The Molecular Mobility of Supercooled Amorphous Indomethacin as a Function of Temperature and Relative Humidity

Purpose. To determine the relaxation times of supercooled indomethacin as a function of temperature and relative humidity above Tg, and to analyze the results in the context of being able to predict such behavior at various storage conditions. Methods. Dielectric relaxation times were measured in the frequency domain (12 to 10⁵ Hz) for amorphous indomethacin equilibrated at 0, 56, and 83% relative humidity. The heating rate dependence of Tg for dry supercooled indomethacin was measured with differential scanning calorimetry and used to determine relaxation times. The results were compared with previously published shear relaxation times and enthalpy recovery data. Results. Very good agreement was observed between dielectric and shear relaxation times, and those obtained from the heating rate dependence of the Tg, for dry indomethacin as a function of temperature above Tg. The introduction of water lowered the dielectric relaxation times of supercooled indomethacin without significantly affecting its fragility. The relaxation times below Tg, found to be lower than those predicted by extrapolation of the data obtained above Tg, were analyzed in the context of the Adam-Gibbs-Vogel equation. Conclusions. The relaxation times of amorphous indomethacin obtained from the heating rate dependence of Tg were in good agreement with those obtained from shear and dielectric measurements, thus validating a relatively simple approach of assessing molecular mobility. The significant molecular mobility of amorphous indomethacin observed below Tg, and the significant plasticizing effects of sorbed water, help to explain why amorphous indomethacin crystallizes well below Tg over relatively short time scales.     

ORDERLY DIETING AND DISORDERED EATING: A CASE REPORT

A moderately obese 49-year-old woman who was enrolled in a nutrition and weight control clinic quickly attained her target weight through an individualized program of balanced deficit diet, routine exercise, and weekly counseling. Weight loss continued until she was 15% below Metropolitan Relative Weight, when family members grew concerned that she had developed an eating disorder. Despite nutritional and behavioral counseling, she has rigorously maintained her exaggerated weight loss. This case report illustrates a potentially serious but often overlooked reason for careful monitoring of patients undergoing treatment for obesity. Health professionals involved in weight control programs should routinely assess patients for potential eating disorders.     

Identification of echocardiographic indices for the early detection of left-ventricular systolic dysfunction in beta-thalassaemia via Self-Organizing Maps: a data-exploration study

Congestive heart failure (CHF) remains the primary cause of death in patients suffering from beta-thalassaemia major. Its early detection allows the prompt initiation of aggressive chelation therapy, when the condition can still be reversed. We aimed at identifying echocardiographic indices for the early detection of left ventricular (LV) systolic dysfunction, the physiological abnormality underlying CHF, in these patients. We used Self-Organizing Maps (SOMs)--an artificial neural network--for identifying novel correlations within our Electronic Healthcare Record (EHCR) database on beta-thalassaemia. We sought echocardiographic parameters that are correlated to future deterioration of the LV ejection fraction and therefore constitute early signs of LV systolic dysfunction. At the same time, we evaluated SOMs as tools for exploring clinical datasets and make recommendations on the setup of the SOM algorithm that is appropriate for such tasks. We found that high values of the LV end-systolic diameter index and of the E/A ratio are early indications of LV systolic dysfunction. From a technical point of view, zero-mean unit-variance normalization of the input data, a large initial neighbourhood radius and a rectangular SOM grid produced optimal maps for the purpose of detecting clinical correlations. We have successfully used SOMs for exploring a clinical dataset and for creating novel medical hypotheses. A clinical study has been launched to confirm these hypotheses, and initial results are encouraging.     

Molecular Mobility of Supercooled Amorphous Indomethacin,Determined by Dynamic Mechanical Analysis

Purpose. To determine the viscosity and the frequency-dependent shear modulus of supercooled indomethacin as a function of temperature near and above its glass transition temperature and from these data to obtain a quantitative measure of its molecular mobility in the amorphous state. Methods. Viscoelastic measurements were carried with a controlled strain rheometer in the frequency domain, at 9 temperatures from 44° to 90°C. Results. The viscosity of supercooled indomethacin shows a strong non-Arrhenius temperature dependence over the temperature range studied, indicative of a fragile amorphous material. Application of the viscosity data to the VTF equation indicates a viscosity of 4.5 × 10¹⁰ Pa.s at the calorimetric Tg of 41°C, and a T₀ of –17°C. From the complex shear modulus and the Cole-Davidson equation the shear relaxation behaviour is found to be non-exponential, and the shear relaxation time at Tg is found to be approximately 100 sec. Conclusions. Supercooled indomethacin near and above its Tg exhibits significant molecular mobility, with relaxation times similar to the timescales covered in the handling and storage of pharmaceutical products.     

Mining of relations between proteins over biomedical scientific literature using a deep-linguistic approach

OBJECTIVE: The amount of new discoveries (as published in the scientific literature) in the biomedical area is growing at an exponential rate. This growth makes it very difficult to filter the most relevant results, and thus the extraction of the core information becomes very expensive. Therefore, there is a growing interest in text processing approaches that can deliver selected information from scientific publications, which can limit the amount of human intervention normally needed to gather those results. MATERIALS AND METHODS: This paper presents and evaluates an approach aimed at automating the process of extracting functional relations (e.g. interactions between genes and proteins) from scientific literature in the biomedical domain. The approach, using a novel dependency-based parser, is based on a complete syntactic analysis of the corpus. RESULTS: We have implemented a state-of-the-art text mining system for biomedical literature, based on a deep-linguistic, full-parsing approach. The results are validated on two different corpora: the manually annotated genomics information access (GENIA) corpus and the automatically annotated arabidopsis thaliana circadian rhythms (ATCR) corpus. CONCLUSION: We show how a deep-linguistic approach (contrary to common belief) can be used in a real world text mining application, offering high-precision relation extraction, while at the same time retaining a sufficient recall.     

Choice of statistical model for cost-effectiveness analysis and covariate adjustment: empirical application of prominent models and assessment of their results

Context

Statistical models employed in analysing patient-level cost and effectiveness data need to be flexible enough to adjust for any imbalanced covariates, account for correlations between key parameters, and accommodate potential skewed distributions of costs and/or effects. We compare prominent statistical models for cost-effectiveness analysis alongside randomised controlled trials (RCTs) and covariate adjustment to assess their performance and accuracy using data from a large RCT.

Method

Seemingly unrelated regressions, linear regression of net monetary benefits, and Bayesian generalized linear models with various distributional assumptions were used to analyse data from the TASMINH2 trial. Each model adjusted for covariates prognostic of costs and outcomes.

Results

Cost-effectiveness results were notably sensitive to model choice. Models assuming normally distributed costs and effects provided a poor fit to the data, and potentially misleading inference. Allowing for a beta distribution captured the true incremental difference in effects and changed the decision as to which treatment is preferable.

Conclusions

Our findings suggest that Bayesian generalized linear models which allow for non-normality in estimation offer an attractive tool for researchers undertaking cost-effectiveness analyses. The flexibility provided by such methods allows the researcher to analyse patient-level data which are not necessarily normally distributed, while at the same time it enables assessing the effect of various baseline covariates on cost-effectiveness results.

     

The protein kinase CK2 is involved in regulation of circadian rhythms in Arabidopsis

A wide range of processes in plants, including expression of certain genes, is regulated by endogenous circadian rhythms. The circadian clock-associated 1 (CCA1) and the late elongated hypocotyl (LHY) proteins have been shown to be closely associated with clock function in Arabidopsis thaliana. The protein kinase CK2 can interact with and phosphorylate CCA1, but its role in the regulation of the circadian clock remains unknown. Here we show that plants overexpressing CKB3, a regulatory subunit of CK2, display increased CK2 activity and shorter periods of rhythmic expression of CCA1 and LHY. CK2 is also able to interact with and phosphorylate LHY in vitro. Additionally, overexpression of CKB3 shortened the periods of four known circadian clock-controlled genes with different phase angles, demonstrating that many clock outputs are affected. This overexpression also reduced phytochrome induction of an Lhcb gene. Finally, we found that the photoperiodic flowering response, which is influenced by circadian rhythms, was diminished in the transgenic lines, and that the plants flowered earlier on both long-day and short-day photoperiods. These data demonstrate that CK2 is involved in regulation of the circadian clock in Arabidopsis.     

Screening for sickle cell and thalassaemia in primary care: a cost-effectiveness study

Background

Haemoglobinopathies, including sickle cell disease and thalassaemia (SCT), are inherited disorders of haemoglobin. Antenatal screening for SCT rarely occurs before 10 weeks of pregnancy.

Aim

To explore the cost-effectiveness of offering SCT screening in a primary care setting, during the pregnancy confirmation visit.

Design and setting

A model-based cost-effectiveness analysis of inner-city areas with a high proportion of residents from ethnic minority groups.

Method

Comparison was made of three SCT screening approaches: ‘primary care parallel’ (primary care screening with test offered to mother and father together); ‘primary care sequential (primary care screening with test offered to the mother and then the father only if the mother is a carrier); and ‘midwife care’ (sequential screening at the first midwife consultation). The model was populated with data from the SHIFT (Screening for Haemoglobinopathies In First Trimester) trial and other sources.

Results

Compared to midwife care, primary care sequential had a higher NHS cost of £34 000 per 10 000 pregnancies (95% confidence interval [CI] = £15 000 to £51 000) and an increase of 2623 women screened (95% CI: 1359 to 4495), giving a cost per additional woman screened by 10 weeks of £13. Primary care parallel was dominated by primary care sequential, with both higher costs and fewer women screened.

Conclusion

The policy judgement is whether an earlier opportunity for informed reproductive choice has a value of at least £13. Further work is required to understand the value attached to earlier informed reproductive choices.     

Novel biological networks modulated by complement

The almost complete deciphering of the human genome has paved the way for the application of new technology platforms in understanding the contribution of complex biological pathways to human pathophysiology and disease. In the post-genomic era, the concept of systems biology has gained significant momentum and biomedical research is now being conducted on an integrated and cross-disciplinary platform that pulls together its resources from diverse fields such as computational biology, bioinformatics, functional genomics, structural biology, and proteomics. In this perspective, the identity of established biologic systems is being re-examined in the light of novel findings that suggest novel associations between otherwise unrelated pathways and individual proteins. Complement exemplifies such a system that, transcending its innate immune identity, has forged functional associations with multiple pathways and networks in modulating basic biologic processes. In the present article, we provide a global overview of these unusual system associations of complement with the aid of a powerful and high-throughput bioinformatics platform. Using a novel approach called systems literature analysis that allows the rapid extraction of text-based associations between genes and pathways from the ever expanding scientific article database, we have selected a broad range of biologic processes modulated by complement proteins and have constructed an integrated map of complement-mediated networks that incorporates well over 85 diverse biologic pathways. Expanding the complement cascade beyond its approximately 35 designated components, we discuss protein-protein interactions involving novel ligands and associations with signaling cascades and cellular networks that affect both inflammatory and non-inflammatory processes. This integrated consideration of complement within a unified 'systems biology' framework underscores the concept that innate immunity goes well beyond the protection of 'self' extending links to critical developmental, homeostatic, and metabolic processes.