There is no consensus for a blood-based test for the early diagnosis of Alzheimer's disease (AD). Expression profiling of small non-coding RNA's, microRNA (miRNA), has revealed diagnostic potential ...in human diseases. Circulating miRNA are found in small vesicles known as exosomes within biological fluids such as human serum. The aim of this work was to determine a set of differential exosomal miRNA biomarkers between healthy and AD patients, which may aid in diagnosis. Using next-generation deep sequencing, we profiled exosomal miRNA from serum (N=49) collected from the Australian Imaging, Biomarkers and Lifestyle Flagship Study (AIBL). Sequencing results were validated using quantitative reverse transcription PCR (qRT-PCR; N=60), with predictions performed using the Random Forest method. Additional risk factors collected during the 4.5-year AIBL Study including clinical, medical and cognitive assessments, and amyloid neuroimaging with positron emission tomography were assessed. An AD-specific 16-miRNA signature was selected and adding established risk factors including age, sex and apolipoprotein ɛ4 (APOE ɛ4) allele status to the panel of deregulated miRNA resulted in a sensitivity and specificity of 87% and 77%, respectively, for predicting AD. Furthermore, amyloid neuroimaging information for those healthy control subjects incorrectly classified with AD-suggested progression in these participants towards AD. These data suggest that an exosomal miRNA signature may have potential to be developed as a suitable peripheral screening tool for AD.
Objective: The goal of this study was to investigate the relationship between default mode network connectivity and the severity of post‐traumatic stress disorder (PTSD) symptoms in a sample of ...eleven acutely traumatized subjects.
Method: Participants underwent a 5.5 min resting functional magnetic resonance imaging scan. Brain areas whose activity positively correlated with that of the posterior cingulate/precuneus (PCC) were assessed. To assess the relationship between severity of PTSD symptoms and PCC connectivity, the contrast image representing areas positively correlated with the PCC was correlated with the subjects’ Clinician Administered PTSD Scale scores.
Results: Results suggest that resting state connectivity of the PCC with the perigenual anterior cingulate and the right amygdala is associated with current PTSD symptoms and that correlation with the right amygdala predicts future PTSD symptoms.
Conclusion: These results may contribute to the development of prognostic tools to distinguish between those who will and those who will not develop PTSD.
This companion article to the VX-445 report shows that VX-659, a new CFTR potentiator, when administered with tezacaftor and ivacaftor improved lung function, sweat chloride concentration, and ...symptoms in patients with cystic fibrosis who harbored one or two Phe508del alleles.
A systematic review relevant to the following research questions was conducted (1) the extent to which different theoretical frameworks have been applied to food risk/benefit communication and (2) ...the impact such food risk/benefit communication interventions have had on related risk/benefit attitudes and behaviors. Fifty four papers were identified. The analysis revealed that (primarily European or US) research interest has been relatively recent. Certain food issues were of greater interest to researchers than others, perhaps reflecting the occurrence of a crisis, or policy concern. Three broad themes relevant to the development of best practice in risk (benefit) communication were identified: the characteristics of the target population; the contents of the information; and the characteristics of the information sources. Within these themes, independent and dependent variables differed considerably. Overall, acute risk (benefit) communication will require advances in communication process whereas chronic communication needs to identify audience requirements. Both citizen's risk/benefit perceptions and (if relevant) related behaviors need to be taken into account, and recommendations for behavioral change need to be concrete and actionable. The application of theoretical frameworks to the study of risk (benefit) communication was infrequent, and developing predictive models of effective risk (benefit) communication may be contingent on improved theoretical perspectives.
Dynamic causal modelling (DCM) of functional magnetic resonance imaging (fMRI) data offers new insights into the pathophysiology of neurological disease and mechanisms of effective therapies. Current ...applications can be used both to identify the most likely functional brain network underlying observed data and estimate the networks' connectivity parameters. We examined the reproducibility of DCM in healthy subjects (young 18–48 years, n=27; old 50–80 years, n=15) in the context of action selection. We then examined the effects of Parkinson's disease (50–78 years, Hoehn and Yahr stage 1–2.5, n=16) and dopaminergic therapy. Forty-eight models were compared, for each of 90 sessions from 58 subjects. Model-evidences clustered according to sets of structurally similar models, with high correlations over two sessions in healthy older subjects. The same model was identified as most likely in healthy controls on both sessions and in medicated patients. In this most likely network model, the selection of action was associated with enhanced coupling between prefrontal cortex and the pre-supplementary motor area. However, the parameters for intrinsic connectivity and contextual modulation in this model were poorly correlated across sessions. A different model was identified in patients with Parkinson's disease after medication withdrawal. In “off” patients, action selection was associated with enhanced connectivity from prefrontal to lateral premotor cortex. This accords with independent evidence of a dopamine-dependent functional disconnection of the SMA in Parkinson's disease. Together, these results suggest that DCM model selection is robust and sensitive enough to study clinical populations and their pharmacological treatment. For critical inferences, model selection may be sufficient. However, caution is required when comparing groups or drug effects in terms of the connectivity parameter estimates, if there are significant posterior covariances among parameters.
We present weak lensing shear catalogues for 139 square degrees of data taken during the Science Verification (SV) time for the new Dark Energy Camera (DECam) being used for the Dark Energy Survey ...(DES). We describe our object selection, point spread function estimation and shear measurement procedures using two independent shear pipelines, im3shape and ngmix, which produce catalogues of 2.12 million and 3.44 million galaxies, respectively. We detail a set of null tests for the shear measurements and find that they pass the requirements for systematic errors at the level necessary for weak lensing science applications using the SV data. We also discuss some of the planned algorithmic improvements that will be necessary to produce sufficiently accurate shear catalogues for the full 5-yr DES, which is expected to cover 5000 square degrees.
Cognitive deficits are very common in Parkinson's disease particularly for ‘executive functions’ associated with frontal cortico-striatal networks. Previous work has identified deficits in tasks that ...require attentional control like task-switching, and reward-based tasks like gambling or reversal learning. However, there is a complex relationship between the specific cognitive problems faced by an individual patient, their stage of disease and dopaminergic treatment. We used a bimodality continuous performance task during fMRI to examine how patients with Parkinson's disease represent the prospect of reward and switch between competing task rules accordingly. The task-switch was not separately cued but was based on the implicit reward relevance of spatial and verbal dimensions of successive compound stimuli. Nineteen patients were studied in relative ‘on’ and ‘off’ states, induced by dopaminergic medication withdrawal (Hoehn and Yahr stages 1–4). Patients were able to successfully complete the task and establish a bias to one or other dimension in order to gain reward. However the lateral prefrontal cortex and caudate nucleus showed a non-linear U-shape relationship between motor disease severity and regional brain activation. Dopaminergic treatment led to a shift in this U-shape function, supporting the hypothesis of differential neurodegeneration in separate motor and cognitive cortico–striato–thalamo–cortical circuits. In addition, anterior cingulate activation associated with reward expectation declined with more severe disease, whereas activation following actual rewards increased with more severe disease. This may facilitate a change in goal-directed behaviours from deferred predicted rewards to immediate actual rewards, particularly when on dopaminergic treatment. We discuss the implications for investigation and optimal treatment of this common condition at different stages of disease.
The objectives of this study were to (1) use partial budget analysis to estimate the cash impact for herds that switch from blanket dry cow therapy (BDCT) to culture- or algorithm-guided selective ...dry cow therapy (SDCT) and (2) conduct a sensitivity analysis to investigate effects in situations where SDCT increased clinical and subclinical mastitis risk during the subsequent lactation. A partial budget model was created using Monte Carlo simulation with @Risk software. Expenditures associated with dry-off procedures and health outcomes (clinical and subclinical mastitis) during the first 30 d in milk were used to model herd-level effects, expressed in units of US dollars per cow dry-off. Values for each economic component were derived from findings from a recent multisite clinical trial, peer-reviewed journal articles, USDA databases, and our experiences in facilitating the implementation of SDCT on farms. Fixed values were used for variables expected to have minimal variation within the US dairy herd population (e.g., cost of rapid culture plates) and sampling distributions were used for variables that were hypothesized to vary enough to effect the herd net cash impact of one or more DCT approach(es). For Objective 1, herd-level udder health was assumed to be unaffected by the implementation of SDCT. For culture-guided SDCT, producers could expect to save an average of +$2.14 (−$2.31 to $7.23 for 5th and 95th percentiles) per cow dry-off as compared with BDCT, with 75.5% of iterations being ≥$0.00. For algorithm-guided SDCT, the mean net cash impact was +$7.85 ($3.39–12.90) per cow dry-off, with 100% of iterations being ≥$0.00. The major contributors to variance in cash impact for both SDCT approaches were percent of quarters treated at dry-off and the cost of dry cow antibiotics. For Objective 2, we repeated the partial budget model with the 30-d clinical and subclinical mastitis incidence increasing by 1, 2, and 5% (i.e., risk difference = 0.01, 0.02, and 0.05) in both SDCT groups compared with BDCT. For algorithm-guided SDCT, average net cash impacts were ≥$0.00 per cow dry-off (i.e., cost effective) when mastitis incidence increased slightly. However, as clinical mastitis incidence increased, economic returns for SDCT diminished. These findings indicate that when SDCT is implemented appropriately (i.e., no to little negative effect on health), it might be a cost-effective practice for US herds under a range of economic conditions.
•A Conditional Generative Adversarial Network was trained to fill in missing fruit surface data.•The deep learning algorithm was trained using a large synthesised dataset.•The model predicted weight ...to within 5%.•The missing parts of kiwifruit surfaces were realistically reconstructed.
Non-destructive crop yield estimation is a major ambition for the development of digital horticulture systems, where the goal is to have a machine that can look at fruit on the vine/tree and estimate key performance metrics such as fruit weight, size and shape. The on-orchard partial occlusion problem is a major obstacle for the creation of such systems, where it is not possible for a single camera/scanner to capture the complete fruit surface due to its limited field of view. In this work, a deep learning approach was taken to solve this problem. Framing the issue as an image-to-image translation problem, a Conditional Generative Adversarial Network was trained to realistically reconstruct the enclosed and complete surface of kiwifruit when supplied with incomplete surface data, where the surface data was missing due to occlusion. Rather than training the deep learning algorithm with empirically collected data, an alternative approach was taken: the model was trained using a synthesised dataset, a large collection of kiwifruit shapes generated computationally via a Monte-Carlo routine. This was an attempt to generalise the approach to be applicable to other crops and other domains, and to provide substantial savings in time, labour and material costs. The trained model was later applied to a smaller population of kiwifruit empirically scanned using an infrared scanner and could predict fruit weight with a mean absolute percentage error of less than 5% and was successful in realistically reconstructing the whole enclosed surface over a range of sizes, shapes and orientations.
Many chemicals can induce skin sensitization, and there is a pressing need for non-animal methods to give a quantitative indication of potency. Using two large published data sets of skin ...sensitizers, we have allocated each sensitizing chemical to one of 10 mechanistic categories and then developed good QSAR models for the seven categories that have a sufficient number of chemicals to allow modeling. Both internal and external validation checks showed that each model had good predictivity.
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