To determine whether healthcare professionals perceive the pain of infants differently due to their understanding of that infant's level of risk for neurological impairment.Neonatal Intensive Care Units (NICU's) at two tertiary pediatric centers. Ninety-five healthcare professionals who practice in the NICU (50 nurses, 19 physicians, 17 respiratory therapists, 9 other) participated. They rated the pain , distress (0–10), effectiveness of cuddling to relieve pain (0–10) and time to calm without intervention (seconds) for nine video clips of neonates receiving a heel stick. Prior to each rating, they were provided with descriptions that suggested the infant had mild, moderate or severe risk for neurological impairment. Ratings were examined as a function of the level of risk described.F (2,93) = 4.4, p = .02]. No differences in ratings were found due to participants' age, gender or site of study. Physicians' ratings were significantly lower than nurses' across ratings.Professionals' ratings of pain, distress, and time to calm did not vary significantly with level of risk, but ratings of the effectiveness of cuddling were significantly lower as risk increased [Professionals provided with visual information regarding an infants' pain during a procedure did not display the belief that infants' level of risk for neurological impairment affected their pain experience. Professionals' estimates of the effectiveness of a nonpharmacological intervention did differ due to level of risk. Research on pain in infants has progressed considerably over the past twenty years. The nature and frequency of procedural pain in the neonatal intensive care unit (NICU) is now understood , many meHowever, much less is known about the pain experienced by neonates who are at risk for neurological impairment (NI), as most studies of neonatal pain have either excluded this group or have not examined data specific to them within larger data sets. We do know that this group represents approximately 10% of infants admitted to the Neonatal Intensive Care Unit  and thatThe crucial first step of pain management is pain assessment. Without a valid and reliable approach to assessing pain, and the demonstrated efficacy of interventions for pain, decisions about pain management may not improve care. However, even with valid, reliable pain assessment tools, the characteristics of healthcare providers may affect ratings provided by them. These characteristics can include the healthcare providers' views of pain interventions , lack ofThe present study was designed to move beyond self-report of beliefs to examine whether healthcare professionals' judgments of pain in neonates are affected by their perception that a neonate has mild, moderate or severe risk for neurological impairment.Research in this area is only emerging, but has important implications for how healthcare professionals deliver care to this vulnerable population. In a previous study using questionnaires, we found that caregivers of children with severe cognitive impairment view the pain of children with more severe impairment as reduced . A seconThese studies suggest that those who manage the pain of infants at risk for, or children with, intellectual deficits believe that pain is less for those at greater risk or who have greater impairment. These results may explain why we also found infants at risk for neurological impairment receive less pain treatment in the NICU . HoweverOne hundred and one healthcare professionals, with at least one year of experience working with infants with neurological impairment in the NICU, were recruited from two tertiary level university affiliated NICU settings in central and eastern Canada. They were recruited through information provided by the research nurses and notices posted within their centers. Each participant was paid a small honorarium for their participation, and all provided informed consent. The study was approved by each health centre's Research Ethics Board.Participants completed a questionnaire that requested information regarding their age, gender, education and work experience.Nine video clips were viewed by each participant. The 30 second video clips depicted term and preterm neonates of Caucasian descent experiencing a heel stick and squeezing for blood collection. Video clips were of the infants' faces only, with most lying on their sides and all bundled. Audio was not included. Prior to each videoclip, a verbal description of the neonate suggesting he/she was at mild, moderate or severe risk for neurological impairment was provided to the participant. These descriptions had been previously recorded on audio tape by a researcher to ensure each participant was read the description in an identical fashion. Descriptions were counterbalanced such that each videoclip was described for some participants as having either mild risk, moderate risk, or severe risk within each of two orders of presentation. Thus, each participant viewed three infants that were described as having mild, moderate or severe risk for neurological impairment, but the level of risk, and the order in which the clips were presented varied. Examples of the descriptions provided to participants are shown in Table Participants rated the pain of infants shown on videotape from 0 (no pain) to 10 (extreme pain). They also rated each infant's pain using a Faces Pain Scale (0 = no pain, 6 = extreme pain). These measures were chosen because they are easy to use and were feasible for this experimental task. Although many validated measures of neonatal pain exist, these are multidimensional in nature. As such, they require the person using them to have access to information regarding the infant's physiological status, something we were unable to provide in the context of this task.r = .74), moderate (.r = .56) and severe risk for neurological impairment (r = .60).The 7 face scale , was incParticipants provided a rating of how effective they believed a behavioural intervention (i.e. cuddling) would be for minimizing the procedural pain for each infant (0 = no effect, 10 = very effective) and of how long (seconds) they believed it would take each infant to calm without intervention.To ensure that the descriptions provided were valid depictions of infants at each level of risk and were understood and accepted by participants, participants were asked to rate the level of risk they believed each infant had for future neurological impairment (0 = no risk, 10 = certain impairment).Participants took part in small groups of 5 to 6 professionals that were randomly assigned to one of the two orders of presentation. They completed the demographic questionnaire and the rating tasks were explained to them. They were then shown the nine video clips. After each videoclip was viewed, the participants were provided with time to make their independent ratings for that videoclip before the next was shown. Participants were not permitted to interact with each other until all tapes had been viewed and rated. After ratings were complete, they were debriefed regarding the purpose of the study and a discussion of their experience was facilitated by the research assistant.n = 88) to 7% (n = 1) of responses (M = 0.2, SD = 0.6).Preliminary analyses indicated that two participants were missing more than 10% of ratings. As per an a priori decision as to how to handle missing data, their data were excluded from further analyses. The remaining 99 participants were missing 0% (F(1,97) = 4.4, p = .04). A more detailed look at the data using stem and leaf plots revealed 4 participants in one group had extreme scores for ratings of Time to Calm (M = 192.8, SD = 39.2) relative to the other participants in that group (M = 37.4, SD = 28.7). The data of these four participants were removed. A second RM ANOVA revealed no significant effect due order of presentation of the video clips [F(1,93) = 1.7, p = .20). Thus, 95 professionals formed the final sample for the study.A 2 (group) X 6 (rating) Repeated Measures Analysis of Variance (RM ANOVA) was conducted on the six ratings provided by participants who viewed the tapes in the two orders to determine whether order of presentation had affected ratings. This analysis revealed a significant effect of order of presentation [M = 3.8, SD = 2.8), moderate (M = 4.9, SD = 2.0) and severe risk  = 13.9, p < .001). Post-hoc paired t-tests indicated these differences were significant between infants described as having mild and moderate risk (t((94) = -3.2, p = .002), mild and severe risk (t((94) = -4.8, p < .001), and moderate and severe risk (t((94) = -5.0, p < .001), Thus, participants believed the infants had different levels of risk when they provided ratings for the video clips.To determine if the descriptions provided to the participants were effective in leading them to believe the infants viewed had mild, moderate or severe risk for neurological impairment, each participant's mean rating for degree of risk for future impairment for the infants they were told had a mild (3), moderate (3) or severe risk (3) for impairment were computed. These ratings were then compared using a RM ANOVA. There was a significant difference in the ratings provided to those clips described as having mild  X 5 (rating type) RM ANOVA was conducted on the scores of the 95 participants. This was followed by 5 one-way RM ANOVA's on each rating  and matched sample t-tests on ratings when the one-way ANOVA was significant.The effect of participants' characteristics on ratings was examined using Mixed Measures ANOVA's on the five ratings at three levels of risk. The first three included Gender, Age, and Site  as between-subjects effects. The fourth included three levels of profession (i.e. staff nurse, physician, respiratory therapist) as the between-subjects effect. Other professionals were not included due to small numbers. The relation between the participants' years of experience in a neonatal setting and their ratings were investigated using Pearson Correlations.M = 11.8, SD = 7.7). The 50 nurses included staff nurses (n = 34), advanced practice nurses (n = 9) and nurse managers/educators (n = 7). The physicians specialized in neonatology (n = 10), neurology (n = 4), pediatrics (n = 3) and other specialties (n = 2). Six of the 19 physician participants were residents or fellows. Additional professions are listed in Table The characteristics of the participants are displayed in Table ties n = . Six of F (2,93) = 0.6, p > .05], a significant effect of Rating [F (4,91) = 91.6, p < .001] and a significant interaction between the two [F (8,87) = 3.4 p = .002]. Thus, there was no overall effect due to the level of risk described, but level of risk described did affect some ratings.The mean ratings provided for video clips of infants described as having mild, moderate or severe risk for neurological impairment are depicted in Table F (2,93) = 2.9, p = .06] and a significant effect on ratings of the perceived effectiveness of cuddling [F (2,93) = 4.4, p = .02], but nonsignificant effects on Faces Pain Scale ratings [F (2,93) = 0.3, p = .70], distress [F (2,93) = 2.2, p = .12] and time to calm [F (2,93) = 0.4, p = .65]. As Table t(94) = 2.5, p = .01] or moderate risk [t(94) = 3.0, p = .004]. The difference in ratings between those described as at mild or moderate risk were nonsignificant [t(95) = -0.2, p = .77]. Thus, participants believed that beyond a moderate level of risk, the effectiveness of cuddling dropped significantly.One-way RM ANOVA's revealed Level of Risk had a marginal effect on participants' ratings of pain on the 0–10 scale [F 2,9 = 2.9, pIn summary, participants did not view the pain of the infants as varying due to level of risk for neurological impairment. Nor did they perceive the distress or time to calm after pain as differing between groups of infants described as having mild, moderate or severe risk for neurological impairment. However, they did perceive that cuddling would be less effective as an intervention for infants with high risk, than for those with mild or moderate risk of neurological impairment.F(1,93) = 0.7, p = .39], the second revealed a nonsignificant main effect of Gender [F(1,93) = 0.9, p = .34], and the third indicated Age also did not significantly effect ratings on the five measures [F(4,90) = 0.2, p = .95]. Thus, participants' ratings did not vary due to their institution, gender or age.Three Mixed Measures ANOVA's were used to examine the effect of participants' characteristics on the five ratings ratings. The first result indicates a nonsignificant main effect of Site [F(4,56) = 3.9, p = .001]. However, the main effect of Level of Risk was nonsignificant and the main effect of Profession only approached significance [F(2,59) = 2.7, p = .07]. Participants' ratings were not affected by their professional background. The interaction between Rating and Level of Risk was significant [F(8,52) = 36.6, p < .001], but all other interactions were nonsignificant. Games-Howell post-hoc comparisons revealed a significant difference in the ratings provided by staff nurses and physicians (p = .004) and a difference between respiratory therapists and physicians that approached significance (p = .06). As shown in Table To examine the effect of participants' profession on their ratings, three groups were included in a Mixed Measures ANOVA: staff nurses n = 34), physicians (n = 11), and respiratory therapists (n = 17). Residents and Fellows, Nurse Managers and Educators and Specialists, and other professionals were not included due to small numbers in those groups. The analysis revealed a significant main effect of Rating Scale [, physiciEighty-nine participants provided information regarding their amount of professional experience. Correlations indicated that years of experience were not correlated significantly with any of the five ratings provided after corrections for multiple tests. Thus, the importance of an infants' level of risk for neurological impairment was neither greater nor less as experience in this setting increased.Overall, the professionals in this study did not rate the pain of neonates differently when provided with information indicating those infants had mild, moderate or severe risk for neurological impairment. The professionals' perception of the infants' level of risk also did not affect their ratings of the infants' distress, or their belief in how long the infant would take to calm after pain without intervention. Professionals did perceive that cuddling would be significantly less effective for infants at high risk for neurological impairment than for infants with mild or moderate impairment. However, this effect was not large, and, although it was statistically significant, it may be spurious. Further research should examine whether beliefs regarding pain experience in this group and beliefs regarding the effectiveness of cuddling and other nonpharmacological interventions are truly independent. These results are inconsistent with the results of our previous questionnaire study indicating professionals, with similar levels of experience in neonatal intensive care settings, perceive the pain experience of infants as reduced as their level of risk for neurological impairment increases . There aThe professionals who participated in this study were asked to rate the risk for neurological impairment of each infant they viewed on videotape. Asking them to do this may have alerted them to the purpose of the study and elicited efforts on their behalf to provide ratings that were unbiased. However, their ratings of the perceived effectiveness of cuddling did vary by level of risk for impairment, suggesting attempts to appear unbiased do not fully explain the results found.relative to the pain experience of those without risk [In our previous studies, questionnaires elicited beliefs about the pain experience of infants and children with varying levels of risk out risk -12. In cIt is also possible that the beliefs expressed by professionals in our previous study  do not mThe finding that pain ratings did not vary due to level of risk for neurological impairment raises questions about our previous study that revealed infants at risk for neurological impairment receive less pain treatment in the NICU . When a Further research is needed to reconcile the current results with beliefs that risk for neurological impairment does affect pain experience expressed by a similar group of professionals in our previous survey  and the Another finding in this study warrants discussion. Professionals' judgments of the effectiveness of cuddling decreased with increasing risk for neurological impairment, despite their having judged pain as similar in intensity. This result is similar to a finding by Fanurik et al. . They foThe current results, along with those of Fanurik's group , raise tIf professionals and caregivers do believe pain behaviour is more reflexive, and that pain experience is more physiologically based when a child has neurological impairment, it could explain the current results regarding the effectiveness of cuddling. Professionals viewing the video clips may have perceived the behavioural responses of the infants with different levels of risk for impairment as being similar in intensity. Nonetheless, they may have interpreted the behaviour of those with more risk as more of a reflexive response to a physiological insult, while they saw the behaviour of those with lesser risk as reflecting a more multidimensional pain experience incorporating both physical and psychological suffering. Thus, we could again speculate that they may have felt cuddling, an intervention that would address physical and psychological aspects of pain, would be more effective for the less impaired groups. This phenomenon would not be novel or unique. For most of recorded history, there has been a belief that cognitive interpretation of pain was necessary for pain to result in long-term negative consequences. This belief was often the justification for poorer pain management for both children and infants . AlthougThe current study has several limitations. Professionals were asked to rate the pain experience of infants receiving heel sticks from videotape. Although this may approximate the real situation in a NICU setting, it is not identical. In a NICU setting, professionals would have rich information from the environment, previous contact with an infant, physiological data, and medical records that guide their assessment of pain. They would also view this infant within the context of all other infants in the unit. Professionals here were also asked only to provide ratings of pain intensity. As the results suggest, this is only one dimension of pain and may not be the dimension that plays the largest role in their judgments regarding pain in a clinical setting. The professionals here were experienced in the types of pain experienced in the NICU and may have held a priori beliefs about the painfulness of this procedure that moderated their judgments. Research suggests professionals' beliefs regarding the painfulness of a procedure play a large role in their assessments of children's pain ,9,25.The current study indicates professionals' perception of the pain intensity of infants does not differ due to their understanding of the infants' level of risk for neurological impairment. Professionals also view cuddling as less effective for infants at greater risk for neurological impairment. Further research is needed to examine the reasoning behind the judgments made by healthcare professionals and to clarify why they might view an intervention as less effective for infants with greater risk of neurological impairment, despite having rated their pain intensity as similar to that of infants at lesser risk.The authors declare that they have no competing interests.The study was conceived and designed by BS, PM & LB with assistance from all remaining authors. The study was conducted under the supervision of PM, BS, KO, AO. Statistical analyses were conducted by LB, with assistance from PM, BS and JB. Interpretation of results were conducted by LB, PM, BS, JB, CC, LF, KB and AO. The manuscript was prepared by LB, and edited by PM and BS, with review and assistance from all remaining authors. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:


Diabetes mellitus (DM) is an important public health concern, the impact of which is increased by the high prevalence of co-existing chronic medical conditions among subjects with DM. The aims of this study were therefore to (1) evaluate the impact of DM and co-existing chronic medical conditions on health-related quality of life (HRQoL) (which could be additive, synergistic or subtractive); (2) to determine the extent to which the SF-6D (a single-index preference measure) captures the multidimensional information provided by the SF-36 (a profile measure).Using data from a cross-sectional, population-based survey of Chinese, Malay and Indians in Singapore, we developed 9 separate multiple linear regression models, with each SF-36 scale or SF-6D index score being the dependent variable for one model. The influence of DM and a second chronic medical condition (hypertension (HTN), heart disease (HD), musculoskeletal illnesses (MS)) and their interactions were studied after adjusting for the influence of potential confounding variables.Among 5,224 subjects, the prevalence of DM, HTN, HD and MS were 5.9%, 10.7%, 2.4% and 26.6% respectively. DM lowered SF-36 scores by more than 2 points on 3 SF-36 scales and lowered SF-6D scores by 0.03 points. Subjects with DM and HTN, DM and HD or DM and MS experienced further lowering of SF-36 scores exceeding 2 points on at least 6 scales and further lowering of SF-6D scores by 0.05, 0.08 and 0.10 points respectively. Generally, DM and co-existing medical conditions exerted additive effects on HRQoL, with the exception of DM and heart disease, where a subtractive effect was noted. SF-6D index scores generally reflected the patterns of influence of DM and chronic medical conditions on SF-36 scores.DM and chronic medical conditions generally reduced HRQoL in this multiethnic general population in an additive, rather than synergistic or subtractive fashion. In this study, the SF-6D was a reasonably good summary measure for the SF-36. Diabetes mellitus, the prevalence of which is reaching epidemic proportions in many parts of the world, is an increasingly important public health concern. In the United States, diabetes is present in 8% of the adult population, and is associated with a two-fold increase in age-adjusted mortality ,2. In adDiabetes has detrimental effects on a range of health outcomes including health-related quality of life (HRQoL) -12. For Subjects with diabetes and multiple co-existing chronic medical conditions have poorer HRQoL than those without these conditions ,17. For In combination, the influence of multiple chronic medical conditions on HRQoL may exhibit an additive, synergistic or possibly subtractive relationship. Assuming that each chronic medical condition results in the lowering of HRQoL, in an additive relationship, the combined effect of two or more chronic medical conditions on HRQoL approximates the sum of the independent effect of each of these conditions, while in a synergistic relationship, the combined effect is greater than the sum of the independent effect of each of these conditions and in a subtractive relationship the combined effect is smaller than the sum of the independent effect of each of these conditions Figure . For exaTwo published studies have evaluated the relationship between diabetes and other chronic medical conditions on HRQoL in the general population ,24. In tThe primary purpose of this study was therefore to evaluate the impact of diabetes and co-existing chronic medical conditions on the physical, mental and social domains of HRQoL in the general population. We also sought to determine if the impact of diabetes and co-existing chronic medical conditions on HRQoL would be additive, synergistic or subtractive. For these purposes, we measured HRQoL using both the SF-36 and the SF-6D. The SF-36 is a comprehensive, generic HRQoL measure that has been extensively validated and allows comparison of HRQoL in subjects with various chronic medical conditions. The SF-6D is a single index utility score derived from the SF-36 which measures health preference, and which is therefore suitable for pharmacoeconomic analyses to assist healthcare resource allocation. We sought to determine the extent to which the SF-6D would reflect the multidimensional information provided by the SF-36.st January 1998 and ability to read a newspaper in English or Chinese; Chinese, Malay or Indian ethnicity as reflected in the National registration identification card, which reflects parental ethnicity; and status as free-living adults in the community. Persons older than 65 years of age were excluded because of low literacy rates in this age group in Singapore [We analyzed data from a cross-sectional, population-based disproportionately stratified sample of ethnic Chinese, Malays and Indians listed in the 1996 electoral register for the Bishan-Toa Payoh district  in Singapore from April 1998 to January 1999, details of which have been reported previously  and are ingapore . FieldwoThe SF-36 measures perceived health in the areas of physical functioning (PF), role-physical (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role-emotional (RE), and mental health (MH), with higher scores (range 0–100) reflecting better perceived health. The UK English  and ChinThe SF-6D is a six-dimensional health classification system assessing physical functioning (PF), role limitations (RL), social functioning (SF), pain (PN), mental health (MH), and vitality (VT), with 4 to 6 levels per dimension ,30. A SFThe Family Functioning Measure is a 3-item Likert scale assessing the quality of interactions among family members , with hiData from participants completing English and Chinese SF-36 versions were pooled to increase the power and representativeness of our study. This approach was supported by previous work demonstrating equivalence of these SF-36  and SF-6To study the influence of diabetes and other chronic medical conditions on HRQoL, we developed 9 multiple linear regression models, with each SF-36 scale and the SF-6D index score being the dependent variable for a separate model. Each model was built in 3 stages. The first stage assessed the effect of diabetes on HRQoL while adjusting for the influence of sociodemographic factors. The second stage assessed the independent effects of diabetes and a second chronic medical condition on HRQoL while adjusting for the influence of sociodemographic factors. The third stage additionally assessed any interactions between diabetes and this second chronic medical condition on HRQoL. Thus, each model studied the effect of diabetes and one other chronic medical condition. The absence of a significant interaction term would suggest that the influence of two chronic medical conditions on HRQoL scores was additive. The presence of a significant interaction term would suggest that a synergistic or subtractive relationship existed, the former if the coefficient for the interaction term was negative, the latter if the coefficient was positive . Ethnicity was coded using dummy variables. Educational level was used as proxy for socioeconomic status. In anticipation that if the number of subjects with a given chronic medical condition was less than 50, the numbers of subjects with this medical condition and diabetes would be very small and not amenable to meaningful interpretation, two chronic medical conditions, stroke and cancer, were thus excluded from analysis because of small numbers of subjects reporting these conditions (n<50). Two other chronic medical conditions were subsequently excluded from analysis because of small numbers of subjects with diabetes and these conditions .Complete data were available from 5,224 of 5,420 subjects in the study, with 196 (3.6%) subjects excluded from analysis (110 because of missing demographic information and 86 because of missing responses to the SF-36). Table The influence of chronic medical conditions on individual SF-36 scales is presented in Table The influence of chronic medical conditions on SF-6D scores is also presented in Table Characteristics of subjects with diabetes, with and without other co-existing chronic medical conditions, are shown in Table The impact of co-existing chronic medical conditions on adjusted SF-36 scores of subjects with diabetes is presented in Table The influence of diabetes and co-existing chronic medical conditions on SF-6D scores is presented in Table In this multiethnic, population-based study, we found that subjects with diabetes experienced lowering of HRQoL as compared to subjects without diabetes. The presence of other chronic medical conditions in subjects with diabetes led to further lowering of HRQoL, the effect of which was generally additive. Our findings further underscore the importance of preventing and treating complications of diabetes to prevent further deterioration in HRQoL among subjects with diabetes, and also highlight the need to identify factors that may be modulated to improve HRQoL in these subjects.Our findings are important for several reasons. First, this is the first study showing that the combination of diabetes and a second chronic medical condition may adversely affect the mental domains of HRQoL as measured by the vitality, social functioning and mental health scales of the SF-36  ,24. SecoWe found that the effect of diabetes on HRQoL was generally mild, with greater impact on the SF-36 scales measuring physical ) relative to mental health components . This was not surprising, given that our subjects were recruited from the general population and were therefore likely to have less severe illness than subjects in hospital or clinic-based studies. Further, other studies have shown that impact of diabetes on HRQoL is intermediate, relative to other chronic medical conditions . For exaWe also found that with the exception of subjects with diabetes and heart disease, the presence of co-existing chronic medical conditions in subjects with diabetes generally resulted in further significant lowering of HRQoL. Our results are important because they demonstrate that the impact of these co-existing chronic medical conditions in diabetes is not only in increasing healthcare costs ,37 and mth or 6th decade of life [In our study, the relationships between diabetes and other chronic medical conditions on HRQoL were largely additive. This is in contrast with the study by Gaynes et al. , where s of life , often m of life  (althoug of life ,43. In c of life . Hence, A secondary objective of this study was to understand the extent to which the single index SF-6D captured information from the multidimensional SF-36. We found that in general, the impact of co-existing chronic medical conditions on the SF-36 was well-reflected in the SF-6D. However, the subtractive effects of diabetes and co-existing heart disease on SF-36 scores were not reflected in SF-6D scores. This suggests that there is some inevitable loss of information associated with a reduction from a multi-dimensional scale to a unidimensional scale. Hence, more studies are needed to evaluate the adequacy of the SF-6D as a summary measure of the SF-36.We recognize several limitations of this study. First, identification of chronic medical conditions was based on self-report which may not be as accurate as physician diagnoses. However, reliability of self-report has been found to be acceptable for conditions that required medical or laboratory diagnostic procedures, including diabetes -47. SecoIn conclusion, in this large, multiethnic, population-based study, we found that subjects with diabetes experienced lowering of HRQoL as compared to subjects without diabetes. The co-existence of other chronic medical conditions in subjects with diabetes led to further lowering of HRQoL, the effect of which was generally additive. Finally, we found that the SF-6D is a reasonably good summary measure of the SF-36 although more studies are needed to confirm this observation.ADL – Activities of Daily Living, DM – Diabetes mellitus, HD – Heart disease, HRQoL – Health-related quality of life, HTN – Hypertension, MS – Musculoskeletal illnesses, OR – Odds ratio, SF-36 – Medical Outcomes Short-Form 36.JT conceived of the study, and participated in its design and coordination. HL Wee and YB Cheung participated in the design of the study and performed the statistical analysis. SC Li and KY Fong participated in the design of the study and its coordination. All authors read and approved the final manuscript.


Metastasis is the leading cause of cancer-related death. Bone marrow (BM) is a frequent site for the settlement of disseminated tumor cells which occurs years before overt metastases signal incurability.Here we describe a new method to assess the initial stage of metastasis development in cancer patients. By immunomagnetic selection with HER2/neu and EpCAM as catcher antigens single disseminated tumor cells can be enriched from BM samples. To examine whether the immunomagnetic enrichment technique may change gene expression in the selected tumor cells, we performed differential expression profiling with the breast cancer cell lines MCF-7 and BT474 as models. The profiles were performed using 1.2 Cancer Arrays (Clontech) containing 1176 cDNAs that can be grouped into different functional categories, such as signal transduction, cell cycle, adhesion, cytoskeleton plasticity, growth factors and others.The reproducibility of the gene expression profiling between duplicate cDNA-array experiments was assessed by two independent experiments with MCF-7 breast cancer cells. Scatter blot analysis revealed a good reproducibility of the cDNA array analysis (i.e. less than 10% difference in the gene expression between the arrays). Subsequent comparative cDNA-array analyses of immunobead-selected and unselected MCF-7 and BT474 cancer cells indicated that the antibody incubation during the immunomagnetic selection procedure did not considerably alter the gene expression profile.The described method offers an excellent tool for the enrichment of micrometastatic tumor cells in BM without largely changing the gene expression pattern of these cells. To predict and monitor therapeutic responses the assessment of the gene expression profile of disseminated tumor cells seems to be of utmost importance. However, it is uncertain to which extent incubation with antibodies used for immunomagnetic isolation of these cells might affect their expression profile. We have addressed this aspect, using monoclonal antibodies against two prominent antigens, EpCAM and HER2/neu that are frequently and independently expressed on micrometastatic tumor cells [Solid tumors derived from epithelial organs are the main form of cancer in industrialized countries. The first phase of the metastatic development consists of local tumor cell invasion, followed by tumor cell circulation in the blood and homing to secondary distant organs ,2. As inor cells .The enrichment of tumor cells from BM by Ficoll density gradient centrifugation and the immunocytochemical detection of epithelial tumor cells in cytological BM preparations has been described elsewhere in detail ,6.6 mononuclear cells were washed with Hank's Salt Solution (Biochrom KG, Germany). The pellet was resuspended in 2 ml Hanks and 3.2 × 107 (80 μl) CELLection™ and pan-mouse immunomagnetic beads  coated with anti-EpCAM (MAb 3B10) and anti-HER2/neu (MAb 7C1) antibodies (Micromet, Munich, Germany) were added. All solutions and cell preparations were kept at 4°C during the whole procedure to avoid nonspecific binding of immunomagnetic beads. After an incubation time of 30 min at 4°C and 20 min at room temperature on a rotating mixer the magnetically labeled cells were isolated in a magnetic particle concentrator and resuspended in 200 μl bead removing buffer (40 mM Tris, 10 mM MgSO4, and 1 mM CaCl2, pH7.4, prewarmed to room temperature). The immunomagnetic beads were removed by DNase treatment with 15 μl DNase (50 U/μl) at room temperature for 15 min. After separation in a magnetic particle concentrator the supernatant was collected and centrifuged onto glass slides. Tumor cells were identified by immunostaining with monoclonal anti-cytokeratin antibody A45-B/B3 according to the manufacturer's instruction (Micromet, Munich, Germany). Cytokeratins are specific constituents of the epithelial cytoskeleton and they have become the marker antigen of choice for the detection of disseminated epithelial tumor cells in mesenchymal organs such as BM [ab fragments of A45-B/B3 that were directly conjugated to the marker enzyme alkaline phosphatase.Two ml of a BM sample usually containing 2 × 10MCF-7 cells and BT474 cells were maintained in RPMI (Invitrogen, Karlsruhe, Germany) supplemented with 5 % glutamine (Invitrogen) and 10 % FCS (C-C Pro, Neustadt, Germany). MCF-7 and BT474 cells (ATCC HTB-22 and HTB-20) were allowed to reach a logarithmic growth phase in culture. At 90 % confluency, the cells were incubated for 30 min at 4°C and 20 min at room temperature in Hanks containing 1 μg/ml of anti-EpCAM (MAb 3B10) as well as anti-HER2/neu (MAb 7C1) antibodies according to the immunomagnetic cell separation protocol. In a negative control experiment, cells were suspended in Hanks devoid of antibodies.2O with 1 U/μl RNase inhibitor (SUPERase. IN™, Ambion). 5 μg purified total RNA was used for [α-33P] dATP  labeled cDNA synthesis as previously described [Total RNA was isolated using the peqGold TriFast™ (Peqlab, Erlangen, Germany) according to the manufacturer's instruction. In order to remove genomic DNA contamination, a DNase step was included using the DNA-free™ kit (Ambion, Cambrigeshire, England) according to manufacturer's instructions. RNA was dissolved in RNase-free Hescribed . The cDNThe membranes were exposed to phosphoimager plates (Raytest Isotopen-Meβgeräte, Straubenhardt, Germany) for 3 days, and plates were scanned with the phosphoimager Fuji Bas (Raytest) at a 100 μm-resolution. The images were analyzed using the Imagene 5.5 software (Biodiscovery, CA, USA). The data of the arrays were normalized on the basis of the genes ubiquitin, HLAC and beta actin. The ratio between antibody-treated and non-treated cells was calculated for each gene. Ratios lower than 0.5 or higher than 2 were considered as differentially expressed if at least one sample showed an expression above 0.5. We performed duplicates of each experiment and created scatter blots with the SPSS software for windows.In a recent work  we demonTo test whether the antibody incubation during the immunomagnetic enrichment approach affects gene expression in the selected cells, we applied cDNA-array analysis. We subsequently evaluated whether the immunomagnetic enrichment method affected gene expression in the selected cells. This aspect is of utmost importance for further molecular description of disseminated tumor cells and has not been addressed before. The profiles were performed using 1.2 Cancer Arrays (Clontech) containing 1176 cDNAs that can be grouped into different functional categories, such as signal transduction, cell cycle, adhesion, cytoskeleton plasticity, growth factors and others [As models, we used the breast cancer cell lines MCF-7 and BT474 (ATCC HTB-22 and HTB-20), because they express heterogeneous levels of the target antigens HER2/neu and EpCAM comparable to micrometastatic breast cancer cells in vivo . The repR) can specifically block cell proliferation and affect gene expression in HER2/neu-positive breast cancer cells [Here, we investigated whether an immunomagnetic enrichment procedure for micrometastatic cancer cells present in BM aspirates leads to significant changes in the gene expression pattern of the enriched tumor cells. In order to mimic the biological conditions of a tumor type with frequent BM involvement, we used two breast cancer cell lines (MCF-7 and BT474). Both cell lines expressed the target antigens, EpCAM and HER2/neu, for immunomagnetic separation at different levels  and theyer cells ,14. Furter cells . Howeverer cells . Taken tThus, we conclude that the immunomagnetic selection protocol described here might be useful for experimental approaches aimed to determine the gene expression profile and genome of disseminated CK-positive cells ,18. As w


By incorporating this concept in left ventricular (LV) models to simulate filling and systolic phases, we have obtained the time-varying expression for Ea and the LV-volume dependent expression for Ep.Description of the heart as a pump has been dominated by models based on elastance and compliance. Here, we are presenting a somewhat new concept of time-varying passive and active elastance. The mathematical basis of time-varying elastance of the ventricle is presented. We have defined elastance in terms of the relationship between ventricular pressure and volume, as: a is expressed as: ; Epis represented as: . Ea is deemed to represent a measure of LV contractility. Hence, Peak dP/dt and ejection fraction (EF) are computed from the monitored data and used as the traditional measures of LV contractility. When our computed peak active elastance (Ea,max) is compared against these traditional indices by linear regression, a high degree of correlation is obtained. As regards Ep, it constitutes a volume-dependent stiffness property of the LV, and is deemed to represent resistance-to-filling.Using the patient's catheterization-ventriculogram data, the values of passive and active elastance are computed. Ea) can be used to characterize the ventricle's contractile state, while passive elastance (Ep) can represent a measure of resistance-to-filling.Passive and active ventricular elastance formulae can be evaluated from a single-beat P-V data by means of a simple-to-apply LV model. The active elastance (E The heart may be conceived as a pump that receives blood from a low-pressure system and raises it to a high-pressure system. Although the mechanism responsible for generation of wall stress (and hence left ventricular (LV) pressure) is contraction of the myocardial fibers, an analytical formulation linking the myocardial and LV dynamics is still lacking. In the absence of this formulation, a popular way of linking LV pressure and volume dynamics is by means of LV compliance (or elastance) ,2. AlthoThe concept of compliance or elastance was first employed for blood vessels , by relaDefares  avoided Classically, ventricular compliance is defined, at any point in time, as the change in ventricular volume concomitant with the change in ventricular pressure, such thatC = dV / dP, E = dP / dV     (1)If C is assumed constant, this equation becomes a linear relation, whose integration givesV = CP + Vc     (2)c is an integration constant. If the compliance varies with time, then all terms in equation (2) may vary with time, as:where VV (t) - Vc (t) = C(t)P(t)     (3)In this context, Suga  opted fod represents the unstressed LV volume corresponding to zero LV-pressure, obtained by drawing a tangent to P-V curves at end-ejection, as illustrated in Figure to represent the elastance of the contracting LV, where Vmax and of the volume-axis intercept (Vd) of the tangent to the P-V curve at end-ejection (as a measure contractility of the cardiac muscle) is not only unreliable [However, the determination of the maximal slope Ereliable ,15, but reliable ,15. It ip) represents the LV pressure response to LV volume change (to LV volume increase during LV filling phase and to LV volume decrease during LV ejection phase). However, simultaneously, we also have active elastance (Ea) representing the contraction of the left ventricle due to its sarcomeric activation (and the development of force between the actin-myosin units) and relaxation (due to disengagement of the actin-myosin units).We have hence come up with a new concept of dual passive and active elastances operating throughout the cardiac cycle. The passive elastance . While the generation of Ea helps us to explain the development of the LV pressure increase during isovolumic contraction, the decrease of Ea during diastole helps us to explain the decrease in LV pressure during early filling. The incorporation of both Ep and Ea helps us to explain the LV pressure changes during the filling and ejection phases.LV EThe subjects in this study were studied in a resting recumbent (baseline) state, after premedication with 100–500 mg of sodium pentobarbital by retrograde aortic catheterization. Left ventricular chamber pressure was measured by a pigtail catheter and Statham P23Eb pressure transducer; the pressure was recorded during ventriculography. Angiography was performed by injecting 30–36 ml of 75% sodium diatrizoate into the LV at 10 to 12 ml/s. It has been found by using biplane angiocardiograms that calculated orthogonal chamber diameters are nearly identical . These fFor our study, monoplane cineangiocardiograms were recorded in a RAO 30° projection from a 9 in image intensifier using 35 mm film at 50 frames/s using INTEGRIS Allura 9 system at the Nation Heart Centre (NHC), Singapore. Automated LV analysis was carried out to calculate LV volume and myocardial wall thickness. The LV data, derived from the cineangiographic films and depicted in Figure In Figure LV is the response to (i) LV Ea continuing to decrease due to the sarcomere continuing to relax well into the filling phase, and (ii) to the rapid inflow of blood and the corresponding increase in LV volume, along with increase in LV Ep. The associated governing differential equation, relating LV pressure and volume, can be put down (by referring to the Appendix for its derivation) as [At the start of diastolic-filling phase, the LV incremental pressure dPtion) as :t represents the time variable (s) from the start of filling phase;where V represents the volume of LV (ml) during the filling phase;PLV represents pressure of the LV, in mmHg (hereafter symbolized by P) (mmHg);M represents the inertia term = [LV wall-density (ρ)/] = ρh / 4πR2, for a spherical LV model (in mmHg/(ml/s2));E represents LV elastance (mmHg/ml).LV) is caused by both Ea variation as well as Ep decrease. The instantaneous time-varying ventricular elastance (E) is the sum of (i) volume-dependent passive elastance (Ep) and (ii) active elastance (Ea) due to the activation of the LV sarcomere. Hence,Likewise during ejection, the LV pressure variation (dPE = Ea + Ep     (6)p and Ea, and then their formulations. The passive (unactivated) myocardium exhibits properties of an elastic material, developing an increasing stress as strain increases, as occurs during ventricular filling. The passive stress-strain relation of myocardial muscle strip is nonlinear, and therefore cannot be described by Hooke's law. As an approximation, it follows an exponential relationship [p (= dP/dV) is volume-dependent, we can express it as:We will now provide the expressions for Etionship -20. TherEp0 is the passive elastance coefficient, zp is the passive elastance exponent, and V is the LV volume; its derivation is provided in a subsequent section.where a as an intrinsic property of the LV (derived later), as:On the other hand, we will represent EEa0 is the active elastance coefficient, (iii) the time-coefficient (τC) describes the rate of elastance rise during the contraction phase, while (τR) describes the rate of elastance fall during the relaxation phase; (iv) the exponents "ZC" and "ZR" are introduced to smoothen the curvatures of the Ea curve during isovolumic contraction and relaxation phases; (v) the parameter d is a time constant whose (to be determined) value is during the ejection phase, and (vi) u(t-d) is the unit step function, u(t-d) = 0 for t<d. The rationale for equation (8), as provided in the next section, is based on Ea incorporating parameters reflecting the (i) generation of LV pressure during isovolumic contraction, (ii) decrease of LV pressure during isovolumic relaxation and early filling, and (iii) the LV pressure-volume relationship during filling and ejection phase.where (i) t is measured from the start of isovolumic contraction, (ii) the parameter a and Ep contribute to the relationship of LV pressure and volume. While Ep incorporates LV pressure change due to LV volume change, Ea incorporates the effect of LV myocardial activation in the generation of LV pressure during the isovolumic phases (when the LV volume remains constant). Since Ea is deemed to be the basis of LV pressure generation, its variation (as given by equation 8) corresponds to the LV pressure variation.Based on equations (5–8), our hypothesis is that both E and Ep is constant), the governing equation (5) becomes VdE = dPLV, which can be detailed as:During isovolumic contraction (because dV = 0, Vi(Ei - Ei-1) = Vi[(Ea,i + Ep,i) - (Ea,i-1 + Ep,i-1)] = Vi(Ea,i + Eped - Ea,i-1 - Eped) = dPLV,i     (9)i and PLV,i are the monitored LV volume and pressure at this instant, and Eped is the passive elastance at the end-diastolic phase.where i is a time instant during the isovolumic contraction and relaxation, V and Ep is constant), the governing equation (5) becomes VdE = dPLV, which can be represented as:Also, during isovolumic relaxation (because dV = 0, Vi (Ea,i + Ep,i - Ea,i-1 - Ep,i-1) = Vi (Ea,i + Epes - Ea,i-1 - Epes) = dPLV,i     (10)pes is the passive elastance at the end-systolic phasewhere ENow, applying equations (9 & 10) to the case shown in the Figure 1. For isovolumic contractionEa,1 = 0     (11-a)Ea,2 = (P2 - P1)/V2 + Ea,1 = 0.029477 mmHg/ml     (11-b)Ea,3 = (P3 - P2)/V3 + Ea,2 = 0.103771 mmHg/ml     (11-c)Ea,4 = (P4 - P3)/V4 + Ea,3 = 0.253584 mmHg/ml     (11-d)Ea,5 = (P5 - P4)/V5 + Ea,4 = 0.463599 mmHg/ml     (11-e)2. For isovolumic relaxationEa,18 = (P18 - P17)/V18 + Ea,17 = Ea,17 - 0.058954 mmHg/ml     (11-f)Ea,19 = (P19 - P18)/V19 + Ea,18 = Ea,17 - 0.177824 mmHg/ml     (11-g)Ea,20 = (P20 - P19)/V20 + Ea,19 = Ea,17 - 0.312656 mmHg/ml     (11-h)Ea,21 = (P21 - P20)/V21 + Ea,20 = Ea,17 - 0.463599 mmHg/ml     (11-i)a,17 at end-ejection is unknown. For different representative values of Ea,17, we can get different Ea curves. We need to determine the optimal value of Ea,17, such that Ea can be described by a smooth curve to fit both isovolumic contraction and ejection phases. In Figure a,17 = 1.1 mmHg/ml, and the polynomial expression for Ea(t) to fit its above calculated values during isovolumic contraction and relaxation. However, in order to (i) more suitably represent Ea to correspond with its role during the cardiac phases (isovolumic, ejection and filling), and (ii) because of the sigmoidal shape of Ea curve and its variation resembling the LV pressure variation during systole  as:Now in the above expressions 11(f-i), ESo that its constituent parameters have physiological significance as indicated following equation (8).a(s) during isovolumic contraction, when u(t-d) = 0, we employ the expressionHence, to compute Ea0, τC and ZC to fit the monitored pressure-volume data. Then, to compute Ea(s) during isovolumic relaxation, we employ the total expressionand determine its parameters EτR and ZR to fit the measured pressure-volume data.and determine its remaining parameters d, a is depicted in Figure a can be employed as an index of contractility.For the sample data of Figure During the diastolic filling phase, equation (5) becomesp is constant at a particular volume Vi, equation (13) becomesNow because Ei and PLV,i are the monitored LV volume and pressure at this time, and M = ρh / 4πR2. For the patient data . Therefore, from equation (15), we can calculate the values of Ep at various instants during filling phase. We then plot Ep vs V, in Figure p, we obtain the values of the parameters Ep0 and zp, as:where i is a time-instant during diastolic filling, Vzp = 0.0395 ml-1, Ep0 = 4.375 × 10-3 mmHg / ml     (16)p function (corresponding to its expression given by equation 7) as follows:and the EEp = 4.375 × 10-3 eV 0.0395    (17)p as a measure of LV resistance-to-filling.We now propose to adopt Ea and Ep are varying. During ejection and filling phases, Ep can be calculated at any time using equation (17). Likewise, Ea can be calculated during ejection and filling phases using equation (8), once its parameters have been determined by employing equation (12-b & 12-b) during isovolumic contraction and relaxation phases. Their values during the cardiac cycle are listed in Table Hence during ejection, both Eequation 7. LikewiThe analyses, presented herewith, are now applied to clinically obtained data consisting of the subject's left ventricular (instant-to-instant) dimensions (obtained by cineangiocardiograph) and chamber pressure (obtained by cardiac catheterization). For each subject, passive and active elastances are determined from the left ventricular data. Table a vs incremental pressure (P-Ped) for this patient HEL. Note that the elastance is much higher at late-ejection than early ejection. This is because of a continuing sarcomere stress development and shortening. The active elastance reaches its maximum value at late-ejection (point 15), and thereafter decreases. However as shown in Figure The variations of model-derived nonlinear passive and active elastances for the subject HEL are shown in Figure p vs LV volume plots, in Figure p increases exponentially with increase LV volume; the parameters (EP0 and zp) characterize this relationship. The passive elastance curve is steeper for a stiffer myocardium, with a corresponding bigger value of the exponential coefficient Zp (subject ML). The Ea vs incremental pressure (P-Ped) plots, in Figure a during systole, which in turn governs the generation of LV pressure.Figures a variation is by means of the Ea vs normalized time (t/ts) plot, shown in Figure a,max could be regarded as an index of LV contractility. Hence, we decided to plot Ea,max vs the traditional contractility indices of EF and (dP/dt)max. These plots are displayed in Figures a,max has a high degree of correlation with both EF and (dP/dt)max. It is interesting to compare our correlation-coefficient value (0.8972) with the value of 0.89 obtained by Mehmel et al [d)]es.Yet another way to study Eel et al , althougThe active elastance curve can explain some critical LV physiological phenomena, namely LV pressure generation during isovolumic contraction and LV suction during early filling. The rapid decrease in elastance during isovolumic relaxation extends into the filling phase, and can explain the decrease in LV pressure (Vi - Vi-1) + Vi (Ea,i - Ea,i-1)     (18)P term, based on the calculation of its value being of the order of 10-2 compared to (i) (Ep,i + Ea,i)(Vi - Vi-1), which is of the order of 100 and (ii) Vi(Ea,i - Ea,i-1) which is the order of 101.by neglecting the i can be less than Pi-1 (or that Pi - Pi-1 < 0) only if (Ea,i - Ea,i-1) is negative, i.e., active elastance is decreasing. Now for subject H.E.L  are:In equation 18), it is seen that P8, it is Ep,22 = 0.2768 mmHg/ml, Ea,22 = 0.0393 mmHg/ml, Ea,21 = 0.1140 mmHg/ml, V22 = 105 ml, V21 = 90.6 ml     (19)P22 - P21) = -3.22 mmHg, confirming decrease of pressure during early filling.Substituting these values into equation (18) gives (a during the early phase of filling" enables us to explain the phenomenon of decreasing LV pressure during the early stage of filling. In other words, it is suggested that the sarcomere actin-myosin activity continues into the filling phase. The decreasing Ea during the filling phase seems to reflect decreasing sarcomeric activity during filling. Likewise, the increase in Ea during isovolumic contraction is responsible for increase in LV pressure at constant volume, as demonstrated by means of equation (11).Hence, our novel concept of "decreasing E10 & t9), as follows:Similarly, both the active and passive elastances can explain LV pressure variation during ejection, using equation (18). Let us show how this happens by just taking two instants (t10 - P9 = (Ep,10 + Ea,10)(V10 - V9) + V10(Ea,10 - Ea,9)     (20)PP10 - P9 = 1.92 mmHg, which is approximately equal to the actual value of 2 mmHg.Substituting these computed values (listed in Table P / (V - Vd) [max (given by ESPVR) as illustrated on Figure Previous works have described elastance as a derived parameter from LV pressure-volume data, based on the definition of (V - Vd) ,10,12-14p and Ea enable us to explain the phenomena of (i) LV suction during early filing, (ii) LV pressure rise during isovolumic contraction (iii) LV pressure variation during the ejection phase, and (iv) LV pressure drop during the relaxation phase. Both the concepts of Ea and Ep are made possible by our redefining elastance and compliance asOur definitions of EdP = d(EV) = d(V/C) = VdE + EdV     (21)a enables us to explain (i) the generation of pressure during isovolumic contraction and decrease of pressure during isovolumic relaxation, when the volume is constant, and (ii) the decrease of pressure during the rapid filling phase.Our concept of Ea along with increasing Ep during filling, which enables us to explain the LV suction effect during early filling, is indirectly supported by the work of Shoucri [Our concept of decreasing E Shoucri . He has a, as provided by us.However, the determination of this active fiber stress in his paper is empirical and not based on a well-defined concept and expression for Ea and Ep are invoked to explain the variations of pressure during the ejection and filling phases. From the viewpoint of intrinsic indices of LV assessment, Ep can represent LV myocardial stiffness property and resistance to LV filling. On the other hand, Ea has been shown to correspond to LV contractility, by means of Figures a,max and (dP/dt)max as well as EF.Finally, both Ep and Ea) with an arterial lumped-parameter model  in order to simulate and explain the mechanisms of chronic hypertensive states [a itself as a measure of LV adaptation to chronic hypertension induced in the circulation system.In future, we can also couple our LV model  = ρh, ρ is the myocardial density, and u is the radial displacement, dPel and dPLV are the incremental elastic-recoil and left ventricular pressures .where the myocardial element mass, Now since,r1 = r2 = RBy assuming we can write:ρs is the surface density, M = ρsh, and V is the LV volume. Now, referring to Figure A-1,where andRe is the resistance to LV filling , ρf is the blood density and v is the blood velocity at site 2.where LVdP) as:Let us now define incremental elastic recoil pressure , we haveIntroducing the term elastance (= 1/C), we can put downLiang Zhong carried out the elastance studies, participated in data acquisition, performed statistical analysis and drafted the manuscript. Dhanjoo N. Ghista conceived of the study, and participated in its design and coordination and helped to draft the manuscript. Eddie Y-K Ng participated in coordination and helped to draft the manuscript. Soo T Lim participated in its design and coordination. All authors read and approved the final manuscript.


Cellular coactivators interacting with Bel1/Tas are unknown to date.Foamy virus Bel1/Tas trans-activator Bel1/Tas in vivo. Here we show that the Bel1/Tas-mediated trans-activation was enhanced by the coactivator p300, histone acetyltransferases PCAF and SRC-1 based on the crucial internal promoter BRE. The Bel1/Tas-interacting region was mapped to the C/H1 domain of p300 by co-immunoprecipitation and pull-down assays. In contrast, coactivator SRC-1 previously reported to bind to the C-terminal domain of p300 did not directly interact with the Bel1 protein but nevertheless enhanced Bel1/Tas-mediated trans-activation. Cotransfection of Bel1/Tas and p300C with an expression plasmid containing the C/H1domain partially inhibited the p300C-driven trans-activation.Transient expression assays, co-immunoprecipitation experiments, pull-down assays, and Western blot analysis were used to demonstrate that the coactivator p300 and histone acetyltransferase PCAF specifically interact with the retroviral trans-activator capable of partially blocking the strong Bel1/Tas-mediated activation of the C-terminal region of coactivator p300. The potential mechanisms and functional roles of the three histone and factor acetyltransferases p300, PCAF, and SRC-1 in Bel1/Tas-mediated trans-activation are discussed.Our data identify p300 and PCAF as functional partner molecules that directly interact with Bel1/Tas. Since the acetylation activities of the three coactivators reside in or bind to the C-terminal regions of p300, a C/H1 expression plasmid was used as inhibitor. This is the first report of a C/H1 domain-interacting retroviral  Both proteins function by mediating positive or negative cross talk between different signaling pathways and participate in fundamental cellular processes that include embryonic development, cell growth, differentiation, and apoptosis. In addition, they can act as tumor suppressors and, last but not least, directly interact with diverse viral trans-activators to facilitate virus replication or viral activator-mediated transformation [In the sequential model of transcriptional regulation including viral template -3. The ftemplate ,4,5. It ormation ,7.trans-activators, for instance p53 [Several models have been proposed to explain transcriptional activation. Coordinated recruitment of coactivators by diverse transcriptional activators to specific promoter target sites has been shown by a collective effort of many groups . Accordiance p53 .trans-activator proteins were found to interact with distinct domains of p300/CBP and PCAF. Prominent among them are the early adenoviral E1A antigen [Diverse viral  antigen ,11, Epst antigen , and hum antigen ,14. Seve antigen ,16.trans-activator of the acidic class and is known to directly interact with its responsive elements (BRE) [trans-activation domain (TAD) was mapped to the C-terminus of Bel1 with little if any protein homology to other FV Bel1/Tas proteins from different species. Previously, we identified the nuclear factor 1 (NF1) as a repressor of Bel1/Tas-mediated trans-activation [trans-activation. This is the first time that these cellular coactivators have been shown to interact with the Bel/Tas1 trans-activator protein. Furthermore, Bel1/Tas binding to the C/H1 domain of p300 and coactivator-driven trans-activation seem to follow a unique pathway.The apparently nonpathogenic primate foamy viruses (PFV) show a wide host range and tissue tropism and have been developed into vectors that efficiently transduce SCID-repopulating cells . The PFVts (BRE) ,19. Bel1ts (BRE) . Additiotivation . This retivation , we invetivation . Here wetrans-activate the Bel1 internal promoter (IP.BRE), transient reporter gene assays were performed. The IP.BRE that extends from -1 to -192 of the second cap site of the PFV genome was cloned into the pGL3-pro-luc reporter plasmid [trans-activator under the control of the CMV-IE promoter. The results of immunoblotting shown in the lower left panel of Figure To examine whether p300 . In contrast, when the HAT PCAF expression plasmid was used for co-expression, an enhancement of Bel1/Tas-induced activation was detectable at a concentration of 0.02 μg PCAF DNA and 0.5 μg pbel1s . It is intriguing that the distribution of the closely spaced Lysines of Bel1/Tas apparently mimics the correspondingly spaced Lysines in histones. This observation is further complicated by our observation that cotransfection with higher levels of PCAF led to a reduced stability of Bel1/Tas  into pCI-p300N digested with SphI/NotI for expression of residues 1 to 424 of p300. Construct no. 7  fusion proteins pGST-C/H1 (328–424) and pGST-KIX (436–661)  for 6 hr. Cells were harvested and used for immunoprecipitation as described above. The precipitates were analyzed by SDS-PAGE on 12% gels, dried, and exposed on KODAK Biomax MR1 films.Plasmid p300FL was transfected into 293T cells and metabolically labeled with L-[Plasmid pCMV-βgal directing β-galactosidase expression from the CMV-IE promoter was used for normalization of transfection efficiency. Luc reporter gene assays were performed and quantified as described  using a Immunoprecipitation was performed as described previously with minor modifications . LysatesE. coli BL21/DE3 cells after transformation with the corresponding plasmids. Expressed proteins were purified by binding to glutathione Sepharose 4B resin. Each of the GST-fusion proteins bound to glutathione Sepharose 4B were mixed with lysates obtained from pbel1s-transfected 293T cells. After incubation at 4°C overnight in binding buffer [The recombinant GST-C/H1 and GST-KIX proteins were expressed in g buffer  and exteg buffer  or detecCells were harvested two days after transfection by lysis in 1% SDS and the protein concentration was determined using the DC protein assay (BioRad). Identical amounts of proteins were separated by SDS-PAGE on 12% gels, blotted, reacted with monoclonal serum directed against the FLAG epitope of the four different FLAG-tagged p300 (Sigma), or polyclonal serum direct against Bel1 , and dettrans-activation domain; NF1, nuclear factor 1; CMV, cytomegalovirus; GST, glutathione-S-transferase.CBP, CREB-binding protein; C/H1, 2, and 3, Cys/His-rich domains of p300; FL, full-length; HAT, histone acetyltransferase; LTR, long terminal repeat; luc, luciferase; PCAF, p300/CBP-associated factor; Q, Glutamine-rich domain of p300; SRC, steroid receptor coactivator; p300N, p300M, and p300C, amino-, middle and C-terminal regions of p300; PFV, primate foamy virus; IP.BRE, internal promoter Bel1 response element; TAD, HB and WM contributed equally to the manuscript. VO carried out the molecular cloning of p300 derivatives. YN participated in the design of the study. All authors read and approved the final manuscript.


Xenopus neural induction starts earlier than previously thought, at the blastula stage, and requires the combined activity of two distinct signaling centers. One is the well-known Nieuwkoop center, located in dorsal-vegetal cells, which expresses Nodal-related endomesodermal inducers. The other is a blastula Chordin- and Noggin-expressing (BCNE) center located in dorsal animal cells that contains both prospective neuroectoderm and Spemann organizer precursor cells. Both centers are downstream of the early β-Catenin signal. Molecular analyses demonstrated that the BCNE center was distinct from the Nieuwkoop center, and that the Nieuwkoop center expressed the secreted protein Cerberus (Cer). We found that explanted blastula dorsal animal cap cells that have not yet contacted a mesodermal substratum can, when cultured in saline solution, express definitive neural markers and differentiate histologically into CNS tissue. Transplantation experiments showed that the BCNE region was required for brain formation, even though it lacked CNS-inducing activity when transplanted ventrally. Cell-lineage studies demonstrated that BCNE cells give rise to a large part of the brain and retina and, in more posterior regions of the embryo, to floor plate and notochord. Loss-of-function experiments with antisense morpholino oligos (MO) showed that the CNS that forms in mesoderm-less Xenopus embryos (generated by injection with Cerberus-Short [CerS] mRNA) required Chordin (Chd), Noggin (Nog), and their upstream regulator β-Catenin. When mesoderm involution was prevented in dorsal marginal-zone explants, the anterior neural tissue formed in ectoderm was derived from BCNE cells and had a complete requirement for Chd. By injecting Chd morpholino oligos (Chd-MO) into prospective neuroectoderm and Cerberus morpholino oligos (Cer-MO) into prospective endomesoderm at the 8-cell stage, we showed that both layers cooperate in CNS formation. The results suggest a model for neural induction in Xenopus in which an early blastula β-Catenin signal predisposes the prospective neuroectoderm to neural induction by endomesodermal signals emanating from Spemann's organizer.The origin of the signals that induce the differentiation of the central nervous system (CNS) is a long-standing question in vertebrate embryology. Here we show that  New insights into the early events of neural induction which render certain cells competent to respond to signals emanating from Spemann's organizer Lens induction is an example of a secondary embryonic induction. Most experimental embryologists concentrated their research on the induction of the neural plate, which is considered the primary embryonic induction  mRNA, a secreted antagonist specific for Nodal-related mesoderm inducers (Xenopus embryos lacking mesoderm still developed a CNS, including a cyclopic eye (Chordin (Chd), Noggin (Nog), and Goosecoid in dorsal endomesoderm at the gastrula stage. Second, a technical revolution has taken place with the availability of antisense morpholino oligos (MO) that permit loss-of-function studies in Xenopus  region that contains both prospective neuroectoderm cells and Spemann organizer precursors. The BCNE region also expresses Xenopus Nodal-related 3(Xnr3), a secreted factor with neural-inducing properties that is expressed at high levels in early Xenopus embryos , a gene expressed in anterior endoderm at gastrula . Neural differentiation could also be obtained in the absence of CerS mRNA when additional care was taken to avoid mesodermal contamination. As shown in In embryology, the test of whether cells are specified to form a particular tissue is to culture them in isolation from the rest of the embryo. Dorsal animal cap explants from embryos injected with  did not A and 3B.Xenopus is one of the best-studied vertebrate embryos, it was surprising that this requirement of a region of the blastula for CNS formation had not been reported previously. To investigate this further, we replaced the deleted fragment with various ectodermal grafts. The brain defects could be rescued by transplantation of dorsal, but not ventral, animal cap grafts  or pan-neural markers  were still expressed, indicating that only anterior neural differentiation was eliminated by Chd-MO and that posterior neural induction continues to take place. We also generated a Noggin antisense morpholino oligo (Nog-MO) reagent, which, like Chd-MO, inhibited brain markers  mRNA, or LiCl. These treatments induced multiple neural markers in animal caps , but not of posterior or pan-neural ones (HoxB9, NCAM) .Two recent studies have described morpholino antisense oligos targeting  factors . Xenopusvolution . Examinaectively A  blastula dorsal animal cells are the sole source of Chd, and anterior CNS differentiation can be completely inhibited by Chd-MO  for 5 min and incubated overnight with reaction buffer containing 10% BM purple solution (Roche) in a Coplin jar in the dark at 4°C. Staining was stopped by incubation in Stop solution (100 mM Tris-HCl, 1 mM EDTA, pH 7.4), and sections dehydrated in 100% methanol and completely air-dried before mounting in Vectashield medium . In some experiments nuclear lacZ mRNA (kind gift of R. Harland), fluorescein dextran amine or Texas red dextran amine were used as lineage tracers.To fate map BCNE descendants, an improved lineage tracing method was developed. Embryos were injected with 1–4 nl of 1% BDA (Molecular Probes, Eugene, Oregon, United States) in Hin MEMFA . SubsequCerS, pCS2-Chd, pCS2-β-catenin, and pCS2-dnGSK3 were linearized with NotI and transcribed with SP6 RNA polymerase as described previously  for Chd, 800 pg  for β-catenin, and 600 pg  for dnGSK3 mRNA.To generate synthetic mRNAs, the plasmids pCS2-eviously . The folChd-MO1 (5′-ACG TTC TGT CTC GTA TAG TGA GCG T-3′) and Chd-MO2 (5′-ACA GCA TTT TTG TGG TTG TCC CGA A-3′) (Nog-MO (5′-TCA CAA GGC ACT GGG AAT GAT CCA T-3′) (this work); β-cat-MO (5′-TTT CAA CCG TTT CCA AAG AAC CAG G-3′) (Cer-MO (5′-ACT TGC TGT TCC TGC ACT GTG C-3′) (this work); and a control-MO (5′-CCT CTT ACC TCA GTT ACA ATT TAT A-3′) (Chd-MO solution (Chd-MO1-SS:Chd-MO2-SS:H2O = 1:1:6), β-cat-MO solution (β-cat-MO-SS:H2O = 1:4), Nog-MO solution (Nog-MO-SS:H2O = 1:1), Cer-MO solution (Cer-MO-SS:H2O =1:1), control-MO solution (control-MO-SS:H2O = 1:1), and Chd-MO/Nog-MO solution (Chd-MO1-SS:Chd-MO2-SS:Nog-MO-SS:H2O = 1:1:4:10). A total of 8 nl (two times 4 nl or four times 2 nl) morpholino solutions were injected at the 2-cell stage or 4 nl (two times 2 nl) of morpholino solution injected at the 8-cell stage.Morpholino oligos were as follows: GA A-3′) ; Nog-MO AG G-3′) ; Cer-MO AT A-3′) . The morFigure S1(A–H) Microinjection of individual 32-cell blastomeres does not faithfully recapitulate the lineage of BCNE grafts at gastrula (compare with (I–L) Diagram indicating the injection of the lower daughter of B1 and the upper daughter of C1 at the 64-cell stage (I), which reliably identify BCNE descendants at stage 9 (J), stage 11 (K), and stage 36 (L). Arrowheads indicate the blastopore. Abbreviations: fp, floor plate; no, notochord.(4.39 MB TIF).Click here for additional data file.http://www.ncbi.nlm.nih.gov/Genbank/index.html) accession numbers discussed in this paper are for β-catenin (M77013), Cer (U64831), Cer pseudoallele (BG160114), Chd (L35764), Goosecoid (M81481), and Nog (M98807).The GenBank (


We investigated lifetime alcohol consumption and prostate cancer risk in a case-control study conducted in Buffalo, NY (1998–2001).The study included 88 men, aged 45 to 85 years with incident, histologically-confirmed prostate cancer and 272 controls. We conducted extensive in-person interviews regarding lifetime alcohol consumption and other epidemiologic data.Prostate cancer risk was not associated with lifetime intake of total and beverage specific ethanol. In addition we found no association with number of drinks per day (average drinks per day over the lifetime) or drinks per drinking day (average drinks per day on drinking days only over the lifetime). However, we observed an inverse association with the total number of drinking years. Men in the lowest tertile of total drinking years had a two-fold prostate cancer risk than men in the highest tertile (OR 2.16, 95% CI 0.98–4.78, p for trend <0.05).Our results suggest that alcohol intake distribution across lifetime may play a more important role in prostate cancer etiology than total lifetime consumption. Prostate cancer is the most frequently diagnosed malignancy and the second leading cause of cancer death among men in the Western countries . NotwithAmong the population-based case-control studies, those carried out by Heyes et al.  and SharAlthough prostate cancer is known to have a long latency period, lifetime alcohol consumption was not addressed in the studies carried out until the late 1990s, and rarely in the more recent studies . FurtherAlcohol may act as a carcinogen itself and may also modulate risk from other carcinogen exposures. It has been implicated in risk of cancer at a number of sites ,20. In tWe conducted a case-control study of prostate cancer and hormones and alcohol intake (the PROMEN STUDY) in Erie and Niagara Counties, NY, USA, between December 1998 and April 2001. The methods for this study have been previously described in detail . ParticiCases were men aged 45 to 85 years with incident, primary, histologically confirmed prostate cancer. Men with a previous history of cancer (except non-melanoma skin cancer), or already on hormonal or chemotherapy treatment (current or in the 6 months prior to diagnosis), as well as those affected by chronic or acute liver diseases, were excluded. Cases aged 35–65 years were also required to have a driver's license, because we used driver's license records to identify age matched controls.During the study period, 504 men were identified with incident prostate cancer. Of these, 336 men did not meet the eligibility criteria; we invited the remaining 163 patients to participate in the PROMEN study. After being contacted, 50 men refused to participate resulting in a participation rate of 70%. Ninety-six patients had complete data for the variables of interest.Controls aged between 35 and 65 years were selected from a list of individuals holding a New York State driver's license and residing in Erie and Niagara Counties. Those aged 65 and over were selected from the rolls of the Health Care Financial Administration. As with cases, men on hormonal treatment (current or in the 6 months prior the diagnosis), or diagnosed with metabolic or endocrine disease were excluded, as well as participants with a previous story of cancer other than non-melanoma skin cancer. Since it is well known that latent prostatic carcinoma has a high prevalence in men over 50 ,23, we eDuring the study period, 1373 potential controls were contacted. One hundred and seventy nine of these individuals were deceased or were too ill to participate, 293 did not meet the eligibility criteria and we were not able to contact 272 persons. We identified eight prostate cancer cases as a result of PSA determination in subjects who initially were recruited as controls. Three hundred and seventeen of the remaining 513 subjects (60%) were enrolled and interviewed: 304 had complete data for analysis.2). Waist to hip ratio (WHR) was calculated as waist circumference divided by hip circumference.Extensive data on demographics, smoking history, alcohol consumption, and other study variables were collected by trained interviewers during in-person computer-assisted interviews  and withDetailed information on alcohol consumption throughout the lifetime was collected using the Cognitive Lifetime Drinking History ,27. PrioDrinks per interval was estimated by multiplying quantity by frequency for days of the week and more than usual and adding. Drinks per interval was translated into ounces of ethanol per interval based on the proportion of drinks represented by specific beverages, respondents' beverage-specific drink size in ounces, and factors representing the average percent per ounce of absolute alcohol for a given beverage to estimates of drinks per interval. Factors used were 0.048, 0.12, 0.04 and 0.40, for beer, wine, wine cooler and hard liquor, respectively. These estimates were summed across drinking intervals to yield lifetime totals.We considered several variables in these analyses: total number of years alcohol was consumed, number of drinks per day during the drinking years , number of drinks per drinking day , total lifetime ounces of ethanol and beverage-specific total lifetime ounces of ethanol. Because few participants consumed wine coolers, wine and wine coolers were combined. A drink was defined as 12 ounces of beer, 5 ounces of wine, and 1.5 ounces of liquor.2 for categorical variables. Lifetime abstainers, defined as those subjects who had less than 12 drinks in any one year over their lifetimes, were excluded from our analyses. The biological and social differences between lifetime abstainers and both former and current drinkers [Statistical analyses were conducted using SPSS for Windows version 11.0. Differences between cases and controls in demographic characteristics and alcohol consumption were assessed using t-tests for continuous variables and χdrinkers ,29 and tIn analyses of risk associated with lifetime alcohol intake, tertiles of total and beverage specific ounces and total drinking years were computed based on the distribution in the controls. For the beverage specific analyses, non-drinkers were those respondents not consuming that particular alcoholic beverage. For risk associated with drinks per day and drinks per drinking day, we categorized consumption as two drinks or less per day and greater than two drinks per day. Odds ratios (OR) and 95% confidence intervals (CI) for risk of prostate cancer associated with alcohol consumption were computed using unconditional logistic regression adjusting for age, cigarette smoking status, education, body mass index (BMI), and waist to hip ratio (WHRATIO). The beverage specific analyses were further mutually adjusted for the other beverages.Characteristics of the participants in the PROMEN study are shown in Table Means and standard deviations for aspects of lifetime alcohol consumption for the sample overall and by current drinking status are shown in Table Odds ratios and 95% confidence intervals for the risk of prostate cancer associated with lifetime alcohol consumption are shown in Table The assessment of lifetime alcohol consumption in cancer etiology has been predominantly expressed through the calculation of either total lifetime volume or an average volume per specified time period across the lifetime. Few investigations have evaluated lifetime drinking patterns in relation to prostate cancer risk. While methodological difficulties challenge the evaluation of drinking patterns, our results suggest that failure to take into account aspects of drinking pattern such as the relative duration and dose of consumption may reduce our ability to clearly elucidate the role alcohol may be playing in cancer development. Although we observed no associations with risk for total lifetime alcohol intake or when alcohol was expressed as average drinks per day or even average drinks per drinking day, our results suggest that the impact may differ when the same volume of alcohol consumption takes place in fewer drinking years over a lifetime.Furthermore, it is notable that alcohol consumption was much higher among the cases compared with controls who were former drinkers. As alcohol consumption has been positively related to many causes of morbidity, a proportion of these men may have stopped drinking in response to poor health. Whether pre-existing morbid conditions or heavier drinking is related to subsequent development of prostate cancer remains to be clarified.Our study has several strengths and limitations. A limitation of our study is the small sample size, especially for cases. However, because one of the original aims of the study was an examination of hormones and prostate cancer, both cases and controls were carefully identified. To eliminate the effect on hormone levels by treatment, cases were enrolled in the study prior to starting chemotherapy or hormone therapy; thus increasing the difficulty of case ascertainment. On the other hand, the exclusion of controls with high circulating PSA levels helped to reduce misclassification and to ensure that the control group was free from prostate cancer. The data used in the present analysis were collected as a part of an in-person interview, and the questionnaire about lifetime alcohol consumption was very detailed allowing us to compute both the dose and frequency aspects of alcohol consumption.Given the difficulties involved in measuring alcohol consumption, studies utilizing data collected before diagnosis would appear more likely to lead to valid inferences. Recently, Dennis in his meta-analysis  pointed The plausibility of alcohol as a risk factor for prostate cancer relates to evidence that alcohol may act as a carcinogen or may modulate risk from other known carcinogens through generation of free radicals, affecting the metabolism of detoxification enzymes, impairment of immune system and depression of DNA repair enzymes . It remaFurther studies focusing on lifetime exposure and more specifically on patterns of consumption may help in prevention of a disease with considerable public health impact.BMI body mass indexPSA prostate-specific antigenWHRATIO waist-to-hip ratioThe authors declare that they have no competing interests.MB performed statistical analyses, interpreted the results and drafted the manuscriptSEM performed statistical analyses, interpreted the results and revised the manuscriptHJS interpreted the results and revised the manuscriptSS interpreted the results and revised the manuscriptBJF performed data analysis, interpreted the results and revised the manuscriptSDP interpreted the results and revised the manuscriptGC interpreted the results and revised the manuscriptJLF interpreted the results and revised the manuscriptMT revised the manuscriptMR defined the exposure variables and revised the manuscriptTN defined the exposure variables and revised the manuscriptPM designed and implemented the study, interpreted the study results, revised the manuscript


Low levels of high density lipoprotein (HDL) cholesterol and disturbed postprandial lipemia are associated with coronary heart disease. In the present study, we evaluated the variation of triglyceride (TG) postprandially in respect to serum HDL cholesterol levels.p = 0.002). The low HDL group had significantly higher TG at 4, 6 and 8 h postprandially compared to the controls (p = 0.006, p = 0.002, and p < 0.001, respectively). The matched-low HDL group revealed higher TG only at 8 h postprandially (p = 0.017) compared to the matched-control group. ROC analysis showed that fasting TG ≥ 121 mg/dl have 100% sensitivity and 81% specificity for an abnormal TG response (auc = 0.962, p < 0.001).Fifty two Greek men were divided into 2 main groups: a) the low HDL group (HDL < 40 mg/dl), and b) the control group. Both groups were further matched according to fasting TG (matched-low HDL, and matched-control groups). The fasting TG concentrations were higher in the low HDL group compared to controls (The delayed TG clearance postprandially seems to result in low HDL cholesterol even in subjects with low fasting TG. The fasting TG > 121 mg/dl are predictable for abnormal response to fatty meal. The hypothesis that low levels of high density lipoprotein (HDL) cholesterol is associated with coronary heart disease (CHD), raised since the 1950s ,3 as it All participants ingested their fatty meal and tolerated it well.The clinical characteristics of the two main study groups (low HDL and controls) are shown in Table p < 0.001, and p = 0.007, respectively) by definition. The fasting TG (TG0) concentrations were higher in low HDL cholesterol group compared to controls (p = 0.002).The plasma HDL cholesterol and apolipoprotein A were lower in low HDL group compared to controls (p < 0.006) TG level compared to the controls.The low HDL subjects had a significantly higher (p < 0.002) TG level compared to controls.The low HDL subjects had a significantly higher (p < 0.001) TG level compared to the controls.The low HDL subjects had a significantly higher  and in low HDL-Abnormal (low HDL-A) and low HDL-Normal (low HDL-N) groups .p = 0.017).Subjects with low HDL cholesterol had higher TG concentration at 8 h postprandially (p = 0.007, and p < 0.012, respectively). As expected, postprandial TG levels were higher in those classified as having an abnormal response.Thirteen (45%) of the low HDL subjects (low HDL-A group) had an abnormal TG response to the fatty meal test compared to the controls. The other sixteen low HDL subjects (low HDL-N group) had a TG response to the fatty meal that was similar to that in the control subjects. The low HDL subjects with an abnormal fatty meal response (low HDL-A group) had higher plasma total cholesterol and lower lipoprotein (a) concentrations  in relation to time are schematically represented in Figure 0 was the only predictor of high AUC values (Coefficience B = 7.15, p = 0.016). ROC analysis showed that TG0 levels ≥ 121 mg/dl have 100% sensitivity and 81% specificity for an abnormal TG response (auc=0.962, p < 0.001). After we divided the low HDL men in low- or high- groups by using the ROC curve cut-off values of TG0, total cholesterol and lipoprotein (a), i.e. low/high TG0, low/high total cholesterol and low/high lipoprotein (a) groups, the only distinction that predicted an abnormal TG response was the high-TG0 group (p < 0.001)In multivariate linear regression analysis, where the independent variables were age, body mass index (BMI), total cholesterol, HDL cholesterol, TG, lipoprotein (a), and areas under the curve (AUC) was the dependent variable, the TGIn the present study, we found that a slower clearance of TG-rich lipoproteins from circulation postprandially results in low fasting levels of HDL cholesterol. Additionally, fasting plasma TG concentration is the primary determinant of the magnitude of postprandial lipemia.Subjects with a low fasting HDL and low TG levels showed a delayed TG clearance at 8 h compared to those with a normal fasting HDL value. The increase in TGs (from 2 to 4 h) after meal consumption mainly reflects dietary TG absorption, whereas the return to fasting levels (from 6 to 9 h) is presumably a function of TG clearance . In our 2 [2, this phenotype may provoke similar metabolic abnormalities. The HDL formation is closely associated with TG catabolism [The high TG and low HDL cholesterol phenotype has been frequently reported in "abdominal" obesity ,21. Obes2 . Our restabolism  as mentitabolism . Patsch tabolism  have pro0 level ≥ 121 mg/dl have 100% sensitivity and 81% specificity for an abnormal TG response.In our study, no difference was observed in the early postprandial TG response (absorption phase) between normolipidemic controls and men with low fasting HDL cholesterol and low fasting plasma TG concentration. In contrast, the group with low HDL cholesterol (31 ± 7 mg/dl) and variable values of fasting TG  revealed a higher TG curve postprandially compared to healthy subjects with moderate HDL cholesterol (53 ± 19 mg/dl) and low fasting TG levels (89 ± 30 mg/dl). When both groups were matched for fasting TG levels, this curve-difference was diminished, although HDL cholesterol levels remained significantly different between the two groups. When subjects with low HDL cholesterol were subdivided based on their response  to fat loading, fasting TG concentration seemed to be the critical determinant of such response. Since there are no official guidelines to determine normal postprandial TG ranges, the characterization of a TG response as "normal" or "abnormal" after fat loading was based on this report and on previous reports of ours and others. The peak TG mean value in control subjects was 139 ± 41 mg/dl (at 6 h) , 176 ± 1Couillard et al.,  reportedPostprandial hypertriglyceridemia is not a uniform abnormality. It pathophysiologic cause is not yet known. It is possible that the response to a fatty meal is gene dependent. It has been reported that a number of gene loci, such as these of apolipoprotein E, lipoprotein lipase, apolipoprotein CIII, apolipoprotein A1, apolipoprotein A4, cholesterol ester transfer protein are related to fat load response ,35. HoweThe delayed TG clearance postprandially seems to result in low HDL cholesterol levels even in subjects with low fasting TG concentration. Moreover, fasting plasma TG levels appear to be the primary determinant of the magnitude of postprandial lipemia. The fasting TG levels higher than 121 mg/dl are predictable for abnormal response to a fatty meal. This should be taken into account for the management of patients with fasting low HDL cholesterol levels.The study population consisted of 52 Greek men recruited from the Lipid Clinic of Onassis Cardiac Surgery Center, Athens, Greece. Heavy drinking, liver and renal disease, diabetes mellitus, metabolic syndrome, according to the NCEP ATP III guidelines , hypothyThe study population was divided into 2 main categories:A: The low HDL group and the control group.1. The low HDL group consisted of 29 men, mean age 45(13) years with low HDL cholesterol (< 40 mg/dl) according to NCEP ATP III guidelines .2. The control group consisted of 23 healthy men, mean age 51(9) years with no family history of premature atherosclerosis, diabetes mellitus, arterial hypertension or dyslipidemia. Their fasting TG levels were < 150 mg/dl, total cholesterol < 240 mg/dl and HDL cholesterol = 40 mg/dl. All subjects were never smokers.B: Matched groups according to fasting TG level.1. The matched-low HDL group consisted of 20 men, mean age 47(13) years with low HDL cholesterol and low fasting TG levels [100(31) mg/dl].2. The matched controls consisted of 20 men, mean age 51(10) years with lasting TG levels 95(27) mg/dl.2).All patients were studied in the outpatient clinic between 8.00–9.00 am after 12 hours (h) overnight fast. The fatty meal was consumed within 20 min and plasma TG concentrations were measured before and 4, 6 and 8 h after the fat load. During this 8 h period, the participants did not eat; they could only drink water and they did not smoke. Blood samples were drawn at 8:00 am , at 12:30 pm , at 2:30 pm , and at 4:30 pm . In all samples total cholesterol, TG, HDL, apolipoprotein A and B, and lipoprotein (a) were measured. BMI was calculated as weight divided by height (expressed in kg/m2).The fatty meal has been previously described . BrieflyWe defined postprandial hypertri-glyceridemia as any postprandial TG concentration (at 4, 6 or 8 h) higher than the highest TG concentration in any hour in any control individual; this TG value was 219 mg/dl.Plasma total cholesterol, TG and HDL cholesterol were measured using enzymatic colorimetric methods on a Roche Integra Biochemical analyzer with commercially available kits (Roche). The serum low-density lipoprotein cholesterol levels were calculated using the Friedewald formula . ApolipoAll participants gave their informed consent before the study. The ethical committee of the Onassis Cardiac Surgery Center approved the study.0), and lipoprotein (a) were the independent variables tested. ROC curve statistics was used to estimate the cutoff value of baseline triglyceride, cholesterol and lipoprotein (a) levels  above which the low HDL men develop an abnormal TG response to fat load. Using those cut-off values, we created dichotomous variables for each one of the univariate predictors to test their significance in discriminating patients with abnormal TG response to fat load. The level of significance was set at p < 0.05. AUC for serial measurements of TG levels at baseline and after the fatty meal were calculated using the trapezoid rule.Values of numerical characteristics were tested for normality and are presented as mean value with one standard deviation, when normally distributed, or as median and range, when they deviated from normality. A t-test for independent samples or a Mann Whitney U test was used for the comparison of numerical values between two groups and ANOVA or Kruskal-Wallis test for three groups, with Bonferoni correction for post hoc analysis. The comparison of clinical categorical variables was performed with the use of chi-square test. Multivariate linear regression analysis was performed to determine the predictors of elevated AUC levels, where age, BMI, total cholesterol, HDL cholesterol, fasting TG (TGGK conceived the study and participated in the development of the hypothesis, the study design and drafting of the manuscript.KA is a research associate who participated in the development of the hypothesis, study design and drafting of the manuscript.NP participated in data analysis and in the interpretation of the findings.NK is a physician who participated in the study design and recruitment of subjects, clinical evaluation and collection of blood samples.KS is a senior nurse who participated in the study design, in the recruitment of subjects and in blood sample collection.EP is a biochemist who participated in the laboratory part of the study.DC participated in the design of the study and its coordination.