Molecular encoding of stimulus features in a single sensory neuron type enables neuronal and behavioral plasticity.

Neurons modify their transcriptomes in response to an animal's experience. How specific experiences are transduced to modulate gene expression and precisely tune neuronal functions are not fully defined. Here, we describe the molecular profile of a thermosensory neuron pair in C. elegans experiencing different temperature stimuli. We find that distinct salient features of the temperature stimulus, including its duration, magnitude of change, and absolute value, are encoded in the gene expression program in this single neuron type, and we identify a novel transmembrane protein and a transcription factor whose specific transcriptional dynamics are essential to drive neuronal, behavioral, and developmental plasticity. Expression changes are driven by broadly expressed activity-dependent transcription factors and corresponding cis-regulatory elements that nevertheless direct neuron- and stimulus-specific gene expression programs. Our results indicate that coupling of defined stimulus characteristics to the gene regulatory logic in individual specialized neuron types can customize neuronal properties to drive precise behavioral adaptation.

Generation of anti-GD2 CAR macrophages from human pluripotent stem cells for cancer immunotherapies.

Macrophages armed with chimeric antigen receptors (CARs) provide a potent new option for treating solid tumors. However, genetic engineering and scalable production of somatic macrophages remains significant challenges. Here, we used CRISPR-Cas9 gene editing methods to integrate an anti-GD2 CAR into the AAVS1 locus of human pluripotent stem cells (hPSCs). We then established a serum- and feeder-free differentiation protocol for generating CAR macrophages (CAR-Ms) through arterial endothelial-to-hematopoietic transition (EHT). CAR-M produced by this method displayed a potent cytotoxic activity against GD2-expressing neuroblastoma and melanoma in vitro and neuroblastoma in vivo. This study provides a new platform for the efficient generation of off-the-shelf CAR-Ms for antitumor immunotherapy.

Molecular encoding of stimulus features in a single sensory neuron type enables neuronal and behavioral plasticity.

Neurons modify their transcriptomes in response to an animal’s experience. How specific experiences are transduced to modulate gene expression and precisely tune neuronal functions are not fully defined. Here, we describe the molecular profile of a thermosensory neuron pair in C. elegans experiencing different temperature stimuli. We find that distinct salient features of the temperature stimulus including its duration, magnitude of change, and absolute value are encoded in the gene expression program in this single neuron, and identify a novel transmembrane protein and a transcription factor whose specific transcriptional dynamics are essential to drive neuronal, behavioral, and developmental plasticity. Expression changes are driven by broadly expressed activity-dependent transcription factors and corresponding cis -regulatory elements that nevertheless direct neuron- and stimulus-specific gene expression programs. Our results indicate that coupling of defined stimulus characteristics to the gene regulatory logic in individual specialized neuron types can customize neuronal properties to drive precise behavioral adaptation.

Quality of Late-Life Depression Information on the Internet: Website Evaluation Study.

BACKGROUND: The internet can increase the accessibility of mental health information and improve the mental health literacy of older adults. The quality of mental health information on the internet can be inaccurate or biased, leading to misinformation. OBJECTIVE: This study aims to evaluate the quality, usability, and readability of websites providing information concerning depression in later life. METHODS: Websites were identified through a Google search and evaluated by assessing quality (DISCERN), usability (Patient Education Materials Assessment Tool), and readability (Simple Measure of Gobbledygook). RESULTS: The overall quality of late-life depression websites (N=19) was adequate, and the usability and readability were poor. No significant relationship was found between the quality and readability of the websites. CONCLUSIONS: The websites can be improved by enhancing information quality, usability, and readability related to late-life depression. The use of high-quality websites may improve mental health literacy and shared treatment decision-making for older adults.

Examining Anxiety Treatment Information Needs: Web-Based Survey Study.

BACKGROUND: Several treatments for anxiety are available, which can make treatment decisions difficult. Resources are often produced with limited knowledge of what information is of interest to consumers. This is a problem because there is limited understanding of what people want to know when considering help for anxiety. OBJECTIVE: This study aimed to examine the information needs and preferences concerning treatment options for anxiety by assessing the following: what information people consider to be important when they are considering treatment options for anxiety, what information people have received on psychological and medication treatment in the past, how they received this information in the past, and whether there are any differences in information needs between specific samples and demographic groups. METHODS: Using a web-based survey, we recruited participants from a peer-support association website (n=288) and clinic samples (psychology, n=113; psychiatry, n=64). RESULTS: Participants in all samples wanted information on a broad range of topics pertaining to anxiety treatment. However, they reported that they did not receive the desired amount of information. Participants in the clinic samples rated the importance of information topics higher than did those in the self-help sample. When considering the anxiety treatment information received in the past, most respondents indicated receiving information from informational websites, family doctors, and mental health practitioners. In terms of what respondents want to learn about, high ratings of importance were given to topics concerning treatment effectiveness, how it works, advantages and disadvantages, what happens when it stops, and common side effects. CONCLUSIONS: It is challenging for individuals to obtain anxiety-related information on the range of topics they desire through currently available information sources. It is also difficult to provide comprehensive information during typical clinical visits. Providing evidence-based information on the web and in a brochure format may help consumers make informed choices and support the advice provided by health professionals.

An evaluation of the quality of online perinatal depression information.

BACKGROUND: During the perinatal period (including pregnancy and up to 12 months after childbirth), expectant and new mothers are at an elevated risk of developing depression. Inadequate knowledge about perinatal depression and treatment options may contribute to the low help-seeking rates exhibited by perinatal people. The Internet can be an accessible source of information about perinatal depression; however, the quality of this information remains to be evaluated. The purpose of this study was to assess the quality of perinatal depression information websites. METHODS: After review, 37 websites were included in our sample. To assess overall website quality, we rated websites based on their reading level (Simple Measure of Gobbledegook; SMOG), information quality (DISCERN), usability (Patient Education Materials Assessment Tool; PEMAT), and visual design (Visual Aesthetics of Website Inventory; VisAWI). RESULTS: Websites often exceeded the National Institute of Health's recommended reading level of grades 6-8, with scores ranging from 6.8 to 13.5. Website information quality ratings ranged from 1.8 to 4.3 out of 5, with websites often containing insufficient information about treatment choices. Website usability ratings were negatively impacted by the lack of information summaries, visual aids, and tangible tools. Visual design ratings ranged from 3.2 to 6.6 out of 7, with a need for more creative design elements to enhance user engagement. CONCLUSIONS: This study outlines the characteristics of high-quality perinatal depression information websites. Our findings illustrate that perinatal depression websites are not meeting the needs of users in terms of reading level, information quality, usability, and visual design. Our results may be helpful in guiding healthcare providers to reliable, evidence-based online resources for their perinatal patients.

Impaired or invalid? Limitations of assessing performance validity using the Boston Naming Test.

The Boston Naming Test (BNT) has been proposed as an embedded performance validity test (PVT), though replication is needed to provide further empirical support of its simultaneous use as a cognitive ability measure and embedded PVT. This cross-sectional study examined BNT performance in a mixed neuropsychiatric sample of 137 patients with/without cognitive impairment. Four independent criterion PVTs classified 109 (80%) as valid and 28 (20%) as invalid. BNT raw and demographically-corrected T-scores were significantly higher among the valid group with small effect sizes (ηp2 = 0.04-0.05). Raw/T-scores differentiated valid/invalid groups, but with low classification accuracy (areas under the curve [AUCs] = 0.68/0.63), and unacceptably weak sensitivities (i.e. 7%/18%). When separated by impairment status, raw score accuracy appreciably increased (AUC = 0.87; 61% sensitivity/89% specificity) among unimpaired patients, whereas T-score accuracy, while significant, remained low (AUC = 0.68; 21% sensitivity/89% specificity). Conversely, among impaired patients, neither the raw (AUC = 0.59) nor T-score (AUC = 0.60) accurately identified invalid performance. In sum, BNT scores were not able to differentiate valid from invalid performance when cognitive impairment was present, and therefore showed limited overall utility as embedded PVTs. These findings further caution against inferring performance validity from measures in which a single score is used to assess both cognitive ability and validity.

SpatialCorr identifies gene sets with spatially varying correlation structure.

Recent advances in spatially resolved transcriptomics technologies enable both the measurement of genome-wide gene expression profiles and their mapping to spatial locations within a tissue. A first step in spatial transcriptomics data analysis is identifying genes with expression that varies spatially, and robust statistical methods exist to address this challenge. While useful, these methods do not detect spatial changes in the coordinated expression within a group of genes. To this end, we present SpatialCorr, a method for identifying sets of genes with spatially varying correlation structure. Given a collection of gene sets pre-defined by a user, SpatialCorr tests for spatially induced differences in the correlation of each gene set within tissue regions, as well as between and among regions. An application to cutaneous squamous cell carcinoma demonstrates the power of the approach for revealing biological insights not identified using existing methods.

Do anxiety websites have the answers people are looking for?

OBJECTIVES AND METHODS: A wealth of online anxiety information exists but much of it is not evidence-based or well-balanced. This study evaluated anxiety websites (N = 20) on readability, quality, usability, visual design, and content. RESULTS: Overall, websites were of reasonable quality but only half were considered understandable according to the PEMAT usability scale (70% cutoff value). The average reading level across websites was 11.2 (SMOG), which is higher than NIH recommended grade 6-7 level. Websites had variable design features and a trending association suggested websites with better design come up earlier in search results. The number of topics covered varied across websites and most did not adequately cover all topics of interest. Most websites included information about psychological and self-help treatments, how treatment works, and what treatment entails. The Top 5 websites were: (1) Anxiety BC, (2) ADAA, (3) Mind, (4) Beyond Blue, and (5) Web MD. CONCLUSIONS: This is the first study to evaluate existing anxiety information websites based on the dimensions described above and their relationship to Google search results. PRACTICE IMPLICATIONS: This study highlights the importance of considering several dimensions in developing mental health resources and provides direction for strategies to improve existing websites and/or develop new resources.

Identification of direct transcriptional targets of NFATC2 that promote ß cell proliferation.

The transcription factor NFATC2 induces ß cell proliferation in mouse and human islets. However, the genomic targets that mediate these effects have not been identified. We expressed active forms of Nfatc2 and Nfatc1 in human islets. By integrating changes in gene expression with genomic binding sites for NFATC2, we identified approximately 2200 transcriptional targets of NFATC2. Genes induced by NFATC2 were enriched for transcripts that regulate the cell cycle and for DNA motifs associated with the transcription factor FOXP. Islets from an endocrine-specific Foxp1, Foxp2, and Foxp4 triple-knockout mouse were less responsive to NFATC2-induced ß cell proliferation, suggesting the FOXP family works to regulate ß cell proliferation in concert with NFATC2. NFATC2 induced ß cell proliferation in both mouse and human islets, whereas NFATC1 did so only in human islets. Exploiting this species difference, we identified approximately 250 direct transcriptional targets of NFAT in human islets. This gene set enriches for cell cycle-associated transcripts and includes Nr4a1. Deletion of Nr4a1 reduced the capacity of NFATC2 to induce ß cell proliferation, suggesting that much of the effect of NFATC2 occurs through its induction of Nr4a1. Integration of noncoding RNA expression, chromatin accessibility, and NFATC2 binding sites enabled us to identify NFATC2-dependent enhancer loci that mediate ß cell proliferation.

Annotating cell types in human single-cell RNA-seq data with CellO.

Cell type annotation is important in the analysis of single-cell RNA-seq data. CellO is a machine-learning-based tool for annotating cells using the Cell Ontology, a rich hierarchy of known cell types. We provide a protocol for using the CellO Python package to annotate human cells. We demonstrate how to use CellO in conjunction with Scanpy, a Python library for performing single-cell analysis, annotate a lung tissue data set, interpret its hierarchically structured cell type annotations, and create publication-ready figures. For complete details on the use and execution of this protocol, please refer to Bernstein et al. (2021).

The Anna Karenina Model of ß-Cell Maturation in Development and Their Dedifferentiation in Type 1 and Type 2 Diabetes.

Loss of mature ß-cell function and identity, or ß-cell dedifferentiation, is seen in both type 1 and type 2 diabetes. Two competing models explain ß-cell dedifferentiation in diabetes. In the first model, ß-cells dedifferentiate in the reverse order of their developmental ontogeny. This model predicts that dedifferentiated ß-cells resemble ß-cell progenitors. In the second model, ß-cell dedifferentiation depends on the type of diabetogenic stress. This model, which we call the "Anna Karenina" model, predicts that in each type of diabetes, ß-cells dedifferentiate in their own way, depending on how their mature identity is disrupted by any particular diabetogenic stress. We directly tested the two models using a ß-cell-specific lineage-tracing system coupled with RNA sequencing in mice. We constructed a multidimensional map of ß-cell transcriptional trajectories during the normal course of ß-cell postnatal development and during their dedifferentiation in models of both type 1 diabetes (NOD) and type 2 diabetes (BTBR-Lepob/ob ). Using this unbiased approach, we show here that despite some similarities between immature and dedifferentiated ß-cells, ß-cell dedifferentiation in the two mouse models is not a reversal of developmental ontogeny and is different between different types of diabetes.

CHARTS: a web application for characterizing and comparing tumor subpopulations in publicly available single-cell RNA-seq data sets.

BACKGROUND: Single-cell RNA-seq (scRNA-seq) enables the profiling of genome-wide gene expression at the single-cell level and in so doing facilitates insight into and information about cellular heterogeneity within a tissue. This is especially important in cancer, where tumor and tumor microenvironment heterogeneity directly impact development, maintenance, and progression of disease. While publicly available scRNA-seq cancer data sets offer unprecedented opportunity to better understand the mechanisms underlying tumor progression, metastasis, drug resistance, and immune evasion, much of the available information has been underutilized, in part, due to the lack of tools available for aggregating and analysing these data. RESULTS: We present CHARacterizing Tumor Subpopulations (CHARTS), a web application for exploring publicly available scRNA-seq cancer data sets in the NCBI's Gene Expression Omnibus. More specifically, CHARTS enables the exploration of individual gene expression, cell type, malignancy-status, differentially expressed genes, and gene set enrichment results in subpopulations of cells across tumors and data sets. Along with the web application, we also make available the backend computational pipeline that was used to produce the analyses that are available for exploration in the web application. CONCLUSION: CHARTS is an easy to use, comprehensive platform for exploring single-cell subpopulations within tumors across the ever-growing collection of public scRNA-seq cancer data sets. CHARTS is freely available at charts.morgridge.org.

A Systematic Review and Meta-Analysis of the Diagnostic Accuracy of the Advanced Clinical Solutions Word Choice Test as a Performance Validity Test.

Thorough assessment of performance validity has become an established standard of practice in neuropsychological assessment. While there has been a large focus on the development and cross-validation of embedded performance validity tests (PVTs) in recent years, new freestanding PVTs have also been developed, including the Word Choice Test (WCT) as part of the Advanced Clinical Solutions Effort System. And, while the WCT's general utility for identifying invalid performance has been demonstrated in the ensuing decade since its initial publication, optimal cut-scores and associated psychometric properties have varied widely across studies. This study sought to synthesize the existing diagnostic accuracy literature regarding the WCT via a systematic review and to conduct a meta-analysis to determine the performance validity cut-score that best maximizes sensitivity while maintaining acceptable specificity. A systematic search of the literature resulted in 14 studies for synthesis, with eight of those available for meta-analysis. Meta-analytic results revealed an optimal cut-score of ≤ 42 with 54% sensitivity and 93% specificity for identifying invalid neuropsychological test performance. Collectively, the WCT demonstrated adequate diagnostic accuracy as a PVT across a variety of populations. Recommendations for future studies are also provided.

Victoria Symptom Validity Test: A Systematic Review and Cross-Validation Study.

The Victoria Symptom Validity Test (VSVT) is a performance validity test (PVT) with over two decades of empirical backing, although methodological limitations within the extant literature restrict its clinical and research generalizability. Chief among these constraints includes limited consensus on the most accurate index within the VSVT and the most appropriate cut-scores within each VSVT validity index. The current systematic review synthesizes existing VSVT validation studies and provides additional cross-validation in an independent sample using a known-groups design. We completed a systematic search of the literature, identifying 17 peer-reviewed studies for synthesis (7 simulation designs, 7 differential prevalence designs, and 3 known-groups designs). The independent cross-validation sample consisted of 200 mixed clinical neuropsychiatric patients referred for outpatient neuropsychological evaluation. Across all indices, Total item accuracy produced the strongest psychometric properties at an optimal cut-score of ≤ 40 (62% sensitivity/88% specificity). However, ROC curve analyses for all VSVT indices yielded statistically significant areas under the curve (AUCs; .73-81), suggestive of moderate classification accuracy. Cut-scores derived using the independent cross-validation sample converged with some previous findings supporting cut-scores of ≤ 22 for Easy item accuracy and ≤ 40 for Total item accuracy, although divergent findings were noted for Difficult item accuracy. Overall, VSVT validity indicators have adequate diagnostic accuracy across populations, with the current study providing additional support for its use as a psychometrically sound PVT in clinical settings. However, caution is recommended among patients with certain verified clinical conditions (e.g., dementia) and those with pronounced working memory deficits due to concerns for increased risk of false positives.

Large-Scale Multi-omic Analysis of COVID-19 Severity.

We performed RNA-seq and high-resolution mass spectrometry on 128 blood samples from COVID-19-positive and COVID-19-negative patients with diverse disease severities and outcomes. Quantified transcripts, proteins, metabolites, and lipids were associated with clinical outcomes in a curated relational database, uniquely enabling systems analysis and cross-ome correlations to molecules and patient prognoses. We mapped 219 molecular features with high significance to COVID-19 status and severity, many of which were involved in complement activation, dysregulated lipid transport, and neutrophil activation. We identified sets of covarying molecules, e.g., protein gelsolin and metabolite citrate or plasmalogens and apolipoproteins, offering pathophysiological insights and therapeutic suggestions. The observed dysregulation of platelet function, blood coagulation, acute phase response, and endotheliopathy further illuminated the unique COVID-19 phenotype. We present a web-based tool (covid-omics.app) enabling interactive exploration of our compendium and illustrate its utility through a machine learning approach for prediction of COVID-19 severity.

Ranking microbiome variance in inflammatory bowel disease: a large longitudinal intercontinental study.

OBJECTIVE: The microbiome contributes to the pathogenesis of inflammatory bowel disease (IBD) but the relative contribution of different lifestyle and environmental factors to the compositional variability of the gut microbiota is unclear. DESIGN: Here, we rank the size effect of disease activity, medications, diet and geographic location of the faecal microbiota composition (16S rRNA gene sequencing) in patients with Crohn's disease (CD; n=303), ulcerative colitis (UC; n = 228) and controls (n=161), followed longitudinally (at three time points with 16 weeks intervals). RESULTS: Reduced microbiota diversity but increased variability was confirmed in CD and UC compared with controls. Significant compositional differences between diseases, particularly CD, and controls were evident. Longitudinal analyses revealed reduced temporal microbiota stability in IBD, particularly in patients with changes in disease activity. Machine learning separated disease from controls, and active from inactive disease, when consecutive time points were modelled. Geographic location accounted for most of the microbiota variance, second to the presence or absence of CD, followed by history of surgical resection, alcohol consumption and UC diagnosis, medications and diet with most (90.3%) of the compositional variance stochastic or unexplained. CONCLUSION: The popular concept of precision medicine and rational design of any therapeutic manipulation of the microbiota will have to contend not only with the heterogeneity of the host response, but also with widely differing lifestyles and with much variance still unaccounted for.

CellO: comprehensive and hierarchical cell type classification of human cells with the Cell Ontology.

Cell type annotation is a fundamental task in the analysis of single-cell RNA-sequencing data. In this work, we present CellO, a machine learning-based tool for annotating human RNA-seq data with the Cell Ontology. CellO enables accurate and standardized cell type classification of cell clusters by considering the rich hierarchical structure of known cell types. Furthermore, CellO comes pre-trained on a comprehensive data set of human, healthy, untreated primary samples in the Sequence Read Archive. CellO's comprehensive training set enables it to run out of the box on diverse cell types and achieves competitive or even superior performance when compared to existing state-of-the-art methods. Lastly, CellO's linear models are easily interpreted, thereby enabling exploration of cell-type-specific expression signatures across the ontology. To this end, we also present the CellO Viewer: a web application for exploring CellO's models across the ontology.

New Patient Education Video on Colonoscopy Preparation: Development and Evaluation Study.

BACKGROUND: Although several patient education materials on colonoscopy preparation exist, few studies have evaluated or compared them; hence, there is no professional consensus on recommended content or media to use. OBJECTIVE: This study aims to address this need by developing and evaluating a new video on colonoscopy preparation. METHODS: We developed a new video explaining split-dose bowel preparation for colonoscopy. Of similar content videos on the internet (n=20), the most favorably reviewed video among patient and physician advisers was used as the comparator for the study. A total of 232 individuals attending gastroenterology or urology clinics reviewed the new and comparator videos. The order of administration of the new and comparator videos was randomly counterbalanced to assess the impact of presentation order. Respondents rated each video on the following dimensions: information amount, clarity, trustworthiness, understandability, new or familiar information, reassurance, information learned, understanding from the patient's point of view, appeal, and the likelihood of recommending the video to others. RESULTS: Overall, 71.6% (166/232) of the participants preferred the new video, 25.0% (58/232) preferred the comparator video, and 3.4% (8/232) were not sure. Furthermore, 64.0% (71/111) of those who viewed the new video first preferred it, whereas 77.7% (94/121) of the participants who viewed the new video second preferred it. Multivariable logistic regression analysis also demonstrated that participants were more likely to prefer the new video if they had viewed it second. Participants who preferred the new video rated it as clearer and more trustworthy than those who preferred the comparator video. CONCLUSIONS: This study developed and assessed the strengths of a newly developed colonoscopy educational video.

Jupyter notebook-based tools for building structured datasets from the Sequence Read Archive.

The Sequence Read Archive (SRA) is a large public repository that stores raw next-generation sequencing data from thousands of diverse scientific investigations.  Despite its promise, reuse and re-analysis of SRA data has been challenged by the heterogeneity and poor quality of the metadata that describe its biological samples. Recently, the MetaSRA project standardized these metadata by annotating each sample with terms from biomedical ontologies. In this work, we present a pair of Jupyter notebook-based tools that utilize the MetaSRA for building structured datasets from the SRA in order to facilitate secondary analyses of the SRA's human RNA-seq data. The first tool, called the Case-Control Finder, finds suitable case and control samples for a given disease or condition where the cases and controls are matched by tissue or cell type.  The second tool, called the Series Finder, finds ordered sets of samples for the purpose of addressing biological questions pertaining to changes over a numerical property such as time. These tools were the result of a three-day-long NCBI Codeathon in March 2019 held at the University of North Carolina at Chapel Hill.