Phage therapy: A software system for phage quantification and kinetic model inference.

One of the most serious problems of the modern medicine is the growing emergence of antibiotic resistance among pathogenic bacteria. In this circumstance, different and innovative approaches for treating infections caused by multidrug-resistant bacteria are imperatively required. Bacteriophage Therapy is one among the fascinating approaches to be taken into account. This consists of the use of bacteriophages, viruses that infect bacteria, in order to defeat specific bacterial pathogens. Phage therapy is not an innovative idea, indeed, it was widely used around the world in the 1930s and 1940s, in order to treat various infection diseases, and it is still used in Eastern Europe and the former Soviet Union. Nevertheless, Western scientists mostly lost interest in further use and study of phage therapy and abandoned it after the discovery and the spread of antibiotics. The advancement of scientific knowledge of the last years, together with the encouraging results from recent animal studies using phages to treat bacterial infections, and above all the urgent need for novel and effective antimicrobials, have given a prompt for additional rigorous researches in this field. In particular, in the laboratory of synthetic biology of the department of Life Sciences at the University of Warwick, a novel approach was adopted, starting from the original concept of phage therapy, in order to study a concrete alternative to antibiotics. The innovative idea of the project consists in the development of experimental methodologies, which allow to engineer a programmable synthetic phage system using a combination of directed evolution, automation and microfluidics. The main aim is to make “the therapeutics of tomorrow individualized, specific, and self-regulated” (Jaramillo, 2015). In this context, one of the most important key points is the Bacteriophage Quantification. Therefore, in this research work, a mathematical model describing complex dynamics occurring in biological systems involving continuous growth of bacteriophages, modulated by the performance of the host organisms, was implemented as algorithms into a working software using MATLAB. The developed program is able to predict different unknown concentrations of phages much faster than the classical overnight Plaque Assay. What is more, it gives a meaning and an explanation to the obtained data, making inference about the parameter set of the model, that are representative of the bacteriophage-host interaction.

Expression, localization, and functional model of cholesterol transporters in lactating and nonlactating mammary tissues of murine, bovine, and human origin

Members of the ATP-binding cassette (ABC) transporters play a pivotal role in cellular lipid efflux. To identify candidate cholesterol transporters implicated in lipid homeostasis and mammary gland (MG) physiology, we compared expression and localization of ABCA1, ABCG1, and ABCA7 and their regulatory genes in mammary tissues of different species during the pregnancy-lactation cycle. Murine and bovine mammary glands (MGs) were investigated during different functional stages. The abundance of mRNAs was determined by quantitative RT-PCR. Furthermore, transporter proteins were localized in murine, bovine, and human MGs by immunohistochemistry. In the murine MG, ABCA1 mRNA abundance was elevated during nonlactating compared with lactating stages, whereas ABCA7 and ABCA1 mRNA profiles were not altered. In the bovine MG, ABCA1, ABCG1, and ABCA7 mRNAs abundances were increased during nonlactating stages compared with lactation. Furthermore, associations between mRNA levels of transporters and their regulatory genes LXRalpha, PPARgamma, and SREBPs were found. ABCA1, ABCG1, and ABCA7 proteins were localized in glandular MG epithelial cells (MEC) during lactation, whereas during nonlactating stages, depending on species, the proteins showed distinct localization patterns in MEC and adipocytes. Our results demonstrate that ABCA1, ABCG1, and ABCA7 are differentially expressed between lactation and nonlactating stages and in association with regulatory genes. Combined expression and localization data suggest that the selected cholesterol transporters are universal MG transporters involved in transport and storage of cholesterol and in lipid homeostasis of MEC. Because of the species-specific expression patterns of transporters in mammary tissue, mechanisms of cholesterol homeostasis seem to be differentially regulated between species.

The effects of a flexible visual acuity-driven ranibizumab treatment regimen in age-related macular degeneration: outcomes of a drug and disease model

Differences in treatment responses to ranibizumab injections observed within trials involving monthly (MARINA and ANCHOR studies) and quarterly (PIER study) treatment suggest that an individualized treatment regimen may be effective in neovascular age-related macular degeneration. In the present study, a drug and disease model was used to evaluate the impact of an individualized, flexible treatment regimen on disease progression.

CCSD(T), W1, and other model chemistry predictions for gas-phase deprotonation reactions

A series of CCSD(T) single-point calculations on MP4(SDQ) geometries and the W1 model chemistry method have been used to calculate ΔH° and ΔG° values for the deprotonation of 17 gas-phase reactions where the experimental values have reported accuracies within 1 kcal/mol. These values have been compared with previous calculations using the G3 and CBS model chemistries and two DFT methods. The most accurate CCSD(T) method uses the aug-cc-pVQZ basis set. Extrapolation of the aug-cc-pVTZ and aug-cc-pVQZ results yields the most accurate agreement with experiment, with a standard deviation of 0.58 kcal/mol for ΔG° and 0.70 kcal/mol for ΔH°. Standard deviations from experiment for ΔG° and ΔH° for the W1 method are 0.95 and 0.83 kcal/mol, respectively. The G3 and CBS-APNO results are competitive with W1 and are much less expensive. Any of the model chemistry methods or the CCSD(T)/aug-cc-pVQZ method can serve as a valuable check on the accuracy of experimental data reported in the National Institutes of Standards and Technology (NIST) database.

Gene expression profiling reveals consistent differences between clinical samples of human leukaemias and their model cell lines

Microarray gene expression profiles of fresh clinical samples of chronic myeloid leukaemia in chronic phase, acute promyelocytic leukaemia and acute monocytic leukaemia were compared with profiles from cell lines representing the corresponding types of leukaemia (K562, NB4, HL60). In a hierarchical clustering analysis, all clinical samples clustered separately from the cell lines, regardless of leukaemic subtype. Gene ontology analysis showed that cell lines chiefly overexpressed genes related to macromolecular metabolism, whereas in clinical samples genes related to the immune response were abundantly expressed. These findings must be taken into consideration when conclusions from cell line-based studies are extrapolated to patients.

A Coordinated and Systematic Model for Adopting, Implementing and Maintaining Effective Sexual Health Education Programs in Schools

Getting evidence-based sexual health education activities into schools can be a complicated process. Working models that assist our educational system in the selection, implementation, and maintenance of effective school-based adolescent health programs are needed. Replicating sexual health programs in school-based settings: A model for schools provides a comprehensive and applied approach that engages all of the important stakeholders within a school district. The results from this study hold much potential to inform Texas and the nation about how a coordinated and practical model can assist school districts to increase the use of evidence-based programs addressing teen pregnancy prevention and sexual health issues.

Influence of microphysical schemes on atmospheric water in the Weather Research and Forecasting model

This study examines how different microphysical parameterization schemes influence orographically induced precipitation and the distributions of hydrometeors and water vapour for midlatitude summer conditions in the Weather Research and Forecasting (WRF) model. A high-resolution two-dimensional idealized simulation is used to assess the differences between the schemes in which a moist air flow is interacting with a bell-shaped 2 km high mountain. Periodic lateral boundary conditions are chosen to recirculate atmospheric water in the domain. It is found that the 13 selected microphysical schemes conserve the water in the model domain. The gain or loss of water is less than 0.81% over a simulation time interval of 61 days. The differences of the microphysical schemes in terms of the distributions of water vapour, hydrometeors and accumulated precipitation are presented and discussed. The Kessler scheme, the only scheme without ice-phase processes, shows final values of cloud liquid water 14 times greater than the other schemes. The differences among the other schemes are not as extreme, but still they differ up to 79% in water vapour, up to 10 times in hydrometeors and up to 64% in accumulated precipitation at the end of the simulation. The microphysical schemes also differ in the surface evaporation rate. The WRF single-moment 3-class scheme has the highest surface evaporation rate compensated by the highest precipitation rate. The different distributions of hydrometeors and water vapour of the microphysical schemes induce differences up to 49 W m−2 in the downwelling shortwave radiation and up to 33 W m−2 in the downwelling longwave radiation.

Bayesian and survival model for tumor relapse status and disease-specific survival, with applications to breast cancer

Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women in the United States. Studies on ipsilateral breast tumor relapse (IBTR) status and disease-specific survival will help guide clinic treatment and predict patient prognosis.^ After breast conservation therapy, patients with breast cancer may experience breast tumor relapse. This relapse is classified into two distinct types: true local recurrence (TR) and new ipsilateral primary tumor (NP). However, the methods used to classify the relapse types are imperfect and are prone to misclassification. In addition, some observed survival data (e.g., time to relapse and time from relapse to death)are strongly correlated with relapse types. The first part of this dissertation presents a Bayesian approach to (1) modeling the potentially misclassified relapse status and the correlated survival information, (2) estimating the sensitivity and specificity of the diagnostic methods, and (3) quantify the covariate effects on event probabilities. A shared frailty was used to account for the within-subject correlation between survival times. The inference was conducted using a Bayesian framework via Markov Chain Monte Carlo simulation implemented in softwareWinBUGS. Simulation was used to validate the Bayesian method and assess its frequentist properties. The new model has two important innovations: (1) it utilizes the additional survival times correlated with the relapse status to improve the parameter estimation, and (2) it provides tools to address the correlation between the two diagnostic methods conditional to the true relapse types.^ Prediction of patients at highest risk for IBTR after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The goals of the second part of this dissertation were to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center, to determine the risk of IBTR in patients with DCIS treated with local excision, and to determine whether there is a subset of patients at low risk of IBTR. Patients who had undergone local excision from 1990 through 2007 at MD Anderson Cancer Center with a final diagnosis of DCIS (n=794) were included in this part. Clinicopathologic factors and the performance of the Memorial Sloan-Kettering Cancer Center nomogram for prediction of IBTR were assessed for 734 patients with complete data. Nomogram for prediction of 5- and 10-year IBTR probabilities were found to demonstrate imperfect calibration and discrimination, with an area under the receiver operating characteristic curve of .63 and a concordance index of .63. In conclusion, predictive models for IBTR in DCIS patients treated with local excision are imperfect. Our current ability to accurately predict recurrence based on clinical parameters is limited.^ The American Joint Committee on Cancer (AJCC) staging of breast cancer is widely used to determine prognosis, yet survival within each AJCC stage shows wide variation and remains unpredictable. For the third part of this dissertation, biologic markers were hypothesized to be responsible for some of this variation, and the addition of biologic markers to current AJCC staging were examined for possibly provide improved prognostication. The initial cohort included patients treated with surgery as first intervention at MDACC from 1997 to 2006. Cox proportional hazards models were used to create prognostic scoring systems. AJCC pathologic staging parameters and biologic tumor markers were investigated to devise the scoring systems. Surveillance Epidemiology and End Results (SEER) data was used as the external cohort to validate the scoring systems. Binary indicators for pathologic stage (PS), estrogen receptor status (E), and tumor grade (G) were summed to create PS+EG scoring systems devised to predict 5-year patient outcomes. These scoring systems facilitated separation of the study population into more refined subgroups than the current AJCC staging system. The ability of the PS+EG score to stratify outcomes was confirmed in both internal and external validation cohorts. The current study proposes and validates a new staging system by incorporating tumor grade and ER status into current AJCC staging. We recommend that biologic markers be incorporating into revised versions of the AJCC staging system for patients receiving surgery as the first intervention.^ Chapter 1 focuses on developing a Bayesian method to solve misclassified relapse status and application to breast cancer data. Chapter 2 focuses on evaluation of a breast cancer nomogram for predicting risk of IBTR in patients with DCIS after local excision gives the statement of the problem in the clinical research. Chapter 3 focuses on validation of a novel staging system for disease-specific survival in patients with breast cancer treated with surgery as the first intervention. ^

Dinoflagellate cyst counts and age model from sediment samples of ODP Hole 175-1085A

Sediment samples from ODP Site 1085 were investigated in order to obtain more information on the initiation and development of the Benguela upwelling system during the middle and upper Miocene. In particular, our intent was to establish the causes of the upwelling as well as the response of the upwelling regime to the development of the Antarctic Circumpolar Current. Based on changes in the calcareous dinoflagellate cyst association, we found an initial increase of the dinoflagellate cyst productivity, probably related to the initiation of upwelling about 11.8 Ma ago. Two distinct increases in cyst productivity in conjunction with temperature decreases of the upper water masses reflect upwelling pulses off Namibia and occur at the end of the Miocene cooling events Mi5 (about 11.5 Ma) and Mi6 (about 10.5 Ma). Both cooling events are associated with an ice volume increase in Antarctica and are thought to have led to an increase in southeasterly winds, possibly causing these two upwelling pulses. We demonstrate a decrease in dinoflagellate cyst productivity and enhanced terrigenous input via the Orange River after the Mi5 event. At about 11.1 Ma, the dinoflagellate cyst productivity increases again. The polar cyst species Caracomia arctica occurs here for the first time. This implies an influence of subantarctic mode water and therefore a change in the quality of the upwelling water which allowed the Benguela upwelling to develop into modern conditions. From about 10.4 Ma, C. arctica forms a permanent part of the association, pointing to an establishment of the upwelling regime.