Ultraviolet emissions from the magnetic footprints of Io, Ganymede and Europa on Jupiter

Io leaves a magnetic footprint on Jupiter's upper atmosphere that appears as a spot of ultraviolet emission that remains fixed underneath Io as Jupiter rotates(1-3). The specific physical mechanisms responsible for generating those emissions are not well understood, but in general the spot seems to arise because of an electromagnetic interaction between Jupiter's magnetic field and the plasma surrounding Io, driving currents of around 1 million amperes down through Jupiter's ionosphere(4-6). The other galilean satellites may also leave footprints, and the presence or absence of such footprints should illuminate the underlying physical mechanism by revealing the strengths of the currents linking the satellites to Jupiter. Here we report persistent, faint, far-ultraviolet emission from the jovian footprints of Ganymede and Europa. We also show that Io's magnetic footprint extends well beyond the immediate vicinity of Io's flux-tube interaction with Jupiter, and much farther than predicted theoretically(4-6); the emission persists for several hours downstream. We infer from these data that Ganymede and Europa have persistent interactions with Jupiter's magnetic field despite their thin atmospheres.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62861/1/415997a.pd

Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects

Diagnostic Utility of Measuring Cerebral Atrophy in the Behavioral Variant of Frontotemporal Dementia and Association With Clinical Deterioration

Can widely available measures of atrophy on magnetic resonance imaging increase diagnostic certainty of underlying frontotemporal lobar degeneration (FTLD) and estimate clinical deterioration in the behavioral variant of frontotemporal dementia (bvFTD)? This diagnostic/prognostic study investigated the clinical utility of 5 validated visual atrophy scales (VAS) and the Magnetic Resonance Parkinsonism Index. When combined, VAS showed excellent diagnostic performance for differentiating between bvFTD with high and low confidence of FTLD and for the estimation of longitudinal clinical deterioration, whereas the Magnetic Resonance Parkinsonism Index was increased in bvFTD with underlying 4-repeat tauopathies. These findings suggest that, in bvFTD, VAS can be used to increase diagnostic certainty of underlying FTLD and estimate longitudinal clinical deterioration. This diagnostic/prognostic study assesses the utility of 6 visual atrophy scales and the Magnetic Resonance Parkinsonism Index in patients with behavioral variant frontotemporal dementia to distinguish those with high vs low confidence of frontotemporal lobar degeneration. The presence of atrophy on magnetic resonance imaging can support the diagnosis of the behavioral variant of frontotemporal dementia (bvFTD), but reproducible measurements are lacking. To assess the diagnostic and prognostic utility of 6 visual atrophy scales (VAS) and the Magnetic Resonance Parkinsonism Index (MRPI). In this diagnostic/prognostic study, data from 235 patients with bvFTD and 225 age- and magnetic resonance imaging-matched control individuals from 3 centers were collected from December 1, 1998, to September 30, 2019. One hundred twenty-one participants with bvFTD had high confidence of frontotemporal lobar degeneration (FTLD) (bvFTD-HC), and 19 had low confidence of FTLD (bvFTD-LC). Blinded clinicians applied 6 previously validated VAS, and the MRPI was calculated with a fully automated approach. Cortical thickness and subcortical volumes were also measured for comparison. Data were analyzed from February 1 to June 30, 2020. The main outcomes of this study were bvFTD-HC or a neuropathological diagnosis of 4-repeat (4R) tauopathy and the clinical deterioration rate (assessed by longitudinal measurements of Clinical Dementia Rating Sum of Boxes). Measures of cerebral atrophy included VAS scores, the bvFTD atrophy score (sum of VAS scores in orbitofrontal, anterior cingulate, anterior temporal, medial temporal lobe, and frontal insula regions), the MRPI, and other computerized quantifications of cortical and subcortical volumes. The areas under the receiver operating characteristic curve (AUROC) were calculated for the differentiation of participants with bvFTD-HC and bvFTD-LC and controls. Linear mixed models were used to evaluate the ability of atrophy measures to estimate longitudinal clinical deterioration. Of the 460 included participants, 296 (64.3%) were men, and the mean (SD) age was 62.6 (11.4) years. The accuracy of the bvFTD atrophy score for the differentiation of bvFTD-HC from controls (AUROC, 0.930; 95% CI, 0.903-0.957) and bvFTD-HC from bvFTD-LC (AUROC, 0.880; 95% CI, 0.787-0.972) was comparable to computerized measures (AUROC, 0.973 [95% CI, 0.954-0.993] and 0.898 [95% CI, 0.834-0.962], respectively). The MRPI was increased in patients with bvFTD and underlying 4R tauopathies compared with other FTLD subtypes (14.1 [2.0] vs 11.2 [2.6] points; P < .001). Higher bvFTD atrophy scores were associated with faster clinical deterioration in bvFTD (1.86-point change in Clinical Dementia Rating Sum of Boxes score per bvFTD atrophy score increase per year; 95% CI, 0.99-2.73; P < .001). Based on these study findings, in bvFTD, VAS increased the diagnostic certainty of underlying FTLD, and the MRPI showed potential for the detection of participants with underlying 4R tauopathies. These widely available measures of atrophy can also be useful to estimate longitudinal clinical deterioration

Exome sequencing identifies novel AD-associated genes

The genetic component of Alzheimer’s disease (AD) has been mainly assessed using Genome Wide Association Studies (GWAS), which do not capture the risk contributed by rare variants. Here, we compared the gene-based burden of rare damaging variants in exome sequencing data from 32,558 individuals —16,036 AD cases and 16,522 controls— in a two-stage analysis. Next to known genes TREM2, SORL1 and ABCA7, we observed a significant association of rare, predicted damaging variants in ATP8B4 and ABCA1 with AD risk, and a suggestive signal in ADAM10. Next to these genes, the rare variant burden in RIN3, CLU, ZCWPW1 and ACE highlighted these genes as potential driver genes in AD-GWAS loci. Rare damaging variants in these genes, and in particular loss-of-function variants, have a large effect on AD-risk, and they are enriched in early onset AD cases. The newly identified AD-associated genes provide additional evidence for a major role for APP-processing, Aβ-aggregation, lipid metabolism and microglial function in AD

Genome-wide meta-analysis for Alzheimer's disease cerebrospinal fluid biomarkers.

Amyloid-beta 42 (Aβ42) and phosphorylated tau (pTau) levels in cerebrospinal fluid (CSF) reflect core features of the pathogenesis of Alzheimer's disease (AD) more directly than clinical diagnosis. Initiated by the European Alzheimer &amp; Dementia Biobank (EADB), the largest collaborative effort on genetics underlying CSF biomarkers was established, including 31 cohorts with a total of 13,116 individuals (discovery n = 8074; replication n = 5042 individuals). Besides the APOE locus, novel associations with two other well-established AD risk loci were observed; CR1 was shown a locus for Aβ42 and BIN1 for pTau. GMNC and C16orf95 were further identified as loci for pTau, of which the latter is novel. Clustering methods exploring the influence of all known AD risk loci on the CSF protein levels, revealed 4 biological categories suggesting multiple Aβ42 and pTau related biological pathways involved in the etiology of AD. In functional follow-up analyses, GMNC and C16orf95 both associated with lateral ventricular volume, implying an overlap in genetic etiology for tau levels and brain ventricular volume

Genome-wide meta-analysis for Alzheimer's disease cerebrospinal fluid biomarkers

Altres ajuts: European Alzheimer DNA BioBank, EADB; EU Joint Programme, Neurodegenerative Disease Research (JPND); Neurodegeneration research program of Amsterdam Neuroscience; Stichting Alzheimer Nederland; Stichting VUmc fonds; Stichting Dioraphte; JPco-fuND FP-829-029 (ZonMW projectnumber 733051061); Dutch Federation of University Medical Centers; Dutch Government (from 2007-2011); JPND EADB grant (German Federal Ministry of Education and Research (BMBF) grant: 01ED1619A); German Research Foundation (DFG RA 1971/6-1, RA1971/7-1, RA 1971/8-1); Grifols SA; Fundación bancaria 'La Caixa'; Fundació ACE; CIBERNED; Fondo Europeo de Desarrollo Regional (FEDER-'Una manera de hacer Europa'); NIH (P30AG066444, P01AG003991); Alzheimer Research Foundation (SAO-FRA), The Research Foundation Flanders (FWO), and the University of Antwerp Research Fund. FK is supported by a BOF DOCPRO fellowship of the University of Antwerp Research Fund; Siemens Healthineers; Valdecilla Biobank (PT17/0015/0019); Academy of Finland (338182); German Center for Neurodegenerative Diseases (DZNE); German Federal Ministry of Education and Research (BMBF 01G10102, 01GI0420, 01GI0422, 01GI0423, 01GI0429, 01GI0431, 01GI0433, 04GI0434, 01GI0711); ZonMW (#73305095007); Health~Holland, Topsector Life Sciences & Health (PPP-allowance #LSHM20106); Hersenstichting; Edwin Bouw Fonds; Gieskes-Strijbisfonds; NWO Gravitation program BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology (NWO: 024.004.012); Swedish Alzheimer Foundation (AF-939988, AF-930582, AF-646061, AF-741361); Dementia Foundation (2020-04-13, 2021-04-17); Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement (ALF 716681); Swedish Research Council (11267, 825-2012-5041, 2013-8717, 2015-02830, 2017-00639, 2019-01096); Swedish Research Council for Health, Working Life and Welfare (2001-2646, 2001-2835, 2001-2849, 2003-0234, 2004-0150, 2005-0762, 2006-0020, 2008-1229, 2008-1210, 2012-1138, 2004-0145, 2006-0596, 2008-1111, 2010-0870, 2013-1202, 2013-2300, 2013-2496); Swedish Brain Power, Hjärnfonden, Sweden (FO2016-0214, FO2018-0214, FO2019-0163); Alzheimer's Association Zenith Award (ZEN-01-3151); Alzheimer's Association Stephanie B. Overstreet Scholars (IIRG-00-2159); Alzheimer's Association (IIRG-03-6168, IIRG-09-131338); Bank of Sweden Tercentenary Foundation; Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement (ALFGBG-81392, ALFGBG-771071); Swedish Alzheimer Foundation (AF-842471, AF-737641, AF-939825); Swedish Research Council (2019-02075); Swedish Research Council (2016-01590); BRAINSCAPES: A Roadmap from Neurogenetics to Neurobiology (024.004.012); Swedish Research Council (2018-02532); Swedish State Support for Clinical Research (ALFGBG-720931); Alzheimer Drug Discovery Foundation (ADDF), USA (201809-2016862); UK Dementia Research Institute at UCL; Swedish Research Council (#2017-00915); Alzheimer Drug Discovery Foundation (ADDF), USA (#RDAPB-201809-2016615); Swedish Alzheimer Foundation (#AF-742881); Hjärnfonden, Sweden (#FO2017-0243); Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986); National Institute of Health (NIH), USA, (#1R01AG068398-01); Alzheimer's Association 2021 Zenith Award (ZEN-21-848495); National Institutes of Health (R01AG044546, R01AG064877, RF1AG053303, R01AG058501, U01AG058922, RF1AG058501, R01AG064614); Chuck Zuckerberg Initiative (CZI).Amyloid-beta 42 (Aβ42) and phosphorylated tau (pTau) levels in cerebrospinal fluid (CSF) reflect core features of the pathogenesis of Alzheimer's disease (AD) more directly than clinical diagnosis. Initiated by the European Alzheimer & Dementia Biobank (EADB), the largest collaborative effort on genetics underlying CSF biomarkers was established, including 31 cohorts with a total of 13,116 individuals (discovery n = 8074; replication n = 5042 individuals). Besides the APOE locus, novel associations with two other well-established AD risk loci were observed; CR1 was shown a locus for Aβ42 and BIN1 for pTau. GMNC and C16orf95 were further identified as loci for pTau, of which the latter is novel. Clustering methods exploring the influence of all known AD risk loci on the CSF protein levels, revealed 4 biological categories suggesting multiple Aβ42 and pTau related biological pathways involved in the etiology of AD. In functional follow-up analyses, GMNC and C16orf95 both associated with lateral ventricular volume, implying an overlap in genetic etiology for tau levels and brain ventricular volume

Improved risk stratification of patients with atrial fibrillation: an integrated GARFIELD-AF tool for the prediction of mortality, stroke and bleed in patients with and without anticoagulation.

OBJECTIVES: To provide an accurate, web-based tool for stratifying patients with atrial fibrillation to facilitate decisions on the potential benefits/risks of anticoagulation, based on mortality, stroke and bleeding risks. DESIGN: The new tool was developed, using stepwise regression, for all and then applied to lower risk patients. C-statistics were compared with CHA2DS2-VASc using 30-fold cross-validation to control for overfitting. External validation was undertaken in an independent dataset, Outcome Registry for Better Informed Treatment of Atrial Fibrillation (ORBIT-AF). PARTICIPANTS: Data from 39 898 patients enrolled in the prospective GARFIELD-AF registry provided the basis for deriving and validating an integrated risk tool to predict stroke risk, mortality and bleeding risk. RESULTS: The discriminatory value of the GARFIELD-AF risk model was superior to CHA2DS2-VASc for patients with or without anticoagulation. C-statistics (95% CI) for all-cause mortality, ischaemic stroke/systemic embolism and haemorrhagic stroke/major bleeding (treated patients) were: 0.77 (0.76 to 0.78), 0.69 (0.67 to 0.71) and 0.66 (0.62 to 0.69), respectively, for the GARFIELD-AF risk models, and 0.66 (0.64-0.67), 0.64 (0.61-0.66) and 0.64 (0.61-0.68), respectively, for CHA2DS2-VASc (or HAS-BLED for bleeding). In very low to low risk patients (CHA2DS2-VASc 0 or 1 (men) and 1 or 2 (women)), the CHA2DS2-VASc and HAS-BLED (for bleeding) scores offered weak discriminatory value for mortality, stroke/systemic embolism and major bleeding. C-statistics for the GARFIELD-AF risk tool were 0.69 (0.64 to 0.75), 0.65 (0.56 to 0.73) and 0.60 (0.47 to 0.73) for each end point, respectively, versus 0.50 (0.45 to 0.55), 0.59 (0.50 to 0.67) and 0.55 (0.53 to 0.56) for CHA2DS2-VASc (or HAS-BLED for bleeding). Upon validation in the ORBIT-AF population, C-statistics showed that the GARFIELD-AF risk tool was effective for predicting 1-year all-cause mortality using the full and simplified model for all-cause mortality: C-statistics 0.75 (0.73 to 0.77) and 0.75 (0.73 to 0.77), respectively, and for predicting for any stroke or systemic embolism over 1 year, C-statistics 0.68 (0.62 to 0.74). CONCLUSIONS: Performance of the GARFIELD-AF risk tool was superior to CHA2DS2-VASc in predicting stroke and mortality and superior to HAS-BLED for bleeding, overall and in lower risk patients. The GARFIELD-AF tool has the potential for incorporation in routine electronic systems, and for the first time, permits simultaneous evaluation of ischaemic stroke, mortality and bleeding risks. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier for GARFIELD-AF (NCT01090362) and for ORBIT-AF (NCT01165710)

Two-year outcomes of patients with newly diagnosed atrial fibrillation: results from GARFIELD-AF.

AIMS: The relationship between outcomes and time after diagnosis for patients with non-valvular atrial fibrillation (NVAF) is poorly defined, especially beyond the first year. METHODS AND RESULTS: GARFIELD-AF is an ongoing, global observational study of adults with newly diagnosed NVAF. Two-year outcomes of 17 162 patients prospectively enrolled in GARFIELD-AF were analysed in light of baseline characteristics, risk profiles for stroke/systemic embolism (SE), and antithrombotic therapy. The mean (standard deviation) age was 69.8 (11.4) years, 43.8% were women, and the mean CHA2DS2-VASc score was 3.3 (1.6); 60.8% of patients were prescribed anticoagulant therapy with/without antiplatelet (AP) therapy, 27.4% AP monotherapy, and 11.8% no antithrombotic therapy. At 2-year follow-up, all-cause mortality, stroke/SE, and major bleeding had occurred at a rate (95% confidence interval) of 3.83 (3.62; 4.05), 1.25 (1.13; 1.38), and 0.70 (0.62; 0.81) per 100 person-years, respectively. Rates for all three major events were highest during the first 4 months. Congestive heart failure, acute coronary syndromes, sudden/unwitnessed death, malignancy, respiratory failure, and infection/sepsis accounted for 65% of all known causes of death and strokes for <10%. Anticoagulant treatment was associated with a 35% lower risk of death. CONCLUSION: The most frequent of the three major outcome measures was death, whose most common causes are not known to be significantly influenced by anticoagulation. This suggests that a more comprehensive approach to the management of NVAF may be needed to improve outcome. This could include, in addition to anticoagulation, interventions targeting modifiable, cause-specific risk factors for death. CLINICAL TRIAL REGISTRATION: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

Why Are Outcomes Different for Registry Patients Enrolled Prospectively and Retrospectively? Insights from the Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF).

Background: Retrospective and prospective observational studies are designed to reflect real-world evidence on clinical practice, but can yield conflicting results. The GARFIELD-AF Registry includes both methods of enrolment and allows analysis of differences in patient characteristics and outcomes that may result. Methods and Results: Patients with atrial fibrillation (AF) and ≥1 risk factor for stroke at diagnosis of AF were recruited either retrospectively (n = 5069) or prospectively (n = 5501) from 19 countries and then followed prospectively. The retrospectively enrolled cohort comprised patients with established AF (for a least 6, and up to 24 months before enrolment), who were identified retrospectively (and baseline and partial follow-up data were collected from the emedical records) and then followed prospectively between 0-18 months (such that the total time of follow-up was 24 months; data collection Dec-2009 and Oct-2010). In the prospectively enrolled cohort, patients with newly diagnosed AF (≤6 weeks after diagnosis) were recruited between Mar-2010 and Oct-2011 and were followed for 24 months after enrolment. Differences between the cohorts were observed in clinical characteristics, including type of AF, stroke prevention strategies, and event rates. More patients in the retrospectively identified cohort received vitamin K antagonists (62.1% vs. 53.2%) and fewer received non-vitamin K oral anticoagulants (1.8% vs . 4.2%). All-cause mortality rates per 100 person-years during the prospective follow-up (starting the first study visit up to 1 year) were significantly lower in the retrospective than prospectively identified cohort (3.04 [95% CI 2.51 to 3.67] vs . 4.05 [95% CI 3.53 to 4.63]; p = 0.016). Conclusions: Interpretations of data from registries that aim to evaluate the characteristics and outcomes of patients with AF must take account of differences in registry design and the impact of recall bias and survivorship bias that is incurred with retrospective enrolment. Clinical Trial Registration: - URL: http://www.clinicaltrials.gov . Unique identifier for GARFIELD-AF (NCT01090362)