Background: A novel immunological approach to colon cancer therapy is the antibody targeting of the fibroblast activation protein (FAP), which is highly expressed by stroma cells of this tumour. Unconjugated sibrotuzumab (BIBH 1), which is a humanised version of the murine anti-FAP mAb F19, was investigated for its anti-tumour activity, safety and pharmacokinetics. Patients and Methods: Patients with metastatic colorectal cancer received weekly intravenous infusions of unconjugated sibrotuzumab at a dose of 100 mg over 12 scheduled weeks. The study was implemented as an open-label, uncontrolled, multicentre trial. Results: 25 patients were enrolled. Patients had one or more measurable lesions, predominantly liver lesions, at baseline. At least 8 repeated weekly infusions of sibrotuzumab in 17 evaluable patients did not result in complete or partial remission. Rather, ongoing tumour progression was noted in all patients except for 2 patients with stable disease. However, progressive disease was also observed post-study in these 2 patients who received 1 and 6 additional infusions, respectively, of sibrotuzumab. Sibrotuzumab exhibited 2-compartment pharmacokinetics with a dominant terminal phase and t1/2 ? = 5.3 ± 2.3 days. Adverse drug reactions (rigors/chills, nausea, flushing and one incidence of bronchospasm) were observed in 5 patients. Of the 24 patients given 2 or more infusions of sibrotuzumab, antibodies against sibrotuzumab were found in 3 patients (12.5%) after 4–12 infusions. Conclusions: Sibrotuzumab was well tolerated and safe. The minimal requirement for the continuation of this exploratory trial, of at least one complete or partial remission, or equivalently, of 4 patients with stable disease, was not met.

We present a stochastic analysis of a data set consisting of 1.25 × 107 samples of the local velocity measured in the turbulent region of a round free jet. We find evidence that the statistics of the longitudinal velocity increment v(r) can be described as a Markov process. This new approach to characterize small-scale turbulence leads to a Fokker–Planck equation for the r-evolution of the probability density function (p.d.f.) of v(r). This equation for p(v, r) is completely determined by two coefficients D1(v, r) and D2(v, r) (drift and diffusion coefficient, respectively). It is shown how these coefficients can be estimated directly from the experimental data without using any assumptions or models for the underlying stochastic process. The solutions of the resulting Fokker–Planck equation are compared with experimentally determined probability density functions. It is shown that the Fokker–Planck equation describes the measured p.d.f.(s) correctly, including intermittency effects. Furthermore, knowledge of the Fokker–Planck equation also allows the joint probability density of N increments on N different scales p(v1, r1, …, vN, rN) to be determined.

It is shown that prize changes of the US dollar -German Mark exchange rates upon different delay times can be regarded as a stochastic Marcovian process. Furthermore we show that from the empirical data the Kramers-Moyal coefficients can be estimated. Finally, we present an explicite Fokker-Planck equation which models very precisely the empirical probabilitiy distributions. PACS: 02.50-r;05.10GSince high-frequency intra-day data are available and easy to access, research on the dynamics of financial markets is enjoying a broad interest. [1,2,3,4,5,6,7]. Well-founded quantitative investigations now seem to be feasible. The identification of the underlying process leading to heavy tailed probability density function (pdf) of price changes and the volatility clustering (see fig.1) are of special interest. The shape of the pdf expresses an unexpected high probability of large price changes on short time scales which is of utmost importance for risk analysis. In a recent work [8], an analogy between the short-time dynamics of foreign exchange (FX) market and hydrodynamic turbulence has been proposed. This analogy postulates the existence of hierarchical features like a cascade process from large to small time scales in the dynamics of prices, similar to the energy cascade in turbulence c.f. [9]. This postulate has been supported by some work [7] and questioned by others [6].1 Friedrich, Peinke, Renner 2 One main claim of the hypothesis of cascade processes is that the statistics of the time series of the financial market can be determined. The aim of the present paper is to discuss a new kind of analysis capable to derive the underlying mathematical model directly from the given data. This method yields an estimation of an effective stochastic equation in the form of a Fokker-Planck equation (also known as Kolmogorov equation). The solutions of this equation yields the probability distributions with sufficient accuracy (see fig. 1). This means that our method is not based on the conventional phenomenological comparison between models and several stochastic aspects of financial data. Our approach demonstrates how multiplicative noise and deterministic forces interact leading to the heavy tailed statistics. [10] Recently it has been demonstrated that from experimental data of turbulent flow the hierarchical features induced by the energy cascade can be extracted in form of a Fokker-Planck equation for the length scale dependence of velocity fluctuations [12]. In the following it will be shown the dynamics of foreign exchange rates can also be described by a Fokker-Planck equation. Here we use a data set consisting of 1,472,241 quotes for US dollar-German mark exchange rates from the years 1992 and 1993 as used in reference [8].We investigate the statistical dependence of prize changes ∆x i := x(t+ ∆t i ) − x(t) upon the delay time ∆t i . Here x(t) denotes the exchange rate at time t. We will show that the prize changes ∆x 1 , ∆x 2 for two delay times ∆t 1 , ∆t 2 are statistically dependent, provided the differ...

The small scale structure of fully developed turbulent flows is commonly believed to form an universal state which exhibits stationarity, homogeneity, and isotropy in a statistical sense [1]. The basic concept for the formation of this state is the turbulent cascade which is usually investigated by the statistics of the longitudinal velocity increments v(r) of the velocity field u(x,t),

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