Subjective measures involving clinician ratings or patient self-assessments have become recognised as an important tool for the assessment of health outcome. The value of a health outcome measure is usually assessed by a psychometric evaluation of its reliability, validity and responsiveness. However, psychometric testing involves an accumulation of evidence and has recognised limitations. It has been suggested that an evaluation of how well a measure has been developed would be a useful additional criteria in assessing the value of a measure. This paper explored the theoretical background and methodological development of subjective health status measures commonly used in osteoarthritis research. Fourteen subjective health outcome measures commonly used in osteoarthritis research were examined. Each measure was explored on the basis of their i) theoretical framework  and ii) methodological development . Only the AIMS, SF-36 and WHOQOL defined what they were assessing (i.e. the construct of interest) and no measure assessed was part of a theoretical model. None of the clinician report measures appeared to have implemented a scaling procedure or described the rationale for the items selected or scoring system. Of the patient self-report measures, the AIMS, MPQ, OXFORD, SF-36, WHOQOL and WOMAC appeared to follow a standard psychometric scaling method. The DRP and EuroQol used alternative scaling methods. The review highlighted the general lack of theoretical framework for both clinician report and patient self-report measures. This review also drew attention to the wide variation in the methodological development of commonly used measures in OA. While, in general the patient self-report measures had good methodological development, the clinician report measures appeared less well developed. It would be of value if new measures defined the construct of interest and, that the construct, be part of theoretical model. By ensuring measures are both theoretically and empirically valid then improvements in subjective health outcome measures should be possible. There has been a huge increase in the use and development of subjective health outcome measures . ConsequThe standard approach to assessing the 'value' of a health outcome measure is to be satisfied that a measure has adequate psychometric properties in terms of reliability, validity, and responsiveness . Howeverbefore time, and probably costs, are involved in psychometrically evaluating the measure. Thus, an evaluation of how well a measure has been developed would appear to be a useful additional criteria in assessing the 'value' of a measure. Therefore this review explores how well measures have been developed in terms of i) theoretical framework and ii) methodological development.Due to the limitations of psychometric testing, other considerations may add to the assessment of the 'value' of a measure. The Scientific Advisory Committee of the Medical Outcomes Trust, 2002  have sugdefines what it is supposed to be assessing (i.e. the construct of interest). For example, if we consider a measure that states it is measuring disability as a health outcome, there are many different interpretations of a what 'disability' encompasses. Disability may mean to some, limitations in physical function, but to others, it may represent a broader measure encompassing the social impact of a condition. Hence, a definition of the intended focus of a measure enhances compatibility, comparisons and understanding between studies.It is advantageous if a measure theoretical framework or model have the advantage of allowing underlying processes to be investigated, and interventions appropriately targeted. The dominant theoretical models of health outcomes or the consequence of disease have been the biomedical models developed by the World Health Organisation [Measures that are developed within a nisation ,12. The scaling procedure  is advantageous as it prescribes a standard, theoretically sound method for developing and scoring measures. Standard scaling methods usually start by collecting a large number of items, and then use defined methods to reduce the number of items, attach a response format, and score the final scale. The most common standard scaling techniques in health status measures have been derived from the scaling of attitudes – Likert [The use of a standard – Likert , Guttman– Likert  and Thur– Likert . These m– Likert ; as a reselecting items is broad enough to sample the full range and not restricted to just one source or domain. For example, in a thorough selection process items, may have been derived from previous measures, research literature, expert judges, patients, and healthy individuals. The resultant pool may then be reduced by going through a systematic sorting or item reduction process. The resultant items may then be explored empirically through item analysis, enabling poor items to be identified and eliminated from the final measure.If a standard method is not implemented, it is preferable if the method for Therefore in this review, considerations are given to the scaling strategy, item generation and reduction, scaling, response format, and scoring method of each of the measures. Additionally, the explanations given for the rationale for the response categories and scoring method are reviewed.In summary, the aim of this review is to explore the theoretical framework and methodological development of common subjective health outcome measures using the criteria specified in Table The measures selected were commonly used to assess subjective health outcome in hip or knee osteoarthritis (OA). The measures were identified as part of a review of interventions used for the treatment of OA . In addiThis resulted in the addition of two measures: the Hospital for Special Surgery knee score (HSS)  and the A literature search was conducted for published papers relating to the development of each measure and they were examined . The focus of this review was on the original measure rather than modified versions (e.g. short forms).The information extracted from the literature for this review was:a) For the basic description of measures: the number of items and item content areas.b) For the theoretical framework: was the underlying construct defined and was the construct part of a theoretical model?c) For the methodological development: what was the scaling strategy, how were the items generated and reduced, what was the response format and what was the scoring method?A summary of the basic measure information is in 'Additional file The clinician report measures stated what the measure was about but none defined what it was supposed to be assessing. These measures also lacked an underlying theoretical framework. The American Knee Society Score (derived to measure knee and patient function), Harris Hip Score , Hospital for Special Surgery Knee Score (disability), Lequesne Hip and Knee Indices (an indices of severity of disease), Merle d'Aubigne Hip Rating (function of the hip) are all measures which, while of value clinically, did not have a well defined construct, nor were they derived from a strong theoretical framework.Some self-report measures were based on conceptual frameworks proposed by the author(s) of the measure. The McGill Pain Questionnaire (MPQ) was based on a Melzack's theory of pain . This reOther measures stated the construct measured but without explicit definition. The EuroQol was developed as a standardised non-disease specific measure for describing and valuing health-related quality of life . The dimno measure was based on both a defined construct and a theoretical framework.Thus although three measures defined the construct of interest, Six of the fourteen measures appeared to use standard psychometric scaling methods. The stated scaling methodology of the SF-36, WOMAC and WHOQOL was Likert scaling. The WOMAC could, alternatively, be implemented using a 0–100 mm visual analogue scale for each item, with descriptive anchors of none and extreme. A numeric rating scale version of the WOMAC has also been developed, with response categories between 0 (none) and 10 (extreme) . While tAn econometric scaling method was used for the development of the EuroQol. This method involved subjects rating health states (from combining different levels from each item) and results in values being attached to each health state. The Disease Repercussion Profile used a combination of open questions and 10-point graphical rating scales to create a graphical profile score. The HAQ-DI did not appear to have been developed using a standard scaling technique.None of the clinician report measures appeared to have been developed using a standard scaling technique nor did they explain their scaling strategy.A range of techniques was used to generate the items within a measure. There was no information on the item selection techniques for the Harris Hip Score, Hospital for Special Surgery Knee Score, Lequesne Hip and Knee Indices and Merle d'Aubigne Hip Rating. The items for the American Knee Society Score were generated by consensus by members of the American Knee Society. Some measures were based on items from existing instruments . Some items were selected from literature, e.g. McGill Pain Questionnaire. Others started by gathering items from patients, e.g. Oxford Hip and Knee Questionnaires, WOMAC and Disease Repercussion Profile. Some measures took a comprehensive approach and used all these techniques and additional ones . In summary, the method of item generation for the patient self-report measures was generally comprehensive, with most measures using appropriate methods to generate a pool of items that cover the domain of interest. In contrast, there was little information about the choice of items in the clinician report measures.The Arthritis Impact Measurement Scale, McGill Pain Questionnaire, WHOQOL and WOMAC used psychometric methods of item reduction to reduce the number of items. The SF-36 used specific methods to construct short-form measures from the 'parent' longer Medical Outcomes Study measure ,52. The The Disease Repercussion Profile used open questions for each domain, with severity being rated on a ten point graphical rating scale. For the McGill Pain Questionnaire-PRI, the respondents select from each of the 20 categories, the individual descriptive words that best represent their pain. If none of the words in a category apply then the respondent leaves the category out. For the present pain intensity item, the respondent selects one of five response categories.All the other twelve measures had ordered response categories with the Arthritis Impact Measurement Scale & the EuroQol additionally including a visual analogue scale. Six of these twelve measures had items with different numbers of response categories . However, the number of response categories was only discussed for the SF-36 and then only for some items . The othTherefore most of the measures used ordinal (ordered) response formats but there was little consistency of the response format and response continuum within measures. There is much discussion on the problems in performing arithmetic operations and statistical analysis on ordinal scales, mainly due to the unknown interval between categories ,54. The The McGill Pain Questionnaire-PRI used three possible scoring methods for the list of pain descriptors: the number of items chosen (NWC), the mean scale values (PRI(S)), or the summed rank values of items chosen ((PRI(R)). An alternative weighted-rank method of scoring was also developed . The PPITwo measures containing items with different numbers response categories addressed this in their scoring. The Arthritis Impact Measurement Scale used a standardised additive scale. The SF-36 recalibrated the additive scores for linearity and transformed the scores. The American Knee Society Score, Harris Hip Score, Hospital for Special Surgery Knee Score, and Lequesne Hip and Knee Indices  used summated scale systems with the Hospital for Special Surgery Knee Score and American Knee Society Score having items that result in deductions from the point score, e.g., Hospital for Special Surgery Knee Score uses a one point deduction for using a cane. It is unclear how this scoring method was derived and why responses to certain items were allocated their particular points with some items having more weighting than others.The scoring of the measures with constant numbers of response categories varies; an additive score was used for the Likert-type scales of the Oxford Hip and Knee Questionnaires and WHOQOL. An additive scale is also most commonly used for the WOMAC, however other weighting and aggregation methods were proposed  . In addiThree of the measures  had only an overall score. All the others also had subscale scores. The SF-36 and American Knee Society Score only had subscale scores and not an overall score. All other measures had an overall score.In sum, the measures use a wide range of scoring procedures, from the complex weightings in the EuroQol to the simple method of the HAQ-DI (using the highest score within each subclass) that does not fully utilise all the information collected. Jenkinson, 1991  demonstrAlthough most measures gave some indication of what they were measuring, few defined the construct or linked it to a theoretical model. The clinician report measures were generally the poorest measures in this respect. The Arthritis Impact Measurement Scale, SF-36 and WHOQOL defined their construct of interest, but it was not related to a theoretical model. The Disease Repercussion Profile and McGill Pain Questionnaire discussed, in detail, their underlying construct .The measures that appeared to have the weakest methodological development were the clinician report measures with none defining a scaling strategy. The item selection for the American Knee Society Score was by 'consensus' with no other clinician report measure describing the item selection method. No clinician report measure explained their choice of response categories or scoring method.Of the patient self-report measures, only the McGill Pain Questionnaire-PRI was completely developed from a standard scaling procedure. The McGill Pain Questionnaire-PRI was also the only measure with an interval scale, and hence has mathematical and statistical advantages over all the other measures. The other measures that appeared to use a standard scaling procedure were the Arthritis Impact Measurement Scale, Oxford Hip and Knee Questionnaires, SF-36, WOMAC and WHOQOL. The Disease Repercussion Profile and EuroQol used alternative scaling methods, while the HAQ-DI did not appear to have a specific scaling strategy.The method of item selection was generally good for the patient self-report measures, although the item reduction methods were not always explained, except for those that used a defined scaling procedure. In addition, the reasoning for the choice of response formats was not often explained. The scoring method was generally appropriate for the scaling method (where used) and for the item response format, although the HAQ-DI used a method that did not maximise the information available.In summary, the clinician report measures were poor in terms of both their theoretical framework and methodological development. The patient self-report measures appeared to have acceptable methodological development, although there were some limitations with the HAQ-DI. However only the Arthritis Impact Measurement Scale, SF-36 & WHOQOL defined the construct that they were assessing and no measure was part of a theoretical model.While this review has focussed on specific theoretical criteria, it is appreciated that there are other theoretical factors that should be explored such as the rationale for the grouping of items into subscales.This review was based on peer reviewed published literature on the development of the measures, and some theoretical aspects of the development may have been unpublished. However, it is important for users of measures to have this background information, and electronic publishing methods may facilitate access to this more detailed information.The review was based on OA measures that were frequently referenced in the literature and hence some of the newer measures such as the Knee injury and Osteoarthritis Outcome Score (KOOS) , Hip disFurther, this review has focussed on measures used as outcome for osteoarthritis and different conclusions may be reached for other health outcomes or for other conditions. Where outcomes are psychologically theorised, e.g. mood measurements such as anxiety, it is likely that they are more theoretically based and would have used development procedures derived from psychometric theory. However, many health outcomes, especially those involving self-report, require a similar level of attention to measurement issues. They assess patients' experience of their health condition and healthcare and therefore relate to unobservable phenomena rather than phenomena that can be observed by others. One reason for the limited development of some of the measures in osteoarthritis may be that such outcomes have not been articulated as psychological in nature and as a result not subjected to normal psychometric evaluation.This review has highlighted the general lack of attention given to the theoretical framework of the health outcome measures. It would be valuable if new measures could define what they are measuring and be a construct within a theoretical model.The review also demonstrates the large variation in the methodological development of commonly used measures in OA. While patient self-report measures had, in general, good methodological development, this review has also highlighted the relatively poor development of clinician report measures.It is suggested that to improve the quality and performance of new measures, the foundations of their theoretical development should be considered before psychometric evaluation is performed. By ensuring measures are both theoretically and empirically valid, improvements in subjective health outcome measures should be possible.The author(s) declare that they have no competing interests.BP participated in the conception and design of the study, the analysis and the drafting and revision of the manuscript. MJ participated in the conception and design of the study and the drafting and revision of the manuscript. DD contributed to the interpretation of the data and revision of the manuscript. All authors read and approved the final manuscript.Summary information on each measure. Table of summary information on each measure (number of items and item content areas)Click here for fileSummary of the theoretical review. Summary table of the reviewClick here for file


Many questions go unanswered, however, due to lack of skills in formulating questions, crafting effective search strategies, and accessing databases to identify best levels of evidence.Supporting 21This randomized trial was designed as a pilot study to measure the relevancy of search results using three different interfaces for the PubMed search system. Two of the search interfaces utilized a specific framework called PICO, which was designed to focus clinical questions and to prompt for publication type or type of question asked. The third interface was the standard PubMed interface readily available on the Web. Study subjects were recruited from interns and residents on an inpatient general medicine rotation at an academic medical center in the US. Thirty-one subjects were randomized to one of the three interfaces, given 3 clinical questions, and asked to search PubMed for a set of relevant articles that would provide an answer for each question. The success of the search results was determined by a precision score, which compared the number of relevant or gold standard articles retrieved in a result set to the total number of articles retrieved in that set.Participants using the PICO templates (Protocol A or Protocol B) had higher precision scores for each question than the participants who used Protocol C, the standard PubMed Web interface.  95% confidence intervals were calculated for the precision for each question using a lower boundary of zero. However, the 95% confidence limits were overlapping, suggesting no statistical difference between the groups.Due to the small number of searches for each arm, this pilot study could not demonstrate a statistically significant difference between the search protocols. However there was a trend towards higher precision that needs to be investigated in a larger study to determine if PICO can improve the relevancy of search results. Clinicians and educators currently utilize a variety of resources and interfaces to search the biomedical literature to answer clinical questions. PubMed is a service of the U.S. National Library of Medicine (NLM) that provides access to over 16 million citations from MEDLINE and other life science journals dating back to the 1950s . However, the common word "blacks" maps to the broader MeSH term "African continental ancestry group" and retrieves 48195 citations [searched 4/18/07]. Most of the relevant citations used either the word "blacks" or were indexed to the broader MeSH term "African continental ancestry group." The second most common error was related to selecting the wrong study design or Clinical Query for the type of question being searched. This was a common problem for Protocol A, which only listed therapy study designs. The third error affected Protocol C and involved limiting search terms to the title field. While searchers often select their articles based on relevant words in the title, a problem arises when more than one word or phrase is appropriate to the topic. For example, a "peg" is also called a "percutaneous endoscopic gastrostomy tube" or "feeding tube." Limiting the search to the word "peg" in the title eliminates mapping to appropriate subject headings (MeSH) such as intubation, gastrointestinal and therefore may exclude relevant articles on the topic that use alternative terminology. Understanding these errors can help in teaching effective searching and in developing better search systems.In addition to quantitative comparisons, this pilot study provided an opportunity for more open-ended insight into how practitioners search. Some searches within each question  did not retrieve any relevant citations. A qualitative assessment of search strategies that produced no acceptable results revealed three common types of errors: ambiguous mapping of subject headings (MeSH); selecting the wrong publication type; and limiting search queries to just words in the title. The error that accounted for the largest number of non-productive searches was related to the MEDLINE indexing structure or MeSH . In question three, most searchers used the phrase "Perceptions of ease of use and time spent searching were approximately the same across all three protocols, as were the numbers of terms used in each search, regardless of protocol used. However, of the 30 searches performed using Protocol B , 25 (83%) actually incorporated the Clinical Queries into the strategy, as opposed to only 2 (7%) of the searches using Protocol C (PubMed/Web). Both Protocol A and B facilitated the use of publication types and the Clinical Queries by prompting the searcher to consider these elements in the strategy. While these elements were also available in Protocol C, they are either behind the Limits tab or listed in the PubMed Services menu.Effective searching requires a series of steps to lead the practitioner from the clinical question or bedside to informed decision making. In March of 2005, over 68,000,000 searches were conducted in PubMed, from seven million unique IP addresses.  This stuSearches performed on a PICO-formatted screen retrieved a higher percentage of relevant citations than searches performed on the standard PubMed search interface. However, due to the small number of searches for each arm, this pilot study could not demonstrate a statistically significant difference between the search protocols. There was a suggestion of a trend towards higher precision that needs to be investigated in a larger study to determine if PICO can improve the relevancy of search results.The author(s) declare that they have no competing interests.CS and TO participated in the study design, carried out the study, analyzed the results, and contributed to the writing of the manuscript. MA participated in the study design, carried out the study, and contributed to the writing of the manuscript. SK participated in the study design, analyzed the results, and contributed to the writing of the manuscript. All authors read and approved the final manuscript. FP conceived of the study, participated in the study design, developed the PICO templates, and contributed to the writing of the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Enlargement of the European Union has caused worries about the possibility of increased migration from its new members, the former Soviet countries, and consequently increased demands on the health care systems of the host countries. This study investigated whether or not earlier immigrants from the former Soviet Bloc have poorer self-reported mental health, measured as self-reported psychiatric illness and psychosomatic complaints, than the host population in Sweden. It also examined the particular factors which might determine the self-reported mental health of these immigrants.The cross-sectional national sample included 25–84-year-old Swedish-born persons  and immigrants from Poland (n = 161), other East European countries (n = 164), and the former Soviet Union (n = 60) who arrived in Sweden after 1944 and were interviewed during 1994–2001. Unconditional multivariate logistic regression was used in the analyses.The findings indicated that the country of birth had a profound influence on self-reported mental health. Polish and other East European immigrants in general had a twofold higher odds ratio of reporting psychiatric illness and psychosomatic complaints, which fact could not be explained by adjustments for the demographic and socioeconomic variables. However, immigrants from the former Soviet Union had odds similar to those of the Swedish-born reference group. Adjustments for migration-related variables (language spoken at home and years in Sweden) changed the association between the country of birth and the outcomes only to a limited extent.Since poor mental health may hinder acculturation, the mental health of immigrants from Poland and other East European countries should be acknowledged, particularly with the expansion of the European Union and inclusion of nine former Soviet Bloc countries by 2007. Sixteen years after its dissolution, the Soviet Bloc started to be mentioned again in the media when seven of its former members  were invited to join the European Union (EU) in 2004, and another two (Bulgaria and Romania) in 2007. It is just as incorrect now to call these countries former members of the Soviet Bloc as to call the United States a former British colony . HoweverSelf-reported mental health (defined here as self-reported psychiatric illness and psychosomatic complaints) was the focus of this study because mental health is fundamentally interconnected with physical and social functioning and health outcomes and is therefore crucial to the overall well-being of individuals, societies, and countries . MoreoveSweden, at the crossroads between the two sides of the Iron Curtain, has become not only one of several transit countries, but also a place of residence for numerous immigrants from Eastern Europe and the former Soviet Union (FSU) after the dissolution of the Soviet Bloc in 1989 and the FSU in 1991, with increasing migration from east to west. Even before that, refugees sought asylum in Sweden after revolts and political persecutions in the Soviet Bloc. However, due to the Cold War and the Iron Curtain, which significantly reduced European East-West migration, for a long time migration from countries of the former Soviet Bloc to Sweden was characterized by distinct 'waves' of migration directly linked to political events in the countries of emigration . Some ofBy 2001 there were about 110,000 immigrants from the former Soviet Bloc in Sweden. Table Immigrants from the former Soviet Bloc have not been systematically studied as a group and previous studies have mostly focused on immigrants from the FSU. However, the determinants of mental health reported by these studies generally correspond with the characteristics which are known to determine the health  of the population in various countries of the former Soviet Bloc and which, we assume, can be associated with mental health among immigrants from these countries as well.Age [sex [marital status [Age , sex [10Age [sex , and marl status ,13 have social networks for mental health, suggesting that coping with stressful events depends on whether a person has access to a social network as a protective factor.Social capital is another widely-discussed health determinant. In Russia, and supposedly in other former Soviet Bloc countries , social occupation (a socioeconomic classification characteristic used in Sweden [Housing tenure (owning or renting one's living quarters) is another important SES characteristic for studying a person's health. Residential areas with privately owned homes are occupied by people with good resources. The turnover of residents is less intensive in such areas and, consequently, there are more contacts between neighbors. "Such conditions give a freedom of action that is beneficial to health" [Socioeconomic status (SES) and many of its components, such as n Sweden ), are aln Sweden . Housing health" .Cigarette smoking has been shown to have a strong effect on health in various countries of the former Soviet Bloc in terms of mortality and morbidity [orbidity -28. Howeorbidity ,29,30.Acculturation – a complex social, cultural, and psychological process of adapting to a different society , is anotThe length of time since immigration has often been referred to as a health determinant and an indirect indicator of acculturation. Ritsner & Ponizovsky have shown that the acculturation of immigrants, and particularly the path of psychological distress connected with the process of acculturation, is not linear or U-shaped, but occurs in several phases . Therefoyears spent in the host country and the year of immigration may also indirectly represent the reason for migration, particularly for immigrants from the former Soviet Bloc to Sweden. While the late 1990s and the beginning of the new millennium brought many economic, labor and family reunion immigrants to Sweden from the countries of the former Soviet Bloc, the previous decades were generally characterized by the wave-immigration of asylum-seekers and political refugees escaping from the persecutions in the Soviet Bloc. The premigration experiences of life under comunist rule, defined by central planning, coercion, terror and communist nationalism [per se . Howeveiew, see . Years smination  in the hThere are various possible pathways of causal influence between these, as well as other factors not mentioned here, and the mental health of immigrants from the former Soviet Bloc. The discussion of each one of them deserves consideration in its own right. Unfortunately, this is not possible in a short article. We therefore limited the scope of this study to the health determinants that have been particularly known to influence the health of persons born in these countries. Our intention in this study was to find out whether these determinants could explain the poorer mental health of immigrants from the former Soviet Bloc often reported in other studies ,10,38-43This study was based on eight pooled, cross-sectional random samples of permanent Swedish residents (including immigrants with permanent residence permits or Swedish citizenship). The samples consisted of men and women aged 25 to 84, of whom 385 were immigrants from Poland (n = 161), Eastern Europe (n = 164), and the FSU (n = 60) who arrived in Sweden after 1944. The information was collected by trained interviewers in face-to-face interviews as part of the Swedish Annual Level of Living Survey (SALLS) between 1994 and 2001.The reliability of the survey questions was tested in other contexts in Swedish  and LatiAlthough ideally it would have been desirable to test the reliability of the questions in the immigrants from the former Soviet Bloc as well, this was not possible because the current study was undertaken 5 to 12 years after the original surveys (1994 to 2001) were made.self-reported psychiatric illness and psychosomatic complaints.Self-reported mental health was defined in the present study as the Self-reported psychiatric illness was derived from two questions:1) "Have you any long-standing illness, after-effects of injury, disability, or other ailment? Name and describe in detail each ailment/illness." The coding group at Statistics Sweden assigned diagnoses according to ICD-9 (even after 1997) to everything the respondents had reported when answering this question. For the present study, all respondents with the diagnoses 290–319 were defined as having a self-reported long-standing psychiatric illness.2) "Do you have anxiety?" . Those who answered "Yes, severe" and "Yes, slight" were regarded as having anxiety.self-reported psychiatric illness.All persons who reported having any long-standing psychiatric illness (1) and/or anxiety (2) were categorized as having a Psychosomatic complaints were derived from the questions:(1) "Have you experienced any of the following during the last two weeks: (a) often feeling tired; (b) feeling tired during the day; (c) feeling tired in the evenings; (d) suffering from repetitive headaches or migraine; and/or (e) sleeping difficulties?" (Yes/No)or "Yes, slight" were considered to experience aching or pain.(2) "Have you (f) experienced aching in the shoulders or neck; (g) back pain, pain in the hips or sciatica; (h) pain or aching in the hands, elbows, legs, or knees?" . Those who answered "Yes, severe" psychosomatic complaints.Persons reporting three or more of the above complaints (a-h) were considered to have Country of birth was categorized into:- "Sweden" (reference group);- "Poland";- "Other East European countries" – a composite of Hungary, Bulgaria, the Czech Republic, Slovakia, and Romania; and- "The former Soviet Union" – a composite of all 15 former republics.With the exception of the German Democratic Republic (GDR), all the countries once making up the Soviet Bloc were included in the study. The GDR was excluded because it has been coded as "Germany" together with the Federal Republic of Germany in the SALLS database for the majority of the years of the present study. This made it impossible to define people born specifically in the GDR for our 1994–2001 study period.de facto already come under Soviet control at the end of the Second World War. Consequently, we chose to include immigrants from the countries of the former Soviet Bloc who came to Sweden after 1944, rather than after its official date of creation. We have also included immigrants who arrived after its dissolution in 1989 because they had lived in the Soviet Bloc before that date.The official date of the creation of the Soviet Bloc is May 14, 1955, although Eastern Europe had age , sex, and marital status ("married/cohabiting"/"single" with or without children under 18 years old). The social network index was based on the frequency of contacts with a close friend (from 1–6 days ago to more than 12 months ago) and the neighborly exchange of small services . The answers were ranked from 0 to 5 and the scores for these answers were added up (range: 0–10). Participants with a score of less than 3 were considered to have a "good" social network, others to have a "poor" social network. The social network variable measured as the frequency of contacts does not reflect the 'extensiveness' and 'resourcefulness' of these contacts; nevertheless, it represents the respondent's potential for obtaining support  if in need.Other independent variables were: occupation and housing tenure, were included as independent variables as well. Occupational status  was regarded as present or, in cases of current retirement/unemployment, previous work. Housing tenure referred to "owning"/"renting" one's home. The employment variable (employed/unemployed) was not included since it did not allow ordinary pensioners, early retirement pensioners, disability pensioners, or students to be taken into account.Two proxies of SES, smoking ("Yes/No"). However, the choice of the lifestyle variable was determined by the limitation of our data, namely the incomplete data on other lifestyle characteristics.One variable characterizing the lifestyle of respondents was included in the present analysis, i.e. language spoken at home ("Swedish"/"Other"), and years in Sweden . Year of immigration to Sweden  is presented in Table years in Sweden and yielded almost the same result, however, with a lower fit of data.The following variables were used in the additional analysis as migration-related variables: Language spoken at home represented mastery of language under the assumption that the general mastery of language partly depends on whether a person speaks Swedish at home .Years spent in Sweden and year of immigration to Sweden were included in the study not as proxies of acculturation, but rather to indirectly control for reasons for migration in the defined sample.p > 0.05).The data were analyzed using the STATA software package . UncondiEthical approval of the study was obtained from the Ethics Committee of the Karolinska Institute, Sweden.The three groups of immigrant respondents differed slightly with respect to the descriptive characteristics Table . The larThe personal characteristics (except the migration-related ones) were included in the logistic regression analysis as independent variables. The odds of reporting psychiatric illness and/or psychosomatic complaints varied in different categories of the independent variables. For example, women reported psychiatric illness and psychosomatic complaints almost twice as often as men. Similarly, respondents occupied with other than the white-color work, respondents who rented their homes, and those who smoked reported psychiatric illness and psychosomatic complaints more often than their counterparts. Those who were single reported psychiatric illness more often than those who were married/cohabiting, as did respondents with a poor social network, compared to those with a good social network. Most importantly, respondents who were born in Poland or other East European countries reported both psychiatric illness and psychosomatic complaints almost twice as often as the respondents born in Sweden. When all variables were included in the analysis simultaneously, the odds ratios changed marginally and remained as described above Table .These results suggest that there is an association between the outcomes and several of the independent variables, the association which could not be explained by other included variables. The association between the self-reporting of both psychiatric illness and psychosomatic complaints and the country of birth was the most profound: the odds ratios for reporting the outcomes were two times higher among persons born in Poland and other East European countries than among the respondents born in Sweden.Language at home did not influence the odds of the outcomes, but years in Sweden (Model 3b) largely decreased the odds ratio of reporting psychosomatic complaints among immigrants from Poland and other East European countries. Thus it can be regarded as a confounder for psychosomatic complaints, but not for psychiatric illness (Model 3a).This association has been tested further. The FSU-born respondents were treated as a reference group, Swedish-born respondents were excluded  for first hospital admissions due to mental disorders among immigrants from the former Soviet Bloc 25–84 years old, who arrived to Sweden after 1944 and lived in Sweden during 1994–2001. We found that both women and men born in Poland , as well as women born in other East European countries  had a higher hazard ratio of being hospitalized due to mental disorders than the Swedish-born women and men. However, persons born in the FSU, regardless of their sex, did not have a higher hazard ratio compared to Swedish-born persons .Country of birth showed to have a profound influence on self-reporting of psychiatric illness and psychosomatic complaints among the immigrants from the countries of the former Soviet Bloc in Sweden. Other variables often mentioned in the literature on the health of immigrants from or populations inhabiting the countries of the former Soviet Bloc (i.e. demographic and socioeconomic variables) influenced the self-reported mental health, but could not explain the association between the country of birth and the outcomes.country of birth has a more profound influence on mental health than age [This is in conformity with the small number of other studies showing that than age  and thanthan age ,52 amongThe influence of the country of birth on the self-reported mental health differed among the three immigrant groups in the present study. Immigrants from Poland and other countries of Eastern Europe had poorer self-reported mental health with, in general, twofold higher odds of reporting psychiatric illness and psychosomatic complaints than persons born in Sweden. This could not be explained by the demographic or socioeconomic variables. However, immigrants from the FSU had odds of reporting psychiatric illness and psychosomatic complaints similar to those of the Swedish-born reference group. This finding was also supported by the analysis of the of hospital admissions due to mental disorders.The finding of higher odds for poor self-reported mental health among immigrants from Poland and other East European countries in the present study agrees with the studies of self-reports and of hospital admissions from Sweden, Britain, and the US and with other cross-sectional and longitudinal studies, as well as studies on war and on political refugees -42. It iThe finding that immigrants from the FSU had similar odds of poor self-reported mental health to those of the host population does not agree with studies conducted elsewhere (the vast majority of the earlier studies have been made in the US and Israel) ,10,38,43We can only speculate as to why immigrants from the FSU did not have higher odds of poor self-reported mental health than the Swedish-born host population and had lower odds than immigrants from the other former Soviet Bloc countries (nonsignificant). It is possible that persons born in the FSU are afraid of stigmatization, have a more negative attitude toward mental disorders and their treatments  and are inclined not to report poor mental health or seek help for mental disorders. The lower odds for psychosomatic complaints among immigrants from the FSU compared to immigrants from Poland might also be explained by the fact that persons born in the FSU are inclined to hide their private feelings , to be aAnother possible explanation of the different odds for poor self-reported mental health among immigrants from the former Soviet Bloc is better mental health among persons born in the FSU than among those born in the other former Soviet Bloc countries. According to the World Health Organization  in 2002, the prevalence of mental disorders in the FSU (2.8%) was lower than in the former Czechoslovakia (3.5%) and Poland (3.2%).psychosomatic complaint is a culturally sensitive variable because representatives of every nation have their specific way of somatizing or expressing their ill-health. Inhabitants in or immigrants from different countries communicate their health, particularly mental health, differently [psychiatric illness variable was self-reported and not clinically validated was the most important limitation of the study. Self-reported health is a reliable indicator of health [It is very difficult, however, to compare rates of self-reported mental health since the self-administered screening instruments in psychiatry show different cut-off points in different cultures. For example, ferently ,55-57. Tf health , pretermf health -61, and f health ,63. HoweNevertheless, the additional testing of this variable by performing an analysis of the hospital admission data for mental disorders in the same population supported the results of the present study, confirming our assumption that self-reported mental health may be a good indicator of mental health. Moreover, self-reported mental health is associated with mortality as self-reported health is ,65 and wAnother limitation of the present study is that the immigrant groups focused on probably lacked homogeneity not only between themselves with regard to self-reported mental health and other characteristics , but also within themselves. For example, the three Baltic FSU republics have joined the European Union and differ from the other FSU republics in many other respects. Therefore, it is difficult to say whether the results of the present study are fully applicable to immigrants from these now independent countries when considered separately from the whole FSU; thus this applies to the East European countries. Nevertheless, immigrants with different backgrounds had to be combined in larger categories ("Other East European countries" and "The former Soviet Union") to achieve sufficient statistical power and to conduct the analyses in the present study. Poland was categorized separately due to a large number of Polish immigrants in Sweden. The FSU was categorized separately due to differences in the economy and health of the inhabitants of the FSU compared to other East European countries .The limitations of the cross-sectional design of the present study prevented us from tracing any causal pathways between the migration of people from the former Soviet Bloc and self-reported mental health, and we could only speculate about the determining mechanisms behind the reporting of psychiatric illness and psychosomatic complaints. A lack of data on alcohol consumption was also a limitation for a study on self-reported mental health, although an adjustment of outcomes was made for smoking. The questionnaire was not specifically designed for the present study and we had to use the available data rather than collect our own. Additionally, it was not possible to perform a clinical evaluation to test the reliability of the instruments because the design of the national survey does not include a clinical examination or a clinical instrument.Finally, the sample size, especially of immigrants from the FSU, was small and possibly affected the significance of the analysis. However, in spite of its small size, it included immigrants from the various former Soviet republics, and the proportion of respondents was representative of all 25–84-year-old FSU immigrants who arrived in Sweden after 1944. The weighted mean population from our sample was similar to the average number of persons of the same age and country of birth living in Sweden registered by Statistics Sweden during 1994–2001 (not shown).The strengths of the extensive SALLS data balanced the limitations. SALLS is performed annually by Statistics Sweden and is designed to obtain information about the Swedish living conditions of the Swedish population. Statistics Sweden is a governmental statistical bureau with a long tradition of carrying out national surveys and analyzing the collected data. The data collected by Statistics Sweden is used in multiple studies and for the national statistical reports. The reliability of the survey questions is high and the nonresponse is rather low. The nonresponse rate in SALLS during 1994–2001 was about 20%, mostly due to refusal to take part. In the earlier samples it was found that those who refused to participate (2/3 of nonrespondents) had the same mortality rate as the respondents. Regretfully, it was impossible to estimate the particular nonresponse among the immigrants in this study because the sample in SALLS is not chosen according to the country of birth.A more detailed description of the SALLS can be found elsewhere .According to the findings of the present study, the influence of country of birth on the self-reported mental health was profound and could not be explained by other health determinants, such as age, sex, marital status, social network, SES, or smoking.The self-reported mental health differed, however, among immigrants from the different former Soviet Bloc countries. Unlike the immigrants from the FSU, immigrants from Poland and other East European countries generally had a twofold higher odds ratio for reporting psychiatric illness and psychosomatic complaints than adults born in Sweden after adjusting for demographic and socioeconomic variables. An adjustment for migration-related variables changed it only to the limited extent.These findings and prior awareness of the health of immigrants from countries focused on in the present study should be acknowledged, particularly with the continuing expansion of the European Union.The author(s) declare that they have no competing interests.All three authors have made substantial contributions to the present study. All the authors read and approved the final version of the manuscript.YB performed the analyses and the literature review and was mainly responsible for the writing of the manuscript.SEJ participated in the design of the study and coordinated the statistical analysis and helped to revise an earlier version of the manuscript.JS participated in the design and coordination of the study and helped to draft the manuscript.The pre-publication history for this paper can be accessed here:


Mitochondrial DNA (mtDNA) haplotypes have become popular tools for tracing maternal ancestry, and several companies offer this service to the general public. Numerous studies have demonstrated that human mtDNA haplotypes can be used with confidence to identify the continent where the haplotype originated. Ideally, mtDNA haplotypes could also be used to identify a particular country or ethnic group from which the maternal ancestor emanated. However, the geographic distribution of mtDNA haplotypes is greatly influenced by the movement of both individuals and population groups. Consequently, common mtDNA haplotypes are shared among multiple ethnic groups. We have studied the distribution of mtDNA haplotypes among West African ethnic groups to determine how often mtDNA haplotypes can be used to reconnect Americans of African descent to a country or ethnic group of a maternal African ancestor. The nucleotide sequence of the mtDNA hypervariable segment I (HVS-I) usually provides sufficient information to assign a particular mtDNA to the proper haplogroup, and it contains most of the variation that is available to distinguish a particular mtDNA haplotype from closely related haplotypes. In this study, samples of general African-American and specific Gullah/Geechee HVS-I haplotypes were compared with two databases of HVS-I haplotypes from sub-Saharan Africa, and the incidence of perfect matches recorded for each sample.When two independent African-American samples were analyzed, more than half of the sampled HVS-I mtDNA haplotypes exactly matched common haplotypes that were shared among multiple African ethnic groups. Another 40% did not match any sequence in the database, and fewer than 10% were an exact match to a sequence from a single African ethnic group. Differences in the regional distribution of haplotypes were observed in the African database, and the African-American haplotypes were more likely to match haplotypes found in ethnic groups from West or West Central Africa than those found in eastern or southern Africa. Fewer than 14% of the African-American mtDNA sequences matched sequences from only West Africa or only West Central Africa.Our database of sub-Saharan mtDNA sequences includes the most common haplotypes that are shared among ethnic groups from multiple regions of Africa. These common haplotypes have been found in half of all sub-Saharan Africans. More than 60% of the remaining haplotypes differ from the common haplotypes at a single nucleotide position in the HVS-I region, and they are likely to occur at varying frequencies within sub-Saharan Africa. However, the finding that 40% of the African-American mtDNAs analyzed had no match in the database indicates that only a small fraction of the total number of African haplotypes has been identified. In addition, the finding that fewer than 10% of African-American mtDNAs matched mtDNA sequences from a single African region suggests that few African Americans might be able to trace their mtDNA lineages to a particular region of Africa, and even fewer will be able to trace their mtDNA to a single ethnic group. However, no firm conclusions should be made until a much larger database is available. It is clear, however, that when identical mtDNA haplotypes are shared among many ethnic groups from different parts of Africa, it is impossible to determine which single ethnic group was the source of a particular maternal ancestor based on the mtDNA sequence. The Atlantic slave trade resulted in the forced migration of an estimated 11 million Africans to the Americas. Only 9 million are thought to have survived the passage, and many more died in the early years of captivity. Historical accounts indicate that virtually all enslaved Africans brought to North America came from either West or West Central Africa. A recent comparison of mtDNA sequences from 1148 African Americans living in the US with a database of African mtDNA sequences showed that more than 55% of the US lineages have a West African ancestor, while fewer than 41% came from West Central or South West Africa . Among tBecause mitochondrial DNA (mtDNA) is passed from mother to daughter with few, if any, changes occurring over many generations, it is possible to compare contemporary African-American mtDNA haplotypes with contemporary mtDNA haplotypes in a worldwide database to obtain information about the ancestral origins of these mtDNAs. In such a comparison, continent-specific haplotypes are readily observed, and the assignment of mtDNAs to continent of origin is relatively straightforward. The more difficult task is to tie particular mtDNA haplotypes to specific geographical regions and ethnic groups within a continent. This task is particularly difficult for Africa, as there is more genetic diversity among Africans than among people from any other continent and because humanity has resided in Africa longer than anywhere else.Comparisons of individual mtDNA haplotypes could be used to identify a geographical region, particular country, or even an ethnic group from which a maternal ancestor emanated. However, the geographic distribution of mtDNA haplotypes is greatly influenced by the migration of individuals or population groups. These movements often result in the assimilation of people from other ethnic groups. Intermarriage also causes mtDNA haplotypes to move from one ethnic group to another. Over time, mtDNA haplotypes that originated in a single ethnic group are distributed among many ethnic groups. Despite these complications, mtDNA analyses for the purposes of ancestry reconstruction are increasing in popularity. Many people have had their mtDNA tested with the hope that the test will match their DNA to an mtDNA haplotype found in a particular ethnic group. For African Americans, who have been disenfranchised from their specific African roots, such a test might provide a clue about the ethnic group or country in Africa where one of their maternal ancestors originated. However, if identical mtDNA haplotypes are shared among many ethnic groups from different parts of Africa, it would be impossible to use DNA sequence information to determine which single ethnic group was the source of a particular maternal ancestor. To date, there are no published assessments that provide quantitative information about how often African-American mtDNAs are exact matches to multiple African ethnic groups. Therefore, we decided to compare samples of Carolina coast and other African-American mtDNAs to a database of sub-Saharan African mtDNAs to generate such an assessment.We assembled a database of 3645 mtDNA HVS-I sequences from the published literature and 80 additional sequences from our own (unpublished) studies of ethnic groups in Mali to generate a database of 3725 sequences. Only sequences from sub-Saharan Africa were included in the database, because North African mtDNAs are quite different from sub-Saharan mtDNAs  and few To provide a regional analysis of the database, samples were assigned to geographic regions as shown in Table Two of the regional groupings, East and South, had an excess of sequences that were found in a single ethnic group, and a corresponding deficit of matches to sequences from multiple regions. This result is consistent with the idea that these two regions are dominated by samples that have low levels of the mtDNA haplotypes that are characteristic of the Bantu ,5. In coBrer Rabbit stories, praise houses) including a distinct linguistic style with roots among the Mende peoples of Sierra Leone, West Africa. When a sample of 74 Gullah/Geechee mtDNA sequences was compared with the sub-Saharan database, approximately half of the mtDNAs were identical to two or more mtDNAs in the database and only seven mtDNAs matched mtDNAs from a single ethnic group , were compared with both the original and the expanded databases to provide a sense of how increasing the database size impacts the distribution of exact matches. The Gullah/Geechee people are an African-American microethnic group residing in the Georgia/South Carolina Lowcountry and coastal islands whose numbers are now estimated between 200,000 and 500,000 in the Sea Islands of South Carolina, Georgia, North Florida, and beyond . Gullah/up Table . The remSimilar results were obtained when the 97 African-American AFDIL mtDNAs were compared with the databases. Approximately half (49) of the mtDNAs were identical to multiple sequences in the original database Table . As withWhen the unmatched AFDIL and Gullah/Geechee mtDNAs were combined and analyzed further, 63% differed from a database sequence at a single nucleotide position Table . Nearly The majority of African-American mtDNAs that were identical to database mtDNAs matched mtDNAs from ethnic groups that were scattered throughout sub-Saharan Africa. However, 41% of the Gullah/Geechee and 37% of the AFDIL mtDNAs that matched database sequences were identical to mtDNAs found only in western  Africa Table . Only onConsidering Africa's geographical size and population density, and the duration of human residence on this continent, linguistic diversity at the taxonomic level of family is amazing low. This low level of linguistic diversity is probably the consequence of protracted mobility and interaction among Africa's indigenous groups, facilitated by the longstanding presence of such organized political-social units as kingdoms and empires and such sociocultural practices as polygamy.Among the AFDIL sequences with more than five matches to various African ethnic groups, most language diversity was within the various subfamilies of the Niger-Congo family. These subfamiliesinclude Atlantic Congo  and Mande . However, in some of the sequence matches, different linguistic families were represented altogether, including the Afro-Asiatic  and Nilo-Saharan  families, along with members of the Niger-Congo family.The most extensive pan-African haplotype (16189 16192 16223 16278 16294 16309 16390) is in the L2a1 haplogroup. This sequence is observed in West Africa among the Niger-Congo family including the Malinke, Wolof, and others; in North Africa among the Afro-Asiatic family including the Hausa and others; in Central Africa among the Niger-Congo family including the Bamileke and others; in South Africa among the Khoisan family including the Khwe and the Niger-Congo family Bantu speakers; and in East Africa among the Niger-Congo family Kikuyu. Closely related variants are observed among the Afro-Asiatic family including the Tuareg in North and West Africa and among the East African Nilo-Saharan family Dinka. Thus, identical mitochondrial haplotypes are often shared among ethnic groups with considerable language diversity.Because only a small fraction of the sub-Saharan African ethnic groups have been sampled, and there are parts of sub-Saharan Africa that are poorly represented in our database Figure , our datAnother way to assess our sub-Saharan mtDNA database would be to see how well African-American mtDNAs match database sequences. Historical accounts of the trans-Atlantic slave trade indicate that most North American slaves came from the western coast of Africa, including the geographical regions from present-day Angola to Senegal. When African-American mitochondrial DNA HVS-I sequences were studied, nearly half were identical to those from two or more African ethnic groups in our expanded database. Furthermore, the average number of perfect matches per matching African-American mtDNA increased from 3.6 different ethnic groups to 6.1 different ethnic groups when the size of the database was increased by 53% to its present size of 3725 sequences. These results reflect the fact that approximately half the mtDNA sequences in our sub-Saharan database are shared by members of three or more ethnic groups.In both of the African-American samples, approximately 40% of the mtDNA sequences did not match any sequence in any other ethnic group Table . HoweverMany African Americans are interested in learning more about their African roots and are willing to pay to have their mtDNA analyzed in the hope that it will match DNA from a particular African ethnic group. However, as more than half of the mtDNA sequences in the African database are identical to sequences from other ethnic groups, African-American mtDNAs will be much more likely to match sequences from multiple ethnic groups than sequences from a single ethnic group. When this result is coupled with the fact that 40% of African-American mtDNAs did not match any sequence in the database, it is clear that matches to a single African ethnic group will not be the outcome for most African Americans, and even when a match to a single ethnic group is obtained, multiple matches may occur in a larger database. Furthermore, for the typical African American, the maternal ancestor who was the source of the mtDNA was just one of hundreds of enslaved African ancestors. In fact, it likely that there has been more mixing of African ethnic groups in the Americas than has ever occurred elsewhere. Thus, the ancestors of virtually all contemporary African Americans came from a large number of ethnic groups located throughout the region from Senegal to Angola.Half of the sub-Saharan mtDNA sequences in our database are common haplotypes that are shared among ethnic groups from multiple regions of sub-Saharan Africa. The finding that fewer than 10% of African-American mtDNAs matched mtDNA sequences from a single African region suggests that as few as one in nine African Americans may be able to trace their mtDNA lineage to a particular region of Africa. However, no firm conclusions should be made until a much larger database is available. It is clear, however, that nearly half of contemporary African-American mtDNAs are identical to African haplotypes that are found in multiple ethnic groups throughout sub-Saharan Africa. For these mtDNAs, it is impossible to use only mtDNA sequence information to determine which single ethnic group was the source of the maternal ancestor.A sample of 78 African Americans who self-identified as Gullah/Geechee was generated by our laboratories from unrelated people sampled in the coastal areas of South Carolina and Georgia using either cheek swabs or mouthwash to collect buccal cells. DNA was isolated using a BuccalAmp DNA Extraction Kit  for the cheek swabs or a DNAzol procedure  for the mouthwash samples. The HVS-I region was amplified and sequenced as described previously . Those mA database of 3725 mtDNA HVS-I sequences from people living in sub-Saharan Africa was assembled from the published literature in October 2005 Table . DNA froBE, JLW, BAJ participated in the assembly of the database. The database comparisons were performed by BE. All authors contributed to the interpretation of the data and the writing of the manuscript.


N-glycosylation plays a key role in the quality of many therapeutic glycoprotein biologics. The biosynthesis reactions of these oligosaccharides are a type of network in which a relatively small number of enzymes give rise to a large number of N-glycans as the reaction intermediates and terminal products. Multiple glycans appear on the glycoprotein molecules and give rise to a heterogeneous product. Controlling the glycan distribution is critical to the quality control of the product. Understanding N-glycan biosynthesis and the etiology of microheterogeneity would provide physiological insights, and facilitate cellular engineering to enhance glycoprotein quality. We developed a mathematical model of glycan biosynthesis in the Golgi and analyzed the various reaction variables on the resulting glycan distribution. The Golgi model was modeled as four compartments in series. The mechanism of protein transport across the Golgi is still controversial. From the viewpoint of their holding time distribution characteristics, the two main hypothesized mechanisms, vesicular transport and Golgi maturation models, resemble four continuous mixing-tanks (4CSTR) and four plug-flow reactors (4PFR) in series, respectively. The two hypotheses were modeled accordingly and compared. The intrinsic reaction kinetics were first evaluated using a batch (or single PFR) reactor. A sufficient holding time is needed to produce terminally-processed glycans. Altering enzyme concentrations has a complex effect on the final glycan distribution, as the changes often affect many reaction steps in the network. Comparison of the glycan profiles predicted by the 4CSTR and 4PFR models points to the 4PFR system as more likely to be the true mechanism. To assess whether glycan heterogeneity can be eliminated in the biosynthesis of biotherapeutics the 4PFR model was further used to assess whether a homogeneous glycan profile can be created through metabolic engineering. We demonstrate by the spatial localization of enzymes to specific compartments all terminally processed N-glycans can be synthesized as homogeneous products with a sufficient holding time in the Golgi compartments. The model developed may serve as a guide to future engineering of glycoproteins. A vast majority of these recombinant proteins are glycoproteins. The extent of glycosylation and the structure of the glycans on those glycoproteins have a profound effect on their biological activities and circulatory half-life  core structure. The high mannose glycans have 5 to 9 mannose (Man5–9GlcNAc2) sugars. Those with 2 GlcNAc's attached to the tri-mannosyl core are called complex type. As its name implies, the hybrid type are a combination of high mannose and complex glycans, and have at least three mannose sugars, but only one GlcNAc on one nonreducing mannose. This diversity of glycan sugar composition on each glycosylation site is referred to as microheterogeneity.N-glycan structures are generally classified into three principal categories: high mannose, complex and hybrid types. All of them share a common tri-mannosyl  cisternae. These cisternae are not biochemically homogeneous. As the secretory glycoproteins traverse through these Golgi compartments the glycan extension reactions are catalyzed by varying compositions of glycosylation enzymes in each compartment. There are still unresolved questions on the nature of Golgi compartmentalization and different models on intra-Golgi transport have been proposed From a classical reaction engineering perspective the two models present two different idealized reactor scenarios. The vesicular transport model resembles a model of continuous stirred tank reactors in series (CSTR's). The glycoprotein molecules enter the first compartment and after a finite amount of holding time they are continuously transported to the next one downstream. Conversely, protein processing in the Golgi maturation model is better represented by a non-stationary batch reactor. The reactor thus closely resembles a plug-flow reactor (PFR), the traversal of protein over time in the maturation model can be viewed in the same way as traveling downstream in a tubular reactor. A key distinction between the two models is that in the maturation model all protein molecules entering the Golgi together will exit at the same time, while in the vesicular transport model, mixing in each compartment facilitates different protein molecules residing in each compartment for different lengths of time. Common to both models is that the enzyme composition varies as the glycans proceed downstream. Since the time each protein molecule spends in the Golgi compartments affects the extent of glycan extension, the distribution of residence times will have a profound effect on their N-glycan structure.The microheterogeneity of N-glycans on glycoproteins can thus be attributed to the nature of the glycosylation reactions and the mixing characteristics of the Golgi apparatus as proteins traverse the system. With the clinical importance of glycoprotein therapeutics, there is a strong desire to better control the variability of glycoforms of those products. A better understanding of kinetics of the reactions involved and the maturation process of Golgi apparatus will certainly aid in the control of microheterogeneity of glycoprotein products. However, with the reaction kinetic parameters difficult to determine experimentally, and with the model of Golgi processing still being debated, experimental assessment of the source of microheterogeneity and exploration of their control is difficult. An alternative to experimental investigation is through mathematical modeling to assess the effectiveness of metabolic intervention towards the channeling of glycans under different models.Previous studies have applied mathematical models to evaluate protein N-glycosylation microheterogeneity The model of N-glycosylation considers the core N-glycan biosynthetic pathway in the Golgi apparatus common to most host cells used for the expression of recombinant proteins. The pathway consists of a large number of reactions catalyzed by a relatively small number of enzymes. The ability of many of these enzymes to catalyze the same reaction on different glycan substrates, and the fact that most glycans can possibly be a substrate of more than one enzyme, makes this pathway form a highly branched, initially divergent, and eventually convergent network. Since the model considers glycosylation reactions in the Golgi, the input into the system is considered to be a 9-mannose glycan on a single Asn-x-Thr/Ser glycosylation site that can be processed in the Golgi.The N-glycosylation enzymes considered in this model are shown in The model considers glycosylation reactions occurring in four compartments of equal volume in series, representing the cis, medial, trans, and trans-Golgi network (TGN) compartments. Inter-compartmental transport of glycosylated protein molecules is limited to adjacent compartments via retrograde and anterrograde transport. The glycoprotein is transferred from the ER into the first compartment. From each subsequent compartment the glycans are transferred to the next, eventually being secreted from the last compartment in an anterrograde manner. The volume of each compartment is assumed to be constant; implicitly balanced by anterrograde transport from the upstream compartment. For simplification, no retrograde transport or the reverse flow of the glycoprotein is considered. The holding time for glycoproteins in each compartment is set to be the same. A schematic of the Golgi system is shown in The enzyme composition in each compartment may differ as reported Mass balances on the N-glycan species for each of the compartments in the CSTR model give the following:In the PFR model both space and time are independent variables as shown below,For both the CSTR and PFR models the anterrograde transport from the ER into the cis compartment is assumed to include only the initial 9-mannose glycan attached to the glycoprotein as input into the entire system. Unless specified, it is assumed that the amount of glycoproteins contributed from retrograde transport in the other compartments is negligible.th reaction catalyzed by enzyme em in compartment n is expressed as:i is any glycan which can be a substrate of em, and in the case of the latter, sj refers to the corresponding nucleotide-sugar  exoglycosidase enzymes use glycans as their sole substrate, while the other eight  glycosyltransferases use both N-glycans and the corresponding nucleotide-sugar as substrates. The one substrate enzymes were considered to follow Michaelis-Menten kinetics with substrate competition. The two substrate enzymes were assumed to follow a rapid equilibrium, random, bi-bi mechanism. Each of the glycosyltransferases can add a monosaccharide to multiple glycans through the formation of a specific glycosidic bond. Those glycans are treated as competing substrates. For the one substrate enzymes, the equation for the pugar see . As a re−9 mg per cell , a level commonly seen in highly secretory cells, and possibly closer to the levels in the types of cells reported in the literature The ten enzymes were considered to have a spatial localization across the Golgi cisternae. The mannosidases are generally localized towards the cis/medial regions of the Golgi, the N-acetylglucosaminyltransferases and fucosyltransferases are localized towards the medial region, and the galactosyltransferases and sialyltransferases are localized towards the trans and trans-Golgi network (TGN) regions of the Golgi. In our model, unless otherwise specified, Man I-II are assumed to be localized in the four compartments in a  ratio; GnT I-V were localized in a  ratio; and GalT and SiaT in a  ratio The model equations were solved in Matlab  using an implicit ODE solver. The initial glycan concentrations were all assumed to be zero, except the first initial 9 mannose glycan, whose concentration was set equal to the total protein concentration. All calculated solutions were stable steady states with negative, real eigenvalues. The simulation results are displayed through a pathway visualization program, GlycoVis An objective of this study was to gain insight on the effects of different variables on the resulting glycan distribution. We sought to obtain a set of parameter values for which all the terminally processed glycans are well represented in the product mixture, so that any perturbation introduced can be better seen. While keeping the kinetic parameters constant  sufficiently long for a complete conversion of all glycans to the terminally processed glycans. The initial 9-mannose glycan that enters the compartment reacts to form intermediate glycans as it moves downstream. At different time points after its entry , a snapshot of the concentration profile of all glycans, and the flux of every reaction was taken. The enzyme and nucleotide-sugar concentrations used were obtained from nonlinear optimization, as explained in the Model section, and are listed in The twelve terminally processed N-glycans at different time points after the initial glycan enters the Golgi are shown in In a reaction system with branched pathways, like the protein N-glycosylation pathway, the branch points determine the distribution of fluxes and are the controlling points where fluxes can be directed towards a particular product. However, the glycosylation reaction system is a complex system with an extensive substrate spectra for many of the enzymes involved. Except for GnT I, which reacts upon only one glycan, and Man I which reacts upon the earliest high mannose glycans, the other enzymes are involved in multiple branches of the pathway. In fact, these eight enzymes generated 326 glycans in the pathway. Many enzymes involved in a reaction at a particular branch point are also involved in other downstream reactions in the same, and/or different branches. Channeling the flux at a branch point by amplifying the enzyme involved, or by suppressing another enzyme catalyzing a competing reaction, will invariably cause changes in other downstream reactions. The end results thus may not be as expected.To assess the effect of different enzyme levels on the resulting N-glycan profile, sensitivity coefficients of the 12 terminally processed glycans were calculated with respect to the 10 enzymes after 40 minutes; sufficiently long for all reactions to complete . As expe1 but also in other GalT catalyzed reactions , to intermediate, and terminally processed glycans Of the 12 terminally processed glycans, some have a shorter reaction path leading to their formation  whereas others have a longer reaction path . The positions of these two different terminal glycan types on the reaction network are highlighted in The 4PFR model simulation results points to how high mannose glycans can become a rather significant fraction of the product glycans as has been reported To assess whether glycans on a glycoprotein can be directed to become “uniform” we applied the non-linear optimization algorithm to vary the spatial distribution of enzymes. The objective function was set to channel the fluxes in the 4PFR model towards glycan 99, a triantennary glycan with a bisecting N-acetylglucosamine. In the 1PFR model this glycan could not be produced as a homogeneous product through the manipulation of enzyme levels alone . We thusThe 10 enzymes considered can be classified into three categories for each compartment. Category I enzymes are those which are essential for channeling glycans to the homogenous end product, category II enzymes are those whose presence in the compartment is neither essential nor detrimental, category III enzymes are detrimental and cause divergence of fluxes and preclude the formation of glycan homogeneity. A number of enzymes in particular compartments are category II; their concentrations in those compartments can be from zero to very high without any consequence on the glycan flux profile. For clarity, the concentrations of category II enzymes in those particular compartments are kept at zero. The entries in Although only the results for glycan 99 are shown, all the other terminal N-glycans could be made to a uniform product given a sufficient holding time and enzyme localization (data not shown). Controlling the order of monosaccharide addition onto the N-glycan, while simultaneously taking advantage of enzyme substrate specificities, facilitates the formation of a less heterogeneous glycoform profile. Experimentally to accomplish the channeling of fluxes towards a homogeneous product may entail localizing category I enzymes in the designated compartments, while simultaneously suppressing category III enzymes in the same compartment. In the case of glycan 99, enzymes Man I, Man II, GnT I, GnT II, GnT V, FucT, SiaT fall into either category I or category II for different compartments. GnT III is a category III enzyme for the medial but falls into category I for the trans compartment. Similarly GalT is a category III enzyme for both the medial and trans compartments, but is an essential enzyme for the final compartment. In the case of GnT IV, even though it doesn't participate in the synthesis of glycan 99, its presence in the medial or trans compartments increases the heterogeneity in the end product, and diverts fluxes away from the glycan.Microheterogeneity of N-glycans is ubiquitously seen in mammalian cell derived recombinant glycoproteins. Since glycan microheterogeneity is a natural phenomenon seen even in glycoproteins in the body, its occurrence per does not pose a concern for therapeutic proteins. However, different glycoforms of therapeutic proteins may affect the pharmacokinetic behavior and the activity of the protein therapeutic. As a result, controlling the microheterogeneity to be within a defined quality range, or even directing the glycan synthesis to the most effective forms is highly desirable. Most glycan intermediates involved in the reaction system can serve as a substrate for multiple enzymes. The ten enzymes considered unequally share 329 glycan substrates. Such extensive competition for these glycan substrates by different enzymes gives the reaction network the look of an intricate web with multiple branches. Rationally engineering the pathway to channel the fluxes towards a preferred glycan may not be an easy task without the aid of careful analysis. In this study we examined a number of factors contributing to heterogeneous glycan distribution.We analyzed the glycosylation reactions at two levels. First the reactions were simulated in a single plug flow reactor to examine the intrinsic reaction kinetics; then we proceeded to examine their behavior in a simulated Golgi apparatus, considering it to be 4PFR in series or 4CSTR in series. The two models resemble the two hypotheses on cargo movement across the Golgi; the cisternal maturation and vesicular transport models.The reaction paths and reaction time to form fully processed N-glycans makes the residence time of the glycoprotein in the Golgi apparatus an important variable. Given a sufficiently long reaction time, all glycan reactants in the input will be converted to fully processed glycans, as can be seen in Since the Golgi is compartmentalized, and is generally thought as having multiple cisternae, it is prudent to examine the glycosylation reactions as such. The Golgi maturation model envisions the Golgi compartments as maturing from early to late cisternae, with its internal content (including enzymes) evolving throughout the maturation process. This time evolution can be viewed as spatial progress over time, just like a plug-flow reactor. We modeled this system as four tubular reactors in series allowing the enzyme concentration to vary in each compartment. An obvious effect of extending from 1PFR to 4PFR is the presence of non-terminal N-glycans in the final product. The holding time used for simulation was more than sufficient for completion of reaction to terminal glycans in a single PFR, nevertheless a substantial amount of non-terminal glycans are seen. The disappearance of early enzymes as the Golgi becomes mature prevents some intermediately processed glycans from achieving terminal processing.1-protease inhibitor to over two hours for transferrin A deviation from plug flow can potentially increase the extent of microheterogeneity since different glycoprotein molecules stay in each compartment for different lengths of time. Indeed, the phenomenon of residence time distribution of secreted protein molecules from the Golgi has been reported By modeling the Golgi apparatus as 4 CSTR's in series the heterogeneity in intermediately processed glycans does increase at a shorter residence time as compared to 4PFR in series.  More speThe simulation of glycan distribution is by no means sufficient to support one model over the other. The true model is likely neither perfect PFR nor perfect CSTR, but a composite between them. Indeed, this has been hypothesized previously Although the 4PFR model predicts a glycan distribution that more closely mimics experimental observation, there are other possible mechanisms which may contribute to the degree of N-glycan microheterogeneity. For example a sorting mechanism may selectively allow cargo to move to the next compartment; thus creating different holding times for different glycan species. The mixing of the enzymes within the compartments may not be best depicted as either perfectly well-mixed or plug flow. The Golgi glycosylation enzymes are all type II transmembrane proteins consisting of an amino terminal cytoplasmic tail, a signal anchor transmembrane domain, a stem region, and a large luminal catalytic domain. Although the proteins being glycosylated are in the lumen of the Golgi, the reactions being catalyzed are on the membranes. As protein substrates travel towards and away from the glycosylation enzymes on the membrane, some degree of micromixing is inevitable.Another key assumption which may have a major effect on microheterogeneity is the relative specificity of the enzymes toward their various substrates. In our model the affinities are assumed to be the same for all glycan substrates for each enzyme. Previous reports have shown that these binding constants are different in some cases In this report we notably did not address the issue of the effect of productivity. Of course, the effect of protein secretion rate on its glycan microheterogeneity is of paramount interest for bioprocessing. One should be reminded that a very large fraction of cellular proteins traverse through the ER and Golgi, in addition to the recombinant protein. The glycosylation machinery, at any given moment, is not only processing glycans on recombinant protein molecules, but also all the other cellular proteins that pass through the Golgi. Strictly speaking, in the kinetic equations an expression of other proteins and their associated glycans ought to be included as competing substrates. The mechanism of high specific productivity is not well-understood. Whether the increased productivity is accompanied by a shorter holding time in the Golgi while maintaining the same Golgi volume, or by an increase in Golgi volume while maintaining the holding time, is not clear. Without a better understanding of the mechanism of increased specific productivity, one cannot rationally predict its effect on the glycoform distribution.Pichia pastoris towards the generation of uniform, and humanized glycoform profiles The order at which the enzymes react upon the N-glycan helps determine the preferential channeling of the biosynthetic pathways towards the product glycans. The results shown in It should also be noted that a large number of proteins transit through the Golgi in addition to the recombinant protein product. Drastically altering the glycosylation pathway may also alter the glycan structure or protein quality of other cellular proteins. Channeling N-glycans to a uniform glycoform thus requires not only information on protein localization, but also a better understanding of the effect of glycan modification on cellular homeostasis. For further exploration of cellular engineering and modulating glycan microheterogeneity one should explore the engineering of enzymatic substrate specificity to direct the N-glycans toward desirable pathways in addition to altering their localization. The model developed in this study can be used to further the exploration of an optimal way of modulating enzymatic substrate specificity in order to alleviate and/or improve N-glycan microheterogeneity towards a desired glycoform profile. Such a systematic approach will continue to enhance our capability in glycoengineering.Table S1List of variables and their symbolic representation in the model.(0.07 MB DOC)Click here for additional data file.Text S1Reaction rate derivation.(0.10 MB DOC)Click here for additional data file.Text S2Enzyme concentration determination.(0.05 MB DOC)Click here for additional data file.Text S3Maximum reaction rate determination.(0.05 MB DOC)Click here for additional data file.


Despite significant efforts from the research community, an extensive portion of the proteins encoded by human genes lack an assigned cellular function. Most metazoan proteins are composed of structural and/or functional domains, of which many appear in multiple proteins. Once a domain is characterized in one protein, the presence of a similar sequence in an uncharacterized protein serves as a basis for inference of function. Thus knowledge of a domain's function, or the protein within which it arises, can facilitate the analysis of an entire set of proteins.From the Pfam domain database, we extracted uncharacterized protein domains represented in proteins from humans, worms, and flies. A data centre was created to facilitate the analysis of the uncharacterized domain-containing proteins. The centre both provides researchers with links to dispersed internet resources containing gene-specific experimental data and enables them to post relevant experimental results or comments. For each human gene in the system, a characterization score is posted, allowing users to track the progress of characterization over time or to identify for study uncharacterized domains in well-characterized genes. As a test of the system, a subset of 39 domains was selected for analysis and the experimental results posted to the NovelFam3000 system. For 25 human protein members of these 39 domain families, detailed sub-cellular localizations were determined. Specific observations are presented based on the analysis of the integrated information provided through the online NovelFam3000 system.Consistent experimental results between multiple members of a domain family allow for inferences of the domain's functional role. We unite bioinformatics resources and experimental data in order to accelerate the functional characterization of scarcely annotated domain families. The number of protein-encoding human genes identified has reached a plateau , leavingCaenorhabditis elegans, Drosophila melanogaster, and Homo sapiens  provide the basis for the study of proteins conserved across metazoan species. In pursuing comparative genomics approaches for functional inference of protein function, the initial selection of related proteins separated by great evolutionary distances can be a challenge. A decision must often be drawn between the study of homologous and orthologous proteins. In addition to technical difficulties and controversies that can arise in ortholog identification, a conservative focus on the study of orthologs greatly limits the number of proteins available to study. For homolog studies, grouping full-length protein sequences by similarity is not always feasible. The modular evolution of proteins presents a systematic complication – unrelated pairs of proteins can be linked through additional proteins sharing a domain with each pair (e.g. a protein with domains A and B may be linked to a protein with domains C and D via an intermediary protein with domains B and C). This problem is ameliorated by placing the focus on modular protein domain families, in which proteins are linked by the presence of a common domain [The genome sequence annotation and functional genomics data of n domain . Resourcn domain -9. Thosen domain .Characterization of protein function remains a fundamental challenge in functional genomics research. We have created the NovelFam3000 data centre to accelerate the study of uncharacterized domains conserved across worm, fly, and human. Building on domains identified in Pfam , we systThe characterization state of each protein domain is dynamic, dependent both on the available experimental literature and the perspective of the observing scientist. Using the Pfam database , we extrFor the selected domains, we constructed a database and an annotation system that unites links to bioinformatics resources with user-submitted experimental data to accelerate inference of domain function  Figure  see Add. Users mUsers may view and post detailed information about each gene using four categories: i) resource links, linking to major bioinformatics resources, ii) news, highlighting the latest annotations submitted to the system, iii) comments, giving users the opportunity to view and post general comments regarding the domain-containing protein of interest, and iv) experimental evidence, displaying results submitted by individual researchers. At the bottom of each page displaying gene-specific information for one of the four categories, the user is prompted to submit new information. Submitted data are rendered accessible through the system within 24 hours, after brief editorial review to confirm relevance .For each gene, links to both diverse external resources and user-submitted experimental results and comments are provided via a "gene page". Organism-centric resource links for each gene include WormBase , Flybaseet al., in preparation) is based on the results of a global survey of research biologists. Each participating scientist was given a sample of ten genes and returned their opinion as to the characterization status. The survey covered a total set of 100 genes with at least three fold redundancy. A machine learning procedure was used to create a scoring function to automatically predict the GCI score for all genes in the human genome. In this step, a Support Vector Machine was trained based on the survey results as training data, and the number of links to common databases (e.g. links to abstracts in PubMed or domains in Pfam).Within the NovelFam3000 system, we report the Gene Characterization Index (GCI) for each human gene, providing users with a measure of the current knowledge of the gene's function. GCI scores assign a continuous score in the range of one (uncharacterized) to ten (fully characterized). The GCI system . The cDNAs of the fly genes were cloned into both fly and mammalian expression vectors. All three fly proteins localized to the nucleus in fly cells displaying a consistent nucleolar staining pattern (CG6712 not shown). The expression of the Drosophila proteins in human HEK 293 cells was monitored by a C-terminal in-frame GFP tag (CG11920 not shown). The Drosophila proteins were found to accumulate in the nucleoli of the human cells, suggesting that the evolutionary conserved protein domain might be implicated in the targeting of these proteins to nucleoli. These results complement published observations for family members in model organisms [For protein domain family PF004427 (Brix domain), human proteins BRIX_HUMAN and IMP4 localized to the nucleoli . Member proteins SH3BP1 and SH3GL1 both localized to cytoplasmic vesicles which appeared to merge with the cellular membrane forming protrusions , a member of protein family PF03357 , gave rise to a unique cytoplasmic staining pattern , similarities between family members can be considered across species . For those selected proteins present in yeast, we extracted and reviewed sub-cellular localization and interacting protein partners. We show in two examples how the integration of functional data from studies of homologous yeast proteins reveals the broad conservation of function.Yeast proteins containing the brix domain PF04427) and their interacting partners have been localized to the nucleolus . Imp4p i7 and theProtein localization and interaction data from yeast studies complement the observed localization of human NP_057480 (HSPC129) and DULLARD, both from protein family PF03031 , with oWe populated the NovelFam3000 experimental data service with an initial panel of results for 25 genes from 39 domain families. The transcripts were detected by RT-PCR and cloned, confirming active transcription. We assigned the proteins to distinct sub-cellular compartments by epitope tagging followed by immunolocalization of the fusion proteins. Consistent localization across members of a protein domain family suggests that the function of the domain is directly linked to location. In some cases, the experimental localization data was complemented by the properties of interacting partners of model organism family members.The race to functional annotation runs at full speed and the level of cellular characterization of genes is constantly changing. The Gene Characterization Index score displayed in NovelFam3000 provides a dynamic indicator of the status of annotation for each gene. As upward shifts in GCI scores are indicative of advances in the elucidation of the functions of genes in NovelFam3000, dramatic changes will be highlighted on the homepage of the system.The NovelFam3000 system facilitates community-based curation of gene information.. The NovelFam3000 software is available for download without restrictions on the website.NovelFam3000 is publicly available and can be accessed at DK participated in the design of the study and generated experimental data. DK, CH, and WWW drafted the manuscript. RMP developed the Gene Characterization Index and contributed to the database design. DA and JL carried out the database development. EH and PR contributed experimental data for model organisms. CH coordinated the generation of the experimental data for the database. ELLS supervised the initial compilation of a collection of novel-domain containing proteins. WWW conceived of the NovalFam3000 database and assisted in the interface design. All authors read and approved of the final manuscript.Supplementary Figure. This drawing represents the NovelFam3000 database schema. Each rectangle, labeled with the table name at the top, represents a table in the database. The field names for each table are listed with symbols to the left. Primary Keys are denoted by a yellow key. Foreign Keys are denoted by a red diamond and "(FK)" after the field name. Regular Fields are denoted by a blue diamond. Relations between the tables are indicated by blue lines, with the diamond-end of the line at the referenced table and the other end at the referencing table. The relations are as follows: Rel_01: Comments can be made about a gene; Rel_02: News items can be associated with a gene; Rel_03: Resources can be associated with a gene; Rel_04: Experiments can be associated with a gene; Rel_05: Pfam sequences can be associated with a gene; Rel_06: Pfam sequences can be associated with a Pfam family; Rel_07: An experiment can be associated with multiple instances of experimental data.Click here for fileMaterials and methods. This file contains detailed materials and methods for both the database implementation and the experimental dataClick here for filePrimer sequences. This file contains nucleotide sequences for the gene-specific primers used for RT-PCR amplification of predicted human genesClick here for file