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PubMed2005

Evidence for white matter abnormalities in schizophrenia.

PURPOSE OF REVIEW: The purpose of this review is to highlight important recent imaging, histological, and genetic findings relevant to white matter abnormalities in schizophrenia. It is cast within the context of research findings conducted over the last 5 years, where we analyze their importance in understanding schizophrenia, as well as discuss future directions for research. RECENT FINDINGS: White matter abnormalities have long been hypothesized in schizophrenia, although only recently has it become possible to investigate them more closely. This has come about as a result of advances in neuroimaging, including new imaging techniques sensitive to white matter structure, as well as advances in computer science, with new analysis techniques making it possible to evaluate several interconnected brain regions at a time. Postmortem studies, with advances such as fluoroscopy and electron microscopy, have also led to quantifying populations of different brain cells, including myelin-forming oligodendrocytes. Moreover, molecular studies enable examination of immunoreactivity of proteins that are responsible for building myelin sheaths. Additionally, microarray genetic studies allow us to investigate myelin-related genes in schizophrenia. Taken together, these technological advances bring us closer to understanding white matter pathology in schizophrenia. SUMMARY: Advances in new imaging techniques likely account for the renewed interest in investigating white matter abnormalities in schizophrenia, with over 30 new articles published on this topic in the last 12 months, compared with 11 the year before. We review recent imaging, histological, and genetic findings that suggest white matter abnormalities in schizophrenia.

Journal Article↗
PubMed1993

Medical imaging databases. A National Institutes of Health workshop.

Development and implementation of a medical imaging database in a PACS-type environment that integrates all the patient data will impact directly on the quality of patient care. In addition, access to the wealth of information that is simply not accessible through the current technology, will contribute to improved disease detection and improved patient treatment, as well as produce significant new medical knowledge. Research and implementations must proceed in interdisciplinary environments which successfully combine the expertise and knowledge from the medical community with that of the database and computer science disciplines.

Database Management Systems↗
PubMed2000

Comparisons of four methods of estimating physical activity in adult women.

PURPOSE: To compare four different methods of measuring physical activity (PA) in adult women under free-living conditions. METHODS: Twelve women participated in a 7-d period during which PA was assessed via self-report, accelerometry and step-counting. Subjects wore at the waist a Tritrac-R3D accelerometer, a Computer Science Application Inc. activity monitor (CSA), both of which measure bodily accelerations in various planes, and a Yamax Digi-Walker-500 that records steps. After the 7-d period subjects responded to a 7-d Physical Activity Recall interview (PAR). RESULTS: Physical activity-related energy expenditure (PAEE) determined from PAR was significantly higher than PAEE estimated from either the Tritrac, CSA, or the Yamax data. Time spent in light, moderate, and hard physical activity was not significantly different between PAR, CSA, and Tritrac. Log-transformed activity counts from CSA were highly correlated with log-transformed Tritrac results (r > 0.90). Number of steps recorded by the Yamax was significantly correlated with untransformed Tritrac and CSA results. CONCLUSIONS: Based upon comparisons with PAR, Tritrac, CSA, and Yamax underestimate the amount of PAEE by 25, 46, and 48%, respectively. The correspondence between the Tritrac and CSA results suggests that both devices produce similar estimates of bodily movement in free-living women. The relationships among results for Tritrac, CSA, and Yamax indicate that the number of steps recorded by the Yamax is representative of the amount of physical activity performed during the day as estimated by Tritrac and CSA. These results should be useful when selecting a method to measure PA in individuals under free-living conditions.

Activities of Daily Living↗
PubMed2000

Activity and immobilization after eccentric exercise: II. Serum CK.

PURPOSE: The purpose of the present study was to examine the effect of muscle activity level on serum creatine kinase (CK) activity after high-force eccentric exercise of the elbow flexors. METHODS: Twenty-six male volunteers were randomly assigned to one of three groups for a 4-d treatment period after exercise: immobilization (N = 9), control (N = 8), and light exercise (N = 9). During the treatment period, the immobilization group had their arm casted and supported in a sling at 90 degrees. The control group had no restriction of their arm activity. The light exercise group performed a daily exercise regimen of 50 biceps curls with a 5-lb dumbbell. Serum CK activity was obtained by venipuncture for three consecutive days before eccentric exercise and during the 4-d treatment period. To quantify activity of the arm, CSA (Computer Science and Applications, Inc.) activity-monitoring devices were worn. RESULTS: Serum CK measurements revealed that there was a significant group by time interaction in the analysis of variance (P < 0.05). Peak serum CK activity of the immobilized group (668 IU) was lower than either the control (4230 IU) or light exercise (2740 IU) group. During the treatment period, activity level among the three groups was significantly different from each other (P < 0.001): 529 counts x min(-1) for the immobilization group, 944 counts x min(-1) for the control group, and 1334 counts x min(-1) for the light exercise group. CONCLUSIONS: These results suggest that immobilization of exercised damaged muscle during recovery significantly blunted serum CK activity, which may be due to attenuated removal of CK from the muscle and/or decrease lymphatic transport.

Adult↗
PubMed2000

Validity of accelerometry for the assessment of moderate intensity physical activity in the field.

PURPOSE: This study was undertaken to examine the validity of accelerometry in assessing moderate intensity physical activity in the field and to evaluate the metabolic cost of various recreational and household activities. METHODS: Twenty-five subjects completed four bouts of overground walking at a range of self-selected speeds, played two holes of golf, and performed indoor (window washing, dusting, vacuuming) and outdoor (lawn mowing, planting shrubs) household tasks. Energy expenditure was measured using a portable metabolic system, and motion was recorded using a Yamax Digiwalker pedometer (walking only), a Computer Science and Application, Inc. (CSA) accelerometer, and a Tritrac accelerometer. Correlations between accelerometer counts and energy cost were examined. In addition, individual equations to predict METs from counts were developed from the walking data and applied to the other activities to compare the relationships between counts and energy cost. RESULTS: Observed MET levels differed from values reported in the Compendium of Physical Activities, although all activities fell in the moderate intensity range. Relationships between counts and METs were stronger for walking (CSA, r = 0.77; Tritrac, r = 0.89) than for all activities combined (CSA, r = 0.59; Tritrac, r = 0.62). Metabolic costs of golf and the household activities were underestimated by 30-60% based on the equations derived from level walking. CONCLUSION: The count versus METs relationship for accelerometry was found to be dependent on the type of activity performed, which may be due to the inability of accelerometers to detect increased energy cost from upper body movement, load carriage, or changes in surface or terrain. This may introduce error in attempts to use accelerometry to assess point estimates of physical activity energy expenditure in free-living situations.

Activities of Daily Living↗
PubMed2000

Estimation of energy expenditure using CSA accelerometers at hip and wrist sites.

PURPOSE: This study was designed to establish prediction models that relate hip and wrist accelerometer data to energy expenditure (EE) in field and laboratory settings. We also sought to determine whether the addition of a wrist accelerometer would significantly improve the prediction of EE (METs), compared with a model that used a hip accelerometer alone. METHODS: Seventy participants completed one to six activities within the categories of yardwork, housework, family care, occupation, recreation, and conditioning, for a total of 5 to 12 participants tested per activity. EE was measured using the Cosmed K4b2 portable metabolic system. Simultaneously, two Computer Science and Applications, Inc. (CSA) accelerometers (model 7164), one worn on the wrist and one worn on the hip, recorded body movement. Correlations between EE measured by the Cosmed and the counts recorded by the CSA accelerometers were calculated, and regression equations were developed to predict EE from the CSA data. RESULTS: The wrist, hip, and combined hip and wrist regression equations accounted for 3.3%, 31.7%, and 34.3% of the variation in EE, respectively. The addition of the wrist accelerometer data to the hip accelerometer data to form a bivariate regression equation, although statistically significant (P = 0.002), resulted in only a minor improvement in prediction of EE. Cut points for 3 METs (574 hip counts), 6 METs (4945 hip counts), and 9 METs (9317 hip counts) were also established. CONCLUSION: The small amount of additional accuracy gained from the wrist accelerometer is offset by the extra time required to analyze the data and the cost of the accelerometer.

Adult↗
PubMed2000

Validity of four motion sensors in measuring moderate intensity physical activity.

PURPOSE: This study tested the validity of four motion sensors for measuring energy expenditure (EE) during moderate intensity physical activities in field and laboratory settings. We also evaluated the accuracy of the EE values for selected moderate activities listed in the 1993 Compendium of Physical Activities. METHODS: A total of 81 participants (age 19-74 yr) completed selected tasks from six general categories: yardwork, housework, occupation, family care, conditioning, and recreation. Twelve individuals performed each of the 28 activities examined. During each activity, EE was measured using a portable metabolic measurement system. Participants also wore three accelerometers (Computer Science and Applications [CSA], Inc. model 7164; Caltrac; and Kenz Select 2) and the Yamax SW-701 electronic pedometer. For the CSA device, three previously developed regression equations were used to convert accelerometer scores to EE. RESULTS: The mean error scores (indirect calorimetry minus device) across all activities were: CSA1, 0.97 MET; CSA2, 0.47 MET, CSA3, 0.05 MET; Caltrac, 0.83 MET; Kenz, 0.96 MET; and Yamax, 1.12 MET. The correlation coefficients between indirect calorimetry and motion sensors ranged from r = 0.33 to r = 0.62. The energy cost for power mowing and sweeping/mopping was higher than that listed in the 1993 Compendium (P < 0.05), and the cost for several household and recreational activities was lower (P < 0.05). CONCLUSION: Motion sensors tended to overpredict EE during walking. However, they underpredicted the energy cost of many other activities because of an inability to detect arm movements and external work. These findings illustrate some of the limitations of using motion sensors to predict EE in field settings.

Activities of Daily Living↗
PubMed2000

A comparative evaluation of three accelerometry-based physical activity monitors.

PURPOSE: Accelerometry-based activity monitors offer promise for the assessment of free-living physical activity. They provide an objective record of frequency, intensity, and duration of physical activity with minimal burden on participants. The purpose of this study was to evaluate the absolute and relative validity of three contemporary activity monitors (Computer Science and Applications, Inc. [CSA], Tritrac, and Biotrainer) under both laboratory and field conditions. METHODS: Fifty-two participants completed two 30-min choreographed routines designed to simulate a variety of lifestyle physical activities. Three different treadmill paces were completed in both routines to evaluate reliability and validity under laboratory conditions. Six different lifestyle activities were also examined to evaluate the validity of the monitors under field conditions. During each routine, the activity levels of participants were monitored with the three activity monitors as well as by indirect calorimetry systems. RESULTS: The correlations between the monitors and measured VO2 were higher for treadmill activity (mean r = 0.86) compared with lifestyle activity (mean r = 0.55). Correlations among the different monitors were high for both treadmill (r = 0.86) and lifestyle activities (r = 0.70), suggesting that the monitors provide similar information under both conditions. Under laboratory conditions, the CSA yielded accurate predictions of energy expenditure (EE), whereas the Tritrac and Biotrainer tended to overestimate the EE (101-136% of measured value). The Tritrac, however, was found to have less error in individual estimates of EE. Under field conditions, all of the monitors underestimated EE (range: 42-67% of measured value). CONCLUSION: The observed differences among the monitors were attributed primarily to differences in the accuracy of the calibration equations rather than to the monitors themselves. Further research is needed to better understand how to use these devices for field-based assessments of physical activity.

Activities of Daily Living↗
PubMed2001

Physical activity assessed by activity monitor and doubly labeled water in children.

PURPOSE: To validate the Computer Science and Application's (CSA) activity monitor for assessment of the total amount of physical activity during two school-weeks in 9-yr-old children and to develop equations to predict total energy expenditure (TEE) and activity energy expenditure (AEE) from activity counts and anthropometric variables. METHODS: A total of 26 children (15 boys and 11 girls, mean age 9.1 +/- 0.3 yr) were monitored for 14 consecutive days. TEE was simultaneously measured by the doubly labeled water method. Averaged activity counts (counts.min(-1)) were compared with data on: 1) TEE, 2) AEE = TEE minus basal metabolic rate (BMR; estimated from predictive equations), and 3) daily physical activity level (PAL = TEE/BMR). RESULTS: Physical activity determined by activity counts was significantly related to the data on energy expenditures: TEE (r = 0.39; P < 0.05), AEE (r = 0.54; P < 0.01), and PAL (r = 0.58; P < 0.01). Multiple stepwise regression analysis showed that TEE was significantly influenced by gender, body composition (body weight or fat free mass), and activity counts (R(2) = 0.54--0.60). AEE was significantly influenced by activity counts and gender (R(2) = 0.45). There were no significant differences between activity counts and PAL in discriminating among activity levels with "low" (PAL < 1.56), "moderate" (1.57 < or = PAL > or = 1.81), and "high" (PAL > 1.81) intensity. CONCLUSION: Activity counts from the CSA activity monitor seems to be a useful measure of the total amount of physical activity in 9-yr-old children. Activity counts contributed significantly to the explained variation in TEE and was the best predictor of AEE.

Activities of Daily Living↗
PubMed2001

Evaluation of methods to assess physical activity in free-living conditions.

PURPOSE: The purpose of this study was to compare different methods of measuring physical activity (PA) in women by the doubly labeled water method (DLW). METHODS: Thirteen subjects participated in a 7-d protocol during which total daily energy expenditure (TDEE) was measured with DLW. Body composition, basal metabolic rate (BMR), and peak oxygen consumption were also measured. Physical activity-related energy expenditure (PAEE) was then calculated by subtracting measured BMR and the estimated thermic effect of food from TDEE. Simultaneously, over the 7 d, PA was assessed via a 7-d Physical Activity Recall questionnaire (PAR), and subjects wore secured at the waist, a Tritrac-R3D (Madison, WI), a Computer Science Application Inc. activity monitor (CSA; Shalimar, FL), and a Yamax Digi Walker-500 (Tokyo, Japan). Pearson-product moment correlations were calculated to determine the relationships among the different methods for estimating PAEE. Paired t-tests with appropriate adjustments were used to compare the different methods with DLW-PAEE. RESULTS: There was no significant difference between PAEE determined from PAR and DLW. The differences between the two methods ranged from -633 to 280 kcal.d(-1). Compared with DLW, PAEE determined from CSA, Tritrac, and Yamax was significantly underestimated by 59% (-495 kcal.d(-1)), 35% (-320 kcal.d(-1)) and 59% (-497 kcal.d(-1)), respectively. VO2peak explained 43% of the variation in DLW-PAEE. CONCLUSION: Although the group average for PAR-PAEE agreed with DLW-PAEE, there were differences in the methods among the subjects. PAEE determined by Tritrac, CSA, and Yamax significantly underestimate free-living PAEE in women.

Activities of Daily Living↗
PubMed2002

Sources of variance in daily physical activity levels as measured by an accelerometer.

PURPOSE: To examine sources of variance in objective measures of physical activity in a group of healthy adults (N = 92) participating in a physical activity measurement study. METHODS: Physical activity was assessed for up to 21 consecutive days using the Computer Science Applications (CSA) accelerometer. Day-of-the-week effects were evaluated for activity counts (ct.min(-1).d(-1), ct.d(-1)) and time (min.d(-1)) spent in inactivity (0-499 ct), moderate-1 (500-1951 ct), and moderate-2-vigorous activity (> or =1952 ct). Random effects models were employed to estimate variance components for subject, day of the week, and residual error from which the number of days of assessment required to achieve 80% reliability were estimated. RESULTS: Physical inactivity was lower on weekend days, and Saturday was the least inactive day of the week for both men and women. Inter-individual variation, or differences between subjects, was proportionally the largest source of variance (55-60% of total) in accelerometer counts and time spent in moderate to vigorous activity. Differences within subjects (intra-individual variation) accounted for 30-45% of the overall variance, and day-of-the-week effects accounted for 1-8%. For activity counts, and time spent in moderate to vigorous activity, at least 3-4 d of monitoring were required to achieve 80% reliability. Reliable measures of physical inactivity required at least 7 d of monitoring. CONCLUSION: These findings provide insight for understanding the behavioral variability in the activity patterns of adults and suggest that reliable measures of activity behaviors require at least 7 d of monitoring.

Acceleration↗
PubMed2001

2001: Things to come.

THIS ARTICLE DISCUSSES elements in the definition of modernity and emerging futurism in neurological surgery. In particular, it describes evolution, discovery, and paradigm shifts in the field and forces responsible for their realization. It analyzes the cyclical reinvention of the discipline experienced during the past generation and attempts to identify apertures to the near and more remote future. Subsequently, it focuses on forces and discovery in computational science, imaging, molecular science, biomedical engineering, and information processing as they relate to the theme of minimalism that is evident in the field. These areas are explained in the light of future possibilities offered by the emerging field of nanotechnology with molecular engineering.

Forecasting↗
PubMed1980

Implications of a biopsychosocial model for research in psychiatry.

Developments in general and living systems theory, in computer science, and in research instrumentation and technology have led to new perspectives on the patient as a person. The biopsychosocial model forces realization that states of health and illness can be understood fully only in terms of their biological, psychological, and social parameters. Research implications of this model, particularly the appreciation it engenders for the brain's role in mediating and regulating transactions along the society-mind-brain-body continuum, are discussed. Objective data generated by skilled clinical psychiatric methods will be needed in addition to data generated in the basic science area for the full range of research challenges in psychiatry to be met.

Adult↗
PubMed2002

Development and evaluation of public health informatics at University of Washington.

Public Health Informatics (PHI) education began at the University of Washington (UW) with a Summer Institute in 1995. The Biomedical and Health Informatics graduate program, which is housed in the School of Medicine, is an interdisciplinary, multi-school program. It demonstrates the UW's cooperative efforts in advancing informatics, encompassing the schools of public health, medicine, nursing, dentistry, pharmacy, information and graduate schools in computer science. This article provides an overview of the developmental milestones related to activities in PHI and describes the evaluation strategy and assessment plan for PHI training at the UW (http://phig.washington.edu).

Curriculum↗
PubMed2000

Coordinate-independent mapping of structural and functional data by objective relational transformation (ORT).

Neuroscience has produced an enormous amount of structural and functional data. Powerful database systems are required to make these data accessible for computational approaches such as higher-order analyses and simulations. Available databases for key data such as anatomical and functional connectivity between cortical areas, however, are still hampered by methodological problems. These problems arise predominantly from the parcellation problem, the use of incongruent parcellation schemes by different authors. We here present a coordinate-independent mathematical method to overcome this problem: objective relational transformation (ORT). Based on new classifications for brain data and on methods from theoretical computer science, ORT represents a formally defined, transparent transformation method for reproducible, coordinate-independent mapping of brain data to freely chosen parcellation schemes. We describe the methodology of ORT and discuss its strengths and limitations. Using two practical examples, we show that ORT in conjunction with connectivity databases like CoCoMac (http://www.cocomac.org) is an important tool for analyses of cortical organization and structure-function relationships.

Animals↗
PubMed2001

Scientific collaboration networks. I. Network construction and fundamental results.

Using computer databases of scientific papers in physics, biomedical research, and computer science, we have constructed networks of collaboration between scientists in each of these disciplines. In these networks two scientists are considered connected if they have coauthored one or more papers together. We study a variety of statistical properties of our networks, including numbers of papers written by authors, numbers of authors per paper, numbers of collaborators that scientists have, existence and size of a giant component of connected scientists, and degree of clustering in the networks. We also highlight some apparent differences in collaboration patterns between the subjects studied. In the following paper, we study a number of measures of centrality and connectedness in the same networks.

Journal Article↗
PubMed2001

Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality.

Using computer databases of scientific papers in physics, biomedical research, and computer science, we have constructed networks of collaboration between scientists in each of these disciplines. In these networks two scientists are considered connected if they have coauthored one or more papers together. Here we study a variety of nonlocal statistics for these networks, such as typical distances between scientists through the network, and measures of centrality such as closeness and betweenness. We further argue that simple networks such as these cannot capture variation in the strength of collaborative ties and propose a measure of collaboration strength based on the number of papers coauthored by pairs of scientists, and the number of other scientists with whom they coauthored those papers.

Journal Article↗
PubMed2003

Scaling laws for critical manifolds in polycrystalline materials.

We study the surfaces of lowest energy through model polycrystalline materials in two and three dimensions. When the grain boundaries are sufficiently weak, these critical manifolds (CM's) lie entirely on grain boundaries, while when the grain boundaries are strong, cleavage occurs. A scaling theory for the intergranular to transgranular transition of CM's is developed. The key parameters are the average grain size g, the ratio of grain boundary to the grain interior energy, epsilon, and the sample size L. The key result is that a critical length scale exists, L(c)(g,epsilon), so that on short length scales l L(c), the critical manifold is rough. We develop a scaling theory for L(c) and find that in two dimensions L(c) approximately gx(y(2)), while in three dimensions L(c) approximately g exp(bx(y(3))), where x=epsilon/(1-epsilon) and b is a constant. Data from realistic polycrystalline grain structures are used to test the scaling theory. The exact lowest energy surface through model grain structures is found using a mapping to the minimum-cut/maximum-flow problem in computer science. As a function of grain-boundary energy, we observe the crossover from grain-boundary rupture to mixed mode failure (a mixture of transgramular and intergranular modes) and finally cleavage and that the two-dimensional data are consistent with y(2) approximately 3.0+/-0.3, while the three-dimensional data are more difficult to analyze, but are consistent with y(3) approximately 3.5+/-1.0.

Journal Article↗