Stabilizing the Retromer Complex in a Human Stem Cell Model of Alzheimer's Disease Reduces TAU Phosphorylation Independently of Amyloid Precursor Protein.

Developing effective therapeutics for complex diseases such as late-onset, sporadic Alzheimer's disease (SAD) is difficult due to genetic and environmental heterogeneity in the human population and the limitations of existing animal models. Here, we used hiPSC-derived neurons to test a compound that stabilizes the retromer, a highly conserved multiprotein assembly that plays a pivotal role in trafficking molecules through the endosomal network. Using this human-specific system, we have confirmed previous data generated in murine models and show that retromer stabilization has a potentially beneficial effect on amyloid beta generation from human stem cell-derived neurons. We further demonstrate that manipulation of retromer complex levels within neurons affects pathogenic TAU phosphorylation in an amyloid-independent manner. Taken together, our work demonstrates that retromer stabilization is a promising candidate for therapeutic development in AD and highlights the advantages of testing novel compounds in a human-specific, neuronal system

An animated depiction of major depression epidemiology

<p>Abstract</p> <p>Background</p> <p>Epidemiologic estimates are now available for a variety of parameters related to major depression epidemiology (incidence, prevalence, etc.). These estimates are potentially useful for policy and planning purposes, but it is first necessary that they be synthesized into a coherent picture of the epidemiology of the condition. Several attempts to do so have been made using mathematical modeling procedures. However, this information is not easy to communicate to users of epidemiological data (clinicians, administrators, policy makers).</p> <p>Methods</p> <p>In this study, up-to-date data on major depression epidemiology were integrated using a discrete event simulation model. The mathematical model was animated in Virtual Reality Modeling Language (VRML) to create a visual, rather than mathematical, depiction of the epidemiology.</p> <p>Results</p> <p>Consistent with existing literature, the model highlights potential advantages of population health strategies that emphasize access to effective long-term treatment. The paper contains a web-link to the animation.</p> <p>Conclusion</p> <p>Visual animation of epidemiological results may be an effective knowledge translation tool. In clinical practice, such animations could potentially assist with patient education and enhanced long-term compliance.</p

Altered brain connectivity in sudden unexpected death in epilepsy (SUDEP) revealed using resting-state fMRI.

The circumstances surrounding SUDEP suggest autonomic or respiratory collapse, implying central failure of regulation or recovery. Characterisation of the communication among brain areas mediating such processes may shed light on mechanisms and noninvasively indicate risk. We used rs-fMRI to examine network properties among brain structures in people with epilepsy who suffered SUDEP (n = 8) over an 8-year follow-up period, compared with matched high- and low-risk subjects (n = 16/group) who did not suffer SUDEP during that period, and a group of healthy controls (n = 16). Network analysis was employed to explore connectivity within a 'regulatory-subnetwork' of brain regions involved in autonomic and respiratory regulation, and over the whole-brain. Modularity, the extent of network organization into separate modules, was significantly reduced in the regulatory-subnetwork, and the whole-brain, in SUDEP and high-risk. Increased participation, a local measure of inter-modular belonging, was evident in SUDEP and high-risk groups, particularly among thalamic structures. The medial prefrontal thalamus was increased in SUDEP compared with all other control groups, including high-risk. Patterns of hub topology were similar in SUDEP and high-risk, but were more extensive in low-risk patients, who displayed greater hub prevalence and a radical reorganization of hubs in the subnetwork. SUDEP is associated with reduced functional organization among cortical and sub-cortical brain regions mediating autonomic and respiratory regulation. Living high-risk subjects demonstrated similar patterns, suggesting such network measures may provide prospective risk-indicating value, though a crucial difference between SUDEP and high-risk was altered connectivity of the medial thalamus in SUDEP, which was also elevated compared with all sub-groups. Disturbed thalamic connectivity may reflect a potential non-invasive marker of elevated SUDEP risk

Neuroticism and Extraversion Magnify Discrepancies Between Retrospective and Concurrent Affect Reports

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Objective: Although research often relies on retrospective affect self-reports, little is known about personality's role in retrospective reports and how these converge or deviate from affect reported in the moment. This micro-longitudinal study examines personality (Neuroticism, Extraversion) and emotional salience (peak and recent affect) associations with retrospective-momentary affect report discrepancies over different time frames. Method: Participants were 179 adults aged 20–78 (M = 48.7 years; 73.7% Caucasian/White) who each provided up to 60 concurrent affect reports over 10 days, then retrospectively reported overall intensity of each affective state after 1 day and again after 1–2 months. Results: Multilevel models revealed that individuals retrospectively overreported or underreported various affective states, exhibiting peak associations for high arousal positive and negative affect, recency associations for low arousal positive affect, and distinct personality profiles that strengthened over time. Individuals high in both Extraversion and Neuroticism exaggerated high arousal positive and negative affect and underreported low arousal positive affect, high Extraversion/low Neuroticism individuals exaggerated high arousal positive affect and underreported low arousal positive affect, and low Extraversion/high Neuroticism individuals exaggerated high and low arousal negative affect. Conclusions: This study is the first to identify arousal-specific retrospective affect report discrepancies over time and suggests retrospective reports also reflect personality differences in affective self-knowledge.National Institutes of HealthMichael Smith Foundation for Health ResearchSocial Sciences and Humanities Research Council of CanadaCanada Research Chairs Programm

Accumulation of major depressive episodes over time in a prospective study indicates that retrospectively assessed lifetime prevalence estimates are too low

<p>Abstract</p> <p>Background</p> <p>Most epidemiologic studies concerned with Major Depressive Disorder have employed cross-sectional study designs. Assessment of lifetime prevalence in such studies depends on recall of past depressive episodes. Such studies may underestimate lifetime prevalence because of incomplete recall of past episodes (recall bias). An opportunity to evaluate this issue arises with a prospective Canadian study called the National Population Health Survey (NPHS).</p> <p>Methods</p> <p>The NPHS is a longitudinal study that has followed a community sample representative of household residents since 1994. Follow-up interviews have been completed every two years and have incorporated the Composite International Diagnostic Interview short form for major depression. Data are currently available for seven such interview cycles spanning the time frame 1994 to 2006. In this study, cumulative prevalence was calculated by determining the proportion of respondents who had one or more major depressive episodes during this follow-up interval.</p> <p>Results</p> <p>The annual prevalence of MDD ranged between 4% and 5% of the population during each assessment, consistent with existing literature. However, 19.7% of the population had at least one major depressive episode during follow-up. This included 24.2% of women and 14.2% of men. These estimates are nearly twice as high as the lifetime prevalence of major depressive episodes reported by cross-sectional studies during same time interval.</p> <p>Conclusion</p> <p>In this study, prospectively observed cumulative prevalence over a relatively brief interval of time exceeded lifetime prevalence estimates by a considerable extent. This supports the idea that lifetime prevalence estimates are vulnerable to recall bias and that existing estimates are too low for this reason.</p

Describing the longitudinal course of major depression using Markov models: Data integration across three national surveys

BACKGROUND: Most epidemiological studies of major depression report period prevalence estimates. These are of limited utility in characterizing the longitudinal epidemiology of this condition. Markov models provide a methodological framework for increasing the utility of epidemiological data. Markov models relating incidence and recovery to major depression prevalence have been described in a series of prior papers. In this paper, the models are extended to describe the longitudinal course of the disorder. METHODS: Data from three national surveys conducted by the Canadian national statistical agency (Statistics Canada) were used in this analysis. These data were integrated using a Markov model. Incidence, recurrence and recovery were represented as weekly transition probabilities. Model parameters were calibrated to the survey estimates. RESULTS: The population was divided into three categories: low, moderate and high recurrence groups. The size of each category was approximated using lifetime data from a study using the WHO Mental Health Composite International Diagnostic Interview (WMH-CIDI). Consistent with previous work, transition probabilities reflecting recovery were high in the initial weeks of the episodes, and declined by a fixed proportion with each passing week. CONCLUSION: Markov models provide a framework for integrating psychiatric epidemiological data. Previous studies have illustrated the utility of Markov models for decomposing prevalence into its various determinants: incidence, recovery and mortality. This study extends the Markov approach by distinguishing several recurrence categories

Altered brain connectivity in sudden unexpected death in epilepsy (SUDEP) revealed using resting-state fMRI

The circumstances surrounding SUDEP suggest autonomic or respiratory collapse, implying central failure of regulation or recovery. Characterisation of the communication among brain areas mediating such processes may shed light on mechanisms and noninvasively indicate risk. We used rs-fMRI to examine network properties among brain structures in people with epilepsy who suffered SUDEP (n = 8) over an 8-year follow-up period, compared with matched high- and low-risk subjects (n = 16/group) who did not suffer SUDEP during that period, and a group of healthy controls (n = 16). Network analysis was employed to explore connectivity within a ‘regulatory-subnetwork’ of brain regions involved in autonomic and respiratory regulation, and over the whole-brain. Modularity, the extent of network organization into separate modules, was significantly reduced in the regulatory-subnetwork, and the whole-brain, in SUDEP and high-risk. Increased participation, a local measure of inter-modular belonging, was evident in SUDEP and high-risk groups, particularly among thalamic structures. The medial prefrontal thalamus was increased in SUDEP compared with all other control groups, including high-risk. Patterns of hub topology were similar in SUDEP and high-risk, but were more extensive in low-risk patients, who displayed greater hub prevalence and a radical reorganization of hubs in the subnetwork. SUDEP is associated with reduced functional organization among cortical and sub-cortical brain regions mediating autonomic and respiratory regulation. Living high-risk subjects demonstrated similar patterns, suggesting such network measures may provide prospective risk-indicating value, though a crucial difference between SUDEP and high-risk was altered connectivity of the medial thalamus in SUDEP, which was also elevated compared with all sub-groups. Disturbed thalamic connectivity may reflect a potential non-invasive marker of elevated SUDEP risk

Distinct Patterns of Brain Metabolism in Patients at Risk of Sudden Unexpected Death in Epilepsy

Objective: To characterize regional brain metabolic differences in patients at high risk of sudden unexpected death in epilepsy (SUDEP), using fluorine-18-fluorodeoxyglucose positron emission tomography (18FDG-PET). Methods: We studied patients with refractory focal epilepsy at high (n = 56) and low (n = 69) risk of SUDEP who underwent interictal 18FDG-PET as part of their pre-surgical evaluation. Binary SUDEP risk was ascertained by thresholding frequency of focal to bilateral tonic-clonic seizures (FBTCS). A whole brain analysis was employed to explore regional differences in interictal metabolic patterns. We contrasted these findings with regional brain metabolism more directly related to frequency of FBTCS. Results: Regions associated with cardiorespiratory and somatomotor regulation differed in interictal metabolism. In patients at relatively high risk of SUDEP, fluorodeoxyglucose (FDG) uptake was increased in the basal ganglia, ventral diencephalon, midbrain, pons, and deep cerebellar nuclei; uptake was decreased in the left planum temporale. These patterns were distinct from the effect of FBTCS frequency, where increasing frequency was associated with decreased uptake in bilateral medial superior frontal gyri, extending into the left dorsal anterior cingulate cortex. Significance: Regions critical to cardiorespiratory and somatomotor regulation and to recovery from vital challenges show altered interictal metabolic activity in patients with frequent FBTCS considered to be at relatively high-risk of SUDEP, and shed light on the processes that may predispose patients to SUDEP

An Integrated-Photonics Optical-Frequency Synthesizer

Integrated-photonics microchips now enable a range of advanced functionalities for high-coherence applications such as data transmission, highly optimized physical sensors, and harnessing quantum states, but with cost, efficiency, and portability much beyond tabletop experiments. Through high-volume semiconductor processing built around advanced materials there exists an opportunity for integrated devices to impact applications cutting across disciplines of basic science and technology. Here we show how to synthesize the absolute frequency of a lightwave signal, using integrated photonics to implement lasers, system interconnects, and nonlinear frequency comb generation. The laser frequency output of our synthesizer is programmed by a microwave clock across 4 THz near 1550 nm with 1 Hz resolution and traceability to the SI second. This is accomplished with a heterogeneously integrated III/V-Si tunable laser, which is guided by dual dissipative-Kerr-soliton frequency combs fabricated on silicon chips. Through out-of-loop measurements of the phase-coherent, microwave-to-optical link, we verify that the fractional-frequency instability of the integrated photonics synthesizer matches the $7.0*10^{-13}$ reference-clock instability for a 1 second acquisition, and constrain any synthesis error to $7.7*10^{-15}$ while stepping the synthesizer across the telecommunication C band. Any application of an optical frequency source would be enabled by the precision optical synthesis presented here. Building on the ubiquitous capability in the microwave domain, our results demonstrate a first path to synthesis with integrated photonics, leveraging low-cost, low-power, and compact features that will be critical for its widespread use.Comment: 10 pages, 6 figure