XPCA: Extending PCA for Combinations of Discrete and Continuous Data.
Abstract not provided.
Kincher-Winoto, Kina↗
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Results for “PCA”
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Streaming Distributed PCA for Climate Modeling
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Wang, Yu↗
Protocatechualdehyde possesses anti-cancer activity through downregulating cyclin D1 and HDAC2 in human colorectal cancer cells
Highlights: Black-Right-Pointing-Pointer Protocatechualdehyde (PCA) suppressed cell proliferation and induced apoptosis in human colorectal cancer cells. Black-Right-Pointing-Pointer PCA enhanced transcriptional downregulation of cyclin D1 gene. Black-Right-Pointing-Pointer PCA suppressed HDAC2 expression and activity. Black-Right-Pointing-Pointer These findings suggest that anti-cancer activity of PCA may be mediated by reducing HDAC2-derived cyclin D1 expression. -- Abstract: Protocatechualdehyde (PCA) is a naturally occurring polyphenol found in barley, green cavendish bananas, and grapevine leaves. Although a few studies reported growth-inhibitory activity of PCA in breast and leukemia cancer cells, the underlying mechanisms are still poorly understood. Thus, we performed in vitro study to investigate if treatment of PCA affects cell proliferation and apoptosis in human colorectal cancer cells and define potential mechanisms by which PCA mediates growth arrest and apoptosis of cancer cells. Exposure of PCA to human colorectal cancer cells (HCT116 and SW480 cells) suppressed cell growth and induced apoptosis in dose-dependent manner. PCA decreased cyclin D1 expression in protein and mRNA level and suppressed luciferase activity of cyclin D1 promoter, indicating transcriptional downregulation of cyclin D1 gene by PCA. We also observed that PCA treatment attenuated enzyme activity of histone deacetylase (HDAC) and reduced expression of HDAC2, but not HDAC1. These findings suggest that cell growth inhibition and apoptosis by PCA may be a result of HDAC2-mediated cyclin D1 suppression.
60 APPLIED LIFE SCIENCES↗
miR-1207-3p regulates the androgen receptor in prostate cancer via FNDC1/fibronectin
Prostate cancer (PCa) is frequently diagnosed in men, and dysregulation of microRNAs is characteristic of many cancers. MicroRNA-1207-3p is encoded at the non-protein coding gene locus PVT1 on the 8q24 human chromosomal region, an established PCa susceptibility locus. However, the role of microRNA-1207-3p in PCa is unclear. We discovered that microRNA-1207-3p is significantly underexpressed in PCa cell lines in comparison to normal prostate epithelial cells. Increased expression of microRNA-1207-3p in PCa cells significantly inhibits proliferation, migration, and induces apoptosis via direct molecular targeting of FNDC1, a protein which contains a conserved protein domain of fibronectin (FN1). FNDC1, FN1, and the androgen receptor (AR) are significantly overexpressed in PCa cell lines and human PCa, and positively correlate with aggressive PCa. Prostate tumor FN1 expression in patients that experienced PCa-specific death is significantly higher than in patients that remained alive. Furthermore, FNDC1, FN1 and AR are concomitantly overexpressed in metastatic PCa. Consequently, these studies have revealed a novel microRNA-1207-3p/FNDC1/FN1/AR regulatory pathway in PCa. - Graphical abstract: miR-1207-3p/FNDC1/FN1/AR is a novel regulatory pathway in prostate cancer. - Highlights: • Expression of microRNA-1207-3p is significantly lost in prostate cancer (PCa) cells. • MicroRNA-1207-3p regulates proliferation, apoptosis, and migration via direct molecular targeting of the 3′UTR of FNDC1. • MicroRNA-1207-3p regulates proliferation, apoptosis, and migration via direct molecular targeting of the 3′UTR of FNDC1. • FNDC1, FN1, and AR are concurrently overexpressed in metastatic PCa.
60 APPLIED LIFE SCIENCES↗
Statistical Modeling of CTV Motion and Deformation for IMRT of Early-Stage Rectal Cancer
Purpose: To derive and validate a statistical model of motion and deformation for the clinical target volume (CTV) of early-stage rectal cancer patients. Methods and Materials: For 16 patients, 4 to 5 magnetic resonance images (MRI) were acquired before each fraction was administered. The CTV was delineated on each MRI. Using a leave-one-out methodology, we constructed a population-based principal component analysis (PCA) model of the CTV motion and deformation of 15 patients, and we tested the model on the left-out patient. The modeling error was calculated as the amount of the CTV motion-deformation of the left-out-patient that could not be explained by the PCA model. Next, the PCA model was used to construct a PCA target volume (PCA-TV) by accumulating motion-deformations simulated by the model. A PCA planning target volume (PTV) was generated by expanding the PCA-TV by uniform margins. The PCA-PTV was compared with uniform and nonuniform CTV-to-PTV margins. To allow comparison, geometric margins were determined to ensure adequate coverage, and the volume difference between the PTV and the daily CTV (CTV-to-PTV volume) was calculated. Results: The modeling error ranged from 0.9 ± 0.5 to 2.9 ± 2.1 mm, corresponding to a reduction of the CTV motion-deformation between 6% and 60% (average, 23% ± 11%). The reduction correlated with the magnitude of the CTV motion-deformation (P<.001, R=0.66). The PCA-TV and the CTV required 2-mm and 7-mm uniform margins, respectively. The nonuniform CTV-to-PTV margins were 4 mm in the left, right, inferior, superior, and posterior directions and 8 mm in the anterior direction. Compared to uniform and nonuniform CTV-to-PTV margins, the PCA-based PTV significantly decreased (P<.001) the average CTV-to-PTV volume by 128 ± 20 mL (49% ± 4%) and by 35 ± 6 mL (20% ± 3.5%), respectively. Conclusions: The CTV motion-deformation of a new patient can be explained by a population-based PCA model. A PCA model-generated PTV significantly improved sparing of organs at risk compared to uniform and nonuniform CTV-to-PTV margins.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Prostate extracellular vesicles in patient plasma as a liquid biopsy platform for prostate cancer using nanoscale flow cytometry
Background: Extracellular vesicles released by prostate cancer present in seminal fluid, urine, and blood may represent a non-invasive means to identify and prioritize patients with intermediate risk and high risk of prostate cancer. We hypothesize that enumeration of circulating prostate microparticles (PMPs), a type of extracellular vesicle (EV), can identify patients with Gleason Score≥4+4 prostate cancer (PCa) in a manner independent of PSA. Patients and Methods: Plasmas from healthy volunteers, benign prostatic hyperplasia patients, and PCa patients with various Gleason score patterns were analyzed for PMPs. We used nanoscale flow cytometry to enumerate PMPs which were defined as submicron events (100-1000nm) immunoreactive to anti-PSMA mAb when compared to isotype control labeled samples. Levels of PMPs (counts/µL of plasma) were also compared to CellSearch CTC Subclasses in various PCa metastatic disease subtypes (treatment naïve, castration resistant prostate cancer) and in serially collected plasma sets from patients undergoing radical prostatectomy. Results: PMP levels in plasma as enumerated by nanoscale flow cytometry are effective in distinguishing PCa patients with Gleason Score≥8 disease, a highrisk prognostic factor, from patients with Gleason Score≤7 PCa, which carries an intermediate risk of PCa recurrence. PMP levels were independent of PSA and significantly decreased after surgical resection of the prostate, demonstrating its prognostic potential for clinical follow-up. CTC subclasses did not decrease after prostatectomy and were not effective in distinguishing localized PCa patients from metastatic PCa patients. Conclusions: PMP enumeration was able to identify patients with Gleason Score ≥8 PCa but not patients with Gleason Score 4+3 PCa, but offers greater confidence than CTC counts in identifying patients with metastatic prostate cancer. CTC Subclass analysis was also not effective for post-prostatectomy follow up and for distinguishing metastatic PCa and localized PCa patients. Nanoscale flow cytometry of PMPs presents an emerging biomarker platform for various stages of prostate cancer.
60 APPLIED LIFE SCIENCES↗
Flight test of a propulsion controlled aircraft system on the NASA F-15 airplane
Flight tests of the propulsion controlled aircraft (PCA) system on the NASA F-15 airplane evolved as a result of a long series of simulation and flight tests. Initially, the simulation results were very optimistic. Early flight tests showed that manual throttles-only control was much more difficult than the simulation, and a flight investigation was flown to acquire data to resolve this discrepancy. The PCA system designed and developed by MDA evolved as these discrepancies were found and resolved, requiring redesign of the PCA software and modification of the flight test plan. Small throttle step inputs were flown to provide data for analysis, simulation update, and control logic modification. The PCA flight tests quickly revealed less than desired performance, but the extensive flexibility built into the flight PCA software allowed rapid evaluation of alternate gains, filters, and control logic, and within 2 weeks, the PCA system was functioning well. The initial objective of achieving adequate control for up-and-away flying and approaches was satisfied, and the option to continue to actual landings was achieved. After the PCA landings were accomplished, other PCA features were added, and additional maneuvers beyond those originally planned were flown. The PCA system was used to recover from extreme upset conditions, descend, and make approaches to landing. A heading mode was added, and a single engine plus rudder PCA mode was also added and flown. The PCA flight envelope was expanded far beyond that originally designed for. Guest pilots from the USAF, USN, NASA, and the contractor also flew the PCA system and were favorably impressed.
Burcham, Frank W., Jr.↗
First Plant Cell Atlas symposium report
The Plant Cell Atlas (PCA) community hosted a virtual symposium on December 9 and 10, 2021 on single cell and spatial omics technologies. The conference gathered almost 500 academic, industry, and government leaders to identify the needs and directions of the PCA community and to explore how establishing a data synthesis center would address these needs and accelerate progress. This report details the presentations and discussions focused on the possibility of a data synthesis center for a PCA and the expected impacts of such a center on advancing science and technology globally. Community discussions focused on topics such as data analysis tools and annotation standards; computational expertise and cyber-infrastructure; modes of community organization and engagement; methods for ensuring a broad reach in the PCA community; recruitment, training, and nurturing of new talent; and the overall impact of the PCA initiative. These targeted discussions facilitated dialogue among the participants to gauge whether PCA might be a vehicle for formulating a data synthesis center. The conversations also explored how online tools can be leveraged to help broaden the reach of the PCA (i.e., online contests, virtual networking, and social media stakeholder engagement) and decrease costs of conducting research (e.g., virtual REU opportunities). Major recommendations for the future of the PCA included establishing standards, creating dashboards for easy and intuitive access to data, and engaging with a broad community of stakeholders. The discussions also identified the following as being essential to the PCA's success: identifying homologous cell-type markers and their biocuration, publishing datasets and computational pipelines, utilizing online tools for communication (such as Slack), and user-friendly data visualization and data sharing. In conclusion, the development of a data synthesis center will help the PCA community achieve these goals by providing a centralized repository for existing and new data, a platform for sharing tools, and new analytical approaches through collaborative, multidisciplinary efforts. A data synthesis center will help the PCA reach milestones, such as community-supported data evaluation metrics, accelerating plant research necessary for human and environmental health.
59 BASIC BIOLOGICAL SCIENCES↗
Identification of candidate diagnostic and prognostic biomarkers for human prostate cancer: RPL22L1 and RPS21
Prostate cancer (PCa) is one of the most common malignancies in men worldwide. This study was designed to investigate the potential of Ribosomal Protein L22-like1 (RPL22L1) and Ribosomal Protein S21 (RPS21) as diagnostic and prognostic biomarkers for PCa. First, RPL22L1 and RPS21 were screened as the key molecular of PCa by bioinformatics analysis. Subsequently, the prostate tissue samples were stained for antibodies against RPL22L1 and RPS21. The unbiased signal quantification was performed by ImageJ software, and the results showed that the expression of RPL22L1 and RPS21 exhibited significant differences between the PCa tissues and the normal prostate tissues. Receiver-operating characteristics (ROC) curves were prepared, and then the area under the curve (AUC) values of RPL22L1 and RPS21 were calculated as 0.798 and 0.768, and the likelihood ratio (LR) values of RPL22L1 and RPS21 were calculated as 2.86 and 2.53. These data implied that the over-expression of RPL22L1 and RPS21 is associated with the presence of PCa. The further analysis suggested that the expression of RPL22L1 and RPS21 were significantly higher in high Gleason grade than they were in low Gleason grade. In addition, in vitro studies were undertaken to evaluate the roles of RPL22L1 and RPS21 in PCa. The results revealed that these genes promote PCa cell proliferation, migration and invasion, and inhibit PCa cell apoptosis. Taken together, these data showed that RPL22L1 and RPS21 exhibited higher expression in human prostate cancer tissue, and involved in PCa cell proliferation and invasion. This research provided a novel insight into diagnostic and prognostic biomarkers for PCa.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
SOX4 is activated by C-MYC in prostate cancer
Although MYC proto-oncogene (C-MYC) amplification has been consistently reported to be a potential marker for prostate cancer (PCa) progression and prognosis, the clinicopathological and prognostic significance of C-MYC protein expression remains controversial. Overexpression of SOX4 has been shown to play important roles in multiple cancers including PCa. However, the link between these two critical genetic aberrations is unclear. In the current study, we showed that C-MYC was overexpressed in 16.2% (17/105) of Chinese patients with localized PCa. Overexpression of C-MYC was significantly associated with high Gleason scores (P = 0.012) and high Ki67 labeling index (P = 0.005). C-MYC overexpression was correlated with cancer-related mortality and suggested to be an unfavorable prognostic factor in Chinese PCa patients (P = 0.018). Overexpression of C-MYC is associated with SOX4 overexpression in PCa tissues. Notably, SOX4 is a direct target gene of C-MYC; C-MYC activates SOX4 expression via binding to its promoter. In addition, Co-IP analysis demonstrated a physical interaction between C-MYC and SOX4 protein in PCa cells. Clinically, C-MYC+/SOX4+ characterized poor prognosis in a subset of PCa patients. In total, C-MYC overexpression may contribute to PCa progression by activating SOX4. Our findings highlight an important role of C-MYC/SOX4 in PCa progression in a subset of PCa patients.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Propulsion Controlled Aircraft design and development
This paper describes the design, development, and ground testing of the propulsion controlled aircraft (PCA) flight control system. A backup flight control system which uses only engine thrust, the PCA system utilizes collective and differential thrust changes to steer an aircraft that experiences partial or complete failure of the hydraulically actuated control surfaces. The objective of the program was to investigate, in flight, the throttles-only control capability of the F-15, using manual control, and also an augmented PCA mode in which computer-controlled thrust was used for flight control. The objective included PCA operation in up-and-away flight and, if performance was adequate, a secondary objective to make actual PCA landings. The PCA design began with a feasibility study which evaluated many control law designs. The study was done using off-line control analysis, simulation, and on-line manned flight simulator tests. Control laws, cockpit displays, and cockpit controls were evaluated by NASA test pilots. A flight test baseline configuration was selected based on projected flight performance, applicability to transport and fighter aircraft, and funding costs. During the PCA software and hardware development, the initial design was updated as data became available from throttle-only flight experiments conducted by NASA on the F-15. This information showed basic airframe characteristics that were not observed in the F-15 flight simulator and resulted in several design changes. After the primary objectives of the PCA flight testing were accomplished, additional PCA modes of operation were developed and implemented. The evolution of the PCA system from the initial feasibility study, control law design, simulation, hardware-in-the-loop tests, pilot-in-the-loop tests, and ground tests is presented.
Wells, Edward A.↗
miR-503 suppresses tumor cell proliferation and metastasis by directly targeting RNF31 in prostate cancer
Microarray data analyses were performed to search for metastasis-associated oncogenes in prostate cancer (PCa). RNF31 mRNA expressions in tumor tissues and benign prostate tissues were evaluated. The RNF31 protein expression levels were also analyzed by western blot and immunohistochemistry. Luciferase reporter assays were used to identify miRNAs that can regulate RNF31. The effect of RNF31 on PCa progression was studied in vitro and in vivo. We found that RNF31 was significantly increased in PCa and its expression level was highly correlated with seminal vesicle invasion, clinical stage, prostate specific antigen (PSA) level, Gleason score, and BCR. Silence of RNF31 suppressed PCa cell proliferation and metastasis in vitro and in vivo. miR-503 can directly regulate RNF31. Enforced expression of miR-503 inhibited the expression of RNF31 significantly and the restoration of RNF31 expression reversed the inhibitory effects of miR-503 on PCa cell proliferation and metastasis. These findings collectively indicated an oncogene role of RNF31 in PCa progression which can be regulated by miR-503, suggesting that RNF31 could serve as a potential prognostic biomarker and therapeutic target for PCa. - Highlights: • RNF31 is a potential metastasis associated gene and is associated with prostate cancer progression. • Silence of RNF31 inhibits PCa cell colony formation, migration and invasion. • RNF31 as a direct target of miR-503. • miR-503 can regulate cell proliferation, invasion and migration by targeting RNF31. • RNF31 plays an important role in PCa growth and metastasis in vivo.
60 APPLIED LIFE SCIENCES↗
The long non-coding RNA PCSEAT exhibits an oncogenic property in prostate cancer and functions as a competing endogenous RNA that associates with EZH2
Highlights: • PCSEAT is specifically overexpressed in prostate cancer. • PCSEAT promotes the growth and motility of prostate cancer cells. • PCSEAT regulates EZH2 by competitively ‘sponge’ miRNA-143-3p and miRNA-24-2-5p. • PCSEAT may serve as a biomarker for EZH2 inhibitors. • PCSEAT can be transmitted via exosomes and function in recipient cell. Prostate cancer (PCa) is the most common malignancy and the leading cause of cancer deaths in males. Recent studies demonstrate that long non-coding RNAs (lncRNAs) are involved in many aspects of PCa. However, their biological roles in PCa remain imperfectly understood. Here, we characterized an lncRNA, PCa specific expression and EZH2-associated transcript (PCSEAT, annotated as PRCAT38), which is specifically overexpressed in PCa. We further demonstrated that knockdown of PCSEAT results in the reduction of PCa cell growth and motility, and overexpression of PCSEAT reverses these phenotypes. Furthermore, bioactive PCSEAT is incorporated into exosomes and transmitted to adjacent cells, thus promoting cell proliferation and motility. Mechanistically, we found that PCSEAT promotes cell proliferation, at least in part by affecting miR-143-3p- and miR-24-2-5p-mediated regulation of EZH2, suggesting that PCSEAT and EZH2 competitively ‘sponge’ miR-143-3p and miR-24-2-5p. Overall, our results reveal that PCSEAT is specifically overexpressed in PCa patients and a potential oncogene in PCa cells via mediating EZH2 activity, indicating that PCSEAT may be a potential therapeutic target in PCa.
60 APPLIED LIFE SCIENCES↗
pH low insertion peptide mediated cell division cycle-associated protein 1 -siRNA transportation for prostatic cancer therapy targeted to the tumor microenvironment
Highlights: • Expression of CDCA1 in prostatic cancer cells and tissues. • Intracellular translocation of CDCA1-siRNA mediated by pHLIP. • pHLIP-CDCA1-siRNA suppresses xenograft prostatic tumor growth in vivo. • pHLIP-CDCA1-siRNA promote xenograft prostatic tumor cells apoptosis in vivo. Prostate cancer (PCa) is a common malignancy in male urinary system. Cell division cycle-associated protein 1 (CDCA1) is expressed highly in many cancer cells. Yet, whether CDCA1 play an important role in PCa progression is uncertain. pH low insertion peptide (pHLIP), a PH-induced transmembrane structure, can pass through the cell membrane into intracellular in an acidic environment. In this study, we try to confirm the expression status of CDCA1 in the PCa patients' tissues and PCa cell line. In addition, to make the CDCA1-siRNA efficiently targeting the PCa cells, pHLIP and CDCA1-siRNA were combined with disulfide bond to become effector molecules. By the characteristics of the pHLIP allosteric occurring in cancer tissue acidic microenvironment, CDCA1-siRNA may be transported specificity into prostatic cancer cells and released in the cytoplasm. The interference effect of the effector molecules on the CDCA1 was detected in vitro and in vivo. The results showed that CDCA1 was highly expressed in PCa cell line and human PCa clinical samples. Knock down CDCA1 significantly inhibit the growth and promote the apoptosis of prostatic cancer cells. In the intracellular translocation experiment, CDCA1-siRNA could be delivered into cytoplasma at pH 6.2, but not at pH 7.4. In the in vivo test, the tumor size was reduced obviously in the NOD/SCID mice treated with pHLIP-CDCA1-siRNA compared to the CDCA1-siRNA and the bioluminescent signal of Cy5-pHLIP-CDCA1-siRNA was focused detected in the tumor site. Our findings indicated that CDCA1 might be a very key molecule regulating survival and proliferation of PCa. pHLIP-CDCA1-siRNA might be a promising targeting therapy for PCa.
60 APPLIED LIFE SCIENCES↗
Phenazine-1-Carboxylic Acid-Producing Bacteria Enhance the Reactivity of Iron Minerals in Dryland and Irrigated Wheat Rhizospheres
Phenazine-1-carboxylic acid (PCA) is a broad-spectrum antibiotic produced by rhizobacteria in the dryland wheat fields of the Columbia Plateau. PCA and other phenazines reductively dissolve Fe and Mn oxyhydroxides in bacterial culture systems, but the impact of PCA upon Fe and Mn cycling in the rhizosphere is unknown. Here, concentrations of dithionite-extractable and poorly crystalline Fe were approximately 10% and 30–40% higher, respectively, in dryland and irrigated rhizospheres inoculated with the PCA-producing (PCA + ) strain Pseudomonas synxantha 2–79 than in rhizospheres inoculated with a PCA-deficient mutant. Yet, rhizosphere concentrations of Fe(II) and Mn did not differ significantly, indicating that PCA-mediated redox transformations of Fe and Mn were transient or were masked by competing processes. Total Fe and Mn uptake into wheat biomass also did not differ significantly, but the PCA + strain significantly altered Fe translocation into shoots. X-ray absorption near edge spectroscopy revealed an abundance of Fe-bearing oxyhydroxides and phyllosilicates in all rhizospheres. These findings indicate that the PCA + strain enhanced the reactivity and mobility of Fe derived from soil minerals without producing parallel changes in plant Fe uptake. This is the first report that directly links significant alterations of Fe-bearing minerals in the rhizosphere to a single bacterial trait.
54 ENVIRONMENTAL SCIENCES↗
Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects
Prostate cancer (PCa) brings huge public health burden in men. A growing number of conventional observational studies report associations of multiple circulating proteins with PCa risk. However, the existing findings may be subject to incoherent biases of conventional epidemiologic studies. To better characterize their associations, herein, we evaluated associations of genetically predicted concentrations of plasma proteins with PCa risk. In this study, we developed comprehensive genetic prediction models for protein levels in plasma. After testing 1308 proteins in 79 194 cases and 61 112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL, 24 proteins showed significant associations with PCa risk, including 16 previously reported proteins and eight novel proteins. Of them, 14 proteins showed negative associations and 10 showed positive associations with PCa risk. For 18 of the identified proteins, potential functional somatic changes of encoding genes were detected in PCa patients in The Cancer Genome Atlas (TCGA). Genes encoding these proteins were significantly involved in cancer-related pathways. We further identified drugs targeting the identified proteins, which may serve as candidates for drug repurposing for treating PCa. In conclusion, this study identifies novel protein biomarker candidates for PCa risk, which may provide new perspectives on the etiology of PCa and improve its therapeutic strategies.
59 BASIC BIOLOGICAL SCIENCES↗
A method of surface marker location optimization for tumor motion estimation in lung stereotactic body radiation therapy
Purpose: Accurately localizing lung tumor localization is essential for high-precision radiation therapy techniques such as stereotactic body radiation therapy (SBRT). Since direct monitoring of tumor motion is not always achievable due to the limitation of imaging modalities for treatment guidance, placement of fiducial markers on the patient’s body surface to act as a surrogate for tumor position prediction is a practical alternative for tracking lung tumor motion during SBRT treatments. In this work, the authors propose an innovative and robust model to solve the multimarker position optimization problem. The model is able to overcome the major drawbacks of the sparse optimization approach (SOA) model. Methods: The principle-component-analysis (PCA) method was employed as the framework to build the authors’ statistical prediction model. The method can be divided into two stages. The first stage is to build the surrogate tumor matrix and calculate its eigenvalues and associated eigenvectors. The second stage is to determine the “best represented” columns of the eigenvector matrix obtained from stage one and subsequently acquire the optimal marker positions as well as numbers. Using 4-dimensional CT (4DCT) and breath hold CT imaging data, the PCA method was compared to the SOA method with respect to calculation time, average prediction accuracy, prediction stability, noise resistance, marker position consistency, and marker distribution. Results: The PCA and SOA methods which were both tested were on all 11 patients for a total of 130 cases including 4DCT and breath-hold CT scenarios. The maximum calculation time for the PCA method was less than 1 s with 64 752 surface points, whereas the average calculation time for the SOA method was over 12 min with 400 surface points. Overall, the tumor center position prediction errors were comparable between the two methods, and all were less than 1.5 mm. However, for the extreme scenarios (breath hold), the prediction errors for the PCA method were not only smaller, but were also more stable than for the SOA method. Results obtained by imposing a series of random noises to the surrogates indicated that the PCA method was much more noise resistant than the SOA method. The marker position consistency tests using various combinations of 4DCT phases to construct the surrogates suggested that the marker position predictions of the PCA method were more consistent than those of the SOA method, in spite of surrogate construction. Marker distribution tests indicated that greater than 80% of the calculated marker positions fell into the high cross correlation and high motion magnitude regions for both of the algorithms. Conclusions: The PCA model is an accurate, efficient, robust, and practical model for solving the multimarker position optimization problem to predict lung tumor motion during SBRT treatments. Due to its generality, PCA model can also be applied to other imaging guidance system whichever using surface motion as the surrogates.
60 APPLIED LIFE SCIENCES↗
PRINCIPAL COMPONENT ANALYSIS STUDIES OF TURBULENCE IN OPTICALLY THICK GAS
In this work we investigate the sensitivity of principal component analysis (PCA) to the velocity power spectrum in high-opacity regimes of the interstellar medium (ISM). For our analysis we use synthetic position–position–velocity (PPV) cubes of fractional Brownian motion and magnetohydrodynamics (MHD) simulations, post-processed to include radiative transfer effects from CO. We find that PCA analysis is very different from the tools based on the traditional power spectrum of PPV data cubes. Our major finding is that PCA is also sensitive to the phase information of PPV cubes and this allows PCA to detect the changes of the underlying velocity and density spectra at high opacities, where the spectral analysis of the maps provides the universal −3 spectrum in accordance with the predictions of the Lazarian and Pogosyan theory. This makes PCA a potentially valuable tool for studies of turbulence at high opacities, provided that proper gauging of the PCA index is made. However, we found the latter to not be easy, as the PCA results change in an irregular way for data with high sonic Mach numbers. This is in contrast to synthetic Brownian noise data used for velocity and density fields that show monotonic PCA behavior. We attribute this difference to the PCA's sensitivity to Fourier phase information.
79 ASTRONOMY AND ASTROPHYSICS↗