Dimethyl fumarate attenuates reactive microglia and long-term memory deficits following systemic immune challenge

BACKGROUND: Systemic inflammation is associated with increased cognitive decline and risk for Alzheimer's disease. Microglia (MG) activated during systemic inflammation can cause exaggerated neuroinflammatory responses and trigger progressive neurodegeneration. Dimethyl fumarate (DMF) is a FDA-approved therapy for multiple sclerosis. The immunomodulatory and anti-oxidant properties of DMF prompted us to investigate whether DMF has translational potential for the treatment of cognitive impairment associated with systemic inflammation. METHODS: Primary murine MG cultures were stimulated with lipopolysaccharide (LPS) in the absence or presence of DMF. MG cultured from nuclear factor (erythroid-derived 2)-like 2-deficient (Nrf2 -/- ) mice were used to examine mechanisms of DMF actions. Conditioned media generated from LPS-primed MG were used to treat hippocampal neuron cultures. Adult C57BL/6 and Nrf2 -/- mice were subjected to peripheral LPS challenge. Acute neuroinflammation, long-term memory function, and reactive astrogliosis were examined to assess therapeutic effects of DMF. RESULTS: DMF suppressed inflammatory activation of MG induced by LPS. DMF suppressed NF-κB activity through Nrf2-depedent and Nrf2-independent mechanisms in MG. DMF treatment reduced MG-mediated toxicity towards neurons. DMF suppressed brain-derived inflammatory cytokines in mice following peripheral LPS challenge. The suppressive effect of DMF on neuroinflammation was blunted in Nrf2 -/- mice. Importantly, DMF treatment alleviated long-term memory deficits and sustained reactive astrogliosis induced by peripheral LPS challenge. DMF might mitigate neurotoxic astrocytes associated with neuroinflammation. CONCLUSIONS: DMF treatment might protect neurons against toxic microenvironments produced by reactive MG and astrocytes associated with systemic inflammation

PETSc Users Manual

The Portable, Extensible Toolkit for Scientific Computation (PETSc), is a suite of data structures and routines for the scalable (parallel) solution of scientific applications modeled by partial differential equations. It supports MPI, and GPUs through CUDA or OpenCL, as well as hybrid MPI-GPU parallelism. PETSc (sometimes called PETSc/Tao) also contains the Tao optimization software library

The Imperative to Share Clinical Study Reports: Recommendations from the Tamiflu Experience

Peter Doshi and colleagues describe their experience trying and failing to access clinical study reports from the manufacturer of Tamiflu and challenge industry to defend their current position of RCT data secrecy

Why we need easy access to all data from all clinical trials and how to accomplish it

International calls for registering all trials involving humans and for sharing the results, and sometimes also the raw data and the trial protocols, have increased in recent years. Such calls have come, for example, from the Organization for Economic Cooperation and Development (OECD), the World Health Organization (WHO), the US National Institutes of Heath, the US Congress, the European Commission, the European ombudsman, journal editors, The Cochrane Collaboration, and several funders, for example the UK Medical Research Council, the Wellcome Trust, the Bill and Melinda Gates Foundation and the Hewlett Foundation

The Tell-Tale Heart: Population-Based Surveillance Reveals an Association of Rofecoxib and Celecoxib with Myocardial Infarction

Background. COX-2 selective inhibitors are associated with myocardial infarction (MI). We sought to determine whether population health monitoring would have revealed the effect of COX-2 inhibitors on population-level patterns of MI. Methodology/Principal Findings. We conducted a retrospective study of inpatients at two Boston hospitals, from January 1997 to March 2006. There was a population-level rise in the rate of MI that reached 52.0 MI-related hospitalizations per 100,000 (a two standard deviation exceedence) in January of 2000, eight months after the introduction of rofecoxib and one year after celecoxib. The exceedence vanished within one month of the withdrawal of rofecoxib. Trends in inpatient stay due to MI were tightly coupled to the rise and fall of prescriptions of COX-2 inhibitors, with an 18.5 % increase in inpatient stays for MI when both rofecoxib and celecoxib were on the market (P,0.001). For every million prescriptions of rofecoxib and celecoxib, there was a 0.5 % increase in MI (95%CI 0.1 to 0.9) explaining 50.3 % of the deviance in yearly variation of MI-related hospitalizations. There was a negative association between mean age at MI and volume of prescriptions for celecoxib and rofecoxib (Spearman correlation, 20.67, P,0.05). Conclusions/Significance. The strong relationship between prescribing and outcome time series supports a population-level impact of COX-2 inhibitors on MI incidence. Further, mean age at MI appears to have been lowered by use of these medications. Use of a population monitoring approach as an adjunct t

Matter-wave Atomic Gradiometer Interferometric Sensor (MAGIS-100)

MAGIS-100 is a next-generation quantum sensor under construction at Fermilab that aims to explore fundamental physics with atom interferometry over a 100-meter baseline. This novel detector will search for ultralight dark matter, test quantum mechanics in new regimes, and serve as a technology pathfinder for future gravitational wave detectors in a previously unexplored frequency band. It combines techniques demonstrated in state-of-the-art 10-meter-scale atom interferometers with the latest technological advances of the world's best atomic clocks. MAGIS-100 will provide a development platform for a future kilometer-scale detector that would be sufficiently sensitive to detect gravitational waves from known sources. Here we present the science case for the MAGIS concept, review the operating principles of the detector, describe the instrument design, and study the detector systematics.Comment: 65 pages, 18 figure

A Systematic Review of Re-Identification Attacks on Health Data

Privacy legislation in most jurisdictions allows the disclosure of health data for secondary purposes without patient consent if it is de-identified. Some recent articles in the medical, legal, and computer science literature have argued that de-identification methods do not provide sufficient protection because they are easy to reverse. Should this be the case, it would have significant and important implications on how health information is disclosed, including: (a) potentially limiting its availability for secondary purposes such as research, and (b) resulting in more identifiable health information being disclosed. Our objectives in this systematic review were to: (a) characterize known re-identification attacks on health data and contrast that to re-identification attacks on other kinds of data, (b) compute the overall proportion of records that have been correctly re-identified in these attacks, and (c) assess whether these demonstrate weaknesses in current de-identification methods.Searches were conducted in IEEE Xplore, ACM Digital Library, and PubMed. After screening, fourteen eligible articles representing distinct attacks were identified. On average, approximately a quarter of the records were re-identified across all studies (0.26 with 95% CI 0.046-0.478) and 0.34 for attacks on health data (95% CI 0-0.744). There was considerable uncertainty around the proportions as evidenced by the wide confidence intervals, and the mean proportion of records re-identified was sensitive to unpublished studies. Two of fourteen attacks were performed with data that was de-identified using existing standards. Only one of these attacks was on health data, which resulted in a success rate of 0.00013.The current evidence shows a high re-identification rate but is dominated by small-scale studies on data that was not de-identified according to existing standards. This evidence is insufficient to draw conclusions about the efficacy of de-identification methods

Reporting bias in medical research - a narrative review

Reporting bias represents a major problem in the assessment of health care interventions. Several prominent cases have been described in the literature, for example, in the reporting of trials of antidepressants, Class I anti-arrhythmic drugs, and selective COX-2 inhibitors. The aim of this narrative review is to gain an overview of reporting bias in the medical literature, focussing on publication bias and selective outcome reporting. We explore whether these types of bias have been shown in areas beyond the well-known cases noted above, in order to gain an impression of how widespread the problem is. For this purpose, we screened relevant articles on reporting bias that had previously been obtained by the German Institute for Quality and Efficiency in Health Care in the context of its health technology assessment reports and other research work, together with the reference lists of these articles