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BACKGROUND: Dysregulation of bile acids (BAs), as important signalling molecules in regulating lipid and glucose metabolism, contributes to the development of non-alcoholic fatty liver disease (NAFLD). However, static BA profiles during fasting may obscure certain pathogenetic aspects. In this study, we investigate the dynamic alterations of BAs in response to an oral glucose tolerance test (OGTT) among children with NAFLD. METHODS: We recruited 230 subjects, including children with overweight/obesity, or complicated with NAFLD, and healthy controls. Serum BAs, 7-hydroxy-4-cholesten-3-one (C4) and fibroblast growth factor 19 (FGF19) were quantified during OGTT. Clinical markers related to liver function, lipid metabolism and glucose metabolism were assessed at baseline or during OGTT. FINDINGS: Conjugated BAs increased while unconjugated ones decreased after glucose uptake. Most BAs were blunted in response to glucose in NAFLD (p > .05); only glycine and taurine-conjugated chenodeoxycholic acid (CDCA) and cholic acid (CA) were responsive (p < .05). Primary BAs were significantly increased while secondary BAs were decreased in NAFLD. C4 and FGF19 were significantly increased while their ratio FGF19/C4 ratio was decreased in NAFLD. The dynamic pattern of CDCA and taurine-conjugated hyocholic acid (THCA) species was closely correlated with glucose (correlation coefficient r = .175 and -.233, p < .05), insulin (r = .327 and -.236, p < .05) and c-peptide (r = .318 and -.238, p < .05). Among which, CDCA was positively associated with liver fat content in NAFLD (r = .438, p < .05). Additionally, glycochenodeoxycholic acid (GCDCA), CDCA and THCA were potential biomarkers to discriminate paediatric NAFLD from healthy controls and children with obesity. INTERPRETATION: This study provides novel insights into the dynamics of BAs during OGTT in paediatric NAFLD. The observed variations in CDCA and HCA species were associated with liver dysfunction, dyslipidaemia and dysglycaemia, highlighting their potential roles as promising diagnostic and therapeutic targets in NAFLD.

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Past research has revealed cognitive improvements resulting from engagement with both traditional action video games and newer action-like video games, such as action real-time strategy games (ARSG). However, the cortical dynamics elicited by different video gaming genres remain unclear. This study explored the temporal dynamics of cortical networks in response to different gaming genres. Functional magnetic resonance imaging (fMRI) data were obtained during eye-closed resting and passive viewing of gameplay videos of three genres: life simulation games (LSG), first-person shooter games (FPS), and ARSG. Data analysis used a seed-free Co-Activation Pattern (CAP) based on Regions of Interest (ROIs). When comparing the viewing of action-like video games (FPS and ARSG) to LSG viewing, significant dynamic distinctions were observed in both primary and higher-order networks. Within action-like video games, compared to FPS viewing, ARSG viewing elicited a more pronounced increase in the Fraction of Time and Counts of attentional control-related CAPs, along with an increased Transition Probability from sensorimotor-related CAPs to attentional control-related CAPs. Compared to ARSG viewing, FPS viewing elicited a significant increase in the Fraction of Time of sensorimotor-related CAPs, when gaming experience was considered as a covariate. Thus, different video gaming genres, including distinct action-like video gaming genres, elicited unique dynamic patterns in whole-brain CAPs, potentially influencing the development of various cognitive processes.

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Affected by the pressure and constraints of available resources, plant growth and development, as well as plant life history strategies, usually vary with environmental conditions. Plant buds play a crucial role in the life history of woody plants. Nitraria tangutorum is a common dominant woody species in desertified areas of northern China and its growth is critical to the desert ecosystem. Revealing the allometry of N. tangutorum aboveground bud fates and the linkage between bud traits and plant nutrient contents and stoichiometric ratios can be useful in understanding plant adaptation strategy. We applied seven nitrogen and phosphorus fertilizer addition treatments to natural N. tangutorum ramets in Ulan Buh Desert in three consecutive years. We surveyed three types of aboveground buds (dormant buds, vegetative buds, and reproductive buds) in each N. tangutorum ramet, then measured the plant carbon (C), nitrogen (N), and phosphorus (P) contents and ratios during three consecutive years. We specified that reserve growth potential (RGP), vegetative growth intensity (VGI) and sexual reproduction effort (SRE) are the three indices of bud dynamic pattern. The results showed that the bud dynamic pattern of N. tangutorum ramets differed significantly among different fertilizer addition treatments and sampling years. The allometry of RGP, VGI, and SRE was obvious, showing size dependence. The allometric growth relationship fluctuated among the sampling years. The linkage between bud traits and plant stoichiometric characteristics of N. tangutorum ramets showed close correlation with plant P content, C:P and N:P ratios, no significant correlation with plant C content, N content and C:N ratio. These results contribute to an improved understanding of the adaptive strategies of woody plants growing in desert ecosystems and provide insights for adoption of effective measures to restore and conserve plant communities in arid and semi-arid regions.

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Dynamic patterns based on luminescent materials play an essential role in the digital age. However, it is still challenging to develop highly emissive photofluorochromic materials with dynamic behaviors to store information with multiple characteristics. Here, we report a series of dihydroazulene-based compounds which show typical aggregation-induced emission (AIE) effect. Moreover, the photo-switching ability of the dihydroazulene units, undergoing light-induced ring-opening, enables photofluorochromic properties. The photofluorochromism also shows quantitively described responses to time and temperature via a reverse ring-closing process. Ultimately, a rewritable 4D information system, embedded with a quick response code, dot matrix with microstructures, color matrix of fluorescence, and time/temperature-dependent intensity change, is established with dynamic patterns. This work not only develops a dynamic AIE skeleton with photofluorochromic properties but also provides a new strategy for information encryption and cybernetics.

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The rate of recurrence and metastasis of non-small cell lung cancer after radical resection is still very high. The risk factors for recurrence and metastasis have been extensively studied, but the dynamic pattern of postoperative recurrence hazard over time is relatively lacking. The dynamic recurrence hazard rate curve is applied to describe the rate of recurrence at any point time among the "at-risk" patients. In this article, by reviewing the previous literature, the characteristics of the dynamic recurrence and metastasis pattern after radical resection of non-small cell lung cancer and the clinical factors affecting the recurrence and metastasis pattern are summarized, in order to screen out specific populations with high recurrence risk and give them personalized follow-up strategy and diagnosis and treatment.
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The rate of recurrence and metastasis of non-small cell lung cancer after radical resection is still very high. The risk factors for recurrence and metastasis have been extensively studied, but the dynamic pattern of postoperative recurrence hazard over time is relatively lacking. The dynamic recurrence hazard rate curve is applied to describe the rate of recurrence at any point time among the "at-risk" patients. In this article, by reviewing the previous literature, the characteristics of the dynamic recurrence and metastasis pattern after radical resection of non-small cell lung cancer and the clinical factors affecting the recurrence and metastasis pattern are summarized, in order to screen out specific populations with high recurrence risk and give them personalized follow-up strategy and diagnosis and treatment.
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In the flash-lag effect (FLE), a flash in spatiotemporal alignment with a moving object is misperceived as lagging behind the moving object. One proposed explanation for this illusion is based on predictive motion extrapolation of trajectories. In this interpretation, the diverging effects of velocity on the perceived position of the moving object suggest that FLE might be based on the neural representation of perceived, rather than physical, velocity. By contrast, alternative explanations based on differential latency or temporal averaging would predict that the FLE does not rely on such a representation of perceived velocity. Here we examined whether the FLE is sensitive to illusory changes in perceived speed that result in changes to perceived velocity, while physical speed is constant. The perceived speed of the moving object was manipulated using revolving wedge stimuli with variable pattern textures (Experiment 1) and luminance contrast (Experiment 2). The motion extrapolation interpretation would predict that the changes in FLE magnitude should correspond to the changes in the perceived speed of the moving object. In the current study, two experiments demonstrated that perceived speed and FLE magnitude increased in the dynamic pattern relative to the static pattern conditions, and that the same effect was found in the low contrast compared to the high contrast conditions. These results showed that manipulations of texture and contrast that are known to alter judgments of perceived speed also modulate perceived position. We interpret this as a consequence of motion extrapolation mechanisms and discuss possible explanations for why we observed no cross-effect correlation.

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OBJECTIVES: To accurately describe the pattern, timing and predictors of disease recurrence after curative resection for different types of early-stage lung adenocarcinoma (LUAD). METHODS: A total of 1962 patients with early-stage LUAD were included. The presence of micropapillary, solid components or poorly differentiated cancer as a clinical variable was named "high-grade" adenocarcinoma (HGADC), while others were classified as "low-grade" adenocarcinoma (LGADC). Predictive factors for specific recurrence patterns were assessed by univariate and multivariate analyses using Cox-proportional hazard regression models. Event dynamics, based on the hazard rate, were evaluated. RESULTS: At a median follow-up of 36.0 months, 137 (6.98%) of 1962 patients suffered from recurrence. Multivariable Cox analysis revealed that HGADC was an independent predictor for overall recurrence (hazard ratio [HR] 3.08, 95% confidence interval [CI] 2.09-4.52, p < 0.001), local recurrence (HR 2.77, 95% CI 1.38-5.55, p < 0.001), distant metastasis (HR 3.22, 95% CI 2.03-5.11, p < 0.001), chest recurrence (HR 2.80, 95% CI 1.65-4.75, p < 0.001) and brain recurrence (HR 4.11, 95% CI 1.83-9.22, p < 0.001). However, HGADC (HR 1.56, 95% CI 0.63-3.86, p = 0.335 in univariate analysis) was not a risk factor for bone recurrence. The hazard curve of the whole group presented a double-peaked pattern. Different types of LUAD had different hazard curves. HGADC patients exhibited higher hazard rates than LGADC patients during the whole follow-up. In addition, the recurrence hazard curve in HGADC patients showed a typical "double-peaked" pattern, while the curve in LGADC patients displayed a smooth curve after surgery. CONCLUSIONS: Different postoperative recurrence patterns were seen in HGADC and LGADC. Site-specific recurrence patterns were also different in HGADC and LGADC types.

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We report robust control over the dynamic assembly, disassembly, and reconfiguration of light-activated molybdenum disulfide (MoS2 ) colloidal motor swarms with features not possible in equilibrium systems. A photochemical reaction produces chemical gradients across the MoS2 colloidal motors to drive them to move. Under illumination of a gradient light, these colloidal motors display a positive phototactic motion. Mesoscale simulations prove that the self-diffusiophoresis induced by the locally consumed oxygen gradient across MoS2 colloidal motors dominates the phototactic process. By programming the structured illumination, the collective migration and well-defined shapes of colloidal motor swarms can be externally regulated. The successful realization of programmable swarm transformation of colloidal motors like the emergent behaviors of living systems in nature provides a direct proof-of-concept for active soft materials and systems, with adaptive and interactive functions.

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BACKGROUND: This experiment was designed to study the respective effects of the closed-state human palm and dynamic arm bending on intra-body communication channel attenuation. METHODS: We selected the right upper arm of a healthy adult male as the experimental object to measure channel attenuation variation in a closed or open palm, and when the arm was bent, so as to analyze channel characteristics. CONCLUSIONS: The experiment showed that, in a quasi-static stable system, the effects of a closed palm on channel attenuation were negligibly minimal. In contrast, the physiological signal of the living body significantly interfered with the channel in the low-frequency mode. In the dynamic arm-bending experiment, we found that the attenuation variation range corresponds to the intersection angle (90∘⩽θ⩽ 180∘) of the upper arm and forearm; these results provide the basis for the establishment of a theoretical model.

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We report on a new quantitative EEG-approach, called Ipsative Trend Assessment which is based on the spatio-temporally defined patterns which are generated by the global interaction of cortical neurons. METHODS: The data were acquired from EEGs being recorded under resting conditions. Target variables are not the usually employed absolute values of the spectral parameters but rather their change being calculated from successive recordings with a single subjects design. RATIONALE: Since the resting-EEG does not provide specific information, we had to decide what else might be addressed by that method. CONCLUSIONS: Our hypothesis according to which the SR-EEG indicates Selye's behaviorally non-specific General Adaptation Syndrome is based on good evidence. MAIN FINDINGS: Dynamic pattern comparison between subsequent EEGs on the single case level is a hitherto neglected method, which may be utilize, for instance, with regard to objective therapeutic outcome assessment. SIGNIFICANCE: In order to substantiate the clinical meaningfulness of our new approach we report two case vignettes of psychiatric impairments. Apart from that, our procedure should provide the desperately needed objective assessment of the therapeutic effect with any disease displaying a certain proportion of unspecific symptoms.

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At present, construction of rural domestic waste treatment facilities is seriously lagging, and in many cases, treatment facilities do not yet exist in some villages of China. Serious rural waste pollution has not only impacted the quality of surface water and groundwater but also the atmosphere and the living environment of farmers of China. There are relatively few studies of rural domestic waste pollution, especially with respect to the spatio-temporal dynamic pattern of rural domestic waste discharge. Using survey data and income per capita, we calculated rural domestic waste discharge per capita per day. From this, we calculated provincial rural domestic waste discharge. According to our study, rural domestic waste discharge was 1.42 × 108 t/year in 2000. This number increased to 2.3 × 108 t/year in 2006 and to 2.47 × 108 t/year in 2010. Rural domestic waste increased dramatically while the actual rural population and the proportion of the rural population declined. When examining the eight regions, the rural domestic waste discharge of northeastern China, Qinghai-Tibet, middle China, and southwestern China had increased dramatically, while that of northern China, southern China, and eastern China increased relatively slowly. The economies of northern China, southern China, and eastern China are more developed; their rural domestic waste discharge has been high since 2000 and has continued to increase slowly. In northeastern China, Qinghai-Tibet, middle China, and southwestern China, rural domestic waste discharge was low in 2000; however, in the ten-year period from 2000 to 2010, their rural domestic waste discharge increased dramatically.

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Photodegradable polymers constitute an emerging class of materials that are expected to possess advances in the areas of micro/nano- and biotechnology. Herein, we report a green and effective strategy to fabricate light-responsive surface micropatterns by taking advantage of photodegradation chemistry. Thanks to the molecular chain breakage during the photolysis process, the stress field of photodegradable polymer-based wrinkling systems undergoes continuous disturbance, leading to the release/reorganization of the internal stress. Revealed by systematic experiments, the light-induced stress release mechanism enables the dynamic adaption of not only thermal-induced labyrinth wrinkles, but uniaxially oriented wrinkle microstructures induced by mechanical straining. This method paves the way for their diverse applications, for example, in optical information display and storage, and the smart fabrication of multifunctional surfaces as demonstrated here.

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The Nunez model for the generation of electroencephalogram (EEG) signals is naturally described as a neural field model on a sphere with space-dependent delays. For simplicity, dynamical realisations of this model either as a damped wave equation or an integro-differential equation, have typically been studied in idealised one dimensional or planar settings. Here we revisit the original Nunez model to specifically address the role of spherical topology on spatio-temporal pattern generation. We do this using a mixture of Turing instability analysis, symmetric bifurcation theory, centre manifold reduction and direct simulations with a bespoke numerical scheme. In particular we examine standing and travelling wave solutions using normal form computation of primary and secondary bifurcations from a steady state. Interestingly, we observe spatio-temporal patterns which have counterparts seen in the EEG patterns of both epileptic and schizophrenic brain conditions.

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BACKGROUND AND OBJECTIVE: Epilepsy is a neurological disorder that causes recurrent and abrupt seizures which makes the patients insecure. Predicting seizures can reduce the burdens of this disorder. METHODS: A new approach in seizure prediction is presented that includes a novel technique in feature extraction from EEG. The algorithm firsts creates an embedding space from EEG time series. Then it takes samples with most of the information using an optimized and data specific Poincare plane. In order to quantify small dynamics on the Poincare plane, based on the order of locations of Poincaré samples in the sequence, 64 fuzzy rules in each channel are defined. Features are extracted based on the frequency distribution of these fuzzy rules in each minute. Then features with higher variance are selected as ictal features and again reduced using PCA. Finally, in order to evaluate how these innovative features can increase the performance of the seizure prediction algorithm, the transition from interictal to preictal state is scored utilizing SVM. RESULTS: The algorithm is tested on 460 h of EEG from 19 patients of Freiburg dataset who had at least 3 seizures. Considering maximum Seizure Prediction Horizon of 42 minutes, average sensitivity was 91.8 - 96.6% and average false prediction rate was 0.05 - 0.08/h. CONCLUSIONS: The presented algorithm shows a better performance and more robustness compare to most of existing methods, and shows power in extracting optimal features from EEG.

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This paper developed a cognitive task-load (CTL) classification algorithm and allocation strategy to sustain the optimal operator CTL levels over time in safety-critical human-machine integrated systems. An adaptive human-machine system is designed based on a non-linear dynamic CTL classifier, which maps a set of electroencephalogram (EEG) and electrocardiogram (ECG) related features to a few CTL classes. The least-squares support vector machine (LSSVM) is used as dynamic pattern classifier. A series of electrophysiological and performance data acquisition experiments were performed on seven volunteer participants under a simulated process control task environment. The participant-specific dynamic LSSVM model is constructed to classify the instantaneous CTL into five classes at each time instant. The initial feature set, comprising 56 EEG and ECG related features, is reduced to a set of 12 salient features (including 11 EEG-related features) by using the locality preserving projection (LPP) technique. An overall correct classification rate of about 80% is achieved for the 5-class CTL classification problem. Then the predicted CTL is used to adaptively allocate the number of process control tasks between operator and computer-based controller. Simulation results showed that the overall performance of the human-machine system can be improved by using the adaptive automation strategy proposed.

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Cephalopods employ their chromomorphic skins for rapid and versatile active camouflage and signalling effects. This is achieved using dense networks of pigmented, muscle-driven chromatophore cells which are neurally stimulated to actuate and affect local skin colouring. This allows cephalopods to adopt numerous dynamic and complex skin patterns, most commonly used to blend into the environment or to communicate with other animals. Our ultimate goal is to create an artificial skin that can mimic such pattern generation techniques, and that could produce a host of novel and compliant devices such as cloaking suits and dynamic illuminated clothing. This paper presents the design, mathematical modelling and analysis of a dynamic biomimetic pattern generation system using bioinspired artificial chromatophores. The artificial skin is made from electroactive dielectric elastomer: a soft, planar-actuating smart material that we show can be effective at mimicking the actuation of biological chromatophores. The proposed system achieves dynamic pattern generation by imposing simple local rules into the artificial chromatophore cells so that they can sense their surroundings in order to manipulate their actuation. By modelling sets of artificial chromatophores in linear arrays of cells, we explore the capability of the system to generate a variety of dynamic pattern types. We show that it is possible to mimic patterning seen in cephalopods, such as the passing cloud display, and other complex dynamic patterning.

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