Journals
2026 EN
Li Ruijie · Iniesta Raquel Revuelta · Barker Alan R.
+4 more
ABSTRACT Background Higher doses of anthracyclines and heart‐relevant radiotherapy increase cardiovascular disease (CVD) risk. This study assessed CVD and CVD risk factors among adult childhood cancer survivors (CCSs) across cardiotoxic treatment risk groups and examined associations between lifestyle behaviors and treatment risks. Methods We invited CCSs aged ≥18 years at study, diagnosed at ages 0–20, who survived ≥5 years for an assessment of anthropometry, CVD, CVD risk factors, lifestyle, and cancer history. We classified participants into three cardiotoxic treatment risk groups (no/low risk, moderate risk, high risk) based on anthracyclines and heart‐relevant radiotherapy. Multinomial logistic regression assessed lifestyle differences across groups. Results With a median age at study of 33 years (IQR: 26–39; 53% male), 356 CCSs participated in this study divided into the no/low risk (25%), moderate risk (40%), or high risk (35%) cardiotoxic treatment groups. Overall, CVD prevalence was 6% and similar across the three risk groups. Heart valve problems were rare, though more common in the high‐risk group (no/low risk, 0%; moderate risk, 1%; vs. high risk, 4%; p = 0.037). CVD risk factors were present in 44% of CCSs—including dyslipidemia, obesity, hypertension, and diabetes—without variation across risk groups. Overall adherence to health behavior recommendations was low, with no differences in diet adherence, physical activity (PA), sedentary behavior, smoking, or alcohol consumption across cardiotoxic risk groups. Conclusion We found no differences in CVD, CVD risk factors, or lifestyle behaviors across cardiotoxic treatment risk groups. Health promotion that engages diet, PA, smoking cessation, and alcohol reduction should be prioritized for all CCSs regardless of cardiotoxic treatment risk levels.
Journals
2026 EN
Yang Zhenwei · Rizopoulos Dimitris · Newcomb Lisa F.
+1 more
ABSTRACT Evaluating the performance of a prediction model is a common task in medical statistics. Standard accuracy metrics require the observation of the true outcomes. This is typically not possible in the setting with time‐to‐event outcomes due to censoring. Interval censoring, the presence of time‐varying covariates, and competing risks present additional challenges in obtaining those accuracy metrics. In this study, we propose two methods to deal with interval censoring in a time‐varying competing risk setting: a model‐based approach and the inverse probability of censoring weighting (IPCW) approach, focusing on three key time‐dependent metrics: area under the receiver‐operating characteristic curve, Brier score, and expected predictive cross‐entropy. The evaluation is conducted over a medically relevant time interval of interest,[ t , Δ t ) $[t, \Delta t)$ . The model‐based approach includes all subjects in the risk set, using their predicted risks to contribute to the accuracy metrics. In contrast, the IPCW approach only considers the subset of subjects who are known to be event‐free or experience the event within the interval of interest. We performed a simulation study to compare the performance of the two approaches with regard to the three metrics. Furthermore, we demonstrated the three metrics using the two approaches on an example prostate cancer surveillance cohort. Risk predictions were generated from a joint model handling the interval‐censored cancer progression and the competing event, early treatment, and repeatedly measured biomarkers.
Journals
2026 EN
Bisiotis Konstantinos · Christopoulos Dimitris · Tzougas George
ABSTRACT Carbon emissions trading is utilized by a growing number of states as a significant tool for addressing greenhouse gas emissions (GHG), global warming problem and the climate crisis. Accurate forecasting of carbon prices is essential for effective policy design and investment strategies in climate change mitigation. This review paper synthesizes recent advancements in carbon price forecasting models, examining time series methods, econometric approaches, and machine learning techniques, including neural networks and Long Short‐Term Memory (LSTM) models. By systematically presenting and comparing these methods, we identify key strengths and limitations, particularly highlighting the superior performance of advanced machine learning models in capturing nonlinear patterns and market complexities. Our review also explores innovative hybrid approaches, which address both short‐ and long‐term dynamics in carbon price trends.
Journals
2026 EN
Georgelou K. · Saridaki E. A. · Apostolidou C. P.
+11 more
ABSTRACT Emerging neurotrophin treatments for optic nerve injury (ONI) aim to prevent the loss of retinal ganglion cells (RGCs) and enhance axonal regeneration. Microneurotrophins (MNTs), small‐molecule mimetics of neurotrophins, have shown neuroprotective effects in various animal models of neurodegeneration, yet MNT effects on ONI remain unknown. Here, we study the effects of BNN27, a MNT that mimics NGF, in a mouse model of optic nerve crush (ONC) and compare the targeted administration via biomaterial grafts placed around the ONC lesion against standard eye drop delivery. Compared to eye drop delivery, targeted biomaterial‐based BNN27 delivery resulted in more consistent and efficient RGC neuroprotection and reduced microglia‐mediated inflammation in the ONC lesion. Our findings demonstrate that targeted delivery of MNTs can alleviate key consequences of ONI and, therefore, be an essential part of effective combinatorial ONI treatments.
Journals
2026 EN
Vasiliki Lazaratou Christina · Gourniezaki Maria · Yan Qun
+2 more
Abstract BACKGROUND Dairy wastewater (DWW) is characterized by high organic and suspended solid loads and its treatment remains a challenge for sustainable dairy industry operation. This study evaluates electrocoagulation‐electroflotation (EC/EF) with aluminum electrodes for treating real DWW under both batch and continuous‐flow conditions. RESULTS Experiments were performed in situ at the industry using fresh wastewater with variable initial pH (5.0–7.0), chemical oxygen demand (COD 0 :10800–3200 mg/L), and total suspended solids (TSS: 880–2030 mg/L). Batch experiments at current intensities of 0.15, 0.25, 0.5, and 1.0 A showed that 0.25 A (89.2 A/m 2 ) was particularly effective, achieving 79.75% COD and 95.76% TSS removal within 10 min at 10800 mg/L COD 0 and natural pH 5.33, with low energy consumption (0.14 kWh/m 3 ) and aluminum dissolution (27.96 g/m 3 ). For adjusted initial pH values of 5, 6, and 7 and COD 0 = 3200 mg/L, maximum COD and TSS removal occurred at pH 5, likely due to its proximity to the isoelectric point (~pH 3.7). Similarly, for COD 0 = 6200 mg/L, treatment at natural pH 6 yielded 79.22% COD and 90.37% TSS removal. At 4500 mg/L COD 0 , maintaining natural pH 6.7 reduced treatment time from 30 to 20 min while sustaining COD removal (~63%), although TSS removal dropped by ~36%. Continuous‐flow experiments at COD 0 = 6500 mg/L achieved steady‐state removal of ~72% COD of and 98% TSS at pH 5 with a 15‐min hydraulic retention time. CONCLUSION Overall, EC/EF proved technically viable, energy‐efficient, and effective for high‐strength DWW treatment, supporting its use as a pretreatment step in decentralized or industrial wastewater treatment systems. © 2026 Society of Chemical Industry (SCI).
Journals
2026 EN
Vayenas Vasilios · Lazaratou Christina Vasiliki · Yan Qun
+3 more
Abstract BACKGROUND Printing ink wastewater (PIW) contains high concentrations of organic matter, suspended solids, and colorants that challenge conventional treatment methods. Electrocoagulation–electroflotation (EC/EF) has emerged as a promising technique for such complex effluents. This study aimed to evaluate the efficiency of EC/EF using aluminum, iron, and stainless‐steel electrodes for PIW treatment and to assess performance improvements when coupled in a single step with adsorbents, such as palygorskite (EC/EF–P) and zeolite (EC/EF–Z). RESULTS Initial optimization focused on pH (5.0, 6.0, 7.5) and electrode type. Varying initial COD concentrations (~10 000–27 000 mg/L) had negligible impact on removal efficiencies, which remained high: COD (>90%), total suspended solids (>99%) and color (>90%). Notably, at lower initial COD levels (12 000 and 9970 mg/L), effluent COD concentrations were reduced below 1000 mg/L, meeting the discharge limits of the regional centralized wastewater treatment plant. The EC/EF–P and EC/EF–Z systems revealed that adsorbent addition significantly enhanced process performance. Palygorskite (6.0 g/L) accelerated COD removal, particularly under suboptimal electrochemical conditions, indicating its synergy with the EC/EF process. Zeolite (6.0 g/L) at pH 6.0 increased COD removal rate to 73.28 mg/(L·h) (20 min), compared to 48.38 mg/(L·h) (30 min) with palygorskite. CONCLUSION These findings highlight EC/EF, especially when augmented with adsorbents, as a highly effective strategy for rapid and compliant treatment of high‐strength industrial wastewater. © 2026 Society of Chemical Industry (SCI).
Journals
2026 EN
Zachariadou Christina · Doshi Anuja · Tatakis Dimitris N.
+1 more
Abstract Background Epithelium is the periodontal first line of defense against microbes. Discoidin domain receptor 1 (DDR1) is a collagen receptor expressed in epithelium. Ddr1 knockout ( Ddr1 −/− ) mice develop periodontitis‐like defects, including junctional epithelium (JE) downgrowth, bacterial invasion, and alveolar bone loss. The objective of this study was to investigate epithelial responses in the absence of DDR1. We hypothesized that Ddr1 −/− mice exhibit increased JE permeability and delayed epithelial wound healing. Methods Epithelium was analyzed in Ddr1 −/− and wild‐type ( Ddr1 +/+ ) mice. JE permeability was studied in vivo by applying a fluorescent dye and measuring dye penetration. Immunohistochemistry (IHC) was used to identify the localization of E‐cadherin and collagens IV, VIII, and XVII in oral epithelium. DDR1 expression in wound healing was confirmed by histology. Epithelial wound healing responses were assessed by creating skin and oral wounds and measuring epithelial migration and wound closure. Results No differences in JE permeability were observed between Ddr1 −/− and Ddr1 +/+ mice, although a trend in the means was observed toward decreased dye surface area ( p = 0.07) and intensity ( p = 0.08–0.09) in the periodontium of the former mice. IHC did not reveal differences in the localization of E‐cadherin or collagens IV, VIII, and XVII between genotypes. In human gingiva, DDR1 was expressed at the epithelial front, migrating to cover palatal wounds. Wound healing experiments revealed a higher % wound healing of dorsal skin in Ddr1 −/− than Ddr1 +/+ mice at 5 days post‐wounding (dpw) ( p = 0.01). Conclusions DDR1 does not affect JE permeability but may play a role in effective epithelial cell migration during cutaneous wound healing. Plain language summary Epithelium is the periodontal first line of defense against microbial attacks. Discoidin domain receptor 1 (DDR1) is a collagen receptor expressed at the epithelium. Mice not expressing the receptor ( Ddr1 −/− mice) develop defects consistent with periodontitis, including epithelium downgrowth and bone loss. In this study, we investigated periodontal epithelial permeability by applying a fluorescent dye in the mouth of Ddr1 +/+ and Ddr1 −/− mice. Additionally, we used histological methods to reveal differences in the localization of gingival proteins between Ddr1 +/+ and Ddr1 −/− . Finally, we investigated the role of DDR1 in wound healing in human sections and in a live animal model. No differences in junctional epithelium (JE) permeability were observed between Ddr1 +/+ and Ddr1 −/− mice, as expressed by the comparable presence of dye in the periodontal tissues of both types of mice. There were no differences in the localization of E‐cadherin or collagens IV, VIII, and XVII between Ddr1 +/+ and Ddr1 −/− . In human gingiva, DDR1 was expressed at the epithelial front, migrating to cover palatal wounds. The animal wound healing study revealed higher healing of skin wounds in Ddr1 −/− than Ddr1 +/+ mice at 5 dpw. In conclusion, this study has elucidated a role for DDR1 in epithelial cell migration during skin wound healing.
Journals
2026 EN
Neves Silva Sara · Uus Alena · Waheed Hadi
+18 more
Abstract Purpose This work aims to enable real‐time automated intra‐uterine volumetric reporting and fetal weight estimation for fetal MRI, deployed directly on the scanner. Methods A multi‐region segmentation nnUNet was trained on 146 images of 73 fetal subjects (coronal and axial orientations) for the parcellation of the fetal head, fetal body, placenta, amniotic fluid, and umbilical cord from whole uterus bSSFP stacks. A reporting tool was then developed to integrate the segmentation outputs into an automated report, providing volumetric measurements, fetal weight estimations, and z‐score visualizations. The complete pipeline was subsequently deployed on a 0.55T MRI scanner, enabling real‐time inference and fully automated reporting in the duration of the acquisition. Results The segmentation pipeline was quantitatively and retrospectively evaluated on 36 stacks of 18 fetal subjects and demonstrated sufficient performance for all labels, with high scores ( > $$ > $$ 0.98) for the fetus, placenta, and amniotic fluid, and 0.91 for the umbilical cord. The prospective evaluation of the scanner deployment step was successfully performed on 50 cases, with the regional volumetric reports available directly on the scanner. Conclusions This work demonstrated the feasibility of multi‐regional intra‐uterine segmentation, fetal weight estimation, and automated reporting in real‐time. This study provides a robust baseline solution for the integration of fully automated scanner‐based measurements into fetal MRI reports.
Journals
2026 EN
Sotiropoulos Dimitris P. · Tori Daniele · Rutterford Janette
This study examines professional asset management in the UK in the 1880s and 1890s focusing on investment trusts during the financial episode of the Baring crisis. It draws upon a large and unique hand-collected dataset of portfolio holdings on a year-on-year basis, comprising 27,058 securities. Using an event analysis, our findings show that investment trusts were the only heavily affected sector in the UK due to their massive portfolio exposure to Argentina. Our analysis does not pick up any strong stock selection skills in the short run but reveals a longer-term investment perspective based on large fixed-income cash flows on both sides of the balance sheet and a ‘carry-trade’ on yields. Our results also provide evidence of well-informed shareholders of these trusts, who had a very clear idea of the underlying fundamentals of their investment.
Journals
2026 EN
Abdollahnejad Azadeh · Georgopoulos Nikos · Katagis Thomas
+2 more
Detailed and updated information on forest extent, forest types, or species composition is essential for monitoring carbon stocks, mapping forest losses and growth, biodiversity conservation, and supporting national policies on natural resources management and climate mitigation, among others. Within the framework of establishing a National Forest Inventory, the availability of a revised baseline forest types map is very important for the subsequent operations, particularly when existent information is based on measurements that occurred decades ago. Advanced satellite optical data and modern machine learning algorithms are promoting efforts for large-scale, cost-effective, and high-resolution mapping of forests and their attributes at frequent intervals. The aim of this study was to propose a remote sensing-based classification approach for generating spatially explicit forest type information, aligned with the Greek National Forest Inventory’s hierarchical classification needs. Seasonal optical imagery and topographic data were utilized for mapping forest types over a large administrative region in Northern Greece. Three machine learning (ML) classification algorithms were also employed LightGBM, Random Forest (RF), and Support Vector Machines (SVM) and evaluated for optimal performance in accuracy and computation efficiency. Methodological steps included fine-tuning of the classifier’s parameters and discrimination of the most important features before assessing their performance. LightGBM demonstrated the highest performance, balancing accuracy (OA = 81%) and computational efficiency, although marginal differences can be observed among the classifiers for certain classes. Class-specific results indicated high classification accuracy for dense forests, while misclassification was primarily observed in spectrally similar classes. Despite the complex classification scheme required for the NFI, the proposed methodology highlights the importance of incorporating seasonal imagery and variables such as high-resolution canopy height models for improving systematic mapping of forest types in heterogeneous Mediterranean ecosystems.