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.

Expression profiling in developing peach seed and mesocarp as affected by growth regulators

Jasmonates (JAs) and spermidine (Sd) influence fruit (and seed) development and ripening. In order to unravel their effects in peach fruit, at molecular level, field applications of methyl jasmonate (MJ) and propyl dihydrojasmonate (PDJ), and Sd were performed at an early developmental stage (late S1). At commercial harvest, JA-treated fruit were less ripe than controls. Realtime RT-PCR analyses confirmed a down-regulation of ethylene biosynthetic, perception and signaling genes, and flesh softening-related genes. The expression of cell wall-related genes, of a sugar-transporter and hormone-related transcript levels was also affected by JAs. Seeds from JA-treated fruit showed a shift in the expression of developmental marker genes suggesting that the developmental program was probably slowed down, in agreement with the contention that JAs divert resources from growth to defense. JAs also affected phenolic content and biosynthetic gene expression in the mesocarp. Levels of hydroxycinnamic acids, as well as those of flavan-3-ols, were enhanced, mainly by MJ, in S2. Transcript levels of phenylpropanoid pathway genes were up-regulated by MJ, in agreement with phenolic content. Sd-treated fruits at harvest showed reduced ethylene production and flesh softening. Sd induced a short-term and long-term response patterns in endogenous polyamines. At ripening the up-regulation of the ethylene biosynthetic genes was dramatically counteracted by Sd, leading to a down-regulation of softening-related genes. Hormone-related gene expression was also altered both in the short- and long-term. Gene expression analyses suggest that Sd interfered with fruit development/ripening by interacting with multiple hormonal pathways and that fruit developmental marker gene expression was shifted ahead in accord with a developmental slowing down. 24-Epibrassinolide was applied to Flaminia peaches under field conditions early (S1) or later (S3) during development. Preliminary results showed that, at harvest, treated fruit tended to be larger and less mature though quality parameters did not change relative to controls.

Impacts of trace element pollution on sewage sludge and soil-plant systems: developing remediation techniques and assessing plant uptake prevention measures

Trace Elements (TEs) pollution is a significant environmental concern due to its toxic effects on human and ecosystem health and its potential to bioaccumulate in the food chain and to threaten species survival, leading to a decline in biodiversity. Urban areas, industrial and mining activities, agricultural practices, all contribute to the release of TEs into the environment posing a significant risk to human health and ecosystems. Several techniques have been developed to control TEs into the environment. This work presents the findings of three-year PhD program that focused on research on TEs pollution. The study discusses three fundamental aspects related to this topic from the perspective of sustainable development, environmental and human health. (1) High levels of TEs contamination prevent the use of sewage sludge (SS) as a fertilizer in agriculture, despite its potential as a soil amendment. Developing effective techniques to manage TEs contamination in SS is critical to ensure its safe use in agriculture and promote resource efficiency through sludge reuse. Another purpose of the study was to evaluate different strategies to limit the TEs uptake by horticultural crops (specifically, Cucumis Melo L.). This study addressed the effect of seasonality, Trichoderma inoculation and clinoptilolite application on chromium (Cr), copper (Cu) and lead (Pb) content of early- and late-ripening cultivars of Cucumis Melo L.. Finally, the accumulation of copper and the effect of its bioavailable fraction on bacterial and fungal communities in the rhizosphere soil of two vineyards, featuring two different varieties of Vitis vinifera grown for varying lengths of time, were evaluated.