The development of 3-D, in vitro, endothelial culture models for the study of coronary artery disease

The response of the vascular endothelium to wall shear stress plays a central role in the development and progression of atherosclerosis. Current studies have investigated endothelial response using idealized in vitro flow chambers. Such cell culture models are unable to accurately replicate the complex in vivo wall shear stress patterns arising from anatomical geometries. To better understand this implication, we have created both simplified/tubular and anatomically realistic in vitro endothelial flow models of the human right coronary artery. A post-mortem vascular cast of the human left ventricular outflow tract was used to create geometrically accurate silicone elastomer models. Straight, tubular models were created using a custom made mold. Following the culture of human abdominal aortic endothelial cells within the inner lumen, cells were exposed to steady flow (Re = 233) for varying time periods. The resulting cell morphology was analyzed in terms of shape index and angle of orientation relative to the flow direction. In both models a progressive elongation and alignment of the endothelium in the flow direction was observed following 8, 12, and 24 hours. This change, however, was significantly less pronounced in the anatomical model (as observed from morphological variations indicative of localized flow features). Differences were also observed between the inner and outer walls at the disease-prone proximal region. Since morphological adaptation is a visual indication of endothelial shear stress activation, the use of anatomical models in endothelial genetic and biochemical studies may offer better insight into the disease process

Use of inert gas jets to measure the forces required for mechanical gene transfection

BACKGROUND: Transferring genes and drugs into cells is central to how we now study, identify and treat diseases. Several non-viral gene therapy methods that rely on the mechanical disruption of the plasma membrane have been proposed, but the success of these methods has been limited due to a lack of understanding of the mechanical parameters that lead to cell membrane permeability. METHODS: We use a simple jet of inert gas to induce local transfection of plasmid DNA both in vitro (HeLa cells) and in vivo (chicken chorioallantoic membrane). Five different capillary tube inner diameters and three different gases were used to treat the cells to understand the dependency of transfection efficiency on the dynamic parameters. RESULTS: The simple setup has the advantage of allowing us to calculate the forces acting on cells during transfection. We found permeabilization efficiency was related to the dynamic pressure of the jet. The range of dynamic pressures that led to transfection in HeLa cells was small (200 ± 20 Pa) above which cell stripping occurred. We determined that the temporary pores allow the passage of dextran up to 40 kDa and reclose in less than 5 seconds after treatment. The optimized parameters were also successfully tested in vivo using the chorioallantoic membrane of the chick embryo. CONCLUSIONS: The results show that the number of cells transfected with the plasmid scales with the dynamic pressure of the jet. Our results show that mechanical methods have a very small window in which cells are permeabilized without injury (200 to 290 Pa). This simple apparatus helps define the forces needed for physical cell transfection methods

Design of a 3D printer head for additive manufacturing of sugar glass for tissue engineering applications

Additive manufacturing is now considered as a new paradigm that is foreseen to improve progress in many fields. The field of tissue engineering has been facing the need for tissue vascularization when producing thick tissues. The use of sugar glass as a fugitive ink to produce vascular networks through rapid casting may offer the key to vascularization of thick tissues produced by tissue engineering. Here, a 3D printer head capable of producing complex structures out of sugar glass is presented. This printer head uses a motorized heated syringe fitted with a custom made nozzle. The printer head was adapted to be mounted on a commercially available 3D printer. A mathematical model was derived to predict the diameter of the filaments based on the printer head feed rate and extrusion rate. Using a 1 mm diameter nozzle, the printer accurately produced filaments ranging from 0.3 mm to 3.2 mm in diameter. One of the main advantages of this manufacturing method is the self-supporting behaviour of sugar glass that allows the production of long, horizontal, curved, as well as overhanging filaments needed to produce complex vascular networks. Finally, to establish a proof of concept, polydimethylsiloxane was used as the gel matrix during the rapid casting to produce various “vascularized” constructs that were successfully perfused, which suggests that this new fabrication method can be used in a number of tissue engineering applications, including the vascularization of thick tissues

Collaborative Research between Aston Research Centre for Healthy Ageing (ARCHA) and the ExtraCare Charitable Trust

Executive Summary A Longitudinal evaluation of the ExtraCare Approach 1.0 Introduction This report consists of a summary of the full findings. Throughout the report the emphasis is on key learning points: what are the implications of the findings and what could be further developed? ExtraCare management have contributed with a brief summary of their responses or plans to emphasise the collaborative nature of this project, to be found in Section 13.0 of the document. Original objectives: We set out with the overall objective of evaluating whether the ExtraCare approach gives positive outcomes for healthy ageing which result in measurable health and social care cost savings. In a longitudinal study, 162 new residents are compared against 39 control participants. We took measures of health, well-being, cognitive ability and mobility at entry, 3, 12 and 18 months. Qualitative data were gathered using focus groups, interviews and case studies. People were additionally invited to keep a diary to record activities. Outcomes also include health and social care usage and costs to contribute to answering the original question. ExtraCare villages and schemes taking part: Fourteen Villages and Schemes took part in the project. 2.0 Numbers of people taking part Initial targets for recruitment of 160 new residents and 25 control participants were slightly exceeded (162 and 33 respectively), although ExtraCare well-being data at baseline was only available for 151 of these. Over the centres used, 17% of new residents took part. By 18 months there were 108 ExtraCare and 29 control participants in the study for the Aston assessments (69 and 29 respectively for well-being data. The attrition is indicated by the difference between initial and final Aston assessments, whereas the difficulties in getting complete well-being (health) data are illustrated by the difference between the final Aston and final well-being data (108-69 = 39 missing well-being assessments). For the crucial 12 month health data (NHS or Care use are measured over 12 months) there are 96 ExtraCare residents (as against 127 residents in the Aston assessments, that is, 31 missing due to missing well-being assessments). There are 666 Aston assessments and 530 well-being assessments across the four time points. For qualitative data we conducted two or three focus groups at eight sites (total of 74 participants). We individually interviewed six residents within 2-5 months of moving into ExtraCare, then at 6 and 18 months after moving in. This was the only longitudinal component of the qualitative work. Three Case studies were conducted which included interviews and observation within the ExtraCare site. We interviewed two managers formally and when on site met with managers and staff groups to discuss general issues. Attrition: 40% of ExtraCare and 29% of Control participants left the study before completion. With our longitudinal design feature of periodically adding in new volunteers with matched duration of residence, this resulted in overall attrition of 29% (33.3% for residents, 6% for controls), comparing favourably with other similar studies. 33% attrition was anticipated in calculations of sample size. Attrition was selective to participants who were less well. Twelve ExtraCare volunteers died during the period (7.4%) and 14 stated their own or partner’s illness as a reason for not continuing. One qualitative interview volunteer died between the second and third meeting. Those lost to sample were no older than those still available at 18 months. Data summary and challenges: There were some challenges with the ExtraCare Well-being Advisors’ data entry throughout the study which did eventually result in some loss of data, resulting in a mismatch between numbers with full Aston data and those with full well-being data, despite our best efforts and those of the Well-being Advisors. One of the most significant issues was gaps and changes in well-being staffing. Additional financial resources were authorised by ExtraCare to ensure that some of the missing assessments could be carried out where there was a longer term staffing vacancy. Nevertheless, there are still sufficient numbers for most of the analyses planned. ExtraCare was already planning a new centrally stored and more user-friendly data base, so any future data will be easier to use for all concerned. Further description of initial sample: ExtraCare participants were significantly older than controls on average, had more chronic illnesses and differed in terms of socio-economic groupings such that there were fewer professional and higher management and more people with unskilled occupational backgrounds. Control group participants perceived their health to be significantly better than did ExtraCare participants at baseline, and had fewer care needs or functional limitations. Cognitive function and emotional well-being differed between the groups at baseline, even controlling for age differences. There were proportionately more men in the ExtraCare sample than in the Control sample (38.3% as compared with 25.8%). 3.0 Summary from the Diary data 57 ExtraCare and 22 control participants agreed at baseline to keep a diary of their activities over the period, down to 35 and 12 respectively by 18 months. Number of activities was categorised broadly into social, physical and intellectual activity types. There was significant increase in activities over the first 3 months in all categories, but then a levelling off or decrease. For the full duration, only social activity increase remained significant. Given our understanding of the benefits of physical, intellectual and social engagement, these findings indicate a need for continued efforts to involve people, support them to get involved, and listen to what they would like in terms of activities. At baseline, there were five people who reported no activities of any nature but there were none at any subsequent time period. 4.0 Summary from the Qualitative data The aim of the qualitative arm of this study was to try to understand residents’ perspectives and experiences of daily life in ExtraCare. We approached the data with openness and regarded participants as experts of their own experience. It is important to emphasise that whether residents’ accounts of life in ExtraCare are ‘true’ or not, they are real to them and can tell us important things about perceptions and feelings. As well as gaining accounts from residents we also met with managers and conducted observations when visiting each of the eight sites in our sample. Sample description: We aimed to gather data from a range of residents and staff. A total of 144 people (131 ExtraCare residents) took part in the qualitative components of the study. Of the 6 focus group resident participants, 83 were in villages and 48 in schemes. Of the six interview participants, three were in receipt of care or social support, one had private care, one was cared for by his wife, and one had no care. All reported at least one significant health concern. Overview of findings: The focus groups generated some rich data around how ExtraCare had changed over time but also whether initial expectations were maintained. We focus on three areas which have shown to be consistent areas of concern to residents of ExtraCare taking part in focus groups and interviews: 1. connectivity in and beyond ExtraCare; 2. perceptions of change in ExtraCare; 3. negotiating transitions and increasing needs. • Volunteering was experienced positively by some as a way of connecting to others in the ExtraCare community, or as a “new lease of life”; for some it was something they felt unable to do and therefore marginalised them from the ‘able’ residents. • Some residents retained connections from the wider community and were able to maintain friendships; others struggled to meet people and felt lonely within the ExtraCare community. • There was a feeling of change at ExtraCare among residents who had lived there a long time. Some of this was financial but other aspects were about a perceived culture shift in the organisation. • Residents’ sense of well-being may come from experiential activities, i.e. finding enjoyment in other people’s activities or through reading or watching television. • Domiciliary care provided can be experienced as a boost of independence to set one free to do activities one enjoys rather than worrying about the mundane activities of everyday life. • Some residents expressed reticence to seek care perhaps through guilt around their own sense of duty to care for a spouse or through embarrassment or pride. • Seeking care was perceived by some as letting go of one’s independence. Identity: There were less obvious subjective changes (or changes at the level of identity) in which residents sought to maintain inclusion in mainstream ExtraCare life and be seen as independent and self-sufficient, but were perhaps struggling to do so. This may not be consciously registered, but some perceptions of changes and decline in ExtraCare raised may relate to transitions in identity and subjectivity. However, in some locations during the period there were changes in provision of care due to Local Authority changing contracting arrangements. Some complaints may be well founded, of course, but there is also a need to listen to residents’ complaints (against ExtraCare management and against other residents) as markers of difficult transitions, requiring emotional support. 5.0 Changes across time in the key psychological and functional measures The most dramatic differences occurred in the early months after moving in, detailed in previous reports. Now there are data at four time points, we can use growth curve modelling to examine effects of time. The analyses employed a set of complex statistical controls for attrition, age differences and in some circumstances for ceiling effects (healthy people having no reported problems on some measures, e.g. Activities of Daily Living measures). As such, great care has been taken to ensure the reliability of findings. Effects over time which were different to control group changes (that is, ExtraCare effects): There were significant continuous improvements across the period in depression, perceived health, memory and autobiographical memory, in a way that was significantly different from the way the measure changed over time for the control group. Positive Effects over time which were not significantly different from control group changes: These are changes that we need to know about but which are not unique to ExtraCare residents. This was the case for: anxiety, communication limitations and fluency (executive function). Variables which varied with age in the control group but not for the residents: This was the case for: Instrumental Activities of Daily living (IADL) and Social Function limitations. ExtraCare may be reducing the normally expected change in function with increasing age. This is also a feature of the fact that decisions to move into ExtraCare are usually needs related, rather than age related. The two most important implications are that: • some factors can be changed: decline is not inevitable and improvement is possible even in variables that commonly decline with increasing age, given a supportive environment; • Age itself is less important than health in terms of determining need for support and potential decline 6.0 Well-being data Comparisons here are focussed on Baseline to 12 month data. Social care costs: 19% of the sample were in receipt of care at both time points. ExtraCare costs an average of £427.98 less per person per annum than comparative local authority charges. This difference is greater at higher levels of care, and varies according to local authority costs in each location. For the people who were in the sample at both time points, the difference reduced from £414.61 to £363.77. Savings for the more expensive levels of care increase over time. NHS Costs – Comparing EC and Control Participants: Total NHS costs were estimated for each participant, including practice and district nurse, GP and outpatient appointments as well as admissions. Average ExtraCare resident NHS costs reduced by 47% over 12 months. Control NHS costs reduced by 14.1%. BUT when you control for the fact that the more poorly are the people who left the sample this is a 38% reduction, (still a significant reduction). This equates to an average saving of £1114.94 per person per year. In using this figure to scale up for the whole population, it should be borne in mind that this is probably a maximum, e.g. we did not assess people who do not have capacity to consent, and we may surmise that many very poorly people do not take part at all. Costs for these people may not have shown reductions to the same extent. Health profile Medications, illnesses and lifestyle: ExtraCare participants took more prescribed medications than did controls and had a significantly greater number of chronic illnesses at baseline. However, this was related to the age difference in the samples, rather than any other difference between the groups. There were subtle differences in prevalence of specific co-morbidities, and the control group fared better throughout in terms of lifestyle factors (exercise, consumption of fruit and vegetables). Over the 18 month period, both groups showed improvements in blood pressure. There were reductions in BMI and Waist circumference between baseline and 18 months in ExtraCare residents while these remained unchanged in control group. There was a significant initial increase in number of prescribed medications for the ExtraCare group perhaps as well-being support resulted in new diagnoses, but this then remained stable. A reduction in polypharmacy was anticipated, given the use of medication review, but this did not clearly occur. There was no significant change in number of co-morbidities. Healthcare use: GP visits and ExtraCare drop-in clinics: After 12 months GP usage (planned) by ExtraCare residents in the sample had decreased by 46%. No such reduction was seen in 8 emergency appointment data. We investigated the hypothesis that this may be because residents use the well-being drop-in clinic as a substitute for booking routine GP appointments, given that well-being drop-in appointments steadily increased over the period. At baseline, number of dropins and number of planned GP visits was significantly positively correlated – the more a person visited their GP, the more they visited the drop-in clinic too. At 12 months, this relationship had gone completely. Drop-ins increased and GP visits reduced over time. Despite this, the relationship does not become negative which would have been definitive evidence that drop-ins are directly replacing GP visits. That is, it is not the case that the more a person visited the drop-in centre, the less they visited their GP. The change is not necessarily reflecting individual level changes, just in the group as a whole. Planned and unplanned hospital admissions and length of stay: The average number of planned admissions to hospital reduced for ExtraCare participants by 12 months by 31% (no change for control participants). The large variance and small effect size means that this was NOT a statistically reliable change. Number of unplanned admissions did not change for either group. Together, these findings support the Drop-in clinic model: (i) Availability of local, accessible, relatively informal health support, particularly for ongoing dayto-day chronic illness care, that does not need an appointment (a drop-in service), can have a significant effect on reducing GP usage, giving potential cost savings. (ii) Communities where homes are accessible, care support is readily available and existing care needs understood may result in reduced length of stays in hospital. Duration of unplanned hospital stays: This reduced from a median of 5-7 days at baseline, to 1-2 days thereafter. This was not related to increase in number of Drop-ins. 7.0 Frailty Frailty is defined as a state of high vulnerability for adverse health outcomes when exposed to a stressor, that is, an absence of resilience. Frailty is related to morbidity and mortality, and utilisation of healthcare. Crucially, frailty, and especially pre-frail states, are malleable. The Frailty Profile: We constructed a frailty measure for this population at each assessment to compare longitudinally, using a frailty profile concept (Rockwood et al, 2006). People were categorised into frail, pre-frail and not frail based on published criteria. ExtraCare residents were frailer than controls throughout. Initial improvements in frailty did not continue over the full period, although the initial improvements may have delayed decline. Nevertheless, a focus on interventions to prevent or reduce frailty could be further developed and evaluated using such an indicator. Frail Participants: Of the 44 residents categorised as frail at baseline, 22 remained in the sample 18 months later, 14 (63.6%) remained categorised as frail with 8 returning to a pre-frail or not frail state. One control participant was categorised as frail at baseline, returning to a not frail state by 18 months. Pre-frail residents: Given that the “pre-frail” is used to indicate people at risk of becoming frail, it is important to know if this occurred for ExtraCare residents. Of the 62 people designated as prefrail at Baseline, 42 were still in the sample at 18 months and 8 (19%) had returned to a not frail state, with 4.7% being designated as frail at 12 months. Ten control participants were categorised as pre-frail at Baseline. Of the 8 remaining at 18 months, all were still in the same category. Putting it together: Frailty and Costs. As indicated in Section 5, NHS costs in total reduced significantly. The reduction for the frail residents was the most striking: for those in the sample at 9 baseline and follow-up, this changed from an average of £3274.21to £1588.04 average per person. That is, a 51.5% drop. Use of this figure needs to bear in mind that the frailest within this group are those who have died or dropped out of the study. Reductions in social care costs over time were much smaller (£2-300 per person on average). Care costs for frail participants are much higher than for pre-frail participants. A frail participant’s average annual care costs were £4720.96 at the 12 month point, as compared to £61.40 for a prefrail resident (given that most pre-frail residents are on zero care). This underlines the importance of strategies to intervene in pre-frailty to reduce the likelihood of it becoming frail. Physical versus cognitive frailty: In order to determine the source of impacts more precisely, we produced a separate cognitive and physical frailty profile. The data showed that cognitive and physical frailty predict care level jumps from one level to the next differently, with cognitive frailty having a more even influence. The main predictor of higher levels was cognitive frailty (although modelling was not possible with the small numbers on care). 8.0 Modelling: What predicts change? Which measures are useful for predicting decline in independence outcomes? IADL: Change in ACE-R (overall cognitive function) and change in frailty: e.g. for every one point increase in ACE-R, it became less likely that IADL would decline. This did not differ by group. Functional Limitations Profile: Baseline age and increase in Depression: e.g. for every one point increase in depressive symptoms, people were 1.36 times more likely to have increases in functional limitations. A focus on rehabilitation and improvement of cognitive function and on treatment or prevention of depression will have important direct effects on independent function and quality of life, and therefore on need for further care and support. Which measures are particularly useful for predicting Care level? Care Level: Frailty, IADL and ADL (a more basic independence measure), and ability to stand up from a chair (time taken or inability). Given that IADL can be impacted by change in its underlying predictors, rehabilitative focus on these predictors would then have an impact on care needed. However, good linguistic ability was also an important predictor of Care Level. Once frailty, IADL and ADL, and sit-to-stand was taken into account, language had an opposite effect – people with higher language ability were more likely to have higher care levels, suggesting that those who could communicate well and understand information may be more likely to get the care they need. Poorer linguistic abilities seem to result in people being less likely to get care, even in the context of frailty. This has important implications for an advocacy role for frail people in helping them get the care they need. This issue reduces from Baseline onwards, validating ExtraCare’s support, but it does still have an effect. Which measures are particularly useful for predicting well-being outcomes? The main predictor of improvement in depression, perceived health and autobiographical memory in the total sample is which group a person is in, the ExtraCare residents or the control group, whereby living in ExtraCare predicts improvements in these wellbeing measures. Depression/mood improvement: change in cognitive function; change in anxiety e.g.an increase in anxiety of one point reduced the chance of mood improving (people were ¾ as likely to 10 improve on mood if their anxiety increased). Number of chronic illnesses was marginally significant (p<0.01) again reducing the chance of improvement in mood as numbers of illnesses increased and should also be borne in mind. Given that we generally an overall improvement in mood for ExtraCare

What do older people do when sitting and why? Implications for decreasing sedentary behaviour

Background and Objectives: Sitting less can reduce older adults’ risk of ill health and disability. Effective sedentary behavior interventions require greater understanding of what older adults do when sitting (and not sitting), and why. This study compares the types, context, and role of sitting activities in the daily lives of older men and women who sit more or less than average. Research Design and Methods: Semistructured interviews with 44 older men and women of different ages, socioeconomic status, and objectively measured sedentary behavior were analyzed using social practice theory to explore the multifactorial, inter-relational influences on their sedentary behavior. Thematic frameworks facilitated between-group comparisons. Results: Older adults described many different leisure time, household, transport, and occupational sitting and non-sitting activities. Leisure-time sitting in the home (e.g., watching TV) was most common, but many non-sitting activities, including “pottering” doing household chores, also took place at home. Other people and access to leisure facilities were associated with lower sedentary behavior. The distinction between being busy/not busy was more important to most participants than sitting/not sitting, and informed their judgments about high-value “purposeful” (social, cognitively active, restorative) sitting and low-value “passive” sitting. Declining physical function contributed to temporal sitting patterns that did not vary much from day-to-day. Discussion and Implications: Sitting is associated with cognitive, social, and/or restorative benefits, embedded within older adults’ daily routines, and therefore difficult to change. Useful strategies include supporting older adults to engage with other people and local facilities outside the home, and break up periods of passive sitting at home

Bats Use Magnetite to Detect the Earth's Magnetic Field

While the role of magnetic cues for compass orientation has been confirmed in numerous animals, the mechanism of detection is still debated. Two hypotheses have been proposed, one based on a light dependent mechanism, apparently used by birds and another based on a “compass organelle” containing the iron oxide particles magnetite (Fe3O4). Bats have recently been shown to use magnetic cues for compass orientation but the method by which they detect the Earth's magnetic field remains unknown. Here we use the classic “Kalmijn-Blakemore” pulse re-magnetization experiment, whereby the polarity of cellular magnetite is reversed. The results demonstrate that the big brown bat Eptesicus fuscus uses single domain magnetite to detect the Earths magnetic field and the response indicates a polarity based receptor. Polarity detection is a prerequisite for the use of magnetite as a compass and suggests that big brown bats use magnetite to detect the magnetic field as a compass. Our results indicate the possibility that sensory cells in bats contain freely rotating magnetite particles, which appears not to be the case in birds. It is crucial that the ultrastructure of the magnetite containing magnetoreceptors is described for our understanding of magnetoreception in animals

The genomes of two key bumblebee species with primitive eusocial organization

Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation

Scleroderma and related disorders: 223. Long Term Outcome in a Contemporary Systemic Sclerosis Cohort

Background: We have previously compared outcome in two groups of systemic sclerosis (SSc) patients with disease onset a decade apart and we reported data on 5 year survival and cumulative incidence of organ disease in a contemporary SSc cohort. The present study examines longer term outcome in an additional cohort of SSc followed for 10 years. Methods: We have examined patients with disease onset between years 1995 and 1999 allowing for at least 10 years of follow-up in a group that has characteristics representative for the patients we see in contemporary clinical practice. Results: Of the 398 patients included in the study, 252 (63.3%) had limited cutaneous (lc) SSc and 146 (36.7%) had diffuse cutaneous (dc) SSc. The proportion of male patients was higher among the dcSSc group (17.1% v 9.9%, p = 0.037) while the mean age of onset was significantly higher among lcSSc patients (50 ± 13 v 46 ± 13 years ± SD, p = 0.003). During a 10 year follow-up from disease onset, 45% of the dcSSc and 21% of the lcSSc subjects developed clinically significant pulmonary fibrosis, p < 0.001. Among them approximately half reached the endpoint within the first 3 years (23% of dcSSc and 10% of lcSSc) and over three quarters within the first 5 years (34% and 16% respectively). There was a similar incidence of pulmonary hypertension (PH) in the two subsets with a steady rate of increase over time. At 10 years 13% of dcSSc and 15% of lcSSc subjects had developed PH (p=0.558), with the earliest cases observed within the first 2 years of disease. Comparison between subjects who developed PH in the first and second 5 years from disease onset demonstrated no difference in demographic or clinical characteristics, but 5-year survival from PH onset was better among those who developed this complication later in their disease (49% v 24%), with a strong trend towards statistical significance (p = 0.058). Incidence of SSc renal crisis (SRC) was significantly higher among the dcSSc patients (12% v 4% in lcSSc, p = 0.002). As previously observed, the rate of development of SRC was highest in the first 3 years of disease- 10% in dcSSc and 3% in lcSSc. All incidences of clinically important cardiac disease developed in the first 5 years from disease onset (7% in dcSSc v 1% in lcSSc, p < 0.001) and remained unchanged at 10 years. As expected, 10-year survival among lcSSc subjects was significantly higher (81%) compared to that of dcSSc patients (70%, p = 0.006). Interestingly, although over the first 5 years the death rate was much higher in the dcSSc cohort (16% v 6% in lcSSc), over the following years it became very similar for both subsets (14% and 13% between years 5 and 10, and 18% and 17% between years 10 and 15 for dcSSc and lcSSc respectively). Conclusions: Even though dcSSc patients have higher incidence for most organ complications compared to lcSSc subjects, the worse survival among them is mainly due to higher early mortality rate. Mortality rate after first 5 years of disease becomes comparable in the two disease subsets. Disclosure statement: The authors have declared no conflicts of interes