Use of Whole Genome Sequencing for Mycobacterium tuberculosis Complex Antimicrobial Susceptibility Testing: From Sequence Data to Resistance Profiles.

Whole genome sequencing of Mycobacterium tuberculosis complex (MTBC) isolates has been shown to provide accurate predictions for resistance and susceptibility for many first- and second-line anti-tuberculosis drugs. However, bioinformatic pipelines and mutation catalogs to predict antimicrobial resistances in MTBC isolates are often customized and detailed protocols are difficult to access. Here, we provide a step-by-step workflow for the processing and interpretation of short-read sequencing data and give an overview of available analysis pipelines.

RIBAP: a comprehensive bacterial core genome annotation pipeline for pangenome calculation beyond the species level.

Microbial pangenome analysis identifies present or absent genes in prokaryotic genomes. However, current tools are limited when analyzing species with higher sequence diversity or higher taxonomic orders such as genera or families. The Roary ILP Bacterial core Annotation Pipeline (RIBAP) uses an integer linear programming approach to refine gene clusters predicted by Roary for identifying core genes. RIBAP successfully handles the complexity and diversity of Chlamydia, Klebsiella, Brucella, and Enterococcus genomes, outperforming other established and recent pangenome tools for identifying all-encompassing core genes at the genus level. RIBAP is a freely available Nextflow pipeline at github.com/hoelzer-lab/ribap and zenodo.org/doi/10.5281/zenodo.10890871.

pVACview: an interactive visualization tool for efficient neoantigen prioritization and selection.

Background: Neoantigen targeting therapies including personalized vaccines have shown promise in the treatment of cancers, particularly when used in combination with checkpoint blockade therapy. At least 100 clinical trials involving these therapies are underway globally. Accurate identification and prioritization of neoantigens is highly relevant to designing these trials, predicting treatment response, and understanding mechanisms of resistance. With the advent of massively parallel DNA and RNA sequencing technologies, it is now possible to computationally predict neoantigens based on patient-specific variant information. However, numerous factors must be considered when prioritizing neoantigens for use in personalized therapies. Complexities such as alternative transcript annotations, various binding, presentation and immunogenicity prediction algorithms, and variable peptide lengths/registers all potentially impact the neoantigen selection process. There has been a rapid development of computational tools that attempt to account for these complexities. While these tools generate numerous algorithmic predictions for neoantigen characterization, results from these pipelines are difficult to navigate and require extensive knowledge of the underlying tools for accurate interpretation. This often leads to over-simplification of pipeline outputs to make them tractable, for example limiting prediction to a single RNA isoform or only summarizing the top ranked of many possible peptide candidates. In addition to variant detection, gene expression and predicted peptide binding affinities, recent studies have also demonstrated the importance of mutation location, allele-specific anchor locations, and variation of T-cell response to long versus short peptides. Due to the intricate nature and number of salient neoantigen features, presenting all relevant information to facilitate candidate selection for downstream applications is a difficult challenge that current tools fail to address. Results: We have created pVACview, the first interactive tool designed to aid in the prioritization and selection of neoantigen candidates for personalized neoantigen therapies including cancer vaccines. pVACview has a user-friendly and intuitive interface where users can upload, explore, select and export their neoantigen candidates. The tool allows users to visualize candidates across three different levels, including variant, transcript and peptide information. Conclusions: pVACview will allow researchers to analyze and prioritize neoantigen candidates with greater efficiency and accuracy in basic and translational settings The application is available as part of the pVACtools pipeline at pvactools.org and as an online server at pvacview.org.

ProcaryaSV: structural variation detection pipeline for bacterial genomes using short-read sequencing.

BACKGROUND: Structural variations play an important role in bacterial genomes. They can mediate genome adaptation quickly in response to the external environment and thus can also play a role in antibiotic resistance. The detection of structural variations in bacteria is challenging, and the recognition of even small rearrangements can be important. Even though most detection tools are aimed at and benchmarked on eukaryotic genomes, they can also be used on prokaryotic genomes. The key features of detection are the ability to detect small rearrangements and support haploid genomes. Because of the limiting performance of a single detection tool, combining the detection abilities of multiple tools can lead to more robust results. There are already available workflows for structural variation detection for long-reads technologies and for the detection of single-nucleotide variation and indels, both aimed at bacteria. Yet we are unaware of structural variations detection workflows for the short-reads sequencing platform. Motivated by this gap we created our workflow. Further, we were interested in increasing the detection performance and providing more robust results. RESULTS: We developed an open-source bioinformatics pipeline, ProcaryaSV, for the detection of structural variations in bacterial isolates from paired-end short sequencing reads. Multiple tools, starting with quality control and trimming of sequencing data, alignment to the reference genome, and multiple structural variation detection tools, are integrated. All the partial results are then processed and merged with an in-house merging algorithm. Compared with a single detection approach, ProcaryaSV has improved detection performance and is a reproducible easy-to-use tool. CONCLUSIONS: The ProcaryaSV pipeline provides an integrative approach to structural variation detection from paired-end next-generation sequencing of bacterial samples. It can be easily installed and used on Linux machines. It is publicly available on GitHub at https://github.com/robinjugas/ProcaryaSV .

Shredding artifacts: extracting brain activity in EEG from extreme artifacts during skateboarding using ASR and ICA.

Introduction: To understand brain function in natural real-world settings, it is crucial to acquire brain activity data in noisy environments with diverse artifacts. Electroencephalography (EEG), while susceptible to environmental and physiological artifacts, can be cleaned using advanced signal processing techniques like Artifact Subspace Reconstruction (ASR) and Independent Component Analysis (ICA). This study aims to demonstrate that ASR and ICA can effectively extract brain activity from the substantial artifacts occurring while skateboarding on a half-pipe ramp. Methods: A dual-task paradigm was used, where subjects were presented with auditory stimuli during skateboarding and rest conditions. The effectiveness of ASR and ICA in cleaning artifacts was evaluated using a support vector machine to classify the presence or absence of a sound stimulus in single-trial EEG data. The study evaluated the effectiveness of ASR and ICA in artifact cleaning using five different pipelines: (1) Minimal cleaning (bandpass filtering), (2) ASR only, (3) ICA only, (4) ICA followed by ASR (ICAASR), and (5) ASR preceding ICA (ASRICA). Three skateboarders participated in the experiment. Results: Results showed that all ICA-containing pipelines, especially ASRICA (69%, 68%, 63%), outperformed minimal cleaning (55%, 52%, 50%) in single-trial classification during skateboarding. The ASRICA pipeline performed significantly better than other pipelines containing ICA for two of the three subjects, with no other pipeline performing better than ASRICA. The superior performance of ASRICA likely results from ASR removing non-stationary artifacts, enhancing ICA decomposition. Evidenced by ASRICA identifying more brain components via ICLabel than ICA alone or ICAASR for all subjects. For the rest condition, with fewer artifacts, the ASRICA pipeline (71%, 82%, 75%) showed slight improvement over minimal cleaning (73%, 70%, 72%), performing significantly better for two subjects. Discussion: This study demonstrates that ASRICA can effectively clean artifacts to extract single-trial brain activity during skateboarding. These findings affirm the feasibility of recording brain activity during physically demanding tasks involving substantial body movement, laying the groundwork for future research into the neural processes governing complex and coordinated body movements.

Oral Lipid Nanocrystal Amphotericin B (MAT2203) for the Treatment of Invasive Fungal Infections.

Amphotericin B (AmB) has broad fungicidal activity against many fungi, but the high incidence of adverse events, particularly nephrotoxicity, and the need for intravenous administration restrict its use for many patients. MAT2203, an investigational oral AmB formulation available under a compassionate use program, uses a lipid nanocrystal bilayer structure to deliver AmB with lower toxicity. We present a synopsis of clinical characteristics, treatment course, and outcomes for 5 patients who were treated with MAT2203. Outcomes were positive, with cure of infection noted in 4 patients and improvement in 1 patient who remains on therapy. MAT2203 was well tolerated with only modest gastrointestinal adverse effects. This new oral formulation might provide a safer treatment option for patients requiring extended courses of AmB.

In Silico Typing and Identification Confirmation of Isolates.

Streptococcus suis is an important zoonotic pathogen causing severe infections in pigs and humans. Serotyping of S. suis strains is crucial for epidemiological surveillance, outbreak investigations, and understanding the pathogenesis of this bacterium. Here, we describe a step-by-step approach that enhances a previously developed pipeline by utilizing a computational script for efficient and accurate typing of S. suis strains. The pipeline is implemented in Perl programming language and leverages the Short Read Sequence Typing for Bacterial Pathogens (SRST2) tool. It integrates various bioinformatics techniques and utilizes multiple databases, including a serotype database, cpsH confirmation database, multi-locus sequence typing (MLST) database, recN species-specific gene database, and virulence gene database. These databases contain comprehensive information on S. suis serotypes, genetic markers, and virulence factors. The script can utilize paired-end or single-end fastq files as input and first confirms the species by sequence read data aligning to the recN gene, ensuring the accurate identification of S. suis strains. The pipeline next performs MLST typing and virulence factor identification using SRST2 while in a parallel processes it performs in silico serotyping of the strains. The pipeline offers a streamlined and semiautomated approach to serotyping S. suis strains, facilitating large-scale studies and reducing the manual effort required for data analysis.

Bottom-up formulations for the multi-criteria decision analysis of oil and gas pipeline decommissioning in the North Sea: Brent field case study.

Many Oil and Gas (O&G) fields in the North Sea have produced their economically recoverable reserves and have entered the decommissioning phase or are close to cessation of production. The subsequent O&G decommissioning process involves a range of stakeholders with specific interests and priorities. This range of inputs to the process highlights the necessity for the development of multi-criteria decision frameworks to help guide the decision-making process. This study presents bottom-up formulations for the economic, environmental, and safety risk criteria to support the multi-criteria decision analysis within the Comparative Assessment (CA) of O&G pipeline decommissioning projects in the North Sea. The approach adapts current guidelines in the O&G industry and considers a range of parameters to provide estimations for the costs, energy usage, greenhouse gas emissions, and safety risks. To verify the effectiveness of the proposed bottom-up formulations, the longest oil export pipeline in the Brent field, PL001/N0501 is selected as a case study. The numerical results revealed the consistency of the results obtained from the proposed approach with those reported in the technical documents by industry. In most cases, the formulations provide estimates with less than 10% differences for the costs, energy usage, emissions, and safety risks. Based on the proposed multi-criteria formulations, the study also presents the use of an immersive decision-making environment within a marine simulator system to help inform the decision-making process by stakeholders.

Pipeline Embolization Device (PED) and Flow Re-Direction Endoluminal Device (FRED) for Intracranial Aneurysms; A Comparative Systematic Review and Meta-Analysis Study.

BACKGROUND: When it comes to intracranial aneurysms, the quest for more effective treatments is ongoing. Flow diversion represents a growing advancement in this field. This review seeks to compare two variants of the endovascular flow diversion method: the Flow Re-Direction Endoluminal Device (FRED) and the Pipeline Embolization Device (PED). METHODS: A systematic review was conducted according to the PRISMA guideline using PubMed, Scopus, Web of Science, and Embase, using appropriate terms to compare PED and FRED in double-arm studies from conception until October 8th, 2023. RESULTS: The meta-analysis encompassed 1,769 patients, with a predominance of females (75.5%), among whom 973 patients underwent FRED procedures, while 651 received PED interventions. At six months, complete occlusion rates were 0.62 for FRED and 0.68 for PED (P = 0.68). At one year and the last follow-up, no significant differences were observed between FRED and PED, respectively. Adequate occlusion rates were similar between FRED and PED (0.82 vs 0.79, P = 0.68). FRED showed a statistically significant higher rate of good mRS scores at follow-up (1.00 vs. 0.97, P = 0.03). Hemorrhage and re-treatment rates were higher in PED (P < 0.01) without considering the rupture status of the aneurysms due to the lack of data. CONCLUSION: This meta-analysis suggests comparable efficacy but different safety profiles between FRED and PED in treating intracranial aneurysms. FRED demonstrated a higher rate of good mRS scores, while PED showed increased hemorrhage and re-treatment rates. Understanding these differences is crucial for informed decision-making in clinical practice.

Inhomogeneous Strain Behaviors of the High Strength Pipeline Girth Weld under Longitudinal Loading.

Unforeseen failures in girth welds present a significant challenge for the pipeline industry. This study utilizes 3D Digital Image Correlation (DIC) assisted cross-weld tensile testing to analyze the strain response of high-strength thick-walled pipelines, providing essential insights into the strain migration and fracture mechanisms specific to girth welds. The results reveal that the welding process significantly affects the mechanical distribution within the girth weld. The tested Shielded Metal Arc Welded (SMAW-ed) pipe exhibited undermatched girth welds due to high heat input, while Gas Metal Arc Welding (GMAW) introduced a narrower weld and Heat-Affected Zone (HAZ) with higher hardness than the base metal, indicative of overmatched girth welds. Strain migration, resulting from a combination of metallurgical heterogeneous materials and geometrical reinforcement strengthening, progressed from the softer HAZ to the base metal in the SMAW-ed sample with reinforcement, ultimately leading to fracture in the base metal. In contrast, the GMAW-ed sample shows no strain migration. Reinforcement significantly improves the tensile strength of girth welds and effectively prevents failure in the weld region. Sufficient reinforcement is crucial for minimizing the risk of failure in critical areas such as the weld metal and HAZ, particularly in SMAW-ed pipes.

A Cybertaxonomic Revision of the "Crocidura pergrisea" Species Complex with a Special Focus on Endemic Rocky Shrews: Crocidura armenica and Crocidura arispa (Soricidae).

The extraction of museum DNA from a unique collection of samples of the "Crocidura pergrisea" species complex, which comprises local endemics of Central and West Asia, allowed us to determine their inter- and intragroup relationships. The first step of this study was the re-evaluation of heavily damaged type specimens of C. armenica via a microcomputed-tomography-based cybertaxonomic approach (CTtax), which enabled a precise description of the species' morphology; three-dimensional models of the cybertypes were made available through the MorphoBank Repository. We developed the "AProMaDesU" pipeline on the basis of five requirements for micro-CT-based cyber-datasets in relation to mammalian collections. Our second step was a combination of several meticulous approaches to morphological investigation against a background of a cytb-based phylogeny, which helped us to make a taxonomic decision about the status of species of the "pergrisea" group, e.g., C. arispa, C. armenica, and C. serezkyensis, when the morphological results were partly incongruent with the molecular phylogeny. Nevertheless, under two assumptions, our findings preserved a separate species-level status of C. serezkyensis and C. arispa. In addition, we restored the species-level status of C. armenica. This taxonomic decision is based on our morphospace analysis, which revealed unique craniomandibular shape transformations within the rocky shrews that helped them with the transition to a new area of morphospace/trophic niches and consequently separated them from the other analyzed Crocidura groups.

Decoding N400m Evoked Component: A Tutorial on Multivariate Pattern Analysis for OP-MEG Data.

Multivariate pattern analysis (MVPA) has played an extensive role in interpreting brain activity, which has been applied in studies with modalities such as functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG) and Electroencephalography (EEG). The advent of wearable MEG systems based on optically pumped magnetometers (OPMs), i.e., OP-MEG, has broadened the application of bio-magnetism in the realm of neuroscience. Nonetheless, it also raises challenges in temporal decoding analysis due to the unique attributes of OP-MEG itself. The efficacy of decoding performance utilizing multimodal fusion, such as MEG-EEG, also remains to be elucidated. In this regard, we investigated the impact of several factors, such as processing methods, models and modalities, on the decoding outcomes of OP-MEG. Our findings indicate that the number of averaged trials, dimensionality reduction (DR) methods, and the number of cross-validation folds significantly affect the decoding performance of OP-MEG data. Additionally, decoding results vary across modalities and fusion strategy. In contrast, decoder type, resampling frequency, and sliding window length exert marginal effects. Furthermore, we introduced mutual information (MI) to investigate how information loss due to OP-MEG data processing affect decoding accuracy. Our study offers insights for linear decoding research using OP-MEG and expand its application in the fields of cognitive neuroscience.

Raman-based PAT for VLP precipitation: systematic data diversification and preprocessing pipeline identification.

Virus-like particles (VLPs) are a promising class of biopharmaceuticals for vaccines and targeted delivery. Starting from clarified lysate, VLPs are typically captured by selective precipitation. While VLP precipitation is induced by step-wise or continuous precipitant addition, current monitoring approaches do not support the direct product quantification, and analytical methods usually require various, time-consuming processing and sample preparation steps. Here, the application of Raman spectroscopy combined with chemometric methods may allow the simultaneous quantification of the precipitated VLPs and precipitant owing to its demonstrated advantages in analyzing crude, complex mixtures. In this study, we present a Raman spectroscopy-based Process Analytical Technology (PAT) tool developed on batch and fed-batch precipitation experiments of Hepatitis B core Antigen VLPs. We conducted small-scale precipitation experiments providing a diversified data set with varying precipitation dynamics and backgrounds induced by initial dilution or spiking of clarified Escherichia coli-derived lysates. For the Raman spectroscopy data, various preprocessing operations were systematically combined allowing the identification of a preprocessing pipeline, which proved to effectively eliminate initial lysate composition variations as well as most interferences attributed to precipitates and the precipitant present in solution. The calibrated partial least squares models seamlessly predicted the precipitant concentration with R 2 of 0.98 and 0.97 in batch and fed-batch experiments, respectively, and captured the observed precipitation trends with R 2 of 0.74 and 0.64. Although the resolution of fine differences between experiments was limited due to the observed non-linear relationship between spectral data and the VLP concentration, this study provides a foundation for employing Raman spectroscopy as a PAT sensor for monitoring VLP precipitation processes with the potential to extend its applicability to other phase-behavior dependent processes or molecules.

Integrating Spatial and Morphological Characteristics into Melanoma Prognosis: A Computational Approach.

In this study, the prognostic value of cellular morphology and spatial configurations in melanoma has been examined, aiming to complement traditional prognostic indicators like mitotic activity and tumor thickness. Through a computational pipeline using machine learning and deep learning methods, we quantified nuclei sizes within different spatial regions and analyzed their prognostic significance using univariate and multivariate Cox models. Nuclei sizes in the invasive band demonstrated a significant hazard ratio (HR) of 1.1 (95% CI: 1.03, 1.18). Similarly, the nuclei sizes of tumor cells and Ki67 S100 co-positive cells in the invasive band achieved HRs of 1.07 (95% CI: 1.02, 1.13) and 1.09 (95% CI: 1.04, 1.16), respectively. Our findings reveal that nuclei sizes, particularly in the invasive band, are potentially prognostic factors. Correlation analyses further demonstrated a meaningful relationship between cellular morphology and tumor progression, notably showing that nuclei size within the invasive band correlates substantially with tumor thickness. These results suggest the potential of integrating spatial and morphological analyses into melanoma prognostication.

Effect of Cyclic Ice Plug Deformation on Microstructure and Mechanical Behaviors of Nuclear-Grade Low-Carbon Tubular Steel.

This study subjected nuclear-grade 20# pipeline steel to cyclic freeze-thaw ice plugging tests, simulating the plastic deformation experienced by pipes during ice plug removal procedures. Subsequently, the dislocation morphology and mechanical properties of the specimens post cyclic ice plugging were examined. The cyclic ice plugging process led to an increase in the dislocation density within the specimens. After 20 and 40 cycles of ice plugging, the internal dislocation structures evolved from individual dislocation lines and dislocation tangles to high-density dislocation walls and dislocation cells. These high-density dislocation walls and cells hindered dislocation motion, giving rise to strain hardening phenomena, thereby resulting in increased strength and hardness of the specimens with an increasing number of ice plugging cycles. In addition, a large stress field was generated around the dislocation buildup, which reduced the pipe material's plastic toughness. The findings elucidate the effects of cyclic ice plugging on the microstructure and properties of nuclear-grade 20# pipeline steel, aiming to provide a theoretical basis for the safe and stable application of ice plugging technology in nuclear piping systems.

Robust Point Cloud Registration for Aircraft Engine Pipeline Systems.

Aircraft engine systems are composed of numerous pipelines. It is crucial to regularly inspect these pipelines to detect any damages or failures that could potentially lead to serious accidents. The inspection process typically involves capturing complete 3D point clouds of the pipelines using 3D scanning techniques from multiple viewpoints. To obtain a complete and accurate representation of the aircraft pipeline system, it is necessary to register and align the individual point clouds acquired from different views. However, the structures of aircraft pipelines often appear similar from different viewpoints, and the scanning process is prone to occlusions, resulting in incomplete point cloud data. The occlusions pose a challenge for existing registration methods, as they can lead to missing or wrong correspondences. To this end, we present a novel registration framework specifically designed for aircraft pipeline scenes. The proposed framework consists of two main steps. First, we extract the point feature structure of the pipeline axis by leveraging the cylindrical characteristics observed between adjacent blocks. Then, we design a new 3D descriptor called PL-PPFs (Point Line-Point Pair Features), which combines information from both the pipeline features and the engine assembly line features within the aircraft pipeline point cloud. By incorporating these relevant features, our descriptor enables accurate identification of the structure of the engine's piping system. Experimental results demonstrate the effectiveness of our approach on aircraft engine pipeline point cloud data.

Entourage: all-in-one sequence analysis software for genome assembly, virus detection, virus discovery, and intrasample variation profiling.

BACKGROUND: Pan-virus detection, and virome investigation in general, can be challenging, mainly due to the lack of universally conserved genetic elements in viruses. Metagenomic next-generation sequencing can offer a promising solution to this problem by providing an unbiased overview of the microbial community, enabling detection of any viruses without prior target selection. However, a major challenge in utilising metagenomic next-generation sequencing for virome investigation is that data analysis can be highly complex, involving numerous data processing steps. RESULTS: Here, we present Entourage to address this challenge. Entourage enables short-read sequence assembly, viral sequence search with or without reference virus targets using contig-based approaches, and intrasample sequence variation quantification. Several workflows are implemented in Entourage to facilitate end-to-end virus sequence detection analysis through a single command line, from read cleaning, sequence assembly, to virus sequence searching. The results generated are comprehensive, allowing for thorough quality control, reliability assessment, and interpretation. We illustrate Entourage's utility as a streamlined workflow for virus detection by employing it to comprehensively search for target virus sequences and beyond in raw sequence read data generated from HeLa cell culture samples spiked with viruses. Furthermore, we showcase its flexibility and performance on a real-world dataset by analysing a preassembled Tara Oceans dataset. Overall, our results show that Entourage performs well even with low virus sequencing depth in single digits, and it can be used to discover novel viruses effectively. Additionally, by using sequence data generated from a patient with chronic SARS-CoV-2 infection, we demonstrate Entourage's capability to quantify virus intrasample genetic variations, and generate publication-quality figures illustrating the results. CONCLUSIONS: Entourage is an all-in-one, versatile, and streamlined bioinformatics software for virome investigation, developed with a focus on ease of use. Entourage is available at https://codeberg.org/CENMIG/Entourage under the MIT license.

Solidifying the minority high school student pathway: evidence from the health professions recruitment and exposure program.

Purpose: The objective of this report is to provide longitudinal insights on the impact of a health professions exposure program for high school students of underrepresented backgrounds in medicine. Context: Medical students at the University of Chicago reviewed data from their chapter of the Health Profession Recruitment and Exposure Program (HPREP) from 2016-2021 to discover trends in enrollment. This data is documented in the context of the program's mission to increase awareness of health disparities, the success of prominent alumni, and recent community efforts post-COVID-19 pandemic. Findings: Two hundred and ninety-nine high school students participated in the University of Chicago HPREP program between 2016 and 2021. Participants ranged in age from 12 to 18 years (mean = 16, SD = 1) and 74% (n = 222) were female students. Of 252 respondents, 58% (n = 147) identified as Black or African American, 31% (n = 77) identified as Latinx or of Hispanic origin, and 10% (n = 24) identified as another race or as bi-racial. Ten or fewer black male students participated in the program every year, including the 2020-2021 year in which 61 students participated. Conclusions: HPREP has played an important role in shaping the face of health care, especially in Chicago. The data suggests significant increases in the number of underrepresented minority women becoming physicians and serving Chicago communities in the next decade. Pathway programs for underrepresented students in medicine should be strategic in recruiting and educating future health professionals based on future workforce needs.

Science, Medicine, and Cytology: an educational program of the Diversity, Equity, and Inclusion Committee of the American Society of Cytopathology.

INTRODUCTION: As our field of pathology continues to grow, our trainee numbers are on the decline. To combat this trend, the ASC Diversity, Equity, and Inclusion Committee established the Science, Medicine, and Cytology SumMer Certificate program to improve exposure to pathology/cytopathology with a focus on diversity, equity, and inclusion. Herein, we report our findings of the first 2 years of the program. MATERIALS AND METHODS: An online course was developed targeting students who are underrepresented in medicine at the high school and college level. It consisted of several didactic sessions, presenting the common procedures involving cytopathologists and cytologists. Interviews with cytopathologists were also included. Participants were surveyed for demographic information and provided course evaluations. RESULTS: In the first year of the program (2021), 34 participants completed the program, which increased to 103 in 2022. In both years there was a diversity in participant demographic backgrounds; however, only a minority of participants self-identified as being underrepresented in medicine. A vast majority (>85%) of participants in both years were high school or college students. In 2021, 100% of participants stated that the program format was effective and 94% thought the content was appropriate for their level of education; in 2022 the results were similar. In 2021, 66% considered health care as a potential career; this value increased in 2022 to 83%. In 2021 and 2022, 31% and 38%, respectively, considered cytology as a career. CONCLUSIONS: Evaluations were excellent, generating interest in cytopathology. Barriers in reaching underrepresented minorities exist and additional work is needed. Expansion to a wider audience may increase outreach.