Insights into the genetic architecture of Phytophthora capsici root rot resistance in chile pepper (Capsicum spp.) from multi-locus genome-wide association study.

BACKGROUND: Phytophthora root rot, a major constraint in chile pepper production worldwide, is caused by the soil-borne oomycete, Phytophthora capsici. This study aimed to detect significant regions in the Capsicum genome linked to Phytophthora root rot resistance using a panel consisting of 157 Capsicum spp. genotypes. Multi-locus genome wide association study (GWAS) was conducted using single nucleotide polymorphism (SNP) markers derived from genotyping-by-sequencing (GBS). Individual plants were separately inoculated with P. capsici isolates, 'PWB-185', 'PWB-186', and '6347', at the 4-8 leaf stage and were scored for disease symptoms up to 14-days post-inoculation. Disease scores were used to calculate disease parameters including disease severity index percentage, percent of resistant plants, area under disease progress curve, and estimated marginal means for each genotype. RESULTS: Most of the genotypes displayed root rot symptoms, whereas five accessions were completely resistant to all the isolates and displayed no symptoms of infection. A total of 55,117 SNP markers derived from GBS were used to perform multi-locus GWAS which identified 330 significant SNP markers associated with disease resistance. Of these, 56 SNP markers distributed across all the 12 chromosomes were common across the isolates, indicating association with more durable resistance. Candidate genes including nucleotide-binding site leucine-rich repeat (NBS-LRR), systemic acquired resistance (SAR8.2), and receptor-like kinase (RLKs), were identified within 0.5 Mb of the associated markers. CONCLUSIONS: Results will be used to improve resistance to Phytophthora root rot in chile pepper by the development of Kompetitive allele-specific markers (KASP®) for marker validation, genomewide selection, and marker-assisted breeding.

Unlocking the adaptive advantage: correlation and machine learning classification to identify optimal online adaptive stereotactic partial breast candidates.

Objective.Online adaptive radiotherapy (OART) is a promising technique for delivering stereotactic accelerated partial breast irradiation (APBI), as lumpectomy cavities vary in location and size between simulation and treatment. However, OART is resource-intensive, increasing planning and treatment times and decreasing machine throughput compared to the standard of care (SOC). Thus, it is pertinent to identify high-yield OART candidates to best allocate resources.Approach.Reference plans (plans based on simulation anatomy), SOC plans (reference plans recalculated onto daily anatomy), and daily adaptive plans were analyzed for 31 sequential APBI targets, resulting in the analysis of 333 treatment plans. Spearman correlations between 22 reference plan metrics and 10 adaptive benefits, defined as the difference between mean SOC and delivered metrics, were analyzed to select a univariate predictor of OART benefit. A multivariate logistic regression model was then trained to stratify high- and low-benefit candidates.Main results.Adaptively delivered plans showed dosimetric benefit as compared to SOC plans for most plan metrics, although the degree of adaptive benefit varied per patient. The univariate model showed high likelihood for dosimetric adaptive benefit when the reference plan ipsilateral breast V15Gy exceeds 23.5%. Recursive feature elimination identified 5 metrics that predict high-dosimetric-benefit adaptive patients. Using leave-one-out cross validation, the univariate and multivariate models classified targets with 74.2% and 83.9% accuracy, resulting in improvement in per-fraction adaptive benefit between targets identified as high- and low-yield for 7/10 and 8/10 plan metrics, respectively.Significance.This retrospective, exploratory study demonstrated that dosimetric benefit can be predicted using only ipsilateral breast V15Gy on the reference treatment plan, allowing for a simple, interpretable model. Using multivariate logistic regression for adaptive benefit prediction led to increased accuracy at the cost of a more complicated model. This work presents a methodology for clinics wishing to triage OART resource allocation.

Incidental discovery of metastatic renal cell carcinoma at the vaginal wall: A case report.

Metastasis of renal cell carcinoma (RCC) to the vaginal wall has rarely been reported in the literature. We present a case of a 48-year-old who was found to have a solitary RCC metastasis at the vaginal wall, five years following radical nephrectomy. This case is noteworthy because this late presentation is unique, with prior reports of synchronous metastasis or metastasis within two years of nephrectomy, highlighting the need to consider metastatic RCC to the vagina a possibility even many years after treatment.

Corrigendum to "Neural distinctiveness and discriminability underlying unitization and associative memory in aging" [Aging Brain 4 (2023) 100097].

[This corrects the article DOI: 10.1016/j.nbas.2023.100097.].

Mapping the genetic architecture of low-temperature stress tolerance in citron watermelon.

Sweet-fleshed watermelon (Citrullus lanatus) is an important vegetable crop of the tropical origin. It is widely grown and consumed around the world for its hydration and nutritional quality values. Low-temperature stress can affect early planting, seedling establishment, and expansion of crop production to new areas. A collection of 122 citron watermelon (Citrullus amarus) accessions were obtained from the USDA's National Plant Germplasm Repository System gene bank in Griffin, GA. The accessions were genotyped using whole genome resequencing to generate single nucleotide polymorphisms (SNPs) molecular markers and screened under cold-stressed and non-stressed control conditions. Four low-temperature stress tolerance related traits including shoot biomass, vine length, maximum quantum efficiency of photosystem II, and chlorophyll content were measured under cold-stressed and non-stressed control treatment conditions. Correlation analysis revealed the presence of positive relationships among traits. Broad-sense heritability for all traits ranged from 0.35 to 0.73, implying the presence of genetic contributions to the observed phenotypic variation. Genomic regions underlying these traits across several citron watermelon chromosomes were identified. Four low-temperature stress tolerance related putative candidate genes co-located with the peak SNPs from genome-wide association study. These genomic regions and marker information could potentially be used in molecular breeding to accelerate genetic improvements for low-temperature stress tolerance in watermelon.

Prospective Evaluation of Automated Contouring for CT-Based Brachytherapy for Gynecologic Malignancies.

Purpose: The use of deep learning to auto-contour organs at risk (OARs) in gynecologic radiation treatment is well established. Yet, there is limited data investigating the prospective use of auto-contouring in clinical practice. In this study, we assess the accuracy and efficiency of auto-contouring OARs for computed tomography-based brachytherapy treatment planning of gynecologic malignancies. Methods and Materials: An inhouse contouring tool automatically delineated 5 OARs in gynecologic radiation treatment planning: the bladder, small bowel, sigmoid, rectum, and urethra. Accuracy of each auto-contour was evaluated using a 5-point Likert scale: a score of 5 indicated the contour could be used without edits, while a score of 1 indicated the contour was unusable. During scoring, automated contours were edited and subsequently used for treatment planning. Dice similarity coefficient, mean surface distance, 95% Hausdorff distance, Hausdorff distance, and dosimetric changes between original and edited contours were calculated. Contour approval time and total planning time of a prospective auto-contoured (AC) cohort were compared with times from a retrospective manually contoured (MC) cohort. Results: Thirty AC cases from January 2022 to July 2022 and 31 MC cases from July 2021 to January 2022 were included. The mean (±SD) Likert score for each OAR was the following: bladder 4.77 (±0.58), small bowel 3.96 (±0.91), sigmoid colon 3.92 (±0.81), rectum 4.6 (±0.71), and urethra 4.27 (±0.78). No ACs required major edits. All OARs had a mean Dice similarity coefficient > 0.86, mean surface distance < 0.48 mm, 95% Hausdorff distance < 3.2 mm, and Hausdorff distance < 10.32 mm between original and edited contours. There was no significant difference in dose-volume histogram metrics (D2.0 cc/D0.1 cc) between original and edited contours (P values > .05). The average time to plan approval in the AC cohort was 19% less than the MC cohort. (AC vs MC, 117.0 + 18.0 minutes vs 144.9 ± 64.5 minutes, P = .045). Conclusions: Automated contouring is useful and accurate in clinical practice. Auto-contouring OARs streamlines radiation treatment workflows and decreases time required to design and approve gynecologic brachytherapy plans.

Acute Toxicity of Total Body Irradiation Using Volumetric Arc Therapy With a Focus on the Effect of Lung Dose Rate.

Purpose: To report adverse effects of high dose total body irradiation (TBI) delivered using a volumetric arc therapy (VMAT) technique and to assess pulmonary toxicity at dose rates of 40 and 100 monitor units per minute (MU/min). Methods and Materials: This retrospective study included patients >18 years old who received ≥8 Gy TBI using a VMAT technique. The TBI dose was prescribed to a planning target volume consisting of a 0.5 cm retraction of the body with the lungs subtracted. The objective function specified planning target volume coverage goals of D100% ≥ 90% and Dmax <130%. A lung dose control structure consisting of a 1 cm retraction of the lung volume was limited to Dmean <75%. Treatments were initially delivered with a dose rate of 40 MU/min for the thoracic isocenters and 100 MU/min for the other isocenters. Beginning in January 2021, a dose rate of 100 MU/min was used for all isocenters. All treatments were administered in 2 Gy fractions delivered twice daily. Acute toxicity was assessed for 30 days after TBI. Results: A total of 29 patients were included in this analysis who received TBI between January 2019 and October 2021. Prescription dose ranged from 8 to 12 Gy. Mean lung dose was 7.9 Gy (SD, 1.4 Gy) for patients treated at 40 MU/min and for patients treated at 100 MU/min 7.1 Gy (SD, 1.3 Gy). Mucositis was the most common grade 3 toxicity and occurred in 10 (34%) patients. Only 1 instance of pneumonitis was observed and occurred in a patient who received a mean lung dose of 10.1 Gy delivered at 40 MU/min. Conclusions: In this cohort of patients who received high dose TBI using a VMAT technique, the composite rate of acute toxicity was not unexpectedly high. We did not observe an increase in lung toxicity after increasing the dose rate of the thoracic isocenters from 40 MU/min to 100 MU/min.

Improved Dosimetry and Plan Quality for Accelerated Partial Breast Irradiation Using Online Adaptive Radiation Therapy: A Single Institutional Study.

Purpose: Accelerated partial breast irradiation (APBI) is an attractive treatment modality for eligible patients as it has been shown to result in similar local control and improved cosmetic outcomes compared with whole breast radiation therapy. The use of online adaptive radiation therapy (OART) for APBI is promising as it allows for a reduction of planning target volume margins because breast motion and lumpectomy cavity volume changes are accounted for in daily imaging. Here we present a retrospective, single-institution evaluation on the adequacy of kV-cone beam computed tomography (CBCT) OART for APBI treatments. Methods and Materials: Nineteen patients (21 treatment sites) were treated to 30 Gy in 5 fractions between January of 2022 and May of 2023. Time between simulation and treatment, change in gross tumor (ie, lumpectomy cavity) volume, and differences in dose volume histogram metrics with adaption were analyzed. The Wilcoxon paired, nonparametric test was used to test for dose volume histogram metric differences between the scheduled plans (initial plans recalculated on daily CBCT anatomy) and delivered plans, either the scheduled or adapted plan, which was reoptimized using daily anatomy. Results: Median (interquartile range) time from simulation to first treatment was 26 days (21-32 days). During this same time, median gross tumor volume reduction was 16.0% (7.3%-23.9%) relative to simulation volume. Adaptive treatments took 31.3 minutes (27.4-36.6 minutes) from start of CBCT to treatment session end. At treatment, the adaptive plan was selected for 86% (89/103) of evaluable fractions. In evaluating plan quality, 78% of delivered plans met all target, organs at risk, and conformity metrics evaluated, compared with 34% of scheduled plans. Conclusions: Use of OART for stereotactic linac-based APBI allowed for safe, high-quality treatments in this cohort of 21 treatment courses. Although treatment delivery times were longer than traditional stereotactic body treatments, there were notable improvements in plan quality for APBI using OART.

Comparative analysis of immune infiltrates in head and neck cancers across anatomical sites.

BACKGROUND: The response rate to immune checkpoint inhibitors targeting programmed cell death 1 (PD-1) receptor is 13%-18% for patients with recurrent or metastatic head and neck squamous cell carcinoma (HNSCC). Detailed understanding of the tumor immune microenvironment (TIME) is crucial in order to explain and improve this response rate. HNSCCs arise at various anatomical locations including the oral cavity, hypopharynx, larynx and oropharynx. Studies directly comparing immune infiltration between anatomical sites are scarce. Since the distinct locations could drive deviating microenvironments, we questioned whether the immune composition varies across these HNSCC sites. METHODS: Here, we characterized the TIME of 76 fresh tumor specimens using flow cytometry and performed single-cell RNA-sequencing on nine head and neck tumor samples. RESULTS: We found major differences in the composition of the TIME between patients. When comparing anatomical sites: tumors originating from the oral cavity had higher T cell infiltrates than tumors from other anatomical sites. The percentage of tumor-infiltrating T-lymphocytes positive for the immune checkpoint PD-1 varied considerably between patients, with the highest fraction of PD-1+ T cells found in larynx squamous cell carcinomas (SCCs). While we had hypothesized that the anatomical sites of tumor origin would drive sample clustering, our data showed that the type of TIME was more dominant and was particularly driven by the fraction of T cells positive for PD-1. Moreover, a high proportion of PD-1+ CD8+ T cells associated with an improved overall survival. Using single-cell RNA-sequencing, we observed that PD-1 expression was highest in the CD8-ENTPD1 tissue resident memory T cell/exhausted T cell and CD4-CXCL13 type 1 T helper cell clusters. CONCLUSIONS: We found that oral cavity SCCs had the highest frequencies of T cells. We also observed considerable interpatient heterogeneity for PD-1 on T cells, with noticeably higher frequencies of PD-1+ CD4+ T helper cells in larynx SCCs. Within the entire cohort, a higher fraction of CD8+ T cells positive for PD-1 was linked to improved overall survival. Whether the fraction of PD-1+ T cells within the TIME enables immune checkpoint inhibitor response prediction for patients with head and neck cancer remains to be determined.

Ridge regression and deep learning models for genome-wide selection of complex traits in New Mexican Chile peppers.

BACKGROUND: Genomewide prediction estimates the genomic breeding values of selection candidates which can be utilized for population improvement and cultivar development. Ridge regression and deep learning-based selection models were implemented for yield and agronomic traits of 204 chile pepper genotypes evaluated in multi-environment trials in New Mexico, USA. RESULTS: Accuracy of prediction differed across different models under ten-fold cross-validations, where high prediction accuracy was observed for highly heritable traits such as plant height and plant width. No model was superior across traits using 14,922 SNP markers for genomewide selection. Bayesian ridge regression had the highest average accuracy for first pod date (0.77) and total yield per plant (0.33). Multilayer perceptron (MLP) was the most superior for flowering time (0.76) and plant height (0.73), whereas the genomic BLUP model had the highest accuracy for plant width (0.62). Using a subset of 7,690 SNP loci resulting from grouping markers based on linkage disequilibrium coefficients resulted in improved accuracy for first pod date, ten pod weight, and total yield per plant, even under a relatively small training population size for MLP and random forest models. Genomic and ridge regression BLUP models were sufficient for optimal prediction accuracies for small training population size. Combining phenotypic selection and genomewide selection resulted in improved selection response for yield-related traits, indicating that integrated approaches can result in improved gains achieved through selection. CONCLUSIONS: Accuracy values for ridge regression and deep learning prediction models demonstrate the potential of implementing genomewide selection for genetic improvement in chile pepper breeding programs. Ultimately, a large training data is relevant for improved genomic selection accuracy for the deep learning models.

Unveiling invisible farm-to-farm PRRSV-2 transmission links and routes through transmission tree and network analysis.

The United States (U.S.) swine industry has struggled to control porcine reproductive and respiratory syndrome (PRRS) for decades, yet the causative virus, PRRSV-2, continues to circulate and rapidly diverges into new variants. In the swine industry, the farm is typically the epidemiological unit for monitoring, prevention, and control; breaking transmission among farms is a critical step in containing disease spread. Despite this, our understanding of farm transmission still is inadequate, precluding the development of tailored control strategies. Therefore, our objective was to infer farm-to-farm transmission links, estimate farm-level transmissibility as defined by reproduction numbers (R), and identify associated risk factors for transmission using PRRSV-2 open reading frame 5 (ORF5) gene sequences, animal movement records, and other data from farms in a swine-dense region of the U.S. from 2014 to 2017. Timed phylogenetic and transmission tree analyses were performed on three sets of sequences (n = 206) from 144 farms that represented the three largest genetic variants of the virus in the study area. The length of inferred pig-to-pig infection chains that corresponded to pairs of farms connected via direct animal movement was used as a threshold value for identifying other feasible transmission links between farms; these links were then transformed into farm-to-farm transmission networks and calculated farm-level R-values. The median farm-level R was one (IQR = 1-2), whereas the R value of 28% of farms was more than one. Exponential random graph models were then used to evaluate the influence of farm attributes and/or farm relationships on the occurrence of farm-to-farm transmission links. These models showed that, even though most transmission events cannot be directly explained by animal movement, movement was strongly associated with transmission. This study demonstrates how integrative techniques may improve disease traceability in a data-rich era by providing a clearer picture of regional disease transmission.

Genetic control of flowering time and fruit yield in citron watermelon.

Flowering time and fruit yield are important traits in watermelon crop improvement. There is limited information on the inheritance and genomic loci underlying flowering time and yield performance, especially in citron watermelon. A total of 125 citron watermelon accessions were evaluated in field trials over two growing seasons for days to male and female flowers, fruit count, fruit weight, and fruit yield. The germplasm was genotyped with more than two million single-nucleotide polymorphism (SNP) markers generated via whole-genome resequencing. Trait mapping was conducted using a genome-wide association study (GWAS). Broad-sense heritability for all traits ranged from moderate to high, indicating that genetic improvement through breeding and selection is feasible. Significant marker-trait associations were uncovered for days to female flower (chromosomes Ca04, Ca05, Ca08, and Ca09), fruit count (on Ca02, Ca03, and Ca05), fruit weight (on Ca02, Ca06, Ca08, Ca10, and Ca11), and fruit yield on chromosomes Ca05, Ca07, and Ca09. The phenotypic variation explained by the significant SNPs ranged from 1.6 to 25.4, highlighting the complex genetic architecture of the evaluated traits. Candidate genes relevant to flowering time and fruit yield component traits were uncovered on chromosomes Ca02, Ca04, Ca05, Ca06, Ca09, and Ca11. These results lay a foundation for marker-assisted trait introgression of flowering time and fruit yield component traits in watermelons.

Neural distinctiveness and discriminability underlying unitization and associative memory in aging.

Previous work has suggested unitized pairs behave as a single unit and more critically, are processed neurally different than those of associative memories. The current works examines the neural differences between unitization and non-unitized memory using fMRI and multivoxel analyses. Specifically, we examined the differences across face-occupation pairings as a function of whether the pairing was viewed as a person performing the given job (unitized binding) or a person saying they knew someone who had a particular job (non-unitized binding). The results show that at encoding and retrieval, the angular gyrus can discriminate between unitized and non-unitized target trials. Additionally, during encoding, the medial temporal lobe (hippocampus and perirhinal cortex), frontal parietal regions (angular gyrus and medial frontal gyrus) and visual regions (middle occipital cortex) exhibit distinct neural patterns to recollected unitized and non-unitized targets. Furthermore, the perirhinal cortex and medial frontal gyrus show greater neural similarity within subsequently recollected unitized trials compared to non-unitized trials. We conclude that an encoding based strategy to elicit unitization can produce greater associative memory compared to non-unitized trials in older adults. Additionally, when unitized trials are subsequently recollected in the perirhinal cortex older adults show greater neural similarity within unitized trials compared to non-unitized trials.

Genome-wide association study of soluble solids content, flesh color, and fruit shape in citron watermelon.

Fruit quality traits are crucial determinants of consumers' willingness to purchase watermelon produce, making them major goals for breeding programs. There is limited information on the genetic underpinnings of fruit quality traits in watermelon. A total of 125 citron watermelon (Citrullus amarus) accessions were genotyped using single nucleotide polymorphisms (SNPs) molecular markers generated via whole-genome resequencing. A total of 2,126,759 genome-wide SNP markers were used to uncover marker-trait associations using single and multi-locus GWAS models. High broad-sense heritability for fruit quality traits was detected. Correlation analysis among traits revealed positive relationships, with the exception of fruit diameter and fruit shape index (ratio of fruit length to fruit diameter), which was negative. A total of 37 significant SNP markers associated with soluble solids content, flesh color, fruit length, fruit diameter, and fruit shape index traits were uncovered. These peak SNPs accounted for 2.1%-23.4% of the phenotypic variation explained showing the quantitative inheritance nature of the evaluated traits. Candidate genes relevant to fruit quality traits were uncovered on chromosomes Ca01, Ca03, Ca06, and Ca07. These significant molecular markers and candidate genes will be useful in marker-assisted breeding of fruit quality traits in watermelon.

Automated evaluation for rapid implementation of knowledge-based radiotherapy planning models.

PURPOSE: Knowledge-based planning (KBP) offers the ability to predict dose-volume metrics based on information extracted from previous plans, reducing plan variability and improving plan quality. As clinical integration of KBP is increasing there is a growing need for quantitative evaluation of KBP models. A .NET-based application, RapidCompare, was created for automated plan creation and analysis of Varian RapidPlan models. METHODS: RapidCompare was designed to read calculation parameters and a list of reference plans. The tool copies the reference plan field geometry and structure set, applies the RapidPlan model, optimizes the KBP plan, and generates data for quantitative evaluation of dose-volume metrics. A cohort of 85 patients, divided into training (50), testing (10), and validation (25) groups, was used to demonstrate the utility of RapidCompare. After training and tuning, the KBP model was paired with three different optimization templates to compare various planning strategies in the validation cohort. All templates used the same set of constraints for the planning target volume (PTV). For organs-at-risk, the optimization template provided constraints using the whole dose-volume histogram (DVH), fixed-dose/volume points, or generalized equivalent uniform dose (gEUD). The resulting plans from each optimization approach were compared using DVH metrics. RESULTS: RapidCompare allowed for the automated generation of 75 total plans for comparison with limited manual intervention. In comparing optimization techniques, the Dose/Volume and Lines optimization templates generated plans with similar DVH metrics, with a slight preference for the Lines technique with reductions in heart V30Gy and spinal cord max dose. The gEUD model produced high target heterogeneity. CONCLUSION: Automated evaluation allowed for the exploration of multiple optimization templates in a larger validation cohort than would have been feasible using a manual approach. A final KBP model using line optimization objectives produced the highest quality plans without human intervention.

Considerations for intensity modulated total body or total marrow and lymphoid irradiation.

We compiled a sampling of the treatment techniques of intensity-modulated total body irradiation, total marrow irradiation and total marrow and lymphoid irradiation utilized by several centers across North America and Europe. This manuscript does not serve as a consensus guideline, but rather is meant to serve as a convenient reference for centers that are considering starting an intensity-modulated program.

Evaluation and correlation of patient movement during online adaptive radiotherapy with CBCT and a surface imaging system.

PURPOSE: With the clinical implementation of kV-CBCT-based daily online-adaptive radiotherapy, the ability to monitor, quantify, and correct patient movement during adaptive sessions is paramount. With sessions lasting between 20-45 min, the ability to detect and correct for small movements without restarting the entire session is critical to the adaptive workflow and dosimetric outcome. The purpose of this study was to quantify and evaluate the correlation of observed patient movement with machine logs and a surface imaging (SI) system during adaptive radiation therapy. METHODS: Treatment machine logs and SGRT registration data log files for 1972 individual sessions were exported and analyzed. For each session, the calculated shifts from a pre-delivery position verification CBCT were extracted from the machine logs and compared to the SGRT registration data log files captured during motion monitoring. The SGRT calculated shifts were compared to the reported shifts of the machine logs for comparison for all patients and eight disease site categories. RESULTS: The average (±STD) net displacement of the SGRT shifts were 2.6 ± 3.4 mm, 2.6 ± 3.5 mm, and 3.0 ± 3.2 in the lateral, longitudinal, and vertical directions, respectively. For the treatment machine logs, the average net displacements in the lateral, longitudinal, and vertical directions were 2.7 ± 3.7 mm, 2.6 ± 3.7 mm, and 3.2 ± 3.6 mm. The average difference (Machine-SGRT) was -0.1 ± 1.8 mm, 0.2 ± 2.1 mm, and -0.5 ± 2.5 mm for the lateral, longitudinal, and vertical directions. On average, a movement of 5.8 ± 5.6 mm and 5.3 ± 4.9 mm was calculated prior to delivery for the CBCT and SGRT systems, respectively. The Pearson correlation coefficient between CBCT and SGRT shifts was r = 0.88. The mean and median difference between the treatment machine logs and SGRT log files was less than 1 mm for all sites. CONCLUSION: Surface imaging should be used to monitor and quantify patient movement during adaptive radiotherapy.

Benchmarking Automated Machine Learning-Enhanced Planning With Ethos Against Manual and Knowledge-Based Planning for Locally Advanced Lung Cancer.

Purpose: Currently, there is insufficient guidance for standard fractionation lung planning using the Varian Ethos adaptive treatment planning system and its unique intelligent optimization engine. Here, we address this gap in knowledge by developing a methodology to automatically generate high-quality Ethos treatment plans for locally advanced lung cancer. Methods and Materials: Fifty patients previously treated with manually generated Eclipse plans for inoperable stage IIIA-IIIC non-small cell lung cancer were included in this institutional review board-approved retrospective study. Fifteen patient plans were used to iteratively optimize a planning template for the Daily Adaptive vs Non-Adaptive External Beam Radiation Therapy With Concurrent Chemotherapy for Locally Advanced Non-Small Cell Lung Cancer: A Prospective Randomized Trial of an Individualized Approach for Toxicity Reduction (ARTIA-Lung); the remaining 35 patients were automatically replanned without intervention. Ethos plan quality was benchmarked against clinical plans and reoptimized knowledge-based RapidPlan (RP) plans, then judged using standard dose-volume histogram metrics, adherence to clinical trial objectives, and qualitative review. Results: Given equal prescription target coverage, Ethos-generated plans showed improved primary and nodal planning target volume V95% coverage (P < .001) and reduced lung gross tumor volume V5 Gy and esophagus D0.03 cc metrics (P ≤ .003) but increased mean esophagus and brachial plexus D0.03 cc metrics (P < .001) compared with RP plans. Eighty percent, 49%, and 51% of Ethos, clinical, and RP plans, respectively, were "per protocol" or met "variation acceptable" ARTIA-Lung planning metrics. Three radiation oncologists qualitatively scored Ethos plans, and 78% of plans were clinically acceptable to all reviewing physicians, with no plans receiving scores requiring major changes. Conclusions: A standard Ethos template produced lung radiation therapy plans with similar quality to RP plans, elucidating a viable approach for automated plan generation in the Ethos adaptive workspace.

Commissioning and clinical evaluation of the IDENTIFYTM surface imaging system for frameless stereotactic radiosurgery.

PURPOSE: To commission and assess the clinical performance of a new commercial surface imaging (SI) system by analyzing intra-fraction motion from the initial cohort of patients treated with frameless stereotactic radiosurgery (fSRS). METHODS: The IDENTIFYTM SI system was commissioned for clinical use on an Edge (Varian Medical Systems, Palo Alto, CA) linear accelerator. All patients who received intracranial radiotherapy with HyperArcTM (Varian Medical Systems, Palo Alto, CA) were immobilized with the EncompassTM (Qfix, Avondale, PA) thermoplastic mask and monitored for intra-fraction motion with SI. IDENTIFYTM log files were correlated with trajectory log files to correlate treatment parameters with SI-reported offsets. IDENTIFYTM reported offsets were correlated with gantry and couch angles to assess system performance for obstructed and clear camera field of view. Data were stratified by race to evaluate performance differences due to skin tone. RESULTS: All commissioning data were found to meet recommended tolerances. IDENTIFYTM was used to monitor intra-fraction motion on 1164 fractions from 386 patients. The median magnitude of translational SI reported offsets at the end of treatment was 0.27 mm. SI reported offsets were shown to increase when camera pods are blocked by the gantry with larger increases seen at non-zero couch angles. With camera obstruction, the median magnitude of the SI reported offset was 0.50 and 0.80 mm for White and Black patients, respectively. CONCLUSIONS: IDENTIFYTM performance during fSRS is comparable to other commercially available SI systems where offsets are shown to increase at non-zero couch angles and during camera pod blockage.

Mapping the Dynamics of Contemporary PRRSV-2 Evolution and Its Emergence and Spreading Hotspots in the U.S. Using Phylogeography.

The repeated emergence of new genetic variants of PRRSV-2, the virus that causes porcine reproductive and respiratory syndrome (PRRS), reflects its rapid evolution and the failure of previous control efforts. Understanding spatiotemporal heterogeneity in variant emergence and spread is critical for future outbreak prevention. Here, we investigate how the pace of evolution varies across time and space, identify the origins of sub-lineage emergence, and map the patterns of the inter-regional spread of PRRSV-2 Lineage 1 (L1)-the current dominant lineage in the U.S. We performed comparative phylogeographic analyses on subsets of 19,395 viral ORF5 sequences collected across the U.S. and Canada between 1991 and 2021. The discrete trait analysis of multiple spatiotemporally stratified sampled sets (n = 500 each) was used to infer the ancestral geographic region and dispersion of each sub-lineage. The robustness of the results was compared to that of other modeling methods and subsampling strategies. Generally, the spatial spread and population dynamics varied across sub-lineages, time, and space. The Upper Midwest was a main spreading hotspot for multiple sub-lineages, e.g., L1C and L1F, though one of the most recent emergence events (L1A(2)) spread outwards from the east. An understanding of historical patterns of emergence and spread can be used to strategize disease control and the containment of emerging variants.