Biomedical subjects

F Dominici

Publications and source records attributed to F Dominici.

14 recordsLinked to original sources

PubMed2005

Cortico-motoneuronal output to intrinsic hand muscles is differentially influenced by static changes in shoulder positions.

We investigated whether shoulder position influenced the recruitment properties of the abductor digiti minimi muscle (ADM) and first dorsal interosseous muscle (FDI). ADM and FDI motor evoked potentials (MEPs) in response to transcranial magnetic stimulation (TMS) were obtained in seven healthy volunteers at two different static positions of the shoulder joint (30 degrees adduction vs 30 degrees abduction) while the arm was passively supported at shoulder level (90 degrees in the horizontal plane) and the elbow joint was fixed at 90 degrees . ADM and FDI voluntary activity was also examined during (1) externally paced finger abductions at 2 Hz in the two different shoulder positions (EMG(ADM) and EMG(FDI) was back-averaged time-locked to the end of finger abduction) and (2) maximal voluntary abduction of the little finger and the index finger. Maximal EMG power and force were analysed in the two shoulder positions. H-reflexes from ADM and FDI were also obtained in two subjects. The ADM stimulus-response curve to TMS showed that the slope and plateau level were significantly reduced with the shoulder at 30 degrees abduction. In contrast, the FDI stimulus-response curve to TMS was not influenced by shoulder position. The back-averaged EMG(ADM) showed a significant decrease in peak amplitude and area with the shoulder at 30 degrees abduction, while no change in EMG(FDI) was observed under the same condition. Similarly, maximal EMG(ADM) and force exertion by the little finger were significantly reduced with the shoulder at 30 degrees abduction, while no such effect was observed for FDI. ADM H-reflex, but not FDI, was also decreased with shoulder abduction. These results indicate that the corticospinal pathway to ADM is less accessible to TMS and to voluntary command when the shoulder is placed at 30 degrees abduction. In contrast, activation of FDI, whether by TMS or by volition, is not influenced by shoulder position. This finding suggests that there are differences in the corticospinal innervation to ADM and FDI, possibly due to the different role of these muscles in hand function.

Adult↗

PubMed2005

Fetal growth in Peru: comparisons with international fetal size charts and implications for fetal growth assessment.

OBJECTIVES: To compare fetal biometry measurements obtained in a Peruvian population with reference fetal size charts obtained in Peruvian and non-Peruvian populations. METHODS: Fetal biometry measurements collected prospectively in 195 uncomplicated pregnancies were included in the presented analysis. At 20, 24, 28, 32, 36 and 38 weeks' gestation, fetal head circumference, abdominal circumference and femur diaphysis length were measured. Fetal biometry measurements were compared with fetal size charts obtained from another Peruvian and two non-Peruvian populations from North America and Europe. RESULTS: When compared with ultrasound-based reference fetal size charts obtained from North American and European populations, fetuses from the studied population appeared to grow more slowly with advancing gestational age. This trend was not observed when a Peruvian population, similar to the one studied here, was used as a reference. CONCLUSIONS: The results suggest that fetal growth in this Peruvian population may not be adequately assessed by using reference charts obtained from other populations and have implications for the use of growth standards in antenatal management.

Abdomen↗

PubMed2004

Changes in corticomotor excitability of hand muscles in relation to static shoulder positions.

We examined whether the recruitment properties of the corticospinal pathway to intrinsic hand muscles are influenced by variations of the shoulder joint angle. Abductor digiti minimi (ADM) motor evoked potentials (MEPs) in response to transcranial magnetic stimulation were examined during different static positions of the shoulder joint in the horizontal plane from 30 degrees adduction to 30 degrees abduction with respect to the neutral position at 0 degrees, while elbow and wrist joints were constrained statically at 90 degrees and 180 degrees respectively. We found that 30 degrees abduction of the shoulder significantly depressed MEP size and prolonged MEP latency in comparison with 30 degrees shoulder adduction. The neutral shoulder angle position (at 0 degrees ) significantly reduced MEP size but had no effect on MEP latency in comparison with 30 degrees shoulder abduction. The input-output relationship between MEP size and stimulus intensity was sigmoidal. The plateau value and maximum slope were significantly lower at 30 degrees abduction than at 30 degrees adduction of the shoulder. However, the threshold value did not differ significantly between the two positions. To differentiate excitability changes at cortical versus subcortical sites, intracortical inhibition (ICI) and intracortical facilitation (ICF) were assessed using a paired-magnetic pulse paradigm. A significant decrease in ICF was observed after changing shoulder position from 30 degrees adduction to 30 degrees abduction. In contrast, no variation in the amount of ICI occurred in relation to the same changes in shoulder position. ADM F-waves elicited by electrical stimulation of the ulnar nerve at the wrist were significantly decreased at 30 degrees shoulder abduction in comparison with 30 degrees adduction. A similar pattern was observed in one subject in whom the H-reflex could be exceptionally elicited in ADM. We conclude that shoulder position influences the recruitment efficiency (gain) of the corticospinal volleys to motoneurons of intrinsic hand muscles. It is proposed that activity of peripheral receptors signalling static shoulder position influences corticomotor excitability of hand muscles both at the cortical and at the spinal level. This modulation may be functionally relevant when reaching to grasp objects.

Action Potentials↗

PubMed2003

Insulin-like growth factor 1 (IGF-1) and aging: controversies and new insights.

Insulin/insulin-like growth factor (IGF) signaling plays a major role in the control of aging and life span in invertebrates. Major extension of life span in growth hormone receptor knock out (GHR-KO) mice that are GH resistant, and subsequently, IGF-I-deficient indicates that similar mechanisms may operate in mammals. This conclusion is supported by association of reduced IGF-I levels and delayed aging in three different GH-deficient mutant mice and in animals subjected to caloric restriction, but is difficult to reconcile with neuroprotective effects of IGF-I and with the suspected role of declining GH levels during aging. We suggest that the role of IGF in the regulation of growth and adult body size is important in mediating the effects of longevity genes on aging and life span. Suspected mechanisms of IGF-I action in aging also include reduced insulin signaling, enhanced sensitivity to insulin, and reduced thermogenesis with diminished oxidative damage of macromolecules being the likely final common pathway of these effects. We suspect that IGF-I is important in evolutionarily conserved mechanisms that link life history, including development, reproduction, and aging with availability of energy resources.

Aging↗

PubMed2001

Bayesian semiparametric analysis of developmental toxicology data.

Modeling of developmental toxicity studies often requires simple parametric analyses of the dose-response relationship between exposure and probability of a birth defect but poses challenges because of nonstandard distributions of birth defects for a fixed level of exposure. This article is motivated by two such experiments in which the distribution of the outcome variable is challenging to both the standard logistic model with binomial response and its parametric multistage elaborations. We approach our analysis using a Bayesian semiparametric model that we tailored specifically to developmental toxicology studies. It combines parametric dose-response relationships with a flexible nonparametric specification of the distribution of the response, obtained via a product of Dirichlet process mixtures approach (PDPM). Our formulation achieves three goals: (1) the distribution of the response is modeled in a general way, (2) the degree to which the distribution of the response adapts nonparametrically to the observations is driven by the data, and (3) the marginal posterior distribution of the parameters of interest is available in closed form. The logistic regression model, as well as many of its extensions such as the beta-binomial model and finite mixture models, are special cases. In the context of the two motivating examples and a simulated example, we provide model comparisons, illustrate overdispersion diagnostics that can assist model specification, show how to derive posterior distributions of the effective dose parameters and predictive distributions of response, and discuss the sensitivity of the results to the choice of the prior distribution.

2,4,5-Trichlorophenoxyacetic Acid↗

PubMed2000

Fine particulate air pollution and mortality in 20 U.S. cities, 1987-1994.

BACKGROUND: Air pollution in cities has been linked to increased rates of mortality and morbidity in developed and developing countries. Although these findings have helped lead to a tightening of air-quality standards, their validity with respect to public health has been questioned. METHODS: We assessed the effects of five major outdoor-air pollutants on daily mortality rates in 20 of the largest cities and metropolitan areas in the United States from 1987 to 1994. The pollutants were particulate matter that is less than 10 microm in aerodynamic diameter (PM10), ozone, carbon monoxide, sulfur dioxide, and nitrogen dioxide. We used a two-stage analytic approach that pooled data from multiple locations. RESULTS: After taking into account potential confounding by other pollutants, we found consistent evidence that the level of PM10 is associated with the rate of death from all causes and from cardiovascular and respiratory illnesses. The estimated increase in the relative rate of death from all causes was 0.51 percent (95 percent posterior interval, 0.07 to 0.93 percent) for each increase in the PM10 level of 10 microg per cubic meter. The estimated increase in the relative rate of death from cardiovascular and respiratory causes was 0.68 percent (95 percent posterior interval, 0.20 to 1.16 percent) for each increase in the PM10 level of 10 microg per cubic meter. There was weaker evidence that increases in ozone levels increased the relative rates of death during the summer, when ozone levels are highest, but not during the winter. Levels of the other pollutants were not significantly related to the mortality rate. CONCLUSIONS: There is consistent evidence that the levels of fine particulate matter in the air are associated with the risk of death from all causes and from cardiovascular and respiratory illnesses. These findings strengthen the rationale for controlling the levels of respirable particles in outdoor air.

Air Pollutants↗

PubMed2000

Estimating particulate matter-mortality dose-response curves and threshold levels: an analysis of daily time-series for the 20 largest US cities.

Numerous studies have shown a positive association between daily mortality and particulate air pollution, even at concentrations below regulatory limits. These findings have motivated interest in the shape of the exposure-response relation. The authors have developed flexible modeling strategies for time-series data that include spline and threshold exposure-response models; they apply these models to daily time-series data for the 20 largest US cities for 1987-1994, using the concentration of particulate matter <10 microm in aerodynamic diameter (PM10) as the exposure measure. The spline model showed a linear relation without indication of threshold for PM10 and relative risk of death for all causes and cardiorespiratory causes; by contrast, for other causes, the risk did not increase until approximately 50 microg/m3 PM10. For all-cause mortality, a linear model without threshold was preferred to the threshold model and to the spline model, using the Akaike information criterion (AIC). The findings were similar for cardiovascular and respiratory deaths combined. By contrast, for causes other than cardiovascular and respiratory, a threshold model was more competitive with a threshold value estimated at 65 microg/m3. These findings indicate that linear models without a threshold are appropriate for assessing the effect of particulate air pollution on daily mortality even at current levels.

Air Pollutants↗

PubMed2000

A measurement error model for time-series studies of air pollution and mortality.

One barrier to interpreting the observational evidence concerning the adverse health effects of air pollution for public policy purposes is the measurement error inherent in estimates of exposure based on ambient pollutant monitors. Exposure assessment studies have shown that data from monitors at central sites may not adequately represent personal exposure. Thus, the exposure error resulting from using centrally measured data as a surrogate for personal exposure can potentially lead to a bias in estimates of the health effects of air pollution. This paper develops a multi-stage Poisson regression model for evaluating the effects of exposure measurement error on estimates of effects of particulate air pollution on mortality in time-series studies. To implement the model, we have used five validation data sets on personal exposure to PM10. Our goal is to combine data on the associations between ambient concentrations of particulate matter and mortality for a specific location, with the validation data on the association between ambient and personal concentrations of particulate matter at the locations where data have been collected. We use these data in a model to estimate the relative risk of mortality associated with estimated personal-exposure concentrations and make a comparison with the risk of mortality estimated with measurements of ambient concentration alone. We apply this method to data comprising daily mortality counts, ambient concentrations of PM10measured at a central site, and temperature for Baltimore, Maryland from 1987 to 1994. We have selected our home city of Baltimore to illustrate the method; the measurement error correction model is general and can be applied to other appropriate locations.Our approach uses a combination of: (1) a generalized additive model with log link and Poisson error for the mortality-personal-exposure association; (2) a multi-stage linear model to estimate the variability across the five validation data sets in the personal-ambient-exposure association; (3) data augmentation methods to address the uncertainty resulting from the missing personal exposure time series in Baltimore. In the Poisson regression model, we account for smooth seasonal and annual trends in mortality using smoothing splines. Taking into account the heterogeneity across locations in the personal-ambient-exposure relationship, we quantify the degree to which the exposure measurement error biases the results toward the null hypothesis of no effect, and estimate the loss of precision in the estimated health effects due to indirectly estimating personal exposures from ambient measurements.

Journal Article↗

PubMed2000

Combining contingency tables with missing dimensions.

We propose a methodology for estimating the cell probabilities in a multiway contingency table by combining partial information from a number of studies when not all of the variables are recorded in all studies. We jointly model the full set of categorical variables recorded in at least one of the studies, and we treat the variables that are not reported as missing dimensions of the study-specific contingency table. For example, we might be interested in combining several cohort studies in which the incidence in the exposed and nonexposed groups is not reported for all risk factors in all studies while the overall numbers of cases and cohort size is always available. To account for study-to-study variability, we adopt a Bayesian hierarchical model. At the first stage of the model, the observation stage, data are modeled by a multinomial distribution with fixed total number of observations. At the second stage, we use the logistic normal (LN) distribution to model variability in the study-specific cells' probabilities. Using this model and data augmentation techniques, we reconstruct the contingency table for each study regardless of which dimensions are missing, and we estimate population parameters of interest. Our hierarchical procedure borrows strength from all the studies and accounts for correlations among the cells' probabilities. The main difficulty in combining studies recording different variables is in maintaining a consistent interpretation of parameters across studies. The approach proposed here overcomes this difficulty and at the same time addresses the uncertainty arising from the missing dimensions. We apply our modeling strategy to analyze data on air pollution and mortality from 1987 to 1994 for six U.S. cities by combining six cross-classifications of low, medium, and high levels of mortality counts, particulate matter, ozone, and carbon monoxide with the complication that four of the six cities do not report all the air pollution variables. Our goals are to investigate the association between air pollution and mortality by reconstructing the tables with missing dimensions, to determine the most harmful pollutant combinations, and to make predictions about these key issues for a city other than the six sampled. We find that, for high levels of ozone and carbon monoxide, the number of cases with a high number of deaths increases as the levels of particulate matter, PM10, increases and that the most harmful combinations corresponds to high levels of PM10, confirming prior findings that levels of PM10 higher than the NAAQS standard are harmful.

Air Pollution↗

PubMed2000

Exposure measurement error in time-series studies of air pollution: concepts and consequences.

Misclassification of exposure is a well-recognized inherent limitation of epidemiologic studies of disease and the environment. For many agents of interest, exposures take place over time and in multiple locations; accurately estimating the relevant exposures for an individual participant in epidemiologic studies is often daunting, particularly within the limits set by feasibility, participant burden, and cost. Researchers have taken steps to deal with the consequences of measurement error by limiting the degree of error through a study's design, estimating the degree of error using a nested validation study, and by adjusting for measurement error in statistical analyses. In this paper, we address measurement error in observational studies of air pollution and health. Because measurement error may have substantial implications for interpreting epidemiologic studies on air pollution, particularly the time-series analyses, we developed a systematic conceptual formulation of the problem of measurement error in epidemiologic studies of air pollution and then considered the consequences within this formulation. When possible, we used available relevant data to make simple estimates of measurement error effects. This paper provides an overview of measurement errors in linear regression, distinguishing two extremes of a continuum-Berkson from classical type errors, and the univariate from the multivariate predictor case. We then propose one conceptual framework for the evaluation of measurement errors in the log-linear regression used for time-series studies of particulate air pollution and mortality and identify three main components of error. We present new simple analyses of data on exposures of particulate matter < 10 microm in aerodynamic diameter from the Particle Total Exposure Assessment Methodology Study. Finally, we summarize open questions regarding measurement error and suggest the kind of additional data necessary to address them.

Air Pollution↗

PubMed2000

The National Morbidity, Mortality, and Air Pollution Study. Part I: Methods and methodologic issues.

The Health Effects Institute, established in 1980, is an independent and unbiased source of information on the health effects of motor vehicle emissions. HEI supports research on all major pollutants, including regulated pollutants (such as carbon monoxide, ozone, nitrogen dioxide, and particulate matter) and unregulated pollutants (such as diesel engine exhaust, methanol, and aldehydes). To date, HEI has supported more than 200 projects at institutions in North America and Europe and has published over 100 research reports. Typically, HEI receives half its funds from the US Environmental Protection Agency and half from 28 manufacturers and marketers of motor vehicles and engines in the US. Occasionally, funds from other public and private organizations either support special projects or provide resources for a portion of an HEI study. Regardless of funding sources, HEI exercises complete autonomy in setting its research priorities and in reaching its conclusions. An independent Board of Directors governs HEI. The Institute's Research and Review Committees serve complementary scientific purposes and draw distinguished scientists as members. The results of HEI-funded studies are made available as Research Reports, which contain both the Investigators' Report and the Review Committee's evaluation of the work's scientific quality and regulatory relevance.

Air Pollutants↗

PubMed2000

The National Morbidity, Mortality, and Air Pollution Study. Part II: Morbidity and mortality from air pollution in the United States.

BACKGROUND: Epidemiologic time-series studies conducted in a number of cities have identified, in general, an association between daily changes in concentration of ambient particulate matter (PM) and daily number of deaths (mortality). Increased hospitalization (a measure of morbidity) among the elderly for specific causes has also been associated with PM. These studies have raised concerns about public health effects of particulate air pollution and have contributed to regulatory decisions in the United States. However, scientists have pointed out uncertainties that raise questions about the interpretation of these studies. One limitation to previous time-series studies of PM and adverse health effects is that the evidence for an association is derived from studies conducted in single locations using diverse analytic methods. Statistical procedures have been used to combine the results of these single location studies in order to produce a summary estimate of the health effects of PM. Difficulties with this approach include the process by which cities were selected to be studied, the different analytic methods applied to each single study, and the variety of methods used to measure or account for variables included in the analysis. These individual studies were also not able to account for the effects of gaseous air pollutants in a systematic manner.

Adolescent↗

PubMed1999

Harvesting-resistant estimates of air pollution effects on mortality.

A number of studies have recently shown an association between particle concentrations in outdoor air and daily mortality counts in urban locations. In the public health interpretation of this evidence, a key issue is whether the increased mortality associated with higher pollution levels is restricted to very frail persons for whom life expectancy is short in the absence of pollution. This possibility has been termed the "harvesting hypothesis." We present an approach to estimating the association between pollution and mortality from times series data that is resistant to short-term harvesting. The method is based in the concept that harvesting alone creates associations only at shorter time scales. We use frequency domain log-linear regression to decompose the information about the pollution-mortality association into distinct time scales, and we then create harvesting-resistant estimates by excluding the short-term information that is affected by harvesting. We illustrate the methods with total suspended particles and mortality counts from Philadelphia for 1974-1988. The total suspended particles-mortality association in Philadelphia is inconsistent with the harvesting-only hypothesis, and the harvesting-resistant estimates of the total suspended particles relative risk are actually larger-not smaller-than the ordinary estimates.

Air Pollution↗

PubMed1998

Testing simultaneous hypotheses in pharmaceutical trials: a Bayesian approach.

The purpose of this paper is to compare the Bayes factor and the likelihood ratio test in a pharmaceutical trial where the two treatments are a new drug and a control (a positive control or a placebo). The goal is to jointly answer the questions (1) is the new drug or the control toxic? (2) Is the new drug more effective and safer than the control? We consider a bivariate model where each treatment is characterized by a target effect (a continuous primary response y) and by a side effect (a continuous supplementary response xi). Using a Bayesian approach, we account for the uncertainty resulting from prediction of the side effect, by making use of the physician's prior inputs about the target-toxicity relationship and the maximum tolerated target effects that are considered to be safe. Finally, we consider an example about a sleeplessness drug, and we show that the Bayes factor provides a more flexible and informative tool than the likelihood ratio test in simultaneous testing. Advantages are greater when the number of experimental subjects is small.

Anti-Anxiety Agents↗