Liquid biopsies, based on cell free DNA (cfDNA) and proteins, have shown the potential to detect early stage cancers of diverse tissue types. However, most of these studies were retrospective, using ...individuals previously diagnosed with cancer as cases and healthy individuals as controls. Here, we developed a liquid biopsy assay, named the hepatocellular carcinoma screen (HCCscreen), to identify HCC from the surface antigen of hepatitis B virus (HBsAg) positive asymptomatic individuals in the community population. The training cohort consisted of individuals who had liver nodules and/or elevated serum α-fetoprotein (AFP) levels, and the assay robustly separated those with HCC from those who were non-HCC with a sensitivity of 85% and a specificity of 93%. We further applied this assay to 331 individuals with normal liver ultrasonography and serum AFP levels. A total of 24 positive cases were identified, and a clinical follow-up for 6–8 mo confirmed four had developed HCC. No HCC cases were diagnosed from the 307 test-negative individuals in the follow-up during the same time-scale. Thus, the assay showed 100% sensitivity, 94% specificity, and 17% positive predictive value in the validation cohort. Notably, each of the four HCC cases was at the early stage (<3 cm) when diagnosed. Our study provides evidence that the use of combined detection of cfDNA alterations and protein markers is a feasible approach to identify early stage HCC from asymptomatic community populations with unknown HCC status.
One major impediment to improving the management of breast cancer is the current lack of tumor marker with sufficient sensitivity and specificity. A growing body of evidence implicates the diagnostic ...potential of circulating miRNAs in cancer detection. MiR-155 plays an important role in the pathogenesis of breast cancer. However, the level of circulating miR-155 and its clinical relevance are not well established. The objective of the current study was to learn more about serum miR-155 in patients with breast cancer.
Using quantitative reverse transcription polymerase chain reaction (RT-qPCR), we demonstrated that serum miR-155 had significant increased levels in breast cancer patients (n = 103) compared with healthy subjects (n = 55) (p<0.001), which had a mean fold change of 2.94. Receiver operating characteristic (ROC) analysis revealed that miR-155 had considerable diagnostic accuracy, yielding an ROC-AUC (the areas under the ROC curve) of 0.801 (sensitivity 65.0%, specificity 81.8%). In addition, sera from a subset of breast cancer patients (n = 29) were collected after surgery and after four cycles of chemotherapy to evaluate the effects of clinical treatment on serum levels of candidate miRNAs. Surprisingly, a decreased level of serum miR-155 was found; whereas the concentrations of carbohydrate antigen 15-3 (CA15-3), carcinoembryonic antigen (CEA) and tissue polypeptide specific antigen (TPS) did not show this trend. Our results revealed that 79% patients showed response or stable disease after therapy had declined levels of serum miR-155.
Our results suggest that serum miR-155 is a potential biomarker to discriminate breast cancer patients from healthy subjects. For the first time, we demonstrated a declined trend of miR-155 after surgery and chemotherapy, which raises the possibility to use it as an indicator for treatment response.
The sluggish kinetics of oxygen evolution reaction (OER) still remains a primary obstacle to hydrogen production via water electrolysis. The evolution of exceptionally active and durable ...non-noble-metal-based OER electrocatalyst as a prerequisite for practical applications is significant. In this paper, we report a facile one-pot hydrothermal method for synthesizing a porous Fe0.67Ni0.33OOH-Fe2O3@NF sheet-like nanoarray as an OER electrocatalyst. As expected, this Fe0.67Ni0.33OOH-Fe2O3@NF electrocatalyst exhibits desirable OER performance with low overpotential (232 mV) at 10 mA cm−2 current density, 34 mV dec−1 Tafel slope, impressive durability over 1000 CV cycles, and 110 h continuous i-t response at 30 mA cm−2 current density. These values exceed those observed from most reported non-/noble-metal-based OER electrocatalysts to date, and these observations are consistent with exposure of numerous intrinsically active sites, synergistic modulation of charge transfer, and intense interactions between Fe, Ni, and O, as well as increased mass transfer based on separation of bubbles generated on the integrated electrode surface. These results illustrate the potential for this strategy to provide a low-cost, highly-active OER electrocatalyst as a kind of renewable energy storage devices, such as metal-air battery and water oxidation.
•A highly-active Fe0.67Ni0.670.0.67033OOH-Fe2O3@NF electrocatalyst was in-situ synthesized by low-temperature hydrothermal method.•A proper amount of Fe3+ can effectively form a sheet-like porous structure.•The Fe0.67Ni0.33OOH-Fe2O3@NF exhibits low overpotential, impressive durability, and continuous i-t response performances.•Fe0.67Ni0.33OOH-Fe2O3@NF were expected to be a practical-oriented excellent OER electrocatalyst.
Due to the negligence of the complex tumor immune microenvironment, traditional treatment for glioblastoma has reached its limitation and cannot achieve a satisfying outcome in the past decade. The ...emergence of immunotherapy based on the theory of cancer-immunity cycle has brought a new dawn to glioblastoma patients. However, the results of most phase II and phase III clinical trials are not optimistic due to the simple focus on T cells activation rather than other immune cells involved in anti-tumor immunity. NK cells play a critical role in both innate and adaptive immunity, having the ability to coordinate immune response in inflammation, autoimmune disease and cancer. They are expected to cooperate with T cells to maximize the anti-tumor immune effect and have great potential in treating glioblastoma. Here, we describe the traditional treatment methods and current immunotherapy strategies for glioblastoma. Then, we list a microenvironment map and discuss the reasons for glioblastoma inhibitory immunity from multiple perspectives. More importantly, we focus on the advantages of NK cells as potential immune regulatory cells and the ways to maximize their anti-tumor immune effect. Finally, our outlook on the directions and potential applications of NK cell-based therapy combining with the advance technologies is presented. This review depicts NK cell awakening as the precondition to unleash the cancer-immunity cycle against glioblastoma and elaborate this idea from biology to clinical treatment.
Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the ...city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.
FeNC catalysts demonstrate remarkable activity and stability for the oxygen reduction reaction (ORR) in polymer electrolyte membrane fuel cells and Zn–air batteries (ZABs). The local coordination ...of Fe single atoms in FeNC catalysts strongly impacts ORR activity. Herein, FeNC catalysts containing Fe single atoms sites with FeN3, FeN4, and FeN5 coordinations are synthesized by carbonization of Fe‐rich polypyrrole precursors. The FeN5 sites possess a higher Fe oxidation state (+2.62) than the FeN3 (+2.23) and FeN4 (+2.47) sites, and higher ORR activity. Density functional theory calculations verify that the FeN5 coordination optimizes the adsorption and desorption of ORR intermediates, dramatically lowering the energy barrier for OH− desorption in the rate‐limiting ORR step. A primary ZAB constructed using the FeNC catalyst with FeN5 sites demonstrates state‐of‐the‐art performance (an open circuit potential of 1.629 V, power density of 159 mW cm−2). Results confirm an intimate structure‐activity relationship between Fe coordination, Fe oxidation state, and ORR activity in FeNC catalysts.
FeNC catalysts with different Fe single‐atom coordination geometries (FeN3, FeN4, or FeN5) are synthesized by pyrolysis of Fe‐polypyrrole precursors. FeN5 sites offer the highest Fe oxidation state (+2.62), strongest Fe–N interaction, lowest energy barrier for OH− desorption, and highest intrinsic activity for oxygen reduction reaction in alkaline media.
People in cities nowadays suffer from increasingly severe traffic jams due to less awareness of how collective human mobility is affected by urban planning. Besides, understanding how region ...functions shape human mobility is critical for business planning but remains unsolved so far. This study aims to discover the association between region functions and resulting human mobility. We establish a linear regression model to predict the traffic flows of Beijing based on the input referred to as bag of POIs. By solving the predictor in the sense of sparse representation, we find that the average prediction precision is over 74% and each type of POI contributes differently in the predictor, which accounts for what factors and how such region functions attract people visiting. Based on these findings, predictive human mobility could be taken into account when planning new regions and region functions.
The injection molding filling process is a complicated non-steady-state, non-isothermal non-Newtonian fluid flow process and heat transfer process. With the development of polymer melt pressure, ...temperature, shear rate and other physical quantities during the mold filling process will affect the melt rheological properties. This research combines the injection molding visualization device and analysis method to collect real-time online parameters of the co-injection self-reinforced parts in the mold under different molding conditions. The distribution and change data provide an effective means for better characterizing the rheological properties of the polymer in the mold and the theoretical analysis of the mold filling rheology. This article starts with the basic equations of viscous fluid mechanics, draws on the establishment of the mathematical model of the filling process of the conventional injection molding, corrects and resets the basic assumptions and boundary conditions, and establishes a flow that can reflect the melt flow at the slender scale. The basic equation of scale effect is made in the process, and it is substituted into the simulation software for simulation analysis. The results show that there is no deviation in the overall structure of the model, but the parameters in the model should be variable factors that change with the change of the melt molding parameters. Therefore, we made a second correction to the variable parameters of the in-mold co-injection self-reinforced cross-scale viscosity model. Although there is a certain difference (12.62%) between the viscosity results obtained after the simulation and the measured values, it is compared with the conventional model deviation value of the model (101.25%) has been better improved, which can better achieve the purpose of simulation prediction.
•A constitutive model of melt-filled in-mold co-injection molding considering the influence of micro-scale effects is established.•Compared with the conventional micro-scale viscosity model, the average prediction error of the size factor model for the IMSR-SPCs melt viscosity is reduced by 14.9%.•We have corrected the variable factors of the in-mold co-injection cross-scale viscosity model, and there is a difference between in comparison with conventional model parameters deviation had a better improved.•Through the visualization experiment, the flow speed of the reinforced melt is faster, the pressure loss is reduced and the temperature decrease is lower than that of the metal flow runners.•The plasticizing temperature has the greatest influence on the enhanced melt viscosity and the injection speed has the least influence.
Ferroptosis is an iron-dependent cell death process mainly triggered by reactive oxygen species (ROS) and lipid peroxidation. Thioredoxin domain protein 12 (TXNDC12) promotes the development of some ...tumors; however, its function in tumor ferroptosis remains unclear. In this study, we found that knockdown of TXNDC12 promoted erastin-induced increase in ROS, lipid peroxidation, and Fe
levels, and decreased glutathione content. TXNDC12 is involved in ferroptosis by regulating SLC7A11. Further studies showed that TXNDC12 knockdown promoted an erastin-induced decrease in glioma cell viability. Overall, TXNDC12 played a significant role in ferroptosis by modulating SLC7A11 expression. Thus, TXNDC12 and ferroptosis may provide new targets for the treatment of gliomas.
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