Over the past decade, the Dutch government has pursued a research-based approach to tackle socioeconomic inequalities in health. We report on the most recent phase in this approach: the development of a strategy to reduce health inequalities in the Netherlands by an independent committee. In addition, we will reflect on the way the report of this committee has influenced health policy and practice.A 6-year research and development program was conducted which covered a number of different policy options and consisted of 12 intervention studies. The study results were discussed with experts and policy makers. A government advisory committee developed a comprehensive strategy that intends to reduce socioeconomic inequalities in disability-free life expectancy by 25% in 2020. The strategy covers 4 different entry-points for reducing socioeconomic inequalities in health, contains 26 specific recommendations, and includes 11 quantitative policy targets. Further research and development efforts are also recommended.Although the Dutch approach has been influenced by similar efforts in other European countries, particularly the United Kingdom and Sweden, it is unique in terms of its emphasis on building a systematic evidence-base for interventions and policies to reduce health inequalities. Both researchers and policy-makers were involved in the process, and there are clear indications that some of the recommendations are being adopted by health policy-makers and health care practice, although more so at the local than at the national level. Before 1980, socioeconomic inequalities in health were a non-issue in public health (research) in the Netherlands. This changed in the early 1980's as a result of the publication of the Black Report in England . GradualSince then, the Dutch Ministry of Health has followed a systematic, research-based approach to tackling socioeconomic inequalities in health. An initial five-year research program mapped the nature and determinants of socioeconomic inequalities in health in the Netherlands . A seconThe report deals with socioeconomic inequalities in health, defined as systematic differences in health status between people with higher and lower socioeconomic status, as indicated by educational level, occupational class, and/or income level. Like other European countries, the Netherlands has substantial inequalities in health between socioeconomic groups. Differences in life expectancy at birth between socioeconomic groups are in the order of 4 years, and differences in healthy life expectancy have recently been calculated to be a staggering 14 years . InequalThe main focus of the program was on developing and evaluating interventions and policies, but a number of other activities  were undertaken as well. Table When the results of the evaluation studies became available, meetings were held in 2000 with scientific experts and representatives from policy makers and from practice in six different areas . During these meetings possible recommendations for new policies and interventions were tested and refined . The inpSubsequently, the committee overseeing the program held a number of plenary meetings to develop a comprehensive strategy to reduce health inequalities. Committee members were appointed by the Minister of Health, and they included former and active politicians of various political backgrounds, as well as a representative of the ministry of health and researchers. A conscious attempt was made to represent the whole (relatively narrow) political spectrum in the Netherlands. Members ranged from left  to right , and the committee was chaired by a former christian-democrat Minister of Social Affairs. Researchers had an important influence on the whole process: JM was secretary of the committee, and KS acted as co-ordinator of the program, and both were involved in writing draft versions of the final report. The committee reported directly to the Minister of Health.The committee started from the assumption that existing inequalities in health at least partly rank as unjust and that the government is responsible for achieving a reduction of these health differences. This assumption was based on the argument that health should be seen as a condition for the options open to individuals to structure their own life as far as possible according to their own ideas. Those health differences that are the consequence of an unequal distribution of living conditions over which individuals have no control, were thus seen as health inequities, to be tackled by the government. It was argued that this would require a comprehensive strategy, given the persistent and widespread character of socio-economic inequalities in health.The committee wanted its strategy for reducing health inequalities to be based on sound evidence. Ideally, factors targeted by the strategy should be known to contribute to the explanation of health inequalities, and interventions and policies should be known to diminish exposure of lower socioeconomic groups to these factors. While the first requirement could be met relatively easily , the second requirement was more difficult to meet. Although the program produced evidence on effectiveness of interventions and policies and showed some positive results, this left important gaps in the knowledge base, both in terms of coverage of various policy options and in terms of strength of evidence. This problem was also encountered in other countries . The comIn addition, the committee also paid attention to the political feasibility of possible policy recommendations. This aspect was discussed during the plenary meetings, in the light of the  experience of the committee members as well as the outcome of the working conferences that were mentioned before.The committee decided to base its strategy on a number of quantitative targets, because these can aid in plotting a clear policy course and can function as milestones for interim assessments of the strategy. It took the World Health Organization target as its starting point , and refIn order to attain such an ambitious goal, major efforts are required, if only because during the last decades inequalities in health in the Netherlands have increased rather than decreased . AlthougTable In a number of other areas, the committee recommended intensified or new policies. These recommendations were partly based on reported positive results of intervention studies. This applies to the recommendations relating to school health promotion programs, technical and organizational measures to reduce physical workload, reinforcement of primary care in disadvantaged areas by employing practice nurses and peer educators, and local care networks to prevent social problems among chronic psychiatric patients. The results of some of the other intervention studies led to recommendations for further development of those interventions, as in the case of special benefit schemes for families living in poverty and counseling schemes for school absenteeism. Most of the other recommendations, however, are primarily based on an understanding of the factors that have been shown to contribute to health inequalities, and of the best way to deliver interventions targeting these factors.The committee did not attempt to estimate the costs of the recommended interventions and policies.As experience has taught that implementing effective interventions should not be taken for granted, the committee advised that a steering group be formed to drive and control the process of implementing effective interventions. On the one hand, this should function as a highly visible focal point at which the expertise available in the Netherlands is made accessible to all relevant policy areas. On the other hand, the steering group should be able to act on its own initiative to capture and retain attention for socio-economic inequalities in health and to promote the implementation of policy proposals. Given these two functions, the committee advised including experts as well as representatives from the main relevant policy areas in the steering group.Given the fact that research has not yet fully disclosed the origins of socioeconomic inequalities in health, the committee considered continuation of explanatory research to be vital because it may lead to new entry-points for intervention. The same applies to further development of effective interventions and policies. The committee therefore recommended evaluation of all recommended interventions and policies during and after their implementation.The committee published its main report in March 2001 . The repA closing conference took place in October 2001. During that conference, the results of the evaluation studies as well as the proposed policy strategy were presented to a broad public, and reflected upon by, among others, Sir Donald Acheson from the UK. In addition, policy implications were discussed. Participants included researchers, policy makers and representatives from practice, not only from the public health and health care field, but also from other policy areas .The official cabinet reaction to the recommendations presented to parliament in November 2001 was positive but further elaboration of the recommendations as well as decision-making was deferred to the next cabinet . A new cThe delay in political decision making does not seem to have hindered the implementation of specific interventions that were evaluated within the programme. So far, at least a few of the interventions that have been proven to be effective have been implemented on a larger scale. These include the integrated programme to prevent school children from starting smoking, and the local care networks for chronic psychiatric patients.While many countries, including the UK, Sweden and Finland have had national research efforts in the field of socioeconomic inequalities in health during the second half of the 1990's, the Dutch program is unique for its emphasis on evaluation of interventions. More generally, the main distinguishing feature of the Dutch approach is its focus on commissioning evaluations of interventions. Although this was done in a systematic way, using an explicit conceptual and methodological framework, the program also had its obvious limitations. It had a modest budget  and funded not more than 12, rather small-scale intervention studies targeting relatively easily modifiable factors. The latter is not only due to the small budget of the program, but also to strict methodological requirements which in practice made it nearly impossible to study the effectiveness of broader policy measures . In hindThe unique elements of the Dutch approach should not distract from the fact that the Dutch experience received important inputs from abroad. Its start is a late response to the British Black Report and is directly related to the efforts of the European Office of the World Health Organization to put health equity on national policy agendas . During The Dutch approach reflects the input of both researchers and policy-makers, although the balance between the two has oscillated over time. The first signals that health inequalities should be addressed came from researchers, but were picked up by policy-makers within the Ministry of Health in the mid-1980's who were then looking for opportunities to strengthen health policy  in the Netherlands. This small group of bureaucrats succeeded in launching and following through the first research program, but left the Ministry or changed posts before the program came to an end. Partly due to continuous personnel changes in the Ministry, the intensity of the exchanges between researchers and policy-makers gradually diminished during the second program. When the final report was published reactions from within the Ministry were rather cool, although the Minister, who had taken a personal interest in the matter, responded very favourably. At this stage, however, it seems that without a continuing "push" from the research-side the bureaucrats could easily loose interest altogether, particularly now that there are rapid changes of cabinet.A major obstacle for a comprehensive package of policy measures seems to be the relatively weak position of the Ministry of Health as compared to other policy areas. It is obvious that a substantial reduction of health inequalities can be achieved only by involving other policy areas next to that of (preventive and curative) health care. This starting point seems to contrast with the ideas of the ministries in other policy areas, that seem to consider this issue as the responsibility of the Ministry of Health in particular. So far, the Ministry of Health does not seem to have a lot of success in convincing other policy areas of the importance of contributing to reducing inequalities in health.The lack of success in mobilising other policy areas at the national level is probably partly related to the fact that the issue of inequalities is perceived as rather abstract by these other areas. This probably requires the issue of inequalities in health to be "re-phrased" for that specific policy area, in terms that fit within their ideas. Housing corporations for example do not consider themselves to be responsible for tackling health inequalities but they do feel responsibility for high quality living conditions, which then might automatically contribute to a better health status of people in lower socio-economic groups. Paradoxically, an approach in which the issue of inequalities in health is cut into small pieces, requires a steering. This forms the background of the plea of the committee for a steering group.Remarkable progress has been made, not only in terms of knowledge production but also in terms of increased confidence among policy-makers and practitioners to take action to reduce inequalities in health. Many health agencies in the Netherlands are working to reduce socioeconomic inequalities in health. This is illustrated by the fact that the 'National Contract on Public Health', concluded in 2001 between many national and local agencies in the field of public health, has selected the reduction of socioeconomic inequalities in health as its first priority. Many local health agencies have already implemented some of the interventions discussed in this paper.


Conventional Comparative Genomic Hybridization (CGH) has been widely used for detecting copy number alterations in cancer and for identifying regions containing candidate tumor responsible genes. Recently, several studies have shown the utility of cDNA microarray CGH for studing gene copy changes in various types of tumors. However, no such studies on T-cell lymphomas have been performed. To date T-cell lymphomas analyzed by the use of chromosome CGH have revealed only slight copy number alterations and not gene amplifications.BCLX, PCNA, FKBP1A, IGFBP2 and cMYC, that are amplified, highly expressed, and also contained in the amplicons on 20p and 2q. The expresion of these genes was analyzed in 39 T-cell lymphomas and 3 other T-cell lines.In the present study, we describe the characterization of three amplicons of the T-cell line huT78 located at 2q34-q37, 8q23-q24 and 20p, where new amplified and overexpressed genes are found. The use of a cDNA microarray containing 7.657 transcripts allowed the identification of certain genes, such as BCLX, PCNA, FKBP1A, IGFBP2 and cMYC). We showed that overexpression of the amplified genes could be attributable to gene dosage. We speculate that deregulation of those genes could be important in the development of T-cell lymphomas and/or in the maintenance of T-cell lines.By the use of conventional CGH and CGH and expression cDNA microarrays we defined three amplicons in the T-cell line huT78 and identified several novel gene amplifications ( ERBB2 (17q12), cMYC (8q24), and CCND1 (11q13) are found in 10–25% of breast tumors. Amplifications are revealed by Comparative Genomic Hybridization (CGH) in small chromosome areas (restricted to 2–10 Mb) where DNA copy number increases from more than 5 to 10-fold. Within these amplicons it is possible to identify critical amplified genes that are also overexpressed: this is the case for cMYC (8q24.12), ERBB2 (17q12-q21), MDM2 (12q14.3-q15) or BCL2 (18q21.3) [Gene amplification plays an important role in the progression and initiation of many solid tumors, as is the case of breast cancer where amplification of the genes ERBB2 7q12, cMYCND1 11q1 are foun cMYC 8q2, and CCN18q21.3)  and in nCCND1 11q are founThe cutaneous T-cell line huT78 was obtained from American Type Culture Collection  and cells were grown under recommended culture conditions. High molecular weight DNA was extracted and CGH was performed as described previously ,14..In order to define regions of high-level amplification and to identify amplified and highly expressed genes contained in the amplicons, we performed cDNA microarray experiments on T-cell line huT78 to obtain expression and genomic profiles of the amplicons. We used the CNIO Oncochip (v1.1a) containing 7.657 different sequence-validated I.M.A.G.E cDNA clones  -some of them duplicated to reach a total of 11.718 spots- that represent known genes and expressed sequence tags (ESTs) related to the tumoral process, and tissue specific genes. A complete list can be found at AluI and RsaI digested, labeled with Cy5 (huT78) and Cy3 (control) using BioPrime labeling kit , and hybridized on microarrays at 50°C for 14–16 h, as previously described [2 values) were calculated and used for the analysis. The CNIO Oncochip contains 7.657 different clones, of which 3.079 are replicated at least twice: thus, we removed and averaged the replicates by using an in-house developed preprocessing tool [Genomic DNA hybridizations on microarrays were performed using DNA extracted from the T-cell line huT78 and from the blood of a control donor used as a reference. Genomic DNAs were escribed . Post-hyin vitro transcription kit  following manufacturer's recommendations. A pool of aRNAs obtained from the Universal Human RNA  was used as a standard reference in all hybridizations. Test or reference amplified RNAs (aRNAs) were labeled with fluorescent Cy5 and Cy3, respectively, as reported [Expression data was also obtained from huT78 cells and from magnetically isolated T lymphocytes obtained from the pooled peripheral blood of 5 anonymous donors that were used as a control. T lymphocytes were isolated by using either magnetic microbeads conjugated to monoclonal mouse anti-human CD3 antibodies purchased from Miltenyi Biotec Inc. , or magnetic depletion of non-T-cells with a cocktail of antibodies using the Pan T-cell Isolation Kit (Miltenyi Biotec Inc.). Total RNAs were extracted with Tri Reagent  following the manufacturer's instructions and amplified using a T7-based method, as previously described ,18. BrieIn order to analyze if the candidate genes contained in the amplicons are altered in primary tumors and other cell lines, we analyzed expression data obtained in a previous study  using tuCGH carried out in huT78 cells revealed three high-level gains at 2q34-q37, 8q23-q24 and 20p, showing copy number gains higher than 5 fold Figure . Low-lev. According to this database, clones were ordered along the chromosomes and their expression and genomic values . Cut-off levels for genomic data were defined at more than 1.7, a significantly high value to assure that the gene is gained at least 4-fold  (data from FISH studies). Within these thirty genes that were gained and overexpressed in the cell line, 5 of them were located in amplicons of chromosome 2  and chromosome 20 (FKBP1A and BCL2L1) revealed by conventional CGH.Only thirty genes that showed high-level genomic gains were also highly expressed in the cutaneous T-cell line huT78 Table . Genes wID1 and BCL2L1 (BCLX) located at 20q11 (Table ID1 and BCLX show amplification (4 and 7 times respectively), only BCLX is highly expressed  and IGFBP2 (2q33-24) around 220 Mb, TUBA1  around 227 Mb and PSMD3 mapped by FISH at 2q35. Amongst these, IGFBP2 is the most highly overexpressed . This gene is upregulated by all-trans-retinoic acid (ATRA), a differentiation inducer capable of causing clinical remission in about 90% of patients with acute promyelocytic leukemia. Other genes located in the amplicon that have not been analyzed in this study could also be important.Amplicon in chromosome 8 is located at 8q23-q24, where the gene FKBP1A and PCNA were overexpressed in 89,7 and 71,8% respectively (35 and 28 out of 39) of the primary tumors and in all the three cell lines analyzed. In addition, BCLX was overexpressed in 64,1% (25/39) of the primary tumors and in Jurkat cell line. Regarding genes in amplicons of chromosome 2 and 8, IGFBP2 was only overexpressed in 15,4% (6/39) of the tumors and cMYC is not highly expressed in any of them. However, both genes were overexpressed in the three cell lines.Expression of the relevant genes found in the amplicons that were gained in this T-cell line were examined in a series of 39 primary T-cell lymphomas and 3 T-cell lines  . Three gConventional chromosome CGH of the T-cell line huT78 showed genomic patterns of copy number changes affecting most of the chromosomes. Three highly amplified regions were detected using this technique. Nevertheless, resolution of chromosome CGH is no less than 2 Mb for copy number gains and is a function of both amplicon size and copy number gains .In order to precisely define regions of high-level amplification and to identify amplified and highly expressed genes contained in the amplicons of the T-cell line huT78, we performed cDNA microarray CGH and expression profiling of the cell line. For this purpose, we used the CNIO Oncochip containing 7.657 different sequence-validated cDNA clones that represent known genes and expressed sequence tags (ESTs) related to the tumoral process, and tissue specific genes.Recently, several studies have shown the utility of cDNA microarray CGH for studing gene copy changes in various types of tumors, and the usefulness of defining amplicon boundaries at high resolution (gene level) to assist in locating and identifying candidate oncogenes -11. HoweBy analyzing mRNA levels in parallel, we observed that not all genes that are amplified are also overexpressed. Thus, by analyzing the expression of the genes contained in the amplicons, we selected several genes whose expression seemed to respond to gene copy number gains. We showed that only a few of the genes contained in the amplicon are highly gained and also overexpressed. In this way we could select the candidate genes to study further that could be involved in the tumorogenesis of the T-cell lymphomas.FKBP1A, PCNA and BCLX were overexpressed in 90–65% of the primary tumors. FKBP1A is a receptor for rapamicin as well as for FK506, a powerful immunosuppressant in T-cells, and PCNA is involved in the control of eukaryotic DNA replication and may have a role in DNA repair synthesis. BCLX is involved in both positive and negative regulation of programmed cell death. Thus, these three genes, could be significant in the development of T-cell lymphomas.As stated before , howeverIGFBP2 was only overexpressed in a low proportion of the primary tumors (15%) and cMYC is not highly expressed in any of them. Curiously, both genes were overexpressed in the three cell lines suggesting that they could be of relevance in the maintenance of the cell lines.When the candidate genes located in amplicons of chromosome 2 and 8 were examined, we observed that BCLX, PCNA and FKBP1A. These genes are also overexpressed in 65–90% of a set of 39 T-cell lymphomas and 3 cell lines, while IGFBP2 and cMYC are only overexpressed in T-cell lines. Our data suggest a different role of these genes in such processes. New studies with more clones covering these amplicons can help us to better identify relevant genes in T-cell lymphomas.We have identified 3 amplicons by CGH in the T-cell line huT78. By cDNA microarray CGH. We have narrowed down the regions and selected some amplified and overexpressed genes: BM carried out the genomic and RNA hybridizations of the cell line onto the microarrays, performed FISH experiments, analyzed the results and drafted the manuscript. BM-D participated in the design of the study and in the analysis and discussion of the results. MC performed the amplification of the RNA and hybridization onto the microarray to carry out expression studies of primary tumors. VF performed nucleic acid extractions for hybridizations onto the microarray, grew and label the BAC clones for FISH assays and performed CGH. RD-U carried out statistical analysis of the microarray results. JB conceived of the study, and participated in its design and coordination. All authors read and approved the final manuscript.This file contains row genomic and expression data for each gene. Each gene is identified by a unique clone identification (Clone ID), the corresponding gene symbol (Gene Symbol) and the Unigene number (Unigene ID). Localization of all clones are also shown .Click here for file


Failure to be comprehensive can distort the results of a systematic review. Conversely, extensive searches may yield unmanageable number of citations of which only few may be relevant. Knowledge of usefulness of each source of information may help to tailor search strategies in systematic reviews.We conducted a systematic review of prevalence/incidence of maternal mortality and morbidities from 1997 to 2002. The search strategy included electronic databases, hand searching, screening of reference lists, congress abstract books, contacting experts active in the field and web sites from less developed countries. We evaluated the effectiveness of each source of data and discuss limitations and implications for future research on this topic.Electronic databases identified 64098 different citations of which 2093 were included. Additionally 487 citations were included from other sources. MEDLINE had the highest yield identifying about 62% of the included citations. BIOSIS was the most precise with 13.2% of screened citations included. Considering electronic citations alone (2093), almost 20% were identified uniquely by MEDLINE (400), 7.4% uniquely by EMBASE (154), and 5.6% uniquely by LILACS (117). About 60% of the electronic citations included were identified by two or more databases.This analysis confirms the need for extending the search to other sources beyond well-known electronic databases in systematic reviews of maternal mortality and morbidity prevalence/incidence. These include regional databases such as LILACS and other topic specific sources such as hand searching of relevant journals not indexed in electronic databases. Guidelines for search strategies for prevalence/incidence studies need to be developed. The importance of comprehensive search strategies to identify 'all relevant articles' when conducting systematic reviews has been long documented . ComprehAt the World Health Organization (WHO), we have conducted a systematic review of prevalence/incidence of maternal mortality and morbidities from 1997 to 2002. The primary objective of this review is to assist in mapping the burden of reproductive ill-health by providing a comprehensive, standardized and reliable tabulation of data on the prevalence/incidence of maternal morbidity and mortality [The methodology of the systematic review and the search strategy have been described elsewhere . In brie® software. Selection of eligible studies involved two stages; the first stage consisted of screening of title and/or abstracts from the citations downloaded. Citations were excluded if any of the following applied: (i) data collection dates were not reported, (ii) data were collected only before 1990, (iii) part of the data were collected before 1980 and disaggregation by year was not possible (in order to exclude data before 1990), (iv) number of study participants was less than 200, (v) the study design was case-control and incidence/prevalence estimates from the defined population cannot be calculated, (vi) the methodology was not described. The second stage consisted of full-text evaluation of those citations that were not excluded in the first step applying the same criteria. For practical reasons, studies identified by other sources were only entered in Reference Manager® if they were eventually included in the review.We downloaded all citations identified by electronic databases into Reference ManagerWe recorded the source or sources of each citation. For each source, we calculated number of citations identified, included, and number included that were unique to the source. The sensitivity of each source was defined as the number of included citations identified by the source over the total number included. The precision was defined as the number of included citations identified by a source over the number of both included and excluded citations identified by that source. This review had no language restrictions and we recorded the language in which the report was written. Detailed results regarding languages will be reported separately.Two reviewers performed the screening for all citations. In order to estimate the level of disagreement between the two reviewers within 2.5% of the true value, they independently screened title/abstracts for a sample of citations (560). This sample size assumes a 95% confidence interval and that the level of disagreement between the two reviewers will not exceed 10% . The perFor the time period from 1997 to 2002, 64098 different citations from electronic databases were identified of which 2093 were included. Additionally, 487 citations were included from other sources. There were 92 citations for which we could not obtain full text and, therefore, they could not be assessed .Table Overall, in terms of precision, we included 1 in 25 screened citations (4%). The most precise database was BIOSIS where 13.2% of the screened citations were included; IMEMR, LILACS and Popline followed this with 10.1%, 9.4% and 9.1%, respectively  citations were identified by reference lists of articles, expert contacts, congress proceedings, abstract books, hand searching of journals available in libraries that are not indexed in electronic databases, and other emerging databases in developing countries. As expected, there has been a large overlap between databases: 60% were identified by two or more databases and about 44% were identified by MEDLINE and EMBASE together. These two databases also provided the largest number of unique citations and both are considered necessary. PAIS International and Econlit only identified 3 and 1 citations, respectively, that were not identified by any other database and they could probably be disregarded in future reviews.The nature of this systematic review with its focus on settings where burden of disease is highest necessitates extensive searching of developing country sources. However, literature from developing countries is difficult to access and it is not well represented in MEDLINE or other well-known electronic databases ,14. An eThe value of LILACS database to improve the quality of systematic reviews has been previously reported . Our anaA limiting factor for identifying citations is related to late indexing of journals in electronic databases. Search strategies for this review were conducted in early 2003 to identify articles published in 2002 or earlier. While only few articles published in 2002 could be expected not to be in the databases by 2003, some articles published in 1997 were only appearing in the databases as late as 2003. Traditionally, EMBASE has been found to index faster than MEDLINE, thus supporting the argument to search multiple databases . FurtherThis systematic review involved significant financial and human resources over a 3-year period [1. In contrast with RCTs, guidelines for search strategy of systematic reviews of observational studies in general, and incidence/prevalence studies in particular, need to be developed.2. Searching beyond the major electronic databases such as MEDLINE or EMBASE is necessary to identify studies in journals from less developed countries.3. Regional databases indexing citations from local journals not reaching MEDLINE are especially relevant for this type of systematic review. They need to be fully functioning and made worldwide accessible. A network for accessing the full text of these articles would be helpful.The author(s) declare that they have no competing interests.APB, LS, AMG, TA and LH developed the search strategy for the systematic review. APB and LS analysed the data and wrote the manuscript. AMG, TA and LH participated in the interpretation of results and provided key comments on the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:Detailed search strategy for electronic databases used for the systematic review.Click here for file


Sub-national figures providing information about the wealth of the population are useful in defining the spatial distribution of both economic activity and poverty within any given country. Furthermore, since several health indicators such as life expectancy are highly correlated with household welfare, sub-national figures allow for the estimation of the distribution of these health indicators within countries when direct measurement is difficult.We have developed methods that utilize spatially distributed information, including night-time light imagery and population to model the distribution of income per capita, as a proxy for wealth, at the country and sub-national level to support the estimation of the distribution of correlated health indicators.A first set of analysis are performed in order to propose a new global model for the prediction of income per capita at the country level. A second set of analysis is then confirming the possibility to transfer the country level approach to the sub-national level on a country by country basis before underlining the difficulties to create a global or regional models for the extrapolation of sub-national figures when no country data set exists.The methods described provide promising results for the extrapolation of national and sub-national income per capita figures. These results are then discussed in order to evaluate if the proposed methods could not represent an alternative approach for the generation of consistent country specific and/or global poverty maps disaggregated to some sub-national level. Economy, income and poverty do affect and are affected by population's health in many ways.At broad scale, the macro relationship between life expectancy and the gross national product (GNP) is well known and has been presented in different publications .At a smaller scale a very robust relationship exist between an adult individual's income and that individual's health. This has been confirmed in the review done by Benzeaval and Judge  of sixteThe conclusion of another study performed in Tanzania  shows thIn return, high level of poverty also becomes an important factor of vulnerability for the population which becomes more exposed to diseases, especially infectious ones.By identifying the poorest area within a country it becomes possible to plan more effective intervention aimed at improving the health status of the population and therefore potentially reducing their level of poverty. As poverty tends to be clustered in specific places it is important to have access to disaggregated data. In addition to that, aggregated, national-level poverty data tends to mask sub-national variations .The development of variables that can be used as indicators of economic status is not straightforward. Even the measurement of the most basic of economic variables – such as national income levels – is fraught with problems. This reliable measurement of income is particularly problematic for low-income countries, given the lack of well-developed national income accounting methods and the large size of the "informal" sector in these economies. These problems are compounded when information is sought on the spatial and temporal changes in economic activity . Recent However, the use of self-reported income for measurement of economic status is widely regarded to be problematic . In a crFor all these reasons, most of the national household surveys, such as the World Bank's Living Standards Measurement Study (LSMS)  and manyIf sub-national level consumption figures are therefore available for most low income countries, through the use of these tools, the data they are producing is not comparable over countries making it impossible, for the moment, to build a consistent global map of poverty, or food insecurity, disaggregated to some sub-national level. In this context the growing uses of Geographic Information Systems (GIS) as well as the generation of new geocoded data sets might offer new perspectives in order to produce globally consistent poverty maps and help predicting the distribution of welfare at the sub-national level when reliable sub-national data are still not available. As the consumption indicators produced are not comparable over countries this attempt is done using income per capita expecting that this indicator might be comparable.In terms of data, satellite imagery is offering great potential for global data sets depicting weather patterns plus the physical and biological environment. If most of the data sensed concerns bio-physical parameters (e.g. clouds and vegetation...) there is one parameter, sensed by some satellites that can be used in the socio-economic context: night-time light.In their publications on the use of this parameter, Elvidge et al. -12 and ] compare2 and  coMore recently, an attempt to obtain a global map of socio-economic parameters at the sub-national level has been made by Doll et al. . In theiThe methodology presented in this paper follows a different approach, using other parameters in combination with light in order to directly predict GDP per capita and adjust the results to specific conditions. It also demonstrates the role played by other environmental and socio-economic factors on this prediction.The analysis performed at both the country and sub-national levels as well as the results obtained are presented in the coming sections.The objective of the country level analysis is to go beyond the observations done so far [-13 and ] and to The relationship between area lit and GDP shown by Elvidge et al. in 1997  has alreStarting from this result, a new set of analysis is performed using the different parameters described in the methods section. For the parameters stored in grids (light and surface area) the GIS tool is used in order to extract the figures based on the country delimitation.The first set of result are reported in Table - Logdp: log of the GDP figure (expressed in ppp)- Logdppc: log of the GDP per capita figures (expressed in ppp)- Lopopun: log of the UN population figures2)- Losurfli: log of the area lit - Losurfco: log of the surface area of the country  the relationship is expected to be linear in logs,b) if there is heteroskedasticity, the log form is one way to remove the problem,c) the parameters can be interpreted as elasticities if both the dependent and the independent variables are in logsThe following observation can then be extracted from Table 1) Three of the light parameters are correlated to each other . The forth one (lomeanf), not correlated to the previous ones, seems to contain a different information content connected to light,2) Apart from the mean frequency of light observation all the parameters are more highly correlated with GDP rather than with GDP per capita,3) There is no significant difference in the values obtained for expressing the correlation between the first three light parameters  and GDP. Lomeanf shows a lower correlation with GDP,4) Population presents a high correlation with GDP but none with GDP per capita. The same is observed for the surface area of the country,5) The correlation between the first three light parameter mentioned under point 1) and population is good which is not the case with the log of the mean frequency of light observation,6) A high correlation exists between the surface area of the country and the population.The above-mentioned observations seem to indicate that the high correlation coefficient observed between the 3 light parameters  and GDP is explained by the strong correlation between these parameters and population and the one between population and GDP. On the contrary the mean frequency of light observation shows a stronger correlation with GDP per capita. By predicting GDP per capita instead of GDP we therefore avoid any circularity in the model.Based on all the observation made it is decided to consider the use of the following variable in order to model GDP per capita at the country level:- the mean frequency of light observation as this variable present the highest correlation with GDP per capita,- the total frequency of light observation as this parameter provides the highest correlation with GDP per capita among the other three light parameters found to be correlated to each other . This parameter also contains more variability than the number of cells or the area lit which is an advantage when working with small areas that could be completely highlighted.- the total population and surface area of the country. Even if these parameters do not provide a good correlation with GDP per capita they are a necessary adjustment factor for the light and population variable (density).As the correlation between GDP per capita and the different variables may not be linear the correlation existing between the log of GDP per capita and the square of the log of these variables is analysed. This analysis shows that the square improves the prediction only for the two selected light parameters  which are used as additional variables, the square of the log of population and the surface area of the country being not used.From that point, 63 combination of the 6 variables kept for the analysis are tested in order to find a regression for modelling the log of GDP per capita at the country level. This is firstly done using the full data set, then trying to analyse the role of the climate and the one of the GDP composition by sector. Table The plot of the observed log of GDP per capita versus the predicted figures obtained with this regression as well as the plot presenting the residuals is reported in Figure The application of this model results in a significant over estimation of GDP per capita for 10 countries  and an under estimation for most of the high income countries presenting a GDP per capita figure higher than 12'500 US$. This can be better visualized by transforming the log of GDP per capita into GDP per capita figures for the 171 countries, creating a new graph Figure  similar Figure There are however some countries for which the model gives a good estimate of GDP per capita, such as Qatar (QAT), United Arab Emirates (ARE); Finland (FIN), Sweden (SWE), Monaco (MCO), Canada (CAN), Norway (NOR). Finally, the model gives a clear overestimation of GDP per capita for the United States of America (USA).The following explanation can be given for these countries:- "over lighting" due to an above-average wealth of the country ,- Two explanations are possible regarding the Nordic European countries that appears in this list  connected to the fact that the night-time light grid that is used in the context of this work is based on data collected during winter: a) specific climatic conditions during winter requiring excessive lighting of the infrastructure which may be at the origin of their location in the graph (the same observation is likely to be done for Canada). b) snow may be at the origin of an over estimation of income in these countries as snow makes lights look bigger and brighter than they appear in the no-snow condition.- The position of the United States in the graph is related to the fact that the square of the log of the total frequency of light observation is the highest observed in the entire sample. Several hypothesis are proposed in order to explain this situation. This includes the fact that light is more easily spread due to the big habitable surface, electricity is cheap and the road network very wide.The Root Mean Square Error (Root MSE) observed when applying this model is of 4000 US$. 27 countries are presenting an error higher than this value. The 5 countries with the highest error are: Luxembourg, Switzerland, Austria, Australia and Germany. The 5 lowest error are observed for: The Federal State of Micronesia, Burkina Faso, Haiti, Mali and Rwanda.Trying to improve the prediction of GDP per capita at the country level by including other variables we can observe that grouping the countries according to their agricultural level is giving better results than grouping them by climatic type.The figures given by the World Bank  or by thIn Figure - below 5 % (38 countries): lopopun, lotofre, losurfun (Adj R-squared: 0.5785)- between 5 and 10 % (28 countries): lopopun, lotofre, losurfun (Adj R-squared: 0.6289)- between 10 and 25 % (55 countries): lopopun lotofre2 losurfun (Adj R-squared: 0.5463)- above 25 % (49 countries): lopopun lotofre losurfun (Adj R-squared: 0.5512)We can observe the same combination of variables (lopopun lotofre losurfun) in 3 of the 4 grouping but the coefficients for each of these variables are significantly different.Figure From the 170 countries used in this analysis, 33 countries are presenting an error higher than the Root MSE (2877 US$). The 5 countries presenting the highest error are: Luxembourg, Australia, Switzerland, New Zealand and Singapore. The 5 lowest error are observed for: Chad, Somalia, Bangladesh, Iran and the Republic of Moldova.The sub-national level analysis has two objectives: to examine the possibility of applying the country level approach to the sub-national level on a country-by-country basis and to explore the possibility of generating global or regional models to be used for countries where sub-national data are either missing or are deemed to be unreliable.This analysis is based on the log of the same parameters successfully used at the country level. The population, total frequency and mean frequency of light observation as well as the surface area figures are extracted from the grids described in the methods section using the boundaries of corresponding sub-national administrative or statistical units.In order to keep the consistency with the values used for country level analysis, the sub-national figures for the population and the total frequency of light observation are adjusted by applying an homogeneous factor and rounding the resulting figures to the closest integer number.The analysis of the correlation factor existing at the sub-national level between each variables and GDP per capita (expressed in log) shows significant heterogeneity from one country to another. For few countries, some variables even appear as being not significant for the prediction of GDP per capita at the sub-national level. The list of variables observed in the country specific regression giving the best prediction vary therefore also from one country to another. In this case we do not look for models that were based on significant variables but take the one that is presenting the highest Adj R-squared value as the number of observation is generally low. The Adj R-squared obtained for these regressions varies from 0.2492 for The Netherlands to 1.00 for Portugal.This analysis indicates that it may be difficult to find a universal global or regional model that could be applied at the sub-national level. It is nevertheless important to underline the fact that at least one of the light variables is present in all the regression which is not the case for the population or the surface area of the sub-national units.For 3 countries  the high correlation existing between GDP and population seems to indicate that these sub-national figures have been generated using a linear model based on population only. This finding demonstrates that not all reported sub-national data are reliable and emphasizes the need for independent methods for generating sub-national estimates. The sub-national level data for these 3 countries are therefore taken out from the sample for all the analysis reported in this publication.Figure Table Among these 97 units, 31 are containing at least one city with a population larger than 1,000,000 inhabitants . Their presence in the list can be explained by the high concentration of buildings which represents vertical highlighted structures for which the satellite sensor is not able to capture the total intensity of the light being produced. This also confirms that in some countries the capital cities are more highly lit than their in country counterparts. Five other units contains oil and/or gas production infrastructure . The separation of the lights produced by gas flares from the city lights could be the explanation for the under prediction of income per capita in these units. The difficulty in these cases is to know if the income produced by this activity remains within the concerned unit or goes directly to the government or even outside the country. This observation is to be extended to the offshore infrastructures that should also be considered in the model.Even if no particular characteristics are identified for the remaining 61 units, these results illustrate the possibility to transfer the approach developed at the country level to the sub-national level on a country-by-country basis. This analysis also demonstrate the need to have income figures for some sub-national units in order to find the regression that provides the extrapolated figures for the remaining ones. This concerns units containing big cities  and units containing oil and/or gas production. Additional analysis have to be performed in order to make sure that these are the only cases or if other specificity also have to be taken into account.An out of sample analysis should also be performed in order to determine what is the smallest sample  necessary to obtain a regression providing prediction of acceptable quality.As the availability of disaggregated income data is very poor, and despite the observation made in the previous section regarding the heterogeneity of the country specific sub-national model, tests and analysis are done in order to see if it is possible to generate a model that would allow the generation of sub-national income per capita series for countries where no sub-national figures are available. Four approaches are used:- application of the country level model described in Table 2- generation of a model based on all the sub-national data (with and without country dummy)- generation of a model grouping the countries by climatic types- generation of a model grouping the countries by agricultural level using the GDP composition by sectorThe best results being obtained with the last approach, only this one is described in details in this section. For the other approaches only the major findings are reported.Applying the country level regression to the sub-national data set and presenting the results on a summary graph  gives an acceptable prediction for sub-national units presenting a GDP per capita figure bellow 5,000 US$. Above this limit the application of this approach under estimate GDP per capita. When we generate country specific graphs we can observe that the important variety of income per capita figures at disposal in the sample is in fact at the origin of the observation done earlier on the summary graph and not the result of a good prediction for each country considered in the sample. This emphasizes the need to make country specific graph for analysing the results.This analysis also demonstrates that applying the country level regression to the sub-national level may introduce an important quantitative error. In this regards, the attempt done by Doll et al. in their publication  should oWhen using the entire sub-national sample for generating one unique regression, the combination of variables giving the best results (Adj R-squared = 0.7692) is the same set found for the country level model  and is presenting an important advantage due to the existing correlation with the country level model we can not consider that the results obtained are of sufficient quality for applying it to other countries where we would not have any sub-national figures.Grouping the countries part of the sub-national data set by climatic types improves the prediction of GDP per capita for Bangladesh, France, India, The Netherlands, The Russian Federation, Sweden and Spain. This improvement mainly concerns sub-national units presenting an observed GDP per capita higher than 10,000 US$ and is not related to a particular climatic type.When the sub-national sample is grouped according to the percentage of GDP associated with agriculture in each country, using the same cut off point than for the country level analysis Figure , the fol- Below 5 % of GDP due to agriculture: Austria, Belgium, Finland, France, Germany, Portugal, Slovenia, Spain, Sweden, the Netherlands and USA,- Between 5 and 10 %: Argentina, Brazil, Greece, Mexico, Russian Federation and South Africa,- Between 10 and 25 %: China, Indonesia, and Thailand,- More than 25 %: Bangladesh, India and Mozambique.The regression found for each group (based on significant variables except for the country specific constant and the country dummy) are presenting an Adj R-squared varying from 0.5731, for the countries presenting a percentage of GDP due to agriculture between 5 and 10 %, to 0.8013 for the countries with a percentage higher than 25 %. Like for the grouping by climatic type, the list of variables found is different for each group. Figure Using this approach, 108 sub-national units are presenting a prediction error bigger than the Root MSE, which represent a mean percentage of units by country of 21 %. The countries for which this grouping induces a significant improvement of the prediction, compare to the models used previously, are: Bangladesh, India, Belgium, Spain, France, the Netherlands, Portugal, Slovenia, Sweden, USA, Finland and the Russian Federation which represents 5 more countries than when using the grouping by climatic types. We can also observe that this improvement does mainly concerns countries were agriculture represent less than 5 % of the country GDP. Only exceptions: Bangladesh, India and the Russian Federation.Even so, 3 of the countries for which the unique regression with dummy variable was not capturing the variability of GDP per capita before  are still presenting the same type of results.Due to the small number of observation for each grouping it is not possible to identify if a correlation exists between the residuals observed at the country level and the country specific sub-national constant making it difficult to generate a regional model for these groupings using the same approach than the one described previously Figure .This study demonstrates that night-time lights data are useful in generating estimates of both national and sub-national GDP per capita figures. Because night-time lights are produced with zero reliance on national reporting data, they provide an independent measure of economic activity.The country level results reported here confirm the conclusion given by Doll et al.  regardinBy introducing parameters other than area lit in the regression we have demonstrated the possibility of independent estimation of GDP per capita at the country level with a high level of confidence. This offers an interesting possibility for completing country level data sets for which data are missing or are in error. Special attention should nevertheless be paid to small densely populated territories with high level of lighting (e.g. Singapore and Monaco). In these areas, the models tend to underestimate GDP per capita as light produced by vertical infrastructures like high rise buildings fails to expand the area of lighting. This effect may be reduced if brightness information on the lights is available.The graph reported in Figure The result demonstrate that the approach developed for the country level can also be apply at the sub-national level but only through the generation of country specific models. Figure In this regard the possibility to generate country specific model for the extrapolation of sub-national income per capita figure is offering an interesting solution for countries where sub-national data on welfare are not available or where the application of other methods  would be difficult.Nevertheless, the fact that income per capita figures are necessary for some sub-national units in order to generate the country specific model represent a limitation to the application of this approach. If the analysis done in the context of this work already gives an indication of the type of units for which it would be necessary to have a good estimation of the income per capita figures additional work would be necessary in order to confirm this list, maybe add other type of units and also have a better indication regarding the minimum number of units for which input data are needed to insure a good prediction. In addition to that, further analysis are also needed in order to define the level of desegregation to which it would be possible to go based on the developed approach. It will finally be necessary to consider including the amount of light due to gas or oil production infrastructure in the model if the income they are producing stays within the sub-national units where they are located.Despite the caveats, the results obtained clearly demonstrate an interesting potential for making independent estimates of GDP per capita at the sub-national level especially for low income countries where the prediction obtained are of good quality and the need for them definitively the most important. Improving the data sets required to operationalize this approach may be far easier than improving the national reporting of sub-national economic data.It would nevertheless be important to compare the results obtained by this approach with other methods also producing sub national estimated using consumption indicators in the context of poverty mapping exercises [ and 17]17]]. In Trying to generate a consistent global or regional poverty map desegregated to some sub-national level, the grouping of the sample at disposal by climate or percentage of GPD due to agricultural level is definitively improving the prediction but does not provide us with a model generating consistent estimates for all the countries. Between these two grouping the preference again goes to the second one which improves the estimation for the middle and high income countries. The result obtained when applying this model to South Africa as well as the distribution of the prediction error expressed in percentages are reported in Figure In this regards, the analysis performed is not offering us the possibility to generate consistent global map showing the sub-national distribution of income per capita figures.These type of exercises are sorely needed to improve our knowledge regarding the health and well being of people in the poorest areas of the world. In this context night-time lights remain a useful data set for the evaluation of the impact of international efforts to improve the economic and therefore health conditions of these populations. It would therefore be important to pursue the type of work described in this paper and to see if the results obtained could not be improved.For both the country and the sub-national level model, the combination of the two groupings used in the context of this present work could for example improve the proposed models but this would have to be confirmed through additional analysis.The more recent global night-time light mosaic that NOAA has compiled is another element which might improve the results presented in the context of this work. This new global mosaic has the advantage of covering a longer period of observation (full years instead of the six month composite used in this study) which would improve the homogeneity of the distribution of the number of observation per pixel and also reduce the effect of the snow observed on images collected during winter. These new products were processed with major improvements in the exclusion of all but the highest quality segments of the individual orbits. They also include one information that was missing in the data set used for the context of this work: the digital number brightness of the lights. It has been found that adding in brightness of the lighting greatly improves the relationship to variables such as electric power consumption and GDP. Even if some difficulties to make products with brightness values remains, due to saturation in urban centers and the lack of on-board calibration, this new generation of grids could allow a significant improvement of the models described in the present paper. Another advantage of this data set is that the NGDC is producing a full global composite for each year from 1992 through 2004 allowing therefore for trend analysis.Before being able to test such new source of spatially distributed information it would be important to correctly address the question of the lack of documentation regarding the methods used for generating sub-national income estimates reported by individual countries in case this indicator would provide better results than consumption when trying to generate a consistent global poverty map. Inclusion of erroneous data may lead to misleading interpretations .Such discrepancies also underline the value of high quality geospatial data for use in making independent estimates of economic activity. This for example includes standardization of the basic vector GIS layers  in order to insure a proper use of the information collected at the sub national level or stored in different raster layers (night-time light and population for the present work). Among the different initiatives that are trying to answer the need for standardization in this area we can mention the Second Administrative Level Boundaries data set project (SALB). The first objective of this project is to create a redistributable Second Administrative Level Boundaries global data set (SALB) representative of January 2000 to be used with the GIS technology. The information finally collected has extended the period of representativity of the database for finally covering the period 1990-present. A process has also been put in place in order to insure the updates of the database in the future. You can find all the relevant information about this project as well as the data already available on the project web site [Finally, the shifts observed between all these layers of geographical distributed information is emphasizing the need for defining a "master" that could be used as a ground reference when generating or working with them. If the precision of its georeferencing is confirmed, the global mosaic of satellite images that are now publicly available (e.g the Landsat mosaic) could for example constitute this master.In order to perform the analysis at the country and at the sub-national level it was necessary to compile existing data sets on income as well as geographically distributed parameters that would be used to model these figures using a GIS. These concerns:- night-time light imagery- population- international and sub-national boundaries- surface area- climateThe data sets used for the context of this paper are presented now. In order to insure the consistency of the analysis, all the data sets compiled or created were adjusted to 1995, which is the year of representativity of the only night-time light grid available at the beginning of this research.We utilized GDP per capita data that have been collected at both the country and sub-national level. For the country level, GDP in International Dollars (GDP I$) for 171 countries have been calculated for the year 1996 from GDP figures expressed in local currency unit using price level data  and wereFor the sub-national level, GDP figures representative of the first or second administrative or statistical level have been collected for 26 countries (653 units) from the 5 continents Table . These fThe night-time light grid used has been provided by NOAA's National Geophysical Data Center (NGDC). This grid data set is the result of a 6-month 1 km resolution composite based on images collected between October 1994 and March 1995 by the U.S. Air Force Defence Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) . Only th- the number of cells highlighted at night- the area lit (surface area being highlighted at night) which is giving an indication of the extension of the highlighted surfaces,- the total frequency of light observation (obtained by adding the percents frequency of light detection observed in each cell on a given surface) which is giving an indication of the total intensity of the highlighting- finally, the mean frequency of light observation, in the highlighted areas, which gives us an indication of the dispersion of this intensity. For example: one pixel with a 100 % of light observation or 100 pixels with 1 % of light observation are giving the same value for the total frequency of light observation but a totally different figure for the mean frequency of light observation and area lit.These information being stored in a grid it is possible to extract them at the country or sub-national level for the analysis.Regarding population, the country level data that have been used are the UN population figures for the year 1995 . For theClimate is known to have an important influence on many elements on the earth surface, including human behaviour and well being , and alsFive major climatic types are recognized in this system, each type being designated by a capital letter (each of them being divided into sub types):A – Tropical moist climates: all months have an average temperature above 18 degrees celsius.B – Dry climates: with deficient precipitation during most of the yearC – Moist mid-latitude climates with mild wintersD – Moist mid-latitude climates with cold wintersE – Polar climates: with extremely cold winters and summersThe delimitation of the units of analysis , corresponding to the GDP figures collected for the context of this study, have also been prepared in a format that could be used in the GIS tool. In order to insure the consistency from one country to another the delimitation of the international borders has been adjusted to 1995.Finally, the surface area of the units of analysis has also been included in the data set.Two types of software have been used in analysing national and sub-national income: a Geographic Information System (GIS) and a statistical package. In order to take advantage of the specificity of the two modes of representation observed in the compiled data set (vector and raster) we have worked with the ArcView GIS software (version 3.2) for the vector part complemented by the Spatial Analyst extension (version 1.1) for the raster part. As no statistical analysis could be done directly in the GIS software the statistical support was provided by the STATA software (Version 5).


Arabidopsis LTR retroelements was identified and relative ages of full-length elements estimated showing that Pseudoviridae are much younger than Metaviridae. The distribution of retroelement insertions across the genome was shown to be non-uniform.The full complement of  Arabidopsis thaliana genome sequence makes it possible to comprehensively characterize retroelement populations and explore factors that contribute to their genomic distribution.Retrotransposons are an abundant component of eukaryotic genomes. The high quality of the A. thaliana long terminal repeat (LTR) retroelements using RetroMap, a software tool that iteratively searches genome sequences for reverse transcriptases and then defines retroelement insertions. Relative ages of full-length elements were estimated by assessing sequence divergence between LTRs: the Pseudoviridae were significantly younger than the Metaviridae. All retroelement insertions were mapped onto the genome sequence and their distribution was distinctly non-uniform. Although both Pseudoviridae and Metaviridae tend to cluster within pericentromeric heterochromatin, this association is significantly more pronounced for all three Metaviridae sublineages . Among these, Tat and Athila are strictly associated with pericentromeric heterochromatin.We identified the full complement of Athila and Tat sublineages of the Metaviridae. We predict that, like retroelements in yeast, the Athila and Tat elements target integration to pericentromeric regions by recognizing a specific feature of pericentromeric heterochromatin.The non-uniform genomic distribution of the Pseudoviridae and the Metaviridae can be explained by a variety of factors including target-site bias, selection against integration into euchromatin and pericentromeric accumulation of elements as a result of suppression of recombination. However, comparisons based on the age of elements and their chromosomal location indicate that integration-site specificity is likely to be the primary factor determining distribution of the  Endogenous retroviruses and long terminal repeat (LTR) retrotransposons  generally comprise a significant portion of higher eukaryotic genomes. Dismissed as parasitic or 'junk' DNA, these sequences have traditionally received less attention than sequences contributing to the functional capacity of the organism. This perspective has changed with the completion of several eukaryotic genome sequences. The contributions of retroelements to genome content range from 3% in baker's yeast to 80% in maize ,2. RetroArabidopsis thaliana and Drosophila melanogaster are clustered in pericentromeric heterochromatin ), where genetic distance is 1 - (percent identity/100) and the substitution rate is 1.5 × 10-8 [LTRs are identical at the time of retroelement integration, and so relative element ages were estimated from the percentage of identical residues shared between 5' and 3' LTRs for FLEs. The age formula used was 5 × 10-8 .A. thaliana NORs are located at the left (north) ends of chromosomes 2 and 4, and as these regions were only sample sequenced, their boundaries were assigned as the left ends of chromosomes 2 and 4. Heterochromatic knobs and pericentromeric regions were assigned as the outermost physical markers delimiting these regions, as determined by the studies listed above.Chromosome coordinates relative to the left (north) end were used to calculate distances between retroelements and heterochromatic domains. Heterochromatin boundaries were derived from -22 and iA. thaliana retroelement families by element category: reverse transcriptase only (R), full-length (F), and solo LTR (S).A RetroMap-generated datafile was used as the data source for statistical testing. The data file contains chromosomal element coordinates, LTR identity, age and lineage information for all p-value for a test whose null hypothesis is that all element categories of interest have the same chromosomal position distribution. This permutation approach is useful for the chromosomal position data because first, no distributional assumptions are required, second, differences in chromosomal position distributions other than simple location shifts are detectable, and third, the method is not as sensitive to outliers as common parametric approaches.For each element type and each chromosome, a Kendall-Sherman test -55 was cF-tests were used to check for interaction between these three factors and to assess the statistical significance of observed differences among the five chromosomes, among the four lineage/sublineage categories , and between elements inside and outside heterochromatin. The square root of age was used as the response variable in the age analysis so that the variance of the response would be roughly constant across categories defined by combinations of chromosome, lineage/sublineage, and location, as required for standard linear model analyses. Outlying observations were present, but the results of the analysis remained essentially the same with or without the outliers. Thus the reported results are based on the full dataset.For FLEs, linear model analyses were used to assess the effects of the factors 'chromosome', 'lineage/sublineage', and 'location' relative to heterochromatin on the response variable 'element age'. ) must be present. To enable searches for LTRs, NCBI's BLAST 2 Sequences must be locally installed.The following additional data are available with the online version of this article: a Microsoft Excel spreadsheet of data generated by RetroMap for each retrotransposon insertion identified; the data in this file was used for all statistical analyses (Additional data file A Microsoft Excel spreadsheet of data generated by RetroMap for each retrotransposon insertion identified; the data in this file was used for all statistical analysesClick here for additional data fileThe Java application used to generate the LTR and retrotransposon coordinates and to estimate retrotransposon agesClick here for additional data file


The development of miniature sensors that can be unobtrusively attached to the body or can be part of clothing items, such as sensing elements embedded in the fabric of garments, have opened countless possibilities of monitoring patients in the field over extended periods of time. This is of particular relevance to the practice of physical medicine and rehabilitation. Wearable technology addresses a major question in the management of patients undergoing rehabilitation, i.e. have clinical interventions a significant impact on the real life of patients? Wearable technology allows clinicians to gather data where it matters the most to answer this question, i.e. the home and community settings. Direct observations concerning the impact of clinical interventions on mobility, level of independence, and quality of life can be performed by means of wearable systems. Researchers have focused on three main areas of work to develop tools of clinical interest: 1)the design and implementation of sensors that are minimally obtrusive and reliably record movement or physiological signals, 2)the development of systems that unobtrusively gather data from multiple wearable sensors and deliver this information to clinicians in the way that is most appropriate for each application, and 3)the design and implementation of algorithms to extract clinically relevant information from data recorded using wearable technology. Journal of NeuroEngineering and Rehabilitation has devoted a series of articles to this topic with the objective of offering a description of the state of the art in this research field and pointing to emerging applications that are relevant to the clinical practice in physical medicine and rehabilitation. Understanding the impact of clinical interventions on the real life of individuals is an essential component of physical medicine and rehabilitation. While assessments performed in the clinical setting have value, it is difficult to perform thorough, costly evaluations of impairment and functional limitation within the time constraints and limited resources available in outpatient units of rehabilitation hospitals. Furthermore, it is often questioned whether assessments performed in the clinical setting are truly representative of how a given clinical intervention affects the real life of patients. While this observation has fostered a great deal of interest for the development and validation of outcome measures that largely rely on the use of questionnaires , researcA number of clinical applications of wearable systems in physical medicine and rehabilitation emerged in the past few years. They range from simple monitoring of daily activities, for the purpose of assessing mobility and level of independence in individuals, to integrating miniature sensors to enhance the function of devices utilized by patients to perform motor tasks that they would be otherwise unable to accomplish.Monitoring functional motor activities was one of the first goals of research teams interested in clinical applications of wearable technology. The focus was initially on using accelerometers -8 or a cA level of complexity was added when researchers started investigating motor disorders and the possibility of utilizing wearable technology to assess the effect of clinical interventions on the quality of movement observed while patients performed functional tasks. Two applications worth mentioning are the one to assess symptoms and motor complications in patients with Parkinson's disease -14 and tFinally, recent studies have been focused on integrating wearable, miniature sensor technology with orthoses, prostheses, and mobility assistive devices. Sensor technology is particularly appealing in these applications because it allows implementing closed-loop strategies that take advantage of the increased complexity and flexibility that robotics is contributing to the design of orthoses, prostheses, and mobility assistive devices. Namely, the characteristics of such devices can be constantly modified as a function of the task individuals are engaged into and environmental disturbances ,24.In all the emerging applications summarized above, either continuous recording of sensor data or at least monitoring over extended periods of time are necessary to design and implement an effective clinical intervention. Unobtrusive, wearable systems providing ease of data gathering and some processing capabilities are essential to achieve the objective of making the leap between the preliminary results obtained as part of the research carried on so far and the daily clinical practice of physical medicine and rehabilitation. Three areas of work are essential to achieve this objective: 1)the development of wearable sensors that unobtrusively and reliably record movement and other physiological data relevant to rehabilitation; 2)the design and implementation of systems that integrate multiple sensors, record data simultaneously from wearable sensors of different types, and relay sensor data to a remote location at the time and in the way that is most appropriate for the clinical application of interest; and 3)the development of methodologies to manipulate wearable sensor data to extract information in a clinically relevant manner to perform clinical assessments or control devices aimed at enhancing mobility in individuals with conditions that limit their level of independence. A series of papers have been assembled to provide the readership of Journal of NeuroEngineering and Rehabilitation with a description of the state of the art of the application of wearable technology in physical medicine and rehabilitation.A first set of the papers that have been assembled for publication on Journal of NeuroEngineering and Rehabilitation on the topic of wearable technology in physical medicine and rehabilitation has the objective of describing recent advances in wearable sensor technology. Two manuscripts describe attempts by different groups of measuring angular displacements for upper and lower extremity joints by embedding conductive fibers into the fabric of undergarments. The paper by Gibbs and Asada, entitled "Wearable conductive fiber sensors for multi-axis human joint angle measurements", reports encouraging preliminary results concerning monitoring lower limb joint displacements during ambulation by utilizing such technology. The manuscript by Tognetti et al, entitled "Wearable kinesthetic system for capturing and classifying upper limb gesture in post-stroke rehabilitation", describes the design and implementation of a system similar to the one proposed by Gibbs and Asada but geared toward monitoring movements of the upper extremities. The authors also explore the application of these wearable sensors to monitoring motor recovery in post-stroke individuals. Simone and Kamper focus their contribution on unobtrusively measuring finger movements in patients undergoing rehabilitation. Their manuscript "Design considerations for a wearable monitor to measure finger posture" summarizes the authors' recent work toward developing ways to record fine motor control tasks involving manipulation of objects requiring fine motor control of the hand and fingers. This technology has immediate application in patients such as post-stroke individuals undergoing rehabilitation that targets fine motor control skills. While initial research in the area of wearable technology was aimed at combining existing, miniature sensors with special fabrics or wireless technology, recent advances in this field have been focused on the development of sensing elements that can be even more easily embedded in clothing items. An example of such effort is reported in the paper by Dunne et al entitled "Initial development and testing of a novel foam-based pressure sensor for wearable sensing". This paper summarizes positive preliminary results by the research team aimed at measuring shoulder movements, neck movements, and scapular pressure. The sensing elements can also be used to monitor respiratory rate. Devoted to monitoring systemic responses is the last of the papers focused on wearable sensors. In this manuscript, Yan et al describe a new method to reliably measure heart rate and oxygen saturation. The paper is entitled "Reduction of motion artifacts in pulse oximetry by smoothed pseudo Wigner-Ville distribution" and demonstrates how advanced processing techniques may be necessary to derive reliable data when recordings are performed in the field.A second area of research relevant to the application of wearable technology in physical medicine and rehabilitation concerns the integration of wearable sensors into systems. Following the seminal work by Park and Jayaraman , severalA final set of papers is focused on applications that are relevant to physical medicine and rehabilitation. Sherrill et al describe in their paper entitled "A clustering technique to assess feasibility of motor activity identification in COPD patients via analysis of wearable-sensor data" a method to design classifiers of motor activities such as walking and stair climbing. The proposed technique relies on the examination of small datasets via clustering methods. Measures are derived from clusters associated with different motor activities to evaluate whether the set of wearable sensors and features derived from the recorded data are suitable to reliably identify the motor tasks of interest. Wang and Winters put the information gathered via wearable systems into a clinical context via processing that relies on neuro-fuzzy models. Their paper entitled "A dynamic neuro-fuzzy model providing bio-state estimation and prognosis prediction for wearable intelligent assistants" presents encouraging results indicating that the proposed method can put in the correct context dynamic changes observed in post-stroke individuals undergoing rehabilitation. Wang and Kiryu in their manuscript entitled "Personal customizing exercise with a wearable measurement and control unit" summarize their results on customizing machine-based exercise routines on the basis of physiological data that are continuously gathered from individuals performing such routines. Their results demonstrate the feasibility of a closed-loop system that optimally adapts workload. Dozza et al describe a wearable system designed to reduce body sway in individuals with severe vestibular problems. Their manuscript entitled "Influence of a portable audio-feedback device on structural properties of postural sway" summarizes positive results obtained with a prototype wearable system that utilizes audio-feedback to improve balance. Finally, Mavroidis et al describe how miniature sensor technology can be used to design a new generation of smart rehabilitation devices. Three devices are described in their paper entitled "Smart portable rehabilitation devices": a passive motion elbow device, a knee brace that provides variable resistance by controlling damping via the use of an electro-rheological fluid, and a portable knee device that combines electrical stimulation and biofeedback. These devices combine sensing technology and control strategies to enhance rehabilitation.This collection of papers provides an up-to-date description of the state of the art in the field of wearable technology applied to physical medicine and rehabilitation. The field is rapidly advancing and numerous research groups have already demonstrated applications of great clinical relevance. The potential impact of this technology on the clinical practice of physical medicine and rehabilitation is remarkable. A significant shift in focus is possible thanks to wearable technology. While the main focus of clinical assessment techniques is currently on methods that are implemented in the clinical setting, wearable technology has the potential to redirect such focus on field recordings. This is expected to allow clinicians to eventually benefit from both data gathered in the home and the community settings during the performance of activities of daily living and data recorded in the clinical setting under controlled conditions. Complementarities are expected between field and clinical evaluations. Future research will surely address optimal ways to combine these two types of assessment to optimize the design of rehabilitation interventions.


At sites of cell adhesion, proteins exist that not only perform structural tasks but also have a signaling function. Previously, we found that the Lipoma Preferred Partner (LPP) protein is localized at sites of cell adhesion such as focal adhesions and cell-cell contacts, and shuttles to the nucleus where it has transcriptional activation capacity. LPP is a member of the zyxin family of proteins, which contains five members: ajuba, LIMD1, LPP, TRIP6 and zyxin. LPP has three LIM domains (zinc-finger protein interaction domains) at its carboxy-terminus, which are preceded by a proline-rich pre-LIM region containing a number of protein interaction domains.scribble, is a member of the leucine-rich repeat and PDZ (LAP) family of proteins that is involved in the regulation of cell adhesion, cell shape and polarity. In addition, Scrib displays tumor suppressor activity. The binding between Scrib and LPP is mediated by the PDZ domains of Scrib and the carboxy-terminus of LPP. Both proteins localize in cell-cell contacts. Whereas LPP is also localized in focal adhesions and in the nucleus, Scrib could not be detected at these locations in MDCKII and CV-1 cells. Furthermore, our investigations indicate that Scrib is dispensable for targeting LPP to focal adhesions and to cell-cell contacts, and that LPP is not necessary for localizing Scrib in cell-cell contacts. We show that all four PDZ domains of Scrib are dispensable for localizing this protein in cell-cell contacts.To catch the role of LPP at sites of cell adhesion, we made an effort to identify binding partners of LPP. We found the tumor suppressor protein Scrib, which is a component of cell-cell contacts, as interaction partner of LPP. Human Scrib, which is a functional homologue of Drosophila Here, we identified an interaction between one of zyxin's family members, LPP, and the tumor suppressor protein Scrib. Both proteins localize in cell-cell contacts. This interaction links Scrib to a communication pathway between cell-cell contacts and the nucleus, and implicates LPP in Scrib-associated functions. At the heart of structural and functional integrity of multicellular entities is the ability of each and every cell of it to successfully integrate signals arising from soluble factors, cell-substratum adhesion and cell-cell adhesion . CorrectA protein that may play a role in these processes is the LPP (Lipoma Preferred Partner) protein . LPP is LPP gene, as being the preferred translocation partner of the HMGA2 gene in a subgroup of lipomas, which are benign tumors of adipose tissue . ReDrosophila Scribble, a tumor suppressor that plays a role in the regulation of cellular adhesion, cell shape and polarity -methionine-labelled full length human Scrib protein, or a portion of the human Scrib protein encompassing all four PDZ domains (amino acids 616–1490) (wild-type or mutated) in NENT100 buffer . This mixture was tumbled overnight at 4°C. Subsequently the beads were washed 5 times in 500 μl NENT100 buffer, resuspended in 25 μl SDS-PAGE sample buffer and incubated at 95°C for 5 minutes. Proteins were separated by SDS-PAGE and interacting Scrib was detected by autoradiography.All in vitro translation reactions were carried out using the TNT T7 Quick Coupled Transcription/Translation System (Promega) following the manufacturer's instructions. For GST pull-down assays, bacterial expression constructs were made using pGEX-5X vectors (Amersham-Pharmacia Biotech) directing the synthesis of glutathione S-transferase (GST) fusion proteins containing wild-type or mutated forms of human LPP. These fusion proteins were purified according to manufacturer's instructions and verified by SDS-PAGE. GST fusion proteins or GST alone, bound to glutathione-agarose beads, were incubated with in vitro synthesized [1612CSSRRPVRPGRRGLGPVPS1630 . For the detection of endogenous LPP in MDCKII cells, a LPP-specific monoclonal antibody was used . For the detection of GAL4-fusion proteins in immunocytochemistry, a rabbit polyclonal anti-GAL4 DNA-binding domain antibody (Tebu Bio) was used. Vinculin was detected in cells with a monoclonal anti-vinculin antibody , Xpress-tagged proteins with a monoclonal anti-Xpress antibody (Life Technologies). Fluorescently-tagged Alexa-antibodies (Molecular Probes) were used as secondary antibodies for immunofluorescence detection.The Scrib-specific polyclonal antiserum Scrib-472 was prepared by Eurogentec by immunization of rabbits with a keyhole limpet hemocyanin (KLH) coupled peptide Eukaryotic cell extracts were prepared by harvesting the cells in PBS , and subsequent lysis of the cell pellets in SDS-PAGE sample buffer . Protein concentrations in cell extracts were determined using BCA Protein Assay Reagent (Pierce) according to the manufacturer's instructions. 30 μg of proteins of each cell extract were loaded on 5% SDS-polyacrylamide gels. After size-separation, proteins were electrophoretically transferred to PROTEAN Nitrocellulose Membranes (Schleicher and Schuell). ECL Western blotting was performed using Western Lightning Chemiluminescence Reagent Plus (Perkin Elmer Life Sciences) according to the supplier's instructions.2 and 0.1 mM MgCl2 (PBS++). For GFP-fluorescence, slides were mounted in vectashield mounting medium  and analyzed on a Zeiss Axiophot fluorescence microscope equipped with an RT slider SPOT camera  using SPOT RT Software v3.4, or by confocal microscopy . For indirect immunocytochemistry, after fixation, quenching was performed by incubating the cells for 10 minutes at room temperature in PBS++ containing 50 mM NH4Cl. Cells were then permeabilized with 0.4% Triton-X-100 for 5–10 minutes at room temperature. Unspecific binding was blocked with 0.5% Blocking Reagent (Roche) in PBS++ for 30 minutes at room temperature. Subsequently, the slides were incubated with primary antibodies for 1 hour at room temperature. After washing the cells three times in PBS++, bound primary antibodies were detected with fluorescently labelled secondary antibodies (Molecular Probes) for 30 minutes at room temperature. Following three washes in PBS++, slides were mounted and analyzed as described for GFP-fluorescence.CV-1 or 293T cells seeded on glass coverslips, and MDCKII cells seeded on glass coverslips or on Transwell-Clear polyester membranes  were fixed in 4% formaldehyde for 20 minutes at room temperature followed by three washes in PBS containing 0.1 mM CaClMMRP designed the study, performed the yeast and mammalian two-hybrid experiments, as well as the mitochondrial targeting experiments, made the LPP-stable cell lines, performed the confocal microscopy with these cell lines, and prepared the manuscript. SMPM constructed most of the DNA constructs, made the Scrib-stable cell lines, performed the epifluorescence microscopy with these cell lines, and carried out the Western blotting experiments. PA performed the GST pull down experiments, and contributed to the characterization of the Scrib-472 antibodies. TAYA contributed to the establishment of a full length Scrib cDNA clone, and to the writing of the manuscript. EJ contributed to the development of the Scrib-472 antibodies, to the establishment of a full length Scrib cDNA clone, and to the funding of the project. WJMVDV contributed to the writing of the manuscript and to the funding of the project.