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Synthesis, antitumoral activity, and in silico studies on Smoothened receptor of new 2,6,9-trisubstituted purine derivatives
No full text© 2024 Elsevier B.V.In this work, a series of 30 new 2,6,9-trisubstituted purine derivatives were synthesised and evaluated in silico as potential ligands of the Smoothened (SMO) receptor, as well as their ability to inhibit growth in Hedgehog (Hh)-dependent and Hh-independent cancer cell lines. The synthesis involved a convergent strategy, conventional methods and microwave irradiation. Initial antitumour evaluation was performed by testing cell growth inhibition in seven cancer cell lines and one non-neoplastic cell line (HEK-293) at 50 μM. IC50 values were determined for compounds showing < 50 % cell viability. Compounds 7l and 9j showed promising results with high cytotoxicity in three Hh-dependent cell lines and low cytotoxicity in HEK-293 cells. Compound 7l was more potent and selective than gemcitabine in BxPC-3, AsPc-1 and MIA-PaCa-2 cells and more than 5-fluorouracil in HT-29 cells, while 9j was more potent and selective than 5-fluorouracil in HCT116 and HT-29 cells. Molecular docking studies in SMO allowed the recognition of two binding sites related to ligand size and purine substitution patterns, while 7l bound to the top pocket (TMD-1), 9j bound to a deeper pocket (TMD-2). This study provides new evidence supporting the purine ring as a privileged scaffold for the development of new antitumour drugs targeting the SMO receptor
How human milk shapes the gut microbiota in preterm infants: potential for optimizing early-life microbial development
No full textBreast milk plays a crucial role in shaping the gut microbiota of preterm infants, with significant microbial sharing influenced by feeding practices and antibiotics, highlighting the benefits of direct breastfeeding for gut health
Finite Control Set Model Predictive Current Control (FCS-MPCC) of Three-Port Converter for Fuel Cell Hybrid Electric Vehicles
No full textFuel cell hybrid electric vehicles (FCEVs) are considered an appealing option for heavy-duty and long-distance vehicles. However, they require the use of multiple power converters to manage power distribution among the fuel cell, battery or ultracapacitor, and AC motor, leading to increased power losses and a more complex system. To overcome this challenge, multi-port power converters have been proposed to combine two power sources and the AC motor into one conversion stage, boosting overall efficiency and power density in hybrid powertrains. However, these converters still rely on a high number of semiconductors and involve complex control systems. This paper introduces a three-port converter (TPC) for FCHEVs, using only one power stage with 6 semiconductors, achieving high performance control of an ac motor, a fuel cell and a battery. A multivariable optimal control (Finite-Control-Set Model Predictive Current Control) manages the power flows between the energy sources and drives the motor simultaneously. Additionally, the performance of the multiport converter is improved by replacing its three inductors with a custom coupled inductor designed to reduce circulating AC currents. This innovation contributes to improved efficiency and overall functionality of the FCHEV system. The proposed system was validated through an 0.5kW experimental test bench and simulations of an urban driving cycle. The system controlled the multiple variables of the hybrid system with proper operation and fast dynamics, meanwhile the coupled inductor decreases the current magnitude in 20% compared to the non-coupled configuration.ANID (National Agency for Research and Development, Chile
Software and computing for Run 3 of the ATLAS experiment at the LHC
No full textThe ATLAS experiment has developed extensive software and distributed computing systems for Run 3 of the LHC. These systems are described in detail, including software infrastructure and workflows, distributed data and workload management, database infrastructure, and validation. The use of these systems to prepare the data for physics analysis and assess its quality are described, along with the software tools used for data analysis itself. An outlook for the development of these projects towards Run 4 is also provided
NLP modeling recommendations for restricted data availability in clinical settings
No full textBackground Clinical decision-making in healthcare often relies on unstructured text data, which can be challenging to analyze using traditional methods. Natural Language Processing (NLP) has emerged as a promising solution, but its application in clinical settings is hindered by restricted data availability and the need for domain-specific knowledge. Methods We conducted an experimental analysis to evaluate the performance of various NLP modeling paradigms on multiple clinical NLP tasks in Spanish. These tasks included referral prioritization and referral specialty classification. We simulated three clinical settings with varying levels of data availability and evaluated the performance of four foundation models. Results Clinical-specific pre-trained language models (PLMs) achieved the highest performance across tasks. For referral prioritization, Clinical PLMs attained an 88.85 % macro F1 score when fine-tuned. In referral specialty classification, the same models achieved a 53.79 % macro F1 score, surpassing domain-agnostic models. Continuing pre-training with environment-specific data improved model performance, but the gains were marginal compared to the computational resources required. Few-shot learning with large language models (LLMs) demonstrated lower performance but showed potential in data-scarce scenarios. Conclusions Our study provides evidence-based recommendations for clinical NLP practitioners on selecting modeling paradigms based on data availability. We highlight the importance of considering data availability, task complexity, and institutional maturity when designing and training clinical NLP models. Our findings can inform the development of effective clinical NLP solutions in real-world settings
Artificial Intelligence and Socio-Scientific Controversies in Science Teaching in Higher Education. Approaches and Projections Based on a Bibliographic Review
No full textThis literature review explores the implementation of Artificial Intelligence (AI) and Natural Language Processing (NLP) in the analysis of student feedback in universities. The methodology includes identification of the topic, systematic search of sources, assessment of the relevance and quality of the studies, and synthesis of the findings. The advantages and challenges of using AI and NLP to analyse student feedback, as well as their impact on improving educational quality, are discussed. The case studies of this literature review provide valuable information for the integration of socio-scientific controversies (SSC) in science education
Inertia and shock effects in public transport: The case of metro line 6 in Santiago using smart card data
No full textTraffic forecasting has traditionally relied solely on characteristics related to services and users. However, recent research has highlighted the importance of considering travellers' psychological factors in explaining travel behaviour. While previous studies have incorporated the role of habits in travel choice behaviour, only a few have analysed the role of inertia and shock related to major changes in transport networks. This study contributes to previous research by revealing the changes in the behaviour of public transport passengers over time after the inauguration of a new metro line in Santiago, Chile, using large-scale revealed-preference data from automated fare collection systems. It explicitly analysed the consequences of the new metro on passenger behaviour by considering different passenger types, using a heteroskedastic mixed latent class public transport mode choice model incorporating both inertia effects resulting from habitual behaviour and shock effects resulting from a significant change to the public transport network. The results confirmed significant habitual behaviour among passengers, in that metro users tended to stick to using the metro, but bus users tended to switch to other modes. However, after the introduction of the new metro line, a significant shock effect was observed, whereby users had an increased tendency to switch to modes that improved their level of service, and this effect increased slightly in the longer term. The results highlight the importance of incorporating inertia and shock effects into behavioural studies.Independent Research Fund Denmar
Probiotics in inflammatory bowel disease: microbial modulation and therapeutic prospects
No full textInflammatory bowel disease (IBD) is a chronic inflammatory disorder that represents a significant public health challenge worldwide. This multifactorial condition results from complex interactions among genetic, environmental, immune, and microbial factors. Some beneficial microbes, known as probiotics, have been identified as promising therapeutic agents for inflammatory conditions, such as IBD. In this review, we explore the potential of probiotics as a therapeutic strategy for managing IBD. Probiotics have shown promise due to their ability to modulate the gut microbiota, regulate histamine levels, and enhance vitamin D metabolism, thereby promoting a tolerant immune profile and reducing inflammation. While the exact mechanisms underlying these benefits remain incompletely understood, probiotics represent a novel and emerging approach for alleviating the exacerbated inflammation characteristic of this disorder
Numerical strategy and openings-focused sensitivity study of the seismic behavior of partially grouted masonry shear walls with openings
No full textPartially grouted reinforced masonry (PG-RM) is a commonly used structural system in several seismic-prone countries. In recent years, experimental and numerical investigations have been conducted to identify the main parameters that influence their seismic performance. However, little attention has been devoted to investigating the influence of openings on their structural response. Although experimental tests have provided valuable insights into their behavior, numerical simulations have emerged as a complementary strategy for lower economic costs and logistical requirements. In this context, a two-dimensional finite element macro-model is implemented to simulate the in-plane behavior of PG-RM walls containing openings. The concrete damage plasticity (CDP) model is used to describe masonry's nonlinear response. The model is validated against the experimental results of four full-scale PG-RM walls previously tested by the authors. Then, considering both loading directions, an openings-focused sensitivity study is conducted to investigate their effect on the in-plane lateral response. The implemented model was capable of simulating the in-plane behavior of PG-RM walls containing openings, as good agreement was achieved between numerical results and experimental tests in terms of lateral strength and failure mode. As expected, sensitivity analysis indicated that the wall shear capacity decreased when the openings' height or width or the number of openings increased. Based on the results, this work proposes an effective height to estimate the shear capacity of PG-RM walls with openings, where the height of the pier is established as the average of the heights that constrain the pier on its sides
Asociación entre los niveles séricos de ácido úrico y síndrome metabólico en pacientes chilenos y respuesta a intervención con dieta mediterránea
No full textTesis (Magíster en Nutrición)--Pontificia Universidad Católica de Chile, 2024Introducción: Aunque la asociación entre hiperuricemia y síndrome metabólico (SMet) ha sido demostrada, existe escasa evidencia para confirmar su valor pronóstico en esta condición. Adicionalmente, una intervención basada en dieta mediterránea (DM) podría disminuir la uricemia. Objetivos: Evaluar la asociación entre niveles de AU y SMet y si estos son modificados por una intervención con DM. Métodos: Estudio transversal y de intervención derivado del estudio CHILEMED que considera 3 grupos: dieta baja en grasas (DBG), DM y DM + apoyo en bienestar psicológico (DM+BP). Se incluyeron participantes adultos con SMet y evaluados sin SMet. Se midieron niveles de AU y adherencia a DM a través del Índice de DM para Chile (IDM Chile) a 0 y 6 meses de intervención. Resultados: Se seleccionaron 325 participantes [244 (75%) con SMet y 81 (25%) sin SMet], 59% mujeres con una mediana de edad de 46 años [40-54]. La mediana de AU en los participantes sin SMet fue 4,7 mg/dL [4-5,6] versus 5,2 mg/dL [4,4-6,2] en aquellos con SMet (p = 0,002). Los modelos de regresión logística identificaron una asociación entre AU y SMet al ajustar por edad, sexo y variables componentes del SMet en participantes hombres (p = 0,034; R2 Nagelkerke = 57,9%). No se demostró correlación entre los cambios de AU e IDM Chile (p = 0,877). Al evaluar los niveles de AU en aquellos con SMet intervenidos con DBG y DM, no se observaron cambios significativos a 6 meses (p = 0,273 y p = 0,149, respectivamente). Conclusiones: Se identificó una asociación entre AU y SMet al ajustar por edad y componentes del SMet en los participantes hombres. No se identificó una reducción significativa en la uricemia de participantes intervenidos con DM