Many patients with chronic heart failure (CHF), a common condition with high morbidity and mortality rates, receive treatment in primary care. To improve the management of CHF in primary care, we developed an implementation programme comprised of educational and organisational components, with support by a practice visitor and focus both on drug treatment and lifestyle advice, and on organisation of care within the practice and collaboration with other healthcare providers. Tailoring has been shown to improve the success of implementation programmes, but little is known about what would be best methods for tailoring, specifically with respect to CHF in primary care.We describe the study protocol of a cluster randomised controlled trial to examine the effectiveness of tailoring a CHF implementation programme to general practices compared to a standardised way of delivering a programme. The study population will consist of 60 general practitioners (GPs) and the CHF patients they include. GPs are randomised in blocks of four, stratified according to practice size. With a tailored implementation programme GPs prioritise the issues that will form the bases of the support for the practice visits. These may comprise several issues, both educational and organizational.The primary outcome measures are patient's experience of receiving structured primary care for CHF , patients' health-related utilities (EQ-5D), and drugs prescriptions using the guideline adherence index. Patients being clustered in practices, multilevel regression analyses will be used to explore the effect of practice size and type of intervention programme. In addition we will examine both changes within groups and differences at follow-up between groups with respect to drug dosages and advice on lifestyle issues. Furthermore, in interviews the feasibility of the programme and goal attainment, organisational changes in CHF care, and formalised cooperation with other disciplines will be assessed.In the tailoring of the programme we will present the GPs a list with barriers; GPs will assess relevance and possibility to solve these barriers. The list is rigorously developed and tested in various projects. The factors for ordering the barriers are related to the innovation, the healthcare professional, the patient, and the context.CHF patients do not form a homogeneous group. Subgroup analyses will be performed based on the distinction between systolic CHF and CHF with preserved left ventricular function (diastolic CHF).ISRCTN18812755ISRCTN:  Chronic heart failure (CHF) is a highly prevalent chronic disease with high morbidity and mortality rates. The prevalence of CHF in the Western world is 1% to 2% in the general population and at least 10% among the age group of 85 years and older . High moe.g., diabetes, COPD and depression -- but at present not for CHF, though several disease management programmes exist for CHF related to outpatient clinics. As a substantial proportion of CHF patients do not attend such clinics but visit their GP instead, these patients are not enrolled in a structured care programme.A large group of patients with CHF receive treatment in primary care. There are many programmes for the management of long-term conditions in primary care -- To improve the management of CHF in primary care, we have developed an implementation programme, comprising both educational and organisational components, the latter aimed at improved and structured care. We pilot tested this programme in 19 general practices . The pilApart from offering a standard implementation programme, another approach is to tailor an intervention to the special needs and conditions in a general practice. Ideally, tailoring has three components: identification of factors associated with implementation (or labelled as 'barriers to change'), to match implementation interventions to those factors, and evaluation of the tailored implementation programme. Tailoring has been shown to have a modest effect on the success of the implementation programme , but litPatients being clustered in practices, we planned to conduct a cluster randomised controlled trial with randomisation at the practice level. The aim of the study will be to examine the effectiveness of tailoring the implementation programme to general practices compared to a standardised way of delivering the implementation programme to general practices.The project will be a collaborative project of IQ healthcare, a research department of Radboud University Nijmegen Medical Centre, and the four regional supportive structures for primary care ('ROS') in the south of the Netherlands and their cooperative bond Robuust. The medical ethical committee (CMO Regio Arnhem -- Nijmegen) assessed the study proposal and waived approval.The study population will consist of 60 general practitioners (GPs) and the CHF patients they will include. GPs will be recruited in the south of the Netherlands, contacted either directly or indirectly via various regional organisations by advisors of the regional supportive structures for primary care. GPs will be informed about the project, and when they agree to participate they will be instructed to send in an admission form with data on practice organization necessary for stratification and randomization.Evidence of change will be assessed by studying the effects of the intervention on patients with CHF registered with the participating GPs. As in the pilot , GPs wilThe implementation pack contains educational materials for the professionals and patients. There is a recommended protocol for multidisciplinary management and a template for clinical care presented as a guiding registration form. Furthermore, we offer support by a visiting practice consultant and the possibility to contact a GP with a special interest in CHF management.e.g., dieticians and physiotherapists, and these professionals will be informed about the project, encouraging the role of the multidisciplinary team in CHF management. The paragraph on non-pharmaceutical treatment was enlarged and the pharmaceutical paragraph had some changes. Now, recommendations on drug treatment are different for patients with systolic CHF compared to patients with a preserved systolic heart function, so called diastolic CHF  and health-related utilities (EQ-5D), and of drug prescriptions.PACIC is a questionnaire consisting of 27 items, which is related to the Chronic Care Model . We tranDrug prescription scores are assessed using the guideline adherence index (GAI), indicating the proportion of indicated drugs that is prescribed ,28. ThesSecondary outcome measures at the patients' level concern lifestyle advice and medication during the study period, based on the patient registration forms providing information on non-pharmaceutical advice and drug prescriptions, continuity of care, and medication adherence. Considering drug therapy we will assess the percentages of ACE inhibitors and beta blockers prescribed in the evidence-based target dosages. Secondary outcome measures at the practice level are goal attainment and qualitative assessment of the programme, focussing on the subjective GP's experiences, for instance on improvement of practice organisation and collaboration with other primary care professionals.The study will be a randomised controlled trial, with a one-year follow-up period. Practices are stratified according to practice size as solo, duo, or group practice. On inclusion, practices are assigned to one of the study groups using randomisation in blocks of four per stratum by a research assistant. Blocks were generated electronically with the help of a statistician. The randomising procedure itself is concealed for practices, consultants, and researchers . The regional advisors including the practices have no access to the randomisation process. After randomisation, both the practice and the regional advisor are informed. The intervention is open to all involved.The primary analysis is a comparison of primary outcomes at follow-up between the study groups, taking into account clustering of patients within practices. Multilevel regression analyses will be used to explore the effect of practice size and type of intervention programme. In addition, we will examine both changes within groups and differences at follow-up between groups with respect to percentage of patients on the maximum tolerated dosage of ACE inhibitor or angiotensin II receptor blocker and of beta blockage; medication completely according to the guideline; having received influenza vaccination in the winter season 2010-2011; having received professionally guided physical activity training; and the number of non-pharmaceutical issues addressed. If possible, subgroup analyses will comprise type of CHF (systolic or diastolic) and diagnostic certainty  The interviews will be used to assess the feasibility of the programme and goal attainment, organisational changes in CHF care, and formalised cooperation with other primary care disciplines and specialist care.Power calculations are based on the primary outcome measurement PACIC. The PACIC comprises 27 questions with an answering scale from 1 to 5. A previous unreported study showed that its standard deviation was 1.0. To detect a difference of 0.3 points with a standard deviation of 1 , with alpha = 0.05 and beta = 0.20, ICC = 0.05, a total of 51 practices with 10 patients each would be required, or 59 practices with 8 patients.Practice inclusion is planned from June until October 2010. After inclusion, practices participate in the programme during one year. At the start of the year, the GPs include all their patients with CHF they treat at least in part themselves. During that year, patients with newly diagnosed CHF can also be included. Data management in the patient registration forms is a continuous process during the project year. After the project period of a year, the forms are anonymised and sent to the researchers coded. Furthermore, practices will send coded patient questionnaires with explanation of the survey and ask for an informed consent; these will be returned to the researchers. Finally the researchers will contact the GPs participating for the telephone interview. The GPs will receive feedback based on the patient registration forms and the questionnaires.There exist various classifications of barriers (and facilitators) and multiple approaches for linking interventions to barriers -31. In tSeveral studies were conducted to assess the effect of tailoring implementation. In a systematic review, the authors conclude that identifying barriers and tailoring intervention to these barriers may improve clinical practice compared to no intervention and to guideline dissemination. In their meta analysis including eight studies identified with a non-tailored intervention in the control group, they report a modest effect of tailoring .All data collection will take place at the end of the project period. Within the context of the evaluation of the implementation project, it is not feasible to have data collection both at the start and at the end, but the patient registration form will have baseline data on treatment issues. This also will allow for within group analyses, giving information about the effectiveness of both implementation strategies separately. Unfortunately, this data collection, either paper based or electronically, will require additional administrative actions from the practices. Enabling data collection from the electronic medical record will be beyond the scope of this project. Considering the patient questionnaire's results, with one measurement at the end, this restricts us to intergroup analyses.Our sample size is based on power calculation considering the PACIC outcomes. In previous research, a difference of 0.5 was found in the evaluation of a CHF and a diabetes programme ,33. ThusDrug prescription is also a primary outcome measure. We will present the GAI as a measure for the percentage of indicated drugs prescribed. In previous research, many patients appeared to receive suboptimal dosages. When considering ACE inhibitors and beta blockers, we will report on the percentage of prescriptions in the indicated, high-target dosages .We decided to stratify practices included based on practice size. There is some evidence of a relation between practice size and quality of care ,37. In oCHF patients do not form a homogeneous group; apart from aetiology, we make a distinction between systolic CHF and CHF with preserved left ventricular function (diastolic CHF). In our study, both patient groups may be included, as the practice guideline gives recommendations for both the patients with and without left ventricular systolic dysfunction. Subgroup analyses will be performed.Michel Wensing is an Associate Editor of Implementation Science. All decisions on this manuscript were made by another senior Editor. The authors declare that they have no competing interests.JvL and MW designed the study; JvL drafted the materials concerning the content; BS and MK made essential contributions to the design and the devolvement of the materials and the practical implications. JvL drafted and revised the manuscript; MW, BS, and MK commented it critically. All authors approved the final version of the manuscript.


Approximately 287,000 women die of causes related to pregnancy and childbirth every year. While effective interventions exist to prevent maternal death, high quality impact evaluations for these interventions are often lacking.We conducted a Delphi process consisting of three rounds in which we asked maternal health experts to provide effectiveness estimates for 31 intervention-cause of death pairs relating to maternal mortality. Anonymous feedback in the form of medians and histograms for each question was given to experts following the first and second rounds. A diverse panel of 37 experts completed all three rounds, for a final response rate 80.4%.This Delphi process produced a total of 31 effectiveness estimates for key maternal interventions on cause-specific maternal mortality. Overall, many interventions had high estimated effectiveness, with the majority of interventions having effectiveness estimates above 70%. Where possible, the estimates of effectiveness of interventions were compared to previous efforts and in general there was strong agreement between the estimates in this exercise as compared to those of earlier efforts.There are many maternal health interventions with high estimated effectiveness that, with expansion of effective delivery channels, have the potential to have a large impact on reducing maternal mortality worldwide. Every year, approximately 287,000 women die of causes related to pregnancy and childbirth worldwide, with nearly all of those deaths occurring in low- and middle-income countries . While eWe set out to conduct this Delphi analysis to generate the best estimates for specific interventions on causes of maternal death, and to use these estimates to update the maternal model in the Lives Saved Tool (LiST) in light of the World Health Organization (WHO)’s new cause of death structure for maternal mortality . LiST isThe Delphi method, developed by the RAND Corporation in 1948, is a method by which consensus is achieved through an iterative process by a panel of experts. The method was originally developed in defense research for scientific and technological forecasting purposes. Essential components of the Delphi method include anonymous response, iteration and controlled feedback, and a statistical definition of consensus . It has Previously, WHO sponsored a Delphi exercise to estimate the impact of interventions on maternal and neonatal mortality . The purpose of WHO’s previous Delphi analysis was to identify areas of consensus and disagreement regarding the efficacy of newborn and maternal health interventions, with the ultimate goal of evaluating the cost-effectiveness of these interventions . The estimates of effectiveness along with others generated within the CHERG framework  were useIn this paper, we describe the process by which these consensus estimates were generated and discuss the key findings of this Delphi analysis. In addition, we outline how these results will be incorporated into the maternal model in LiST. It is important to note that this study does not constitute a literature review or meta-analysis, but rather presents a series of effectiveness estimates generated through an iterative process involving a group of experts in maternal health.We identified 90 international experts in maternal health and contacted them by email for participation in this study. The original set of experts we contacted was selected by identifying researchers who had worked with the CHERG and asking those people to suggest other participants. The pool also included some experts in maternal health who had participated in a prior Delphi panel with WHO. We tried to ensure diversity in professional experience and in geographic background, and to achieve a mix of experts in public health research and clinical work, and those with familiarity or experience in global health.Of the 90 experts we contacted, 46 completed the initial questionnaire. The response rate for round one was 100% by definition. Four experts declined to participate, and 40 did not respond. 40 of the 46 experts who completed the round one questionnaire completed round two, for a response rate of 87%. The final response rate was 82.6%, with 38 out of the original 46 experts completing the third round. One of these 38 experts completed the third round, but did not complete the second round.Of the experts who completed the round one questionnaire, a slight majority were female. Expert panel members represented 22 different nationalities and worked in every region of the globe.The expert panel was comprised primarily of obstetricians and researchers, with nurse/midwives also being represented. In addition to being physicians and nurses, 11 clinical experts identified themselves as researchers, and three identified education as a secondary profession. A majority of the experts had medical degrees, and many had more than one degree  of 20 percentage points or fewer. The median response was used as the final effectiveness estimate.We first conducted an analysis to characterize changes in effectiveness estimates and the degree of consensus across rounds. We then present the resulting effectiveness estimates for each intervention-cause of death pair across all rounds.The median change in response for all responses for all questions was 0  percentage points from round one to round two, ranging from -85 to 78. The median change was 0  percentage points from round two to round three, ranging from -53 to 95. The IQRs for all intervention-cause of death pairs diminished from round to round. The IQRs in round one ranged from five to 63.75, with a median IQR of 36.25 . The IQRs in round two ranged from five to 41.25, with a median of 20 . In round three, the median IQR of all the pairs was 15 , ranging from 3.75 to 30.4 . Safe abortion services and post-abortion care were both estimated to be highly effective against deaths due to abortion , and ectopic pregnancy case management had a comparably high estimated effectiveness against ectopic pregnancy deaths (90% effectiveness). Parenteral antibiotics and packages that include them  were more effective than clean delivery practices or blood transfusion against deaths due to pregnancy-related sepsis according to our estimates  (90% effectiveness) as compared to BEmOC (40% effectiveness). Caesarean section and CEmOC had the highest estimated effectiveness against obstructed labor deaths , and packages of interventions such as active management of the third stage of labor (AMTSL) (70% effectiveness), BEmOC (75%), and CEmOC (90%) were highly effective against deaths due to postpartum hemorrhage (PPH). Finally, intermittent preventive treatment in pregnancy (IPTp)/insecticide-treated nets (ITNs) and malaria case management had moderately high effectiveness estimates against malaria-specific maternal deaths , and adult antiretrovirals (ARVs) had an effectiveness estimate of 70% against maternal deaths due to HIV. Interestingly, CEmOC not only had high estimated effectiveness against five causes of maternal death , but the uncertainty for the effectiveness of CEmOC against these causes of death was also low, with IQRs of 10 or narrower for all five estimates.4, which can be delivered at small community health centers as opposed to hospitals, are estimated to be very effective against maternal death due to a variety of causes. These results suggest that the next step in combating maternal mortality may be to develop better ways to deliver these interventions to communities that are the most in need, as opposed to developing and testing new interventions. With regard to group agreement, the IQRs for nearly all intervention-cause of death pairs decreased across rounds, indicating consistent movement toward consensus. By the final round, a total of four intervention-cause of death pairs had an IQR of effectiveness estimates greater than 20 percentage points, although none of these had an IQR greater than 30 percentage points. Two of these pairs were related to HDPs and are discussed later. One of these pairs asked for the effectiveness of clean delivery practices on maternal deaths due to pregnancy-related sepsis. As clean delivery practices are an intervention more often associated with newborn health, experts may have been less familiar or confident in their ability to assess the impact of this intervention on maternal mortality. It is also interesting to note that while the IQR of the estimates of effectiveness did get smaller over the rounds, the mean and median point estimates did not change by a large degree for most intervention-outcome pairs.Overall, most interventions showed high estimated effectiveness, suggesting that there are many highly-effective interventions to prevent maternal death. Even interventions such as MgSOThere are several strengths to our study that likely enhance the validity of our results. First, a diverse panel of experts participated in this Delphi process, representing multiple professions, 22 different nationalities, and working in many countries in all regions of the world. This diversity promotes a more predictive and valid consensus in studies related to health . Further4 on deaths due to HDPs, this affected fraction will be multiplied by the effectiveness of that intervention on pre-eclampsia/eclampsia in order to determine the number of maternal deaths prevented within the larger category. In addition, in the case of packages such as BEmOC, LiST users will have the option to scale up certain individual interventions within the package or to scale up the entire intervention package as a unit.The estimates generated from this Delphi analysis, in conjunction with estimates generated from other sources, will be used in the maternal mortality model in LiST. Each intervention-cause of death pair and the corresponding effectiveness estimate from this Delphi process will represent a link in the model, and all pairs described in this paper will be included in the final model. We will structure the model using the most recent WHO maternal cause of death categories as a framework . In inst4, and CEmOC for treatment of pre-eclampsia and eclampsia, and hypertensive drugs and induction of labor for the treatment of HDPs. The results of this review are largely consistent with the results of our Delphi process  after the final round. Ronsmans and Campbell report that while antihypertensive drugs halve the risk of developing severe hypertension, their effect on mortality is unclear due to lack of quality evidence. In addition, they conclude that while induction of labor is effective in reducing adverse maternal outcomes, it is impossible to assess the consistency of the effect of induction of labor on HDP mortality based on current evidence . While several factors limit our ability to directly compare these two analyses, the results of these two Delphi processes are overall consistent and confirmatory  than that for AMTSL (70%). AMTSL is a package that includes uterotonics, controlled cord traction, and manual removal of the placenta; thus, we would expect that AMTSL would have the same or higher effectiveness on PPH than uterotonics in isolation. Similarly, the effectiveness estimate for parenteral antibiotics, a component of BEmOC, on pregnancy-related sepsis, was higher (80%) than that for BEmOC (70%). While these inconsistencies are important to be aware of, in both cases, the differing effectiveness estimates are within their respective limits of uncertainty. For this reason, we have chosen to include these pairs in our model despite the inconsistencies. Furthermore, the fact that we were able to identify these inconsistencies shows a benefit to our approach in that had we only asked about packages as a whole, these differences would not have been identifiable. In order to handle these inconsistencies in the model, we will use the higher effectiveness value of the individual component to represent both the effectiveness of that component and the package contained within.There are several limitations to our methodology. An important limitation of the Delphi method lies in the method for defining consensus. While there has been considerable discussion surrounding this issue, there seems to be little agreement as to how to define consensus . Thus, tThe maternal mortality and other models used in LiST are constantly evolving, requiring periodic updating to incorporate new and emerging evidence. In addition, it may be important to include certain risk factors such as anemia in future maternal models, which may impact maternal survival by affecting multiple causes of maternal death simultaneously.The results of this Delphi process suggest that there are many existing maternal health interventions with high estimated effectiveness. With the expansion of effective delivery channels, existing interventions have the potential to have a large impact on reducing maternal mortality worldwide.AMTSL: Active Management of the Third Stage of Labor; APH: Antepartum hemorrhage; ARVs: Antiretrovirals; BEmOC: Basic Emergency Obstetric Care; COD: Cause of death; CHERG: Child Health Epidemiology Reference Group; CEmOC: Comprehensive Emergency Obstetric Care; HDP: Hypertensive disorders/diseases of pregnancy; ITNs: Insecticide-treated nets; IPTp: Intermittent preventive treatment in pregnancy; IQR: Interquartile range; LiST: Lives Saved Tool; PPH: Postpartum hemorrhage; UNICEF: United Nations Children’s Fund; WHO: World Health Organization.The authors have no competing interests to declare.SLP participated in the design of the study, coordinated the Delphi process, conducted the analyses, and drafted the manuscript. MM participated in the design and coordination of the study. NW conceived of the study, participated in its design and coordination, and helped to draft the manuscript. All authors read and approved the final manuscript.


In the scientific biodiversity community, it is increasingly perceived the need to build a bridge between molecular and traditional biodiversity studies. We believe that the information technology could have a preeminent role in integrating the information generated by these studies with the large amount of molecular data we can find in bioinformatics public databases. This work is primarily aimed at building a bioinformatic infrastructure for the integration of public and private biodiversity data through the development of GIDL, an Intelligent Data Loader coupled with the Molecular Biodiversity Database. The system presented here organizes in an ontological way and locally stores the sequence and annotation data contained in the GenBank primary database.The GIDL architecture consists of a relational database and of an intelligent data loader software. The relational database schema is designed to manage biodiversity information (Molecular Biodiversity Database) and it is organized in four areas: MolecularData, Experiment, Collection and Taxonomy. The MolecularData area is inspired to an established standard in Generic Model Organism Databases, the Chado relational schema. The peculiarity of Chado, and also its strength, is the adoption of an ontological schema which makes use of the Sequence Ontology.The Intelligent Data Loader (IDL) component of GIDL is an Extract, Transform and Load software able to parse data, to discover hidden information in the GenBank entries and to populate the Molecular Biodiversity Database. The IDL is composed by three main modules: the Parser, able to parse GenBank flat files; the Reasoner, which automatically builds CLIPS facts mapping the biological knowledge expressed by the Sequence Ontology; the DBFiller, which translates the CLIPS facts into ordered SQL statements used to populate the database. In GIDL Semantic Web technologies have been adopted due to their advantages in data representation, integration and processing.Entries coming from Virus , Plant  and Invertebrate  divisions of GenBank rel.180 have been loaded in the Molecular Biodiversity Database by GIDL. Our system, combining the Sequence Ontology and the Chado schema, allows a more powerful query expressiveness compared with the most commonly used sequence retrieval systems like Entrez or SRS. We are living an historical moment characterized by deep changes in the life sciences due to the widespread use of new technologies. The huge production of molecular data obtained by high-throughput technologies are moving the research groups from "reductionist approach" to "holistic approach" studies.For example, in the biodiversity domain, several researchers analyze molecular data obtained by high-throughput DNA sequencing technology and compare them with morphological and geographical data obtained by classical methods ,2.So new challenges arise in biology and the need for transforming large volumes of raw data into usable knowledge about our world and its inhabitants emerges. This transformation poses significant challenges that necessitate the assistance of automated methods. The organization of biological information from an array of resources into consolidated knowledge bases for subsequent archival and research purposes is a significant informatics task. Recent advances in information technology are creating a revolution in the way the biology data are organized, stored, integrated and distributed towards the development of testable hypotheses ,4. SeverThe centralization of heterogeneous data into a single resource is one of the possible solution as it can enable a range of comparative studies, can help the integration of locally produced data with bioinformatics public databases and can facilitate the computation of millions of data records carried out by modern bioinformatic software.In the bioinformatics community, centralized systems like the Entrez system  at NCBI To overcome this issue we have built an intelligent loading system (GIDL) that allows to extract, transform and store data in a target database schema, implementing a knowledge base constituted by public NCBI GenBank  entries Other similar applications are available in the bioinformatics community, like Biospida  or varioThe system described in this paper addresses some of the aims of the Molecular Biodiversity Laboratory (MBLab) project , a privaTarget Database Schema, dedicated to store ontology-driven information extracted from GenBank, and by the Intelligent Data Loader (IDL), the core component which parses, adds semantics and populates the database. Most of the software implementation has been done in JAVA language, whereas we used Relational Database Management System (DBMS) to implement the Target Database Schema.The overall GIDL architecture is composed by the A relational data model is used to represent all the information extracted from GIDL. The schema is designed considering all the biological entities involved in the molecular biodiversity domain. In this paper we refer to the Target Database Schema as Molecular Biodiversity Database schema. It encompasses four main areas: MolecularData, Experiment, Collection, Taxonomy. This schema is a part of a more extensive logical schema built by our group, in the MBLab project, to store and integrate public and private biodiversity data.As depicted in Figure The Molecular Biodiversity Database schema design is inspired by international standards used in the molecular biodiversity domain. The BOLD Barcode of Life Data System (BOLD)  schema hIn order to represent the semantic information related to biological sequences, Chado makes use of the Sequence Ontology (SO) , an accuThe proposed Molecular Biodiversity Database schema, according to Chado concepts, uses the same table for all different types of features, and uses the SO as a typing system, that is, it stores sequence features replaced by the corresponding SO terms. Sequence features info, SO terms and sequence features/SO terms mapping are stored in three different tables; the use of the latter guarantees that any future mapping change will not impact the sequence features and SO terms tables. Other sequence annotations (attributes) are stored in another table and mapped to SO too. In the schema implementation, each SO term is represented as a record in the OntologyTerm table. Another important table is the SequenceFeature table: its identifier constitutes a foreign key for tables storing feature annotations, feature evidences and relationships between annotations and evidences.part_of relationship, uses a subsumption hierarchy to describe the feature types and a meronomy  to describe their part-whole structures [SO, through the ructures ,21. Featis_a relationship, thus allowing to retrieve items by a subsumption inference .The ontological organization of the data is made persistent in the CVPath table, that is part of the CHADO schema. It implements a transitive closure (pre-computed at setup time by an OWL reasoner) of the The relational approach behind the design of the schema allows the use of any relational Database Management System (DBMS). In our prototype the Molecular Biodiversity Database schema is implemented in the IBM DB2 DBMS. So the query system performance of the prototype takes advantages of the DB2 performances due to the advanced indexing and storage capabilities.Parser, the Reasoner and the DBFiller.GenBank sequence and feature data are populated in the Molecular Biodiversity Database by an Extract, Transformation and Loading (ETL) software we designed and implemented named Intelligent Data Loader (IDL). It is able to parse and add semantic information to the GenBank entries. IDL is composed by three main modules: the IDL architecture, as shown in Figure The job server indexes a local copy of the flat files to be loaded and draws up a list of entries, each one with an associated state: ready, pending, loaded. It performs the following operations: creates the list of jobs, returns a job to be executed, marks a job as completed, writes the list of completed jobs, re-adds jobs dispatched but not completed to the "to-do" list.The creation of the job list consists of a set of records (jobs or entries) each one keeping the information about the seek position of the entry first line in the flat file (each flat file contains many entries), the seek position of the first nucleotide of the sequence and the current GenBank GI number of the entry.When the client asks for a new job, some pieces of data are sent to it via socket communication and the job is set in the pending state. When the DBThread component finishes to process the entry, it sends a "completed" message to the server and the job can be set in the completed state. The DBFiller, once in a while sends a message to the server to write in a persistent way the status of the jobs in the list. If a job runs up against an exception during its processing, remaining in the pending condition, it can be processed again after a reset of the pending jobs list. By means of the job server, IDL handles faults and exceptions and implements the upgrading procedure necessary to load new entries available in a new GenBank release.The IDL, through an OWL reasoner, automatically builds CLIPS  facts reThe IDL, the job server and the DBMS can be scattered on different machines in order to distribute the computational load, as we discuss in the following.Currently, several parser libraries for the GenBank flat-files have been developed, such as BioJava , BioPythInitially, four portions of the entry are localized within the GenBank flat-file: the header, the references, the features and the sequence section. The nucleotide sequences are not translated into a clips fact in order not to overload the reasoner. Some regular expressions are applied to extract the information contained in the header string, then the header is translated into a single clips header fact. The references string is split into several single reference strings, the regular expressions are applied and each reference is translated into a reference fact with one or more reference location, i.e. the features a reference is the evidence of. The features are initially indexed to locate each feature string within the file; those indexes are then passed to a method that builds a feature object. Each feature object owns one or more locations and qualifier objects, extracted by means of regular expressions. Finally each feature object is serialized into a key fact in relationship with several location and qualifier facts.IDL makes use of two different reasoners: an OWL Reasoner (Fact++) and a CLIPS Reasoner.una tantum, in the setup phase of the IDL execution. It is used to make all the admissible relationships among features explicit and to consequently build CLIPS facts representing the knowledge in the Sequence Ontology.The OWL  reasonerIn this phase a Java program, given an SO term and an SO object property, creates an OWLObjectPropertySomeRestriction  propositOn the other hand, the CLIPS reasoner is the component dedicated to the ETL rules execution. This reasoning environment is based on CLIPS, one of the most popular software tools for building expert systems (further details in ). It makIn our implementation, a representation based on one header and one sequence, and one or more key, portion, reference and reference_portion templates are transformed into an ordered set of statements in the form of insert and select templates. The entry-templates have all the slots required by the DDBJ/EMBL/GenBank FTv8.The insert template includes a "tableName" slot to identify the involved table and two multislots, "columnName" and "columnValue", to identify respectively the columns and the values. Two more multislots have been conceived to manage the cross-reference of foreign keys that refer to automatically generated keys. Each statement is identified by a "count" slot; this identifier is used in the "foreignCount" multislot of a different insert to refer to the first one. This value will be substituted in run-time with the real value assigned by the DBMS. As an example, in Figure During the transformation process each feature key type was mapped to an SO term using the correspondence given in the feature table SO mapping file , made puSince bibliographic references in the FTv8 are assigned to specific sequence locations, a relationship between the feature and its bibliographic evidence was assigned basing it on location coherence.The Rule Facility also produces rules for the translation of qualifiers into SQL statements for those qualifiers that didn't need to be loaded into the Collection portion of the schema. These rules are not the result of an OWL reasoning. Instead, biodiversity specific qualifiers, including experimental, taxonomic and sampling details, were managed through rules coded with the help of a domain expert, and stored in specific tables of the database (e.g. the Collection area). Generally speaking, whenever any qualifier had to be elaborated and stored in dedicated tables other than the Chado schema tables, a specific rule had to be coded. The other pieces of information are managed by the näive rules generated by the Rule Facility.member_of, part_of and derives_from relationships among features of an entry were reconstructed. The subsumption and transitive closure entailments were used to compute all the biologically possible relationships among types of features. This information was derived by the SO, and the corresponding knowledge was made available in CLIPS by the Rule Facility, as previously described. Feature-specific relationships were assessed on the bases of the feature types and of the qualifier and location consistency. The qualifiers used were locus_tag, gene, product and protein_id. The latter is an example of implicit information that can be easily extracted from the GenBank entries, coding appropriate rules.Finally, the The DBFiller component asks the job client for a set of ready-state entries and assigns each one to a DBThread (an extension of ours for a Java Thread). The threads can be run with a configurable degree of parallelism to maximize loading performances. Each DBThread performs three steps: parsing, reasoning and statement building. The parser transforms a flat file in a set of CLIPS facts, that is, the initial facts. The reasoning component performs a call to the CLIPS engine through a Java Native Interface. The initial facts combined with the rules, partially encoded by a human expert and partially derived from the ontology, give rise to the reasoner results, i.e., a set of statement-like facts. The DBThread extracts the statement facts and builds real SQL statements that can therefore be submitted to the DBMS. After the execution of a configurable set of jobs, the DBFiller commits the job handling results to the Job Server, that is the main controller class in the IDL architecture. The pipeline is summarized in Figure Connections to the DBMS are managed by means of a connection pooling that allows a considerable time saving: the connections don't need to be opened and closed by each thread, but they are shared-in turn-among threads.The modular solution conceived for the IDL allows the system to be deployed in different topologies, involving a different number of servers. The Figure Asteraceae. The GIDL tool arranged the entries in 50,758,000 sequence feature annotations and associated 13,298,000 instances to 1,342 Sequence Ontology terms.GIDL was used to parse and load in the Molecular Biodiversity Database the entries extracted from four GenBank divisions (rel.180): VRL, INV, PNL and EST. VRL is the set of entries of the complete Viral division ; INV refers to the set of entries of the complete Invertebrate division ; PLN concerns the entries of the complete Plant division ; finally, we denote with EST a sub-set of 1,035,087 entries of the GenBank division of Expressed Sequence Tag belonging to organisms of the family We used GIDL to support a set of bioinformatics applications developed in the Molecular Biodiversity Laboratory (MBLab) . FirstlySequenceLength) in base pairs; the length of the feature table of the GenBank entries (FatureTableLength), measured in bytes; the number of features in the entries (# Features); and the number of SQL INSERT statements (# Statements) produced by the IDL, in order to insert each entry in the relational database in terms of the database schema discussed above. All these parameters depend on the sets, and neither on the computational capabilities of the server used nor on the topology chosen in the deployment phase.Loading performances are crucial in a data loading system that manages huge volumes of data as those involved in the bioinformatics domains. In order to evaluate the GIDL performances, this component has been armed with a logging sub-module that traces relevant loading parameters in an appropriate table of the database instance it works on. Our loading test has been performed with the four sets of entries previously described. Some of the most relevant observable parameters traced by the logging sub-module of GIDL are synthesized, in a synoptic view in Table ParsingTime, measured in milliseconds), the elaboration time taken by the Reasoner (ReasoningTime), the time needed by the DBFiller to send all the composed SQL INSERT statements against the database (InsertTime). Finally, the total time to elaborate each entry is reported .On the other hand, the following four rows for each data set refer to measured times that are, in principle, dependent on the computational setup. They refer, respectively, to the time spent to parse the entry  to topology (b) leads to an improvement of about 15% in the TotalTime (672.8 ms instead of 778 ms), and this is principally due to the improved InsertTime . This means that in the "INSERT phase", when IDL sends INSERT statements and the DBMS executes them, a configuration with these two components on different boxes is preferable. The gain due to more resources for computation is higher than the loss due to network latency. This and other considerations, however, indicate topology (b) as the preferable configuration with respect to any others.A scrupulous testing procedure was needed to verify the correctness of the CLIPS rules and the correct insertion of the GenBank entries into the MBLab Database. In order to accomplish this task, a "controlled dataset", i.e. a relatively small dataset containing entries with pre-established characteristics, was prepared.We selected five GenBank divisions  and we scanned all the entries for each division to find and extract a subsample containing at least two entries for each of the 60 GenBank feature keys. Thus we obtained 492 entries, instead of the expected 600 (5 division × 60 feature keys × 2 sample entries) due to the lack of the selected feature key in some entries (a feature key may or may not be present in a particular division). Following the same procedure for the 96 available GenBank qualifiers, we extracted 824 entries, instead of the expected 930 . So the resulting controlled dataset included a total of 1316 entries. Using the IDL those entries were loaded in a Target Database instance dedicated to the test.The entries were parcelled out and delivered to a panel of 20 bioinformatics researchers with knowledge of the GenBank entry structure. The researchers received the entries to be checked in flat file format, a spreadsheet file, and the access to a minimal web interface of the database Figure . For eacAfter the reports were gathered and the detected bugs corrected, a second test session was performed using the same dataset. In this session 5 entries per person, different from those assigned before, were assigned to be checked with the same procedure for both header and feature key sections. This final session of tests ensured that the code debugging was carried out extensively and correctly.By means of a JDBC SQL client access it is possible to query and retrieve data stored in the Molecular Biodiversity Database, populated by the Intelligent Data Loader. As a demonstration of GIDL capabilities we have built a graphical web interface querying prototype on top of the Molecular Biodiversity Database. The interface was used by trained bioinformatic researchers to test the correctness of IDL (illustrated in the Testing Procedure). The web interface prototype implements the use case of structured consultation of a GenBank entry. Entry information  are shown in separate dynamic boxes and are exploitable on request; so using this web interface the entry consultation is more concise than the GenBank website visualization.Information about the features are further structured and for each of them it is possible to explore portions, nucleotides, annotations, evidences and relationships (according to the SO) with other features  of genes having a coding sequence (Sequence Ontology term: 'CDS') with a particular defined annotation. In our query system prototype, it is possible to formulate this query by means of a tree view  according to the 'is_a' SO relations.Query results will consist of all entries satisfying this criterion. In this way it is possible to retrieve features (regulatory regions as in the above example) defining a criterion not only on that particular feature, but also on features related to it. Moreover query results will provide not only the features mapped to the SO term 'We want to point out that the web interface is just a prototype, with reduced functionality which does not allow currently to explore all the features of the Molecular Biodiversity Database. Further developments are in progress and out of the scope of this paper.Frequently, in the molecular biodiversity domain in order to accomplish properly their analyses, the researchers need to retrieve large quantity of data  from remote public databases, store them locally and integrate these information with data contained in private databases and collections. To carry out this task, researchers may usually spend about 80% of their time in retrieving, assembling and preparing data for analysis  .Our aim was to develop an intelligent solution to parse, retrieve and load the entire GenBank database locally. In fact, giving scientists access to a system in a high-bandwidth local network enhances large queries response and the data could be easily retrieved with lower latency than attempting to retrieve the same data over the Internet, like "net" solution  .Furthermore, we believe that GIDL, by means of the semantic web approach, has at least two advantages comparing it with other similar tools. First of all, it provides the users with an innovative way to query molecular data annotations. The integration of the SO knowledge base in GIDL allows to execute complex biological queries in a single step  in local DBMS is computational intensive, GIDL overcomes these obstacles satisfying the following requirements:flexibility: the user can easily re-define the extraction procedure logics and adapt it to his needs. The system would be able to adapt to changes in the knowledge of the biological domain. Actually, compared to traditional programming techniques, expert-system approaches provide more flexibility (and hence an easier modifiability) modelling rules as data rather than as code. The flexibility of the rule based approach also allows to easily manage the changes of the database schema or of the ontology. Although a rule based system can be perceived as more complex than an object-oriented system, and the object structure as more useful than the rule modularization and documentation, an initial steeper learning curve can give an effort ease later on;- speed: the IDL application parses and transforms millions of GenBank entries and generates and executes tens of millions of SQL statements in a reasonable time;- knowledge representation: the relationships between the entities of the entry and the attributes of those entities, give rise to implicit knowledge that has to be made explicit according to knowledge of the domain, as discussed before;- updatability: the loader is able to manage frequent updates of new GenBank release;- robustness: the modular design conceived for the IDL system  scalability. In the "System deployment topologies" section we thoroughly discussed the numerous possibilities of deployment topologies its architecture makes possible. These solutions can cover scenarios ranging from the loading of small data sets up to very large databases in a reasonable time.- In this work we have presented the concepts, the design and the implementation of the GIDL system, a toolkit consisting of a relational DB schema (based on the Molecular Biodiversity Database) and of an Intelligent Data Loader software that parse GenBank public entries, add semantics and load these information into an ontology-driven schema. The toolkit can be downloaded on request and installed by users who want to use a local instance of GIDL. Future developments for GIDL include the development of software modules to provide programmatic accesses via Application Programming Interface (API) in order to perform useful automatized operations on biological data.BCT: Bacterial GenBank division; DB: Database; DBMS: Database Management System; GIDL: GenBank Intelligent Data Loader; EST: Expressed Sequence Tag GenBank division; ETL: Extraction, Transformation, Loading; FTv8: DDBJ/GenBank/EMBL Feature Table definition ver.8; IDL: Intelligent Data Loader; NCBI: National Center for Biotechnology Information; PLN: Plant GenBank division; SO: Sequence Ontology; VRL: Viral GenBank division; VRT: Vertebrate GenBank division.The authors declare that they have no competing interests.PP designed and developed the Molecular Biodiversity Database schema, the CLIPS rules and drafted the manuscript; DC participated to the schema design and drafted the manuscript; FR implemented the feature table to SO term mapping; GDC developed the query prototype interface and participated to the schema development: GG participated to the feature table to SO term mapping implementation and participated to the schema development; PL participated to the architectural design of the system and coordinated the IBM team; GP carried out the testing procedure and participated to the development of the parser for the GenBank entries; GS conceived the study, designed the system architecture, participated to the schema design and drafted the manuscript; FL conceived of the study, participated to the schema design, drafted the manuscript and coordinated the work. All authors read and approved the manuscript.PDF file containing a working example of the GIDL execution pipeline.Click here for file


Patio limpio consists of training local people to identify, eliminate, monitor and evaluate vector breeding sites systematically in households under their supervision. A community participation programme in Guerrero State found that approximately 54% were clean and free of breeding sites. Households that were not visited and assessed had a 2·4-times higher risk of developing dengue than those that were. However, after a year, only 30% of trained households had a clean backyard. This emphasises the need for a sustainable process to encourage individuals to maintain efforts in keeping their environment free of dengue.Community participation is vital to prevent and control the spread of dengue in Latin America. Initiatives such as the integrated management strategy for dengue prevention and control (IMS-Dengue) and integrated vector management (IVM) incorporate social mobilisation and behavioural change at the community level as part of a wider strategy to control dengue. These strategies aim to improve the efficacy, cost-effectiveness, environmental impact and sustainability of vector control strategies. Community empowerment is a key aspect of the strategy as it allows the local population to drive eradication of the disease in their environment. Through the  In order to counter the significant public health burden of dengue in Latin America, the Pan American Health Organization (PAHO) has developed a regional initiative that utilises public participation at community level to encourage behavioural change as part of a wider strategy to control dengue.2,3This article discusses how community participation is vital to prevent and control the spread of dengue in Latin America.IVM is a global strategic framework first adopted in 2004 by the World Health Organization (WHO) for all vector-borne diseases .4 A furt6Social mobilisation integrates different members of the community, from householders to political leaders, in order to raise awareness of dengue, deliver resources and services and ensure sustained community participation.8Community empowerment is one of the most important elements of the IVM strategy, allowing the local population, who most suffer the consequences of dengue, to drive eradication of the disease in their environment.Sustainable programmes and modification of individual behaviour are essential in mosquito-control initiatives. This means that individual households must accept responsibility for the control of mosquitoes in their surroundings. However, to maintain sustainability, such efforts should continue as long as the threat of dengue exists and become culturally embedded. To enable this, capacity-building and training of individuals in surveillance, laboratory diagnosis, case management and vector control are important for effective community interventions to be carried out.7As part of the community mobilisation framework, leadership support from local political, religious and community heads is crucial to engage the local population. A multidisciplinary approach, for example between vector control personnel, entomologists, anthropologists, epidemiologists and social marketing experts, is also an important aspect of community mobilisation.7patio limpio in Spanish, or ‘clean backyard’, integrates surveillance information and vector control strategies with social mobilisation.The concept of community participation as part of social mobilisation has been employed in Mexico in an attempt to raise awareness of the consequences of dengue and to explore how this can impact the risk of contracting the disease.Patio limpio consists of training local people to identify and eliminate vector breeding sites in an organised manner. The strategy emphasises the importance of each household in the fight against dengue and the need for all households to work together with the common aim of living in a dengue-free community. The initiative relies on thorough cleaning of the home, which has benefits in addition to the creation of an environment free of dengue. These include an overall clean and presentable home, prevention of bites from other insect types as breeding sites are cleared, and the availability of the yard for recreational family activities. Furthermore, the family can work together as cleaning is an activity that can be carried out by all its members.The implementation phase of the strategy begins with a local assembly in which the concept of group empowerment and the need for commitment from each household in keeping their surroundings clean and free of breeding sites are explained. Community leaders are identified for each block in the neighbourhood and they are then empowered by being trained and given official identification as ‘block activators’.The role of block activators is to pass on to families in a given neighbourhood knowledge of how to identify and eliminate breeding sites and help them understand the benefits of keeping the household clean. Families are subsequently responsible for their own environment. Each block activator is responsible for visiting a number of households to train individuals in the process of vector breeding site identification and elimination. Block activators, usually women, also perform a monthly assessment of the area under their supervision and attend community assemblies. Larval indices are shared with block activators and recommendations are provided when expected outcomes are not met, which contributes to the concept of group empowerment.The impact of community participation over 1 year (2007) on mosquito-breeding sites in Guerrero, a state in south Mexico, is shown in 10More than 1000 block activators were generated and trained, with an average of approximately 15 households managed by each activator. From a sample of 5477 backyards, approximately 54% (2918) were designated as ‘clean’ and free of breeding sites. Further analysis revealed that households not visited and assessed by a block activator, had a 2·4-times higher risk of developing dengue, compared to those who had been trained and supervised by an activator. In addition, 80% of trained households were able to identify a breeding site and mosquito larvae at the 3-month follow-up visit. However, after a year, only 30% of trained households had a clean backyard and were conscious of the risks associated with breeding sites in their households. This emphasises the need for a sustainable process to encourage individuals to maintain efforts in keeping their environment dengue-free.Social communication was an important element in the social mobilisation strategy employed in the State of Guerrero. The communication strategy included displaying 18 signboards and 130 posters, three daily loudspeaker transmissions in areas such as shopping centres and markets throughout the community, and distributing pamphlets to every household visited by block activators. Households already visited and trained were identified by stickers.10Even with the potential future availability of a dengue vaccine, community participation is crucial to achieving sustainable control programmes. There is a danger that, with the introduction of a vaccine, community members would regard social mobilisation and community participation as unnecessary. Further education should therefore clarify the role of a vaccine in dengue prevention and how its introduction should be combined with other aspects of vector control, such as community empowerment, in order to maintain preventive practices. The rotavirus vaccine is an example of the need to provide the public with information: communities at risk of infection had to be advised to maintain hygienic practices, despite the existence of a vaccine against rotavirus.11Undoubtedly, dengue control programmes require a clear, integrated approach with strong community involvement, characteristics that are at the heart of the IVM and social mobilisation concepts. However, for sustained benefit, long-term behavioural modifications at an individual level are imperative. Results of the study carried out in a Mexican community demonstrate the need for community participation programmes to continue as long as dengue continues to be a threat in order to extend the benefits of such initiatives. The lack of continuity of long-term community participation programmes also results in subsequent reluctance by funding and government bodies to invest in and support such initiatives as these strategies fail to achieve desired goals and fulfil expectations. Consequently, these programmes are often relegated to serve as epidemiological projects during dengue outbreaks.To encourage continuity of programmes, community leaders are effective channels through which to disseminate information, educate communities and catalyse behavioural change at the household level, in turn stimulating progress in the wider community.


Few studies have investigated mortality in seafood workers worldwide, and no such study has been conducted in the United States. The objective of this study was to investigate mortality in American seafood workers.The study population was derived from 4 states and consisted of 4116 subjects who worked mainly in seafood processing plants. They were followed up from 1966 to 2003. Standardized mortality ratios (SMRs) and proportional mortality ratios (PMRs) were estimated, using the US general population for comparison.About 45% of the cohort was born after 1949. A total of 788 deaths were recorded; 53% of the decedents were female, and 88% were white. The SMRs for stomach cancer and disorders of the thyroid gland in the cohort as a whole were 2.1  and 6.1 (95% CI 1.3–18.0), respectively. The SMRs for breast cancer, and occlusion/stenosis of the pre-cerebral/cerebral arteries in the cohort as a whole were 0.5  and 0.5 , respectively. The SMR for ischemic heart disease in white females was 0.8 .This cohort had excess deaths from stomach cancer and disorders of the thyroid gland, and deficit of deaths from breast cancer, stroke and ischemic heart disease. The significance of these findings is unknown, especially as less than 20% of the cohort were deceased. Nevertheless, the cohort is unique and important, and further follow-up may shed more light on mortality patterns in this occupational group. Therefore, we investigated mortality in a cohort of seafood workers in the United States.The seafood industry has experienced tremendous growth in recent years.n = 4116) was defined as all people who worked in seafood occupations anytime between 1966 and 1990 and were members of the United Food and Commercial Workers (UFCW) International Pension Fund. It included employees of 7 seafood companies in the northern United States who worked on fishing vessels or in wholesale processing plants or warehouses where various fresh or frozen seafood  were cut, cleaned, scaled, gutted, filleted, packed in containers and crates, or stored. Processing activities also include battering, breading, and frying of various types of fish and other seafood, as well as production of shrimp paste. The cohort also included subjects who worked in seafood retail stores and a seafood restaurant. Study subjects were followed up for mortality from 1 January 1966 to 31 December 2003, during which 788 deaths occurred in the cohort. The cause of death was coded according to the Ninth Revision of the International Classification of Diseases (ICD-9).The study population  which records all deaths in the country, Social Security Administration, state Departments of Vital Records, state Departments of Motor Vehicles, personal contact by telephone and mail, and internet tracing methods. Pension Benefit Information Inc, a private company, was also used to identify deceased persons. This company matches subjects against US death records for all years from the 1800s to the present, using information received from various government databases such as the Social Security Administration, Health Care Financing Administration, and state Departments of Vital Records, as well as the Civil Service Commission, Railroad Retirement Board, and the Department of Defense. Because we carried out a comprehensive search for death records (it has been shown for example that NDI will identify greater than 98% to 99% of deaths if matching information is good), subjects for whom no death records could be identified at the end of follow-up were assumed to be alive at the end of study.Information on date of birth was missing for 39 seafood workers (0.9%) whose vital status was also unknown. Rather than excluding such persons from the analysis, their date of birth was imputed, based on the median year of birth recorded for workers with known dates of birth who joined the union the same year. Thus, if a member with an unknown date of birth joined the union in 1975, she was assigned as her year of birth the median year of birth for persons with known birth dates who joined the union in that particular year. This crude measure was deemed to be associated with minimal bias, since the effect on total person-years would be negligible and non-significant.5 The cohort was stratified by plant and then further stratified into 4 subgroups by race and sex , after which each of these groups was stratified according to age  and calendar year at entry into the cohort . Person-years were accumulated from the date the company joined the union for those subjects who were already employed in the company by that date. For those who started working after their company had joined the union, accumulation of their person-years commenced on the date of union membership, which was virtually the same as their date of hire, since membership in the union was compulsory from the first day of employment. Person-years were enumerated up to the date of death or date of termination of the study on 31 December 2003, whichever was earlier. Expected deaths were derived by multiplying the person-years in each cell by the corresponding sex-, race-, calendar year-, and age-specific mortality rate for the US general population. Observed and expected deaths for each cell were summed over all ages and calendar years, and over all strata, and the SMR was estimated as the total observed number of deaths divided by the total expected. The 95% confidence intervals for the SMRs were calculated according to a simple exact method that links the Poisson and chi-square distributions.6 A similar method of stratification was used to estimate the PMR, except that for each cell in the study population, the corresponding proportion of all deaths due to a given cause in the US population was multiplied by the total number of deaths in that cell to obtain the expected number of deaths. The ratio of observed deaths in the cell to expected deaths is the PMR. Observed and expected deaths for each cell were summed over all ages and calendar years, and over all strata, and the PMR was estimated as the total observed number of deaths divided by the total number of expected deaths.Statistical analyses involved estimation of standardized mortality ratios (SMRs), stratified by age, calendar time, sex, race and processing plant, using the US general population as the comparison group. Analysis was conducted using the OCMAP Plus software package from the University of Pittsburgh, USA. US mortality rates were purchased from the University of Pittsburgh. Information on race was available only for decedents with a known cause of death. Therefore, to perform the SMR analyses, race was artificially assigned at random to each individual without a known cause of death, based on the racial distribution of decedents with known race. In a similar study of UFCW workers in the meat industry, the racial distribution of deceased subjects was found to be no different from that of a sample of current workers representing more than half the union membership.The protocol for this study was approved by the University of North Texas Health Science Center Institutional Review Board.Table The absence of major differences between the SMR results in which race was imputed for nondeceased subjects, and the PMR results which were based on complete information on race, is reassuring and indicates that no serious bias resulted from imputing race in the SMR analyses. With the exception of white males, seafood workers in the current study tend to exhibit the healthy worker effect, ie, lower overall mortality than that of the general population. It is not clear why decreased mortality was not observed in white men.7 A study of Swedish fishermen reported a significant excess incidence of stomach cancer in fishermen on the east coast but not on the west coast.4 Thus our findings for stomach cancer are consistent with the results of those 2 studies. In addition, in the Swedish study, the wives of east coast fishermen had a significantly increased risk of stomach cancer, while the wives of west coast fishermen had an elevated risk that was not statistically significant.4 East coast fishermen and their wives had a higher intake of fatty fish than those on the west coast. They also had increased concentrations of persistent organochlorine pollutants in their blood, while west coast fishermen and their wives did not.7,8 Other reports have noted significantly higher fish consumption among seafood workers as compared with the general population, based on information from dietary interviews.4,9 These reports raise the possibility that the excess of stomach cancer reported in seafood workers could be partly explained by dietary factors rather than, or in addition to, occupational factors. Unfortunately, we have no evidence that seafood workers in the United States consume more seafood than the US general population. A possible explanation for the excess is that seafood workers generally have unhealthy lifestyles.9 Previous studies have reported high levels of smoking and alcohol intake in the fisheries sector.9,10 Smoking and alcohol intake are known risk factors for many cancers, including stomach cancer, although the association with alcohol is inconsistent.11 Another possibility is that seafood workers may have higher dietary intakes of salted fish, “rotted” seafood, or both. Seafood salting increases the content of nitrates in the diet.7 Furthermore, rotted seafood could lead to bacterial contamination of the stomach. Nitrates could be subsequently reduced to nitrites in the gastrointestinal tract, and the bacterial flora or amines present in food could lead to conversion of nitrites to carcinogenic N-nitroso compounds.7 It is also possible that seafood workers in trawlers and fishing boats are exposed to carcinogenic diesel fumes or asbestos, although these exposures are not usually associated with stomach cancer.12–17An excess of stomach cancer was recorded in all race/sex subgroups except nonwhite males, although the small sample size of this subgroup may be partly responsible for the apparent absence of risk. An excess occurrence of stomach cancer was previously reported in Chinese fishermen in Singapore, and all cases were divers.in vitro and in animal experiments.18–20 However, the reported association between fish consumption and breast cancer in women has not been consistent, as some epidemiologic studies have found a significant inverse association, while others have not.21–25In the present study, the lower occurrence of breast cancer among female seafood workers could be partly attributed to their high fish intake, as mentioned above. The omega-3 fatty acids in fatty fish, have consistently been shown to retard the growth of breast cancer cells 26,27 Thus the excess occurrence of thyroid diseases in workers could be related to nonoccupational rather than occupational factors. The reason why the excess of thyroid diseases was restricted to whites is also not known, but the small sample size of nonwhites is a possible explanation.It is unclear why an excess of disorders of the thyroid gland was observed in this cohort. Thyroid disorders can be caused by excess iodine intake, which can result from high consumption of seafood rich in iodine.4 the SMR for ischemic heart disease as in our cohort, was significantly depressed in west coast fishermen and their wives, but not in those on the east coast. Similarly, the SMR for cerebrovascular accidents was depressed in west coast fishermen, but not in east coast fishermen, although the reduction was not significant.4 Frequent consumption of seafood, particularly fish, has been associated with reduced stroke and coronary heart disease mortality in several reports.28–33 Thus, the present observations although somewhat inconsistent, suggest that dietary factors such as increased seafood consumption play a role in the occurrence of cardiovascular and cerebrovascular diseases in seafood workers.Our findings indicate that ischemic heart disease and stenosis of the pre-cerebral and cerebral vessels were less frequent among female sea-food workers in this cohort. In the Swedish study described above,1 No deaths from water transportation accidents were recorded in this cohort, with 0.5 expected. The low statistical power of the study may be partly responsible for this finding. In addition, most seafood workers in this cohort were employed in processing plants, and very few were likely to have worked in fishing vessels as fishermen.Fishermen in fishing boats are known to be at high risk of water transportation accidents.34 in each of several race/sex subgroups; thus, some of the observed associations could have been due to chance, especially as only a small number of deaths were involved in some instances. Finally, it was not possible to identify and analyze in detail the data separately for fishermen who worked in fishing vessels, workers in retail stores and workers in processing plants, because company records did not precisely distinguish these groups. A limited examination however, indicated that the excess of stomach cancer appeared to occur in all these groups.This study should be interpreted in the context of its limitations. Firstly, as is the case in many retrospective cohort mortality studies, information was missing on specific occupational exposures and nonoccupational factors such as smoking and seafood consumption. Thus the specific cause(s) responsible for the excesses and deficits cannot be identified in this type of study. Secondly, the statistical power was low, and important associations could have been missed. Thirdly, multiple comparisons were made, as we examined in total 185 separate causes of death35 and polycyclic aromatic hydrocarbons and heterocyclic amines that are formed during cooking or smoking of seafood.36,37There was no excess of the cancers known to be associated with the specific carcinogenic exposures that may have occurred in this occupational group. These exposures include oncogenic viruses that cause tumors in fish,38–40 and none of the cancers that were in excess in the poultry cohorts were in excess in the seafood cohort. Similarly, the findings for breast cancer and stroke in this seafood cohort were not observed in the poultry cohorts. Thus the findings in this cohort of seafood workers appear unique.Interestingly, no association between these occupational exposures and stomach cancer has been previously observed. Indeed, we observed no excess stomach cancer in our concurrent investigation of 3 poultry cohorts from the same Pension Fund,The study has some advantages. Firstly, to our knowledge, this is one of the largest studies of seafood workers to date, particularly of workers in processing plants, and the only study of this occupational group in the United States. Secondly, the definition of the cohort was uniquely comprehensive. Because of the exceptional union recordkeeping system, all employees  had a personal record, making selection bias unlikely. Thirdly, because the present investigation was a cohort study, a temporal relationship between the exposure surrogate (affiliation with the cohort) and the outcome  could be established.In summary, the findings of this study are preliminary and hypothesis-generating and draw attention to seafood workers in the United States. Further follow-up and case-control studies nested within this cohort are encouraged. Nested case-control studies will allow for more comprehensive assessment of exposures and better control of occupational and nonoccupational confounding factors.


When we see a human sitting down, standing up, or walking, we can recognize one of these poses independently of the individual, or we can recognize the individual person, independently of the pose. The same issues arise for deforming objects. For example, if we see a flag deformed by the wind, either blowing out or hanging languidly, we can usually recognize the flag, independently of its deformation; or we can recognize the deformation independently of the identity of the flag. We hypothesize that these types of recognition can be implemented by the primate visual system using temporo-spatial continuity as objects transform as a learning principle. In particular, we hypothesize that pose or deformation can be learned under conditions in which large numbers of different people are successively seen in the same pose, or objects in the same deformation. We also hypothesize that person-specific representations that are independent of pose, and object-specific representations that are independent of deformation and view, could be built, when individual people or objects are observed successively transforming from one pose or deformation and view to another. These hypotheses were tested in a simulation of the ventral visual system, VisNet, that uses temporal continuity, implemented in a synaptic learning rule with a short-term memory trace of previous neuronal activity, to learn invariant representations. It was found that depending on the statistics of the visual input, either pose-specific or deformation-specific representations could be built that were invariant with respect to individual and view; or that identity-specific representations could be built that were invariant with respect to pose or deformation and view. We propose that this is how pose-specific and pose-invariant, and deformation-specific and deformation-invariant, perceptual representations are built in the brain. When we see a human sitting down, standing up, or walking, we can recognize one of these poses independently of the individual, or we can recognize the individual person, independently of the pose. How might this be achieved in the visual system? Might both types of encoding of visual stimuli be present simultaneously, in different cortical areas? What mechanisms in the visual cortex might be involved?The same issues arise for deforming objects. If we see a flag deformed by the wind, either blowing out or hanging languidly, we can usually recognize the flag, independently of its deformation. Similarly, we can describe the deformation of an object, for example the flag blowing out or hanging loosely, independently of the identity  of the flag.In general, dealing with deformation in images is difficult for object recognition systems. For example, one approach has used part-based representations to recognize human poses  person identity. On another occasion, most of the people successively viewed might be standing up, for example waiting in a bus queue. On another occasion, all the individuals successively fixated might be walking to work. The second hypothesis is that person-specific representations that are independent of pose could be built, in another part of the ventral cortical visual system, when we watch one individual change posture, for example sitting down, then standing up, and then walking. The representation of the identity of another person that is invariant with respect to pose and view could be built using the temporal continuity inherent is seeing another particular person transform through a set of poses and views, etc.These hypotheses were tested in a simulation of the ventral visual system, VisNet, that uses temporal continuity, implemented in a synaptic learning rule with a short-term memory trace of previous neuronal activity, to learn invariant representations Rolls, .The stimuli for the human pose experiment consisted of three individuals , shown in each of three different poses . Each image was shown in 12 different rotational views each 30° apart. To train for pose identification, during training all 36 images had the same pose in succession but with the 36 images otherwise presented in random permuted sequence. One training epoch consisted of showing successively all people and views of one pose, then all people and views of another pose, and then all identities and views of the third pose. This enabled us to test whether VisNet under these circumstances would allocate some neurons to one pose independently of individual and view, other neurons invariantly to the second pose, and other neurons invariantly to the third pose.To train for recognition of each individual, a training epoch consisted of showing all poses and all views of one individual in a random sequence, then all poses and all views of the second individual in a random sequence, and then all poses and all views of the third individual in a random sequence. This enabled us to test whether VisNet under these circumstances would allocate some neurons to one individual person independently of pose, other neurons to the second individual independently of pose, and other neurons to the third individual. It may be emphasized that the images shown in each of these experiments were identical, and only the order in which they were presented differed.After training, the trained networks were then tested to determine whether the poses could be identified independently of the person and view transforms; or whether the individual people could be identified independently of the pose and view transforms.For the flag deformation experiment, there were flags of four individual countries  each shown with five different deformations produced by equally spaced wind values, with each condition shown in two views, from one side, and from the other side. To train to identify the country of the flag, all the deformations and views of the flag of one country were shown in random sequence, then all the transforms of the flag of the second country, etc. To train to identify the deformation (how much the flag drooped because of different wind strengths), one deformation was trained with all images of that deformation, then all images of the second deformation, etc.After training, the trained networks were then tested to determine whether the particular deformations of the flags produced by each wind speed could be identified independently of the country and view transforms of the flags; or whether the individual countries of each flag image could be identified independently of the deformation produced by the different wind speeds and views.www.blender.org) to ensure uniform lighting conditions. The models used for rendering were generated from the MakeHuman software (www.makehuman.org). Each model was posed in three variations  inside Blender. The camera position in Blender was rotated around each model in 30° increments to produce 12 views of each model in each pose, as illustrated in Figure The images of humans used for training were rendered using Blender software  were also created in Blender using its cloth simulation. A force field was placed laterally from the position of the flag to give it a fluttering motion from wind. The wind force was set to five different equally spaced values in the range 0–200 Blender units, chosen so to give a wind effect varying from no wind to strong wind. Images were rendered with the camera looking straight on to the flag and on the opposite side, as illustrated in Figure Training images were presented at the center of the VisNet retina in one of two modes, object or deformation recognition mode. These modes were made distinct so that we could measure either how well the VisNet architecture performs in recognizing stimulus identity  invariantly with respect to deformation and view; and deformation  invariantly with respect to stimulus identity and view.In object recognition mode each of the images was grouped depending on the model . Each of the image groups then had each model shown in the 3 different deformations, with 12 rotational views of each deformation. During each epoch of training, using the trace synaptic learning rule, a randomly ordered permutation of the set of all images corresponding to different deformations and views was presented to VisNet. After each group of deformations and views was presented for a single model, the trace values reflecting for each neuron its recent firing rate was reset to 0 before moving on to the next model. . For the pose learning of people, each training group consisted of the images of the 3 people in 12 different rotations in the same deformation. Trace learning operated in a similar fashion as above with the trace being reset after each set of a particular pose or deformation.Simulations were run using 50 training epochs, which was sufficient to enable convergence of the synaptic weights.A series of competitive networks, organized in hierarchical layers, exhibiting mutual inhibition over a short range within each layer. These networks allow combinations of features or inputs occurring in a given spatial arrangement to be learned by neurons using competitive learning Rolls, , ensurinA convergent series of connections from a localized population of neurons in the preceding layer to each neuron of the following layer, thus allowing the receptive field size of neurons to increase through the visual processing areas or layers, as illustrated in Figure A modified associative (Hebb-like) learning rule incorporating a temporal trace of each neuron's previous activity, which, it is suggested Földiák, , will enFundamental elements of Rolls' The performance of VisNet was measured by Shannon information-theoretic measures that are essentially identical to those used to quantify the specificity and selectiveness of the representations provided by neurons in the brain . Figure Figure Figure 2 of the number of flag countries). The single cell information for the 100 most selective cells was 2.0 bits (perfect discrimination), as shown in Figure Figure 2 of the number of deformation types). The single cell information for many of the 125 most selective cells was 2.32 bits (perfect discrimination), as shown in Figure Figure The deformation invariant recognition of flags described above was obtained with a set of four flags , or all sitting down (for example in a theatre or stadium). As the eyes moved over scenes of this type, the natural environment would provide the conditions of temporal continuity for pose to be learned independently of identity. To learn identity independently of pose, appropriate environmental conditions might include looking at a single person while that person alters pose, from perhaps lying down, then sitting, and then standing up. This leads to the interesting prediction that neurons that encode pose independently of identity might be more likely to be close to parts of the temporal lobe visual cortex where the representations are of large-scale, such as scenes; whereas neurons sensitive to identity independently of pose might be more likely to be found close to cortical areas where single objects are represented, such as faces. In any case, self-organizing topological maps would be likely to be formed so that these two types of representation would be somewhat separated into different cortical regions or neuronal clusters Rolls, . FurtherThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.