A Lateral-Flow Device for the Rapid Detection of Scedosporium Species.

Scedosporium species are human pathogenic fungi, responsible for chronic, localised, and life-threatening disseminated infections in both immunocompetent and immunocompromised individuals. The diagnosis of Scedosporium infections currently relies on non-specific CT, lengthy and insensitive culture from invasive biopsy, and the time-consuming histopathology of tissue samples. At present, there are no rapid antigen tests that detect Scedosporium-specific biomarkers. Here, we report the development of a rapid (30 min) and sensitive (pmol/L sensitivity) lateral-flow device (LFD) test, incorporating a Scedosporium-specific IgG1 monoclonal antibody (mAb), HG12, which binds to extracellular polysaccharide (EPS) antigens between ~15 kDa and 250 kDa secreted during the hyphal growth of the pathogens. The test is compatible with human serum and allows for the detection of the Scedosporium species most frequently reported as agents of human disease (Scedosporium apiospermum, Scedosporium aurantiacum, and Scedosporium boydii), with limits of detection (LODs) of the EPS biomarkers in human serum of ~0.81 ng/mL (S. apiospermum), ~0.94 ng/mL (S. aurantiacum), and ~1.95 ng/mL (S. boydii). The Scedosporium-specific LFD (ScedLFD) test therefore provides a potential novel opportunity for the detection of infections caused by different Scedosporium species.

The potential for rapid antigen testing for mucormycosis in the context of COVID-19.

INTRODUCTION: Mucormycosis is a highly aggressive angio-invasive disease of humans caused by Mucorales fungi. Prior to the COVID-19 pandemic, mucormycosis was a rare mycosis typically seen in immunocompromised patients with hematological malignancies or in transplant recipients. During the second wave of the pandemic, there was a dramatic increase in the disease, especially in India where a unique set of circumstances led to large numbers of life-threatening and disfiguring rhino-orbital-cerebral mucormycosis (ROCM) infections. AREAS COVERED: The review examines mucormycosis as a super-infection of COVID-19 patients, and the risk factors for COVID-19-associated mucormycosis (CAM) that drove the ROCM epidemic in India. The limitations of current diagnostic procedures are identified, and the measures needed to improve the speed and accuracy of detection discussed. EXPERT OPINION: Despite increased awareness, global healthcare systems remain unprepared for further outbreaks of ROCM. Current diagnosis of the disease is slow and inaccurate, negatively impacting on patient survival. This is most evident in low- to middle-income countries which lack suitably equipped diagnostic facilities for rapid identification of the infecting pathogens. Rapid antigen testing using point-of-care lateral-flow assays could potentially have aided in the quick and accurate diagnosis of the disease, allowing earlier intervention with surgery and Mucorales-active antifungal drugs.

Development of a monoclonal antibody and a lateral-flow device for the rapid detection of a Mucorales-specific biomarker.

Mucoromycosis is a highly aggressive angio-invasive disease of humans caused by fungi in the zygomycete order, Mucorales. While Rhizopus arrhizus is the principal agent of mucoromycosis, other Mucorales fungi including Apophysomyces, Cunninghamella, Lichtheimia, Mucor, Rhizomucor and Syncephalastrum are able to cause life-threatening rhino-orbital-cerebral, pulmonary, gastro-intestinal and necrotising cutaneous infections in humans. Diagnosis of the disease currently relies on non-specific CT, lengthy and insensitive culture from invasive biopsy, and time-consuming histopathology of tissue samples. At present, there are no rapid antigen tests that detect Mucorales-specific biomarkers of infection, and which allow point-of-care diagnosis of mucoromycosis. Here, we report the development of an IgG2b monoclonal antibody (mAb), TG11, which binds to extracellular polysaccharide (EPS) antigens of between 20 kDa and 250 kDa secreted during hyphal growth of Mucorales fungi. The mAb is Mucorales-specific and does not cross-react with other yeasts and molds of clinical importance including Aspergillus, Candida, Cryptococcus, Fusarium, Lomentospora and Scedosporium species. Using the mAb, we have developed a Competitive lateral-flow device that allows rapid (30 min) detection of the EPS biomarker in human serum and bronchoalveolar lavage (BAL), with a limit of detection (LOD) in human serum of ~100 ng/mL serum (~224.7 pmol/L serum). The LFD therefore provides a potential novel opportunity for detection of mucoromycosis caused by different Mucorales species.

Scoping the Priorities and Concerns of Parents: Infodemiology Study of Posts on Mumsnet and Reddit.

BACKGROUND: Health technology innovation is increasingly supported by a bottom-up approach to priority setting, aiming to better reflect the concerns of its intended beneficiaries. Web-based forums provide parents with an outlet to share concerns, advice, and information related to parenting and the health and well-being of their children. They provide a rich source of data on parenting concerns and priorities that could inform future child health research and innovation. OBJECTIVE: The aim of the study is to identify common concerns expressed on 2 major web-based forums and cluster these to identify potential family health concern topics as indicative priority areas for future research and innovation. METHODS: We text-mined the r/Parenting subreddit (69,846 posts) and the parenting section of Mumsnet (99,848 posts) to create a large corpus of posts. A generative statistical model (latent Dirichlet allocation) was used to identify the most discussed topics in the corpus, and content analysis was applied to identify the parenting concerns found in a subset of posts. RESULTS: A model with 25 topics produced the highest coherence and a wide range of meaningful parenting concern topics. The most frequently expressed parenting concerns are related to their child's sleep, self-care, eating (and food), behavior, childcare context, and the parental context including parental conflict. Topics directly associated with infants, such as potty training and bottle feeding, were more common on Mumsnet, while parental context and screen time were more common on r/Parenting. CONCLUSIONS: Latent Dirichlet allocation topic modeling can be applied to gain a rapid, yet meaningful overview of parent concerns expressed on a large and diverse set of social media posts and used to complement traditional insight gathering methods. Parents framed their concerns in terms of children's everyday health concerns, generating topics that overlap significantly with established family health concern topics. We provide evidence of the range of family health concerns found at these sources and hope this can be used to generate material for use alongside traditional insight gathering methods.

Physical activity in young children across developmental and health states: the ActiveCHILD study.

Background: Evidence about physical activity of young children across developmental and health states is very limited. Using data from an inclusive UK cohort, ActiveCHILD, we investigated relationships between objectively measured physical activity, child development, social context, and health-related quality of life (HRQoL). Methods: Children (12-36 months), purposively sampled across health pathways, developmental abilities, and sociodemographic factors, were recruited through thirteen National Health Service organisations in England. Data were collected from 07/2017 to 08/2019 on: weekly physical activity (3-7 days) using waist-worn accelerometer (ActiGraph 3GTX); sociodemographics, parent actions, child HRQoL, and child development using questionnaires; and child health conditions using clinical records. A data-driven, unsupervised method, called hidden semi-Markov model (HSMM) segmented the accelerometery data and provided estimates of the total time spent active (any intensity) and very active (greater intensity) for each child. Relationships with the explanatory factors were investigated using multiple linear regression. Findings: Physical activity data were obtained for 282 children (56% females, mean age 21 months, 37.5% with a health condition) covering all index of multiple deprivation deciles. The patterns of physical activity consisted of two daily peaks, children spending 6.44 (SD = 1.39) hours active (any intensity), of which 2.78 (SD = 1.38) hours very active, 91% meeting WHO guidelines. The model for total time active (any intensity) explained 24% of variance, with mobility capacity the strongest predictor (ß = 0.41). The model for time spent very active explained 59% of variance, with mobility capacity again the strongest predictor (ß = 0.76). There was no evidence of physical activity explaining HRQoL. Interpretation: The findings provide new evidence that young children across developmental states regularly achieve mainstream recommended physical activity levels and challenges the belief that children with development problems need lower expectations for daily physical activity compared to peers. Advancing the rights of all children to participate in physical activity requires inclusive, equally ambitious, expectations for all. Funding: Niina Kolehmainen, HEE/NIHR Integrated Clinical Academic Senior Clinical Lecturer, NIHR ICA-SCL-2015-01-00, was funded by the NIHR for this research project. Christopher Thornton, Olivia Craw, Laura Kudlek, and Laura Cutler were also funded from this award. Tim Rapley is a member of the NIHR Applied Research Collaboration North East and North Cumbria, with part of his time funded through the related award (NIHR200173). The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR, NHS, or the UK Department of Health and Social Care. The work of Kianoush Nazarpour is supported by Engineering and Physical Sciences Research Council (EPSRC), under grant number EP/R004242/2.

Using unsupervised machine learning to quantify physical activity from accelerometry in a diverse and rapidly changing population.

Accelerometers are widely used to measure physical activity behaviour, including in children. The traditional method for processing acceleration data uses cut points to define physical activity intensity, relying on calibration studies that relate the magnitude of acceleration to energy expenditure. However, these relationships do not generalise across diverse populations and hence they must be parametrised for each subpopulation (e.g., age groups) which is costly and makes studies across diverse populations and over time difficult. A data-driven approach that allows physical activity intensity states to emerge from the data, without relying on parameters derived from external populations, offers a new perspective on this problem and potentially improved results. We applied an unsupervised machine learning approach, namely a hidden semi-Markov model, to segment and cluster the raw accelerometer data recorded (using a waist-worn ActiGraph GT3X+) from 279 children (9-38 months old) with a diverse range of developmental abilities (measured using the Paediatric Evaluation of Disability Inventory-Computer Adaptive Testing measure). We benchmarked this analysis with the cut points approach, calculated using thresholds from the literature which had been validated using the same device and for a population which most closely matched ours. Time spent active as measured by this unsupervised approach correlated more strongly with PEDI-CAT measures of the child's mobility (R2: 0.51 vs 0.39), social-cognitive capacity (R2: 0.32 vs 0.20), responsibility (R2: 0.21 vs 0.13), daily activity (R2: 0.35 vs 0.24), and age (R2: 0.15 vs 0.1) than that measured using the cut points approach. Unsupervised machine learning offers the potential to provide a more sensitive, appropriate, and cost-effective approach to quantifying physical activity behaviour in diverse populations, compared to the current cut points approach. This, in turn, supports research that is more inclusive of diverse or rapidly changing populations.

Development of a Web-Based System to Report Medication-Related Adverse Effects: Design and Usability Study.

BACKGROUND: Medicine use is the most common intervention in health care. The frequency with which medicines are used means medication-related problems are very common. One common type of medication-related problems is adverse drug events, which are unintended and harmful effects associated with use of medicines. Reporting of adverse drug events to regulatory authorities is important for evaluation of safety of medicines; however, these adverse effects are frequently unreported due to various factors, including lack of consumer-friendly reporting tools. OBJECTIVE: The aim of this study was to develop a user-friendly digital tool for consumers to report medication-related adverse effects. METHODS: The project consisted of 3 parts: (1) content development, including a systematic literature search; (2) iterative system development; and (3) usability testing. The project was guided by participatory design principles, which suggest involving key stakeholders throughout the design process. The first 2 versions were developed as a mobile app and were tested with end users in 2 workshops. The third version was developed as a web application and was tested with consumers who were taking regular medicines. Consumers were asked to complete a modified version of the mHealth app usability questionnaire (MAUQ), an 18-item questionnaire with each item scored using a 7-point Likert scale ranging from 0 (strongly disagree) to 7 (strongly agree). The MAUQ assessed 3 subscales including ease of use (5 items), interface and satisfaction (7 items), and usefulness (6 items). Continuous variables were reported as mean (SD) values, whereas categorical variables were presented as frequencies (percentages). Data analysis was conducted in Microsoft Excel. RESULTS: The content for the system was based on a systematic literature search and short-listing of questions, followed by feedback from project team members and consumers. Feedback from consumers in the 2 workshops were incorporated to improve the functionality, visual design, and stability of the third (current) version. The third version of the system was tested with 26 consumers. A total of 79% (N=307/390) of all responses on the MAUQ were scored 6 or 7, indicating that users generally strongly agree with the usability of the system. When looking at the individual domains, the system had an average score of 6.3 (SD 0.9) for "ease of use," 6.3 (SD 0.8) for "interface and satisfaction," and 5.2 (SD 1.4) for "usefulness." CONCLUSIONS: The web-based system for medicine adverse effects reporting is a user-friendly tool developed using an iterative participatory design approach. Future research includes further improving the system, particularly the usefulness of the system, as well as testing the scalability and performance of the system in practice.

Development of a Monoclonal Antibody and a Serodiagnostic Lateral-Flow Device Specific to Rhizopus arrhizus (Syn. R. oryzae), the Principal Global Agent of Mucormycosis in Humans.

Mucormycosis is a highly aggressive angio-invasive disease of humans caused by fungi in the zygomycete order, Mucorales. Though a number of different species can cause mucormycosis, the principal agent of the disease worldwide is Rhizopus arrhizus, which accounts for the majority of rhino-orbital-cerebral, pulmonary, and disseminated infections in immunocompromised individuals. It is also the main cause of life-threatening infections in patients with poorly controlled diabetes mellitus, and in corticosteroid-treated patients with SARS-CoV-2 infection, where it causes the newly described disease, COVID-19-associated mucormycosis (CAM). Diagnosis currently relies on non-specific CT, a lengthy and insensitive culture from invasive biopsy, and a time-consuming histopathology of tissue samples. At present, there are no rapid antigen tests for the disease that detect biomarkers of infection, and which allow point-of-care diagnosis. Here, we report the development of an IgG1 monoclonal antibody (mAb), KC9, which is specific to Rhizopus arrhizus var. arrhizus (syn. Rhizopus oryzae) and Rhizopus arrhizus var. delemar (Rhizopus delemar), and which binds to a 15 kDa extracellular polysaccharide (EPS) antigen secreted during hyphal growth of the pathogen. Using the mAb, we have developed a competitive lateral-flow device (LFD) that allows rapid (30 min) and sensitive (~50 ng/mL running buffer) detection of the EPS biomarker, and which is compatible with human serum (limit of detection of ~500 ng/mL) and bronchoalveolar lavage fluid (limit of detection of ~100 ng/mL). The LFD, therefore, provides a potential novel opportunity for the non-invasive detection of mucormycosis caused by Rhizopus arrhizus.

Continuing Shifts in Epidemiology and Antifungal Susceptibility Highlight the Need for Improved Disease Management of Invasive Candidiasis.

Invasive candidiasis (IC) is a systemic life-threatening infection of immunocompromised humans, but remains a relatively neglected disease among public health authorities. Ongoing assessments of disease epidemiology are needed to identify and map trends of importance that may necessitate improvements in disease management and patient care. Well-established incidence increases, largely due to expanding populations of patients with pre-disposing risk factors, has led to increased clinical use and pressures on antifungal drugs. This has been exacerbated by a lack of fast, accurate diagnostics that have led treatment guidelines to often recommend preventative strategies in the absence of proven infection, resulting in unnecessary antifungal use in many instances. The consequences of this are multifactorial, but a contribution to emerging drug resistance is of primary concern, with high levels of antifungal use heavily implicated in global shifts to more resistant Candida strains. Preserving and expanding the utility and number of antifungals should therefore be of the highest priority. This may be achievable through the development and use of biomarker tests, bringing about a new era in improved antifungal stewardship, as well as novel antifungals that offer favorable profiles by targeting Candida pathogenesis mechanisms over cell viability.

Emotion Dysregulation and Eating Disorder Symptoms: Examining Distinct Associations and Interactions in Adolescents.

Emotion dysregulation has been posited as a key transdiagnostic factor of mental health difficulties, including eating disorders. However, how this transdiagnostic factor interacts with the disorder-specific factor of weight and shape concerns remains unclear. The current study examined whether emotion dysregulation is associated with eating disorder behaviors over and above the association between weight and shape concerns and whether these two factors interacted. The current study used data from two samples, a community sample of high school students (n = 2699), and a clinical sample of adolescents receiving outpatient treatment for an eating disorder (n = 149). Participants completed self-report measures on their eating behaviors, weight/shape concerns, and emotion dysregulation. Findings showed that emotion dysregulation had a unique association with engaging in binge eating and purging (community sample only). Weight and shape concerns were found to have a unique association with engaging in binge eating, fasting, purging, and driven exercise (community sample only). Additionally, weight and shape concerns moderated the association between emotion dysregulation and the probability of engaging in binge eating and driven exercise, whereby the strongest association between emotion dysregulation and these behaviors were observed among adolescents with the lowest levels of weight and shape concerns. Regarding the frequency of eating disorder behaviors, emotion dysregulation had a unique association with severity of binge eating and fasting. Weight and shape concerns were uniquely associated with severity of fasting and driven exercise (community sample only). Findings suggest that emotion dysregulation is a distinct factor of eating disorder behaviors among adolescents.

Understanding treatment delay: Perceived barriers preventing treatment-seeking for eating disorders.

OBJECTIVE: Only a small proportion of individuals with an eating disorder will receive targeted treatment for their illness. The aim of this study was to examine the length of delay to treatment-seeking and determine the barriers preventing earlier access and utilisation of eating disorder treatment for each diagnostic group - anorexia nervosa, bulimia nervosa, binge eating disorder and other specified feeding or eating disorder. METHOD: Participants were recruited as part of the TrEAT multi-phase consortium study. One hundred and nineteen Australians (13-60 years; 96.9% female) with eating disorders currently accessing outpatient treatment for their illness completed an online survey comprised of self-report measures of eating disorder severity, treatment delay and perceived barriers to treatment-seeking. The treating clinician for each participant also provided additional information (e.g. body mass index and diagnosis). RESULTS: Overall, the average length of delay between onset of eating disorder symptoms and treatment-seeking was 5.28 years. Controlling for age, latency to treatment-seeking was significantly longer for individuals with bulimia nervosa and binge eating disorder compared to anorexia nervosa. However, when perceived barriers to treatment-seeking were investigated, there were no significant differences between the diagnostic groups in regard to the perceived barriers they experienced. Stigma was rated as the most impactful barrier for each diagnostic group. CONCLUSION: Findings suggest that individuals with eating disorders face substantial delays in accessing appropriate treatment and that latency to treatment-seeking is often magnified for counter-stereotypical eating disorder presentations. Further research is required to investigate other factors contributing to this delay.

Safe and stable generation of induced pluripotent stem cells using doggybone DNA vectors.

The application of induced pluripotent stem cells (iPSCs) in advanced therapies is increasing at pace, but concerns remain over their clinical safety profile. We report the first-ever application of doggybone DNA (dbDNA) vectors to generate human iPSCs. dbDNA vectors are closed-capped linear double-stranded DNA gene expression cassettes that contain no bacterial DNA and are amplified by a chemically defined, current good manufacturing practice (cGMP)-compliant methodology. We achieved comparable iPSC reprogramming efficiencies using transiently expressing dbDNA vectors with the same iPSC reprogramming coding sequences as the state-of-the-art OriP/EBNA1 episomal vectors but, crucially, in the absence of p53 shRNA repression. Moreover, persistent expression of EBNA1 from bacterially derived episomes resulted in stimulation of the interferon response, elevated DNA damage, and increased spontaneous differentiation. These cellular activities were diminished or absent in dbDNA-iPSCs, resulting in lines with a greater stability and safety potential for cell therapy.

Antibody-guided in vivo imaging of Aspergillus fumigatus lung infections during antifungal azole treatment.

Invasive pulmonary aspergillosis (IPA) is a life-threatening lung disease of immunocompromised humans, caused by the opportunistic fungal pathogen Aspergillus fumigatus. Inadequacies in current diagnostic procedures mean that early diagnosis of the disease, critical to patient survival, remains a major clinical challenge, and is leading to the empiric use of antifungal drugs and emergence of azole resistance. A non-invasive procedure that allows both unambiguous detection of IPA and its response to azole treatment is therefore needed. Here, we show that a humanised Aspergillus-specific monoclonal antibody, dual labelled with a radionuclide and fluorophore, can be used in immunoPET/MRI in vivo in a neutropenic mouse model and 3D light sheet fluorescence microscopy ex vivo in the infected mouse lungs to quantify early A. fumigatus lung infections and to monitor the efficacy of azole therapy. Our antibody-guided approach reveals that early drug intervention is critical to prevent complete invasion of the lungs by the fungus, and demonstrates the power of molecular imaging as a non-invasive procedure for tracking IPA in vivo.

Differences between Australian adolescents with eating disorder symptoms who are in treatment or not in treatment for an eating disorder.

BACKGROUND: Mental health problems frequently occur during adolescence, however, few adolescents seek treatment for these problems, especially for eating disorders. The current study aimed to quantify how adolescents in a clinical sample (ie, those receiving treatment for an eating disorder), differ in terms of psychological factors (eating disorder symptoms and psychological distress), compared to adolescents with eating pathology in a community sample (ie, those not receiving treatment). METHOD: Data were used from a community sample of adolescents with eating disorder pathology who have not sought treatment (n = 1011) and a clinical sample of adolescents presenting at eating disorder services for treatment (n = 153). Participants reported demographics and completed questionnaires assessing weight/shape concerns, disordered eating and psychological distress. RESULTS: Adolescents with a lower BMI, more frequent purging and higher weight/shape concerns were more common in the clinical sample, while those engaging in more frequent driven exercise were less common in the clinical sample. The samples did not differ in severity of psychological distress. CONCLUSIONS: The findings highlight the need for increasing mental health literacy about the role of BMI and driven exercise in eating disorder symptom presentation to increase early detection of these disorders among adolescents.

Advances in the In Vivo Molecular Imaging of Invasive Aspergillosis.

Invasive pulmonary aspergillosis (IPA) is a life-threatening infection of immunocompromised patients with Aspergillus fumigatus, a ubiquitous environmental mould. While there are numerous functioning antifungal therapies, their high cost, substantial side effects and fear of overt resistance development preclude permanent prophylactic medication of risk-patients. Hence, a fast and definitive diagnosis of IPA is desirable, to quickly identify those patients that really require aggressive antimycotic treatment and to follow the course of the therapeutic intervention. However, despite decades of research into this issue, such a diagnostic procedure is still not available. Here, we discuss the array of currently available methods for IPA detection and their limits. We then show that molecular imaging using positron emission tomography (PET) combined with morphological computed tomography or magnetic imaging is highly promising to become a future non-invasive approach for IPA diagnosis and therapy monitoring, albeit still requiring thorough validation and relying on further acceptance and dissemination of the approach. Thereby, our approach using the A. fumigatus-specific humanized monoclonal antibody hJF5 labelled with 64Cu as PET-tracer has proven highly effective in pre-clinical models and hence bears high potential for human application.

Localized effect of treated wastewater effluent on the resistome of an urban watershed.

BACKGROUND: Wastewater treatment is an essential tool for maintaining water quality in urban environments. While the treatment of wastewater can remove most bacterial cells, some will inevitably survive treatment to be released into natural environments. Previous studies have investigated antibiotic resistance within wastewater treatment plants, but few studies have explored how a river's complete set of antibiotic resistance genes (the "resistome") is affected by the release of treated effluent into surface waters. RESULTS: Here we used high-throughput, deep metagenomic sequencing to investigate the effect of treated wastewater effluent on the resistome of an urban river and the downstream distribution of effluent-associated antibiotic resistance genes and mobile genetic elements. Treated effluent release was found to be associated with increased abundance and diversity of antibiotic resistance genes and mobile genetic elements. The impact of wastewater discharge on the river's resistome diminished with increasing distance from effluent discharge points. The resistome at river locations that were not immediately downstream from any wastewater discharge points was dominated by a single integron carrying genes associated with resistance to sulfonamides and quaternary ammonium compounds. CONCLUSIONS: Our study documents variations in the resistome of an urban watershed from headwaters to a major confluence in an urban center. Greater abundances and diversity of antibiotic resistance genes are associated with human fecal contamination in river surface water, but the fecal contamination effect seems to be localized, with little measurable effect in downstream waters. The diverse composition of antibiotic resistance genes throughout the watershed suggests the influence of multiple environmental and biological factors.

Detection of the 'Big Five' mold killers of humans: Aspergillus, Fusarium, Lomentospora, Scedosporium and Mucormycetes.

Fungi are an important but frequently overlooked cause of morbidity and mortality in humans. Life-threatening fungal infections mainly occur in immunocompromised patients, and are typically caused by environmental opportunists that take advantage of a weakened immune system. The filamentous fungus Aspergillus fumigatus is the most important and well-documented mold pathogen of humans, causing a number of complex respiratory diseases, including invasive pulmonary aspergillosis, an often fatal disease in patients with acute leukemia or in immunosuppressed bone marrow or solid organ transplant recipients. However, non-Aspergillus molds are increasingly reported as agents of disseminated diseases, with Fusarium, Scedosporium, Lomentospora and mucormycete species now firmly established as pathogens of immunosuppressed and immunocompetent individuals. Despite well-documented risk factors for invasive fungal diseases, and increased awareness of the risk factors for life-threatening infections, the number of deaths attributable to molds is likely to be severely underestimated driven, to a large extent, by the lack of readily accessible, cheap, and accurate tests that allow detection and differentiation of infecting species. Early diagnosis is critical to patient survival but, unlike Aspergillus diseases, where a number of CE-marked or FDA-approved biomarker tests are now available for clinical diagnosis, similar tests for fusariosis, scedosporiosis and mucormycosis remain experimental, with detection reliant on insensitive and slow culture of pathogens from invasive bronchoalveolar lavage fluid, tissue biopsy, or from blood. This review examines the ecology, epidemiology, and contemporary methods of detection of these mold pathogens, and the obstacles to diagnostic test development and translation of novel biomarkers to the clinical setting.

Three-Dimensional Light Sheet Fluorescence Microscopy of Lungs To Dissect Local Host Immune-Aspergillus fumigatus Interactions.

Aspergillus fumigatus is an opportunistic fungal pathogen that can cause life-threatening invasive lung infections in immunodeficient patients. The cellular and molecular processes of infection during onset, establishment, and progression of A. fumigatus infections are highly complex and depend on both fungal attributes and the immune status of the host. Therefore, preclinical animal models are of paramount importance to investigate and gain better insight into the infection process. Yet, despite their extensive use, commonly employed murine models of invasive pulmonary aspergillosis are not well understood due to analytical limitations. Here, we present quantitative light sheet fluorescence microscopy (LSFM) to describe fungal growth and the local immune response in whole lungs at cellular resolution within its anatomical context. We analyzed three very common murine models of pulmonary aspergillosis based on immunosuppression with corticosteroids, chemotherapy-induced leukopenia, or myeloablative irradiation. LSFM uncovered distinct architectures of fungal growth and degrees of tissue invasion in each model. Furthermore, LSFM revealed the spatial distribution, interaction, and activation of two key immune cell populations in antifungal defense: alveolar macrophages and polymorphonuclear neutrophils. Interestingly, the patterns of fungal growth correlated with the detected effects of the immunosuppressive regimens on the local immune cell populations. Moreover, LSFM demonstrates that the commonly used intranasal route of spore administration did not result in complete intra-alveolar deposition, as about 80% of fungal growth occurred outside the alveolar space. Hence, characterization by LSFM is more rigorous than by previously used methods employing murine models of invasive pulmonary aspergillosis and pinpoints their strengths and limitations.IMPORTANCE The use of animal models of infection is essential to advance our understanding of the complex host-pathogen interactions that take place during Aspergillus fumigatus lung infections. As in the case of humans, mice need to suffer an immune imbalance in order to become susceptible to invasive pulmonary aspergillosis (IPA), the most serious infection caused by A. fumigatus There are several immunosuppressive regimens that are routinely used to investigate fungal growth and/or immune responses in murine models of invasive pulmonary aspergillosis. However, the precise consequences of the use of each immunosuppressive model for the local immune populations and for fungal growth are not completely understood. Here, to pin down the scenarios involving commonly used IPA models, we employed light sheet fluorescence microscopy (LSFM) to analyze whole lungs at cellular resolution. Our results will be valuable to optimize and refine animal models to maximize their use in future research.

Aspergillus fumigatus and Its Allergenic Ribotoxin Asp f I: Old Enemies but New Opportunities for Urine-Based Detection of Invasive Pulmonary Aspergillosis Using Lateral-Flow Technology.

Invasive pulmonary aspergillosis (IPA) caused by Aspergillus fumigatus is a life-threatening lung disease of immunocompromised patients. Diagnosis currently relies on non-specific chest CT, culture of the fungus from invasive lung biopsy, and detection of the cell wall carbohydrate galactomannan (GM) in serum or in BAL fluids recovered during invasive bronchoscopy. Urine provides an ideal bodily fluid for the non-invasive detection of pathogen biomarkers, with current urine-based immunodiagnostics for IPA focused on GM. Surrogate protein biomarkers might serve to improve disease detection. Here, we report the development of a monoclonal antibody (mAb), PD7, which is specific to A. fumigatus and related species in the section Fumigati, and which binds to its 18 kDa ribotoxin Asp f I. Using PD7, we show that the protein is secreted during hyphal development, and so represents an ideal candidate for detecting invasive growth. We have developed a lateral-flow device (Afu-LFD®) incorporating the mAb which has a limit of detection of ~15 ng Asp f I/mL urine. Preliminary evidence of the test's diagnostic potential is demonstrated with urine from a patient with acute lymphoid leukaemia with probable IPA. The Afu-LFD® therefore provides a potential novel opportunity for non-invasive urine-based detection of IPA caused by A. fumigatus.