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.

The impact of paramagnetic rim lesions on cortical thickness and gray to white matter contrast in relapsing-remitting multiple sclerosis.

Background: Paramagnetic rim lesions (PRLs) on susceptibility magnetic resonance sequences have been suggested as an imaging marker of disease progression in multiple sclerosis. This retrospective cross-sectional study aimed to investigate the impact of PRLs on cortical thickness and gray matter (GM) to white matter (WM) contrast in relapsing-remitting multiple sclerosis (RRMS). Methods: A total of 82 RRMS patients (40 patients with at least 1 PRL and 42 patients without PRL) and 43 healthy controls (HC) were included in this study. The T1-weighted images (T1WI) were processed with the FreeSurfer pipeline. GM to WM signal intensity ratio (GWR) was obtained from T1WI by dividing the GM signal intensity by the WM signal intensity for each vertex. Group differences in cortical thickness and GWR were tested on reconstructed cortical surface. Results: Compared to HC, patients with PRL had thinner mean cortical thickness (P<0.001), higher mean GWR (P=0.001), and lower brain structure volumes (cortex volume, P=0.001; WM volume, P<0.001; deep GM volume, P<0.001). Vertex-based analysis found significant cortical thinning in several regions and increased GWR in a wider range of regions in patients with PRL. The two types of clusters had both overlapping regions and independent regions. However, in patients without PRL, only a few regions showed significant cortical thickness changes. Correlation analysis found that in patients with PRL, only PRL volume showed a significant negative correlation with mean cortical thickness (P=0.048), and PRL volume and count, non-PRL count, and total lesion volume were significantly and positively correlated with mean GWR (P<0.05). Conclusions: There were significant changes in cortical thickness, GWR, and brain structure volume in RRMS patients with PRL that may contribute to further understanding of the pathological mechanisms underlying neurological tissue damage.

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.

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.

Large-scale functional network connectivity mediates the association between nigral neuromelanin hypopigmentation and motor impairment in Parkinson's disease.

Neuromelanin hypopigmentation within substantia nigra pars compacta (SNc) reflects the loss of pigmented neurons, which in turn contributes to the dysfunction of the nigrostriatal and striato-cortical pathways in Parkinson's disease (PD). Our study aims to investigate the relationships between SN degeneration manifested by neuromelanin reduction, functional connectivity (FC) among large-scale brain networks, and motor impairment in PD. This study included 68 idiopathic PD patients and 32 age-, sex- and education level-matched healthy controls who underwent neuromelanin-sensitive magnetic resonance imaging (MRI), functional MRI, and motor assessments. SN integrity was measured using the subregional contrast-to-noise ratio calculated from neuromelanin-sensitive MRI. Resting-state FC maps were obtained based on the independent component analysis. Subsequently, we performed partial correlation and mediation analyses in SN degeneration, network disruption, and motor impairment for PD patients. We found significantly decreased neuromelanin within SN and widely altered inter-network FCs, mainly involved in the basal ganglia (BG), sensorimotor and frontoparietal networks in PD. In addition, decreased neuromelanin content was negatively correlated with the dorsal sensorimotor network (dSMN)-medial visual network connection (P = 0.012) and dSMN-BG connection (P = 0.004). Importantly, the effect of SN neuromelanin hypopigmentation on motor symptom severity in PD is partially mediated by the increased connectivity strength between BG and dSMN (indirect effect = - 1.358, 95% CI: - 2.997, - 0.147). Our results advanced our understanding of the interactions between neuromelanin hypopigmentation in SN and altered FCs of functional networks in PD and suggested the potential of multimodal metrics for early diagnosis and monitoring the response to therapies.

A normative modeling approach to quantify white matter changes and predict functional outcomes in stroke patients.

Objectives: The diverse nature of stroke necessitates individualized assessment, presenting challenges to case-control neuroimaging studies. The normative model, measuring deviations from a normal distribution, provides a solution. We aim to evaluate stroke-induced white matter microstructural abnormalities at group and individual levels and identify potential prognostic biomarkers. Methods: Forty-six basal ganglia stroke patients and 46 healthy controls were recruited. Diffusion-weighted imaging and clinical assessment were performed within 7 days after stroke. We used automated fiber quantification to characterize intergroup alterations of segmental diffusion properties along 20 fiber tracts. Then each patient was compared to normative reference (46 healthy participants) by Mahalanobis distance tractometry for 7 significant fiber tracts. Mahalanobis distance-based deviation loads (MaDDLs) and fused MaDDLmulti were extracted to quantify individual deviations. We also conducted correlation and logistic regression analyses to explore relationships between MaDDL metrics and functional outcomes. Results: Disrupted microstructural integrity was observed across the left corticospinal tract, bilateral inferior fronto-occipital fasciculus, left inferior longitudinal fasciculus, bilateral thalamic radiation, and right uncinate fasciculus. The correlation coefficients between MaDDL metrics and initial functional impairment ranged from 0.364 to 0.618 (p < 0.05), with the highest being MaDDLmulti. Furthermore, MaDDLmulti demonstrated a significant enhancement in predictive efficacy compared to MaDDL (integrated discrimination improvement [IDI] = 9.62%, p = 0.005) and FA (IDI = 34.04%, p < 0.001) of the left corticospinal tract. Conclusion: MaDDLmulti allows for assessing behavioral disorders and predicting prognosis, offering significant implications for personalized clinical decision-making and stroke recovery. Importantly, our method demonstrates prospects for widespread application in heterogeneous neurological diseases.

An engineered influenza virus to deliver antigens for lung cancer vaccination.

The development of cancer neoantigen vaccines that prime the anti-tumor immune responses has been hindered in part by challenges in delivery of neoantigens to the tumor. Here, using the model antigen ovalbumin (OVA) in a melanoma model, we demonstrate a chimeric antigenic peptide influenza virus (CAP-Flu) system for delivery of antigenic peptides bound to influenza A virus (IAV) to the lung. We conjugated attenuated IAVs with the innate immunostimulatory agent CpG and, after intranasal administration to the mouse lung, observed increased immune cell infiltration to the tumor. OVA was then covalently displayed on IAV-CPG using click chemistry. Vaccination with this construct yielded robust antigen uptake by dendritic cells, a specific immune cell response and a significant increase in tumor-infiltrating lymphocytes compared to peptides alone. Lastly, we engineered the IAV to express anti-PD1-L1 nanobodies that further enhanced regression of lung metastases and prolonged mouse survival after rechallenge. Engineered IAVs can be equipped with any tumor neoantigen of interest to generate lung cancer vaccines.

A new magnetic state selection method in high-performance optically detected compact cesium beam clocks.

We perform a new scheme of magnetic state selection in optically detected compact cesium beam clocks. Unlike the conventional method, we select atoms in the ground state |F = 4, mF ≠ -4⟩ by pointing the atomic collimator to the convex pole of the magnet realizing the two-wire magnetic field and detect atoms in |F = 3⟩ after interacting with the microwave field using a distributed feedback laser. The fluorescence background is greatly reduced as the inherent residual atoms |F = 4, mF = -4⟩ are avoided in this reversed scheme. The velocity distribution is narrowed, and the most probable velocity is decreased, since atomic trajectories are close to the weak-field region. We also investigate the relationship between the position of the atomic collimator and the distributions of the atomic beam, which is consistent with the Monte Carlo-based simulation model. By applying the reversed scheme and setting the deviated position of the collimator to 1.3 mm, the signal contrast is improved from 0.7 to 3, and the short-term frequency stability reaches 3.0 × 10-12 τ-1/2, nearly three times better than that of the high-performance version of Microsemi 5071A.

Diffusion along the perivascular space as a potential biomarker for glioma grading and isocitrate dehydrogenase 1 mutation status prediction.

Background: The diffusion tensor image analysis along the perivascular space (DTI-ALPS) may have the potential to reflect glymphatic dysfunction in patients with glioma. The study aimed to determine the correlation of DTI-ALPS with glioma grade and isocitrate dehydrogenase 1 (IDH1) genotype and to then compare the ALPS index with other diffusion metrics. Methods: In this study, 81 patients with glioma and 31 healthy controls underwent magnetic resonance imaging (MRI) examination. The ALPS-index, fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK) were calculated. Comparisons were made between the left and right hemispheres and between patients and controls. IDH1 status was compared after age adjustment. The diagnostic performance of each metric was assessed via receiver operating characteristic (ROC) analysis. Results: In patients with glioma, the ALPS-index of the hemisphere ipsilateral to glioma was significantly lower than that of the hemisphere contralateral to glioma (1.417±0.177 vs. 1.478±0.165; P=0.002), and the bilateral ALPS-index values in patients were significantly decreased compared with those in healthy controls. The ALPS-index was significantly higher in lower-grade gliomas (LrGGs) than that in glioblastomas (GBMs) (1.495±0.151 vs. 1.320±0.159; P<0.001) and was significantly lower in IDH1-wild-type LrGGs than in IDH1-mutant LrGGs (1.400±0.185 vs. 1.530±0.123; P=0.036). FA, MD, and MK also showed significant differences between LrGGs and GBMs and between IDH1-mutant and IDH1-wild-type LrGGs (P<0.05). Furthermore, the combination of the ALPS-index with FA, MD, or MK, exhibited superior discrimination ability compared to each metric used alone. The ALPS-index combined with MD had the highest area under the curve (AUC) of 0.854 as compared to that of 0.614-0.807 for a single metric in glioma grading, while for IDH1 mutation prediction, this combination had the highest AUC of 0.861 as compared to that of 0.707-0.778 for a single metric. Conclusions: The reduced ALPS-index may reflect tumor-induced glymphatic system impairment, and the ALPS-index may be able to complement conventional diffusion metrics in glioma grading and IDH1 genotyping.

Enhanced Resonance for Facilitated Modulation of Large-Area Perovskite Films with Stable Photovoltaics.

Upscaling efficient and stable perovskite films is a challenging task in the industrialization of perovskite solar cells partly due to the lack of high-performance hole transport materials (HTMs), which can simultaneously promote hole transport and regulate the quality of perovskite films especially in inverted solar cells. Here, a novel HTM based on N-C = O resonance structure is designed for facilitating the modulation of the crystallization and bottom-surface defects of perovskite films. Benefiting from the resonance interconversion (N-C = O and N+ = C-O- ) in donor-resonance-donor (D-r-D) architecture and interactions with uncoordinated Pb2+ in perovskite, the resulting D-r-D HTM with two donor units exhibits not only excellent hole extraction and transport capacities, but also efficient crystallization modulation of perovskite for high-quality photovoltaic films in large area. The D-r-D HTM-based large-area (1.02 cm2 ) devices exhibit high power conversion efficiencies (PCEs) up to 21.0%. Moreover, the large-area devices have excellent photo-thermal stability, showing only a 2.6% reduction in PCE under continuous AM 1.5G light illumination at elevated temperature (≈65 °C) for over 1320 h without encapsulation.

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.

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.

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.

Partial maximum correntropy regression for robust electrocorticography decoding.

The Partial Least Square Regression (PLSR) method has shown admirable competence for predicting continuous variables from inter-correlated electrocorticography signals in the brain-computer interface. However, PLSR is essentially formulated with the least square criterion, thus, being considerably prone to the performance deterioration caused by the brain recording noises. To address this problem, this study aims to propose a new robust variant for PLSR. To this end, the maximum correntropy criterion (MCC) is utilized to propose a new robust implementation of PLSR, called Partial Maximum Correntropy Regression (PMCR). The half-quadratic optimization is utilized to calculate the robust projectors for the dimensionality reduction, and the regression coefficients are optimized by a fixed-point optimization method. The proposed PMCR is evaluated with a synthetic example and a public electrocorticography dataset under three performance indicators. For the synthetic example, PMCR realized better prediction results compared with the other existing methods. PMCR could also abstract valid information with a limited number of decomposition factors in a noisy regression scenario. For the electrocorticography dataset, PMCR achieved superior decoding performance in most cases, and also realized the minimal neurophysiological pattern deterioration with the interference of the noises. The experimental results demonstrate that, the proposed PMCR could outperform the existing methods in a noisy, inter-correlated, and high-dimensional decoding task. PMCR could alleviate the performance degradation caused by the adverse noises and ameliorate the electrocorticography decoding robustness for the brain-computer interface.

A Fault Diagnosis Method of Four-Mass Vibration MEMS Gyroscope Based on ResNeXt-50 with Attention Mechanism and Improved EWT Algorithm.

In this paper, a fault identification algorithm combining a signal processing algorithm and machine learning algorithm is proposed, using a four-mass vibration MEMS gyroscope (FMVMG) for signal acquisition work, constructing a gyroscope fault dataset, and performing the model training task based on this dataset. Combining the improved EWT algorithm with SEResNeXt-50 reduces the impact of white noise in the signal on the identification task and significantly improves the accuracy of fault identification. The EWT algorithm is a wavelet analysis algorithm with adaptive wavelet analysis, which can significantly reduce the impact of boundary effects, and has a good effect on decomposition of signal segments with short length, but a reconstruction method is needed to effectively separate the noise signal and effective signal, and so this paper uses multiscale permutation entropy for calculation. For the reason that the neural network has a better ability to characterize high-dimensional signals, the one-dimensional signal is reconstructed into a two-dimensional image signal and the signal features are extracted. Then, the constructed image signals are fed into the SEResNeXt-50 network, and the characterization ability of the model is further improved in the network with the addition of the Squeeze-and-Excitation module. Finally, the proposed model is applied to the FMVMG fault dataset and compared with other models. In terms of recognition accuracy, the proposed method improves about 30.25% over the BP neural network and about 1.85% over ResNeXt-50, proving the effectiveness of the proposed method.

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.

Fine-scale measurement of the blind spot borders.

The blind spot is both a necessity and a nuisance for seeing. It is the portion of the visual field projecting to where the optic nerve crosses the retina, a region devoid of photoreceptors and hence visual input. The precise way in which vision transitions into blindness at the blind spot border is to date unknown. A chief challenge to map this transition is the incessant movement of the eye, which unavoidably smears measurements across space. In this study, we used high-resolution eye-tracking and state-of-the-art retinal stabilization to finely map the blind spot borders. Participants reported the onset of tiny high-contrast probes that were briefly flashed at precise positions around the blind spot. This method has sufficient resolution to enable mapping of blood vessels from psychophysical measurements. Our data show that, even after accounting for eye movements, the transition zones at the edges of the blind spot are considerable. On the horizontal meridian, the regions with detection rates between 80% and 20% span approximately 25% of the overall width of the blind spot. These borders also vary considerably in size across different axes. These data show that the transition from full visibility to blindness at the blind spot border is not abrupt but occurs over a broad area.