Preclinical Models for Neuroblastoma: Establishing a Baseline for Treatment

Preclinical models of pediatric cancers are essential for testing new chemotherapeutic combinations for clinical trials. The most widely used genetic model for preclinical testing of neuroblastoma is the TH-MYCN mouse. This neuroblastoma-prone mouse recapitulates many of the features of human neuroblastoma. Limitations of this model include the low frequency of bone marrow metastasis, the lack of information on whether the gene expression patterns in this system parallels human neuroblastomas, the relatively slow rate of tumor formation and variability in tumor penetrance on different genetic backgrounds. As an alternative, preclinical studies are frequently performed using human cell lines xenografted into immunocompromised mice, either as flank implant or orthtotopically. Drawbacks of this system include the use of cell lines that have been in culture for years, the inappropriate microenvironment of the flank or difficult, time consuming surgery for orthotopic transplants and the absence of an intact immune system.Here we characterize and optimize both systems to increase their utility for preclinical studies. We show that TH-MYCN mice develop tumors in the paraspinal ganglia, but not in the adrenal, with cellular and gene expression patterns similar to human NB. In addition, we present a new ultrasound guided, minimally invasive orthotopic xenograft method. This injection technique is rapid, provides accurate targeting of the injected cells and leads to efficient engraftment. We also demonstrate that tumors can be detected, monitored and quantified prior to visualization using ultrasound, MRI and bioluminescence. Finally we develop and test a "standard of care" chemotherapy regimen. This protocol, which is based on current treatments for neuroblastoma, provides a baseline for comparison of new therapeutic agents.The studies suggest that use of both the TH-NMYC model of neuroblastoma and the orthotopic xenograft model provide the optimal combination for testing new chemotherapies for this devastating childhood cancer

Characterising within-hospital SARS-CoV-2 transmission events using epidemiological and viral genomic data across two pandemic waves

Hospital outbreaks of COVID19 result in considerable mortality and disruption to healthcare services and yet little is known about transmission within this setting. We characterise within hospital transmission by combining viral genomic and epidemiological data using Bayesian modelling amongst 2181 patients and healthcare workers from a large UK NHS Trust. Transmission events were compared between Wave 1 (1st March to 25th July 2020) and Wave 2 (30th November 2020 to 24th January 2021). We show that staff-to-staff transmissions reduced from 31.6% to 12.9% of all infections. Patient-to-patient transmissions increased from 27.1% to 52.1%. 40%-50% of hospital-onset patient cases resulted in onward transmission compared to 4% of community-acquired cases. Control measures introduced during the pandemic likely reduced transmissions between healthcare workers but were insufficient to prevent increasing numbers of patient-to-patient transmissions. As hospital-acquired cases drive most onward transmission, earlier identification of nosocomial cases will be required to break hospital transmission chains

Establishment and cryptic transmission of Zika virus in Brazil and the Americas

Transmission of Zika virus (ZIKV) in the Americas was first confirmed in May 2015 in northeast Brazil1. Brazil has had the highest number of reported ZIKV cases worldwide (more than 200,000 by 24 December 20162) and the most cases associated with microcephaly and other birth defects (2,366 confirmed by 31 December 20162). Since the initial detection of ZIKV in Brazil, more than 45 countries in the Americas have reported local ZIKV transmission, with 24 of these reporting severe ZIKV-associated disease3. However, the origin and epidemic history of ZIKV in Brazil and the Americas remain poorly understood, despite the value of this information for interpreting observed trends in reported microcephaly. Here we address this issue by generating 54 complete or partial ZIKV genomes, mostly from Brazil, and reporting data generated by a mobile genomics laboratory that travelled across northeast Brazil in 2016. One sequence represents the earliest confirmed ZIKV infection in Brazil. Analyses of viral genomes with ecological and epidemiological data yield an estimate that ZIKV was present in northeast Brazil by February 2014 and is likely to have disseminated from there, nationally and internationally, before the first detection of ZIKV in the Americas. Estimated dates for the international spread of ZIKV from Brazil indicate the duration of pre-detection cryptic transmission in recipient regions. The role of northeast Brazil in the establishment of ZIKV in the Americas is further supported by geographic analysis of ZIKV transmission potential and by estimates of the basic reproduction number of the virus

Modelling the transmission of healthcare associated infections: a systematic review.

BACKGROUND: Dynamic transmission models are increasingly being used to improve our understanding of the epidemiology of healthcare-associated infections (HCAI). However, there has been no recent comprehensive review of this emerging field. This paper summarises how mathematical models have informed the field of HCAI and how methods have developed over time. METHODS: MEDLINE, EMBASE, Scopus, CINAHL plus and Global Health databases were systematically searched for dynamic mathematical models of HCAI transmission and/or the dynamics of antimicrobial resistance in healthcare settings. RESULTS: In total, 96 papers met the eligibility criteria. The main research themes considered were evaluation of infection control effectiveness (64%), variability in transmission routes (7%), the impact of movement patterns between healthcare institutes (5%), the development of antimicrobial resistance (3%), and strain competitiveness or co-colonisation with different strains (3%). Methicillin-resistant Staphylococcus aureus was the most commonly modelled HCAI (34%), followed by vancomycin resistant enterococci (16%). Other common HCAIs, e.g. Clostridum difficile, were rarely investigated (3%). Very few models have been published on HCAI from low or middle-income countries.The first HCAI model has looked at antimicrobial resistance in hospital settings using compartmental deterministic approaches. Stochastic models (which include the role of chance in the transmission process) are becoming increasingly common. Model calibration (inference of unknown parameters by fitting models to data) and sensitivity analysis are comparatively uncommon, occurring in 35% and 36% of studies respectively, but their application is increasing. Only 5% of models compared their predictions to external data. CONCLUSIONS: Transmission models have been used to understand complex systems and to predict the impact of control policies. Methods have generally improved, with an increased use of stochastic models, and more advanced methods for formal model fitting and sensitivity analyses. Insights gained from these models could be broadened to a wider range of pathogens and settings. Improvements in the availability of data and statistical methods could enhance the predictive ability of models

Field Evaluation of a Prototype Paper-Based Point-of-Care Fingerstick Transaminase Test

Monitoring for drug-induced liver injury (DILI) via serial transaminase measurements in patients on potentially hepatotoxic medications (e.g., for HIV and tuberculosis) is routine in resource-rich nations, but often unavailable in resource-limited settings. Towards enabling universal access to affordable point-of-care (POC) screening for DILI, we have performed the first field evaluation of a paper-based, microfluidic fingerstick test for rapid, semi-quantitative, visual measurement of blood alanine aminotransferase (ALT). Our objectives were to assess operational feasibility, inter-operator variability, lot variability, device failure rate, and accuracy, to inform device modification for further field testing. The paper-based ALT test was performed at POC on fingerstick samples from 600 outpatients receiving HIV treatment in Vietnam. Results, read independently by two clinic nurses, were compared with gold-standard automated (Roche Cobas) results from venipuncture samples obtained in parallel. Two device lots were used sequentially. We demonstrated high inter-operator agreement, with 96.3% (95% C.I., 94.3–97.7%) agreement in placing visual results into clinically-defined “bins” (5x upper limit of normal), >90% agreement in validity determination, and intraclass correlation coefficient of 0.89 (95% C.I., 0.87–0.91). Lot variability was observed in % invalids due to hemolysis (21.1% for Lot 1, 1.6% for Lot 2) and correlated with lots of incorporated plasma separation membranes. Invalid rates <1% were observed for all other device controls. Overall bin placement accuracy for the two readers was 84% (84.3%/83.6%). Our findings of extremely high inter-operator agreement for visual reading–obtained in a target clinical environment, as performed by local practitioners–indicate that the device operation and reading process is feasible and reproducible. Bin placement accuracy and lot-to-lot variability data identified specific targets for device optimization and material quality control. This is the first field study performed with a patterned paper-based microfluidic device and opens the door to development of similar assays for other important analytes.National Institutes of Health (U.S.) (PATH Center to Advance Point of Care Diagnostics for Global Health NIBIB U54-EB007949)National Institute of Neurological Disorders and Stroke (U.S.) (Grant 5F30NS06468

Eu habitats of interest: An insight into atlantic and mediterranean beach and foredunes

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