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The integration of advanced materials and photonic nanostructures can lead to enhanced biodetection capabilities, crucial in clinical scenarios and point-of-care diagnostics, where simplified strategies are essential. Herein, a molecularly imprinted polymer (MIP) photonic nanostructure is demonstrated, which selectively binding to transforming growth factor-beta (TGF-β), in which the sensing transduction is enhanced by bound states in the continuum (BICs). The MIP operating as a synthetic antibody matrix and coupled with BIC resonance, enhances the optical response to TGF-β at imprinted sites, leading to an augmented detection capability, thoroughly evaluated through spectral shift and optical lever analogue readout. The validation underscores the MIP-BIC sensor capability to detect TGF-β in spiked saliva, achieving a limit of detection of 10 fM and a resolution of 0.5 pM at physiological concentrations, with a precision of two orders of magnitude above discrimination threshold in patients. The MIP tailored selectivity is highlighted by an imprinting factor of 52, showcasing the sensor resistance to interference from other analytes. The MIP-BIC sensor architecture streamlines the detection process eliminating the need for complex sandwich immunoassays and demonstrates the potential for high-precision quantification. This positions the system as a robust tool for biomarker detection, especially in real-world diagnostic scenarios.

The Earth system has long lived with fires,1 , 2 but the impact of climate change on fire regimes has led to extreme wildfire events with higher intensity and faster spread.3 , 4 , 5 This has effects on ecosystems and resources, air pollution, and, ultimately, human societies.6 Facing these compounding challenges require interdisciplinary solutions and collaborations. In this Backstory, we bring together fire researchers across fields, aiming to foster discussions and collaborations across disciplines, for us to better understand how we can learn to live with fire.

We assembled the first gridded burned area (BA) database of national wildfire data (ONFIRE), a comprehensive and integrated resource for researchers, non-government organisations, and government agencies analysing wildfires in various regions of the Earth. We extracted and harmonised records from different regions and sources using open and reproducible methods, providing data in a common framework for the whole period available (starting from 1950 in Australia, 1959 in Canada, 1985 in Chile, 1980 in Europe, and 1984 in the United States) up to 2021 on a common 1° × 1° grid. The data originate from national agencies (often, ground mapping), thus representing the best local expert knowledge. Key opportunities and limits in using this dataset are discussed as well as possible future expansions of this open-source approach that should be explored. This dataset complements existing gridded BA data based on remote sensing and offers a valuable opportunity to better understand and assess fire regime changes, and their drivers, in these regions. The ONFIRE database can be freely accessed at https://zenodo.org/record/8289245 .

DESIGNING AND ASSESSING WITH THE SUPPORT OF ARTIFICIAL INTELLIGENCE: ELEMENTS FOR A CRITICAL APPROACH TO THE USE OF CHATBOTS Abstract This paper explores the critical integration of artificial intelligence (AI), specifically focusing on using chatbots in training design and learning assessment, aiming to uncover both the potential and challenges in educational and training contexts. Through two exploratory empirical studies – one centered on the use of ChatGPT in training design and the other on its application in school learning assessments – the analysis examines the perceptions of teachers and students. The findings reveal that chatbots, such as ChatGPT, can significantly reduce the workload of teachers and future training designers, improve access to educational resources, and provide timely feedback. However, concerns emerge regarding technological dependency and superficial learning, with ethical and pedagogical implications that warrant a critical examination of the pedagogical effectiveness of AI tools. The paper concludes by proposing strategies for AI’s ethical and thoughtful integration in education, promoting a balance between technology and reflective, critical educational practice.

Background and objective: Hypertension (HTN) has been linked to an elevated risk of prostate cancer (PC) development and poorer prognosis in localized cases, and is a common side effect of hormonal PC treatments. However, its relationship with the prognosis of metastatic PC is still unclear. We assessed the prognostic role of treatment-related HTN in patients with de novo metastatic hormone-sensitive PC (mHSPC) undergoing androgen deprivation therapy (ADT) alone or in combination with docetaxel or androgen receptor pathway inhibitors (ARPIs). Methods: Our retrospective analysis included 100 patients with de novo mHSPC treated with ADT, ADT + docetaxel, or ADT + ARPI between 2014 and 2021. Data on clinical variables, antihypertensive drugs, and blood pressure were collected from treatment initiation to 7 mo from ADT start. HTN development within 7 mo from hormonal treatment initiation was graded according to the Common Toxicity Criteria for Adverse Events version 5.0, and Cox analyses were performed for time to castration resistance (TTCR) and overall survival (OS). Key findings and limitations: In the overall population, grade (G) 2–3 HTN development within 7 mo from hormonal treatment initiation was associated with improved TTCR and OS at both univariate (TTCR: 19.8 vs 7.9 mo, hazard ratio [HR]: 0.35, 95% confidence interval [CI]: 0.20–0.63, p

Plant-derived rennet sources have been recognized as effective alternatives to traditional animal-derived rennet in cheese processing, producing various cheeses for vegetarians and Halal consumers. The aim of the present study was to assess the quality and identify potential chemical and sensory markers of Canestrato cheese made from pasteurized mixed cow/sheep milk (50:50 ratio) using a kiwifruit extract (prepared in the laboratory) as a rennet source of vegetable origin. The milk was curdled with an aqueous kiwi extract (cK group), with commercial calf rennet (cT group), or with commercial microbial rennet obtained from the controlled fermentation of Rhizomucor miehei (cH group). For each cheesemaking process, 30 L of mixed milk was used, resulting in 10 forms, each weighing approximately 1 kg. Cheese produced using kiwifruit rennet exhibited improved nutritional characteristics, such as lower total lipid, cholesterol, and sodium content and greater levels of polyphenols, potassium, and phytosterols compared with the cheese of the cT group. The cheese of the cK group had a slightly more pronounced bitterness compared to cheeses made with conventional rennets (cH and cT). Overall, the use of kiwifruit extract as a milk coagulant has proved to be a promising alternative, improving both the nutritional profile and functional properties of the resulting cheese.

Advanced urothelial carcinoma (aUC) has a dismal prognosis, with a 5-year survival rate of approximately 10%. Platinum-based chemotherapy has been the backbone of the first-line treatment of aUC for over 40 years. Only in the last decade, the treatment of aUC has evolved and been enriched with new classes of drugs that demonstrated pivotal improvements in terms of oncological responses and, ultimately, survival. Thus, the approach to aUC is becoming more and more tailored to the single patient, particularly owing to targeted therapies, such as fibroblast growth factor receptor (FGFR) inhibitors, antibody-drug conjugates (ADCs) targeting TROP2 and Nectin-4, anti-Her-2 therapies and others. However, due to the rapidly evolving scenario, the optimal sequence of systemic treatment is unknown and several important research questions remain unanswered, including the identification of reliable biomarkers to guide treatment decisions. Through ongoing research and clinical trials, we can continue to refine personalized treatment strategies and ultimately enhance patient care in this challenging disease setting. In this review, we provide a comprehensive overview of the current and emerging landscape of targeted therapies for aUC. We delved into the opportunities and challenges presented by personalized treatment approaches and explored potential future directions in this rapidly evolving field.

Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO2 net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr−1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr−1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7×103 ± 0.9×103 km3 globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.