Clinical M2 Macrophage-Related Genes Can Serve as a Reliable Predictor of Lung Adenocarcinoma

BackgroundNumerous studies have found that infiltrating M2 macrophages play an important role in the tumor progression of lung adenocarcinoma (LUAD). However, the roles of M2 macrophage infiltration and M2 macrophage-related genes in immunotherapy and clinical outcomes remain obscure.MethodsSample information was extracted from TCGA and GEO databases. The TIME landscape was revealed using the CIBERSORT algorithm. Weighted gene co-expression network analysis (WGCNA) was used to find M2 macrophage-related gene modules. Through univariate Cox regression, lasso regression analysis, and multivariate Cox regression, the genes strongly associated with the prognosis of LUAD were screened out. Risk score (RS) was calculated, and all samples were divided into high-risk group (HRG) and low-risk group (LRG) according to the median RS. External validation of RS was performed using GSE68571 data information. Prognostic nomogram based on risk signatures and other clinical information were constructed and validated with calibration curves. Potential associations of tumor mutational burden (TMB) and risk signatures were analyzed. Finally, the potential association of risk signatures with chemotherapy efficacy was investigated using the pRRophetic algorithm.ResultsBased on 504 samples extracted from TCGA database, 183 core genes were identified using WGCNA. Through a series of screening, two M2 macrophage-related genes (GRIA1 and CLEC3B) strongly correlated with LUAD prognosis were finally selected. RS was calculated, and prognostic risk nomogram including gender, age, T, N, M stage, clinical stage, and RS were constructed. The calibration curve shows that our constructed model has good performance. HRG patients were suitable for new ICI immunotherapy, while LRG was more suitable for CTLA4-immunosuppressive therapy alone. The half-maximal inhibitory concentrations (IC50) of the four chemotherapeutic drugs (metformin, cisplatin, paclitaxel, and gemcitabine) showed significant differences in HRG/LRG.ConclusionsIn conclusion, a comprehensive analysis of the role of M2 macrophages in tumor progression will help predict prognosis and facilitate the advancement of therapeutic techniques

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Research on Risk Management of Gongbei Tunnel Engineering Excavation Team

Gongbei tunnel is the key project of Hong kong-Zhuhai-macao bridge Zhuhai connecting line. The tunnel adopts frozen Curve pipe curtain digging method. In order to ensure the safety of Gongbei tunnel engineering, the rsik management of tunnel excavation team has studied. It has studied on the relevancy between on the organizational structure, rules and regulations, education and training, assessment of rewards and punishments of construction team. Then it make sure the best relevancy risk to plan the risk prevention and controlling measures. Finally, the safety management strategy has targeted to the Excavation team. After practical application, the excavation team of Gongbei tunnel has achieved all-round and focused risk management, which has guided the implementation of the excavation work

Etching characteristics for tracks of carbon cluster ions in polycarbonate

A series of chemical etching experiments were carried out on polycarbonate foils irradiated by carbon cluster ions with an energy of 0.6 MeV/atom. The bulk etching rate was calculated from weight loss. The transversal etching rate was obtained by using linear fit to the pore diameters under a time sequence. It was found that the transversal etching rate depends on the rate of electronic energy deposition of projectiles. A distinctly irregular pore size distribution was found on the image of etched pores after C4+ irradiation and after one hour etching and explained as the contribution of dissociation of the carbon cluster

Distribution characteristics and source identification of shallow groundwater pollution in Yongcheng City

In order to effectively manage and protect the shallow groundwater resource in Yongcheng City and maintain the sustainable utilization of water resource, distribution characteristics and sources of pollutants must be identified.On the basis of sampling and analysis of shallow groundwater, this paper studies the sources and distribution characteristics of main pollution components, combining with the influence of industrial layout change and land use type distribution caused by urban development.The results show that the growth of urban secondary industry (industry and mining) and GDP are correlated with the increase of SO42- and NO3- contents in shallow groundwater, the dense areas of urban industry and population tend to be the same as the seriously polluted areas of shallow groundwater.The main source of shallow groundwater pollution is the increase of SO42- content, in addition to directly causing the deterioration of water quality.It also indirectly changes the intensity of hydrogeochemical action.It leads to an increase in the dissolution of the insoluble carbonate and silicate, which further increases the content of TDS and changes the water quality.In addition, NO3- and COD are also the main pollution sources.It comes partly from industrial waste water and partly from the excessive use of pesticides and fertilizer in agriculture

Clinical Eosinophil-Associated Genes can Serve as a Reliable Predictor of Bladder Urothelial Cancer

Background: Numerous studies have shown that infiltrating eosinophils play a key role in the tumor progression of bladder urothelial carcinoma (BLCA). However, the roles of eosinophils and associated hub genes in clinical outcomes and immunotherapy are not well known. Methods: BLCA patient data were extracted from the TCGA database. The tumor immune microenvironment (TIME) was revealed by the CIBERSORT algorithm. Candidate modules and hub genes associated with eosinophils were identified by weighted gene co-expression network analysis (WGCNA). The external GEO database was applied to validate the above results. TIME-related genes with prognostic significance were screened by univariate Cox regression analysis, lasso regression, and multivariate Cox regression analysis. The patient’s risk score (RS) was calculated and divided subjects into high-risk group (HRG) and low-risk group (LRG). The nomogram was developed based on the risk signature. Models were validated via receiver operating characteristic (ROC) curves and calibration curves. Differences between HRG and LRG in clinical features and tumor mutational burden (TMB) were compared. The Immune Phenomenon Score (IPS) was calculated to estimate the immunotherapeutic significance of RS. Half-maximal inhibitory concentrations (IC50s) of chemotherapeutic drugs were predicted by the pRRophetic algorithm. Results: 313 eosinophil-related genes were identified by WGCNA. Subsequently, a risk signature containing 9 eosinophil-related genes (AGXT, B3GALT2, CCDC62, CLEC1B, CLEC2D, CYP19A1, DNM3, SLC5A9, SLC26A8) was finally developed via multiplex analysis and screening. Age (p < 0.001), grade (p < 0.001), and RS (p < 0.001) were independent predictors of survival in BLCA patients. Based on the calibration curve, our risk signature nomogram was confirmed as a good predictor of BLCA patients’ prognosis at 1, 3, and 5 years. The association analysis of RS and immunotherapy indicated that low-risk patients were more credible for novel immune checkpoint inhibitors (ICI) immunotherapy. The chemotherapeutic drug model suggests that RS has an effect on the drug sensitivity of patients. Conclusions: In conclusion, the eosinophil-based RS can be used as a reliable clinical predictor and provide insights into the precise treatment of BLCA

Clinical characteristics and prostate-cancer-specific mortality of competitive risk nomogram in the second primary prostate cancer

BackgroundWith the development of early diagnosis and treatment, the second primary malignancy (SPM) attracts increasing attention. The second primary prostate cancer (spPCa) is an important class of SPM, but remains poorly understood.MethodsWe retrospectively analyzed 3,322 patients with spPCa diagnosed between 2004 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database. Chi-square test was applied to compare demographic and clinical variables and analyze causes of death. Multivariate competitive risk regression model was used to identify risk factors associated with prostate-cancer-specific mortality (PCSM), and these factors were enrolled to build a nomogram of competitive risk. The C-index, calibration curve, and decision curve analysis (DCA) were employed to evaluate the discrimination ability of our nomogram.ResultsThe median follow-up (interquartile range, IQR) time was 47 (24–75) months, and the median (IQR) diagnosis interval between the first primary cancer (FPC) and spPCa was 32 (16–57) months. We found that the three most common sites of SPM were the urinary system, digestive system, and skin. Through multivariate competitive risk analysis, we enrolled race (p &lt; 0.05), tumor–node–metastasis (TNM) stage (p &lt; 0.001), Gleason score (p &lt; 0.05), surgery (p = 0.002), and radiotherapy (p = 0.032) to construct the model to predict the outcomes of spPCa. The C-index was 0.856 (95% CI, 0.813–0.899) and 0.905 (95% CI, 0.941–0.868) in the training and validation set, respectively. Moreover, both the calibration curve and DCA illustrated that our nomogram performed well in predicting PCSM.ConclusionIn conclusion, we identified four risk factors associated with the prognosis of spPCa and construct a competing risk nomogram, which performed well in predicting the 3-, 5-, and 10-year PCSM

Ultralow-voltage operation of light-emitting diodes.

For a light-emitting diode (LED) to generate light, the minimum voltage required is widely considered to be the emitter's bandgap divided by the elementary charge. Here we show for many classes of LEDs, including those based on perovskite, organic, quantum-dot and III-V semiconductors, light emission can be observed at record-low voltages of 36-60% of their bandgaps, exhibiting a large apparent energy gain of 0.6-1.4 eV per photon. For 17 types of LEDs with different modes of charge injection and recombination (dark saturation currents of ~10-39-10-15 mA cm-2), their emission intensity-voltage curves under low voltages show similar behaviours. These observations and their consistency with the diode simulations suggest the ultralow-voltage electroluminescence arises from a universal origin-the radiative recombination of non-thermal-equilibrium band-edge carriers whose populations are determined by the Fermi-Dirac function perturbed by a small external bias. These results indicate the potential of low-voltage LEDs for communications, computational and energy applications

Probing the effect of the Pt-Ni-Pt(111) bimetallic surface electronic structures on the ammonia decomposition reaction

We report a detailed investigation of elementary catalytic decomposition of ammonia on the Pt-Ni-Pt(111) bimetallic surface using in situ near ambient pressure X-ray photoelectron spectroscopy. Under the near ambient pressure (0.6 mbar) reaction conditions, a different dehydrogenation pathway with a reduced activation energy barrier for recombinative nitrogen desorption on the Pt-Ni-Pt(111) bimetallic surface is observed. The unique surface catalytic activity is correlated with the downward shift of the Pt 5d band states induced by the Ni subsurface atoms via charge redistribution of the topmost Pt layer. Our results provide a practical understanding of the unique chemistry of bimetallic catalysts for facile ammonia decomposition under realistic reaction conditions

Quantitative study of spin relaxation in rubrene thin films by inverse spin Hall effect

Spin relaxation properties of π-conjugated organic semiconductors are key indicators of the performance of organic spintronic devices. However, reliable determination of spin relaxation parameters in organic materials is hindered by complex interfacial phenomena at organic/ferromagnetic metal interfaces that couple spin injection with charge injection. Here, we study the spin pumping induced pure spin transport in Permalloy/rubrene/Pt trilayers and determine the spin diffusion length λs = 132 ± 9 nm and the spin relaxation time τs = 3.8 ± 0.5 ms in rubrene films at room temperature by using the inverse spin Hall effect. The determined spin diffusion length λs is found to be almost two times larger than that of ∼46.3 nm at 100 K extracted from rubrene spin valve devices in which charge carrier injection/detection occurs at organic/ferromagnetic metal interfaces. Our results demonstrate experimentally that the efficiency and the rate of spin polarized charge transport through the organic/ferromagnetic metal interface play a dominant role in determining the spin relaxation process of spin valve devices in which charge and spin currents are coupled