Characterization of Neutral Lipids of the Oleaginous Alga Micractinum inermum.

An oleaginous microalga Micractinum inermum isolated from Mariana Lake, AB, Canada was cultured in a 1000 L photobioreactor with an f/2 medium to study its lipid content and neutral lipid profile. Algal biomass was collected at the stationary phase contained a significant amount of lipids (44.2%), as determined by Folch's method. The lipid was fractionated into neutral lipid, glycolipid and phospholipid fractions. The neutral lipid constitutes almost 77.3% of the total lipid species and is mainly composed of triacylglycerols (TAGs) determined by a proton NMR study. UHPLC-HRMS analysis allows us for the first time to identify 81 TAGs in the neutral lipid fraction of M. inermum. The fatty acid acyl side chains were identified based on fragment ions observed in MSMS analysis. TAGs with fatty acid acyl chains 18:1/18:1/18:1, 18:1/18:1/16:0, 18:2/18:1/16:0, and 18:2/18:2/18:0 were the major ones among the identified TAGs. Fatty acid analysis further supports the fact that oleic acid was the major fatty acid present in the neutral lipid fraction of M. inermum constituting 41.7%, followed by linoleic acid at 21.5%, and palmitic acid at 21.2%. The saturated and monounsaturated fatty acids were 67.8% or higher in the lipid fraction. Long-chain fatty acids were only present in a minor quantity. The results clearly demonstrate that M. inermum is an excellent source for TAGs.

Dementia with Lewy bodies: Impact of co-pathologies and implications for clinical trial design.

Dementia with Lewy bodies (DLB) is clinically defined by the presence of visual hallucinations, fluctuations, rapid eye movement (REM) sleep behavioral disorder, and parkinsonism. Neuropathologically, it is characterized by the presence of Lewy pathology. However, neuropathological studies have demonstrated the high prevalence of coexistent Alzheimer's disease, TAR DNA-binding protein 43 (TDP-43), and cerebrovascular pathologic cases. Due to their high prevalence and clinical impact on DLB individuals, clinical trials should account for these co-pathologies in their design and selection and the interpretation of biomarkers values and outcomes. Here we discuss the frequency of the different co-pathologies in DLB and their cross-sectional and longitudinal clinical impact. We then evaluate the utility and possible applications of disease-specific and disease-nonspecific biomarkers and how co-pathologies can impact these biomarkers. We propose a framework for integrating multi-modal biomarker fingerprints and step-wise selection and assessment of DLB individuals for clinical trials, monitoring target engagement, and interpreting outcomes in the setting of co-pathologies.

Production of quorum sensing-related metabolites and phytoalexins during Pseudomonas aeruginosa-Brassica napus interaction.

Pseudomonas aeruginosa is an opportunistic bacterial pathogen that has been shown to interact with many organisms throughout the domains of life, including plants. How this broad-host-range bacterium interacts with each of its diverse hosts, especially the metabolites that mediate these interactions, is not completely known. In this work, we used a liquid culture root infection system to collect plant and bacterial metabolites on days 1, 3 and 5 post-P. aeruginosa (strain PA14) infection of the oilseed plant, canola (Brassica napus). Using MS-based metabolomics approaches, we identified the overproduction of quorum sensing (QS)-related (both signalling molecules and regulated products) metabolites by P. aeruginosa while interacting with canola plants. However, the P. aeruginosa infection induced the production of several phytoalexins, which is a part of the hallmark plant defence response to microbes. The QS system of PA14 appears to only mediate part of the canola-P. aeruginosa metabolomic interactions, as the use of isogenic mutant strains of each of the three QS signalling branches did not significantly affect the induction of the phytoalexin brassilexin, while induction of spirobrassinin was significantly decreased. Interestingly, a treatment of purified QS molecules in the absence of bacteria was not able to induce any phytoalexin production, suggesting that active bacterial colonization is required for eliciting phytoalexin production. Furthermore, we identified that brassilexin, the only commercially available phytoalexin that was detected in this study, demonstrated a MIC of 400 µg ml-1 against P. aeruginosa PA14. The production of phytoalexins can be an effective component of canola innate immunity to keep potential infections by the opportunistic pathogen P. aeruginosa at bay.

Triacylglycerols and Other Lipids Profiling of Hemp By-Products.

Hemp seed by-products, namely hemp cake (hemp meal) and hemp hulls were studied for their lipid content and composition. Total lipid content of hemp cake and hemp hulls was 13.1% and 17.5%, respectively. Oil extraction yields using hexane, on the other hand, were much lower in hemp cake (7.4%) and hemp hulls (12.1%). Oil derived from both hemp seeds and by-products were primarily composed of neutral lipids (>97.1%), mainly triacylglycerols (TAGs), determined by SPE and confirmed by NMR study. Linoleic acid was the major fatty acid present in oils derived from hemp by-products, covering almost 55%, followed by α-linolenic acid, covering around 18% of the total fatty acids. For the first time, 47 intact TAGs were identified in the hemp oils using UPLC-HRMS. Among them, TAGs with fatty acid acyl chain 18:3/18:2/18:2 and 18:3/18:2/18:1 were the major ones, followed by TAGs with fatty acid acyl chain of 18:3/18:3/18:2, 18:2/18:2/16:0, 18:2/18:2/18:1, 18:3/18:2.18:0, 18:2/18:2/18:0, 18:2/18:1/18:1 and 18:3/18:2:16:0. Besides TAGs, low levels of terpenes, carotenoids and cannabidiolic acid were also detected in the oils. Moreover, the oils extracted from hemp by-products possessed a dose-dependent DPPH radical scavenging property and their potencies were in a similar range compared to other vegetable oils.

Analysis of Polar Lipids in Hemp (Cannabis sativa L.) By-Products by Ultra-High Performance Liquid Chromatography and High-Resolution Mass Spectrometry.

Polar lipids were extracted from residual biomass of hemp (Cannabis sativa L.) by-products with EtOH and partitioned into aqueous and chloroform fractions. The chloroform fractions were studied for their lipid composition using solid-phase extraction (SPE) followed by UHPLC/HRMS and NMR analyses. The 1H NMR and gravimetric yield of SPE indicated triacylglycerols covered ≥ 51.3% of the chloroform fraction of hemp seed hulls and hemp cake. UHPLC/HRMS analyses of remaining polar lipids led to the identification of nine diacylglycerols (DAGs), six lysophosphatidylcholines (LPCs), five lysophosphatidylethanolamines (LPEs), eight phosphatidylethanolamines (PEs), and thirteen phosphatidylcholines (PCs) for the first time from hemp seed hulls. The regiospecificity of fatty acyl substitutes in glycerol backbone of individual phospholipids were assigned by analyzing the diagnostic fragment ions and their intensities. The heat-map analysis suggested that DAG 18:2/18:2, 1-LPC 18:2, 1-LPE 18:2, PE 18:2/18:2, and PC 18:2/18:2 were the predominant molecules within their classes, supported by the fact that linoleic acid was the major fatty acid covering > 41.1% of the total fatty acids determined by GC-FID analysis. The 31P NMR analysis confirmed the identification of phospholipids and suggested PC covers ≥ 37.9% of the total phospholipid present in hemp by-products. HPLC purification led to the isolation of 1,2-dilinoleoylphosphatidylcholine and 1-palmitoyl-2-linoleoylphosphatidylcholine. These two major PCs further confirmed the UHPLC/HRMS finding.

Introduction of a Management Toolkit for Lewy Body Dementia: A Pilot Cluster-Randomized Trial.

BACKGROUND: Lewy body dementia, comprising both dementia with Lewy bodies and Parkinson's disease dementia, is challenging to manage because of a complex symptom profile and lack of clear evidence-based management guidelines. OBJECTIVES: We assessed the feasibility of undertaking a cluster randomized study of the introduction of an evidence-based management toolkit for Lewy body dementia, assessing the outcomes for patients and carers as secondary measures. METHODS: We randomized 23 memory/dementia, movement disorder, or nonspecialist secondary care services to the management toolkit or usual care. People with dementia with Lewy bodies or Parkinson's disease dementia underwent assessments of cognition, motor and neuropsychiatric symptoms, and global outcome at baseline and 3 and 6 months. Healthcare, personal and social care costs, and carer-related outcomes of carer stress, depression, and anxiety were also examined. RESULTS: A total of 131 participants were recruited (target 120), for whom 6-month data were available on 108 (83%). There was a benefit of being in the intervention arm for carers (reduced Zarit Burden Scale [P < 0.01], reduced depressive symptoms [P < 0.05]), who also reported less marked patient deterioration on the global outcome measure (P < 0.05). There were no significant differences in other outcomes or in costs between groups. CONCLUSIONS: The introduction of an evidence-based management toolkit for Lewy body dementia was feasible and associated with some benefits, especially for carers. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Uniformity of cardiac 123I-MIBG uptake on SPECT images in older adults with normal cognition and patients with dementia.

INTRODUCTION: Some studies report that assessing regional 123I-cardiac MIBG uptake can aid in the diagnosis of Lewy body disease, but others report heterogeneity in healthy controls. We aimed to evaluate regional cardiac MIBG uptake patterns in healthy older adults and patients with dementia. METHODS: 31 older adults with normal cognition, 15 Alzheimer's disease (AD), and 17 Dementia with Lewy bodies (DLB) patients were recruited. 5 individuals had previous myocardial infarction. Participants with sufficient cardiac uptake for regional SPECT analysis (29/31 controls, 15/15 AD, 5/17 DLB) had relative uptake pattern recorded. Controls were assessed for risk of future cardiovascular events using QRISK2, a validated online tool. RESULTS: In controls uptake was reduced in the inferior wall (85%), apex (23%), septum (15%), and lateral wall (8%). AD and DLB showed similar patterns to controls. Lung or liver interference was present in 61% of cases. Myocardial infarction cases showed regional reductions in uptake, but normal/borderline planar uptake. In controls, there was no relationship between cardiovascular risk score and uptake pattern. CONCLUSIONS: Significant variability of regional cardiac 123I-MIBG uptake is common in cases with normal planar cardiac uptake. Heterogeneity of regional uptake appears non-specific and unlikely to aid in the diagnosis of Lewy body disease.

Characterization of Shrimp Oil from Pandalus borealis by High Performance Liquid Chromatography and High Resolution Mass Spectrometry.

Northern shrimp (Pandalus borealis) oil, which is rich in omega-3 fatty acids, was recovered from the cooking water of shrimp processing facilities. The oil contains significant amounts of omega-3 fatty acids in triglyceride form, along with substantial long-chain monounsaturated fatty acids (MUFAs). It also features natural isomeric forms of astaxanthin, a nutritional carotenoid, which gives the oil a brilliant red color. As part of our efforts in developing value added products from waste streams of the seafood processing industry, we present in this paper a comprehensive characterization of the triacylglycerols (TAGs) and astaxanthin esters that predominate in the shrimp oil by using HPLC-HRMS and MS/MS, as well as 13C-NMR. This approach, in combination with FAME analysis, offers direct characterization of fatty acid molecules in their intact forms, including the distribution of regioisomers in TAGs. The information is important for the standardization and quality control, as well as for differentiation of composition features of shrimp oil, which could be sold as an ingredient in health supplements and functional foods.

Differentiating Prodromal Dementia with Lewy Bodies from Prodromal Alzheimer's Disease: A Pragmatic Review for Clinicians.

This pragmatic review synthesises the current understanding of prodromal dementia with Lewy bodies (pDLB) and prodromal Alzheimer's disease (pAD), including clinical presentations, neuropsychological profiles, neuropsychiatric symptoms, biomarkers, and indications for disease management. The core clinical features of dementia with Lewy bodies (DLB)-parkinsonism, complex visual hallucinations, cognitive fluctuations, and REM sleep behaviour disorder are common prodromal symptoms. Supportive clinical features of pDLB include severe neuroleptic sensitivity, as well as autonomic and neuropsychiatric symptoms. The neuropsychological profile in mild cognitive impairment attributable to Lewy body pathology (MCI-LB) tends to include impairment in visuospatial skills and executive functioning, distinguishing it from MCI due to AD, which typically presents with impairment in memory. pDLB may present with cognitive impairment, psychiatric symptoms, and/or recurrent episodes of delirium, indicating that it is not necessarily synonymous with MCI-LB. Imaging, fluid and other biomarkers may play a crucial role in differentiating pDLB from pAD. The current MCI-LB criteria recognise low dopamine transporter uptake using positron emission tomography or single photon emission computed tomography (SPECT), loss of REM atonia on polysomnography, and sympathetic cardiac denervation using meta-iodobenzylguanidine SPECT as indicative biomarkers with slowing of dominant frequency on EEG among others as supportive biomarkers. This review also highlights the emergence of fluid and skin-based biomarkers. There is little research evidence for the treatment of pDLB, but pharmacological and non-pharmacological treatments for DLB may be discussed with patients. Non-pharmacological interventions such as diet, exercise, and cognitive stimulation may provide benefit, while evaluation and management of contributing factors like medications and sleep disturbances are vital. There is a need to expand research across diverse patient populations to address existing disparities in clinical trial participation. In conclusion, an early and accurate diagnosis of pDLB or pAD presents an opportunity for tailored interventions, improved healthcare outcomes, and enhanced quality of life for patients and care partners.

Plant Growth-Promoting Rhizobacteria (PGPR) with Microbial Growth Broth Improve Biomass and Secondary Metabolite Accumulation of Cannabis sativa L.

Plant growth-promoting rhizobacteria (PGPR) are a sustainable crop production input; some show positive effects under laboratory conditions but poorly colonize host field-grown plants. Inoculating with PGPR in microbial growth medium (e.g., King's B) could overcome this. We evaluated cannabis plant (cv. CBD Kush) growth promotion by inoculating three PGPR (Bacillus sp., Mucilaginibacter sp., and Pseudomonas sp.) in King's B at vegetative and flower stages. At the vegetative stage, Mucilaginibacter sp. inoculation increased flower dry weight (24%), total CBD (11.1%), and THC (11.6%); Pseudomonas sp. increased stem (28%) dry matter, total CBD (7.2%), and THC (5.9%); and Bacillus sp. increased total THC by 4.8%. Inoculation with Mucilaginibacter sp. and Pseudomonas sp. at the flowering stage led to 23 and 18% increases in total terpene accumulation, respectively. Overall, vegetative inoculation with PGPR enhanced cannabis yield attributes and chemical profiles. Further research into PGPR inoculation onto cannabis and the subsequent level of colonization could provide key insights regarding PGPR-host interactions.

Development of LuxIA, a Cloud-Based AI Diabetic Retinopathy Screening Tool Using a Single Color Fundus Image.

Purpose: Diabetic retinopathy (DR) is the leading cause of vision impairment in working-age adults. Automated screening can increase DR detection at early stages at relatively low costs. We developed and evaluated a cloud-based screening tool that uses artificial intelligence (AI), the LuxIA algorithm, to detect DR from a single fundus image. Methods: Color fundus images that were previously graded by expert readers were collected from the Canarian Health Service (Retisalud) and used to train LuxIA, a deep-learning-based algorithm for the detection of more than mild DR. The algorithm was deployed in the Discovery cloud platform to evaluate each test set. Sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve were computed using a bootstrapping method to evaluate the algorithm performance and compared through different publicly available datasets. A usability test was performed to assess the integration into a clinical tool. Results: Three separate datasets, Messidor-2, APTOS, and a holdout set from Retisalud were evaluated. Mean sensitivity and specificity with 95% confidence intervals (CIs) reached for these three datasets were 0.901 (0.901-0.902) and 0.955 (0.955-0.956), 0.995 (0.995-0.995) and 0.821 (0.821-0.823), and 0.911 (0.907-0.912) and 0.880 (0.879-0.880), respectively. The usability test confirmed the successful integration of LuxIA into Discovery. Conclusions: Clinical data were used to train the deep-learning-based algorithm LuxIA to an expert-level performance. The whole process (image uploading and analysis) was integrated into the cloud-based platform Discovery, allowing more patients to have access to expert-level screening tools. Translational Relevance: Using the cloud-based LuxIA tool as part of a screening program may give diabetic patients greater access to specialist-level decisions, without the need for consultation.

Citrullinated and MMP-degraded vimentin is associated with chronic pulmonary diseases and genetic variants in PADI3/PADI4 and CFH in postmenopausal women.

Citrullinated vimentin has been linked to several chronic and autoimmune diseases, but how citrullinated vimentin is associated with disease prevalence and genetic variants in a clinical setting remains unknown. The aim of this study was to obtain a better understanding of the genetic variants and pathologies associated with citrullinated and MMP-degraded vimentin. Patient Registry data, serum samples and genotypes were collected for a total of 4369 Danish post-menopausal women enrolled in the Prospective Epidemiologic and Risk Factor study (PERF). Circulating citrullinated and MMP-degraded vimentin (VICM) was measured. Genome-wide association studies (GWAS) and phenome wide association studies (PheWAS) with levels of VICM were performed. High levels of VICM were significantly associated with the prevalence of chronic pulmonary diseases and death from respiratory and cardiovascular diseases (CVD). GWAS identified 33 single nucleotide polymorphisms (SNPs) with a significant association with VICM. These variants were in the peptidylarginine deiminase 3/4 (PADI3/PADI4) and Complement Factor H (CFH)/KCNT2 gene loci on chromosome 1. Serum levels of VICM, a marker of citrullinated and MMP-degraded vimentin, were associated with chronic pulmonary diseases and genetic variance in PADI3/PADI4 and CFH/ KCNT2. This points to the potential for VICM to be used as an activity marker of both citrullination and inflammation, identifying responders to targeted treatment and patients likely to experience disease progression.

Plasma metabolites distinguish dementia with Lewy bodies from Alzheimer's disease: a cross-sectional metabolomic analysis.

Background: In multifactorial diseases, alterations in the concentration of metabolites can identify novel pathological mechanisms at the intersection between genetic and environmental influences. This study aimed to profile the plasma metabolome of patients with dementia with Lewy bodies (DLB) and Alzheimer's disease (AD), two neurodegenerative disorders for which our understanding of the pathophysiology is incomplete. In the clinical setting, DLB is often mistaken for AD, highlighting a need for accurate diagnostic biomarkers. We therefore also aimed to determine the overlapping and differentiating metabolite patterns associated with each and establish whether identification of these patterns could be leveraged as biomarkers to support clinical diagnosis. Methods: A panel of 630 metabolites (Biocrates MxP Quant 500) and a further 232 metabolism indicators (biologically informative sums and ratios calculated from measured metabolites, each indicative for a specific pathway or synthesis; MetaboINDICATOR) were analyzed in plasma from patients with probable DLB (n = 15; age 77.6 ± 8.2 years), probable AD (n = 15; 76.1 ± 6.4 years), and age-matched cognitively healthy controls (HC; n = 15; 75.2 ± 6.9 years). Metabolites were quantified using a reversed-phase ultra-performance liquid chromatography column and triple-quadrupole mass spectrometer in multiple reaction monitoring (MRM) mode, or by using flow injection analysis in MRM mode. Data underwent multivariate (PCA analysis), univariate and receiving operator characteristic (ROC) analysis. Metabolite data were also correlated (Spearman r) with the collected clinical neuroimaging and protein biomarker data. Results: The PCA plot separated DLB, AD and HC groups (R2 = 0.518, Q2 = 0.348). Significant alterations in 17 detected metabolite parameters were identified (q ≤ 0.05), including neurotransmitters, amino acids and glycerophospholipids. Glutamine (Glu; q = 0.045) concentrations and indicators of sphingomyelin hydroxylation (q = 0.039) distinguished AD and DLB, and these significantly correlated with semi-quantitative measurement of cardiac sympathetic denervation. The most promising biomarker differentiating AD from DLB was Glu:lysophosphatidylcholine (lysoPC a 24:0) ratio (AUC = 0.92; 95%CI 0.809-0.996; sensitivity = 0.90; specificity = 0.90). Discussion: Several plasma metabolomic aberrations are shared by both DLB and AD, but a rise in plasma glutamine was specific to DLB. When measured against plasma lysoPC a C24:0, glutamine could differentiate DLB from AD, and the reproducibility of this biomarker should be investigated in larger cohorts.

Strategic identification of in vitro metabolites of 13-desmethyl spirolide C using liquid chromatography/high-resolution mass spectrometry.

A strategy to identify metabolites of a marine biotoxin, 13-desmethyl spirolide C, has been developed using liquid chromatography coupled to high-resolution mass spectrometry (LC/HRMS). Metabolites were generated in vitro through incubation with human liver microsomes. A list of metabolites was established by selecting precursor ions of a common fragment ion characteristic of the spirolide toxin which was known to contain a cyclic imine ring. Accurate mass measurements were subsequently used to confirm the molecular formula of each biotransformation product. Using this approach, a total of nine phase I metabolites was successfully identified with deviations of mass accuracy less than 2 ppm. The biotransformations observed included hydroxylation, dihydroxylation, oxidation of a quaternary methyl group to hydroxymethyl or carboxylic acid groups, dehydrogenation and hydroxylation, as well as demethylation and dihydroxylation reactions. In a second step, tandem mass spectrometry (MS/MS) was performed to elucidate structures of the metabolites. Using the unique fragment ions in the spectra, the structures of the three major metabolites, 13,19-didesmethyl-19-carboxy spirolide C, 13,19-didesmethyl-19-hydroxymethyl spirolide C and 13-desmethyl-17-hydroxy spirolide C, were assigned. Levels of 13-desmethyl spirolide C and its metabolites were monitored at selected time points over a 32-h incubation period with human liver microsomes. It was determined that 13,19-didesmethyl-19-carboxy spirolide C became the predominant metabolite after 2 h of incubation. The stability plot of 13-desmethyl spirolide C showed first-order kinetics for its metabolism and the intrinsic clearance was calculated to be 41 µL/min/mg, suggesting first-pass metabolism may contribute to limiting oral toxicity of 13-desmethyl spirolide C.

9,10-Dihydro-5-hydroxy-2,3,6-trimethoxyphenanthrene-1,4-dione: a new dihydrophenanthrene from commercial cannabis and its effect on zebrafish larval behaviour.

A new dihydrophenanthrene derivative namely 9,10-dihydro-5-hydroxy-2, 3,6-trimethoxyphenanthrene-1,4-dione (1) was isolated from commercial cannabis product together with 4,5-dihydroxy-2,3,6-trimethoxy-9,10-dihydrophenanthrene (2), 4-hydroxy-2,3,6,7-tetramethoxy-9,10-dihydrophenanthrene (3), combretastatin B-2 (4) and isocannbispiradienone (5). Structure elucidation of the isolated compounds were done based on the interpretation of the mass spectrometry (MS) and nuclear magnetic resonance (NMR) data. New dihydrophenanthrene derivative (1) was tested for its effect on zebrafish larval behaviour. Preliminary results suggested that the new dihydrophenanthrene derivative (1) exhibits similar effect on zebrafish larval behaviour as cannabidiol (CBD), a biologically active component of Cannabis.

Evaluation of the Uptake, Metabolism, and Secretion of Toxicants by Zebrafish Larvae.

Zebrafish larvae have classically been used as a high-throughput model with which to test both the bioactivity and toxicity of known and novel compounds, making them a promising whole organism New Approach Method in the context of the international momentum to eliminate animal testing. Larvae are generally exposed to the chemicals being tested in a static environment and the concentration-response patterns are calculated based on the initial bath concentrations of the compounds. This approach rarely takes into account the absorption, distribution, metabolism, and excretion of the compounds being tested, which can have a significant effect on the toxicokinetic profiles of the compounds and thus impact the predictive ability of the model. In this study, we have evaluated the toxicokinetic profile of 5 known toxicants, 3 phenolic compounds, along with thiabendazole and 3,4-dicholoronalanine, at 6, 8, 24, 72, and 120 h postfertilization in order to match the exposure timelines of a standard in vitro fish embryo toxicity test. It was revealed that in addition to bioaccumulation effects, the compounds were all actively metabolized and excreted by the larvae. Importantly, comparisons between the toxicants revealed that the patterns of uptake and metabolism were varied and could often partially explain the differences in their concentration-response patterns. The findings of this study are significant as they highlight the requirement for an assessment of the stability and toxicokinetic profile of chemicals tested using standard zebrafish larval toxicity assays in order to better understand and compare their toxicity profiles.

Implementation of personalised medicine policies in mental healthcare: results from a stated preference study in the UK.

BACKGROUND: Public support for the implementation of personalised medicine policies (PMPs) within routine care is important owing to the high financial costs involved and the potential for redirection of resources from other services. AIMS: We aimed to determine the attributes of a PMP most likely to elicit public support for implementation. We also aimed to determine whether such support differed between a depression PMP and one for cystic fibrosis. METHOD: In a discrete-choice experiment, paired vignettes illustrating both the current model of care (CMoC) and a hypothetical PMP for either depression or cystic fibrosis were presented to a representative sample of the UK public (n = 2804). Each vignette integrated varying attributes, including anticipated therapeutic benefit over CMoC, and the annual cost to the taxpayer. Respondents were invited to express their preference for either the PMP or CMoC within each pair. RESULTS: The financial cost was the most important attribute influencing public support for PMPs. Respondents favoured PMP implementation where it benefited a higher proportion of patients or was anticipated to be more effective than CMoC. A reduction in services for non-eligible patients reduced the likelihood of support for PMPs. Respondents were more willing to fund PMPs for cystic fibrosis than for depression. CONCLUSIONS: Cost is a significant factor in the public's support for PMPs, but essential caveats, such as protection for services available to PMP-ineligible patients, may also apply. Further research should explore the factors contributing to condition-specific nuances in public support for PMPs.

Can early phase cardiac [123I]mIBG images be used to diagnose Lewy body disease?

PURPOSE: Some studies have suggested that cardiac [123I]metaiodobenzylguanidine images obtained 15-20 min after tracer administration are as accurate for dementia with Lewy bodies (DLB) diagnosis as standard images acquired after a delay of 3-4 h; some suggest delayed imaging is preferable. We compare early and delayed heart-to-mediastinum ratios (HMR) in a well-characterised research dataset and make recommendations for clinical practice. METHODS: Images were acquired using a Siemens gamma camera with medium energy collimators. Early images were obtained at 20 min and delayed at 4 h (± 30) min. In total 167 pairs of images were reviewed: 30 controls, 39 people with dementia and 98 with mild cognitive impairment. HMR normal cutoff values derived from control data were ≥2.10 for early imaging and ≥1.85 for delayed. RESULTS: HMR tended to drop between early and delayed for abnormal images, but increase for normal images. Histograms of early and delayed HMR showed a slightly better separation of results into two groups for delayed imaging. Accuracy results were slightly higher for delayed imaging than early imaging (73 vs. 77%), sensitivity 63 vs. 65% and specificity 82 vs. 88%. However, this was not statistically significant - in total only 8/167 (5%) of scans changed designation between early and delayed imaging. CONCLUSION: We suggest that a delayed image could be acquired only if the early result is borderline. This removes the need for delayed imaging in about 70% of patients. Adopting this protocol in clinical practice would reduce the time most patients have to wait and could free up scanner time.

Distinguishing Lewy Body Dementia from Alzheimer's Disease using Machine Learning on Heterogeneous Data: A Feasibility Study.

Dementia with Lewy Bodies (DLB) is the second most common form of dementia, but diagnostic markers for DLB can be expensive and inaccessible, and many cases of DLB are undiagnosed. This work applies machine learning techniques to determine the feasibility of distinguishing DLB from Alzheimer's Disease (AD) using heterogeneous data features. The Repeated Incremental Pruning to Produce Error Reduction (RIPPER) algorithm was first applied using a Leave-One-Out Cross-Validation protocol to a dataset comprising DLB and AD cases. Then, interpretable association rule-based diagnostic classifiers were obtained for distinguishing DLB from AD. The various diagnostic classifiers generated by this process had high accuracy over the whole dataset (mean accuracy of 94%). The mean accuracy in classifying their out-of-sample case was 80.5%. Every classifier generated consisted of very simple structure, each using 1-2 classification rules and 1-3 data features. As a group, the classifiers were heterogeneous and used several different data features. In particular, some of the classifiers used very simple and inexpensive diagnostic features, yet with high diagnostic accuracy. This work suggests that opportunities may exist for incorporating accessible diagnostic assessments while improving diagnostic rate for DLB. Clinical Relevance- Simple and interpretable high-performing machine learning algorithms identified a variety of readily available clinical assessments for differential diagnosis of dementia offering the opportunities to incorporate various simple and inexpensive screening tests for DLB and addressing the problem of DLB underdiagnosis.

Molecular characterization of zebrafish embryogenesis via DNA microarrays and multiplatform time course metabolomics studies.

One of the greatest strengths of "-omics" technologies is their ability to capture a molecular snapshot of multiple cellular processes simultaneously. Transcriptomics, proteomics, and metabolomics have, individually, been used in wide-ranging studies involving cell lines, tissues, model organisms, and human subjects. Nonetheless, despite the fact that their power lies in the global acquisition of parallel data streams, these methods continue to be employed separately. We highlight work done to merge transcriptomics and metabolomics technologies to study zebrafish (Danio rerio) embryogenesis. We combine information from three bioanalytical platforms, that is, DNA microarrays, (1)H nuclear magnetic resonance ((1)H NMR), and mass spectrometry (MS)-based metabolomics, to identify and provide insights into the organism's developmental regulators. We apply a customized approach to the analysis of such time-ordered measurements to provide temporal profiles that depict the modulation of metabolites and gene transcription. Initially, the three data sets were analyzed individually but later they were fused to highlight the advantages gained through such an integrated approach. Unique challenges posed by fusion of such data are discussed given differences in the measurement error structures, the wide dynamic range for the molecular species, and the analytical platforms used to measure them (i.e., fluorescence ratios, NMR, and MS intensities). Our data analysis reveals that changes in transcript levels at specific developmental stages correlate with previously published data with over 90% accuracy. In addition, transcript profiles exhibited trends that were similar to the accumulation of metabolites over time. Profiles for metabolites such as choline-like compounds (Trimethylamine-N-oxide, phosphocholine, betaine), creatinine/creatine, and other metabolites involved in energy metabolism exhibited a steady increase from 15 hours post fertilization (hpf) to 48 hpf. Other metabolite and transcript profiles were transiently rising and then falling back to baseline. The "house keeping" metabolites such as branched chain amino acids exhibited a steady presence throughout embryogenesis. Although the transcript profiling corresponds to only 16 384 genes, a subset of the total number of genes in the zebrafish genome, we identified examples where gene transcript and metabolite profiles correlate with one another, reflective of a relationship between gene and metabolite regulation over the course of embryogenesis.