The research of prediction model on intelligent vehicle based on driver’s perception

In the field of self-driving technology, the stability and comfort of the intelligent vehicle are the focus of attention. The paper applies cognitive psychology theory to the research of driving behavior and analyzes the behavior mechanism about the driver’s operation. Through applying the theory of hierarchical analysis, we take the safety and comfort of intelligent vehicle as the breakthrough point. And then we took the data of human drivers’ perception behavior as the training set and did regression analysis using the method of regression analysis of machine learning according to the charts of the vehicle speed and the visual field, the vehicle speed and the gaze point as well as the vehicle speed and the dynamic vision. At last we established linear and nonlinear regression models (including the logarithmic model) for the training set. The change in thinking is the first novelty of this paper. Last but not least important, we verified the accuracy of the model through the comparison of different regression analysis. Eventually, it turned out that using logarithmic relationship to express the relationship between the vehicle speed and the visual field, the vehicle speed and the gaze point as well as the vehicle speed and the dynamic vision is better than other models. In the aspect of application, we adopted the technology of multi-sensor fusion and transformed the acquired data from radar, navigation and image to log-polar coordinates, which makes us greatly simplify information when dealing with massive data problems from different sensors. This approach can not only reduce the complexity of the server’s processing but also drives the development of intelligent vehicle in information computing. We also make this model applied in the intelligent driver’s cognitive interactive debugging program, which can better explain and understand the intelligent driving behavior and improved the safety of intelligent vehicle to some extent.     

Procedures to characterize and study P2Z/P2X7 purinoceptor: flow cytometry as a promising practical, reliable tool

The expression of P2Z/P2X7 purinoceptor in different cell types is well established. This receptor is a member of the ionotropic P2X receptor family, which is composed by seven cloned receptor subtypes (P2X1 - P2X7). Interestingly, the P2Z/P2X7 has a unique feature of being linked to a non-selective pore which allows the passage of molecules up to 900 Da depending on the cell type. Early studies of P2Z/P2X7 purinoceptor were exclusively based on classical pharmacological studies but the recent tools of molecular biology have enriched the analysis of the receptor expression. The majority of assays and techniques chosen so far to study the expression of P2Z/P2X7 receptor explore directly or indirectly the effects of the opening of P2Z/P2X7 linked pore. In this review we describe the main techniques used to study the expression and functionality of P2Z/P2X7 receptor. Additionally, the increasing need and importance of a multifunctional analysis of P2Z/P2X7 expression based on flow cytometry technology is discussed, as well as the adoption of a more complete analysis of P2Z/P2X7 expression involving different techniques.     

The Deep Structure of Literary Representations

The cognitive rhetoricians have introduced the idea of cognitive domains into literary theory, but they have not yet developed a model for a comprehensive, species-typical structure of human motives. Evolutionary psychology can provide this model. Elemental human motives and basic emotions provide the deep structure of literary representations, and this deep structure serves to organize the particularities of circumstance and individual identity. Personal power and reproductive success are governing purposes in life and in literary representations. The concept of individual identity is necessary to literary representation, and a theory of literature based in evolutionary psychology has to incorporate models of personality. Literature and its oral antecedents organize experience in personally meaningful ways. They provide models of behavior and help regulate the complex cognitive machinery through which humans negotiate their social and cultural environments.     

P2RX7 Purinoceptor: A Therapeutic Target for Ameliorating the Symptoms of Duchenne Muscular Dystrophy

Background

Duchenne muscular dystrophy (DMD) is the most common inherited muscle disease, leading to severe disability and death in young men. Death is caused by the progressive degeneration of striated muscles aggravated by sterile inflammation. The pleiotropic effects of the mutant gene also include cognitive and behavioral impairments and low bone density.Current interventions in DMD are palliative only as no treatment improves the long-term outcome. Therefore, approaches with a translational potential should be investigated, and key abnormalities downstream from the absence of the DMD product, dystrophin, appear to be strong therapeutic targets. We and others have demonstrated that DMD mutations alter ATP signaling and have identified P2RX7 purinoceptor up-regulation as being responsible for the death of muscles in the mdx mouse model of DMD and human DMD lymphoblasts. Moreover, the ATP–P2RX7 axis, being a crucial activator of innate immune responses, can contribute to DMD pathology by stimulating chronic inflammation. We investigated whether ablation of P2RX7 attenuates the DMD model mouse phenotype to assess receptor suitability as a therapeutic target.

Methods and Findings

Using a combination of molecular, histological, and biochemical methods and behavioral analyses in vivo we demonstrate, to our knowledge for the first time, that genetic ablation of P2RX7 in the DMD model mouse produces a widespread functional attenuation of both muscle and non-muscle symptoms. In dystrophic muscles at 4 wk there was an evident recovery in key functional and molecular parameters such as improved muscle structure (minimum Feret diameter, p < 0.001), increased muscle strength in vitro (p < 0.001) and in vivo (p = 0.012), and pro-fibrotic molecular signatures. Serum creatine kinase (CK) levels were lower (p = 0.025), and reduced cognitive impairment (p = 0.006) and bone structure alterations (p < 0.001) were also apparent. Reduction of inflammation and fibrosis persisted at 20 mo in leg (p = 0.038), diaphragm (p = 0.042), and heart muscles (p < 0.001). We show that the amelioration of symptoms was proportional to the extent of receptor depletion and that improvements were observed following administration of two P2RX7 antagonists (CK, p = 0.030 and p = 0.050) without any detectable side effects. However, approaches successful in animal models still need to be proved effective in clinical practice.

Conclusions

These results are, to our knowledge, the first to establish that a single treatment can improve muscle function both short and long term and also correct cognitive impairment and bone loss in DMD model mice. The wide-ranging improvements reflect the convergence of P2RX7 ablation on multiple disease mechanisms affecting skeletal and cardiac muscles, inflammatory cells, brain, and bone. Given the impact of P2RX7 blockade in the DMD mouse model, this receptor is an attractive target for translational research: existing drugs with established safety records could potentially be repurposed for treatment of this lethal disease.     

Gating properties of the P2X2a and P2X2b receptor channels: experiments and mathematical modeling

Adenosine triphosphate (ATP)-gated P2X2 receptors exhibit two opposite activation-dependent changes, pore dilation and pore closing (desensitization), through a process that is incompletely understood. To address this issue and to clarify the roles of calcium and the C-terminal domain in gating, we combined biophysical and mathematical approaches using two splice forms of receptors: the full-size form (P2X2aR) and the shorter form missing 69 residues in the C-terminal domain (P2X2bR). Both receptors developed conductivity for N-methyl-D-glucamine within 2-6 s of ATP application. However, pore dilation was accompanied with a decrease rather than an increase in the total conductance, which temporally coincided with rapid and partial desensitization. During sustained agonist application, receptors continued to desensitize in calcium-independent and calcium-dependent modes. Calcium-independent desensitization was more pronounced in P2X2bR, and calcium-dependent desensitization was more pronounced in P2X2aR. In whole cell recording, we also observed use-dependent facilitation of desensitization of both receptors. Such behavior was accounted for by a 16-state Markov kinetic model describing ATP binding/unbinding and activation/desensitization. The model assumes that naive receptors open when two to three ATP molecules bind and undergo calcium-independent desensitization, causing a decrease in the total conductance, or pore dilation, causing a shift in the reversal potential. In calcium-containing media, receptor desensitization is facilitated and the use-dependent desensitization can be modeled by a calcium-dependent toggle switch. The experiments and the model together provide a rationale for the lack of sustained current growth in dilating P2X2Rs and show that receptors in the dilated state can also desensitize in the presence of calcium.     

Differential expression of ATP-gated P2X receptors in DRG between chronic neuropathic pain and visceralgia rat models

There are divergences between neuropathic pain and visceralgia in terms of the duration, location, and character of hyperalgesia. It is generally recognized that nociceptive receptors, including P2X receptors, may play different roles in nociceptive mechanisms. The different roles of P2X1–7 receptors have not been fully understood both in neuropathic pain and visceral hyperalgesia. In order to explore the different expressions of P2X1–7 receptors in these two hyperalgesia models, the lumbosacral dorsal root ganglion (DRG) neurons from rat sciatic nerve chronic constriction injury (CCI) model and neonatal colorectal distention (NCRD) model were studied (both the primary nociceptive neuron afferents of those two models projected to the same segment of spinal cord). Both immunohistochemistry (IHC) technique and real-time fluorescence quantitative polymerase chain reaction (RT-PCR) technology were applied to analyze the protein expression levels and nucleic acid of P2X1–7 receptors. We found that except P2X2 and P2X3, the expression levels of P2X1 and P2X5 receptors increased in neuropathic pain while those expression levels of P2X4, P2X6, and P2X7 receptors increased in visceral pain. Our results also suggested that in addition to P2X2/3 heteromeric, other P2X subunits may also involved in generation heteromeric such as P2X1/5 and/or P2X2/5 in neuropathic pain and P2X4/6 and/or P2X4/7 in visceral pain.     

Grist and mills: on the cultural origins of cultural learning

Cumulative cultural evolution is what 'makes us odd'; our capacity to learn facts and techniques from others, and to refine them over generations, plays a major role in making human minds and lives radically different from those of other animals. In this article, I discuss cognitive processes that are known collectively as 'cultural learning' because they enable cumulative cultural evolution. These cognitive processes include reading, social learning, imitation, teaching, social motivation and theory of mind. Taking the first of these three types of cultural learning as examples, I ask whether and to what extent these cognitive processes have been adapted genetically or culturally to enable cumulative cultural evolution. I find that recent empirical work in comparative psychology, developmental psychology and cognitive neuroscience provides surprisingly little evidence of genetic adaptation, and ample evidence of cultural adaptation. This raises the possibility that it is not only 'grist' but also 'mills' that are culturally inherited; through social interaction in the course of development, we not only acquire facts about the world and how to deal with it (grist), we also build the cognitive processes that make 'fact inheritance' possible (mills).     

The empathic brain and its dysfunction in psychiatric populations: implications for intervention across different clinical conditions

Empathy is a concept central to psychiatry, psychotherapy and clinical psychology. The construct of empathy involves not only the affective experience of the other person's actual or inferred emotional state but also some minimal recognition and understanding of another's emotional state. It is proposed, in the light of multiple levels of analysis including social psychology, cognitive neuroscience and clinical neuropsychology, a model of empathy that involves both bottom-up and top-down information processing underpinned by parallel and distributed computational mechanisms. The predictive validity of this model is explored with reference to clinical conditions. As many psychiatric conditions are associated with deficits or even lack of empathy, we discuss a limited number of these disorders including psychopathy/antisocial personality disorders, borderline and narcissistic personality disorders, autistic spectrum disorders, and alexithymia. We argue that future clinical investigations of empathy disorders can only be informative if behavioral, dispositional and biological factors are combined.     

PEATmoss (Physcomitrella Expression Atlas Tool): a unified gene expression atlas for the model plant Physcomitrella patens

Physcomitrella patens is a bryophyte model plant that is often used to study plant evolution and development. Its resources are of great importance for comparative genomics and evo‐devo approaches. However, expression data from Physcomitrella patens were so far generated using different gene annotation versions and three different platforms: CombiMatrix and NimbleGen expression microarrays and RNA sequencing. The currently available P. patens expression data are distributed across three tools with different visualization methods to access the data. Here, we introduce an interactive expression atlas, Physcomitrella Expression Atlas Tool (PEATmoss), that unifies publicly available expression data for P. patens and provides multiple visualization methods to query the data in a single web‐based tool. Moreover, PEATmoss includes 35 expression experiments not previously available in any other expression atlas. To facilitate gene expression queries across different gene annotation versions, and to access P. patens annotations and related resources, a lookup database and web tool linked to PEATmoss was implemented. PEATmoss can be accessed at https://peatmoss.online.uni-marburg.de     

Quantum-like brain: "Interference of minds"

We present a contextualist statistical realistic model for quantum-like representations in physics, cognitive science, and psychology. We apply this model to describe cognitive experiments to check quantum-like structures of mental processes. The crucial role is played by interference of probabilities for mental observables. Recently one such experiment based on recognition of images was performed. This experiment confirmed our prediction on the quantum-like behavior of mind. In our approach "quantumness of mind" has no direct relation to the fact that the brain (as any physical body) is composed of quantum particles. We invented a new terminology "quantum-like (QL) mind." Cognitive QL-behavior is characterized by a nonzero coefficient of interference lambda. This coefficient can be found on the basis of statistical data. There are predicted not only cos theta-interference of probabilities, but also hyperbolic cosh theta-interference. This interference was never observed for physical systems, but we could not exclude this possibility for cognitive systems. We propose a model of brain functioning as a QL-computer (there is a discussion on the difference between quantum and QL computers).     

Pdc1 Functions in the Assembly of P Bodies in Schizosaccharomyces pombe

P bodies are cytoplasmic RNA granules containing the Dcp1-Dcp2 decapping enzymes where mRNA decay can occur. Here, we describe the characterization of P bodies in the fission yeast Schizosaccharomyces pombe. Most information on the property and function of P bodies stems from studies in the distantly related budding yeast Saccharomyces cerevisiae, and Edc3 was identified as a scaffold protein required for P-body assembly. However, we found that, unlike in S. cerevisiae, fission yeast Edc3 was dispensable for P-body formation. Pdc1, a novel partner of the fission yeast decapping enzyme, with a limited similarity to plant Edc4/Varicose that is required for the assembly of P bodies, was identified (tandem affinity purification–matrix-assisted laser desorption ionization tandem mass spectrometry [TAP-MALDI MS/MS]). Pdc1 interacts with Dcp2 through its C terminus and contains a coiled-coil region for self-interaction to mediate P-body formation. In line with the model that Pdc1 cross-bridges different proteins, additional interactions can be demonstrated with components such as Edc3 and Ste13. Although Pdc1 is not required for the interaction between Dcp1 and Dcp2, our data suggest that Pdc1 acts as a functional homologue of Edc4, a third component of the decapping enzymes that is thought to be absent from fungi. Together, these results highlight the diverse P-body protein compositions between different species and might help to provide insight into their evolutionary paths.     

An Improved Method for P2X7R Antagonist Screening

ATP physiologically activates the P2X7 receptor (P2X7R), a member of the P2X ionotropic receptor family. When activated by high concentrations of ATP (i.e., at inflammation sites), this receptor is capable of forming a pore that allows molecules of up to 900 Da to pass through. This receptor is upregulated in several diseases, particularly leukemia, rheumatoid arthritis and Alzheimer''s disease. A selective antagonist of this receptor could be useful in the treatment of P2X7R activation-related diseases. In the present study, we have evaluated several parameters using in vitro protocols to validate a high-throughput screening (HTS) method to identify P2X7R antagonists. We generated dose-response curves to determine the EC₅₀ value of the known agonist ATP and the IC_s50 values for the known antagonists Brilliant Blue G (BBG) and oxidized ATP (OATP). The values obtained were consistent with those found in the literature (0.7 ± 0.07 mM, 1.3-2.6 mM and 173-285 μM for ATP, BBG and OATP, respectively). The Z-factor, an important statistical tool that can be used to validate the robustness and suitability of an HTS assay, was 0.635 for PI uptake and 0.867 for LY uptake. No inter-operator variation was observed, and the results obtained using our improved method were reproducible. Our data indicate that our assay is suitable for the selective and reliable evaluation of P2X7 activity in multiwell plates using spectrophotometry-based methodology. This method might improve the high-throughput screening of conventional chemical or natural product libraries for possible candidate P2X7R antagonist or agonist     

New perspectives on the conformational equilibrium regulating multi-phasic reduction of cytochrome P450 2B4 by cytochrome P450 reductase

The pre-steady-state reduction of cytochrome P450 (P450) 2B4 by P450 reductase (reductase) was modeled by assuming that an equilibrium between three catalytic conformers of P450 regulates the multi-phasic reduction of the enzyme. This model was compared to a model of reduction involving a minimum number of phases. Based on several criteria, the former model seems to provide an improved fit to the reduction data. Substrates were divided into two groups based on their effects at different concentrations of reductase. Surprisingly, in the presence of some substrates (group 1) but not others (group 2), the rate of reduction was actually slower with an excess of reductase than with equimolar reductase and P450. Presumably, oxidized reductase binds differently to P450 than reduced reductase. A schematic model based on two sites of interaction between reductase and P450 2B4 is offered to explain the unusual reduction kinetics with the two different groups of substrates.     

Toward an adequate mathematical model of mental space: conscious/unconscious dynamics on m-adic trees

We try to perform geometrization of cognitive science and psychology by representing information states of cognitive systems by points of mental space given by a hierarchic m-adic tree. Associations are represented by balls and ideas by collections of balls. We consider dynamics of ideas based on lifting of dynamics of mental points. We apply our dynamical model for modeling of flows of unconscious and conscious information in the human brain. In a series of models, Models 1–3, we consider cognitive systems with increasing complexity of psychological behavior determined by structure of flows of associations and ideas.     

Transfer learning for cytochrome P450 isozyme selectivity prediction

In the drug discovery process, the metabolic fate of drugs is crucially important to prevent drug-drug interactions. Therefore, P450 isozyme selectivity prediction is an important task for screening drugs of appropriate metabolism profiles. Recently, large-scale activity data of five P450 isozymes (CYP1A2 CYP2C9, CYP3A4, CYP2D6, and CYP2C19) have been obtained using quantitative high-throughput screening with a bioluminescence assay. Although some isozymes share similar selectivities, conventional supervised learning algorithms independently learn a prediction model from each P450 isozyme. They are unable to exploit the other P450 isozyme activity data to improve the predictive performance of each P450 isozyme's selectivity. To address this issue, we apply transfer learning that uses activity data of the other isozymes to learn a prediction model from multiple P450 isozymes. After using the large-scale P450 isozyme selectivity dataset for five P450 isozymes, we evaluate the model's predictive performance. Experimental results show that, overall, our algorithm outperforms conventional supervised learning algorithms such as support vector machine (SVM), Weighted k-nearest neighbor classifier, Bagging, Adaboost, and latent semantic indexing (LSI). Moreover, our results show that the predictive performance of our algorithm is improved by exploiting the multiple P450 isozyme activity data in the learning process. Our algorithm can be an effective tool for P450 selectivity prediction for new chemical entities using multiple P450 isozyme activity data.     

A biomechanical model to estimate corrective changes in muscle activation patterns for stroke patients

We have created a model to estimate the corrective changes in muscle activation patterns needed for a person who has had a stroke to walk with an improved gait-nearing that of an unimpaired person. Using this model, we examined how different functional electrical stimulation (FES) protocols would alter gait patterns. The approach is based on an electromyographically (EMG)-driven model to estimate joint moments. Different stimulation protocols were examined, which generated different corrective muscle activation patterns. These approaches grouped the muscles together into flexor and extensor groups (to simulate FES using surface electrodes) or left each muscle to vary independently (to simulate FES using intramuscular electrodes). In addition, we limited the maximal change in muscle activation (to reduce fatigue). We observed that with the two protocols (grouped and ungrouped muscles), the calculated corrective changes in muscle activation yielded improved joint moments nearly matching those of unimpaired subjects. The protocols yielded different muscle activation patterns, which could be selected based on practical condition. These calculated corrective muscle activation changes can be used in studying FES protocols, to determine the feasibility of gait retraining with FES for a given subject and to determine which protocols are most reasonable.     

脑源定位技术的精度评估及其在实际中的应用

脑源定位技术旨在通过头皮表面的脑电、脑磁信号来识别大脑内的神经活动源，是研究大脑皮层神经活动、认知过程和病理功能的基础。其毫秒级的时间分辨率可以有效弥补功能核磁共振在低时间分辨率方面的不足。然而，理论分析层面中逆问题的不适定性，以及实践操作层面上不同的记录方式、电极数量和头模型构建等过程带来的误差，给脑源定位的准确性带来极大挑战，也在一定程度上限制了脑源定位方法在神经科学和心理学研究以及临床诊断治疗中的实际应用。因此，理论分析和实践操作层面中的精度评估在脑源定位方法的实际使用中至关重要。针对以上问题，本文在对现有脑源定位方法介绍的基础上，着重分析了脑源定位技术的精度评估方法以及其在基础研究和临床诊断治疗中的实际应用。具体地，本文在理论分析中总结了基于空间分辨率、基于点扩散以及串扰函数的评估方法对于不同脑源定位方法中源的重叠程度和其他源对目标源的影响；在实践操作中介绍了记录方式、电极数量和密度、头部容积传导模型等因素对源定位精度的影响；进一步介绍了脑源定位技术在时频分析、连通性分析中的应用，以及其在临床中的应用，包括癫痫、注意缺陷与多动障碍等脑部疾病。     

情绪的脑机制研究在社会认知神经科学中的进展

社会认知神经科学是近几年国外新兴起的交叉学科,旨在阐述社会性、情绪性的体验与行为的心理和神经基础。它综合了认知神经科学与社会心理学研究的长处,对刻板印象、态度与态度改变、他人知觉、自我认知以及情绪与认知交互作用等方面进行了深入研究。主要范式是应用认知神经科学的方法来验证社会心理学在这些范畴上的各种不同理论观点,并在某些方面取得了突破性进展,但仍存在着广泛的发展空间。随着当前各种脑成像技术的革新,人们对情绪状态下大脑的神经活动的了解在原来认知的层面上有了进一步提升。本文主要阐述社会认知神经科学在情绪的脑机制研究上所取得的进展。