Positioning error analysis of the fraxion localization system in the intracranial stereotactic radiotherapy of tumors.

OBJECTIVE: To investigate positioning error analysis of the Fraxion localization system in the intracranial stereotactic radiotherapy of tumors. METHODS: 64 patients were divided into two groups: a control group (36 patients with the standard thermoplastic mask) and a model group (28 patients with the Fraxion localization system). 3D images of the treated position were obtained by cone-beam computed tomography (CBCT). Positioning errors were obtained by, respectively, registering these two sets of CBCT images to planning CT images, using a 6°-freedom robotic patient positioning system (HexaPOD Evo RT System). The changes in positioning errors with the Fraxion localization system and with the standard thermoplastic mask were analyzed. RESULTS: CBCT scan results of the model group showed that the mean of linear error of three directions [superior-inferior (SI), lateral (LAT), and anterior-posterior (AP)] was 0.710 ± 0.676 mm, 0.817 ± 0.687 mm, and 0.710 ± 0.685 mm, respectively. The corresponding PTV was 1.23 mm, 1.26 mm, and 1.36 mm. The differences between the 3D images and the planned CT images were significant (p < 0.001). CONCLUSION: The Fraxion radiotherapy system can not only improve the positioning accuracy and reduce positioning errors but also narrow the PTV margin and reduce the radiated volume of normal tissue.

LECT2 association with macrophage-mediated killing of Helicobacter pylori by activating NF-κB and nitric oxide production.

Helicobacter pylori employs unique methods to colonize the stomach, which induces chronic inflammation. It is also able to avoid eradication by macrophages and other immune cells. Leukocyte cell-derived chemotaxin 2 (LECT2), a multi-functional cytokine involved in many pathological conditions, has recently been shown to activate macrophages via the CD209a receptor. Therefore, we aimed to investigate the effects of LECT2 on H. pylori-infected macrophages. Macrophages were treated with recombinant LECT2, and both their ability to kill H. pylori and produce nitric oxide were analyzed. Western blot was performed to determine nuclear translocation and protein phosphorylation of p65, a subunit of nuclear factor (NF)-κB. Transfection experiments were performed to analyze the signaling pathway of LECT2 in macrophages. We found that treatment with LECT2 enhanced H. pylori killing and nitric oxide production in macrophages. In addition, DNA-binding activity and nuclear translocation of p65 were up-regulated by LECT2 treatment. Furthermore, we found that NF-κB activation by LECT2 was mediated by Raf-1 in macrophages, and Raf-1 phosphorylation was specifically altered in response to LECT2. Moreover, LECT2 induced Ser28 phosphorylation in the intracellular domain of CD209a. CD209a Ser28 phosphorylation was required for LECT2-induced Raf-1 and NF-κB activation in RAW264.7 macrophages. Our study showed that the effects of LECT2 on H. pylori killing and nitric oxide production were dependent on CD209a phosphorylation, Raf-1, and NF-κB activation. Together, these results demonstrate for the first time that exposure to LECT2 can modulate specific intracellular mechanisms downstream of CD209a to enhance H. pylori killing and nitric oxide production in macrophages.

Structural analysis of neural circuits using the theory of directed graphs.

A new approach to analysis of structural properties of biological neural circuits is proposed based on their representation in the form of abstract structures called directed graphs. To exemplify this methodology, structural properties of a biological neural network and randomly wired circuits (RC) were compared. The analyzed biological circuit (BC) represented a sample of 39 neural nuclei which are responsible for the control of the cardiovascular function in higher vertebrates. Initially, direct connections of both circuits were stored in a square matrix format. Then, standard algorithms derived from the theory of directed graphs were applied to analyze the pathways of the circuits according to their length (in number of synapses), degree of connectedness, and structural strength. Thus, the BC was characterized by the presence of short, reciprocal, and unidirectional pathways which presented a high degree of heterogeneity in their strengths. This heterogeneity was mainly due to the existence of a small cluster of reciprocally connected neural nuclei in the circuit that have access, through short pathways, to most of the network. On the other hand, RCs were characterized by the presence of long and mainly reciprocal pathways which showed lower and absolute homogeneous strengths. Through this study the proposed methodology was demonstrated to be a simple and efficient way to store, analyze, and compare basic neuroanatomical information.

Connection, a microcomputer program for storing and analyzing structural properties of neural circuits.

The application of a microcomputer-based system (the Connection system) designed to deal with neuroanatomical information commonly analyzed by researchers and involved in the study of structural properties of neural circuits is presented. This system can be employed at first as a readily-accessible database containing physiological and anatomical data from nuclei of the central nervous system which define a network with up to 45 elements and their subdivisions and connections. Once the database from a specific network is built and stored in a file, routines of this system can be used to classify the nuclei in term of their afferents and efferents and also to display all possible pathways linking any pair of nuclei and their respective length (number of synapses). The role of such a system as an auxiliary tool in neuroanatomical and electrophysiological research is discussed by presenting the results obtained from the analysis of the neural circuits involved in cardiovascular function control in higher vertebrates.

Structural characterization of the neural circuit responsible for control of cardiovascular functions in higher vertebrates.

A comparison of structural properties of a biological neural system responsible for cardiovascular function control in higher vertebrates with randomly connected networks was pursued using matrix representations of those circuits. The biological circuit was characterized by the presence of some heavily connected nuclei in contrast to the random networks that had equally distributed connections between their elements. This property of the analysed biological circuit was shown to account for a high logarithmic correlation found between two indexes defined to represent pointwise features of the nuclei and their global contribution to the whole network. The first index is obtained by the product of the number of inputs and of outputs of a nucleus and was called power index (PI). The second one, called occurrence index (OI), defines how many times a specific nucleus is crossed when all possible pathways joining two nuclei of the circuit are obtained. This PI-OI correlation was clearly dependent on the pathway length distribution (expressed in number of synapses), and was maximal considering pathways with a low number of synapses. When randomly connected circuits were analysed lower correlation was found between the same two indexes and only for much longer pathways. Therefore, it is proposed that the analysis of the PI-OI correlation can be useful to quantify structural differences between biological neural circuits as distinguished from randomly connected networks and also between neural systems at different levels of phylogenetic and ontogenetic development.