Establishing a Lung Model for Evaluation of Engineered Lung Microbiome Therapies

Benzene, a toxin and carcinogen found in air polluted by cigarette smoke, car exhaust, and industrial processes, is associated with the development of leukemia and lymphoma. Other than avoiding exposure, there is no current method to deter the effects of benzene. One potential strategy to prevent these effects is to engineer the bacteria of the human lung microbiome to degrade benzene. To evaluate this novel approach, we must verify that the bacteria remain viable within the lung microenvironment. To do so, lungs were harvested from rats and swabbed to determine the contents of the original lung microbiome. Then green fluorescent protein (GFP)-transformed E. coli were introduced to the lungs and the lungs were ventilated for five minutes before being swabbed again. The lungs were sliced with a vibratome and cultured for three days. They were analyzed under a microscope and swabbed daily to determine how the bacteria disperse upon delivery and detect changes within the lung microbiome. If results show that introduction of a new bacterial species does not significantly change the lung microbiome over time, the project can move forward to test the engineered bacteria’s viability in the lung environment and effectiveness in rescuing lung cells from benzene’s toxicity

An iterative design of experiments based data collection approach for ultrasonic guided waves

To validate modelling results it is necessary to collect experimental data, in this case ultrasonic guided wave measurements to validate a forward model of an acoustic emission system on a complex structure. Traditionally when ultrasonic data is collected over an area of a structure it is collected in a raster scan. This approach comprehensively covers the area of interest at a desired resolution which is determined by the feature of the signals that needs to be measured. In most cases however the feature of interest, such as a defect or, in this work, a geometrical feature, is only present in a small portion of the measurement region. In the remainder of the region the ultrasonic behavior tends to be more consistent and well understood and therefore this remaining area is effectively oversampled. If the data collection process is fast, then this is not a problem. However, in the case of performing manual guided wave measurements across a large structure, repositioning the transducer is the most time consuming part of the experiment. If the number of measurements taken in the regions where the ultrasonic behavior is simple can be reduced, this will save both time and effort. The approach demonstrated here is based upon the HilomotDoE (HIeracchical LOcal MOdel Tree for Design of Experiments) algorithm [1]. The algorithm and therefore the data collection is iterative. In each iteration data points are collected in the region where there is the most difference between the model of the experimental data and the actual experimental data. This means the model is refined in regions where there is the greatest change from a simple polynomial model. This corresponds with taking more experimental measurements in regions where the ultrasonic response is changing the most. This typically corresponds to regions of interest such as geometrical features. The algorithm will be tested on guided wave measurements collected on a real structure and its performance is compared with a raster scan

An experimental study on the manufacture and characterization of in-plane fibre-waviness defects in composites

A new method has been developed for creating localized in-plane fibre waviness in composite coupons and used to create a large batch of specimens. This method could be used by manufacturers to experimentally explore the effect of fibre waviness on composite structures both directly and indirectly to develop and validate computational models. The specimens were assessed using ultrasound, digital image correlation and a novel inspection technique capable of measuring residual strain fields. To explore how the defect affects the performance of composite structures, the specimens were then loaded to failure. Predictions of remnant strength were made using a simple ultrasound damage metric and a new residual strain-based damage metric. The predictions made using residual strain measurements were found to be substantially more effective at characterizing ultimate strength than ultrasound measurements. This suggests that residual strains have a significant effect on the failure of laminates containing fibre waviness and that these strains could be incorporated into computational models to improve their ability to simulate the defect

Improving health outcome for young people with long term conditions: The role of digital communication in current and future patient-clinician communication for NHS providers of specialist clinical services for young people receiving specialist clinical services:LYNC study protocol.

Background: Young people living with long term conditions are vulnerable to health service disengagement. This endangers their long term health. Studies report requests for digital forms of communication - email, text, social media - with their health care team. Digital clinical communication is troublesome for the UK NHS. Aim: To present the research protocol for evaluating the impacts and outcomes of digital clinical communications for young people living with long term conditions and provide critical analysis of their use, monitoring and evaluation by NHS providers. Methods: The research involves: 1) Patient and Public Involvement activities with 16-24 year olds with and without long term health conditions; 2) six literature reviews; 3) case studies – the main empirical part of the study – and 4) synthesis and a consensus meeting. Case studies use a mixed methods design. Interviews and non-participant observation of practitioners and patients communicating in up to 20 specialist clinical settings will be combined with data, aggregated at the case level (non-identifiable patient data), on a range of clinical outcomes meaningful within the case and across cases. We will describe the use of digital clinical communication from the perspective of patients, clinical staff, support staff and managers, interviewing up to 15 young people and 15 staff per case study. Outcome data includes emergency admissions, A&E attendance and DNA rates. Case studies will be analysed to understand impacts of digital clinical communication on patient health outcomes, health care costs and consumption, ethics and patient safety

Slow wave sleep and accelerated forgetting

We investigated whether the benefit of slow wave sleep (SWS) for memory consolidation typically observed in healthy individuals is disrupted in people with accelerated long-term forgetting (ALF) due to epilepsy. SWS is thought to play an active role in declarative memory in healthy individuals and, furthermore, electrographic epileptiform activity is often more prevalent during SWS than during wakefulness or other sleep stages. We studied the relationship between SWS and the benefit of sleep for memory retention using a word-pair associates task. In both the ALF and the healthy control groups, sleep conferred a memory benefit. However, the relationship between the amount of SWS and sleep-related memory benefits differed significantly between the groups. In healthy participants, the amount of SWS correlated positively with sleep-related memory benefits. In stark contrast, the more SWS, the smaller the sleep-related memory benefit in the ALF group. Therefore, contrary to its role in healthy people, SWS-associated brain activity appears to be deleterious for memory in patients with ALF

An Iterative Design of Experiments Based Data Collection Approach for Ultrasonic Guided Waves

To validate modelling results it is necessary to collect experimental data, in this case ultrasonic guided wave measurements to validate a forward model of an acoustic emission system on a complex structure. Traditionally when ultrasonic data is collected over an area of a structure it is collected in a raster scan. This approach comprehensively covers the area of interest at a desired resolution which is determined by the feature of the signals that needs to be measured. In most cases however the feature of interest, such as a defect or, in this work, a geometrical feature, is only present in a small portion of the measurement region. In the remainder of the region the ultrasonic behavior tends to be more consistent and well understood and therefore this remaining area is effectively oversampled. If the data collection process is fast, then this is not a problem. However, in the case of performing manual guided wave measurements across a large structure, repositioning the transducer is the most time consuming part of the experiment. If the number of measurements taken in the regions where the ultrasonic behavior is simple can be reduced, this will save both time and effort. The approach demonstrated here is based upon the HilomotDoE (HIeracchical LOcal MOdel Tree for Design of Experiments) algorithm [1]. The algorithm and therefore the data collection is iterative. In each iteration data points are collected in the region where there is the most difference between the model of the experimental data and the actual experimental data. This means the model is refined in regions where there is the greatest change from a simple polynomial model. This corresponds with taking more experimental measurements in regions where the ultrasonic response is changing the most. This typically corresponds to regions of interest such as geometrical features. The algorithm will be tested on guided wave measurements collected on a real structure and its performance is compared with a raster scan.</p

DIC Data (10% Nominal Waviness)

DIC Data for the 10% nominal waviness specimens. Data is exported from Istra-4D in a standardized file type