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This study conducted a large root box experiment with Schefflera arboricola monoculture, Neolamarckia cadamba monoculture, and co-planting of Schefflera arboricola and Neolamarckia cadamba. The dynamic changes in Cu, Zn, Cd, and Hg contents in fresh and litter leaves of Schefflera arboricola and Neolamarckia cadamba and their litter leaves yield were analyzed for three months (September, October, and November 2020) after the surface application of 2% (W/W) sewage sludge (SS). The relationship between the heavy metal contents of fresh and litter leaves and the changes in the heavy metal return amount in litter leaves were further analyzed. The results were as follows: (1) N. cadamba had significantly higher Cu contents in fresh and litter leaves than those of S. arboricola, while had significantly lower Zn and Cd contents than those of S. arboricola. (2) The fresh leaves of S. arboricola had the lowest Zn content and the highest Hg content in November. (3) The fresh leaves of monoculture and co-planting Neolamarckia cadamba had the highest Zn, Cd, and Hg contents in November. (4) The Hg content in the litter leaves of co-planting of N. cadamba increased significantly with the time of SS application, while those of Cu, Zn, and Cd contents showed no significance. (5) The Cd content in fresh leaves was significantly and positively correlated with the Hg and Cd contents of litter leaves in Schefflera arboricola in both September and November. (6) The highest yield of litter leaves and the highest return amount of Cu, Zn, Cd, and Hg in S. arboricola occurred one month after SS application (September), while those in Neolamarckia cadamba occurred two months after SS application (October). In summary, the application time of SS showed a greater effect on the heavy metal contents in fresh leaves of N. cadamba and Schefflera arboricola than those in litter leaves; there was a positive correlation between the Cd content in the fresh leaves and the Cd and Hg contents in the litter leaves of S. arboricola; the heavy metal pollution risk of the litter leaves of S. arboricola and Neolamarckia cadamba was easy to occur in one month (September) and two months (October) after SS application, respectively. This study provides a reference for safe SS utilization and reasonable litter disposal in the landscape.

The Open Science Grid (OSG) provides a common service for resource providers and scientific institutions, and supports sciences such as High Energy Physics, Structural Biology, and other community sciences. As scientific frontiers expand, so does the need for resources to analyze new data. For example, High Energy Physics experiments such as the LHC experiments foresee an exponential growth in the amount of data collected, which comes with corresponding growth in the need for computing resources. Allowing resource providers an easy way to share their resources is paramount to ensure the grow of resources available to scientists. In this context, the OSG Hosted CE initiative provides site administrator a way to reduce the effort needed to install and maintain a Compute Element (CE), and represents a solution for sites who do not have the effort and expertise to run their own Grid middleware. An HTCondor Compute Element is installed on a remote VM at UChicago for each site that joins the Hosted CE initiative. The hardware/software stack is maintained by OSG Operations staff in a homogeneus and automated way, providing a reduction in the overall operational effort needed to maintain the CEs: one single organization does it in an uniform way, instead of each single resource provider doing it in their own way. Currently, more than 20 institutions joined the Hosted CE initiative. This contribution discusses the technical details behind a Hosted CE installation, highlighting key strengths and common pitfalls, and outlining future plans to further reduce operational experience.

Abstract Background Latent membrane protein (LMP) 1 and LMP2A encoded by Epstein-Barr virus (EBV) are associated with the development of malignancies, but their expression in extranodal NK/T-cell lymphoma, nasal type (ENKTL) and the relationship with clinical characteristics of this disease remain poorly understood. In the present study, we examined the expression of LMP1 and LMP2A in ENKTL, and investigated the correlations between LMP1 and LMP2A expression with clinicopathological characteristics of ENKTL patients. Methods Paraffin sections of surgically removed samples from 16 ENKTL patients were analyzed by immunohistochemistry and the related clinicopathological data were collected and analyzed. Results Elevated expression (immunohistochemistry score ≥ 4) of LMP1 and LMP2A was detected in the tumor cells of ENKTL. High LMP1 expression was associated with positive B symptoms (p = 0.012), while high LMP2A expression was related to gender (p = 0.029). The expression of both LMP1 and LMP2A showed significant correlations with patients’ overall survival (p = 0.049, p = 0.036). Conclusion LMP1 and LMP2A may be prognostic indicators of survival in patients with ENKTL. Virtual slides http://www.diagnosticpathology.diagnomx.eu/vs/2443352538545899

Abstract Background Many anticancer agents and carcinogens are DNA damaging chemicals and exposure to such chemicals results in the deregulation of cell cycle progression. The molecular mechanisms of DNA damage-induced cell cycle alteration are not well understood. We have studied the effects of etoposide (an anticancer agent), cryptolepine (CLP, a cytotoxic alkaloid), benzo [a]pyrene (BaP, a carcinogenic polycyclic aromatic hydrocarbon) and 2-amino-1-methyl-6-phenylimidazo [4,5-b]pyridine (PhIP, a cooked-meat derived carcinogen) on the expression of cell cycle regulatory genes to understand the molecular mechanisms of the cell cycle disturbance. Results A549 cells were treated with DMSO or chemicals for up to 72 h and periodically sampled for cell cycle analysis, mRNA and protein expression. DMSO treated cells showed a dominant G1 peak in cell cycle at all times examined. Etoposide and CLP both induced G2/M phase arrest yet the former altered the expression of genes functioning at multiple phases, whilst the latter was more effective in inhibiting the expression of genes in G2-M transition. Both etoposide and CLP induced an accumulation of p53 protein and upregulation of p53 transcriptional target genes. Neither BaP nor PhIP had substantial phase-specific cell cycle effect, however, they induced distinctive changes in gene expression. BaP upregulated the expression of CYP1B1 at 6–24 h and downregulated many cell cycle regulatory genes at 48–72 h. By contrast, PhIP increased the expression of many cell cycle regulatory genes. Changes in the expression of key mRNAs were confirmed at protein level. Conclusion Our experiments show that DNA damaging agents with different mechanisms of action induced distinctive changes in the expression pattern of a panel of cell cycle regulatory genes. We suggest that examining the genomic response to chemical exposure provides an exceptional opportunity to understand the molecular mechanism involved in cellular response to toxicants.

The average winding temperature of a transformer (AWTT), serving as a key indicator for assessing the running state of the transformer, is of utmost importance in determining a transformer's electrical properties and the insulation longevity of the transformer. An accurate prediction of AWTT is essential for ensuring the safe operation of the transformer. A novel method for predicting AWTT is introduced based on the analysis of field monitoring data. Firstly, the thermal characteristics and operational mechanisms of oil-immersed transformers are examined. Secondly, a factor analysis model is developed to streamline the network structure, accounting for the strong correlations among ambient temperature, load current, and top oil temperature. Thirdly, the independent temperature factor and load factor are extracted as pivotal features, and then input into the fully connected neural network to predict AWTT. Through a case study involving a 110 kV/10 kV oil-immersed transformer, the results show that the proposed method reduces redundant correlation information compared to traditional methods and improves the prediction accuracy of AWTT, establishing a foundation for further transformer state assessments. [ABSTRACT FROM AUTHOR]