Automated sulfur-[18F]fluoride exchange radiolabelling of a prostate specific membrane antigen (PSMA) targeted ligand using the GE FASTlab™ cassette-based platform

Sulfur-[18F]fluoride exchange radiochemistry is a rapid and convenient method for incorporating fluorine-18 into biologically active molecules. We report a fully automated radiolabelling procedure for the synthesis of a [18F]SO3F-bearing prostate specific membrane antigen (PSMA) targeted ligand ([18F]5) using the GE FASTLab™ cassette-based platform in a 25.0 ± 2.6% radiochemical yield (decay corrected). Uptake in vitro and in vivo correlated with PSMA expression, and the radioligand exhibited favourable biodistribution and pharmacokinetic profiles

SCH 48973: a Potent, Broad-Spectrum, Antienterovirus Compound.

SCH 48973 is a novel molecule with potent, selective, antienterovirus activity. In assays of the cytopathic effect against five picornaviruses, SCH 48973 had antiviral activity (50% inhibitory concentrations [IC50s]) of 0.02 to 0.11 microg/ml, with no detectable cytotoxicity at 50 microg/ml. SCH 48973 inhibited 80% of 154 recent human enterovirus isolates at an IC50 of 0.9 microg/ml. The antiviral activity of SCH 48973 is derived from its specific interaction with viral capsid, as confirmed by competition binding studies. The affinity constant (Ki) for SCH 48973 binding to poliovirus was 8.85 x 10(-8) M. In kinetic studies, a maximum of approximately 44 molecules of SCH 48973 were bound to poliovirus capsid. SCH 48973 demonstrated efficacy in a murine poliovirus model of enterovirus disease. SCH 48973 increased the survival of infected mice when it was administered orally at dosages of 3 to 20 mg/kg of body weight/day. Oral administration of SCH 48973 also reduced viral titers in the brains of infected mice. On the basis of its in vitro and in vivo profiles, SCH 48973 represents a potential candidate for therapeutic intervention against enterovirus infections

Climate emotions, thoughts, and plans among US adolescents and young adults: a cross-sectional descriptive survey and analysis by political party identification and self-reported exposure to severe weather events

Background Climate change has adverse effects on youth mental health and wellbeing, but limited large-scale data exist globally or in the USA. Understanding the patterns and consequences of climate-related distress among US youth can inform necessary responses at the individual, community, and policy level.Methods A cross-sectional descriptive online survey was done of US youth aged 16–25 years from all 50 states and Washington, DC, between July 20 and Nov 7, 2023, via the Cint digital survey marketplace. The survey assessed: climate-related emotions and thoughts, including indicators of mental health; relational aspects of climate-related emotions; beliefs about who or what has responsibility for causing and responding to climate change; desired and planned actions in response to climate change; and emotions and thoughts about the US Government response to climate change. Respondents were asked whether they had been affected by various severe weather events linked to climate change and for their political party identification. Sample percentages were weighted according to 2022 US census age, sex, and race estimates. To test the effects of political party identification and self-reported exposure to severe weather events on climate-related thoughts and beliefs we used linear and logistic regression models, which included terms for political party identification, the number of self-reported severe weather event types in respondents’ area of residence in the past year, and demographic control variables.Findings We evaluated survey responses from 15 793 individuals (weighted proportions: 80·5% aged 18–25 years and 19·5% aged 16–17 years; 48·8% female and 51·2% male). Overall, 85·0% of respondents endorsed being at least moderately worried, and 57·9% very or extremely worried, about climate change and its impacts on people and the planet. 42·8% indicated an impact of climate change on self-reported mental health, and 38·3% indicated that their feelings about climate change negatively affect their daily life. Respondents reported negative thoughts about the future due to climate change and actions planned in response, including being likely to vote for political candidates who support aggressive climate policy (72·8%). In regression models, self-reported exposure to more types of severe weather events was significantly associated with stronger endorsement of climate-related distress and desire and plans for action. Political party identification as Democrat or as Independent or Other (vs Republican) was also significantly associated with stronger endorsement of distress and desire and plans for action, although a majority of self-identified Republicans reported at least moderate distress. For all survey outcomes assessed in the models, the effect of experiencing more types of severe weather events did not significantly differ by political party identification.Interpretation Climate change is causing widespread distress among US youth and affecting their beliefs and plans for the future. These effects may intensify, across the political spectrum, as exposure to climate-related severe weather events increases

The scale of population structure in Arabidopsis thaliana

The population structure of an organism reflects its evolutionary history and influences its evolutionary trajectory. It constrains the combination of genetic diversity and reveals patterns of past gene flow. Understanding it is a prerequisite for detecting genomic regions under selection, predicting the effect of population disturbances, or modeling gene flow. This paper examines the detailed global population structure of Arabidopsis thaliana. Using a set of 5,707 plants collected from around the globe and genotyped at 149 SNPs, we show that while A. thaliana as a species self-fertilizes 97% of the time, there is considerable variation among local groups. This level of outcrossing greatly limits observed heterozygosity but is sufficient to generate considerable local haplotypic diversity. We also find that in its native Eurasian range A. thaliana exhibits continuous isolation by distance at every geographic scale without natural breaks corresponding to classical notions of populations. By contrast, in North America, where it exists as an exotic species, A. thaliana exhibits little or no population structure at a continental scale but local isolation by distance that extends hundreds of km. This suggests a pattern for the development of isolation by distance that can establish itself shortly after an organism fills a new habitat range. It also raises questions about the general applicability of many standard population genetics models. Any model based on discrete clusters of interchangeable individuals will be an uneasy fit to organisms like A. thaliana which exhibit continuous isolation by distance on many scales

Pre- and Postnatal Fine Particulate Matter Exposure and Childhood Cognitive and Adaptive Function

Increasing evidence exists for an association between early life fine particulate matter (PM2.5) exposure and several neurodevelopmental outcomes, including autism spectrum disorder (ASD); however, the association between PM2.5 and adaptive and cognitive function remains poorly understood. Participants included 658 children with ASD, 771 with a non-ASD developmental disorder, and 849 population controls from the Study to Explore Early Development. Adaptive functioning was assessed in ASD cases using the Vineland Adaptive Behavior Scales (VABS); cognitive functioning was assessed in all groups using the Mullen Scales of Early Learning (MSEL). A satellite-based model was used to assign PM2.5 exposure averages during pregnancy, each trimester, and the first year of life. Linear regression was used to estimate beta coefficients and 95% confidence intervals, adjusting for maternal age, education, prenatal tobacco use, race-ethnicity, study site, and season of birth. PM2.5 exposure was associated with poorer VABS scores for several domains, including daily living skills and socialization. Associations were present between prenatal PM2.5 and lower MSEL scores for all groups combined; results were most prominent for population controls in stratified analyses. These data suggest that early life PM2.5 exposure is associated with specific aspects of cognitive and adaptive functioning in children with and without ASD

First radial velocity results from the MINiature Exoplanet Radial Velocity Array (MINERVA)

The MINiature Exoplanet Radial Velocity Array (MINERVA) is a dedicated observatory of four 0.7m robotic telescopes fiber-fed to a KiwiSpec spectrograph. The MINERVA mission is to discover super-Earths in the habitable zones of nearby stars. This can be accomplished with MINERVA's unique combination of high precision and high cadence over long time periods. In this work, we detail changes to the MINERVA facility that have occurred since our previous paper. We then describe MINERVA's robotic control software, the process by which we perform 1D spectral extraction, and our forward modeling Doppler pipeline. In the process of improving our forward modeling procedure, we found that our spectrograph's intrinsic instrumental profile is stable for at least nine months. Because of that, we characterized our instrumental profile with a time-independent, cubic spline function based on the profile in the cross dispersion direction, with which we achieved a radial velocity precision similar to using a conventional "sum-of-Gaussians" instrumental profile: 1.8 m s$^{-1}$ over 1.5 months on the RV standard star HD 122064. Therefore, we conclude that the instrumental profile need not be perfectly accurate as long as it is stable. In addition, we observed 51 Peg and our results are consistent with the literature, confirming our spectrograph and Doppler pipeline are producing accurate and precise radial velocities.Comment: 22 pages, 9 figures, submitted to PASP, Peer-Reviewed and Accepte

A call for using natural compounds in the development of new antimalarial treatments – an introduction

Natural compounds, mostly from plants, have been the mainstay of traditional medicine for thousands of years. They have also been the source of lead compounds for modern medicine, but the extent of mining of natural compounds for such leads decreased during the second half of the 20th century. The advantage of natural compounds for the development of drugs derives from their innate affinity for biological receptors. Natural compounds have provided the best anti-malarials known to date. Recent surveys have identified many extracts of various organisms (mostly plants) as having antiplasmodial activity. Huge libraries of fractionated natural compounds have been screened with impressive hit rates. Importantly, many cases are known where the crude biological extract is more efficient pharmacologically than the most active purified compound from this extract. This could be due to synergism with other compounds present in the extract, that as such have no pharmacological activity. Indeed, such compounds are best screened by cell-based assay where all potential targets in the cell are probed and possible synergies identified. Traditional medicine uses crude extracts. These have often been shown to provide many concoctions that deal better with the overall disease condition than with the causative agent itself. Traditional medicines are used by ~80 % of Africans as a first response to ailment. Many of the traditional medicines have demonstrable anti-plasmodial activities. It is suggested that rigorous evaluation of traditional medicines involving controlled clinical trials in parallel with agronomical development for more reproducible levels of active compounds could improve the availability of drugs at an acceptable cost and a source of income in malaria endemic countries

The Effective Temperature Scale of Galactic Red Supergiants: Cool, But Not As Cool As We Thought

We use moderate-resolution optical spectrophotometry and the new MARCS stellar atmosphere models to determine the effective temperatures of 74 Galactic red supergiants. From these we find a new effective temperature scale that is significantly warmer than those in the literature. We show that this temperature scale, along with the newly derived bolometric corrections, gives much better agreement between our red supergiants and stellar evolutionary tracks. This agreement provides an independent verification of our new temperature scale. The combination of effective temperature and bolometric luminosities allows us to calculate stellar radii; the coolest and most luminous stars have radii of roughly 1500 solar radii (7 AU), in excellent accordance with the largest stellar radii predicted from current evolutionary theory. We find that similar results are obtained for the effective temperatures and bolometric luminosities using only the de-reddened V-K colors, providing a powerful demonstration of the self-consistency of the MARCS models.Comment: 32 pages, 16 figures; Accepted by the Astrophysical Journa

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes