Association of ABCB1, 5-HT3B receptor and CYP2D6 genetic polymorphisms with ondansetron and metoclopramide antiemetic response in Indonesian cancer patients treated with highly emetogenic chemotherapy.

Our study shows that in Indonesian cancer patients treated with highly cytostatic emetogenic, carriership of the CTG haplotype of the ABCB1 gene is related to an increased risk of delayed chemotherapy-induced nausea and vomiting

Proton Beam Energy Characterization

Introduction The Los Alamos Isotope Production Facility (IPF) is actively engaged in the development of isotope production technologies that can utilize its 100 MeV proton beam. Characterization of the proton beam energy and current is vital for optimizing isotope production and accurately conducting research at the IPF. Motivation In order to monitor beam intensity during research irradiations, aluminum foils are interspersed in experimental stacks. A theoretical yield of 22Na from 27Al(p,x)22Na reactions is cal-culated using MCNP6 (Monte Carlo N-Particle), TRIM (Transport of Ions in Matter), and Andersen & Ziegler (A&Z) [1] computational models. For some recent experiments, experimentally measured activities did not match computational predictions. This discrepancy motivated further experimental investigations including a direct time-of-flight measurement of the proton beam energy upstream of the target stack. The Isotope Production Program now tracks the beam energy and current by a complement of experimental and computational methods described below. Material and Methods A stacked-foil activation technique, utilizing aluminum monitor foils [2] in conjunction with a direct time-of-flight measurement helps define the current and energy of the proton beam. Theoretical yields of 22Na activity generated in the Al monitor foils are compared with experimental measurements. Additionally, MCNP, TRIM, and A&Z computational simulations are compared with one another and with experimental data. Experimental Approach Thin foils (0.254mm) of high purity aluminum are encapsulated in kapton tape and stacked with Tb foils in between aluminum degraders. Following irradiation, the Al foils are assayed using γ-spectroscopy on calibrated HPGe detectors in the Chemistry Division countroom at LANL. We use the well-characterized 27Al(p,x)22Na energy dependent production cross section [3] to calculate a predicted yield of 22Na in each foil. Details of the experimental activity determination and associated uncertainties have been addressed previously [4]. The nominally stated beam parameters are 100 MeV and 100–120 nA for the foil stack irradiation experiments. Time-of-flight measurements performed in the month of January 2014 revealed beam energy of 99.1 ± 0.5 MeV. Computational Simulations Andersen & Zeigler (A&Z) is a deterministic method and also the simplest of the three com-putational methods considered. While the mean energy degradation can be calculated using the A&Z formalism, the beam current attenuation cannot. Consequentially, A&Z will also lack the ability to account for a broadening in the beam energy that a stochastic method affords. Additionally, A&Z does not account for nuclear recoil or contributions from secondary interactions. TRIM uses a stochastic based method to calculate the stopping range of incident particles applying Bethe-Block formalisms. TRIM, like A&Z, does not include contributions from nuclear recoil or contributions from secondary interactions. Computationally, TRIM is a very expensive code to run. TRIM is able to calculate a broadening in the energy of the beam; however, beam attenuation predictions are much less reliable. TRIM determines the overall beam attenuation in the whole stack to be less than one percent, whereas 7–10 % is expected. MCNP6 is arguably the most sophisticated approach to modeling the physics of the experiment. It also uses a stochastic procedure for calculation, adopting the Cascade-Exciton Model (CEM03) to track particles. The physics card is enabled in the MCNP input to track light ion recoils. Contributions from neutron and proton secondary particle interactions are included, although their contribution is minimal. For both MCNP and TRIM, the proton beam is simulated as a pencil beam. To find the current, an F4 volumetric tally of proton flux from MCNP simulation is matched to the experimental current for the first foil in the stack. Subsequent foil currents are calculated relative to the first foil based on MCNP predictions for beam attenuation. The equation used for calculating the current from the experi-mental activity is [5]: where: is the cross section for the process, [mbarns] is the atomic mass of the target [amu] is the is the number of product nuclei pre-sent at End-of-Bombardment is the average beam current, [μA] is the density of the target material, [g/cc] is the target thickness, [cm] is the decay constant, [s−1] is the irradiation time, [s] For each foil in the experimental stack, we also have a statistically driven broadening of the incident energy. The beam energy is modeled as a Gaussian distribution, with the tallies for each energy bin determining the parameters of the fit. TABLE 1 and FIG. 3 summarize the mean energy and standard deviation of the energy for each aluminum monitor foil. To address the energy distribution, we calculate an effective or weighted cross-section. It is especially important to account for energy broadening in regions where the associated excitation function varies rapidly. In the excitation function, we see a strong variation in the energy range from 30–65 MeV, the energy region cov-ered by the last 3 foils in the stack. Cross section weighting also accounts for the mean energy variation within each foil. The excitation function will overlay the Gaussian shaped flux distribution, giving rise to a lateral distribution where incrementally weighted values of the cross section are determined by the flux tally of the corresponding energy bin. With the effective cross section and the current at each of the foils, it is straight-forward to calculate the number of 22Na atoms created and the activity of each foil using the previously stated equation. Results and Conclusion The general trend in the amount of activity produced follows the shape of the excitation func-tion for the 27Al(p,x)22Na reaction. Small shifts in the incident energy upstream trickle down to produce much more pronounced shifts in the energy range of foils towards the back of the foil stack. The characteristic “rolling over” of the activity seen in the experimental foils indicates that the 6th foil must be in the energy region below 45 MeV, where the peak of the excitation function occurs. Conservatively, computational simulations are able to accurately determine the proton beam’s energy for an energy range from 100 to 50 MeV. As the beam degrades below 50 MeV, computa-tional simulations diverge from experimentally observed energies by over-predicting the energy. This observation has been noted in past studies [6,7] that compare the stacked foil technique with stopping-power based calculations. A complement of experimental and computational predictions allows for energy determinations at several points within target stacks. While this study focuses on an Al-Tb foil stack, the analysis of a similar Al-Th foil stack resulted in the same conclusions. Although we do not have a concurrent time-of-flight energy measurement at the time of the foil stack experiments, it is reasonable to assume that the energy at the time of the stacked foil experiments was also lower than the assumed energy of 100 MeV. Computational simulations developed in this work firmly support this assumption. Various computational models are able to predict with good agreement the energy as a function of depth for complex foil stack geometries. Their predictions diverge as the beam energy distribution broadens and statistical uncertainties propagate. A careful inspection of the codes reveals that these discrepancies likely originate from minute differences between the cross sections and stopping power tables that MCNP and TRIM/A&Z use respectively

Initial high anti-emetic efficacy of granisetron with dexamethasone is not maintained over repeated cycles.

We have reported previously that the anti-emetic efficacy of single agent 5HT3 antagonists is not maintained when analysed with the measurement of cumulative probabilities. Presently, the most effective anti-emetic regimen is a combination of a 5HT3 antagonist plus dexamethasone. We, therefore, assessed the sustainment of efficacy of such a combination in 125 patients, scheduled to receive cisplatin > or = 70 mg m(-2) either alone or in combination with other cytotoxic drugs. Anti-emetic therapy was initiated with 10 mg of dexamethasone and 3 mg of granisetron intravenously, before cisplatin. On days 1-6, patients received 8 mg of dexamethasone and 1 mg of granisetron twice daily by oral administration. Protection was assessed during all cycles and calculated based on cumulative probability analyses using the method of Kaplan-Meier and a model for transitional probabilities. Irrespective of the type of analysis used, the anti-emetic efficacy of granisetron/dexamethasone decreased over cycles. The initial complete acute emesis protection rate of 66% decreased to 30% according to the method of Kaplan-Meier and to 39% using the model for transitional probabilities. For delayed emesis, the initial complete protection rate of 52% decreased to 21% (Kaplan-Meier) and to 43% (transitional probabilities). In addition, we observed that protection failure in the delayed emesis period adversely influenced the acute emesis protection in the next cycle. We conclude that the anti-emetic efficacy of a 5HT3 antagonist plus dexamethasone is not maintained over multiple cycles of highly emetogenic chemotherapy, and that the acute emesis protection is adversely influenced by protection failure in the delayed emesis phase

A phase II study of raltitrexed and gemcitabine in patients with advanced pancreatic carcinoma

Advanced adenocarcinoma of the pancreas has a very poor prognosis. The aim of this study was to assess the efficacy and tolerability of a combination of the chemotherapeutic agents gemcitabine and raltitrexed. Chemonaïve patients with advanced adenocarcinoma of the pancreas were treated with a combination of raltitrexed (3.5 mg m−2 on day 1 of a 21-day treatment cycle) and gemcitabine (800 mg m−2 intravenously (i.v.) on days 1 and 8 of a 21-day cycle). Between April 2000 and February 2003, 27 patients were enrolled onto the study. The mean duration of treatment was 11 weeks. Four of 27 patients experienced at least one episode of grade 3 or 4 neutropenia. One patient with grade 4 neutropenia died due to sepsis. Four of 27 patients experienced grade 4 diarrhoea. There was one partial remission (4%) and 12 patients experienced disease stabilisation (44%). The 6-month and 1-year survival rates were 37 and 11%, respectively. Symptomatic benefit occurred in seven (26%) patients. We conclude that a combination of raltitrexed and gemcitabine, using the schedule and doses in this study, cannot be recommended for patients with advanced pancreatic cancer

Assumptions behind grammatical approaches to code-switching: when the blueprint is a red herring

Many of the so-called ‘grammars’ of code-switching are based on various underlying assumptions, e.g. that informal speech can be adequately or appropriately described in terms of ‘‘grammar’’; that deep, rather than surface, structures are involved in code-switching; that one ‘language’ is the ‘base’ or ‘matrix’; and that constraints derived from existing data are universal and predictive. We question these assumptions on several grounds. First, ‘grammar’ is arguably distinct from the processes driving speech production. Second, the role of grammar is mediated by the variable, poly-idiolectal repertoires of bilingual speakers. Third, in many instances of CS the notion of a ‘base’ system is either irrelevant, or fails to explain the facts. Fourth, sociolinguistic factors frequently override ‘grammatical’ factors, as evidence from the same language pairs in different settings has shown. No principles proposed to date account for all the facts, and it seems unlikely that ‘grammar’, as conventionally conceived, can provide definitive answers. We conclude that rather than seeking universal, predictive grammatical rules, research on CS should focus on the variability of bilingual grammars