Associations between patterns of human intestinal schistosomiasis and snail and mammal species richness in Uganda:can we detect a decoy effect?

In recent years, ecological research has suggested several mechanisms by which biodiversity might affect the risk of acquiring infectious diseases (i.e., the decoy, dilution or amplification effects), but the topic remains controversial. While many experimental studies suggest a negative relationship between biodiversity and disease, this relationship is inherently complex, and might be negative, positive or neutral depending on the geographical scale and ecological context. Here, applying a macroecological approach, we look for associations between diversity and disease by comparing the distribution of human schistosomiasis and biogeographical patterns of freshwater snail and mammal species richness in Uganda. We found that the association between estimated snail richness and human infection was best described by a negative correlation in non-spatial bi- and multivariate logistic mixed effect models. However, this association lost significance after the inclusion of a spatial component in a full geostatistical model, highlighting the importance of accounting for spatial correlation to obtain more precise parameter estimates. Furthermore, we found no significant relationships between mammal richness and schistosomiasis risk. We discuss the limitations of the data and methods used to test the decoy hypothesis for schistosomiasis, and highlight key future research directions that can facilitate more powerful tests of the decoy effect in snail-borne infections, at geographical scales that are relevant for public health and conservation.<br /

A multi-chamber microfluidic intestinal barrier model using Caco-2 cells for drug transport studies

This paper presents the design and fabrication of a multi-layer and multi-chamber microchip system using thiol-ene 'click chemistry' aimed for drug transport studies across tissue barrier models. The fabrication process enables rapid prototyping of multi-layer microfluidic chips using different thiol-ene polymer mixtures, where porous Teflon membranes for cell monolayer growth were incorporated by masked sandwiching thiol-ene-based fluid layers. Electrodes for trans-epithelial electrical resistance (TEER) measurements were incorporated using low-melting soldering wires in combination with platinum wires, enabling parallel real-time monitoring of barrier integrity for the eight chambers. Additionally, the translucent porous Teflon membrane enabled optical monitoring of cell monolayers. The device was developed and tested with the Caco-2 intestinal model, and compared to the conventional Transwell system. Cell monolayer differentiation was assessed via in situ immunocytochemistry of tight junction and mucus proteins, P-glycoprotein 1 (P-gp) mediated efflux of Rhodamine 123, and brush border aminopeptidase activity. Monolayer tightness and relevance for drug delivery research was evaluated through permeability studies of mannitol, dextran and insulin, alone or in combination with the absorption enhancer tetradecylmaltoside (TDM). The thiol-ene-based microchip material and electrodes were highly compatible with cell growth. In fact, Caco-2 cells cultured in the device displayed differentiation, mucus production, directional transport and aminopeptidase activity within 9-10 days of cell culture, indicating robust barrier formation at a faster rate than in conventional Transwell models. The cell monolayer displayed high TEER and tightness towards hydrophilic compounds, whereas co-administration of an absorption enhancer elicited TEER-decrease and increased permeability similar to the Transwell cultures. The presented cell barrier microdevice constitutes a relevant tissue barrier model, enabling transport studies of drugs and chemicals under real-time optical and functional monitoring in eight parallel chambers, thereby increasing the throughput compared to previously reported microdevices

<i>In Vivo</i> phenotyping of tumor metabolism in a canine cancer patient with simultaneous ¹⁸F-FDG-PET and hyperpolarized ¹³C-Pyruvate magnetic resonance spectroscopic imaging (hyperPET):mismatch demonstrates that FDG may not always reflect the Warburg effect

In this communication the mismatch between simultaneous 18F-FDG-PET and a 13C-lactate imaging (hyperPET) in a biopsy verified squamous cell carcinoma in the right tonsil of a canine cancer patient is shown. The results demonstrate that 18F-FDG-PET may not always reflect the Warburg effect in all tumors

Optimized flip angle schemes for the split acquisition of fast spin-echo signals (SPLICE) sequence and application to diffusion-weighted imaging

Purpose: The diffusion-weighted SPLICE (split acquisition of fast spin-echo signals) sequence employs split-echo rapid acquisition with relaxation enhancement (RARE) readout to provide images almost free of geometric distortions. However, due to the varying T (Formula presented.) -weighting during k-space traversal, SPLICE suffers from blurring. This work extends a method for controlling the spatial point spread function (PSF) while optimizing the signal-to-noise ratio (SNR) achieved by adjusting the flip angles in the refocusing pulse train of SPLICE. Methods: An algorithm based on extended phase graph (EPG) simulations optimizes the flip angles by maximizing SNR for a flexibly chosen predefined target PSF that describes the desired k-space density weighting and spatial resolution. An optimized flip angle scheme and a corresponding post-processing correction filter which together achieve the target PSF was tested by healthy subject brain imaging using a clinical 1.5 T scanner. Results: Brain images showed a clear and consistent improvement over those obtained with a standard constant flip angle scheme. SNR was increased and apparent diffusion coefficient estimates were more accurate. For a modified Hann k-space weighting example, considerable benefits resulted from acquisition weighting by flip angle control. Conclusion: The presented flexible method for optimizing SPLICE flip angle schemes offers improved MR image quality of geometrically accurate diffusion-weighted images that makes the sequence a strong candidate for radiotherapy planning or stereotactic surgery

Advances in MRI-guided radiotherapy:Acquisition, analysis and evaluation methods

In radiotherapy the main goal is to kill tumor cells with ionizing radiation, typically high-energy photons, while sparing the surrounding healthy tissue. The precision of the radiation dose delivery is crucial for the efficacy of radiotherapy and imaging is utilized for tumor and normal tissue delineation and for guidance at the moment of treatment, leading to the concept image-guided radiotherapy (IGRT). The most recent advancement here is the hybrid MRI – linear accelerator system (MR-linac), which enables high soft-tissue contrast images for adapting the dose plan to the anatomy-of-the-day. The MR-linac also makes it feasible to obtain daily advanced MRI which may potentially be used for revealing functional features of the tumor informative of local radio-sensitivities in the tumor and predictive of the overall treatment outcome. Utilizing MRI for such purposes requires high image quality and advanced data processing that involves analysis of multi-contrast measurements, such as multi-echo T2-weighted measurements, to extract characteristics of the tumor tissue. A model-based method is most commonly used, but the resulting quantitative maps are often prone to partial volume effects and may be biased or uninformative if the chosen model does not properly fit the data. Here, monotonous slope non-negative matrix factorization (msNMF) is proposed as a novel data-driven method. This extended version of the NMF decomposes the data under monotony constraints that fit many types of MRI data. A demonstration of the method showed its ability to extract interpretable components related to the underlying tissue micro-structure, and applications was also exemplified by estimation of edema water fractions in spinal cord white matter.MR-linacs enable longitudinal imaging data series, which requires dedicated handling of the covarying time-resolved measurements to investigate the tumor dynamics during the course of fractionated radiotherapy. This work also proposes a prediction framework as a tool to search for biomarkers using longitudinal MRI data. The framework relies on an initial data-driven decomposition and includes fitting over time to capture therapy-induced tumor changes that may be predictive of the outcome. Its feasibility was demonstrated using example datasets and the msNMF for decomposition, and results indicated a value of early T2-relaxation changes for predicting tumor response.Diffusion-weighted imaging (DWI) is an interesting multi-contrast technique due to the lower diffusivity of many tumor types that is altered when the ionizing radiation induces microstructural changes. Unfortunately, standard DWI suffers from geometric distortions, incompatible with radiotherapy purposes which includes both target delineation and response prediction. To address this, the current work includes optimization of the single-shot split acquisition for fast spin-echo (SPLICE) sequence. Contrary to standard diffusion-weighted echo-planar imaging, the SPLICE sequence is based on a fast spin-echo readout and results in geometrically robust images, but with a relatively poor voxel shape due to signal modulation during readout. The suggested optimization method maximizes the signal-to-noise ratio (SNR) for a controlled pointspread-function by varying the refocusing flip angles. A clear SNR gain, which also improved the accuracy of apparent diffusion coefficient (ADC) estimates, was seen for a healthy subject brain. In summary, the acquisition and analysis strategies developed during this research project may provide directions for future radiotherapy studies and can advance the usage of MRI for both treatment planning and evaluation

Modeling freshwater snail habitat suitability and areas of potential snail-borne disease transmission in Uganda

Geographic information system (GIS)-based modeling of an intermediate host snail species’ environmental requirements using known occurrence records can provide estimates of its spatial distribution. When other data are lacking, this can be used as a rough spatial prediction of potential snail-borne disease transmission areas. Furthermore, knowledge of abiotic factors affecting intra-molluscan parasitic development can be used to make “masks” based on remotely sensed climatic data, and these can in turn be used to refine these predictions. We used data from a recent freshwater snail survey from Uganda, environmental data and the genetic algorithm for rule-set prediction (GARP) to map the potential distribution of snail species known to act as intermediate hosts of several human and animal parasites. The results suggest that large areas of Uganda are suitable habitats for many of these snail species, indicating a large potential for disease transmission. The lack of parasitological data still makes it difficult to determine the magnitude of actual disease transmission, but the predicted snail distributions might be used as indicators of potential present and future risk areas. Some of the predicted snail distribution maps were furthermore combined with temperature masks delineating suitable temperature regimes of the parasites they host. This revealed the coinciding suitable areas for snail and parasite, but also areas suitable for host snails, but apparently not for the parasites. Assuming that the developed models correctly reflect areas suitable for transmission, the applied approach could prove useful for targeting control intervention