A new approach for extracellular RNA recovery from Rhodovulum sulfidophilum

The development of RNA-based drugs is highly pursued due to the possibility of creating viable and effective therapies. However, their translation to clinical practice strongly depends on efficient technologies to produce substantial levels of these biomolecules, with high purity and high quality. RNAs are commonly produced by chemical or enzymatic methods, displaying these limitations. In this sense, recombinant production arises as a promising, cost-effective method, allowing large-scale production of RNA. Rhodovulum sulfidophilum (R. sulfidophilum), a marine purple bacterium, offers the advantage of RNA secretion into the extracellular medium, which contains low levels of RNases and other impurities. Therefore, RNA recovery can be simplified compared to standard extraction protocols involving cell lysis, resulting in a more clarified sample and an improved downstream process. In this work, R. sulfidophilum was transformed with a plasmid DNA encoding pre-miR-29b-1, which is known to be involved in the Alzheimer's disease pathway. After production, the pre-miR-29b-1 was recovered through different extraction methods to verify the most advantageous one. A protocol for extracellular RNA recovery was then established, revealing to be a simpler and less time-consuming method, reducing around 16 h in execution time and the quantity of reagents needed when compared to other established methods. The new strategy brings the additional advantage of eliminating the toxic organic compounds routinely used in intracellular RNA extractions. Overall, the optimized process described here, using isopropanol as the precipitation agent, offers a greener, safer, and faster alternative for recombinant RNA recovery and concentration, with an extracellular RNA recovery of 7 μg/mL and target pre-miRNA-29b-1 recovery of 0.7 μg/L of medium

High-density perfusion cultures of the marine bacterium Rhodovulum sulfidophilum for the biomanufacturing of oligonucleotides

Therapeutic oligonucleotides (ONs) are typically manufactured via solid-phase synthesis, characterized by limited scalability and huge environmental footprint, limiting their availability. Biomanufactured ONs have the potential to reduce the immunogenic side-effects, and to improve the sustainability of their chemical counterparts. Rhodovulum sulfidophilum was demonstrated a valuable host for the extracellular production of recombinant ONs. However, low viable cell densities and product titer were reported so far. In this work, perfusion cell cultures were established for the intensification of ON biomanufacturing. First, the perfusion conditions were simulated in 50 mL spin tubes, selected as a scale-down model of the process, with the aim of optimizing the medium composition and process parameters. This optimization stage led to an increase in the cell density by 44 % compared to the reference medium formulation. In addition, tests at increasing perfusion rates were conducted until achieving the maximum viable cell density (VCDmax), allowing the determination of the minimum cell-specific perfusion rate (CSPRmin) required to sustain the cell culture. Intriguingly, we discovered in this system also a maximum CSPR, above which growth inhibition starts. By leveraging this process optimization, we show for the first time the conduction of perfusion cultures of R. sulfidophilum in bench-scale bioreactors. This process development pipeline allowed stable cultures for more than 20 days and the continuous biomanufacturing of ONs, testifying the great potential of perfusion processes

Terrestrial very-long-baseline atom interferometry: Workshop summary

This document presents a summary of the 2023 Terrestrial Very-Long-Baseline Atom Interferometry Workshop hosted by CERN. The workshop brought together experts from around the world to discuss the exciting developments in large-scale atom interferometer (AI) prototypes and their potential for detecting ultralight dark matter and gravitational waves. The primary objective of the workshop was to lay the groundwork for an international TVLBAI proto-collaboration. This collaboration aims to unite researchers from different institutions to strategize and secure funding for terrestrial large-scale AI projects. The ultimate goal is to create a roadmap detailing the design and technology choices for one or more kilometer–scale detectors, which will be operational in the mid-2030s. The key sections of this report present the physics case and technical challenges, together with a comprehensive overview of the discussions at the workshop together with the main conclusions

Pulsed antihydrogen production for direct gravitational measurement on antimatter

openOne of the biggest efforts of the antimatter community is to measure gravity on a neutral antimatter system towards a direct test of the validity of the Weak Equivalence Principle (WEP). WEP is a cornerstone of the General Relativity and such a test has never been carried out on antimatter. Electrically neutral antimatter systems are expected to behave in exactly the same way as their matter counterparts. Several indirect arguments indicate that possible differences between the free fall of matter and antimatter, if existing, wouldn't be greater than 10^-6 g. To date, however, the question of whether antimatter falls in the Earth's gravitational field with the same acceleration g as ordinary matter does not yet have a direct experimental answer. Antihydrogen is the bound state of an antiproton and a positron. It is the simplest antimatter atom - and the only one ever synthesised. In AEgIS, antihydrogen is formed through charge exchange reaction between laser-excited positronium and cold trapped antiprotons. Positronium (Ps) is a purely leptonic hydrogen-like bound state composed of an electron and a positron. In this thesis, I present the first pulsed formation of antihydrogen, achieved in aegis as a core topic of my work in the last three years, from late 2016 to early 2020. The work here presented was carried out between the end of the Run 2 and the beginning of the Long Shut down 2 (LS2). During this period, I was a member of the aegis Collaboration and part of the aegis Genoa Group. The experimental activities involving antiprotons are expected to resume in 2021. Pulsed antihydrogen production is the crucial achievement to validate the aegis experimental approach to perform the gravity measurement on antimatter. A key feature of this result is the knowledge, within few hundred ns, of the Hbar production time. Previous production schemes provide a quasi-continuous source of antihydrogen without the possibility of precisely tagging the time of formation. The achievement of a pulsed production of antihydrogen opens the possibility to measure the atoms' time-of-flight, unavailable from currently available trap-based methods. This is an important accomplishment and a paper with the results presented in this thesis was submitted to Nature Physics. The aegis Genoa Group is responsible for the trap system, detection and data acquisition systems. The trap system is the main system of the experimental apparatus. The electronics of all the other systems depend on that of the trap system. I strongly contributed to the developments on antiproton manipulation procedures and related detection techniques. Among the results of this thesis work, an outstanding antiproton plasma compression was obtained, allowing the movement of antiproton clouds into the production trap in suitable conditions for the formation of antihydrogen and its detection. Remarkably, with a minimum cloud radius of 0.17 mm, such compression is the best ever reached for antiprotons. A number of stored antiprotons about 10 times larger than expected in the original aegis proposal was stored in the production trap for macroscopic times, despite the design limitations of the electrodes. Several novel detection techniques were implemented in the positronium diagnostics, also with my contribution. In particular, the use of a kicker pulser to detect the charge induced by the passage of the positron bunch was developed, tested and used as a main technique to monitor the condition of the positrons entering the main apparatus. This work was carried out by the Genoa Group, also responsible for the pos transfer line, its mechanics and detection system. On the top of this, the conversion of the MCP into a position sensitive detector for slow positronium allowed to characterise the Rydberg state of this unstable atom in magnetic field. The work for the fine tuning and characterisation of the new detection techniques was part of the activities I carried out during the data taking period. Finally, I evaluated the possibility to use a novel scintillating material in the detection of excited positronium produced in the Hbar production region to fully overcome the present existing limitations. I completed an extensive calibration of the material and I assembled a detector coupling such scintillator with a fast response photomultiplier tube. Such detector succeeded in detecting the formation of positronium and gave encouraging results for the detection of the elusive Rydberg-Ps states in magnetic field. I wrote a paper on this activity for the submission to a technical newspaper. At the moment, the article is under internal review.embargoed_20200918XXXII CICLO - FISICADr. Gemma Testera, INFN Coordinatore del corso: Prof. Riccardo Ferrando, non presente nell'elencoFani', Matti

Collaborative Visual Place Recognition through Federated Learning

Visual Place Recognition (VPR) aims to estimate the location of an image by treating it as a retrieval problem. VPR uses a database of geo-tagged images and leverages deep neural networks to extract a global representation, called descriptor, from each image. While the training data for VPR models often originates from diverse, geographically scattered sources (geo-tagged images), the training process itself is typically assumed to be centralized. This research revisits the task of VPR through the lens of Federated Learning (FL), addressing several key challenges associated with this adaptation. VPR data inherently lacks well-defined classes, and models are typically trained using contrastive learning, which necessitates a data mining step on a centralized database. Additionally, client devices in federated systems can be highly heterogeneous in terms of their processing capabilities. The proposed FedVPR framework not only presents a novel approach for VPR but also introduces a new, challenging, and realistic task for FL research. This has the potential to spur the application of FL to other image retrieval tasks