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55 result(s) for "Marsh, Laura F"
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Use of the TELE-ASD-PEDS for Autism Evaluations in Response to COVID-19: Preliminary Outcomes and Clinician Acceptability
The COVID-19 pandemic has caused unprecedented disruptions to healthcare, including direct impacts on service delivery related to autism spectrum disorder (ASD). Caregiver-mediated tele-assessment offers an opportunity to continue services while adhering to social distancing guidelines. The present study describes a model of tele-assessment for ASD in young children, implemented in direct response to disruptions in care caused by the COVID-19 pandemic. We present preliminary data on the outcomes and provider perceptions of tele-assessments, together with several lessons learned during the period of initial implementation.
Wolves
\"They run in packs, stalk their prey, and howl at the moon. And no matter where you are--they're always lurking somewhere nearby. Wolves, the predatory puppy dogs of the wild, are feared and loved by people everywhere. But are they misunderstood?\"--Amazon.com.
Comparative neurofilament light chain trajectories in CSF and plasma in autosomal dominant Alzheimer’s disease
Disease-modifying therapies for Alzheimer’s disease (AD) are likely to be most beneficial when initiated in the presymptomatic phase. To track the benefit of such interventions, fluid biomarkers are of great importance, with neurofilament light chain protein (NfL) showing promise for monitoring neurodegeneration and predicting cognitive outcomes. Here, we update and complement previous findings from the Dominantly Inherited Alzheimer Network Observational Study by using matched cross-sectional and longitudinal cerebrospinal fluid (CSF) and plasma samples from 567 individuals, allowing timely comparative analyses of CSF and blood trajectories across the entire disease spectrum. CSF and plasma trajectories were similar at presymptomatic stages, discriminating mutation carriers from non-carrier controls 10-20 years before the estimated onset of clinical symptoms, depending on the statistical model used. However, after symptom onset the rate of change in CSF NfL continued to increase steadily, whereas the rate of change in plasma NfL leveled off. Both plasma and CSF NfL changes were associated with grey-matter atrophy, but not with Aβ-PET changes, supporting a temporal decoupling of Aβ deposition and neurodegeneration. These observations support NfL in both CSF and blood as an early marker of neurodegeneration but suggest that NfL measured in the CSF may be better suited for monitoring clinical trial outcomes in symptomatic AD patients. This study supports neurofilament light chain protein (NfL) in both cerebrospinal fluid (CSF) and blood as an early marker of neurodegeneration in Alzheimer’s disease but suggests that NfL in CSF may be better suited than blood for monitoring clinical trial outcomes in symptomatic patients.
Comparison of tau spread in people with Down syndrome versus autosomal-dominant Alzheimer's disease: a cross-sectional study
In people with genetic forms of Alzheimer's disease, such as in Down syndrome and autosomal-dominant Alzheimer's disease, pathological changes specific to Alzheimer's disease (ie, accumulation of amyloid and tau) occur in the brain at a young age, when comorbidities related to ageing are not present. Studies including these cohorts could, therefore, improve our understanding of the early pathogenesis of Alzheimer's disease and be useful when designing preventive interventions targeted at disease pathology or when planning clinical trials. We compared the magnitude, spatial extent, and temporal ordering of tau spread in people with Down syndrome and autosomal-dominant Alzheimer's disease. In this cross-sectional observational study, we included participants (aged ≥25 years) from two cohort studies. First, we collected data from the Dominantly Inherited Alzheimer's Network studies (DIAN-OBS and DIAN-TU), which include carriers of autosomal-dominant Alzheimer's disease genetic mutations and non-carrier familial controls recruited in Australia, Europe, and the USA between 2008 and 2022. Second, we collected data from the Alzheimer Biomarkers Consortium–Down Syndrome study, which includes people with Down syndrome and sibling controls recruited from the UK and USA between 2015 and 2021. Controls from the two studies were combined into a single group of familial controls. All participants had completed structural MRI and tau PET (18F-flortaucipir) imaging. We applied Gaussian mixture modelling to identify regions of high tau PET burden and regions with the earliest changes in tau binding for each cohort separately. We estimated regional tau PET burden as a function of cortical amyloid burden for both cohorts. Finally, we compared the temporal pattern of tau PET burden relative to that of amyloid. We included 137 people with Down syndrome (mean age 38·5 years [SD 8·2], 74 [54%] male, and 63 [46%] female), 49 individuals with autosomal-dominant Alzheimer's disease (mean age 43·9 years [11·2], 22 [45%] male, and 27 [55%] female), and 85 familial controls, pooled from across both studies (mean age 41·5 years [12·1], 28 [33%] male, and 57 [67%] female), who satisfied the PET quality-control procedure for tau-PET imaging processing. 134 (98%) people with Down syndrome, 44 (90%) with autosomal-dominant Alzheimer's disease, and 77 (91%) controls also completed an amyloid PET scan within 3 years of tau PET imaging. Spatially, tau PET burden was observed most frequently in subcortical and medial temporal regions in people with Down syndrome, and within the medial temporal lobe in people with autosomal-dominant Alzheimer's disease. Across the brain, people with Down syndrome had greater concentrations of tau for a given level of amyloid compared with people with autosomal-dominant Alzheimer's disease. Temporally, increases in tau were more strongly associated with increases in amyloid for people with Down syndrome compared with autosomal-dominant Alzheimer's disease. Although the general progression of amyloid followed by tau is similar for people Down syndrome and people with autosomal-dominant Alzheimer's disease, we found subtle differences in the spatial distribution, timing, and magnitude of the tau burden between these two cohorts. These differences might have important implications; differences in the temporal pattern of tau accumulation might influence the timing of drug administration in clinical trials, whereas differences in the spatial pattern and magnitude of tau burden might affect disease progression. None.
Whales
Introduces sperm whales, including their different body parts, how they travel in groups, what they eat, and how they care for their young.
Biodiversity impacts of the 2019–2020 Australian megafires
With large wildfires becoming more frequent 1 , 2 , we must rapidly learn how megafires impact biodiversity to prioritize mitigation and improve policy. A key challenge is to discover how interactions among fire-regime components, drought and land tenure shape wildfire impacts. The globally unprecedented 3 , 4 2019–2020 Australian megafires burnt more than 10 million hectares 5 , prompting major investment in biodiversity monitoring. Collated data include responses of more than 2,000 taxa, providing an unparalleled opportunity to quantify how megafires affect biodiversity. We reveal that the largest effects on plants and animals were in areas with frequent or recent past fires and within extensively burnt areas. Areas burnt at high severity, outside protected areas or under extreme drought also had larger effects. The effects included declines and increases after fire, with the largest responses in rainforests and by mammals. Our results implicate species interactions, dispersal and extent of in situ survival as mechanisms underlying fire responses. Building wildfire resilience into these ecosystems depends on reducing fire recurrence, including with rapid wildfire suppression in areas frequently burnt. Defending wet ecosystems, expanding protected areas and considering localized drought could also contribute. While these countermeasures can help mitigate the impacts of more frequent megafires, reversing anthropogenic climate change remains the urgent broad-scale solution. Data collected from more than 2,000 taxa provide an unparalleled opportunity to quantify how extreme wildfires affect biodiversity, revealing that the largest effects on plants and animals were in areas with frequent or recent past fires and within extensively burnt areas.
γ-Secretase activity, clinical features, and biomarkers of autosomal dominant Alzheimer's disease: cross-sectional and longitudinal analysis of the Dominantly Inherited Alzheimer Network observational study (DIAN-OBS)
Genetic variants that cause autosomal dominant Alzheimer's disease are highly penetrant but vary substantially regarding age at symptom onset (AAO), rates of cognitive decline, and biomarker changes. Most pathogenic variants that cause autosomal dominant Alzheimer's disease are in presenilin 1 (PSEN1), which encodes the catalytic core of γ-secretase, an enzyme complex that is crucial in production of amyloid β. We aimed to investigate whether the heterogeneity in AAO and biomarker trajectories in carriers of PSEN1 pathogenic variants could be predicted on the basis of the effects of individual PSEN1 variants on γ-secretase activity and amyloid β production. For this cross-sectional and longitudinal analysis, we used data from participants enrolled in the Dominantly Inherited Alzheimer Network observational study (DIAN-OBS) via the DIAN-OBS data freeze version 15 (data collected between Feb 29, 2008, and June 30, 2020). The data freeze included data from 20 study sites in research institutions, universities, hospitals, and clinics across Europe, North and South America, Asia, and Oceania. We included individuals with PSEN1 pathogenic variants for whom relevant genetic, clinical, imaging, and CSF data were available. PSEN1 pathogenic variants were characterised via genetically modified PSEN1 and PSEN2 double-knockout human embryonic kidney 293T cells and immunoassays for Aβ37, Aβ38, Aβ40, Aβ42, and Aβ43. A summary measure of γ-secretase activity (γ-secretase composite [GSC]) was calculated for each variant and compared with clinical history-derived AAO using correlation analyses. We used linear mixed-effect models to assess associations between GSC scores and multimodal-biomarker and clinical data from DIAN-OBS. We used separate models to assess associations with Clinical Dementia Rating Sum of Boxes (CDR-SB), Mini-Mental State Examination (MMSE), and Wechsler Memory Scale-Revised (WMS-R) Logical Memory Delayed Recall, [11C]Pittsburgh compound B (PiB)–PET and brain glucose metabolism using [18F] fluorodeoxyglucose (FDG)–PET, CSF Aβ42-to-Aβ40 ratio (Aβ42/40), CSF log10 (phosphorylated tau 181), CSF log10 (phosphorylated tau 217), and MRI-based hippocampal volume. Data were included from 190 people carrying PSEN1 pathogenic variants, among whom median age was 39·0 years (IQR 32·0 to 48·0) and AAO was 44·5 years (40·6 to 51·4). 109 (57%) of 190 carriers were female and 81 (43%) were male. Lower GSC values (ie, lower γ-secretase activity than wild-type PSEN1) were associated with earlier AAO (r=0·58; p<0·0001). GSC was associated with MMSE (β=0·08, SE 0·03; p=0·0043), CDR-SB (–0·05, 0·02; p=0·0027), and WMS-R Logical Memory Delayed Recall scores (0·09, 0·02; p=0·0006). Lower GSC values were associated with faster increase in PiB–PET signal (p=0·0054), more rapid decreases in hippocampal volume (4·19, 0·77; p<0·0001), MMSE (0·02, 0·01; p=0·0020), and WMS-R Logical Memory Delayed Recall (0·004, 0·001; p=0·0003). Our findings suggest that clinical heterogeneity in people with autosomal dominant Alzheimer's disease can be at least partly explained by different effects of PSEN1 variants on γ-secretase activity and amyloid β production. They support targeting γ-secretase as a therapeutic approach and suggest that cell-based models could be used to improve prediction of symptom onset. US National Institute on Aging, Alzheimer's Association, German Center for Neurodegenerative Diseases, Raul Carrea Institute for Neurological Research, Japan Agency for Medical Research and Development, Korea Health Industry Development Institute, South Korean Ministry of Health and Welfare, South Korean Ministry of Science and ICT, and Spanish Institute of Health Carlos III.