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Urine drug testing (UDT) monitors prescription compliance and/or drug abuse. However, interpretation of UDT results obtained by liquid chromatography-tandem mass spectrometry (LC-MS-MS) can be complicated by the presence of drug impurities that are detected by highly sensitive methods. Hydrocodone is a drug impurity that can be found as high as 1% in oxycodone pills.We evaluated the frequency and concentration of hydrocodone and its metabolite, hydromorphone, in patients taking oxycodone to check if the ratio of hydrocodone or hydromorphone to oxycodone could distinguish between oxycodone only use from those consuming additional opiates.We correlated LC-MS/MS results with medication records of 319 patients with positive oxycodone results over 7 months (4/2021-11/2021).Fifteen of 319 patients with positive oxycodone results were taking oxycodone only. For these 15 patients, the mean ratio of hydrocodone to oxycodone was 0.57% (range 0.05%-3.35%), and the mean ratio of hydromorphone to oxycodone was 0.81% (range 0.18-3.51%).Hydrocodone and/or hydromorphone are detectable in patients taking only oxycodone and can likely be identified as an impurity if their calculated ratio to oxycodone is1%. Further validation of the ratios in a larger sample size is recommended.

Laboratorians are left unguided by a paucity of literature on how to configure rules for the detection of intravenous (IV) fluid contamination in blood samples. We designed a study to determine the in vitro effect of increasing blood sample contamination from commonly used crystalloid solutions and how these observations can guide the derivation of multianalyte delta checks to detect such pre-analytical error.In this study, we spiked increasing volumes of commonly used IV fluids (normal saline (NS), lactated ringers (LR), and 5% dextrose) into blood samples that were collected from healthy donors. Routine chemistry analytes were measured and compared between neat and contrived samples. From these observations, we derived several permutations of multianalyte delta checks using the basic metabolic panel framework and evaluated rule performance using retrospective data.The wet chemistry experiments showed that increasing the volume of crystalloid solution contamination significantly changed several analytes. Subsequently derived multianalyte delta check procedures were applied to retrospective data. For all IV fluids tested, smaller magnitudes of analyte change resulted in more samples flagged.Multianalyte delta checks may be an effective method for the detection of IV fluid contamination.

In this pilot study, we used a mixed methods online survey to ask science popularizers how gender harassment influences the way they communicate science to the public. Popularizers reported that gender harassment caused the science popularization field to increasingly strive for gender inclusivity in the creation of content. However, harassment made female popularizers feel they must emphasize their legitimacy, quite conscious of their clothing choices, and wary of engaging the public through mediums or topics that provoke more severe harassment. Implications for science communication and public engagement are discussed.

The biological effects of environmental metal contamination are important issues in an industrialized, resource-dependent world. Different metals have different roles in biology and can be classified as essential if they are required by a living organism (e.g., as cofactors), or as non-essential metals if they are not. While essential metal ions have been well studied in many eukaryotic species, less is known about the effects of non-essential metals, even though essential and non-essential metals are often chemically similar and can bind to the same biological ligands. Insects are often exposed to a variety of contaminated environments and associated essential and non-essential metal toxicity, but many questions regarding their response to toxicity remain unanswered. Drosophila melanogaster is an excellent insect model species in which to study the effects of toxic metal due to the extensive experimental and genetic resources available for this species. Here, we review the current understanding of the impact of a suite of essential and non-essential metals (Cu, Fe, Zn, Hg, Pb, Cd, and Ni) on the D. melanogaster metal response system, highlighting the knowledge gaps between essential and non-essential metals in D. melanogaster. This review emphasizes the need to use multiple metals, multiple genetic backgrounds, and both sexes in future studies to help guide future research towards better understanding the effects of metal contamination in general.

Insects hold considerable ecological and agricultural importance making it vital to understand the factors impacting their reproductive output. Environmental stressors are examples of such factors which have a substantial and significant influence on insect reproductive fitness. Insects are also ectothermic and small in size which makes them even more susceptible to environmental stresses. The present study assesses the consequence of desiccation on the mating latency and copulations duration in tropical Drosophila melanogaster. We tested flies for these reproductive behavioral parameters at varying body water levels and with whole metabolome analysis in order to gain a further understanding of the physiological response to desiccation. Our results showed that the duration of desiccation is positively correlated with mating latency and mating failure, while having no influence on the copulation duration. The metabolomic analysis revealed three biological pathways highly affected by desiccation: starch and sucrose metabolism, galactose metabolism, and phenylalanine, tyrosine and tryptophan biosynthesis. These results are consistent with carbohydrate metabolism providing an energy source in desiccated flies and also suggests that the phenylalanine biosynthesis pathway plays a role in the reproductive fitness of the flies. Desiccation is a common issue with smaller insects, like Drosophila and other tropical insects, and our findings indicate that this lack of ambient water can immediately and drastically affect the insect reproductive behaviour, which becomes more crucial because of unpredictable and dynamic weather conditions.

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome datasets from natural populations of this species have been published over the last 20 years. A major challenge is the integration of these disparate datasets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution and population structure of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 population samples from over 100 locations in >20 countries on four continents based on a combination of 121 unpublished and 150 previously published genomic datasets. Several of these locations have been sampled at different seasons across multiple years. This dataset, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental meta-data. A web-based genome browser and web portal provide easy access to the SNP dataset. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan dataset. Our resource will enable population geneticists to analyze spatio-temporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.

To advance our understanding of adaptation to temporally varying selection pressures, we identified signatures of seasonal adaptation occurring in parallel among Drosophila melanogaster populations. Specifically, we estimated allele frequencies genome-wide from flies sampled early and late in the growing season from 20 widely dispersed populations. We identified parallel seasonal allele frequency shifts across North America and Europe, demonstrating that seasonal adaptation is a general phenomenon of temperate fly populations. Seasonally fluctuating polymorphisms are enriched in large chromosomal inversions, and we find a broad concordance between seasonal and spatial allele frequency change. The direction of allele frequency change at seasonally variable polymorphisms can be predicted by weather conditions in the weeks prior to sampling, linking the environment and the genomic response to selection. Our results suggest that fluctuating selection is an important evolutionary force affecting patterns of genetic variation in Drosophila.

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome datasets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate datasets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in > 20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This dataset, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental meta-data. A web-based genome browser and web portal provide easy access to the SNP dataset. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan dataset. Our resource will enable population geneticists to analyze spatio-temporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail., DrosEU is funded by a Special Topic Networks (STN) grant from the European Society for Evolutionary Biology (ESEB). MK (M. Kapun) was supported by the Austrian Science Foundation (grant no. FWF P32275); JG by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (H2020-ERC-2014-CoG-647900) and by the Spanish Ministry of Science and Innovation (BFU-2011-24397); TF by the Swiss National Science Foundation (SNSF grants PP00P3_133641, PP00P3_165836, and 31003A_182262) and a Mercator Fellowship from the German Research Foundation (DFG), held as a EvoPAD Visiting Professor at the Institute for Evolution and Biodiversity, University of Münster; AOB by the National Institutes of Health (R35 GM119686); MK (M. Kankare) by Academy of Finland grant 322980; VL by Danish Natural Science Research Council (FNU) grant 4002-00113B; FS Deutsche Forschungsgemeinschaft (DFG) grant STA1154/4-1, Project 408908608; JP by the Deutsche Forschungsgemeinschaft Projects 274388701 and 347368302; AU by FPI fellowship (BES-2012-052999); ET Israel Science Foundation (ISF) grant 1737/17; MSV, MSR and MJ by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200178); AP, KE and MT by a grant from the Ministry of Education, Science and Technological Development of the Republic of Serbia (451-03-68/2020-14/200007); and TM NSERC grant RGPIN-2018-05551.