980 resultados para sample range
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OBJECTIVE: to assess the levels and determinants of interleukin (IL)-1ß, IL-6, tumour necrosis factor (TNF)-a and C-reactive protein (CRP) in a healthy Caucasian population.METHODS: population sample of 2884 men and 3201 women aged 35 to 75. IL-1ß, IL-6 and TNF-a were assessed by a multiplexed particle-based flow cytometric assay and CRP by an immunometric assay.RESULTS: Spearman rank correlations between duplicate cytokine measurements (N?=?80) ranged between 0.89 and 0.96; intra-class correlation coefficients ranged between 0.94 and 0.97, indicating good reproducibility. Among the 6085 participants, 2289 (37.6%), 451 (7.4%) and 43 (0.7%) had IL-1ß, IL-6 and TNF-a levels below detection limits, respectively. Median (interquartile range) for participants with detectable values were 1.17 (0.48-3.90) pg/ml for IL-1ß; 1.47 (0.71-3.53) pg/ml for IL-6; 2.89 (1.82-4.53) pg/ml for TNF-a and 1.3 (0.6-2.7) ng/ml for CRP. On multivariate analysis, greater age was the only factor inversely associated with IL-1ß levels. Male sex, increased BMI and smoking were associated with greater IL-6 levels, while no relationship was found for age and leisure-time PA. Male sex, greater age, increased BMI and current smoking were associated with greater TNF-a levels, while no relationship was found with leisure-time PA. CRP levels were positively related to age, BMI and smoking, and inversely to male sex and physical activity.CONCLUSION: Population-based levels of several cytokines were established. Increased age and BMI, and to a lesser degree sex and smoking, significantly and differentially impact cytokine levels, while leisure-time physical activity has little effect.
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A wide range of modelling algorithms is used by ecologists, conservation practitioners, and others to predict species ranges from point locality data. Unfortunately, the amount of data available is limited for many taxa and regions, making it essential to quantify the sensitivity of these algorithms to sample size. This is the first study to address this need by rigorously evaluating a broad suite of algorithms with independent presence-absence data from multiple species and regions. We evaluated predictions from 12 algorithms for 46 species (from six different regions of the world) at three sample sizes (100, 30, and 10 records). We used data from natural history collections to run the models, and evaluated the quality of model predictions with area under the receiver operating characteristic curve (AUC). With decreasing sample size, model accuracy decreased and variability increased across species and between models. Novel modelling methods that incorporate both interactions between predictor variables and complex response shapes (i.e. GBM, MARS-INT, BRUTO) performed better than most methods at large sample sizes but not at the smallest sample sizes. Other algorithms were much less sensitive to sample size, including an algorithm based on maximum entropy (MAXENT) that had among the best predictive power across all sample sizes. Relative to other algorithms, a distance metric algorithm (DOMAIN) and a genetic algorithm (OM-GARP) had intermediate performance at the largest sample size and among the best performance at the lowest sample size. No algorithm predicted consistently well with small sample size (n < 30) and this should encourage highly conservative use of predictions based on small sample size and restrict their use to exploratory modelling.
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OBJECTIVES:: For certain major operations, inpatient mortality risk is lower in high-volume hospitals than those in low-volume hospitals. Extending the analysis to a broader range of interventions and outcomes is necessary before adopting policies based on minimum volume thresholds. METHODS:: Using the United States 2004 Nationwide Inpatient Sample, we assessed the effect of intervention-specific and overall hospital volume on surgical complications, potentially avoidable reoperations, and deaths across 1.4 million interventions in 353 hospitals. Outcome variations across hospitals were analyzed through a 3-level hierarchical logistic regression model (patients, surgical interventions, and hospitals), which took into account interventions on multiple organs, 144 intervention categories, and structural hospital characteristics. Discriminative performance and calibration were good. RESULTS:: Hospitals with more experience in a given intervention had similar reoperation rates but lower mortality and complication rates: odds ratio per volume deciles 0.93 and 0.97. However, the benefit was limited to heart surgery and a small number of other operations. Risks were higher for hospitals that performed more interventions overall: odds ratio per 1000 for each event was approximately 1.02. Even after adjustment for specific volume, mortality varied substantially across both high- and low-volume hospitals. CONCLUSION:: Although the link between specific volume and certain inpatient outcomes suggests that specialization might help improve surgical safety, the variable magnitude of this link and the heterogeneity of hospital effect do not support the systematic use of volume-based referrals. It may be more efficient to monitor risk-adjusted postoperative outcomes and to investigate facilities with worse than expected outcomes.
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ABSTRACT: BACKGROUND: The Psychiatric arm of the population-based CoLaus study (PsyCoLaus) is designed to: 1) establish the prevalence of threshold and subthreshold psychiatric syndromes in the 35 to 66 year-old population of the city of Lausanne (Switzerland); 2) test the validity of postulated definitions for subthreshold mood and anxiety syndromes; 3) determine the associations between psychiatric disorders, personality traits and cardiovascular diseases (CVD), 4) identify genetic variants that can modify the risk for psychiatric disorders and determine whether genetic risk factors are shared between psychiatric disorders and CVD. This paper presents the method as well as somatic and sociodemographic characteristics of the sample. METHODS: All 35 to 66 year-old persons previously selected for the population-based CoLaus survey on risk factors for CVD were asked to participate in a substudy assessing psychiatric conditions. This investigation included the Diagnostic Interview for Genetic Studies to elicit diagnostic criteria for threshold disorders according to DSM-IV and algorithmically defined subthreshold syndromes. Complementary information was gathered on potential risk and protective factors for psychiatric disorders, migraine and on the morbidity of first-degree family members, whereas the collection of DNA and plasma samples was part of the original somatic study (CoLaus). RESULTS: A total of 3,691 individuals completed the psychiatric evaluation (67% participation). The gender distribution of the sample did not differ significantly from that of the general population in the same age range. Although the youngest 5-year band of the cohort was underrepresented and the oldest 5-year band overrepresented, participants of PsyCoLaus and individuals who refused to participate revealed comparable scores on the General Health Questionnaire, a self-rating instrument completed at the somatic exam. CONCLUSIONS: Despite limitations resulting from the relatively low participation in the context of a comprehensive and time-consuming investigation, the PsyCoLaus study should significantly contribute to the current understanding of psychiatric disorders and comorbid somatic conditions by: 1) establishing the clinical relevance of specific psychiatric syndromes below the DSM-IV threshold; 2) determining comorbidity between risk factors for CVD and psychiatric disorders; 3) assessing genetic variants associated with common psychiatric disorders and 4) identifying DNA markers shared between CVD and psychiatric disorders.
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Forensic Anthropology and Bioarchaeology studies depend critically on the accuracy and reliability of age-estimation techniques. In this study we have evaluated two age-estimation methods for adults based on the pubic symphysis (Suchey-Brooks) and the auricular surface (Buckberry-Chamberlain) in a current sample of 139 individuals (67 women and 72 men) from Madrid in order to verify the accuracy of both methods applied to a sample of innominate bones from the central Iberian Peninsula. Based on the overall results of this study, the Buckberry-Chamberlain method seems to be the method that provides better estimates in terms of accuracy (percentage of hits) and absolute difference to the chronological age taking into account the total sample. The percentage of hits and mean absolute difference of the Buckberry-Chamberlain and Suchey-Brooks methods are 97.3% and 11.24 years, and 85.7% and 14.38 years, respectively. However, this apparently greater applicability of the Buckberry-Chamberlain method is mainly due to the broad age ranges provided. Results indicated that Suchey-Brooks method is more appropriate for populations with a majority of young individuals, whereas Buckberry-Chamberlain method is recommended for populations with a higher percentage of individuals in the range 60-70 years. These different age estimation methodologies significantly influence the resulting demographic profile, consequently affecting the biological characteristics reconstruction of the samples in which they are applied.
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BACKGROUND: Alcohol consumption--in particular drinking volume (DV) and risky single occasion drinking (RSOD)--has been related to a wide range of negative consequences and health problems. Previous studies also suggested that drinking in certain locations may be more strongly associated with the occurrence of alcohol-related harm than drinking in others. However, they were conducted in countries culturally and legally different from European countries and were limited to cross-sectional designs. This study investigates the cross-sectional and longitudinal associations of alcohol-related harm with DVs in different locations in a sample of young Swiss men. METHODS: A representative sample of 4536 young Swiss male drinkers completed baseline and 15-month follow-up questionnaires. These assessed DVs in 11 locations, alcohol-related harm (i.e. number of alcohol-related consequences and alcohol use disorder criteria) and frequency of RSOD. Cross-sectional and longitudinal associations of alcohol-related harm with DVs in each location were tested using regression models, with and without adjustment for frequency of RSOD. RESULTS: Both cross-sectional and longitudinal analyses showed significant positive associations between alcohol-related harm and DVs at friends' homes, in discos/nightclubs and in outdoor public places, when controlling for frequency of RSOD. In contrast, the contribution of DVs at one's own home and in restaurants was consistently not significant when adjusted for frequency of RSOD. When controlling for RSOD, associations between alcohol-related harm and DVs in bars/pubs, when playing sports, during other leisure activities, at cinemas/theatres, during sporting events, and during special events were not consistent between cross-sectional and longitudinal analyses. CONCLUSION: Results suggest that prevention interventions should not only target reducing the overall volume of alcohol consumed and the frequency of RSOD in general, but they should additionally focus on limiting alcohol consumption in outdoor public places, discos/nightclubs, and in friends' homes in particular, or at least on preventing harm occurring in these occasions.
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A direct, extraction-free spectrophotometric method has been developed for the determination of acebutolol hydrochloride (ABH) in pharmaceutical preparations. The method is based on ion-pair complex formation between the drug and two acidic dyes (sulphonaphthalein) namely bromocresol green (BCG) and bromothymol blue (BTB). Conformity to Beer's law enabled the assay of the drug in the range of 0.5-13.8 µg mL-1 with BCG and 1.8-15.9 µg mL-1 with BTB. Compared with a reference method, the results obtained were of equal accuracy and precision. In addition, these methods were also found to be specific for the analysis of acebutolol hydrochloride in the presence of excipients, which are co-formulated in the drug.
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The nature of this research is to investigate paleoseismic deformation of glacial soft sediments from three sampling sites throughout the Scottish Highlands; Arrat's Mills, Meikleour and Glen Roy. The paleoseismic evidence investigated in this research will provide a basis for applying criteria to soft sediment deformation structures, and the trigger mechanisms that create these structures. Micromorphology is the tool used in this to investigate paleoseismic deformation structures in thin section. Thin section analysis, (micromorphology) of glacial sediments from the three sampling sites is used to determine microscale evidence of past earthquakes that can be correlated to modem-day events and possibly lead to a better understanding of the impact of earthquakes throughout a range of sediment types. The significance of the three sampling locations is their proximity to two major active fault zones that cross Scotland. The fault zones are the Highland Boundary Fault and the Great Glen Fault, these two major faults that parallel each other and divide the country in half Sims (1975) used a set of seven criteria that identified soft sediment deformation structures created by a magnitude six earthquake in Cahfomia. Using criteria set forth by Sims (1975), the paleoseismic evidence can be correlated to the magnitude of the deformation structures found in the glacial sediments. This research determined that the microstructures at Arrat's Mill, Meikleour and Glen Roy are consistent with a seismically induced origin. It has also been demonstrated that, even without the presence of macrostructures, the use of micromorphology techniques in detecting such activity within sediments is of immense value.
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Light brown sediment with clasts ranging from small to medium in size. The clast shape ranges from sub-angular to sub-rounded. Lineations are abundant throughout the sample. Light folding structures can also be seen in this sample. There are minor amounts of grain crushing/stacking also present.
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A wide range of tests for heteroskedasticity have been proposed in the econometric and statistics literature. Although a few exact homoskedasticity tests are available, the commonly employed procedures are quite generally based on asymptotic approximations which may not provide good size control in finite samples. There has been a number of recent studies that seek to improve the reliability of common heteroskedasticity tests using Edgeworth, Bartlett, jackknife and bootstrap methods. Yet the latter remain approximate. In this paper, we describe a solution to the problem of controlling the size of homoskedasticity tests in linear regression contexts. We study procedures based on the standard test statistics [e.g., the Goldfeld-Quandt, Glejser, Bartlett, Cochran, Hartley, Breusch-Pagan-Godfrey, White and Szroeter criteria] as well as tests for autoregressive conditional heteroskedasticity (ARCH-type models). We also suggest several extensions of the existing procedures (sup-type of combined test statistics) to allow for unknown breakpoints in the error variance. We exploit the technique of Monte Carlo tests to obtain provably exact p-values, for both the standard and the new tests suggested. We show that the MC test procedure conveniently solves the intractable null distribution problem, in particular those raised by the sup-type and combined test statistics as well as (when relevant) unidentified nuisance parameter problems under the null hypothesis. The method proposed works in exactly the same way with both Gaussian and non-Gaussian disturbance distributions [such as heavy-tailed or stable distributions]. The performance of the procedures is examined by simulation. The Monte Carlo experiments conducted focus on : (1) ARCH, GARCH, and ARCH-in-mean alternatives; (2) the case where the variance increases monotonically with : (i) one exogenous variable, and (ii) the mean of the dependent variable; (3) grouped heteroskedasticity; (4) breaks in variance at unknown points. We find that the proposed tests achieve perfect size control and have good power.
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We work out a semiclassical theory of shot noise in ballistic n+-i-n+ semiconductor structures aiming at studying two fundamental physical correlations coming from Pauli exclusion principle and long-range Coulomb interaction. The theory provides a unifying scheme which, in addition to the current-voltage characteristics, describes the suppression of shot noise due to Pauli and Coulomb correlations in the whole range of system parameters and applied bias. The whole scenario is summarized by a phase diagram in the plane of two dimensionless variables related to the sample length and contact chemical potential. Here different regions of physical interest can be identified where only Coulomb or only Pauli correlations are active, or where both are present with different relevance. The predictions of the theory are proven to be fully corroborated by Monte Carlo simulations.
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This paper presents a case study to illustrate the range of decisions involved in designing a sampling strategy for a complex, longitudinal research study. It is based on experience from the Young Lives project and identifies the approaches used to sample children for longitudinal follow-up in four less developed countries (LDCs). The rationale for decisions made and the resulting benefits, and limitations, of the approaches adopted are discussed. Of particular importance is the choice of sampling approach to yield useful analysis; specific examples are presented of how this informed the design of the Young Lives sampling strategy.
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This paper presents practical approaches to the problem of sample size re-estimation in the case of clinical trials with survival data when proportional hazards can be assumed. When data are readily available at the time of the review, on a full range of survival experiences across the recruited patients, it is shown that, as expected, performing a blinded re-estimation procedure is straightforward and can help to maintain the trial's pre-specified error rates. Two alternative methods for dealing with the situation where limited survival experiences are available at the time of the sample size review are then presented and compared. In this instance, extrapolation is required in order to undertake the sample size re-estimation. Worked examples, together with results from a simulation study are described. It is concluded that, as in the standard case, use of either extrapolation approach successfully protects the trial error rates. Copyright © 2012 John Wiley & Sons, Ltd.
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The detection of long-range dependence in time series analysis is an important task to which this paper contributes by showing that whilst the theoretical definition of a long-memory (or long-range dependent) process is based on the autocorrelation function, it is not possible for long memory to be identified using the sum of the sample autocorrelations, as usually defined. The reason for this is that the sample sum is a predetermined constant for any stationary time series; a result that is independent of the sample size. Diagnostic or estimation procedures, such as those in the frequency domain, that embed this sum are equally open to this criticism. We develop this result in the context of long memory, extending it to the implications for the spectral density function and the variance of partial sums of a stationary stochastic process. The results are further extended to higher order sample autocorrelations and the bispectral density. The corresponding result is that the sum of the third order sample (auto) bicorrelations at lags h,k≥1, is also a predetermined constant, different from that in the second order case, for any stationary time series of arbitrary length.
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The self-assembly of proteins and peptides into b-sheet-rich amyloid fibers is a process that has gained notoriety because of its association with human diseases and disorders. Spontaneous self-assembly of peptides into nonfibrillar supramolecular structures can also provide a versatile and convenient mechanism for the bottom-up design of biocompatible materials with functional properties favoring a wide range of practical applications.[1] One subset of these fascinating and potentially useful nanoscale constructions are the peptide nanotubes, elongated cylindrical structures with a hollow center bounded by a thin wall of peptide molecules.[2] A formidable challenge in optimizing and harnessing the properties of nanotube assemblies is to gain atomistic insight into their architecture, and to elucidate precisely how the tubular morphology is constructed from the peptide building blocks. Some of these fine details have been elucidated recently with the use of magic-angle-spinning (MAS) solidstate NMR (SSNMR) spectroscopy.[3] MAS SSNMR measurements of chemical shifts and through-space interatomic distances provide constraints on peptide conformation (e.g., b-strands and turns) and quaternary packing. We describe here a new application of a straightforward SSNMR technique which, when combined with FTIR spectroscopy, reports quantitatively on the orientation of the peptide molecules within the nanotube structure, thereby providing an additional structural constraint not accessible to MAS SSNMR.