The impact of asymptomatic vertebral fractures on quality of life in older community-dwelling women: the Sao Paulo Ageing & Health Study

OBJECTIVES: The aim of this study was to investigate the impact of asymptomatic vertebral fractures on the quality of life in older women as part of the Sao Paulo Ageing & Health Study. METHODS: This study was a cross-sectional study with a random sample of 180 women 65 years of age or older with or without vertebral fractures. The Quality of Life Questionnaire of the European Foundation for Osteoporosis was administered to all subjects. Anthropometric data were obtained by physical examination, and the body mass index was calculated. Lateral thoracic and lumbar spine X-ray scans were obtained to identify asymptomatic vertebral fractures using a semi-quantitative method. RESULTS: Women with asymptomatic vertebral fractures had lower total scores [61.4(15.3) vs. 67.1(14.2), p = 0.03] and worse physical function domain scores [69.5(20.1) vs. 77.3(17.1), p = 0.02] for the Quality of Life Questionnaire of the European Foundation for Osteoporosis compared with women without fractures. The total score of this questionnaire was also worse in women classified as obese than in women classified as overweight or normal. High physical activity was related to a better total score for this questionnaire (p = 0.01). Likewise, lower physical function scores were observed in women with higher body mass index values (p < 0.05) and lower physical activity levels (p < 0.05). Generalized linear models with gamma distributions and logarithmic link functions, adjusted for age, showed that lower total scores and physical function domain scores for the Quality of Life Questionnaire of the European Foundation for Osteoporosis were related to a high body mass index, lower physical activity, and the presence of vertebral fractures (p < 0.05). CONCLUSION: Vertebral fractures are associated with decreased quality of life mainly physical functioning in older community-dwelling women regardless of age, body mass index, and physical activity. Therefore, the results highlight the importance of preventing and controlling asymptomatic vertebral fractures to reduce their impact on quality of life among older women.

Direct Determination of Sugar Cane Quality Parameters by X-ray Spectrometry and Multivariate Analysis

Current methods for quality control of sugar cane are performed in extracted juice using several methodologies, often requiring appreciable time and chemicals (eventually toxic), making the methods not green and expensive. The present study proposes the use of X-ray spectrometry together with chemometric methods as an innovative and alternative technique for determining sugar cane quality parameters, specifically sucrose concentration, POL, and fiber content. Measurements in stem, leaf, and juice were performed, and those applied directly in stem provided the best results. Prediction models for sugar cane stem determinations with a single 60 s irradiation using portable X-ray fluorescence equipment allows estimating the % sucrose, % fiber, and POL simultaneously. Average relative deviations in the prediction step of around 8% are acceptable if considering that field measurements were done. These results may indicate the best period to cut a particular crop as well as for evaluating the quality of sugar cane for the sugar and alcohol industries.

On the impact of disproportional samples in credit scoring models: An application to a Brazilian bank data

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.

Loss of interest, depressed mood and impact on the quality of life: Cross-sectional survey

Abstract Background Depressive symptoms and chronic disease have adverse effects on patients' health-related quality of life (H-RQOL). However, little is known about this effect on H-RQOL when only the two core depressive symptoms - loss of interest and depressed mood - are considered. The objective of this study is to investigate H-RQOL in the presence of loss of interest and depressed mood at a general medical outpatient unit. Methods We evaluated 553 patients at their first attendance at a general medical outpatient unit of a teaching hospital. H-RQOL was assessed with the Medical Outcomes Study 36-item Short-Form Health Survey (SF-36). Depressed mood and loss of interest were assessed by the Primary Care Evaluation of Mental Disorders (PRIME-MD)-Patient Questionnaire. A physician performed the diagnosis of chronic diseases by clinical judgment and classified them in 13 possible pre-defined categories. We used multiple linear regression to investigate associations between each domain of H-RQOL and our two core depression symptoms. The presence of chronic diseases and demographic variables were included in the models as covariates. Results Among the 553 patients, 70.5% were women with a mean age of 41.0 years (range 18-85, SD ± 15.4). Loss of interest was reported by 54.6%, and depressed mood by 59.7% of the patients. At least one chronic disease was diagnosed in 59.5% of patients; cardiovascular disease was the most prevalent, affecting 20.6% of our patients. Loss of interest and depressed mood was significantly associated with decreased scores in all domains of H-RQOL after adjustment for possible confounders. The presence of any chronic disease was associated with a decrease in the domain of vitality. The analysis of each individual chronic disease category revealed that no category was associated with a decrease in more than one domain of H-RQOL. Conclusion Loss of interest and depressed mood were associated with significant decreases in H-RQOL. We recommend these simple tests for screening in general practice.

The impact of asymptomatic vertebral fractures on quality of life in older community-dwelling women: the São Paulo Ageing & Health Study

OBJECTIVES: The aim of this study was to investigate the impact of asymptomatic vertebral fractures on the quality of life in older women as part of the Sao Paulo Ageing & Health Study. METHODS: This study was a cross-sectional study with a random sample of 180 women 65 years of age or older with or without vertebral fractures. The Quality of Life Questionnaire of the European Foundation for Osteoporosis was administered to all subjects. Anthropometric data were obtained by physical examination, and the body mass index was calculated. Lateral thoracic and lumbar spine X-ray scans were obtained to identify asymptomatic vertebral fractures using a semi-quantitative method. RESULTS: Women with asymptomatic vertebral fractures had lower total scores [61.4(15.3) vs. 67.1(14.2), p = 0.03] and worse physical function domain scores [69.5(20.1) vs. 77.3(17.1), p = 0.02] for the Quality of Life Questionnaire of the European Foundation for Osteoporosis compared with women without fractures. The total score of this questionnaire was also worse in women classified as obese than in women classified as overweight or normal. High physical activity was related to a better total score for this questionnaire (p = 0.01). Likewise, lower physical function scores were observed in women with higher body mass index values (p<0.05) and lower physical activity levels (p,0.05). Generalized linear models with gamma distributions and logarithmic link functions, adjusted for age, showed that lower total scores and physical function domain scores for the Quality of Life Questionnaire of the European Foundation for Osteoporosis were related to a high body mass index, lower physical activity, and the presence of vertebral fractures (p<0.05). CONCLUSION: Vertebral fractures are associated with decreased quality of life mainly physical functioning in older community-dwelling women regardless of age, body mass index, and physical activity. Therefore, the results highlight the importance of preventing and controlling asymptomatic vertebral fractures to reduce their impact on quality of life among older women.

QSAR models for inhibitors of physiological impact of Escherichia coli that leads to diarrhea

Quantitative structure – activity relationships (QSARs) developed to evaluate percentage of inhibition of STa-stimulated (Escherichia coli) cGMP accumulation in T84 cells are calculated by the Monte Carlo method. This endpoint represents a measure of biological activity of a substance against diarrhea. Statistical quality of the developed models is quite good. The approach is tested using three random splits of data into the training and test sets. The statistical characteristics for three splits are the following: (1) n = 20, r2 = 0.7208, q2 = 0.6583, s = 16.9, F = 46 (training set); n = 11, r2 = 0.8986, s = 14.6 (test set); (2) n = 19, r2 = 0.6689, q2 = 0.5683, s = 17.6, F = 34 (training set); n = 12, r2 = 0.8998, s = 12.1 (test set); and (3) n = 20, r2 = 0.7141, q2 = 0.6525, s = 14.7, F = 45 (training set); n = 11, r2 = 0.8858, s = 19.5 (test set). Based on the proposed here models hypothetical compounds which can be useful agents against diarrhea are suggested.

Air quality simulations for Londrina region, Brazil

The objective of this work were apply and provide a preliminary evaluation of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) performance, for Londrina region. We performed comparison with measurements obtained in meteorological stations. The model was configured to run with three domains with 27,9 and 3 km of grid resolution, using the ndown program and also was realized a simulation with the model configured to run with a single domain using a land use file based in a classified image for region of MODIS sensor. The emission files to supply the chemistry run were generated based in the work of Martins et al., 2012. RADM2 chemical mechanism and MADE/SORGAM modal aerosol models were used in the simulations. The results demonstrated that model was able to represent coherently the formation and dispersion of the pollution in Metropolitan Region of Londrina and also the importance of using the appropriate land use file for the region.

Development of musculoskeletal models for the design and the pre-clinical validation of hip resurfacing prosthesis

Background. The surgical treatment of dysfunctional hips is a severe condition for the patient and a costly therapy for the public health. Hip resurfacing techniques seem to hold the promise of various advantages over traditional THR, with particular attention to young and active patients. Although the lesson provided in the past by many branches of engineering is that success in designing competitive products can be achieved only by predicting the possible scenario of failure, to date the understanding of the implant quality is poorly pre-clinically addressed. Thus revision is the only delayed and reliable end point for assessment. The aim of the present work was to model the musculoskeletal system so as to develop a protocol for predicting failure of hip resurfacing prosthesis. Methods. Preliminary studies validated the technique for the generation of subject specific finite element (FE) models of long bones from Computed Thomography data. The proposed protocol consisted in the numerical analysis of the prosthesis biomechanics by deterministic and statistic studies so as to assess the risk of biomechanical failure on the different operative conditions the implant might face in a population of interest during various activities of daily living. Physiological conditions were defined including the variability of the anatomy, bone densitometry, surgery uncertainties and published boundary conditions at the hip. The protocol was tested by analysing a successful design on the market and a new prototype of a resurfacing prosthesis. Results. The intrinsic accuracy of models on bone stress predictions (RMSE < 10%) was aligned to the current state of the art in this field. The accuracy of prediction on the bone-prosthesis contact mechanics was also excellent (< 0.001 mm). The sensitivity of models prediction to uncertainties on modelling parameter was found below 8.4%. The analysis of the successful design resulted in a very good agreement with published retrospective studies. The geometry optimisation of the new prototype lead to a final design with a low risk of failure. The statistical analysis confirmed the minimal risk of the optimised design over the entire population of interest. The performances of the optimised design showed a significant improvement with respect to the first prototype (+35%). Limitations. On the authors opinion the major limitation of this study is on boundary conditions. The muscular forces and the hip joint reaction were derived from the few data available in the literature, which can be considered significant but hardly representative of the entire variability of boundary conditions the implant might face over the patients population. This moved the focus of the research on modelling the musculoskeletal system; the ongoing activity is to develop subject-specific musculoskeletal models of the lower limb from medical images. Conclusions. The developed protocol was able to accurately predict known clinical outcomes when applied to a well-established device and, to support the design optimisation phase providing important information on critical characteristics of the patients when applied to a new prosthesis. The presented approach does have a relevant generality that would allow the extension of the protocol to a large set of orthopaedic scenarios with minor changes. Hence, a failure mode analysis criterion can be considered a suitable tool in developing new orthopaedic devices.

Retrieval of trace gases vertical profile in the lower atmosphere combining. Differential Optical Absorption Spectroscopy with radiative transfer models

The motivation for the work presented in this thesis is to retrieve profile information for the atmospheric trace constituents nitrogen dioxide (NO2) and ozone (O3) in the lower troposphere from remote sensing measurements. The remote sensing technique used, referred to as Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS), is a recent technique that represents a significant advance on the well-established DOAS, especially for what it concerns the study of tropospheric trace consituents. NO2 is an important trace gas in the lower troposphere due to the fact that it is involved in the production of tropospheric ozone; ozone and nitrogen dioxide are key factors in determining the quality of air with consequences, for example, on human health and the growth of vegetation. To understand the NO2 and ozone chemistry in more detail not only the concentrations at ground but also the acquisition of the vertical distribution is necessary. In fact, the budget of nitrogen oxides and ozone in the atmosphere is determined both by local emissions and non-local chemical and dynamical processes (i.e. diffusion and transport at various scales) that greatly impact on their vertical and temporal distribution: thus a tool to resolve the vertical profile information is really important. Useful measurement techniques for atmospheric trace species should fulfill at least two main requirements. First, they must be sufficiently sensitive to detect the species under consideration at their ambient concentration levels. Second, they must be specific, which means that the results of the measurement of a particular species must be neither positively nor negatively influenced by any other trace species simultaneously present in the probed volume of air. Air monitoring by spectroscopic techniques has proven to be a very useful tool to fulfill these desirable requirements as well as a number of other important properties. During the last decades, many such instruments have been developed which are based on the absorption properties of the constituents in various regions of the electromagnetic spectrum, ranging from the far infrared to the ultraviolet. Among them, Differential Optical Absorption Spectroscopy (DOAS) has played an important role. DOAS is an established remote sensing technique for atmospheric trace gases probing, which identifies and quantifies the trace gases in the atmosphere taking advantage of their molecular absorption structures in the near UV and visible wavelengths of the electromagnetic spectrum (from 0.25 μm to 0.75 μm). Passive DOAS, in particular, can detect the presence of a trace gas in terms of its integrated concentration over the atmospheric path from the sun to the receiver (the so called slant column density). The receiver can be located at ground, as well as on board an aircraft or a satellite platform. Passive DOAS has, therefore, a flexible measurement configuration that allows multiple applications. The ability to properly interpret passive DOAS measurements of atmospheric constituents depends crucially on how well the optical path of light collected by the system is understood. This is because the final product of DOAS is the concentration of a particular species integrated along the path that radiation covers in the atmosphere. This path is not known a priori and can only be evaluated by Radiative Transfer Models (RTMs). These models are used to calculate the so called vertical column density of a given trace gas, which is obtained by dividing the measured slant column density to the so called air mass factor, which is used to quantify the enhancement of the light path length within the absorber layers. In the case of the standard DOAS set-up, in which radiation is collected along the vertical direction (zenith-sky DOAS), calculations of the air mass factor have been made using “simple” single scattering radiative transfer models. This configuration has its highest sensitivity in the stratosphere, in particular during twilight. This is the result of the large enhancement in stratospheric light path at dawn and dusk combined with a relatively short tropospheric path. In order to increase the sensitivity of the instrument towards tropospheric signals, measurements with the telescope pointing the horizon (offaxis DOAS) have to be performed. In this circumstances, the light path in the lower layers can become very long and necessitate the use of radiative transfer models including multiple scattering, the full treatment of atmospheric sphericity and refraction. In this thesis, a recent development in the well-established DOAS technique is described, referred to as Multiple AXis Differential Optical Absorption Spectroscopy (MAX-DOAS). The MAX-DOAS consists in the simultaneous use of several off-axis directions near the horizon: using this configuration, not only the sensitivity to tropospheric trace gases is greatly improved, but vertical profile information can also be retrieved by combining the simultaneous off-axis measurements with sophisticated RTM calculations and inversion techniques. In particular there is a need for a RTM which is capable of dealing with all the processes intervening along the light path, supporting all DOAS geometries used, and treating multiple scattering events with varying phase functions involved. To achieve these multiple goals a statistical approach based on the Monte Carlo technique should be used. A Monte Carlo RTM generates an ensemble of random photon paths between the light source and the detector, and uses these paths to reconstruct a remote sensing measurement. Within the present study, the Monte Carlo radiative transfer model PROMSAR (PROcessing of Multi-Scattered Atmospheric Radiation) has been developed and used to correctly interpret the slant column densities obtained from MAX-DOAS measurements. In order to derive the vertical concentration profile of a trace gas from its slant column measurement, the AMF is only one part in the quantitative retrieval process. One indispensable requirement is a robust approach to invert the measurements and obtain the unknown concentrations, the air mass factors being known. For this purpose, in the present thesis, we have used the Chahine relaxation method. Ground-based Multiple AXis DOAS, combined with appropriate radiative transfer models and inversion techniques, is a promising tool for atmospheric studies in the lower troposphere and boundary layer, including the retrieval of profile information with a good degree of vertical resolution. This thesis has presented an application of this powerful comprehensive tool for the study of a preserved natural Mediterranean area (the Castel Porziano Estate, located 20 km South-West of Rome) where pollution is transported from remote sources. Application of this tool in densely populated or industrial areas is beginning to look particularly fruitful and represents an important subject for future studies.

Calibration and validation of an air quality finite element model around an electric power plant in Gran Canaria island

[EN]This work presents the calibration and validation of an air quality finite element model applied to the surroundings of Jinamar electric power plant in Gran Canaria island (Spain). The model involves the generation of an adaptive tetrahedral mesh, the computation of an ambient wind field, the inclusion of the plume rise effect in the wind field, and the simulation of transport and reaction of pollutants. The main advantage of the model is the treatment of complex terrains that introduces an alternative to the standard implementation of current models. In addition, it improves the computational cost through the use of unstructured meshes...

NMR, Metabonomics and Molecular Profiles: Applications to the Quality Assessment of Foodstuffs

Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

Genetic Manipulation, Gene Silencing and Biomarker Development in Multiple Experimental Models.

The thesis is set in three different parts, according to the relative experimental models. First, the domestic pig (Sus scrofa) is part of the study on reproductive biotechnologies: the transgenesis technique of Sperm Mediated Gene Transfer is widely studied starting from the quality of the semen, through the study of multiple uptakes of exogenous DNA and lastly used in the production of multi-transgenic blastocysts. Finally we managed to couple the transgenesis pipeline with sperm sorting and therefore produced transgenic embryos of predetermined sex. In the second part of the thesis the attention is on the fruit fly (Drosophila melanogaster) and on its derived cell line: the S2 cells. The in vitro and in vivo models are used to develop and validate an efficient way to knock down the myc gene. First an efficient in vitro protocol is described, than we demonstrate how the decrease in myc transcript remarkably affects the ribosome biogenesis through the study of Polysome gradients, rRNA content and qPCR. In vivo we identified two optimal drivers for the conditional silencing of myc, once the flies are fed with RU486: the first one is throughout the whole body (Tubulin), while the second is a head fat body driver (S32). With these results we present a very efficient model to study the role of myc in multiple aspects of translation. In the third and last part, the focus is on human derived lung fibroblasts (hLF-1), mouse tail fibroblasts and mouse tissues. We developed an efficient assay to quantify the total protein content of the nucleus on a single cell level via fluorescence. We coupled the protocol with classical immunofluorescence so to have at the same time general and particular information, demonstrating that during senescence nuclear proteins increase by 1.8 fold either in human cells, mouse cells and mouse tissues.

Development of models and methods to simulate peptide-assisted nucleation and growth of calcium-minerals

In den vergangenen Jahren wurden einige bislang unbekannte Phänomene experimentell beobachtet, wie etwa die Existenz unterschiedlicher Prä-Nukleations-Strukturen. Diese haben zu einem neuen Verständnis von Prozessen, die auf molekularer Ebene während der Nukleation und dem Wachstum von Kristallen auftreten, beigetragen. Die Auswirkungen solcher Prä-Nukleations-Strukturen auf den Prozess der Biomineralisation sind noch nicht hinreichend verstanden. Die Mechanismen, mittels derer biomolekulare Modifikatoren, wie Peptide, mit Prä-Nukleations-Strukturen interagieren und somit den Nukleationsprozess von Mineralen beeinflussen könnten, sind vielfältig. Molekulare Simulationen sind zur Analyse der Formation von Prä-Nukleations-Strukturen in Anwesenheit von Modifikatoren gut geeignet. Die vorliegende Arbeit beschreibt einen Ansatz zur Analyse der Interaktion von Peptiden mit den in Lösung befindlichen Bestandteilen der entstehenden Kristalle mit Hilfe von Molekular-Dynamik Simulationen.rnUm informative Simulationen zu ermöglichen, wurde in einem ersten Schritt die Qualität bestehender Kraftfelder im Hinblick auf die Beschreibung von mit Calciumionen interagierenden Oligoglutamaten in wässrigen Lösungen untersucht. Es zeigte sich, dass große Unstimmigkeiten zwischen etablierten Kraftfeldern bestehen, und dass keines der untersuchten Kraftfelder eine realistische Beschreibung der Ionen-Paarung dieser komplexen Ionen widerspiegelte. Daher wurde eine Strategie zur Optimierung bestehender biomolekularer Kraftfelder in dieser Hinsicht entwickelt. Relativ geringe Veränderungen der auf die Ionen–Peptid van-der-Waals-Wechselwirkungen bezogenen Parameter reichten aus, um ein verlässliches Modell für das untersuchte System zu erzielen. rnDas umfassende Sampling des Phasenraumes der Systeme stellt aufgrund der zahlreichen Freiheitsgrade und der starken Interaktionen zwischen Calciumionen und Glutamat in Lösung eine besondere Herausforderung dar. Daher wurde die Methode der Biasing Potential Replica Exchange Molekular-Dynamik Simulationen im Hinblick auf das Sampling von Oligoglutamaten justiert und es erfolgte die Simulation von Peptiden verschiedener Kettenlängen in Anwesenheit von Calciumionen. Mit Hilfe der Sketch-Map Analyse konnten im Rahmen der Simulationen zahlreiche stabile Ionen-Peptid-Komplexe identifiziert werden, welche die Formation von Prä-Nukleations-Strukturen beeinflussen könnten. Abhängig von der Kettenlänge des Peptids weisen diese Komplexe charakteristische Abstände zwischen den Calciumionen auf. Diese ähneln einigen Abständen zwischen den Calciumionen in jenen Phasen von Calcium-Oxalat Kristallen, die in Anwesenheit von Oligoglutamaten gewachsen sind. Die Analogie der Abstände zwischen Calciumionen in gelösten Ionen-Peptid-Komplexen und in Calcium-Oxalat Kristallen könnte auf die Bedeutung von Ionen-Peptid-Komplexen im Prozess der Nukleation und des Wachstums von Biomineralen hindeuten und stellt einen möglichen Erklärungsansatz für die Fähigkeit von Oligoglutamaten zur Beeinflussung der Phase des sich formierenden Kristalls dar, die experimentell beobachtet wurde.

Association between symptoms and quality of life in patients with schizophrenia: a pooled analysis of changes over time

Quality of life is an important outcome in the treatment of patients with schizophrenia. It has been suggested that patients' quality of life ratings (referred to as subjective quality of life, SQOL) might be too heavily influenced by symptomatology to be a valid independent outcome criterion. There has been only limited evidence on the association of symptom change and changes in SQOL over time. This study aimed to examine the association between changes in symptoms and in SQOL among patients with schizophrenia. A pooled data set was obtained from eight longitudinal studies that had used the Brief Psychiatric Rating Scale (BPRS) for measuring psychiatric symptoms and either the Lancashire Quality of Life Profile or the Manchester Short Assessment of Quality of Life for assessing SQOL. The sample comprised 886 patients with schizophrenia. After controlling for heterogeneity of findings across studies using linear mixed models, a reduction in psychiatric symptoms was associated with improvements in SQOL scores. In univariate analyses, changes in all BPRS subscales were associated with changes in SQOL scores. In a multivariate model, only associations between changes in the BPRS depression/anxiety and hostility subscales and changes in SQOL remained significant, with 5% and 0.5% of the variance in SQOL changes being attributable to changes in depression/anxiety and hostility respectively. All BPRS subscales together explained 8.5% of variance. The findings indicate that SQOL changes are influenced by symptom change, in particular in depression/anxiety. The level of influence is limited and may not compromise using SQOL as an independent outcome measure.

Factors influencing subjective quality of life in patients with schizophrenia and other mental disorders: a pooled analysis

Subjective quality of life (SQOL) is an important outcome in the treatment of patients with schizophrenia. However, there is only limited evidence on factors influencing SQOL, and little is known about whether the same factors influence SQOL in patients with schizophrenia and other mental disorders. This study aimed to identify the factors associated with SQOL and test whether these factors are equally important in schizophrenia and other disorders. For this we used a pooled data set obtained from 16 studies that had used either the Lancashire Quality of Life Profile or the Manchester Short Assessment of Quality of Life for assessing SQOL. The sample comprised 3936 patients with schizophrenia, mood disorders, and neurotic disorders. After controlling for confounding factors, within-subject clustering, and heterogeneity of findings across studies in linear mixed models, patients with schizophrenia had more favourable SQOL scores than those with mood and neurotic disorders. In all diagnostic groups, older patients, those in employment, and those with lower symptom scores had higher SQOL scores. Whilst the strength of the association between age and SQOL did not differ across diagnostic groups, symptom levels were more strongly associated with SQOL in neurotic than in mood disorders and schizophrenia. The association of employment and SQOL was stronger in mood and neurotic disorders than in schizophrenia. The findings may inform the use and interpretation of SQOL data for patients with schizophrenia.