2,022 research outputs found

    Utilising proteomic approaches to understand oncogenic human herpesviruses

    Get PDF
    The γ‑herpesviruses Epstein-Barr virus and Kaposi's sarcoma‑associated herpesvirus are successful pathogens, each infecting a large proportion of the human population. These viruses persist for the life of the host and may each contribute to a number of malignancies, for which there are currently no cures. Large‑scale proteomic-based approaches provide an excellent means of increasing the collective understanding of the proteomes of these complex viruses and elucidating their numerous interactions within the infected host cell. These large‑scale studies are important for the identification of the intricacies of viral infection and the development of novel therapeutics against these two important pathogens

    Boundaries of Semantic Distraction: Dominance and Lexicality Act at Retrieval

    Get PDF
    Three experiments investigated memory for semantic information with the goal of determining boundary conditions for the manifestation of semantic auditory distraction. Irrelevant speech disrupted the free recall of semantic category-exemplars to an equal degree regardless of whether the speech coincided with presentation or test phases of the task (Experiment 1) and occurred regardless of whether it comprised random words or coherent sentences (Experiment 2). The effects of background speech were greater when the irrelevant speech was semantically related to the to-be-remembered material, but only when the irrelevant words were high in output dominance (Experiment 3). The implications of these findings in relation to the processing of task material and the processing of background speech is discussed

    How Are the Interests of Incapacitated Research Participants Protected through Legislation? An Italian Study on Legal Agency for Dementia Patients

    Get PDF
    Patients with dementia may have limited capacity to give informed consent to participate in clinical research. One possible way to safeguard the patients' interests in research is the involvement of a proxy in the recruitment process. In Italy, the system of proxy is determined by the courts. In this study we evaluate the timing for appointment of a legal proxy in Italy and identify predictive variables of appointment.Subjects were recruited among the outpatients seeking medical advice for cognitive complaints at the Centre for Research and Treatment of Cognitive Dysfunctions, University of Milan, "Luigi Sacco" Hospital. The Centre was participating to the AdCare Study, a no-profit randomised clinical trial coordinated by the Italian National Institute of Health. The requirement that informed consent be given by a legal representative dramatically slowed down the recruitment process in AdCare, which was prematurely interrupted. The Centre for Research and Treatment of Cognitive Dysfunctions collected data on the timing required to appoint the legal representatives. Patients diagnosed with dementia and their caregivers were provided information on the Italian law on legal agency (law 6/2004). At each scheduled check-up the caregiver was asked whether she/he had applied to appoint a legal proxy for the patient and the time interval between the presentation of the law, the registration of the application at the law court chancellery and the sentence of appointment was registered. The study involved 169 demented patients. Seventy-eight patients (46.2%) applied to appoint a legal proxy. These subjects were usually younger, had been suffering from dementia for a longer time, had less than two children and made more use of memantine. The mean interval time between the presentation of the law and the patients' application to the law court chancellery was two months. The mean interval time between the patient's application to the law court chancellery and the sentence of appointment was four months.In Italy the requirement that legal representatives be appointed by the courts slows down subjects' participation in research. Other procedures for legal agency of the incapacitated patients may be adopted, taking as examples other EU countries' systems

    Measurement of health-related quality by multimorbidity groups in primary health care

    Full text link
    [EN] Background: Increased life expectancy in Western societies does not necessarily mean better quality of life. To improve resources management, management systems have been set up in health systems to stratify patients according to morbidity, such as Clinical Risk Groups (CRG). The main objective of this study was to evaluate the effect of multimorbidity on health-related quality of life (HRQL) in primary care. Methods: An observational cross-sectional study, based on a representative random sample (n = 306) of adults from a health district (N = 32,667) in east Spain (Valencian Community), was conducted in 2013. Multimorbidity was measured by stratifying the population with the CRG system into nine mean health statuses (MHS). HRQL was assessed by EQ-5D dimensions and the EQ Visual Analogue Scale (EQ VAS). The effect of the CRG system, age and gender on the utility value and VAS was analysed by multiple linear regression. A predictive analysis was run by binary logistic regression with all the sample groups classified according to the CRG system into the five HRQL dimensions by taking the ¿healthy¿ group as a reference. Multivariate logistic regression studied the joint influence of the nine CRG system MHS, age and gender on the five EQ-5D dimensions. Results: Of the 306 subjects, 165 were female (mean age of 53). The most affected dimension was pain/discomfort (53%), followed by anxiety/depression (42%). The EQ-5D utility value and EQ VAS progressively lowered for the MHS with higher morbidity, except for MHS 6, more affected in the five dimensions, save self-care, which exceeded MHS 7 patients who were older, and MHS 8 and 9 patients, whose condition was more serious. The CRG system alone was the variable that best explained health problems in HRQL with 17%, which rose to 21% when associated with female gender. Age explained only 4%. Conclusions: This work demonstrates that the multimorbidity groups obtained by the CRG classification system can be used as an overall indicator of HRQL. These utility values can be employed for health policy decisions based on cost-effectiveness to estimate incremental quality-adjusted life years (QALY) with routinely e-health data. Patients under 65 years with multimorbidity perceived worse HRQL than older patients or disease severity. Knowledge of multimorbidity with a stronger impact can help primary healthcare doctors to pay attention to these population groups.The authors would like to thank the Conselleria de Sanitat Universal i Sanitat Pública of the Generalitat Valenciana (the Regional Valencian Health Government) for providing the study data. We would also like to thank Helen Warbuton for editing the English.Milá-Perseguer, M.; Guadalajara Olmeda, MN.; Vivas-Consuelo, D.; Usó-Talamantes, R. (2019). Measurement of health-related quality by multimorbidity groups in primary health care. Health and Quality of Life Outcomes. 17(8):1-10. https://doi.org/10.1186/s12955-018-1063-zS110178Ministerio de Sanidad SS, Igualdad e. Indicadores de Salud 2013. Evolución de los indicadores del estado de salud en España y su magnitud en el contexto de la Unión Europea. Madrid: Ministerio de Sanidad, Servicios Sociales e Igualdad; 2014.OECD/EU: Health at a Glance: Europe 2016 – State of Health in the EU Cycle, OECD Publishing, Paris. In.; 2016.WHO: Disability and health. In. Edited by WHO; 2017.Nicholson K, Makovski TT, Griffith LE, Raina P, Stranges S, van den Akker M. Multimorbidity and comorbidity revisited: refining the concepts for international health research. J Clin Epidemiol. 2018.Palmer K, Marengoni A, Forjaz MJ, Jureviciene E, Laatikainen T, Mammarella F, Muth C, Navickas R, Prados-Torres A, Rijken M, et al. Multimorbidity care model: recommendations from the consensus meeting of the joint action on chronic diseases and promoting healthy ageing across the life cycle (JA-CHRODIS). Health Policy. 2018;122(1):4–11.WHO: Innovative Care for Chronic Conditions. Building blocks for action. In.: WHO; 2014.Fortin M, Bravo G, Hudon C, Vanasse A, Lapointe L. Prevalence of multimorbidity among adults seen in family practice. Ann Fam Med. 2005;3(3):223–8.Inoriza JM, Coderch J, Carreras M, Vall-Llosera L, Garcia-Goni M, Lisbona JM, Ibern P. Measurement of morbidity attended in an integrated health care organization. Gac Sanit. 2009;23(1):29–37.Hunger M, Thorand B, Schunk M, Döring A, Menn P, Peters A, Holle R. Multimorbidity and health-related quality of life in the older population: results from the German KORA-age study. Health Qual Life Outcomes. 2011;9:53.de Miguel P, Caballero I, Rivas FJ, Manera J, de Vicente MA, Gómez Á. Morbidity observed in a health area: impact on professionals and funding. Aten Primaria. 2015;47(5):301–7.Agborsangaya CB, Lau D, Lahtinen M, Cooke T, Johnson JA. Multimorbidity prevalence and patterns across socioeconomic determinants: a cross-sectional survey. BMC Public Health. 2012;12:201.Orueta JF, García-Álvarez A, García-Goñi M, Paolucci F, Nuño-Solinís R. Prevalence and costs of multimorbidity by deprivation levels in the Basque Country: a population based study using health administrative databases. PLoS One. 2014;9(2):e89787.Mujica-Mota RE, Roberts M, Abel G, Elliott M, Lyratzopoulos G, Roland M, Campbell J. Common patterns of morbidity and multi-morbidity and their impact on health-related quality of life: evidence from a national survey. Qual Life Res. 2015;24(4):909–18.Caballer Tarazona V, Guadalajara Olmeda N, Vivas Consuelo D, Clemente Collado A. Impact of morbidity on health care costs of a Department of Health through clinical risk groups. Valencian Community, Spain. Rev Esp Salud Publica. 2016;90:e1–e15.Calderon-Larranaga A, Abrams C, Poblador-Plou B, Weiner JP, Prados-Torres A. Applying diagnosis and pharmacy-based risk models to predict pharmacy use in Aragon, Spain: the impact of a local calibration. BMC Health Serv Res. 2010;10:22.Hughes JS, Averill RF, Eisenhandler J, Goldfield NI, Muldoon J, Neff JM, Gay JC. Clinical risk groups (CRGs): a classification system for risk-adjusted capitation-based payment and health care management. Med Care. 2004;42(1):81–90.Vivas-Consuelo D, Uso-Talamantes R, Trillo-Mata JL, Caballer-Tarazona M, Barrachina-Martinez I, Buigues-Pastor L. Predictability of pharmaceutical spending in primary health services using clinical risk groups. Health Policy. 2014;116(2–3):188–95.Milla Perseguer M, Guadalajara Olmeda N, Vivas Consuelo D. Impact of cardiovascular risk factors on the consumption of resources in primary care according to clinical risk groups. Aten Primaria. 2018.WHOQOL. The World Health Organization quality of life assessment (WHOQOL): development and general psychometric properties. Soc Sci Med. 1998;46(12):1569–85.Badia X, Carne X. The evaluation of quality of life in clinical trials. Medicina Clinica. 1998;110(14):550–6.Revicki DA. Health-related quality of life in the evaluation of medical therapy for chronic illness. J Fam Pract. 1989;29(4):377–80.Agborsangaya CB, Lau D, Lahtinen M, Cooke T, Johnson JA. Health-related quality of life and healthcare utilization in multimorbidity: results of a cross-sectional survey. Qual Life Res. 2013;22(4):791–9.Romero M, Vivas-Consuelo D, Alvis-Guzman N. Is health related quality of life (HRQoL) a valid indicator for health systems evaluation? Springerplus. 2013;2:664.Hanmer J, Feeny D, Fischhoff B, Hays RD, Hess R, Pilkonis PA, Revicki DA, Roberts MS, Tsevat J, Yu L. The PROMIS of QALYs. Health Qual Life Outcomes. 2015;13.Herdman M, Badia X, Berra S. EuroQol-5D: a simple alternative for measuring health-related quality of life in primary care. Atencion primaria / Sociedad Espanola de Medicina de Familia y Comunitaria. 2001;28(6):425–30.EuroQol G. EuroQol-a new facility for the measurement of health-related quality of life. Health Policy. 1990;16(199–208).Agborsangaya CB, Lahtinen M, Cooke T, Johnson JA. Comparing the EQ-5D 3L and 5L: measurement properties and association with chronic conditions and multimorbidity in the general population. Health Qual Life Outcomes. 2014;12:7.Real Decreto Legislativo 8/2015, de 30 de octubre, por el que se aprueba el texto refundido de la Ley General de la Seguridad Social. In. «BOE» núm. 261, de 31/10/2015.: Ministerio de Empleo y Seguridad Social.; 2015.Ministry of Health and Social Policy:. Estudios sobre la calidad de vida de pacientes afectados por determinadas patologías. [ http://www.mscbs.gob.es/organizacion/sns/planCalidadSNS/ ].Ministry of Health and Social Policy: Encuesta Nacional de Salud. España 2011/12. Calidad de vida relacionada con la salud en adultos: EQ-5D-5L. Serie Informes monográficos n° 3. Madrid: Ministerio de Sanidad, Servicios Sociales e Igualdad; 2014.Fortin M, Bravo G, Hudon C, Lapointe L, Almirall J, Dubois MF, Vanasse A. Relationship between multimorbidity and health-related quality of life of patients in primary care. Qual Life Res. 2006;15(1):83–91.Fortin M, Dubois MF, Hudon C, Soubhi H, Almirall J. Multimorbidity and quality of life: a closer look. Health Qual Life Outcomes. 2007;5:52.Brazier JE, Yang Y, Tsuchiya A, Rowen DL. A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. Eur J Health Econ. 2010;11.Peak J, Goranitis I, Day E, Copello A, Freemantle N, Frew E. Predicting health-related quality of life (EQ-5D-5 L) and capability wellbeing (ICECAP-A) in the context of opiate dependence using routine clinical outcome measures: CORE-OM, LDQ and TOP. Health Qual Life Outcomes. 2018;16(1):106.Rivero-Arias O, Ouellet M, Gray A, Wolstenholme J, Rothwell PM, Luengo-Fernandez R. Mapping the modified Rankin scale (mRS) measurement into the generic EuroQol (EQ-5D) health outcome. Med Decis Mak. 2010;30.Argimon Pallás JM, Jiménez Villa J: Métodos de investigación clínica y epidemiológica, vol. Capítulo 15. Tamaño de la muestra; 2013.Yepes-Núñez JJ, García García HI: Preferencias de estados de salud y medidas de utilidad. In., vol. 24. Iatreia; 2011: 365–377.Attema AE, Edelaar-Peeters Y, Versteegh MM, Stolk EA. Time trade-off: one methodology, different methods. Eur J Health Econ. 2013;14(Suppl 1):S53–64.Badia X, Roset M, Herdman M, Kind P. A comparison of United Kingdom and Spanish general population time trade-off values for EQ-5D health states. Med Decis Mak. 2001;21(1):7–16.Garin N, Olaya B, Moneta MV, Miret M, Lobo A, Ayuso-Mateos JL, Haro JM. Impact of multimorbidity on disability and quality of life in the Spanish older population. PLoS One. 2014;9(11):e111498.Mielck A, Vogelmann M, Leidl R. Health-related quality of life and socioeconomic status: inequalities among adults with a chronic disease. Health Qual Life Outcomes. 2014;12:58.Usó Talamantes R: Análisis y desarrollo de un modelo predictivo del gasto farmacéutico ambulatorio ajustado a morbilidad y riesgo clínico [tesis doctoral]. Universidad Politécnica de Valencia; 2015. https://www.educacion.gob.es/teseo/mostrarRef.do?ref=1183638 .Sánchez Mollá M, Candela García I, Gómez-Romero FJ, Orozco Beltrán D, Ollero Baturone M. Concordance between stratification systems and identification of patients with multiple chronic diseases in primary care. Rev Calid Asist. 2017;32(1):10–6.Vivas-Consuelo D, Uso-Talamantes R, Guadalajara-Olmeda N, Trillo-Mata J-L, Sancho-Mestre C, Buigues-Pastor L. Pharmaceutical cost management in an ambulatory setting using a risk adjustment tool. BMC Health Serv Res. 2014;14:462.Coderch J, Sánchez-Pérez I, Ibern P, Carreras M, Pérez-Berruezo X, Inoriza JM. Predicting individual risk of high healthcare cost to identify complex chronic patients. Gac Sanit. 2014;28(4):292–300.Osca Guadalajara M, Guadalajara Olmeda N, Escartín Martínez R. Impact of Teriparatide on quality of life in osteoporotic patients. Rev Esp Salud Publica. 2015;89(2):215–25.Prazeres F, Santiago L. Relationship between health-related quality of life, perceived family support and unmet health needs in adult patients with multimorbidity attending primary care in Portugal: a multicentre cross-sectional study. Health Qual Life Outcomes. 2016;14(1):156.Brettschneider C, Leicht H, Bickel H, Dahlhaus A, Fuchs A, Gensichen J, Maier W, Group MS. Relative impact of multimorbid chronic conditions on health-related quality of life--results from the MultiCare cohort study. PLoS One. 2013;8(6):e66742

    Best Practices in Researching Service-Learning at Community Colleges

    Get PDF
    In recent years, an increasing number of community colleges have integrated some form of service-learning into their programs or courses with the idea that it will promote civic engagement, increase student satisfaction with their courses and college experience as a whole, and improve learning outcomes. There is a good amount of research published on service-learning programs and outcomes conducted at four-year institutions, though there is a dearth of studies available on service-learning at community colleges. Because community colleges serve a purpose unique from that of four-year colleges and universities, both in their mission and often in the students they serve, research on service-learning at community colleges should also be distinct from investigations at the four-year level

    Comparative Population Genetics of the Immunity Gene, Relish: Is Adaptive Evolution Idiosyncratic?

    Get PDF
    The frequency of adaptive evolution acting on common loci in distant lineages remains an outstanding question in evolutionary biology. We asked whether the immunity factor, Relish, a gene with a history of directional selection in Drosophila simulans, shows evidence of a similar selective history in other Drosophila species. We found only weak evidence of recurrent adaptive protein evolution at the Relish locus in three sister species pairs, suggesting that this key component of the insect immune system has an idiosyncratic evolutionary history in Drosophila

    Connectivity and resilience of coral reef metapopulations in marine protected areas : matching empirical efforts to predictive needs

    Get PDF
    © 2009 The Authors. This is an open-access article distributed under the terms of the Creative Commons Attribution Noncommercial License. The definitive version was published in Coral Reefs 28 (2009): 327-337, doi:10.1007/s00338-009-0466-z.Design and decision-making for marine protected areas (MPAs) on coral reefs require prediction of MPA effects with population models. Modeling of MPAs has shown how the persistence of metapopulations in systems of MPAs depends on the size and spacing of MPAs, and levels of fishing outside the MPAs. However, the pattern of demographic connectivity produced by larval dispersal is a key uncertainty in those modeling studies. The information required to assess population persistence is a dispersal matrix containing the fraction of larvae traveling to each location from each location, not just the current number of larvae exchanged among locations. Recent metapopulation modeling research with hypothetical dispersal matrices has shown how the spatial scale of dispersal, degree of advection versus diffusion, total larval output, and temporal and spatial variability in dispersal influence population persistence. Recent empirical studies using population genetics, parentage analysis, and geochemical and artificial marks in calcified structures have improved the understanding of dispersal. However, many such studies report current self-recruitment (locally produced settlement/settlement from elsewhere), which is not as directly useful as local retention (locally produced settlement/total locally released), which is a component of the dispersal matrix. Modeling of biophysical circulation with larval particle tracking can provide the required elements of dispersal matrices and assess their sensitivity to flows and larval behavior, but it requires more assumptions than direct empirical methods. To make rapid progress in understanding the scales and patterns of connectivity, greater communication between empiricists and population modelers will be needed. Empiricists need to focus more on identifying the characteristics of the dispersal matrix, while population modelers need to track and assimilate evolving empirical results.Work by CB Paris was supported by the National Science Foundation grant NSF-OCE 0550732. Work by M-A Coffroth and SR Thorrold was supported by the National Science Foundation grant NSF-OCE 0424688. Work by TL Shearer was supported by an International Cooperative Biodiversity Group grant R21 TW006662-01 from the Fogarty International Center at the National Institutes of Health

    Autoimmune inflammatory disorders, systemic corticosteroids and pneumocystis pneumonia: A strategy for prevention

    Get PDF
    BACKGROUND: Pneumocystis pneumonia (PCP) is an increasing problem amongst patients on immunosuppression with autoimmune inflammatory disorders (AID). The disease presents acutely and its diagnosis requires bronchoalveolar lavage in most cases. Despite treatment with intravenous antibiotics, PCP carries a worse prognosis in AID patients than HIV positive patients. The overall incidence of PCP in patients with AID remains low, although patients with Wegener's granulomatosis are at particular risk. DISCUSSION: In adults with AID, the risk of PCP is related to treatment with systemic steroid, ill-defined individual variation in steroid sensitivity and CD4+ lymphocyte count. Rather than opting for PCP prophylaxis on the basis of disease or treatment with cyclophosphamide, we argue the case for carrying out CD4+ lymphocyte counts on selected patients as a means of identifying individuals who are most likely to benefit from PCP prophylaxis. SUMMARY: Corticosteroids, lymphopenia and a low CD4+ count in particular, have been identified as risk factors for the development of PCP in adults with AID. Trimethoprim-sulfamethoxazole (co-trimoxazole) is an effective prophylactic agent, but indications for its use remain ill-defined. Further prospective trials are required to validate our proposed prevention strategy
    corecore