A Polyclonal SELEX Aptamer Library Allows Differentiation of Candida albicans, C. auris and C. parapsilosis Cells from Human Dermal Fibroblasts

Easy and reliable identification of pathogenic species such as yeasts, emerging as problematic microbes originating from the genus Candida, is a task in the management and treatment of infections, especially in hospitals and other healthcare environments. Aptamers are seizing an already indispensable role in different sensing applications as binding entities with almost arbitrarily tunable specificities and optimizable affinities. Here, we describe a polyclonal SELEX library that not only can specifically recognize and fluorescently label Candida cells, but is also capable to differentiate C. albicans, C. auris and C. parapsilosis cells in flow-cytometry, fluorometric microtiter plate assays and fluorescence microscopy from human cells, exemplified here by human dermal fibroblasts. This offers the opportunity to develop diagnostic tools based on this library. Moreover, these specific and robust affinity molecules could also serve in the future as potent binding entities on biomaterials and as constituents of technical devices and will thus open avenues for the development of cost-effective and easily accessible next generations of electronic biosensors in clinical diagnostics and novel materials for the specific removal of pathogenic cells from human bio-samples

Biclustering models for two-mode ordinal data

The work in this paper introduces finite mixture models that can be used to simul- taneously cluster the rows and columns of two-mode ordinal categorical response data, such as those resulting from Likert scale responses. We use the popular proportional odds parameterisation and propose models which provide insights into major patterns in the data. Model-fitting is performed using the EM algorithm and a fuzzy allocation of rows and columns to corresponding clusters is obtained. The clustering ability of the models is evaluated in a simulation study and demonstrated using two real data sets

Prepatterning in the Stem Cell Compartment

The mechanism by which an apparently uniform population of cells can generate a heterogeneous population of differentiated derivatives is a fundamental aspect of pluripotent and multipotent stem cell behaviour. One possibility is that the environment and the differentiation cues to which the cells are exposed are not uniform. An alternative, but not mutually exclusive possibility is that the observed heterogeneity arises from the stem cells themselves through the existence of different interconvertible substates that pre-exist before the cells commit to differentiate. We have tested this hypothesis in the case of apparently homogeneous pluripotent human embryonal carcinoma (EC) stem cells, which do not follow a uniform pattern of differentiation when exposed to retinoic acid. Instead, they produce differentiated progeny that include both neuronal and non-neural phenotypes. Our results suggest that pluripotent NTERA2 stem cells oscillate between functionally distinct substates that are primed to select distinct lineages when differentiation is induced

Fragmented in space: the oral history narrative of an Arab Christian from Antioch, Turkey

This study uses the case of Can Kılçıksız, an Arab Christian refugee youth from Antioch, Turkey, to argue that globalization may result in fragmented families and subjectivities and can also accelerate processes initiated by modernity and the construction of national identities. Can Kılçıksız and his siblings now live in Turkey, Germany, France and Finland. His life story suggests that males of Arab Christian origin from Antioch who had access to schooling are more likely to be involved in politics whereas females tend to be drawn to evangelical Christian organizations. The case also suggests that sibling ties might prove more durable in the course of transnational migration than conjugal ties. The case of Can Kılçıksız shows that the time/space linked to childhood through memory can play an important role in identity construction of subjects circulating in transnational space

What are the living conditions and health status of those who don't report their migration status? a population-based study in Chile

BACKGROUND: Undocumented immigrants are likely to be missing from population databases, making it impossible to identify an accurate sampling frame in migration research. No population-based data has been collected in Chile regarding the living conditions and health status of undocumented immigrants. However, the CASEN survey (Caracterizacion Socio- Economica Nacional) asked about migration status in Chile for the first time in 2006 and provides an opportunity to set the base for future analysis of available migration data. We explored the living conditions and health of self-reported immigrants and respondents who preferred not to report their migration status in this survey. METHODS: Cross-sectional secondary analysis of CASEN survey in Chile in 2006. Outcomes: any disability, illness/accident, hospitalization/surgery, cancer/chronic condition (all binary variables); and the number of medical/emergency attentions received (count variables). Covariates: Demographics (age, sex, marital status, urban/rural, ethnicity), socioeconomic status (education level, employment status and household income), and material standard of living (overcrowding, sanitation, housing quality). Weighted regression models were estimated for each health outcome, crude and adjusted by sets of covariates, in STATA 10.0. RESULTS: About 1% of the total sample reported being immigrants and 0.7% preferred not to report their migration status (Migration Status - Missing Values; MS-MV). The MS-MV lived in more deprived conditions and reported a higher rate of health problems than immigrants. Some gender differences were observed by health status among immigrants and the MS-MV but they were not statistically significant. Regressions indicated that age, sex, SES and material factors consistently affected MS-MVs’ chance of presenting poor health and these patterns were different to those found among immigrants. Great heterogeneity in both the MS-MV and the immigrants, as indicated by wide confidence intervals, prevented the identification of other significantly associated covariates. CONCLUSION: This is the first study to look at the living conditions and health of those that preferred not to respond their migration status in Chile. Respondents that do not report their migration status are vulnerable to poor health and may represent undocumented immigrants. Surveys that fail to identify these people are likely to misrepresent the experiences of immigrants and further quantitative and qualitative research is urgently required

Sloppy Models, Parameter Uncertainty, and the Role of Experimental Design

Computational models are increasingly used to understand and predict complex biological phenomena. These models contain many unknown parameters, at least some of which are difficult to measure directly, and instead are estimated by fitting to time-course data. Previous work has suggested that even with precise data sets, many parameters are unknowable by trajectory measurements. We examined this question in the context of a pathway model of epidermal growth factor (EGF) and neuronal growth factor (NGF) signaling. Computationally, we examined a palette of experimental perturbations that included different doses of EGF and NGF as well as single and multiple gene knockdowns and overexpressions. While no single experiment could accurately estimate all of the parameters, experimental design methodology identified a set of five complementary experiments that could. These results suggest optimism for the prospects for calibrating even large models, that the success of parameter estimation is intimately linked to the experimental perturbations used, and that experimental design methodology is important for parameter fitting of biological models and likely for the accuracy that can be expected from them.National Institutes of Health (U.S.) (U54 CA112967)MIT-Portugal ProgramSingapore-MIT Alliance for Research and Technolog

Sex differences in experiences of multiple traumas and mental health problems in the UK Biobank cohort

PurposeExperiences of reported trauma are common and are associated with a range of mental health problems. Sex differences in how reported traumas are experienced over the life course in relation to mental health require further exploration. Methods157,358 participants contributed data for the UK Biobank Mental Health Questionnaire (MHQ). Stratified Latent Class Analysis (LCA) was used to analyse combinations of reported traumatic experiences in males and females separately, and associations with mental health. ResultsIn females, five trauma classes were identified: a low-risk class (58.6%), a childhood trauma class (13.5%), an intimate partner violence class (12.9%), a sexual violence class (9.1%), and a high-risk class (5.9%). In males, a three-class solution was preferred: a low-risk class (72.6%), a physical and emotional trauma class (21.9%), and a sexual violence class (5.5%). In comparison to the low-risk class in each sex, all trauma classes were associated with increased odds of current depression, anxiety, and hazardous/harmful alcohol use after adjustment for covariates. The high-risk class in females and the sexual violence class in males produced significantly increased odds for recent psychotic experiences. ConclusionThere are sex differences in how reported traumatic experiences co-occur across a lifespan, with females at the greatest risk. However, reporting either sexual violence or multiple types of trauma was associated with increased odds of mental health problems for both males and females. Findings emphasise the public mental health importance of identifying and responding to both men and women’s experiences of trauma, including sexual violence