Factors Affecting Trust in Chinese Digital Journalism: Approach Based on Folk Theories

Trust in online digital news has become a significant concern affecting social cohesion in China. Under the framework of folk theories, we interviewed urban and rural residents' perceptions and imaginations of digital news credibility in China's digital journalism environment. The study finds that digital media giants in China are utilised by both urban and rural residents. Regarding the behaviour of news avoidance, scepticism of digital news accounts for only a tiny fraction of the reasons held by news avoiders. Chinese urban and rural residents have similar perceptions about the impact of news forms, quality of information, and individual stances on digital news, while rural residents show uncertainty about the transparency of news production, which may be related to their education level and media literacy. The relationship between recommendation algorithms and news trust is overlooked by respondents. In addition, news seekers are more likely to display herd behaviours, which may mislead their judgment of news credibility. News avoiders may refuse to consume news because of their distaste for China's digital news atmosphere, such as the ubiquity of unpleasant emotions, preconceived opinions, and attention-grabbing clickbait headlines

ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network Approach

Given a complex graph database of node- and edge-attributed multi-graphs as well as associated metadata for each graph, how can we spot the anomalous instances? Many real-world problems can be cast as graph inference tasks where the graph representation could capture complex relational phenomena (e.g., transactions among financial accounts in a journal entry), along with metadata reflecting tabular features (e.g. approver, effective date, etc.). While numerous anomaly detectors based on Graph Neural Networks (GNNs) have been proposed, none are capable of directly handling directed graphs with multi-edges and self-loops. Furthermore, the simultaneous handling of relational and tabular features remains an unexplored area. In this work we propose ADAMM, a novel graph neural network model that handles directed multi-graphs, providing a unified end-to-end architecture that fuses metadata and graph-level representation learning through an unsupervised anomaly detection objective. Experiments on datasets from two different domains, namely, general-ledger journal entries from different firms (accounting) as well as human GPS trajectories from thousands of individuals (urban mobility) validate ADAMM's generality and detection effectiveness of expert-guided and ground-truth anomalies. Notably, ADAMM outperforms existing baselines that handle the two data modalities (graph and metadata) separately with post hoc synthesis efforts.Comment: Accepted at IEEE BigData 202

Pyroptosis: The Determinator of Cell Death and Fate in Acute Kidney Injury

Background: Acute kidney injury (AKI) is kidney damage that leads to a rapid decline in function. AKI primarily occurs when the tubular epithelium is damaged, causing swelling, loss of brush margin, and eventual apoptosis. Research has shown that tubular epithelial cell damage in AKI is linked to cell cycle arrest, autophagy, and regulation of cell death. Summary: Pyroptosis, a type of programmed cell death triggered by inflammation, is believed to play a role in the pathophysiology of AKI. Cumulative evidence has shown that pyroptosis is the main cause of tubular cell death in AKI. Thus, targeted intervention of pyroptosis may be a promising therapeutic approach for AKI. In this review, we delve deep into the cutting-edge research surrounding pyroptosis in the context of AKI, shedding light on its intricate mechanisms and potential implications for clinical practice. Additionally, we explore the exciting realm of potential pre-clinical treatment options for AKI, aiming to pave the way for future therapeutic advancements. Key Messages: Pyroptosis, a highly regulated form of cell death, plays a crucial role in determining the fate of cells during the development of AKI. This intricate process involves the activation of inflammasomes, which are multi-protein complexes that initiate pyroptotic cell death. By understanding the mechanisms underlying pyroptosis, researchers aim to gain insights into the pathogenesis of AKI and potentially identify new therapeutic targets for this condition

Direct numerical simulation of Taylor-Couette flow with vertical asymmetric rough walls

Direct numerical simulations are performed to explore the effects of rotating direction of the vertical asymmetric rough wall on the transport properties of Taylor-Couette (TC) flow up to a Taylor number of $\textit{Ta} = 2.39 \times 10^7$. It is shown that compared to the smooth wall, the rough wall with vertical asymmetric strips can enhance the dimensionless torque \textit{Nu}$_\omega$, and more importantly, at high \textit{Ta} clockwise rotation of the inner rough wall (the fluid is sheared by the steeper slope side of the strips) results in a significantly bigger torque enhancement as compared to the counter-clockwise rotation (the fluid is sheared by the smaller slope side of the strips) due to the larger convective contribution to the angular velocity flux, although the rotating direction has a negligible effect on the torque at low \textit{Ta}. The larger torque enhancement caused by the clockwise rotation of vertical asymmetric rough wall at high \textit{Ta} is then explained by the stronger coupling between the rough wall and the bulk due to the larger biased azimuthal velocity towards the rough wall at the mid-gap of TC system, the increased intensity of turbulence manifesting by larger Reynolds stress and thinner boundary layer, and the more significant contribution of the pressure force on the surface of rough wall to the torque.Comment: 17 pages,11 figure

Controlling nutritional status score is associated with renal progression, cardiovascular events, and all-cause mortality in biopsy-proved diabetic kidney disease

Background: The Controlled Nutritional Status (CONUT) score, calculated from albumin, total cholesterol, and lymphocyte count, is a useful indicator for immune-nutritional assessment and is associated with the prognosis of various diseases. However, its relationship with renal outcomes, cardiovascular disease (CVD), and all-cause mortality in patients with diabetic kidney disease is unclear.Methods: This retrospective single-center study enrolled 336 patients with biopsy-confirmed diabetic kidney disease from August 2009 to December 2018. The outcomes were progression to end-stage renal disease (ESRD), CVD events, and death. Univariate and multivariate Cox regression analyses were performed to estimate the association between confounding factors and outcomes. The Kaplan-Meier curve was used to compare the outcomes of the patients according to the median CONUT score. The area under the curve (AUC) evaluated with time-dependent receiver operating characteristics was used to test discriminative power of COUNT score.Results: During a median follow-up period of 5.1 years. The Kaplan-Meier analysis showed that patients in the high CONUT group (CONUT score > 3) had a significantly higher incidence of ESRD, CVD events, and all-cause mortality than those in the low CONUT group (CONUT score ≤ 3). The multivariate COX regression analysis indicated that, The CONUT score was an independent predictor of ESRD (hazards ration [HR] = 1.129, 95% confidence interval [CI] 1.037-1.228, p = 0.005), CVD events (HR = 1.159, 95% CI 1.057-1.271, p = 0.002), and all-cause mortality (HR = 1.299, 95% CI 1.143-1.478, p < 0.001).Conclusion: The CONUT score is an independent risk factor for ESRD, CVD events, and overall death in patients with diabetic kidney disease

Identification of copper death-associated molecular clusters and immunological profiles in rheumatoid arthritis

Objective: An analysis of the relationship between rheumatoid arthritis (RA) and copper death-related genes (CRG) was explored based on the GEO dataset. / Methods: Based on the differential gene expression profiles in the GSE93272 dataset, their relationship to CRG and immune signature were analysed. Using 232 RA samples, molecular clusters with CRG were delineated and analysed for expression and immune infiltration. Genes specific to the CRGcluster were identified by the WGCNA algorithm. Four machine learning models were then built and validated after selecting the optimal model to obtain the significant predicted genes, and validated by constructing RA rat models. / Results: The location of the 13 CRGs on the chromosome was determined and, except for GCSH. LIPT1, FDX1, DLD, DBT, LIAS and ATP7A were expressed at significantly higher levels in RA samples than in non-RA, and DLST was significantly lower. RA samples were significantly expressed in immune cells such as B cells memory and differentially expressed genes such as LIPT1 were also strongly associated with the presence of immune infiltration. Two copper death-related molecular clusters were identified in RA samples. A higher level of immune infiltration and expression of CRGcluster C2 was found in the RA population. There were 314 crossover genes between the 2 molecular clusters, which were further divided into two molecular clusters. A significant difference in immune infiltration and expression levels was found between the two. Based on the five genes obtained from the RF model (AUC = 0.843), the Nomogram model, calibration curve and DCA also demonstrated their accuracy in predicting RA subtypes. The expression levels of the five genes were significantly higher in RA samples than in non-RA, and the ROC curves demonstrated their better predictive effect. Identification of predictive genes by RA animal model experiments was also confirmed. / Conclusion: This study provides some insight into the correlation between rheumatoid arthritis and copper mortality, as well as a predictive model that is expected to support the development of targeted treatment options in the future

Nickel pyrithione induces apoptosis in chronic myeloid leukemia cells resistant to imatinib via both Bcr/Abl-dependent and Bcr/Abl-independent mechanisms

Abstract Background Acquired imatinib (IM) resistance is frequently characterized by Bcr-Abl mutations that affect IM binding and kinase inhibition in patients with chronic myelogenous leukemia (CML). Bcr-Abl-T315I mutation is the predominant mechanism of the acquired resistance to IM. Therefore, it is urgent to search for additional approaches and targeting strategies to overcome IM resistance. We recently reported that nickel pyrithione (NiPT) potently inhibits the ubiquitin proteasome system via targeting the 19S proteasome-associated deubiquitinases (UCHL5 and USP14), without effecting on the 20S proteasome. In this present study, we investigated the effect of NiPT, a novel proteasomal deubiquitinase inhibitor, on cell survival or apoptosis in CML cells bearing Bcr-Abl-T315I or wild-type Bcr-Abl. Methods Cell viability was examined by MTS assay and trypan blue exclusion staining assay in KBM5, KBM5R, K562, BaF3-p210-WT, BaF3-p210-T315I cells, and CML patients’ bone marrow samples treated with NiPT. Cell apoptosis in CML cells was detected with Annexin V-FITC/PI and rhodamine-123 staining followed by fluorescence microscopy and flow cytometry and with western blot analyses for apoptosis-associated proteins. Expression levels of Bcr-Abl in CML cells were analyzed by using western blotting and real-time PCR. The 20S proteasome peptidase activity was measured using specific fluorogenic substrate. Active-site-directed labeling of proteasomal DUBs, as well as the phosphorylation of USP14 was used for evaluating the inhibition of the DUBs activity by NiPT. Mouse xenograft models of KBM5 and KBM5R cells were analyzed, and Bcr-Abl-related proteins and protein biomarkers related to proliferation, differentiation, and adhesion in tumor tissues were detected by western blots and/or immunohistological analyses. Results NiPT induced apoptosis in CML cells and inhibited the growth of IM-resistant Bcr-Abl-T315I xenografts in nude mice. Mechanistically, NiPT induced decreases in Bcr-Abl proteins, which were associated with downregulation of Bcr-Abl transcription and with the cleavage of Bcr-Abl protein by activated caspases. NiPT-induced ubiquitin proteasome system inhibition induced caspase activation in both IM-resistant and IM-sensitive CML cells, and the caspase activation was required for NiPT-induced Bcr-Abl downregulation and apoptotic cell death. Conclusions These findings support that NiPT can overcome IM resistance through both Bcr-Abl-dependent and Bcr-Abl-independent mechanisms, providing potentially a new option for CML treatment