Fractional Calculus as Modelling Tool

Cancer is a complex disease, responsible for a significant portion of global deaths. The increasing prioritisation of know-why over know-how approaches in biological research has favoured the rising use of both white- and black-box mathematical techniques for cancer modelling, seeking to better grasp the multi-scale mechanistic workings of its complex phenomena (such as tumour-immune interactions, drug resistance, tumour growth and diffusion, etc.). In light of this wide-ranging use of mathematics in cancer modelling, the unique memory and non-local properties of Fractional Calculus (FC) have been sought after in the last decade to replace ordinary differentiation in the hypothesising of FC’s superior modelling of complex oncological phenomena, which has been shown to possess an accumulated knowledge of its past states. As such, this review aims to present a thorough and structured survey about the main guiding trends and modelling categories in cancer research, emphasising in the field of oncology FC’s increasing employment in mathematical modelling as a whole. The most pivotal research questions, challenges and future perspectives are also outlined.publishersversionpublishe

Characterization of multi-drug resistant Escherichia coli in the UV-treated outflow of an urban wastewater treatment plant

info:eu-repo/semantics/publishedVersio

Non-essential elements and their role in sustainable agriculture

Agricultural systems are constantly under environmental pressure, and the continuous rise of the global population requires an increasingly intensification of agronomical productivity. To meet the current global food demand, particularly in depleted ecosystems under adverse climate conditions, the development of novel agronomical practices, which ensure crop productivity while safeguarding minimal impact to the environment, must be encouraged. Since aluminium (Al), cobalt (Co), selenium (Se), silicon (Si) and sodium (Na) are not essential to plant metabolism, their benefits are often neglected or underestimated in agriculture; however, several studies support their advantages in sustainable agriculture when properly employed. The agronomical uses of these elements have been studied in the last decades, delivering important cues for the improvement of food and feed production worldwide due to beneficial effects in plant growth and productivity, nutrient balance, pest and pathogen resistance, water stress management, heavy-metal toxicity alleviation, and postharvest performance. However, their application has not been addressed as part of a holistic conservation strategy that supports the sustainability of agroecosystems. Here, we discuss the potential use of these elements in sustainable agriculture, and the knowledge gaps that hinder their effective integration into agronomical practices, which result in equally profitable applications while supporting environmental sustainability.info:eu-repo/semantics/publishedVersio

Computing the Largest Bond of a Graph

A bond of a graph G is an inclusion-wise minimal disconnecting set of G, i.e., bonds are cut-sets that determine cuts [S,VS] of G such that G[S] and G[VS] are both connected. Given s,t in V(G), an st-bond of G is a bond whose removal disconnects s and t. Contrasting with the large number of studies related to maximum cuts, there are very few results regarding the largest bond of general graphs. In this paper, we aim to reduce this gap on the complexity of computing the largest bond and the largest st-bond of a graph. Although cuts and bonds are similar, we remark that computing the largest bond of a graph tends to be harder than computing its maximum cut. We show that Largest Bond remains NP-hard even for planar bipartite graphs, and it does not admit a constant-factor approximation algorithm, unless P = NP. We also show that Largest Bond and Largest st-Bond on graphs of clique-width w cannot be solved in time f(w) x n^{o(w)} unless the Exponential Time Hypothesis fails, but they can be solved in time f(w) x n^{O(w)}. In addition, we show that both problems are fixed-parameter tractable when parameterized by the size of the solution, but they do not admit polynomial kernels unless NP subseteq coNP/poly

Labrys portucalensis F11 efficiently degrades Di-(2-ethylhexyl) Phthalate

info:eu-repo/semantics/publishedVersio

Implications of nanoparticles functionalization in supramolecular magnetogels for drug delivery

In this work, dehydropeptide gels were loaded with citrate- or lipid-stabilized nanoparticles to evaluate the effect over doxorubicin release. Particularly, the lipid-stabilized nanoparticles co-assembled with the hydrogel fibres forming lipid-fibre interface domains.Portugal2020, Compete2020, FEDER. SFRH/BD/144017/2019. PTDC/QUI-QFI/28020/2017. UIDB/04650/202

Supramolecular magnetolipogels: a co-assembly strategy for on-demand drug release

In this work, magnetic liposomes, both solid and aqueous, were loaded with a model drug and combined with dehydropeptide-based hydrogels. The encapsulated drug distributed between hydrogel fibres and magnetoliposomes lipid bilayer, which was demonstrated to be independent of the magnetoliposome’s nanoarchitecture, resulting in an attenuated drug release from the magnetolipogels compared to hydrogels.UIDB/00686/2020. UIDB/04650/2020. SFRH/BD/144017/201

Dehydropeptide-based plasmonic lipogels as bionanosystems for controlled drug release

In this work, silica-coated gold nanoparticles and liposomes (storage units) were combined with dehydropeptide-based hydrogels as a proof-of-concept to afford peptide-based NIR light-responsive lipogels. Several liposomes compositions were assessed to study its influence on the final assembly properties. Gold nanospheres were used to assess the preparation method that enabled a closer proximity of the nanoparticles to the liposomes.Ministerio de Economía y Competitividad de España (PID2020-113704RB-I00), Xunta de Galicia (Centro Singular de Investigación de Galicia - Accreditation 2019-2022 ED431G 2019/06 and IN607A 2018/5), and European Union-ERDF (Interreg V-A - Spain-Portugal 0245_IBEROS_1_E, 0712_ACUINANO_1_E, and 0624_2IQBIONEURO_6_E, and Interreg Atlantic Area NANOCULTURE 1.102.531)