Cholesterol impairment contributes to neuroserpin aggregation

Intraneural accumulation of misfolded proteins is a common feature of several neurodegenerative pathologies including Alzheimer's and Parkinson's diseases, and Familial Encephalopathy with Neuroserpin Inclusion Bodies (FENIB). FENIB is a rare disease due to a point mutation in neuroserpin which accelerates protein aggregation in the endoplasmic reticulum (ER). Here we show that cholesterol depletion induced either by prolonged exposure to statins or by inhibiting the sterol regulatory binding-element protein (SREBP) pathway also enhances aggregation of neuroserpin proteins. These findings can be explained considering a computational model of protein aggregation under non-equilibrium conditions, where a decrease in the rate of protein clearance improves aggregation. Decreasing cholesterol in cell membranes affects their biophysical properties, including their ability to form the vesicles needed for protein clearance, as we illustrate by a simple mathematical model. Taken together, these results suggest that cholesterol reduction induces neuroserpin aggregation, even in absence of specific neuroserpin mutations. The new mechanism we uncover could be relevant also for other neurodegenerative diseases associated with protein aggregation.Comment: 7 figure

Optimal task positioning in multi-robot cells, using nested meta-heuristic swarm algorithms

Abstract Process planning of multi-robot cells is usually a manual and time consuming activity, based on trials-and-errors. A co-manipulation problem is analysed, where one robot handles the work-piece and one robot performs a task on it and a method to find the optimal pose of the work-piece is proposed. The method, based on a combination of Whale Optimization Algorithm and Ant Colony Optimization algorithm, minimize a performance index while taking into account technological and kinematics constraints. The index evaluates process accuracy considering transmission elasticity, backslashes and distance from joint limits. Numerical simulations demonstrate the method robustness and convergence

A proximal minimization based distributed approach to power control in wireless networks: performance and comparative analysis

In this paper, we address power control in a wireless cellular network where multiple mobile users are served by a set of base stations, one per cell. Their reference base station has then to set their transmission power so as to maximize the level of service measured in terms of transmission throughput. Interference due to communication of devices on the same wireless channel is coupling the decisions of all base stations in the cellular network. We propose a distributed algorithm based on proximal minimization that makes the base stations reach consensus to a solution that guarantees an optimal throughput for all mobile devices, by appropriately setting the Signal to Interference plus Noise Ratio (SINR). The introduced algorithm is compared with a gradient-based distributed algorithm via an extensive simulation study, which reveals the advantage of proximal minimization in the case when the cost function is non-differentiable and the sub-gradient has to be computed

Integrated Robot Motion and Process control for manufacturing reshaping

The future of metal manufacturing processes like laser cutting, welding, and additive manufacturing shall rely on intelligent systems spearheaded by Industry 4.0. Such a digital innovation is indeed driving machinery builders to a profound transformation. From custom machines designed and optimized for a specific process, the ambition is to exploit the openness and the large availability of industrial robots to increase flexibility and reconfigurability of multi processes implementations. The challenge is that machinery builders transform themselves into high-knowledge specialized process-driven robot integrators, able to optimize the robot motion with the process controller leveraging on intelligent sensing and cognition. The work describes the multi-annual collaboration of the BLM group and Politecnico di Milano, with the support of CNR, focused on the deployment of a complete working robotic workstation characterized by the full integration of the robot control and motion planning with manufacturing processes

Multimodal imaging for clinical target volume definition in prone whole-breast irradiation: a single institution experience

Aim: The aim was identification of reference structures for breast clinical target volume (CTV) in prone position, throughout image fusion process. Materials & methods: We analyzed breast glandular tissue distribution in 20 diagnostic MRIs, referring to structures reported in ESTRO guidelines for supine irradiation. The volume containing breast glandular tissue in all cases was defined as MRI prone CTV (MRIpCTV). Then in ten subsequent patients planned for prone irradiation, MRI and computed tomography (CT) simulation was acquired. MRIpCTV was defined followed by our findings and transferred to CT for definitive delineation. Results: MRIpCTV was defined by the caudal edge of clavicular head, 3 mm above inframammary fold, by the medial thoracic artery, by a plane passing through the lateral surface of pectoralis muscles, by the anterior surface of pectoralis muscles and 3 mm from the skin. Deformed CTV was consistent with anatomy on CT; the limits chosen for MRIpCTV fit adequately also for CT. Conclusion: Prone irradiation is an alternative set up for selected cases, so the sample is very small. However, our suggestions could be of aid in defining prone CTV. The good consistency between MRI and CT seems to confirm that MRI may be unnecessary in routine practice

Tissue expression of lactate transporters (MCT1 and MCT4) and prognosis of malignant pleural mesothelioma (brief report)

Funder: NIHR Cambridge Biomedical Research CentreFunder: Medical Research Council; doi: http://dx.doi.org/10.13039/501100000265Abstract: Background: Malignant pleural mesothelioma (MPM) is an aggressive neoplasm of the pleura, mainly related to asbestos exposure. As in other solid tumors, malignant cells exhibit high glucose uptake and glycolytic rates with increased lactic acid efflux into the interstitial space. Lactate transport into and out of cells, crucial to maintaining intracellular pH homeostasis and glycolysis, is carried out by monocarboxylate transporters (MCTs) and the chaperone basigin (CD147). We set out to examine the clinical significance of basigin, MCT1 and MCT4 in the context of MPM and to evaluate their expression in relation to the evolution of the disease. Methods: We used immunohistochemistry to measure the expression of basigin, MCT1 and MCT4 in a cohort of 135 individuals with MPM compared to a series of 15 non-MPM pleura specimens. Moreover, by Kaplan–Meier and Cox analyses we evaluated whether an expression over the average of these markers could be associated with the patients’ overall survival (OS). Results: We detected positive staining of basigin, MCT1, and MCT4 in most MPM specimens. In particular, MCT4 was always positive in malignant tissues but undetectable in the 4 normal pleural specimens incorporated within the tissue microarray. This was confirmed in the additional series of 15 normal pleural samples. Moreover, MCT4 expression was significantly associated with reduced OS. Conclusion: In this study, the tissue expression of basigin did not prove to be exploitable as a diagnostic or prognostic marker for MPM patients. The expression of MCT1 was not informative either, being tightly correlated with that of basigin. However, the expression of MCT4 showed promise as a diagnostic/therapeutic and prognostic biomarker

Metabolism of the EGFR tyrosin kinase inhibitor gefitinib by cytochrome P450 1A1 enzyme in EGFR-wild type non small cell lung cancer cell lines

<p>Abstract</p> <p>Background</p> <p>Gefitinib is a tyrosine kinase inhibitor (TKI) of the epidermal growth factor receptor (EGFR) especially effective in tumors with activating EGFR gene mutations while EGFR wild-type non small cell lung cancer (NSCLC) patients at present do not benefit from this treatment.</p> <p>The primary site of gefitinib metabolism is the liver, nevertheless tumor cell metabolism can significantly affect treatment effectiveness.</p> <p>Results</p> <p>In this study, we investigated the intracellular metabolism of gefitinib in a panel of EGFR wild-type gefitinib-sensitive and -resistant NSCLC cell lines, assessing the role of cytochrome P450 1A1 (CYP1A1) inhibition on gefitinib efficacy. Our results indicate that there is a significant difference in drug metabolism between gefitinib-sensitive and -resistant cell lines. Unexpectedly, only sensitive cells metabolized gefitinib, producing metabolites which were detected both inside and outside the cells. As a consequence of gefitinib metabolism, the intracellular level of gefitinib was markedly reduced after 12-24 h of treatment. Consistent with this observation, RT-PCR analysis and EROD assay showed that mRNA and activity of CYP1A1 were present at significant levels and were induced by gefitinib only in sensitive cells. Gefitinib metabolism was elevated in crowded cells, stimulated by exposure to cigarette smoke extract and prevented by hypoxic condition. It is worth noting that the metabolism of gefitinib in the sensitive cells is a consequence and not the cause of drug responsiveness, indeed treatment with a CYP1A1 inhibitor increased the efficacy of the drug because it prevented the fall in intracellular gefitinib level and significantly enhanced the inhibition of EGFR autophosphorylation, MAPK and PI3K/AKT/mTOR signalling pathways and cell proliferation.</p> <p>Conclusion</p> <p>Our findings suggest that gefitinib metabolism in lung cancer cells, elicited by CYP1A1 activity, might represent an early assessment of gefitinib responsiveness in NSCLC cells lacking activating mutations. On the other hand, in metabolizing cells, the inhibition of CYP1A1 might lead to increased local exposure to the active drug and thus increase gefitinib potency.</p