Validating the Philadelphia Mindfulness Scale [PMS] for Those with Fibromyalgia

Objectives: Dispositional mindfulness [DM] has become an important construct in understanding and treating fibromyalgia. However, few DM measures exist that have been validated in those with fibromyalgia. The Philadelphia Mindfulness Scale [PMS] is a self-report of DM. In the current study, we validate the PMS within a sample of individuals with fibromyalgia. Design: This was a cross-sectional online study. This enabled the recruitment of a larger sample of individuals with experiences of fibromyalgia than may have been achieved through face-to-face assessment. A cross-sectional approach was adopted to minimise resource demands. Method: The PMS alongside measures of fibromyalgia severity [The Revised Fibromyalgia Impact Questionnaire], affect [Positive and Negative Affect Scale] and decentring [Experiences Questionnaire] were completed online by a sample of N=936 individuals with fibromyalgia. Results: Confirmatory factor analysis supported a revised three-factor structure for the PMS. This factor structure excluded items which could overlap with hypervigilance within fibromyalgia. The three supported factors were Awareness, Non-judging/Control and Non-suppression/reactivity. Concurrent validity of the subscales was partially supported via correlations with positive affect [PA] and negative affect [NA] and decentring. Conclusions: The results support the use of the PMS in individuals with fibromyalgia, and in particular the use of this measure to compare those with and without experience of meditation. The PMS may be a useful tool in evaluating mindfulness-based interventions [MBIs] within this population. Limitations: The online design prevented more in-depth assessment of fibromyalgia. As the study was cross-sectional, test re-test reliability could not be assessed

Infectious Disease Modeling of Social Contagion in Networks

Many behavioral phenomena have been found to spread interpersonally through social networks, in a manner similar to infectious diseases. An important difference between social contagion and traditional infectious diseases, however, is that behavioral phenomena can be acquired by non-social mechanisms as well as through social transmission. We introduce a novel theoretical framework for studying these phenomena (the SISa model) by adapting a classic disease model to include the possibility for ‘automatic’ (or ‘spontaneous’) non-social infection. We provide an example of the use of this framework by examining the spread of obesity in the Framingham Heart Study Network. The interaction assumptions of the model are validated using longitudinal network transmission data. We find that the current rate of becoming obese is 2 per year and increases by 0.5 percentage points for each obese social contact. The rate of recovering from obesity is 4 per year, and does not depend on the number of non-obese contacts. The model predicts a long-term obesity prevalence of approximately 42, and can be used to evaluate the effect of different interventions on steady-state obesity. Model predictions quantitatively reproduce the actual historical time course for the prevalence of obesity. We find that since the 1970s, the rate of recovery from obesity has remained relatively constant, while the rates of both spontaneous infection and transmission have steadily increased over time. This suggests that the obesity epidemic may be driven by increasing rates of becoming obese, both spontaneously and transmissively, rather than by decreasing rates of losing weight. A key feature of the SISa model is its ability to characterize the relative importance of social transmission by quantitatively comparing rates of spontaneous versus contagious infection. It provides a theoretical framework for studying the interpersonal spread of any state that may also arise spontaneously, such as emotions, behaviors, health states, ideas or diseases with reservoirs.National Institutes of Health (U.S.) (grant R01GM078986)National Science Foundation (U.S.)Bill & Melinda Gates FoundationTempleton FoundationNational Institute on Aging (grant P01 AG031093)Framingham Heart Study (contract number N01-HC-25195

Dynamics and Control of Diseases in Networks with Community Structure

The dynamics of infectious diseases spread via direct person-to-person transmission (such as influenza, smallpox, HIV/AIDS, etc.) depends on the underlying host contact network. Human contact networks exhibit strong community structure. Understanding how such community structure affects epidemics may provide insights for preventing the spread of disease between communities by changing the structure of the contact network through pharmaceutical or non-pharmaceutical interventions. We use empirical and simulated networks to investigate the spread of disease in networks with community structure. We find that community structure has a major impact on disease dynamics, and we show that in networks with strong community structure, immunization interventions targeted at individuals bridging communities are more effective than those simply targeting highly connected individuals. Because the structure of relevant contact networks is generally not known, and vaccine supply is often limited, there is great need for efficient vaccination algorithms that do not require full knowledge of the network. We developed an algorithm that acts only on locally available network information and is able to quickly identify targets for successful immunization intervention. The algorithm generally outperforms existing algorithms when vaccine supply is limited, particularly in networks with strong community structure. Understanding the spread of infectious diseases and designing optimal control strategies is a major goal of public health. Social networks show marked patterns of community structure, and our results, based on empirical and simulated data, demonstrate that community structure strongly affects disease dynamics. These results have implications for the design of control strategies

Models of epidemics: when contact repetition and clustering should be included

Background The spread of infectious disease is determined by biological factors, e.g. the duration of the infectious period, and social factors, e.g. the arrangement of potentially contagious contacts. Repetitiveness and clustering of contacts are known to be relevant factors influencing the transmission of droplet or contact transmitted diseases. However, we do not yet completely know under what conditions repetitiveness and clustering should be included for realistically modelling disease spread. Methods We compare two different types of individual-based models: One assumes random mixing without repetition of contacts, whereas the other assumes that the same contacts repeat day-by-day. The latter exists in two variants, with and without clustering. We systematically test and compare how the total size of an outbreak differs between these model types depending on the key parameters transmission probability, number of contacts per day, duration of the infectious period, different levels of clustering and varying proportions of repetitive contacts. Results The simulation runs under different parameter constellations provide the following results: The difference between both model types is highest for low numbers of contacts per day and low transmission probabilities. The number of contacts and the transmission probability have a higher influence on this difference than the duration of the infectious period. Even when only minor parts of the daily contacts are repetitive and clustered can there be relevant differences compared to a purely random mixing model. Conclusion We show that random mixing models provide acceptable estimates of the total outbreak size if the number of contacts per day is high or if the per-contact transmission probability is high, as seen in typical childhood diseases such as measles. In the case of very short infectious periods, for instance, as in Norovirus, models assuming repeating contacts will also behave similarly as random mixing models. If the number of daily contacts or the transmission probability is low, as assumed for MRSA or Ebola, particular consideration should be given to the actual structure of potentially contagious contacts when designing the model.ISSN:1742-468

SOX9 Governs Differentiation Stage-Specific Gene Expression in Growth Plate Chondrocytes via Direct Concomitant Transactivation and Repression

Cartilage and endochondral bone development require SOX9 activity to regulate chondrogenesis, chondrocyte proliferation, and transition to a non-mitotic hypertrophic state. The restricted and reciprocal expression of the collagen X gene, Col10a1, in hypertrophic chondrocytes and Sox9 in immature chondrocytes epitomise the precise spatiotemporal control of gene expression as chondrocytes progress through phases of differentiation, but how this is achieved is not clear. Here, we have identified a regulatory element upstream of Col10a1 that enhances its expression in hypertrophic chondrocytes in vivo. In immature chondrocytes, where Col10a1 is not expressed, SOX9 interacts with a conserved sequence within this element that is analogous to that within the intronic enhancer of the collagen II gene Col2a1, the known transactivation target of SOX9. By analysing a series of Col10a1 reporter genes in transgenic mice, we show that the SOX9 binding consensus in this element is required to repress expression of the transgene in non-hypertrophic chondrocytes. Forced ectopic Sox9 expression in hypertrophic chondrocytes in vitro and in mice resulted in down-regulation of Col10a1. Mutation of a binding consensus motif for GLI transcription factors, which are the effectors of Indian hedgehog signaling, close to the SOX9 site in the Col10a1 regulatory element, also derepressed transgene expression in non-hypertrophic chondrocytes. GLI2 and GLI3 bound to the Col10a1 regulatory element but not to the enhancer of Col2a1. In addition to Col10a1, paired SOX9–GLI binding motifs are present in the conserved non-coding regions of several genes that are preferentially expressed in hypertrophic chondrocytes and the occurrence of pairing is unlikely to be by chance. We propose a regulatory paradigm whereby direct concomitant positive and negative transcriptional control by SOX9 ensures differentiation phase-specific gene expression in chondrocytes. Discrimination between these opposing modes of transcriptional control by SOX9 may be mediated by cooperation with different partners such as GLI factors

A New Mechanistic Scenario for the Origin and Evolution of Vertebrate Cartilage

The appearance of cellular cartilage was a defining event in vertebrate evolution because it made possible the physical expansion of the vertebrate “new head”. Despite its central role in vertebrate evolution, the origin of cellular cartilage has been difficult to understand. This is largely due to a lack of informative evolutionary intermediates linking vertebrate cellular cartilage to the acellular cartilage of invertebrate chordates. The basal jawless vertebrate, lamprey, has long been considered key to understanding the evolution of vertebrate cartilage. However, histological analyses of the lamprey head skeleton suggest it is composed of modern cellular cartilage and a putatively unrelated connective tissue called mucocartilage, with no obvious transitional tissue. Here we take a molecular approach to better understand the evolutionary relationships between lamprey cellular cartilage, gnathostome cellular cartilage, and lamprey mucocartilage. We find that despite overt histological similarity, lamprey and gnathostome cellular cartilage utilize divergent gene regulatory networks (GRNs). While the gnathostome cellular cartilage GRN broadly incorporates Runx, Barx, and Alx transcription factors, lamprey cellular cartilage does not express Runx or Barx, and only deploys Alx genes in certain regions. Furthermore, we find that lamprey mucocartilage, despite its distinctive mesenchymal morphology, deploys every component of the gnathostome cartilage GRN, albeit in different domains. Based on these findings, and previous work, we propose a stepwise model for the evolution of vertebrate cellular cartilage in which the appearance of a generic neural crest-derived skeletal tissue was followed by a phase of skeletal tissue diversification in early agnathans. In the gnathostome lineage, a single type of rigid cellular cartilage became dominant, replacing other skeletal tissues and evolving via gene cooption to become the definitive cellular cartilage of modern jawed vertebrates

Containing the accidental laboratory escape of potential pandemic influenza viruses

BACKGROUND: The recent work on the modified H5N1 has stirred an intense debate on the risk associated with the accidental release from biosafety laboratory of potential pandemic pathogens. Here, we assess the risk that the accidental escape of a novel transmissible influenza strain would not be contained in the local community. METHODS: We develop here a detailed agent-based model that specifically considers laboratory workers and their contacts in microsimulations of the epidemic onset. We consider the following non-pharmaceutical interventions: isolation of the laboratory, laboratory workers’ household quarantine, contact tracing of cases and subsequent household quarantine of identified secondary cases, and school and workplace closure both preventive and reactive. RESULTS: Model simulations suggest that there is a non-negligible probability (5% to 15%), strongly dependent on reproduction number and probability of developing clinical symptoms, that the escape event is not detected at all. We find that the containment depends on the timely implementation of non-pharmaceutical interventions and contact tracing and it may be effective (>90% probability per event) only for pathogens with moderate transmissibility (reproductive number no larger than R(0) = 1.5). Containment depends on population density and structure as well, with a probability of giving rise to a global event that is three to five times lower in rural areas. CONCLUSIONS: Results suggest that controllability of escape events is not guaranteed and, given the rapid increase of biosafety laboratories worldwide, this poses a serious threat to human health. Our findings may be relevant to policy makers when designing adequate preparedness plans and may have important implications for determining the location of new biosafety laboratories worldwide