Quantitative physiologically based modeling of subjective fatigue during sleep deprivation

A quantitative physiologically based model of the sleep-wake switch is used to predict variations in subjective fatigue-related measures during total sleep deprivation. The model includes the mutual inhibition of the sleep-active neurons in the hypothalamic ventrolateral preoptic area (VLPO) and the wake-active monoaminergic brainstem populations (MA), as well as circadian and homeostatic drives. We simulate sleep deprivation by introducing a drive to the MA, which we call wake effort, to maintain the system in a wakeful state. Physiologically this drive is proposed to be afferent from the cortex or the orexin group of the lateral hypothalamus. It is hypothesized that the need to exert this effort to maintain wakefulness at high homeostatic sleep pressure correlates with subjective fatigue levels. The model's output indeed exhibits good agreement with existing clinical time series of subjective fatigue-related measures, supporting this hypothesis. Subjective fatigue, adrenaline, and body temperature variations during two 72 h sleep deprivation protocols are reproduced by the model. By distinguishing a motivation-dependent orexinergic contribution to the wake-effort drive, the model can be extended to interpret variation in performance levels during sleep deprivation in a way that is qualitatively consistent with existing, clinically derived results. The example of sleep deprivation thus demonstrates the ability of physiologically based sleep modeling to predict psychological measures from the underlying physiological interactions that produce them.     

The reorganization of the electrical activity of the human brain during the depression of consciousness (comatose states)

To study the problem of consciousness an original structural-functional approach has been applied with the use of possibilities of spectral-coherent EEG analysis in evaluation of human brain functional state together with the specificity of the cerebral coma having local focal belonging. It is revealed that the most informative signs for characteristics of consciousness state are peculiarities of reconstruction of intercentral relations of the electrical brain processes: decrease of mean levels of the EEG coherence at progressive development of coma; staged approach to relative norm at regressive course of comatose state and recovery of consciousness; their stability on the low level at prolonged coma; increase in low or high (above optimum) frequencies band at neighbouring with coma states of consciousness. It may be considered that one of the necessary conditions of normal state of consciousness is preservation of the optimum level of correlation of electrical brain activity alongside with frequency-regional specificity of the EEG coherence spectrum. Any deviation from the optimum is unfavourable condition for normal course of cerebral reactions because of the disturbance of intercentral connections mosaic necessary for their realization.     

Performance measures in evaluating machine learning based bioinformatics predictors for classifications

Background: Many existing bioinformatics predictors are based on machine learning technology. When applying these predictors in practical studies, their predictive performances should be well understood. Different performance measures are applied in various studies as well as different evaluation methods. Even for the same performance measure, different terms, nomenclatures or notations may appear in different context. Results: We carried out a review on the most commonly used performance measures and the evaluation methods for bioinformatics predictors. Conclusions: It is important in bioinformatics to correctly understand and interpret the performance, as it is the key to rigorously compare performances of different predictors and to choose the right predictor.     

EEG Reflection of Clinical Effects Dynamics during Botulinum Toxin Therapy of Movement Disorders under Long-Term Consciousness Disorders

When studying the dynamics of brain electric activity (BEA) in the course of botulinum toxin (Incobotulinumtoxin A) injections into all hypertonic muscles of 16 patients suffering from post-coma longterm consciousness disorders, BEA changes were observed to start within the first minutes after the first intramuscular injection of botulinum toxin, while not being associated with any pain stimulus response. Despite the diversity of brain lesions in these patients, the dynamics of BEA reorganisation during botulinum toxin therapy showed the presence of pathological sensorimotor integration involving the whole brain in case of long-term consciousness disorders. In our opinion, it is expressed in a pathological state developing in the brain, which affects the polyfunctional capabilities of neurons. This state is unbalanced due to destabilizing effect at the beginning of the reduction by pathological hyperafferentation from muscles and, in principle, can be disrupted at a complete reduction. It is, however, maintained by memory matrix, which manifests itself in the shape of oscillation process during its disruption when the newly build-up BEA is occasionally displaced by the previous one. During the reduction of sensory hyperafferentation, BEA reorganisation initially involved the motor cortex (in 15 out of 16 patients) and then spread to other brain areas, including those responsible for the higher mental functions, vision, and hearing. The first transiently decreased muscle tone (in all patients) and improvement of neurological signs of awareness (in some patients) were observed immediately after injecting all hypertonic muscles with widespread BEA changes. The appearance of high-frequency EEG activity in the frontal areas was considered as a universal marker of an improved functional state of the brain during the disruption of pathological sensorimotor integration even before clinical signs, suggesting neuronal readiness to maintain various activities. In view of data obtained, the first-stage clinical measures in patients with disorders of consciousness should focus on disrupting pathological sensorimotor integration, opening a way for restoring neuronal functional activity, provided that all “pathological afferents” are reduced.     

Graphical representations and summary indicators to assess the performance of risk predictors

The availability of novel biomarkers in several branches of medicine opens room for refining prognosis by adding factors on top of those having an established role. It is accepted that the impact of novel factors should not rely solely on regression coefficients and their significance but also on predictive power measures, such as Brier score and ROC‐based quantities. However, novel factors that are promising at the exploratory stage often result in disappointingly low impact in the predictive power. This motivated the proposal of the net reclassification improvement and the integrated discrimination improvement, as direct measures of predictive power gain due to additional factors based on the concept of reclassification tables. These measures became extremely popular in cardiovascular disease and cancer applications, given the apparently easy interpretation. However, recent contributions in the biostatistical literature enlightened the tendency to indicate as advantageous models obtained by adding unrelated factors. These measures should not be used in practice. A further measure proposed a decade ago, the net benefit, is becoming a standard in assessing the consequences in terms of costs and benefits when using a risk predictor in practice for classification. This work reviews the conceptual formulations and interpretations of the available graphical methods and summary measures for evaluating risk predictor models. The aim is to provide guidance in the evaluation process that from the model development brings the risk predictor to be used in clinical practice for binary decision rules.     

基于模糊决策的临床科室主任绩效考核的研究

通过研究临床科室主任绩效考核指标,调动科室主任管理的积极性,增强科室员工质量管理意识和医疗安全意识,促进医院的发展。在分析传统临床科室绩效考核方法不足的基础上,结合模糊决策的概念,提出了一种基于模糊决策的临床科室主任综合评判方法。该方法充分利用了模糊逻辑中模糊决策的概念,对医院临床科室主任进行了模糊意见集中决策和模糊综合评判决策。最后通过具体的数值实验对该方法进行了性能分析,结果证明该方法具有良好的性能。     

Assessment of Robotic Patient Simulators for Training in Manual Physical Therapy Examination Techniques

Robots that simulate patients suffering from joint resistance caused by biomechanical and neural impairments are used to aid the training of physical therapists in manual examination techniques. However, there are few methods for assessing such robots. This article proposes two types of assessment measures based on typical judgments of clinicians. One of the measures involves the evaluation of how well the simulator presents different severities of a specified disease. Experienced clinicians were requested to rate the simulated symptoms in terms of severity, and the consistency of their ratings was used as a performance measure. The other measure involves the evaluation of how well the simulator presents different types of symptoms. In this case, the clinicians were requested to classify the simulated resistances in terms of symptom type, and the average ratios of their answers were used as performance measures. For both types of assessment measures, a higher index implied higher agreement among the experienced clinicians that subjectively assessed the symptoms based on typical symptom features. We applied these two assessment methods to a patient knee robot and achieved positive appraisals. The assessment measures have potential for use in comparing several patient simulators for training physical therapists, rather than as absolute indices for developing a standard.     

Ecological restoration as precaution and not as restitutional compensation

Ecological restoration has become a major issue in environmental management. To overcome the backward orientation of the restoration concept (focusing on reference states and natural ecosystems) the introduction of a precautionary principle is proposed. The principle has been developed for decision-making under high uncertainty about the probability and severity of an environmental damage. Meanwhile, it has been accepted in many countries of the world as a guiding principle for environmental legislation. Likewise it is the basis for international conventions aiming at the conservation of biodiversity. Nevertheless, biodiversity is still neglected in large reclamation projects. Several links between precaution and restoration are described. Restoration can be used to prevent future damage. Otherwise restoration is plagued by uncertainty about the outcome of the measures and may have negative effects or even fail. An analysis of common evaluation methods of restoration projects shows that most approaches focus on comparison of restoration results with a reference state, and are thus useless in a precautionary context. Other methods (e.g. comparing restored with unrestored sites) require data gathered by long-term observation (monitoring) of socio-economically defined desired states (Leitbild). Two large-scale restoration projects are analyzed, coastal land reclamation in Korea and open cast mining reclamation in Germany. Both projects had or have honorific aims and are legally admissible. However, they violate both international law based on precaution and simple rules of prudence or wise use. Costly post hoc ‘restoration’ measures are the usual consequence.     

基于RS的湖岸带物理结构完整性评价方法——以查干湖为例

以查干湖流域为研究区,利用RS和GIS技术,基于水利部《河流(湖)健康评估指标、标准与方法 V1.0》并加以改进,以500m×1000m为评价基本单元,整个研究区共有315个物理结构基本评价单元,建立基于RS的湖岸带物理结构完整性评价体系,该评价体系由目标层、准则层和指标层构成,其中准则层由湖岸带状况、湖岸线发育率和湖泊萎缩率3项组成,指标层由地形坡度、植被覆盖率等8项指标构成。研究结果表明:38个监测点中,查干湖23个,新庙泡15个,基于RS物理结构评价结果分别为0.67—0.76和0.35—0.45,地面实测评价结果分别是0.64—0.77和0.35—0.55。两种评价方法结果一致,并表明查干湖的湖岸带物理结构健康状态属于健康,新庙泡则属于亚健康。     

The design and fabrication of three-chamber microscale cell culture analog devices with integrated dissolved oxygen sensors

Whole animal testing is an essential part in evaluating the toxicological and pharmacological profiles of chemicals and pharmaceuticals, but these experiments are expensive and cumbersome. A cell culture analog (CCA) system, when used in conjunction with a physiologically based pharmacokinetic (PBPK) model, provides an in vitro supplement to animal studies and the possibility of a human surrogate for predicting human response in clinical trials. A PBPK model mathematically simulates animal metabolism by modeling the absorption, distribution, metabolism, and elimination kinetics of a chemical in interconnected tissue compartments. A CCA uses mammalian cells cultured in interconnected chambers to physically represent the corresponding PBPK. These compartments are connected by recirculating tissue culture medium that acts as a blood surrogate. The purpose of this article is to describe the design and basic operation of the microscale manifestation of such a system. Microscale CCAs offer the potential for inexpensive, relatively high throughput evaluation of chemicals while minimizing demand for reagents and cells. Using microfabrication technology, a three-chamber ("lung"-"liver"-"other") microscale cell culture analog (microCCA) device was fabricated on a 1 in. (2.54 cm) square silicon chip. With a design flow rate of 1.76 microL/min, this microCCA device achieves approximate physiological liquid-to-cell ratio and hydrodynamic shear stress while replicating the liquid residence time parameters in the PBPK model. A dissolved oxygen sensor based on collision quenching of a fluorescent ruthenium complex by oxygen molecules was integrated into the system, demonstrating the potential to integrate real-time sensors into such devices.     

EEG-based automatic classification of 'awake' versus 'anesthetized' state in general anesthesia using Granger Causality

Background

General anesthesia is a reversible state of unconsciousness and depression of reflexes to afferent stimuli induced by administration of a “cocktail” of chemical agents. The multi-component nature of general anesthesia complicates the identification of the precise mechanisms by which anesthetics disrupt consciousness. Devices that monitor the depth of anesthesia are an important aide for the anesthetist. This paper investigates the use of effective connectivity measures from human electrical brain activity as a means of discriminating between ‘awake’ and ‘anesthetized’ state during induction and recovery of consciousness under general anesthesia.

Methodology/Principal Findings

Granger Causality (GC), a linear measure of effective connectivity, is utilized in automated classification of ‘awake’ versus ‘anesthetized’ state using Linear Discriminant Analysis and Support Vector Machines (with linear and non-linear kernel). Based on our investigations, the most characteristic change of GC observed between the two states is the sharp increase of GC from frontal to posterior regions when the subject was anesthetized, and reversal at recovery of consciousness. Features derived from the GC estimates resulted in classification of ‘awake’ and ‘anesthetized’ states in 21 patients with maximum average accuracies of 0.98 and 0.95, during loss and recovery of consciousness respectively. The differences in linear and non-linear classification are not statistically significant, implying that GC features are linearly separable, eliminating the need for a complex and computationally expensive non-linear classifier. In addition, the observed GC patterns are particularly interesting in terms of a physiological interpretation of the disruption of consciousness by anesthetics. Bidirectional interaction or strong unidirectional interaction in the presence of a common input as captured by GC are most likely related to mechanisms of information flow in cortical circuits.

Conclusions/Significance

GC-based features could be utilized effectively in a device for monitoring depth of anesthesia during surgery.     

Patterns of host-plant choice in bees of the genus Chelostoma: the constraint hypothesis of host-range evolution in bees

To trace the evolution of host-plant choice in bees of the genus Chelostoma (Megachilidae), we assessed the host plants of 35 Palearctic, North American and Indomalayan species by microscopically analyzing the pollen loads of 634 females and reconstructed their phylogenetic history based on four genes and a morphological dataset, applying both parsimony and Bayesian methods. All species except two were found to be strict pollen specialists at the level of plant family or genus. These oligolectic species together exploit the flowers of eight different plant orders that are distributed among all major angiosperm lineages. Based on ancestral state reconstruction, we found that oligolecty is the ancestral state in Chelostoma and that the two pollen generalists evolved from oligolectic ancestors. The distinct pattern of host broadening in these two polylectic species, the highly conserved floral specializations within the different clades, the exploitation of unrelated hosts with a striking floral similarity as well as a recent report on larval performance on nonhost pollen in two Chelostoma species clearly suggest that floral host choice is physiologically or neurologically constrained in bees of the genus Chelostoma. Based on this finding, we propose a new hypothesis on the evolution of host range in bees.     

Pharmacokinetic modelling of [2-13C]uracil metabolism in normal and DPD-deficient dogs

A physiologically based pharmacokinetic (PBPK) model to simulate the plasma concentration and 13CO2 exhalation after [2-13C]uracil administration to DPD-suppressed dogs was developed. Simulation using this PBPK model should be useful in clinical situations where DPD-deficient patients at risk are to be detected with [2-13C]uracil as an in vivo probe.     

Functional neuroimaging of the vegetative state

A number of recent studies have demonstrated a role for state-of-the-art neuroimaging methods in the assessment of patients in the vegetative state and other so-called 'disorders of consciousness'. In several cases, functional MRI has been used to show that aspects of speech perception, emotional processing, language comprehension and even conscious awareness might be retained in some patients who behaviourally meet all of the criteria that define the vegetative state. This work has profound implications for clinical care, diagnosis, prognosis and medical-legal decision making (relating to the prolongation, or otherwise, of life after severe brain injury), as well as for more basic scientific questions about the nature of consciousness and the neural representation of our own thoughts and intentions.     

Automatism

Individuals can carry out complex activity while in a state of impaired consciousness, a condition termed “automatism”. Consciousness must be considered from both an organic and a psychological aspect, because impairment of consciousness may occur in both ways. Automatism may be classified as normal (hypnosis), organic (temporal lobe epilepsy), psychogenic (dissociative fugue) or feigned. Often painstaking clinical investigation is necessary to clarify the diagnosis. There is legal precedent for assuming that all crimes must embody both consciousness and will. Jurists are loath to apply this principle without reservation, as this would necessitate acquittal and release of potentially dangerous individuals. However, with the sole exception of the defence of insanity, there is at present no legislation to prohibit release without further investigation of anyone acquitted of a crime on the grounds of “automatism”.     

Markov chain models of coupled calcium channels: Kronecker representations and iterative solution methods

Mathematical models of calcium release sites derived from Markov chain models of intracellular calcium channels exhibit collective gating reminiscent of the experimentally observed phenomenon of stochastic calcium excitability (i.e., calcium puffs and sparks). Calcium release site models are stochastic automata networks that involve many functional transitions, that is, the transition probabilities of each channel depend on the local calcium concentration and thus the state of the other channels. We present a Kronecker-structured representation for calcium release site models and perform benchmark stationary distribution calculations using both exact and approximate iterative numerical solution techniques that leverage this structure. When it is possible to obtain an exact solution, response measures such as the number of channels in a particular state converge more quickly using the iterative numerical methods than occupation measures calculated via Monte Carlo simulation. In particular, multi-level methods provide excellent convergence with modest additional memory requirements for the Kronecker representation of calcium release site models. When an exact solution is not feasible, iterative approximate methods based on the power method may be used, with performance similar to Monte Carlo estimates. This suggests approximate methods with multi-level iterative engines as a promising avenue of future research for large-scale calcium release site models.     

Diagnostic accuracy of the vegetative and minimally conscious state: Clinical consensus versus standardized neurobehavioral assessment

Background  

Previously published studies have reported that up to 43% of patients with disorders of consciousness are erroneously assigned a diagnosis of vegetative state (VS). However, no recent studies have investigated the accuracy of this grave clinical diagnosis. In this study, we compared consensus-based diagnoses of VS and MCS to those based on a well-established standardized neurobehavioral rating scale, the JFK Coma Recovery Scale-Revised (CRS-R).     

Influence of lateral association on forced unfolding of antiparallel spectrin heterodimers

Protein extensibility appears to be based broadly on conformational changes that can in principle be modulated by protein-protein interactions. Spectrin family proteins, with their extensible three-helix folds, enable evaluation of dimerization effects at the single molecule level by atomic force microscopy. Although some spectrin family members function physiologically only as homodimers (e.g. alpha-actinin) or are strictly monomers (e.g. dystrophin), alpha- and beta-spectrins are stable as monomeric forms but occur physiologically as alpha,beta-heterodimers bound laterally lengthwise. For short constructs of alpha- and beta-spectrin, either as monomers or as alpha,beta-dimers, sawtooth patterns in atomic force microscopy-forced extension show that unfolding stochastically extends repeats approximately 4-5-fold greater in length than native conformations. For both dimers and monomers, distributions of unfolding lengths appear bimodal; major unfolding peaks reflect single repeats, and minor unfolding peaks at twice the length reflect tandem repeats. Cooperative unfolding thus propagates through helical linkers between serial repeats (1, 2). With lateral heterodimers, however, the force distribution is broad and shifted to higher forces. The associated chains in a dimer can stay together and unfold simultaneously in addition to unfolding independently. Weak lateral interactions do not inhibit unfolding, but strong lateral interactions facilitate simultaneous unfolding analogous to serial repeat coupling within spectrin family proteins.     

区域生态效应研究中人类活动强度定量化评价

人类活动及其干扰会产生不同的生态环境效应,定量化评价区域人类活动干扰的特点是分析人类活动对区域生态环境影响的基础。人类活动强度的定量评价有助于更好地理解生态系统变化的驱动机制,对于合理调控人类活动,预防或减少可能产生的生态危机以及区域的规划管理和政策的制定具有重要意义。目前研究主要是从压力变化和状态变化两方面对人类活动强度进行的评价。本文基于人类活动压力的视角,建立了基于权重的多指标叠加体系对人类活动强度进行评估;从状态变化的角度,从土地利用变化、生态系统服务变化或多因子状态变化等方面进行评价。介绍了在定量化评价人类活动强度中应用较为广泛的方法,如人类足迹指数、喀斯特干扰指数、生态足迹方法和景观发展指数等。指出了目前人类活动强度定量化评价研究中存在的问题及对未来发展提出了建议。     

Perturbations in dynamical models of whole-brain activity dissociate between the level and stability of consciousness

Consciousness transiently fades away during deep sleep, more stably under anesthesia, and sometimes permanently due to brain injury. The development of an index to quantify the level of consciousness across these different states is regarded as a key problem both in basic and clinical neuroscience. We argue that this problem is ill-defined since such an index would not exhaust all the relevant information about a given state of consciousness. While the level of consciousness can be taken to describe the actual brain state, a complete characterization should also include its potential behavior against external perturbations. We developed and analyzed whole-brain computational models to show that the stability of conscious states provides information complementary to their similarity to conscious wakefulness. Our work leads to a novel methodological framework to sort out different brain states by their stability and reversibility, and illustrates its usefulness to dissociate between physiological (sleep), pathological (brain-injured patients), and pharmacologically-induced (anesthesia) loss of consciousness.