Feasibility analysis of phase transition signals based on e-bike rider behavior

This article evaluates the feasibility of two scenarios of phase transition signals, that is, the flashing green together with red–yellow light and the green countdown together with red countdown, at signalized intersections in terms of e-bike rider behavior. An evaluation framework is first proposed. During the phase transition, the stop-go and start-up behavioral parameters are collected at four intersections in Shanghai, China. Sensitivity analysis is then performed to identify the most significant factors that influence the occurrence of traffic conflicts during the phase transition. Based on the above analysis results, case studies were finally done to look into safety performance of the two scenarios of phase tran- sition signals, indicated by the distributions of post encroachment time at the conflict point and the occurring probability of extremely small post encroachment times. Research result shows the transition signal combination of green countdown + red countdown tends to cause traffic accidents more easily and thus less safe compared to the transition signal combination of flashing green + red-yellow. Unlike the conventional method generally based on the deterministic traffic flow theory, the proposed methodology has a wide application. With the aid of it, traffic engineers are capable of designing transition signals in a more scientific manner

Hydrothermal combustion synthesis and characterization of Sr2CeO4 phosphor powders

In this paper, the blue-light-emitting Sr2CeO4 phosphor powders were prepared by hydrothermal combustion reactions and a subsequent sintering process. During the process, the mixed urea and glycine were both used as leavening agent and fuel. The particle crystallization, surface morphology as well as the luminescence intensities of the Sr2CeO4 phosphor powders were effectively improved by adjusting the amount of glycine and post-sintering temperatures. The Sr2CeO4 phosphor exhibited strong crystallization and well-distributed spherical particle after optimization. Moreover, the intense blue-light emission band with the maximum at 468 nm in the range of 400–600 nm was observed as excited with ultraviolet light 277 nm. In particular, after the precursors were heat-treated at 1100 °C, the samples could be well-excited around 350 nm. The excitation bands were ascribed to the charge transfer from O to Ce, and the enlarged excitation range may facilitate its uses in optoelectronic fields.publishe

Ln3+ (Ln = Eu, Dy) - doped Sr2CeO4 fine phosphor particles: wet chemical preparation, energy transfer and tunable luminescence

The Sr2CeO4:Ln3+ (Ln = Eu, Dy) fine phosphor particles were prepared by a facile wet chemical approach, in which the consecutive hydrothermal-combustion reaction was performed. The doping of Ln3+ into Sr2CeO4 has little influence on the structure of host, and the as-prepared samples display well-crystallized spherical or elliptical shape with an average particle size at about 100–200 nm. For Eu3+ ions-doped Sr2CeO4, with the increase of Eu3+-doping concentration, the blue light emission band with the maximum at 468 nm originating from a Ce4+ → O2− charge transfer of the host decreases obviously and the characteristic red light emission of Eu3+ (5D0→7F2 transition at 618 nm) is enhanced gradually. Simultaneously, the fluorescent lifetime of the broadband emission of Sr2CeO4 decreases with the doping of Eu3+, indicating an efficient energy transfer from the host to the doping Eu3+ ions. The energy transfer efficiency from the host to Eu3+ was investigated in detail, and the emitting color of Sr2CeO4:Eu3+ can be easily tuned from blue to red by varying the doping concentration of Eu3+ ions. Moreover, the luminescence of Dy3+-doped Sr2CeO4 was also studied. Similar energy transfer phenomenon can be observed, and the incorporation of Dy3+ into Sr2CeO4 host leads to the characteristic emission of 4F9/2 → 6H15/2 (488 nm, blue light) and 4F9/2 → 6H13/2 (574 nm, yellow light) of Dy3+. The Sr2CeO4:Ln3+ fine particles with tunable luminescence are quite beneficial for its potential applications in the optoelectronic fields.publishe

Prediction of recurrence of ischemic stroke within 1 year of discharge based on machine learning MRI radiomics

PurposeThis study aimed to investigate the value of a machine learning-based magnetic resonance imaging (MRI) radiomics model in predicting the risk of recurrence within 1 year following an acute ischemic stroke (AIS).MethodsThe MRI and clinical data of 612 patients diagnosed with AIS at the Second Affiliated Hospital of Nanchang University from March 1, 2019, to March 5, 2021, were obtained. The patients were divided into recurrence and non-recurrence groups according to whether they had a recurrent stroke within 1 year after discharge. Randomized splitting was used to divide the data into training and validation sets using a ratio of 7:3. Two radiologists used the 3D-slicer software to label the lesions on brain diffusion-weighted (DWI) MRI sequences. Radiomics features were extracted from the annotated images using the pyradiomics software package, and the features were filtered using the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. Four machine learning algorithms, logistic regression (LR), Support Vector Classification (SVC), LightGBM, and Random forest (RF), were used to construct a recurrence prediction model. For each algorithm, three models were constructed based on the MRI radiomics features, clinical features, and combined MRI radiomics and clinical features. The sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) were used to compare the predictive efficacy of the models.ResultsTwenty features were selected from 1,037 radiomics features extracted from DWI images. The LightGBM model based on data with three different features achieved the best prediction accuracy from all 4 models in the validation set. The LightGBM model based solely on radiomics features achieved a sensitivity, specificity, and AUC of 0.65, 0.671, and 0.647, respectively, and the model based on clinical data achieved a sensitivity, specificity, and AUC of 0.7, 0.799, 0.735, respectively. The sensitivity, specificity, and AUC of the LightGBM model base on both radiomics and clinical features achieved the best performance with a sensitivity, specificity, and AUC of 0.85, 0.805, 0.789, respectively.ConclusionThe ischemic stroke recurrence prediction model based on LightGBM achieved the best prediction of recurrence within 1 year following an AIS. The combination of MRI radiomics features and clinical data improved the prediction performance of the model

The NLRP3 inflammasome is involved in resident intruder paradigm-induced aggressive behaviors in mice

Background: Aggressive behaviors are one of the most important negative behaviors that seriously endangers human health. Also, the central para-inflammation of microglia triggered by stress can affect neurological function, plasticity, and behavior. NLRP3 integrates stress-related signals and is a key driver of this neural para-inflammation. However, it is unclear whether the NLRP3 inflammasome is implicated in the development of aggressive behaviors.Methods: First, aggressive behavior model mice were established using the resident intruder paradigm. Then, aggressive behaviors were determined with open-field tests (OFT), elevated plus-maze (EPM), and aggressive behavior tests (AT). Moreover, the expression of P2X7R and NLRP3 inflammasome complexes were assessed by immunofluorescence and Western blot. The levels of NLRP3 and inflammatory cytokines were evaluated using enzyme-linked immunosorbent assay (ELISA) kits. Finally, nerve plasticity damage was observed by immunofluorescence, transmission electron microscope, and BrdU staining.Results: Overall, the resident intruder paradigm induced aggressive behaviors, activated the hippocampal P2X7R and NLRP3 inflammasome, and promoted the release of proinflammatory cytokines IL-1β in mice. Moreover, NLRP3 knockdown, administration of P2X7R antagonist (A804598), and IL-1β blocker (IL-1Ra) prevented NLRP3 inflammasome-driven inflammatory responses and ameliorated resident intruder paradigm-induced aggressive behaviors. Also, the resident intruder paradigm promoted the activation of mouse microglia, damaging synapses in the hippocampus, and suppressing hippocampal regeneration in mice. Besides, NLRP3 knockdown, administration of A804598, and IL-1Ra inhibited the activation of microglia, improved synaptic damage, and restored hippocampal regeneration.Conclusion: The NLRP3 inflammasome-driven inflammatory response contributed to resident intruder paradigm-induced aggressive behavior, which might be related to neuroplasticity. Therefore, the NLRP3 inflammasome can be a potential target to treat aggressive behavior-related mental illnesses

The oyster genome reveals stress adaptation and complexity of shell formation

The Pacific oyster Crassostrea gigas belongs to one of the most species-rich but genomically poorly explored phyla, the Mollusca. Here we report the sequencing and assembly of the oyster genome using short reads and a fosmid-pooling strategy, along with transcriptomes of development and stress response and the proteome of the shell. The oyster genome is highly polymorphic and rich in repetitive sequences, with some transposable elements still actively shaping variation. Transcriptome studies reveal an extensive set of genes responding to environmental stress. The expansion of genes coding for heat shock protein 70 and inhibitors of apoptosis is probably central to the oyster's adaptation to sessile life in the highly stressful intertidal zone. Our analyses also show that shell formation in molluscs is more complex than currently understood and involves extensive participation of cells and their exosomes. The oyster genome sequence fills a void in our understanding of the Lophotrochozoa. © 2012 Macmillan Publishers Limited. All rights reserved

Bile acid receptors link nutrient sensing to metabolic regulation

Non-alcoholic fatty liver disease (NAFLD) is a common liver disease in Western populations. Non-alcoholic steatohepatitis (NASH) is a more debilitating form of NAFLD characterized by hepatocellular injury and inflammation, which significantly increase the risk of end-stage liver and cardiovascular diseases. Unfortunately, there are no available drug therapies for NASH. Bile acids are physiological detergent molecules that are synthesized from cholesterol exclusively in the hepatocytes. Bile acids circulate between the liver and intestine, where they are required for cholesterol solubilization in the bile and dietary fat emulsification in the gut. Bile acids also act as signaling molecules that regulate metabolic homeostasis and inflammatory processes. Many of these effects are mediated by the bile acid-activated nuclear receptor farnesoid X receptor (FXR) and the G protein-coupled receptor TGR5. Nutrient signaling regulates hepatic bile acid synthesis and circulating plasma bile acid concentrations, which in turn control metabolic homeostasis. The FXR agonist obeticholic acid has had beneficial effects on NASH in recent clinical trials. Preclinical studies have suggested that the TGR5 agonist and the FXR/TGR5 dual agonist are also potential therapies for metabolic liver diseases. Extensive studies in the past few decades have significantly improved our understanding of the metabolic regulatory function of bile acids, which has provided the molecular basis for developing promising bile acid-based therapeutic agents for NASH treatment. Keywords: Nuclear receptor, TGR5, Metabolic syndromes, Fatty liver diseas

Unique water H-bonding types on metal surfaces: from the bonding nature to cooperativity rules

Understanding the nature of H-bonding interactions is essential to modern sciences, such as biology, chemistry, and physics. Using density functional theory calculations, herein, we have identified two unique H-bonding types existing in a single sheet of a mixed water–hydroxyl phase on close-packed metal surfaces, in sharp contrast to conventional H-bonds in liquid water and water ices. Interestingly, the shallow H-bonds show reduced electrostatic and Pauli repulsion interactions, with an electrostatic polar character resulted from complete σ resonances, whereas the deep H-bonds exhibit enhanced electrostatic and Pauli repulsion interactions, with an electrostatic dipolar feature originated from hybrid orbital interactions. A trade-off-like cooperativity law of the two types of H-bonds was discovered, that is, strengthening in the internal bonds (dO–H) leads to weakening in the external bonds (dO:H) or vice versa. However, the shallow H-bonds exhibit a non-linear cooperativity, whereas the deep H-bonds show a linear cooperativity. We also identified an oxygen backbone cooperativity rule that strengthening the adsorbate–metal interactions has a net effect in analogy to reducing the O–O repulsion within the adlayer. Furthermore, we have discovered several universality classes in geometrical, vibrational, and electronic spaces for the two H-bonding types. Although shared by electronic universality classes, the two contrasting H-bonding types are featured by divergent trends with significant overlapping, where competitive variations in the electrostatic and Pauli repulsion strengths are basic rules for the cooperative H-bonding types. The knowledge of the unconventional H-bonding types expands our current understanding of H-bonding interactions in liquid water and water ices and points to the importance of H-bonding manipulation at electronic levels. These findings not only shed new light on probing the fundamental nature of H-bonds in general but also have insightful implications for resolving the cooperative H-bonding nature of interfacial water, liquid water, water ices, and aqueous solutions.Published versionThis work was supported by Na- tional Natural Science Foundation of China under Contract No. 21875024