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Multivariate Analysis as a Tool for Validating Tester Matching
A method of applying Principal Component Analysis, Soft Independent Modeling of Class Analysis, and statistical analysis is described that can be applied to many types of testers to ascertain how well matched the performance of the testers in the analysis are to one another or how well matched a tester is to itself at a later time. This method is most useful for situations for which the same units have not been run across the testers being analyzed for matched performance.
Surface-Enhanced Raman Spectroscopy Combined with Multivariate Analysis for Fingerprinting Clinically Similar Fibromyalgia and Long COVID Syndromes
Fibromyalgia (FM) is a chronic central sensitivity syndrome characterized by augmented pain processing at diffuse body sites and presents as a multimorbid clinical condition. Long COVID (LC) is a heterogenous clinical syndrome that affects 10–20% of individuals following COVID-19 infection. FM and LC share similarities with regard to the pain and other clinical symptoms experienced, thereby posing a challenge for accurate diagnosis. This research explores the feasibility of using surface-enhanced Raman spectroscopy (SERS) combined with soft independent modelling of class analogies (SIMCAs) to develop classification models differentiating LC and FM. Venous blood samples were collected using two supports, dried bloodspot cards (DBS, n = 48 FM and n = 46 LC) and volumetric absorptive micro-sampling tips (VAMS, n = 39 FM and n = 39 LC). A semi-permeable membrane (10 kDa) was used to extract low molecular fraction (LMF) from the blood samples, and Raman spectra were acquired using SERS with gold nanoparticles (AuNPs). Soft independent modelling of class analogy (SIMCA) models developed with spectral data of blood samples collected in VAMS tips showed superior performance with a validation performance of 100% accuracy, sensitivity, and specificity, achieving an excellent classification accuracy of 0.86 area under the curve (AUC). Amide groups, aromatic and acidic amino acids were responsible for the discrimination patterns among FM and LC syndromes, emphasizing the findings from our previous studies. Overall, our results demonstrate the ability of AuNP SERS to identify unique metabolites that can be potentially used as spectral biomarkers to differentiate FM and LC.
Multivariate Analysis of Biomass Pyrolysis Vapor Mass Spectra Using Pyrolysis Molecular Beam Mass Spectrometry - PCA, PLS, MCR
Abstract not provided
Measuring the Oxidation of Artificially Aged Elastomers with Multivariate Analysis and Imaging NEXAFS.
Abstract not provided.
Applying Multivariate Analysis Approaches to 1H-MRS Data to Detect Neuronal Currents.
Abstract not provided.
A Method for Automated Data Extraction and Peak Identification from Large GC-MS Data Sets Using Multivariate Analysis.
Abstract not provided.
Multivariate Analysis: A Tool for Turning Data to Information.
Abstract not provided.
USE OF MULTIVARIATE ANALYSIS FOR DETECTING ORIENTATION CHANGES IN STEEL VIA LAUE DIFFRACTION ARTIFACTS WITHIN XRF SPECTRA.
Abstract not provided.
USE OF MULTIVARIATE ANALYSIS FOR DETECTING ORIENTATION CHANGES IN STEEL VIA LAUE DIFFRACTION ARTIFACTS WITHIN XRF SPECTRA.
Abstract not provided.
Spectroscopic and Multivariate Analysis Development in Support of the Plutonium-238 Supply Program
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Prognostic Significance of the Number of Positive Lymph Nodes in Women With T1-2N1 Breast Cancer Treated With Mastectomy: Should Patients With 1, 2, and 3 Positive Lymph Nodes Be Grouped Together?
Purpose: To determine whether patients with 1, 2, or 3 positive lymph nodes (LNs) have similar survival outcomes. Methods and Materials: We analyzed the Surveillance, Epidemiology, and End Results registry of breast cancer patients diagnosed between 1990 and 2003. We identified 10,415 women with T1-2N1M0 breast cancer who were treated with mastectomy with no adjuvant radiation, with at least 10 LNs examined and 6 months of follow-up. The Kaplan-Meier method and log–rank test were used for survival analysis. Multivariate analysis was performed using the Cox proportional hazard model. Results: Median follow-up was 92 months. Ten-year overall survival (OS) and cause-specific survival (CSS) were progressively worse with increasing number of positive LNs. Survival rates were 70%, 64%, and 60% (OS), and 82%, 76%, and 72% (CSS) for 1, 2, and 3 positive LNs, respectively. Pairwise log–rank test P values were <.001 (1 vs 2 positive LNs), <.001 (1 vs 3 positive LNs), and .002 (2 vs 3 positive LNs). Multivariate analysis showed that number of positive LNs was a significant predictor of OS and CSS. Hazard ratios increased with the number of positive LNs. In addition, age, primary tumor size, grade, estrogen receptor and progesterone receptor status, race, and year of diagnosis were significant prognostic factors. Conclusions: Our study suggests that patients with 1, 2, and 3 positive LNs have distinct survival outcomes, with increasing number of positive LNs associated with worse OS and CSS. The conventional grouping of 1-3 positive LNs needs to be reconsidered.
A Study of Pseudoprogression After Spine Stereotactic Body Radiation Therapy
Purpose: To determine the incidence of pseudoprogression (PP) after spine stereotactic body radiation therapy based on a detailed and quantitative assessment of magnetic resonance imaging (MRI) morphologic tumor alterations, and to identify predictive factors distinguishing PP from local recurrence (LR). Methods and Materials: A retrospective analysis of 35 patients with 49 spinal segments treated with spine stereotactic body radiation therapy, from 2009 to 2014, was conducted. The median number of follow-up MRI studies was 4 (range, 2-7). The gross tumor volumes (GTVs) within each of the 49 spinal segments were contoured on the pretreatment and each subsequent follow-up T1- and T2-weighted MRI sagittal sequence. T2 signal intensity was reported as the mean intensity of voxels constituting each volume. LR was defined as persistent GTV enlargement on ≥2 serial MRI studies for ≥6 months or on pathologic confirmation. PP was defined as a GTV enlargement followed by stability or regression on subsequent imaging within 6 months. Kaplan-Meier analysis was used for estimation of actuarial local control, disease-free survival, and overall survival. Results: The median follow-up was 23 months (range, 1-39 months). PP was identified in 18% of treated segments (9 of 49) and LR in 29% (14 of 49). Earlier volume enlargement (5 months for PP vs 15 months for LR, P=.005), greater GTV to reference nonirradiated vertebral body T2 intensity ratio (+30% for PP vs −10% for LR, P=.005), and growth confined to 80% of the prescription isodose line (80% IDL) (8 of 9 PP cases vs 1 of 14 LR cases, P=.002) were associated with PP on univariate analysis. Multivariate analysis confirmed an earlier time to volume enlargement and growth within the 80% IDL as significant predictors of PP. LR involved the epidural space in all but 1 lesion, whereas PP was confined to the vertebral body in 7 of 9 cases. Conclusions: PP was observed in 18% of treated spinal segments. Tumor growth confined to the 80% IDL and earlier time to tumor enlargement were predictive for PP.
Interval Between Hysterectomy and Start of Radiation Treatment Is Predictive of Recurrence in Patients With Endometrial Carcinoma
Purpose: Adjuvant radiation therapy (RT) has been shown to improve local control in patients with endometrial carcinoma. We analyzed the impact of the time interval between hysterectomy and RT initiation in patients with endometrial carcinoma. Methods and Materials: In this institutional review board-approved study, we identified 308 patients with endometrial carcinoma who received adjuvant RT after hysterectomy. All patients had undergone hysterectomy, oophorectomy, and pelvic and para-aortic lymph node evaluation from 1988 to 2010. Patients' demographics, pathologic features, and treatments were compared. The time interval between hysterectomy and the start of RT was calculated. The effects of time interval on recurrence-free (RFS), disease-specific (DSS), and overall survival (OS) were calculated. Following univariate analysis, multivariate modeling was performed. Results: The median age and follow-up for the study cohort was 65 years and 72 months, respectively. Eighty-five percent of the patients had endometrioid carcinoma. RT was delivered with high-dose-rate brachytherapy alone (29%), pelvic RT alone (20%), or both (51%). Median time interval to start RT was 42 days (range, 21-130 days). A total of 269 patients (74%) started their RT <9 weeks after undergoing hysterectomy (group 1) and 26% started ≥9 weeks after surgery (group 2). There were a total of 43 recurrences. Tumor recurrence was significantly associated with treatment delay of ≥9 weeks, with 5-year RFS of 90% for group 1 compared to only 39% for group 2 (P<.001). On multivariate analysis, RT delay of ≥9 weeks (P<.001), presence of lymphovascular space involvement (P=.001), and higher International Federation of Gynecology and Obstetrics grade (P=.012) were independent predictors of recurrence. In addition, RT delay of ≥9 weeks was an independent significant predictor for worse DSS and OS (P=.001 and P=.01, respectively). Conclusions: Delay in administering adjuvant RT after hysterectomy was associated with worse survival endpoints. Our data suggest that shorter time interval between hysterectomy and start of RT may be beneficial.
Pulmonary Toxicity in Stage III Non-Small Cell Lung Cancer Patients Treated With High-Dose (74 Gy) 3-Dimensional Conformal Thoracic Radiotherapy and Concurrent Chemotherapy Following Induction Chemotherapy: A Secondary Analysis of Cancer and Leukemia Group B (CALGB) Trial 30105
Purpose: Cancer and Leukemia Group B (CALGB) 30105 tested two different concurrent chemoradiotherapy platforms with high-dose (74 Gy) three-dimensional conformal radiotherapy (3D-CRT) after two cycles of induction chemotherapy for Stage IIIA/IIIB non-small cell lung cancer (NSCLC) patients to determine if either could achieve a primary endpoint of >18-month median survival. Final results of 30105 demonstrated that induction carboplatin and gemcitabine and concurrent gemcitabine 3D-CRT was not feasible because of treatment-related toxicity. However, induction and concurrent carboplatin/paclitaxel with 74 Gy 3D-CRT had a median survival of 24 months, and is the basis for the experimental arm in CALGB 30610/RTOG 0617/N0628. We conducted a secondary analysis of all patients to determine predictors of treatment-related pulmonary toxicity. Methods and Materials: Patient, tumor, and treatment-related variables were analyzed to determine their relation with treatment-related pulmonary toxicity. Results: Older age, higher N stage, larger planning target volume (PTV)1, smaller total lung volume/PTV1 ratio, larger V20, and larger mean lung dose were associated with increasing pulmonary toxicity on univariate analysis. Multivariate analysis confirmed that V20 and nodal stage as well as treatment with concurrent gemcitabine were associated with treatment-related toxicity. A high-risk group comprising patients with N3 disease and V20 >38% was associated with 80% of Grades 3-5 pulmonary toxicity cases. Conclusions: Elevated V20 and N3 disease status are important predictors of treatment related pulmonary toxicity in patients treated with high-dose 3D-CRT and concurrent chemotherapy. Further studies may use these metrics in considering patients for these treatments.
Dataset_for_Conserved_macromolecular_architecture_of_Poplar_secondary_cell_walls_revealed_by_ssNMR_and_atomistic_modeling
This dataset contains solid-state 13C NMR data and atomistic molecular dynamics simulation files supporting the study of nanoscale secondary cell wall architecture across 13 genetically diverse Populus trichocarpa genotypes grown under uniform greenhouse conditions in 13C-enriched CO2 atmospheres (~89% 13C enrichment).The dataset contains two collections of solid-state 13C NMR data. (1) 200 MHz data (Bruker Avance III HD, 4 mm HX probe, 10 kHz MAS): raw Bruker TopSpin experiment folders and DMFIT-exported ascii spectra for selective and non-selective 1D 13C-13C spin diffusion experiments (3000 ms mixing) used to quantify inter-polymer spatial proximities, and short-mixing (1 ms) reference spectra used for polymeric abundance quantification by spectral deconvolution. (2) 600 MHz data (Bruker Avance III, 1.6 mm PhoenixNMR HXY probe, 30 kHz MAS): raw Bruker TopSpin experiment folders containing 2D CORD, 2D CP-INADEQUATE, and 13C/1H relaxation (T1, T1rho) experiments for all 13 genotypes, with processed Excel workbooks per experiment type. Molecular dynamics simulation code, coordinate files, and analysis scripts (NAMD/CHARMM/Python) for six atomistic cell wall models are included. Summarized ssNMR data are compiled into a single excel file and subjected to statistical analysis. Multivariate analysis code (PCA, Pearson correlation) and summary data are provided as excel worksheets and Jupyter notebooks (Python 3).
Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis
Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1 x Sex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.
Synthesis route attribution of sulfur mustard by multivariate data analysis of chemical signatures
A multivariate model was developed here to attribute samples to a synthetic method used in the production of sulfur mustard (HD). Eleven synthetic methods were used to produce 66 samples for model construction. Three chemists working in both participating laboratories took part in the production, with the aim to introduce variability while reducing the influence of laboratory or chemist specific impurities in multivariate analysis. A gas chromatographic/mass spectrometric data set of peak areas for 103 compounds was subjected to orthogonal partial least squares - discriminant analysis to extract chemical attribution signature profiles and to construct multivariate models for classification of samples. For one- and two-step routes, model quality allowed the classification of an external test set (16/16 samples) according to synthesis conditions in the reaction yielding sulfur mustard. Classification of samples according to first-step methodology was considerably more difficult, given the high purity and uniform quality of the intermediate thiodiglycol produced in the study. Model performance in classification of aged samples was also investigated.