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Poster presentation: Introduction We study the problem of object recognition invariant to transformations, such as translation, rotation and scale. A system is underdetermined if its degrees of freedom (number of possible transformations and potential objects) exceed the available information (image size). The regularization theory solves this problem by adding constraints [1]. It is unclear what constraints biological systems use. We suggest that rather than seeking constraints, an underdetermined system can make decisions based on available information by grouping its variables. We propose a dynamical system as a minimum system for invariant recognition to demonstrate this strategy. ...
Poster presentation: Introduction Dopaminergic neurons in the midbrain show a variety of firing patterns, ranging from very regular firing pacemaker cells to bursty and irregular neurons. The effects of different experimental conditions (like pharmacological treatment or genetical manipulations) on these neuronal discharge patterns may be subtle. Applying a stochastic model is a quantitative approach to reveal these changes. ...
NeuroXidence: reliable and efficient analysis of an excess or deficiency of joint-spike events
(2009)
Poster presentation: We present a non-parametric and computationally-efficient method named NeuroXidence (see http://www.NeuroXidence.com ) that detects coordinated firing within a group of two or more neurons and tests whether the observed level of coordinated firing is significantly different from that expected by chance. NeuroXidence [1] considers the full auto-structure of the data, including the changes in the rate responses and the history dependencies in the spiking activity. We demonstrate that NeuroXidence can identify epochs with significant spike synchronisation even if these coincide with strong and fast rate modulations. We also show, that the method accounts for trial-by-trial variability in the rate responses and their latencies, and that it can be applied to short data windows lasting only tens of milliseconds. Based on simulated data we compare the performance of NeuroXidence with the UE-method [2,3] and the cross-correlation analysis. An application of NeuroXidence to 42 single-units (SU) recorded in area 17 of an anesthetized cat revealed significant coincident events of high complexities, involving firing of up to 8 SUs simultaneously (5 ms window). The results were highly consistent with those obtained by traditional pair-wise measures based on cross-correlation: Neuronal synchrony was strongest in stimulation conditions in which the orientation of the sinusoidal grating matched the preferred orientation of most of the SUs included in the analysis, and was the weakest when the neurons were stimulated least optimally. Interestingly, events of higher complexities showed stronger stimulus-specific modulation than pair-wise interactions. The results suggest strong evidence for stimulus specific synchronous firing and, therefore, support the temporal coding hypothesis in visual cortex. ...
Poster presentation: Introduction We here focus on constructing a hierarchical neural system for position-invariant recognition, which is one of the most fundamental invariant recognition achieved in visual processing [1,2]. The invariant recognition have been hypothesized to be done by matching a sensory image of a particular object stimulated on the retina to the most suitable representation stored in memory of the higher visual cortical area. Here arises a general problem: In such a visual processing, the position of the object image on the retina must be initially uncertain. Furthermore, the retinal activities possessing sensory information are being far from the ones in the higher area with a loss of the sensory object information. Nevertheless, with such recognition ambiguity, the particular object can effortlessly and easily be recognized. Our aim in this work is an attempt to resolve such a general recognition problem. ...
Poster presentation: Introduction We here address the problem of integrating information about multiple objects and their positions on the visual scene. A primate visual system has little difficulty in rapidly achieving integration, given only a few objects. Unfortunately, computer vision still has great difficultly achieving comparable performance. It has been hypothesized that temporal binding or temporal separation could serve as a crucial mechanism to deal with information about objects and their positions in parallel to each other. Elaborating on this idea, we propose a neurally plausible mechanism for reaching local decision-making for "what" and "where" information to the global multi-object recognition. ...
We model the dynamics of ask and bid curves in a limit order book market using a dynamic semiparametric factor model. The shape of the curves is captured by a factor structure which is estimated nonparametrically. Corresponding factor loadings are assumed to follow multivariate dynamics and are modelled using a vector autoregressive model. Applying the framework to four stocks traded at the Australian Stock Exchange (ASX) in 2002, we show that the suggested model captures the spatial and temporal dependencies of the limit order book. Relating the shape of the curves to variables reflecting the current state of the market, we show that the recent liquidity demand has the strongest impact. In an extensive forecasting analysis we show that the model is successful in forecasting the liquidity supply over various time horizons during a trading day. Moreover, it is shown that the model’s forecasting power can be used to improve optimal order execution strategies.
A generic drug product (World Health Organization (WHO) terminology: multisource product) is usually marketed and manufactured after the expiry date of the innovator’s patent. Generic drugs are less expensive than the innovator products because generic manufacturers do not have to amortize the investment costs of research, development, marketing, and promotion. Multisource products must contain the same active pharmaceutical ingredients (APIs) as the original formulation and have to be shown to be interchangeable with the original formulation. Multisource products have to be shown bioequivalent to the innovator counterpart with respect to pharmacokinetic and pharmacodynamic properties. Multisource products are therefore identical in dose, strength, route of administration, safety, efficacy, and intended use. Bioequivalence can be demonstrated by in vitro dissolution, pharmacokinetic, pharmacodynamic or clinical studies. Since 2000, the U.S. Food and Drug Administration (FDA) allows the approval of certain multisource products solely on the basis of in vitro studies, i.e. by waiving in vivo studies in humans (“Biowaiver”), based on the Biopharmaceutics Classification Scheme (BCS). The BCS characterizes APIs by their solubility and permeability in the gastrointestinal tract (GIT). The different BCS Classes I-IV (Class I: high solubility, high permeability; Class II: low solubility, high permeability; Class III: high solubility, low permeability and Class IV: low solubility, low permeability) result from all possible combinations of high and low solubility with high and low permeability. Since the adoption of the BCS by the FDA in 1995, the BCS criteria have been under continuous development. In 2006, the WHO has released the most recent bioequivalence guidance including relaxed criteria for bioequivalence studies based on modified BCS criteria. According to this guidance, APIs belonging to the BCS classes I – and under defined conditions - II and III – are eligible for a biowaiver-based approval. The principal objective of this work was to characterize the first-line anti tuberculosis APIs, isoniazid, pyrazinamide, ethambutol dihydrochloride and rifampicin, according to their physicochemical, biopharmaceutical, pharmacokinetic and pharmacological properties and to classify them according to the BCS. Ethambutol dihydrochloride and isoniazid were classified as borderline BCS class I/III APIs. Pyrazinamide was classified as a BCS class III and rifampicin as a BCS class II API. Based on the BCS classification and the additional criteria defined in the WHO bioequivalence guidance, the possibility of biowaiver-based approval for immediate release (immediate release) solid oral dosage forms containing the first-line antituberculosis drugs was evaluated. A biowaiver-based approval with defined constraints was recommended for immediate release solid oral dosage forms containing isoniazid (interaction with reducing sugars), pyrazinamide and ethambutol dihydrochloride (relative narrow therapeutic index). Rifampicin was classified as a BCS class II API, and it was concluded that rifampicin containing solid oral immediate release drug products as well as Scale-Up and Post-Approval Changes (SUPAC) changes should not be approved by a biowaiver on the following basis: (i) its solubility and dissolution are highly variable due to polymorphism and instability, (ii) concomitant intake of food and antacids reduces its absorption and bioavailability, (iii) no in vitro predictive dissolution test has been found which correlates to in vivo absorption and (iv) several publications reporting cases of non-bioequivalent and bioinequivalent rifampicin products have been located in the literature. Thus, it is recommended that bioequivalence of rifampicin containing solid oral immediate release drug products should be established by in vivo pharmacokinetic studies in humans. This risk-benefit benefit assessment of a biowaiver-based approval was presented as a poster at the American Association of Pharmaceutical Scientists (AAPS) 2005 and subsequently published as “Biowaiver Monographs” in the Journal of Pharmaceutical Sciences. Based on the assessment of the dissolution properties of the antituberculosis drugs for a biowaiver approval, quality control dissolution methodologies for the International Pharmacopoeia (Pharm. Int.) were developed, presented at the WHO expert meeting and adopted in the Pharm. Int. (http://www.who.int/medicines/publications/pharmprep/OMS_TRS_948.pdf). Additionally, preliminary biowaiver recommendations were also developed for four firstline antimalarial drugs listed on the WHO Essential Medicines List (EML): Quinine, as both the hydrochloride and sulphate, and proguanil hydrochloride were classified as borderline BCS class I/III APIs. Since quinine is a narrow therapeutic index drug and many cases of non-bioequivalence have been reported in the literature, a biowaiverbased approval was not recommended. For solid oral immediate release dosage forms containing proguanil a biowaiver-based approval was recommended under the condition that they dissolve very rapidly. Primaquine phosphate was classified as a BCS class I API. Therefore, a biowaiver-based approval was recommended for immediate release solid oral dosage forms containing primaquine phosphate. Mefloquine hydrochloride was classified as a basic, BCS class IV/II API, making it ineligible for the biowaiver. Additionally, reports of non-bioequivalence and a narrow therapeutic index were found in the scientific literature. Consequently, bioequivalence of solid oral immediate release dosage forms containing mefloquine hydrochloride should be established by in vivo pharmacokinetic studies. The results for quinine hydrochloride and sulphate, proguanil hydrochloride, primaquine diphosphate and mefloquine hydrochloride were presented as a poster at the Pharmaceutical Sciences World Congress (PSWC) 2007 and published as a WHO Collaborating Center Report in June 2006. The aim of this project was to collect, evaluate, generate and publish relevant information for a biowaiver-based approval of essential medicines in order to provide a summary to local regulatory authorities. This information complements the selected list of essential medicines by providing information about the biopharmaceutical properties and pharmaceutical quality of solid oral immediate release dosage forms containing these APIs. The aim of the biowaiver project, inspired by the WHO and brought in life by the International Pharmaceutical Federation (FIP), is to enable access to essential medicines in standardized quality at an affordable price. In this work, a significant contribution to this aim in the form of four biowaiver monographs for the antituberculosis drugs and several reports on the antimalarials has been achieved.
Background: Microarray analysis still remains a powerful tool to identify new components of the transcriptosome and it has helped to increase the knowledge of targets triggered by stress conditions such as hypoxia and nitric oxide. However, analysis of transcriptional regulatory events remain elusive due to the contribution of altered mRNA stability to gene expression patterns, as well as changes in the half-life of mRNAs, which influence mRNA expression levels and their turn over rates. To circumvent these problems, we have focused on the analysis of newly transcribed (nascent) mRNAs by nuclear run on (NRO), followed by microarray analysis. Result: We identified 188 genes that were significantly regulated by hypoxia, 81 genes were affected by nitric oxide, and 292 genes were induced by the co-treatment of macrophages with both NO and hypoxia. Fourteen genes (Bnip3, Ddit4, Vegfa, Trib3, Atf3, Cdkn1a, Scd1, D4Ertd765e, Sesn2, Son, Nnt, Lst1, Hps6 and Fxyd5) were common to hypoxia and/or nitric oxide treatments, but with different levels of expression. We observed that 166 transcripts were regulated only when cells were co-treated with hypoxia and NO but not with either treatment alone, pointing to the importance of a crosstalk between hypoxia and NO. In addition, both array and proteomics data supported a consistent repression of hypoxia regulated targets by NO. Conclusion: By eliminating the interference of steady state mRNA in gene expression profiling, we increased the sensitivity of mRNA analysis and identified previously unknown hypoxia-induced targets. Gene analysis profiling corroborated the interplay between NO- and hypoxia-induced signalling.
Photo-initiated processes, like photo-excitation and -deexcitation, internal conversion, excitation energy transfer and electron transfer, are of importance in many areas of physics, chemistry and biology. For the understanding of such processes, detailed knowledge of excitation energies, potential energy surfaces and excited state properties of the involved molecules is an essential prerequisite. To obtain these informations, quantum chemical calculations are required. Several quantum chemical methods exist which allow for the calculation of excited states. Most of these methods are computationally costly what makes them only applicable to small molecules. However, many biological systems where photo-processes are of interest like light-harvesting complexes in photosynthesis or the reception of light in the human eye by rhodopsin are quite large. For large systems, however, only few theoretical methods remain applicable. The currently most widely used method is time-dependent density functional theory (TD-DFT), which can treat systems of up to 200–300 atoms with the excitation energies of some excited states exhibiting errors of less than 0.5 eV. Yet, TD-DFT has several drawbacks. The most severe failure of TD-DFT is the false description of charge transfer states which is particularly problematic in case of larger systems where it yields a multitude of artificially low-lying charge transfer states. But also Rydberg states and states with large double excitation character are not described correctly. Still, if these deficiencies are kept in mind during the interpretation of results, TD-DFT is a useful tool for the calculation of excited states. In my thesis, TD-DFT is applied in investigations of excitation energy and electron transfer processes in light-harvesting complexes. Since light-harvesting complexes, which consist of thousands of atoms, are by far too large to be calculated, model complexes for the processes of interest are constructed from available crystal structures. The model complexes are used to calculate potential energy curves along meaningful reaction coordinates. Artificial charge transfer states are corrected with the help of the so-called ∆DFT method. The resulting potential energy curves are then interpreted by comparison with experimental results. For the light-harvesting complex LH2 from purple bacteria the experimentally observed formation of carotenoid radical cations is studied. It is shown that the carotenoid radical cation is formed most likely via the optically forbidden S1 state of the carotenoid. In light-harvesting complex LHC-II of green plants the fast component of the so-called non-photochemical quenching (NPQ) is investigated. Two of several different hypotheses on the mechanism of NPQ, which have been proposed recently, are studied in detail. The first one suggests that NPQ proceeds via simple replacement of violaxanthin by zeaxanthin in the binding pocket in LHC-II. However, the calculated potential energy curves exhibit no difference between violaxanthin and zeaxanthin in the binding pocket. In combination with experimental results it is thus shown that simple replacement alone does not mediate NPQ in LHC-II. The second hypothesis proposes conformational changes of LHC-II that lead to quenching at the central lutein and chlorophyll molecules during NPQ. My TD-DFT calculations demonstrate that if this mechanism is operative, only the lutein 1 which is one of two central luteins present in LHC-II can take part in the quenching process. This is corroborated by recent experiments. Though several conclusions can be drawn from the investigations using TD-DFT, the interpretability of the results is limited due to the deficiencies of the method and of the models. To overcome the methodological deficiencies, more accurate methods have to be employed. Therefore, the so-called algebraic diagrammatic construction scheme (ADC) is implemented. ADC is a widely overlooked ab initio method for the calculation of excited states, which is based on propagator theory. Its theoretical derivation proceeds via perturbation expansion of the polarization propagator, which describes electronic excitations. This yields separate schemes for every order of perturbation theory. The second order scheme ADC(2), which is employed here, is the equivalent to the Møller-Plesset ground state method MP(2), but for excited states. It represents the computationally cheapest excited state method which can correctly describe doubly excited states, as well as Rydberg and charge transfer states. The quality of ADC(2) results is demonstrated in calculations on linear polyenes which serve as model systems for the larger carotenoid molecules. The calculations show that ADC(2) describes the three lowest excited states of polyenes sufficiently well, particularly the optically forbidden S1 state which is known to possess large double excitation character. Yet, the applicability of the method is limited compared to TD-DFT due to the much larger computational requirements. To facilitate the calculation of larger systems with ADC(2) a new variant of the method is developed and implemented. The variant employs the short-range behavior of electron correlation to reduce the computational effort. As a first step, the working equations of ADC(2) are transformed into a basis of local orbitals. In this basis negligible contributions of the equations which are due to electron correlation can be identified based on the distances of local orbitals. A so-called “bumping” scheme is implemented which removes the negligible parts during a calculation. This way, the computation times as well as the disk space requirements can be reduced. With the “bumping” scheme several new parameters are introduced that regulate the amount of “bumping” and thereby the speed and the accuracy of computations. To determine useful values for the parameters an evaluation is performed using the linear polyene octatetraene as test molecule. From the evaluation an optimal set of parameter values is obtained, so that the computation times become minimal, while the errors in the excitation energies due to the “bumping” do not exceed 0.15 eV. With further calculations on various molecules of different sizes it is tested if these parameter values are universal, i.e. if they can be used for all molecules. The test calculations show that the errors in the excitation energies are below 0.15 eV for all test systems. Additionally, no trend is visible for the errors that their magnitude might depend on the system. In contrast, the amount of disregarded contributions in the calculations increases drastically with growing system size. Thus, the local variant of ADC(2) can be used in future to reliably calculate excited states of systems which are not accessible with conventional ADC(2).
This paper explores the relationship between equity prices and the current account for 17 industrialized countries in the period 1980-2007. Based on a panel vector autoregression, I compare the effects of equity price shocks to those originating from monetary policy and exchange rates. While monetary policy shocks have a limited impact, shocks to equity prices have sizeable effects. The results suggest that equity prices impact on the current account through their effects on real activity and exchange rates. Furthermore, shocks to exchange rates play a key role as well. Keywords: current account fluctuations, equity prices, panel vector autoregression