Targeted computational analysis of the C3HEB/FEJ mouse model for drug efficacy testing

2020 Spring.Includes bibliographical references.Efforts to develop effective and safe drugs for the treatment of tuberculosis (TB) require preclinical evaluation in animal models. Alongside efficacy testing of novel therapies, effects on pulmonary pathology and disease progression are monitored by using histopathology images from these infected animals. To compare the severity of disease across treatment cohorts, pathologists have historically assigned a semi-quantitative histopathology score that may be subjective in terms of their training, experience, and personal bias. Manual histopathology, therefore, has limitations regarding reproducibility between studies and pathologists, potentially masking successful treatments. This report describes a pathologist-assistive software tool that reduces these user limitations while providing a rapid, quantitative scoring system for digital histopathology image analysis. The software, called 'Lesion Image Recognition and Analysis' (LIRA), employs convolutional neural networks to classify seven different pathology features, including three different lesion types from pulmonary tissues of the C3HeB/FeJ tuberculosis mouse model. LIRA was developed to improve the efficiency of histopathology analysis for mouse tuberculosis infection models. The model approach also has broader applications to other diseases and tissues. This also includes animals that are undergoing anti-mycobacterial treatment and host immune system modulation. A complimentary software package called 'Mycobacterial Image Analysis' (MIA) had also been developed that characterizes the varying bacilli characteristics such as density, aggregate/planktonic bacilli size, fluorescent intensity, and total counts. This further groups the bacilli characteristic data depending on the seven different classifications that are selected by the user. Using this approach allows for an even more targeted analysis approach that can determine how therapy and microenvironments influence the Mtb response

THE EXPLORATION OF THE VALIDITY OF QUANTITATIVE 2-DEOXY-2-[FLUORINE-18] FLUORO-D-GLUCOSE (18F-FDG) POSITRON EMISSION TOMOGRAPHY/COMPUTED TOMOGRAPHY (PET/CT) TO ASSESS LUNG INFLAMMATION

Lung diseases are one of the leading causes of death in the UK; responsible for 20% of all deaths each year. Inflammation is thought to be an important driver of the pathogenesis and progression of several lung diseases. Positron emission tomography/computed tomography (PET/CT) is an imaging modality capable of providing functional and molecular imaging through detection of trace quantities of a radioactive tracer. 18F-FDG is the most widely available tracer and in several small studies has been used to investigate diffuse lung diseases such as chronic obstructive pulmonary disease (COPD). These studies rely on quantification of the PET image. Static acquisitions provide information on the biodistribution of the tracer at a single time point after administration, the standardised uptake value (SUV) is the most widely used measure of 18F-FDG uptake. Dynamic acquisitions provide information on the spatial and temporal distribution of the tracer; linear and non-linear modelling techniques allow estimation of the metabolic rate of 18F-FDG in the lung. Previous studies have used a linear method called Patlak graphical analysis, whilst non-linear compartmental models have been used more recently to estimate metabolism. However, these contending measures of pulmonary 18F-FDG uptake, which are putative biomarkers of lung inflammation, have so far been disparately applied. Further, there is nascent understanding that these imaging endpoints are affected by pulmonary air and blood volume; the importance of this effect will likely depend on the disease and its severity. These issues are exacerbated by the presence of respiratory motion and the low signal- to-noise ratio achieved in PET studies. This has led to questions regarding the utility of quantitative 18F-FDG PET to assess lung inflammation. In this work, prospective and retrospective clinical studies were used to assess the clinical, biological and technical validity of 18F-FDG PET imaging endpoints in several clinically relevant diseases. The central hypothesis was that pulmonary inflammation can be assessed using quantitative 18F-FDG. Using retrospective data from two complementary imaging studies, pulmonary 18F- FDG uptake was investigated in COPD patients, α1ATD patients, smokers without COPD and heathy non-smokers. The results demonstrate that the different 18F-FDG imaging endpoints produce disparate findings, and this is exacerbated by the presence of varying blood and air volumes due to emphysema. Nevertheless, measures derived from Patlak analysis revealed elevated uptake consistent with the pathophysiologi- cal understanding of the disease process and further demonstrated correlation with other putative markers of inflammation hence, one could speculate that it relates to inflammation. Further, 18F-FDG imaging outcomes assessed using Patlak analysis were shown to be more reliable than compartmental modelling outcomes. However, the Patlak outcomes are composite measures, not only driven by inflammation but also by pulmonary blood and air. In circumstances where differences in pulmonary blood and air volume between subjects are substantial, it may not be a suitable biomarker of inflammation, but it could be a useful marker of disease activity. Further tissue validation and independent measures of pulmonary blood are required to support its role as a marker of inflammation. In a prospective study, dynamic 18F-FDG PET scans were used to evaluate pulmonary inflammation in sarcoidosis patients and healthy controls. The results show that 18F-FDG uptake was increased in sarcoidosis using Patlak analysis, whilst no difference was found using SUV or compartmental models. Preliminary findings suggest that the signal relates to inflammatory cell counts (macrophages and lymphocytes were most numerous) rather than any one specific cell line; however, further evidence is required to determine if 18F-FDG uptake is driven by underlying inflammation. Consistent with previous findings, mismatch in CT and PET lung images has substantial effect on the quantitative 18F-FDG outcomes; notably, Patlak outcomes were less influenced than compartmental modelling. In summary, the observations made in this work demonstrate the substantial challenges of using 18F-FDG PET/CT to assess diffuse lung disease. Given the incongruity between the different imaging outcomes, these data highlight that future studies should be carefully planned with particular justification of the acquisition and analysis methods. The results of this work suggest that Patlak measures may have the most utility in diffuse lung disease. However, differences in Patlak measures should be interpreted judiciously, as they may be driven by differences in pulmonary blood and air along with inflammation; further study is required to determine if it may be a useful marker of disease activity. In contrast, no differences in pulmonary 18F-FDG uptake between patients and controls were found using compartmental modelling across all studies. Equally, the SUV was found to have poor utility across studies. Future efforts to expedite the use of novel tracers that are more specific to inflammation combined with the development of improved noise reduction techniques may improve the utility of quantitative PET/CT in the context of lung inflammation

An investigation into the effects of commencing haemodialysis in the critically ill

<b>Introduction:</b> We have aimed to describe haemodynamic changes when haemodialysis is instituted in the critically ill. 3 hypotheses are tested: 1)The initial session is associated with cardiovascular instability, 2)The initial session is associated with more cardiovascular instability compared to subsequent sessions, and 3)Looking at unstable sessions alone, there will be a greater proportion of potentially harmful changes in the initial sessions compared to subsequent ones. <b>Methods:</b> Data was collected for 209 patients, identifying 1605 dialysis sessions. Analysis was performed on hourly records, classifying sessions as stable/unstable by a cutoff of >+/-20% change in baseline physiology (HR/MAP). Data from 3 hours prior, and 4 hours after dialysis was included, and average and minimum values derived. 3 time comparisons were made (pre-HD:during, during HD:post, pre-HD:post). Initial sessions were analysed separately from subsequent sessions to derive 2 groups. If a session was identified as being unstable, then the nature of instability was examined by recording whether changes crossed defined physiological ranges. The changes seen in unstable sessions could be described as to their effects: being harmful/potentially harmful, or beneficial/potentially beneficial. <b>Results:</b> Discarding incomplete data, 181 initial and 1382 subsequent sessions were analysed. A session was deemed to be stable if there was no significant change (>+/-20%) in the time-averaged or minimum MAP/HR across time comparisons. By this definition 85/181 initial sessions were unstable (47%, 95% CI SEM 39.8-54.2). Therefore Hypothesis 1 is accepted. This compares to 44% of subsequent sessions (95% CI 41.1-46.3). Comparing these proportions and their respective CI gives a 95% CI for the standard error of the difference of -4% to 10%. Therefore Hypothesis 2 is rejected. In initial sessions there were 92/1020 harmful changes. This gives a proportion of 9.0% (95% CI SEM 7.4-10.9). In the subsequent sessions there were 712/7248 harmful changes. This gives a proportion of 9.8% (95% CI SEM 9.1-10.5). Comparing the two unpaired proportions gives a difference of -0.08% with a 95% CI of the SE of the difference of -2.5 to +1.2. Hypothesis 3 is rejected. Fisher’s exact test gives a result of p=0.68, reinforcing the lack of significant variance. <b>Conclusions:</b> Our results reject the claims that using haemodialysis is an inherently unstable choice of therapy. Although proportionally more of the initial sessions are classed as unstable, the majority of MAP and HR changes are beneficial in nature

Proteomic Fingerprint of Lung Fibrosis Progression and Response to Therapy in Bleomycin-Induced Mouse Model

Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease characterized by the aberrant accumulation of extracellular matrix in the lungs. nintedanib is one of the two FDA-approved drugs for IPF treatment; however, the exact pathophysiological mechanisms of fibrosis progression and response to therapy are still poorly understood. In this work, the molecular fingerprint of fibrosis progression and response to nintedanib treatment have been investigated by mass spectrometry-based bottom-up proteomics in paraffin-embedded lung tissues from bleomycin-induced (BLM) pulmonary fibrosis mice. Our proteomics results unveiled that (i) samples clustered depending on the tissue fibrotic grade (mild, moderate, and severe) and not on the time course after BLM treatment; (ii) the dysregulation of different pathways involved in fibrosis progression such as the complement coagulation cascades, advanced glycation end products (AGEs) and their receptors (RAGEs) signaling, the extracellular matrix-receptor interaction, the regulation of actin cytoskeleton, and ribosomes; (iii) Coronin 1A (Coro1a) as the protein with the highest correlation when evaluating the progression of fibrosis, with an increased expression from mild to severe fibrosis; and (iv) a total of 10 differentially expressed proteins (padj-value ≤ 0.05 and Fold change ≤-1.5 or ≥1.5), whose abundance varied in the base of the severity of fibrosis (mild and moderate), were modulated by the antifibrotic treatment with nintedanib, reverting their trend. Notably, nintedanib significantly restored lactate dehydrogenase B (Ldhb) expression but not lactate dehydrogenase A (Ldha). Notwithstanding the need for further investigations to validate the roles of both Coro1a and Ldhb, our findings provide an extensive proteomic characterization with a strong relationship with histomorphometric measurements. These results unveil some biological processes in pulmonary fibrosis and drug-mediated fibrosis therapy