The tidyomics ecosystem: enhancing omic data analyses.

The growth of omic data presents evolving challenges in data manipulation, analysis and integration. Addressing these challenges, Bioconductor provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming offers a revolutionary data organization and manipulation standard. Here we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analyzing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas, spanning six data frameworks and ten analysis tools.

Phase separation drives aberrant chromatin looping and cancer development.

The development of cancer is intimately associated with genetic abnormalities that target proteins with intrinsically disordered regions (IDRs). In human haematological malignancies, recurrent chromosomal translocation of nucleoporin (NUP98 or NUP214) generates an aberrant chimera that invariably retains the nucleoporin IDR-tandemly dispersed repeats of phenylalanine and glycine residues1,2. However, how unstructured IDRs contribute to oncogenesis remains unclear. Here we show that IDRs contained within NUP98-HOXA9, a homeodomain-containing transcription factor chimera recurrently detected in leukaemias1,2, are essential for establishing liquid-liquid phase separation (LLPS) puncta of chimera and for inducing leukaemic transformation. Notably, LLPS of NUP98-HOXA9 not only promotes chromatin occupancy of chimera transcription factors, but also is required for the formation of a broad 'super-enhancer'-like binding pattern typically seen at leukaemogenic genes, which potentiates transcriptional activation. An artificial HOX chimera, created by replacing the phenylalanine and glycine repeats of NUP98 with an unrelated LLPS-forming IDR of the FUS protein3,4, had similar enhancing effects on the genome-wide binding and target gene activation of the chimera. Deeply sequenced Hi-C revealed that phase-separated NUP98-HOXA9 induces CTCF-independent chromatin loops that are enriched at proto-oncogenes. Together, this report describes a proof-of-principle example in which cancer acquires mutation to establish oncogenic transcription factor condensates via phase separation, which simultaneously enhances their genomic targeting and induces organization of aberrant three-dimensional chromatin structure during tumourous transformation. As LLPS-competent molecules are frequently implicated in diseases1,2,4-7, this mechanism can potentially be generalized to many malignant and pathological settings.

Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features.

Three-dimensional (3D) chromatin structure has been shown to play a role in regulating gene transcription during biological transitions. Although our understanding of loop formation and maintenance is rapidly improving, much less is known about the mechanisms driving changes in looping and the impact of differential looping on gene transcription. One limitation has been a lack of well-powered differential looping data sets. To address this, we conducted a deeply sequenced Hi-C time course of megakaryocyte development comprising four biological replicates and 6 billion reads per time point. Statistical analysis revealed 1503 differential loops. Gained loop anchors were enriched for AP-1 occupancy and were characterized by large increases in histone H3K27ac (over 11-fold) but relatively small increases in CTCF and RAD21 binding (1.26- and 1.23-fold, respectively). Linear modeling revealed that changes in histone H3K27ac, chromatin accessibility, and JUN binding were better correlated with changes in looping than RAD21 and almost as well correlated as CTCF. Changes to epigenetic features between-rather than at-boundaries were highly predictive of changes in looping. Together these data suggest that although CTCF and RAD21 may be the core machinery dictating where loops form, other features (both at the anchors and within the loop boundaries) may play a larger role than previously anticipated in determining the relative loop strength across cell types and conditions.

Mariner: explore the Hi-Cs.

MOTIVATION: 3D chromatin structure plays an important role in regulating gene expression and alterations to this structure can result in developmental abnormalities and disease. While genomic approaches like Hi-C and Micro-C can provide valuable insights in 3D chromatin architecture, the resulting datasets are extremely large and difficult to manipulate. RESULTS: Here, we present mariner, a rapid and memory efficient tool to extract, aggregate, and plot data from Hi-C matrices within the R/Bioconductor environment. Mariner simplifies the process of querying and extracting contacts from multiple Hi-C files using a parallel and block-processing approach. Modular functions allow complete workflow customization for advanced users, yet all-in-one functions are available for running the most common types of analyses. Finally, tight integration with existing Bioconductor infrastructure enables complete analysis and visualization of Hi-C data in R. AVAILABILITY AND IMPLEMENTATION: Available on GitHub at https://github.com/EricSDavis/mariner and on Bioconductor at https://www.bioconductor.org/packages/release/bioc/html/mariner.html.

bootRanges: flexible generation of null sets of genomic ranges for hypothesis testing.

MOTIVATION: Enrichment analysis is a widely utilized technique in genomic analysis that aims to determine if there is a statistically significant association between two sets of genomic features. To conduct this type of hypothesis testing, an appropriate null model is typically required. However, the null distribution that is commonly used can be overly simplistic and may result in inaccurate conclusions. RESULTS: bootRanges provides fast functions for generation of block bootstrapped genomic ranges representing the null hypothesis in enrichment analysis. As part of a modular workflow, bootRanges offers greater flexibility for computing various test statistics leveraging other Bioconductor packages. We show that shuffling or permutation schemes may result in overly narrow test statistic null distributions and over-estimation of statistical significance, while creating new range sets with a block bootstrap preserves local genomic correlation structure and generates more reliable null distributions. It can also be used in more complex analyses, such as accessing correlations between cis-regulatory elements (CREs) and genes across cell types or providing optimized thresholds, e.g. log fold change (logFC) from differential analysis. AVAILABILITY AND IMPLEMENTATION: bootRanges is freely available in the R/Bioconductor package nullranges hosted at https://bioconductor.org/packages/nullranges.

matchRanges: generating null hypothesis genomic ranges via covariate-matched sampling.

MOTIVATION: Deriving biological insights from genomic data commonly requires comparing attributes of selected genomic loci to a null set of loci. The selection of this null set is non-trivial, as it requires careful consideration of potential covariates, a problem that is exacerbated by the non-uniform distribution of genomic features including genes, enhancers, and transcription factor binding sites. Propensity score-based covariate matching methods allow the selection of null sets from a pool of possible items while controlling for multiple covariates; however, existing packages do not operate on genomic data classes and can be slow for large data sets making them difficult to integrate into genomic workflows. RESULTS: To address this, we developed matchRanges, a propensity score-based covariate matching method for the efficient and convenient generation of matched null ranges from a set of background ranges within the Bioconductor framework. AVAILABILITY AND IMPLEMENTATION: Package: https://bioconductor.org/packages/nullranges, Code: https://github.com/nullranges, Documentation: https://nullranges.github.io/nullranges.

excluderanges: exclusion sets for T2T-CHM13, GRCm39, and other genome assemblies.

SUMMARY: Exclusion regions are sections of reference genomes with abnormal pileups of short sequencing reads. Removing reads overlapping them improves biological signal, and these benefits are most pronounced in differential analysis settings. Several labs created exclusion region sets, available primarily through ENCODE and Github. However, the variety of exclusion sets creates uncertainty which sets to use. Furthermore, gap regions (e.g. centromeres, telomeres, short arms) create additional considerations in generating exclusion sets. We generated exclusion sets for the latest human T2T-CHM13 and mouse GRCm39 genomes and systematically assembled and annotated these and other sets in the excluderanges R/Bioconductor data package, also accessible via the BEDbase.org API. The package provides unified access to 82 GenomicRanges objects covering six organisms, multiple genome assemblies, and types of exclusion regions. For human hg38 genome assembly, we recommend hg38.Kundaje.GRCh38_unified_blacklist as the most well-curated and annotated, and sets generated by the Blacklist tool for other organisms. AVAILABILITY AND IMPLEMENTATION: https://bioconductor.org/packages/excluderanges/. Package website: https://dozmorovlab.github.io/excluderanges/.

Anatomical Substrates of Rapid Eye Movement Sleep Rebound in a Rodent Model of Post-sevoflurane Sleep Disruption.

BACKGROUND: Previous research suggests that sevoflurane anesthesia may prevent the brain from accessing rapid eye movement (REM) sleep. If true, then patterns of neural activity observed in REM-on and REM-off neuronal populations during recovery from sevoflurane should resemble those seen after REM sleep deprivation. In this study, the authors hypothesized that, relative to controls, animals exposed to sevoflurane present with a distinct expression pattern of c-Fos, a marker of neuronal activation, in a cluster of nuclei classically associated with REM sleep, and that such expression in sevoflurane-exposed and REM sleep-deprived animals is largely similar. METHODS: Adult rats and Targeted Recombination in Active Populations mice were implanted with electroencephalographic electrodes for sleep-wake recording and randomized to sevoflurane, REM deprivation, or control conditions. Conventional c-Fos immunohistochemistry and genetically tagged c-Fos labeling were used to quantify activated neurons in a group of REM-associated nuclei in the midbrain and basal forebrain. RESULTS: REM sleep duration increased during recovery from sevoflurane anesthesia relative to controls (157.0 ± 24.8 min vs. 124.2 ± 27.8 min; P = 0.003) and temporally correlated with increased c-Fos expression in the sublaterodorsal nucleus, a region active during REM sleep (176.0 ± 36.6 cells vs. 58.8 ± 8.7; P = 0.014), and decreased c-Fos expression in the ventrolateral periaqueductal gray, a region that is inactive during REM sleep (34.8 ± 5.3 cells vs. 136.2 ± 19.6; P = 0.001). Fos changes similar to those seen in sevoflurane-exposed mice were observed in REM-deprived animals relative to controls (sublaterodorsal nucleus: 85.0 ± 15.5 cells vs. 23.0 ± 1.2, P = 0.004; ventrolateral periaqueductal gray: 652.8 ± 71.7 cells vs. 889.3 ± 66.8, P = 0.042). CONCLUSIONS: In rodents recovering from sevoflurane, REM-on and REM-off neuronal activity maps closely resemble those of REM sleep-deprived animals. These findings provide new evidence in support of the idea that sevoflurane does not substitute for endogenous REM sleep.

Characterization of sleep efficiency transitions in family caregivers.

Family caregivers are at high risk of psychological distress and low sleep efficiency resulting from their caregiving responsibilities. Although psychological symptoms are associated with sleep efficiency, there is limited knowledge about the association of psychological distress with variations in sleep efficiency. We aimed to characterize the short- and long-term patterns of caregivers' sleep efficiency using Markov chain models and compare these patterns between groups with high and low psychological symptoms (i.e., depression, anxiety, and caregiving stress). Based on 7-day actigraphy data from 33 caregivers, we categorized sleep efficiency into three states, < 75% (S1), 75-84% (S2), and ≥ 85% (S3), and developed Markov chain models. Caregivers were likely to maintain a consistent sleep efficiency state from one night to the next without returning efficiently to a normal state. On average, it took 3.6-5.1 days to return to a night of normal sleep efficiency (S3) from lower states, and the long-term probability of achieving normal sleep was 42%. We observed lower probabilities of transitioning to or remaining in a normal sleep efficiency state (S3) in the high depression and anxiety groups compared to the low symptom groups. The differences in the time required to return to a normal state were inconsistent by symptom levels. The long-term probability of achieving normal sleep efficiency was significantly lower for caregivers with high depression and anxiety compared to the low symptom groups. Caregivers' sleep efficiency appears to remain relatively consistent over time and does not show rapid recovery. Caregivers with higher levels of depression and anxiety may be more vulnerable to sustained suboptimal sleep efficiency.

On the Generalizability of Time-of-Flight Convolutional Neural Networks for Noninvasive Acoustic Measurements.

Bulk wave acoustic time-of-flight (ToF) measurements in pipes and closed containers can be hindered by guided waves with similar arrival times propagating in the container wall, especially when a low excitation frequency is used to mitigate sound attenuation from the material. Convolutional neural networks (CNNs) have emerged as a new paradigm for obtaining accurate ToF in non-destructive evaluation (NDE) and have been demonstrated for such complicated conditions. However, the generalizability of ToF-CNNs has not been investigated. In this work, we analyze the generalizability of the ToF-CNN for broader applications, given limited training data. We first investigate the CNN performance with respect to training dataset size and different training data and test data parameters (container dimensions and material properties). Furthermore, we perform a series of tests to understand the distribution of data parameters that need to be incorporated in training for enhanced model generalizability. This is investigated by training the model on a set of small- and large-container datasets regardless of the test data. We observe that the quantity of data partitioned for training must be of a good representation of the entire sets and sufficient to span through the input space. The result of the network also shows that the learning model with the training data on small containers delivers a sufficiently stable result on different feature interactions compared to the learning model with the training data on large containers. To check the robustness of the model, we tested the trained model to predict the ToF of different sound speed mediums, which shows excellent accuracy. Furthermore, to mimic real experimental scenarios, data are augmented by adding noise. We envision that the proposed approach will extend the applications of CNNs for ToF prediction in a broader range.

Plotgardener: cultivating precise multi-panel figures in R.

MOTIVATION: The R programming language is one of the most widely used programming languages for transforming raw genomic datasets into meaningful biological conclusions through analysis and visualization, which has been largely facilitated by infrastructure and tools developed by the Bioconductor project. However, existing plotting packages rely on relative positioning and sizing of plots, which is often sufficient for exploratory analysis but is poorly suited for the creation of publication-quality multi-panel images inherent to scientific manuscript preparation. RESULTS: We present plotgardener, a coordinate-based genomic data visualization package that offers a new paradigm for multi-plot figure generation in R. Plotgardener allows precise, programmatic control over the placement, esthetics and arrangements of plots while maximizing user experience through fast and memory-efficient data access, support for a wide variety of data and file types, and tight integration with the Bioconductor environment. Plotgardener also allows precise placement and sizing of ggplot2 plots, making it an invaluable tool for R users and data scientists from virtually any discipline. AVAILABILITY AND IMPLEMENTATION: Package: https://bioconductor.org/packages/plotgardener, Code: https://github.com/PhanstielLab/plotgardener, Documentation: https://phanstiellab.github.io/plotgardener/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Sleep Fragmentation, Electroencephalographic Slowing, and Circadian Disarray in a Mouse Model for Intensive Care Unit Delirium.

BACKGROUND: We aimed to further validate our previously published animal model for delirium by testing the hypothesis that in aged mice, Anesthesia, Surgery and simulated ICU conditions (ASI) induce sleep fragmentation, electroencephalographic (EEG) slowing, and circadian disarray consistent with intensive care unit (ICU) patients with delirium. METHODS: A total of 41 mice were used. Mice were implanted with EEG electrodes and randomized to ASI or control groups. ASI mice received laparotomy, anesthesia, and simulated ICU conditions. Controls did not receive ASI. Sleep was recorded at the end of ICU conditions, and hippocampal tissue was collected on EEG recording. Arousals, EEG dynamics, and circadian gene expression were compared with t tests. Two-way repeated measures analysis of variance (RM ANOVA) was used to assess sleep according to light. RESULTS: ASI mice experienced frequent arousals (36.6 ± 3.2 vs 26.5 ± 3.4; P = .044; 95% confidence interval [CI], 0.29-19.79; difference in mean ± SEM, 10.04 ± 4.62) and EEG slowing (frontal theta ratio, 0.223 ± 0.010 vs 0.272 ± 0.019; P = .026; 95% CI, -0.091 to -0.007; difference in mean ± SEM, -0.05 ± 0.02) relative to controls. In ASI mice with low theta ratio, EEG slowing was associated with a higher percentage of quiet wakefulness (38.2 ± 3.6 vs 13.4 ± 3.8; P = .0002; 95% CI, -35.87 to -13.84; difference in mean ± SEM, -24.86 ± 5.19). ASI mice slept longer during the dark phases of the circadian cycle (nonrapid eye movement [NREM], dark phase 1 [D1]: 138.9 ± 8.1 minutes vs 79.6 ± 9.6 minutes, P = .0003, 95% CI, -95.87 to -22.69, predicted mean difference ± SE: -59.28 ± 13.89; NREM, dark phase 2 (D2): 159.3 ± 7.3 minutes vs 112.6 ± 15.5 minutes, P = .006, 95% CI, -83.25 to -10.07, mean difference ± SE, -46.66 ± 13.89; rapid eye movement (REM), D1: 20.5 ± 2.1 minutes vs 5.8 ± 0.8 minutes, P = .001, 95% CI, -24.60 to -4.71, mean difference ± SE, -14. 65 ± 3.77; REM, D2: 21.0 ± 2.2 minutes vs 10.3 ± 1.4 minutes, P = .029, 95% CI, -20.64 to -0.76, mean difference ± SE, -10.70 ± 3.77). The expression of essential circadian genes was also lower in ASI mice (basic helix-loop-helix ARNT like [BMAL1] : -1.3 fold change; circadian locomotor output cycles protein kaput [CLOCK] : -1.2). CONCLUSIONS: ASI mice experienced EEG and circadian changes mimicking those of delirious ICU patients. These findings support further exploration of this mouse approach to characterize the neurobiology of delirium.

Role of nanoparticle size and surface chemistry on ion transport and nanostructure of perfluorosulfonic acid ionomer nanocomposites.

Herein, we present a systematic investigation of the impact of silica nanoparticle (SiNP) size and surface chemistry on the nanoparticle dispersion state and the resulting morphology and vanadium ion permeability of the composite ionomer membranes. Specifically, Nafion containing a mass fraction of 5% silica particles, ranging in nominal diameters from 10 nm to >1 µm and with both sulfonic acid- and amine-functionalized surfaces, was fabricated. Most notably, an 80% reduction in vanadium ion permeability was observed for ionomer membranes containing amine-functionalized SiNPs at a nominal diameter of 200 nm. Further, these membranes exhibited an almost 400% increase in proton selectivity when compared to pristine Nafion. Trends in vanadium ion permeability within a particular nominal diameter were seen to be a function of the surface chemistry, where, for example, vanadyl ion permeability was observed to increase with increasing particle size for membranes containing unfunctionalized SiNPs, while it was seen to remain relatively constant for membranes containing amine-functionalized SiNPs. In general, the silica particles tended to exhibit a higher extent of aggregation as the size of the particles was increased. From small-angle neutron scattering experiments, an increase in the spacing of the hydrophobic domains was observed for all composite membranes, though particle size and surface chemistry were seen to have varying impacts on the spacing of the ionic domains of the ionomer.

Chronic E-Cigarette Exposure Alters Human Alveolar Macrophage Morphology and Gene Expression.

INTRODUCTION: Alveolar macrophages (AMs) are lung-resident immune cells that phagocytose inhaled particles and pathogens, and help coordinate the lung's immune response to infection. Little is known about the impact of chronic e-cigarette use (ie, vaping) on this important pulmonary cell type. Thus, we determined the effect of vaping on AM phenotype and gene expression. AIMS AND METHODS: We recruited never-smokers, smokers, and e-cigarette users (vapers) and performed research bronchoscopies to isolate AMs from bronchoalveolar lavage fluid samples and epithelial cells from bronchial brushings. We then performed morphological analyses and used the Nanostring platform to look for changes in gene expression. RESULTS: AMs obtained from smokers and vapers were phenotypically distinct from those obtained from nonsmokers, and from each other. Immunocytochemistry revealed that vapers AMs had significantly elevated inducible nitric oxide synthase (M1) expression and significantly reduced CD301a (M2) expression compared with nonsmokers or smokers. Vapers' AMs and bronchial epithelia exhibited unique changes in gene expression compared with nonsmokers or smokers. Moreover, vapers' AMs were the most affected of all groups and had 124 genes uniquely downregulated. Gene ontology analysis revealed that vapers and smokers had opposing changes in biological processes. CONCLUSIONS: These data indicate that vaping causes unique changes to AMs and bronchial epithelia compared with nonsmokers and smokers which may impact pulmonary host defense. IMPLICATIONS: These data indicate that normal "healthy" vapers have altered AMs and may be at risk of developing abnormal immune responses to inflammatory stimuli.

Preoperative REM sleep is associated with complication development after colorectal surgery.

BACKGROUND: While total sleep duration and rapid eye movement (REM) sleep duration have been associated with long-term mortality in non-surgical cohorts, the impact of preoperative sleep on postoperative outcomes has not been well studied. METHODS: In this secondary analysis of a prospective observational cohort study, patients who recorded at least 1 sleep episode using a consumer wearable device in the 7 days before elective colorectal surgery were included. 30-day postoperative outcomes among those who did and did not receive at least 6 h of total sleep, as well as those who did and did not receive at least 1 h of rapid eye movement (REM) sleep, were compared. RESULTS: 34 out of 95 (35.8%) patients averaged at least 6 h of sleep per night, while 44 out of 82 (53.7%) averaged 1 h or more of REM sleep. Patients who slept less than 6 h had similar postoperative outcomes compared to those who slept 6 h or more. Patients who averaged less than 1 h of REM sleep, compared to those who achieved 1 h or more of REM sleep, had significantly higher rates of complication development (29.0% vs. 9.1%, P = 0.02), and return to the OR (10.5% vs. 0%, P = 0.04). After adjustment for confounding factors, increased REM sleep duration remained significantly associated with decreased complication development (increase in REM sleep from 50 to 60 min: OR 0.72, P = 0.009; REM sleep ≥ 1 h: OR 0.22, P = 0.03). CONCLUSION: In this cohort of patients undergoing elective colorectal surgery, those who developed a complication within 30 days were less likely to average at least 1 h of REM sleep in the week before surgery than those who did not develop a complication. Preoperative REM sleep duration may represent a risk factor for surgical complications; however additional research is necessary to confirm this relationship.

Cardiovascular Disease Incidence and Risk in Family Caregivers of Adults With Chronic Conditions: A Systematic Review.

BACKGROUND: Family caregivers experience psychological distress or physical strain that may lead to an increased risk of cardiovascular disease (CVD) morbidity and mortality. OBJECTIVE: This systematic review aimed to describe the current evidence and gaps in the literature on measures used to assess CVD outcomes in family caregivers, the association of caregiving with CVD incidence/risk outcomes, and associated factors in family caregivers of patients with chronic disease. METHODS: Medline, PubMed, CINAHL, Web of Science, and Google Scholar were searched for English-language, peer-reviewed studies published from 2008 to 2020 that examined CVD incidence and risk among family caregivers of adults with chronic conditions. RESULTS: Forty-one studies were included in this review. The measures used to assess CVD risk were categorized into biochemical, subclinical markers, components of metabolic syndrome, and global risk scores. Compared with noncaregivers, caregivers were more likely to have higher CVD incidence rates and objectively measured risk. Cardiovascular disease risks were also increased by their caregiving experience, including hours/duration of caregiving, caregivers' poor sleep status, psychological symptoms, poor engagement in physical/leisure activities, and care recipient's disease severity. CONCLUSIONS: Although there were limited longitudinal studies in caregivers of patients with diverse health conditions, we found evidence that caregivers are at high risk of CVD. Further research for various caregiver groups using robust methods of measuring CVD risk is needed. Caregiver factors should be considered in developing interventions aimed at reducing CVD risk for caregivers.

Phytonematode peptide effectors exploit a host post-translational trafficking mechanism to the ER using a novel translocation signal.

Cyst nematodes induce a multicellular feeding site within roots called a syncytium. It remains unknown how root cells are primed for incorporation into the developing syncytium. Furthermore, it is unclear how CLAVATA3/EMBRYO SURROUNDING REGION (CLE) peptide effectors secreted into the cytoplasm of the initial feeding cell could have an effect on plant cells so distant from where the nematode is feeding as the syncytium expands. Here we describe a novel translocation signal within nematode CLE effectors that is recognized by plant cell secretory machinery to redirect these peptides from the cytoplasm to the apoplast of plant cells. We show that the translocation signal is functionally conserved across CLE effectors identified in nematode species spanning three genera and multiple plant species, operative across plant cell types, and can traffic other unrelated small peptides from the cytoplasm to the apoplast of host cells via a previously unknown post-translational mechanism of endoplasmic reticulum (ER) translocation. Our results uncover a mechanism of effector trafficking that is unprecedented in any plant pathogen to date, andthey illustrate how phytonematodes can deliver effector proteins into host cells and then hijack plant cellular processes for their export back out of the cell to function as external signaling molecules to distant cells.

Evaluation of e-liquid toxicity using an open-source high-throughput screening assay.

The e-liquids used in electronic cigarettes (E-cigs) consist of propylene glycol (PG), vegetable glycerin (VG), nicotine, and chemical additives for flavoring. There are currently over 7,700 e-liquid flavors available, and while some have been tested for toxicity in the laboratory, most have not. Here, we developed a 3-phase, 384-well, plate-based, high-throughput screening (HTS) assay to rapidly triage and validate the toxicity of multiple e-liquids. Our data demonstrated that the PG/VG vehicle adversely affected cell viability and that a large number of e-liquids were more toxic than PG/VG. We also performed gas chromatography-mass spectrometry (GC-MS) analysis on all tested e-liquids. Subsequent nonmetric multidimensional scaling (NMDS) analysis revealed that e-liquids are an extremely heterogeneous group. Furthermore, these data indicated that (i) the more chemicals contained in an e-liquid, the more toxic it was likely to be and (ii) the presence of vanillin was associated with higher toxicity values. Further analysis of common constituents by electron ionization revealed that the concentration of cinnamaldehyde and vanillin, but not triacetin, correlated with toxicity. We have also developed a publicly available searchable website (www.eliquidinfo.org). Given the large numbers of available e-liquids, this website will serve as a resource to facilitate dissemination of this information. Our data suggest that an HTS approach to evaluate the toxicity of multiple e-liquids is feasible. Such an approach may serve as a roadmap to enable bodies such as the Food and Drug Administration (FDA) to better regulate e-liquid composition.

Cellular effects of nicotine salt-containing e-liquids.

"Pod-based" e-cigarettes such as JUUL are currently the most prevalent electronic nicotine delivery systems (ENDS) in the United States. JUUL-type ENDS utilize nicotine salts protonated with benzoic acid rather than freebase nicotine. However, limited information is available on the cellular effects of these products. Cytoplasmic Ca2+ is a universal second messenger that controls many cellular functions including cell growth and cell death. Of note, dysregulation of cell Ca2+ homeostasis has been linked with several disease processes including autoimmune disease and several types of cancer. We exposed HEK293T cells and THP-1 macrophage-like cells to different JUUL e-liquids. We evaluated their effects on cellular viability and Ca2+ signaling by measuring fluorescence from calcein-AM/propidium iodide and Fluo-4, respectively. E-liquid autofluorescence was used to look for e-liquid permeation into cells. To identify the mechanisms behind the Ca2+ responses, different inhibitors of Ca2+ channels and phospholipase C signaling were used. JUUL e-liquids caused significant cytotoxic effects, with "Mint" flavor being the most cytotoxic. The Mint flavored e-liquid also caused a significant elevation in cytoplasmic Ca2+ . Using autofluorescence, the permeation of JUUL e-liquids into live cells was confirmed, indicating that intracellular organelles are directly exposed to e-liquids. Further studies identified the endoplasmic reticulum as being the source of e-liquid-induced changes in cytoplasmic Ca2+ . Nicotine salt-based e-liquids cause cytotoxicity and elevate cytoplasmic Ca2+ , indicating that they can exert biological effects beyond what would be expected with nicotine alone. These effects are flavor-dependent, and we propose that flavored e-liquids be reassessed for potential lung toxicity.

Screening Sweetpotato Genotypes for Resistance to a North Carolina Isolate of Meloidogyne enterolobii.

Potential resistance to the guava root-knot nematode, Meloidogyne enterolobii, in 91 selected sweetpotato (Ipomoea batatas [L.] Lam.) genotypes was evaluated in six greenhouse experiments. Ten thousand eggs of M. enterolobii were inoculated on each sweetpotato genotype grown in a 3:1 sand to soil mixture. Sixty days after inoculation, the percentage of total roots with nematode-induced galls was determined, and nematode eggs were extracted from roots. Significant differences (P < 0.001) between sweetpotato genotypes were found in all six tests for gall rating, total eggs, and eggs per gram of root. Resistant sweetpotato genotypes were calculated as final eggs per root system divided by the initial inoculum, where Pf/Pi < 1 (reproduction factor; final egg count divided by initial inoculum of 10,000 eggs), and statistical mean separations were confirmed by Fisher's least significant difference t test. Our results indicated that 19 out of 91 tested sweetpotato genotypes were resistant to M. enterolobii. Some of the susceptible genotypes included 'Covington,' 'Beauregard,' 'NCDM04-001', and 'Hernandez.' Some of the resistant sweetpotato genotypes included 'Tanzania,' 'Murasaki-29,' 'Bwanjule,' 'Dimbuka-Bukulula,' 'Jewel,' and 'Centennial.' Most of the 19 resistant sweetpotato genotypes supported almost no M. enterolobii reproduction, with <20 eggs/g root of M. enterolobii. A number of segregants from a 'Tanzania' × 'Beauregard' cross demonstrated strong resistance to M. enterolobii observed in the 'Tanzania' parent. In collaboration with North Carolina State University sweetpotato breeding program, several genotypes evaluated in these tests are being used to incorporate the observed resistance to M. enterolobii into commercial sweetpotato cultivars.