HybridFusion: LiDAR and Vision Cross-Source Point Cloud Fusion

Recently, cross-source point cloud registration from different sensors has become a significant research focus. However, traditional methods confront challenges due to the varying density and structure of cross-source point clouds. In order to solve these problems, we propose a cross-source point cloud fusion algorithm called HybridFusion. It can register cross-source dense point clouds from different viewing angle in outdoor large scenes. The entire registration process is a coarse-to-fine procedure. First, the point cloud is divided into small patches, and a matching patch set is selected based on global descriptors and spatial distribution, which constitutes the coarse matching process. To achieve fine matching, 2D registration is performed by extracting 2D boundary points from patches, followed by 3D adjustment. Finally, the results of multiple patch pose estimates are clustered and fused to determine the final pose. The proposed approach is evaluated comprehensively through qualitative and quantitative experiments. In order to compare the robustness of cross-source point cloud registration, the proposed method and generalized iterative closest point method are compared. Furthermore, a metric for describing the degree of point cloud filling is proposed. The experimental results demonstrate that our approach achieves state-of-the-art performance in cross-source point cloud registration

BMAL1 but not CLOCK is associated with monochromatic green light-induced circadian rhythm of melatonin in chick pinealocytes

The avian pineal gland, an independent circadian oscillator, receives external photic cues and translates them for the rhythmical synthesis of melatonin. Our previous study found that monochromatic green light could increase the secretion of melatonin and expression of CLOCK and BMAL1 in chick pinealocytes. This study further investigated the role of BMAL1 and CLOCK in monochromatic green light-induced melatonin secretion in chick pinealocytes using siRNAs interference and overexpression techniques. The results showed that si-BMAL1 destroyed the circadian rhythms of AANAT and melatonin, along with the disruption of the expression of all the seven clock genes, except CRY1. Furthermore, overexpression of BMAL1 also disturbed the circadian rhythms of AANAT and melatonin, in addition to causing arrhythmic expression of BMAL1 and CRY1/2, but had no effect on the circadian rhythms of CLOCK, BMAL2 and PER2/3. The knockdown or overexpression of CLOCK had no impact on the circadian rhythms of AANAT, melatonin, BMAL1 and PER2, but it significantly deregulated the circadian rhythms of CLOCK, BMAL2, CRY1/2 and PER3. These results suggested that BMAL1 rather than CLOCK plays a critical role in the regulation of monochromatic green light-induced melatonin rhythm synthesis in chicken pinealocytes. Moreover, both knockdown and overexpression of BMAL1 could change the expression levels of CRY2, it indicated CRY2 may be involved in the BMAL1 pathway by modulating the circadian rhythms of AANAT and melatonin

ClusterFusion: Real-time Relative Positioning and Dense Reconstruction for UAV Cluster

As robotics technology advances, dense point cloud maps are increasingly in demand. However, dense reconstruction using a single unmanned aerial vehicle (UAV) suffers from limitations in flight speed and battery power, resulting in slow reconstruction and low coverage. Cluster UAV systems offer greater flexibility and wider coverage for map building. Existing methods of cluster UAVs face challenges with accurate relative positioning, scale drift, and high-speed dense point cloud map generation. To address these issues, we propose a cluster framework for large-scale dense reconstruction and real-time collaborative localization. The front-end of the framework is an improved visual odometry which can effectively handle large-scale scenes. Collaborative localization between UAVs is enabled through a two-stage joint optimization algorithm and a relative pose optimization algorithm, effectively achieving accurate relative positioning of UAVs and mitigating scale drift. Estimated poses are used to achieve real-time dense reconstruction and fusion of point cloud maps. To evaluate the performance of our proposed method, we conduct qualitative and quantitative experiments on real-world data. The results demonstrate that our framework can effectively suppress scale drift and generate large-scale dense point cloud maps in real-time, with the reconstruction speed increasing as more UAVs are added to the system

ShRNA-Targeted Centromere Protein A Inhibits Hepatocellular Carcinoma Growth

Centromere protein A (CENP-A) plays important roles in cell-cycle regulation and genetic stability. Herein, we aimed to investigate its expression pattern, clinical significance, and biological function in hepatocellular carcinoma (HCC).. Conversely, CENP-A overexpression promoted HCC cell growth and reduced apoptosis. Furthermore, many genes implicated in cell-cycle regulation and apoptosis, including CHK2, P21waf1, P27 Kip1, SKP2, cyclin G1, MDM2, Bcl-2, and Bax, were deregulated by manipulating CENP-A.Overexpression of CENP-A is frequently observed in HCC. Targeting CENP-A can inhibit HCC growth, likely through the regulation of a large number genes involved in cell-cycle progression and apoptosis, and thereby represents a potential therapeutic strategy for this malignancy

(1)H NMR-based metabonomics study of urine and serum samples from diabetic db/db mice

A metabonomics approach based on high resolution (1)H NMR spectroscopy was applied to investigate the metabolite fingerprints in urine and serum samples from db/db mice of 8 weeks old, an animal model of type 2 diabetes mellitus (T2DM). Both NMR spectra and metabonomics results were discussed and the variations on related metabolic pathway were analyzed. The urinary excretions of diabetic mice have elevated levels of citrate, alanine, acetate, TMAO, hippurate, taurine, creatinine, succinate, pyruvate, glycine in addition to evident increase of glucose compared to the control ones. The metabolic variation in serum samples of db/db mice is marked by the increases of lactate, 3-hydroxybutyrate, glutamine, glutamate and choline and the decreases of leucine and valine. These results indicate that NMR-based metabonomics is an efficient approach for investigating the subtle metabolic alterations in urine and serum from diabetic mice and the findings of the characteristic metabolites would be helpful for early diagnosis and prevention of T2DM and its related complications

Construction and validation of a nomogram of risk factors for new-onset atrial fibrillation in advanced lung cancer patients after non-surgical therapy

ObjectiveRisk factors of new-onset atrial fibrillation (NOAF) in advanced lung cancer patients are not well defined. We aim to construct and validate a nomogram model between NOAF and advanced lung cancer.MethodsWe retrospectively enrolled 19484 patients with Stage III-IV lung cancer undergoing first-line antitumor therapy in Shanghai Chest Hospital between January 2016 and December 2020 (15837 in training set, and 3647 in testing set). Patients with pre-existing AF, valvular heart disease, cardiomyopathy were excluded. Logistic regression analysis and propensity score matching (PSM) were performed to identify predictors of NOAF, and nomogram model was constructed and validated.ResultsA total of 1089 patients were included in this study (807 in the training set, and 282 in the testing set). Multivariate logistic regression analysis showed that age, c-reactive protein, centric pulmonary carcinoma, and pericardial effusion were independent risk factors, the last two of which were important independent risk factors as confirmed by PSM analysis. Nomogram included independent risk factors of age, c-reactive protein, centric pulmonary carcinoma, and pericardial effusion. The AUC was 0.716 (95% CI 0.661–0.770) and further evaluation of this model showed that the C-index was 0.716, while the bias-corrected C-index after internal validation was 0.748 in the training set. The calibration curves presented good concordance between the predicted and actual outcomes.ConclusionCentric pulmonary carcinoma and pericardial effusion were important independent risk factors for NOAF besides common ones in advanced lung cancer patients. Furthermore, the new nomogram model contributed to the prediction of NOAF

Reconstruction of Self-Sparse 2D NMR Spectra from Undersampled Data in the Indirect Dimension†

Reducing the acquisition time for two-dimensional nuclear magnetic resonance (2D NMR) spectra is important. One way to achieve this goal is reducing the acquired data. In this paper, within the framework of compressed sensing, we proposed to undersample the data in the indirect dimension for a type of self-sparse 2D NMR spectra, that is, only a few meaningful spectral peaks occupy partial locations, while the rest of locations have very small or even no peaks. The spectrum is reconstructed by enforcing its sparsity in an identity matrix domain with ℓp (p = 0.5) norm optimization algorithm. Both theoretical analysis and simulation results show that the proposed method can reduce the reconstruction errors compared with the wavelet-based ℓ1 norm optimization

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

The original version of this article unfortunately contained a mistake