A Novel GAN-based Fault Diagnosis Approach for Imbalanced Industrial Time Series

This paper proposes a novel fault diagnosis approach based on generative adversarial networks (GAN) for imbalanced industrial time series where normal samples are much larger than failure cases. We combine a well-designed feature extractor with GAN to help train the whole network. Aimed at obtaining data distribution and hidden pattern in both original distinguishing features and latent space, the encoder-decoder-encoder three-sub-network is employed in GAN, based on Deep Convolution Generative Adversarial Networks (DCGAN) but without Tanh activation layer and only trained on normal samples. In order to verify the validity and feasibility of our approach, we test it on rolling bearing data from Case Western Reserve University and further verify it on data collected from our laboratory. The results show that our proposed approach can achieve excellent performance in detecting faulty by outputting much larger evaluation scores

What Motivates People to Share Online Rumors? Deconstructing the Ambiguity of Rumors from a Perspective of Digital Storytelling

With the proliferation of social networks and the development of digital technology, the content structure and propagation mode of rumors have become more complicated with ambiguity, which has greatly influenced people’s behaviors when facing digitalized rumors. Based on the digital storytelling theory, this study takes an early initiative by deconstructing and identifying the basic components of online rumors and revealing the conditions under which people’s sharing behaviors in a social environment. A data set of health-related rumors related to Covid-19 was used to test the research hypotheses. The results indicated that causality explicitness, element integrality and source explicitness have different influences on rumor sharing behavior. And rumor vividness plays a negative moderating effect during the sharing process. This research offers insight to viewers and website authorities on ways to monitor and debunk online rumors

Guiding kinetic trajectories between jammed and unjammed states in 2D colloidal nanocrystal-polymer assemblies with zwitterionic ligands

Mesostructured matter composed of colloidal nanocrystals in solidified architectures abounds with broadly tunable catalytic, magnetic, optoelectronic, and energy storing properties. Less common are liquid-like assemblies of colloidal nanocrystals in a condensed phase, which may have different energy transduction behaviors owing to their dynamic character. Limiting investigations into dynamic colloidal nanocrystal architectures is the lack of schemes to control or redirect the tendency of the system to solidify. We show how to solidify and subsequently reconfigure colloidal nanocrystal assemblies dimensionally confined to a liquid-liquid interface. Our success in this regard hinged on the development of competitive chemistries anchoring or releasing the nanocrystals to or from the interface. With these chemistries, it was possible to control the kinetic trajectory between quasi–two-dimensional jammed (solid-like) and unjammed (liquid-like) states. In future schemes, it may be possible to leverage this control to direct the formation or destruction of explicit physical pathways for energy carriers to migrate in the system in response to an external field

PLEKHA4 is a novel prognostic biomarker that reshapes the tumor microenvironment in lower-grade glioma

BackgroundLower-grade glioma (LGG) is a primary intracranial tumor that carry a high risk of malignant transformation and limited therapeutic options. Emerging evidence indicates that the tumor microenvironment (TME) is a superior predictor for tumor progression and therapy response. PLEKHA4 has been demonstrated to be a biomarker for LGG that correlate with immune infiltration. However, the fundamental mechanism by which PLEKHA4 contributes to LGG is still poorly understood.MethodsMultiple bioinformatic tools, including Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA2), Shiny Methylation Analysis Resource Tool (SMART), etc., were incorporated to analyze the PLEKHA4. ESTIMATE, ssGSEA, CIBERSORT, TIDE and CellMiner algorithms were employed to determine the association of PLEKHA4 with TME, immunotherapy response and drug sensitivities. Immunohistochemistry (IHC)-based tissue microarrays and M2 macrophage infiltration assay were conducted to verify their associations.ResultsPLEKHA4 expression was found to be dramatically upregulated and strongly associated with unfavorable overall survival (OS) and disease-specific survival (DSS) in LGG patients, as well as their poor clinicopathological characteristics. Cox regression analysis identified that PLEKHA4 was an independent prognostic factor. Methylation analysis revealed that DNA methylation correlates with PLEKHA4 expression and indicates a better outcome in LGG. Moreover, PLEKHA4 was remarkably correlated with immune responses and TME remodeling, as evidenced by its positive correlation with particular immune marker subsets and the putative infiltration of immune cells. Surprisingly, the proportion of M2 macrophages in TME was strikingly higher than others, inferring that PLEKHA4 may regulate the infiltration and polarization of M2 macrophages. Evidence provided by IHC-based tissue microarrays and M2 macrophage infiltration assay further validated our findings. Moreover, PLEKHA4 expression was found to be significantly correlated with chemokines, interleukins, and their receptors, further supporting the critical role of PLEKHA4 in reshaping the TME. Additionally, we found that PLEKHA4 expression was closely associated with drug sensitivities and immunotherapy responses, indicating that PLEKHA4 expression also had potential clinical significance in guiding immunotherapy and chemotherapy in LGG.ConclusionPLEKHA4 plays a pivotal role in reshaping the TME of LGG patients, and may serve as a potential predictor for LGG prognosis and therapy

Attenuation of PITPNM1 signaling cascade can inhibit breast cancer progression

Phosphatidylinositol transfer protein membrane-associated 1 (PITPNM1) contains a highly conserved phosphatidylinositol transfer domain which is involved in phosphoinositide trafficking and signaling transduction under physiological conditions. However, the functional role of PITPNM1 in cancer progression remains unknown. Here, by integrating datasets of The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer (METABRIC), we found that the expression of PITPNM1 is much higher in breast cancer tissues than in normal breast tissues, and a high expression of PITPNM1 predicts a poor prognosis for breast cancer patients. Through gene set variation analysis (GSEA) and gene ontology (GO) analysis, we found PITPNM1 is mainly associated with carcinogenesis and cell-to-cell signaling ontology. Silencing of PITPNM1, in vitro, significantly abrogates proliferation and colony formation of breast cancer cells. Collectively, PITPNM1 is an important prognostic indicator and a potential therapeutic target for breast cancer

Silencing CTNND1 Mediates Triple-Negative Breast Cancer Bone Metastasis via Upregulating CXCR4/CXCL12 Axis and Neutrophils Infiltration in Bone

Bone metastasis from triple-negative breast cancer (TNBC) frequently results in poorer prognosis than other types of breast cancer due to the delay in diagnosis and intervention, lack of effective treatments and more skeletal-related complications. In the present study, we identified CTNND1 as a most reduced molecule in metastatic bone lesion from TNBC by way of high throughput sequencing of TNBC samples. In vivo experiments revealed that knockdown of CTNND1 enhanced tumor cells metastasis to bones and also increased neutrophils infiltration in bones. In vitro, we demonstrated that knockdown of CTNND1 accelerated epithelial–mesenchymal transformation (EMT) of tumor cells and their recruitment to bones. The involvement by CTNND1 in EMT and bone homing was achieved by upregulating CXCR4 via activating the PI3K/AKT/HIF-1αpathway. Moreover, TNBC cells with reduced expression of CTNND1 elicited cytotoxic T-cells responses through accelerating neutrophils infiltration by secreting more GM-CSF and IL-8. Clinically, patients with triple-negative breast cancer and lower level of CTNND1 had shorter overall survival (OS) and distant metastasis-free survival (DMFS). It was concluded that downregulation of CTNND1 played a critical role in facilitating bone metastasis of TNBC and that CTNND1 might be a potential biomarker for predicting the risk of bone metastases in TNBC

Fine-Tuning Stomatal Movement Through Small Signaling Peptides

As sessile organisms, plants are continuously exposed to a wide range of environmental stress. In addition to their crucial roles in plant growth and development, small signaling peptides are also implicated in sensing environmental stimuli. Notably, recent studies in plants have revealed that small signaling peptides are actively involved in controlling stomatal aperture to defend against biotic and abiotic stress. This review illustrates our growing knowledge of small signaling peptides in the modulation of stomatal aperture and highlights future challenges to decipher peptide signaling pathways in guard cells

Association of FTH1-expressing circulating tumor cells with efficacy of neoadjuvant chemotherapy for patients with breast cancer: a prospective cohort study

Background The association between different phenotypes and genotypes of circulating tumor cells (CTCs) and efficacy of neoadjuvant chemotherapy (NAC) remains uncertain. This study was conducted to evaluate the relationship of FTH1 gene-associated CTCs (F-CTC) with/without epithelial-mesenchymal transition (EMT) markers, or their dynamic changes with the efficacy of NAC in patients with non-metastatic breast cancer. Patients and Methods This study enrolled 120 patients with non-metastatic breast cancer who planned to undergo NAC. The FTH1 gene and EMT markers in CTCs were detected before NAC (T0), after 2 cycles of chemotherapy (T1), and before surgery (T2). The associations of these different types of CTCs with rates of pathological complete response (pCR) and breast-conserving surgery (BCS) were evaluated using the binary logistic regression analysis. Results F-CTC in peripheral blood ≥1 at T0 was an independent factor for pCR rate in patients with HER2-positive (odds ratio [OR]=0.08, 95% confidence interval [CI], 0.01-0.98, P = .048). The reduction in the number of F-CTC at T2 was an independent factor for BCS rate (OR = 4.54, 95% CI, 1.14-18.08, P = .03). Conclusions The number of F-CTC prior to NAC was related to poor response to NAC. Monitoring of F-CTC may help clinicians formulate personalized NAC regimens and implement BCS for patients with non-metastatic breast cancer

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants