Uncovering a hidden functional role of the XRE-cupin protein PsdR as a novel quorum-sensing regulator in Pseudomonas aeruginosa.

XRE-cupin family proteins containing an DNA-binding domain and a cupin signal-sensing domain are widely distributed in bacteria. In Pseudomonas aeruginosa, XRE-cupin transcription factors have long been recognized as regulators exclusively controlling cellular metabolism pathways. However, their potential functional roles beyond metabolism regulation remain unknown. PsdR, a typical XRE-cupin transcriptional regulator, was previously characterized as a local repressor involved solely in dipeptide metabolism. Here, by measuring quorum-sensing (QS) activities and QS-controlled metabolites, we uncover that PsdR is a new QS regulator in P. aeruginosa. Our RNA-seq analysis showed that rather than a local regulator, PsdR controls a large regulon, including genes associated with both the QS circuit and non-QS pathways. To unveil the underlying mechanism of PsdR in modulating QS, we developed a comparative transcriptome approach named "transcriptome profile similarity analysis" (TPSA). Using this TPSA method, we revealed that PsdR expression causes a QS-null-like transcriptome profile, resulting in QS-inactive phenotypes. Based on the results of TPSA, we further demonstrate that PsdR directly binds to the promoter for the gene encoding the QS master transcription factor LasR, thereby negatively regulating its expression and influencing QS activation. Moreover, our results showed that PsdR functions as a negative virulence regulator, as inactivation of PsdR enhanced bacterial cytotoxicity on host cells. In conclusion, we report on a new QS regulation role for PsdR, providing insights into its role in manipulating QS-controlled virulence. Most importantly, our findings open the door for a further discovery of untapped functions for other XRE-Cupin family proteins.

Uncovering the GacS-mediated role in evolutionary progression through trajectory reconstruction in Pseudomonas aeruginosa.

The genetic diversities of subpopulations drive the evolution of pathogens and affect their ability to infect hosts and cause diseases. However, most studies to date have focused on the identification and characterization of adaptive mutations in single colonies, which do not accurately reflect the phenotypes of an entire population. Here, to identify the composition of variant subpopulations within a pathogen population, we developed a streamlined approach that combines high-throughput sequencing of the entire population cells with genotyping of single colonies. Using this method, we reconstructed a detailed quorum-sensing (QS) evolutionary trajectory in Pseudomonas aeruginosa. Our results revealed a new adaptive mutation in the gacS gene, which codes for a histidine kinase sensor of a two-component system (TCS), during QS evolution. This mutation reduced QS activity, allowing the variant to sweep throughout the whole population, while still being vulnerable to invasion by the emerging QS master regulator LasR-null mutants. By tracking the evolutionary trajectory, we found that mutations in gacS facilitated QS-rewiring in the LasR-null mutant. This rapid QS revertant caused by inactive GacS was found to be associated with the promotion of ribosome biogenesis and accompanied by a trade-off of reduced bacterial virulence on host cells. In conclusion, our findings highlight the crucial role of the global regulator GacS in modulating the progression of QS evolution and the virulence of the pathogen population.

Quantitative susceptibility mapping of multiple system atrophy and Parkinson's disease correlates with neurotransmitter reference maps.

BACKGROUND: Multiple system atrophy (MSA) and Parkinson's disease (PD) are neurodegenerative disorders characterized by α-synuclein pathology, disrupted iron homeostasis and impaired neurochemical transmission. Considering the critical role of iron in neurotransmitter synthesis and transport, our study aims to identify distinct patterns of whole-brain iron accumulation in MSA and PD, and to elucidate the corresponding neurochemical substrates. METHODS: A total of 122 PD patients, 58 MSA patients and 78 age-, sex-matched health controls underwent multi-echo gradient echo sequences and neurological evaluations. We conducted voxel-wise and regional analyses using quantitative susceptibility mapping to explore MSA or PD-specific alterations in cortical and subcortical iron concentrations. Spatial correlation approaches were employed to examine the topographical alignment of cortical iron accumulation patterns with normative atlases of neurotransmitter receptor and transporter densities. Furthermore, we assessed the associations between the colocalization strength of neurochemical systems and disease severity. RESULTS: MSA patients exhibited increased susceptibility in the striatal, midbrain, cerebellar nuclei, as well as the frontal, temporal, occipital lobes, and anterior cingulate gyrus. In contrast, PD patients displayed elevated iron levels in the left inferior occipital gyrus, precentral gyrus, and substantia nigra. The excessive iron accumulation in MSA or PD correlated with the spatial distribution of cholinergic, noradrenaline, glutamate, serotonin, cannabinoids, and opioid neurotransmitters, and the degree of this alignment was related to motor deficits. CONCLUSIONS: Our findings provide evidence of the interaction between iron accumulation and non-dopamine neurotransmitters in the pathogenesis of MSA and PD, which inspires research on potential targets for pharmacotherapy.

The influence of accelerated brain aging on coactivation pattern dynamics in Parkinson's disease.

Aging is widely acknowledged as the primary risk factor for brain degeneration, with Parkinson's disease (PD) tending to follow accelerated aging trajectories. We aim to investigate the impact of structural brain aging on the temporal dynamics of a large-scale functional network in PD. We enrolled 62 PD patients and 32 healthy controls (HCs). The level of brain aging was determined by calculating global and local brain age gap estimates (G-brainAGE and L-brainAGE) from structural images. The neural network activity of the whole brain was captured by identifying coactivation patterns (CAPs) from resting-state functional images. Intergroup differences were assessed using the general linear model. Subsequently, a spatial correlation analysis between the L-brainAGE difference map and CAPs was conducted to uncover the anatomical underpinnings of functional alterations. Compared to HCs (-3.73 years), G-brainAGE was significantly higher in PD patients (+1.93 years), who also exhibited widespread elevation in L-brainAGE. G-brainAGE was correlated with disease severity and duration. PD patients spent less time in CAPs involving activated default mode and the fronto-parietal network (DMN-FPN), as well as the sensorimotor and salience network (SMN-SN), and had a reduced transition frequency from other CAPs to the DMN-FPN and SMN-SN CAPs. Furthermore, the pattern of localized brain age acceleration showed spatial similarities with the SMN-SN CAP. Accelerated structural brain aging in PD adversely affects brain function, manifesting as dysregulated brain network dynamics. These findings provide insights into the neuropathological mechanisms underlying neurodegenerative diseases and imply the possibility of interventions for modifying PD progression by slowing the brain aging process.

Multi-pool chemical exchange saturation transfer MRI in glioma grading, molecular subtyping and evaluating tumor proliferation.

PURPOSE: To evaluate the performance of multi-pool Chemical exchange saturation transfer (CEST) MRI in prediction of glioma grade, isocitrate dehydrogenase (IDH) mutation, alpha-thalassemia/mental retardation syndrome X-linked (ATRX) loss and Ki-67 labeling index (LI), based on the fifth edition of the World Health Organization classification of central nervous system tumors (WHO CNS5). METHODS: 95 patients with adult-type diffuse gliomas were analyzed. The amide, direct water saturation (DS), nuclear Overhauser enhancement (NOE), semi-solid magnetization transfer (MT) and amine signals were derived using Lorentzian fitting, and asymmetry-based amide proton transfer-weighted (APTwasym) signal was calculated. The mean value of tumor region was measured and intergroup differences were estimated using student-t test. The receiver operating curve (ROC) and area under the curve (AUC) analysis were used to evaluate the diagnostic performance of signals and their combinations. Spearman correlation analysis was performed to evaluate tumor proliferation. RESULTS: The amide and DS signals were significantly higher in high-grade gliomas compared to low-grade gliomas, as well as in IDH-wildtype gliomas compared to IDH-mutant gliomas (all p < 0.001). The DS, MT and amine signals showed significantly differences between ATRX loss and retention in grade 2/3 IDH-mutant gliomas (all p < 0.05). The combination of signals showed the highest AUC in prediction of grade (0.857), IDH mutation (0.814) and ATRX loss (0.769). Additionally, the amide and DS signals were positively correlated with Ki-67 LI (both p < 0.001). CONCLUSION: Multi-pool CEST MRI demonstrated good potential to predict glioma grade, IDH mutation, ATRX loss and Ki-67 LI.

Aquaporin ZmTIP2;3 Promotes Drought Resistance of Maize through Symbiosis with Arbuscular Mycorrhizal Fungi.

Arbuscular mycorrhizal fungi symbiosis plays important roles in enhancing plant tolerance to biotic and abiotic stresses. Aquaporins have also been linked to improved drought tolerance in plants and the regulation of water transport. However, the mechanisms that underlie this association remain to be further explored. In this study, we found that arbuscular mycorrhiza fungi symbiosis could induce the gene expression of the aquaporin ZmTIP2;3 in maize roots. Moreover, compared with the wild-type plants, the maize zmtip2;3 mutant also showed a lower total biomass, colonization rate, relative water content, and POD and SOD activities after arbuscular mycorrhiza fungi symbiosis under drought stress. qRT-PCR assays revealed reduced expression levels of stress genes including LEA3, P5CS4, and NECD1 in the maize zmtip2;3 mutant. Taken together, these data suggest that ZmTIP2;3 plays an important role in promoting maize tolerance to drought stress during arbuscular mycorrhiza fungi symbiosis.

Genome-wide identification of nitrate transporter 1/peptide transporter family (NPF) induced by arbuscular mycorrhiza in the maize genome.

The Transporter 1/Peptide Transporter Family (NPF) is essential for the uptake and transport of nitrate nitrogen. Significant increases in nitrogen have been increasingly reported for many mycorrhizal plants, but there are few reports on maize. Here, we have identified the maize NPF family and screened for arbuscular mycorrhiza fungi (AMF) induced NPFs. In this study, a systematic analysis of the maize NPF gene family was performed. A total of 82 NPF genes were identified in maize. ZmNPF4.5 was strongly induced by AMF in both low and high nitrogen. Lotus japonicus hairy root-induced transformation experiments showed that ZmNPF4.5 promoter-driven GUS activity was restricted to cells containing tufts. Yeast backfill experiments indicate that ZmNPF4.5 functions in nitrate uptake. Therefore, we speculate that ZmNPF4.5 is a key gene for nitrate-nitrogen uptake in maize through the mycorrhizal pathway. This is a reference value for further exploring the acquisition of nitrate-nitrogen by maize through AMF pathway. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01464-3.

Incremental Value of Stroke-Induced Structural Disconnection in Predicting Global Cognitive Impairment After Stroke.

BACKGROUND: Poststroke cognitive impairment (PSCI) is highly prevalent in stroke survivors and correlated with unfavorable clinical outcomes. This study aimed to identify the neural substrate of PSCI using atlas-based disconnectome analysis and assess the value of disconnection score, a baseline measure for stroke-induced structural disconnection, in PSCI prediction. METHODS: A multicenter prospective cohort of 676 first-ever patients with acute ischemic stroke was enrolled from 3 independent hospitals in China. Sociodemographic, clinical, and neuroimaging data were collected at acute stage of stroke. Cognitive assessment was performed at 3 months after stroke. Voxel-wise and tract-wise disconnectome analysis were performed to uncover the strategic structural disconnection pattern for global PSCI. Disconnection score was calculated for each participant in leave-one-dataset-out cross-validation. Multivariable logistic regression was performed for the association between disconnection score and PSCI. Prediction models with and without disconnection score were developed, cross-validated, and compared in terms of discrimination and goodness-of-fit. RESULTS: Compared with lesions of non-PSCI, those of PSCI were more likely to have fiber connections with left prefrontal cortex and left deep structures (thalamus and basal ganglia). Disconnection score could predict the risk and severity of PSCI during cross-validation, and was independently associated with PSCI after controlling for all baseline covariates (odds ratio, 1.38 [95% CI, 1.17-1.64]; P<0.001). Incorporating disconnection score into a reference model with 6 known predictors resulted in significant improvement in both discrimination and goodness-of-fit throughout cross-validation. CONCLUSIONS: A strategic structural disconnection pattern centered on left prefrontal cortex, thalamus, and basal ganglia is identified for global PSCI using indirect disconnectome analysis. The baseline disconnection score is independently predictive of PSCI and has significant incremental value to preexisting sociodemographic, clinical, and neuroimaging predictors. REGISTRATION: URL: http://www.chictr.org.cn/enIndex.aspx; Unique identifier: ChiCTR-ROC-17013993.

Individual functional parcellation revealed compensation of dynamic limbic network organization in healthy ageing.

Using group-level functional parcellations and constant-length sliding window analysis, dynamic functional connectivity studies have revealed network-specific impairment and compensation in healthy ageing. However, functional parcellation and dynamic time windows vary across individuals; individual-level ageing-related brain dynamics are uncertain. Here, we performed individual parcellation and individual-length sliding window clustering to characterize ageing-related dynamic network changes. Healthy participants (n = 637, 18-88 years) from the Cambridge Centre for Ageing and Neuroscience dataset were included. An individual seven-network parcellation, varied from group-level parcellation, was mapped for each participant. For each network, strong and weak cognitive brain states were revealed by individual-length sliding window clustering and canonical correlation analysis. The results showed negative linear correlations between age and change ratios of sizes in the default mode, frontoparietal, and salience networks and a positive linear correlation between age and change ratios of size in the limbic network (LN). With increasing age, the occurrence and dwell time of strong states showed inverted U-shaped patterns or a linear decreasing pattern in most networks but showed a linear increasing pattern in the LN. Overall, this study reveals a compensative increase in emotional networks (i.e., the LN) and a decline in cognitive and primary sensory networks in healthy ageing. These findings may provide insights into network-specific and individual-level targeting during neuromodulation in ageing and ageing-related diseases.

Dynamic effective connectivity among large-scale brain networks mediates risk of anxiety.

Anxiety is characterized by altered brain networks. Directional information flows among dynamic brain networks concerning neuropathogenesis of anxiety have not yet been investigated. The role of directional influences between networks in gene-environment effects on anxiety remains to be further elucidated. In a large community sample, this resting-state functional MRI study estimated dynamic effective connectivity among large-scale brain networks based on a sliding-window approach and Granger causality analysis, providing dynamic and directional information for signal transmission in networks. We first explored altered effective connectivity among networks related to anxiety in distinct connectivity states. Due to the potential gene-environment effects on brain and anxiety, we further performed mediation and moderated mediation analyses to investigate the role of altered effective connectivity networks in relationships between polygenic risk scores, childhood trauma, and anxiety. State and trait anxiety scores showed correlations with altered effective connectivity among extensive networks in distinct connectivity states (p < .05, uncorrected). Only in a more frequent and strongly connected state, there were significant correlations between altered effective connectivity networks and trait anxiety (PFDR <0.05). Furthermore, mediation and moderated mediation analyses showed that the effective connectivity networks played a mediating role in the effects of childhood trauma and polygenic risk on trait anxiety. State-dependent effective connectivity changes among brain networks were significantly related to trait anxiety, and mediated gene-environment effects on trait anxiety. Our work sheds novel light on the neurobiological mechanisms underlying anxiety, and provides new insights into early objective diagnosis and intervention evaluation.

Practical security analysis of a continuous-variable source-independent quantum random number generator based on heterodyne detection.

Heterodyne-based continuous-variable source-independent quantum random number generator (CV-SI-QRNG) can produce true random numbers without any assumptions on source. However, practical implementations always contain imperfections, which will greatly influence the extractable randomness and even open loopholes for eavesdroppers to steal information about the final output. In this work, based on the theoretical model, we systematically analyzed the effects of imperfect implementations on the practical security of heterodyne-based CV-SI-QRNG. The influences of local oscillator (LO) fluctuation under imbalanced heterodyne detection are first analyzed. The simulation results show that the lower bound of extractable randomness will be overestimated without considering the influence of LO fluctuation, which will threaten the practical security of CV-SI-QRNG system. Moreover, we analyze the effects of the degree of imbalance and the magnitude of LO fluctuation on evaluating the extractable randomness. Finally, we investigate the impact of an imperfect phase modulator on the practical security of CV-SI-QRNG and find it will reduce the extractable randomness. Our analysis reveals that one should carefully consider the imperfections in the actual implementations of CV-SI-QRNGs.

Spatiotemporal patterns of brain iron-oxygen metabolism in patients with Parkinson's disease.

OBJECTIVES: Iron deposition and mitochondrial dysfunction are closely associated with the genesis and progression of Parkinson's disease (PD). This study aims to extract susceptibility and oxygen extraction fraction (OEF) values of deep grey matter (DGM) to explore spatiotemporal progression patterns of brain iron-oxygen metabolism in PD. METHODS: Ninety-five PD patients and forty healthy controls (HCs) were included. Quantitative susceptibility mapping (QSM) and OEF maps were computed from MRI multi-echo gradient echo data. Analysis of covariance (ANCOVA) was used to compare mean susceptibility and OEF values in DGM between early-stage PD (ESP), advanced-stage PD (ASP) patients and HCs. Then Granger causality analysis on the pseudo-time-series of MRI data was applied to assess the causal effect of early altered nuclei on iron content and oxygen extraction in other DGM nuclei. RESULTS: The susceptibility values in substantia nigra (SN), red nucleus, and globus pallidus (GP) significantly increased in PD patients compared with HCs, while the iron content in GP did not elevate obviously until the late stage. The mean OEF values for the caudate nucleus, putamen, and dentate nucleus were higher in ESP patients than in ASP patients or/and HCs. We also found that iron accumulation progressively expands from the midbrain to the striatum. These alterations were correlated with clinical features and improved AUC for early PD diagnosis to 0.824. CONCLUSIONS: Abnormal cerebral iron deposition and tissue oxygen utilization in PD measured by QSM and OEF maps could reflect pathological alterations in neurodegenerative processes and provide valuable indicators for disease identification and management. CLINICAL RELEVANCE STATEMENT: Noninvasive assessment of cerebral iron-oxygen metabolism may serve as clinical evidence of pathological changes in PD and improve the validity of diagnosis and disease monitoring. KEY POINTS: • Quantitative susceptibility mapping and oxygen extraction fraction maps indicated the cerebral pathology of abnormal iron accumulation and oxygen metabolism in Parkinson's disease. • Iron deposition is mainly in the midbrain, while altered oxygen metabolism is concentrated in the striatum and cerebellum. • The susceptibility and oxygen extraction fraction values in subcortical nuclei were associated with clinical severity.

Poster Session: Spatial-frequency-selective enhancement of visual sensitivity from saccade dynamics.

Eye movements transform a spatial scene into luminance modulations on the retina. Recent work has shown that this transformation is highly structured: within human temporal sensitivity, saccades deliver power that increases in proportion to spatial frequency (SF) up to a critical frequency and remains constant beyond that. Importantly, the critical SF increases with decreasing amplitude. Therefore, at sufficiently low SFs, larger saccades effectively deliver stronger input signals to the retina. Here we tested whether this input reformatting has the predicted perceptual consequences, by examining how large and small saccades (6o & 1o) affect contrast sensitivity. We measured relative sensitivity at two SFs: a reference (0.5 cpd), equal to the critical SF for the small saccade, and a probe at either a lower or higher SF (0.1/2.5 cpd). We predicted that large saccades enhance visibility only when the probe has a lower SF than the reference. Subjects (N=7) made instructed saccades while presented with a plaid of overlapping orthogonal gratings at the two SFs and reported which grating was more visible. Results closely follow theoretical predictions: psychometric functions following small and large saccades only differed with the lower SF probe, in which case the larger saccade significantly enhanced visibility. In sum, saccades enable selectivity not only in the spatial domain, but also in the spatial-frequency domain.

Development of a predictive nomogram for acute respiratory distress syndrome in patients with acute pancreatitis complicated with acute kidney injury.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a common complication in patients with acute pancreatitis (AP), especially when patients complicated with acute kidney injury (AKI), resulting in increased duration of hospitalization and mortality. It is of potential clinical significance to develop a predictive model to identify the the high-risk patients. METHOD: AP patients complicated with AKI from January 2019 to March 2022 were enrolled in this study and randomly divided into training cohort and validation cohort at a ratio of 2:1. The Least absolute shrinkage and selection operator(LASSO) regression and machine learning algorithms were applied to select features. A nomogram was developed based on the multivariate logistic regression. The performance of the nomogram was evaluated by AUC, calibration curves, and decision curve analysis. RESULTS: A total of 292 patients were enrolled in the study, with 206 in the training cohort and 86 in the validation cohort. Multivariate logistic analysis showed that IAP (Odds Ratio (OR)=4.60, 95%CI:1.23-18.24, p = 0.02), shock (OR = 12.99, 95%CI:3.47-64.04, p < 0.001), CRP(OR= 26.19, 95%CI:9.37-85.57, p < 0.001), LDH (OR = 13.13, 95%CI:4.76-40.42, p < 0.001) were independent predictors of ARDS. The nomogram was developed based on IAP, shock, CRP and LDH. The nomogram showed good discriminative ability with an AUC value of 0.954 and 0.995 in the training and validation cohort, respectively. The calibration curve indicating good concordance between the predicted and observed values. The DCA showed favorable net clinical benefit. CONCLUSION: This study developed a simple model for predicting ARDS in AP patients complicated with AKI. The nomogram can help clinicians identify high-risk patients and optimize therapeutic strategies.

Horizontal gene transfer: Driving the evolution and adaptation of plants.

Horizontal gene transfer greatly contributes to the diversification and long-term evolution of green plants. Recent studies suggest that horizontal gene transfer events drove the evolution and adaptation of charophyte green algae and land plants.

The asymmetry of glymphatic system dysfunction in patients with temporal lobe epilepsy: A DTI-ALPS study.

BACKGROUND AND PURPOSE: While the occurrence of glymphatic system dysfunction has been observed in temporal lobe epilepsy (TLE), the potential asymmetry of this system has yet to be investigated in the TLE context. We aimed to investigate the glymphatic system function in both hemispheres and to analyze asymmetric features of the glymphatic system in TLE patients using diffusion tensor image analysis along the perivascular space (DTI-ALPS) method. MATERIALS AND METHODS: 43 patients (left TLE (LTLE), n = 20; right TLE (RTLE), n = 23) and 39 healthy controls (HC) were enrolled in this study. The DTI-ALPS index was calculated for the left (left ALPS index) and right (right ALPS index) hemispheres respectively. An asymmetry index (AI) was calculated by AI = (Right - Left)/ [(Right + Left)/2] to represent the asymmetric pattern. Independent two sample t-test, two-sample paired t-test or one-way ANOVA with Bonferroni correction were conducted to compare the differences in ALPS indices and AI among the groups. RESULTS: Both left ALPS index (p = 0.040) and right ALPS index (p = 0.001) of RTLE patients were significantly decreased, while only left ALPS index of LTLE patients (p = 0.005) was reduced. Compared to contralateral ALPS index, the ipsilateral ALPS index was significantly decreased in TLE (p = 0.008) and RTLE (p = 0.009) patients. Leftward asymmetry of the glymphatic system was found in HC (p = 0.045) and RTLE (p = 0.009) patients. The LTLE patients presented reduced asymmetric traits when compared to RTLE patients (p = 0.029). CONCLUSION: The TLE patients exhibited altered ALPS indices, which could be triggered by glymphatic system dysfunction. Altered ALPS indices were more severe in ipsilateral than in the contralateral hemisphere. Moreover, LTLE and RTLE patients exhibited different change patterns of the glymphatic system. In addition, glymphatic system function presented asymmetric patterns in both normal adult brain and RTLE patients.

Impaired topological properties of cortical morphological brain networks correlate with motor symptoms in Parkinson's disease.

BACKGROUND: Parkinson's disease (PD) is characterized by loss of selectively vulnerable neurons within the basal ganglia circuit and progressive atrophy in subcortical and cortical regions. However, the impact of neurodegenerative pathology on the topological organization of cortical morphological networks has not been explored. The aims of this study were to investigate altered network patterns of covariance in cortical thickness and complexity, and to evaluate how morphological network integrity in PD is related to motor impairment. METHODS: Individual morphological networks were constructed for 50 PD patients and 46 healthy controls (HCs) by estimating interregional similarity distributions in surface-based indices. We performed graph theoretical analysis and network-based statistics to detect PD-related alterations and further examined the correlation of network metrics with clinical scores. Furthermore, support vector regression based on topological characteristics was applied to predict the severity of motor impairment in PD. RESULTS: Compared with HCs, PD patients showed lower local efficiency (p = 0.004), normalized characteristic path length (p = 0.022), and clustering coefficient (p = 0.005) for gyrification index-based morphological brain networks. Nodal topological abnormalities were mainly in the frontal, parietal and temporal regions, and impaired morphological connectivity was involved in the sensorimotor and default mode networks. The support vector regression model using network-based features allowed prediction of motor symptom severity with a correlation coefficient of 0.606. CONCLUSIONS: This study identified a disrupted topological organization of cortical morphological networks that could substantially advance our understanding of the network degeneration mechanism of PD and might offer indicators for monitoring disease progression.

Making graphs compact by lossless contraction.

This paper proposes a scheme to reduce big graphs to small graphs. It contracts obsolete parts and regular structures into supernodes. The supernodes carry a synopsis S Q for each query class Q in use, to abstract key features of the contracted parts for answering queries of Q . Moreover, for various types of graphs, we identify regular structures to contract. The contraction scheme provides a compact graph representation and prioritizes up-to-date data. Better still, it is generic and lossless. We show that the same contracted graph is able to support multiple query classes at the same time, no matter whether their queries are label based or not, local or non-local. Moreover, existing algorithms for these queries can be readily adapted to compute exact answers by using the synopses when possible and decontracting the supernodes only when necessary. As a proof of concept, we show how to adapt existing algorithms for subgraph isomorphism, triangle counting, shortest distance, connected component and clique decision to contracted graphs. We also provide a bounded incremental contraction algorithm in response to updates, such that its cost is determined by the size of areas affected by the updates alone, not by the entire graphs. We experimentally verify that on average, the contraction scheme reduces graphs by 71.9% and improves the evaluation of these queries by 1.69, 1.44, 1.47, 2.24 and 1.37 times, respectively.

Intelligent Nanodelivery System-Generated 1 O2 Mediates Tumor Vessel Normalization by Activating Endothelial TRPV4-eNOS Signaling.

Tumor microenvironment (TME)-responsive intelligent photodynamic therapy (PDT) systems have attracted increasing interest in anticancer therapy, due to their potential to address significant and unsatisfactory therapeutic issues, such as limited tissue penetration, inevitable normal tissue damage, and excessive impaired vessels. Here, an H2 O2 -triggered intelligent LCL/ZnO PDT nanodelivery system is elaborately designed. LCL/ZnO can selectively regulate tumor-derived endothelial cells (TECs) and specifically kill tumor cells, by responding to different H2 O2 gradients in TECs and tumor cells. The LCL/ZnO is able to normalize tumor vessels, thereby resulting in decreased metastases, and ameliorating the immunosuppressive TME. Further analysis demonstrates that singlet oxygen (1 O2 )-activated transient receptor potential vanilloid-4-endothelial nitric oxide synthase signals generated in TECs by LCL/ZnO induce tumor vascular normalization, which is identified as a novel mechanism contributing to the increased ability of PDT to promote cancer therapy. In conclusion, designing an intelligent PDT nanodelivery system response to the TME, that includes both selective TECs regulation and specific tumor-killing, will facilitate the development of effective interventions for future clinical applications.

Light shift suppression with pulsed light detection in magnetic-state-selected cesium beam clocks.

Light detection is widely used in atomic clocks. The simple detecting structure induces the light shift which influences the clock's long-term stability. We introduce a new method to suppress light shift by using pulsed light instead of continuous light to detect atomic states. Under a suitable pulsed sequence, the part of the atoms which do not simultaneously interact with light and microwave field are detected. We demonstrate the validity of our approach in a magnetic-state-selected cesium beam clock. Using a well-tuned sequence, the light shift coefficient is reduced by a factor of about 10, in comparison with the continuous light detection scheme. In a clock stability test with extra light power noise, the result shows good immunity of the method to laser power fluctuations. We also analyze the sources of the clock short-term stability degradation, including the Dick effect and the fact that a reduced number of atoms is detected in the pulsed detection case.