Journals
2026 EN
Quarta Leonardo · Polverino Federico · Petix Michele
+16 more
ABSTRACT Introduction It is unknown whether marital status affects years of life lost (YLL) in metastatic prostate cancer (mPCa) according to race/ethnicity. Methods Within the SEER database (2004–2021), unmarried and married mPCa patients aged 40–80 years were identified. Age‐ and sex‐matched controls were generated (Social Security Administration life tables and Monte Carlo simulation). YLL were quantified for unmarried and married mPCa patients and controls according to race/ethnicity. Subsequently, multivariable competing risks regression (CRR) models were fitted to assess cancer‐specific mortality (CSM) and other‐cause mortality (OCM). Results Among 34,202 mPCa patients, the distribution of unmarried patients according to race/ethnicity was as follows: 7267 (34.0%) in Caucasians; 3680 (57.0%) in African Americans; 1659 (37.0%) in Hispanics; and 478 (24.0%) in Asians/Pacific Islanders. YLL values in unmarried vs. married patients relative to age‐ and sex‐matched population simulated controls, were as follows: 7.7 vs. 5.8 in Caucasians (Δ: 1.9), 9.6 vs. 7.9 in African Americans (Δ: 1.7), 7.9 vs. 6.7 in Hispanics (Δ: 1.2), and 6.3 vs. 4.7 in Asians/Pacific Islanders (Δ: 1.6). In multivariable CRR models, unmarried status independently predicted higher CSM (1.2‐fold, p < 0.001) and OCM (1.2‐fold, p < 0.001) in Caucasians, only higher CSM in African Americans (1.1‐fold, p = 0.008) and in Asians/Pacific Islanders (1.2‐fold, p = 0.02), but only higher OCM in Hispanics (1.5‐fold, p < 0.001). Conclusion Unmarried mPCa patients exhibited higher YLL values than their married counterparts, relative to age‐ and sex‐matched population simulated controls, across all races/ethnicities. Interestingly, the YLL detriments originated from both CSM and OCM in Caucasians, only CSM in African Americans and Asians/Pacific Islanders, and only OCM in Hispanics.
Journals
2026 EN
De Michele Vincenzo · Marcandella Claude · Paillet Philippe
+1 more
In this study, we compare the pulsed X‐ray radiation responses of standard, radiation‐tolerant optical fibers with those of super‐hard, radiation‐resistant multimode (MM‐SRH) and single‐mode (SM‐SRH) fluorine‐doped optical fibers. Real‐time measurements of radiation‐induced attenuation (RIA) spectra were conducted in the spectral range of 0.6 to 3.0 eV (400–2000 nm), both at room temperature and at liquid nitrogen temperature, to characterize the nature of metastable defects, quickly recombining after the short (a few tens of ns) irradiation pulse. Additionally, we monitored the RIA kinetics at the two telecommunication wavelengths, 1550 and 1310 nm, from the microsecond timescale to several hundreds of seconds. MM‐SRH fibers exhibit superior light transmission efficiency following the X‐ray irradiation pulse, better than the other fiber compositions and the one expected from current literature on transient responses of silica‐based optical fibers. Possible explanation of this radiation hardness could be the very high level F‐doping distribution in this graded‐index optical fiber, demonstrating how the RIA in optical fibers strongly depends on fiber composition and manufacturing parameters.
Journals
2026 EN
Gardella Matteo · Massetti Chiara · Lamperti Alessio
+7 more
Topological semimetals, being characterized by symmetry‐protected band crossings, represent a fascinating class of materials with extraordinary electronic properties. Type‐II Dirac semimetals, featuring highly tilted Dirac cones, offer unique opportunities for both fundamental research and technological advancements. Platinum ditelluride (PtTe 2 ) has emerged as a promising candidate for a type‐II Dirac semimetal, exhibiting relevant properties for future spintronic and optoelectronic devices. While the existence of type‐II Dirac cones in PtTe 2 has been confirmed by cryogenic temperature angle‐resolved photoemission spectroscopy (ARPES), practical applications necessitate their stability at ambient conditions. Here, we present a melt growth method for the synthesis of high‐quality PtTe 2 crystals and we perform ARPES characterization both at cryogenic and at room temperature, providing compelling evidence for the robust nature of its topological electronic structure under realistic operating conditions. This demonstration paves the way for the development of PtTe 2 ‐based devices leveraging its distinctive topological properties in practical settings.
Journals
2026 EN
Wu Ruirui · Gong Shunfa · Wu Yijun
+4 more
CsPbBr 3 nanocrystals (CPB NCs), an all‐inorganic halide perovskite, have demonstrated high efficiency and significant commercialization potential in fields such as light‐emitting diodes, solar cells, photodetectors, lasers, and bioimaging. However, the instability of CPB NCs in ambient environments remains a major challenge that must be addressed before their widespread commercial applications. Core–shell structural engineering of CPB NCs has been widely employed to mitigate the impacts of external environmental factors, significantly enhancing long‐term stability against moisture, thermal, and oxygen. A protective shell layer covering CPB NCs prevents direct exposure to these environmental factors, providing excellent stability. This review summarizes recent advancements and challenges in CPB NCs‐based core–shell materials, systematically analyzing how shell material types and bandgap structures influence luminescence stability. The energy band structure and configuration of CPB NCs‐shell are discussed in detail, and the classification of shell types, such as perovskite and its derivatives, oxide shells, and polymer shells in single‐layer configurations, is reviewed. Special attention is given to the applications of the CPB NCs‐based core–shell materials with enhanced stability. Finally, the main challenges and further research directions for the core–shell structure of CPB NCs are discussed, with the aim of promoting the development of stable metal halide perovskite materials in the future.
Journals
2026 EN
Wu Ruirui · Gong Shunfa · Wu Yijun
+4 more
In this Review (DOI: 10.1002/pssr.202500439 ) Michele Saba, Rui Chen, and co‐workers introduce the crystal structure, optical characteristics, and morphology of CsPbBr 3 nanocrystals, focusing on clarifying the degradation mechanisms by which environmental influences, including hydrothermal conditions, affect its performance. Enhancements in the stability and optoelectronic characteristics of CsPbBr 3 nanocrystals via core‐shell structure are investigated.
Journals
2026 EN
Caravita Sergio · Baratto Claudia · Dewachter Céline
+11 more
ABSTRACT Invasive exercise hemodynamics are used to diagnose heart failure with preserved ejection fraction (HFpEF), based on pulmonary artery wedge pressure (PAWP) or left atrial (LA) pressure elevations. We hypothesized that applying unsupervised cluster analysis to comprehensive hemodynamic characterization might provide data‐driven phenotypes, with pathophysiological and prognostic implications. Eighty consecutive HFpEF patients underwent right heart catheterization at rest, during passive leg raise, and at peak exercise. We performed unsupervised k ‐means clustering analysis, using eight hemodynamic variables that were not strongly correlated (Pearson correlation coefficient < 0.80). Hemodynamics and clinical characteristics, as well as event‐free survival, were assessed. k = 5 clusters were identified. Hemodynamic severity increased from Cluster 1 to Clusters 4–5 ( p < 0.01 for most of the hemodynamic variables), mirrored by different event‐free survival (log‐rank test p < 0.001). Clusters 1 and 2 presented with either steep PAWP rise or LA hypertension and pulmonary hypertension (PH) only during exercise. Cluster 3 presented with LA hypertension and PH already at rest, as well as with tall PAWP V waves during exercise. Cluster 4 presented with post‐ and precapillary PH, tall PAWP V waves, right atrial (RA) hypertension, dynamic tricuspid regurgitation (TR), and low cardiac output (CO) reserve. Cluster 5 presented with TR and RA hypertension, low CO, and a lack of decrease in PVR. Data‐driven unsupervised cluster analysis of advanced invasive hemodynamics allowed for the identification of distinct HFpEF phenotypes across the spectrum of disease severity. We found a progressive involvement of the pulmonary circulation and of the right heart, coupled with a worse prognosis.
Journals
2026 EN
Antonazzi Michele · Luperto Matteo · Borghese N. Alberto
+1 more
ABSTRACT Autonomous service robots are becoming increasingly common in human‐centric, long‐term deployments in unstructured indoor environments. Robotic vision is a crucial capability, enabling robots to perceive and interpret high‐level environmental features from visual input. While data‐driven approaches based on deep learning have advanced the capabilities of vision systems, applying these techniques in real robotic scenarios still presents unique methodological challenges. Conventional datasets often do not represent the object categories that a service robot needs to detect. More importantly, state‐of‐the‐art models struggle to address the demanding perception constraints faced by service robots, posing the need for adaptations to the specific environments in which the robots operate. We devise a method that addresses these challenges by leveraging photorealistic simulations to create synthetic visual datasets from a robot's perspective. This approach balances data quality with acquisition costs, enabling the training of deep, general‐purpose detectors tailored for service robots. We then demonstrate the benefits of qualifying a general detector for the domain in which the robot is deployed, studying the trade‐off between data‐acquisition efforts and performance improvement. We evaluate our method using a representative selection of prominent deep‐learning object detectors for the challenge of recognizing, in real time, the presence and traversability of doorways. This task, which we refer to as door detection , is fundamental to numerous significant robotic tasks, such as tracking the changing topology of dynamic environments. We conduct an extensive experimental campaign in the field, considering different real‐world setups while emulating the typical challenges encountered in long‐term deployments of service robots. Our key findings demonstrate that simulation and qualification techniques can significantly reduce costs associated with domain adaptation for service robots. While simulation allows embedding the robot's perspective during the training of end‐to‐end robotic vision modules, qualification is essential to improve their robustness over challenging detection instances, thus reaching the performance level typically required by realistic long‐term deployments of service robots.
Journals
2026 EN
Durante Lorenzo · Lanzoni Stefano · Pittaluga Michele Bolla
ABSTRACT River systems worldwide are undergoing severe ecological and morphological degradation due to prolonged anthropogenic interventions, such as channelization and dam construction, which disrupt sediment continuity and natural flow regimes. In response, river re‐naturalization projects have emerged as essential strategies to restore the dynamics of fluvial systems. However, these actions frequently encounter unintended morphodynamic consequences, including sediment erosion and deposition, altered flow patterns, and disrupted channel stability, which pose significant challenges to achieving ecological, navigational, and flood management objectives. This study addresses the critical challenges associated with secondary channel re‐opening, a common practice in re‐naturalization projects, focusing specifically on lowland river systems. By employing a combination of numerical modeling and theoretical analysis, we investigate how key design parameters, such as localized levee lowering, influence the equilibrium of a river reach. The research highlights how an inappropriate project design can amplify sedimentation in the primary channel branch, reducing navigability, increasing maintenance costs, and offsetting ecological gains. To support management authorities and project designers, this work emphasizes the need for a multidisciplinary framework that incorporates long‐term morphodynamic projections alongside ecological restoration goals. The findings provide insights into balancing environmental sustainability with operational functionality, offering guidance for improving the resilience and success of future re‐naturalization efforts worldwide.
Journals
2026 EN
Moretta Michele · Rossi Riccardo · Palchetti Enrico
+7 more
ABSTRACT Agrivoltaic systems (AVS) integrate renewable energy production with agricultural use, creating novel microclimatic gradients that can affect ecosystem structure and function. However, the ecological consequences of these gradients on vegetation composition and soil biological quality remain poorly understood, particularly in pasture‐based AVS configurations. In this study, we investigated seasonal and spatial changes in plant functional groups and soil microarthropod communities across shading gradients in a Mediterranean AVS pasture using the Pasture Value (PV) and the Soil Biological Quality‐arthropods (QBS‐ar) indices. Results revealed marked seasonal differences driven by panel‐induced microclimatic variability. In spring, strong microclimatic contrasts generated pronounced differences across treatments, with inter‐row areas showing higher PV and QBS‐ar values and supporting more diverse plant and soil faunal communities. These areas supported the co‐dominance of legumes and a richer assemblage of microarthropods, indicating a positive relationship between productive, nitrogen‐fixing vegetation and soil faunal diversity. By contrast, shaded under‐panel zones hosted stress‐tolerant forbs and showed reduced QBS‐ar values, indicating lower biological quality. These integrative indicators can guide AVS pasture management while supporting long‐term monitoring of soil fertility and ecosystem functioning.
Journals
2026 EN
D'Alessandro Antonio · Kim Jiyu · Adhikari Samrachana
+3 more
ABSTRACT Randomized controlled trials (RCTs) often include subgroup analyses to assess whether treatment effects vary across prespecified patient populations. However, these analyses frequently suffer from small sample sizes, which limit the power to detect heterogeneous effects. Power can be improved by leveraging predictors of the outcome—that is, through covariate adjustment—as well as by borrowing external data from similar RCTs or observational studies. The benefits of covariate adjustment may be limited when the trial sample is small. Borrowing external data can increase the effective sample size and improve power, but it introduces two key challenges: (i) integrating data across sources can lead to model misspecification, and (ii) practical violations of the positivity assumption—where the probability of receiving the target treatment is near zero for some covariate profiles in the external data—can lead to extreme inverse‐probability weights and unstable inferences, ultimately negating potential power gains. To account for these shortcomings, we present an approach to improving power in preplanned subgroup analyses of small RCTs that leverages both baseline predictors and external data. We propose de‐biased estimators that accommodate parametric, machine learning (ML), and nonparametric Bayesian methods. To address practical positivity violations (PPVs), we introduce three estimators: A covariate‐balancing approach, an automated de‐biased machine learning (DML) estimator, and a calibrated‐DML estimator. We show improved power in various simulations and offer practical recommendations for the application of the proposed methods. Finally, we apply them to evaluate the effectiveness of citalopram for negative symptoms in first‐episode schizophrenia (FES) patients across subgroups defined by duration of untreated psychosis (DUP), using data from two small RCTs.