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Proposals for achieving net-zero emissions by 2050 include scaling-up electrolytic hydrogen production, however, this poses technical, economic, and environmental challenges. One such challenge is for policymakers to ensure a sustainable future for the environment including freshwater and land resources while facilitating low-carbon hydrogen production using renewable wind and solar energy. We establish a country-by-country reference scenario for hydrogen demand in 2050 and compare it with land and water availability. Our analysis highlights countries that will be constrained by domestic natural resources to achieve electrolytic hydrogen self-sufficiency in a net-zero target. Depending on land allocation for the installation of solar panels or wind turbines, less than 50% of hydrogen demand in 2050 could be met through a local production without land or water scarcity. Our findings identify potential importers and exporters of hydrogen or, conversely, exporters or importers of industries that would rely on electrolytic hydrogen. The abundance of land and water resources in Southern and Central-East Africa, West Africa, South America, Canada, and Australia make these countries potential leaders in hydrogen export. This study composes a country-specific analysis of land and water requirements for electrolytic hydrogen production, revealing nations constrained in achieving self-sufficiency in hydrogen supply and nations who can become hydrogen exporters.

BackgroundCorrelations between postoperative complications and oncological outcomes have been reported in several malignancies, but their impact in retroperitoneal sarcoma (RPS) is unclear. Our study aimed to evaluate the association between postoperative complications and prognosis in patients with RPS.MethodsPatients undergoing surgery for primary RPS from 2008 to 2019 at a sarcoma center were evaluated. The cumulative burden of postoperative complications was quantified using the Comprehensive Complication Index (CCI), and associations with local recurrence (LR), distant metastases (DM) and overall survival (OS) were assessed.ResultsData were available for 191 patients, of whom 160 (82.9%) developed at least one postoperative complication, with a median CCI of 20.9 (interquartile range 8.7–33.5). After postoperative deaths were excluded (n = 3, 1.6%), the remaining patients were divided into those with a CCI of 0–20.9 (n = 97) and > 20.9 (n = 91). Patients with a CCI >20.9 had significantly shorter OS than those with a CCI of 0–20.9 (43.3% vs. 69.5% at 5 years; p = 0.005), and this difference remained significant after multivariable adjustment for patient- and treatment-related factors [hazard ratio (HR) 2.31, 95% confidence interval (CI) 1.30–4.09; p = 0.004]. However, CCI > 20.9 was not found to be a significant independent predictor of either LR (HR 1.30, 95% CI 0.76–2.23; p = 0.333) or DM (HR 1.08, 95% CI 0.61–1.93; p = 0.786).ConclusionIncreasing complication burden, as quantified by the CCI, is a significant independent predictor of OS; however, there is no evidence of a significant association with either LR or DM, which may be more related to tumor biological factors.

In reduced-order modeling, complex systems that exhibit high state-space dimensionality are described and evolved using a small number of parameters. These parameters can be obtained in a data-driven way, where a high-dimensional dataset is projected onto a lower-dimensional basis. A complex system is then restricted to states on a low-dimensional manifold where it can be efficiently modeled. While this approach brings computational benefits, obtaining a good quality of the manifold topology becomes a crucial aspect when models, such as nonlinear regression, are built on top of the manifold. Here, we present a quantitative metric for characterizing manifold topologies. Our metric pays attention to non-uniqueness and spatial gradients in physical quantities of interest, and can be applied to manifolds of arbitrary dimensionality. Using the metric as a cost function in optimization algorithms, we show that optimized low-dimensional projections can be found. We delineate a few applications of the cost function to datasets representing argon plasma, reacting flows and atmospheric pollutant dispersion. We demonstrate how the cost function can assess various dimensionality reduction and manifold learning techniques as well as data preprocessing strategies in their capacity to yield quality low-dimensional projections. We show that improved manifold topologies can facilitate building nonlinear regression models.

The large number of species included in the detailed kinetic mechanisms represents a serious challenge for numerical simulations of reactive flows, as it can lead to large CPU times, even for relatively simple systems. One possible solution to mitigate the computational cost of detailed numerical simulations, without sacrificing their accuracy, is to adopt a Sample-Partitioning Adaptive Reduced Chemistry (SPARC) approach. The first step of the aforementioned approach is the thermochemical space partitioning for the generation of locally reduced mechanisms, but this task is often challenging because of the high-dimensionality, as well as the high non-linearity associated to reacting systems. Moreover, the importance of this step in the overall approach is not negligible, as it has effects on the mechanisms’ level of chemical reduction and, consequently, on the accuracy and the computational speed-up of the adaptive simulation. In this work, two different clustering algorithms for the partitioning of the thermochemical space were evaluated by means of an adaptive CFD simulation of a 2D unsteady laminar flame of a nitrogen-diluted methane stream in air. The first one is a hybrid approach based on the coupling between the Self-Organizing Maps with K-Means (SKM), and the second one is the Local Principal Component Analysis (LPCA). Comparable results in terms of mechanism reduction (i.e., the mean number of species in the reduced mechanisms) and simulation accuracy were obtained for both the tested methods, but LPCA showed superior performances in terms of reduced mechanisms uniformity and speed-up of the adaptive simulation. Moreover, the local algorithm showed a lower sensitivity to the training dataset size in terms of the required CPU-time for convergence, thus also being optimal, with respect to SKM, for massive dataset clustering tasks.

This review aims to evaluate the cumulative incidence proportion, incidence rate, and risk factors for progression of incidentally diagnosed, asymptomatic gallstones to symptomatic gallstone disease (GSD) and associated complications. Systematic Review and Meta-Analysis. Four electronic databases were searched (PubMed, Scopus, Web of Science, and ScienceDirect) with no start date restriction, up to July 2025. Inclusion criteria: patients who were diagnosed with gallstones incidentally. Exclusion criteria: known history of GSD, patients who have undergone bariatric surgery or cholecystectomy, recurrence of gallstones, pregnancy, estrogen therapy, pediatric age group, review, case report, case series, editorial, letters, and abstracts. This review is registered with PROSPERO (CRD42024526889). Primary screening by title and abstract was conducted in Rayyan; full-text screening was performed, and the references of the included studies were manually searched for relevant papers. Data were extracted into an Excel sheet, and the meta-analysis was conducted using RStudio. Single-arm outcomes were summarized in proportion, and comparative outcomes were summarized in Risk Ratio (RR) for categorical outcomes and mean difference for continuous ones. Heterogeneity was evaluated using the I statistic and the Q test. Eight cohort studies, reported in 9, with a total of 25,924 participants, were included. The cumulative incidence proportion of symptomatic progression was 0.10, 95% CI: [[0.10; 0.11]] at 5 years, 0.19, 95% CI: [0.14; 0.25] at 10 years, and 0.26, 95% CI: [0.12; 0.40] at 15 years. Alcohol consumption (RR: 1.32, 95% CI: [1.27; 1.38]) and hyperlipidemia (RR: 1.19, 95% CI: [1.07; 1.32]) were identified as risk factors. Chronic liver disease (RR: 0.76, 95% CI: 0.67; 0.87) and male gender (RR: 0.54, 95% CI: 0.33; 0.87) were observed as protective factors. This systematic review examines factors influencing symptomatic progression of ASG and guides the identification of high-risk patients who may benefit from prophylactic measures such as cholecystectomy.

Introduction Data supporting the utilization of neoadjuvant chemotherapy (NAC) in patients receiving resection for cholangiocarcinoma (CCA) remains uncertain. We aimed to determine whether NAC followed by resection improves long-term survival in intrahepatic (iCCA), perihilar (hCCA), and distal (dCCA) cholangiocarcinoma, analyzed separately. Methods Patients undergoing surgery for iCCA, hCCA, and dCCA, receiving either none, NAC, or adjuvant chemotherapy (AC) from 2010 to 2016 were identified from the National Cancer Database (NCDB). Cox regression was performed to account for selection bias and to assess the impact of surgery alone (SA) versus either NAC or AC on overall survival (OS). Results There were 9411 patients undergoing surgery for iCCA ( n = 3772, 39.5%), hCCA ( n = 1879, 20%), and dCCA ( n = 3760, 40%). Of these, 10.6% ( n = 399), 6.5% ( n = 123), and 7.2% ( n = 271) with iCCA, hCCA, and dCCA received NAC, respectively. On adjusted analyses, patients receiving NAC followed by surgery had significantly improved OS, compared to SA for iCCA ( HR 0.75, CI 95% 0.64–0.88, p < 0.001), hCCA ( HR 0.72, CI 95% 0.54–0.97, p = 0.033), and for dCCA ( HR 0.65, CI 95% 0.53–0.78, p < 0.001). However, sensitivity analyses demonstrated no differences in OS between NACs, followed by surgery or AC after surgery in iCCA ( HR 1.19, CI 95% 0.99–1.45, p = 0.068), hCCA ( HR 0.83 CI 95% 0.59–1.19, p = 0.311), and dCCA ( HR 1.13 CI 95% 0.91–1.41, p = 0.264). Conclusions This study associated NAC with increased OS for all CCA subtypes, even in patients with margin-negative and node-negative disease; however, no differences were found between NAC and AC. Our results highlight that a careful and interdisciplinary evaluation should be sought to consider NAC in CCA and warrant the need of larger studies to provide robust recommendation.

The objective of this work is to build a Digital Twin of a semi-industrial furnace using Gaussian Process Regression coupled with dimensionality reduction via Proper Orthogonal Decomposition. The Digital Twin is capable of integrating different sources of information, such as temperature, chemiluminescence intensity and species concentration at the outlet. The parameters selected to build the design space are the equivalence ratio and the benzene concentration in the fuel stream. The fuel consists of a H2/CH4/CO blend, doped with a progressive addition of C6H6. It is an H2-rich fuel mixture, representing a surrogate of a more complex Coke Oven Gas industrial mixture. The experimental measurements include the flame temperature distribution, measured on a 6×8 grid using an air-cooled suction pyrometer, spatially resolved chemiluminescence measurements of OH* and CH*, and the species concentration (i.e., NO, NO2, CO, H2O, CO2, O2) measured in the exhaust gases. The GPR-based Digital Twin approach has already been successfully applied on numerical datasets coming from CFD simulations. In this work, we demonstrate that the same approach can be applied on heterogeneous datasets, obtained from experimental measurements.

Liver transplantation is the only recognized effective treatment for end-stage liver disease. However, organ shortages have become the main challenge for patients and physicians within the transplant community. Waiting list mortality remains an issue with around 10% of patients dying whilst waiting for an available organ. The post-transplantation period is also associated with an adverse complication rate for these specific cohorts of high-risk patients, particularly regarding patient and graft survival. Ischaemia reperfusion injury (IRI) has been highlighted as the mechanism of injury that increases parenchymal damage, which eventually lead to significant graft dysfunction and other poor outcome indicators. The consequences of IRI in clinical practice such as reperfusion syndrome, primary non-function of graft, allograft dysfunction, ischaemic biliary damage and early biliary complications can be life-threatening. IRI dictates the development of a significant inflammatory response that drives the pathway to eventual cell death. The main mechanisms of IRI are mitochondrial damage due to low oxygen tension within the hepatic micro-environment and severe adenosine triphosphate (ATP) depletion during the ischaemic period. After the restoration of normal blood flow, this damage is further enhanced by reoxygenation as the mitochondria respond to reperfusion by releasing reactive oxygen species (ROS), which in turn activate Kupffer cells within the hepatic micro-environment, leading to a pro-inflammatory response and eventual parenchymal cell apoptosis and associated tissue degradation. Machine perfusion (MP) is one emergent strategy considered to be one of the most important advances in organ preservation, restoration and transplantation. Indeed, MP has the potential to rescue frequently discarded organs and has been shown to limit the extent of IRI, leading to suppression of the deleterious pro-inflammatory response. This immunomodulation reduces the prevalence of allograft rejection, the use of immunosuppression therapy and minimizes post-transplant complications. This review aims to update the current knowledge of MP with a focus on normothermic machine liver perfusion (NMLP) and its potential role in immune response pathways.

Background: Primary sclerosing cholangitis (PSC) accounts for 10–15% of liver transplants but is the leading cause of retransplant. This study evaluates whether PSC patients have different survival and graft outcomes when receiving grafts from donors after brain death (DBD) versus circulatory (DCD) death. Methods: Using the SRTR database (2004–2024), we compared PSC patients receiving DCD vs. DBD grafts. Demographics and outcomes including graft loss, mortality, and retransplant were analyzed using multivariable logistic and Cox regression, along with propensity-matched analysis. Results: Among 5762 PSC patients, 391 (6.8%) received DCD grafts. Patients receiving DCD grafts were older but had lower MELD scores (19 vs. 22; p < 0.001) and were less often functionally dependent (11.3% vs. 24.4%; p < 0.001). Multivariable Cox regression demonstrated that receipt of a DCD graft was independently associated with time to graft loss (HR 1.59; CI 1.10–2.31; p = 0.013. Similarly, DCD graft receipt significantly increased the likelihood of requiring retransplant (HR 3.25; CI: 1.93–5.46; p < 0.001) but did not increase the likelihood of mortality. Propensity matched analysis further supported these finding with significantly higher graft loss with DCD grafts at one and two years and higher retransplant rates at all time points including 5-years (+7.9%, CI 4.4 to 11.4%; p < 0.001). Conclusions: DCD grafts in PSC patients are linked to worse graft survival and higher retransplant rates. They may be best suited for older, lower-MELD patients, but further studies on perfusion strategies are needed.