Response of fine particulate matter and ozone concentrations to meteorology and anthropogenic precursors over the "2+26" cities of northern China.

Analyzing the influencing factors of fine particulate matter and ozone formation and identifying the coupling relationship between the two are the basis for implementing the synergistic pollutants control. However, the current research on the synergistic relationship between the two still needs to be further explored. Using the Geodetector model, we analyzed the effects of meteorology and emissions on fine particulate matter and ozone concentrations over the "2 + 26" cities at multiple timescales, and also explored the coupling relationship between the two pollutants. Fine particulate matter concentrations showed overall decreasing trends on inter-season and inter-annual scale from 2015 to 2021, whereas ozone concentrations showed overall increasing trends. While ozone concentrations displayed an inverted U-shaped distribution from month to month, fine particulate matter concentrations displayed a U-shaped fluctuation. On inter-annual scale, climatic factors, with planet boundary layer height as the main determinant, have higher effects for both pollutants than human precursors. In summer and autumn, sunshine duration had the most influence on fine particulate matter, while planet boundary layer height was the greatest factor in winter. Fine particulate matter is the leading impacting factor on ozone concentrations in summer, and there were positive associations between them on both annual and seasonal scale. The impact of nitrogen oxides and volatile organic compounds for both pollutants concentrations varied significantly between seasons. The two pollutants concentration were enhanced by the interactions between the various components. On inter-annual scale, interactions between the planet boundary layer height and other factors dominated the concentrations of the two pollutants, whereas in summer, interactions between fine particulate matter and other factors dominated the concentrations of ozone. The study has implications for the treatment of atmospheric pollution in China and other nations and can serve as an important reference for the creation of integrated atmospheric pollution regulation policies over the "2 + 26" cities.

RNA N6-methyladenosine modification mediates downregulation of NR4A1 to facilitate malignancy of cervical cancer.

BACKGROUND: N6-methyladenosine is the most abundant eukaryotic mRNA modification and alters a wide range of cellular processes in cancer. Therefore, defining the molecular details are critical for understanding the regulatory mechanism of m6A modification. RESULTS: We found that METTL3, a core m6A methyltransferase component, is upregulated and functions as an oncogene in cervical cancer. Mechanistically, METTL3 induces the degradation of m6A-modified transcripts of NR4A1 though YTHDF2-DDX6 pathway. In addition, NR4A1 overexpression attenuates the malignant progression through recruiting the LSD1/HDAC1/CoREST transcriptional repression complex to AKT1 promoter. CONCLUSIONS: Our findings reveal that m6A regulates cervical cancer cellular progression through manipulating NR4A1 pathway.

MicroRNA-10 Family Promotes the Epithelial-to-Mesenchymal Transition in Renal Fibrosis by the PTEN/Akt Pathway.

Renal fibrosis (RF) is a common reason for renal failure, and epithelial-mesenchymal transition (EMT) is a vital mechanism that promotes the development of RF. It is known that microRNA-10 (miR-10) plays an important role in cancer EMT; however, whether it takes part in the EMT process of RF remains unclear. Therefore, we established an in vivo model of unilateral ureteral obstruction (UUO), and an in vitro model using TGF-ß1, to investigate whether and how miR-10a and miR-10b take part in the EMT of RF. In addition, the combinatorial effects of miR-10a and miR-10b were assessed. We discovered that miR-10a and miR-10b are overexpressed in UUO mice, and miR-10a, miR-10b, and miRs-10a/10b knockout attenuated RF and EMT in UUO-treated mouse kidneys. Moreover, miR-10a and miR-10b overexpression combinatorially promoted RF and EMT in TGF-ß1-treated HK-2 cells. Inhibiting miR-10a and miR-10b attenuated RF and EMT induced by TGF-ß1. Mechanistically, miR-10a and miR-10b suppressed PTEN expression by binding to its mRNA3'-UTR and promoting the Akt pathway. Moreover, PTEN overexpression reduced miR-10a and miR-10b effects on Akt phosphorylation (p-Akt), RF, and EMT in HK-2 cells treated with TGF-ß1. Taken together, miR-10a and miR-10b act combinatorially to negatively regulate PTEN, thereby activating the Akt pathway and promoting the EMT process, which exacerbates RF progression.

Apatinib enhances the anti-tumor effect of paclitaxel via the PI3K/p65/Bcl-xl pathway in triple-negative breast cancer.

BACKGROUND: Apatinib is a new generation of small molecule tyrosine kinase inhibitor, which can highly selectively inhibit phosphorylation of vascular endothelial growth factor receptor 2 (VEGFR-2). This study aimed to investigate the synergistic effects of apatinib and paclitaxel (PTX) on triple-negative breast cancer (TNBC) in vivo and in vitro, and to explore the molecular mechanism of the PI3K/p65/Bcl-xl pathway. METHODS: In vitro, 3-(4,5-dimethylthiazol-2-Yl)-2,5-diphenyltetrazolium bromide (MTT) method, flow cytometry (FCM), wound healing assay, and transwell matrix assay were conducted to measure the effects of apatinib and PTX on cell viability, apoptosis, migration, and invasion in TNBC cell line MDA-MB-468. Western blot (WB) was conducted to detect protein expression levels of PI3K, p65, and Bcl-xl after the application of apatinib and PTX. In vivo, MDA-MB-468 tumor-bearing nude mice were treated with apatinib and PTX, and tumor growth was observed. RESULTS: In vitro, apatinib and PTX could synergistically suppress the cell viability, the combined group had the most obvious effect. Apatinib and PTX could promote apoptosis and suppress migration and invasion of TNBC cells. Apatinib could reduce the expression of p-PI3K, p65, and Bcl-xl proteins (P<0.05). In vivo, apatinib and PTX could inhibit tumor size and weight of model mice, and the combined agents had a more significant effect. CONCLUSIONS: Apatinib could enhance the anti-tumor effect of PTX on TNBC cells through the PI3K/p65/Bcl-xl molecular pathway, and apatinib combined with PTX might be a promising option for TNBC treatment.

The Synergistic Effects of Pyrotinib Combined With Adriamycin on HER2-Positive Breast Cancer.

Pyrotinib (PYR) is a pan-HER kinase inhibitor that inhibits signaling via the RAS/RAF/MEK/MAPK and PI3K/AKT pathways. In this study, we aimed to investigate the antitumor efficacy of pyrotinib combined with adriamycin (ADM) and explore its mechanisms on HER2+ breast cancer. We investigated the effects of PYR and ADM on breast cancer in vitro and in vivo. MTT assay, Wound-healing, and transwell invasion assays were used to determine the effects of PYR, ADM or PYR combined with ADM on cell proliferation, migration, and invasion of SK-BR-3 and AU565 cells in vitro. Cell apoptosis and cycle were detected through flow cytometry. In vivo, xenograft models were established to test the effect of PYR, ADM, or the combined therapy on the nude mice. Western blotting was performed to assess the expression of Akt, p-Akt, p-65, p-p65, and FOXC1. The results indicated that PYR and ADM significantly inhibited the proliferation, migration, and invasion of SK-BR-3 and AU565 cells, and the inhibitory rate of the combination group was higher than each monotherapy group. PYR induced G1 phase cell-cycle arrest, while ADM induced G2 phase arrest, while the combination group induced G2 phase arrest. The combined treatment showed synergistic anticancer activities. Moreover, PYR significantly downregulated the expression of p-Akt, p-p65, and FOXC1. In clinical settings, PYR also exerts satisfactory efficacy against breast cancer. These findings suggest that the combination of PYR and ADM shows synergistic effects both in vitro and in vivo. PYR suppresses the proliferation, migration, and invasion of breast cancers through down-regulation of the Akt/p65/FOXC1 pathway.

A Systematic Review and Meta-Analysis of Immune-Related Adverse Events of Anti-PD-1 Drugs in Randomized Controlled Trials.

OBJECTIVE: We aimed to evaluate immune-related adverse events occurring in clinical trials of anti-programmed cell death 1 (PD-1) drugs, compared with control treatments, including chemotherapy, targeted drugs, or placebo. Further we compared the occurrence of immune -related events in patients treated with different anti-PD-1 drugs. DATA SOURCES: Randomized controlled trial (RCT) data were sourced from PubMed, Embase, and the Cochrane Central Register of Controlled Trials combined with https://clinicaltrials.gov. METHODS: Randomized controlled trial of anti-PD-1 drugs compared with control treatments published between January 1, 1970 and March 1,2019, were searched and data on trial patient characteristics, and adverse events extracted, reviewed, and subjected to meta-analysis. RESULTS: Eighteen Randomized controlled trials were included in our study. The Randomized controlled trials compared nivolumab (n = 12), pembrolizumab (n = 6), with chemotherapy (n = 13), targeted drugs (n = 2), or placebo (n = 3). Compared with the control group, the risk of any immune-related adverse events in patients treated with anti-PD-1 drugs was increased (RR, 2.65; 95% confidence interval, 1.84-3.83; P < 0.00001). Of the immune-related adverse events, the risk rates of pneumonitis (risk ratio, 2.10; 95% CI, 0.85-5.18), colitis (2.96;1.62-5.38), hypophysitis(4.79;1.54-14.89), hypothyroidism(7.87;5.36-11.57), hyperthyroidism (7.03;4.35-11.34), rash (1.58;0.98-2.54), pruritus (2.28; 1.38-3.76), and hepatitis (9.31;2.18-39.85) were increased by anti-PD-1 drugs. Further, the risk of immune-related adverse events was similar for patients treated with pembrolizumab and nivolumab (P = 0.14). CONCLUSIONS: In addition to previously reported organ-specific immune-related adverse events, we found that the risk of hyperthyroidism was also increased, in anit-PD-1-treated patients, relative to control treatments. The risk of total immune-related adverse events, was similar for pembrolizumab and nivolumab.

Dual HER2 Blockade in Neoadjuvant Treatment of HER2+ Breast Cancer: A Meta-Analysis and Review.

BACKGROUND: To investigate the pathologic complete response (pCR) rates of dual human epidermal growth factor receptor 2 (HER2) blockade in a neoadjuvant setting for HER2+ breast cancer. METHODS: We searched randomized clinical trials (RCTs) using dual HER2 blockade in a neoadjuvant setting for HER2+ breast cancer in PubMed, the Cochrane Library, Embase and ClinicalTrials.gov up to July 5, 2020, and all included studies were assessed according to the Cochrane Collaboration tool for assessing the risk of bias of RCTs, and the statistical analyses were performed using STATA 14.0 software. RESULTS: A total of 9 RCTs involving 2758 patients were included. Meta-analysis indicated that the pCR rates of lapatinib/pertuzumab/neratinib plus trastuzumab versus trastuzumab [relative risk (RR) = 1.31; 95% confidence interval (CI): 1.21-1.43; p < 0.001)] and lapatinib plus trastuzumab versus lapatinib (RR = 1.39; 95%CI: 1.25-1.53; p < 0.001) showed a significant statistical difference between dual HER2-blockade treatment and single-agent treatment in a neoadjuvant setting for HER2+ breast cancer. Additionally, there was no statistically significant difference in disease-free survival (HR = 0.72; 95% CI: 0.47-1.09; p = 0.123), incidence of serious adverse events (SAEs) (RR = 1.04; 95%CI: 0.81-1.33; p = 0.778) and cardiotoxicity(RR = 1.30; 95%CI: 0.81-2.08; p = 0.280), and the pCR rate was unaffected by hormone receptor status. CONCLUSIONS: The pCR rate of neoadjuvant dual-target therapy for HER2+ breast cancer was significantly higher than that of single-target therapy. Furthermore, the results indicated that the safety of dual-target therapy is similar to that of single-target therapy.

Circulating microRNAs as novel potential diagnostic biomarkers for ovarian cancer: a systematic review and updated meta-analysis.

OBJECT: Ovarian cancer is the primary cause of cancer-associated deaths among gynaecological malignancies. Increasing evidence suggests that microRNAs may be potential biomarkers for the diagnosis and prognosis of cancer. In this study, we conducted a systematic review and meta-analysis to summarize the global research and to evaluate the overall diagnostic accuracy of miRNAs in detecting ovarian cancer. METHODS: A systematic literature search was conducted for relevant studies through July 20, 2017, in English databases (CENTRAL, MEDLINE, and EMBASE), the Grey reference database and Chinese databases. Statistical analysis was conducted using OpenMetaAnalyst, STATA 14.0 and RevMan 5.3. Pooled sensitivity, specificity, and other parameters were used to assess the overall miRNA assay performance using a bivariate random-effects model (BRM). Meta-regression and subgroup analyses were performed to dissect the heterogeneity. Sensitivity analysis was performed to assess the robustness of our analysis, and the publication bias of the selected studies was assessed using Deeks' funnel plot asymmetry test. RESULTS: Thirteen articles described 33 studies, including 1081 patients with ovarian cancer and 518 controls. The pooled results were as follows: sensitivity, 0.89 (95% CI: 0.84-0.93); specificity, 0.64 (95% CI: 0.56-0.72); positive likelihood ratio, 2.18 (95% CI: 1.89-2.51); negative likelihood ratio, 0.15 (95% CI: 0.11-0.22); and diagnostic odds ratio (DOR), 13.21 (95% CI: 9.00-19.38). We conducted subgroup analyses based on ethnicity, research design, and miRNA profiling and found that multiple miRNA panels were more accurate in detecting ovarian cancer, with a combined DOR of 30.06 (95% CI: 8.58-105.37). CONCLUSION: Per the meta-analysis, circulating miRNAs may be novel and non-invasive biomarkers for detecting ovarian cancer, particularly multiple miRNA panels, which have potential diagnostic value as screening tools in clinical practice.

NMLPA: Uncovering Overlapping Communities in Attributed Networks via a Multi-Label Propagation Approach.

With the enrichment of the entity information in the real world, many networks with attributed nodes are proposed and studied widely. Community detection in these attributed networks is an essential task that aims to find groups where the intra-nodes are much more densely connected than the inter-nodes. However, many existing community detection methods in attributed networks do not distinguish overlapping communities from non-overlapping communities when designing algorithms. In this paper, we propose a novel and accurate algorithm called Node-similarity-based Multi-Label Propagation Algorithm (NMLPA) for detecting overlapping communities in attributed networks. NMLPA first calculates the similarity between nodes and then propagates multiple labels based on the network structure and the node similarity. Moreover, NMLPA uses a pruning strategy to keep the number of labels per node within a suitable range. Extensive experiments conducted on both synthetic and real-world networks show that our new method significantly outperforms state-of-the-art methods.

Learning the Personalized Intransitive Preferences of Images.

Most of the previous studies on the user preferences assume that there is a personal transitive preference ranking of the consumable media like images. For example, the transitivity of preferences is one of the most important assumptions in the recommender system research. However, the intransitive relations have also been widely observed, such as the win/loss relations in online video games, in sport matches, and even in rock-paper-scissors games. It is also found that different subjects demonstrate the personalized intransitive preferences in the pairwise comparisons between the applicants for college admission. Since the intransitivity of preferences on images has barely been studied before and has a large impact on the research of personalized image search and recommendation, it is necessary to propose a novel method to predict the personalized intransitive preferences of images. In this paper, we propose the novel Multi-Criterion preference (MuCri) models to predict the intransitive relations in the image preferences. The MuCri models utilize different kinds of image content features as well as the latent features of users and images. Meanwhile, a new data set is constructed in this paper, in order to evaluate the performance of the MuCri models. The experimental evaluation shows that the MuCri models outperform all the baselines. Due to the interdisciplinary nature of this topic, we believe it would widely attract the attention of researchers in the image processing community as well as in other communities, such as machine learning, multimedia, and recommender system.