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Purpose: Positional errors resulting from motion are a principal challenge across all disease sites in radiation therapy. This is particularly pertinent when treating lesions in the liver with stereotactic body radiation therapy (SBRT). To achieve dose escalation and margin reduction for liver SBRT, kV real-time imaging interventions may serve as a potential solution. In this study, we report results of a retrospective cohort of liver patients treated using real-time 2D kV-image guidance SBRT with emphasis on the impact of (1) clinical workflow, (2) treatment accuracy, and (3) tumor dose. Methods and Materials: Data from 33 patients treated with 41 courses of liver SBRT were analyzed. During treatment, planar kV images orthogonal to the treatment beam were acquired to determine treatment interventions, namely treatment pauses (ie, adequacy of gating thresholds) or treatment shifts. Patients were shifted if internal markers were >3 mm, corresponding to the PTV margin used, from the expected reference condition. The frequency, duration, and nature of treatment interventions (ie, pause vs shift) were recorded, and the dosimetric impact associated with treatment shifts was estimated using a machine learning dosimetric model. Results: Of all fractions delivered, 39% required intervention, which took on average 1.9 ± 1.6 minutes and occurred more frequently in treatments lasting longer than 7 minutes. The median realignment shift was 5.7 mm in size, and the effect of these shifts on minimum tumor dose in simulated clinical scenarios ranged from 0% to 50% of prescription dose per fraction. Conclusion: Real-time kV-based imaging interventions for liver SBRT minimally affect clinical workflow and dosimetrically benefit patients. This potential solution for addressing positional errors from motion addresses concerns about target accuracy and may enable safe dose escalation and margin reduction in the context of liver SBRT.

Abstract In Parkinson’s disease, pathogenic factors such as the intraneuronal accumulation of the protein α-synuclein affect key metabolic processes. New approaches are required to understand how metabolic dysregulations cause degeneration of vulnerable subtypes of neurons in the brain. Here, we apply correlative electron microscopy and NanoSIMS isotopic imaging to map and quantify 13C enrichments in dopaminergic neurons at the subcellular level after pulse-chase administration of 13C-labeled glucose. To model a condition leading to neurodegeneration in Parkinson’s disease, human α-synuclein was unilaterally overexpressed in the substantia nigra of one brain hemisphere in rats. When comparing neurons overexpressing α-synuclein to those located in the control hemisphere, the carbon anabolism and turnover rates revealed metabolic anomalies in specific neuronal compartments and organelles. Overexpression of α-synuclein enhanced the overall carbon turnover in nigral neurons, despite a lower relative incorporation of carbon inside the nucleus. Furthermore, mitochondria and Golgi apparatus showed metabolic defects consistent with the effects of α-synuclein on inter-organellar communication. By revealing changes in the kinetics of carbon anabolism and turnover at the subcellular level, this approach can be used to explore how neurodegeneration unfolds in specific subpopulations of neurons.

Abstract Background Joint efforts by government and non-government organizations have helped to reduce malaria in Bangladesh and set the country on a clear path to eventual malaria elimination. However, achieving that goal would be challenging without a comprehensive understanding of vector bionomics. Methods Targeted capturing of Anopheles mosquitoes over a rainy season, utilizing specific sampling methods, including human landing catches (HLCs), CDC-light traps (CDC-LTs), and pyrethrum spray catches (PSCs) were aimed to characterize entomological drivers of transmission in four sites of Bandarban, Bangladesh. Results Molecular characterization of a subset of 4637 mosquitoes has demonstrated the presence of at least 17 species whose capture rates were representative of the rainy season. Species compositions and bionomic traits did not vary between sites with Anopheles maculatus having the highest landing rate by HLCs and Anopheles vagus having the highest capture rate with CDC-LTs. Interestingly, Anopheles species compositions and capture rates varied significantly (p

Fiducial markers are utilized for image guided radiotherapy (IGRT) alignment during the delivery of liver stereotactic body radiosurgery (SBRT). There are limited data demonstrating the impact of matching fiducials on the accuracy of liver SBRT. This study quantifies the benefit of fiducial-based alignment and improvements in inter-observer reliability. Nineteen patients with 24 liver lesions were treated with SBRT. Target localization was performed using fiducial markers on cone-beam computed tomography (CBCT). Each CBCT procedure was retrospectively realigned to match both the liver edge and fiducial markers. The shifts were recorded by seven independent observers. Inter-observer variability was analyzed by calculating the mean error and uncertainty for the set-up. The mean absolute Cartesian error observed from fiducial and liver edge-based alignment was 1.5 mm and 5.3 mm, respectively. The mean uncertainty from fiducial and liver edge-based alignment was 1.8 mm and 4.5 mm, respectively. An error of 5 mm or greater was observed 50% of the time when aligning to the liver surface versus 5% of the time when aligning to fiducial markers. Aligning to the liver edge significantly increased the error, resulting in increased shifts when compared to alignment to fiducials. Tumors of 3 cm or farther from the liver dome had higher mean errors when aligned without fiducials (4.8 cm vs. 4.4 cm, p = 0.003). Our data support the use of fiducial markers for safer and more accurate liver SBRT.

Purpose: Four-dimensional computed tomography (4DCT)–ventilation-based functional avoidance uses 4DCT images to generate plans that avoid functional regions of the lung with the goal of reducing pulmonary toxic effects. A phase 2, multicenter, prospective study was completed to evaluate 4DCT-ventilation functional avoidance radiation therapy. The purpose of this study was to report the results for pretreatment to posttreatment pulmonary function test (PFT) changes for patients treated with functional avoidance radiation therapy. Methods and Materials: Patients with locally advanced lung cancer receiving chemoradiation were accrued. Functional avoidance plans based on 4DCT-ventilation images were generated. PFTs were obtained at baseline and 3 months after chemoradiation. Differences for PFT metrics are reported, including diffusing capacity for carbon monoxide (DLCO), forced expiratory volume in 1 second (FEV1), and forced vital capacity (FVC). PFT metrics were compared for patients who did and did not experience grade 2 or higher pneumonitis. Results: Fifty-six patients enrolled on the study had baseline and posttreatment PFTs evaluable for analysis. The mean change in DLCO, FEV1, and FVC was –11.6% ± 14.2%, –5.6% ± 16.9%, and –9.0% ± 20.1%, respectively. The mean change in DLCO was –15.4% ± 14.4% for patients with grade 2 or higher radiation pneumonitis and –10.8% ± 14.1% for patients with grade

Flexible dielectric materials with environmental-friendly, low-cost and high-energy density characteristics are in increasing demand as the world steps into the new Industrial 4.0 era. In this work, an elastomeric nanocomposite was developed by incorporating two components: cellulose nanofibrils (CNFs) and recycled alum sludge, as the reinforcement phase and to improve the dielectric properties, in a bio-elastomer matrix. CNF and alum sludge were produced by processing waste materials that would otherwise be disposed to landfills. A biodegradable elastomer polydimethylsiloxane was used as the matrix and the nanocomposites were processed by casting the materials in Petri dishes. Nanocellulose extraction and heat treatment of alum sludge were conducted and characterized using various techniques including scanning electron microscopy (SEM), thermogravimetric analysis/derivative thermogravimetric (TGA/DTG) and X-ray diffraction (XRD) analysis. When preparing the nanocomposite samples, various amount of alum sludge was added to examine their impact on the mechanical, thermal and electrical properties. Results have shown that it could be a sustainable practice of reusing such wastes in preparing flexible, lightweight and miniature dielectric materials that can be used for energy storage applications.

PrecisThe exclusion of unmatched observations in propensity score matching has implications for the generalizability of causal effects. Machine learning methods can help to identify how the study population differs from the unmatched subpopulation.BackgroundThere has been widespread use of propensity scores in evaluating the effect of cancer treatments on survival, particularly in administrative databases and cancer registries. A byproduct of certain matching schemes is the exclusion of observations. Borrowing an analogy from clinical trials, one can view these exclusions as subjects that do not satisfy eligibility criteria.MethodsDeveloping identification rules for these “data-driven eligibility criteria” in observational studies on both population and individual levels helps to ascertain the population on which causal effects are being made. This article presents a machine learning method to determine the representativeness of causal effects in two different datasets from the National Cancer Database.ResultsDecision trees reveal that groups with certain features have a higher probability of inclusion in the study population than older patients. In the first dataset, younger age categories had an inclusion probability of at least 0.90 in all models, while the probability for the older category ranged from 0.47 to 0.65. Most trees split once more on an even higher age at a lower node, suggesting that the oldest patients are the least likely to be matched. In the second set of data, both age and surgery status were associated with inclusion.ConclusionThe methodology presented in this paper underscores the need to consider exclusions in propensity score matching procedures as well as complementing matching with other propensity score adjustments.

Abstract There is no FDA-approved medication for methamphetamine (METH) use disorder. New therapeutic approaches are needed, especially for people who use METH heavily and are at high risk for overdose. This study used genetically engineered rats to evaluate PARKIN as a potential target for METH use disorder. PARKIN knockout, PARKIN-overexpressing, and wild-type young adult male Long Evans rats were trained to self-administer high doses of METH using an extended-access METH self-administration paradigm. Reinforcing/rewarding properties of METH were assessed by quantifying drug-taking behavior and time spent in a METH-paired environment. PARKIN knockout rats self-administered more METH and spent more time in the METH-paired environment than wild-type rats. Wild-type rats overexpressing PARKIN self-administered less METH and spent less time in the METH-paired environment. PARKIN knockout rats overexpressing PARKIN self-administered less METH during the first half of drug self-administration days than PARKIN-deficient rats. The results indicate that rats with PARKIN excess or PARKIN deficit are useful models for studying neural substrates underlying “resilience” or vulnerability to METH use disorder and identify PARKIN as a novel potential drug target to treat heavy use of METH.