Legionella Eukaryotic-Like Type IV Substrates Interfere with Organelle Trafficking

Legionella pneumophila, the causative agent of Legionnaires' disease, evades phago-lysosome fusion in mammalian and protozoan hosts to create a suitable niche for intracellular replication. To modulate vesicle trafficking pathways, L. pneumophila translocates effector proteins into eukaryotic cells through a Type IVB macro-molecular transport system called the Icm-Dot system. In this study, we employed a fluorescence-based translocation assay to show that 33 previously identified Legionella eukaryotic-like genes (leg) encode substrates of the Icm-Dot secretion system. To assess which of these proteins may contribute to the disruption of vesicle trafficking, we expressed each gene in yeast and looked for phenotypes related to vacuolar protein sorting. We found that LegC3-GFP and LegC7/YlfA-GFP caused the mis-secretion of CPY-Invertase, a fusion protein normally restricted to the yeast vacuole. We also found that LegC7/YlfA-GFP and its paralog LegC2/YlfB-GFP formed large structures around the yeast vacuole while LegC3-GFP localized to the plasma membrane and a fragmented vacuole. In mammalian cells, LegC2/YlfB-GFP and LegC7/YlfA-GFP were found within large structures that co-localized with anti-KDEL antibodies but excluded the lysosomal marker LAMP-1, similar to what is observed in Legionella-containing vacuoles. LegC3-GFP, in contrast, was observed as smaller structures which had no obvious co-localization with KDEL or LAMP-1. Finally, LegC3-GFP caused the accumulation of many endosome-like structures containing undigested material when expressed in the protozoan host Dictyostelium discoideum. Our results demonstrate that multiple Leg proteins are Icm/Dot-dependent substrates and that LegC3, LegC7/YlfA, and LegC2/YlfB may contribute to the intracellular trafficking of L. pneumophila by interfering with highly conserved pathways that modulate vesicle maturation

Investigation on the Protective Effect of α-Mannan against the DNA Damage Induced by Aflatoxin B1 in Mouse Hepatocytes

Aflatoxin B1 is a contaminant of agricultural and dairy products that can be related to mutagenic and carcinogenic effects. In this report we explore the capacity of α-mannan (Man) to reduce the DNA damage induced by AFB1 in mouse hepatocytes. For this purpose we applied the comet assay to groups of animals which were first administered Man (100, 400 and 700 mg/kg, respectively) and 20 min later 1.0 mg/kg of AFB1. Liver cells were obtained at 4, 10, and 16 h after the chemical administration and examined. The results showed no protection of the damage induced by AFB1 with the low dose of the polysaccharide, but they did reveal antigenotoxic activity exerted by the two high doses. In addition, we induced a co-crystallization between both compounds, determined their fusion points and analyzed the molecules by UV spectroscopy. The obtained data suggested the formation of a supramolecular complex between AFB1 and Man

Use of mobile technology-based participatory mapping approaches to geolocate health facility attendees for disease surveillance in low resource settings.

BACKGROUND: Identifying fine-scale spatial patterns of disease is essential for effective disease control and elimination programmes. In low resource areas without formal addresses, novel strategies are needed to locate residences of individuals attending health facilities in order to efficiently map disease patterns. We aimed to assess the use of Android tablet-based applications containing high resolution maps to geolocate individual residences, whilst comparing the functionality, usability and cost of three software packages designed to collect spatial information. RESULTS: Using Open Data Kit GeoODK, we designed and piloted an electronic questionnaire for rolling cross sectional surveys of health facility attendees as part of a malaria elimination campaign in two predominantly rural sites in the Rizal, Palawan, the Philippines and Kulon Progo Regency, Yogyakarta, Indonesia. The majority of health workers were able to use the tablets effectively, including locating participant households on electronic maps. For all households sampled (n = 603), health facility workers were able to retrospectively find the participant household using the Global Positioning System (GPS) coordinates and data collected by tablet computers. Median distance between actual house locations and points collected on the tablet was 116 m (IQR 42-368) in Rizal and 493 m (IQR 258-886) in Kulon Progo Regency. Accuracy varied between health facilities and decreased in less populated areas with fewer prominent landmarks. CONCLUSIONS: Results demonstrate the utility of this approach to develop real-time high-resolution maps of disease in resource-poor environments. This method provides an attractive approach for quickly obtaining spatial information on individuals presenting at health facilities in resource poor areas where formal addresses are unavailable and internet connectivity is limited. Further research is needed on how to integrate these with other health data management systems and implement in a wider operational context

Urban Forest and the Tree Canopy: A Pathway to Climate Resilience

Background: Urban ecosystems face many environmental, infrastructure, and social systems challenges. Urban forest plays an important role in urban ecology but continue to face many direct and indirect threats. Research indicates that climate change, insects, disease, and urbanization are the major causes of urban forest decline. Tree canopies play a major role in ecosystem services, providing the advantages of a natural, cost-effective system of green infrastructure, removal of air and water pollutants, modulation of energy use, and improvement in water quality. These services increase climate resilience. Purpose: The purpose of this service-learning project was to gain a better understanding of ecosystem service benefits from trees in Washington, DC and whether these benefits facilitated Washington, DC being more climate resilient. Our aim was two-folds, to describe the monetary value of carbon sequestration from trees in DC, and to assist in identifying tree species in local neighborhoods. Methods: We collected tree canopy data using the i-Tree tool designed to provide an estimate of ecosystem service benefits and the TreeSnap tool designed to allow citizen scientists to make observations of trees in local communities and provide pictorial documents to scientists who catalog tree species. Results: Our results showed on average carbon sequestered by trees valued at $10,196,999 million dollars and carbon stored in trees was valued at$256,084,907 million dollars. Our other results showed the variety of tree species such as the Japanese Cherry Tree, have large bases, are plentiful throughout Washington, DC, and capable of storing large amounts of carbon. Conclusion: Washington, DC has increased the number of trees planted annually, which we believe creates a pathway to a climate-resilient city. As urban sustainability majors, this project enlightened our understanding of urban sustainability and climate resilience

Saliency-Enhanced Content-Based Image Retrieval for Diagnosis Support in Dermatology Consultation: Reader Study.

BACKGROUND Previous research studies have demonstrated that medical content image retrieval can play an important role by assisting dermatologists in skin lesion diagnosis. However, current state-of-the-art approaches have not been adopted in routine consultation, partly due to the lack of interpretability limiting trust by clinical users. OBJECTIVE This study developed a new image retrieval architecture for polarized or dermoscopic imaging guided by interpretable saliency maps. This approach provides better feature extraction, leading to better quantitative retrieval performance as well as providing interpretability for an eventual real-world implementation. METHODS Content-based image retrieval (CBIR) algorithms rely on the comparison of image features embedded by convolutional neural network (CNN) against a labeled data set. Saliency maps are computer vision-interpretable methods that highlight the most relevant regions for the prediction made by a neural network. By introducing a fine-tuning stage that includes saliency maps to guide feature extraction, the accuracy of image retrieval is optimized. We refer to this approach as saliency-enhanced CBIR (SE-CBIR). A reader study was designed at the University Hospital Zurich Dermatology Clinic to evaluate SE-CBIR's retrieval accuracy as well as the impact of the participant's confidence on the diagnosis. RESULTS SE-CBIR improved the retrieval accuracy by 7% (77% vs 84%) when doing single-lesion retrieval against traditional CBIR. The reader study showed an overall increase in classification accuracy of 22% (62% vs 84%) when the participant is provided with SE-CBIR retrieved images. In addition, the overall confidence in the lesion's diagnosis increased by 24%. Finally, the use of SE-CBIR as a support tool helped the participants reduce the number of nonmelanoma lesions previously diagnosed as melanoma (overdiagnosis) by 53%. CONCLUSIONS SE-CBIR presents better retrieval accuracy compared to traditional CBIR CNN-based approaches. Furthermore, we have shown how these support tools can help dermatologists and residents improve diagnosis accuracy and confidence. Additionally, by introducing interpretable methods, we should expect increased acceptance and use of these tools in routine consultation

Saliency-Enhanced Content-Based Image Retrieval for Diagnosis Support in Dermatology Consultation: Reader Study

BACKGROUND Previous research studies have demonstrated that medical content image retrieval can play an important role by assisting dermatologists in skin lesion diagnosis. However, current state-of-the-art approaches have not been adopted in routine consultation, partly due to the lack of interpretability limiting trust by clinical users. OBJECTIVE This study developed a new image retrieval architecture for polarized or dermoscopic imaging guided by interpretable saliency maps. This approach provides better feature extraction, leading to better quantitative retrieval performance as well as providing interpretability for an eventual real-world implementation. METHODS Content-based image retrieval (CBIR) algorithms rely on the comparison of image features embedded by convolutional neural network (CNN) against a labeled data set. Saliency maps are computer vision-interpretable methods that highlight the most relevant regions for the prediction made by a neural network. By introducing a fine-tuning stage that includes saliency maps to guide feature extraction, the accuracy of image retrieval is optimized. We refer to this approach as saliency-enhanced CBIR (SE-CBIR). A reader study was designed at the University Hospital Zurich Dermatology Clinic to evaluate SE-CBIR's retrieval accuracy as well as the impact of the participant's confidence on the diagnosis. RESULTS SE-CBIR improved the retrieval accuracy by 7% (77% vs 84%) when doing single-lesion retrieval against traditional CBIR. The reader study showed an overall increase in classification accuracy of 22% (62% vs 84%) when the participant is provided with SE-CBIR retrieved images. In addition, the overall confidence in the lesion's diagnosis increased by 24%. Finally, the use of SE-CBIR as a support tool helped the participants reduce the number of nonmelanoma lesions previously diagnosed as melanoma (overdiagnosis) by 53%. CONCLUSIONS SE-CBIR presents better retrieval accuracy compared to traditional CBIR CNN-based approaches. Furthermore, we have shown how these support tools can help dermatologists and residents improve diagnosis accuracy and confidence. Additionally, by introducing interpretable methods, we should expect increased acceptance and use of these tools in routine consultation

Current Priorities for Public Health Practice in Addressing the Role of Human Genomics in Improving Population Health

In spite of accelerating human genome discoveries in a wide variety of diseases of public health significance, the promise of personalized health care and disease prevention based on genomics has lagged behind. In a time of limited resources, public health agencies must continue to focus on implementing programs that can improve health and prevent disease now. Nevertheless, public health has an important and assertive leadership role in addressing the promise and pitfalls of human genomics for population health. Such efforts are needed not only to implement what is known in genomics to improve health but also to reduce potential harm and create the infrastructure needed to derive health benefits in the future

Control of intestinal stem cell function and proliferation by mitochondrial pyruvate metabolism.

Most differentiated cells convert glucose to pyruvate in the cytosol through glycolysis, followed by pyruvate oxidation in the mitochondria. These processes are linked by the mitochondrial pyruvate carrier (MPC), which is required for efficient mitochondrial pyruvate uptake. In contrast, proliferative cells, including many cancer and stem cells, perform glycolysis robustly but limit fractional mitochondrial pyruvate oxidation. We sought to understand the role this transition from glycolysis to pyruvate oxidation plays in stem cell maintenance and differentiation. Loss of the MPC in Lgr5-EGFP-positive stem cells, or treatment of intestinal organoids with an MPC inhibitor, increases proliferation and expands the stem cell compartment. Similarly, genetic deletion of the MPC in Drosophila intestinal stem cells also increases proliferation, whereas MPC overexpression suppresses stem cell proliferation. These data demonstrate that limiting mitochondrial pyruvate metabolism is necessary and sufficient to maintain the proliferation of intestinal stem cells

Disentangling fine-scale effects of environment on malaria detection and infection to design risk-based disease surveillance systems in changing landscapes

AbstractLandscape changes have complex effects on malaria transmission, disrupting social and ecological systems determining the spatial distribution of risk. Within Southeast Asia, forested landscapes are associated with both increased malaria transmission and reduced healthcare access. Here, we adapt an ecological modelling framework to identify how local environmental factors influence the spatial distributions of malaria infections, diagnostic sensitivity and detection probabilities in the Philippines. Using convenience sampling of health facility attendees and Bayesian latent process models, we demonstrate how risk-based surveillance incorporating forest data increases the probability of detecting malaria foci over three-fold and enables estimation of underlying distributions of malaria infections. We show the sensitivity of routine diagnostics varies spatially, with the decreased sensitivity in closed canopy forest areas limiting the utility of passive reporting to identify spatial patterns of transmission. By adjusting for diagnostic sensitivity and targeting spatial coverage of health systems, we develop a model approach for how to use landscape data within disease surveillance systems. Together, this illustrates the essential role of environmental data in designing risk-based surveillance to provide an operationally feasible and cost-effective method to characterise malaria transmission while accounting for imperfect detection.</jats:p