Two-dimensional linear-combination model fitting of magnetic resonance spectra to define the macromolecule baseline using FiTAID, a Fitting Tool for Arrays of Interrelated Datasets

To propose the determination of the macromolecular baseline (MMBL) in clinical 1H MR spectra based on T(1) and T(2) differentiation using 2D fitting in FiTAID, a general Fitting Tool for Arrays of Interrelated Datasets.

Pathology hinting as the combination of automatic segmentation with a statistical shape model

With improvements in acquisition speed and quality, the amount of medical image data to be screened by clinicians is starting to become challenging in the daily clinical practice. To quickly visualize and find abnormalities in medical images, we propose a new method combining segmentation algorithms with statistical shape models. A statistical shape model built from a healthy population will have a close fit in healthy regions. The model will however not fit to morphological abnormalities often present in the areas of pathologies. Using the residual fitting error of the statistical shape model, pathologies can be visualized very quickly. This idea is applied to finding drusen in the retinal pigment epithelium (RPE) of optical coherence tomography (OCT) volumes. A segmentation technique able to accurately segment drusen in patients with age-related macular degeneration (AMD) is applied. The segmentation is then analyzed with a statistical shape model to visualize potentially pathological areas. An extensive evaluation is performed to validate the segmentation algorithm, as well as the quality and sensitivity of the hinting system. Most of the drusen with a height of 85.5 microm were detected, and all drusen at least 93.6 microm high were detected.

Efficacy of gatifloxacin alone and in combination with cefepime against penicillin-resistant Streptococcus pneumoniae in a rabbit meningitis model and in vitro

Gatifloxacin penetrated well into cerebrospinal fluid (CSF) (49 +/- 11%), measured by comparison of AUC(CSF)/AUC(serum), and showed good bactericidal activity (leading to a decrease of 0.75 +/- 0.17 log10 cfu/mL/h) in the treatment of experimental meningitis in rabbits caused by a penicillin-resistant pneumococcal strain (MIC 4 mg/L). It was significantly more effective than the standard regimen, ceftriaxone with vancomycin, which led to a decrease of 0.53 +/- 0.17 log10 cfu/mL/h. The addition of cefepime to gatifloxacin slightly improved the killing rates (giving a decrease of 0.84 +/- 0.14 log10 cfu/mL/h). In vitro, synergy was demonstrated between cefepime and gatifloxacin by the chequerboard method (fractional inhibitory concentration index = 0.5) and by viable counts over 8 h.

Evaluation of cefepime alone and in combination with vancomycin against penicillin-resistant pneumococci in the rabbit meningitis model and in vitro

Cefepime, a broad-spectrum, fourth-generation cephalosporin, showed excellent CSF penetration with levels ranging between 10 and 16 mg/L after two intravenous injections (100 mg/kg). The bactericidal activity of cefepime (-0.60 +/- 0.28 Deltalog(10) cfu/mL/h) was superior to that of ceftriaxone (-0.34 +/- 0.23 Deltalog(10) cfu/mL/h, P < 0.05) and vancomycin (-0.39 +/- 0.19 Deltalog(10) cfu/mL/h, P < 0.05) in the treatment of rabbits with meningitis caused by an isolate highly resistant to penicillin (MIC of penicillin G: 4 mg/L). The addition of vancomycin to both cephalosporins did not significantly increase the killing rate compared with monotherapies (P > 0.05). Similar results were obtained in time-killing experiments in vitro.

Trovafloxacin in combination with vancomycin against penicillin-resistant pneumococci in the rabbit meningitis model

Trovafloxacin, a new fluoroquinolone, produced bactericidal activity (-0.33 +/- 0.13 delta log10 CFU/ml.h; intravenously [i.v.] administered dose, 15 mg/kg) comparable to that of vancomycin (-0.39 +/- 0.18 delta log10 CFU/ml.h; i.v. admininistered dose, 20 mg/kg) in the treatment of experimental meningitis in rabbits due to a pneumococcal strain highly resistant to penicillin (MIC of penicillin G, 4 micrograms/ml). The combination of both drugs significantly increased (P < 0.05) the killing rate (-0.60 +/- 0.23 delta log10 CFU/ml.h) compared to that produced by either monotherapy. These results were also confirmed in vitro.

Inhibition of mTOR in combination with doxorubicin in an experimental model of hepatocellular carcinoma

BACKGROUND/AIMS: Hepatocellular carcinoma (HCC) is resistant to chemotherapy. We reported that sirolimus, an mTOR inhibitor, has antiangiogenic properties in HCC. Since antiangiogenic therapy may enhance chemotherapy effects, we tested the antitumorigenic properties of sirolimus combined with doxorubicin in experimental HCC. METHODS: Morris Hepatoma (MH) cells were implanted into livers of syngeneic rats. Animals were assigned to sirolimus, pegylated liposomal doxorubicin, both combined or control groups. Tumoral growth was followed by MRI. Antiangiogenic effects were assessed by CD31 immunostaining and capillary tube formation assays. Cell proliferation was monitored in vitro by thymidine incorporation. Expression of p21 and phosphorylated MAPKAP kinase-2 was quantified by immunoblotting. RESULTS: Animals treated with the combination developed smaller tumors with decreased tumor microvessel density compared to animals that received monotherapies. In vitro, inhibition of mTOR further impaired capillary formation in the presence of doxorubicin. Doxorubicin reduced endothelial cell proliferation; inhibition of mTOR accentuated this effect. Doxorubicin stimulated p21 expression and the phosphorylation of MAPKAP kinase-2 in endothelial cells. Addition of mTOR inhibitor down-regulated p21, but did not decrease MAPKAP kinase-2 phosphorylation. CONCLUSIONS: Sirolimus has additive antitumoral and antiangiogenic effects when administered with doxorubicin. These findings offer a rationale for combining mTOR inhibitors with chemotherapy in HCC treatment.

Quantitative 1H-magnetic resonance spectroscopy of human brain: Influence of composition and parameterization of the basis set in linear combination model-fitting

Localized short-echo-time (1)H-MR spectra of human brain contain contributions of many low-molecular-weight metabolites and baseline contributions of macromolecules. Two approaches to model such spectra are compared and the data acquisition sequence, optimized for reproducibility, is presented. Modeling relies on prior knowledge constraints and linear combination of metabolite spectra. Investigated was what can be gained by basis parameterization, i.e., description of basis spectra as sums of parametric lineshapes. Effects of basis composition and addition of experimentally measured macromolecular baselines were investigated also. Both fitting methods yielded quantitatively similar values, model deviations, error estimates, and reproducibility in the evaluation of 64 spectra of human gray and white matter from 40 subjects. Major advantages of parameterized basis functions are the possibilities to evaluate fitting parameters separately, to treat subgroup spectra as independent moieties, and to incorporate deviations from straightforward metabolite models. It was found that most of the 22 basis metabolites used may provide meaningful data when comparing patient cohorts. In individual spectra, sums of closely related metabolites are often more meaningful. Inclusion of a macromolecular basis component leads to relatively small, but significantly different tissue content for most metabolites. It provides a means to quantitate baseline contributions that may contain crucial clinical information.

A model-based approach for assessing in vivo combination therapy interactions

We present an approach for evaluating the efficacy of combination antitumor agent schedules that accounts for order and timing of drug administration. Our model-based approach compares in vivo tumor volume data over a time course and offers a quantitative definition for additivity of drug effects, relative to which synergism and antagonism are interpreted. We begin by fitting data from individual mice receiving at most one drug to a differential equation tumor growth/drug effect model and combine individual parameter estimates to obtain population statistics. Using two null hypotheses: (i) combination therapy is consistent with additivity or (ii) combination therapy is equivalent to treating with the more effective single agent alone, we compute predicted tumor growth trajectories and their distribution for combination treated animals. We illustrate this approach by comparing entire observed and expected tumor volume trajectories for a data set in which HER-2/neu-overexpressing MCF-7 human breast cancer xenografts are treated with a humanized, anti-HER-2 monoclonal antibody (rhuMAb HER-2), doxorubicin, or one of five proposed combination therapy schedules.

Functional-structural plant modelling using a combination of architectural analysis, L-systems and a canonical model of function

This paper presents a new method for producing a functional-structural plant model that simulates response to different growth conditions, yet does not require detailed knowledge of underlying physiology. The example used to present this method is the modelling of the mountain birch tree. This new functional-structural modelling approach is based on linking an L-system representation of the dynamic structure of the plant with a canonical mathematical model of plant function. Growth indicated by the canonical model is allocated to the structural model according to probabilistic growth rules, such as rules for the placement and length of new shoots, which were derived from an analysis of architectural data. The main advantage of the approach is that it is relatively simple compared to the prevalent process-based functional-structural plant models and does not require a detailed understanding of underlying physiological processes, yet it is able to capture important aspects of plant function and adaptability, unlike simple empirical models. This approach, combining canonical modelling, architectural analysis and L-systems, thus fills the important role of providing an intermediate level of abstraction between the two extremes of deeply mechanistic process-based modelling and purely empirical modelling. We also investigated the relative importance of various aspects of this integrated modelling approach by analysing the sensitivity of the standard birch model to a number of variations in its parameters, functions and algorithms. The results show that using light as the sole factor determining the structural location of new growth gives satisfactory results. Including the influence of additional regulating factors made little difference to global characteristics of the emergent architecture. Changing the form of the probability functions and using alternative methods for choosing the sites of new growth also had little effect. (c) 2004 Elsevier B.V. All rights reserved.

Personal knowledge development in online learning:a model for measuring externalisation, combination and internalisation

This paper presents a model for measuring personal knowledge development in online learning environments. It is based on Nonaka‘s SECI model of organisational knowledge creation. It is argued that Socialisation is not a relevant mode in the context of online learning and was therefore not covered in the measurement instrument. Therefore, the remaining three of SECI‘s knowledge conversion modes, namely Externalisation, Combination, and Internalisation were used and a measurement instrument was created which also examines the interrelationships between the three modes. Data was collected using an online survey, in which online learners report on their experiences of personal knowledge development in online learning environments. In other words, the instrument measures the magnitude of online learners‘ Externalisation and combination activities as well as their level of internalisation, which is the outcome of their personal knowledge development in online learning.

Prostatic Angiogenic Responses In Late Life: Antiangiogenic Therapy Influences And Relation With The Glandular Microenvironment In The Transgenic Adenocarcinoma Of Mouse Prostate (tramp) Model.

Aging is considered one of the main predisposing factors for the development of prostate malignancies. Angiogenesis is fundamental for tumor growth and its inhibition represents a promising therapeutic approach in cancer treatment. Thus, we sought to determine angiogenic responses and the effects of antiangiogenic therapy in the mouse prostate during late life, comparing these findings with the prostatic microenvironment in the Transgenic Adenocarcinoma of Mouse Prostate (TRAMP) model. Male mice (52 week-old FVB) were submitted to treatments with SU5416 (6 mg/kg; i.p.) and/or TNP-470 (15 mg/kg; s.c.). Finasteride was administered (20 mg/kg; s.c.), alone or in association to both inhibitors. The dorsolateral prostate was collected for VEGF, HIF-1α, FGF-2 and endostatin immunohistochemical and Western Blotting analyses and for microvessel density (MVD) count. Senescence led to increased MVD and VEGF, HIF-1α and FGF-2 protein levels in the prostatic microenvironment, similarly to what was observed in TRAMP mice prostate. The angiogenic process was impaired in all the treated groups, demonstrating significantly decreased MVD. Antiangiogenic and/or finasteride treatments resulted in decreased VEGF and HIF-1α levels, especially following TNP-470 administration, either alone or associated to SU5416. The combination of these agents resulted in increased endostatin levels, regardless of the presence of finasteride. Prostatic angiogenesis stimulation during senescence favored the development of neoplastic lesions, considering the pro-angiogenic microenvironment as a common aspect also observed during cancer progression in TRAMP mice. The combined antiangiogenic therapy was more efficient, leading to enhanced imbalance towards angiogenic inhibition in the organ. Finally, finasteride administration might secondarily upregulate the expression of pro-angiogenic factors, pointing to the harmful effects of this therapy. Prostate 75: 484-499, 2015. © 2014 Wiley Periodicals, Inc.