MAC: Maximal Cliques for 3D Registration.

This paper presents a 3D registration method with maximal cliques (MAC) for 3D point cloud registration (PCR). The key insight is to loosen the previous maximum clique constraint and mine more local consensus information in a graph for accurate pose hypotheses generation: 1) A compatibility graph is constructed to render the affinity relationship between initial correspondences. 2) We search for maximal cliques in the graph, each representing a consensus set. 3) Transformation hypotheses are computed for the selected cliques by the SVD algorithm and the best hypothesis is used to perform registration. In addition, we present a variant of MAC if given overlap prior, called MAC-OP. Overlap prior further enhances MAC from many technical aspects, such as graph construction with re-weighted nodes, hypotheses generation from cliques with additional constraints, and hypothesis evaluation with overlap-aware weights. Extensive experiments demonstrate that both MAC and MAC-OP effectively increase registration recall, outperform various state-of-the-art methods, and boost the performance of deep-learned methods. For instance, MAC combined with GeoTransformer achieves a state-of-the-art registration recall of 95.7% / 78.9% on 3DMatch / 3DLoMatch. We perform synthetic experiments on 3DMatch-LIR / 3DLoMatch-LIR, a dataset with extremely low inlier ratios for 3D registration in ultra-challenging cases. Code will be available at: https://github.com/zhangxy0517/3D-Registration-with-Maximal-Cliques.

Association between physical activity and cardiovascular parameters in 7-year-old children: a Chinese cross-sectional study.

INTRODUCTION: Physical activity (PA) is believed to play an important part in many aspects during childhood and adolescence, especially cardiorespiratory fitness and cardiometabolic health. However, whether different levels of PA in daily life influence the structure or function of heart in school-aged children remains unknown. We aimed to investigate the association between PA and cardiovascular parameters in 7-year-old children. METHODS: Follow-up data from the Shanghai Prenatal Cohort Study and the Shanghai Birth Cohort was analyzed. Perinatal information including both maternal and offspring datum was recorded. A refined questionnaire was used to evaluate the frequency and duration of children's PA levels. Blood pressure, echocardiography, and anthropometry assessment were conducted during the follow-up of 7-year-old children. RESULTS: Overall, high PA level was associated with higher left ventricle posterior wall thickness in diastole (LVPWd, ß coefficient: 0.36, 95% CI: 0.12, 0.61), higher left ventricle mass index (LVMI, ß = 0.28, 95% CI: 0.07, 0.48), mitral E/a ratio (ß = 0.47, 95% CI: 0.22, 0.71) and slower heart rate (ß = -0.32, 95% CI: -0.57, -0.07), compared to low PA level. Medium PA level was associated with lower diastolic blood pressure (DBP, ß = -0.18, 95% CI: -0.35, -0.01). In subgroup analysis, increased relative wall thickness (RWT) was found in high PA level boys (ß = 0.36, 95% CI: 0.05, 0.67), and systolic blood pressure (SBP) showed a significant decrease in high PA level girls (ß = -0.42, 95% CI: -0.78, -0.06). CONCLUSIONS: This study suggested non-athlete children having higher PA level were associated with thicker left ventricle (LV) walls and better LV diastolic function, as well as slower heart rate and DBP at the age of 7. Furthermore, disparity in the association between PA level with morphological heart patterns and blood pressure existed in different sex category.

ccdc141 is required for left-right axis development by regulating cilia formation in the Kupffer's vesicle of zebrafish.

Laterality is a crucial physiological process intricately linked to the cilium-centrosome complex during embryo development. Defects in the process can result in severe organ mispositioning. Coiled-coil domain containing 141 (CCDC141) has been previously known as a centrosome-related gene, but its role in left-right (LR) asymmetry has not been characterized. In this study, we utilize the zebrafish model and human exome analysis to elucidate the function of ccdc141 in laterality defects. The knockdown of ccdc141 in zebrafish disrupts early LR signaling pathways, cilia function, and Kupffer's vesicle (KV) formation. Unlike ccdc141-knockdown embryos exhibiting aberrant LR patterns, ccdc141-null mutants show no apparent abnormality, suggesting a genetic compensation response effect. In parallel, we observe a marked reduction in α-tubulin acetylation levels in the ccdc141 crispants. The treatment with histone deacetylase (HDAC) inhibitors, particularly the HDAC6 inhibitor, rescues the ccdc141 crispant phenotypes. Furthermore, exome analysis of 70 patients with laterality defects reveals an increased burden of CCDC141 mutations, with in-vivo studies verifying the pathogenicity of the patient mutation CCDC141-R123G. Our findings highlight the critical role of CCDC141 in ciliogenesis and demonstrate that CCDC141 mutations lead to abnormal LR patterns. Thus, we identify CCDC141 as a causative gene for laterality defects.

Study on temperature field in the process of induction heat treatment with current assisted weld double side method.

At present, in the process of weld induction heat treatment, the common method is to carry out centralized induction heating in the weld area, which will lead to large radial temperature difference of the weld, poor controllability of temperature distribution and easy to cause the defects of residual stress concentration in the weld area. To solve the above problems, this paper adopts the two-sided method to conduct induction heating on both sides of the weld, and at the same time, the auxiliary pulse current is passed into the weld to improve the quality of the weld. ANSYS finite element software is used to establish a multi-field coupling prediction model of electric-magnetic-thermal structure, and explore the distribution law of the auxiliary pulse current and the temperature field of the weld. Finally, an experimental study of pulsed current assisted two-sided induction heating is carried out. Temperature test and metallographic test were carried out respectively to verify the effectiveness of pulsed current assisted induction heating technology.

Homogenizing The Low-Dimensional Phases for Stable 2D-3D Tin Perovskite Solar Cells.

2D-3D tin-based perovskites are considered as promising candidates for achieving efficient lead-free perovskite solar cells (PSCs). However, the existence of multiple low-dimensional phases formed during the film preparation hinders the efficient transport of charge carriers. In addition, the non-homogeneous distribution of low-dimensional phases leads to lattice distortion and increases the defect density, which are undesirable for the stability of tin-based PSCs. Here, mixed spacer cations [diethylamine (DEA+) and phenethylamine (PEA+)] are introduced into tin perovskite films to modulate the distribution of the 2D phases. It is found that compared to the film with only PEA+, the combination of DEA+ and PEA+ favors the formation of homogeneous low-dimensional perovskite phases with three octahedral monolayers (n = 3), especially near the bottom interface between perovskite and hole transport layer. The homogenization of 2D phases help improve the film quality with reduced lattice distortion and released strain. With these merits, the tin PSC shows significantly improved stability with 94% of its initial efficiency retained after storing in a nitrogen atmosphere for over 4600 h, and over 80% efficiency maintained after continuous illumination for 400 h.

Hole Localization in Bulk and 2D Lead-Halide Perovskites Studied by Time-Resolved Infrared Spectroscopy.

Scattering and localization dynamics of charge carriers in the soft lattice of lead-halide perovskites impact polaron formation and recombination, which are key mechanisms of material function in optoelectronic devices. In this study, we probe the photoinduced lattice and carrier dynamics in perovskite thin films (CsFAPbX3, X = I, Br) using time-resolved infrared spectroscopy. We examine the CN stretching mode of formamidinium (FA) cations located within the lead-halide octahedra of the perovskite structure. Our investigation reveals the formation of an infrared mode due to spatial symmetry breaking within a hundred picoseconds in 3D perovskites. Experiments at cryogenic temperatures show much-reduced carrier localization, in agreement with a localization mechanism that is driven by the dynamic disorder. We extend our analysis to 2D perovskites, where the precise nature of charge carriers is uncertain. Remarkably, the signatures of charge localization we found in bulk perovskites are not observed for 2D Ruddlesden-Popper perovskites ((HexA)2FAPb2I7). This observation implies that the previously reported stabilization of free charge carriers in these materials follows different mechanisms than polaron formation in bulk perovskites. Through the exploration of heterostructures with electron/hole excess, we provide evidence that holes drive the formation of the emerging infrared mode.

Astrocyte reactivity is associated with tau tangle load and cortical thinning in Alzheimer's disease.

BACKGROUND: It is not fully established whether plasma ß-amyloid(Aß)42/Aß40 and phosphorylated Tau181 (p-Tau181) can effectively detect Alzheimer's disease (AD) pathophysiology in older Chinese adults and how these biomarkers correlate with astrocyte reactivity, Aß plaque deposition, tau tangle aggregation, and neurodegeneration. METHODS: We recruited 470 older adults and analyzed plasma Aß42/Aß40, p-Tau181, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) using the Simoa platform. Among them, 301, 195, and 70 underwent magnetic resonance imaging, Aß and tau positron emission tomography imaging. The plasma Aß42/Aß40 and p-Tau181 thresholds were defined as ≤0.0609 and ≥2.418 based on the receiver operating characteristic curve analysis using the Youden index by comparing Aß-PET negative cognitively unimpaired individuals and Aß-PET positive cognitively impaired patients. To evaluate the feasibility of using plasma Aß42/Aß40 (A) and p-Tau181 (T) to detect AD and understand how astrocyte reactivity affects this process, we compared plasma GFAP, Aß plaque, tau tangle, plasma NfL, hippocampal volume, and temporal-metaROI cortical thickness between different plasma A/T profiles and explored their relations with each other using general linear models, including age, sex, APOE-ε4, and diagnosis as covariates. RESULTS: Plasma A+/T + individuals showed the highest levels of astrocyte reactivity, Aß plaque, tau tangle, and axonal degeneration, and the lowest hippocampal volume and temporal-metaROI cortical thickness. Lower plasma Aß42/Aß40 and higher plasma p-Tau181 were independently and synergistically correlated with higher plasma GFAP and Aß plaque. Elevated plasma p-Tau181 and GFAP concentrations were directly and interactively associated with more tau tangle formation. Regarding neurodegeneration, higher plasma p-Tau181 and GFAP concentrations strongly correlated with more axonal degeneration, as measured by plasma NfL, and lower plasma Aß42/Aß40 and higher plasma p-Tau181 were related to greater hippocampal atrophy. Higher plasma GFAP levels were associated with thinner cortical thickness and significantly interacted with lower plasma Aß42/Aß40 and higher plasma p-Tau181 in predicting more temporal-metaROI cortical thinning. Voxel-wise imaging analysis confirmed these findings. DISCUSSION: This study provides a valuable reference for using plasma biomarkers to detect AD in the Chinese community population and offers novel insights into how astrocyte reactivity contributes to AD progression, highlighting the importance of targeting reactive astrogliosis to prevent AD.

Prototype Learning Guided Hybrid Network for Breast Tumor Segmentation in DCE-MRI.

Automated breast tumor segmentation on the basis of dynamic contrast-enhancement magnetic resonance imaging (DCE-MRI) has shown great promise in clinical practice, particularly for identifying the presence of breast disease. However, accurate segmentation of breast tumor is a challenging task, often necessitating the development of complex networks. To strike an optimal tradeoff between computational costs and segmentation performance, we propose a hybrid network via the combination of convolution neural network (CNN) and transformer layers. Specifically, the hybrid network consists of a encoder-decoder architecture by stacking convolution and deconvolution layers. Effective 3D transformer layers are then implemented after the encoder subnetworks, to capture global dependencies between the bottleneck features. To improve the efficiency of hybrid network, two parallel encoder sub-networks are designed for the decoder and the transformer layers, respectively. To further enhance the discriminative capability of hybrid network, a prototype learning guided prediction module is proposed, where the category-specified prototypical features are calculated through online clustering. All learned prototypical features are finally combined with the features from decoder for tumor mask prediction. The experimental results on private and public DCE-MRI datasets demonstrate that the proposed hybrid network achieves superior performance than the state-of-the-art (SOTA) methods, while maintaining balance between segmentation accuracy and computation cost. Moreover, we demonstrate that automatically generated tumor masks can be effectively applied to identify HER2-positive subtype from HER2-negative subtype with the similar accuracy to the analysis based on manual tumor segmentation. The source code is available at https://github.com/ZhouL-lab/ PLHN.

Operando Study Insights into Lithiation/Delithiation Processes in a Poly(ethylene oxide) Electrolyte of All-Solid-State Lithium Batteries by Grazing-Incidence X-ray Scattering.

Poly(ethylene oxide) (PEO)-based composite electrolytes (PCEs) are considered as promising candidates for next-generation lithium-metal batteries (LMBs) due to their high safety, easy fabrication, and good electrochemical stability. Here, we utilize operando grazing-incidence small-angle and wide-angle X-ray scattering to probe the correlation of electrochemically induced changes and the buried morphology and crystalline structure of the PCE. Results show that the two irreversible reactions, PEO-Li+ reduction and TFSI- decomposition, cause changes in the crystalline structure, array orientation, and morphology of the PCE. In addition, the reversible Li plating/stripping process alters the inner morphology, especially the PEO-LiTFSI domain radius and distance between PEO-LiTFSI domains, rather than causing crystalline structure and orientation changes. This work provides a new path to monitor a working battery in real time and to a detailed understanding of the Li+ diffusion mechanism, which is essential for developing highly transferable and interface-stable PCE-based LMBs.

Estimation of Genetic Parameters for Growth and WSSV Resistance Traits in Litopenaeus vannamei.

The current study aimed to provide a precise assessment of the genetic parameters associated with growth and white spot syndrome virus (WSSV) resistance traits in Pacific white shrimp (Litopenaeus vannamei). This was achieved through a controlled WSSV challenge assay and the analysis of phenotypic values of five traits: body weight (BW), overall length (OL), body length (BL), tail length (TL), and survival hour post-infection (HPI). The analysis included test data from a total of 1017 individuals belonging to 20 families, of which 293 individuals underwent whole-genome resequencing, resulting in 18,137,179 high-quality SNP loci being obtained. Three methods, including pedigree-based best linear unbiased prediction (pBLUP), genomic best linear unbiased prediction (GBLUP), and single-step genomic BLUP (ssGBLUP) were utilized. Compared to the pBLUP model, the heritability of growth-related traits obtained from GBLUP and ssGBLUP was lower, whereas the heritability of WSSV resistance was higher. Both the GBLUP and ssGBLUP models significantly enhanced prediction accuracy. Specifically, the GBLUP model improved the prediction accuracy of BW, OL, BL, TL, and HPI by 4.77%, 21.93%, 19.73%, 19.34%, and 63.44%, respectively. Similarly, the ssGBLUP model improved prediction accuracy by 10.07%, 25.44%, 25.72%, 19.34%, and 122.58%, respectively. The WSSV resistance trait demonstrated the most substantial enhancement using both genomic prediction models, followed by body size traits (e.g., OL, BL, and TL), with BW showing the least improvement. Furthermore, the choice of models minimally impacted the assessment of genetic and phenotypic correlations. Genetic correlations among growth traits ranged from 0.767 to 0.999 across models, indicating high levels of positive correlations. Genetic correlations between growth and WSSV resistance traits ranged from (-0.198) to (-0.019), indicating low levels of negative correlations. This study assured significant advantages of the GBLUP and ssGBLUP models over the pBLUP model in the genetic parameter estimation of growth and WSSV resistance in L. vannamei, providing a foundation for further breeding programs.

Systematic biases in reference-based plasma cell-free DNA fragmentomic profiling.

Plasma cell-free DNA (cfDNA) fragmentation patterns are emerging directions in cancer liquid biopsy with high translational significance. Conventionally, the cfDNA sequencing reads are aligned to a reference genome to extract their fragmentomic features. In this study, through cfDNA fragmentomics profiling using different reference genomes on the same datasets in parallel, we report systematic biases in such conventional reference-based approaches. The biases in cfDNA fragmentomic features vary among races in a sample-dependent manner and therefore might adversely affect the performances of cancer diagnosis assays across multiple clinical centers. In addition, to circumvent the analytical biases, we develop Freefly, a reference-free approach for cfDNA fragmentomics profiling. Freefly runs ∼60-fold faster than the conventional reference-based approach while generating highly consistent results. Moreover, cfDNA fragmentomic features reported by Freefly can be directly used for cancer diagnosis. Hence, Freefly possesses translational merit toward the rapid and unbiased measurement of cfDNA fragmentomics.

Genome-wide analysis of the MADS-box gene family of sea buckthorn (Hippophae rhamnoides ssp. sinensis) and their potential role in floral organ development.

Sea buckthorn (Hippophae rhamnoides ssp. sinensis) is a deciduous shrub or small tree in the Elaeagnaceae family. It is dioecious, featuring distinct structures in female and male flowers. The MADS-box gene family plays a crucial role in flower development and differentiation of floral organs in plants. However, systematic information on the MADS-box family in sea buckthorn is currently lacking. This study presents a genome-wide survey and expression profile of the MADS-box family of sea buckthorn. We identified 92 MADS-box genes in the H. rhamnoides ssp. Sinensis genome. These genes are distributed across 12 chromosomes and classified into Type I (42 genes) and Type II (50 genes). Based on the FPKM values in the transcriptome data, the expression profiles of HrMADS genes in male and female flowers of sea buckthorn showed that most Type II genes had higher expression levels than Type I genes. This suggesting that Type II HrMADS may play a more significant role in sea buckthorn flower development. Using the phylogenetic relationship between sea buckthorn and Arabidopsis thaliana, the ABCDE model genes of sea buckthorn were identified and some ABCDE model-related genes were selected for qRT-PCR analysis in sea buckthorn flowers and floral organs. Four B-type genes may be involved in the identity determination of floral organs in male flowers, and D-type genes may be involved in pistil development. It is hypothesized that ABCDE model genes may play an important role in the identity of sea buckthorn floral organs. This study analyzed the role of MADS-box gene family in the development of flower organs in sea buckthorn, which provides an important theoretical basis for understanding the regulatory mechanism of sex differentiation in sea buckthorn.

Structural optimization and flow field analysis of turbomolecular pump based on a new performance prediction algorithm.

In the present study, a new turbomolecular pump (TMP) performance prediction algorithm is proposed according to the variable surface combined blade row (VSCBR) geometric model. The simulation calculation program is designed to perform structural optimization and flow field analysis. Research on the pumping performance of the traditional straight blade row (TSBR) indicates that when the blade velocity ratio is greater than 1, the increase in the pumping speed and compression ratio of the TMP gradually tends to stabilize. Response surface methodology is used to optimize the structural parameters of the first four stages of the combined blade row. The optimized VSCBR increases the pumping speed by 18.2% compared to that of the TSBR. The flow field analysis based on the optimized VSCBR shows that gas molecules reaching the rear blades are likely to approach the outlet, and the proportion of gas molecules in this region exceeds 50%. Therefore, the blades we designed should be conducive to additional gas molecules reaching the outlet.

Chiral perovskite-CdSe/ZnS QDs composites with high circularly polarized luminescence performance achieved through additive-solvent engineering.

Chiral perovskite materials are being extensively studied as one of the most promising candidates for circularly polarized luminescence (CPL)-related applications. Balancing chirality and photoluminescence (PL) properties is of great importance for enhancing the value of the dissymmetry factor (glum), and a higher glum value indicates better CPL. Chiral perovskite/quantum dot (QD) composites emerge as an effective strategy for overcoming the dilemma that achieving strong chirality and PL in chiral perovskite while at the same time achieving high glum in this composite is very crucial. Here, we choose diphenyl sulfoxide (DPSO) as an additive in the precursor solution of chiral perovskite to regulate the lattice distortion. How structural variation affects the chiral optoelectronic properties of the chiral perovskite has been further investigated. We find that chiral perovskite/CdSe-ZnS QD composites with strong CPL have been achieved, and the calculated maximum |glum| of the composites increased over one order of magnitude after solvent-additive modulation (1.55 × 10-3 for R-DMF/QDs, 1.58 × 10-2 for R-NMP-DPSO/QDs, -2.63 × 10-3 for S-DMF/QDs, and -2.65 × 10-2 for S-NMP-DPSO/QDs), even at room temperature. Our findings suggest that solvent-additive modulation can effectively regulate the lattice distortion of chiral perovskite, enhancing the value of glum for chiral perovskite/CdSe-ZnS QD composites.

Accelerating 3D genomics data analysis with Microcket.

The three-dimensional (3D) organization of genome is fundamental to cell biology. To explore 3D genome, emerging high-throughput approaches have produced billions of sequencing reads, which is challenging and time-consuming to analyze. Here we present Microcket, a package for mapping and extracting interacting pairs from 3D genomics data, including Hi-C, Micro-C, and derivant protocols. Microcket utilizes a unique read-stitch strategy that takes advantage of the long read cycles in modern DNA sequencers; benchmark evaluations reveal that Microcket runs much faster than the current tools along with improved mapping efficiency, and thus shows high potential in accelerating and enhancing the biological investigations into 3D genome. Microcket is freely available at https://github.com/hellosunking/Microcket .

Allele-Specific Suppression of Variant MHC With High-Precision RNA Nuclease CRISPR-Cas13d Prevents Hypertrophic Cardiomyopathy.

BACKGROUND: Familial hypertrophic cardiomyopathy has severe clinical complications of heart failure, arrhythmia, and sudden cardiac death. Heterozygous single nucleotide variants (SNVs) of sarcomere genes such as MYH7 are the leading cause of this type of disease. CRISPR-Cas13 (clustered regularly interspaced short palindromic repeats and their associated protein 13) is an emerging gene therapy approach for treating genetic disorders, but its therapeutic potential in genetic cardiomyopathy remains unexplored. METHODS: We developed a sensitive allelic point mutation reporter system to screen the mutagenic variants of Cas13d. On the basis of Cas13d homology structure, we rationally designed a series of Cas13d variants and obtained a high-precision Cas13d variant (hpCas13d) that specifically cleaves the MYH7 variant RNAs containing 1 allelic SNV. We validated the high precision and low collateral cleavage activity of hpCas13d through various in vitro assays. We generated 2 HCM mouse models bearing distinct MYH7 SNVs and used adenovirus-associated virus serotype 9 to deliver hpCas13d specifically to the cardiomyocytes. We performed a large-scale library screening to assess the potency of hpCas13d in resolving 45 human MYH7 allelic pathogenic SNVs. RESULTS: Wild-type Cas13d cannot distinguish and specifically cleave the heterozygous MYH7 allele with SNV. hpCas13d, with 3 amino acid substitutions, had minimized collateral RNase activity and was able to resolve various human MYH7 pathological sequence variations that cause hypertrophic cardiomyopathy. In vivo application of hpCas13d to 2 hypertrophic cardiomyopathy models caused by distinct human MYH7 analogous sequence variations specifically suppressed the altered allele and prevented cardiac hypertrophy. CONCLUSIONS: Our study unveils the great potential of CRISPR-Cas nucleases with high precision in treating inheritable cardiomyopathy and opens a new avenue for therapeutic management of inherited cardiac diseases.

Generalizable transcriptome-based tumor malignant level evaluation and molecular subtyping towards precision oncology.

In cancer treatment, therapeutic strategies that integrate tumor-specific characteristics (i.e., precision oncology) are widely implemented to provide clinical benefits for cancer patients. Here, through in-depth integration of tumor transcriptome and patients' prognoses across cancers, we investigated dysregulated and prognosis-associated genes and catalogued such important genes in a cancer type-dependent manner. Utilizing the expression matrices of these genes, we built models to quantitatively evaluate the malignant levels of tumors across cancers, which could add value to the clinical staging system for improved prediction of patients' survival. Furthermore, we performed a transcriptome-based molecular subtyping on hepatocellular carcinoma, which revealed three subtypes with significantly diversified clinical outcomes, mutation landscapes, immune microenvironment, and dysregulated pathways. As tumor transcriptome was commonly profiled in clinical practice with low experimental complexity and cost, this work proposed easy-to-perform approaches for practical clinical promotion towards better healthcare and precision oncology of cancer patients.

The mediating role of perceived social support on the relationship between lack of occupational coping self-efficacy and implicit absenteeism among intensive care unit nurses: a multicenter cross­sectional study.

BACKGROUND: Implicit absenteeism is very common among nurses. Poor perceived social support of intensive care unit nurses has a negative impact on their mental and physical health. There is evidence that lack of occupational coping self-efficacy can promote implicit absenteeism; however, the relationship between lack of occupational coping self-efficacy in perceived social support and implicit absenteeism of intensive care unit nurses is unclear. Therefore, this study aimed to evaluate the role of perceived social support between lack of occupational coping self-efficacy and implicit absenteeism of intensive care unit nurses, and to provide reliable evidence to the management of clinical nurses. METHODS: A cross-sectional study of 517 intensive care unit nurses in 10 tertiary hospitals in Sichuan province, China was conducted, of which 474 were valid questionnaires with a valid recovery rate of 91.6%. The survey tools included the Chinese version of Implicit Absenteeism Scale, the Chinese version of Perceived Social Support Scale, the Chinese version of Occupational Coping Self-Efficacy Scale and the Sociodemographic characteristics. Descriptive analysis and Pearson correlation analysis were performed using SPSS version 22.0, while the mediating effects were performed using AMOS version 24.0. RESULTS: The average of intensive care unit nurses had a total implicit absenteeism score of (16.87 ± 3.98), in this study, the median of intensive care unit nurses' implicit absenteeism score was 17, there were 210 intensive care unit nurses with low implicit absenteeism (44.3%) and 264 ICU nurses with high implicit absenteeism (55.7%). A total perceived social support score of (62.87 ± 11.61), and a total lack of occupational coping self-efficacy score of (22.78 ± 5.98). The results of Pearson correlation analysis showed that implicit absenteeism was negatively correlated with perceived social support (r = -0.260, P < 0.001) and positively correlated with lack of occupational coping self-efficacy (r = 0.414, P < 0.001). In addition, we found that perceived social support plays a mediating role in lack of occupational coping self-efficacy and implicit absenteeism [ß = 0.049, 95% CI of (0.002, 0.101)]. CONCLUSIONS: Intensive care unit nurses had a high level of implicit absenteeism with a moderate level of perceived social support and lack of occupational coping self-efficacy. Nursing managers should pay attention to the nurses those who were within low levels of social support and negative coping strategies, and take measures to reduce intensive care unit nurses' professional stress, minimize implicit absenteeism.

Genome-wide profiling of angiogenic cis-regulatory elements unravels cis-regulatory SNPs for vascular abnormality.

Angiogenesis is extensively involved in embryonic development and requires complex regulation networks, whose defects can cause a variety of vascular abnormalities. Cis-regulatory elements control gene expression at all developmental stages, but they have not been studied or profiled in angiogenesis yet. In this study, we exploited public DNase-seq and RNA-seq datasets from a VEGFA-stimulated in vitro angiogenic model, and carried out an integrated analysis of the transcriptome and chromatin accessibility across the entire process. Totally, we generated a bank of 47,125 angiogenic cis-regulatory elements with promoter (marker by H3K4me3) and/or enhancer (marker by H3K27ac) activities. Motif enrichment analysis revealed that these angiogenic cis-regulatory elements interacted preferentially with ETS family TFs. With this tool, we performed an association study using our WES data of TAPVC and identified rs199530718 as a cis-regulatory SNP associated with disease risk. Altogether, this study generated a genome-wide bank of angiogenic cis-regulatory elements and illustrated its utility in identifying novel cis-regulatory SNPs for TAPVC, expanding new horizons of angiogenesis as well as vascular abnormality genetics.

One-Step Multiview Clustering via Adaptive Graph Learning and Spectral Rotation.

In graph based multiview clustering methods, the ultimate partition result is usually achieved by spectral embedding of the consistent graph using some traditional clustering methods, such as k -means. However, optimal performance will be reduced by this multistep procedure since it cannot unify graph learning with partition generation closely. In this article, we propose a one-step multiview clustering method through adaptive graph learning and spectral rotation (AGLSR). For every view, AGLSR adaptively learns affinity graphs to capture similar relationships of samples. Then, a spectral embedding is designed to take advantage of the potential feature space shared by different views. In addition, AGLSR utilizes a spectral rotation strategy to obtain the discrete clustering labels from the learned spectral embeddings directly. An effective updating algorithm with proven convergence is derived to optimize the optimization problem. Sufficient experiments on benchmark datasets have clearly demonstrated the effectiveness of the proposed method in six metrics. The code of AGLSR is uploaded at https://github.com/tangchuan2000/AGLSR.