Parameter estimation in Bayesian reconstruction of SPECT images: An aid in nuclear medicine diagnosis

Despite the adequacy of Bayesian methods to reconstruct nuclear medicine SPECT (single‐photon emission computed tomography) images, they are rarely used in everyday medical practice. This is primarily because of their computational cost and the need to appropriately select the prior model hyperparameters. We propose a simple procedure for the estimation of these hyperparameters and the reconstruction of the original image and test the procedure on both synthetic and real SPECT images. The experimental results demonstrate that the proposed hyperparameter estimation method produces satisfactory reconstructions. Although we have used generalized Gaussian Markov random fields (GGMRF) as prior models, the proposed estimation method can be applied to any priors with convex potential and tractable partition function with respect to the scale hyperparameter. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 21–27, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20003     

Distributed machining control and monitoring using smart sensors/actuators

The study of smart sensors and actuators led, during the past few years, to the development of facilities which improve traditional sensors and actuators in a necessary way to automate production systems. In another context, many studies have been carried out aimed at defining a decisional structure for production activity control and the increasing need of reactivity leads to the autonomization of decisional levels close to the operational system. We study in this paper the natural convergence between these two approaches and we propose an integration architecture, dealing with machine tool and machining control, that enables the exploitation of distributed smart sensors and actuators in the decisional system.     

Neuropathic Pain Induces Interleukin-1β Sensitive Bimodal Glycinergic Activity in the Central Amygdala

Neuropathic pain reduces GABA and glycine receptor (GlyR)-mediated activity in spinal and supraspinal regions associated with pain processing. Interleukin-1β (IL-1β) alters Central Amygdala (CeA) excitability by reducing glycinergic inhibition in a mechanism that involves the auxiliary β-subunit of GlyR (βGlyR), which is highly expressed in this region. However, GlyR activity and its modulation by IL-1β in supraspinal brain regions under neuropathic pain have not been studied. We performed chronic constriction injury (CCI) of the sciatic nerve in male Sprague Dawley rats, a procedure that induces hind paw plantar hyperalgesia and neuropathic pain. Ten days later, the rats were euthanized, and their brains were sliced. Glycinergic spontaneous inhibitory currents (sIPSCs) were recorded in the CeA slices. The sIPSCs from CeA neurons of CCI animals show a bimodal amplitude distribution, different from the normal distribution in Sham animals, with small and large amplitudes of similar decay constants. The perfusion of IL-1β (10 ng/mL) in these slices reduced the amplitudes within the first five minutes, with a pronounced effect on the largest amplitudes. Our data support a possible role for CeA GlyRs in pain processing and in the neuroimmune modulation of pain perception.     

Improving the Management of Endometrial Cancer Patients through the Use of Liquid Biopsy Analyses: A Case Report

Endometrial cancer (EC) is the 4th most common neoplasm of the female genital tract, with 15–20% of patients being of high risk of recurrence which leads to a significant decrease in patient survival. Current therapeutic options for patients with EC are poor, being the combined therapy of carboplatin and paclitaxel the standard of care, with limited efficacy. Therefore, new therapeutic options and better monitoring tools are needed to improve the management of the disease. In the current case report, we showcase the value of liquid biopsy analyses in a microsatellite instability EC patient with initially good prognosis that however underwent rapid progression disease within 6 months post-surgery; through the study of plasma cfDNA/ctDNA dynamics to assess the tumour evolution during treatment, as well as the study of the uterine aspirate as a valuable sample that captures the intra-tumour heterogeneity that allows a comprehensive genomic profiling of the disease to identify potential therapeutic options. Furthermore, preclinical models were generated at the time of tumour progression to assess the efficacy of the identified targeted therapies.     

NMDA and P2X7 Receptors Require Pannexin 1 Activation to Initiate and Maintain Nociceptive Signaling in the Spinal Cord of Neuropathic Rats

Pannexin 1 (Panx1) is involved in the spinal central sensitization process in rats with neuropathic pain, but its interaction with well-known, pain-related, ligand-dependent receptors, such as NMDA receptors (NMDAR) and P2X7 purinoceptors (P2X7R), remains largely unexplored. Here, we studied whether NMDAR- and P2X7R-dependent nociceptive signaling in neuropathic rats require the activation of Panx1 channels to generate spinal central sensitization, as assessed by behavioral (mechanical hyperalgesia) and electrophysiological (C-reflex wind-up potentiation) indexes. Administration of either a selective NMDAR agonist i.t. (NMDA, 2 mM) or a P2X7R agonist (BzATP, 150 μM) significantly increased both the mechanical hyperalgesia and the C-reflex wind-up potentiation, effects that were rapidly reversed (minutes) by i.t. administration of a selective pannexin 1 antagonist (10panx peptide, 300 μM), with the scores even reaching values of rats without neuropathy. Accordingly, 300 μM 10panx completely prevented the effects of NMDA and BzATP administered 1 h later, on mechanical hyperalgesia and C-reflex wind-up potentiation. Confocal immunofluorescence imaging revealed coexpression of Panx1 with NeuN protein in intrinsic dorsal horn neurons of neuropathic rats. The results indicate that both NMDAR- and P2X7R-mediated increases in mechanical hyperalgesia and C-reflex wind-up potentiation require neuronal Panx1 channel activation to initiate and maintain nociceptive signaling in neuropathic rats.     

Energy Deposition around Swift Carbon-Ion Tracks in Liquid Water

Energetic carbon ions are promising projectiles used for cancer radiotherapy. A thorough knowledge of how the energy of these ions is deposited in biological media (mainly composed of liquid water) is required. This can be attained by means of detailed computer simulations, both macroscopically (relevant for appropriately delivering the dose) and at the nanoscale (important for determining the inflicted radiobiological damage). The energy lost per unit path length (i.e., the so-called stopping power) of carbon ions is here theoretically calculated within the dielectric formalism from the excitation spectrum of liquid water obtained from two complementary approaches (one relying on an optical-data model and the other exclusively on ab initio calculations). In addition, the energy carried at the nanometre scale by the generated secondary electrons around the ion’s path is simulated by means of a detailed Monte Carlo code. For this purpose, we use the ion and electron cross sections calculated by means of state-of-the art approaches suited to take into account the condensed-phase nature of the liquid water target. As a result of these simulations, the radial dose around the ion’s path is obtained, as well as the distributions of clustered events in nanometric volumes similar to the dimensions of DNA convolutions, contributing to the biological damage for carbon ions in a wide energy range, covering from the plateau to the maximum of the Bragg peak.     

3′5-Dimaleamylbenzoic Acid Attenuates Bleomycin-Induced Pulmonary Fibrosis in Mice

Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease characterized by parenchymal scarring, leading progressively to alveolar architecture distortion, respiratory failure, and eventually death. Currently, there is no effective treatment for IPF. Previously, 3′5-dimaleamylbenzoic acid (3′5-DMBA), a maleimide, demonstrated pro-apoptotic, anti-inflammatory, and anti-cancer properties; however, its potential therapeutic effects on IPF have not been addressed. Bleomycin (BLM) 100 U/kg was administered to CD1 mice through an osmotic minipump. After fourteen days of BLM administration, 3′5-DMBA (6 mg/kg or 10 mg/kg) and its vehicle carboxymethylcellulose (CMC) were administered intragastrically every two days until day 26. On day 28, all mice were euthanized. The 3′5-DMBA effect was assessed by histological and immunohistochemical staining, as well as by RT-qPCR. The redox status on lung tissue was evaluated by determining the glutathione content and the GSH/GSSG ratio. 3′5-DMBA treatment re-established typical lung histological features and decreased the expression of BLM-induced fibrotic markers: collagen, α-SMA, and TGF-β1. Furthermore, 3′5-DMBA significantly reduced the expression of genes involved in fibrogenesis. In addition, it decreased reduced glutathione and increased oxidized glutathione content without promoting oxidative damage to lipids, as evidenced by the decrease in the lipid peroxidation marker 4-HNE. Therefore, 3′5-DMBA may be a promising candidate for IPF treatment.     

MEXICA: A computer model of a cognitive account of creative writing

MEXICA is a computer model that produces frameworks for short stories based on the engagement-reflection cognitive account of writing. During engagement MEXICA generates material guided by content and rhetorical constraints, avoiding the use of explicit goals or story-structure information. During reflection the system breaks impasses, evaluates the novelty and interestingness of the story in progress and verifies that coherence requirements are satisfied. In this way, MEXICA complements and extends those models of computerised story-telling based on traditional problem-solving techniques where explicit goals drive the generation of stories. This paper describes the engagement-reflection account of writing, the general characteristics of MEXICA and reports an evaluation of the program.     

A semantic role labelling-based framework for learning ontologies from Spanish documents

Currently, most of the information available in the Web is adapted primarily for human consumption, but there is so much information that can no longer be processed by a person in a reasonable time, either in digital or physical formats. To solve this problem, the idea of the Semantic Web arose. The Semantic Web deals with adding machine-readable information to Web pages. Ontologies represent a very important element of this web, as they provide a valid and robust structure to represent knowledge based on concepts, relations, axioms, etc. The need for overcoming the bottleneck provoked by the manual construction of ontologies has generated several studies and research on obtaining semiautomatic methods to learn ontologies. In this sense, this paper proposes a new ontology learning methodology based on semantic role labeling from digital Spanish documents. The method makes it possible to represent multiple semantic relations specially taxonomic and partonomic ones in the standardized OWL 2.0. A set of experiments has been performed with the approach implemented in educational domain that show promising results.