Oncocytic/Hürthle cell lesions have the same implied risk of neoplasm/malignancy as their follicular counterparts.

INTRODUCTION: There are conflicting results on whether the presence of oncocytes modifies the risk of neoplasm (RON) or malignancy (ROM) for thyroid fine-needle aspirates (FNAs): Atypia of undetermined significance AUS and Follicular Neoplasm, FN, or Oncocytic Neoplasm, ON. To our knowledge, the effect of non-invasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) has not yet been studied. We compared RON and ROM between follicular type AUS (AUS-FT) and oncocytic type AUS (AUS-OT) and between FN and ON. MATERIALS AND METHODS: We retrospectively analysed all thyroid FNAs with the diagnostic category of AUS-other or Neoplasm (2005-2015). AUS-FT had predominance of microfollicles and AUS-OT had predominance of oncocytes. Histology follow-up was then reviewed and RON, ROM was then calculated and compared (significant at p < 0.05). We repeated the search for 2018 to evaluate for NIFTP effect. RESULTS: Pre-NIFTP, 859/5063 cases (17%) were AUS-FT, AUS-OT, FN, and ON. Histology follow-up was available for 297 cases (35%). RON was 83/183 (45%) for AUS-FT, 35/76 (46%) for AUS-OT, 15/25 (60%) for FN and 11/13 (85%) for ON. Post-NIFTP, RON was 11/31 (35%) for AUS-FT, 5/8 (63%) for AUS-OT, 1/2 (50%) for FN and 4/5 (80%) for ON. For both periods, RON, ROM of AUS-FT was not significantly different than AUS-OT, and no significant differences were observed comparing FN and ON. CONCLUSION: The predominance of oncocytes does not modify the implied RON, ROM for categories of AUS or FN\ON, even after the adoption of NIFTP.

Interim Phase II Results Using Panitumumab-IRDye800CW During Transoral Robotic Surgery in Patients with Oropharyngeal Cancer.

PURPOSE: The incidence of oropharyngeal squamous cell carcinoma (OPSCC) has continually increased during the past several decades. Using transoral robotic surgery (TORS) significantly improves functional outcomes relative to open surgery for OPSCC. However, TORS limits tactile feedback, which is often the most important element of cancer surgery. Fluorescence guided surgery (FGS) strategies to aid surgeon assessment of malignancy for resection are in various phases of clinical research but have the greatest potential impact for improving patient care when the surgeon has limited tactile feedback, such as during TORS. Here, we assessed the feasibility of intraoperative fluorescence imaging using panitumumab-IRDye800CW (PAN800) during TORS in OPSCC patients. PATIENTS AND METHODS: 12 consecutive patients with OPSCC were enrolled as part of a non-randomized, prospective, phase II FGS clinical trial using PAN800. TORS was performed with an integrated robot camera for surgeon assessment of fluorescence. Intraoperative and ex vivo fluorescence signals in tumors and normal tissue were quantified and correlated with histopathology. RESULTS: Intraoperative robot fluorescence views delineated OPSCC from normal tissue throughout the TORS procedure (10.7 mean tumor-to-background ratio), including in tumors with low expression of the molecular target. Tumor-specific fluorescence was consistent with surgeon-defined tumor borders requiring resection. Intraoperative robot fluorescence imaging revealed an OPSCC fragment initially overlooked during TORS based on brightfield views, further substantiating the clinical benefit of this FGS approach. CONCLUSIONS: Results from this OPSCC patient cohort support further clinical assessment of FGS during TORS to aid resection of solid tumors.

Associations Between Radiation Oncologist Demographic Factors and Segmentation Similarity Benchmarks: Insights From a Crowd-Sourced Challenge Using Bayesian Estimation.

PURPOSE: The quality of radiotherapy auto-segmentation training data, primarily derived from clinician observers, is of utmost importance. However, the factors influencing the quality of clinician-derived segmentations are poorly understood; our study aims to quantify these factors. METHODS: Organ at risk (OAR) and tumor-related segmentations provided by radiation oncologists from the Contouring Collaborative for Consensus in Radiation Oncology data set were used. Segmentations were derived from five disease sites: breast, sarcoma, head and neck (H&N), gynecologic (GYN), and GI. Segmentation quality was determined on a structure-by-structure basis by comparing the observer segmentations with an expert-derived consensus, which served as a reference standard benchmark. The Dice similarity coefficient (DSC) was primarily used as a metric for the comparisons. DSC was stratified into binary groups on the basis of structure-specific expert-derived interobserver variability (IOV) cutoffs. Generalized linear mixed-effects models using Bayesian estimation were used to investigate the association between demographic variables and the binarized DSC for each disease site. Variables with a highest density interval excluding zero were considered to substantially affect the outcome measure. RESULTS: Five hundred seventy-four, 110, 452, 112, and 48 segmentations were used for the breast, sarcoma, H&N, GYN, and GI cases, respectively. The median percentage of segmentations that crossed the expert DSC IOV cutoff when stratified by structure type was 55% and 31% for OARs and tumors, respectively. Regression analysis revealed that the structure being tumor-related had a substantial negative impact on binarized DSC for the breast, sarcoma, H&N, and GI cases. There were no recurring relationships between segmentation quality and demographic variables across the cases, with most variables demonstrating large standard deviations. CONCLUSION: Our study highlights substantial uncertainty surrounding conventionally presumed factors influencing segmentation quality relative to benchmarks.

Evaluating Patients' Health Literacy to Improve Thyroid Pathology Reports.

INTRODUCTION: As our growing population demonstrates a significant increase in the incidence of thyroid cancer, so does patient access to their medical records. Poor health literacy and understanding of disease severity, underscores the importance of effective and accessible patient-doctor communication. No previous studies on patient understanding of thyroid pathology reports exist; therefore, we sought to characterize health literacy in this population. METHODS: Using a modified Delphi technique, a 12-question multiple-choice survey regarding common pathology terms with possible definitions for each term was synthesized and administered to patients in a high-volume endocrine surgery clinic. Survey results, patient demographics, history of prior thyroid procedure (biopsy or surgery), and self-reported health literacy were collected. Data analysis included t tests, chi-squared, and multivariable linear regression using R. RESULTS: The survey was completed by 54 patients (response rate: 69.8%). On univariate analysis, White race, previous thyroid procedure, and at least a high school level education were all more likely to score higher on the survey than their counterparts (P < 0.05). On multivariable logistic regression for predicting a higher survey score, only race (est: 2.48 [95% confidence interval: 1.01-3.96]) and higher educational attainment (est: 3.98 [95% confidence interval: 2.32-5.64]) remained predictive (P < 0.05). The remaining demographic groups (age, health literacy confidence, and previous thyroid procedure) did not show a statistically significant difference. CONCLUSIONS: Overall, terms on a thyroid pathology report are poorly understood by patients. This is exacerbated by non-White race and low educational attainment. There is a need for patient-facing pathology education.

Changing digital and telecytology practices post COVID-19 comparing ASC survey results from 2016 to 2023.

INTRODUCTION: During the COVID-19 pandemic, the need for digital pathology tools became more urgent. However, there needs to be more knowledge of the use in cytology. We aimed to evaluate current digital cytology practices and attitudes and compare the results with a pre-COVID-19 American Society of Cytopathology (ASC) survey. MATERIALS AND METHODS: Fourteen survey questions assessing current attitudes toward digital cytology were developed from a 2016 ASC Digital Pathology Survey. Ten new survey questions were also created to evaluate telecytology use. The survey was e-mailed to ASC members over 6 weeks in 2023. RESULTS: A total of 123 individuals responded (116 in 2016). Attitudes toward digital cytology were unchanged; most participants stated digital cytology is beneficial (87% 2023 versus 90% 2016). The percentage of individuals using digital cytology was unchanged (56% in 2016 and 2023). However, telecytology for rapid onsite assessment (ROSE) is now considered the best application (55% 2023 versus 31% 2016). Forty-three institutions reported using digital and telecytology tools; 40% made implementations after 2020; most did not feel that COVID-19 affected digital cytology (56%). Telecytology for ROSE is the most common application now (78%) compared with education (30%) in 2016. Limitations for implementing digital imaging in cytology included inability to focus (38%) and expense (33%). CONCLUSIONS: General attitudes toward digital tools by the cytology community have essentially remained the same between 2016 and now. However, telecytology for ROSE is increasingly being used, which supports a need for validation and competency guidelines.

Where the rubber meets the road: Emerging environmental impacts of tire wear particles and their chemical cocktails.

About 3 billion new tires are produced each year and about 800 million tires become waste annually. Global dependence upon tires produced from natural rubber and petroleum-based compounds represents a persistent and complex environmental problem with only partial and often-times, ineffective solutions. Tire emissions may be in the form of whole tires, tire particles, and chemical compounds, each of which is transported through various atmospheric, terrestrial, and aquatic routes in the natural and built environments. Production and use of tires generates multiple heavy metals, plastics, PAH's, and other compounds that can be toxic alone or as chemical cocktails. Used tires require storage space, are energy intensive to recycle, and generally have few post-wear uses that are not also potential sources of pollutants (e.g., crumb rubber, pavements, burning). Tire particles emitted during use are a major component of microplastics in urban runoff and a source of unique and highly potent toxic substances. Thus, tires represent a ubiquitous and complex pollutant that requires a comprehensive examination to develop effective management and remediation. We approach the issue of tire pollution holistically by examining the life cycle of tires across production, emissions, recycling, and disposal. In this paper, we synthesize recent research and data about the environmental and human health risks associated with the production, use, and disposal of tires and discuss gaps in our knowledge about fate and transport, as well as the toxicology of tire particles and chemical leachates. We examine potential management and remediation approaches for addressing exposure risks across the life cycle of tires. We consider tires as pollutants across three levels: tires in their whole state, as particulates, and as a mixture of chemical cocktails. Finally, we discuss information gaps in our understanding of tires as a pollutant and outline key questions to improve our knowledge and ability to manage and remediate tire pollution.

Excessive Use of Benzodiazepines Is a Risk Factor for Endotracheal Intubation in Children Who Present to Emergency With Prehospital Status Epilepticus.

OBJECTIVES: There is lack of evidence-based information on the use and timing of endotracheal intubation (ETI) in children with prehospital status epilepticus (SE). METHODS: The aim of this study was to investigate ETI use, timing, risk factors, and outcomes in children presenting to a single-center children's emergency (CE) with prehospital SE, over a 5-year period. RESULTS: A total of 118 events involving children presenting to CE with ongoing prehospital SE were included, and 39% (46/118) of the events required ETI. The most common indication for ETI was respiratory depression. The median time to intubation after arrival at CE was 20.0 minutes (1-155 minutes). Risk factors associated with ETI use include the administration of more than 2 benzodiazepines (26.1% vs 4.2%, P < 0.001) and the use of second- or third-line antiepileptic therapy ( P < 0.001). The use of more than 2 doses of benzodiazepines was found in 12.7% (15/118) of the patients. In patients who received excessive benzodiazepines, 87% (13/15) of them required intubation. CONCLUSIONS: Excessive use of benzodiazepine was found to be a main risk factor for ETI in patients with prehospital SE. Avoidance of the excessive use of benzodiazepines and adhering to clinical management guidelines may reduce the risk for ETI in the CE. The best approach to airway management in children with prehospital SE is lacking and urgently needed.

Thyroid-stimulating hormone receptor (TSHR) as a target for imaging differentiated thyroid cancer.

BACKGROUND: Of the half a million cases of thyroid cancer diagnosed annually, 95% are differentiated thyroid cancers. Although clinical guidelines recommend surgical resection followed by radioactive iodine ablation, loss of sodium-iodine symporter expression causes up to 20% of differentiated thyroid cancers to become radioactive iodine refractory. For patients with radioactive iodine refractory disease, there is an urgent need for new diagnostic and therapeutic approaches. We evaluated the thyroid-stimulating hormone receptor as a potential target for imaging of differentiated thyroid cancer. METHODS: We immunostained tissue microarrays containing 52 Hurthle cell carcinomas to confirm thyroid-stimulating hormone receptor expression. We radiolabeled chelator deferoxamine conjugated to recombinant human thyroid-stimulating hormone analog superagonist TR1402 with 89Zr (t1/2 = 78.4 h, ß+ =22.7%) to produce [89Zr]Zr-TR1402. We performed in vitro uptake assays in high-thyroid-stimulating hormone receptor and low-thyroid-stimulating hormone receptor-expressing THJ529T and FTC133 thyroid cancer cell lines. We performed in vivo positron emission tomography/computed tomography and biodistribution studies in male athymic nude mice bearing thyroid-stimulating hormone receptor-positive THJ529T tumors. RESULTS: Immunohistochemical analysis revealed 62% of patients (27 primary and 5 recurrent) were thyroid-stimulating hormone receptor membranous immunostain positive. In vitro uptake of 1nM [89Zr]Zr-TR1402 was 38 ± 17% bound/mg in thyroid-stimulating hormone receptor-positive THJ529T thyroid cancer cell lines compared to 3.2 ± 0.5 in the low-expressing cell line (P < .01), with a similar difference seen in FTC133 cell lines (P < .0001). In vivo and biodistribution studies showed uptake of [89Zr]Zr-TR1402 in thyroid-stimulating hormone receptor-expressing tumors, with a mean percentage of injected dose/g of 1.9 ± 0.4 at 3 days post-injection. CONCLUSION: Our observation of thyroid-stimulating hormone receptor expression in tissue microarrays and [89Zr]Zr-TR1402 accumulation in thyroid-stimulating hormone receptor-positive thyroid cancer cells and tumors suggests thyroid-stimulating hormone receptor is a promising target for imaging of differentiated thyroid cancer.

Somatostatin Receptor Type 2 and Thyroid-Stimulating Hormone Receptor Expression in Oncocytic Thyroid Neoplasms: Implications for Prognosis and Treatment.

Somatostatin receptor type 2 (SSTR2) and thyroid-stimulating hormone receptor (TSHR) display variable expression in primary thyroid tumors and have been implicated as theranostic targets. This study was designed to explore the differential expression of SSTR2 and TSHR in oncocytic (Hurthle cell) carcinoma (OC) vs oncocytic adenoma (OA). We performed a retrospective review for oncocytic neoplasms treated at our institution from 2012 to 2019. Formalin-fixed paraffin-embedded tissue blocks were used for tissue microarray construction. Tissue microarray blocks were cut into 5-µm sections and stained with anti-SSTR2 and anti-TSHR antibodies. Immunostains were analyzed by 3 independent pathologists. χ2 and logistic regression analysis were used to analyze clinical and pathologic variables. Sixty-seven specimens were analyzed with 15 OA and 52 OC. The mean age was 57 years, 61.2% were women, and 70% were White. SSTR2 positivity was noted in 2 OA (13%) and 15 OC (28%; 10 primary, 4 recurrent, and 1 metastatic) (P = .22). TSHR positivity was noted in 11 OA (73%) and 32 OC (62%; 31 primary and 1 metastatic) (P = .40). Those who presented with or developed clinical recurrence/metastasis were more likely to be SSTR2-positive (50% vs 21%; P = .04) and TSHR-negative (64.3% vs 28.9%; P = .02) than primary OC patients. Widely invasive OC was more likely to be SSTR2-positive compared to all other OC subtypes (minimally invasive and angioinvasive) (P = .003). For all patients with OC, TSHR positivity was inversely correlated with SSTR2 positivity (odds ratio, 0.12; CI, 0.03-0.43; P = .006). This relationship was not seen in the patients with OA (odds ratio, 0.30; CI, 0.01-9.14; P = .440). Our results show that recurrent/metastatic OC was more likely to be SSTR2-positive and TSHR-negative than primary OC. Patients with OC displayed a significant inverse relationship between SSTR2 and TSHR expression that was not seen in patients with OA. This may be a key relationship that can be used to prognosticate and treat OCs.

Determining The Role Of Radiation Oncologist Demographic Factors On Segmentation Quality: Insights From A Crowd-Sourced Challenge Using Bayesian Estimation.

BACKGROUND: Medical image auto-segmentation is poised to revolutionize radiotherapy workflows. The quality of auto-segmentation training data, primarily derived from clinician observers, is of utmost importance. However, the factors influencing the quality of these clinician-derived segmentations have yet to be fully understood or quantified. Therefore, the purpose of this study was to determine the role of common observer demographic variables on quantitative segmentation performance. METHODS: Organ at risk (OAR) and tumor volume segmentations provided by radiation oncologist observers from the Contouring Collaborative for Consensus in Radiation Oncology public dataset were utilized for this study. Segmentations were derived from five separate disease sites comprised of one patient case each: breast, sarcoma, head and neck (H&N), gynecologic (GYN), and gastrointestinal (GI). Segmentation quality was determined on a structure-by-structure basis by comparing the observer segmentations with an expert-derived consensus gold standard primarily using the Dice Similarity Coefficient (DSC); surface DSC was investigated as a secondary metric. Metrics were stratified into binary groups based on previously established structure-specific expert-derived interobserver variability (IOV) cutoffs. Generalized linear mixed-effects models using Markov chain Monte Carlo Bayesian estimation were used to investigate the association between demographic variables and the binarized segmentation quality for each disease site separately. Variables with a highest density interval excluding zero - loosely analogous to frequentist significance - were considered to substantially impact the outcome measure. RESULTS: After filtering by practicing radiation oncologists, 574, 110, 452, 112, and 48 structure observations remained for the breast, sarcoma, H&N, GYN, and GI cases, respectively. The median percentage of observations that crossed the expert DSC IOV cutoff when stratified by structure type was 55% and 31% for OARs and tumor volumes, respectively. Bayesian regression analysis revealed tumor category had a substantial negative impact on binarized DSC for the breast (coefficient mean ± standard deviation: -0.97 ± 0.20), sarcoma (-1.04 ± 0.54), H&N (-1.00 ± 0.24), and GI (-2.95 ± 0.98) cases. There were no clear recurring relationships between segmentation quality and demographic variables across the cases, with most variables demonstrating large standard deviations and wide highest density intervals. CONCLUSION: Our study highlights substantial uncertainty surrounding conventionally presumed factors influencing segmentation quality. Future studies should investigate additional demographic variables, more patients and imaging modalities, and alternative metrics of segmentation acceptability.

Pharmaceuticals, pesticides, and ultraviolet filters in wastewater discharges to San Francisco Bay as drivers of ecotoxicity.

Research in the United States evaluating ecotoxic risk to receiving waters posed by contaminants occurring in wastewater discharges typically has focused on measurements of pharmaceuticals and personal care products (PPCPs), with limited evaluations of UV filters and phenylpyrazole and neonicotinoid pesticides. In this study, concentrations of 5 representative pharmaceuticals, 11 pesticides or pesticide degradation products, and 5 ultraviolet filters were measured in 24 h composite samples of six wastewater discharges representing ∼70% of the total wastewater discharged to San Francisco Bay during the summer and fall of 2021. No significant difference was observed between concentrations measured on weekdays vs. weekends. A hydrodynamic model of San Francisco Bay was used to estimate annual average dilution factors associated with different subembayments. With and without considering dilution effects, Risk Quotients were calculated using the 90th percentile of measured concentrations in wastewater effluents and threshold concentrations associated with ecotoxicity. Risk Quotients were highest for the neonicotinoid pesticide, imidacloprid, and exceeded ecotoxicity thresholds in the lower South Bay by a factor of 2.4, even when considering dilution. Compared to commonly measured pharmaceuticals, Risk Quotients for imidacloprid were higher than those for carbamazepine, trimethoprim and diclofenac, and comparable to those for propranolol and metoprolol. Risk Quotients for the pesticide, fipronil, and the UV filter, oxybenzone, were higher than for carbamazepine. The results highlight the need to incorporate pesticides and UV filters with high Risk Quotients into studies in the United States evaluating ecotoxic risk associated with contaminants in municipal wastewater discharges.

Faulty Metabolism: A Potential Instigator of an Aggressive Phenotype in Cdk5-dependent Medullary Thyroid Carcinoma.

Mechanistic modeling of cancers such as Medullary Thyroid Carcinoma (MTC) to emulate patient-specific phenotypes is challenging. The discovery of potential diagnostic markers and druggable targets in MTC urgently requires clinically relevant animal models. Here we established orthotopic mouse models of MTC driven by aberrantly active Cdk5 using cell-specific promoters. Each of the two models elicits distinct growth differences that recapitulate the less or more aggressive forms of human tumors. The comparative mutational and transcriptomic landscape of tumors revealed significant alterations in mitotic cell cycle processes coupled with the slow-growing tumor phenotype. Conversely, perturbation in metabolic pathways emerged as critical for aggressive tumor growth. Moreover, an overlapping mutational profile was identified between mouse and human tumors. Gene prioritization revealed putative downstream effectors of Cdk5 which may contribute to the slow and aggressive growth in the mouse MTC models. In addition, Cdk5/p25 phosphorylation sites identified as biomarkers for Cdk5-driven neuroendocrine tumors (NETs) were detected in both slow and rapid onset models and were also histologically present in human MTC. Thus, this study directly relates mouse and human MTC models and uncovers vulnerable pathways potentially responsible for differential tumor growth rates. Functional validation of our findings may lead to better prediction of patient-specific personalized combinational therapies.

PD-L1 (22C3) Expression Correlates with Clinical and Molecular Features of Lung Adenocarcinomas in Cytological Samples.

INTRODUCTION: PD-L1 expression is the most widely used predictive marker for immune checkpoint inhibitor (ICI) therapy in patients with lung adenocarcinoma. However, the current understanding of the association between PD-L1 expression and treatment response is suboptimal. A significant percentage of patients have only a cytological specimen available for clinical management. Therefore, it is relevant to examine the impact of molecular features on PD-L1 expression in cytological samples and how it might correlate with a therapeutic response. METHODS: We evaluated patients diagnosed with adenocarcinoma of the lung who had both in-house targeted next-generation sequencing analysis and paired PD-L1 (22C3) immunohistochemical staining performed on the same cell blocks. We explored the association between molecular features and PD-L1 expression. In patients who underwent ICIs therapy, we assessed how a specific gene mutation impacted a therapeutic response. RESULTS: 145 patients with lung adenocarcinoma were included in this study. PD-L1-high expression was found to be more common in pleural fluid than in other sample sites. Regional lymph node samples showed a higher proportion of PD-L1-high expression (29%) compared with lung samples (6%). The predictive value of PD-L1 expression was retained in cytological samples. Mutations in KRAS were also associated with a PD-L1-high expression. However, tumors with TP53 or KRAS mutations showed a lower therapy response rate regardless of the PD-L1 expression. CONCLUSION: Cytological samples maintain a predictive value for PD-L1 expression in patients with lung adenocarcinoma as regards the benefit of ICI treatment. Specific molecular alterations additionally impact PD-L1 expression and its predictive value.

Voltage-Gated Sodium Channel NaV1.7 Inhibitors with Potent Anticancer Activities in Medullary Thyroid Cancer Cells.

Our results from quantitative RT-PCR, Western blotting, immunohistochemistry, and the tissue microarray of medullary thyroid cancer (MTC) cell lines and patient specimens confirm that VGSC subtype NaV1.7 is uniquely expressed in aggressive MTC and not expressed in normal thyroid cells and tissues. We establish the druggability of NaV1.7 in MTC by identifying a novel inhibitor (SV188) and investigate its mode of binding and ability to inhibit INa current in NaV1.7. The whole-cell patch-clamp studies of the SV188 in the NaV1.7 channels expressed in HEK-293 cells show that SV188 inhibited the INa current in NaV1.7 with an IC50 value of 3.6 µM by a voltage- and use-dependent blockade mechanism, and the maximum inhibitory effect is observed when the channel is open. SV188 inhibited the viability of MTC cell lines, MZ-CRC-1 and TT, with IC50 values of 8.47 µM and 9.32 µM, respectively, and significantly inhibited the invasion of MZ-CRC-1 cells by 35% and 52% at 3 µM and 6 µM, respectively. In contrast, SV188 had no effect on the invasion of TT cells derived from primary tumor, which have lower basal expression of NaV1.7. In addition, SV188 at 3 µM significantly inhibited the migration of MZ-CRC-1 and TT cells by 27% and 57%, respectively.

Gastrointestinal transit time of radiopaque ingested foreign bodies in children: experience of two paediatric tertiary centres.

Introduction: Foreign body (FB) ingestion is a common paediatric emergency. While guidelines exist for urgent intervention, less is known of the natural progress of FBs passing through the gastrointestinal tract (GIT). We reviewed these FB transit times in an outpatient cohort. Methods: A retrospective review was performed on all children (≤18 years) treated for radiopaque FB ingestion at two major tertiary paediatric centres from 2015 to 2016. Demographic data, FB types, outcomes and hospital visits (emergency department [ED] and outpatient) were recorded. All cases discharged from the ED with outpatient follow-up were included. We excluded those who were not given follow-up appointments and those admitted to inpatient wards. We categorised the outcomes into confirmed passage (ascertained via abdominal X-ray or reported direct stool visualisation by patients/caregivers) and assumed passage (if patients did not attend follow-up appointments). Results: Of the 2,122 ED visits for FB ingestion, 350 patients who were given outpatient follow-up appointments were reviewed (median age 4.35 years [range: 0.5-14.7], 196 [56%] male). The largest proportion (16%) was aged 1-2 years. Coins were the most common ingested FB, followed by toys. High-risk FB (magnets or batteries) formed 9% of cases (n=33). The 50th centile for FB retention was 8, 4 and 7 days for coins, batteries and other radiopaque FBs, respectively; all confirmed passages occurred at 37, 7 and 23 days, respectively. Overall, 197 (68%) patients defaulted on their last given follow-up. Conclusion: This study provides insight into the transit times of FB ingested by children, which helps medical professionals to decide on the optimal time for follow-up visits and provide appropriate counsel to caregivers.

Large scale crowdsourced radiotherapy segmentations across a variety of cancer anatomic sites.

Clinician generated segmentation of tumor and healthy tissue regions of interest (ROIs) on medical images is crucial for radiotherapy. However, interobserver segmentation variability has long been considered a significant detriment to the implementation of high-quality and consistent radiotherapy dose delivery. This has prompted the increasing development of automated segmentation approaches. However, extant segmentation datasets typically only provide segmentations generated by a limited number of annotators with varying, and often unspecified, levels of expertise. In this data descriptor, numerous clinician annotators manually generated segmentations for ROIs on computed tomography images across a variety of cancer sites (breast, sarcoma, head and neck, gynecologic, gastrointestinal; one patient per cancer site) for the Contouring Collaborative for Consensus in Radiation Oncology challenge. In total, over 200 annotators (experts and non-experts) contributed using a standardized annotation platform (ProKnow). Subsequently, we converted Digital Imaging and Communications in Medicine data into Neuroimaging Informatics Technology Initiative format with standardized nomenclature for ease of use. In addition, we generated consensus segmentations for experts and non-experts using the Simultaneous Truth and Performance Level Estimation method. These standardized, structured, and easily accessible data are a valuable resource for systematically studying variability in segmentation applications.

E pluribus unum: prospective acceptability benchmarking from the Contouring Collaborative for Consensus in Radiation Oncology crowdsourced initiative for multiobserver segmentation.

Purpose: Contouring Collaborative for Consensus in Radiation Oncology (C3RO) is a crowdsourced challenge engaging radiation oncologists across various expertise levels in segmentation. An obstacle to artificial intelligence (AI) development is the paucity of multiexpert datasets; consequently, we sought to characterize whether aggregate segmentations generated from multiple nonexperts could meet or exceed recognized expert agreement. Approach: Participants who contoured ≥ 1 region of interest (ROI) for the breast, sarcoma, head and neck (H&N), gynecologic (GYN), or gastrointestinal (GI) cases were identified as a nonexpert or recognized expert. Cohort-specific ROIs were combined into single simultaneous truth and performance level estimation (STAPLE) consensus segmentations. STAPLE nonexpert ROIs were evaluated against STAPLE expert contours using Dice similarity coefficient (DSC). The expert interobserver DSC ( IODSC expert ) was calculated as an acceptability threshold between STAPLE nonexpert and STAPLE expert . To determine the number of nonexperts required to match the IODSC expert for each ROI, a single consensus contour was generated using variable numbers of nonexperts and then compared to the IODSC expert . Results: For all cases, the DSC values for STAPLE nonexpert versus STAPLE expert were higher than comparator expert IODSC expert for most ROIs. The minimum number of nonexpert segmentations needed for a consensus ROI to achieve IODSC expert acceptability criteria ranged between 2 and 4 for breast, 3 and 5 for sarcoma, 3 and 5 for H&N, 3 and 5 for GYN, and 3 for GI. Conclusions: Multiple nonexpert-generated consensus ROIs met or exceeded expert-derived acceptability thresholds. Five nonexperts could potentially generate consensus segmentations for most ROIs with performance approximating experts, suggesting nonexpert segmentations as feasible cost-effective AI inputs.

Triclosan and Methyl Triclosan in Prey Fish in a Wastewater-Influenced Estuary.

While the antimicrobial ingredient triclosan has been widely monitored in the environment, much less is known about the occurrence and toxicity of its major transformation product, methyl triclosan. An improved method was developed and validated to effectively extract and quantify both contaminants in fish tissue and used to characterize concentrations in small prey fish in areas of San Francisco Bay where exposure to triclosan via municipal wastewater discharges was expected to be highest. Concentrations of triclosan (0.44-57 ng/g wet wt, median 1.9 ng/g wet wt) and methyl triclosan (1.1-200 ng/g wet wt, median 36 ng/g wet wt) in fish tissue decreased linearly with concentrations of nitrate in site water, used as indicators of wastewater influence. The total concentrations of triclosan and methyl triclosan measured in prey fish were below available toxicity thresholds for triclosan, but there are few ecotoxicological studies to evaluate impacts of methyl triclosan. Methyl triclosan represented up to 96% of the total concentrations observed. These results emphasize the importance of monitoring contaminant transformation products, which can be present at higher levels than the parent compound. Environ Toxicol Chem 2023;42:620-627. © 2023 SETAC.

Associating Biological Activity and Predicted Structure of Antimicrobial Peptides from Amphibians and Insects.

Antimicrobial peptides (AMPs) are a diverse class of short, often cationic biological molecules that present promising opportunities in the development of new therapeutics to combat antimicrobial resistance. Newly developed in silico methods offer the ability to rapidly discover numerous novel AMPs with a variety of physiochemical properties. Herein, using the rAMPage AMP discovery pipeline, we bioinformatically identified 51 AMP candidates from amphibia and insect RNA-seq data and present their in-depth characterization. The studied AMPs demonstrate activity against a panel of bacterial pathogens and have undetected or low toxicity to red blood cells and human cultured cells. Amino acid sequence analysis revealed that 30 of these bioactive peptides belong to either the Brevinin-1, Brevinin-2, Nigrocin-2, or Apidaecin AMP families. Prediction of three-dimensional structures using ColabFold indicated an association between peptides predicted to adopt a helical structure and broad-spectrum antibacterial activity against the Gram-negative and Gram-positive species tested in our panel. These findings highlight the utility of associating the diverse sequences of novel AMPs with their estimated peptide structures in categorizing AMPs and predicting their antimicrobial activity.

Histology segmentation using active learning on regions of interest in oral cavity squamous cell carcinoma.

In digital pathology, deep learning has been shown to have a wide range of applications, from cancer grading to segmenting structures like glomeruli. One of the main hurdles for digital pathology to be truly effective is the size of the dataset needed for generalization to address the spectrum of possible morphologies. Small datasets limit classifiers' ability to generalize. Yet, when we move to larger datasets of whole slide images (WSIs) of tissue, these datasets may cause network bottlenecks as each WSI at its original magnification can be upwards of 100 000 by 100 000 pixels, and over a gigabyte in file size. Compounding this problem, high quality pathologist annotations are difficult to obtain, as the volume of necessary annotations to create a classifier that can generalize would be extremely costly in terms of pathologist-hours. In this work, we use Active Learning (AL), a process for iterative interactive training, to create a modified U-net classifier on the region of interest (ROI) scale. We then compare this to Random Learning (RL), where images for addition to the dataset for retraining are randomly selected. Our hypothesis is that AL shows benefits for generating segmentation results versus randomly selecting images to annotate. We show that after 3 iterations, that AL, with an average Dice coefficient of 0.461, outperforms RL, with an average Dice Coefficient of 0.375, by 0.086.