Effect of Corrosion and Corrosion Rate on the Mechanical Performance of Carbon and Stainless Steel Reinforcing Bars

Steel corrosion is a predominant factor leading to age-related structural degradation. To understand the different effects of pitting corrosion on the mechanical performances of deformed carbon and stainless steel reinforcing bars, an artificially accelerated method was conducted to corrode the steel bars. Using a 3D laser scanner, the three-dimensional models of corroded steel bars were reconstructed. The corrosion characterization was identified based on these 3D profiles. The results indicate that the number and the depth of corrosion pits of both types of steel increase with the increase of corrosion rate, however the pitting corrosion of stainless steel is much more obvious than the carbon steel. Axial tensile tests of corroded carbon and stainless steel bars were carried out. The tensile test results show that both the yield and ultimate loads linearly decreased with an increase of corrosion loss while the ductility decreased correspondingly. With the increase of corrosion loss, brittle fracture gradually occurred in the corroded carbon steel bars at the location of critical cross-sectional area. However, the degradation ratio of elongation of stainless steel is less than that of the carbon steel

Density-dependent prophylaxis in crowded Beet Webworm, Loxostege sticticalis (Lepidoptera: Pyralidae) larvae to a parasitoid and a fungal pathogen

Transmission of parasites and pathogens is generally positively density-dependent: as an insect population\u27s density increases, the risk of an individual becoming attacked or infected also increases. In some insect species, individuals experiencing crowded conditions are more resistant to natural enemies than those experiencing low density conditions, and they are predicted to divert resources to increase resistance. This phenomenon is called density-dependent prophylaxis. Here, possible expression of prophylaxis in fifth-instar larvae of Beet Webworm, Loxostege sticticalis, to biocontrol agents was investigated under rearing densities of 1, 10, and 30 larvae per jar (650 mL). Larvae reared at the moderate density and those reared in isolation displayed the greatest and lowest resistance, respectively, to an entomopathogenic fungus and a parasitoid. Moreover, larvae from the moderate density treatment exhibited elevated phenoloxidase, total haemocyte count and antibacterial activity in the haemolymph, whereas phenoloxidase levels in the midgut were not affected. The results suggest that larval rearing density significantly affects the immune system, and they provide evidence for density-dependent prophylaxis of larval L. sticticalis against its biocontrol agents. These results have implications for understanding the population dynamics and biocontrol of beet webworm

Identification and characterization of a 25-lncRNA prognostic signature for early recurrence in hepatocellular carcinoma

Background Early recurrence is the major cause of poor prognosis in hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) are deeply involved in HCC prognosis. In this study, we aimed to establish a prognostic lncRNA signature for HCC early recurrence. Methods The lncRNA expression profile and corresponding clinical data were retrieved from total 299 HCC patients in TCGA database. LncRNA candidates correlated to early recurrence were selected by differentially expressed gene (DEG), univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. A 25-lncRNA prognostic signature was constructed according to receiver operating characteristic curve (ROC). Kaplan-Meier and multivariate Cox regression analyses were used to evaluate the performance of this signature. ROC and nomogram were used to evaluate the integrated models based on this signature with other independent clinical risk factors. Gene set enrichment analysis (GSEA) was used to reveal enriched gene sets in the high-risk group. Tumor infiltrating lymphocytes (TILs) levels were analyzed with single sample Gene Set Enrichment Analysis (ssGSEA). Immune therapy response prediction was performed with TIDE and SubMap. Chemotherapeutic response prediction was conducted by using Genomics of Drug Sensitivity in Cancer (GDSC) pharmacogenomics database. Results Compared to low-risk group, patients in high-risk group showed reduced disease-free survival (DFS) in the training (p < 0.0001) and validation cohort (p = 0.0132). The 25-lncRNA signature, AFP, TNM and vascular invasion could serve as independent risk factors for HCC early recurrence. Among them, the 25-lncRNA signature had the best predictive performance, and combination of those four risk factors further improves the prognostic potential. Moreover, GSEA showed significant enrichment of “E2F TARGETS”, “G2M CHECKPOINT”, “MYC TARGETS V1” and “DNA REPAIR” pathways in the high-risk group. In addition, increased TILs were observed in the low-risk group compared to the high-risk group. The 25-lncRNA signature negatively associates with the levels of some types of antitumor immune cells. Immunotherapies and chemotherapies prediction revealed differential responses to PD-1 inhibitor and several chemotherapeutic drugs in the low- and high-risk group. Conclusions Our study proposed a 25-lncRNA prognostic signature for predicting HCC early recurrence, which may guide postoperative treatment and recurrence surveillance in HCC patients

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Overview of the MOSAiC expedition: Physical oceanography

Arctic Ocean properties and processes are highly relevant to the regional and global coupled climate system, yet still scarcely observed, especially in winter. Team OCEAN conducted a full year of physical oceanography observations as part of the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC), a drift with the Arctic sea ice from October 2019 to September 2020. An international team designed and implemented the program to characterize the Arctic Ocean system in unprecedented detail, from the seafloor to the air-sea ice-ocean interface, from sub-mesoscales to pan-Arctic. The oceanographic measurements were coordinated with the other teams to explore the ocean physics and linkages to the climate and ecosystem. This paper introduces the major components of the physical oceanography program and complements the other team overviews of the MOSAiC observational program. Team OCEAN’s sampling strategy was designed around hydrographic ship-, ice- and autonomous platform-based measurements to improve the understanding of regional circulation and mixing processes. Measurements were carried out both routinely, with a regular schedule, and in response to storms or opening leads. Here we present alongdrift time series of hydrographic properties, allowing insights into the seasonal and regional evolution of the water column from winter in the Laptev Sea to early summer in Fram Strait: freshening of the surface, deepening of the mixed layer, increase in temperature and salinity of the Atlantic Water. We also highlight the presence of Canada Basin deep water intrusions and a surface meltwater layer in leads. MOSAiC most likely was the most comprehensive program ever conducted over the ice-covered Arctic Ocean. While data analysis and interpretation are ongoing, the acquired datasets will support a wide range of physical oceanography and multi-disciplinary research. They will provide a significant foundation for assessing and advancing modeling capabilities in the Arctic Ocean