Proteome sequence features carry signatures of the environmental niche of prokaryotes

<p>Abstract</p> <p>Background</p> <p>Prokaryotic environmental adaptations occur at different levels within cells to ensure the preservation of genome integrity, proper protein folding and function as well as membrane fluidity. Although specific composition and structure of cellular components suitable for the variety of extreme conditions has already been postulated, a systematic study describing such adaptations has not yet been performed. We therefore explored whether the environmental niche of a prokaryote could be deduced from the sequence of its proteome. Finally, we aimed at finding the precise differences between proteome sequences of prokaryotes from different environments.</p> <p>Results</p> <p>We analyzed the proteomes of 192 prokaryotes from different habitats. We collected detailed information about the optimal growth conditions of each microorganism. Furthermore, we selected 42 physico-chemical properties of amino acids and computed their values for each proteome. Further, on the same set of features we applied two fundamentally different machine learning methods, Support Vector Machines and Random Forests, to successfully classify between bacteria and archaea, halophiles and non-halophiles, as well as mesophiles, thermophiles and mesothermophiles. Finally, we performed feature selection by using Random Forests.</p> <p>Conclusions</p> <p>To our knowledge, this is the first time that three different classification cases (domain of life, halophilicity and thermophilicity) of proteome adaptation are successfully performed with the same set of 42 features. The characteristic features of a specific adaptation constitute a signature that may help understanding the mechanisms of adaptation to extreme environments.</p

Allergic sensitization: screening methods

Experimental in silico, in vitro, and rodent models for screening and predicting protein sensitizing potential are discussed, including whether there is evidence of new sensitizations and allergies since the introduction of genetically modified crops in 1996, the importance of linear versus conformational epitopes, and protein families that become allergens. Some common challenges for predicting protein sensitization are addressed: (a) exposure routes; (b) frequency and dose of exposure; (c) dose-response relationships; (d) role of digestion, food processing, and the food matrix; (e) role of infection; (f) role of the gut microbiota; (g) influence of the structure and physicochemical properties of the protein; and (h) the genetic background and physiology of consumers. The consensus view is that sensitization screening models are not yet validated to definitively predict the de novo sensitizing potential of a novel protein. However, they would be extremely useful in the discovery and research phases of understanding the mechanisms of food allergy development, and may prove fruitful to provide information regarding potential allergenicity risk assessment of future products on a case by case basis. These data and findings were presented at a 2012 international symposium in Prague organized by the Protein Allergenicity Technical Committee of the International Life Sciences Institute’s Health and Environmental Sciences Institute

Cumulative Prognostic Score Predicting Mortality in Patients Older Than 80 Years Admitted to the ICU.

OBJECTIVES: To develop a scoring system model that predicts mortality within 30 days of admission of patients older than 80 years admitted to intensive care units (ICUs). DESIGN: Prospective cohort study. SETTING: A total of 306 ICUs from 24 European countries. PARTICIPANTS: Older adults admitted to European ICUs (N = 3730; median age = 84 years [interquartile range = 81-87 y]; 51.8% male). MEASUREMENTS: Overall, 24 variables available during ICU admission were included as potential predictive variables. Multivariable logistic regression was used to identify independent predictors of 30-day mortality. Model sensitivity, specificity, and accuracy were evaluated with receiver operating characteristic curves. RESULTS: The 30-day-mortality was 1562 (41.9%). In multivariable analysis, these variables were selected as independent predictors of mortality: age, sex, ICU admission diagnosis, Clinical Frailty Scale, Sequential Organ Failure Score, invasive mechanical ventilation, and renal replacement therapy. The discrimination, accuracy, and calibration of the model were good: the area under the curve for a score of 10 or higher was .80, and the Brier score was .18. At a cut point of 10 or higher (75% of all patients), the model predicts 30-day mortality in 91.1% of all patients who die. CONCLUSION: A predictive model of cumulative events predicts 30-day mortality in patients older than 80 years admitted to ICUs. Future studies should include other potential predictor variables including functional status, presence of advance care plans, and assessment of each patient's decision-making capacity

Relationship between the Clinical Frailty Scale and short-term mortality in patients ≥ 80 years old acutely admitted to the ICU: a prospective cohort study.

BACKGROUND: The Clinical Frailty Scale (CFS) is frequently used to measure frailty in critically ill adults. There is wide variation in the approach to analysing the relationship between the CFS score and mortality after admission to the ICU. This study aimed to evaluate the influence of modelling approach on the association between the CFS score and short-term mortality and quantify the prognostic value of frailty in this context. METHODS: We analysed data from two multicentre prospective cohort studies which enrolled intensive care unit patients ≥ 80 years old in 26 countries. The primary outcome was mortality within 30-days from admission to the ICU. Logistic regression models for both ICU and 30-day mortality included the CFS score as either a categorical, continuous or dichotomous variable and were adjusted for patient's age, sex, reason for admission to the ICU, and admission Sequential Organ Failure Assessment score. RESULTS: The median age in the sample of 7487 consecutive patients was 84 years (IQR 81-87). The highest fraction of new prognostic information from frailty in the context of 30-day mortality was observed when the CFS score was treated as either a categorical variable using all original levels of frailty or a nonlinear continuous variable and was equal to 9% using these modelling approaches (p < 0.001). The relationship between the CFS score and mortality was nonlinear (p < 0.01). CONCLUSION: Knowledge about a patient's frailty status adds a substantial amount of new prognostic information at the moment of admission to the ICU. Arbitrary simplification of the CFS score into fewer groups than originally intended leads to a loss of information and should be avoided. Trial registration NCT03134807 (VIP1), NCT03370692 (VIP2)

Electron velocity in superlattices

Calculations of the electron velocity in superlattices based on the miniband dispersion relation, and the velocity defined through the tunneling time are discussed. The former definition is based on the intrinsically infinite modified Kronig-Penney model, while the latter rests upon the transfer matrix method and takes the finiteness of the superlattice into account. The main result is that the velocities differ: for weakly coupled structures where the tunneling time can be defined through the linewidth, the transfer matrix method predicts a smaller velocity than the modified Kronig-Penney model. Copyright Springer-Verlag Berlin/Heidelberg 2003

Supplementary Material for: Differential T-Helper Cell Polarization after Allergen-Specific Stimulation of Autologous Dendritic Cells in Polysensitized Allergic Patients

<p><b><i>Background:</i></b> Dendritic cells (DCs) play an important role in the induction and regulation of adaptive immune responses by polarizing T-helper (Th) cells. In allergic disease this response is dominated by Th2 cells. It is still unclear whether the activation of Th cells by DCs in atopic individuals is allergen specific. <b><i>Methods:</i></b> Monocyte-derived DCs (MoDCs) obtained from polysensitized patients were stimulated with purified Bet v 1, Phl p 5 and Act d 10, and the surface marker expression was analysed. Proliferation and cytokine profiles of autologous naïve CD4+ T cells co-cultured with allergen-pulsed MoDCs were assessed. <b><i>Results:</i></b> The addition of either Bet v 1 or Phl p 5 did not further increase the expression of surface markers from matured MoDCs in all study groups. In co-cultures, autologous naïve CD4+ T cells proliferated when DCs obtained from individuals allergic to birch and grass pollen were stimulated with Bet v 1 and Phl p 5, respectively. In the co-culture supernatants, significantly increased levels of IL-5 and IL-13 were detected. This effect correlated with the sensitization background and was absent when applying an unspecific allergen, Act d 10. The levels of IL-10 in supernatants of MoDCs and the levels of IL-10 and IFN-γ in supernatants of T cells remained unchanged upon stimulation with allergens. <b><i>Conclusions:</i></b> In this study we observed that allergen-specific stimulation of MoDCs induces T-cell proliferation and upregulation of Th2-type cytokines. Interestingly, this Th2 polarization was only observed in cells stimulated with the allergen to which the patients were sensitized.</p

Genetic restriction of antigen-presentation dictates allergic sensitization and disease in humanized mice.

Immunoglobulin(Ig)E-associated allergies result from misguided immune responses against innocuous antigens. CD4+ T lymphocytes are critical for initiating and perpetuating that process, yet the crucial factors determining whether an individual becomes sensitized towards a given allergen remain largely unknown