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Solubility enhancement of antimalarial drugs through eutectic formation
Publication . Araújo, Nathalie Ladares de
Malaria is a potentially fatal disease transmitted by infected mosquitoes and remains a serious public health problem, especially in sub-Saharan Africa, where it causes hundreds of thousands of deaths annually. One of the main treatments for malaria involves artemisinin-based combination therapies, which have proven highly effective in controlling the disease. However, despite their crucial role in treatment, these therapies face a significant challenge due to the low water solubility of the most commonly used active pharmaceutical ingredients (APIs), such as artemisinin. This limits their absorption into the body, also reducing their therapeutic efficacy. The aim of this thesis is to explore greener solvents to enhance the solubility and bioavailability of antimalarial APIs through the formation of eutectic mixtures. Initially, the COSMO-RS predictive tool was employed to investigate the interactions between API molecules and a variety of terpenes and their mixtures. Thymol was selected based on the lower activity coefficient at infinite dilution, indicating strong interactions with the drugs. Subsequently, the solid–liquid equilibria of binary mixtures composed of thymol and artemisinin, artemether, artesunate, quinidine, tetracycline, quinine, dapsone, sulfadoxine or pyrimethamine were experimentally measured. The data revealed a significant reduction in the melting points of the APIs, particularly for artemisinin, quinidine, and quinine. Moreover, for these three systems, notable negative deviations from ideal behavior were observed, suggesting strong drug–thymol interactions. For these cases, the label "deep eutectic systems" may be appropriately applied. The measured phase diagrams were successfully modeled using the COSMO-RS approach, demonstrating excellent agreement with the experimental results and confirming the model's capability to screen and predict suitable solvent candidates for eutectic systems. The methodologies explored in this work are aligned with the principles of green chemistry, promoting more sustainable solutions for the pharmaceutical industry.
Navigating Methodological Trade‐Offs in eDNA Metabarcoding Biodiversity Monitoring: Insights From a Mediterranean Watershed
Publication . Veríssimo, Joana; Lopes‐Lima, Manuel; Amaral, Fábio; Chaves, Cátia; Fernandes, Vasco; Kemanja, Mutaleni; Teixeira, Amilcar; Martins, Filipa M. S.; Beja, Pedro
Environmental DNA (eDNA) metabarcoding technologies promise significant advances in biodiversity monitoring, yet their application requires extensive optimisation and standardisation. Recent research demonstrated that increased sampling and analytical efforts are needed to improve biodiversity estimates, though fully optimising study designs is often hindered by resource constraints. Consequently, researchers must carefully navigate methodological trade‐offs to design effective eDNA metabarcoding monitoring studies. We conducted a water eDNA survey of vertebrates in a Mediterranean watershed to identify key methodological factors influencing species richness and composition estimates. We examined the impacts of using high‐ versus low‐capacity filtration capsules, varying levels of biological and technical replication, and the pooling of PCR replicates before indexing. The primary sources of variation identified were capsule filtration capacity and site replication across the watershed. While biological replication within sites and PCR replication also improved biodiversity estimates, their effects were comparatively smaller. Pooling PCR replicates before indexing performed more poorly than analysing them independently. Methodological impacts were stronger on terrestrial than on aquatic species. Based on these results, we recommend that priority should be given to high‐capacity filtration and sampling across multiple sites. Site‐level replication deserves lower priority, especially when filtering large water volumes. PCR replication is crucial for detecting rare species but should be balanced with increased site sampling and eventually site‐level replication. Avoiding the pooling of PCR replicates is important to enhance sensitivity for rare species. Overall, we stress the importance of balancing methodological choices with resource constraints and monitoring goals, and we emphasise the need for research assessing methodological trade‐offs in different study systems.
Comparison of intra-colonial genetic diversity of the founder and leading edge populations of Vespa velutina
Publication . Maamri, Sarra Wassila; Henriques, Dora; Souai, Oussama; Pinto, M. Alice
Vespa velutina nigrithorax, commonly known as the yellow-legged hornet is a species of Vespidae native to Southwestern Asia. It was first observed in 2004 in Southwestern France (Lot-et-Garonne) and rapidly spread to neighboring countries; reaching Spain in 2010 and Portugal in 2011 in Viana do Castelo. Since 2011 it has been spreading through Portugal, with Bragança representing the most marginal distribution area of V. velutina in the northern region. Its spread rate is explained by its great capacity for climate adaptation and its polyandry. The invasion of V. velutina in Europe has caused significant ecological and economic damages. In fact, this hornet is a major threat to beekeeping since Apis mellifera consists in a third of its diet. Genetic studies have provided insights into the colonization patterns of this invasive predator, revealing a genetic bottleneck upon its arrival in Europe, which led to reduced genetic diversity. In this study, we used 16 microsatellites to genotype a total of 120 female hornets from two nests of Viana do Castelo (Vila de Punhe) and two from Bragança (Macedo de Cavaleiros and Mirandela). This study aims to assess and compare the genetic diversity of V. velutina population in the districts of Bragança and Viana do Castelo in Portugal. Bragança represents the leading edge of the northeastern expansion in the Portuguese territory. Surprisingly, the genetic diversity observed in the two colonies from Bragança was higher than that in the colonies from Viana do Castelo. This discrepancy suggests that the population in Bragança is a result of expansion from multiple sources, introducing new alleles to the local population.
Innovative and Sustainable Cultivation of Brassica Eruca vesicaria with Reuse of Wastewater from the Production of Squalius alburnoides by Decoupled Aquaponics
Publication . Noamane, Mohamed Wajdi; Dias, Maria Inês; Teixeira, Amílcar
The growth of the world population represents a great challenge for an adequate response to sustainable food production. Unfortunately, the conventional approach to agriculture, adopted in response to this challenge, entails adverse consequences for both the environment and consumer health. To control and/or reduce these consequences, various sustainable plant production techniques have been employed with great success.
Aquaponics is a practice that combines hydroponics with aquaculture, distinguishing itself from conventional practices through the more efficient use of water, as the essential nutrients for plant matrix growth come from fish production wastewater. This practice can be established in a coupled or decoupled manner (without a water recirculation system between the hydroponic and aquaculture systems).
To meet the specific nutritional needs for sustainable plant production, this project proposes the implementation of a decoupled aquaponics system for the hydroponic production of rocket (Eruca vesicaria L.) using wastewater from the production of a native freshwater fish, Calandino (Squalius alburnoides), in an aquaculture system. The wastewater will be monitored in terms of physicochemical and microbiological parameters, namely, pH, conductivity,
temperature, dissolved oxygen concentration and aeration, ammonia and nitrate concentrations, total nitrogen and phosphorus, total coliforms, thermotolerant coliforms, Escherichia coli, and sulfite-reducing Clostridium spores. Additionally, the quality of aquaponics produced rocket will be evaluated through physiological growth characteristics and through its nutritional, chemical, and bioactive profile compared to commercial arugula.
The results revealed critical challenges that affected the performance of the aquaponic system, including suboptimal environmental and water quality conditions for both fish and plants. For the aquaculture component, high nitrite, phosphorus, and dissolved oxygen levels, along with high microbial contamination, compromised fish health and nutrient availability.
Similarly, the hydroponic component experienced growth challenges due to fluctuating environmental factors such as temperature, humidity, pH, and electrical conductivity, which negatively impacted rocket plant development. Despite these challenges, the aquaponic system showed potential for producing nutrient-dense crops, with the microbial load in fish wastewater underscoring the need for effective water treatment and microbial management.
This study emphasizes the importance of rigorous control over key environmental parameters in aquaponics, highlighting the need for optimized systems that balance the specific requirements of both the aquaculture and hydroponic components. By fine-tuning nutrient concentrations, improving water quality management, and implementing better climate control, aquaponics systems can enhance both fish health and plant productivity, offering a sustainable alternative to conventional agriculture. The findings contribute valuable insights into refining aquaponic practices for improved sustainability and productivity in food production systems.
Disease detection and mapping in olive groves using UAVs and deep learning for precision agriculture
Publication . Morais, Maurício Herche Fófano de; Lima, José; Santos, Murillo Ferreira dos; Mendes, João Carlos
This dissertation presents the implementation and validation of a cost-effective, Unmanned Aerial Vehicle (UAV) based system for automated detection and spatial mapping of olive knot disease in olive groves. Addressing the need for accessible and efficient plant disease monitoring in Precision Agriculture (PA), the proposed methodology leverages existing UAV imagery capabilities with lightweight Deep Learning (DL) models, specifically the You Only Look Once (YOLO) object detection architecture, to enable scalable and accurate detection. The academic contributions presented in this work have resulted in two peer-reviewed publications related to the dissertation topic, as detailed at the end of this document. An annotated dataset of UAV-acquired images was compiled, and several state-of-the-art YOLO object detection models were trained and evaluated under identical conditions. The best-performing model achieved a strong F1-score, demonstrating good results in detecting olive knot disease and accurately mapping its spatial distribution within the plantation. The workflow integrates spatial cross-referencing of detections with UAV flight path data and proximity analysis, enabling the assignment of disease detections to individual trees. An interactive map interface, developed using the Folium Python library, provides visualization of the disease distribution and supports practical grove management. The experimental results indicate that cost-effective UAVs and lightweight DL models can be effectively combined for plant disease detection and spatial analysis, offering a robust and scalable approach for real-world agricultural applications. Limitations regarding early symptom detection and image quality are discussed, and directions for future work are proposed.