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Statisticians are increasingly posed with thought-provoking and even paradoxical questions, challenging our qualifications for entering the statistical paradises created by Big Data. By developing measures for data quality, this article suggests a framework to address such a question: “Which one should I trust more: a 1% survey with 60% response rate or a self-reported administrative dataset covering 80% of the population?” A 5-element Euler-formula-like identity shows that for any dataset of size n, probabilistic or not, the difference between the sample average X̅n and the population average X̅N is the product of three terms: (1) a data quality measure, ρR, X, the correlation between Xj and the response/recording indicator Rj ; (2) a data quantity measure, ( N − n ) / n , where N is the population size; and (3) a problem difficulty measure, σX , the standard deviation of X. This decomposition provides multiple insights: (I) Probabilistic sampling ensures high data quality by controlling ρR, X at the level of N −1/2; (II) When we lose this control, the impact of N is no longer canceled by ρR, X , leading to a Law of Large Populations (LLP), that is, our estimation error, relative to the benchmarking rate 1/√n, increases with √N; and (III) the “bigness” of such Big Data (for population inferences) should be measured by the relative size f = n/N, not the absolute size n; (IV) When combining data sources for population inferences, those relatively tiny but higher quality ones should be given far more weights than suggested by their sizes. Estimates obtained from the Cooperative Congressional Election Study (CCES) of the 2016 US presidential election suggest a ρR, X ≈ −0.005 for self-reporting to vote for Donald Trump. Because of LLP, this seemingly minuscule data defect correlation implies that the simple sample proportion of the self-reported voting preference for Trump from 1% of the US eligible voters, that is, n ≈ 2,300,000, has the same mean squared error as the corresponding sample proportion from a genuine simple random sample of size n ≈ 400, a 99.98% reduction of sample size (and hence our confidence). The CCES data demonstrate LLP vividly: on average, the larger the state’s voter populations, the further away the actual Trump vote shares from the usual 95% confidence intervals based on the sample proportions. This should remind us that, without taking data quality into account, population inferences with Big Data are subject to a Big Data Paradox: the more the data, the surer we fool ourselves.

This paper focuses on the phenomenon of “big data killing” implied in e-commerce and discusses how to take the government as the lead to coordinately supervise the price discrimination behavior of e-commerce companies towards loyal customers. First, the four-party evolutionary game model of the government regulatory department, e-commerce platform, e-commerce company, and consumer is built. Second, the stability of the strategy choice of each game subject is analyzed. On this basis, the evolutionary stable strategy in the system based on First Law of Lyapunov is explored. Finally, the influences of key elements on system evolution are simulated and analyzed by MATLAB2021. Results demonstrate that (1) the government supervision mechanism can effectively supervise the price discrimination of e-commerce company based on big data to loyal customers; (2) when the government chooses the strict supervision strategy, reducing the information supervision cost of the e-commerce platform and the strict supervision cost of the government enable the government and the e-commerce platform to coordinate supervision and make the e-commerce company incline to choose the nondifferential pricing strategy; (3) when the government chooses the loose supervision strategy, reducing the information supervision cost of the e-commerce platform and increasing the probability of consumer discovering differential pricing and the penalties for differential pricing of e-commerce company enable the e-commerce platform and consumer to coordinate supervision, and make the e-commerce company incline to choose the nondifferential pricing strategy. The results of this study can provide theoretical guidance for the government and companies to make beneficial strategic decisions in the development of e-commerce.

Severe acute pancreatitis (SAP) is an acute abdominal disease with the strong systemic inflammatory response, and rapidly progresses from a local pancreatic damage into multiple organ dysfunction. For many decades, the contributions of neutrophils to the pathology of SAP were traditionally thought to be the chemokine and cytokine cascades that accompany inflammation. In this review, we focus mainly on those recently recognized aspects of neutrophils in SAP processes. First, emerging evidence suggests that therapeutic interventions targeting neutrophils significantly lower tissue damage and protect against the occurrence of pancreatitis. Second, trypsin activation promotes the initial neutrophils recruitment into local pancreas, and subsequently neutrophils infiltration in turn triggers trypsin production. Finally, neutrophils have the unique ability to release neutrophil extracellular traps even in the absence of pathogens.

Background Treatment strategies targeting tumor-associated macrophages (TAMs) have been proposed in cancer areas. The functional alterations of macrophages in the microenvironment during the tumorigenesis of human epithelial cancer remain poorly understood. Here, we explored phenotypic alteration of macrophages during the development of oral squamous cell carcinoma (OSCC). Methods Conditioned media (CM) and exosome supernatants were harvested from normal oral epithelium, oral leukoplakia cells and OSCC cells. We measured phenotypic alteration of macrophages using flow cytometry, luminex assays, and quantitative real-time PCR assay. Intracellular signaling pathway analysis, mass spectrometry proteomics, western blotting, enzyme-linked immunosorbent assay, immunohistochemical staining, and bioinformatics analysis were performed to uncover the underlying mechanisms. Results THP-1-derived and PBMCs derived macrophages exhibited an M1-like phenotype but not M2-like phenotype, when treated with CM from OSCC cells but not with the CM from normal epithelium or leukoplakia cells. Further investigations revealed that macrophages were activated by taking up exosomes released from OSCC cells through p38, Akt, and SAPK/JNK signaling at the early phase. We further provided evidences that THBS1 derived from OSCC exosomes participated in the polarization of macrophages to an M1-like phenotype. Reciprocally, CM from exosomes induced M1-like TAMs and significantly promoted migration of OSCC cells. Conclusions We proposed a novel paracrine loop between cancer cells and macrophages based on exosomes from OSCC. Therefore, target management of M1-like TAMs polarized by exosomes shows great potential as a therapeutic target for the control of cancerous migration in OSCC.

Cardiac arterial bulbs of Skipjack tuna (Katsuwonus pelamis) are rich in elastin, and its hydrolysates are high quality raw materials for daily cosmetics. In order to effectively utilizing Skipjack tuna processing byproducts-cardiac arterial bulbs and to prepare peptides with high antioxidant activity, pepsin was selected from six proteases for hydrolyzing proteins, and the best hydrolysis conditions of pepsin were optimized. Using ultrafiltration and chromatographic methods, eleven antioxidant peptides were purified from protein hydrolysate of tuna cardiac arterial bulbs. Four tripeptides (QGD, PKK, GPQ and GLN) were identified as well as seven pentapeptides (GEQSN, GEEGD, YEGGD, GEGER, GEGQR, GPGLM and GDRGD). Three out of them, namely the tripeptide PKK and the pentapeptides YEGGD and GPGLM exhibited the highest radical scavenging activities on 2,2-diphenyl-1-picrylhydrazyl (DPPH), hydroxyl, 2,2′-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) and superoxide anion assays. They also showed to protect plasmid DNA and HepG2 cells against H2O2-induced oxidative stress. Furthermore, they exhibited high stability under temperature ranged from 20-100 °C, pH values ranged from 3-11, and they simulated gastrointestinal digestion for 240 min. These results suggest that the prepared eleven antioxidant peptides from cardiac arterial bulbs, especially the three peptides PKK, YEGGD, and GPGLM, could serve as promising candidates in health-promoting products due to their high antioxidant activity and their stability.

Non‐small‐cell lung cancer (NSCLC), with its aggressive biological behavior, is one of the most diagnosed cancers. Tumor‐associated inflammatory cells play important roles in the interaction between chronic inflammation and lung cancer, however the mechanisms involved are far from defined. In the present study, by developing an orthotopic NSCLC mouse model based on chronic inflammation, we proved that an inflammatory microenvironment accelerated the growth of orthotopic xenografts in vivo. Tumor‐associated macrophages, the most abundant population of inflammatory cells, were identified. Treatment with macrophage‐conditioned medium (MCM) promoted the growth and migration of NSCLC cells. Using bioinformatics analysis, we identified downregulated PP2Ac expression in NSCLC cells upon treatment with MCM. We further confirmed that this downregulation was executed in an NF‐κB pathway‐dependent manner. As IκB kinase (IKK) has been proved to be a substrate of PP2Ac, inhibition on PP2Ac could result in amplification of NF‐κB pathway signaling. Overexpression of PP2Ac, or the dominant‐negative forms of IKK or IκB, attenuated the acceleration of growth and metastasis by MCM. Using bioinformatics analysis, we further identified that CXCL1 and COL6A1 could be downstream of NF‐κB/PP2Ac pathway. Luciferase assay and ChIP assay further confirmed the location of response elements on the promoter regions of CXCL1 and COL6A1. Elevated CXCL1 facilitated angiogenesis, whereas upregulated COL6A1 promoted proliferation and migration. Tumor‐associated macrophages, the prominent type of inflammatory cells in non‐small‐cell lung cancer, can promote the growth and metastasis of cancer cells. Overexpression of PP2Ac, or the dominant‐negative forms of IKK or IκB, attenuated the acceleration on cancer cell growth and metastasis by TAMs. CXCL1 and COL6A1 could be downstream of NF‐κB/PP2Ac pathway. Elevated CXCL1 facilitated angiogenesis, whereas upregulated COL6A1 promoted cancer cell proliferation and migration.

Autophagy is a highly conserved catabolic process that mediates degradation of pernicious or dysfunctional cellular components, such as invasive pathogens, senescent proteins, and organelles. It can promote or suppress tumor development, so it is a “double-edged sword” in tumors that depends on the cell and tissue types and the stages of tumor. The epithelial-mesenchymal transition (EMT) is a complex biological trans-differentiation process that allows epithelial cells to transiently obtain mesenchymal features, including motility and metastatic potential. EMT is considered as an important contributor to the invasion and metastasis of cancers. Thus, clarifying the crosstalk between autophagy and EMT will provide novel targets for cancer therapy. It was reported that EMT-related signal pathways have an impact on autophagy; conversely, autophagy activation can suppress or strengthen EMT by regulating various signaling pathways. On one hand, autophagy activation provides energy and basic nutrients for EMT during metastatic spreading, which assists cells to survive in stressful environmental and intracellular conditions. On the other hand, autophagy, acting as a cancer-suppressive function, is inclined to hinder metastasis by selectively down-regulating critical transcription factors of EMT in the early phases. Therefore, the inhibition of EMT by autophagy inhibitors or activators might be a novel strategy that provides thought and enlightenment for the treatment of cancer. In this article, we discuss in detail the role of autophagy and EMT in the development of cancers, the regulatory mechanisms between autophagy and EMT, the effects of autophagy inhibition or activation on EMT, and the potential applications in anticancer therapy.

The aim of this study was to investigate the protective function and mechanism of TCP3 (PKK), TCP6 (YEGGD) and TCP9 (GPGLM) from skipjack tuna cardiac arterial bulbs on skin photoaging using UVB-irradiated HaCaT cell model. The present results indicated that TCP3 (PKK), TCP6 (YEGGD) and TCP9 (GPGLM) had significant cytoprotective effect on UVB-irradiated HaCaT cells (p < 0.001). Hoechst 33342 staining showed that apoptosis of UV-irradiated HaCaT cells could be significantly reduced by the treatment of TCP3 (PKK), TCP6 (YEGGD) and TCP9 (GPGLM); JC-1 staining showed that TCP3 (PKK), TCP6 (YEGGD) and TCP9 (GPGLM) could protect HaCaT cells from apoptosis by restoring mitochondrial membrane potential (MMP); Furthermore, TCP3 (PKK), TCP6 (YEGGD) and TCP9 (GPGLM) could significantly down-regulate the ratio of Bax/Bcl-2 and reduce the expression level of the apoptosis-executing protein Caspase-3 by decreasing the expression of protein Caspase-8 and Caspase-9 (p < 0.05). The action mechanism indicated that TCP3 (PKK), TCP6 (YEGGD) and TCP9 (GPGLM) could up-regulate the expression levels of Nrf2, NQO1 and HO-1 (p < 0.05), which further increased the activity of downstream proteases (SOD, CAT and GSH-Px), and scavenged reactive oxygen species (ROS) and decreased the intracellular levels of malondialdehyde (MDA). In addition, molecular docking indicated that TCP3 (PKK) and TCP6 (YEGGD) could competitively inhibit the Nrf2 binding site because they can occupy the connection site of Nrf2 by binding to the Kelch domain of Keap1 protein. TCP9 (GPGLM) was inferred to be non-competitive inhibition because it could not bind to the active site of the Kelch domain of Keap1 protein. In summary, the antioxidant peptides TCP3 (PKK), TCP6 (YEGGD) and TCP9 (GPGLM) from cardiac arterial bulbs of skipjack tuna can effectively protect HaCaT cells from UVB-irradiated damage and can be used in the development of healthy and cosmetic products to treat diseases caused by UV radiation.

Surveys are a crucial tool for understanding public opinion and behaviour, and their accuracy depends on maintaining statistical representativeness of their target populations by minimizing biases from all sources. Increasing data size shrinks confidence intervals but magnifies the effect of survey bias: an instance of the Big Data Paradox 1 . Here we demonstrate this paradox in estimates of first-dose COVID-19 vaccine uptake in US adults from 9 January to 19 May 2021 from two large surveys: Delphi–Facebook 2 , 3 (about 250,000 responses per week) and Census Household Pulse 4 (about 75,000 every two weeks). In May 2021, Delphi–Facebook overestimated uptake by 17 percentage points (14–20 percentage points with 5% benchmark imprecision) and Census Household Pulse by 14 (11–17 percentage points with 5% benchmark imprecision), compared to a retroactively updated benchmark the Centers for Disease Control and Prevention published on 26 May 2021. Moreover, their large sample sizes led to miniscule margins of error on the incorrect estimates. By contrast, an Axios–Ipsos online panel 5 with about 1,000 responses per week following survey research best practices 6 provided reliable estimates and uncertainty quantification. We decompose observed error using a recent analytic framework 1 to explain the inaccuracy in the three surveys. We then analyse the implications for vaccine hesitancy and willingness. We show how a survey of 250,000 respondents can produce an estimate of the population mean that is no more accurate than an estimate from a simple random sample of size 10. Our central message is that data quality matters more than data quantity, and that compensating the former with the latter is a mathematically provable losing proposition. An analysis of three surveys of COVID-19 vaccine behaviour shows that larger surveys overconfidently overestimated vaccine uptake, a demonstration of how larger sample sizes can paradoxically lead to less accurate estimates.

Weyl points, as a signature of 3D topological states, have been extensively studied in condensed matter systems. Recently, the physics of Weyl points has also been explored in electromagnetic structures such as photonic crystals and metamaterials. These structures typically have complex three-dimensional geometries, which limits the potential for exploring Weyl point physics in on-chip integrated systems. Here we show that Weyl point physics emerges in a system of two-dimensional arrays of resonators undergoing dynamic modulation of refractive index. In addition, the phase of modulation can be controlled to explore Weyl points under different symmetries. Furthermore, unlike static structures, in this system the non-trivial topology of the Weyl point manifests in terms of surface state arcs in the synthetic space that exhibit one-way frequency conversion. Our system therefore provides a versatile platform to explore and exploit Weyl point physics on chip. Weyl points, point degeneracies surrounded by linear dispersions, are the 3-dimensional analogue of the Dirac points known from 2D materials. Here, Lin et al . propose a scheme for realizing on-chip electromagnetic Weyl points by utilizing the concept of synthetic dimensions.