The effect of rapamycin treatment on cerebral ischemia: A systematic review and meta-analysis of animal model studies

Background:Amplifying endogenous neuroprotective mechanisms is a promising avenue for stroke therapy. One target is mammalian target of rapamycin (mTOR), a serine/threonine kinase regulating cell proliferation, cell survival, protein synthesis, and autophagy. Animal studies investigating the effect of rapamycin on mTOR inhibition following cerebral ischemia have shown conflicting results.Aim:To conduct a systematic review and meta-analysis evaluating the effectiveness of rapamycin in reducing infarct volume in animal models of ischemic stroke.Summary of review:Our search identified 328 publications. Seventeen publications met inclusion criteria (52 comparisons: 30 reported infarct size and 22 reported neurobehavioral score). Study quality was modest (median 4 of 9) with no evidence of publication bias. The point estimate for the effect of rapamycin was a 21.6% (95% CI, 7.6%–35.7% p Conclusion:Low-dose rapamycin treatment may be an effective therapeutic option for stroke. Modest study quality means there is a potential risk of bias. We recommend further high-quality preclinical studies on rapamycin in stroke before progressing to clinical trials

Reprint: Good laboratory practice: preventing introduction of bias at the bench

As a research community, we have failed to show that drugs, which show substantial efficacy in animal models of cerebral ischemia, can also improve outcome in human stroke. Accumulating evidence suggests this may be due, at least in part, to problems in the design, conduct, and reporting of animal experiments which create a systematic bias resulting in the overstatement of neuroprotective efficacy. Here, we set out a series of measures to reduce bias in the design, conduct and reporting of animal experiments modeling human stroke

Derivation of phenotypically diverse neural culture from hESC by combining adherent and dissociation methods

Background:Differentiation of human embryonic stem cells (hESCs) into distinct neural lineages has been widely studied. However, preparation of mixed yet neurochemically mature populations, for the study of neurological diseases involving mixed cell types has received less attention.New method:We combined two commonly used differentiation methods to provide robust and reproducible cultures in which a mixture of primarily GABAergic and Glutamatergic neurons was obtained. Detailed characterisation by immunocytochemistry (ICC) and quantitative real-time PCR (qPCR) assessed the neurochemical phenotype, and the maturation state of these neurons.Results:We found that once neurospheres (NSs) had attached to the culture plates, proliferation of neural stem cell was suppressed. Neuronal differentiation and synaptic development then occurred after 21 days in vitro (DIV). By 49DIV, there were large numbers of neurochemically and structurally mature neurons. The qPCR studies indicated that expression of GABAergic genes increased the most (93.3-fold increase), followed by glutamatergic (51-fold increase), along with smaller changes in expression of cholinergic (3-fold increase) and dopaminergic genes (6-fold increase), as well as a small change in glial cell marker expression (5-fold increase).Comparison with existing method (s):Existing methods isolate hESC-derived neural progenitors for onward differentiation to mature neurons using either migration or dissociative paradigms. These give poor survival or yield. By combining these approaches, we obtain high yields of morphologically and neurochemically mature neurons. These can be maintained in culture for extended periods.Conclusion:Our method provides a novel, effective and robust neural culture system with structurally and neurochemically mature cell populations and neural networks, suitable for studying a range of neurological diseases from a human perspective

Longitudinal stroke recovery associated with dysregulation of complement system - A proteomics pathway analysis

Currently the longitudinal proteomic profile of post-ischemic stroke recovery is relativelyunknown with few well-accepted biomarkers or understanding of the biological systemsthat underpin recovery. We aimed to characterize plasma derived biological pathwaysassociated with recovery during the first year post event using a discovery proteomicsworkflow coupled with a topological pathway systems biology approach. Blood samples(n = 180, ethylenediaminetetraacetic acid plasma) were collected from a subgroup of60 first episode stroke survivors from the Australian START study at 3 timepoints: 3–7days (T1), 3-months (T2) and 12-months (T3) post-stroke. Samples were analyzed byliquid chromatography mass spectrometry using label-free quantification (data availableat ProteomeXchange with identifier PXD015006). Differential expression analysis revealedthat 29 proteins between T1 and T2, and 33 proteins between T1 and T3 weresignificantly different, with 18 proteins commonly differentially expressed across thetwo time periods. Pathway analysis was conducted using Gene Graph EnrichmentAnalysis on both the Kyoto Encyclopedia of Genes and Genomes and Reactomedatabases. Pathway analysis revealed that the significantly differentiated proteinsbetween T1 and T2 were consistently found to belong to the complement pathway.Further correlational analyses utilized to examine the changes in regulatory effects ofproteins over time identified significant inhibitory regulation of clusterin on complementcomponent 9. Longitudinal post-stroke blood proteomics profiles suggest that thealternative pathway of complement activation remains in a state of higher activation from3-7 days to 3 months post-stroke, while simultaneously being regulated by clusterin andvitronectin. These findings also suggest that post-stroke induced sterile inflammation andimmunosuppression could inhibit recovery within the 3-month window post-stroke

Meta-analysis of variation suggests that embracing variability improves both replicability and generalizability in preclinical research

The replicability of research results has been a cause of increasing concern to the scientific community. The long-held belief that experimental standardization begets replicability has also been recently challenged, with the observation that the reduction of variability within studies can lead to idiosyncratic, lab-specific results that cannot be replicated. An alternative approach is to, instead, deliberately introduce heterogeneity, known as "heterogenization" of experimental design. Here, we explore a novel perspective in the heterogenization program in a meta-analysis of variability in observed phenotypic outcomes in both control and experimental animal models of ischemic stroke. First, by quantifying interindividual variability across control groups, we illustrate that the amount of heterogeneity in disease state (infarct volume) differs according to methodological approach, for example, in disease induction methods and disease models. We argue that such methods may improve replicability by creating diverse and representative distribution of baseline disease state in the reference group, against which treatment efficacy is assessed. Second, we illustrate how meta-analysis can be used to simultaneously assess efficacy and stability (i.e., mean effect and among-individual variability). We identify treatments that have efficacy and are generalizable to the population level (i.e., low interindividual variability), as well as those where there is high interindividual variability in response; for these, latter treatments translation to a clinical setting may require nuance. We argue that by embracing rather than seeking to minimize variability in phenotypic outcomes, we can motivate the shift toward heterogenization and improve both the replicability and generalizability of preclinical research

Connecting climate action with other sustainable development goals

The international community has committed to combat climate change and achieve 17 Sustainable Development Goals (SDGs). Here we explore (dis)connections in evidence and governance between these commitments. Our structured evidence review suggests that climate change can undermine 16 SDGs, while combatting climate change can reinforce all 17 SDGs but undermine efforts to achieve 12. Understanding these relationships requires wider and deeper interdisciplinary collaboration. Climate change and sustainable development governance should be better connected to maximize the effectiveness of action in both domains. The emergence around the world of new coordinating institutions and sustainable development planning represents promising progress