Controlling legs for locomotion-insights from robotics and neurobiology.

Walking is the most common terrestrial form of locomotion in animals. Its great versatility and flexibility has led to many attempts at building walking machines with similar capabilities. The control of walking is an active research area both in neurobiology and robotics, with a large and growing body of work. This paper gives an overview of the current knowledge on the control of legged locomotion in animals and machines and attempts to give walking control researchers from biology and robotics an overview of the current knowledge in both fields. We try to summarize the knowledge on the neurobiological basis of walking control in animals, emphasizing common principles seen in different species. In a section on walking robots, we review common approaches to walking controller design with a slight emphasis on biped walking control. We show where parallels between robotic and neurobiological walking controllers exist and how robotics and biology may benefit from each other. Finally, we discuss where research in the two fields diverges and suggest ways to bridge these gaps.

Humanoid robot Lola: design and walking control.

In this paper we present the humanoid robot LOLA, its mechatronic hardware design, simulation and real-time walking control. The goal of the LOLA-project is to build a machine capable of stable, autonomous, fast and human-like walking. LOLA is characterized by a redundant kinematic configuration with 7-DoF legs, an extremely lightweight design, joint actuators with brushless motors and an electronics architecture using decentralized joint control. Special emphasis was put on an improved mass distribution of the legs to achieve good dynamic performance. Trajectory generation and control aim at faster, more flexible and robust walking. Center of mass trajectories are calculated in real-time from footstep locations using quadratic programming and spline collocation methods. Stabilizing control uses hybrid position/force control in task space with an inner joint position control loop. Inertial stabilization is achieved by modifying the contact force trajectories.

Advances in clinical cancer proteomics: SELDI-ToF-mass spectrometry and biomarker discovery.

For most cancers, survival rates depend on the early detection of the disease. So far, no biomarkers exist to cope with this difficult task. New proteomic technologies have brought the hope of discovering novel early cancer-specific biomarkers in complex biological samples and/or of the setting up of new clinically relevant test systems. Novel mass spectrometry-(MS) based technologies in particular, such as surface-enhanced laser desorption/ionisation time of flight (SELDI-ToF-MS), have shown promising results in the recent literature. Here, proteomic profiles of control and disease states are compared to find biomarkers for diagnosis. This paper aims to address the authors' own work and that of other groups in clinical cancer proteomics based on SELDI-ToF-MS. Shortcomings and hopes for the future are discussed.

Identification of the thrombin light chain a as the single best mass for differentiation of gastric cancer patients from individuals with dyspepsia by proteome analysis.

Gastric cancer mortality is second only to lung cancer, and its prognosis is dismal. Using surface-enhanced laser desorption/ionization-time-of-flight mass spectrometry, we previously identified a single best mass, which could separate gastric cancer from patients without cancer, with a sensitivity of 89.9% and a specificity of 90%. Using protein liquid chromatography systems with various chromatography media and MS/MS analysis, we were able to identify thrombin light chain A, a proteolytic fragment of prothrombin, as the single best mass for early detection of gastric cancer patients. These findings indicate that disturbances in the coagulation-system are early events in gastric cancer biology and that a decrease or loss of thrombin light chain A, which we termed negative serum protein profiling, may contribute to the diagnosis of cancer patients.

Surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI TOF-MS) and ProteinChip technology in proteomics research.

In this review article, we describe some of the studies that have been performed using the surface-enhanced laser desorption ionization (SELDI) time-of-flight mass spectrometry and ProteinChip technology over the past few years, and highlight both their findings as well as limitations. Proteomic applications, such as target or marker identification and target validation or toxicology, will be addressed. We will also provide an examination of SELDI technology and go into the question of where possible future research may lead us.

Proteome analysis for the identification of tumor-associated biomarkers in gastrointestinal cancer.

Gastrointestinal cancers are usually diagnosed at advanced stages, making a curative treatment difficult. Biomarkers can help to overcome this problem by allowing earlier diagnosis, and thus better therapy. Proteomics tools are novel technologies to identify such biomarkers. This review summarizes advances in biomarker detection using two-dimensional gel electrophoresis (2D-PAGE), chromatography and mass spectrometry technologies. 2D-PAGE combined with mass spectrometry has led to the identification of several differentially expressed proteins in cancer tissue. However, for serum analysis, 2D-PAGE has severe limitations. For serum-based cancer diagnosis, surface-enhanced laser desorption-ionization time-of-flight (SELDI-TOF) mass spectrometry is a promising new technology. The potential of proteins identified with this technology as novel cancer biomarkers still needs to be confirmed in clinical trials.