Turmeric shortens lifespan in houseflies

The authors would like to thank Elissavet Kaplaneli for the technical support in keeping the housefly colonies.Peer reviewe

Equity in Global Health Law - Policy Brief

Equity has been sorely lacking in pandemic preparedness and response, and COVID-19 is but the latest example (O’Cuinn and Switzer, 2019; Rourke, 2019). The response to COVID-19 was characterised by nationalism, inequity in access to diagnostics, vaccines, therapeutics and personal protective equipment (PPE) between the Global North and the Global South, as well as discriminatory, and in some instances racist, border closures chiefly impacting low- and middle-income countries. In response to the widespread inequity witnessed during the COVID-19 pandemic, Member States of the World Health Organisation (WHO) are currently negotiating a new international legal instrument - the Pandemic Treaty - intended to prevent pandemics and mitigate associated inequalities such as vaccine access, and improve compliance with international law during pandemic events. From the initial proposal for the Treaty, through the many rounds of discussions that have occurred to date, it is clear that the new instrument is intended to be grounded in equity, with equity positioned as both an objective and as an operational output (Wenham, Eccleston- Turner & Voss, 2022). However, while equity is recognised as a general principle of international law, it does not have a precise and defined meaning. From the start of negotiations, it was unclear what an instrument ‘grounded’ in equity should look like, what the principle of equity actually means in this context, and how this principle can translate into meaningful obligations within international law more generally, as well as pandemic preparedness and global health governance specifically. In an attempt to answer these questions, we convened - with the assistance of funding from the Scottish Council for Global Affairs and the ESRC IAA Policy Impact Fund - a workshop at King’s College, London at which we gathered together experts on equity from different disciplinary backgrounds in an attempt to understand and conceptualize equity as a legal concept, charting its history, development and application within both domestic and international law. In the following short discussion, we distill some of the lessons at this workshop from both national law as well as other international arenas, before offering suggestions on how this somewhat opaque concept might be effectively operationalised within the Pandemic Treaty. The aim of this discussion is therefore not to engage in a lengthy, academic literature review of the different conceptions of equity found in academic texts - of which there is an abundance of relevant literature - but rather to offer practical insights to the operationalisation of equity to the Pandemic Treaty. What we find is that there is no ‘one’ way to do equity or for an international agreement to be equitable. Our discussions found that equity must be more than an abstract buzzword - simply inserting the word equity into a legal text does not achieve equity. However, international law offers a number of lessons for responding to instances of inequity arising in the absence of a perfect, overarching functional definition of equity

LILRA2 Selectively Modulates LPS-Mediated Cytokine Production and Inhibits Phagocytosis by Monocytes

The activating immunoglobulin-like receptor, subfamily A, member 2 (LILRA2) is primarily expressed on the surface of cells of the innate immunity including monocytes, macrophages, neutrophils, basophils and eosinophils but not on lymphocytes and NK cells. LILRA2 cross-linking on monocytes induces pro-inflammatory cytokines while inhibiting dendritic cell differentiation and antigen presentation. A similar activating receptor, LILRA4, has been shown to modulate functions of TLR7/9 in dendritic cells. These suggest a selective immune regulatory role for LILRAs during innate immune responses. However, whether LILRA2 has functions distinct from other receptors of the innate immunity including Toll-like receptor (TLR) 4 and FcγRI remains unknown. Moreover, the effects of LILRA2 on TLR4 and FcγRI-mediated monocyte functions are not elucidated. Here, we show activation of monocytes via LILRA2 cross-linking selectively increased GM-CSF production but failed to induce IL-12 and MCP-1 production that were strongly up-regulated by LPS, suggesting functions distinct from TLR4. Interestingly, LILRA2 cross-linking on monocytes induced similar amounts of IL-6, IL-8, G-CSF and MIP-1α but lower levels of TNFα, IL-1β, IL-10 and IFNγ compared to those stimulated with LPS. Furthermore, cross-linking of LILRA2 on monocytes significantly decreased phagocytosis of IgG-coated micro-beads and serum opsonized Escherichia coli but had limited effect on phagocytosis of non-opsonized bacteria. Simultaneous co-stimulation of monocytes through LILRA2 and LPS or sequential activation of monocytes through LILRA2 followed by LPS led lower levels of TNFα, IL-1β and IL-12 production compared to LPS alone, but had additive effect on levels of IL-10 and IFNγ but not on IL-6. Interestingly, LILRA2 cross-linking on monocytes caused significant inhibition of TLR4 mRNA and protein, suggesting LILRA2-mediated suppression of LPS responses might be partly via regulation of this receptor. Taken together, we provide evidence that LILRA2-mediated activation of monocytes is significantly different to LPS and that LILRA2 selectively modulates LPS-mediated monocyte activation and FcγRI-dependent phagocytosis

A test of financial incentives to improve warfarin adherence

<p>Abstract</p> <p>Background</p> <p>Sub-optimal adherence to warfarin places millions of patients at risk for stroke and bleeding complications each year. Novel methods are needed to improve adherence for warfarin. We conducted two pilot studies to determine whether a lottery-based daily financial incentive is feasible and improves warfarin adherence and anticoagulation control.</p> <p>Methods</p> <p>Volunteers from the University of Pennsylvania Anticoagulation Management Center who had taken warfarin for at least 3 months participated in either a pilot study with a lottery with a daily expected value of $5 (N = 10) or a daily expected value of$3 (N = 10). All subjects received use of an Informedix Med-eMonitor™ System with a daily reminder feature. If subjects opened up their pill compartments appropriately, they were entered into a daily lottery with a 1 in 5 chance of winning $10 and a 1 in 100 chance of winning$100 (pilot 1) or a 1 in 10 chance of winning $10 and a 1 in 100 chance of winning$100 (pilot 2). The primary study outcome was proportion of incorrect warfarin doses. The secondary outcome was proportion of INR measurements not within therapeutic range. Within-subject pre-post comparisons were done of INR measurements with comparisons with either historic means or within-subject comparisons of incorrect warfarin doses.</p> <p>Results</p> <p>In the first pilot, the percent of out-of-range INRs decreased from 35.0% to 12.2% during the intervention, before increasing to 42% post-intervention. The mean proportion of incorrect pills taken during the intervention was 2.3% incorrect pills, compared with a historic mean of 22% incorrect pill taking in this clinic population. Among the five subjects who also had MEMS cap adherence data from warfarin use in our prior study, mean incorrect pill taking decreased from 26% pre-pilot to 2.8% in the pilot. In the second pilot, the time out of INR range decreased from 65.0% to 40.4%, with the proportion of mean incorrect pill taking dropping to 1.6%.</p> <p>Conclusion</p> <p>A daily lottery-based financial incentive demonstrated the potential for significant improvements in missed doses of warfarin and time out of INR range. Further testing should be done of this approach to determine its effectiveness and potential application to both warfarin and other chronic medications.</p

Temporal-Difference Reinforcement Learning with Distributed Representations

Temporal-difference (TD) algorithms have been proposed as models of reinforcement learning (RL). We examine two issues of distributed representation in these TD algorithms: distributed representations of belief and distributed discounting factors. Distributed representation of belief allows the believed state of the world to distribute across sets of equivalent states. Distributed exponential discounting factors produce hyperbolic discounting in the behavior of the agent itself. We examine these issues in the context of a TD RL model in which state-belief is distributed over a set of exponentially-discounting “micro-Agents”, each of which has a separate discounting factor (γ). Each µAgent maintains an independent hypothesis about the state of the world, and a separate value-estimate of taking actions within that hypothesized state. The overall agent thus instantiates a flexible representation of an evolving world-state. As with other TD models, the value-error (δ) signal within the model matches dopamine signals recorded from animals in standard conditioning reward-paradigms. The distributed representation of belief provides an explanation for the decrease in dopamine at the conditioned stimulus seen in overtrained animals, for the differences between trace and delay conditioning, and for transient bursts of dopamine seen at movement initiation. Because each µAgent also includes its own exponential discounting factor, the overall agent shows hyperbolic discounting, consistent with behavioral experiments

The role of simulation in intertemporal choices

One route to understanding the thoughts and feelings of others is by mentally putting one's self in their shoes and seeing the world from their perspective, i.e., by simulation. Simulation is potentially used not only for inferring how others feel, but also for predicting how we ourselves will feel in the future. For instance, one might judge the worth of a future reward by simulating how much it will eventually be enjoyed. In intertemporal choices between smaller immediate and larger delayed rewards, it is observed that as the length of delay increases, delayed rewards lose subjective value; a phenomenon known as temporal discounting. In this article, we develop a theoretical framework for the proposition that simulation mechanisms involved in empathizing with others also underlie intertemporal choices. This framework yields a testable psychological account of temporal discounting based on simulation. Such an account, if experimentally validated, could have important implications for how simulation mechanisms are investigated, and makes predictions about special populations characterized by putative deficits in simulating others

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues