Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

NRAS and BRAF mutations in primary cutaneous melanoma: A comparison of mutation rates between radial and vertical growth phases in individual tumors

Primary cutaneous melanoma is a cancer arising from melanocytes in the skin. In recent decades the incidence of this malignancy has increased significantly. Mortality rates are high for patients with tumors measuring over a few millimeters in thickness. Response rates to conventional radiation and chemotherapy are very low in patients with metastatic melanoma. New therapies targeting melanoma’s aberrant cell signaling pathways such as the MAP Kinase pathway are being developed. Mutations of NRAS and BRAF genes are quite common in cutaneous melanoma and lead to constitutive activation of the MAP Kinase pathway. This study tests the hypothesis that NRAS and BRAF mutations increase as a tumor progresses from the noninvasive radial growth phase (RGP) to the invasive vertical growth phase (VGP). Laser capture microdissection was used to obtain separate, pure tumor DNA samples from the RGP and VGP of thirty primary cutaneous melanomas. PCR was used to amplify NRAS exon 2 and BRAF exon 15 tumor DNA. The amplified DNA was sequenced and analyzed for mutations. An overall mutation rate of 74% was obtained for the twenty-three melanomas in which there were complete sequence results. With the exception of one melanoma NRAS and BRAF mutations were mutually exclusive. All seven NRAS exon 2 mutations involved codon 61. Three of these melanomas had mutations in both the RGP and VGP. The remaining four tumors were wild type for NRAS exon 2 in the RGP but mutated in the VGP. Of the fifteen BRAF exon 15 mutated melanomas all but one involved codon 600. Twelve of the fifteen BRAF exon 15 mutations were the T1799A type. Nine of the fifteen BRAF mutated tumors had the same mutation in both the RGP and VGP. Five of fifteen melanomas had wild type RGP DNA and BRAF exon 15 mutated VGP DNA. A single melanoma had BRAF exon 15 mutated DNA in the RGP and wild type DNA in the VGP. Overall, these results suggest a trend toward the acquisition of NRAS and BRAF mutations as cutaneous melanomas change from a noninvasive to an invasive, potentially deadly cancer.^

STUDIES ON CHOLINERGIC FUNCTION AND MEMORY IN MICE (CHOLINOTOXINS, WORKING, REFERENCE MEMORY, RADIAL ARM MAZE)

Considerable evidence suggests that central cholinergic neurons participate in either acquisition, storage or retrieval of information. Experiments were designed to evaluate information processing in mice following either reversible or irreversible impairment in central cholinergic activity. The cholinergic receptor antagonists, atropine and methylatropine were used to reversibly inhibit cholinergic transmission. Irreversible impairment in central cholinergic function was achieved by central administration of the cholinergic-specific neurotoxins, N-ethyl-choline aziridinium (ECA) and N-ethyl-acetylcholine aziridinium (EACA).^ ECA and EACA appear to act by irreversible inhibition of high affinity choline uptake (proposed rate-limiting step in acetylcholine synthesis). Intraventricular administration of ECA or EACA produced persistent reduction in hippocampal choline acetyltransferase activity. Other neuronal systems and brain regions showed no evidence of toxicity.^ Mice treated with either ECA or EACA showed behavioral deficits associated with cholinergic dysfunction. Passive avoidance behavior was significantly impaired by cholinotoxin treatment. Radial arm maze performance was also significantly impaired in cholinotoxin-treated animals. Deficits in radial arm maze performance were transient, however, such that rapid and apparent complete behavioral recovery was seen during retention testing. The centrally active cholinergic receptor antagonist atropine also caused significant impairment in radial arm maze behavior, while equivalent doses of methylatropine were without effect.^ The relative effects of cholinotoxin and receptor antagonist treatment on short-term (working) memory and long-term (reference) memory in radial arm maze behavior were examined. Maze rotation studies indicated that there were at least two different response strategies which could result in accurate maze performance. One strategy involved the use of response algorithms and was considered to be a function of reference memory. Another strategy appeared to be primarily dependent on spatial working memory. However, all behavioral paradigms with multiple trails have reference memory requirements (i.e. information useful over all trials). Performance was similarly affected following either cholinotoxin or anticholinergic treatment, regardless of the response strategy utilized. In addition, rates of behavioral recovery following cholinotoxin treatment were similar between response groups. It was concluded that both cholinotoxin and anticholinergic treatment primarily resulted in impaired reference memory processes. ^

EVALUATION OF THE EFFECTIVENESS OF ANISOTROPIC ANALYTICAL ALGORITHM IN FLATTENED AND FLATTENING-FILTER-FREE BEAMS FOR HIGH ENERGY LUNG DOSE DELIVERY USING THE RADIOLOGICAL PHYSICS CENTER LUNG PHANTOM

The effectiveness of the Anisotropic Analytical Algorithm (AAA) implemented in the Eclipse treatment planning system (TPS) was evaluated using theRadiologicalPhysicsCenteranthropomorphic lung phantom using both flattened and flattening-filter-free high energy beams. Radiation treatment plans were developed following the Radiation Therapy Oncology Group and theRadiologicalPhysicsCenterguidelines for lung treatment using Stereotactic Radiation Body Therapy. The tumor was covered such that at least 95% of Planning Target Volume (PTV) received 100% of the prescribed dose while ensuring that normal tissue constraints were followed as well. Calculated doses were exported from the Eclipse TPS and compared with the experimental data as measured using thermoluminescence detectors (TLD) and radiochromic films that were placed inside the phantom. The results demonstrate that the AAA superposition-convolution algorithm is able to calculate SBRT treatment plans with all clinically used photon beams in the range from 6 MV to 18 MV. The measured dose distribution showed a good agreement with the calculated distribution using clinically acceptable criteria of ±5% dose or 3mm distance to agreement. These results show that in a heterogeneous environment a 3D pencil beam superposition-convolution algorithms with Monte Carlo pre-calculated scatter kernels, such as AAA, are able to reliably calculate dose, accounting for increased lateral scattering due to the loss of electronic equilibrium in low density medium. The data for high energy plans (15 MV and 18 MV) showed very good tumor coverage in contrast to findings by other investigators for less sophisticated dose calculation algorithms, which demonstrated less than expected tumor doses and generally worse tumor coverage for high energy plans compared to 6MV plans. This demonstrates that the modern superposition-convolution AAA algorithm is a significant improvement over previous algorithms and is able to calculate doses accurately for SBRT treatment plans in the highly heterogeneous environment of the thorax for both lower (≤12 MV) and higher (greater than 12 MV) beam energies.