Regulatory role of rpL3 in cell response to nucleolar stress induced by Act D in tumor cells lacking functional p53

Many chemotherapeutic drugs cause nucleolar stress and p53-independent pathways mediating the nucleolar stress response are emerging. Here, we demonstrate that ribosomal stress induced by Actinomycin D (Act D) is associated to the up-regulation of ribosomal protein L3 (rpL3) and its accumulation as ribosome-free form in lung and colon cancer cell lines devoid of p53. Free rpL3 regulates p21 expression at transcriptional and post-translational levels through a molecular mechanism involving extracellular-signal-regulated kinases1/2 (ERK1/2) and mouse double minute-2 homolog (MDM2). Our data reveal that rpL3 participates to cell response acting as a critical regulator of apoptosis and cell migration. It is noteworthy that silencing of rpL3 abolishes the cytotoxic effects of Act D suggesting that the loss of rpL3 makes chemotherapy drugs ineffective while rpL3 overexpression was associated to a strong increase of Act D-mediated inhibition of cell migration. Taking together our results show that the efficacy of Act D chemotherapy depends on rpL3 status revealing new specific targets involved in the molecular pathways activated by Act D in cancers lacking of p53. Hence, the development of treatments aimed at upregulating rpL3 may be beneficial for the treatment of these cancers

Cysteine Prevents the Reduction in Keratin Synthesis Induced by Iron Deficiency in Human Keratinocytes

L-cysteine is currently recognized as a conditionally essential sulphur amino acid. Besides contributing to many biological pathways, cysteine is a key component of the keratin protein by its ability to form disulfide bridges that confer strength and rigidity to the protein. In addition to cysteine, iron represents another critical factor in regulating keratins expression in epidermal tissues, as well as in hair follicle growth and maturation. By focusing on human keratinocytes, the aim of this study was to evaluate the effect of cysteine supplementation as nutraceutical on keratin biosynthesis, as well as to get an insight on the interplay of cysteine availability and cellular iron status in regulating keratins expression in vitro. Herein we demonstrate that cysteine promotes a significant up-regulation of keratins expression as a result of de novo protein synthesis, while the lack of iron impairs keratin expression. Interestingly, cysteine supplementation counteracts the adverse effect of iron deficiency on cellular keratin expression. This effect was likely mediated by the up-regulation of transferrin receptor and ferritin, the main cellular proteins involved in iron homeostasis, at last affecting the labile iron pool. In this manner, cysteine may also enhance the metabolic iron availability for DNA synthesis without creating a detrimental condition of iron overload. To the best of our knowledge, this is one of the first study in an in vitro keratinocyte model providing evidence that cysteine and iron cooperate for keratins expression, indicative of their central role in maintaining healthy epithelia. This article is protected by copyright. All rights reserved

Active deep learning for nonlinear optics design of a vertical FFA accelerator

Vertical Fixed-Field Alternating Gradient (vFFA) accelerators exhibit particle orbits which move vertically during acceleration. This recently rediscovered circular accelerator type has several advantages over conventional ring accelerators, such as zero momentum compaction factor. At the same time, inherently non-planar orbits and a unique transverse coupling make controlling the beam dynamics a complex task. In general, betatron tune adjustment is crucial to avoid resonances, particularly when space charge effects are present. Due to highly nonlinear magnetic fields in the vFFA, it remains a challenging task to determine an optimal lattice design in terms of maximising the dynamic aperture. This contribution describes a deep learning based algorithm which strongly improves on regular grid scans and random search to find an optimal lattice: a surrogate model is built iteratively from simulations with varying lattice parameters to predict the dynamic aperture. The training of the model follows an active learning paradigm, which thus considerably reduces the number of samples needed from the computationally expensive simulations

Assessment of plaque morphology in alzheimer’s mouse cerebellum using three-dimensional X-ray phase-based virtual histology

Visualization and characterization of beta -amyloid deposits is a fundamental task in pre-clinical study of Alzheimer's disease (AD) to assess its evolution and monitor the efficiency of new therapeutic strategies. While the cerebellum is one of the brain areas most underestimated in the context of AD, renewed interest in cerebellar lesions has recently arisen as they may link to motor and cognitive alterations. Thus, we quantitatively investigated three-dimensional plaque morphology in the cerebellum in APP/PS1 transgenic mouse, as a model of AD. In order to obtain a complete high-resolution three-dimensional view of the investigated tissue, we exploited synchrotron X-ray phase contrast tomography (XPCT), providing virtual slices with histology-matching resolution. We found the formation of plaques elongated in shape, and with a specific orientation in space depending on the investigated region of the cerebellar cortex. Remarkably, a similar shape is observed in human cerebellum from demented patients. Our findings demonstrate the capability of XPCT in volumetric quantification, supporting the current knowledge about plaque morphology in the cerebellum and the fundamental role of the surrounding tissue in driving their evolution. A good correlation with the human neuropathology is also reported

P2‐111: MESENCHYMAL STEM CELL‐DERIVED SECRETOME FULLY REPLICATE CELL‐MEDIATED NEURO‐REPARATIVE ACTIVITIES IN THE APP/PS1 MOUSE MODEL OF ALZHEIMER'S DISEASE

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Online fit of an analytical response matrix model for orbit correction and optical function measurement

At the Karlsruhe Research Accelerator (KARA), an analytical online model of the orbit response matrix (ORM) has been developed and tested. The model, called the bilinear-exponential model with dispersion (BE+d model), is derived from the Mais-Ripken formalism describing coupled betatron motion. Compared to the standard approach of measuring the ORM, this method continuously adapts to changing beam optics without a dedicated measurement. It is especially useful for storage rings without turn-by-turn capable beam position monitors (BPMs) as the online model also gives access to estimates of the coupled optical functions. In the following, experimental orbit correction results and a comparison of fitted and simulated optical functions are presented

Consensus communication strategies to improve doctor-patient relationship in paediatric severe asthma

Background: Asthma is a chronic inflammatory disease that is very common among youth worldwide. The burden of this illness is very high not only considering financial costs but also on emotional and social functioning. Guidelines and many researches recommend to develop a good communication between physicians and children/caregiver and their parents. Nevertheless, a previous Italian project showed some criticalities in paediatric severe asthma management. The consensus gathered together experts in paediatric asthma management, experts in narrative medicine and patient associations with the aim of identify simple recommendation to improve communication strategies. Methods: Participants to the consensus received the results of the project and a selection of narratives two weeks before the meeting. The meeting was structured in plenary session and in three working groups discussing respectively about communication strategies with children, adolescents and parents. The task of each working group was to identify the most effective (DO) and least effective practices (DON' T) for 5 phases of the visit: welcome, comprehension of the context, emotions management, duration and end of the visit and endurance of the relationship. Results: Participants agreed that good relationships translate into positive outcomes and reached consensus on communication strategies to implement in the different phase of relationships. Conclusions: The future challenges identified by the participants are the dissemination of this Consensus document and the implementation of effective communication strategies to improve the management of pediatric asthma

Analysis of diabetic patients through their examination history

The analysis of medical data is a challenging task for health care systems since a huge amount of interesting knowledge can be automatically mined to effectively support both physicians and health care organizations. This paper proposes a data analysis framework based on a multiple-level clustering technique to identify the examination pathways commonly followed by patients with a given disease. This knowledge can support health care organizations in evaluating the medical treatments usually adopted, and thus the incurred costs. The proposed multiple-level strategy allows clustering patient examination datasets with a variable distribution. To measure the relevance of specific examinations for a given disease complication, patient examination data has been represented in the Vector Space Model using the TF-IDF method. As a case study, the proposed approach has been applied to the diabetic care scenario. The experimental validation, performed on a real collection of diabetic patients, demonstrates the effectiveness of the approach in identifying groups of patients with a similar examination history and increasing severity in diabetes complication

A low-latency feedback system for the control of horizontal betatron oscillations

Reinforcement learning (RL) algorithms are investigated at KIT as an option to control the beam dynamics at storage rings. These methods require specialized hardware to satisfy throughput and latency constraints dictated by the timescale of the relevant phenomena. The KINGFISHER platform, based on the novel Xilinx Versal Adaptive Compute and Acceleration Platform, is an ideal candidate to deploy RL-on-a-chip thanks to its ability to execute computationally intensive and low latency feedback loops in the order of tens of microseconds. In this publication, we will present the integration of the KINGFISHER system at the Karlsruhe Research Accelerator (KARA), as a proof-of-principle turn-by-turn control feedback loop, to control induced transversal oscillations of an electron beam