Uniting statistical and individual-based approaches for animal movement modelling

<div><p>The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.</p></div

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

[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

Exploring the effects of telehealth on medical human resources supply: a qualitative case study in remote regions

BACKGROUND: The availability of medical human resource supply is a growing concern for rural and remote communities in many countries. In the last decade, various telehealth experiences in Canada have highlighted the potential impact of this technology on professional practice. The purpose of this study was to explore physicians' and managers' perceptions regarding the potential of telehealth to support recruitment and retention of physicians in remote and rural regions. METHODS: A case study in Eastern Quebec was performed to explore this complex phenomenon. The analytical framework was based on two literature reviews and a Delphi study. Data were collected from semi-structured interviews with 41 physicians and 22 managers. Transcripts were produced and interview content was coded independently by two judges and validated by an expert panel. RESULTS: Interviews have highlighted the potential impact of telehealth on several factors influencing the recruitment and retention of physicians in rural and remote regions. The potential effects of telehealth on physicians' choice of practice location could be seen at the professional, organizational, educational and individual levels. For instance, telehealth could improve work satisfaction by allowing a regional on-call duty system and a better follow-up of patients. However, there are also certain limits related to telehealth, such as the fear that it would eventually replace all continuing medical education activities and onsite specialists in remoteregions. CONCLUSION: Telehealth is likely to have an impact on several factors related to medical workforce supply in remote and rural regions. However, the expected benefits will materialize if and only if this technology is properly integrated into organizations as a support to professional practice

“Excellence R Us”: university research and the fetishisation of excellence

The rhetoric of “excellence” is pervasive across the academy. It is used to refer to research outputs as well as researchers, theory and education, individuals and organisations, from art history to zoology. But does “excellence” actually mean anything? Does this pervasive narrative of “excellence” do any good? Drawing on a range of sources we interrogate “excellence” as a concept and find that it has no intrinsic meaning in academia. Rather it functions as a linguistic interchange mechanism. To investigate whether this linguistic function is useful we examine how the rhetoric of excellence combines with narratives of scarcity and competition to show that the hypercompetition that arises from the performance of “excellence” is completely at odds with the qualities of good research. We trace the roots of issues in reproducibility, fraud, and homophily to this rhetoric. But we also show that this rhetoric is an internal, and not primarily an external, imposition. We conclude by proposing an alternative rhetoric based on soundness and capacity-building. In the final analysis, it turns out that that “excellence” is not excellent. Used in its current unqualified form it is a pernicious and dangerous rhetoric that undermines the very foundations of good research and scholarship

Cluster analysis for the identification of clinical phenotypes among antiphospholipid antibody-positive patients from the APS ACTION Registry

Objective: This study aimed to use cluster analysis (CA) to identify different clinical phenotypes among antiphospholipid antibodies (aPL)-positive patients. Methods: The Alliance for Clinical Trials and International Networking (APS ACTION) Registry includes persistently positive aPL of any isotype based on the Sydney antiphospholipid syndrome (APS) classification criteria. We performed CA on the baseline characteristics collected retrospectively at the time of the registry entry of the first 500 patients included in the registry. A total of 30 clinical data points were included in the primary CA to cover the broad spectrum of aPL-positive patients. Results: A total of 497 patients from international centres were analysed, resulting in three main exclusive clusters: (a) female patients with no other autoimmune diseases but with venous thromboembolism (VTE) and triple-aPL positivity; (b) female patients with systemic lupus erythematosus, VTE, aPL nephropathy, thrombocytopaenia, haemolytic anaemia and a positive lupus anticoagulant test; and (c) older men with arterial thrombosis, heart valve disease, livedo, skin ulcers, neurological manifestations and cardiovascular disease (CVD) risk factors. Conclusions: Based on our hierarchical cluster analysis, we identified different clinical phenotypes of aPL-positive patients discriminated by aPL profile, lupus or CVD risk factors. Our results, while supporting the heterogeneity of aPL-positive patients, also provide a foundation to understand disease mechanisms, create new approaches for APS classification and ultimately develop new management approaches

Characteristics of Antiphospholipid Antibody Positive Patients in AntiPhospholipid Syndrome Alliance for Clinical Trials and InternatiOnal Networking

OBJECTIVE: To describe baseline characteristics of antiphospholipid antibody (aPL)-positive patients, overall and by clinical and laboratory subtypes, enrolled in an international registry. METHODS: AntiPhospholipid Syndrome Alliance for Clinical Trials and InternatiOnal Networking Registry includes persistently aPL-positive adults. We evaluated baseline sociodemographic and aPL-related (APS classification criteria and "non-criteria") characteristics of patients overall and in subgroups (aPL-positive without APS, APS overall, thrombotic APS [TAPS] only, obstetric APS [OAPS] only, and both TAPS/OAPS). We assessed baseline characteristics of patients tested for three aPL (lupus anticoagulant test [LA], anticardiolipin antibody [aCL], and anti-β2 -Glycoprotein-I [aβ2 GPI]) by aPL profiles (LA only, single, double, and triple aPL positivity). RESULTS: Of 804 aPL-positive patients (mean age: 45 ± 13y; female: 74%; white 68%; other systemic autoimmune diseases: 36%), 80% were classified as APS (55% TAPS, 9% OAPS, and 15% TAPS/OAPS). In the overall cohort, 71% had vascular thrombosis, 50% with pregnancy history had obstetric morbidity, and 56% had at least one non-criteria manifestation. Among those with three aPL tested (n: 660), 42% were triple aPL positive. While single, double and triple aPL positive subgroups had similar frequencies of vascular, obstetric, and non-criteria events, these events were lowest in the single aPL subgroup consisting of aCL or aβ2 GPI only. CONCLUSION: Our study demonstrates the heterogeneity of aPL-related clinical manifestations and laboratory profiles in a multicenter, international cohort. Within single aPL-positivity, LA may be a major contributor to clinical events. Future prospective analyses, using standardized core laboratory aPL tests, will help clarify aPL risk profiles and improve risk stratification

Co-morbidity and visual acuity are risk factors for health-related quality of life decline: five-month follow-up EQ-5D data of visually impaired older patients

<p>Abstract</p> <p>Background</p> <p>Co-morbidity is a common phenomenon in the elderly and is considered to be a major threat to quality of life (QOL). Knowledge of co-existing conditions or patient characteristics that lead to an increased QOL decline is important for individual care, and for public health purposes. In visually impaired older adults, it remains unclear which co-existing conditions or other characteristics influence their health-related QOL. Our aim was to present a risk profile of characteristics and conditions which predict deterioration of QOL in visually impaired older patients.</p> <p>Methods</p> <p>Analyses were performed on data from an observational study among 296 visually impaired older patients from four Dutch hospitals. QOL was measured with the EuroQol-5D (EQ-5D) at baseline and at five-month follow-up. Nine co-existing condition categories (musculoskeletal; diabetes; heart; hypertension; chronic obstructive pulmonary disease (COPD) or asthma; hearing impairment; stroke; cancer; gastrointestinal conditions) and six patient characteristics (age; gender; visual acuity; social status; independent living; rehabilitation type) were tested in a linear regression model to determine the risk profile. The model was corrected for baseline EQ-5D scores. In addition, baseline EQ-5D scores were compared with reference scores from a younger visually impaired population and from elderly in the general population.</p> <p>Results</p> <p>From the 296 patients, 50 (16.9%) were lost to follow-up. Patients who reported diabetes, COPD or asthma, consequences of stroke, musculoskeletal conditions, cancer, gastrointestinal conditions or higher logMAR Visual Acuity values, experienced a lower QOL. After five months, visual acuity, musculoskeletal conditions, COPD/asthma and stroke predicted a decline in QOL (R²= 0.20). At baseline, the visually impaired older patients more often reported moderate or severe problems on most EQ-5D dimensions than the two reference groups.</p> <p>Conclusion</p> <p>In visually impaired older patients, visual acuity, musculoskeletal conditions, COPD/asthma and stroke predicted a relatively rapid decline in health-related QOL. With this risk profile, a specific referral by the ophthalmologist to another sub-specialty may have a beneficial effect on the patient's health-related QOL. A referral by the ophthalmologist or optometrist to a multidisciplinary rehabilitation service seems appropriate for some patients with co-morbidity. The current results need to be confirmed in studies using pre-structured questionnaires to assess co-morbidity.</p

The Terebridae and teretoxins: Combining phylogeny and anatomy for concerted discovery of bioactive compounds

The Conoidea superfamily, comprised of cone snails, terebrids, and turrids, is an exceptionally promising group for the discovery of natural peptide toxins. The potential of conoidean toxins has been realized with the distribution of the first Conus (cone snail) drug, Prialt (ziconotide), an analgesic used to alleviate chronic pain in HIV and cancer patients. Cone snail toxins (conotoxins) are highly variable, a consequence of a high mutation rate associated to duplication events and positive selection. As Conus and terebrids diverged in the early Paleocene, the toxins from terebrids (teretoxins) may demonstrate highly divergent and unique functionalities. Recent analyses of the Terebridae, a largely distributed family with more than 300 described species, indicate they have evolutionary and pharmacological potential. Based on a three gene (COI, 12S and 16S) molecular phylogeny, including ~50 species from the West-Pacific, five main terebrid lineages were discriminated: two of these lineages independently lost their venom apparatus, and one venomous lineage was previously unknown. Knowing the phylogenetic relationships within the Terebridae aids in effectively targeting divergent lineages with novel peptide toxins. Preliminary results indicate that teretoxins are similar in structure and composition to conotoxins, suggesting teretoxins are an attractive line of research to discover and develop new therapeutics that target ion channels and receptors. Using conotoxins as a guideline, and innovative natural products discovery strategies, such as the Concerted Discovery Strategy, the potential of the Terebridae and their toxins are explored as a pioneering pharmacological resource

E2F1 Mediated Apoptosis Induced by the DNA Damage Response Is Blocked by EBV Nuclear Antigen 3C in Lymphoblastoid Cells

EBV latent antigen EBNA3C is indispensible for in vitro B-cell immortalization resulting in continuously proliferating lymphoblastoid cell lines (LCLs). EBNA3C was previously shown to target pRb for ubiquitin-proteasome mediated degradation, which facilitates G1 to S transition controlled by the major transcriptional activator E2F1. E2F1 also plays a pivotal role in regulating DNA damage induced apoptosis through both p53-dependent and -independent pathways. In this study, we demonstrate that in response to DNA damage LCLs knocked down for EBNA3C undergo a drastic induction of apoptosis, as a possible consequence of both p53- and E2F1-mediated activities. Importantly, EBNA3C was previously shown to suppress p53-induced apoptosis. Now, we also show that EBNA3C efficiently blocks E2F1-mediated apoptosis, as well as its anti-proliferative effects in a p53-independent manner, in response to DNA damage. The N- and C-terminal domains of EBNA3C form a stable pRb independent complex with the N-terminal DNA-binding region of E2F1 responsible for inducing apoptosis. Mechanistically, we show that EBNA3C represses E2F1 transcriptional activity via blocking its DNA-binding activity at the responsive promoters of p73 and Apaf-1 apoptosis induced genes, and also facilitates E2F1 degradation in an ubiquitin-proteasome dependent fashion. Moreover, in response to DNA damage, E2F1 knockdown LCLs exhibited a significant reduction in apoptosis with higher cell-viability. In the presence of normal mitogenic stimuli the growth rate of LCLs knockdown for E2F1 was markedly impaired; indicating that E2F1 plays a dual role in EBV positive cells and that active engagement of the EBNA3C-E2F1 complex is crucial for inhibition of DNA damage induced E2F1-mediated apoptosis. This study offers novel insights into our current understanding of EBV biology and enhances the potential for development of effective therapies against EBV associated B-cell lymphomas

The effects of spatial legacies following shifting management practices and fire on boreal forest age structure

Forest age structure and its spatial arrangement are important elements of sustainable forestry because of their effects on biodiversity and timber availability. Forest management objectives that include specific forest age structure may not be easily attained due to constraints imposed by the legacies of historical management and natural disturbance. We used a spatially explicit stochastic model to explore the synergetic effects of forest management and fire on boreal forest age structure. Specifically, we examined (1) the duration of spatial legacies of different management practices in the boreal forest, (2) how multiple shifts in management practices affect legacy duration and the spatial trajectories of forest age structure, and (3) how fire influences legacy duration and pattern development in combination with harvesting. Results based on 30 replicates of 500 years for each scenario indicate that (1) spatial legacies persist over 200 years and the rate at which legacies are overcome depends on whether new management targets are in synchrony with existing spatial pattern; (2) age specific goals were met faster after multiple management shifts due to the similar spatial scale of the preceding management types; (3) because large fires can erase the spatial pattern created by smaller disturbances, scenarios with fire had shorter lags than scenarios without fire. These results suggest that forest management goals can be accelerated by applying management at a similar spatial scale as existing spatial patterns. Also, management planning should include careful consideration of historical management as well as current and likely future disturbances