In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

[Q]: Background. Before kidney transplantation, donors and recipients are routinely screened for viral pathogens using specific tests. Little is known about unrecognized viruses of the urinary tract that potentially result in transmission. Using an open metagenomic approach, we aimed to comprehensively assess virus transmission in living-donor kidney transplantation. Methods. Living kidney donors and their corresponding recipients were enrolled at the time of transplantation. Follow-up study visits for recipients were scheduled 4-6 weeks and 1 year thereafter. At each visit, plasma and urine samples were collected and transplant recipients were evaluated for signs of infection or other transplant-related complications. For metagenomic analysis, samples were enriched for viruses, amplified by anchored random polymerase chain reaction (PCR), and sequenced using high-throughput metagenomic sequencing. Viruses detected by sequencing were confirmed using real-time PCR. Results. We analyzed a total of 30 living kidney donor and recipient pairs, with a follow-up of at least 1 year. In addition to viruses commonly detected during routine post-transplant virus monitoring, metagenomic sequencing detected JC polyomavirus (JCPyV) in the urine of 7 donors and their corresponding recipients. Phylogenetic analysis confirmed infection with the donor strain in 6 cases, suggesting transmission from the transplant donor to the recipient, despite recipient seropositivity for JCPyV at the time of transplantation. Conclusions. Metagenomic sequencing identified frequent transmission of JCPyV from kidney transplant donors to recipients. Considering the high incidence rate, future studies within larger cohorts are needed to define the relevance of JCPyV infection and the donor's virome for transplant outcomes.
[A]: Clinical Infectious Diseases Metagenomic Virome Sequencing in Living Donor and Recipient Kidney Transplant Pairs Revealed JC Polyomavirus Transmission


[Q]: Background: Adverse events are associated with significant morbidity, mortality and cost in hospitalized patients. Measuring adverse events is necessary for quality improvement, but current detection methods are inaccurate, untimely and expensive. The advent of electronic health records and the development of automated methods for encoding and classifying electronic narrative data, such as natural language processing, offer an opportunity to identify potentially better methods. The objective of this study is to determine the accuracy of using automated methods for detecting three highly prevalent adverse events: a) hospital-acquired pneumonia, b) catheter-associated bloodstream infections, and c) in-hospital falls. Methods/design: This validation study will be conducted at two large Canadian academic health centres: the McGill University Health Centre (MUHC) and The Ottawa Hospital (TOH). The study population consists of all medical, surgical and intensive care unit patients admitted to these centres between 2008 and 2014. An automated detection algorithm will be developed and validated for each of the three adverse events using electronic data extracted from multiple clinical databases. A random sample of MUHC patients will be used to develop the automated detection algorithms (cohort 1, development set). The accuracy of these algorithms will be assessed using chart review as the reference standard. Then, receiver operating characteristic curves will be used to identify optimal cut points for each of the data sources. Multivariate logistic regression and the areas under curve (AUC) will be used to identify the optimal combination of data sources that maximize the accuracy of adverse event detection. The most accurate algorithms will then be validated on a second random sample of MUHC patients (cohort 1, validation set), and accuracy will be measured using chart review as the reference standard. The most accurate algorithms validated at the MUHC will then be applied to TOH data (cohort 2), and their accuracy will be assessed using a reference standard assessment of the medical chart. Discussion: There is a need for more accurate, timely and efficient measures of adverse events in acute care hospitals. This is a critical requirement for evaluating the effectiveness of preventive interventions and for tracking progress in patient safety through time.
[A]: Accuracy of using automated methods for detecting adverse events from electronic health record data: a research protocol


[Q]: Objective: Tumor-treating fields are currently used to successfully treat various cancers; however, the specific pathways associated with its efficacy remain unknown in the immune responses. Here, we evaluated tumor-treating fields-mediated initiation of the macrophage-specific immune response. Materials and Methods: We subjected RAW 264.7 mouse macrophages to clinically relevant levels of tumor-treating fields (0.9 V/cm, 150 kHz) and evaluated alterations in cytokine expression and release, as well as cell viability. Additionally, we investigated the status of immunomodulatory pathways to determine their roles in tumor-treating fields-mediated immune activation. Results and Discussion: Our results indicated that tumor-treating fields treatment at 0.9 V/cm decreased cell viability and increased cytokine messenger RNA/protein levels, as well as levels of nitric oxide and reactive oxygen species, relative to controls. The levels of tumor necrosis factor a, interleukin 1b, and interleukin 6 were markedly increased in tumor-treating fields-treated RAW 264.7 cells cocultured with 4T1 murine mammary carcinoma cells compared with those in 4T1 or RAW 264.7 cells with or without tumor-treating fields treatment. Moreover, the viability of 4T1 cells treated with the conditioned medium of tumor-treating fields-stimulated RAW 264.7 cells decreased, indicating that macrophage activation by tumor-treating fields effectively killed the tumor cells. Moreover, tumor-treating fields treatment activated the nuclear factor kB and mitogen-activated protein kinase pathways involved in immunomodulatory signaling. Conclusion: These results provide critical insights into the mechanisms through which tumor-treating fields affect macrophagespecific immune responses and the efficacy of this method for cancer treatment.
[A]:
Tumor-Treating Fields Induce RAW264.7 Macrophage Activation Via NK-kB/MAPK Signaling Pathways