Plasmodium falciparum serology: A comparison of two protein production methods for analysis of antibody responses by protein microarray.

The evaluation of protein antigens as putative serologic biomarkers of infection has increasingly shifted to high-throughput, multiplex approaches such as the protein microarray. In vitro transcription/translation (IVTT) systems-a similarly high-throughput protein expression method-are already widely utilised in the production of protein microarrays, though purified recombinant proteins derived from more traditional whole cell based expression systems also play an important role in biomarker characterisation. Here we have performed a side-by-side comparison of antigen-matched protein targets from an IVTT and purified recombinant system, on the same protein microarray. The magnitude and range of antibody responses to purified recombinants was found to be greater than that of IVTT proteins, and responses between targets from different expression systems did not clearly correlate. However, responses between amino acid sequence-matched targets from each expression system were more closely correlated. Despite the lack of a clear correlation between antigen-matched targets produced in each expression system, our data indicate that protein microarrays produced using either method can be used confidently, in a context dependent manner, though care should be taken when comparing data derived from contrasting approaches

Fully-automated patient-level malaria assessment on field-prepared thin blood film microscopy images, including Supplementary Information

Malaria is a life-threatening disease affecting millions. Microscopy-based assessment of thin blood films is a standard method to (i) determine malaria species and (ii) quantitate high-parasitemia infections. Full automation of malaria microscopy by machine learning (ML) is a challenging task because field-prepared slides vary widely in quality and presentation, and artifacts often heavily outnumber relatively rare parasites. In this work, we describe a complete, fully-automated framework for thin film malaria analysis that applies ML methods, including convolutional neural nets (CNNs), trained on a large and diverse dataset of field-prepared thin blood films. Quantitation and species identification results are close to sufficiently accurate for the concrete needs of drug resistance monitoring and clinical use-cases on field-prepared samples. We focus our methods and our performance metrics on the field use-case requirements. We discuss key issues and important metrics for the application of ML methods to malaria microscopy.Comment: 16 pages, 13 figure

Performance of a fully‐automated system on a WHO malaria microscopy evaluation slide set

Background: Manual microscopy remains a widely-used tool for malaria diagnosis and clinical studies, but it has inconsistent quality in the field due to variability in training and field practices. Automated diagnostic systems based on machine learning hold promise to improve quality and reproducibility of field microscopy. The World Health Organization (WHO) has designed a 55-slide set (WHO 55) for their External Competence Assessment of Malaria Microscopists (ECAMM) programme, which can also serve as a valuable benchmark for automated systems. The performance of a fully-automated malaria diagnostic system, EasyScan GO, on a WHO 55 slide set was evaluated. Methods: The WHO 55 slide set is designed to evaluate microscopist competence in three areas of malaria diagnosis using Giemsa-stained blood films, focused on crucial field needs: malaria parasite detection, malaria parasite species identification (ID), and malaria parasite quantitation. The EasyScan GO is a fully-automated system that combines scanning of Giemsa-stained blood films with assessment algorithms to deliver malaria diagnoses. This system was tested on a WHO 55 slide set. Results: The EasyScan GO achieved 94.3 % detection accuracy, 82.9 % species ID accuracy, and 50 % quantitation accuracy, corresponding to WHO microscopy competence Levels 1, 2, and 1, respectively. This is, to our knowledge, the best performance of a fully-automated system on a WHO 55 set. Conclusions: EasyScan GO’s expert ratings in detection and quantitation on the WHO 55 slide set point towards its potential value in drug efficacy use-cases, as well as in some case management situations with less stringent species ID needs. Improved runtime may enable use in general case management settings

A plasmid locus associated with Klebsiella clinical infections encodes a microbiome-dependent gut fitness factor.

Klebsiella pneumoniae (Kp) is an important cause of healthcare-associated infections, which increases patient morbidity, mortality, and hospitalization costs. Gut colonization by Kp is consistently associated with subsequent Kp disease, and patients are predominantly infected with their colonizing strain. Our previous comparative genomics study, between disease-causing and asymptomatically colonizing Kp isolates, identified a plasmid-encoded tellurite (TeO3-2)-resistance (ter) operon as strongly associated with infection. However, TeO3-2 is extremely rare and toxic to humans. Thus, we used a multidisciplinary approach to determine the biological link between ter and Kp infection. First, we used a genomic and bioinformatic approach to extensively characterize Kp plasmids encoding the ter locus. These plasmids displayed substantial variation in plasmid incompatibility type and gene content. Moreover, the ter operon was genetically independent of other plasmid-encoded virulence and antibiotic resistance loci, both in our original patient cohort and in a large set (n = 88) of publicly available ter operon-encoding Kp plasmids, indicating that the ter operon is likely playing a direct, but yet undescribed role in Kp disease. Next, we employed multiple mouse models of infection and colonization to show that 1) the ter operon is dispensable during bacteremia, 2) the ter operon enhances fitness in the gut, 3) this phenotype is dependent on the colony of origin of mice, and 4) antibiotic disruption of the gut microbiota eliminates the requirement for ter. Furthermore, using 16S rRNA gene sequencing, we show that the ter operon enhances Kp fitness in the gut in the presence of specific indigenous microbiota, including those predicted to produce short chain fatty acids. Finally, administration of exogenous short-chain fatty acids in our mouse model of colonization was sufficient to reduce fitness of a ter mutant. These findings indicate that the ter operon, strongly associated with human infection, encodes factors that resist stress induced by the indigenous gut microbiota during colonization. This work represents a substantial advancement in our molecular understanding of Kp pathogenesis and gut colonization, directly relevant to Kp disease in healthcare settings

Talking about depression: a qualitative study of barriers to managing depression in people with long term conditions in primary care

<p>Abstract</p> <p>Background</p> <p>The risk of depression is increased in people with long term conditions (LTCs) and is associated with poorer patient outcomes for both the depressive illness and the LTC, but often remains undetected and poorly managed. The aim of this study was to identify and explore barriers to detecting and managing depression in primary care in people with two exemplar LTCs: diabetes and coronary heart disease (CHD).</p> <p>Methods</p> <p>Qualitative in-depth interviews were conducted with 19 healthcare professionals drawn predominately from primary care, along with 7 service users and 3 carers (n = 29). One focus group was then held with a set of 6 healthcare professionals and a set of 7 service users and 1 carer (n = 14). Interviews and the focus group were digitally recorded, transcribed verbatim, and analysed independently. The two data sets were then inspected for commonalities using a constant comparative method, leading to a final thematic framework used in this paper.</p> <p>Results</p> <p>Barriers to detecting and managing depression in people with LTCs in primary care exist: i) when practitioners in partnership with patients conceptualise depression as a common and understandable response to the losses associated with LTCs - depression in the presence of LTCs is normalised, militating against its recognition and treatment; ii) where highly performanced managed consultations under the terms of the Quality and Outcomes Framework encourage reductionist approaches to case-finding in people with CHD and diabetes, and iii) where there is uncertainty among practitioners about how to negotiate labels for depression in people with LTCs in ways that might facilitate shared understanding and future management.</p> <p>Conclusion</p> <p>Depression was often normalised in the presence of LTCs, obviating rather than facilitating further assessment and management. Furthermore, structural constraints imposed by the QOF encouraged reductionist approaches to case-finding for depression in consultations for CHD and diabetes. Future work might focus on how interventions that draw on the principles of the chronic care model, such as collaborative care, could support primary care practitioners to better recognise and manage depression in patients with LTCs.</p

Normative modeling of brain morphometry in Clinical High-Risk for Psychosis

Importance: The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in the majority of individuals at psychosis risk may be nested within the range observed in healthy individuals. Objective: To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high-risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder. Design setting and participants: Clinical, IQ and FreeSurfer-derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1,340 CHR-P individuals [47.09% female; mean age: 20.75 (4.74) years] and 1,237 healthy individuals [44.70% female; mean age: 22.32 (4.95) years] from 29 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. Main outcomes and measures: For each regional morphometric measure, z-scores were computed that index the degree of deviation from the normative means of that measure in a healthy reference population (N=37,407). Average deviation scores (ADS) for CT, SA, SV, and globally across all measures (G) were generated by averaging the respective regional z-scores. Regression analyses were used to quantify the association of deviation scores with clinical severity and cognition and two-proportion z-tests to identify case-control differences in the proportion of individuals with infranormal (z1.96) scores. Results: CHR-P and healthy individuals overlapped in the distributions of the observed values, regional z-scores, and all ADS vales. The proportion of CHR-P individuals with infranormal or supranormal values in any metric was low (<12%) and similar to that of healthy individuals. CHR-P individuals who converted to psychosis compared to those who did not convert had a higher percentage of infranormal values in temporal regions (5-7% vs 0.9-1.4%). In the CHR-P group, only the ADS SA showed significant but weak associations (|β|<0.09; P FDR <0.05) with positive symptoms and IQ. Conclusions and relevance: The study findings challenge the usefulness of macroscale neuromorphometric measures as diagnostic biomarkers of psychosis risk and suggest that such measures do not provide an adequate explanation for psychosis risk. Key points: Question: Is the risk of psychosis associated with brain morphometric changes that deviate significantly from healthy variation?Findings: In this study of 1340 individuals high-risk for psychosis (CHR-P) and 1237 healthy participants, individual-level variation in macroscale neuromorphometric measures of the CHR-P group was largely nested within healthy variation and was not associated with the severity of positive psychotic symptoms or conversion to a psychotic disorder.Meaning: The findings suggest the macroscale neuromorphometric measures have limited utility as diagnostic biomarkers of psychosis risk

Madagascar’s extraordinary biodiversity: Threats and opportunities

Madagascar's unique biota is heavily affected by human activity and is under intense threat. Here, we review the current state of knowledge on the conservation status of Madagascar's terrestrial and freshwater biodiversity by presenting data and analyses on documented and predicted species-level conservation statuses, the most prevalent and relevant threats, ex situ collections and programs, and the coverage and comprehensiveness of protected areas. The existing terrestrial protected area network in Madagascar covers 10.4% of its land area and includes at least part of the range of the majority of described native species of vertebrates with known distributions (97.1% of freshwater fishes, amphibians, reptiles, birds, and mammals combined) and plants (67.7%). The overall figures are higher for threatened species (97.7% of threatened vertebrates and 79.6% of threatened plants occurring within at least one protected area). International Union for Conservation of Nature (IUCN) Red List assessments and Bayesian neural network analyses for plants identify overexploitation of biological resources and unsustainable agriculture as themost prominent threats to biodiversity. We highlight five opportunities for action at multiple levels to ensure that conservation and ecological restoration objectives, programs, and activities take account of complex underlying and interacting factors and produce tangible benefits for the biodiversity and people of Madagascar

Madagascar’s extraordinary biodiversity: Evolution, distribution, and use

Madagascar's biota is hyperdiverse and includes exceptional levels of endemicity. We review the current state of knowledge on Madagascar's past and current terrestrial and freshwater biodiversity by compiling and presenting comprehensive data on species diversity, endemism, and rates of species description and human uses, in addition to presenting an updated and simplified map of vegetation types. We report a substantial increase of records and species new to science in recent years; however, the diversity and evolution of many groups remain practically unknown (e.g., fungi and most invertebrates). Digitization efforts are increasing the resolution of species richness patterns and we highlight the crucial role of field- and collections-based research for advancing biodiversity knowledge and identifying gaps in our understanding, particularly as species richness corresponds closely to collection effort. Phylogenetic diversity patterns mirror that of species richness and endemism in most of the analyzed groups. We highlight humid forests as centers of diversity and endemism because of their role as refugia and centers of recent and rapid radiations. However, the distinct endemism of other areas, such as the grassland-woodland mosaic of the Central Highlands and the spiny forest of the southwest, is also biologically important despite lower species richness. The documented uses of Malagasy biodiversity are manifold, with much potential for the uncovering of new useful traits for food, medicine, and climate mitigation. The data presented here showcase Madagascar as a unique living laboratory for our understanding of evolution and the complex interactions between people and nature. The gathering and analysis of biodiversity data must continue and accelerate if we are to fully understand and safeguard this unique subset of Earth's biodiversity

Neuroanatomical heterogeneity and homogeneity in individuals at clinical high risk for psychosis

Individuals at Clinical High Risk for Psychosis (CHR-P) demonstrate heterogeneity in clinical profiles and outcome features. However, the extent of neuroanatomical heterogeneity in the CHR-P state is largely undetermined. We aimed to quantify the neuroanatomical heterogeneity in structural magnetic resonance imaging measures of cortical surface area (SA), cortical thickness (CT), subcortical volume (SV), and intracranial volume (ICV) in CHR-P individuals compared with healthy controls (HC), and in relation to subsequent transition to a first episode of psychosis. The ENIGMA CHR-P consortium applied a harmonised analysis to neuroimaging data across 29 international sites, including 1579 CHR-P individuals and 1243 HC, offering the largest pooled CHR-P neuroimaging dataset to date. Regional heterogeneity was indexed with the Variability Ratio (VR) and Coefficient of Variation (CV) ratio applied at the group level. Personalised estimates of heterogeneity of SA, CT and SV brain profiles were indexed with the novel Person-Based Similarity Index (PBSI), with two complementary applications. First, to assess the extent of within-diagnosis similarity or divergence of neuroanatomical profiles between individuals. Second, using a normative modelling approach, to assess the ‘normativeness’ of neuroanatomical profiles in individuals at CHR-P. CHR-P individuals demonstrated no greater regional heterogeneity after applying FDR corrections. However, PBSI scores indicated significantly greater neuroanatomical divergence in global SA, CT and SV profiles in CHR-P individuals compared with HC. Normative PBSI analysis identified 11 CHR-P individuals (0.70%) with marked deviation (>1.5 SD) in SA, 118 (7.47%) in CT and 161 (10.20%) in SV. Psychosis transition was not significantly associated with any measure of heterogeneity. Overall, our examination of neuroanatomical heterogeneity within the CHR-P state indicated greater divergence in neuroanatomical profiles at an individual level, irrespective of psychosis conversion. Further large-scale investigations are required of those who demonstrate marked deviation.publishedVersio