Risk of severe asthma episodes predicted from fluctuation analysis of airway function

Asthma is an increasing health problem worldwide, but the long-term temporal pattern of clinical symptoms is not understood and predicting asthma episodes is not generally possible. We analyse the time series of peak expiratory flows, a standard measurement of airway function that has been assessed twice daily in a large asthmatic population during a long-term crossover clinical trial. Here we introduce an approach to predict the risk of worsening airflow obstruction by calculating the conditional probability that, given the current airway condition, a severe obstruction will occur within 30 days. We find that, compared with a placebo, a regular long-acting bronchodilator (salmeterol) that is widely used to improve asthma control decreases the risk of airway obstruction. Unexpectedly, however, a regular short-acting beta2-agonist bronchodilator (albuterol) increases this risk. Furthermore, we find that the time series of peak expiratory flows show long-range correlations that change significantly with disease severity, approaching a random process with increased variability in the most severe cases. Using a nonlinear stochastic model, we show that both the increased variability and the loss of correlations augment the risk of unstable airway function. The characterization of fluctuations in airway function provides a quantitative basis for objective risk prediction of asthma episodes and for evaluating the effectiveness of therapy.

Integration of electrical neuroimaging with other functional imaging methods

Integrating evidence from different imaging modalities is important to overcome specific limitations of any given imaging method, such as insensitivity of the EEG to unsynchronized neural events, or the lack of fMRI sensitivity to events of low metabolic demand. Processes that are visible in one modality may be related in a nontrivial way to other processes visible in another modality and insight may only be obtained by integrating both methods through a common analysis. For example, brain activity at rest seems to be at least partly determined by an interaction of cortical rhythms (visible to EEG but not to fMRI) with sub-cortical activity (visible to fMRI, but usually not to EEG without averaging). A combination of EEG and fMRI data during rest may thus be more informative than the sum of two separate analyses in both modalities. Integration is also an important source of converging evidence about specific aspects and general principles of neural functions and their dysfunctions in certain pathologies. This is because not only electrical, but also energetic, biochemical, hemodynamic and metabolic processes characterize neural states and functions, and because brain structure provides crucial constraints upon neural functions. Focusing on multimodal integration of functional data should not distract from the privileged status of the electric field as the primary direct, noninvasive real-time measure of neural transmission. The preceding chapters illustrate how electrical neuroimaging has turned scalp EEG into an imaging modality which directly captures the full temporal dynamics of neural activity in the brain.

Statistical analysis of multichannel scalp field data

High density spatial and temporal sampling of EEG data enhances the quality of results of electrophysiological experiments. Because EEG sources typically produce widespread electric fields (see Chapter 3) and operate at frequencies well below the sampling rate, increasing the number of electrodes and time samples will not necessarily increase the number of observed processes, but mainly increase the accuracy of the representation of these processes. This is namely the case when inverse solutions are computed. As a consequence, increasing the sampling in space and time increases the redundancy of the data (in space, because electrodes are correlated due to volume conduction, and time, because neighboring time points are correlated), while the degrees of freedom of the data change only little. This has to be taken into account when statistical inferences are to be made from the data. However, in many ERP studies, the intrinsic correlation structure of the data has been disregarded. Often, some electrodes or groups of electrodes are a priori selected as the analysis entity and considered as repeated (within subject) measures that are analyzed using standard univariate statistics. The increased spatial resolution obtained with more electrodes is thus poorly represented by the resulting statistics. In addition, the assumptions made (e.g. in terms of what constitutes a repeated measure) are not supported by what we know about the properties of EEG data. From the point of view of physics (see Chapter 3), the natural “atomic” analysis entity of EEG and ERP data is the scalp electric field

An immunohistochemical procedure to detect patients with paraganglioma and phaeochromocytoma with germline SDHB, SDHC, or SDHD gene mutations: a retrospective and prospective analysis

BACKGROUND: Phaeochromocytomas and paragangliomas are neuro-endocrine tumours that occur sporadically and in several hereditary tumour syndromes, including the phaeochromocytoma-paraganglioma syndrome. This syndrome is caused by germline mutations in succinate dehydrogenase B (SDHB), C (SDHC), or D (SDHD) genes. Clinically, the phaeochromocytoma-paraganglioma syndrome is often unrecognised, although 10-30% of apparently sporadic phaeochromocytomas and paragangliomas harbour germline SDH-gene mutations. Despite these figures, the screening of phaeochromocytomas and paragangliomas for mutations in the SDH genes to detect phaeochromocytoma-paraganglioma syndrome is rarely done because of time and financial constraints. We investigated whether SDHB immunohistochemistry could effectively discriminate between SDH-related and non-SDH-related phaeochromocytomas and paragangliomas in large retrospective and prospective tumour series. METHODS: Immunohistochemistry for SDHB was done on 220 tumours. Two retrospective series of 175 phaeochromocytomas and paragangliomas with known germline mutation status for phaeochromocytoma-susceptibility or paraganglioma-susceptibility genes were investigated. Additionally, a prospective series of 45 phaeochromocytomas and paragangliomas was investigated for SDHB immunostaining followed by SDHB, SDHC, and SDHD mutation testing. FINDINGS: SDHB protein expression was absent in all 102 phaeochromocytomas and paragangliomas with an SDHB, SDHC, or SDHD mutation, but was present in all 65 paraganglionic tumours related to multiple endocrine neoplasia type 2, von Hippel-Lindau disease, and neurofibromatosis type 1. 47 (89%) of the 53 phaeochromocytomas and paragangliomas with no syndromic germline mutation showed SDHB expression. The sensitivity and specificity of the SDHB immunohistochemistry to detect the presence of an SDH mutation in the prospective series were 100% (95% CI 87-100) and 84% (60-97), respectively. INTERPRETATION: Phaeochromocytoma-paraganglioma syndrome can be diagnosed reliably by an immunohistochemical procedure. SDHB, SDHC, and SDHD germline mutation testing is indicated only in patients with SDHB-negative tumours. SDHB immunohistochemistry on phaeochromocytomas and paragangliomas could improve the diagnosis of phaeochromocytoma-paraganglioma syndrome. FUNDING: The Netherlands Organisation for Scientific Research, Dutch Cancer Society, Vanderes Foundation, Association pour la Recherche contre le Cancer, Institut National de la Santé et de la Recherche Médicale, and a PHRC grant COMETE 3 for the COMETE network.

Anger and posttraumatic stress disorder symptoms in crime victims: A longitudinal analysis

Among trauma-exposed individuals, severity of posttraumatic stress disorder (PTSD) symptoms is strongly correlated with anger. The authors used 2 longitudinal data sets with 282 and 218 crime victims, respectively, to investigate the temporal sequence of anger and PTSD symptoms following the assault. Cross-lagged regression analyses indicated that PTSD symptoms predicted subsequent level of anger, but that anger did not predict subsequent PTSD symptoms. Testing alternative models (common factor model, unmeasured 3rd variable model) that might account for spuriousness of the relation strengthened confidence in the results of the cross-lagged analyses. Further analyses suggested that rumination mediates the effect of PTSD symptoms on anger.

Campylobacter monitoring in German broiler flocks: an explorative time series analysis

Campylobacter, a major zoonotic pathogen, displays seasonality in poultry and in humans. In order to identify temporal patterns in the prevalence of thermophilic Campylobacter spp. in a voluntary monitoring programme in broiler flocks in Germany and in the reported human incidence, time series methods were used. The data originated between May 2004 and June 2007. By the use of seasonal decomposition, autocorrelation and cross-correlation functions, it could be shown that an annual seasonality is present. However, the peak month differs between sample submission, prevalence in broilers and human incidence. Strikingly, the peak in human campylobacterioses preceded the peak in broiler prevalence in Lower Saxony rather than occurring after it. Significant cross-correlations between monthly temperature and prevalence in broilers as well as between human incidence, monthly temperature, rainfall and wind-force were identified. The results highlight the necessity to quantify the transmission of Campylobacter from broiler to humans and to include climatic factors in order to gain further insight into the epidemiology of this zoonotic disease.

Synoptic Analysis of the New York March 1888 Blizzard

The meteorological circumstances that led to the Blizzard of March 1888 that hit New York are analysed in Version 2 of the “Twentieth Century Reanalysis” (20CR). The potential of this data set for studying historical extreme events has not yet been fully explored. A detailed analysis of 20CR data alongside other data sources (including historical instrumental data and weather maps) for historical extremes such as the March 1888 blizzard may give insights into the limitations of 20CR. We find that 20CR reproduces the circulation pattern as well as the temperature development very well. Regarding the absolute values of variables such as snow fall or minimum and maximum surface pressure, there is anunderestimation of the observed extremes, which may be due to the low spatial resolution of 20CR and the fact that only the ensemble mean is considered. Despite this drawback, the dataset allows us to gain new information due to its complete spatial and temporal coverage.

Spatio-temporal dynamics of alpha brain electric fields, and cognitive modes

Brian electric activity is viewed as sequences of momentary maps of potential distribution. Frequency-domain source modeling, estimation of the complexity of the trajectory of the mapped brain field distributions in state space, and microstate parsing were used as analysis tools. Input-presentation as well as task-free (spontaneous thought) data collection paradigms were employed. We found: Alpha EEG field strength is more affected by visualizing mentation than by abstract mentation, both input-driven as well as self-generated. There are different neuronal populations and brain locations of the electric generators for different temporal frequencies of the brain field. Different alpha frequencies execute different brain functions as revealed by canonical correlations with mentation profiles. Different modes of mentation engage the same temporal frequencies at different brain locations. The basic structure of alpha electric fields implies inhomogeneity over time — alpha consists of concatenated global microstates in the sub-second range, characterized by quasi-stable field topographies, and rapid transitions between the microstates. In general, brain activity is strongly discontinuous, indicating that parsing into field landscape-defined microstates is appropriate. Different modes of spontaneous and induced mentation are associated with different brain electric microstates; these are proposed as candidates for psychophysiological ``atoms of thought''.

Observations of the northern seasonal polar cap on Mars II: HiRISE photometric analysis of evolution of northern polar dunes in spring

We present an overview of our analyses of HiRISE observations of spring evolution of selected dune areas of the north polar erg. The north polar erg is covered annually by seasonal volatile ice layer, a mixture of CO2 and H2O with mineral dust contamination. In spring, this layer sublimes creating visually enigmatic phenomena, e.g. dark and bright fan-shaped deposits, dark–bright–dark bandings, dark down-slope streaks, and seasonal polygonal cracks. Similar phenomena in southern polar areas are believed to be related to the specific process of solid-state greenhouse effect. In the north, it is currently unclear if the solid-state greenhouse effect is able to explain all the observed phenomena especially because the increased influence of H2O on the time scales of this process has not yet been quantified. HiRISE observations of our selected locations show that the ground exhibits a temporal behaviour similar to the one observed in the southern polar areas: a brightening phase starting close to the spring equinox with a subsequent darkening towards summer solstice. The resolution of HiRISE enabled us to study dunes and substrate individually and even distinguish between different developments on windward and slip face sides of single dunes. Differences in the seasonal evolution between steep slip faces and flatter substrate and windward sides of dunes have been identified and compared to CRISM data of CO2 and H2O distributions on dunes. We also observe small scale dark blotches that appear in early observations and tend to sustain a low reflectivity throughout the spring. These blotches can be regarded as the analogue of dark fan deposits in southern polar areas, leading us to the conclusion that both martian polar areas follow similar spring evolutions.

Lateral sediment sources and knickzones as controls on spatio-temporal variations of sediment transport in an Alpine river

Modern mixed alluvial-bedrock channels in mountainous areas provide natural laboratories for understanding the time scales at which coarse-grained material has been entrained and transported from their sources to the adjacent sedimentary sink, where these deposits are preserved as conglomerates. This article assesses the shear stress conditions needed for the entrainment of the coarse-bed particles in the Glogn River that drains the 400 km2 Val Lumnezia basin, eastern Swiss Alps. In addition, quantitative data are presented on sediment transport patterns in this stream. The longitudinal stream profile of this river is characterized by three ca 500 m long knickzones where channel gradients range from 0·02 to 0·2 m m−1, and where the valley bottom confined into a <10 m wide gorge. Downstream of these knickzones, the stream is flat with gradients <0·01 m m−1 and widths ≥30 m. Measurements of the grain-size distribution along the trunk stream yield a mean D84 value of ca 270 mm, whereas the mean D50 is ca 100 mm. The consequences of the channel morphology and the grain-size distribution for the time scales of sediment transport were explored by using a one-dimensional step-backwater hydraulic model (Hydrologic Engineering Centre – River Analysis System). The results reveal that, along the entire trunk stream, a two to 10 year return period flood event is capable of mobilizing both the D50 and D84 fractions where the Shields stress exceeds the critical Shields stress for the initiation of particle motion. These return periods, however, varied substantially depending on the channel geometry and the pebble/boulder size distribution of the supplied material. Accordingly, the stream exhibits a highly dynamic boulder cover behaviour. It is likely that these time scales might also have been at work when coarse-grained conglomerates were constructed in the geological past.

Evaluating the disparity of female breast cancer mortality among racial groups - a spatiotemporal analysis

Background The literature suggests that the distribution of female breast cancer mortality demonstrates spatial concentration. There remains a lack of studies on how the mortality burden may impact racial groups across space and over time. The present study evaluated the geographic variations in breast cancer mortality in Texas females according to three predominant racial groups (non-Hispanic White, Black, and Hispanic females) over a twelve-year period. It sought to clarify whether the spatiotemporal trend might place an uneven burden on particular racial groups, and whether the excess trend has persisted into the current decade. Methods The Spatial Scan Statistic was employed to examine the geographic excess of breast cancer mortality by race in Texas counties between 1990 and 2001. The statistic was conducted with a scan window of a maximum of 90% of the study period and a spatial cluster size of 50% of the population at risk. The next scan was conducted with a purely spatial option to verify whether the excess mortality persisted further. Spatial queries were performed to locate the regions of excess mortality affecting multiple racial groups. Results The first scan identified 4 regions with breast cancer mortality excess in both non-Hispanic White and Hispanic female populations. The most likely excess mortality with a relative risk of 1.12 (p = 0.001) occurred between 1990 and 1996 for non-Hispanic Whites, including 42 Texas counties along Gulf Coast and Central Texas. For Hispanics, West Texas with a relative risk of 1.18 was the most probable region of excess mortality (p = 0.001). Results of the second scan were identical to the first. This suggested that the excess mortality might not persist to the present decade. Spatial queries found that 3 counties in Southeast and 9 counties in Central Texas had excess mortality involving multiple racial groups. Conclusion Spatiotemporal variations in breast cancer mortality affected racial groups at varying levels. There was neither evidence of hot-spot clusters nor persistent spatiotemporal trends of excess mortality into the present decade. Non-Hispanic Whites in the Gulf Coast and Hispanics in West Texas carried the highest burden of mortality, as evidenced by spatial concentration and temporal persistence.