The In Vitro Permeation Test (IVPT) is a valuable tool for the study of topical pharmacokinetics of dermatologic formulations. A 45 year retrospective analysis was performed on archived percutaneous absorption data from various corticosteroids found in the author's files. The objective was to collate archived data on the relative bioavailability of topical corticosteroids from 15 steroids found in 62 formulations using the in vitro permeation test (IVPT) and the finite dose human cadaver skin model. Studies were conducted with and without occlusion, at different active ingredient concentrations and dose durations. Select steroids also had evaluations with vasoconstriction, and stratum corneum content by tape stripping. The percutaneous absorption of topical corticosteroids is highly dependent on formulation, but less so on steroid concentration within the formulation, and whether the applied dose is occluded or not occluded. In addition vasoconstriction does not necessarily correlate with steroid permeation. The IVPT method demonstrates that it can characterize the topical pharmacokinetics of topical corticosteroids. Overall, this retrospective analysis of data supports the value of the IVPT method for evaluating percutaneous absorption pharmacokinetics for topical therapeutic agents.
The AGENT project established a network of actively cooperating European genebanks, integrating genomic and phenotypic data from accessions of wheat and barley. Due to specific storage demands for phenotypic and genotypic data, the project used separate database instances and backend technologies to manage integrated phenotypic and genotypic data. We discuss the challenges encountered when integrating dispersed data to serve through a single interface such as the Plant Breeding Application Programming Interface, BrAPI. We examine how the consistent mappability of genebank data to the BrAPI model can enable the implementation of effective services. The advantages of BrAPI in transparently linking distributed data entities through embedded, unique identifiers are highlighted. We present a technical solution involving a BrAPI proxy, which combines and merges separate BrAPI endpoints. Finally, we demonstrate the AGENT BrAPI implementation with an illustrative example that validates a suggested SNP for a trait from the literature by linking phenotypic, genotypic and passport data. The BrAPI proxy implementation and documentation is available at the Python Package Index (https://pypi.org/project/brapi-proxy) and archived in Zenodo (doi : 10.5281/zenodo.19436445). Supplementary data are available at Bioinformatics online.
To evaluate the relationship between cervical area (CA) measured by two-dimensional (2D) transvaginal ultrasonography (TVUS) and the latency period in pregnancies complicated by preterm premature rupture of membranes (PPROM), and to compare its predictive performance with that of cervical length (CL). This retrospective cohort study included 164 singleton pregnancies with PPROM (24 + 0-32 + 3 weeks). Archived TVUS images obtained within 24 h of admission were reanalyzed in a blinded manner. CA (cm2), CL (mm), and cervical funneling were recorded. The latency period was defined as the time from membrane rupture to delivery and categorized as short (≤ 10 days) or long (> 10 days). Group comparisons, correlation analyses, receiver operating characteristic (ROC) curves, and multivariable logistic regression were performed to identify independent predictors. Seventy-eight pregnancies had a short latency period. Both CL and CA were significantly lower in the short-latency group. Although the area under the curve (AUC) for CA was higher than that for CL (0.763 vs. 0.678), pairwise comparison using the DeLong test did not show a statistically significant difference (p = 0.064). In the multivariable analysis, cervical funneling (adjusted OR 10.777, 95% CI 4.456-26.063; p < 0.001) and CA (adjusted OR 0.701, 95% CI 0.598-0.822; p < 0.001) remained independent predictors of a short latency, whereas CL lost significance (p = 0.383). CA and CL showed a positive correlation with the latency period (p < 0.001). CA measured by 2D-TVUS is an independent predictor of the latency period in PPROM and shows comparable discriminative ability to CL. Incorporating CA assessment may improve risk stratification and aid in timely perinatal management decisions in PPROM pregnancies.
Transcription factors (TFs) regulate gene expression by binding to specific DNA sites on genome, making accurate TF binding site prediction critical for understanding gene regulation and downstream phenotypes. Almost all current deep learning methods use only DNA-related information to predict TF binding sites, ignoring the fact that different TF protein sequences and structures recognize distinct DNA patterns. Not leveraging TF information not only limits prediction accuracy but also makes the methods not generalizable to predicting binding sites of new TFs that do not exist in the training data. Here, we present TransBind, a protein-aware deep learning architecture that integrates DNA sequence information with protein embeddings containing both sequence and structural information derived from a protein language model pretrained on DNA-binding proteins, to improve TF binding site prediction. Through the cross-attention, a TF embedding selectively attends to genomic regions according to its unique binding properties. Evaluated on the data of 690 ChIP-seq experiments spanning 161 TFs across 91 human cell types, TransBind achieves an AUROC of 0.9508 and AUPR of 0.3741-representing a [Formula: see text]11.8% relative AUPR improvement over state-of-the-art methods including TBiNet, EPBDXDNABERT-2, DanQ, and DeepSEA. The model outperformed existing methods in [Formula: see text]98% of TF-cell type combinations. It also recovered 160 known TF binding motifs in the JASPAR database, providing the biological interpretability of the model. Moreover, the approach enables label-zero-shot prediction for unseen TFs, demonstrating its potential of generalizing to new, poorly characterized TFs. The source code of TransBind is available at https://github.com/jianlin-cheng/TransBind. The version used in this work is archived at https://doi.org/10.5281/zenodo.19462292.
Gluteal prominence is a central feature of Brazilian beauty standards, historically reinforced by cultural expressions such as samba, carnival, and popular media. In recent years, this aesthetic has been amplified by the global popularization of the Brazilian Butt Lift (BBL), elevating the symbolic and commercial value of gluteal volume. Yet, no longitudinal study to date has examined how these ideals evolved in Brazilian visual culture. This study investigated temporal changes in the anthropometric profiles of nude models featured in Playboy Brazil from 1975 to 2018. A total of 491 models with reported measurements were analyzed. Linear correlation showed a significant increase in hip circumference over time (r = 0.47, p < 0.0001). This association remained significant after normalization to height (hip-to-height ratio: r = 0.43, p < 0.0001). Models with hips ≥ 100 cm exhibited lower waist-to-hip ratios (WHR) and higher body mass index (BMI), and WHR decreased despite larger waist sizes, indicating disproportionate enlargement of the lower body. Collectively, these findings document a progressive shift toward more accentuated lower-body profiles within this media archive. These findings contribute to understanding how culturally rooted aesthetic ideals may intensify or become reconfigured within evolving media contexts.
Dedifferentiated liposarcoma (DDLPS) is a typically non-lipogenic malignant neoplasm that arises from progression of an underlying atypical lipomatous tumour/well-differentiated liposarcoma (ALT/WDLPS) and is classically defined by amplification of chromosome 12q15, including MDM2 and frequently cyclin-dependent kinase 4 (CDK4). Detection of MDM2 amplification by fluorescence in situ hybridization (FISH) and/or MDM2 protein expression immunohistochemistry (IHC) has, therefore, become central to the diagnosis of DDLPS, particularly in small biopsies from the retroperitoneum. Rare exceptions to this paradigm have been described, but the clinicopathologic and molecular spectrum of MDM2 non-amplified DDLPS remains poorly characterized. We report a series of MDM2 non-amplified DDLPS to better define their diagnostic features, genomic alterations and clinical behaviour. Pathology archives from 2010 to 2025 were queried for cases diagnosed as DDLPS. Inclusion criteria required a high-grade sarcoma arising in a histologically confirmed ALT/WDLPS background, absence of MDM2 overexpression by IHC and lack of MDM2 amplification by FISH and/or single nucleotide polymorphism array. Clinicopathologic features, immunophenotype, treatment and outcomes were reviewed. Among 253 cases of DDLPS identified during the study period, four (1.6%) fulfilled criteria for MDM2-negative DDLPS. All tumours arose in the retroperitoneum or intra-abdominal soft tissues and demonstrated high-grade sarcoma morphology with an associated WDLPS component on resection. Despite the absence of MDM2 amplification, all cases showed strong CDK4 expression by IHC. Molecular analysis revealed recurrent alterations involving cell-cycle regulation, including CDK4 copy number gain in all cases and loss of CDKN2A in three. Two cases harboured TP53 alterations. Clinically, outcomes were heterogeneous, ranging from aggressive disease with rapid recurrence and death within months to prolonged disease-free survival exceeding 5 years. MDM2 non-amplified DDLPS represents a rare subset of DDLPS that appear to be driven by alternative mechanisms of cell-cycle dysregulation, most commonly involving CDK4 gain and CDKN2A loss, with occasional TP53 alterations. Awareness of this variant is critical to avoid misclassification as other high-grade sarcomas, particularly on limited biopsies, and underscores the importance of integrating morphology, IHC and broad genomic profiling in diagnostically challenging retroperitoneal sarcomas.
The westerlies moisture transport underpins water security for over two billion people dependent on the Asian water towers (AWTs). However, the mechanisms by which large-scale westerlies-advected moisture is integrated into the AWTs' atmospheric water budget remain poorly understood due to observational gaps. Here, we combine three-dimensional observations of atmospheric water vapor stable isotopes with isotope-enabled modeling. We identify the conveyor mechanism that regulates the vertical moisture transport under calm conditions during the winter-spring period when the westerlies are dominant. Sharp vertical isotopic gradients show that large-scale westerlies-advected moisture is predominantly confined aloft, while local residual moisture persists near the surface. Our results show the interplay of the westerlies' subsidence at night with thermodynamically distinct local residual air, yielding thermal inversions and condensation that suppresses vertical mixing and decouples moisture between the free troposphere and the atmospheric boundary layer. This process constitutes a primary pathway for integrating westerlies-advected moisture into the local moisture budget without precipitation, sustaining near-surface moisture accumulation. Our results provide critical benchmarks for improving atmospheric models, refining climate projections of the intensifying water cycle over the AWTs, and advancing interpretations of isotopic records in regional climatic archives.
This study aims to investigate the role of biliary microbiota (defined as the microbial community colonizing the biliary tract, including the gallbladder, intrahepatic and extrahepatic bile ducts) in the pathogenesis of cholelithiasis (CHOL) and cholangiocarcinoma (CCA), with a focus on the associations between microbial communities and these biliary diseases. We conducted a comprehensive bioinformatics analysis using high-throughput sequencing data obtained from the Sequence Read Archive (SRA) database to characterize the composition of microbial communities in patients with CCA and CHOL. We performed operational taxonomic unit (OTU) clustering, statistical analyses and Mendelian randomization (MR) to elucidate the causal relationships between specific bacterial strains and disease outcomes. Our findings revealed differences in the relative abundance of specific microbial taxa among research groups. The CCA + CHOL group exhibited a significant increase in the abundance of Fusobacteria, particularly Fusobacterium, compared to the Control or CCA group. This suggests a potential pathogenic role for these microorganisms in CHOL formation. Additionally, the CCA group demonstrated a higher diversity index, indicating that increased microbial diversity may contribute to the progression of the disease. MR analysis identified nominally significant statistical associations between specific bacterial strains. However, the presence of pleiotropy in some analyses necessitates caution when interpreting causal relationships. Our study highlights the complex interplay between biliary microbiota and the pathogenesis of CHOL and CCA. Modulating biliary microbiota may represent a promising therapeutic strategy for managing these diseases. Future research should focus on the functional roles of specific taxa in bile metabolism and immune modulation, ultimately improving our understanding of biliary health and disease management.
Monitoring human papillomavirus (HPV) types detected in cervical precancers has been one approach to evaluate HPV vaccination impact in the United States. During 2008-2014, the proportion of cervical precancers positive for HPV16/18 decreased overall and among some demographic and histologic subgroups. This updated analysis describes trends through 2019. We analyzed cervical precancers among women aged 20-39 years from a 5-site, population-based surveillance program for cervical intraepithelial neoplasia grades 2 or higher and adenocarcinoma in situ (AIS; collectively CIN2+). Available archived diagnostic tissue was tested for HPV 16, 18, and other HPV types. We evaluated the average annual percent change (AAPC) in the proportion of cervical precancers with HPV 16 or 18 detected overall and by vaccination status, age group, diagnosis, race/ethnicity, and surveillance site. During 2008-2019, 17,323 CIN2+ cases had valid typing results. The proportion of cases positive for HPV16/18 significantly decreased 3.6% per year. The largest decrease occurred among cases in vaccinated women (AAPC = -8.9), with smaller but still significant decreases among unvaccinated women (AAPC = -2.3). Significant decreases were observed among all subgroups evaluated except women aged 35-39 years, AIS, and Asian women. During 2008-2019, decreases in the proportion of CIN2+ that were HPV16/18-positive among vaccinated and unvaccinated women, and in most subgroups evaluated, suggest direct and indirect HPV vaccination impact. HPV vaccination impact on precancers is prognostic of future decreases in cervical cancer. Continued monitoring can enable evaluation of vaccination impact in population subgroups.
To describe both host gene expression and microbiome composition in a single sample, parallel experimental and computational workflows (mRNA-sequencing and either 16S rRNA gene or metagenomics) have been traditionally applied. The vulvar milieu represents an area of emerging research for its role in health and disease. Located at the interface between the vagina and the perineum, the vulvar microbiome displays an intermediate signature, with influx from both ecosystems. Following validation of the reliability of poly(A)-enriched mRNA-sequencing in reconstructing the microbiota composition using both a quantitative microbial standard (mock) and metagenomic analysis, we analyze a full cohort of 30 healthy vulvar samples. Crucially, the analysis of the entire cohort relies solely on mRNA-sequencing without the use of parallel DNA metagenomics. This unified approach allows us to analyze not only the vulvar cell transcriptome, but also the composition and dynamics of microbial communities, including the microbial gene expression signatures. This three-level analysis (host-mRNA, individual bacterial species, bacterial gene pathways) on the very same specimens further enables a gene-level exploration of host-microbe molecular crosstalk. Using this unified framework, we reveal marked heterogeneity and high inter-individual variability in the vulvar microbiota, identifying community state types that mirror those described in the vagina. Importantly, we show that distinct microbial configurations are associated with specific host transcriptional programs: Lactobacillus crispatus correlates with epithelial differentiation and barrier integrity, whereas communities enriched in Gardnerella vaginalis, or other taxa associated with dysbiosis, exhibit transcriptional signatures linked to inflammation. Interestingly, Lactobacillus gasseri, which has been associated with lower protection, shows an intermediate effect on vulvar cells. Beyond providing new biological insights into an understudied anatomical niche, our study introduces a broadly applicable strategy with substantial impact for the field. With tens of thousands of human RNA-seq datasets already available in public repositories, our approach enables retrospective extraction of microbiome information and host-microbe interaction signals from existing transcriptomic data, without the need for additional sequencing or specialized microbiome protocols. This unlocks a powerful and cost-effective opportunity to revisit archived RNA-seq studies across tissues, diseases, and low-biomass environments, revealing previously inaccessible layers of host-microbiome crosstalk and maximizing the scientific value of published data. Video Abstract.
Vision Transformers (ViTs) are one of the powerful tools in medical imaging, providing new possibilities for pancreatic cancer diagnosis. In recent years, several studies have reported deep learning (DL) techniques to computed tomography (CT) images for pancreatic cancer diagnosis using ViT-based architectures. Existing methods often suffer from high computational complexity and there are limitations in reducing false negatives, particularly for malignant lesion. This paper proposes an intelligent pancreatic tumor detection framework called Rotary Positional Siamese Vision Transformer (RPSViT), designed to accurately detect and classify pancreatic tumors by effectively localizing abnormalities in CT scan images. RPSViT employs a patch-based approach, dividing input images into fixed-size patches that are treated as tokens via linear patch embedding. Rotary positional embedding is then incorporated to capture better spatial relationships within the images, thereby enhancing tumor localisation accuracy. The Siamese Transformer Encoder extracts high-level feature vectors from the input samples and performs disease classification. The model was trained and evaluated on Pancreatic-CT scan images from The Cancer Imaging Archive (TCIA) datasets and Medical Segmentation Decathlon (MSD) datasets using a 5-fold cross-validation. Experimental results shows that the proposed RPSViT achieves a mean accuracy of 96.97 ± 1.81%, sensitivity of 96.06 ± 2.38%, specificity of 100.00 ± 0.00%, and mean AUC of 0.9989 ± 0.0015. Additionally, the framework attains an F1-score of 0.9798 ± 0.0125, Matthews correlation coefficient (MCC) of 0.9225 ± 0.0414, Cohen's kappa coefficient of 0.9188 ± 0.0448, average precision of 0.9997 ± 0.0004, and Jaccard index of 0.9606 ± 0.0238. These RPSViT performance results shows that it effectively bridges advanced transformer architectures with practical medical diagnostics, providing more accurate and automated tools in pancreatic oncology.
The computational burden of individual-level genetically regulated gene expression (GReX) imputation has risen sharply with the growth of human mega-biobanks and the rapid expansion of transcriptomic imputation models across tissues and single-cell hierarchies. Existing tools were not designed for this setting and require complex, memory-intensive workflows that are poorly matched to shared and cloud-based compute environments, where runtime, memory, and I/O directly determine cost and throughput. GROMTools is an open-source C++ engine with an R interface that exploits sparse prediction weights, streams PLINK2 genotypes, and writes compact binary outputs for scalable individual-level GReX imputation. In UK Biobank (UKBB), benchmarks on chromosome 1 across 50,000-450,000 individuals, 388,017 variants, and 11,724 gene-tissue pairs from 32 single-cell models, GROMTools produced near-identical predictions to PrediXcan and PLINK2, with minimum Pearson correlation >0.999 and maximum RMSE <0.001 across all of the imputed genes, while reducing CPU time by about 100-fold and peak memory by about 33-fold. These gains make routine biobank-scale individual-level GReX imputation practical and cost-efficient on standard CPU infrastructure. GROMTools is freely available at https://github.com/voloudakislab/gromtools under the GPL v3 license. Documentation available at https://voloudakislab.github.io/gromtools/ . All of our coding scripts used for quality control of data and benchmarking pipelines and all of our log files are archived at DOI: https://doi.org/10.5281/zenodo.19547333 .
This dataset comprises time-resolved 3D fluid field data (pressure and the three velocity components) from the viscous sublayer of a canonical zero-pressure-gradient turbulent boundary layer. In total it contains 16,384 snapshots, amounting to approximately 11.1 TiB of data (pre-compression). In addition to the snapshot data, the dataset also includes time-averaged turbulent statistics over the full boundary layer for the four primary quantities (pressure and velocity) together with the second-order velocity products, enabling validation and comparison with existing literature. To create the data, direct numerical simulations were performed with the high-order flow solver Incompact3d on the ARCHER2 UK national supercomputer. Following the simulation, the raw Incompact3d outputs were converted to Zarr v3 and uploaded to a remote object store, together with accompanying materials (metadata, example scripts, licence, and readme). Other than format conversion, no additional processing has been applied. The data are hosted on the Edinburgh International Data Facility (EIDF), which provides a graphical web interface via the Comprehensive Knowledge Archive Network (CKAN) interface. Given the size and structure of the dataset, programmatic access is expected to be most convenient; accordingly, the EIDF also exposes an interface compatible with a subset of the Amazon Simple Storage Service (S3) REST API. Performance-aware storage choices were made to facilitate efficient remote access. Chunk sizes were selected to optimise anticipated common access patterns. Where appropriate, sharding was applied to reduce the number of files and the load on the remote filesystem and compression has also been applied to reduce network traffic. Example Python scripts demonstrate end-to-end usage (opening the stores, plotting, unit conversion, and chunk-aware sampling for machine-learning pipelines), lowering the barrier to entry and serving as templates for custom analyses. The dataset will enable a broad range of research activities, including developing and testing turbulence theory, training and evaluating data-driven models, and validating experimental protocols and lower-fidelity computational fluid dynamics models.
The fruit fly Drosophila melanogaster is an excellent model for dissecting the molecular processes that regulate host-microbe interactions and the role of the microbiome in host homeostasis. More recently, the fly has also been used as a model for understanding entomopathogenic nematode infection and host response against these parasites. To gain insights into the effect of entomopathogenic nematode infection on the insect microbiome, D. melanogaster larvae were exposed to Heterorhabditis bacteriophora containing their symbiotic bacteria Photorhabdus luminescens (symbiotic worms) and nematodes lacking their bacterial symbionts (axenic worms). Microbiome changes were examined through 16S rRNA sequencing. Data were collected at 24- and 48-hours following infection of D. melanogaster larvae with either type of nematode. The complete set of raw sequencing data generated in this study has been deposited in the European Nucleotide Archive under accession number PRJEB85826.
This study investigates how terminally ill cancer patients on Douyin manage death anxiety through the curation of a "digital body." Drawing on a 12-month digital ethnography of 25 vloggers, the practice is theorized as "platformed thanatography." The analysis reveals the digital body serves a dual function: as a prosthetic self, it creates a persistent, future-oriented archive for symbolic immortality; as a therapeutic tool, it transforms chaotic suffering into a publicly validated narrative. It is argued that Douyin operates as a contemporary "technology of the dying self." Crucially, this existential agency is enacted within the platform's affective infrastructure, where algorithmic governance and a sympathy economy impose normative scripts of "ambivalent positivity" and commodify vulnerability. The study concludes that while digital platforms offer new resources for confronting mortality, they simultaneously subject the dying experience to the logics of datafication and extraction, highlighting critical tensions between digital immortality and embodied decay.
Grown in a transplant garden that provides field conditions but prevents predation by pocket gophers, plants of Erythronium grandiflorum (Liliaceae) have been exhumed annually (as dormant corms), photographed, and weighed over 33 years. From seed, plants grow to flowering size in about 5-6 years. They subsequently regulate their size by occasional vegetative splitting and by flowering and fruiting; producing one fruit costs a plant about 8% of the weight it would have gained if it had not flowered. Death is rare: a few plants have gradually lost weight and died in a way consistent with classical senescence, but others have died suddenly from fungal infection after previously growing robustly. Additional years of observation will be needed to clarify the issue of senescence. The data are archived and future collaborators are sought.
Changes in genome organisation contribute to genetic disease when they disrupt gene function or regulation. Structural rearrangements may interrupt coding sequence or alter expression through promoter loss or gain, chromatin changes, copy-number variation, or disruption of short-range regulatory elements. Although short-read sequencing excels at detecting small variants, it performs poorly at resolving breakpoints of large rearrangements, especially in repetitive or low-complexity regions. Long-read sequencing overcomes these limitations, but analytical tools have not kept pace, making accurate identification and annotation of large structural variants challenging. We developed AgileStructure, a desktop application for locating and annotating large‑scale genomic rearrangements using aligned long‑read data. The software enables user‑guided exploration of breakpoint‑spanning reads, supporting accurate interpretation of complex events and filling a key gap in current structural variant analysis workflows. Source code, binaries, user guide, and example aligned read data, are available on GitHub: https://github.com/msjimc/AgileStructure. An archived version is also available on Zenodo at https://doi.org/10.5281/zenodo.18610110. Supplementary data are available at Bioinformatics online.
Global demand for beef is projected to rise, coinciding with increasing climate change-related threats to animal welfare and productivity. Heat stress represents a major risk, impairing cattle health, growth, and reproductive efficiency. This study employed the Heat-Load Index, a composite measure of temperature, humidity, solar radiation, and wind speed, to classify heat stress into five categories. Using high-resolution climate projections from the NEX-GDDP-CMIP6 archive and a Multi-Model Ensemble of 27 global circulation models, we assessed heat stress risk for beef cattle worldwide under four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) through 2100. Results indicated a progressive expansion of severe and extreme heat stress categories, particularly in tropical and subtropical regions, with increasing encroachment into temperate zones by the late century. These findings highlight the urgent need for climate-smart livestock strategies, including genetic selection, improved housing, and adaptive management, to safeguard animal welfare and sustain global beef production.
Clinical pharmacy education originated in the United States during the 1950s and was introduced to China in the 1960s. In China, clinical pharmacy education encompasses degree-oriented and vocational education. The purpose of this study is to offer insights and references that may guide the future development of China's clinical pharmacy education. To acquire targeted and authoritative information, the study conducted a systematic literature and data retrieval process. This study searched academic databases, reviewed monographs on the history of pharmaceutical education, examined university archives, analyzed media reports, and browsed the official websites of educational institutions and healthcare facilities. Then this study classified, counted and analyzed the collected information according to the literature analysis method. Following a chronological framework, the study integrated the key policies and regulations, influential figures, and significant historical events that had shaped the development of degree-oriented and vocational education in China's clinical pharmacy. Findings reveal that China's degree-oriented education has evolved from a marginalized field to a multi-tiered and diversified training system. Likewise, vocational education has progressed from a fragmented and disorganized state into a more structured and standardized system. Nevertheless, significant challenges persist. Currently, universities and healthcare institutions often operate independently in the training of clinical pharmacists, lacking a unified and standardized educational model comparable to the Pharm. D. system in the US or the medical education system in China. There remains the absence of cohesive assessment standards and coordinated mechanisms across the country.
Vascular anomalies (VAs) are rare disorders with abnormal development of blood and lymphatic vasculature and surrounding tissues. Understanding the genetic etiology of VAs guides treatment with targeted inhibitors. This study compares patterns and outcomes of genetic testing in VA populations at 2 centers. Of 421 patients (mean age, 10 years; 55.6% female), 61.7% underwent prior authorization (PA) for genetic testing, 84% had their testing approved, 93% completed the testing. About 70% of the completed tests had pathogenic or likely pathogenic results. A positive result was not associated with sample type (skin biopsy vs surgical pathology; fresh vs archived). Greater odds of initiating PA were associated with presence of skin findings and male sex, whereas lower odds were associated with higher Area Deprivation Index at 1 center. This study highlights that genetic testing effectively finds causative variants, but not all patients can complete it and advocates for increased access to genetic testing.