Measuring the complexity of social associations using mixture models

This is final version. Available on open access from Springer via the DOI in this record.We propose a method for examining and measuring the complexity of animal social networks that are characterized using association indices. The method focusses on the diversity of types of dyadic relationship within the social network. Binomial mixture models cluster dyadic relationships into relationship types, and variation in the preponderance and strength of these relationship types can be used to estimate association complexity using Shannon’s information index. We use simulated data to test the method, and find that models chosen using integrated complete likelihood give estimates of complexity that closely reflect the true complexity of social systems, but these estimates can be downwardly biased by low intensity sampling and upwardly biased by extreme overdispersion within components. We also illustrate the use of the method on two real data sets. The method could be extended for use on interaction rate data using Poisson mixture models, or on multidimensional relationship data using multivariate mixture models

A systematic analysis of experimental immunotherapies on tumors differing in size and duration of growth

We conducted a systematic analysis to determine the reason for the apparent disparity of success of immunotherapy between clinical and experimental cancers. To do this, we performed a search of PubMed using the keywords “immunotherapy” AND “cancer” for the years of 1980 and 2010. The midspread of experimental tumors used in all the relevant literature published in 2010 were between 0.5–121 mm3 in volume or had grown for four to eight days. Few studies reported large tumors that could be considered representative of clinical tumors, in terms of size and duration of growth. The predominant effect of cancer immunotherapies was slowed or delayed outgrowth. Regression of tumors larger than 200 mm3 was observed only after passive antibody or adoptive T cell therapy. The effectiveness of other types of immunotherapy was generally scattered. By comparison, very few publications retrieved by the 1980 search could meet our selection criteria; all of these used tumors smaller than 100 mm3, and none reported regression. In the entire year of 2010, only 13 used tumors larger than 400 mm3, and nine of these reported tumor regression. Together, these results indicate that most recent studies, using many diverse approaches, still treat small tumors only to report slowed or delayed growth. Nevertheless, a few recent studies indicate effective therapy against large tumors when using passive antibody or adoptive T cell therapy. For the future, we aspire to witness the increased use of experimental studies treating tumors that model clinical cancers in terms of size and duration of growth

Health literacy, health status, and healthcare utilization of Taiwanese adults: results from a national survey

Abstract Background Low health literacy is considered a worldwide health threat. The purpose of this study is to assess the prevalence and socio-demographic covariates of low health literacy in Taiwanese adults and to investigate the relationships between health literacy and health status and health care utilization. Methods A national survey of 1493 adults was conducted in 2008. Health literacy was measured using the Mandarin Health Literacy Scale. Health status was measured based on self-rated physical and mental health. Health care utilization was measured based on self-reported outpatient clinic visits, emergency room visits, and hospitalizations. Results Approximately thirty percent of adults were found to have low (inadequate or marginal) health literacy. They tended to be older, have fewer years of schooling, lower household income, and reside in less populated areas. Inadequate health literacy was associated with poorer mental health (OR, 0.57; 95% CI, 0.35-0.91). No association was found between health literacy and health care utilization even after adjusting for other covariates. Conclusions Low (inadequate and marginal) health literacy is prevalent in Taiwan. High prevalence of low health literacy is not necessarily indicative of the need for interventions. Systematic efforts to evaluate the impact of low health literacy on health outcomes in other countries would help to illuminate features of health care delivery and financing systems that may mitigate the adverse health effects of low health literacy.http://deepblue.lib.umich.edu/bitstream/2027.42/78252/1/1471-2458-10-614.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78252/2/1471-2458-10-614.pdfPeer Reviewe

Common permutation methods in animal social network analysis do not control for non-independence

This is the final version. Available on open access from Springer via the DOI in this recordData availability: The R code required to repeat the simulations has been deposited at: https://doi.org/10.5281/zenodo.4903396).The non-independence of social network data is a cause for concern among behavioural ecologists conducting social network analysis. This has led to the adoption of several permutation-based methods for testing common hypotheses. One of the most common types of analysis is nodal regression, where the relationships between node-level network metrics and nodal covariates are analysed using a permutation technique known as node-label permutations. We show that, contrary to accepted wisdom, node-label permutations do not automatically account for the non-independences assumed to exist in network data, because regression-based permutation tests still assume exchangeability of residuals. The same assumption also applies to the quadratic assignment procedure (QAP), a permutation-based method often used for conducting dyadic regression. We highlight that node-label permutations produce the same p-values as equivalent parametric regression models, but that in the presence of non-independence, parametric regression models can also produce accurate effect size estimates. We also note that QAP only controls for a specific type of non-independence between edges that are connected to the same nodes, and that appropriate parametric regression models are also able to account for this type of non-independence. Based on this, we suggest that standard parametric models could be used in the place of permutation-based methods. Moving away from permutation-based methods could have several benefits, including reducing over-reliance on p-values, generating more reliable effect size estimates, and facilitating the adoption of causal inference methods and alternative types of statistical analysis.Engineering and Physical Sciences Research Council (EPSRC)European Research Council (ERC)National Institutes of Health (NIH)Natural Environment Research Council (NERC

The evolution of menopause in toothed whales

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: All data used in this analysis are available as a database at: github.com/samellisq/marinelifehistdataCode availability: All R and stan code used for this analysis are available at osf.io/26s7m/. In addition, the mortality model is implemented as an R package available from: github.com/samellisq/marinesurvivalUnderstanding how and why menopause has evolved is a long-standing challenge across disciplines. Females can typically maximize their reproductive success by reproducing for the whole of their adult life. In humans, however, women cease reproduction several decades before the end of their natural lifespan1,2. Although progress has been made in understanding the adaptive value of menopause in humans3,4, the generality of these findings remains unclear. Toothed whales are the only mammal taxon in which menopause has evolved several times5, providing a unique opportunity to test the theories of how and why menopause evolves in a comparative context. Here, we assemble and analyse a comparative database to test competing evolutionary hypotheses. We find that menopause evolved in toothed whales by females extending their lifespan without increasing their reproductive lifespan, as predicted by the 'live-long' hypotheses. We further show that menopause results in females increasing their opportunity for intergenerational help by increasing their lifespan overlap with their grandoffspring and offspring without increasing their reproductive overlap with their daughters. Our results provide an informative comparison for the evolution of human life history and demonstrate that the same pathway that led to menopause in humans can also explain the evolution of menopause in toothed whales.Leverhulme TrustNatural Environment Research Council (NERC

Calculating effect sizes in animal social network analysis

This is the final version. Available on open access from Wiley via the DOI in this record1. Because of the nature of social interaction or association data, when testing hypotheses using social network data it is common for network studies to rely on permutations to control for confounding variables, and to not also control for them in the fitted statistical model. This can be a problem because it does not adjust for any bias in effect sizes generated by these confounding effects, and thus the effect sizes are not informative in the presence of counfouding variables. 2. We implemented two network simulation examples and analysed an empirical data set to demonstrate how relying solely on permutations to control for confounding variables can result in highly biased effect size estimates of animal social preferences that are uninformative when quantifying differences in behaviour. 3. Using these simulations, we show that this can sometimes even lead to effect sizes that have the wrong sign and are thus the effect size is not biologically interpretable. We demonstrate how this problem can be addressed by controlling for confounding variables in the statistical dyadic or nodal model. 4. We recommend this approach should be adopted as standard practice in the statistical analysis of animal social network dataNatural Environment Research Council (NERC

Somatization in response to undiagnosed obsessive compulsive disorder in a family

BACKGROUND: Somatization is a common problem in primary care and often presents puzzling problems for the family physician. A family or contextual approach is often useful in investigating and treating refractory symptoms. CASE PRESENTATION: A 63 year-old patient presented to his family physician with recurrent episodes of syncope, weakness and various other somatic symptoms. Lengthy clinical investigations found no organic pathological findings but a brief family assessment by the family physician revealed that the patient's wife was the "hidden" patient. Successful treatment of the patient's wife led to full recovery for both. CONCLUSIONS: Exploration and treatment of the family context may often hold the key to the solution of difficult problems in somatizing patients

Common datastream permutations of animal social network data are not appropriate for hypothesis testing using regression models

This is the final version. Available on open access from Wiley via the DOI in this record1. Social network methods have become a key tool for describing, modelling, and testing hypotheses about the social structures of animals. However, due to the non-independence of network data and the presence of confounds, specialized statistical techniques are often needed to test hypotheses in these networks. Datastream permutations, originally developed to test the null hypothesis of random social structure, have become a popular tool for testing a wide array of null hypotheses in animal social networks. In particular, they have been used to test whether exogenous factors are related to network structure by interfacing these permutations with regression models. 2. Here, we show that these datastream permutations typically do not represent the null hypothesis of interest to researchers interfacing animal social network analysis with regression modelling, and use simulations to demonstrate the potential pitfalls of using this methodology. 3. Our simulations show that, if used to indicate whether a relationship exists between network structure and a covariate, datastream permutations can result in extremely high type I error rates, in some cases approaching 50%. In the same set of simulations, traditional node-label permutations produced appropriate type I error rates (~ 5%). 4. Our analysis shows that datastream permutations do not represent the appropriate null hypothesis for these analyses. We suggest that potential alternatives to this procedure may be found in regarding the problems of non-independence of network data and unreliability of observations separately. If biases introduced during data collection can be corrected, either prior to model fitting or within the model itself, node-label permutations then serve as a useful test for interfacing animal social network analysis with regression modellingNatural Environment Research Council (NERC)NI

Perturbation with Intrabodies Reveals That Calpain Cleavage Is Required for Degradation of Huntingtin Exon 1

Background: Proteolytic processing of mutant huntingtin (mHtt), the protein that causes Huntington's disease (HD), is critical for mHtt toxicity and disease progression. mHtt contains several caspase and calpain cleavage sites that generate N-terminal fragments that are more toxic than full-length mHtt. Further processing is then required for the degradation of these fragments, which in turn, reduces toxicity. This unknown, secondary degradative process represents a promising therapeutic target for HD. Methodology/Principal Findings: We have used intrabodies, intracellularly expressed antibody fragments, to gain insight into the mechanism of mutant huntingtin exon 1 (mHDx-1) clearance. Happ1, an intrabody recognizing the proline-rich region of mHDx-1, reduces the level of soluble mHDx-1 by increasing clearance. While proteasome and macroautophagy inhibitors reduce turnover of mHDx-1, Happ1 is still able to reduce mHDx-1 under these conditions, indicating Happ1-accelerated mHDx-1 clearance does not rely on these processes. In contrast, a calpain inhibitor or an inhibitor of lysosomal pH block Happ1-mediated acceleration of mHDx-1 clearance. These results suggest that mHDx-1 is cleaved by calpain, likely followed by lysosomal degradation and this process regulates the turnover rate of mHDx-1. Sequence analysis identifies amino acid (AA) 15 as a potential calpain cleavage site. Calpain cleavage of recombinant mHDx-1 in vitro yields fragments of sizes corresponding to this prediction. Moreover, when the site is blocked by binding of another intrabody, V_L12.3, turnover of soluble mHDx-1 in living cells is blocked. Conclusions/Significance: These results indicate that calpain-mediated removal of the 15 N-terminal AAs is required for the degradation of mHDx-1, a finding that may have therapeutic implications