Low-risk persistent gestational trophoblastic disease treated with low-dose methotrexate: efficacy, acute and long-term effects

The aim of this study was to evaluate the efficacy and toxicity of low-dose methotrexate with folinic acid rescue in a large series of consecutively treated patients with low-risk persistent gestational trophoblastic disease. Between January 1987 and December 2000, 250 patients were treated with intramuscular methotrexate (50 mg on alternate days 1, 3, 5, 7) with folinic acid (7.5 mg orally on alternate days 2, 4, 6, 8) rescue. The overall complete response rate without recurrence was 72% for first-line treatment and 95% for those who required second-line chemotherapy. Eight women (3.2%) had recurrence following remission and two (0.8%) had new moles. Two women (0.8%) died of their disease giving an overall cure of 99%. Only 10 women (4%) experienced grade III/IV toxicity during the first course of treatment and 13 women (5.2%) subsequently. Toxicity included mucositis and stomatitis, pleuritic chest pain, thrombocytopenia, uterine bleeding, abdominal pain, liver function changes, rash and pericardial effusion. A total of 59 women (23.6%) required second-line chemotherapy; 48 women had methotrexate resistance, eight had methotrexate toxicity and an empirical decision to change therapy was made in three. In all, 11 women (4.4%) had a hysterectomy before, during or after treatment; 141 women (56.4%) became pregnant following treatment: in 128 (90.7%), the outcome was successful. Methotrexate with folinic acid rescue is an effective treatment for low-risk persistent trophoblastic disease. It has minimal severe toxicity, excellent cure rates and does not appear to affect fertility

Pulse polarization for Li-ion battery under constant state of charge

Thesis (Ph. D.)--University of Rochester. Department of Chemical Engineering, 2016.Daily human life has become increasingly reliant on energy storage technology, with an increasing use of batteries for energy or power applications. In energy batteries, current is supplied at a relatively low constant rate over a long time, while power batteries deliver high current for short durations or bursts. Energy batteries are used in laptop and cell phone applications, while power batteries are used in electric vehicles, where bursts of high power are needed during acceleration, regenerative braking, and up hill driving. Energy batteries contain a high amount of active material (thicker paste) per unit area, while power batteries contain less active material (thinner paste). Additionally, voltage relaxation is an important consideration in power batteries, but not in energy batteries. Given this increased dependence on battery-powered devices, it is necessary to develop new and robust methods to evaluate and predict battery performance. Since Li-Ion batteries are unsteady state systems, there is a need to evaluate performance under constant state of charge (SOC). The purpose of this thesis was to develop and construct pulse polarization curves (PPC) for a Li-Ion battery (power) under constant SOC in order to analyze individual overvoltages and SOC dependence. The development of the PPC will facilitate the investigation of not only individual overvoltages, such as charge transfer kinetic and mass transport, but overall performance dependence on SOC. The effect of the SOC on pulse discharge and relaxation is of importance as it reveals the performance of a power battery during various stages of the battery discharge. Consequently, we elected to conduct pulse discharges at various duration and discharge current densities, all under well maintained SOC. Based on the results we modeled the pulse discharges which allows us to predict performance of power batteries and construct PPCs for the modeled battery. An important consideration was that as the battery’s SOC changes, the open circuit voltage (OCV) also changes. Therefore, the pulse discharge method we used needed to end at the same SOC in all cases to enable creation of a PPC with the same OCV. To ensure that this method applied to various sizes and chemistries of batteries reliably, we ran pulse discharge experiments on a high Amp hour (15Ah) large electrode pouch battery (power) that used a NMC LMO cathode, as well as on a low Amp hour (0.04Ah) small electrode coin battery (energy) with a CoO2 cathode. The pulse discharges were also simulated using a computer model, allowing the determination of battery performance and its individual overpotentials, a tedious and difficult experimental task. We adapted the Multiphysics COMSOL 3.5a Li-Ion battery model to predict battery performance and individual overpotentials for the large (15Ah) Li-Ion battery. We fit the model to our experimental data using the diffusion and charge transfer kinetic rate constant parameters for both the positive and negative electrodes. Once optimized, these four parameters remained constant for all simulations. The model predicted PPCs are consistent with our experimental PPCs. The simulated PPCs were used to identify the relative magnitudes of individual overpotentials of each electrode and electrolyte including: charge transfer kinetic, electrolyte Li+ mass transport, and Li solidstate diffusion, under various SOC conditions and pulse times. Furthermore, the application of the model to longer pulse durations (240 s) allowed us to construct steady state PPCs under various SOC conditions. It was found that OCV and battery performance depends on SOC. To improve the accuracy of our model, we measured tortuosity (5.95 and 3.47) and porosity (28.5% and 21.5%) of the graphite and Li oxide electrodes, respectively, utilizing a gas diffusion method. This method involved measuring the electrode porosity using the standard method of porosimetry. The tortuosity was determined from measuring the electrode MacMullin number, a ratio of the tortuosity and porosity of a porous medium. These measurements were incorporated into the electrode parameters of the computer model in order to improve its accuracy and reduce reliance on first-order calculated parameters. Our model successfully predicted battery performance across a wide range of conditions, including various SOCs, current densities, and discharge times, and generated steady state polarization curves under constant SOC. The pulse discharge method we utilized represents a significant step forward in providing an experimental method to verify individual overvoltages. Both model predictions and experimental results showed an inverse, nonlinear relationship between voltage loss and SOC at a given pulse discharge time and current. Utilizing the pulse discharge method with model analysis to create PPCs will provide industry with a robust performance measurement tool and an accurate method to predict SOC. These tools are necessary to ensure batteries are able to safely satisfy the power and energy requirements needed for innovative devices in the future, such as electric cars and beyond

Changes in clinical measures of autonomic nervous system function related to cancer chemotherapy-induced nausea

Individual cancer patients differ in their nausea/vomiting response to chemotherapy. It is not known why patients receiving the same chemotherapy have different severity of side effects. Several lines of research implicate the autonomic nervous system (ANS) in the development of chemotherapy-induced nausea. We examined the association between autonomic reactivity and the level of nausea experienced following chemotherapy in 20 patients with ovarian cancer treated with cisplatin or carboplatin who received the same antiemetic. We applied eight common non-invasive clinical tests of autonomic function prior to inpatient chemotherapy treatment, 2 h after treatment and again 24 h following treatment. Two hours after chemotherapy and before any nausea was reported by the patients, the nine patients who subsequently experienced high levels of nausea had a greater overall percentage of abnormal clinical ANS tests than the 11 patients who subsequently developed low levels of nausea ( P<0.01). Twenty-four hours after treatment, the overall number of abnormal autonomic tests remained non-significantly higher than at the pretreatment baseline for the high nausea group. Demographic and clinical characteristics were not related to chemotherapy-induced nausea in this sample. Autonomic reactivity appears to be related to the development of nausea following chemotherapy. Further investigation of ANS involvement in chemotherapy-induced nausea could increase understanding of nausea etiology and potentially lead to the prediction of susceptible patients