Mechanistic safety assessment via multi-omic characterisation of systemic pathway perturbations following in vivo MAT2A inhibition.

The tumour suppressor p16/CDKN2A and the metabolic gene, methyl-thio-adenosine phosphorylase (MTAP), are frequently co-deleted in some of the most aggressive and currently untreatable cancers. Cells with MTAP deletion are vulnerable to inhibition of the metabolic enzyme, methionine-adenosyl transferase 2A (MAT2A), and the protein arginine methyl transferase (PRMT5). This synthetic lethality has paved the way for the rapid development of drugs targeting the MAT2A/PRMT5 axis. MAT2A and its liver- and pancreas-specific isoform, MAT1A, generate the universal methyl donor S-adenosylmethionine (SAM) from ATP and methionine. Given the pleiotropic role SAM plays in methylation of diverse substrates, characterising the extent of SAM depletion and downstream perturbations following MAT2A/MAT1A inhibition (MATi) is critical for safety assessment. We have assessed in vivo target engagement and the resultant systemic phenotype using multi-omic tools to characterise response to a MAT2A inhibitor (AZ'9567). We observed significant SAM depletion and extensive methionine accumulation in the plasma, liver, brain and heart of treated rats, providing the first assessment of both global SAM depletion and evidence of hepatic MAT1A target engagement. An integrative analysis of multi-omic data from liver tissue identified broad perturbations in pathways covering one-carbon metabolism, trans-sulfuration and lipid metabolism. We infer that these pathway-wide perturbations represent adaptive responses to SAM depletion and confer a risk of oxidative stress, hepatic steatosis and an associated disturbance in plasma and cellular lipid homeostasis. The alterations also explain the dramatic increase in plasma and tissue methionine, which could be used as a safety and PD biomarker going forward to the clinic.

Suspected Interstitial Lung Disease in COPDGene Study.

Rationale: Although interstitial lung abnormalities (ILA), specific patterns of incidentally-detected abnormal density on computed tomography, have been associated with abnormal lung function and increased mortality, it is unclear if a subset with incidental interstitial lung disease (ILD) accounts for these adverse consequences. Objectives: To define the prevalence and risk factors of suspected ILD and assess outcomes. Methods: Suspected ILD was evaluated in the COPDGene (Chronic Obstructive Pulmonary Disease Genetic Epidemiology) study, defined as ILA and at least one additional criterion: definite fibrosis on computed tomography, FVC less than 80% predicted, or DLCO less than 70% predicted. Multivariable linear, longitudinal, and Cox proportional hazards regression models were used to assess associations with St. George's Respiratory Questionnaire, 6-minute-walk test, supplemental oxygen use, respiratory exacerbations, and mortality. Measurements and Main Results: Of 4,361 participants with available data, 239 (5%) had evidence for suspected ILD, whereas 204 (5%) had ILA without suspected ILD. In multivariable analyses, suspected ILD was associated with increased St. George's Respiratory Questionnaire score (mean difference [MD], 3.9 points; 95% confidence interval [CI], 0.6-7.1; P = 0.02), reduced 6-minute-walk test (MD, -35 m; 95% CI, -56 m to -13 m; P = 0.002), greater supplemental oxygen use (odds ratio [OR], 2.3; 95% CI, 1.1-5.1; P = 0.03) and severe respiratory exacerbations (OR, 2.9; 95% CI, 1.1-7.5; P = 0.03), and higher mortality (hazard ratio, 2.4; 95% CI, 1.2-4.6; P = 0.01) compared with ILA without suspected ILD. Risk factors associated with suspected ILD included self-identified Black race (OR, 2.0; 95% CI, 1.1-3.3; P = 0.01) and pack-years smoking history (OR, 1.2; 95% CI, 1.1-1.3; P = 0.0005). Conclusions: Suspected ILD is present in half of those with ILA in COPDGene and is associated with exercise decrements and increased symptoms, supplemental oxygen use, severe respiratory exacerbations, and mortality.

Identifying determinants of varenicline adherence using the Theoretical Domains framework: a rapid review.

BACKGROUND: Adhering to varenicline has been shown to significantly improve the chances of successfully quitting smoking, with studies indicating a twofold increase in 6-month quit rates. However, despite its potential benefits, many individuals struggle with maintaining good adherence to varenicline; thus there is a need to develop scalable strategies to help people adhere. As a first step to inform the development of an intervention to improve adherence to varenicline, we conducted a rapid literature review to identify: 1) modifiable barriers and facilitators to varenicline adherence, and 2) behaviour change techniques associated with increased adherence to varenicline. METHODS: We searched MEDLINE, Embase, APA PsycINFO, CINAHL, and the Cochrane Central Register of Controlled Trials for relevant studies published between 2006 and 2022. Search terms included "varenicline," "smoking cessation," and "adherence," and their respective subject headings and synonyms. We screened and included studies reporting modifiable determinants of adherence to varenicline and then assessed quality, extracted modifiable determinants and mapped them to the Theoretical Domains Framework version 2 and the Behaviour Change Technique Taxonomy version 1. RESULTS: A total of 1,221 titles were identified through the database searches; 61 met the eligibility criteria. Most of the studies were randomized controlled trials and predominantly focused on barriers to varenicline. Only nine studies explicitly mentioned behaviour change techniques used to help varenicline adherence. Eight domains were identified as barriers to varenicline adherence (behavioural regulation, memory, goals, intentions, beliefs about capabilities, beliefs about consequences, optimism/pessimism, and environmental context) and five as facilitators (knowledge, behavioural regulation, beliefs about capabilities, social influences, and environmental context). CONCLUSIONS: This study identifies barriers and facilitators that should be addressed when developing a complex adherence intervention tailored to patients' needs based on modifiable determinants of medication adherence, some of which are under- used by existing adherence interventions. The findings from this review will inform the design of a theory-based healthbot planned to improve varenicline adherence in people undergoing smoking cessation treatment. SYSTEMATIC REVIEW REGISTRATION: This study was registered with PROSPERO (# CRD42022321838).

Bronchial epithelial gene expression and interstitial lung abnormalities.

INTRODUCTION: Interstitial lung abnormalities (ILA) often represent early fibrotic changes that can portend a progressive fibrotic phenotype. In particular, the fibrotic subtype of ILA is associated with increased mortality and rapid decline in lung function. Understanding the differential gene expression that occurs in the lungs of participants with fibrotic ILA may provide insight into development of a useful biomarker for early detection and therapeutic targets for progressive pulmonary fibrosis. METHODS: Measures of ILA and gene expression data were available in 213 participants in the Detection of Early Lung Cancer Among Military Personnel (DECAMP1 and DECAMP2) cohorts. ILA was defined using Fleischner Society guidelines and determined by sequential reading of computed tomography (CT) scans. Primary analysis focused on comparing gene expression in ILA with usual interstitial pneumonia (UIP) pattern with those with no ILA. RESULTS: ILA was present in 51 (24%) participants, of which 16 (7%) were subtyped as ILA with a UIP pattern. One gene, pro platelet basic protein (PPBP) and seventeen pathways (e.g. TNF-α signalling) were significantly differentially expressed between those with a probable or definite UIP pattern of ILA compared to those without ILA. 16 of these 17 pathways, but no individual gene, met significance when comparing those with ILA to those without ILA. CONCLUSION: Our study demonstrates that abnormal inflammatory processes are apparent in the bronchial airway gene expression profiles of smokers with and without lung cancer with ILA. Future studies with larger and more diverse populations will be needed to confirm these findings.

Establishing the consistency of a voice recognition symbol digit modalities test analogue.

BACKGROUND: We previously demonstrated the convergent validity of a fully automated voice recognition analogue of the Symbol Digit Modalities Test (VR-SDMT) for evaluating processing speed in people with multiple sclerosis (pwMS). OBJECTIVE/METHODS: We aimed to replicate these results in 54 pwMS and 18 healthy controls (HCs), demonstrating the VR-SDMT's reliability. RESULTS: Significant correlations were found between the VR-SDMT and the traditional oral SDMT in the multiple sclerosis (MS) (r = -0.771, p < 0.001) and HC (r = -0.785, p < 0.001) groups. CONCLUSION: Taken collectively, our two studies demonstrate the reliability and validity of the VR-SDMT for assessing processing speed in pwMS.

A French Version of a Voice Recognition Symbol Digit Modalities Test Analog.

We previously showed that a fully automated voice recognition analog of the Symbol Digit Modalities Test (VR-SDMT) is sensitive in detecting processing speed deficits in people with multiple sclerosis (pwMS). We subsequently developed a French language version and administered it to 49 French-Canadian pwMS and 29 matched healthy control (HC) subjects. Significant correlations between the VR-SDMT and traditional oral SDMT were found in the MS (r = -0.716, p < 0.001) and HC (r = -0.623, p < 0.001) groups. These findings in French replicate our previous findings and confirm the utility of voice recognition software in assessing cognition in pwMS.

Mass Spectrometry Detection and Imaging of a Non-Covalent Protein-Drug Complex in Tissue from Orally Dosed Rats.

Here, we demonstrate detection by mass spectrometry of an intact protein-drug complex directly from liver tissue from rats that had been orally dosed with the drug. The protein-drug complex comprised fatty acid binding protein 1, FABP1, non-covalently bound to the small molecule therapeutic bezafibrate. Moreover, we demonstrate spatial mapping of the [FABP1+bezafibrate] complex across a thin section of liver by targeted mass spectrometry imaging. This work is the first demonstration of in situ mass spectrometry analysis of a non-covalent protein-drug complex formed in vivo and has implications for early stage drug discovery by providing a route to target-drug characterization directly from the physiological environment.

Method to Investigate the Distribution of Water-Soluble Drug-Delivery Systems in Fresh Frozen Tissues Using Imaging Mass Cytometry.

Imaging mass cytometry (IMC) offers the opportunity to image metal- and heavy halogen-containing xenobiotics in a highly multiplexed experiment with other immunochemistry-based reagents to distinguish uptake into different tissue structures or cell types. However, in practice, many xenobiotics are not amenable to this analysis, as any compound which is not bound to the tissue matrix will delocalize during aqueous sample-processing steps required for IMC analysis. Here, we present a strategy to perform IMC experiments on a water-soluble polysarcosine-modified dendrimer drug-delivery system (S-Dends). This strategy involves two consecutive imaging acquisitions on the same tissue section using the same instrumental platform, an initial laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MSI) experiment followed by tissue staining and a standard IMC experiment. We demonstrated that settings can be found for the initial ablation step that leave sufficient residual tissue for subsequent antibody staining and visualization. This workflow results in lateral resolution for the S-Dends of 2 µm followed by imaging of metal-tagged antibodies at 1 µm.

Time-to-detection occupancy methods: performance and utility for improving efficiency of surveys.

Occupancy methods propelled the quantitative study of species distributions forward by separating the observation process, or the imperfect detectability of species, from the ecological processes of interest governing species distributions. Occupancy studies come at a cost, however: the collection of additional data to account for nondetections at sites where the species is present. The most common occupancy designs (repeated-measures designs) require repeat visits to sites or the use of multiple observers or detection methods. Time-to-detection methods have been identified as a potentially efficient alternative, requiring only one visit to each site by a single observer. A comparison of time-to-detection methods to repeated-measures designs for visual encounter surveys would allow researchers to evaluate whether time-to-detection methods might be appropriate for their study system and can inform optimal survey design. We collected time-to-detection data during two different repeated-measures design occupancy surveys for four amphibians and compared the performance of time-to-detection methods to the other designs using the location (potential bias) and precision of posterior distributions for occurrence parameters. We further used results of time-to-detection surveys to optimize survey design. Time-to-detection methods performed best for species that are widespread and have high detection probabilities and rates, but performed less well for cryptic species with lower probability of occurrence or whose detection was strongly affected by survey conditions. In all cases, single surveys were most efficient in terms of person-hours expended, but under some conditions the survey duration required to achieve high detection probabilities would be prohibitively long for a single survey. Regardless of occupancy survey design, time-to-detection methods provide important information that can be used to optimize surveys, allowing researchers and resource managers to efficiently achieve monitoring and conservation goals. Collecting time-to-detection data while conducting repeated-measures occupancy surveys requires only small modifications to field methods but could have large benefits in terms of time spent surveying in the long term.

Automated Screening for Social Anxiety, Generalized Anxiety, and Depression From Objective Smartphone-Collected Data: Cross-sectional Study.

BACKGROUND: The lack of access to mental health care could be addressed, in part, through the development of automated screening technologies for detecting the most common mental health disorders without the direct involvement of clinicians. Objective smartphone-collected data may contain sufficient information about individuals' behaviors to infer their mental states and therefore screen for anxiety disorders and depression. OBJECTIVE: The objective of this study is to compare how a single set of recognized and novel features, extracted from smartphone-collected data, can be used for predicting generalized anxiety disorder (GAD), social anxiety disorder (SAD), and depression. METHODS: An Android app was designed, together with a centralized server system, to collect periodic measurements of objective smartphone data. The types of data included samples of ambient audio, GPS location, screen state, and light sensor data. Subjects were recruited into a 2-week observational study in which the app was run on their personal smartphones. The subjects also completed self-report severity measures of SAD, GAD, and depression. The participants were 112 Canadian adults from a nonclinical population. High-level features were extracted from the data of 84 participants, and predictive models of SAD, GAD, and depression were built and evaluated. RESULTS: Models of SAD and depression achieved a significantly greater screening accuracy than uninformative models (area under the receiver operating characteristic means of 0.64, SD 0.13 and 0.72, SD 0.12, respectively), whereas models of GAD failed to be predictive. Investigation of the model coefficients revealed key features that were predictive of SAD and depression. CONCLUSIONS: We demonstrate the ability of a common set of features to act as predictors in the models of both SAD and depression. This suggests that the types of behaviors that can be inferred from smartphone-collected data are broad indicators of mental health, which can be used to study, assess, and track psychopathology simultaneously across multiple disorders and diagnostic boundaries.

Engaging Unmotivated Smokers to Move Toward Quitting: Design of Motivational Interviewing-Based Chatbot Through Iterative Interactions.

BACKGROUND: At any given time, most smokers in a population are ambivalent with no motivation to quit. Motivational interviewing (MI) is an evidence-based technique that aims to elicit change in ambivalent smokers. MI practitioners are scarce and expensive, and smokers are difficult to reach. Smokers are potentially reachable through the web, and if an automated chatbot could emulate an MI conversation, it could form the basis of a low-cost and scalable intervention motivating smokers to quit. OBJECTIVE: The primary goal of this study is to design, train, and test an automated MI-based chatbot capable of eliciting reflection in a conversation with cigarette smokers. This study describes the process of collecting training data to improve the chatbot's ability to generate MI-oriented responses, particularly reflections and summary statements. The secondary goal of this study is to observe the effects on participants through voluntary feedback given after completing a conversation with the chatbot. METHODS: An interdisciplinary collaboration between an MI expert and experts in computer engineering and natural language processing (NLP) co-designed the conversation and algorithms underlying the chatbot. A sample of 121 adult cigarette smokers in 11 successive groups were recruited from a web-based platform for a single-arm prospective iterative design study. The chatbot was designed to stimulate reflections on the pros and cons of smoking using MI's running head start technique. Participants were also asked to confirm the chatbot's classification of their free-form responses to measure the classification accuracy of the underlying NLP models. Each group provided responses that were used to train the chatbot for the next group. RESULTS: A total of 6568 responses from 121 participants in 11 successive groups over 14 weeks were received. From these responses, we were able to isolate 21 unique reasons for and against smoking and the relative frequency of each. The gradual collection of responses as inputs and smoking reasons as labels over the 11 iterations improved the F1 score of the classification within the chatbot from 0.63 in the first group to 0.82 in the final group. The mean time spent by each participant interacting with the chatbot was 21.3 (SD 14.0) min (minimum 6.4 and maximum 89.2). We also found that 34.7% (42/121) of participants enjoyed the interaction with the chatbot, and 8.3% (10/121) of participants noted explicit smoking cessation benefits from the conversation in voluntary feedback that did not solicit this explicitly. CONCLUSIONS: Recruiting ambivalent smokers through the web is a viable method to train a chatbot to increase accuracy in reflection and summary statements, the building blocks of MI. A new set of 21 smoking reasons (both for and against) has been identified. Initial feedback from smokers on the experience shows promise toward using it in an intervention.

Hybrid Eye-Tracking on a Smartphone with CNN Feature Extraction and an Infrared 3D Model.

This paper describes a low-cost, robust, and accurate remote eye-tracking system that uses an industrial prototype smartphone with integrated infrared illumination and camera. Numerous studies have demonstrated the beneficial use of eye-tracking in domains such as neurological and neuropsychiatric testing, advertising evaluation, pilot training, and automotive safety. Remote eye-tracking on a smartphone could enable the significant growth in the deployment of applications in these domains. Our system uses a 3D gaze-estimation model that enables accurate point-of-gaze (PoG) estimation with free head and device motion. To accurately determine the input eye features (pupil center and corneal reflections), the system uses Convolutional Neural Networks (CNNs) together with a novel center-of-mass output layer. The use of CNNs improves the system's robustness to the significant variability in the appearance of eye-images found in handheld eye trackers. The system was tested with 8 subjects with the device free to move in their hands and produced a gaze bias of 0.72°. Our hybrid approach that uses artificial illumination, a 3D gaze-estimation model, and a CNN feature extractor achieved an accuracy that is significantly (400%) better than current eye-tracking systems on smartphones that use natural illumination and machine-learning techniques to estimate the PoG.

Interdependence of hypoxia and ß-adrenergic receptor signaling in pulmonary arterial hypertension.

The ß-adrenergic receptor (ßAR) exists in an equilibrium of inactive and active conformational states, which shifts in response to different ligands and results in downstream signaling. In addition to cAMP, ßAR signals to hypoxia-inducible factor 1 (HIF-1). We hypothesized that a ßAR-active conformation (R**) that leads to HIF-1 is separable from the cAMP-activating conformation (R*) and that pulmonary arterial hypertension (PAH) patients with HIF-biased conformations would not respond to a cAMP agonist. We compared two cAMP agonists, isoproterenol and salbutamol, in vitro. Isoproterenol increased cAMP and HIF-1 activity, while salbutamol increased cAMP and reduced HIF-1. Hypoxia blunted agonist-stimulated cAMP, consistent with receptor equilibrium shifting toward HIF-activating conformations. Similarly, isoproterenol increased HIF-1 and erythropoiesis in mice, while salbutamol decreased erythropoiesis. ßAR overexpression in cells increased glycolysis, which was blunted by HIF-1 inhibitors, suggesting increased ßAR leads to increased hypoxia-metabolic effects. Because PAH is also characterized by HIF-related glycolytic shift, we dichotomized PAH patients in the Pulmonary Arterial Hypertension Treatment with Carvedilol for Heart Failure trial (NCT01586156) based on right ventricular (RV) glucose uptake to evaluate ßAR ligands. Patients with high glucose uptake had more severe disease than those with low uptake. cAMP increased in response to isoproterenol in mononuclear cells from low-uptake patients but not in high-uptake patients' cells. When patients were treated with carvedilol for 1 wk, the low-uptake group decreased RV systolic pressures and pulmonary vascular resistance, but high-uptake patients had no physiologic responses. The findings expand the paradigm of ßAR activation and uncover a novel PAH subtype that might benefit from ß-blockers.

Taking the tester out of the SDMT: A proof of concept fully automated approach to assessing processing speed in people with MS.

BACKGROUND: One factor hindering the widespread use of cognitive testing for people with multiple sclerosis (pwMS) is the need for a tester to administer tests. OBJECTIVE: To undertake a proof of concept study assessing the feasibility of a fully automated speech recognition version of the Symbol Digit Modalities Test (auto-SDMT) in detecting abnormalities in processing speed in pwMS. METHODS: A sample of 50 pwMS and 32 matched healthy control (HC) subjects was tested with the auto-SDMT and the Brief International Cognitive Assessment for MS (BICAMS). RESULTS: The percentages of MS participants impaired on the auto-SDMT and the traditional oral SDMT were 34% and 32%, respectively. Excellent convergent validity was found between the two tests (MS: r = -0.806, p < 0.001 and HC: r = -0.629, p < 0.001). The auto-SDMT had a similar sensitivity and specificity to the traditional oral SDMT in predicting overall impairment on the BICAMS. CONCLUSION: The auto-SDMT is a sensitive measure for detecting processing speed deficits in pwMS. The test, the first entirely computer administrated oral response version of the SDMT, uses speech recognition technology, thereby eliminating the need for a human tester. Replication of the results is required in a larger representative sample of pwMS.

Relative quantification of beta-adrenergic receptor in peripheral blood cells using flow cytometry.

Beta-adrenergic receptors (ß-ARs) play a critical role in many diseases. Quantification of ß-AR density may have clinical implications in terms of assessing disease severity and identifying patients who could potentially benefit from beta-blocker therapy. Classical methods for ß-AR quantification are based on labor-intensive and time-consuming radioligand binding assays. Here, we report optimization of a flow cytometry-based method utilizing a biotinylated ß-AR ligand alprenolol as a probe and use of this method to quantify relative receptor expression in healthy controls (HC). Quantum™ MESF beads were used for quantification in absolute fluorescence units. The probe was chemically modified by adding a spacer moiety between biotin and alprenolol to stabilize receptor binding, thus preventing binding decay. Testing of three different standard cell fixation and permeabilization methods (formaldehyde fixation and saponin, Tween-20, or Triton-X 100 permeabilization) showed that the formaldehyde/Triton-X 100 method yielded the best results. ß-AR expression was significantly higher in granulocytes compared to mononuclear cells. These data show that flow cytometric quantification of relative ß-AR expression in circulating leukocytes is a suitable technology for large-scale clinical application. © 2018 International Society for Advancement of Cytometry.

Infection risk decreases with increasing mismatch in host and pathogen environmental tolerances.

The fungal pathogen Batrachochytrium dendrobatidis (Bd) has caused the greatest known wildlife pandemic, infecting over 500 amphibian species. It remains unclear why some host species decline from disease-related mortality whereas others persist. We introduce a conceptual model that predicts that infection risk in ectotherms will decrease as the difference between host and pathogen environmental tolerances (i.e. tolerance mismatch) increases. We test this prediction using both local-scale data from Costa Rica and global analyses of over 11 000 Bd infection assays. We find that infection prevalence decreases with increasing thermal tolerance mismatch and with increasing host tolerance of habitat modification. The relationship between environmental tolerance mismatches and Bd infection prevalence is generalisable across multiple amphibian families and spatial scales, and the magnitude of the tolerance mismatch effect depends on environmental context. These findings may help explain patterns of amphibian declines driven by a global wildlife pandemic.

Application of Osmotic Pumps for Sustained Release of 1-Aminobenzotriazole and Inhibition of Cytochrome P450 Enzymes in Mice: Model Comparison with the Hepatic P450 Reductase Null Mouse.

The effectiveness of controlled release 1-aminobenzotriazole (ABT) administration to inhibit cytochrome P450 (P450) enzymes has been evaluated in mice. To maximize the duration of P450 inhibition in vivo, ABT was administered via an osmotic pump. The degree of P450 inhibition was compared with that achieved with a single bolus dose of ABT. Two-hour prior subcutaneous treatment of mice with ABT (50 mg/kg) inhibited antipyrine clearance by 88%. A less pronounced inhibitory effect (29% reduction in clearance) was observed when ABT was administered 24-hours before antipyrine administration, indicating partial restoration of P450 activity during this longer pretreatment time. The duration of ABT in mice was very short (mean residence time = 1.7 hours) after subcutaneous bolus administration. When the inhibitor was delivered by an osmotic pump, maximum blood concentrations of the inhibitor were observed 24 hours after device implantation and were maintained at steady state for 6 days. Inhibition of P450 activity, as measured by antipyrine clearance, was confirmed at 24 hours and 120 hours after pump implantation, highlighting the utility of this method as a longer-term model for P450 inhibition in mice. The magnitude of P450 inhibition in ABT-treated mice was compared with that in hepatic P450 reductase null mice and both models were comparable. In vivo ABT administration by an osmotic pump offers an effective approach for longer-term P450 inhibition in mice and avoids the necessity for multiple dosing of the inhibitor.

Using citizen science data to identify the sensitivity of species to human land use.

Conservation practitioners must contend with an increasing array of threats that affect biodiversity. Citizen scientists can provide timely and expansive information for addressing these threats across large scales, but their data may contain sampling biases. We used randomization procedures to account for possible sampling biases in opportunistically reported citizen science data to identify species' sensitivities to human land use. We analyzed 21,044 records of 143 native reptile and amphibian species reported to the Carolina Herp Atlas from North Carolina and South Carolina between 1 January 1990 and 12 July 2014. Sensitive species significantly associated with natural landscapes were 3.4 times more likely to be legally protected or treated as of conservation concern by state resource agencies than less sensitive species significantly associated with human-dominated landscapes. Many of the species significantly associated with natural landscapes occurred primarily in habitats that had been nearly eradicated or otherwise altered in the Carolinas, including isolated wetlands, longleaf pine savannas, and Appalachian forests. Rare species with few reports were more likely to be associated with natural landscapes and 3.2 times more likely to be legally protected or treated as of conservation concern than species with at least 20 reported occurrences. Our results suggest that opportunistically reported citizen science data can be used to identify sensitive species and that species currently restricted primarily to natural landscapes are likely at greatest risk of decline from future losses of natural habitat. Our approach demonstrates the usefulness of citizen science data in prioritizing conservation and in helping practitioners address species declines and extinctions at large extents.