Towards Optimal Testing of Auditory Memory : Methodological development of recording of the mismatch negativity (MMN) of the auditory event-related potential (ERP)

The overlapping sound pressure waves that enter our brain via the ears and auditory nerves must be organized into a coherent percept. Modelling the regularities of the auditory environment and detecting unexpected changes in these regularities, even in the absence of attention, is a necessary prerequisite for orientating towards significant information as well as speech perception and communication, for instance. The processing of auditory information, in particular the detection of changes in the regularities of the auditory input, gives rise to neural activity in the brain that is seen as a mismatch negativity (MMN) response of the event-related potential (ERP) recorded by electroencephalography (EEG). --- As the recording of MMN requires neither a subject s behavioural response nor attention towards the sounds, it can be done even with subjects with problems in communicating or difficulties in performing a discrimination task, for example, from aphasic and comatose patients, newborns, and even fetuses. Thus with MMN one can follow the evolution of central auditory processing from the very early, often critical stages of development, and also in subjects who cannot be examined with the more traditional behavioural measures of auditory discrimination. Indeed, recent studies show that central auditory processing, as indicated by MMN, is affected in different clinical populations, such as schizophrenics, as well as during normal aging and abnormal childhood development. Moreover, the processing of auditory information can be selectively impaired for certain auditory attributes (e.g., sound duration, frequency) and can also depend on the context of the sound changes (e.g., speech or non-speech). Although its advantages over behavioral measures are undeniable, a major obstacle to the larger-scale routine use of the MMN method, especially in clinical settings, is the relatively long duration of its measurement. Typically, approximately 15 minutes of recording time is needed for measuring the MMN for a single auditory attribute. Recording a complete central auditory processing profile consisting of several auditory attributes would thus require from one hour to several hours. In this research, I have contributed to the development of new fast multi-attribute MMN recording paradigms in which several types and magnitudes of sound changes are presented in both speech and non-speech contexts in order to obtain a comprehensive profile of auditory sensory memory and discrimination accuracy in a short measurement time (altogether approximately 15 min for 5 auditory attributes). The speed of the paradigms makes them highly attractive for clinical research, their reliability brings fidelity to longitudinal studies, and the language context is especially suitable for studies on language impairments such as dyslexia and aphasia. In addition I have presented an even more ecological paradigm, and more importantly, an interesting result in view of the theory of MMN where the MMN responses are recorded entirely without a repetitive standard tone. All in all, these paradigms contribute to the development of the theory of auditory perception, and increase the feasibility of MMN recordings in both basic and clinical research. Moreover, they have already proven useful in studying for instance dyslexia, Asperger syndrome and schizophrenia.

Introduction of high-content screening method for studying drug-induced mitochondrial dysfunction in hepatocytes

Drug induced liver injury is one of the frequent reasons for the drug removal from the market. During the recent years there has been a pressure to develop more cost efficient, faster and easier ways to investigate drug-induced toxicity in order to recognize hepatotoxic drugs in the earlier phases of drug development. High Content Screening (HCS) instrument is an automated microscope equipped with image analysis software. It makes the image analysis faster and decreases the risk for an error caused by a person by analyzing the images always in the same way. Because the amount of drug and time needed in the analysis are smaller and multiple parameters can be analyzed from the same cells, the method should be more sensitive, effective and cheaper than the conventional assays in cytotoxicity testing. Liver cells are rich in mitochondria and many drugs target their toxicity to hepatocyte mitochondria. Mitochondria produce the majority of the ATP in the cell through oxidative phosphorylation. They maintain biochemical homeostasis in the cell and participate in cell death. Mitochondria is divided into two compartments by inner and outer mitochondrial membranes. The oxidative phosphorylation happens in the inner mitochondrial membrane. A part of the respiratory chain, a protein called cytochrome c, activates caspase cascades when released. This leads to apoptosis. The aim of this study was to implement, optimize and compare mitochondrial toxicity HCS assays in live cells and fixed cells in two cellular models: human HepG2 hepatoma cell line and rat primary hepatocytes. Three different hepato- and mitochondriatoxic drugs (staurosporine, rotenone and tolcapone) were used. Cells were treated with the drugs, incubated with the fluorescent probes and then the images were analyzed using Cellomics ArrayScan VTI reader. Finally the results obtained after optimizing methods were compared to each other and to the results of the conventional cytotoxicity assays, ATP and LDH measurements. After optimization the live cell method and rat primary hepatocytes were selected to be used in the experiments. Staurosporine was the most toxic of the three drugs and caused most damage to the cells most quickly. Rotenone was not that toxic, but the results were more reproducible and thus it would serve as a good positive control in the screening. Tolcapone was the least toxic. So far the conventional analysis of cytotoxicity worked better than the HCS methods. More optimization needs to be done to get the HCS method more sensitive. This was not possible in this study due to time limit.

Sensitivity of wetland methane emissions to model assumptions: application and model testing against site observations

Abstract. Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources is still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al., 2011) into the Community Land Model 4.0 (CLM4CN) in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model because there are large differences between simulated fractional inundation and satellite observations. A rice paddy module is also incorporated into the model, where the fraction of land used for rice production is explicitly prescribed. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993–2004 were 256 Tg CH4 yr−1, and rice paddy emissions in the year 2000 were 42 Tg CH4 yr−1. Tropical wetlands contributed 201 Tg CH4 yr−1, or 78 % of the global wetland flux. Northern latitude (>50 N) systems contributed 12 Tg CH4 yr−1. We expect this latter number may be an underestimate due to the low high-latitude inundated area captured by satellites and unrealistically low high-latitude productivity and soil carbon predicted by CLM4. Sensitivity analysis showed a large range (150–346 Tg CH4 yr−1) in predicted global methane emissions. The large range was sensitive to: (1) the amount of methane transported through aerenchyma, (2) soil pH (± 100 Tg CH4 yr−1), and (3) redox inhibition (± 45 Tg CH4 yr−1).