to traffic-related air pollution and mortality in a Dutch cohort. METHODS: We used data from an ongoing cohort study on diet and cancer with 120,852 subjects who were followed from 1987 to 1996. Exposure to black smoke (BS), nitrogen dioxide, sulfur dioxide, and particulate matter ≤ 2.5 µm (PM 2.5 ), as well as various exposure variables related to traffic, were estimated at the home address. We conducted Cox analyses in the full cohort adjusting for age, sex, smoking, and area-level socioeconomic status. RESULTS: Traffic intensity on the nearest road was independently associated with mortality. Relative risks (95% confidence intervals) for a 10-µg/m 3 increase in BS concentrations (difference between 5th and 95th percentile) were 1.05 (1.00-1.11) for natural cause, 1.04 (0.95-1.13) for cardiovascular, 1.22 (0.99-1.50) for respiratory, 1.03 (0.88-1.20) for lung cancer, and 1.04 (0.97-1.12) for mortality other than cardiovascular, respiratory, or lung cancer. Results were similar for NO 2 and PM 2.5 , but no associations were found for SO 2 . CONCLUSIONS: Traffic-related air pollution and several traffic exposure variables were associated with mortality in the full cohort. Relative risks were generally small. Associations between natural-cause and respiratory mortality were statistically significant for NO 2 and BS. These results add to the evidence that long-term exposure to ambient air pollution is associated with increased mortality. Mean 34.5 μg/m 3 Min 14.6 μg/m 3 Max 52.8 μg/m 3 SD 7.3 μg/m 3 Mean 36.9 μg/m 3 Min 14.6 μg/m 3 Max 66.7 μg/m 3 SD 8.2 μg/m 3 Mean 13.9 μg/m 3 Min 8.7 μg/m 3 Max 19.5 μg/m 3 SD 2.2 μg/m 3 Mean 16.5 μg/m 3 Min 8.7 μg/m 3 Max 35.8 μg/m 3 SD 3.5 μg/m 3 Mean 13.7 μg/m 3 Min 4.2 μg/m 3 Max 33.8 μg/m 3 SD 5.1 μg/m 3 Mean 28.3 μg/m 3 Min 23.0 μg/m 3 Max 36.8 μg/m 3 SD 2.1 μg/m 3 Mean 2,284 mvh/24hr Min 1 mvh/24hr Max 104,275 mvh/24hr SD 3,767 mvh/24hr Mean 140,903 mvh/24hr Min 0 mvh/24hr Max 893,722 mvh/24hr SD 116,104 mvh/24hr
Background: There is evidence for adverse effects of outdoor air pollution on lung function of ch... more Background: There is evidence for adverse effects of outdoor air pollution on lung function of children. Quantitative summaries of the effects of air pollution on lung function, however, are lacking due to large differences among studies. oBjectives: We aimed to study the association between residential exposure to air pollution and lung function in five European birth cohorts with a standardized exposure assessment following a common protocol.
h i g h l i g h t s < LUR models were developed in 36 study areas in Europe using a standardized ... more h i g h l i g h t s < LUR models were developed in 36 study areas in Europe using a standardized approach. < NO 2 models explained a large fraction of concentration variability (median R 2 82%). < Local traffic intensity data were important predictors for LUR model development.
This article appeared in a journal published by Elsevier. The attached copy is furnished to the a... more This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright a b s t r a c t The immune system's efficacy in detecting and destroying cancer cells varies considerably throughout the stages of cancer development and its role may be critical particularly during the surgical period. Although surgery causes tumor cells to shed into the blood, immune cells have the capacity to destroy these tumor cells. However, surgery also suppresses cytotoxic capacity. It is particularly during this surgical period that psychological factors can have a significant dampening or strengthening impact on surgery-related immunomodulation response, thus exerting an effect on survival. This review describes the immune changes during the peri-surgical period and the influences psychological factors have on immune function, including the immune effects caused by psychological interventions in cancer patients. We recommend that future studies exploring the role of psychological factors on immune function and survival focus more on their influence during the peri-surgical period.
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