593 research outputs found
Magnetic Resonance Imaging for Monitoring Irreversible Electroporation of Hepatocellular Carcinoma
Hepatocellular carcinoma (HCC) is the 6th most common neoplasm worldwidely and is 4th leading cause of cancer death in United States. It is estimated that there will be 30,640 new cases diagnosed and 21,670 deaths due to this disease in the United States in 2013. Irreversible electroporation (IRE) is a novel tumor ablation modality which involves applying external electrical field to induce cell death through increasing cell membrane permeability. Compared to conventional thermal ablation methods, IRE has demonstrated multiple potential benefits as a tumor ablation modality. However, further pre-clinical validation in liver tumor animal models is warranted prior to clinical translation for the treatment of HCC and intra-procedural imaging techniques will be critical to permit ‘patient-specific’ optimization of these IRE procedures. In this dissertation, a Magnetic resonance imaging (MRI) monitoring method was developed to assess immediate response to IRE. Imaging characteristics after ablation were evaluated in normal liver ad tumor tissues. A MRI-based pre-procedural finite element method was developed to predict IRE ablation zone and applied in a liver tumor model. MRI-based ablation zone was measured and correlated with histology-confirmed ablation zone. Finally, diffusion-weighted MRI was performed before and after IRE and the corresponding apparent diffusion coefficient map was measured to investigate the cell membrane change due to electroporation
Optimal Dose Allocation Considering Toxicity and Efficacy Jointly in Phase I/II Dose Finding Studies
Novel anticancer therapies are challenging the standards of drug development in Phase I dose-finding studies. Agents with specific biologic targets, unknown dose-efficacy trends, and limited toxicity motivate innovative designs to identify optimal biological dose (OBD), the dose jointly defined by toxicity and efficacy probabilities. In this thesis, a novel design to identify OBD is developed by combining optimal design theory with the continual reassessment method (CRM). The optimal design theory is implemented based on the continuation ratio model and straightforward OBD selection criteria. To better fit practical needs, the new design is progressed to identify adjusted-OBD with modified criteria. The possible candidates of OBD and adjusted-OBD are proposed. The C-optimal designs or variance functions of all candidates of both OBD and adjusted-OBD are demonstrated. Our simulation studies show that, under a wide range of dose-outcome scenarios compared to Isotonic, L-logistic, Logistic, EffTox and TriCRM, the proposed design has high probabilities in correctly recommending OBD when the assumed model is true. Under extensive settings of adjusted-OBD identification, our design keeps its outstanding performance in correctly recommending adjusted-OBD compared with TriCRM
Dynamic latent trait models with mixed hidden Markov structure for mixed longitudinal outcomes
<div><p>We propose a general Bayesian joint modeling approach to model mixed longitudinal outcomes from the exponential family for taking into account any differential misclassification that may exist among categorical outcomes. Under this framework, outcomes observed without measurement error are related to latent trait variables through generalized linear mixed effect models. The misclassified outcomes are related to the latent class variables, which represent unobserved real states, using mixed hidden Markov models (MHMMs). In addition to enabling the estimation of parameters in prevalence, transition and misclassification probabilities, MHMMs capture cluster level heterogeneity. A transition modeling structure allows the latent trait and latent class variables to depend on observed predictors at the same time period and also on latent trait and latent class variables at previous time periods for each individual. Simulation studies are conducted to make comparisons with traditional models in order to illustrate the gains from the proposed approach. The new approach is applied to data from the Southern California Children Health Study to jointly model questionnaire-based asthma state and multiple lung function measurements in order to gain better insight about the underlying biological mechanism that governs the inter-relationship between asthma state and lung function development.</p></div
Optimal strategy for VAC system in metro station of small and medium size city
This paper was reviewed and accepted by the APCWE-IX Programme Committee for Presentation at the 9th Asia-Pacific Conference on Wind Engineering, University of Auckland, Auckland, New Zealand, held from 3-7 December 2017
Yield and Gel Strength of Gelatin Extracted from Smoked Salmon (S<i>almo salar</i>) Skins
<p>The gelatin yield and gel strength of gelatin extracted from the skins of smoked salmon were determined. The skins had a crude protein content of 43.5 ± 1.2% and an estimated collagen content of 23.6 ± 1.0%. Following an alkali extraction process under varying extraction conditions, the protein content varied from 2.78% to 32.1%, and the gelatin yield ranged from 2.23% to 22.4% of the initial skin weight. The gelatin purity (gelatin/protein) ranged from 55.4% to 100%, with the highest Hyp/protein sample arbitrarily designated as being 100% pure, i.e., an assumption of pure gelatin. Statistical analysis showed that HCl concentration, pretreatment temperature, and extraction temperature significantly affected the protein yield and gelatin yield. The wide range of gel strengths indicates that the gelatin might have been hydrolyzed to different extents during the different extraction and cooling processes. Statistical analysis did not show that any of the factors studied affected the gel strength. However, the data indicated that low NaOH concentrations and HCl concentrations might not prevent hydrolysis during the extraction process. Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS–PAGE) showed that the gelatins contained α- and β-chains and that the gelatins composed of higher concentrations of larger molecular weight polypeptide chains had higher gel strengths.</p
Additional file 1 of Whole-genome sequencing and functional annotation of pathogenic Paraconiothyrium brasiliense causing human cellulitis
Additional file 1: Table S1. KEGG functional annotation of P. brasiliense GGX 41
Additional file 2 of Whole-genome sequencing and functional annotation of pathogenic Paraconiothyrium brasiliense causing human cellulitis
Additional file 2: Table S2. The secretome of P. brasiliense GGX 41
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