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Introduction: This study aims to evaluate the persistence, treatment adherence and drug cost associated with biologic and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) in the management of psoriatic arthritis (PsA) in Italy, with a focus on biosimilar drugs. Methods: This was a retrospective observational study involving eight hospital pharmacies, between January 2017 and December 2020, on naïve patients with at least one b/tsDMARD dispensation indicated for PsA. Patients were followed up for 12 months and persistence and adherence were evaluated by proportion of days covered (PDC). The originator and biosimilar for adalimumab and etanercept were compared. Furthermore, the real annual cost per patient based on adherence to therapy was calculated. Results: Patients initiating b/tsDMARDs for PsA had a mean persistence of 263 days and 48.6% remained persistent for 1 year. Adherent patients (PDC ≥ 0.8) were 47.6% for the overall population. Similar persistence and adherence were observed between patients treated with the adalimumab originator and its biosimilar, while patients treated with the etanercept originator showed lower persistence and adherence compared to those treated with its biosimilar (mean persistence: 222 vs. 267 days, patient persistent at 1 year: 29.4% vs. 51.5%, mean PDC: 0.53 vs. 0.70, adherent patients: 23.5% vs. 51.5%). The average annual drug cost ranged from €8,724 (etanercept) to €14,783 (ustekinumab), with an annual saving of more than €2,500 by using biosimilars. Conclusion: Poor adherence to medications contributes to suboptimal clinical outcomes. The comparison between biosimilar and originator offers further evidence in support of the biosimilar to optimizing resources in healthcare.

This paper introduces a multiphysics code, named nemoFoam, designed within the OpenFOAM environment to address the coupling of neutron and photon transport with thermal-hydraulics in nuclear reactor simulations. The code, conceived both for fusion and fission applications, employs a modular approach where the neutronic module is currently based on multi-group neutron diffusion equations, including a mono-kinetic treatment for photons. The thermal-hydraulic module is built on the standard OpenFOAM solver. The paper focuses on presenting the key features of nemoFoam and discussing the structure of the code, the nuclear and thermal-hydraulic models, and the coupling strategy between them.In order to assess the performance of the neutronic module, the code is applied to a fusion case study, indeed a benchmark against the Serpent Monte Carlo code for neutron and photon transport is performed, applying nemoFoam to the Affordable, Robust and Compact (ARC) fusion reactor design. Simulation results demonstrate good agreement with Monte Carlo benchmarks, emphasizing the potential of the code for multiphysics simulations. The modular design of nemoFoam allows users to extend the implemented model equations to study additional phenomena, focus only on selected aspects independently and, potentially, to add new solvers in each module.

Citizen science (CS) has so far failed to achieve its potential to contribute to water resource management globally despite a significant body of work proclaiming the benefits of such an approach. Also, this work has addressed concerns over precision, accuracy and reliability of methods used. This article presents the findings of a hackathon-type workshop challenge that brought together water quality experts and CS practitioners to explore barriers and possible solutions to mainstream citizen scientist-generated data into national, regional, and global reporting processes, and thereby provide a tangible connection between policy makers and community-based citizen scientists. We present the findings here as a perspective-type summary. This workshop challenge highlighted the breadth and scope of CS activities globally yet recognized that their potential for positive impact is going unrealized. The challenge team proposed that impact could be improved by: developing awareness; applying a simultaneous bottom-up/top-down approach to increase success rates; that local leaders or ‘catalysts' are key to initiate and sustain activities; that generated data need to fulfill a purpose and create required information, and ultimately, lead to actions (data > information > action); recognizing that we are all potential citizen scientists is important; recognizing that “good water quality” is subjective; and lastly that developing a communication gateway that allows bi-directional data and information transfer is essential.

Addressing the global water quality challenges requires collaborative efforts, multidisciplinary approaches, and innovative solutions. Here we report on the success of a special collective intelligence “hackathon event,” organized by five United Nations agencies and the European Commission, with the aim of reinventing engagement with diverse experts and stakeholders to tackle real-world challenges in water quality monitoring and assessment. Participants from diverse backgrounds and regions convened to devise inventive solutions in four key challenge areas, including (1) transformation of water quality data into water stewardship action, (2) empowering citizen scientists to improve water quality, (3) incorporation of Indigenous communities and their water quality knowledge in global information systems, and (4) routine monitoring of antimicrobial resistance in water. The hackathon approach fosters collective intelligence in a safe, creative and collaborative environment, enabling participants to harness their collective knowledge, expertise and skills. Key outcomes were conceptualizing practical frameworks and tailored toolboxes for diverse water quality innovations to improve monitoring, empower communities, and support policy-making. Emphasis was placed on the purpose and value of interdisciplinary collaborations to address complex global challenges, showcasing synergies between technology, environmental science, and social engagement. Hackathons are catalysts for collaborative innovation which unlock future endeavors in harnessing collective intelligence to safeguard our most precious resource – water.

Introducción: Durante la pandemia por COVID-19, los pacientes con peor evolución presentaron deterioro clínico a los 7-10 días del inicio de síntomas, lo cual sugiere que la respuesta inflamatoria podría participar de la fisiopatogenia de la enfermedad. El objetivo de este estudio fue evaluar la asociación entre los valores de proteína C reactiva (PCr) en plasma al ingreso sanatorial en adultos con COVID-19 y el requerimiento de asistencia respiratoria mecánica (ARM) durante la internación. Métodos: Cohorte retrospectiva, observacional, en un centro privado de la provincia de Buenos Aires. Se incluyeron a adultos internados con diagnóstico de COVID-19 por hisopado nasal, mediante real time transcription polymerasa chain reaction o antígeno. El desenlace primario fue la asociación entre valores altos de PCr en plasma al ingreso sanatorial (≥8 mg/L) y el requerimiento de ARM durante la internación. Resultados: De los 1.242 pacientes enrolados, 19,4% requirieron ARM y 11,7% fallecieron durante la internación. La PCr de los pacientes que requirieron ARM fue mayor que la de los que no la requirieron (9,45 [5,20-18,70] mg/L vs 4,95 [1,80-10,70] mg/L; p < 0,01). La PCr analizada como variable continua (OR = 1,39; IC95% 1,21-1,60; p < 0,001) y como variable categórica (≥8 mg/L) (OR = 2,66; IC95% 2,19-3,78; p < 0,001) presentó una asociación significativa con el requerimiento de ARM durante la internación. Secundariamente, se encontró una asociación significativa entre PCr y mortalidad intrahospitalaria. Conclusión: El valor de PCr en plasma al ingreso sanatorial podría predecir la evolución clínica en pacientes adultos internados por COVID-19.

One of the main challenges to be addressed to achieve a reliable electricity production from the EU DEMO reactor is the realization of a closed fuel cycle, for which a suitable Tritium Extraction and Removal System (TERS) is required. One of the possible technologies identified for the EU DEMO TERS is the Permeator Against Vacuum (PAV): the tritium dissolved in the liquid PbLi flowing within several parallel channels will permeate towards the vacuum pumped on the other side of the channel wall (the membrane).A recently-developed model of the tritium permeation across the membrane in the PAV, involving both transport phenomena in the wall and surface processes, was already used to size the EU DEMO PAV. However, besides the component itself, it is important to properly define the interfaces of the PAV in the TERS, and of the TERS in the entire PbLi and tritium loops. The model of such a complex system is therefore implemented here in the Modelica object-oriented language used by system-level tool GETTHEM, that already includes a model of the PbLi loop. The resulting, lumped-parameter component will be able to capture the thermal-hydraulic behaviour of the PbLi, to model the tritium transport in the fluid and to estimate the tritium permeated flux supplied to the tritium processing. Such a model is tested here on a sub-scale circuit to demonstrate its capability to simulate the operation of the EU DEMO TERS using the GETTHEM code.As the physical parameters of the model are subject to a large uncertainty, an uncertainty propagation analysis is also performed, to have a preliminary quantification of the impact of such uncertainties on the model output and, therefore, on the TERS efficiency, and to drive further investigations of these physical properties. In particular, results show how the uncertainty on the solubility constant of hydrogen in PbLi represents the dominant contribution on the total variance, highlighting the need for a better accuracy of such parameter.

ABSTRACTConventional CD4+ T (Tconv) lymphocytes play important roles in tumor immunity; however, their contribution to tumor elimination remains poorly understood. Here, we describe a subset of tumor-infiltrating Tconv cells characterized by the expression of CD39. In several mouse cancer models, we observed that CD39+ Tconv cells accumulated in tumors but were absent in lymphoid organs. Compared to tumor CD39− counterparts, CD39+ Tconv cells exhibited a cytotoxic and exhausted signature at the transcriptomic level, confirmed by high protein expression of inhibitory receptors and transcription factors related to the exhaustion. Additionally, CD39+ Tconv cells showed increased production of IFN[Formula: see text], granzyme B, perforin and CD107a expression, but reduced production of TNF. Around 55% of OVA-specific Tconv from B16-OVA tumor-bearing mice, expressed CD39. In vivo CTLA-4 blockade induced the expansion of tumor CD39+ Tconv cells, which maintained their cytotoxic and exhausted features. In breast cancer patients, CD39+ Tconv cells were found in tumors and in metastatic lymph nodes but were less frequent in adjacent non-tumoral mammary tissue and not detected in non-metastatic lymph nodes and blood. Human tumor CD39+ Tconv cells constituted a heterogeneous cell population with features of exhaustion, high expression of inhibitory receptors and CD107a. We found that high CD4 and ENTPD1 (CD39) gene expression in human tumor tissues correlated with a higher overall survival rate in breast cancer patients. Our results identify CD39 as a biomarker of Tconv cells, with characteristics of both exhaustion and cytotoxic potential, and indicate CD39+ Tconv cells as players within the immune response against tumors.

Abstract We employ Natural Language Processing techniques to analyse 377,808 English song lyrics from the “Two Million Song Database” corpus, focusing on the expression of sexism across five decades (1960–2010) and the measurement of gender biases. Using a sexism classifier, we identify sexist lyrics at a larger scale than previous studies using small samples of manually annotated popular songs. Furthermore, we reveal gender biases by measuring associations in word embeddings learned on song lyrics. We find sexist content to increase across time, especially from male artists and for popular songs appearing in Billboard charts. Songs are also shown to contain different language biases depending on the gender of the performer, with male solo artist songs containing more and stronger biases. This is the first large scale analysis of this type, giving insights into language usage in such an influential part of popular culture.

This paper describes the Integration of Archives and Cultural Places (IaCuP) project, which aims to integrate information about a historical cemetery, including its map and grave inventory, with genealogical and documentary knowledge extracted from relevant historical archives. The integrated data are accessible to cemetery visitors through an interactive mobile application, enabling them to navigate a graphical representation of the cemetery while exploring comprehensive visualizations of genealogical data. The basic idea stems from the desire to provide people with access to the rich context of cultural sites, which have often lost their original references over the centuries, making it challenging for individuals today to interpret the meanings embedded within them. The proposed approach leverages large language models (LLMs) to extract information from relevant documents and Web technologies to represent such information as interactive visualizations. As a practical case study, this paper focuses on the Jewish Cemetery in Pisa and the Historical Archives of the Jewish Community in Pisa, working on the genealogical tree of one of the most representative families resting in the cemetery.

This paper presents the application of a variance reduction technique for radiation shielding calculations in Lead-cooled Fast Reactors (LFRs) using the OpenMC Monte Carlo code. The study focuses on assessing the computational efficiency of the Method of Automatic Generation of Importances by Calculation (MAGIC). This technique is employed to generate weight windows for Monte Carlo simulations, aiming at enhancing the efficiency of dose rate estimations for LFRs. Through a detailed study of a LFR mock-up model, the performance differences between a MAGIC-accelerated and a non-accelerated simulation are investigated in terms of both accuracy and computational cost. The results demonstrate the benefits of the variance reduction method, showing its effectiveness in spreading particles throughout the model while improving the accuracy of Monte Carlo estimates far from the core. In addition, this work demonstrates the performances of the MAGIC method in eigenvalue calculations. This work shows an interesting optimisation of Monte Carlo simulations for LFRs and can be considered as a first milestone for newcleo’s radiation shielding studies.

El proceso de envejecimiento poblacional que acontece en el mundo, y en especial en América Latina, vuelve fundamental colocar la mirada en las necesidades que presentan las y los adultos mayores en el desarrollo de esta etapa de su vida. El objetivo general de este artículo es caracterizar la existencia de los espacios de cuidados de las personas adultas mayores en el territorio nacional, a partir de datos del Censo Nacional de Hogares 2010 y del mapa Federal de Cuidados. Del total de establecimientos registrados, 13% son para personas mayores, y de ellos, 71,6% son instituciones privadas. Existe una distribución desigual de características socio-demográficas a nivel nacional, y esto genera una situación que puede aumentar la vulnerabilidad de la persona mayor e interferir en el poseer una adecuada calidad de vida.