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Apolipoprotein E (APOE) E4 is the main genetic risk factor for Alzheimer’s disease (AD). Due to the consistent association, there is interest as to whether E4 influences the risk of other neurodegenerative diseases. Further, there is a constant search for other genetic biomarkers contributing to these phenotypes, such as microtubule-associated protein tau (MAPT) haplotypes. Here, participants from the Ontario Neurodegenerative Disease Research Initiative were genotyped to investigate whether the APOE E4 allele or MAPT H1 haplotype are associated with five neurodegenerative diseases: (1) AD and mild cognitive impairment (MCI), (2) amyotrophic lateral sclerosis, (3) frontotemporal dementia (FTD), (4) Parkinson’s disease, and (5) vascular cognitive impairment.
Genotypes were defined for their respective APOE allele and MAPT haplotype calls for each participant, and logistic regression analyses were performed to identify the associations with the presentations of neurodegenerative diseases.
Our work confirmed the association of the E4 allele with a dose-dependent increased presentation of AD, and an association between the E4 allele alone and MCI; however, the other four diseases were not associated with E4. Further, the APOE E2 allele was associated with decreased presentation of both AD and MCI. No associations were identified between MAPT haplotype and the neurodegenerative disease cohorts; but following subtyping of the FTD cohort, the H1 haplotype was significantly associated with progressive supranuclear palsy.
This is the first study to concurrently analyze the association of APOE isoforms and MAPT haplotypes with five neurodegenerative diseases using consistent enrollment criteria and broad phenotypic analysis.
While some single-celled intestinal parasites are direct causes of diarrhoea and other types of intestinal pathology, the impact of other gut micro-eukaryotes on human health remains elusive. The fact that some common luminal intestinal parasitic protists (CLIPPs) have lately been found more often in healthy than in diseased individuals has fuelled the hypothesis that some parasites might in fact be protective against disease. To this end, the use of new DNA technologies has helped us investigate trans-kingdom relationships in the gut. However, research into these relationships is currently hampered by the limited data available on the genetic diversity within the CLIPPs genera, which results in limited efficacy of publicly available DNA sequence databases for taxonomic annotation of sequences belonging to the eukaryotic component of the gut microbiota. In this paper, I give a brief overview of the status on CLIPPs in human health and disease and challenges related to the mapping of intestinal eukaryotic diversity of the human gut.
Amoebae are single-celled parasites frequently colonizing human gut. However, few molecular tools are available for accurate identification. Here, we evaluated a panel of polymerase chain reactions (PCRs) targeting Entamoeba histolytica, Entamoeba dispar, Entamoeba coli, Entamoeba hartmanni, Entamoeba polecki, Endolimax nana and Iodamoeba bütschlii. Thirty-six faecal samples (18 containing at least one amoeba species by microscopy and 18 microscopy negative for amoebae) were tested. Real-time PCRs were used for detection and differentiation of E. histolytica and E. dispar. Conventional PCR with Sanger sequencing were applied for detection and differentiation of E. coli, E. hartmanni, E. polecki, E. nana and I. bütschlii. All microscopy results were confirmed by DNA-based methods. However, more samples were positive for single and mixed amoebic species by DNA-based assays than by microscopy (22 vs 18 and 7 vs 1, respectively). DNA sequencing allowed identification of E. coli subtypes (ST1 and ST2), showed low intra-specific variation within E. hartmanni, identified two phylogenetically distinct groups within E. nana, and identified Iodamoeba at the ribosomal lineage level. Taking into account the high intra-genetic diversity within some of the species at the small subunit (SSU) rRNA gene level, amplification of SSU rRNA genes with subsequent sequencing represents a useful method for detecting, differentiating and subtyping intestinal amoebae.
Background: Amyotrophic lateral sclerosis (ALS) is a progressive motor neuron disease resulting in muscle weakness, dysarthria and dysphagia, and ultimately respiratory failure leading to death. Half of the ALS patients survive less than 3 years, and 80% of the patients survive less than 5 years. Riluzole is the only approved medication in Canada with randomized controlled clinical trial evidence to slow the progression of ALS, albeit only to a modest degree. The Canadian Neuromuscular Disease Registry (CNDR) collects data on over 140 different neuromuscular diseases including ALS across ten academic institutions and 28 clinics including ten multidisciplinary ALS clinics. Methods: In this study, CNDR registry data were analyzed to examine potential differences in ALS care among provinces in time to diagnosis, riluzole and feeding tube use. Results: Significant differences were found among provinces, in time to diagnosis from symptom onset, in the use of riluzole and in feeding tube use. Conclusions: Future investigations should be undertaken to identify factors contributing to such differences, and to propose potential interventions to address the provincial differences reported.
Background: Non-invasive ventilation (NIV) improves quality of life and survival in patients with amyotrophic lateral sclerosis (ALS) and respiratory symptoms. Little is known about the patterns of NIV use over time and the impact of NIV on end-of-life decision-making in ALS. Objective: This study assessed the pattern of NIV use over the course of the disease and the timing of end-of-life discussions in people living with ALS. Method: A retrospective single-center cohort study was performed at London Health Sciences Centre. Daily NIV duration of use was evaluated at 3-month intervals. The timing of diagnosis, NIV initiation, discussions relating to do-not-attempt-resuscitation (DNAR) and death were examined. Results: In total, 48 patients were included in the analysis. Duration of NIV use increased over time, and tolerance to NIV was observed to be better than expected in patients with bulbar-onset ALS. There was a high degree of variability in the timing of end-of-life discussions in patients with ALS (356±451 days from diagnosis). In this cohort, there was a strong association between the timing of discussions regarding code status and establishment of a DNAR order (r2=0.93). Conclusion: This retrospective cohort study suggests that the use of NIV in ALS increases over time and that there remains a great deal of variability in the timing of end-of-life discussions in people living with ALS. Future prospective studies exploring the use NIV over the disease trajectory and how NIV affects end-of-life decision-making in people with ALS are needed.
Two- and three-dimensional avalanche dynamics models are being increasingly used in hazard-mitigation studies. These models can provide improved and more accurate results for hazard mapping than the simple one-dimensional models presently used in practice. However, two- and three-dimensional models generate an extensive amount of output data, making the interpretation of simulation results more difficult. To perform a simulation in three-dimensional terrain, numerical models require a digital elevation model, specification of avalanche release areas (spatial extent and volume), selection of solution methods, finding an adequate calculation resolution and, finally, the choice of friction parameters. In this paper, the importance and difficulty of correctly setting up and analysing the results of a numerical avalanche dynamics simulation is discussed. We apply the two-dimensional simulation program RAMMS to the 1968 extreme avalanche event In den Arelen. We show the effect of model input variations on simulation results and the dangers and complexities in their interpretation.
To investigate the effects of steel snow-supporting structures on the thermal regime of the ground in typical Alpine permafrost avalanche terrain, ground temperatures were monitored and simulated on an avalanche slope equipped with experimental snow-supporting structures. Temperature measurements were effected in lm boreholes above and below a row of snow nets and in two 18 m boreholes located between the structures and in a reference location. The presence of the structures can induce modifications of the temporal and spatial snow-cover distribution, leading to differences in active-layer temperatures just below and above the structures: snow accumulates above the supporting surface of the structures, and frequently there is less snow below. The long-term thermal effect of these variations near a snow net was simulated using a two-dimensional finite-element program based on heat conduction. The material and thermal characteristics of the ground simulated are obtained from temperature measurements and from borehole-core information.
Digital elevation models (DEMs), represent the three-dimensional terrain and are the basic input for numerical snow avalanche dynamics simulations. DEMs can be acquired using topographic maps or remote-sensing technologies, such as photogrammetry or lidar. Depending on the acquisition technique, different spatial resolutions and qualities are achieved. However, there is a lack of studies that investigate the sensitivity of snow avalanche simulation algorithms to the quality and resolution of DEMs. Here, we perform calculations using the numerical avalance dynamics model RAMMS, varying the quality and spatial resolution of the underlying DEMs, while holding the simulation parameters constant. We study both channelized and open-terrain avalanche tracks with variable roughness. To quantify the variance of these simulations, we use well-documented large-scale avalanche events from Davos, Switzerland (winter 2007/08), and from our large-scale avalanche test site, Vallée de la Sionne (winter 2005/06).We find that the DEM resolution and quality is critical for modeled flow paths, run-out distances, deposits, velocities and impact pressures. Although a spatial resolution of ∼25m is sufficient for large-scale avalanche modeling, the DEM datasets must be checked carefully for anomalies and artifacts before using them for dynamics calculations.