Citations

AbstractBackgroundKilo‐voltage cone‐beam computed tomography (CBCT) is a prevalent modality used for adaptive radiotherapy (ART) due to its compatibility with linear accelerators and ability to provide online imaging. However, the widely‐used Feldkamp‐Davis‐Kress (FDK) reconstruction algorithm has several limitations, including potential streak aliasing artifacts and elevated noise levels. Iterative reconstruction (IR) techniques, such as total variation (TV) minimization, dictionary‐based methods, and prior information‐based methods, have emerged as viable solutions to address these limitations and improve the quality and applicability of CBCT in ART.PurposeOne of the primary challenges in IR‐based techniques is finding the right balance between minimizing image noise and preserving image resolution. To overcome this challenge, we have developed a new reconstruction technique called high‐resolution CBCT (HRCBCT) that specifically focuses on improving image resolution while reducing noise levels.MethodsThe HRCBCT reconstruction technique builds upon the conventional IR approach, incorporating three components: the data fidelity term, the resolution preservation term, and the regularization term. The data fidelity term ensures alignment between reconstructed values and measured projection data, while the resolution preservation term exploits the high resolution of the initial Feldkamp‐Davis‐Kress (FDK) algorithm. The regularization term mitigates noise during the IR process. To enhance convergence and resolution at each iterative stage, we applied Iterative Filtered Backprojection (IFBP) to the data fidelity minimization process.ResultsWe evaluated the performance of the proposed HRCBCT algorithm using data from two physical phantoms and one head and neck patient. The HRCBCT algorithm outperformed all four different algorithms; FDK, Iterative Filtered Back Projection (IFBP), Compressed Sensing based Iterative Reconstruction (CSIR), and Prior Image Constrained Compressed Sensing (PICCS) methods in terms of resolution and noise reduction for all data sets. Line profiles across three line pairs of resolution revealed that the HRCBCT algorithm delivered the highest distinguishable line pairs compared to the other algorithms. Similarly, the Modulation Transfer Function (MTF) measurements, obtained from the tungsten wire insert on the CatPhan 600 physical phantom, showed a significant improvement with HRCBCT over traditional algorithms.ConclusionThe proposed HRCBCT algorithm offers a promising solution for enhancing CBCT image quality in adaptive radiotherapy settings. By addressing the challenges inherent in traditional IR methods, the algorithm delivers high‐definition CBCT images with improved resolution and reduced noise throughout each iterative step. Implementing the HR CBCT algorithm could significantly impact the accuracy of treatment planning during online adaptive therapy.

AbstractMotivationGenomic data are subject to various sources of confounding, such as demographic variables, biological heterogeneity, and batch effects. To identify genomic features associated with a variable of interest in the presence of confounders, the traditional approach involves fitting a confounder-adjusted regression model to each genomic feature, followed by multiplicity correction.ResultsThis study shows that the traditional approach is suboptimal and proposes a new two-dimensional false discovery rate control framework (2DFDR+) that provides significant power improvement over the conventional method and applies to a wide range of settings. 2DFDR+ uses marginal independence test statistics as auxiliary information to filter out less promising features, and FDR control is performed based on conditional independence test statistics in the remaining features. 2DFDR+ provides (asymptotically) valid inference from samples in settings where the conditional distribution of the genomic variables given the covariate of interest and the confounders is arbitrary and completely unknown. Promising finite sample performance is demonstrated via extensive simulations and real data applications.Availability and implementationR codes and vignettes are available at https://github.com/asmita112358/tdfdr.np.

Although the etiology of rheumatoid arthritis (RA) is unknown, a strong genetic predisposition and the presence of preclinical antibodies before the onset of symptoms is documented. An expansion of Eggerthella lenta is associated with severe disease in RA. Here, using a humanized mouse model of collagen-induced arthritis, we determined the impact of E. lenta abundance on RA severity. Naïve mice gavaged with E. lenta produce preclinical rheumatoid factor and, when induced for arthritis, develop severe disease. The augmented antibody response was much higher in female mice, and among patients with RA, women had higher average load of E. lenta . Expansion of E. lenta increased CXCL5 and CD4 T cells, and both interleukin-17– and interferon-γ–producing B cells. Further, E. lenta gavage caused gut dysbiosis and decline in amino acids and nicotinamide adenine dinucleotide with an increase in microbe-dependent bile acids and succinyl carnitine causing systemic senescent-like inflammation.

Small-for-size syndrome (SFSS) is a well-recognized complication following liver transplantation (LT), with up to 20% developing this following living donor LT (LDLT). Preventing SFSS involves consideration of factors before the surgical procedure, including donor and recipient selection, and factors during the surgical procedure, including adequate outflow reconstruction, graft portal inflow modulation, and management of portosystemic shunts. International Liver Transplantation Society, International Living Donor Liver Transplantation Group, and Liver Transplant Society of India Consensus Conference was convened in January 2023 to develop recommendations for the prediction and management of SFSS in LDLT. The format of the conference was based on the Grading of Recommendations, Assessment, Development, and Evaluation system. International experts in this field were allocated to 4 working groups (diagnosis, prevention, anesthesia, and critical care considerations, and management of established SFSS). The working groups prepared evidence-based recommendations to answer-specific questions considering the currently available literature. The working group members, independent panel, and conference attendees served as jury to edit and confirm the final recommendations presented at the end of the conference by each working group separately. This report presents the final statements and evidence-based recommendations provided by working group 2 that can be implemented to prevent SFSS in LDLT patients.

In this article, we present a flexible model for microbiome count data. We consider a quasi‐likelihood framework, in which we do not make any assumptions on the distribution of the microbiome count except that its variance is an unknown but smooth function of the mean. By comparing our model to the negative binomial generalized linear model (GLM) and Poisson GLM in simulation studies, we show that our flexible quasi‐likelihood method yields valid inferential results. Using a real microbiome study, we demonstrate the utility of our method by examining the relationship between adenomas and microbiota. We also provide an R package “fql” for the application of our method.

Abstract Background: Scattered tubular-like cells (STCs) are differentiated renal tubular cells that during recovery from ischemic injury dedifferentiate to repair other injured renal cells. Renal artery stenosis (RAS), often associated with chronic inflammatory injury, compromises the integrity and function of STCs, but the underlying mechanisms remain unknown. We hypothesized that RAS alters the transcriptomic and epigenetic profile of inflammatory genes in swine STCs. Methods: STCs were harvested from pig kidneys after 10 weeks of RAS or sham (n=6 each). STC mRNA profiles of inflammatory genes were analyzed using high-throughput mRNA-sequencing (seq) and their DNA methylation (5mC) and hydroxymethylation (5hmC) profiles by DNA immunoprecipitation and next-generation sequencing (MeDIP-seq) (n=3 each), followed by an integrated (mRNA-seq/MeDIP-seq) analysis. STC protein expression of candidate differentially expressed (DE) genes and common proinflammatory proteins were subsequently assessed in vitro before and after epigenetic (Bobcat339) modulation. Results: mRNA-seq identified 57 inflammatory genes up-regulated in RAS-STCs versus Normal-STCs (>1.4 or <0.7-fold, P<0.05), of which 14% exhibited lower 5mC and 5% higher 5hmC levels in RAS-STCs versus Normal-STCs, respectively. Inflammatory gene and protein expression was higher in RAS-STCs compared with Normal-STCs but normalized after epigenetic modulation. Conclusions: These observations highlight a novel modulatory mechanism of this renal endogenous repair system and support development of epigenetic or anti-inflammatory therapies to preserve the reparative capacity of STCs in individuals with RAS.

Pencil beam scanning delivered with continuous scanning has several advantages over conventional discrete spot scanning. Such advantages include improved beam delivery efficiency and reduced beam delivery time. However, a move dose is delivered between consecutive spots with continuous scanning, and current treatment planning systems do not take this into account. Therefore, continuous scanning and discrete spot plans have an inherent dose discrepancy. Using the operating parameters of the state-of-the-art particle therapy system, we conducted a proof-of-concept study in which we systematically generated 28 plans for cubic targets with different combinations of plan parameters and simulated the dose discrepancies between continuous scanning and a planned one. A nomograph to guide the selection of plan parameters was developed to reduce the dose discrepancy. The effectiveness of the nomograph was evaluated with two clinical cases (one prostate and one liver). Plans with parameters guided by the nomograph decreased dose discrepancy than those used standard plan parameters. Specifically, the 2%/2 mm gamma passing rate increased from 96.3% to 100% for the prostate case and from 97.8% to 99.7% for the liver case. The CTV DVH root mean square error decreased from 2.2% to 0.2% for the prostate case and from 1.8% to 0.9% for the liver case. The decreased dose discrepancy may allow the relaxing of the delivery constraint for some cases, leading to greater benefits in continuous scanning. Further investigation is warranted.