Differential expression of sPLA2 following spinal cord injury and a functional role for sPLA2-IIA in mediating oligodendrocyte death

After the initial mechanical insult of spinal cord injury (SCI), secondary mediators propagate a massive loss of oligodendrocytes. We previously showed that following SCI both the total phospholipase activity and cytosolic PLA(2)-IV alpha protein expression increased. However, the expression of secreted isoforms of PLA(2) (sPLA(2)) and their possible roles in oligodendrocyte death following SCI remained unclear. Here we report that mRNAs extracted 15 min, 4 h, 1 day, or 1 month after cervical SCI show marked upregulation of sPLA(2)-IIA and IIE at 4 h after injury. In contrast, SCI induced down regulation of sPLA(2)-X, and no change in sPLA(2)-IB, IIC, V, and XIIA expression. At the lesion site, sPLA(2)-IIA and IIE expression were localized to oligodendrocytes. Recombinant human sPLA(2)-IIA (0.01, 0.1, or 2 microM) induced a dose-dependent cytotoxicity in differentiated adult oligodendrocyte precursor cells but not primary astrocytes or Schwann cells in vitro. Most importantly, pretreatment with S3319, a sPLA(2)-IIA inhibitor, before a 30 min H(2)O(2) injury (1 or 10 mM) significantly reduced oligodendrocyte cell death at 48 h. Similarly, pretreatment with S3319 before injury with IL-1 beta and TNFalpha prevented cell death and loss of oligodendrocyte processes at 72 h. Collectively, these findings suggest that sPLA(2)-IIA and IIE are increased following SCI, that increased sPLA(2)-IIA can be cytotoxic to oligodendrocytes, and that in vitro blockade of sPLA(2) can create sparing of oligodendrocytes in two distinct injury models. Therefore, sPLA(2)-IIA may be an important mediator of oligodendrocyte death and a novel target for therapeutic intervention following SCI

MARLIN: A Cloud Integrated Robotic Solution to Support Intralogistics in Retail

In this paper, we present the service robot MARLIN and its integration with the K4R platform, a cloud system for complex AI applications in retail. At its core, this platform contains so-called semantic digital twins, a semantically annotated representation of the retail store. MARLIN continuously exchanges data with the K4R platform, improving the robot's capabilities in perception, autonomous navigation, and task planning. We exploit these capabilities in a retail intralogistics scenario, specifically by assisting store employees in stocking shelves. We demonstrate that MARLIN is able to update the digital representation of the retail store by detecting and classifying obstacles, autonomously planning and executing replenishment missions, adapting to unforeseen changes in the environment, and interacting with store employees. Experiments are conducted in simulation, in a laboratory environment, and in a real store. We also describe and evaluate a novel algorithm for autonomous navigation of articulated tractor-trailer systems. The algorithm outperforms the manufacturer's proprietary navigation approach and improves MARLIN's navigation capabilities in confined spaces

Robotic manipulation for the shoe-packaging process

[EN] This paper presents the integration of a robotic system in a human-centered environment, as it can be found in the shoe manufacturing industry. Fashion footwear is nowadays mainly handcrafted due to the big amount of small production tasks. Therefore, the introduction of intelligent robotic systems in this industry may contribute to automate and improve the manual production steps, such us polishing, cleaning, packaging, and visual inspection. Due to the high complexity of the manual tasks in shoe production, cooperative robotic systems (which can work in collaboration with humans) are required. Thus, the focus of the robot lays on grasping, collision detection, and avoidance, as well as on considering the human intervention to supervise the work being performed. For this research, the robot has been equipped with a Kinect camera and a wrist force/ torque sensor so that it is able to detect human interaction and the dynamic environment in order to modify the robot¿s behavior. To illustrate the applicability of the proposed approach, this work presents the experimental results obtained for two actual platforms, which are located at different research laboratories, that share similarities in their morphology, sensor equipment and actuation system.This work has been partly supported by the Ministerio de Economia y Competitividad of the Spanish Government (Key No.: 0201603139 of Invest in Spain program and Grant No. RTC-2016-5408-6) and by the Deutscher Akademischer Austauschdienst (DAAD) of the German Government (Projekt-ID 54368155).Gracia Calandin, LI.; Perez-Vidal, C.; Mronga, D.; Paco, JD.; Azorin, J.; Gea, JD. (2017). Robotic manipulation for the shoe-packaging process. The International Journal of Advanced Manufacturing Technology. 92(1-4):1053-1067. https://doi.org/10.1007/s00170-017-0212-6S10531067921-4Pedrocchi N, Villagrossi E, Cenati C, Tosatti LM (2017) Design of fuzzy logic controller of industrial robot for roughing the uppers of fashion shoes. 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Central neuropeptide Y receptors are involved in 3(rd )ventricular ghrelin induced alteration of colonic transit time in conscious fed rats

BACKGROUND: Feeding related peptides have been shown to be additionally involved in the central autonomic control of gastrointestinal functions. Recent studies have shown that ghrelin, a stomach-derived orexigenic peptide, is involved in the autonomic regulation of GI function besides feeding behavior. Pharmacological evidence indicates that ghrelin effects on food intake are mediated by neuropeptide Y in the central nervous system. METHODS: In the present study we examine the role of ghrelin in the central autonomic control of GI motility using intracerobroventricular and IP microinjections in a freely moving conscious rat model. Further the hypothesis that a functional relationship between NPY and ghrelin within the CNS exists was addressed. RESULTS: ICV injections of ghrelin (0.03 nmol, 0.3 nmol and 3.0 nmol/5 μl and saline controls) decreased the colonic transit time up to 43%. IP injections of ghrelin (0.3 nmol – 3.0 nmol kg(-1 )BW and saline controls) decreased colonic transit time dose related. Central administration of the NPY(1 )receptor antagonist, BIBP-3226, prior to centrally or peripherally administration of ghrelin antagonized the ghrelin induced stimulation of colonic transit. On the contrary ICV-pretreatment with the NPY(2 )receptor antagonist, BIIE-0246, failed to modulate the ghrelin induced stimulation of colonic motility. CONCLUSION: The results suggest that ghrelin acts in the central nervous system to modulate gastrointestinal motor function utilizing NPY(1 )receptor dependent mechanisms

Burden of Uncontrolled Severe Asthma With and Without Elevated Type-2 Inflammatory Biomarkers

Background: Many patients with asthma have type-2 airway inflammation, identified by the presence of biomarkers, including history of allergy, high blood eosinophil (EOS) count, and high fractional exhaled nitric oxide levels. Objective: To assess disease burden in relation to type-2 inflammatory biomarker status (history of allergy, blood EOS count, and fractional exhaled nitric oxide level) in patients with uncontrolled and controlled severe asthma in the NOVEL observational longiTudinal studY (NOVELTY) (NCT02760329). Methods: Asthma diagnosis and severity were physician-reported. Control was defined using Asthma Control Test score (uncontrolled <20, controlled ≥20) and/or 1 or more severe physician-reported exacerbation in the previous year. Biomarker distribution (history of allergy, blood EOS count, and fractional exhaled nitric oxide level), symptom burden (Asthma Control Test score, modified Medical Research Council dyspnea scale), health status (St George's Respiratory Questionnaire score), exacerbations, and health care resource utilization were assessed. Results: Of 647 patients with severe asthma, 446 had uncontrolled and 123 had controlled asthma. Among those with uncontrolled asthma, 196 (44%) had 2 or more positive biomarkers, 187 (42%) had 1 positive biomarker, 325 (73%) had low blood EOS, and 63 (14%) were triple-negative. Disease burden was similarly high across uncontrolled subgroups, irrespective of biomarker status, with poor symptom control (Asthma Control Test score 14.9-16.6), impaired health status (St George's Respiratory Questionnaire total score 46.7-49.4), clinically important breathlessness (modified Medical Research Council grade ≥2 in 47.3%-57.1%), and 1 or more severe exacerbation (70.6%-76.2%). Conclusions: Type-2 inflammatory biomarkers did not differentiate disease burden in patients with severe asthma. Patients with low type-2 inflammatory biomarker levels have few biologic therapy options; their needs should be addressed

Burden of Uncontrolled Severe Asthma With and Without Elevated Type-2 Inflammatory Biomarkers

Background: Many patients with asthma have type-2 airway inflammation, identified by the presence of biomarkers, including history of allergy, high blood eosinophil (EOS) count, and high fractional exhaled nitric oxide levels. Objective: To assess disease burden in relation to type-2 inflammatory biomarker status (history of allergy, blood EOS count, and fractional exhaled nitric oxide level) in patients with uncontrolled and controlled severe asthma in the NOVEL observational longiTudinal studY (NOVELTY) (NCT02760329). Methods: Asthma diagnosis and severity were physician-reported. Control was defined using Asthma Control Test score (uncontrolled = 20) and/or 1 or more severe physician-reported exacerbation in the previous year. Biomarker distribution (history of allergy, blood EOS count, and fractional exhaled nitric oxide level), symptom burden (Asthma Control Test score, modified Medical Research Council dyspnea scale), health status (St George's Respiratory Questionnaire score), exacerbations, and health care resource utilization were assessed. Results: Of 647 patients with severe asthma, 446 had uncontrolled and 123 had controlled asthma. Among those with uncontrolled asthma, 196 (44%) had 2 or more positive biomarkers, 187 (42%) had 1 positive biomarker, 325 (73%) had low blood EOS, and 63 (14%) were triple-negative. Disease burden was similarly high across uncontrolled subgroups, irrespective of biomarker status, with poor symptom control (Asthma Control Test score 14.9-16.6), impaired health status (St George's Respiratory Questionnaire total score 46.7-49.4), clinically important breathlessness (modified Medical Research Council grade >= 2 in 47.3%-57.1%), and 1 or more severe exacerbation (70.6%-76.2%). Conclusions: Type-2 inflammatory biomarkers did not differentiate disease burden in patients with severe asthma. Patients with low type-2 inflammatory biomarker levels have few biologic therapy options; their needs should be addressed

Cluster Analyses From the Real-World NOVELTY Study: Six Clusters Across the Asthma-COPD Spectrum

Background: Asthma and chronic obstructive pulmonary disease (COPD) are complex diseases, the definitions of which overlap. Objective: To investigate clustering of clinical/physiological features and readily available biomarkers in patients with physician-assigned diagnoses of asthma and/or COPD in the NOVEL observational longiTudinal studY (NOVELTY; NCT02760329). Methods: Two approaches were taken to variable selection using baseline data: approach A was data-driven, hypothesis-free and used the Pearson dissimilarity matrix; approach B used an unsupervised Random Forest guided by clinical input. Cluster analyses were conducted across 100 random resamples using partitioning around medoids, followed by consensus clustering. Results: Approach A included 3796 individuals (mean age, 59.5 years; 54% female); approach B included 2934 patients (mean age, 60.7 years; 53% female). Each identified 6 mathematically stable clusters, which had overlapping characteristics. Overall, 67% to 75% of patients with asthma were in 3 clusters, and approximately 90% of patients with COPD were in 3 clusters. Although traditional features such as allergies and current/ex-smoking (respectively) were higher in these clusters, there were differences between clusters and approaches in features such as sex, ethnicity, breathlessness, frequent productive cough, and blood cell counts. The strongest predictors of the approach A cluster membership were age, weight, childhood onset, prebronchodilator FEV1, duration of dust/fume exposure, and number of daily medications. Conclusions: Cluster analyses in patients from NOVELTY with asthma and/or COPD yielded identifiable clusters, with several discriminatory features that differed from conventional diagnostic characteristics. The overlap between clusters suggests that they do not reflect discrete underlying mechanisms and points to the need for identification of molecular endotypes and potential treatment targets across asthma and/or COPD