Pyrvinium Pamoate: Past, Present, and Future as an Anti-Cancer Drug

Pyrvinium, a lipophilic cation belonging to the cyanine dye family, has been used in the clinic as a safe and effective anthelminthic for over 70 years. Its structure, similar to some polyaminopyrimidines and mitochondrial-targeting peptoids, has been linked with mitochondrial localization and targeting. Over the past two decades, increasing evidence has emerged showing pyrvinium to be a strong anti-cancer molecule in various human cancers in vitro and in vivo. This efficacy against cancers has been attributed to diverse mechanisms of action, with the weight of evidence supporting the inhibition of mitochondrial function, the WNT pathway, and cancer stem cell renewal. Despite the overwhelming evidence demonstrating the efficacy of pyrvinium for the treatment of human cancers, pyrvinium has not yet been repurposed for the treatment of cancers. This review provides an in-depth analysis of the history of pyrvinium as a therapeutic, the rationale and data supporting its use as an anticancer agent, and the challenges associated with repurposing pyrvinium as an anti-cancer agent

Continued need for non-human primate neuroscience research.

Neuroscience research in non-human primates (NHPs) has delivered fundamental knowledge about human brain function as well as some valuable therapies that have improved the lives of human patients with a variety of brain disorders. Research using NHPs, although it is facing serious challenges, continues to complement studies in human volunteers and patients, and will continue to be needed as the burdens of mental health problems and neurodegenerative diseases increase. At the same time, research into the 3Rs is helping to ameliorate the harms experienced by NHPs in experimental procedures, allowing the effective combination of optimal welfare conditions for the NHPs and high quality research

Mid-infrared Period-Luminosity Relations of RR Lyrae Stars Derived from the WISE Preliminary Data Release

Interstellar dust presents a significant challenge to extending parallax-determined distances of optically observed pulsational variables to larger volumes. Distance ladder work at mid-infrared wavebands, where dust effects are negligible and metallicity correlations are minimized, have been largely focused on few-epoch Cepheid studies. Here we present the first determination of mid-infrared period-luminosity (PL) relations of RR Lyrae stars from phase-resolved imaging using the preliminary data release of the Wide-Field Infrared Survey Explorer (WISE). We present a novel statistical framework to predict posterior distances of 76 well-observed RR Lyrae that uses the optically constructed prior distance moduli while simultaneously imposing a power-law PL relation to WISE-determined mean magnitudes. We find that the absolute magnitude in the bluest WISE filter is M_W1 = (-0.421+-0.014) - (1.681+-0.147)*log(P/0.50118 day), with no evidence for a correlation with metallicity. Combining the results from the three bluest WISE filters, we find that a typical star in our sample has a distance measurement uncertainty of 0.97% (statistical) plus 1.17% (systematic). We do not fundamentalize the periods of RRc stars to improve their fit to the relations. Taking the Hipparcos-derived mean V-band magnitudes, we use the distance posteriors to determine a new optical metallicity-luminosity relation which we present in Section 5. The results of this analysis will soon be tested by HST parallax measurements and, eventually, with the Gaia astrometric mission.Comment: 33 pages, 12 figures, 2 tables. Accepted for publication in ApJ, June 27th, 201

Adaptive Lévy processes and area-restricted search in human foraging

A considerable amount of research has claimed that animals’ foraging behaviors display movement lengths with power-law distributed tails, characteristic of Lévy flights and Lévy walks. Though these claims have recently come into question, the proposal that many animals forage using Lévy processes nonetheless remains. A Lévy process does not consider when or where resources are encountered, and samples movement lengths independently of past experience. However, Lévy processes too have come into question based on the observation that in patchy resource environments resource-sensitive foraging strategies, like area-restricted search, perform better than Lévy flights yet can still generate heavy-tailed distributions of movement lengths. To investigate these questions further, we tracked humans as they searched for hidden resources in an open-field virtual environment, with either patchy or dispersed resource distributions. Supporting previous research, for both conditions logarithmic binning methods were consistent with Lévy flights and rank-frequency methods–comparing alternative distributions using maximum likelihood methods–showed the strongest support for bounded power-law distributions (truncated Lévy flights). However, goodness-of-fit tests found that even bounded power-law distributions only accurately characterized movement behavior for 4 (out of 32) participants. Moreover, paths in the patchy environment (but not the dispersed environment) showed a transition to intensive search following resource encounters, characteristic of area-restricted search. Transferring paths between environments revealed that paths generated in the patchy environment were adapted to that environment. Our results suggest that though power-law distributions do not accurately reflect human search, Lévy processes may still describe movement in dispersed environments, but not in patchy environments–where search was area-restricted. Furthermore, our results indicate that search strategies cannot be inferred without knowing how organisms respond to resources–as both patched and dispersed conditions led to similar Lévy-like movement distributions

Properties of the H-alpha-emitting Circumstellar Regions of Be Stars

Long-baseline interferometric observations obtained with the Navy Prototype Optical Interferometer of the H-alpha-emitting envelopes of the Be stars eta Tauri and beta Canis Minoris are presented. For compatibility with the previously published interferometric results in the literature of other Be stars, circularly symmetric and elliptical Gaussian models were fitted to the calibrated H-alpha observations. The models are sufficient in characterizing the angular distribution of the H-alpha-emitting circumstellar material associated with these Be stars. To study the correlations between the various model parameters and the stellar properties, the model parameters for eta Tau and beta CMi were combined with data for other Be stars from the literature. After accounting for the different distances to the sources and stellar continuum flux levels, it was possible to study the relationship between the net H-alpha emission and the physical extent of the H-alpha-emitting circumstellar region. A clear dependence of the net H-alpha emission on the linear size of the emitting region is demonstrated and these results are consistent with an optically thick line emission that is directly proportional to the effective area of the emitting disk. Within the small sample of stars considered in this analysis, no clear dependence on the spectral type or stellar rotation is found, although the results do suggest that hotter stars might have more extended H-alpha-emitting regions.Comment: 24 pages, 16 figures, accepted for publication in Ap

30 days wild: development and evaluation of a large-scale nature engagement campaign to improve well-being

There is a need to increase people’s engagement with and connection to nature, both for human well-being and the conservation of nature itself. In order to suggest ways for people to engage with nature and create a wider social context to normalise nature engagement, The Wildlife Trusts developed a mass engagement campaign, 30 Days Wild. The campaign asked people to engage with nature every day for a month. 12,400 people signed up for 30 Days Wild via an online sign-up with an estimated 18,500 taking part overall, resulting in an estimated 300,000 engagements with nature by participants. Samples of those taking part were found to have sustained increases in happiness, health, connection to nature and pro-nature behaviours. With the improvement in health being predicted by the improvement in happiness, this relationship was mediated by the change in connection to nature

STEPPING INTO THE FUTURE: THE NEXT GENERATION OF CRISIS FORECASTING MODELS

Abstract. Developing political forecasting models is not only relevant for scientific advancement, but also increases the ability of political scientists to inform public policy decisions. Taking this perspective seriously, the International Crisis Early Warning System (ICEWS) was developed under a DARPA initiative to provide predictions of international crisis, domestic crisis, rebellion, insurgency, and ethnic violence (Events of Interest/EOIs) in about two-dozen countries in the US PACOM Area of Responsibility. As part of a larger project coordinated by Lockheed Martin Advanced Technology Labs, a team at Duke University created a series of geographically informed statistical models for these EOIs. The generated predictions have been highly accurate, with few false negative and positive categorizations. Predictions are made at the monthly level for three months periods into the future. The major variables to generate the predictions include 1) event data culled from FACTIVA reports, 2) structural political characteristics of states, 3) economic characteristics of states, and 4) contextual features of each country. These later characteristics take into account the social-spatial context of each individual country, thereby allowing the models to escape the limitations of treating each country as independent from the influence of events and forces in nearby countries. For each EOI we present a separate prediction model, which captures the unique dynamics of each outcome. Each of these models has a high degree of accuracy in reproducing historical data measured monthly over the past 10 years, and is approximately equally accurate in making three-month forecasts out-of-sample

Towards a General Theory of Neural Computation Based on Prediction by Single Neurons

Although there has been tremendous progress in understanding the mechanics of the nervous system, there has not been a general theory of its computational function. Here I present a theory that relates the established biophysical properties of single generic neurons to principles of Bayesian probability theory, reinforcement learning and efficient coding. I suggest that this theory addresses the general computational problem facing the nervous system. Each neuron is proposed to mirror the function of the whole system in learning to predict aspects of the world related to future reward. According to the model, a typical neuron receives current information about the state of the world from a subset of its excitatory synaptic inputs, and prior information from its other inputs. Prior information would be contributed by synaptic inputs representing distinct regions of space, and by different types of non-synaptic, voltage-regulated channels representing distinct periods of the past. The neuron's membrane voltage is proposed to signal the difference between current and prior information (“prediction error” or “surprise”). A neuron would apply a Hebbian plasticity rule to select those excitatory inputs that are the most closely correlated with reward but are the least predictable, since unpredictable inputs provide the neuron with the most “new” information about future reward. To minimize the error in its predictions and to respond only when excitation is “new and surprising,” the neuron selects amongst its prior information sources through an anti-Hebbian rule. The unique inputs of a mature neuron would therefore result from learning about spatial and temporal patterns in its local environment, and by extension, the external world. Thus the theory describes how the structure of the mature nervous system could reflect the structure of the external world, and how the complexity and intelligence of the system might develop from a population of undifferentiated neurons, each implementing similar learning algorithms

Repurposing the FDA-Approved Anthelmintic Pyrvinium Pamoate for Pancreatic Cancer Treatment: Study Protocol for a Phase I Clinical Trial in Early-Stage Pancreatic Ductal Adenocarcinoma

BACKGROUND: Recent reports of the utilisation of pyrvinium pamoate (PP), an FDA-approved anti-helminth, have shown that it inhibits pancreatic ductal adenocarcinoma (PDAC) cell growth and proliferation in-vitro and in-vivo in preclinical models. Here, we report about an ongoing phase I open-label, single-arm, dose escalation clinical trial to determine the safety and tolerability of PP in PDAC surgical candidates. METHODS AND ANALYSIS: In a 3+3 dose design, PP is initiated 3 days prior to surgery. The first three patients will be treated with the initial dose of PP at 5 mg/kg orally for 3 days prior to surgery. Dose doubling will be continued to a reach a maximum of 20 mg/kg orally for 3 days, if the previous two dosages (5 mg/kg and 10 mg/kg) were tolerated. Dose-limiting toxicity grade≥3 is used as the primary endpoint. The pharmacokinetic and pharmacodynamic (PK/PD) profile of PP and bioavailability in humans will be used as the secondary objective. Each participant will be monitored weekly for a total of 30 days from the final dose of PP for any side effects. The purpose of this clinical trial is to examine whether PP is safe and tolerable in patients with pancreatic cancer, as well as assess the drug\u27s PK/PD profile in plasma and fatty tissue. Potential implications include the utilisation of PP in a synergistic manner with chemotherapeutics for the treatment of pancreatic cancer. ETHICS AND DISSEMINATION: This study was approved by the Thomas Jefferson Institutional Review Board. The protocol number for this study is 20F.041 (Version 3.1 as of 27 October 2021). The data collected and analysed from this study will be used to present at local and national conferences, as well as, written into peer-reviewed manuscript publications. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov: NCT05055323