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Abstract Automation of surveillance of infectious diseases—where algorithms are applied to routine care data to replace manual decisions—likely reduces workload and improves quality of surveillance. However, various barriers limit large-scale implementation of automated surveillance (AS). Current implementation strategies for AS in surveillance networks include central implementation (i.e. collecting all data centrally, and central algorithm application for case ascertainment) or local implementation (i.e. local algorithm application and sharing surveillance results with the network coordinating center). In this perspective, we explore whether current challenges can be solved by federated AS. In federated AS, scripts for analyses are developed centrally and applied locally. We focus on the potential of federated AS in the context of healthcare associated infections (AS-HAI) and of severe acute respiratory illness (AS-SARI). AS-HAI and AS-SARI have common and specific requirements, but both would benefit from decreased local surveillance burden, alignment of AS and increased central and local oversight, and improved access to data while preserving privacy. Federated AS combines some benefits of a centrally implemented system, such as standardization and alignment of an easily scalable methodology, with some of the benefits of a locally implemented system including (near) real-time access to data and flexibility in algorithms, meeting different information needs and improving sustainability, and allowance of a broader range of clinically relevant case-definitions. From a global perspective, it can promote the development of automated surveillance where it is not currently possible and foster international collaboration.The necessary transformation of source data likely will place a significant burden on healthcare facilities. However, this may be outweighed by the potential benefits: improved comparability of surveillance results, flexibility and reuse of data for multiple purposes. Governance and stakeholder agreement to address accuracy, accountability, transparency, digital literacy, and data protection, warrants clear attention to create acceptance of the methodology. In conclusion, federated automated surveillance seems a potential solution for current barriers of large-scale implementation of AS-HAI and AS-SARI. Prerequisites for successful implementation include validation of results and evaluation requirements of network participants to govern understanding and acceptance of the methodology.

Abstract Background Self-perceived general health (SPGH) is a general health indicator commonly used in epidemiological research and is associated with a wide range of exposures from different domains. However, most studies on SPGH only investigated a limited set of exposures and did not take the entire external exposome into account. We aimed to develop predictive models for SPGH based on exposome datasets using machine learning techniques and identify the most important predictors of poor SPGH status. Methods Random forest (RF) was used on two datasets based on personal characteristics from the 2012 and 2016 editions of the Dutch national health survey, enriched with environmental and neighborhood characteristics. Model performance was determined using the area under the curve (AUC) score. The most important predictors were identified using a variable importance procedure and individual effects of exposures using partial dependence and accumulated local effect plots. The final 2012 dataset contained information on 199,840 individuals and 81 variables, whereas the final 2016 dataset had 244,557 individuals with 91 variables. Results Our RF models had overall good predictive performance (2012: AUC = 0.864 (CI: 0.852–0.876); 2016: AUC = 0.890 (CI: 0.883–0.896)) and the most important predictors were “Control of own life”, “Physical activity”, “Loneliness” and “Making ends meet”. Subjects who felt insufficiently in control of their own life, scored high on the De Jong-Gierveld loneliness scale or had difficulty in making ends meet were more likely to have poor SPGH status, whereas increased physical activity per week reduced the probability of poor SPGH. We observed associations between some neighborhood and environmental characteristics, but these variables did not contribute to the overall predictive strength of the models. Conclusions This study identified that within an external exposome dataset, the most important predictors for SPGH status are related to mental wellbeing, physical exercise, loneliness, and financial status.

Abstract Background Predicting healthy physiological aging is of major interest within public health research. However, longitudinal studies into predictors of healthy physiological aging that include numerous exposures from different domains (i.e. the exposome) are scarce. Our aim is to identify the most important exposome-related predictors of healthy physiological aging over the life course and across generations. Methods Data were used from 2815 participants from four generations (generation 1960s/1950s/1940s/1930s aged respectively 20–29/30–39/40–49/50–59 years old at baseline, wave 1) of the Doetinchem Cohort Study who were measured every 5 years for 30 years. The Healthy Aging Index, a physiological aging index consisting of blood pressure, glucose, creatinine, lung function, and cognitive functioning, was measured at age 46–85 years (wave 6). The average exposure and trend of exposure over time of demographic, lifestyle, environmental, and biological exposures were included, resulting in 86 exposures. Random forest was used to identify important predictors. Results The most important predictors of healthy physiological aging were overweight-related (BMI, waist circumference, waist/hip ratio) and cholesterol-related (using cholesterol lowering medication, HDL and total cholesterol) measures. Diet and educational level also ranked in the top of important exposures. No substantial differences were observed in the predictors of healthy physiological aging across generations. The final prediction model’s performance was modest with an R2 of 17%. Conclusions Taken together, our findings suggest that longitudinal cardiometabolic exposures (i.e. overweight- and cholesterol-related measures) are most important in predicting healthy physiological aging. This finding was similar across generations. More work is needed to confirm our findings in other study populations.

Abstract Cognitive decline is part of the normal aging process. However, some people experience a more rapid decline than others due to environmental and genetic factors. Numerous single nucleotide polymorphisms (SNPs) have been linked to cognitive function, but only a few to cognitive decline. To understand whether cognitive function and cognitive decline are driven by the same mechanisms, we investigated whether 433 SNPs previously linked to cognitive function and 2 SNPs previously linked to cognitive decline are associated with both general cognitive functioning at baseline and general cognitive decline up to 20-years follow-up in the Doetinchem Cohort Study (DCS). The DCS is a longitudinal population-based study that enrolled men and women aged 20–59 years between 1987–1991, with follow-up examinations every 5 years. We used data of rounds 2–6 (1993–2017, n = 2559). General cognitive function was assessed using four cognition tests measuring memory, speed, fluency and flexibility. With these test scores, standardized residuals (adjusted for sex, age and examination round) were calculated for each cognition test at each round and subsequently combined into one general cognitive function measure using principal component analyses. None of the 435 previously identified variants were associated with baseline general cognitive function in the DCS. But rs429358-C, a coding apolipoprotein E (APOE) SNP and one of the variants previously associated with cognitive decline, was associated with general cognitive decline in our study as well (p-value = 1 × 10−5, Beta = −0.013). These findings suggest that decline of general cognitive function is influenced by other mechanisms than those that are involved in the regulation of general cognitive function.

Abstract Due to the wealth of exposome data from longitudinal cohort studies that is currently available, the need for methods to adequately analyze these data is growing. We propose an approach in which machine learning is used to identify longitudinal exposome-related predictors of health, and illustrate its potential through an application. Our application involves studying the relation between exposome and self-perceived health based on the 30-year running Doetinchem Cohort Study. Random Forest (RF) was used to identify the strongest predictors due to its favorable prediction performance in prior research. The relation between predictors and outcome was visualized with partial dependence and accumulated local effects plots. To facilitate interpretation, exposures were summarized by expressing them as the average exposure and average trend over time. The RF model’s ability to discriminate poor from good self-perceived health was acceptable (Area-Under-the-Curve = 0.707). Nine exposures from different exposome-related domains were largely responsible for the model’s performance, while 87 exposures seemed to contribute little to the performance. Our approach demonstrates that ML can be interpreted more than widely believed, and can be applied to identify important longitudinal predictors of health over the life course in studies with repeated measures of exposure. The approach is context-independent and broadly applicable.

Abstract Background Worldwide, socioeconomic differences in health and use of healthcare resources have been reported, even in countries providing universal healthcare coverage. However, it is unclear how large these socioeconomic differences are for different types of care and to what extent health status plays a role. Therefore, our aim was to examine to what extent healthcare expenditure and utilization differ according to educational level and income, and whether these differences can be explained by health inequalities. Methods Data from 18,936 participants aged 25–79 years of the Dutch Health Interview Survey were linked at the individual level to nationwide claims data that included healthcare expenditure covered in 2017. For healthcare utilization, participants reported use of different types of healthcare in the past 12 months. The association of education/income with healthcare expenditure/utilization was studied separately for different types of healthcare such as GP and hospital care. Subsequently, analyses were adjusted for general health, physical limitations, and mental health. Results For most types of healthcare, participants with lower educational and income levels had higher healthcare expenditure and used more healthcare compared to participants with the highest educational and income levels. Total healthcare expenditure was approximately between 50 and 150 % higher (depending on age group) among people in the lowest educational and income levels. These differences generally disappeared or decreased after including health covariates in the analyses. After adjustment for health, socioeconomic differences in total healthcare expenditure were reduced by 74–91 %. Conclusions In this study among Dutch adults, lower socioeconomic status was associated with increased healthcare expenditure and utilization. These socioeconomic differences largely disappeared after taking into account health status, which implies that, within the universal Dutch healthcare system, resources are being spent where they are most needed. Improving health among lower socioeconomic groups may contribute to decreasing health inequalities and healthcare spending.

Introduction A substantial proportion of individuals infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), report persisting symptoms weeks and months following acute infection. Estimates on prevalence vary due to differences in study designs, populations, heterogeneity of symptoms and the way symptoms are measured. Common symptoms include fatigue, cognitive impairment and dyspnoea. However, knowledge regarding the nature and risk factors for developing persisting symptoms is still limited. Hence, in this study, we aim to determine the prevalence, severity, risk factors and impact on quality of life of persisting symptoms in the first year following acute SARS-CoV-2 infection.Methods and analysis The LongCOVID-study is both a prospective and retrospective cohort study being conducted in the Netherlands, with a one year follow-up. Participants aged 5 years and above, with self-reported positive or negative tests for SARS-CoV-2 will be included in the study. The primary outcome is the prevalence and severity of persistent symptoms in participants that tested positive for SARS-CoV-2 compared with controls. Symptom severity will be assessed for fatigue (Checklist Individual Strength (CIS subscale fatigue severity)), pain (Rand-36/SF-36 subscale bodily pain), dyspnoea (Medical Research Council (mMRC)) and cognitive impairment (Cognitive Failure Questionnaire (CFQ)). Secondary outcomes include effect of vaccination prior to infection on persistent symptoms, loss of health-related quality of life (HRQoL) and risk factors for persisting symptoms following infection with SARS-CoV-2.Ethics and dissemination The Utrecht Medical Ethics Committee (METC) declared in February 2021 that the Medical Research Involving Human Subjects Act (WMO) does not apply to this study (METC protocol number 21-124/C). Informed consent is required prior to participation in the study. Results of this study will be submitted for publication in a peer-reviewed journal.

To control the rise in Neisseria meningitidis strain W infections, during 2018–2019, the Netherlands launched a catch-up meningococcal conjugate (MenACWY) vaccination campaign for teenagers (13–18 years of age). Applying a mental models approach, we surveyed teenagers and their parents about their knowledge and beliefs about meningococcal disease, the MenACWY vaccination, vaccinations in general, and their MenACWY vaccination intentions. Using random forest analysis, we studied predictions of vaccination intentions by knowledge and beliefs. Survey response rate was 52.8% among teenagers and 59.4% among parents. MenACWY vaccination intentions were best predicted by knowledge and beliefs about vaccinations in general, surpassing knowledge and beliefs about meningococcal disease and the MenACWY vaccination. For teenagers, their parents’ intention that the teenager be vaccinated was a strong predictor of the teenagers’ own vaccination intention. To optimize vaccination uptake during future outbreaks, we recommend that communications emphasize the effectiveness and safety of vaccines and continue to focus on parents.

Abstract Background Early detection, identification, and treatment of chronic hepatitis B through screening is vital for those at increased risk, e.g. born in hepatitis B endemic countries. In the Netherlands, Moroccan immigrants show low participation rates in health-related screening programmes. Since social networks influence health behaviour, we investigated whether similar screening intentions for chronic hepatitis B cluster within social networks of Moroccan immigrants. Methods We used respondent-driven sampling (RDS) where each participant (“recruiter”) was asked to complete a questionnaire and to recruit three Moroccans (“recruitees”) from their social network. Logistic regression analyses were used to analyse whether the recruiters’ intention to request a screening test was similar to the intention of their recruitees. Results We sampled 354 recruiter-recruitee pairs: for 154 pairs both participants had a positive screening intention, for 68 pairs both had a negative screening intention, and the remaining 132 pairs had a discordant intention to request a screening test. A tie between a recruiter and recruitee was associated with having the same screening intention, after correction for sociodemographic variables (OR 1.70 [1.15–2.51]). Conclusions The findings of our pilot study show clustering of screening intention among individuals in the same network. This provides opportunities for social network interventions to encourage participation in hepatitis B screening initiatives.

BackgroundUrban renewal traditionally involves policy sectors such as housing, transport, and employment, which potentially can enhance the health of residents living in deprived areas. Additional involvement of the public health sector might increase the health impact of these urban renewal activities. This study evaluates the health impact of an additional focus on health, under the heading of Healthy District Experiments (HDE), within districts where an urban renewal programme was carried out.MethodsWe evaluated changes in health outcomes before the start of the HDE and after implementation, and compared these changes with health changes in control areas, e.g. districts from the urban renewal programme where no additional HDE was implemented. Additionally, we gathered information on the content of the experiments to determine what types of activities have been implemented.ResultsThe additional activities from the HDE were mostly aimed at strengthening the health care in the districts and at promoting physical activity. When we compared the prevalence in general health, mental health, overweight, obesity, smoking, and physical activity during the study period between the HDE districts and control districts, we found no significant differences in the rate of change. The study is limited by a small sample size and the cross-sectional nature of the data. These and other limitations are discussed.ConclusionWe found no evidence for a beneficial health impact of the activities that were initiated with a specific focus on health, within a Dutch urban renewal programme. Specific attention for network management and the integration of such activities in the wider programme, as well as an allocated budget might be needed in order to sort a health impact.

Abstract Background We developed a system to automatically classify stance towards vaccination in Twitter messages, with a focus on messages with a negative stance. Such a system makes it possible to monitor the ongoing stream of messages on social media, offering actionable insights into public hesitance with respect to vaccination. At the moment, such monitoring is done by means of regular sentiment analysis with a poor performance on detecting negative stance towards vaccination. For Dutch Twitter messages that mention vaccination-related key terms, we annotated their stance and feeling in relation to vaccination (provided that they referred to this topic). Subsequently, we used these coded data to train and test different machine learning set-ups. With the aim to best identify messages with a negative stance towards vaccination, we compared set-ups at an increasing dataset size and decreasing reliability, at an increasing number of categories to distinguish, and with different classification algorithms. Results We found that Support Vector Machines trained on a combination of strictly and laxly labeled data with a more fine-grained labeling yielded the best result, at an F1-score of 0.36 and an Area under the ROC curve of 0.66, considerably outperforming the currently used sentiment analysis that yielded an F1-score of 0.25 and an Area under the ROC curve of 0.57. We also show that the recall of our system could be optimized to 0.60 at little loss of precision. Conclusion The outcomes of our study indicate that stance prediction by a computerized system only is a challenging task. Nonetheless, the model showed sufficient recall on identifying negative tweets so as to reduce the manual effort of reviewing messages. Our analysis of the data and behavior of our system suggests that an approach is needed in which the use of a larger training dataset is combined with a setting in which a human-in-the-loop provides the system with feedback on its predictions.

Summary: Background: Concerns about long-lasting symptoms attributed to Lyme borreliosis (LB) are widespread in the Western world, while such symptoms are highly prevalent in the general population. Methods: In the largest prospective study to date, adults with physician-confirmed LB were included at the start of antibiotic treatment. Primary outcomes, prevalence of persistent symptoms and symptom severity, were assessed using three-monthly standardised questionnaires during one year. Persistent symptoms were defined as impaired scores for fatigue (CIS, subscale fatigue), cognitive impairment (CFQ) or pain (SF-36, subscale bodily pain) ≥6 months, with onset

Abstract Background In November 2016, the Dutch Health Council recommended hepatitis B (HBV) screening for first-generation immigrants from HBV endemic countries. However, these communities show relatively low attendance rates for screening programmes, and our knowledge on their participation behaviour is limited. We identified determinants associated with the intention to request an HBV screening test in first-generation Moroccan-Dutch immigrants. We also investigated the influence of non-refundable costs for HBV screening on their intention. Methods Offline and online questionnaires were distributed among first- and second/third-generation Moroccan-Dutch immigrants using respondent-driven sampling. Random forest analyses were conducted to determine which determinants had the greatest impact on (1) the intention to request an HBV screening test on one’s own initiative, and (2) the intention to participate in non-refundable HBV screening at €70,-. Results Of the 379 Moroccan-Dutch respondents, 49.3% intended to request a test on their own initiative, and 44.1% were willing to attend non-refundable screening for €70,-. Clarity regarding infection status, not having symptoms, fatalism, perceived self-efficacy, and perceived risk of having HBV were the strongest predictors to request a test. Shame and stigma, fatalism, perceived burden of screening participation, and social influence of Islamic religious leaders had the greatest predictive value for not intending to participate in screening at €70,- non-refundable costs. Perceived severity and possible health benefit were facilitators for this intention measure. These predictions were satisfyingly accurate, as the random forest method retrieved area under the curve scores of 0.72 for intention to request a test and 0.67 for intention to participate in screening at €70,- non-refundable costs. Conclusions By the use of respondent-driven sampling, we succeeded in studying screening behaviour among a hard-to-reach minority population. Despite the limitations associated with correlated data and the sampling method, we recommend to (1) incorporate clarity regarding HBV status, (2) stress the risk of an asymptomatic infection, (3) emphasise mother-to-child transmission as the main transmission route, and (4) team up with Islamic religious leaders to help decrease elements of fatalism, shame, and stigma to enhance screening uptake of Moroccan immigrants in the Netherlands.

Abstract Background The Ebola outbreak in West-Africa triggered risk communication activities to promote adequate preventive behaviour in the Netherlands. Our study investigated the level of knowledge, perceptions, and media use regarding Ebola. Methods In December 2014, an online questionnaire was administered to the Dutch population (n = 526) and Health Care Workers (HCW) (n = 760). Results The mean knowledge score (range 0–15) of HCW (m = 13.3;SD = 1.4) was significantly higher than the general public (m = 10.8;SD = 2.0). No significant difference was found in perceived severity and susceptibility. Perceived fear of the general public (m = 2.5; SD = 0.8) was significantly higher than among HCW (m = 2.4; SD = 0.7). Respondents primarily used television to obtain information. Conclusions While Ebola was perceived severe, it did not lead to excessive fear or perceived susceptibility for developing the disease. Nonetheless, our research showed that knowledge with respect to human-to-human transmission is low, while this is crucial to complying with preventive measures. Our study reveals priorities for improving risk communication.

Abstract Background Since in an ageing society more long-term care (LTC) facilities are needed, it is important to understand the main determinants of first-time utilization of (LTC) services. Methods The Andersen service model, which distinguishes predisposing, enabling and need factors, was used to develop a model for first-time utilization of LTC services among the general population of the Netherlands. We used data on 214,821 persons registered in a database of general practitioners (NIVEL Primary Care Database). For each person the medical history was known, as well as characteristics such as ethnicity, income, home-ownership, and marital status. Utilization data from the national register on long-term care was linked at a personal level. Generalized Linear Models were used to determine the relative importance of factors of incident LTC-service utilization. Results Top 5 determinants of LTC are need, measured as the presence of chronic diseases, age, household size, household income and homeownership. When controlling for all other determinants, the presence of an additional chronic disease increases the probability of utilizing any LTC service by 45% among the 20+ population (OR = 1.45, 95% CI: 1.41–1.49), and 31% among the 65+ population (OR = 1.31, 95% CI: 1.27–1.36). With respect to the 20+ population, living in social rent (OR = 2.45, 95% CI = 2.25–2.67, ref. = home-owner) had a large impact on utilizing any LTC service. In a lesser degree this was the case for living alone (OR = 1.63, 95% CI = 1.52–1.75, ref. = not living alone). A higher household income was linked with a lower utilization of any LTC service. Conclusions All three factors of the Anderson model, predisposing, enabling, and need determinants influence the likelihood of future LTC service utilization. This implies that none of these factors can be left out of the analysis of what determines this use. New in our analysis is the focus on incident utilization. This provides a better estimate of the effects of predictors than a prevalence based analysis, as there is less confounding by changes in determinants occurring after LTC initiation. Especially the need of care is a strong factor. A policy implication of this relative importance of health status is therefore that LTC reforms should take health aspects into account.

Abstract Background Lyme disease (LD) has become the most common vector borne illness in the Northern hemisphere. Prevention relies predominantly on fostering protective behaviors (e.g., avoiding tick areas, using protective clothing and repellent, and doing routine tick checks post-exposure). The objective of this study was to evaluate the effectiveness (in terms of knowledge, perceived severity and susceptibility, self-efficacy, response efficacy, intention, and behavior over time) and appreciation of a leaflet and a movie as tools for informing the public in the Netherlands about ticks and LD protective behaviors. Methods Participants (1,677 at t1 and 361 extra at t2) were members of a representative Internet panel (adults aged 18 years and above). A four group randomized controlled design was used to test the effect of an information leaflet and a movie (two intervention groups), compared to a control group and a follow-up only control group. Data were collected over two periods: July 15–29, 2013 (t1) and at follow-up 4 weeks later, August 16–31, 2013 (t2). Results Post-intervention results show all respondents in all groups possess good general basic knowledge of ticks and LD. Respondents in both the leaflet and movie groups knew more than respondents in the control group, and had greater awareness of best practices after a tick bite. Intention to perform protective behavior in future was stronger among respondents in the intervention groups. While respondents generally appreciated both the movie and the leaflet, they found the movie ran too long. Follow-up revealed no lasting positive effects from either the leaflet or the movie. Conclusions Our results suggest that both the movie and the leaflet are valued and effective intervention tools for improving knowledge about tick bites and strengthening self-efficacy and intentions to perform protective behavior against ticks and LD . Achieving lasting effects, however, calls for more action.

Dietary supplements are products that are widely used for instance as energisers or to lose weight. There have been cases reported where undeclared ingredients present in such supplements have caused adverse effects on the health of the user. As there are many different products to choose from, it seems impossible to predict which might contain harmful components and to ban them from the market. Nonetheless, the use of dietary supplements and the experiences of users are shared in online discussions. We describe the development of a search engine to retrieve products associated with certain effects. Upon application we were able to retrieve a list of dietary supplements that are repeatedly associated with excessive effects by users on public fora. The top of the list contains supplements that have previously been banned because they contained undeclared harmful components. The use of the search engine as described here is a powerful method for making a risk-based selection of dietary supplements which can then be analysed for the presence of illegal or other unwanted components.

Plants are sessile organisms requiring mechanisms that enable them to balance water supply and demand in dry environments. Demand (D) is largely driven by canopy size (transpirational leaf area), although differences in transpiration per unit leaf area also occur. Supply (S) is primarily driven by water capture via the root system. Drought stress can be defined as the situation where supply of water cannot meet demand of the crop, such that water availability is the limiting factor for biomass accumulation. Under such conditions, plants will need to reduce D in order to meet the limited S, access more water to increase S, or increase the efficiency with which water is utilised. We used sorghum, a model C4 crop species, to demonstrate how the stay-green trait can modulate canopy development and root architecture to enhance adaptation. We show how stay-green positively impacts the balance between S and D under post-flowering drought, including insights at the molecular level. We provide examples of how canopy and root traits impact the S/D balance in other cereals under water limitation. For example, on the supply side, the extent of genetic variation for root angle (RA) has been evaluated in sorghum, wheat and barley, and genomic regions associated with RA have been mapped. Furthermore, the relationship between RA and grain yield has been explored in barley and sorghum field trials. The capacity to manipulate components of S and D to optimise the S/D balance should assist crop improvement programs to develop enhanced ideotypes for dry environments.

Respondent-driven detection is a chain recruitment method used to sample contact persons of infected persons in order to enhance case finding. It starts with initial individuals, so-called seeds, who are invited for participation. Afterwards, seeds receive a fixed number of coupons to invite individuals with whom they had contact during a specific time period. Recruitees are then asked to do the same, resulting in successive waves of contact persons who are connected in one recruitment tree. However, often the majority of participants fail to invite others, or invitees do not accept an invitation, and recruitment stops after several waves. A mathematical model can help to analyse how various factors influence peer recruitment and to understand under which circumstances sustainable recruitment is possible. We implemented a stochastic simulation model, where parameters were suggested by empirical data from an online survey, to determine the thresholds for obtaining large recruitment trees and the number of waves needed to reach a steady state in the sample composition for individual characteristics. We also examined the relationship between mean and variance of the number of invitations sent out by participants and the probability of obtaining a large recruitment tree. Our main finding is that a situation where participants send out any number of coupons between one and the maximum number is more effective in reaching large recruitment trees, compared to a situation where the majority of participants does not send out any invitations and a smaller group sends out the maximum number of invitations. The presented model is a helpful tool that can assist public health professionals in preparing research and contact tracing using online respondent-driven detection. In particular, it can provide information on the required minimum number of successfully sent invitations to reach large recruitment trees, a certain sample composition or certain number of waves.

Activation of the β2 integrin lymphocyte function-associated antigen-1 (LFA-1) in T cells induces stabilization of proinflammatory AU-rich element (ARE)-bearing mRNAs, by triggering the nuclear-to-cytoplasmic translocation of the mRNA-binding and -stabilizing protein HuR. However, the mechanism by which LFA-1 engagement controls HuR localization is not known. Here, we identify and characterize four key regulators of LFA-1-induced changes in HuR activity: the p38 pathway kinase MK2 and the constitutive nuclear proteins hnRNPs C, H1 and K. LFA-1 engagement results in rapid, sequential activation of p38 and MK2. Post-LFA-1 activation, MK2 inducibly associates with both hnRNPC and HuR, resulting in the dissociation of HuR from hnRNPs C, H1 and K. Freed from the three hnRNPs, HuR translocates from the nucleus to the cytoplasm, and mediates the stabilization of labile cytokine transcripts. Our results suggest that the modulation of T cell cytokine mRNA half-life is an intricate process that is negatively regulated by hnRNPs C, H1 and K and requires MK2 as a critical activator.

Older adults are more vulnerable to influenza virus infection and at higher risk for severe complications and influenza-related death compared to younger adults. Unfortunately, influenza vaccine responses tend to be impaired in older adults due to aging of the immune system (immunosenescence). Latent infection with cytomegalovirus (CMV) is assumed to enhance age-associated deleterious changes of the immune system. Although lower responses to influenza vaccination were reported in CMV-seropositive compared to CMV-seronegative adults and elderly, beneficial effects of CMV infection were observed as well. The lack of consensus in literature on the effect of latent CMV infection on influenza vaccination may be due to the presence of pre-existing immunity to influenza in these studies influencing the subsequent influenza vaccine response. We had the unique opportunity to evaluate the effect of age and latent CMV infection on the antibody response to the novel influenza H1N1pdm vaccine strain during the pandemic of 2009, thereby reducing the effect of pre-existing immunity on the vaccine-induced antibody response. This analysis was performed in a large study population (n = 263) in adults (18–52 years old). As a control, memory responses to the seasonal vaccination, including the same H1N1pdm and an H3N2 strain, were investigated in the subsequent season 2010–2011. With higher age, we found decreased antibody responses to the pandemic vaccination even within this age range, indicating signs of immunosenescence to this novel antigen in the study population. Using a generalized estimation equation regression model, adjusted for age, sex, and previous influenza vaccinations, we observed that CMV infection in contrast did not influence the influenza virus-specific antibody titer after H1N1pdm vaccination. Yet, we found higher residual protection rates (antibody level ≥40 hemagglutinin units (HAU)) in CMV-seropositive individuals than in CMV-seronegative individuals 6 months and 1 year after pandemic vaccination. In the subsequent season, no effect of age or CMV infection on seasonal influenza vaccine response was observed. In conclusion, we observed no evidence for CMV-induced impairment of antibody responses to a novel influenza strain vaccine in adults. If anything, our data suggest that there might be a beneficial effect of latent CMV infection on the protection rate after novel influenza vaccination.

Rapid growth of information technology development as well as increasing level of competition make every company need to establish an information system to support its business process. Research & Technology Transfer Directorate of Binus University is aware of this matter and makes a goal to improve the existing business process and develop a web-based information system that is able to support the existing business process to be more effective and efficient. This study aims to conduct an analysis and a design of information system for Research & Technology Transfer Directorate Binus University that can enhance the existing business process. Research used two methods, firstly data gathering done by conducting field studies and literature reviews, secondly the analysis and design of the system with object-oriented method. The result achieved from this research is a web-based information system that can support Research & Technology Transfer Directorate business process. The conclusion of this research is a new integrated web-based information system that can support and enhance current business process by connecting all parts of the system with the result to make all process more effective and efficient.

BACKGROUND:Large-scale regeneration programmes to improve the personal conditions and living circumstances in deprived areas may affect health and the lifestyle of the residents. Previous evaluations concluded that a large-scale urban regeneration programme in the Netherlands had some positive effects within 3.5 years. The aim of the current study was to evaluate the effects at the longer run. METHODS:With a quasi-experimental research design we assessed changes in the prevalence of general health, mental health, physical activity, overweight, obesity, and smoking between the pre-intervention (2003-04 -mid 2008) and intervention period (mid 2008-2013-14) in 40 deprived target districts and comparably deprived control districts. We used the Difference-in-Difference (DiD) to assess programme impact. Additionally, we stratified analyses by sex and by the intensity of the regeneration programme. RESULTS:Changes in health and health related behaviours from pre-intervention to the intervention period were about equally large in the target districts as in control districts. DiD impact estimates were inconsistent and not statistically significant. Sex differences in DiD estimates were not consistent or significant. Furthermore, DiD impact estimates were not consistently larger in target districts with more intensive intervention programmes. CONCLUSION:We found no evidence that this Dutch urban regeneration programme had an impact in the longer run on self-reported health and related behaviour at the area level.

bespreking recent onderzoek Tranzo is het wetenschappelijk centrum voor zorg en welzijn van Tilburg University. Binnen Tranzo werken mensen uit wetenschap, beleid en praktijk samen in onderzoeksprogramma’s op alle terreinen van zorg en welzijn. Rondom de door het RIVM ingestelde leerstoel ‘economische aspecten van gezondheid en zorg’ (Johan Polder) onderzoeken enkele promovendi de kosten van de gezondheidszorg vanuit het perspectief van de grote demografische en epidemiologische veranderingen die zich aan het voltrekken zijn.

In developing liposomes for in vivo use, it is important to design the liposomes to have optimal in vivo kinetics, and it is also necessary to identify optimal high-throughput production conditions for these liposomes. Previous work has not definitively established the general relationship between liposomes' configuration and composition, and their in vivo kinetics. Also, no straightforward method exists to calculate optimal liposome high-throughput production conditions for specific liposome compositions. This work presents first-principles quantitative correlations describing liposomes' in vivo drug leakage and vascular mass transfer kinetics. This work further presents a simple quantitative model relating specific liposome compositions to ideal high-throughput production parameters. The results have implications for the identification of promising liposome compositions via high-throughput screening methodologies, as well as the design and optimization of high-throughput reactors for liposome production.

Cancers often overexpress EGF and other growth factors to promote cell replication and migration. Previous work has not produced targeted drug carriers sensitive to abnormal amounts of growth factors. This work demonstrates that liposomes bearing EGF receptors covalently crosslinked to p-toluic acid or methyl-PEO(4)-NHS ester (or, in short, MRBLs) exhibit an increased rate of release of encapsulated drug compounds when EGF is present in solution. Furthermore, the modified EGF receptors retain the abilities to form dimers in the presence of EGF and bind specifically to EGF. These results demonstrate that MRBLs are sensitive to EGF in solution and indicate that MRBL-reconstituted modified EGF receptors, in the presence of EGF in solution, form dimers which increase MRBL permeability to encapsulated compounds.