Projected land ice contributions to twenty-first-century sea level rise.

The land ice contribution to global mean sea level rise has not yet been predicted1 using ice sheet and glacier models for the latest set of socio-economic scenarios, nor using coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects generated a large suite of projections using multiple models2-8, but primarily used previous-generation scenarios9 and climate models10, and could not fully explore known uncertainties. Here we estimate probability distributions for these projections under the new scenarios11,12 using statistical emulation of the ice sheet and glacier models. We find that limiting global warming to 1.5 degrees Celsius would halve the land ice contribution to twenty-first-century sea level rise, relative to current emissions pledges. The median decreases from 25 to 13 centimetres sea level equivalent (SLE) by 2100, with glaciers responsible for half the sea level contribution. The projected Antarctic contribution does not show a clear response to the emissions scenario, owing to uncertainties in the competing processes of increasing ice loss and snowfall accumulation in a warming climate. However, under risk-averse (pessimistic) assumptions, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 centimetres SLE under current policies and pledges, with the 95th percentile projection exceeding half a metre even under 1.5 degrees Celsius warming. This would severely limit the possibility of mitigating future coastal flooding. Given this large range (between 13 centimetres SLE using the main projections under 1.5 degrees Celsius warming and 42 centimetres SLE using risk-averse projections under current pledges), adaptation planning for twenty-first-century sea level rise must account for a factor-of-three uncertainty in the land ice contribution until climate policies and the Antarctic response are further constrained.

A City-Wide Emissions Inventory of Plastic Pollution.

A global agreement on plastic should have quantitative reduction targets for the emissions of plastic pollution and regular measurements to track success. Here, we present a framework for measuring plastic emissions, akin to greenhouse gas emissions, and demonstrate its utility by calculating a baseline measurement for the City of Toronto in Ontario, Canada. We identify relevant sources of plastic pollution in the city, calculate emissions for each source by multiplying activity data by emission factors for each source, and sum the emissions to obtain the total annual emissions of plastic pollution generated. Using Monte Carlo simulations, we estimate that 3,531 to 3,852 tonnes (T) of plastic pollution were emitted from Toronto in 2020. Littering is the largest source overall (3,099 T), and artificial turf is the largest source of microplastic (237 T). Quantifying source emissions can inform the most effective mitigation strategies to achieve reduction targets. We recommend this framework be scaled up and replicated in cities, states, provinces, and countries around the world to inform global reduction targets and measure progress toward reducing plastic pollution.

Informing the Exposure Landscape: The Fate of Microplastics in a Large Pelagic In-Lake Mesocosm Experiment.

Understanding microplastic exposure and effects is critical to understanding risk. Here, we used large, in-lake closed-bottom mesocosms to investigate exposure and effects on pelagic freshwater ecosystems. This article provides details about the experimental design and results on the transport of microplastics and exposure to pelagic organisms. Our experiment included three polymers of microplastics (PE, PS, and PET) ranging in density and size. Nominal concentrations ranged from 0 to 29,240 microplastics per liter on a log scale. Mesocosms enclosed natural microbial, phytoplankton, and zooplankton communities and yellow perch (Perca flavescens). We quantified and characterized microplastics in the water column and in components of the food web (biofilm on the walls, zooplankton, and fish). The microplastics in the water stratified vertically according to size and density. After 10 weeks, about 1% of the microplastics added were in the water column, 0.4% attached to biofilm on the walls, 0.01% within zooplankton, and 0.0001% in fish. Visual observations suggest the remaining >98% were in a surface slick and on the bottom. Our study suggests organisms that feed at the surface and in the benthos are likely most at risk, and demonstrates the value of measuring exposure and transport to inform experimental designs and achieve target concentrations in different matrices within toxicity tests.

A data-assimilation approach to predict population dynamics during epithelial-mesenchymal transition.

Epithelial-mesenchymal transition (EMT) is a biological process that plays a central role in embryonic development, tissue regeneration, and cancer metastasis. Transforming growth factor-ß (TGFß) is a potent inducer of this cellular transition, comprising transitions from an epithelial state to partial or hybrid EMT state(s), to a mesenchymal state. Recent experimental studies have shown that, within a population of epithelial cells, heterogeneous phenotypical profiles arise in response to different time- and TGFß dose-dependent stimuli. This offers a challenge for computational models, as most model parameters are generally obtained to represent typical cell responses, not necessarily specific responses nor to capture population variability. In this study, we applied a data-assimilation approach that combines limited noisy observations with predictions from a computational model, paired with parameter estimation. Synthetic experiments mimic the biological heterogeneity in cell states that is observed in epithelial cell populations by generating a large population of model parameter sets. Analysis of the parameters for virtual epithelial cells with biologically significant characteristics (e.g., EMT prone or resistant) illustrates that these sub-populations have identifiable critical model parameters. We perform a series of in silico experiments in which a forecasting system reconstructs the EMT dynamics of each virtual cell within a heterogeneous population exposed to time-dependent exogenous TGFß dose and either an EMT-suppressing or EMT-promoting perturbation. We find that estimating population-specific critical parameters significantly improved the prediction accuracy of cell responses. Thus, with appropriate protocol design, we demonstrate that a data-assimilation approach successfully reconstructs and predicts the dynamics of a heterogeneous virtual epithelial cell population in the presence of physiological model error and parameter uncertainty.

Btg2 mutation induces renal injury and impairs blood pressure control in female rats.

Hypertension (HTN) is a complex disease influenced by heritable genetic elements and environmental interactions. Dietary salt is among the most influential modifiable factors contributing to increased blood pressure (BP). It is well established that men and women develop BP impairment in different patterns and a recent emphasis has been placed on identifying mechanisms leading to the differences observed between the sexes in HTN development. The current work reported here builds on an extensive genetic mapping experiment that sought to identify genetic determinants of salt-sensitive (SS) HTN using the Dahl SS rat. BTG antiproliferation factor 2 (Btg2) was previously identified by our group as a candidate gene contributing to SS HTN in female rats. In the current study, Btg2 was mutated using transcription activator-like effector nuclease (TALEN)-targeted gene disruption on the SSBN congenic rat background. The Btg2 mutated rats exhibited impaired BP and proteinuria responses to a high-salt diet compared with wild-type rats. Differences in body weight, mutant pup viability, skeletal morphology, and adult nephron density suggest a potential role for Btg2 in developmental signaling pathways. Subsequent cell cycle gene expression assessment provides several additional signaling pathways that Btg2 may function through during salt handling in the kidney. The expression analysis also identified several potential upstream targets that can be explored to further isolate therapeutic approaches for SS HTN.

The Year of the Rat: The Rat Genome Database at 20: a multi-species knowledgebase and analysis platform.

Formed in late 1999, the Rat Genome Database (RGD, https://rgd.mcw.edu) will be 20 in 2020, the Year of the Rat. Because the laboratory rat, Rattus norvegicus, has been used as a model for complex human diseases such as cardiovascular disease, diabetes, cancer, neurological disorders and arthritis, among others, for >150 years, RGD has always been disease-focused and committed to providing data and tools for researchers doing comparative genomics and translational studies. At its inception, before the sequencing of the rat genome, RGD started with only a few data types localized on genetic and radiation hybrid (RH) maps and offered only a few tools for querying and consolidating that data. Since that time, RGD has expanded to include a wealth of structured and standardized genetic, genomic, phenotypic, and disease-related data for eight species, and a suite of innovative tools for querying, analyzing and visualizing this data. This article provides an overview of recent substantial additions and improvements to RGD's data and tools that can assist researchers in finding and utilizing the data they need, whether their goal is to develop new precision models of disease or to more fully explore emerging details within a system or across multiple systems.

Robust data assimilation with noise: Applications to cardiac dynamics.

Reconstructions of excitation patterns in cardiac tissue must contend with uncertainties due to model error, observation error, and hidden state variables. The accuracy of these state reconstructions may be improved by efforts to account for each of these sources of uncertainty, in particular, through the incorporation of uncertainty in model specification and model dynamics. To this end, we introduce stochastic modeling methods in the context of ensemble-based data assimilation and state reconstruction for cardiac dynamics in one- and three-dimensional cardiac systems. We propose two classes of methods, one following the canonical stochastic differential equation formalism, and another perturbing the ensemble evolution in the parameter space of the model, which are further characterized according to the details of the models used in the ensemble. The stochastic methods are applied to a simple model of cardiac dynamics with fast-slow time-scale separation, which permits tuning the form of effective stochastic assimilation schemes based on a similar separation of dynamical time scales. We find that the selection of slow or fast time scales in the formulation of stochastic forcing terms can be understood analogously to existing ensemble inflation techniques for accounting for finite-size effects in ensemble Kalman filter methods; however, like existing inflation methods, care must be taken in choosing relevant parameters to avoid over-driving the data assimilation process. In particular, we find that a combination of stochastic processes-analogously to the combination of additive and multiplicative inflation methods-yields improvements to the assimilation error and ensemble spread over these classical methods.

Cell Fate Forecasting: A Data-Assimilation Approach to Predict Epithelial-Mesenchymal Transition.

Epithelial-mesenchymal transition (EMT) is a fundamental biological process that plays a central role in embryonic development, tissue regeneration, and cancer metastasis. Transforming growth factor-ß (TGFß) is a potent inducer of this cellular transition, which is composed of transitions from an epithelial state to intermediate or partial EMT state(s) to a mesenchymal state. Using computational models to predict cell state transitions in a specific experiment is inherently difficult for reasons including model parameter uncertainty and error associated with experimental observations. In this study, we demonstrate that a data-assimilation approach using an ensemble Kalman filter, which combines limited noisy observations with predictions from a computational model of TGFß-induced EMT, can reconstruct the cell state and predict the timing of state transitions. We used our approach in proof-of-concept "synthetic" in silico experiments, in which experimental observations were produced from a known computational model with the addition of noise. We mimic parameter uncertainty in in vitro experiments by incorporating model error that shifts the TGFß doses associated with the state transitions and reproduces experimentally observed variability in cell state by either shifting a single parameter or generating "populations" of model parameters. We performed synthetic experiments for a wide range of TGFß doses, investigating different cell steady-state conditions, and conducted parameter studies varying properties of the data-assimilation approach including the time interval between observations and incorporating multiplicative inflation, a technique to compensate for underestimation of the model uncertainty and mitigate the influence of model error. We find that cell state can be successfully reconstructed and the future cell state predicted in synthetic experiments, even in the setting of model error, when experimental observations are performed at a sufficiently short time interval and incorporate multiplicative inflation. Our study demonstrates the feasibility and utility of a data-assimilation approach to forecasting the fate of cells undergoing EMT.

Sensitivity of a data-assimilation system for reconstructing three-dimensional cardiac electrical dynamics.

Modelling of cardiac electrical behaviour has led to important mechanistic insights, but important challenges, including uncertainty in model formulations and parameter values, make it difficult to obtain quantitatively accurate results. An alternative approach is combining models with observations from experiments to produce a data-informed reconstruction of system states over time. Here, we extend our earlier data-assimilation studies using an ensemble Kalman filter to reconstruct a three-dimensional time series of states with complex spatio-temporal dynamics using only surface observations of voltage. We consider the effects of several algorithmic and model parameters on the accuracy of reconstructions of known scroll-wave truth states using synthetic observations. In particular, we study the algorithm's sensitivity to parameters governing different parts of the process and its robustness to several model-error conditions. We find that the algorithm can achieve an acceptable level of error in many cases, with the weakest performance occurring for model-error cases and more extreme parameter regimes with more complex dynamics. Analysis of the poorest-performing cases indicates an initial decrease in error followed by an increase when the ensemble spread is reduced. Our results suggest avenues for further improvement through increasing ensemble spread by incorporating additive inflation or using a parameter or multi-model ensemble. This article is part of the theme issue 'Uncertainty quantification in cardiac and cardiovascular modelling and simulation'.

Direct observations of evolving subglacial drainage beneath the Greenland Ice Sheet.

Seasonal acceleration of the Greenland Ice Sheet is influenced by the dynamic response of the subglacial hydrologic system to variability in meltwater delivery to the bed via crevasses and moulins (vertical conduits connecting supraglacial water to the bed of the ice sheet). As the melt season progresses, the subglacial hydrologic system drains supraglacial meltwater more efficiently, decreasing basal water pressure and moderating the ice velocity response to surface melting. However, limited direct observations of subglacial water pressure mean that the spatiotemporal evolution of the subglacial hydrologic system remains poorly understood. Here we show that ice velocity is well correlated with moulin hydraulic head but is out of phase with that of nearby (0.3-2 kilometres away) boreholes, indicating that moulins connect to an efficient, channelized component of the subglacial hydrologic system, which exerts the primary control on diurnal and multi-day changes in ice velocity. Our simultaneous measurements of moulin and borehole hydraulic head and ice velocity in the Paakitsoq region of western Greenland show that decreasing trends in ice velocity during the latter part of the melt season cannot be explained by changes in the ability of moulin-connected channels to convey supraglacial melt. Instead, these observations suggest that decreasing late-season ice velocity may be caused by changes in connectivity in unchannelized regions of the subglacial hydrologic system. Understanding this spatiotemporal variability in subglacial pressures is increasingly important because melt-season dynamics affect ice velocity beyond the conclusion of the melt season.

Mutation of Plekha7 attenuates salt-sensitive hypertension in the rat.

PLEKHA7 (pleckstrin homology domain containing family A member 7) has been found in multiple studies as a candidate gene for human hypertension, yet functional data supporting this association are lacking. We investigated the contribution of this gene to the pathogenesis of salt-sensitive hypertension by mutating Plekha7 in the Dahl salt-sensitive (SS/JrHsdMcwi) rat using zinc-finger nuclease technology. After four weeks on an 8% NaCl diet, homozygous mutant rats had lower mean arterial (149 ± 9 mmHg vs. 178 ± 7 mmHg; P < 0.05) and systolic (180 ± 7 mmHg vs. 213 ± 8 mmHg; P < 0.05) blood pressure compared with WT littermates. Albumin and protein excretion rates were also significantly lower in mutant rats, demonstrating a renoprotective effect of the mutation. Total peripheral resistance and perivascular fibrosis in the heart and kidney were significantly reduced in Plekha7 mutant animals, suggesting a potential role of the vasculature in the attenuation of hypertension. Indeed, both flow-mediated dilation and endothelium-dependent vasodilation in response to acetylcholine were improved in isolated mesenteric resistance arteries of Plekha7 mutant rats compared with WT. These vascular improvements were correlated with changes in intracellular calcium handling, resulting in increased nitric oxide bioavailability in mutant vessels. Collectively, these data provide the first functional evidence that Plekha7 may contribute to blood pressure regulation and cardiovascular function through its effects on the vasculature.

Effects of model error on cardiac electrical wave state reconstruction using data assimilation.

Reentrant electrical scroll waves have been shown to underlie many cardiac arrhythmias, but the inability to observe locations away from the heart surfaces and the restriction of observations to only one or two state variables have made understanding arrhythmia mechanisms challenging. Recently, we showed that data assimilation from spatiotemporally sparse surrogate observations could be used to reconstruct a reliable time series of state estimates of reentrant cardiac electrical waves including unobserved variables in one and three spatial dimensions. However, real cardiac tissue is unlikely to be described accurately by mathematical models because of errors in model formulation and parameterization as well as intrinsic but poorly described spatial heterogeneity of electrophysiological properties in the heart. Here, we extend our previous work to assess how model error affects the accuracy of cardiac state estimates achieved using data assimilation with the Local Ensemble Transform Kalman Filter. We focus on one-dimensional states of discordant alternans characterized by significant wavelength oscillations. We demonstrate that data assimilation can provide high-quality estimates under a wide range of model error conditions, ranging from varying one or more parameter values to using an entirely different model to generate the truth state. We illustrate how multiplicative and additive inflation can be used to reduce error in the state estimates. Even when the truth state contains underlying spatial heterogeneity, we show that using a homogeneous model in the data assimilation algorithm can achieve good results. Overall, we find data assimilation to be a robust approach for reconstructing complex cardiac electrical states corresponding to arrhythmias even in the presence of model error.

Identifying multiple causative genes at a single GWAS locus.

Genome-wide association studies (GWAS) are useful for nominating candidate genes, but typically are unable to establish disease causality or differentiate between the effects of variants in linkage disequilibrium (LD). Additionally, some GWAS loci might contain multiple causative variants or genes that contribute to the overall disease susceptibility at a single locus. However, the majority of current GWAS lack the statistical power to test whether multiple causative genes underlie the same locus, prompting us to adopt an alternative approach to testing multiple GWAS genes empirically. We used gene targeting in a disease-susceptible rat model of genetic hypertension to test all six genes at the Agtrap-Plod1 locus (Agtrap, Mthfr, Clcn6, Nppa, Nppb, and Plod1) for blood pressure (BP) and renal phenotypes. This revealed that the majority of genes at this locus (five out of six) can impact hypertension by modifying BP and renal phenotypes. Mutations of Nppa, Plod1, and Mthfr increased disease susceptibility, whereas Agtrap and Clcn6 mutations decreased hypertension risk. Reanalysis of the human AGTRAP-PLOD1 locus also implied that disease-associated haplotype blocks with polygenic effects were not only possible, but rather were highly plausible. Combined, these data demonstrate for the first time that multiple modifiers of hypertension can cosegregate at a single GWAS locus.

Enhanced basal lubrication and the contribution of the Greenland ice sheet to future sea-level rise.

We assess the effect of enhanced basal sliding on the flow and mass budget of the Greenland ice sheet, using a newly developed parameterization of the relation between meltwater runoff and ice flow. A wide range of observations suggest that water generated by melt at the surface of the ice sheet reaches its bed by both fracture and drainage through moulins. Once at the bed, this water is likely to affect lubrication, although current observations are insufficient to determine whether changes in subglacial hydraulics will limit the potential for the speedup of flow. An uncertainty analysis based on our best-fit parameterization admits both possibilities: continuously increasing or bounded lubrication. We apply the parameterization to four higher-order ice-sheet models in a series of experiments forced by changes in both lubrication and surface mass budget and determine the additional mass loss brought about by lubrication in comparison with experiments forced only by changes in surface mass balance. We use forcing from a regional climate model, itself forced by output from the European Centre Hamburg Model (ECHAM5) global climate model run under scenario A1B. Although changes in lubrication generate widespread effects on the flow and form of the ice sheet, they do not affect substantial net mass loss; increase in the ice sheet's contribution to sea-level rise from basal lubrication is projected by all models to be no more than 5% of the contribution from surface mass budget forcing alone.

Renin knockout rat: control of adrenal aldosterone and corticosterone synthesis in vitro and adrenal gene expression.

The classic renin-angiotensin system is partly responsible for controlling aldosterone secretion from the adrenal cortex via the peptide angiotensin II (ANG II). In addition, there is a local adrenocortical renin-angiotensin system that may be involved in the control of aldosterone synthesis in the zona glomerulosa (ZG). To characterize the long-term control of adrenal steroidogenesis, we utilized adrenal glands from renin knockout (KO) rats and compared steroidogenesis in vitro and steroidogenic enzyme expression to wild-type (WT) controls (Dahl S rat). Adrenal capsules (ZG; aldosterone production) and subcapsules [zona reticularis/fasciculata (ZFR); corticosterone production] were separately dispersed and studied in vitro. Plasma renin activity and ANG II concentrations were extremely low in the KO rats. Basal and cAMP-stimulated aldosterone production was significantly reduced in renin KO ZG cells, whereas corticosterone production was not different between WT and KO ZFR cells. As expected, adrenal renin mRNA expression was lower in the renin KO compared with the WT rat. Real-time PCR and immunohistochemical analysis showed a significant decrease in P450aldo (Cyp11b2) mRNA and protein expression in the ZG from the renin KO rat. The reduction in aldosterone synthesis in the ZG of the renin KO adrenal seems to be accounted for by a specific decrease in P450aldo and may be due to the absence of chronic stimulation of the ZG by circulating ANG II or to a reduction in locally released ANG II within the adrenal gland.

Vascular dysfunction precedes hypertension associated with a blood pressure locus on rat chromosome 12.

We previously isolated a 6.1-Mb region of SS/Mcwi (Dahl salt-sensitive) rat chromosome 12 (13.4-19.5 Mb) that significantly elevated blood pressure (BP) (Δ+34 mmHg, P < 0.001) compared with the SS-12(BN) consomic control. In the present study, we examined the role of vascular dysfunction and remodeling in hypertension risk associated with the 6.1-Mb (13.4-19.5 Mb) locus on rat chromosome 12 by reducing dietary salt, which lowered BP levels so that there were no substantial differences in BP between strains. Consequently, any observed differences in the vasculature were considered BP-independent. We also reduced the candidate region from 6.1 Mb with 133 genes to 2 Mb with 23 genes by congenic mapping. Both the 2 Mb and 6.1 Mb congenic intervals were associated with hypercontractility and decreased elasticity of resistance vasculature prior to elevations of BP, suggesting that the vascular remodeling and dysfunction likely contribute to the pathogenesis of hypertension in these congenic models. Of the 23 genes within the narrowed congenic interval, 12 were differentially expressed between the resistance vasculature of the 2 Mb congenic and SS-12(BN) consomic strains. Among these, Grifin was consistently upregulated 2.7 ± 0.6-fold (P < 0.05) and 2.0 ± 0.3-fold (P < 0.01), and Chst12 was consistently downregulated -2.8 ± 0.3-fold (P < 0.01) and -4.4 ± 0.4-fold (P < 0.00001) in the 2 Mb congenic compared with SS-12(BN) consomic under normotensive and hypertensive conditions, respectively. A syntenic region on human chromosome 7 has also been associated with BP regulation, suggesting that identification of the genetic mechanism(s) underlying cardiovascular phenotypes in this congenic strain will likely be translated to a better understanding of human hypertension.

A Multicompartment Assessment of Microplastic Contamination in Semi-remote Boreal Lakes.

Microplastic contamination is ubiquitous across the globe, even in remote locations. Still, the sources and pathways of microplastics to such locations are largely unknown. To investigate microplastic contamination in a semi-remote location, we measured microplastic concentrations in nine oligotrophic lakes within and around the International Institute for Sustainable Development-Experimental Lakes Area in northwestern Ontario, Canada. Our first objective was to establish ambient concentrations of microplastics in bottom sediments, surface water, and atmospheric deposition in semi-remote boreal lakes. Across all lakes, mean shallow and deep sediment microplastic concentrations, near-surface water microplastic concentrations from in situ filtering, and dry atmospheric microplastic deposition rates were 551 ± 354 particles kg-1, 177 ± 103 particles kg-1, 0.2 ± 0.3 particles L-1, and 0.4 ± 0.2 particles m-2 day-1, respectively. Our second objective was to investigate whether microplastic contamination of these lakes is driven by point sources including local runoff and direct anthropogenic inputs or nonpoint sources such as atmospheric deposition. Lakes were selected based on three levels of anthropogenic activity-low, medium, and high-though activity levels were minimal across all study lakes compared with highly populated areas. Whereas a positive correlation would indicate that point sources were a likely pathway, we observed no relationship between the level of anthropogenic activity and microplastic contamination of surface water. Moreover, the composition of microplastics in surface water and atmospheric deposition were similar, comprising mostly polyester and acrylic fibers. Together, these results suggest that atmospheric deposition may be the main pathway of microplastics to these remote boreal lakes. Environ Toxicol Chem 2024;43:999-1011. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Reconstructing Cardiac Electrical Excitations from Optical Mapping Recordings.

The reconstruction of electrical excitation patterns through the unobserved depth of the tissue is essential to realizing the potential of computational models in cardiac medicine. We have utilized experimental optical-mapping recordings of cardiac electrical excitation on the epicardial and endocardial surfaces of a canine ventricle as observations directing a local ensemble transform Kalman Filter (LETKF) data assimilation scheme. We demonstrate that the inclusion of explicit information about the stimulation protocol can marginally improve the confidence of the ensemble reconstruction and the reliability of the assimilation over time. Likewise, we consider the efficacy of stochastic modeling additions to the assimilation scheme in the context of experimentally derived observation sets. Approximation error is addressed at both the observation and modeling stages, through the uncertainty of observations and the specification of the model used in the assimilation ensemble. We find that perturbative modifications to the observations have marginal to deleterious effects on the accuracy and robustness of the state reconstruction. Further, we find that incorporating additional information from the observations into the model itself (in the case of stimulus and stochastic currents) has a marginal improvement on the reconstruction accuracy over a fully autonomous model, while complicating the model itself and thus introducing potential for new types of model error. That the inclusion of explicit modeling information has negligible to negative effects on the reconstruction implies the need for new avenues for optimization of data assimilation schemes applied to cardiac electrical excitation.

Patient Characteristics in Oral Cancer Staging.

Background: Oral cancer is a largely preventable malignancy with many modifiable risk factors, such as tobacco use and proper oral hygiene. Early detection of oral cancer is an important goal for oral healthcare providers, as survival rates for oral cancers diagnosed at an advanced stage are less than half the rates for cancers diagnosed in early stages. As many patients are asymptomatic in early stages, it is crucial for oral healthcare providers to have a high index of suspicion while treating patients at risk for late diagnosis. Objectives: To identify characteristics associated with early vs. late stage diagnosis of oral cancer. Methods: We performed a retrospective chart review using the TriNetX database. We identified two cohorts of interest: patients with an initial diagnosis of stage 1 oral cancer, and patients with an initial diagnosis of stage 3 or 4 oral cancer. Statistical comparison of cohort characteristics was completed through the TriNetX statistical software platform. Results: We identified 386 patients diagnosed at stage 1 and 869 patients diagnosed at stage 3 or 4. We identified several characteristics not previously reported in the literature. Race, BMI between 20 and 29, malnurition, anemia were all associated with late stage diagnosis. Certain medications were also associated with late stage diagnosis, such as heparin derivatives and diclofenac. Our findings also reinforced prior research for characteristics such as nicotine use and ethnicity. Conclusion: Our findings offer new characteristics that may aid oral healthcare providers in detecting oral cancer at an early stage. Increasing provider awareness of factors that they may not have considered previously could increase the rates of early stage cancer detection, improving overall patient mortality and curative outcomes.