Intracranial Pressure Time Course in Primary Intracerebral Hemorrhage

Neurosurgery ◽  
1979 ◽  
Vol 4 (6) ◽  
pp. 504-511 ◽  
Author(s):  
Isacco Papo ◽  
Pierre Janny ◽  
Giuseppe Caruselli ◽  
Gilles Colnet ◽  
Antonio Luongo
Keyword(s):  
Intracranial Pressure ◽  
Time Course ◽  
Elevated Pressure ◽  
Deep Coma ◽  
Postoperative Course ◽  
Disturbance Of Consciousness ◽  
Pressure Time ◽  
Intermediate Disturbances ◽  
Over Time ◽  
Definite Correlation

abstract The course of intracranial pressure (ICP) over time was studied in 66 hypertensive and/or atherosclerotic patients harboring intracerebral hematomas. Patients with no disturbance of consciousness showed normal or only slightly elevated pressure. Conversely, most patients in deep coma exhibited high pressure with a tendency to rise further no matter what treatment was used. In the remaining patients with intermediate disturbances of consciousness, no definite correlation was found between ICP, clinical condition, and outcome. In all of the patients who underwent operation, the postoperative course of ICP over time was also studied and seemed to depend to a certain extent on the timing of the operation.

Intracranial pressure time course in primary intracerebral hemorrhage

Neurosurgery ◽  
1979 ◽  
Vol 4 (6) ◽  
pp. 504???11 ◽  
Author(s):  
I Papo ◽  
P Janny ◽  
G Caruselli ◽  
G Colnet ◽  
A Luongo
Keyword(s):  
Intracranial Pressure ◽  
Intracerebral Hemorrhage ◽  
Time Course ◽  
Pressure Time

Time in International Organizations and International Organizations in Time

2019 ◽  
Author(s):  
Eugénia C. Heldt
Keyword(s):  
International Organizations ◽  
Path Dependence ◽  
Time Pressure ◽  
Temporal Dimension ◽  
Incremental Change ◽  
Critical Junctures ◽  
Pressure Time ◽  
Multilateral System ◽  
System Time ◽  
Over Time

Time plays a central role in international organizations (IOs). Interactions among actors are embedded in a temporal dimension, and actors use formal and informal time rules, time discourses, and time pressure to obtain concessions from their counterparts. By the same token, legacies and innovations within and outside IOs can be examined as a dynamic process evolving over time. Against this background, this chapter has a twofold aim. First, it examines how actors use time in IOs with a particular focus on multilateral negotiations to justify their actions. Drawing on international relations studies and negotiation analysis, this piece explores six different dimensions of time in the multilateral system: time pressure, time discourse, time rules, time costs, time horizons, and time as a resource. Second, this chapter delineates the evolution of IOs over time with the focus on innovations that emerge to adapt their institutional system to new political and economic circumstances. This piece looks particularly at endogenous and exogenous changes in IOs, recurring to central concepts used by historical institutionalism, including path dependence, critical junctures, and sequencing. This allows us to map patterns of incremental change, such as displacement, conversion, drift, and layering.

scholarly journals Jonckheere–Terpstra–Kendall-based non-parametric analysis of temporal differential gene expression

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Hitoshi Iuchi ◽  
Michiaki Hamada
Keyword(s):  
Gene Expression ◽  
Time Series ◽  
Time Course ◽  
Time Series Data ◽  
Expression Patterns ◽  
Detection Methods ◽  
Series Data ◽  
Expression Levels ◽  
Over Time ◽  
Non Parametric

Abstract Time-course experiments using parallel sequencers have the potential to uncover gradual changes in cells over time that cannot be observed in a two-point comparison. An essential step in time-series data analysis is the identification of temporal differentially expressed genes (TEGs) under two conditions (e.g. control versus case). Model-based approaches, which are typical TEG detection methods, often set one parameter (e.g. degree or degree of freedom) for one dataset. This approach risks modeling of linearly increasing genes with higher-order functions, or fitting of cyclic gene expression with linear functions, thereby leading to false positives/negatives. Here, we present a Jonckheere–Terpstra–Kendall (JTK)-based non-parametric algorithm for TEG detection. Benchmarks, using simulation data, show that the JTK-based approach outperforms existing methods, especially in long time-series experiments. Additionally, application of JTK in the analysis of time-series RNA-seq data from seven tissue types, across developmental stages in mouse and rat, suggested that the wave pattern contributes to the TEG identification of JTK, not the difference in expression levels. This result suggests that JTK is a suitable algorithm when focusing on expression patterns over time rather than expression levels, such as comparisons between different species. These results show that JTK is an excellent candidate for TEG detection.

Decomposition of Growth Curves into Growth Rate and Acceleration: a Novel Procedure to Monitor Bacterial Growth and the Time-Dependent Effect of Antimicrobials

2021 ◽  
Author(s):  
M. Luisa Navarro-Pérez ◽  
M. Coronada Fernández-Calderón ◽  
Virginia Vadillo-Rodríguez
Keyword(s):  
Growth Rate ◽  
Mathematical Models ◽  
Bacterial Growth ◽  
Time Course ◽  
Antimicrobial Agents ◽  
Numerical Procedure ◽  
Growth Curves ◽  
Predictive Microbiology ◽  
Insight Into ◽  
Over Time

In this paper, a simple numerical procedure is presented to monitor the growth of Streptococcus sanguinis over time in the absence and presence of propolis, a natural antimicrobial. In particular, it is shown that the real-time decomposition of growth curves obtained through optical density measurements into growth rate and acceleration can be a powerful tool to precisely assess a large range of key parameters [ i.e. lag time ( t 0 ), starting growth rate ( γ 0 ), initial acceleration of the growth ( a 0 ), maximum growth rate ( γ max ), maximum acceleration ( a max ) and deceleration ( a min ) of the growth and the total number of cells at the beginning of the saturation phase ( N s )] that can be readily used to fully describe growth over time. Consequently, the procedure presented provides precise data of the time course of the different growth phases and features, which is expected to be relevant, for instance, to thoroughly evaluate the effect of new antimicrobial agents. It further provides insight into predictive microbiology, likely having important implications to assumptions adopted in mathematical models to predict the progress of bacterial growth. Importance: The new and simple numerical procedure presented in this paper to analyze bacterial growth will possibly allow identifying true differences in efficacy among antimicrobial drugs for their applications in human health, food security, and environment, among others. It further provides insight into predictive microbiology, likely helping in the development of proper mathematical models to predict the course of bacterial growth under diverse circumstances.

Sleep Disorder Over Time: Psychiatric Correlates Among Males

1980 ◽  
Vol 136 (5) ◽  
pp. 456-462 ◽  
Author(s):  
Hervey Sweetwood ◽  
Igor Grant ◽  
Daniel F. Kripke ◽  
Marvin S. Gerst ◽  
Joel Yager
Keyword(s):  
Prospective Study ◽  
Sleep Disorder ◽  
Sleep Disturbances ◽  
Time Course ◽  
Psychiatric Symptomatology ◽  
Over Time

SummaryThis 18 month prospective study assessed the time course of sleep disturbances in 85 male psychiatric out-patients and 103 male non-patients. Over one-third of the patients and 5 per cent of the non-patients reported frequent symptoms of insomnia during at least 14 of the 18 months. Frequency and chronicity of insomnia were strongly associated with intensity of psychiatric symptomatology, but not with diagnosis. Minor tranquillizers and hypnotics were used frequently by patients and occasionally by non-patients, but there was little indication that they altered the course of insomnia.

scholarly journals Predicting context specific enhancer-promoter interactions from ChIP-Seq time course data

2017 ◽  
Author(s):  
Tomasz Dzida ◽  
Mudassar Iqbal ◽  
Iryna Charapitsa ◽  
George Reid ◽  
Henk Stunnenberg ◽  
...  
Keyword(s):  
Estrogen Receptor Alpha ◽  
Time Course ◽  
Target Genes ◽  
Mcf7 Cells ◽  
Genome Wide ◽  
A Genome ◽  
Machine Learning Approach ◽  
Protein Occupancy ◽  
Context Specific ◽  
Over Time

We have developed a machine learning approach to predict context specific enhancer-promoter interactions using evidence from changes in genomic protein occupancy over time. The occupancy of estrogen receptor alpha (ERα), RNA polymerase (Pol II) and histone marks H2AZ and H3K4me3 were measured over time using ChIP-Seq experiments in MCF7 cells stimulated with estrogen. A Bayesian classifier was developed which uses the correlation of temporal binding patterns at enhancers and promoters and genomic proximity as features to predict interactions. This method was trained using experimentally determined interactions from the same system and was shown to achieve much higher precision than predictions based on the genomic proximity of nearest ERα binding. We use the method to identify a genome-wide confident set of ERα target genes and their regulatory enhancers genome-wide. Validation with publicly available GRO-Seq data demonstrates that our predicted targets are much more likely to show early nascent transcription than predictions based on genomic ERα binding proximity alone.

Evaluation of a method for noninvasive intracranial pressure assessment during infusion studies in patients with hydrocephalus

2000 ◽  
Vol 92 (5) ◽  
pp. 793-800 ◽  
Author(s):  
Bernhard Schmidt ◽  
Marek Czosnyka ◽  
Jens Jürgen Schwarze ◽  
Dirk Sander ◽  
Werner Gerstner ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Intracranial Pressure ◽  
Time Course ◽  
Cerebral Blood Flow Velocity ◽  
Absolute Error ◽  
Content Type ◽  
Arterial Blood ◽  
Potential Clinical Benefit ◽  
The Mean ◽  
Fine Print

Object. A mathematical model previously introduced by the authors allowed noninvasive intracranial pressure (nICP) assessment. In the present study the authors investigated this model as an aid in predicting the time course of raised ICP during infusion tests in patients with hydrocephalus and its suitability for estimating the resistance to outflow of cerebrospinal fluid (Rcsf).Methods. Twenty-one patients with hydrocephalus were studied. The nICP was calculated from the arterial blood pressure (ABP) waveform by using a linear signal transformation, which was dynamically modified by the relationship between ABP and cerebral blood flow velocity. This model was verified by comparison of nICP with “real” ICP measured during lumbar infusion tests. In all simulations, parallel increases in real ICP and nICP were evident. The simulated Rcsf was computed using nICP and then compared with Rcsf computed from real ICP. The mean absolute error between real and simulated Rcsf was 4.1 ± 2.2 mm Hg minute/ml. By the construction of simulations specific to different subtypes of hydrocephalus arising from various causes, the mean error decreased to 2.7 ± 1.7 mm Hg minute/ml, whereas the correlation between real and simulated Rcsf increased from R = 0.73 to R = 0.89 (p < 0.001).Conclusions. The validity of the mathematical model was confirmed in this study. The creation of type-specific simulations resulted in substantial improvements in the accuracy of ICP assessment. Improvement strategies could be important because of a potential clinical benefit from this method.

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