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A pandemic of Salmonella enterica serotype Enteritidis emerged in the 1980s due to contaminated poultry products. How Salmonella Enteritidis rapidly swept through continents remains a historical puzzle as the pathogen continues to cause outbreaks and poultry supply becomes globalized. We hypothesize that international trade of infected breeding stocks causes global spread of the pathogen. By integrating over 30,000 Salmonella Enteritidis genomes from 98 countries during 1949–2020 and international trade of live poultry from the 1980s to the late 2010s, we present multifaceted evidence that converges on a high likelihood, global scale, and extended protraction of Salmonella Enteritidis dissemination via centralized sourcing and international trade of breeding stocks. We discovered recent, genetically near-identical isolates from domestically raised poultry in North and South America. We obtained phylodynamic characteristics of global Salmonella Enteritidis populations that lend spatiotemporal support for its dispersal from centralized origins during the pandemic. We identified concordant patterns of international trade of breeding stocks and quantitatively established a driving role of the trade in the geographic dispersal of Salmonella Enteritidis, suggesting that the centralized origins were infected breeding stocks. Here we demonstrate the value of integrative and hypothesis-driven data mining in unravelling otherwise difficult-to-probe pathogen dissemination from hidden origins. Salmonella enterica serotype Enteritidis is a pathogen of poultry that can cause outbreaks in humans. Here the authors use genomic and trade data to investigate a pandemic in the 1980s, finding evidence that international trade of breeding stocks led to global spread of the pathogen.

Similar to most chronic diseases, Alzheimer's disease (AD) develops slowly from a preclinical phase into a fully expressed clinical syndrome. We aimed to use longitudinal data to calculate the rates of amyloid β (Aβ) deposition, cerebral atrophy, and cognitive decline. In this prospective cohort study, healthy controls, patients with mild cognitive impairment (MCI), and patients with AD were assessed at enrolment and every 18 months. At every visit, participants underwent neuropsychological examination, MRI, and a carbon-11-labelled Pittsburgh compound B (11C-PiB) PET scan. We included participants with three or more 11C-PiB PET follow-up assessments. Aβ burden was expressed as 11C-PiB standardised uptake value ratio (SUVR) with the cerebellar cortex as reference region. An SUVR of 1·5 was used to discriminate high from low Aβ burdens. The slope of the regression plots over 3–5 years was used to estimate rates of change for Aβ deposition, MRI volumetrics, and cognition. We included those participants with a positive rate of Aβ deposition to calculate the trajectory of each variable over time. 200 participants (145 healthy controls, 36 participants with MCI, and 19 participants with AD) were assessed at enrolment and every 18 months for a mean follow-up of 3·8 (95% CI CI 3·6–3·9) years. At baseline, significantly higher Aβ burdens were noted in patients with AD (2·27, SD 0·43) and those with MCI (1·94, 0·64) than in healthy controls (1·38, 0·39). At follow-up, 163 (82%) of the 200 participants showed positive rates of Aβ accumulation. Aβ deposition was estimated to take 19·2 (95% CI 16·8–22·5) years in an almost linear fashion—with a mean increase of 0·043 (95% CI 0·037–0·049) SUVR per year—to go from the threshold of 11C-PiB positivity (1·5 SUVR) to the levels observed in AD. It was estimated to take 12·0 (95% CI 10·1–14·9) years from the levels observed in healthy controls with low Aβ deposition (1·2 [SD 0·1] SUVR) to the threshold of 11C-PiB positivity. As AD progressed, the rate of Aβ deposition slowed towards a plateau. Our projections suggest a prolonged preclinical phase of AD in which Aβ deposition reaches our threshold of positivity at 17·0 (95% CI 14·9–19·9) years, hippocampal atrophy at 4·2 (3·6–5·1) years, and memory impairment at 3·3 (2·5–4·5) years before the onset of dementia (clinical dementia rating score 1). Aβ deposition is slow and protracted, likely to extend for more than two decades. Such predictions of the rate of preclinical changes and the onset of the clinical phase of AD will facilitate the design and timing of therapeutic interventions aimed at modifying the course of this illness. Science and Industry Endowment Fund (Australia), The Commonwealth Scientific and Industrial Research Organisation (Australia), The National Health and Medical Research Council of Australia Program and Project Grants, the Austin Hospital Medical Research Foundation, Victorian State Government, The Alzheimer's Drug Discovery Foundation, and the Alzheimer's Association.

Understanding Alzheimer’s disease (AD) heterogeneity is important for understanding the underlying pathophysiological mechanisms of AD. However, AD atrophy subtypes may reflect different disease stages or biologically distinct subtypes. Here we use longitudinal magnetic resonance imaging data (891 participants with AD dementia, 305 healthy control participants) from four international cohorts, and longitudinal clustering to estimate differential atrophy trajectories from the age of clinical disease onset. Our findings (in amyloid-β positive AD patients) show five distinct longitudinal patterns of atrophy with different demographical and cognitive characteristics. Some previously reported atrophy subtypes may reflect disease stages rather than distinct subtypes. The heterogeneity in atrophy rates and cognitive decline within the five longitudinal atrophy patterns, potentially expresses a complex combination of protective/risk factors and concomitant non-AD pathologies. By alternating between the cross-sectional and longitudinal understanding of AD subtypes these analyses may allow better understanding of disease heterogeneity. Different types of atrophy in Alzheimer’s disease may reflect different disease stages or biologically distinct subtypes. Here the authors use longitudinal neuroimaging data to demonstrate five distinct patterns of atrophy with different demographical and cognitive characteristics.

Changes to lipid metabolism are tightly associated with the onset and pathology of Alzheimer’s disease (AD). Lipids are complex molecules comprising many isomeric and isobaric species, necessitating detailed analysis to enable interpretation of biological significance. Our expanded targeted lipidomics platform (569 species across 32 classes) allows for detailed lipid separation and characterisation. In this study we examined peripheral samples of two cohorts (AIBL, n  = 1112 and ADNI, n  = 800). We are able to identify concordant peripheral signatures associated with prevalent AD arising from lipid pathways including; ether lipids, sphingolipids (notably GM 3 gangliosides) and lipid classes previously associated with cardiometabolic disease (phosphatidylethanolamine and triglycerides). We subsequently identified similar lipid signatures in both cohorts with future disease. Lastly, we developed multivariate lipid models that improved classification and prediction. Our results provide a holistic view between the lipidome and AD using a comprehensive approach, providing targets for further mechanistic investigation. The onset and pathology of Alzheimer’s disease (AD) is associated with changes to lipid metabolism. Here, the authors analysed 569 lipids from 32 classes and subclasses in two independent patient cohorts to identify key lipid pathways to link the plasma lipidome with AD and the future onset of AD.

Brain amyloid β (Aβ) deposition and neurodegeneration have been documented in about 50–60% of cognitively healthy elderly individuals (aged 60 years or older). The long-term cognitive consequences of the presence of Alzheimer's disease pathology and neurodegeneration, and whether they have an independent or synergistic effect on cognition, are unclear. We aimed to characterise the long-term clinical and cognitive trajectories of healthy elderly individuals using a two-marker (Alzheimer's disease pathology and neurodegeneration) imaging construct. Between Nov 3, 2006, and Nov 25, 2014, 573 cognitively healthy individuals in Melbourne and Perth, Australia, (mean age 73·1 years [SD 6·2]; 58% women) were enrolled in the Australian Imaging, Biomarker and Lifestyle (AIBL) study. Alzheimer's disease pathology (A) was determined by measuring Aβ deposition by PET, and neurodegeneration (N) was established by measuring hippocampal volume using MRI. Individuals were categorised as A−N−, A+N−, A+N+, or suspected non-Alzheimer's disease pathophysiology (A−N+, SNAP). Clinical progression, hippocampal volume, standard neuropsychological tests, and domain-specific and global cognitive composite scores were assessed over 6 years of follow-up. Linear mixed effect models and a Cox proportional hazards model of survival were used to evaluate, compare, and contrast the clinical, cognitive, and volumetric trajectories of patients in the four AN categories. 50 (9%) healthy individuals were classified as A+N+, 87 (15%) as A+N−, 310 (54%) as A−N−, and 126 (22%) as SNAP. APOE ε4 was more frequent in participants in the A+N+ (27; 54%) and A+N− (42; 48%) groups than in the A−N− (66; 21%) and SNAP groups (23; 18%). The A+N− and A+N+ groups had significantly faster cognitive decline than the A−N− group (0·08 SD per year for AIBL-Preclinical AD Cognitive Composite [PACC]; p<0·0001; and 0·25; p<0·0001; respectively). The A +N+ group also had faster hippocampal atrophy than the A−N− group (0·04 cm3 per year; p=0·02). The SNAP group generally did not show significant decline over time compared with the A−N− group (0·03 SD per year [p=0·19] for AIBL-PACC and a 0·02 cm3 per year increase [p=0·16] for hippocampal volume), although SNAP was sometimes associated with lower baseline cognitive scores (0·20 SD less than A−N− for AIBL-PACC). Within the follow-up, 24% (n=12) of individuals in the A+N+ group and 16% (n=14) in the A+N− group progressed to amnestic mild cognitive impairment or Alzheimer's disease, compared with 9% (n=11) in the SNAP group. Brain amyloidosis, a surrogate marker of Alzheimer's disease pathology, is a risk factor for cognitive decline and for progression from preclinical stages to symptomatic stages of the disease, with neurodegeneration acting as a compounding factor. However, neurodegeneration alone does not confer a significantly different risk of cognitive decline from that in the group with neither brain amyloidosis or neurodegeneration. CSIRO Flagship Collaboration Fund and the Science and Industry Endowment Fund (SIEF), National Health and Medical Research Council, the Dementia Collaborative Research Centres programme, McCusker Alzheimer's Research Foundation, and Operational Infrastructure Support from the Government of Victoria.

: Centiloid was introduced to harmonise β-Amyloid (Aβ) PET quantification across different tracers, scanners and analysis techniques. Unfortunately, Centiloid still suffers from some quantification disparities in longitudinal analysis when normalising data from different tracers or scanners. In this work, we aim to reduce this variability using a different analysis technique applied to the existing calibration data. : All PET images from the Centiloid calibration dataset, along with 3762 PET images from the AIBL study were analysed using the recommended SPM pipeline. The PET images were SUVR normalised using the whole cerebellum. All SUVR normalised PiB images from the calibration dataset were decomposed using non-negative matrix factorisation (NMF). The NMF coefficients related to the first component were strongly correlated with global SUVR and were subsequently used as a surrogate for Aβ retention. For each tracer of the calibration dataset, the components of the NMF were computed in a way such that the coefficients of the first component would match those of the corresponding PiB. Given the strong correlations between the SUVR and the NMF coefficients on the calibration dataset, all PET images from AIBL were subsequently decomposed using the computed NMF, and their coefficients transformed into Centiloids. : Using the AIBL data, the correlation between the standard Centiloid and the novel NMF-based Centiloid was high in each tracer. The NMF-based Centiloids showed a reduction of outliers, and improved longitudinal consistency. Furthermore, it removed the effects of switching tracers from the longitudinal variance of the Centiloid measure, when assessed using a linear mixed effects model. : We here propose a novel image driven method to perform the Centiloid quantification. The methods is highly correlated with standard Centiloids while improving the longitudinal reliability when switching tracers. Implementation of this method across multiple studies may lend to more robust and comparable data for future research.

Goldberg v. Kelly and its progeny imposed a judicial model for decisionmaking on much of the administrative state. The linchpin of procedural due process was accuracy: Goldberg’s premise was that agencies could improve the accuracy of their decisionmaking by giving individuals the sort of procedural rights enjoyed in court. In the wake of the due process revolution, federal agencies now adjudicate more cases than all Article III courts combined, and state adjudicators handle millions of cases with court-like procedures in their administrative systems. Yet despite Goldberg’s premise, mass adjudication has struggled to achieve an adequate threshold of accuracy. In much of the administrative state, this struggle has deepened into an urgent crisis. The leading academic response argues for a turn to “internal administrative law” and management techniques, not external law, to improve the quality of agency adjudication. Many agencies in turn have responded with such quality assurance programs, but we know next to nothing about how such programs have evolved, how they function, and whether they work. Our Article is the first to rigorously investigate the promise and pitfalls of quality assurance as a guarantor of accuracy in agency adjudication. We make three contributions. First, we use in-depth interviews with senior agency officials and a wide array of internal agency materials to document the evolving use of quality assurance at three federal agencies whose mass adjudication epitomizes Goldberg’s domain. This history documents years of fits and starts, as agencies tried to manage what is commonly referred to as a “quantity-quality” tradeoff. It also reveals deep tensions and ambiguities in what the agencies intend as the purpose of quality assurance. Second, we provide the first rigorous test of quality assurance, the leading academic response to Goldberg’s limitations. We use a rich dataset, never before available to outside academics, of over 500,000 cases decided by the Board of Veterans’ Appeals (BVA) to craft a rigorous evaluation of a natural experiment created by its “Quality Review” program. Under this program, cases were randomly selected for review of draft decisions by an elite squadron of attorneys to correct substantive legal errors. BVA used this program ostensibly to reduce appeals to and remands from the courts reviewing its decisions. We show that the program failed on its own terms: Cases selected for Quality Review fared no better than cases that were not. BVA used the program not to vindicate Goldberg’s premise, but to mollify external oversight bodies, most notably Congress, with the appearance of accuracy. Third, our historical and empirical evidence has substantial implications for major theoretical debates about “internal administrative law” and the emerging crisis in mass adjudication. We show that conventional scholarly accounts are in need of much refinement. Deficiencies in mass adjudication will not be fixed solely through external constitutional law, with courts imposing remedies from outside. Nor will they be fixed solely by internal administrative law. Goldberg’s original premise of decisional accuracy requires a hybrid of external intervention, stakeholder oversight, and internal agency management. We offer concrete policy prescriptions, based on a pilot one of us designed as BVA’s Chief of the Office for Quality Review, for how quality assurance might be reenvisioned to solve the looming crisis of decisional quality.

Subjective cognitive decline (SCD) has been proposed as a risk factor for future cognitive decline and dementia. Given the heterogeneity of SCD and the lack of consensus about how to classify this condition, different operationalization approaches still need to be compared. In this study, we used the same sample of individuals to compare  different SCD operationalization approaches. We included 399 cognitively healthy individuals from a community-based cohort. SCD was assessed through nine questions about memory and non-memory subjective complaints. We applied four approaches to operationalize SCD: two hypothesis-driven approaches and two data-driven approaches. We characterized the resulting groups from each operationalization approach using multivariate methods on comprehensive demographic, clinical, cognitive, and neuroimaging data. We identified two main phenotypes: an amnestic phenotype characterized by an Alzheimer’s Disease (AD) signature pattern of brain atrophy; and an anomic phenotype, which was mainly related to cerebrovascular pathology. Furthermore, language complaints other than naming helped to identify a subgroup with subclinical cognitive impairment and difficulties in activities of daily living. This subgroup also showed an AD signature pattern of atrophy. The identification of SCD phenotypes, characterized by different syndromic and biomarker profiles, varies depending on the operationalization approach used. In this study we discuss how these findings may be used in clinical practice and research.

PBT2 is a metal-protein attenuating compound (MPAC) that affects the Cu2 +-mediated and Zn2 +-mediated toxic oligomerisation of Aβ seen in Alzheimer's disease (AD). Strong preclinical efficacy data and the completion of early, clinical safety studies have preceded this phase IIa study, the aim of which was to assess the effects of PBT2 on safety, efficacy, and biomarkers of AD. Between December 6, 2006, and September 21, 2007, community-dwelling patients over age 55 years were recruited to this 12-week, double-blind, randomised trial of PBT2. Patients were randomly allocated to receive 50 mg PBT2, 250 mg PBT2, or placebo. Inclusion criteria were early AD (mini-mental state examination [MMSE] score between 20 and 26 points or Alzheimer's disease assessment scale-cognitive subscale (ADAS-cog) score between 10 and 25 points), taking a stable dose of acetylcholinesterase inhibitor (donepezil, galantamine, or rivastigmine) for at least 4 months, a modified Hachinski score of 4 points or less, and CT or MRI results that were consistent with AD. The principal outcomes were safety and tolerability. Secondary outcomes were plasma and CSF biomarkers and cognition. Analysis was intention to treat. The trial is registered with ClinicalTrials.gov, number NCT00471211. 78 patients were randomly assigned (29 to placebo, 20 to PBT2 50 mg, and 29 to PBT2 250 mg) and 74 (95%) completed the study. 42 (54%) patients had at least one treatment emergent adverse event (10 [50%] on PBT2 50 mg, 18 [62%] on PBT2 250 mg, and 14 [48%] on placebo). No serious adverse events were reported by patients on PBT2. Patients treated with PBT2 250 mg had a dose-dependent (p=0·023) and significant reduction in CSF Aβ 42 concentration compared with those treated with placebo (difference in least squares mean change from baseline was −56·0 pg/mL, 95% CI −101·5 to −11·0; p=0·006). PBT2 had no effect on plasma biomarkers of AD or serum Zn 2+ and Cu 2+ concentrations. Cognition testing included ADAS-cog, MMSE, and a neuropsychological test battery (NTB). Of these tests, two executive function component tests of the NTB showed significant improvement over placebo in the PBT2 250 mg group: category fluency test (2·8 words, 0·1 to 5·4; p=0·041) and trail making part B (−48·0 s, −83·0 to −13·0; p=0·009). The safety profile is favourable for the ongoing development of PBT2. The effect on putative biomarkers for AD in CSF but not in plasma is suggestive of a central effect of the drug on Aβ metabolism. Cognitive efficacy was restricted to two measures of executive function. Future trials that are larger and longer will establish if the effects of PBT2 on biomarkers and cognition that are reported here translate into clinical effectiveness. Prana Biotechnology.