Public Data Repositories Research Articles

Micromix: web infrastructure for visualizing and remixing microbial 'omics data.

Micromix is a flexible web platform for sharing and integrating microbial omics data, including RNA sequencing and transposon-insertion sequencing. Currently, the lack of solutions for making data web-accessible results in omics data being fragmented across supplementary spreadsheets or languishing as raw read data in public repositories. Micromix solves this problem and can be easily deployed on a standard web server or using cloud services. It is organism-agnostic, accommodates data and annotations from various sources, and allows filtering based on KEGG pathways, Gene Ontology terms, and curated gene sets. Visualizations are provided through a plug-in system that integrates existing visualization services and allows rapid development of new services, with available plug-ins currently supporting interactive heatmap and clustering functions. Users can upload their own data in a variety of formats to perform integrative analyses in the context of existing datasets. To support collaborative research, Micromix allows sharing of interactive sessions that maintain defined filtering and/or visualization options. We demonstrate the utility of Micromix with case studies focusing on the SPI-2 pathogenicity island in Salmonella enterica and polysaccharide utilization loci in Bacteroides thetaiotaomicron, showcasing the platform's capabilities for integrating, filtering, and visualizing diverse functional genomic datasets. Micromix is available at http://micromix.systems.

Histone variant H3.5 in testicular cell differentiation and its interactions with histone chaperones

Testicular cell differentiation is a highly regulated process, essential for male reproductive health. The histone variant H3.5 is apparently a critical player in this intricate orchestra of cell types, but its regulation and function remains poorly understood. To elucidate its role, we fractionized testicular cells using c-Kit/CD117 as a separation marker and analyzed H3.5 expression. Further, we investigated the regulation of H3.5 expression using public data repositories. We explored DNA methylation patterns in specific regions of the H3-5 gene and assessed H3-5 copy number gain in seminoma specimens. Additionally, we examined the testicular localization of H3.5 and its histone chaperone interactions to understand its regulation at the protein level. We used qRT-PCR, MeDIP, and qPCR to study H3.5 expression and DNA methylation in various cell types. H3-5 copy number gain was analyzed using qPCR. Protein interactions were investigated through fluorescence-2-hybrid assays in baby hamster kidney cells. H3.5 is primarily enriched in spermatocytes. DNA methylation of a CpG island overlapping the H3-5 promoter appeared to be involved in the tissue-specific regulation of H3.5 expression. Elevated H3.5 expression was observed in seminoma specimens, suggesting a potential link to testicular tumors. H3-5 copy number gain was associated with elevated H3.5 expression in seminoma specimens. Furthermore, we identified physical interactions between H3.5 and histone chaperones Asf1a and Asf1b, HIRA, CAF p150 and DAXX, shedding light on the protein-level regulation of H3.5. These findings provide valuable insights into the molecular mechanisms governing testicular cell differentiation and the potential role of H3.5 in testicular pathologies.

Annotating full-scan MS data using tandem MS libraries.

Full-scan mass spectrometry (MS) data from both liquid chromatography (LC) and MS imaging capture multiple ion forms, including their in-source fragments. Here we leverage such fragments to structurally annotate full-scan data from LC-MS or MS imaging by matching against peak intensity scaled tandem MS spectral libraries using precursor-tolerant reverse match scoring. Applied to inflammatory bowel disease and imaging datasets, we show the approach facilitates re-analyses of data in public repositories.

Scoping Review: Methods and Applications of Spatial Transcriptomics in Tumor Research.

Spatial transcriptomics (ST) examines gene expression within its spatial context on tissue, linking morphology and function. Advances in ST resolution and throughput have led to an increase in scientific interest, notably in cancer research. This scoping study reviews the challenges and practical applications of ST, summarizing current methods, trends, and data analysis techniques for ST in neoplasm research. We analyzed 41 articles published by the end of 2023 alongside public data repositories. The findings indicate cancer biology is an important focus of ST research, with a rising number of studies each year. Visium (10x Genomics, Pleasanton, CA, USA) is the leading ST platform, and SCTransform from Seurat R library is the preferred method for data normalization and integration. Many studies incorporate additional data types like single-cell sequencing and immunohistochemistry. Common ST applications include discovering the composition and function of tumor tissues in the context of their heterogeneity, characterizing the tumor microenvironment, or identifying interactions between cells, including spatial patterns of expression and co-occurrence. However, nearly half of the studies lacked comprehensive data processing protocols, hindering their reproducibility. By recommending greater transparency in sharing analysis methods and adapting single-cell analysis techniques with caution, this review aims to improve the reproducibility and reliability of future studies in cancer research.

GeoPick ‐ A web application for georeferencing natural history collections following best practices

Georeferencing is a key process in the digitization of natural history collections as it assigns spatial coordinates to preserved specimen collecting locations, facilitating their use in ecological, evolutionary and conservation research. Georeference data in public repositories such as GBIF is often missing or incomplete, jeopardising their use in research and limiting the return on investment made by public institutions. Despite the existence of guidelines for best practices for georeferencing and widely accepted standards for biodiversity data, there is a lack of a simple yet effective software tool that offers the implementation of both concepts. We present GeoPick with the aim to offer the collections community a standards‐compliant tool that eases the georeferencing process, making it more cost‐effective, and which, by applying best practices, contributes to the betterment of the occurrence data in public repositories. GeoPick also offers the possibility of collaboration between users and institutions through the sharing of georeferences. The tool is hosted by GBIF at https://geopick.gbif.org, and is open source. Its code is available at a public GitHub repository (https://github.com/rtdeb/GeoPick).Keywords: Darwin Core, georeferencing, natural history collections, point‐radius method, web application, Well Known Text Format, WKT

Racial distribution of molecularly classified brain tumors.

In many cancers, specific subtypes are more prevalent in specific racial backgrounds. However, little is known about the racial distribution of specific molecular types of brain tumors. Public data repositories lack data on many brain tumor subtypes as well as diagnostic annotation using the current World Health Organization classification. A better understanding of the prevalence of brain tumors in different racial backgrounds may provide insight into tumor predisposition and development, and improve prevention. We retrospectively analyzed the racial distribution of 1709 primary brain tumors classified by their methylation profiles using clinically validated whole genome DNA methylation. Self-reported race was obtained from medical records. Our cohort included 82% White, 10% Black, and 8% Asian patients with 74% of patients reporting their race. There was a significant difference in the racial distribution of specific types of brain tumors. Blacks were overrepresented in pituitary adenomas (35%, P < .001), with the largest proportion of FSH/LH subtype. Whites were underrepresented at 47% of all pituitary adenoma patients (P < .001). Glioblastoma (GBM) IDH wild-type showed an enrichment of Whites, at 90% (P < .001), and a significantly smaller percentage of Blacks, at 3% (P < .001). Molecularly classified brain tumor groups and subgroups show different distributions among the three main racial backgrounds suggesting the contribution of race to brain tumor development.

Exploring and retrieving sequence and metadata for species across the tree of life with NCBI Datasets

To explore complex biological questions, it is often necessary to access various data types from public data repositories. As the volume and complexity of biological sequence data grow, public repositories face significant challenges in ensuring that the data is easily discoverable and usable by the biological research community. To address these challenges, the National Center for Biotechnology Information (NCBI) has created NCBI Datasets. This resource provides straightforward, comprehensive, and scalable access to biological sequences, annotations, and metadata for a wide range of taxa. Following the FAIR (Findable, Accessible, Interoperable, and Reusable) data management principles, NCBI Datasets offers user-friendly web interfaces, command-line tools, and documented APIs, empowering researchers to access NCBI data seamlessly. The data is delivered as packages of sequences and metadata, thus facilitating improved data retrieval, sharing, and usability in research. Moreover, this data delivery method fosters effective data attribution and promotes its further reuse. This paper outlines the current scope of data accessible through NCBI Datasets and explains various options for exploring and downloading the data.

Integrative bioinformatics approach for identifying key genes and potential therapeutic targets in the concurrent manifestation of hypertrophic cardiomyopathy and pulmonary hypertension.

Hypertrophic cardiomyopathy (HCM), identified as a primary cause of sudden cardiac death (SCD), intertwines with pulmonary hypertension (PH) to amplify cardiovascular morbidity. This complex synergy poses significant therapeutic challenges due to the absence of drugs specifically targeting their concurrent manifestation. This study seeks to unravel the molecular intricacies linking HCM and PH, aiming to lay the groundwork for targeted therapeutic interventions. Through the analysis of gene expression profiles from datasets GSE36961 (HCM) and GSE113439 (PH) within the public data repository of Gene Expression Omnibus (GEO), this research systematically identified differentially expressed genes (DEGs), conducted extensive functional annotations, and constructed detailed protein-protein interaction (PPI) networks to uncover crucial hub genes. Further, co-expression analyses, alongside drug prediction and molecular docking simulations, were employed to pinpoint potential therapeutic agents that could ameliorate the combined pathology of HCM and PH. Our comprehensive analysis unearthed 79 DEGs shared between HCM and PH, highlighting fourteen as pivotal hub genes. Validation across three additional datasets (GSE35229, GSE32453, and GSE53408) from GEO accentuated secreted phosphoprotein 1 (SPP1) as a key gene of interest. Remarkably, the study identified tacrolimus, ponatinib, bosutinib, dasatinib, doxorubicin, and zanubrutinib as promising drugs for addressing the dual challenge of HCM and PH. The findings of this investigation shed light on the genetic underpinnings of HCM and PH's simultaneous occurrence, emphasizing the central role of SPP1 in their pathogenesis. The identification of six candidate drugs offers a hopeful vista for future therapeutic strategies targeting this complex cardiovascular interplay, marking a significant stride towards mitigating the compounded morbidity of HCM and PH. Future mechanistic and clinical studies are warranted for the investigation of this potential target and therapeutics.

Identification of a Novel miR-195-5p/PNN Axis in Colorectal Cancer.

Pinin (PNN) is a desmosome-associated protein that reinforces the organization of keratin intermediate filaments and stabilizes the anchoring of the cytoskeleton network to the lateral surface of the plasma membrane. The aberrant expression of PNN affects the strength of cell adhesion as well as modifies the intracellular signal transduction pathways leading to the onset of CRC. In our previous studies, we characterized the role of miR-195-5p in the regulation of desmosome junctions and in CRC progression. Here, with the aim of investigating additional mechanisms related to the desmosome complex, we identified PNN as a miR-195-5p putative target. Using a public data repository, we found that PNN was a negative prognostic factor and was overexpressed in colon cancer tissues from stage 1 of the disease. Then, we assessed PNN expression in CRC tissue specimens, confirming the overexpression of PNN in tumor sections. The increase in intracellular levels of miR-195-5p revealed a significant decrease in PNN at the mRNA and protein levels. As a consequence of PNN regulation by miR-195-5p, the expression of KRT8 and KRT19, closely connected to PNN, was affected. Finally, we investigated the in vivo effect of miR-195-5p on PNN expression in the colon of AOM/DSS-treated mice. In conclusion, we have revealed a new mechanism driven by miR-195-5p in the regulation of desmosome components, suggesting a potential pharmacological target for CRC therapy.

Defining a malaria diagnostic pathway from innovation to adoption: Stakeholder perspectives on data and evidence gaps.

Malaria, a major global health concern, requires effective diagnostic tools for patient care, disease control, and elimination. The pathway from concept to the adoption of diagnostic products is complex, involving multiple steps and stakeholders. To map this process, our study introduces a malaria-specific diagnostic pathway, synthesising existing frameworks with expert insights. Comprising six major stages and 31 related activities, the pathway retains the core stages from existing frameworks and integrates essential malaria diagnostic activities, such as WHO prequalification processes, global stakeholder involvement, and broader health systems considerations. To understand the scope and availability of evidence guiding the activities along this pathway, we conducted an online survey with 113 participants from various stages of the malaria diagnostic pathway. The survey assessed perceptions on four critical attributes of evidence: clear requirements, alignment with user needs, accuracy and reliability, and public and free availability. It also explored the types of evidence used and the challenges and potential solutions related to evidence generation and use. Respondents reported using a broad range of formal and informal data sources. Findings indicated differing levels of agreement on the attributes across pathway stages, with notable challenges in the Approvals and Manufacturing stage and consistent concerns regarding the public availability of data/evidence. The study offers valuable insights for optimising evidence generation and utilisation across the malaria diagnostic pathway. It highlights the need for enhanced stakeholder collaboration, improved data availability, and increased funding to support effective evidence generation, sharing, and use. We propose actionable solutions, including the use of public data repositories, progressive data sharing policies, open-access publishing, capacity-building initiatives, stakeholder engagement forums, and innovative funding solutions. The developed framework and study insights have broader applications, offering a model adaptable for other diseases, particularly for neglected tropical diseases, which face similar diagnostic challenges.

Screening of Metal Reduction Potential for Thermochemical Hydrogen Storage

The screening of all non-radioactive metals without lanthanides for thermochemical hydrogen storage was performed based on physical chemistry calculations. The thermodynamic data were collected from the NIST (National Institute of Standards and Technology) public data repository, which was followed by calculations regarding the change in enthalpy, entropy, Gibbs free energy and equilibrium reaction temperature. The results were critically evaluated based on thermodynamic parameters, viable metals were identified, and their hydrogen storage densities and energy–enthalpy ratios were evaluated. The elements viable for controlled thermochemical hydrogen storage via the reversible reduction and oxidation of metal oxides and metals are manganese (Mn), iron (Fe), molybdenum (Mo) and tungsten (W). Manganese has the largest theoretical potential for hydrogen storage with reversible reduction and oxidation of metal oxides and metals. The second candidate is iron, while the other two (Mo and W) have much lower potential. More research efforts should be dedicated to experimental testing of the identified metals (Mn, Fe, Mo and W) and their different oxides for thermochemical hydrogen storage capabilities both on laboratory and pilot scales. Ferromanganese alloy(s) might also prove itself as an efficient and affordable thermochemical hydrogen storage material. Our theoretical investigation expanded the knowledge on thermochemical hydrogen storage and is accompanied with a brief literature review revealing the lack of experimental studies, especially on oxidation of metals with water vapor occurring during the hydrogen release phase of the cycle. Consequently, accurate modelling of transport, kinetics and other phenomena during hydrogen storage and release is scarce.

The efficacy of single mitochondrial genes at reconciling the complete mitogenome phylogeny-a case study on dwarf chameleons.

Although genome-scale data generation is becoming more tractable for phylogenetics, there are large quantities of single gene fragment data in public repositories and such data are still being generated. We therefore investigated whether single mitochondrial genes are suitable proxies for phylogenetic reconstruction as compared to the application of full mitogenomes. With near complete taxon sampling for the southern African dwarf chameleons (Bradypodion), we estimated and compared phylogenies for the complete mitogenome with topologies generated from individual mitochondrial genes and various combinations of these genes. Our results show that the topologies produced by single genes (ND2, ND4, ND5, COI, and COIII) were analogous to the complete mitogenome, suggesting that these genes may be reliable markers for generating mitochondrial phylogenies in lieu of generating entire mitogenomes. In contrast, the short fragment of 16S commonly used in herpetological systematics, produced a topology quite dissimilar to the complete mitogenome and its concatenation with ND2 weakened the resolution of ND2. We therefore recommend the avoidance of this 16S fragment in future phylogenetic work.

Advancing bee conservation in the US: gaps and opportunities in data collection and reporting

IntroductionBee conservation in the US is currently hindered by challenges associated with assessing the status and trends of a diverse group of &amp;gt;3000 species, many of which are rare, endemic to small areas, and/or exhibit high inter-annual variationin population size. Fundamental information about the distribution of most species across space and time, thus, is lacking yet urgently needed to assess population status, guide conservation plans, and prioritize actions among species and geographies.MethodsUsing wild bee data from two public data repositories representing the contiguous US, we evaluated the availability and sufficiency of data for use in species assessments of wild bees. We also examined the number of bee species recorded in each US state and the proportion of species with recent records (2012–2021).ResultsAlthough efforts to monitor bees continue to grow, there remains a massive paucity of data. Exceedingly few records (0.04%)reported both sampling protocol and effort, greatly limiting the usefulness of the data. Few species or locations have adequate publicly available data to support analyses of population status or trends, and fewer than half of species have sufficient data to delineate geographic range. Despite an exponential increase in data submissions since the 2000s, only 47% of species were reported within the last decade, which may be driven by how data are collected, reported, and shared, or may reflect troubling patterns of local or large-scale declines and extirpations.DiscussionBased on our analysis, we provide recommendations to improve the quality and quantity of data that can be used to detect, understand, and respond to changes in wild bee populations.

Canonical notch activation in patients with scrub typhus: association with organ dysfunction and poor outcome

PurposeThe mechanisms that control inflammation in scrub typhus are not fully elucidated. The Notch pathways are important regulators of inflammation and infection, but have not been investigated in scrub typhus.MethodsPlasma levels of the canonical Notch ligand Delta-like protein 1 (DLL1) were measured by enzyme immunoassay and RNA expression of the Notch receptors (NOTCH1, NOTCH2 and NOTCH4) in whole blood was analyzed by real-time PCR in patients with scrub typhus (n = 129), in patients with similar febrile illness without O. tsutsugamushi infection (n = 31) and in healthy controls (n = 31); all from the same area of South India.ResultsOur main results were: (i) plasma DLL1 was markedly increased in scrub typhus patients at hospital admission with a significant decrease during recovery. (ii) RNA expression of NOTCH4 was decreased at admission in whole blood. (iii) A similar pattern for DLL1 and NOTCH4 was seen in febrile disease controls. (iv) Admission DLL1 in plasma was associated with disease severity and short-term survival. (vi) Regulation of Notch pathways in O. tsutsugamushi-infected monocytes as evaluated by public repository data revealed enhanced canonical Notch activation with upregulation of DLL1 and downregulation of NOTCH4.ConclusionOur findings suggest that scrub typhus patients are characterized by enhanced canonical Notch activation. Elevated plasma levels of DLL1 were associated with organ dysfunction and poor outcomes in these patients.

Unveiling the impacts of land use on the phylogeography of zoonotic New World Hantaviruses

Billions of genomic sequences and records of species occurrence are available in public repositories (e.g. National Center for Biotechnology Information, NCBI and the Global Biodiversity Information Facility, GBIF). By implementing analytical tools from different scientific disciplines, data mining these databases can aid in the global surveillance of zoonotic pathogens that circulate among wildlife. We illustrate this by investigating the Hantavirus–rodent system in the Americas, i.e. New World Hantaviruses (NWH). First, we considered the circulation of pathogenic NWH among Cricetidae rodents, by inferring the phylogenetic links among 277 genomic samples of the S segment (N protein) of NWH found in 55 species. Second, we used machine learning to assess the impact of land use on the probability of presence of the rodent species linked with reservoirs of pathogenic Hantaviruses. Our results show that hosts are widely present across the Americas. Some hosts are present in the primary forest and agricultural land, but not in the secondary forest, whereas other hosts are present in secondary forest and agricultural land. The diversity of host species allows Hantavirus to circulate in a wide spectrum of habitats, in particular rural rather than urban. We highlight that public repositories of genomic data and species occurrence are very useful resources for monitoring potential enzootic transmission and spillover of zoonotic viruses in relation with the changes that humans produce in the biosphere.

Ability to Simulate Absorption and Melt Pool Dynamics for Laser Melting of Bare Aluminum Plate: Results and Insights from the 2022 Asynchronous AM-Bench Challenge

The 2022 Asynchronous AM-Bench challenge was designed to test the ability of simulations to accurately predict laser power absorption as well as various melt pool behaviors (width, depth, and solidification) during laser melting of solid metal during stationary and scanned laser illumination. In this challenge, participants were asked to predict a series of experimental outcomes. Experimental data were obtained from a series of experiments performed at the Advanced Photon Source at Argonne National Laboratories in 2019. These experiments combined integrating sphere radiometry with high-speed X-ray imaging, allowing for the simultaneous recording of absolute laser power absorption and two-dimensional, projected images of the melt pool. All challenge problems were based on experiments using bare aluminum solid metal. Participants were provided with pertinent experimental information like laser power, scan speed, laser spot size, and material composition. Additionally, participants were given absorptance and X-ray imaging data from stationary and scanned laser experiments on solid Ti–6Al–4V that could be used for testing their models before attempting challenge problems. In total, this challenge received 56 submissions from eight different research groups for eight individual challenge problems. The data for this challenge, and associated information, are available for download from the NIST Public Data Repository. This paper summarizes the results from the 2022 Asynchronous AM-Bench challenge as well as discusses the lessons learned to help inform future challenges.

Integrated meta-analysis of colorectal cancer public proteomic datasets for biomarker discovery and validation.

The cancer biomarker field has been an object of thorough investigation in the last decades. Despite this, colorectal cancer (CRC) heterogeneity makes it challenging to identify and validate effective prognostic biomarkers for patient classification according to outcome and treatment response. Although a massive amount of proteomics data has been deposited in public data repositories, this rich source of information is vastly underused. Here, we attempted to reuse public proteomics datasets with two main objectives: i) to generate hypotheses (detection of biomarkers) for their posterior/downstream validation, and (ii) to validate, using an orthogonal approach, a previously described biomarker panel. Twelve CRC public proteomics datasets (mostly from the PRIDE database) were re-analysed and integrated to create a landscape of protein expression. Samples from both solid and liquid biopsies were included in the reanalysis. Integrating this data with survival annotation data, we have validated in silico a six-gene signature for CRC classification at the protein level, and identified five new blood-detectable biomarkers (CD14, PPIA, MRC2, PRDX1, and TXNDC5) associated with CRC prognosis. The prognostic value of these blood-derived proteins was confirmed using additional public datasets, supporting their potential clinical value. As a conclusion, this proof-of-the-concept study demonstrates the value of re-using public proteomics datasets as the basis to create a useful resource for biomarker discovery and validation. The protein expression data has been made available in the public resource Expression Atlas.

Streamlining remote nanopore data access with slow5curl.

As adoption of nanopore sequencing technology continues to advance, the need to maintain large volumes of raw current signal data for reanalysis with updated algorithms is a growing challenge. Here we introduce slow5curl, a software package designed to streamline nanopore data sharing, accessibility, and reanalysis. Slow5curl allows a user to fetch a specified read or group of reads from a raw nanopore dataset stored on a remote server, such as a public data repository, without downloading the entire file. Slow5curl uses an index to quickly fetch specific reads from a large dataset in SLOW5/BLOW5 format and highly parallelized data access requests to maximize download speeds. Using all public nanopore data from the Human Pangenome Reference Consortium (>22 TB), we demonstrate how slow5curl can be used to quickly fetch and reanalyze raw signal reads corresponding to a set of target genes from each individual in large cohort dataset (n = 91), minimizing the time, egress costs, and local storage requirements for their reanalysis. We provide slow5curl as a free, open-source package that will reduce frictions in data sharing for the nanopore community: https://github.com/BonsonW/slow5curl.

Retrieving biodiversity data from multiple sources: making secondary data standardised and accessible.

Biodiversity data, particularly species occurrence and abundance, are indispensable for testing empirical hypothesis in natural sciences. However, datasets built for research programmes do not often meet FAIR (findable, accessible, interoperable and reusable) principles, which raises questions about data quality, accuracy and availability. The 21st century has markedly been a new era for data science and analytics and every effort to aggregate, standardise, filter and share biodiversity data from multiple sources have become increasingly necessary. In this study, we propose a framework for refining and conforming secondary biodiversity data to FAIR standards to make them available for use such as macroecological modelling and other studies. We relied on a Darwin Core base model to standardise and further facilitate the curation and validation of data related including the occurrence and abundance of multiple taxa of a region that encompasses estuarine ecosystems in an ecotonal area bordering the easternmost Amazonia. We further discuss the significance of feeding standardised public data repositories to advance scientific progress and highlight their role in contributing to the biodiversity management and conservation.

Modeling multiple correlated end-organ disease trajectories: A tutorial for multistate and joint models with applications in diabetes complications.

State-of-the-art biostatistics methods allow for the simultaneous modeling of several correlated non-fatal disease processes over time, but there is no clear guidance on the optimal analysis in most settings. An example occurs in diabetes, where it is not known with certainty how microvascular complications of the eyes, kidneys, and nerves co-develop over time. In this article, we propose and contrast two general model frameworks for studying complications (sequential state and parallel trajectory frameworks) and review multivariate methods for their analysis, focusing on multistate and joint modeling. We illustrate these methods in a tutorial format using the long-term follow-up from the Diabetes Control and Complications Trial and Epidemiology of Diabetes Interventions and Complications study public data repository. A formal comparison of prediction error and discrimination is included. Multistate models are particularly advantageous for determining the order and timing of complications, but require discretization of the longitudinal outcomes and possibly a very complex state space process. Intermittent observation of the states must be accounted for, and discretization is a probable disadvantage in this setting. In contrast, joint models can account for variations of continuous biomarkers over time and are particularly designed for modeling complex association structures between the complications and for performing dynamic predictions of an outcome of interest to inform clinical decisions (eg, a late-stage complication). We found that both models have helpful features that can better-inform our understanding of the complex trajectories that complications may take and can therefore help with decision making for patients presenting with diabetes complications.