Bayesian Methods in Tensor Analysis

Tensors, also known as multidimensional arrays, are useful data structures in machine learning and statistics. In recent years, Bayesian methods have emerged as a popular direction for analyzing tensor-valued data since they provide a convenient way to introduce sparsity into the model and conduct uncertainty quantification. In this article, we provide an overview of frequentist and Bayesian methods for solving tensor completion and regression problems, with a focus on Bayesian methods. We review common Bayesian tensor approaches including model formulation, prior assignment, posterior computation, and theoretical properties. We also discuss potential future directions in this field.Comment: 32 pages, 8 figures, 2 table

Inhibition of neutrophil extracellular trap formation attenuates NLRP1-dependent neuronal pyroptosis via STING/IRE1α pathway after traumatic brain injury in mice

IntroductionIncreased neutrophil extracellular trap (NET) formation has been reported to be associated with cerebrovascular dysfunction and neurological deficits in traumatic brain injury (TBI). However, the biological function and underlying mechanisms of NETs in TBI-induced neuronal cell death are not yet fully understood.MethodsFirst, brain tissue and peripheral blood samples of TBI patients were collected, and NETs infiltration in TBI patients was detected by immunofluorescence staining and Western blot. Then, a controlled cortical impact device was used to model brain trauma in mice, and Anti-Ly6G, DNase, and CL-amidine were given to reduce the formation of neutrophilic or NETs in TBI mice to evaluate neuronal death and neurological function. Finally, the pathway changes of neuronal pyroptosis induced by NETs after TBI were investigated by administration of peptidylarginine deiminase 4 (a key enzyme of NET formation) adenovirus and inositol-requiring enzyme-1 alpha (IRE1α) inhibitors in TBI mice.ResultsWe detected that both peripheral circulating biomarkers of NETs and local NETs infiltration in the brain tissue were significantly increased and had positive correlations with worse intracranial pressure (ICP) and neurological dysfunction in TBI patients. Furthermore, the depletion of neutrophils effectively reduced the formation of NET in mice subjected to TBI. we found that degradation of NETs or inhibition of NET formation significantly inhibited nucleotide-binding oligomerization domain (NOD)-like receptor pyrin domain containing 1 (NLRP1) inflammasome-mediated neuronal pyroptosis after TBI, whereas these inhibitory effects were abolished by cyclic GMP-AMP (cGAMP), an activator of stimulating Interferon genes (STING). Moreover, overexpression of PAD4 in the cortex by adenoviruses could aggravate NLRP1-mediated neuronal pyroptosis and neurological deficits after TBI, whereas these pro-pyroptotic effects were rescued in mice also receiving STING antagonists. Finally, IRE1α activation was significantly upregulated after TBI, and NET formation or STING activation was found to promote this process. Notably, IRE1α inhibitor administration significantly abrogated NETs-induced NLRP1 inflammasome-mediated neuronal pyroptosis in TBI mice.DiscussionOur findings indicated that NETs could contribute to TBI-induced neurological deficits and neuronal death by promoting NLRP1-mediated neuronal pyroptosis. Suppression of the STING/ IRE1α signaling pathway can ameliorate NETs-induced neuronal pyroptotic death after TBI

Properties of the Long-Term Oscillations in the Middle Atmosphere Based on Observations from TIMED/SABER Instrument and FPI over Kelan

The properties of the long-term oscillations in the middle atmosphere have been investigated using the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) temperature data and Fabry–Perot interferometer (FPI) data. Results for SABER temperature show that the semiannual oscillation (SAO) has three amplitude maxima at altitudes of 45, 75, and 85 km, respectively, and shows prominent seasonal asymmetries there. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K on average at each equinox, contributing to the lower mesospheric inversion layer (MIL). It is shown that stronger enhancement can be found at the spring equinox than at the autumn equinox. The triennial oscillation (TO) is significant in the tropical region. The spectral peak of the TO is probably a sub-peak of the quasi-biennial oscillation (QBO) and is due to modulation of QBO. In addition, there may be potential interaction of the TO with SAO at 85 km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The annual oscillation (AO) and SAO are analyzed over Kelan by FPI data. Generally, the amplitudes of FPI wind are smaller than those of the Horizontal Wind Model (HWM07). The comparison between FPI and TIMED Doppler Interferometer (TIDI) winds shows relatively large discrepancy. This may be due to the tidal aliasing in the nighttime results derived from the FPI data. Results also show that the algorithm to derive FPI temperature needs improvements

MicroRNA‐144‐3p controls the apoptosis of pulmonary artery endothelial cells in pulmonary arterial hypertension via the BMPR2/Smad4 signaling pathway

Abstract Background This study was to determine the molecular mechanism of miR‐144‐3p in the treatment of pulmonary arterial hypertension (PAH). Methods Luciferase assays detected the binding site of miR‐144‐3p. Quantitative reverse transcription‐polymerase chain reaction (PCR) measured the expression of downstream genes of Smad4 in pulmonary artery endothelial cells (PAECs). Cell apoptosis was analysed by fluorescence activated cell sorting (FACS) analysis. In a monocrotaline‐induced rat PAH model, the integrity of PAECs was detected by hematoxylin eosin (H&E) staining, immunohistochemistry, and immunofluorescence. The protein expression of the bone morphogenetic protein receptor 2 (BMPR2)/Smad4 signaling pathway was analysed by Western blotting. Results MiR‐144‐3p targeted Smad4 directly and down‐regulated the expression of α‐smooth muscle actin (SMA), Connective tissue growth factor (CTGF) and c‐myelocytomatosis (MYC) in PAECs. There was a significant change in the apoptosis of PAECs transfected with miR‐144‐3p. After transfection, the phosphorylation of Smad4 decreased only at 24 h. The integrity of PAECs was improved by miR‐144‐3p. There was a down‐regulation in BMPR2, Smad1/5 and p‐Smad1/5 in the PAH group. The fold change in Smad4 and p‐Smad4 expression decreased significantly in the PAH‐miR group. Moreover, we observed decreased α‐SMA, CTGF and c‐MYC expression and an up‐regulation of vascular endothelial (VE)‐cadherin. Conclusions MiR‐144‐3p modulates apoptosis and phenotype switching of PAECs via phosphorylation of the BMPR2/Smad4 signaling pathway

A System Fault Diagnosis Method with a Reclustering Algorithm

The log analysis-based system fault diagnosis method can help engineers analyze the fault events generated by the system. The K-means algorithm can perform log analysis well and does not require a lot of prior knowledge, but the K-means-based system fault diagnosis method needs to be improved in both efficiency and accuracy. To solve this problem, we propose a system fault diagnosis method based on a reclustering algorithm. First, we propose a log vectorization method based on the PV-DM language model to obtain low-dimensional log vectors which can provide effective data support for the subsequent fault diagnosis; then, we improve the K-means algorithm and make the effect of K-means algorithm based log clustering; finally, we propose a reclustering method based on keywords’ extraction to improve the accuracy of fault diagnosis. We use system log data generated by two supercomputers to verify our method. The experimental results show that compared with the traditional K-means method, our method can improve the accuracy of fault diagnosis while ensuring the efficiency of fault diagnosis

The role of single-cell RNA sequencing in cardiac tumour - a case report

A 65-year-old woman presented to our hospital with 5 days of chest tightness, dyspnoea, and lower abdominal distension. Echocardiography revealed a mass in the right atrium. An emergency operation was carried out to prevent tumour shedding. The patient was discharged on the 4th day of tumour resection, without any complications At the 18 months follow-up, she suffered from kidney and lung tumours. She refused any treatment and passed away. scRNA-seq was applied to analyse the nature of the tumour. The cellular components of benign tumours include chondrocytes, smooth muscle cells, fibroblasts, mesenchymal stromal cells, and osteoblasts. Additionally, the cyclic guanosine monophosphate (cGMP-PKG) signalling pathway, transcriptional misregulation in cancer, and the p53 signalling pathway may be related to the growth of this tumour. scRNA-seq is a good approach to analyse growth patterns of cardiac tumours and helpful for distinguishing the nature of the tumour. Keywords: Sequence Analysis, RNA, Cardiac tumour

Copper-64 labeled PEGylated exosomes for in vivo positron emission tomography and enhanced tumor retention

Exosomes have attracted tremendous attention due to their important role in physiology, pathology, and oncology, as well as promising potential in biomedical applications. Although great efforts have been dedicated to investigating their biological properties and applications as natural cancer drug-delivery systems, the systemic biodistribution of exosomes remains underexplored. In addition, exosome-based drug delivery is inevitably hindered by the robust liver clearance, leading to suboptimal tumor retention and therapeutic efficiency. In this study, we report one of the first examples using in vivo positron emission tomography (PET) for noninvasive monitoring of copper-64 (Cu-64)-radiolabeled polyethylene glycol (PEG)-modified exosomes, achieving excellent imaging quality and quantitative measurement of blood residence and tumor retention. PEGylation not only endowed exosomes with a superior pharmacokinetic profile and great accumulation in the tumor versus traditionally reported native exosomes but also reduced premature hepatic sequestration and clearance of exosomes, findings that promise enhanced therapeutic delivery efficacy and safety in future studies. More importantly, this study provides important guidelines about surface engineering, radiochemistry, and molecular imaging in obtaining accurate and quantitative biodistribution information on exosomes, which may benefit future exploration in the realm of exosomes

Airborne particulate matter, population mobility and COVID-19: a multi-city study in China

Background: Coronavirus disease 2019 (COVID-19) is an emerging infectious disease, which has caused numerous deaths and health problems worldwide. This study aims to examine the effects of airborne particulate matter (PM) pollution and population mobility on COVID-19 across China. Methods: We obtained daily confirmed cases of COVID-19, air particulate matter (PM2.5, PM10), weather parameters such as ambient temperature (AT) and absolute humidity (AH), and population mobility scale index (MSI) in 63 cities of China on a daily basis (excluding Wuhan) from January 01 to March 02, 2020. Then, the Generalized additive models (GAM) with a quasi-Poisson distribution were fitted to estimate the effects of PM10, PM2.5 and MSI on daily confirmed COVID-19 cases. Results: We found each 1 unit increase in daily MSI was significantly positively associated with daily confirmed cases of COVID-19 in all lag days and the strongest estimated RR (1.21, 95% CIs:1.14 ~ 1.28) was observed at lag 014. In PM analysis, we found each 10 μg/m3 increase in the concentration of PM10 and PM2.5 was positively associated with the confirmed cases of COVID-19, and the estimated strongest RRs (both at lag 7) were 1.05 (95% CIs: 1.04, 1.07) and 1.06 (95% CIs: 1.04, 1.07), respectively. A similar trend was also found in all cumulative lag periods (from lag 01 to lag 014). The strongest effects for both PM10 and PM2.5 were at lag 014, and the RRs of each 10 μg/m3 increase were 1.18 (95% CIs:1.14, 1.22) and 1.23 (95% CIs:1.18, 1.29), respectively. Conclusions: Population mobility and airborne particulate matter may be associated with an increased risk of COVID-19 transmission