Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients

Background: Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods: Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results: We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. Conclusions: The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.

Chronic Pain and Depression in the Quality of Life of Women With Migraine - A Controlled Study

Background. Migraine is comorbid to depression and widespread chronic pain (WCP), but the influence of these conditions on the health-related quality of life (HRQoL) of individuals with episodic (EM) and chronic migraine (CM) is poorly understood. Objective.-To assess the prevalence of depressive symptoms and WCP in individuals with EM and CM, as well as to estimate the joint impact of these conditions on the HRQoL of these individuals. Methods.-All women aged 18 to 65 years with a first diagnosis of EM or CM from September of 2006 to September of 2008 seen in an outpatient headache service were invited to participate. They were asked to attend a separate appointment in the service, and to bring another woman of similar age that also agreed to participate. Depressive symptoms were assessed using the Beck Depression Inventory. Questions about WCP followed the protocol of the American College of Rheumatology. HRQoL was assessed using the Short-Form 36 (SF-36). Multivariate analysis modeled HRQoL as a function of headache status, depressive symptoms, and pain, using quantile regression. Results.-Sample consisted of 179 women, 53 in the EM group, 37 in the CM group and 89 in control group. Groups did not differ by demographics. Mean scores of SF-36 were 53.6 (standard deviation [SD] = 23.5) for EM, 44.2 (SD = 18.5) for CM and 61.8 (SD = 21.5) for controls. In multivariate analysis, SF-36 scores were predicted by a CM status (P =.02; -10.05 [95% CI -18.52; -1.58]) and by a Beck Depression Inventory score (P <.01; -1.27 [95% CI -1.55; -0.99]). The influence of WCP in the SF-36 scores approached significance (P =.08; -0.78 [95% CI -1.64; 0.88]). Age did not contribute to the model. Conclusion.-Women with migraine are at an increased chance of WCP, and the chance increases as a function of headache frequency. Both depressive symptoms and CM independently predict HRQoL status.

The impact of dental caries and trauma in children on family quality of life

Objectives: To assess the impact of childrens dental caries (DC) and traumatic dental injuries (TDI) on parents quality of life (QoL), adjusted by family income. Methods: Parents of 219 children aged 5 and 6 years answered the Family Impact Scale (FIS) on their perception of QoL and data about income. Three calibrated dentists examined the severity of DC according to decayed, missing and filled permanent teeth index, and children were categorized into: 0 = caries free; 15 = low severity; and =6 = high severity. TDI were classified into uncomplicated and complicated injuries. QoL was measured through FIS items and total score, and Poisson regression was used to associate the variables with the outcome. Results: Severity of DC showed a negative impact on the total score and subscales on parental/family activities, parental emotions and financial burden (P < 0.001). TDI showed a negative impact on total score and in some FIS items. The multivariate-adjusted model showed that only the increase in the severity of childrens DC (RR = 3.19; 95% CI = 2.36, 4.31; P < 0.001) was associated with a greater negative impact on parents QoL, while high family income was a protective factor (RR = 0.68; 95% CI = 0.48, 0.95; P < 0.001). Conclusions: The severity of childrens DC has a negative impact on parents QoL, whereas TDI do not. A lower family income might have a negative impact on parents QoL.

Three-feature model to reproduce the topology of citation networks and the effects from authors' visibility on their h-index

Various factors are believed to govern the selection of references in citation networks, but a precise, quantitative determination of their importance has remained elusive. In this paper, we show that three factors can account for the referencing pattern of citation networks for two topics, namely "graphenes" and "complex networks", thus allowing one to reproduce the topological features of the networks built with papers being the nodes and the edges established by citations. The most relevant factor was content similarity, while the other two - in-degree (i.e. citation counts) and age of publication - had varying importance depending on the topic studied. This dependence indicates that additional factors could play a role. Indeed, by intuition one should expect the reputation (or visibility) of authors and/or institutions to affect the referencing pattern, and this is only indirectly considered via the in-degree that should correlate with such reputation. Because information on reputation is not readily available, we simulated its effect on artificial citation networks considering two communities with distinct fitness (visibility) parameters. One community was assumed to have twice the fitness value of the other, which amounts to a double probability for a paper being cited. While the h-index for authors in the community with larger fitness evolved with time with slightly higher values than for the control network (no fitness considered), a drastic effect was noted for the community with smaller fitness. (C) 2012 Elsevier Ltd. All rights reserved.

Exercise Training Restores Cardiac Protein Quality Control in Heart Failure

Exercise training is a well-known coadjuvant in heart failure treatment; however, the molecular mechanisms underlying its beneficial effects remain elusive. Despite the primary cause, heart failure is often preceded by two distinct phenomena: mitochondria dysfunction and cytosolic protein quality control disruption. The objective of the study was to determine the contribution of exercise training in regulating cardiac mitochondria metabolism and cytosolic protein quality control in a post-myocardial infarction-induced heart failure (MI-HF) animal model. Our data demonstrated that isolated cardiac mitochondria from MI-HF rats displayed decreased oxygen consumption, reduced maximum calcium uptake and elevated H2O2 release. These changes were accompanied by exacerbated cardiac oxidative stress and proteasomal insufficiency. Declined proteasomal activity contributes to cardiac protein quality control disruption in our MI-HF model. Using cultured neonatal cardiomyocytes, we showed that either antimycin A or H2O2 resulted in inactivation of proteasomal peptidase activity, accumulation of oxidized proteins and cell death, recapitulating our in vivo model. Of interest, eight weeks of exercise training improved cardiac function, peak oxygen uptake and exercise tolerance in MI-HF rats. Moreover, exercise training restored mitochondrial oxygen consumption, increased Ca2+-induced permeability transition and reduced H2O2 release in MI-HF rats. These changes were followed by reduced oxidative stress and better cardiac protein quality control. Taken together, our findings uncover the potential contribution of mitochondrial dysfunction and cytosolic protein quality control disruption to heart failure and highlight the positive effects of exercise training in re-establishing cardiac mitochondrial physiology and protein quality control, reinforcing the importance of this intervention as a nonpharmacological tool for heart failure therapy.

The consequences of growth hormone-releasing hormone receptor haploinsufficiency for bone quality and insulin resistance

Objective Growth hormone (GH)/insulin-like growth factor (IGF) axis and insulin are key determinants of bone remodelling. Homozygous mutations in the GH-releasing hormone receptor (GHRHR) gene (GHRHR) are a frequent cause of genetic isolated GH deficiency (IGHD). Heterozygosity for GHRHR mutation causes changes in body composition and possibly an increase in insulin sensitivity, but its effects on bone quality are still unknown. The objective of this study was to assess the bone quality and metabolism and its correlation with insulin sensitivity in subjects heterozygous for a null mutation in the GHRHR. Patients and methods A cross-sectional study was performed on 76 normal subjects (68.4% females) (N/N) and 64 individuals (64.1% females) heterozygous for a mutation in the GHRHR (MUT/N). Anthropometric features, quantitative ultrasound (QUS) of the heel, bone markers [osteocalcin (OC) and CrossLaps], IGF-I, glucose and insulin were measured, and homeostasis model assessment of insulin resistance (HOMAIR) was calculated. Results There were no differences in age or height between the two groups, but weight (P = 0.007) and BMI (P = 0.001) were lower in MUT/N. There were no differences in serum levels of IGF-I, glucose, T-score or absolute values of stiffness and OC, but insulin (P = 0.01), HOMAIR (P = 0.01) and CrossLaps (P = 0.01) were lower in MUT/N. There was no correlation between OC and glucose, OC and HOMAIR in the 140 individuals as a whole or in the separate MUT/N or N/N groups. Conclusions This study suggests that one allele mutation in the GHRHR gene has a greater impact on energy metabolism than on bone quality.

Sperm head morphometry in ejaculates of adult marmosets (Callithrix jacchus): a model for studying sperm subpopulations and among-donor variations

In humans and other mammals, sperm morphology has been considered one of the most important predictive parameters of fertility. The objective was to determine the presence and distribution of sperm head morphometric subpopulations in a nonhuman primate model (Callithrix jacchus), using an objective computer analysis system and principal component analysis (PCA) methods to establish the relationship between the subpopulation distribution observed and among-donor variation. The PCA method revealed a stable number of principal components in all donors studied, that represented more than 85% of the cumulative variance in all cases. After cluster analysis, a variable number (from three to seven) sperm morphometric subpopulations were identified with defined sperm dimensions and shapes. There were differences in the distribution of the sperm morphometric subpopulations (P < 0.001) in all ejaculates among the four donors analyzed. In conclusion, in this study, computerized sperm analysis methods combined with PCA cluster analyses were useful to identify, classify, and characterize various head sperm morphometric subpopulations in nonhuman primates, yielding considerable biological information. In addition, because all individuals were kept in the same conditions, differences in the distribution of these subpopulations were not attributed to external or management factors. Finally, the substantial information derived from subpopulation analyses provided new and relevant biological knowledge which may have a practical use for future studies in human and nonhuman primate ejaculates, including identifying individuals more suitable for assisted reproductive technologies. (c) 2012 Elsevier Inc. All rights reserved.

Influence of children's oral health-related quality of life on school performance and school absenteeism

Objective: This study assessed the relation of child oral health-related quality of life with school performance and school absenteeism. Methods: We followed a cross-sectional design with a multistage random sample of 312 12-year-old schoolchildren living in Brazil. The participants completed the child perceptions questionnaire (CPQ1114) that provides information about psychological factors, while their parents or guardians answered questions on their socioeconomic status measured by parents' education level and household income. A dental examination of each child provided information on the prevalence of caries and dental trauma. Data on school performance, which included the results of baseline Brazilian language (Portuguese) tests, and school absenteeism (school days missed) were obtained from the school register. Multilevel linear regression was used to investigate the association among psychological and socioeconomic status and children's school performance. Results: In the multiple model, after adjusting for individual covariates, being a girl was associated with higher school performance (P < 0.05), whereas low household income (P < 0.05), higher mean of CPQ1114 (P < 0.05), and higher school days missed (P < 0.001) were identified as individual determinants of lower school performance. When the school-level covariates were included in the model, the association between subjects' level characteristics and school performance still persisted. Conclusion: Children's school performance and absence were influenced by psychological and socioeconomic conditions.

An integrated approach to remanufacturing: model of a remanufacturing system

Remanufacturing is the process of rebuilding used products that ensures that the quality of remanufactured products is equivalent to that of new ones. Although the theme is gaining ground, it is still little explored due to lack of knowledge, the difficulty of visualizing it systemically, and implementing it effectively. Few models treat remanufacturing as a system. Most of the studies still treated remanufacturing as an isolated process, preventing it from being seen in an integrated manner. Therefore, the aim of this work is to organize the knowledge about remanufacturing, offering a vision of remanufacturing system and contributing to an integrated view about the theme. The methodology employed was a literature review, adopting the General Theory of Systems to characterize the remanufacturing system. This work consolidates and organizes the elements of this system, enabling a better understanding of remanufacturing and assisting companies in adopting the concept.

Loudness scattering due to vibro-acoustic model variability

The use of numerical simulation in the design and evaluation of products performance is ever increasing. To a greater extent, such estimates are needed in a early design stage, when physical prototypes are not available. When dealing with vibro-acoustic models, known to be computationally expensive, a question remains, which is related to the accuracy of such models in view of the well-know variability inherent to the mass manufacturing production techniques. In addition, both academia and industry have recently realized the importance of actually listening to a products sound, either by measurements or by virtual sound synthesis, in order to assess its performance. In this work, the scatter of significant parameter variations on a simplified vehicle vibro-acoustic model is calculated on loudness metrics using Monte Carlo analysis. The mapping from the system parameters to sound quality metric is performed by a fully-coupled vibro-acoustic finite element model. Different loudness metrics are used, including overall sound pressure level expressed in dB and Specific Loudness in Sones. Sound quality equivalent sources are used to excite this model and the sound pressure level at the driver's head position is acquired to be evaluated according to sound quality metrics. No significant variation has been perceived when evaluating the system using regular sound pressure level expressed in in dB and dB(A). This happens because of the third-octave filters that averages the results under some frequency bands. On the other hand, Zwicker Loudness presents important variations, arguably, due to the masking effects.

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.

Pattern-based segmentation of digital documents: model and implementation

This thesis proposes a new document model, according to which any document can be segmented in some independent components and transformed in a pattern-based projection, that only uses a very small set of objects and composition rules. The point is that such a normalized document expresses the same fundamental information of the original one, in a simple, clear and unambiguous way. The central part of my work consists of discussing that model, investigating how a digital document can be segmented, and how a segmented version can be used to implement advanced tools of conversion. I present seven patterns which are versatile enough to capture the most relevant documents’ structures, and whose minimality and rigour make that implementation possible. The abstract model is then instantiated into an actual markup language, called IML. IML is a general and extensible language, which basically adopts an XHTML syntax, able to capture a posteriori the only content of a digital document. It is compared with other languages and proposals, in order to clarify its role and objectives. Finally, I present some systems built upon these ideas. These applications are evaluated in terms of users’ advantages, workflow improvements and impact over the overall quality of the output. In particular, they cover heterogeneous content management processes: from web editing to collaboration (IsaWiki and WikiFactory), from e-learning (IsaLearning) to professional printing (IsaPress).

Assimilation of Meteosat Second Generation (MSG) satellite data in a regional numerical weather prediction model using a one-dimensional variational approach

The quality of temperature and humidity retrievals from the infrared SEVIRI sensors on the geostationary Meteosat Second Generation (MSG) satellites is assessed by means of a one dimensional variational algorithm. The study is performed with the aim of improving the spatial and temporal resolution of available observations to feed analysis systems designed for high resolution regional scale numerical weather prediction (NWP) models. The non-hydrostatic forecast model COSMO (COnsortium for Small scale MOdelling) in the ARPA-SIM operational configuration is used to provide background fields. Only clear sky observations over sea are processed. An optimised 1D–VAR set-up comprising of the two water vapour and the three window channels is selected. It maximises the reduction of errors in the model backgrounds while ensuring ease of operational implementation through accurate bias correction procedures and correct radiative transfer simulations. The 1D–VAR retrieval quality is firstly quantified in relative terms employing statistics to estimate the reduction in the background model errors. Additionally the absolute retrieval accuracy is assessed comparing the analysis with independent radiosonde and satellite observations. The inclusion of satellite data brings a substantial reduction in the warm and dry biases present in the forecast model. Moreover it is shown that the retrieval profiles generated by the 1D–VAR are well correlated with the radiosonde measurements. Subsequently the 1D–VAR technique is applied to two three–dimensional case–studies: a false alarm case–study occurred in Friuli–Venezia–Giulia on the 8th of July 2004 and a heavy precipitation case occurred in Emilia–Romagna region between 9th and 12th of April 2005. The impact of satellite data for these two events is evaluated in terms of increments in the integrated water vapour and saturation water vapour over the column, in the 2 meters temperature and specific humidity and in the surface temperature. To improve the 1D–VAR technique a method to calculate flow–dependent model error covariance matrices is also assessed. The approach employs members from an ensemble forecast system generated by perturbing physical parameterisation schemes inside the model. The improved set–up applied to the case of 8th of July 2004 shows a substantial neutral impact.

Study of the components of quality in SO2-free wines obtained by innovative vinification protocols. Evaluation of the pre-fermentative addition of lysozyme and oenological tannins.

The research performed during the PhD candidature was intended to evaluate the quality of white wines, as a function of the reduction in SO2 use during the first steps of the winemaking process. In order to investigate the mechanism and intensity of interactions occurring between lysozyme and the principal macro-components of musts and wines, a series of experiments on model wine solutions were undertaken, focusing attention on the polyphenols, SO2, oenological tannins, pectines, ethanol, and sugar components. In the second part of this research program, a series of conventional sulphite added vinifications were compared to vinifications in which sulphur dioxide was replaced by lysozyme and consequently define potential winemaking protocols suitable for the production of SO2-free wines. To reach the final goal, the technological performance of two selected yeast strains with a low aptitude to produce SO2 during fermentation were also evaluated. The data obtained suggested that the addition of lysozyme and oenological tannins during the alcoholic fermentation could represent a promising alternative to the use of sulphur dioxide and a reliable starting point for the production of SO2-free wines. The different vinification protocols studied influenced the composition of the volatile profile in wines at the end of the alcoholic fermentation, especially with regards to alcohols and ethyl esters also a consequence of the yeast’s response to the presence or absence of sulphites during fermentation, contributing in different ways to the sensory profiles of wines. In fact, the aminoacids analysis showed that lysozyme can affect the consumption of nitrogen as a function of the yeast strain used in fermentation. During the bottle storage, the evolution of volatile compounds is affected by the presence of SO2 and oenological tannins, confirming their positive role in scaveging oxygen and maintaining the amounts of esters over certain levels, avoiding a decline in the wine’s quality. Even though a natural decrease was found on phenolic profiles due to oxidation effects caused by the presence of oxygen dissolved in the medium during the storage period, the presence of SO2 together with tannins contrasted the decay of phenolic content at the end of the fermentation. Tannins also showed a central role in preserving the polyphenolic profile of wines during the storage period, confirming their antioxidant property, acting as reductants. Our study focused on the fundamental chemistry relevant to the oxidative phenolic spoilage of white wines has demonstrated the suitability of glutathione to inhibit the production of yellow xanthylium cation pigments generated from flavanols and glyoxylic acid at the concentration that it typically exists in wine. The ability of glutathione to bind glyoxylic acid rather than acetaldehyde may enable glutathione to be used as a ‘switch’ for glyoxylic acid-induced polymerisation mechanisms, as opposed to the equivalent acetaldehyde polymerisation, in processes such as microoxidation. Further research is required to assess the ability of glutathione to prevent xanthylium cation production during the in-situ production of glyoxylic acid and in the presence of sulphur dioxide.

Different approaches to identify markers for meat quality and production traits in pigs: analysis of the transcriptome in post mortem skeletal muscle and investigation of candidate genes

Due to the growing attention of consumers towards their food, improvement of quality of animal products has become one of the main focus of research. To this aim, the application of modern molecular genetics approaches has been proved extremely useful and effective. This innovative drive includes all livestock species productions, including pork. The Italian pig breeding industry is unique because needs heavy pigs slaughtered at about 160 kg for the production of high quality processed products. For this reason, it requires precise meat quality and carcass characteristics. Two aspects have been considered in this thesis: the application of the transcriptome analysis in post mortem pig muscles as a possible method to evaluate meat quality parameters related to the pre mortem status of the animals, including health, nutrition, welfare, and with potential applications for product traceability (chapters 3 and 4); the study of candidate genes for obesity related traits in order to identify markers associated with fatness in pigs that could be applied to improve carcass quality (chapters 5, 6, and 7). Chapter three addresses the first issue from a methodological point of view. When we considered this issue, it was not obvious that post mortem skeletal muscle could be useful for transcriptomic analysis. Therefore we demonstrated that the quality of RNA extracted from skeletal muscle of pigs sampled at different post mortem intervals (20 minutes, 2 hours, 6 hours, and 24 hours) is good for downstream applications. Degradation occurred starting from 48 h post mortem even if at this time it is still possible to use some RNA products. In the fourth chapter, in order to demonstrate the potential use of RNA obtained up to 24 hours post mortem, we present the results of RNA analysis with the Affymetrix microarray platform that made it possible to assess the level of expression of more of 24000 mRNAs. We did not identify any significant differences between the different post mortem times suggesting that this technique could be applied to retrieve information coming from the transcriptome of skeletal muscle samples not collected just after slaughtering. This study represents the first contribution of this kind applied to pork. In the fifth chapter, we investigated as candidate for fat deposition the TBC1D1 [TBC1 (tre-2/USP6, BUB2, cdc16) gene. This gene is involved in mechanisms regulating energy homeostasis in skeletal muscle and is associated with predisposition to obesity in humans. By resequencing a fragment of the TBC1D1 gene we identified three synonymous mutations localized in exon 2 (g.40A>G, g.151C>T, and g.172T>C) and 2 polymorphisms localized in intron 2 (g.219G>A and g.252G>A). One of these polymorphisms (g.219G>A) was genotyped by high resolution melting (HRM) analysis and PCR-RFLP. Moreover, this gene sequence was mapped by radiation hybrid analysis on porcine chromosome 8. The association study was conducted in 756 performance tested pigs of Italian Large White and Italian Duroc breeds. Significant results were obtained for lean meat content, back fat thickness, visible intermuscular fat and ham weight. In chapter six, a second candidate gene (tribbles homolog 3, TRIB3) is analyzed in a study of association with carcass and meat quality traits. The TRIB3 gene is involved in energy metabolism of skeletal muscle and plays a role as suppressor of adipocyte differentiation. We identified two polymorphisms in the first coding exon of the porcine TRIB3 gene, one is a synonymous SNP (c.132T> C), a second is a missense mutation (c.146C> T, p.P49L). The two polymorphisms appear to be in complete linkage disequilibrium between and within breeds. The in silico analysis of the p.P49L substitution suggests that it might have a functional effect. The association study in about 650 pigs indicates that this marker is associated with back fat thickness in Italian Large White and Italian Duroc breeds in two different experimental designs. This polymorphisms is also associated with lactate content of muscle semimembranosus in Italian Large White pigs. Expression analysis indicated that this gene is transcribed in skeletal muscle and adipose tissue as well as in other tissues. In the seventh chapter, we reported the genotyping results for of 677 SNPs in extreme divergent groups of pigs chosen according to the extreme estimated breeding values for back fat thickness. SNPs were identified by resequencing, literature mining and in silico database mining. analysis, data reported in the literature of 60 candidates genes for obesity. Genotyping was carried out using the GoldenGate (Illumina) platform. Of the analyzed SNPs more that 300 were polymorphic in the genotyped population and had minor allele frequency (MAF) >0.05. Of these SNPs, 65 were associated (P<0.10) with back fat thickness. One of the most significant gene marker was the same TBC1D1 SNPs reported in chapter 5, confirming the role of this gene in fat deposition in pig. These results could be important to better define the pig as a model for human obesity other than for marker assisted selection to improve carcass characteristics.