Advancing Open Science

Climate change poses significant threats to forest ecosystems, with drought stress being a major factor affecting tree growth and survival. The accurate and early diagnosis of plant water status is, therefore, critical for advancing climate-smart forestry. However, traditional monitoring approaches often rely on single-sensor data or manual field surveys, limiting their capacity to comprehensively capture the complex physiological and structural dynamics of plants under water deficit. To address this gap, this study developed an indoor multi-sensor phenotyping platform, based on a three-axis mobile truss system, which integrates a hyperspectral camera, a thermal infrared imager, and a LiDAR scanner for coordinated high-throughput data acquisition. We further propose a novel hybrid model, the Whale Optimization Algorithm-based Multi-Kernel Extreme Learning Machine (WOA-MK-ELM), which enhances classification robustness by adaptively fusing hyperspectral and thermal features within a dual Gaussian kernel space. We use Perilla frutescens as a model species, achieving an accuracy of 93.03%, an average precision of 93.11%, an average recall of 94.04%, and an F1-score of 0.94 in water stress degree classification. The results demonstrate that the proposed framework not only achieves high prediction accuracy but also provides a powerful prototype and a robust analytical approach for smart forestry and early warning systems.

Background: Endoscopic Electroporation (EE) is an innovative minimally invasive therapy that utilises short electrical pulses combined with intratumoural (IT) calcium or IT/intravenous (IV) chemotherapy to induce tumour cell death in colorectal cancer (CRC). Based on electrochemotherapy protocols developed for the treatment of skin cancers, EE has shown promising results in salvage therapy, local tumour control, and symptom palliation, particularly in patients who are unsuitable for surgery or standard treatments. Objective: To establish, for the first time, a comprehensive and standardised protocol for setting up a Salvage Endoscopic Electroporation (SEE) service in CRC clinical practice, covering multidisciplinary patient selection, procedural steps, equipment needs, and follow-up care. Methods: Drawing from the European Standard Operating Procedures of Electrochemotherapy (ESOPE) and emerging clinical evidence on EE from King’s College London, we detail infrastructure, treatment delivery, and monitoring for CRC. Key procedural elements, safety considerations, and patient management strategies are outlined. Electroporation pulses were delivered using the Conformité Européenne (CE) approved ePORE^® electroporation generator and single-use CE-marked EndoVE^® probe (Mirai Medical, Galway, Ireland). Results: Tumour assessment involves both clinical evaluation and endoscopic imaging, with radiological correlation. EE treatment has been safely carried out under sedation using specialised endoscopic probes, leading to effective local tumour response, symptomatic relief, and improved quality of life. Follow-up schedules allow for timely assessment of treatment response and enable repeat treatments if needed. Conclusions: This novel protocol provides a practical framework for centres aiming to implement SEE services, promoting consistency, safety, and better patient outcomes. Future prospective studies will refine indications and improve integration of this approach into colorectal cancer management pathways.

Winemaking is facing significant challenges caused by industrialization of the process, climate change, and increased consumer awareness regarding the use of chemical preservatives. Although several solutions have been proposed, the utilization of non-Saccharomyces species seems to be the most efficient one. Several non-Saccharomyces species have been employed for this purpose, with Hanseniaspora uvarum, H. vineae, Kluyveromyces marxianus, Lachancea thermotolerans, Metschnikowia pulcherrima, Pichia fermentans, P. kluyveri, Schizosaccharomyces pombe, Starmerella bacillaris, Torulaspora delbrueckii, and Wickerhamomyces anomalus being the most promising ones. However, only a restricted amount of metabolic activities can be reliably attributed to the species level, while most of them are characterized by strain variability and are also affected by the Saccharomyces cerevisiae strains used to carry out alcoholic fermentation, as well as the efficient supply of precursor molecules by the grape varieties and the conditions for their effective bioconversion. This variability necessitates the application of optimization strategies, taking into consideration all these parameters. This review article aims to assist in this direction by collecting the data referring to the winemaking practice of the most interesting non-Saccharomyces species, presenting clearly and comprehensively their most relevant features, and highlighting the effect of strain diversity.

Host factors play critical roles in viral IRES-mediated translation by modulating the efficiency and specificity of viral protein synthesis. In this study, we used small interfering RNA (siRNA) treatment to silence and plasmid-based expression to overexpress PKD1L3 and USP31. Silencing PKD1L3 and USP31 suppressed IRES activity in FMDV and CSFV RNAs, whereas the overexpression of PKD1L3 did not have a significant effect, and USP31 overexpression resulted in only a modest increase in CSFV-IRES activity. Silencing PKD1L3 significantly reduced EMCV-IRES activity but had no significant effect on HCV- or DENV-IRES activity, and silencing USP31 had no significant effect on the activities of these three IRESs. Notably, the combined overexpression of PKD1L3 and USP31 significantly suppressed HCV-IRES activity, suggesting potential context-dependent interactions. These findings indicated that PKD1L3 and USP31 contribute more prominently to CSFV-, FMDV-, and EMCV-IRES-mediated translation than to HCV- or DENV-IRES-driven translation. Collectively, our results provide new insights into the host factors involved in IRES-mediated viral translation, establish a foundation for future in vivo studies to elucidate the specific roles of PKD1L3 and USP31 during viral infection, and indicate potential strategies for mitigating these viruses.

Five novel PEPPSI-type palladium(II) complexes, dichloro[1-isopropyl-3-(arylmethyl)-5,6-dimethylbenzimidazolin-2-ylidene]pyridine palladium(II), were synthesized and characterized through nuclear magnetic resonance and Fourier-transform infrared spectroscopy. The DNA- and BSA-binding analyses of PEPPSI-type palladium (II) complexes were performed with UV-Vis spectroscopy by means of the Benesi-Hildebrand method. The results indicated that complex 1b (arylmethyl = 3-methylbenzyl) exhibited the strongest binding constant against DNA, with a value of 5.5 × 10³ M⁻¹, while complex 1d (arylmethyl = 2-chlorobenzyl) exhibited the highest binding affinity for BSA, reaching 2.8 × 10⁴ M⁻¹. In addition, the binding characteristics of DNA and BSA were assessed through the implementation of molecular docking methodologies. These methodologies displayed results that were in accordance with the experimental results. The molecules were also assessed for their ADME properties, with a focus on determining their drug-likeness potential. The five complexes were found to be compatible with the Veber and Egan rules.

Wildfires in the Wildland–Urban Interface (WUI) pose escalating threats to socio-ecological systems, challenging regional resilience and sustainable recovery. Understanding the compound impacts of such fires requires an integrated, data-driven assessment of both ecological disturbance and social response. This study develops a multi-dimensional framework combining multisource remote sensing data (Landsat/Sentinel-2 NDVI and VIIRS nighttime light) with socio-structural indicators. A Composite Disturbance Index (ImpactIndex) was constructed to quantify ecological, population, and socioeconomic disruption across six fire clusters in the January 2025 Southern California wildfires. Mechanism analysis was conducted using Fixed-Effects OLS (M2) and Geographically Weighted Regression (GWR, M3) models. The ImpactIndex revealed that Eaton and Palisades experienced the most severe compound disturbances, while Border 2 showed purely ecological impacts. During-disaster CNLI signals were statistically decoupled from ecological disturbance (ΔNDVI) and dominated by site-specific effects (p < 0.001). GWR results (Adj. R² = 0.354) confirmed asymmetric spatial heterogeneity: high-density clusters (Palisades, Kenneth) exhibited a significant “Structural Burden” effect, whereas low-density areas showed weak, nonsignificant recovery trends. This “Index-to-Mechanism” framework redefines the interpretation of nighttime light in disaster contexts and provides a robust, spatially explicit tool for targeted WUI resilience planning and post-fire recovery management.

Sepsis is a systemic inflammatory response syndrome induced by infection, characterized by high morbidity and mortality, and responsible for over 11 million deaths worldwide annually. Recent studies have demonstrated that immune dysfunction represents a core element in the pathophysiology of sepsis, in which cluster of differentiation 8–positive (CD8⁺) T cells, as key executors of cellular immunity, play a critical role in immune dysregulation. This review systematically elaborates on the quantitative changes, functional status, and molecular regulatory mechanisms of CD8⁺ T cells in sepsis, including abnormalities in metabolic reprogramming, cell death pathways, transcriptional regulation, and intercellular communication. Additionally, it explores potential therapeutic strategies targeting CD8⁺ T cells, such as immune checkpoint modulation, cell death intervention, and metabolic regulation, and offers an outlook on future research directions, aiming to provide novel insights for immunotherapy in sepsis.

We quantitatively investigate the physical origins of the non-Markovianity measure proposed in our previous work, which can be directly interpreted as memory effects, i.e., the dependence of a quantum system’s future evolution on its history. Using the properties of the trace norm and the trace distance, we find that the strength of memory effects in an evolution is upper (lower) bounded by the sum (difference) of two quantities. One originates from (bounded by) the change of environment state caused by the system, the other from (bounded by) the correlations between the system and the environment. The simulation results for the Jaynes–Cummings model show that the two origins may contribute to the memory effects in different manners, depending on the initial states of the environment and the system.