Comparative Study of Different Methods for the Prediction of Drug− Polymer Solubility

In this study, a comparison of different methods to predict drug−polymer solubility was carried out on binary systems consisting of five model drugs (paracetamol, chloramphenicol, celecoxib, indomethacin, and felodipine) and polyvinylpyrrolidone/vinyl acetate copolymers (PVP/VA) of different monomer weight ratios. The drug−polymer solubility at 25 °C was predicted using the Flory−Huggins model, from data obtained at elevated temperature using thermal analysis methods based on the recrystallization of a supersaturated amorphous solid dispersion and two variations of the melting point depression method. These predictions were compared with the solubility in the low molecular weight liquid analogues of the PVP/VA copolymer (N-vinylpyrrolidone and vinyl acetate). The predicted solubilities at 25 °C varied considerably depending on the method used. However, the three thermal analysis methods ranked the predicted solubilities in the same order, except for the felodipine−PVP system. Furthermore, the magnitude of the predicted solubilities from the recrystallization method and melting point depression method correlated well with the estimates based on the solubility in the liquid analogues, which suggests that this method can be used as an initial screening tool if a liquid analogue is available. The learnings of this important comparative study provided general guidance for the selection of the most suitable method(s) for the screening of drug−polymer solubility.

An Evaluation of Vaneless Diffuser Modelling Methods as a Means of Improving the Off-Design Performance Prediction of Centrifugal Compressors

An evaluation of existing 1-D vaneless diffuser design tools in the context of improving the off-design performance prediction of automotive turbocharger centrifugal compressors is described. A combination of extensive gas stand test data and single passage CFD simulations have been employed in order to permit evaluation of the different methods, allowing conclusions about the relative benefits and deficiencies of each of the different approaches to be determined. The vaneless diffuser itself has been isolated from the incumbent limitations in the accuracy of 1-D impeller modelling tools through development of a method to fully specify impeller exit conditions (in terms of mean quantities) using only standard test stand data with additional interstage static pressure measurements at the entrance to the diffuser. This method allowed a direct comparison between the test data and 1-D methods through sharing common inputs, thus achieving the aim of diffuser isolation.

Crucial to the accuracy of determining the performance of each of the vaneless diffuser configurations was the ability to quantify the presence and extent of the spanwise aerodynamic blockage present at the diffuser inlet section. A method to evaluate this critical parameter using CFD data is described herein, along with a correlation for blockage related to a new diffuser inlet flow parameter ⚡, equal to the quotient of the local flow coefficient and impeller tip speed Mach number. The resulting correlation permitted the variation of blockage with operating condition to be captured.

Monitoring of lineage-specific chimaerism allows early prediction of response following donor lymphocyte infusions for relapsed chronic myeloid leukaemia

Donor lymphocyte infusions (DLI) have been shown to enhance the graft-versus-leukaemia (GVL) effect and induce haematological and molecular remission in patients with relapsed CML following allogeneic bone marrow transplantation (BMT). The potent donor cell-mediated cytolysis following DLI may lead to a short period of aplasia before the re-establishment of donor haematopoiesis. The absence of detectable donor cells in patients prior to DLI infusion may result in permanent aplasia in certain patients. We report on four patients who relapsed 1, 3, 6.5 and 7 years post-BMT for chronic phase CML and were treated with DLI from their original BMT donor. Polymorphic short tandem repeats (STRs) were used to assess haematological chimaerism both prior to and following DLI. At the time of relapse, STR-PCR indicated the presence of donor cells in all four patients, at levels ranging from 1-40%. A clinical and molecular response was seen in 4/4 patients following a short period of cytopenia and all patients remain in clinical remission with a follow-up of 2 months-3 years post-DLI. STR-PCR indicated that a response was occurring during the period of pancytopenia when metaphase analysis was unsuccessful. Lineage-specific analysis of the cellular response to DLI was monitored using STR-PCR of peripheral blood (PB) and bone marrow (BM) lymphocyte-enriched fractions and CD2-positive and -negative T cell fractions. In one patient BM and PB CD34-positive and -negative fractions were also assessed. A change in the ratio of donor:recipient cells in the PB lymphocyte fraction was the earliest molecular indication of an anti-leukaemic response. Subsequent conversion to donor chimaerism occurred in the other lineages and the granulocyte fraction was the last lineage to convert. In conclusion, lineage-specific STR-PCR permits detailed monitoring of subtle changes in donor/recipient cell dynamics in specific lineages following DLI during the crucial pancytopenic phase and may be a useful predictor of haematological response to DLI therapy.

Discrete Conditional Phase-type Model Utilising a Multiclass Support Vector Machine for the Prediction of Retinopathy of Prematurity

Retinopathy of prematurity (ROP) is a rare disease in which retinal blood vessels of premature infants fail to develop normally, and is one of the major causes of childhood blindness throughout the world. The Discrete Conditional Phase-type (DC-Ph) model consists of two components, the conditional component measuring the inter-relationships between covariates and the survival component which models the survival distribution using a Coxian phase-type distribution. This paper expands the DC-Ph models by introducing a support vector machine (SVM), in the role of the conditional component. The SVM is capable of classifying multiple outcomes and is used to identify the infant's risk of developing ROP. Class imbalance makes predicting rare events difficult. A new class decomposition technique, which deals with the problem of multiclass imbalance, is introduced. Based on the SVM classification, the length of stay in the neonatal ward is modelled using a 5, 8 or 9 phase Coxian distribution.

An Irish eclipse prediction of AD 754: the earliest in the Latin West

This note announces the discovery of a tract on eclipse prediction in Paris, BnF, lat. 6400b, composed by an Irish scholar in ad 754. It is the earliest such text in the early middle ages and it is here placed in its scientific context.

Interactions between pyrazole derived enantiomers and Chiralcel OJ: Prediction of enantiomer absolute configurations and elution order by molecular dynamics simulations

The separation of enantiomers and confirmation of their absolute configurations is significant in the development of chiral drugs. The interactions between the enantiomers of chiral pyrazole derivative and polysaccharide-based chiral stationary phase cellulose tris(4-methylbenzoate) (Chiralcel OJ) in seven solvents and under different temperature were studied using molecular dynamics simulations. The results show that solvent effect has remarkable influence on the interactions. Structure analysis discloses that the different interactions between two isomers and chiral stationary phase are dependent on the nature of solvents, which may invert the elution order. The computational method in the present study can be used to predict the elution order and the absolute configurations of enantiomers in HPLC separations and therefore would be valuable in development of chiral drugs.

Appropriate complexity for the prediction of coastal and estuarine geomorphic behaviour at decadal to centennial scales

Coastal and estuarine landforms provide a physical template that not only accommodates diverse ecosystem functions and human activities, but also mediates flood and erosion risks that are expected to increase with climate change. In this paper, we explore some of the issues associated with the conceptualisation and modelling of coastal morphological change at time and space scales relevant to managers and policy makers. Firstly, we revisit the question of how to define the most appropriate scales at which to seek quantitative predictions of landform change within an age defined by human interference with natural sediment systems and by the prospect of significant changes in climate and ocean forcing. Secondly, we consider the theoretical bases and conceptual frameworks for determining which processes are most important at a given scale of interest and the related problem of how to translate this understanding into models that are computationally feasible, retain a sound physical basis and demonstrate useful predictive skill. In particular, we explore the limitations of a primary scale approach and the extent to which these can be resolved with reference to the concept of the coastal tract and application of systems theory. Thirdly, we consider the importance of different styles of landform change and the need to resolve not only incremental evolution of morphology but also changes in the qualitative dynamics of a system and/or its gross morphological configuration. The extreme complexity and spatially distributed nature of landform systems means that quantitative prediction of future changes must necessarily be approached through mechanistic modelling of some form or another. Geomorphology has increasingly embraced so-called ‘reduced complexity’ models as a means of moving from an essentially reductionist focus on the mechanics of sediment transport towards a more synthesist view of landform evolution. However, there is little consensus on exactly what constitutes a reduced complexity model and the term itself is both misleading and, arguably, unhelpful. Accordingly, we synthesise a set of requirements for what might be termed ‘appropriate complexity modelling’ of quantitative coastal morphological change at scales commensurate with contemporary management and policy-making requirements: 1) The system being studied must be bounded with reference to the time and space scales at which behaviours of interest emerge and/or scientific or management problems arise; 2) model complexity and comprehensiveness must be appropriate to the problem at hand; 3) modellers should seek a priori insights into what kind of behaviours are likely to be evident at the scale of interest and the extent to which the behavioural validity of a model may be constrained by its underlying assumptions and its comprehensiveness; 4) informed by qualitative insights into likely dynamic behaviour, models should then be formulated with a view to resolving critical state changes; and 5) meso-scale modelling of coastal morphological change should reflect critically on the role of modelling and its relation to the observable world.

Evaluation of biomarkers for the prediction of pre-eclampsia in women with type 1 diabetes mellitus: A systematic review.

BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal morbidity and mortality. Women with type 1 diabetes are considered a high-risk group for developing pre-eclampsia. Much research has focused on biomarkers as a means of screening for pre-eclampsia in the general maternal population; however, there is a lack of evidence for women with type 1 diabetes.
OBJECTIVES: To undertake a systematic review to identify potential biomarkers for the prediction of pre-eclampsia in women with type 1 diabetes.
SEARCH STRATEGY: We searched Medline, EMBASE, Maternity and Infant Care, Scopus, Web of Science and CINAHL SELECTION CRITERIA: Studies were included if they measured biomarkers in blood or urine of women who developed pre-eclampsia and had pre-gestational type 1 diabetes mellitus Data collection and analysis A narrative synthesis was adopted as a meta-analysis could not be performed, due to high study heterogeneity.
MAIN RESULTS: A total of 72 records were screened, with 21 eligible studies being included in the review. A wide range of biomarkers was investigated and study size varied from 34 to 1258 participants. No single biomarker appeared to be effective in predicting pre-eclampsia; however, glycaemic control was associated with an increased risk while a combination of angiogenic and anti-angiogenic factors seemed to be potentially useful.
CONCLUSIONS: Limited evidence suggests that combinations of biomarkers may be more effective in predicting pre-eclampsia than single biomarkers. Further research is needed to verify the predictive potential of biomarkers that have been measured in the general maternal population, as many studies exclude women with diabetes preceding pregnancy.