Climate Effects and Feedback Structure Determining Weed Population Dynamics in a Long-Term Experiment

Pest control is one of the areas in which population dynamic theory has been successfully applied to solve practical problems. However, the links between population dynamic theory and model construction have been less emphasized in the management and control of weed populations. Most management models of weed population dynamics have emphasized the role of the endogenous process, but the role of exogenous variables such as climate have been ignored in the study of weed populations and their management. Here, we use long-term data (22 years) on two annual weed species from a locality in Central Spain to determine the importance of endogenous and exogenous processes (local and large-scale climate factors). Our modeling study determined two different feedback structures and climate effects in the two weed species analyzed. While Descurainia sophia exhibited a second-order feedback and low climate influence, Veronica hederifolia was characterized by a first-order feedback structure and important effects from temperature and rainfall. Our results strongly suggest the importance of theoretical population dynamics in understanding plant population systems. Moreover, the use of this approach, discerning between the effect of exogenous and endogenous factors, can be fundamental to applying weed management practices in agricultural systems and to controlling invasive weedy species. This is a radical change from most approaches currently used to guide weed and invasive weedy species managements

Individualization as driving force of clustering phenomena in humans

One of the most intriguing dynamics in biological systems is the emergence of clustering, the self-organization into separated agglomerations of individuals. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is clustering of opinions in human populations. The puzzle is particularly pressing if opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing opinion formation models suggest that "monoculture" is unavoidable in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness did not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution of the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct simulation experiments to demonstrate that with this kind of noise, a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting.Comment: 12 pages, 4 figure

Trends in healthcare utilization among older Americans with colorectal cancer: A retrospective database analysis

<p>Abstract</p> <p>Background</p> <p>Analyses of utilization trends (cost drivers) allow us to understand changes in colorectal cancer (CRC) costs over time, better predict future costs, identify changes in the use of specific types of care (eg, hospice), and provide inputs for cost-effectiveness models. This retrospective cohort study evaluated healthcare resource use among US Medicare beneficiaries diagnosed with CRC between 1992 and 2002.</p> <p>Methods</p> <p>Cohorts included patients aged 66+ newly diagnosed with adenocarcinoma of the colon (n = 52,371) or rectum (n = 18,619) between 1992 and 2002 and matched patients from the general Medicare population, followed until death or December 31, 2005. Demographic and clinical characteristics were evaluated by cancer subsite. Resource use, including the percentage that used each type of resource, number of hospitalizations, and number of hospital and skilled nursing facility days, was evaluated by stage and subsite. The number of office, outpatient, and inpatient visits per person-year was calculated for each cohort, and was described by year of service, subsite, and treatment phase. Hospice use rates in the last year of life were calculated by year of service, stage, and subsite for CRC patients who died of CRC.</p> <p>Results</p> <p>CRC patients (mean age: 77.3 years; 44.9% male) used more resources than controls in every category (<it>P </it>< .001), with the largest differences seen in hospital days and home health use. Most resource use (except hospice) remained relatively steady over time. The initial phase was the most resource intense in terms of office and outpatient visits. Hospice use among patients who died of CRC increased from 20.0% in 1992 to 70.5% in 2004, and age-related differences appear to have evened out in later years.</p> <p>Conclusion</p> <p>Use of hospice care among CRC decedents increased substantially over the study period, while other resource use remained generally steady. Our findings may be useful for understanding CRC cost drivers, tracking trends, and forecasting resource needs for CRC patients in the future.</p

Development and validation of a population-based prediction scale for osteoporotic fracture in the region of Valencia, Spain: the ESOSVAL-R study

<p>Abstract</p> <p>Background</p> <p>Today, while there are effective drugs that reduce the risk of osteoporotic fracture, yet there are no broadly accepted criteria that can be used to estimate risks and decide who should receive treatment. One of the actual priorities of clinical research is to develop a set of simple and readily-available clinical data that can be used in routine clinical practice to identify patients at high risk of bone fracture, and to establish thresholds for therapeutic interventions. Such a tool would have high impact on healthcare policies. The main objective of the ESOSVAL-R is to develop a risk prediction scale of osteoporotic fracture in adult population using data from the Region of Valencia, Spain.</p> <p>Methods/Design</p> <p><it>Study design</it>: An observational, longitudinal, prospective cohort study, undertaken in the Region of Valencia, with an initial follow-up period of five years; <it>Subjects</it>: 14,500 men and women over the age of 50, residing in the Region and receiving healthcare from centers where the ABUCASIS electronic clinical records system is implanted; <it>Sources of data</it>: The ABUCASIS electronic clinical record system, complemented with hospital morbidity registers, hospital Accidents & Emergency records and the Regional Ministry of Health's mortality register; <it>Measurement of results</it>: Incident osteoporotic fracture (in the hip and/or major osteoporotic fracture) during the study's follow-up period. Independent variables include clinical data and complementary examinations; <it>Analysis</it>: 1) Descriptive analysis of the cohorts' baseline data; 2) Upon completion of the follow-up period, analysis of the strength of association between the risk factors and the incidence of osteoporotic fracture using Cox's proportional hazards model; 3) Development and validation of a model to predict risk of osteoporotic fracture; the validated model will serve to develop a simplified scale that can be used during routine clinical visits.</p> <p>Discussion</p> <p>The ESOSVAL-R study will establish a prediction scale for osteoporotic fracture in Spanish adult population. This scale not only will constitute a useful prognostic tool, but also it will allow identifying intervention thresholds to support treatment decision-making in the Valencia setting, based mainly on the information registered in the electronic clinical records.</p

Axelrod’s metanorm games on networks

Metanorms is a mechanism proposed to promote cooperation in social dilemmas. Recent experimental results show that network structures that underlie social interactions influence the emergence of norms that promote cooperation. We generalize Axelrod’s analysis of metanorms dynamics to interactions unfolding on networks through simulation and mathematical modeling. Network topology strongly influences the effectiveness of the metanorms mechanism in establishing cooperation. In particular, we find that average degree, clustering coefficient and the average number of triplets per node play key roles in sustaining or collapsing cooperationSpanish MICINN projects CSD2010-00034 (CONSOLIDER-INGENIO 2010) and DPI2010-16920, and by the Junta de Castilla y Leo´ n, references BU034A08 and GREX251-2009

Mesoscopic effects in an agent-based bargaining model in regular lattices

The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young [1] modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent’s most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders.Spanish Ministry of Science and Innovation, references TIN2008-06464-C03-02 and CSD2010-00034 (CONSOLIDER-INGENIO 2010), and by the Junta de Castilla y Leon, references VA006A009, BU034A08 and GREX251-200

Cognitive Dysfunction Is Sustained after Rescue Therapy in Experimental Cerebral Malaria, and Is Reduced by Additive Antioxidant Therapy

Neurological impairments are frequently detected in children surviving cerebral malaria (CM), the most severe neurological complication of infection with Plasmodium falciparum. The pathophysiology and therapy of long lasting cognitive deficits in malaria patients after treatment of the parasitic disease is a critical area of investigation. In the present study we used several models of experimental malaria with differential features to investigate persistent cognitive damage after rescue treatment. Infection of C57BL/6 and Swiss (SW) mice with Plasmodium berghei ANKA (PbA) or a lethal strain of Plasmodium yoelii XL (PyXL), respectively, resulted in documented CM and sustained persistent cognitive damage detected by a battery of behavioral tests after cure of the acute parasitic disease with chloroquine therapy. Strikingly, cognitive impairment was still present 30 days after the initial infection. In contrast, BALB/c mice infected with PbA, C57BL6 infected with Plasmodium chabaudi chabaudi and SW infected with non lethal Plasmodium yoelii NXL (PyNXL) did not develop signs of CM, were cured of the acute parasitic infection by chloroquine, and showed no persistent cognitive impairment. Reactive oxygen species have been reported to mediate neurological injury in CM. Increased production of malondialdehyde (MDA) and conjugated dienes was detected in the brains of PbA-infected C57BL/6 mice with CM, indicating high oxidative stress. Treatment of PbA-infected C57BL/6 mice with additive antioxidants together with chloroquine at the first signs of CM prevented the development of persistent cognitive damage. These studies provide new insights into the natural history of cognitive dysfunction after rescue therapy for CM that may have clinical relevance, and may also be relevant to cerebral sequelae of sepsis and other disorders