Evaluation of three protein methodologies for marine plankton

[EN]Protein is an important biomass parameter and critical in the enzyme analysis of plankton. When plankton biomass is abundant, obtaining protein samples is not difficult. However, when biomass is a scarce quantity and it needs to be used for many other measurements, obtaining sufficient material for a protein sample is a challenge. If the protein analysis can be made on samples simultaneously prepared for other types of biochemical analyses, this challenge is partially mitigated. The objective of this research was to determine the optimal method for measuring protein content in plankton samples prepared for enzyme analysis.

Research in practice: Bringing behavioural change from lab to studio

Design influences behaviour, whether it's planned or not. Service Design has a great opportunity to lead the emerging field of design for behavioural change, helping guide and shape experiences to benefit users, service providers and wider society. In this article, presented as an evolving conversation between research and practice, Nick Marsh (EMC Consulting) and Dan Lockton (Brunel University) discuss and explore design patterns for influencing behaviour through Service Design, and how Service Designers and academics can work together for social benefit.

New methodologies for risk assessment of GMOs: an experiment of public consultation in Brazil.

2008

New methodologies in CT perfusion and MRI analysis to develop cancer imaging biomarkers

Quantitative imaging in oncology aims at developing imaging biomarkers for diagnosis and prediction of cancer aggressiveness and therapy response before any morphological change become visible. This Thesis exploits Computed Tomography perfusion (CTp) and multiparametric Magnetic Resonance Imaging (mpMRI) for investigating diverse cancer features on different organs. I developed a voxel-based image analysis methodology in CTp and extended its use to mpMRI, for performing precise and accurate analyses at single-voxel level. This is expected to improve reproducibility of measurements and cancer mechanisms’ comprehension and clinical interpretability. CTp has not entered the clinical routine yet, although its usefulness in the monitoring of cancer angiogenesis, due to different perfusion computing methods yielding unreproducible results. Instead, machine learning applications in mpMRI, useful to detect imaging features representative of cancer heterogeneity, are mostly limited to clinical research, because of results’ variability and difficult interpretability, which make clinicians not confident in clinical applications. In hepatic CTp, I investigated whether, and under what conditions, two widely adopted perfusion methods, Maximum Slope (MS) and Deconvolution (DV), could yield reproducible parameters. To this end, I developed signal processing methods to model the first pass kinetics and remove any numerical cause hampering the reproducibility. In mpMRI, I proposed a new approach to extract local first-order features, aiming at preserving spatial reference and making their interpretation easier. In CTp, I found out the cause of MS and DV non-reproducibility: MS and DV represent two different states of the system. Transport delays invalidate MS assumptions and, by correcting MS formulation, I have obtained the voxel-based equivalence of the two methods. In mpMRI, the developed predictive models allowed (i) detecting rectal cancers responding to neoadjuvant chemoradiation showing, at pre-therapy, sparse coarse subregions with altered density, and (ii) predicting clinically significant prostate cancers stemming from the disproportion between high- and low- diffusivity gland components.

Multifarious tumor-oriented small molecules: development of synthetic methodologies and application for diagnostic platforms

Cancer represents one of the most relevant and widespread diseases in the modern age. In this context, integrin receptors are important for the interactions of cells with extracellular matrix and for the development of both inflammation and carcinogenic phenomena. There are many tricks to improve the bioactivity and receptor selectivity of exogenous ligands; one of these is to integrate the amino acid sequence into a cyclic peptide to restrict its conformational space. Another approach is to develop small peptidomimetic molecules in order to enhance the molecular stability and open the way to versatile synthetic strategies. Starting from isoxazoline-based peptidomimetic molecules we recently reported, in this thesis we are going to present the synthesis of new integrin ligands obtained by modifying or introducing appendages on already reported structures. Initially, we are going to introduce the synthesis of linear and cyclic α-dehydro-β-amino acids as scaffolds for the preparation of bioactive peptidomimetics. Subsequently, we are going to present the construction of small molecule ligands (SMLs) based delivery systems performed starting from a polyfunctionalised isoxazoline scaffold, whose potency towards αVβ3 and α5β1 integrins has already been established by our research group. In the light of these results and due to the necessity to understand the behaviour of a single enantiomer of the isoxazoline-based compounds, the research group decided to synthesise the enantiopure heterocycle using a 1,3-dipolar cycloaddiction approach. Subsequently, we are going to introduce the synthesis of a Reporting Drug Delivery System composed by a carrier, a first spacer, a linker, a self-immolative system, a second spacer and a latent fluorophore. The last part of this work will describe the results obtained during the internship abroad in Prof. Aggarwal’s laboratory at the University of Bristol. The project was focused on the Mycapolyol A synthesis.

Supporting Scientific Research Through Machine and Deep Learning: Fluorescence Microscopy and Operational Intelligence Use Cases

Although the debate of what data science is has a long history and has not reached a complete consensus yet, Data Science can be summarized as the process of learning from data. Guided by the above vision, this thesis presents two independent data science projects developed in the scope of multidisciplinary applied research. The first part analyzes fluorescence microscopy images typically produced in life science experiments, where the objective is to count how many marked neuronal cells are present in each image. Aiming to automate the task for supporting research in the area, we propose a neural network architecture tuned specifically for this use case, cell ResUnet (c-ResUnet), and discuss the impact of alternative training strategies in overcoming particular challenges of our data. The approach provides good results in terms of both detection and counting, showing performance comparable to the interpretation of human operators. As a meaningful addition, we release the pre-trained model and the Fluorescent Neuronal Cells dataset collecting pixel-level annotations of where neuronal cells are located. In this way, we hope to help future research in the area and foster innovative methodologies for tackling similar problems. The second part deals with the problem of distributed data management in the context of LHC experiments, with a focus on supporting ATLAS operations concerning data transfer failures. In particular, we analyze error messages produced by failed transfers and propose a Machine Learning pipeline that leverages the word2vec language model and K-means clustering. This provides groups of similar errors that are presented to human operators as suggestions of potential issues to investigate. The approach is demonstrated on one full day of data, showing promising ability in understanding the message content and providing meaningful groupings, in line with previously reported incidents by human operators.

Applications of network-based approaches in drug research

Recent research trends in computer-aided drug design have shown an increasing interest towards the implementation of advanced approaches able to deal with large amount of data. This demand arose from the awareness of the complexity of biological systems and from the availability of data provided by high-throughput technologies. As a consequence, drug research has embraced this paradigm shift exploiting approaches such as that based on networks. Indeed, the process of drug discovery can benefit from the implementation of network-based methods at different steps from target identification to drug repurposing. From this broad range of opportunities, this thesis is focused on three main topics: (i) chemical space networks (CSNs), which are designed to represent and characterize bioactive compound data sets; (ii) drug-target interactions (DTIs) prediction through a network-based algorithm that predicts missing links; (iii) COVID-19 drug research which was explored implementing COVIDrugNet, a network-based tool for COVID-19 related drugs. The main highlight emerged from this thesis is that network-based approaches can be considered useful methodologies to tackle different issues in drug research. In detail, CSNs are valuable coordinate-free, graphically accessible representations of structure-activity relationships of bioactive compounds data sets especially for medium-large libraries of molecules. DTIs prediction through the random walk with restart algorithm on heterogeneous networks can be a helpful method for target identification. COVIDrugNet is an example of the usefulness of network-based approaches for studying drugs related to a specific condition, i.e., COVID-19, and the same ‘systems-based’ approaches can be used for other diseases. To conclude, network-based tools are proving to be suitable in many applications in drug research and provide the opportunity to model and analyze diverse drug-related data sets, even large ones, also integrating different multi-domain information.

Understanding, defining and assessing food systems’ social and economic sustainability indicators: implementation of mixed methodologies for policy insights

Sustainability encompasses the presence of three dimensions that must coexist simultaneously, namely the environmental, social, and economic ones. The economic and social dimensions are gaining the spotlight in recent years, especially within food systems. To assess social and economic impacts, indicators and tools play a fundamental role in contributing to the achievements of sustainability targets, although few of them have deepen the focus on social and economic impacts. Moreover, in a framework of citizen science and bottom-up approach for improving food systems, citizen play a key role in defying their priorities in terms of social and economic interventions. This research expands the knowledge of social and economic sustainability indicators within the food systems for robust policy insights and interventions. This work accomplishes the following objectives: 1) to define social and economic indicators within the supply chain with a stakeholder perspective, 2) to test social and economic sustainability indicators for future food systems engaging young generations. The first objective was accomplished through the development of a systematic literature review of 34 social sustainability tools, based on five food supply chain stages, namely production, processing, wholesale, retail, and consumer considering farmers, workers, consumers, and society as stakeholders. The second objective was achieved by defining and testing new food systems social and economic sustainability indicators through youth engagement for informed and robust policy insights, to provide policymakers suggestions that would incorporate young generations ones. Future food systems scenarios were evaluated by youth through focus groups, whose results were analyzed through NVivo and then through a survey with a wider platform. Conclusion addressed the main areas of policy interventions in terms of social and economic aspects of sustainable food systems youth pointed out as in need of interventions, spanning from food labelling reporting sustainable origins to better access to online food services.

RICORDACI: Research on the Conservation, Restoration and Diagnosis of Cinematographic Films

This thesis is the result of the RICORDACI project, a three-year European-funded initiative involving the collaboration between the University of Bologna and the restoration laboratory of the Cineteca di Bologna, L'immagine Ritrovata, which aimed to develop innovative solutions and technologies for the preservation of cinematographic film heritage. In particular, this thesis presents new analytical methodologies to exploit two types of portable miniaturized Near Infrared spectrometers working in Diffuse Reflectance over the Short Wave Infrared (SWIR) range, to study the near infrared (NIR) spectral behavior of film base materials for an accurate, non-invasive and fast characterization of the polymer type; and for films with cellulose acetate supports, they can be employed as a diagnostic tool for monitoring the Degree of substitution (DS) affected by the loss of acetyl groups. The proposed methods offer non-invasive, fast, inexpensive and simple alternatives for the characterization and diagnosis of film bases to help the strategic planning and decision-making regarding storage, digitalization and intervention of film collections. Secondly, the thesis includes the evaluation of new green cleaning systems and solvents for the effective, fast and innocuous removal of undesired substances from degraded cinematographic films bases; these tests compared the efficiency of traditional systems and solvents against the new proposals. Firstly, the use of Deep Eutectic Solvent formulations for removing softened gelatin residues from cellulose nitrate bases; and secondly, the employment of green volatile solvents with different application methods, including the use of new electrospun nylon mats, for avoiding the dangerous use of friction for the removal of Triphenyl Phosphate blooms from the surface of cellulose acetate bases. The results obtained will help improving the efficiency of the interventions needed before the digitalization of historical cinematographic films and will pave the way for further investigation on the use of green solvents for cleaning polymeric heritage objects.

Historic and modern alloys: atmospheric corrosion and development of accelerated ageing methodologies

The atmospheric corrosion of modern and historic alloys used in cultural heritage has been investigated by applying specific accelerated ageing methods. Three main research lines were carried out, involving different materials. In the first part, the atmospheric corrosion of a modern Cu-3Si-1Mn bronze was investigated through accelerated ageing tests simulating outdoor runoff conditions. The corrosion processes were evaluated through different analyses, and the results obtained were compared to those of a traditional quaternary bronze. The second line was carried out to characterise historic aluminium alloys used in aeronautics to develop and apply innovative protection strategies for their conservation. Historic wrecks were identified and characterised through micro and macroscale observations. Moreover, accelerated ageing tests were performed on both historic and modern alloys to compare their behaviour and select the best modern substrate to be used for the development of effective coatings. The third research line aimed to develop accelerate sampling and ageing methods to investigate the role of particulate matter (PM) in the atmospheric corrosion of bronzes and metals in general. The first approach consisted in the fine-tuning of an efficient accelerated method for ambient PM sampling on bronze specimens followed by their accelerated ageing, in order to establish a correlation between the PM and the substrate’s corrosion. After the accelerated ageing of the specimens, the corrosion was evaluated by surface characterisation and correlated to the PM features. The second approach consisted in the development of a synthetic PM formulation and of an artificial deposition method, which was performed by spraying mixtures containing the main PM inorganic fractions on a G-85 bronze with an airbrush. The deposition efficiency was assessed, and the effect of synthetic PM on the bronze corrosion was evaluated. The results were compared to those obtained by ambient PM deposition.

Methodologies for the analysis and interpretation of environmental datasets from areas interested by offshore activities

The exploitation of hydrocarbon reservoirs by the oil and gas industries represents one of the most relevant and concerning anthropic stressor in various marine areas worldwide and the presence of extractive structures can have severe consequences on the marine environment. Environmental monitoring surveys are carried out to monitor the effects and impacts of offshore energy facilities. Macrobenthic communities, inhabiting the soft-bottom, represent a key component of these surveys given their great responsiveness to natural and anthropic changes. A comprehensive collection of monitoring data from four Italian seas was used to investigate distributional pattern of macrozoobenthos assemblages confirming a high spatial variability in relation to the environmental variables analyzed. Since these datasets could represent a powerful tool for the industrial and scientific research, the steps and standardized procedures needed to obtain robust and comparable high-quality data were investigated and outlined. Over recent years, decommissioning of old platforms is a growing topic in this sector, involving many actors in the various decision-making processes. A Multi-Criteria Decision Analysis, specific for the Adriatic Sea, was developed to investigate the impacts of decommissioning of a gas platform on environmental and socio-economic aspects, to select the best decommissioning scenario. From the scenarios studied, the most impacting one has resulted to be total removal, affecting all the faunal component considered in the study. Currently, the European nations are increasing the production of energy from offshore wind farms with an exponential expansion. A comparative study of methodologies used five countries of the North Sea countries was carried out to investigate the best approaches to monitor the effects of wind farms on the benthic communities. In the foreseeable future, collaboration between industry, scientific communities, national and international policies are needed to gain knowledge concerning the effects of these industrial activities on the ecological status of the ecosystems.

Boys In White: A Classic Of Qualitative Research Turns 50.

This article analyzes Boys in white: student culture in medical schoolby Howard S. Becker, Blanche Geer, Everett C. Hughes and Anselm Strauss, considered a model of qualitative research in sociology. The analysis investigates the trajectories of the authors, the book, qualitative analysis, and the medical students, emphasizing their importance in the origins of medical sociology and the sociology of medical education. In the trajectory of the authors, bibliographical information is given. The trajectory of qualitative research focuses on how this methodology influences the construction of the field. The investigation of the students' trajectory shows how they progress through their first years at medical school to build their own student culture.

[strategies For Tackling Absenteeism In Dental Appointments In The Family Health Units Of A Large Municipality: Action Research].

The aim of this study was to analyze the reasons for missed appointments in dental Family Health Units (FHU) and implement strategies to reduce same through action research. This is a study conducted in 12 FHUs in Piracicaba in the State of São Paulo from January, 1 to December, 31 2010. The sample was composed of 385 users of these health units who were interviewed over the phone and asked about the reasons for missing dental appointments, as well as 12 dentists and 12 nurses. Two workshops were staged with professionals: the first to assess the data collected in interviews and develop strategy, and the second for evaluation after 4 months. The primary cause for missed appointments was the opening hours of the units coinciding with the work schedule of the users. Among the strategies suggested were lectures on oral health, ongoing education in team meetings, training of Community Health Agents, participation in therapeutic groups and partnerships between Oral Health Teams and the social infrastructure of the community. The adoption of the single medical record was the strategy proposed by professionals. The strategies implemented led to a 66.6% reduction in missed appointments by the units and the motivating nature of the workshops elicited critical reflection to redirect health practices.