Saved Queries

by Karolin Heinze, Tia S. Murdoch, Evan Cairns, Derek S. Chiu, Aline Talhouk, Ulrich Canzler, Jalid Sehouli, Sven Mahner, Philipp Harter, Jacobus Pfisterer, Stefan Kommoss and Michael S. Anglesio

Cancers 2026, 18(13), 2115; https://doi.org/10.3390/cancers18132115 (registering DOI) - 30 Jun 2026

Abstract

Background: High-grade serous ovarian carcinoma (HGSOC) can be subdivided into four prognostic molecular subtypes based on gene expression: C1/Mesenchymal (C1.MES), C2/Immunoreactive (C2.IMM), C4/Differentiated (C4.DIF) and C5/Proliferative (C5.PRO), each representing distinct biological characteristics with immune and stromal microenvironments. PrOTYPE enables prognosis and treatment guidance from biopsy material. Metastatic biopsies are often more accessible than primary adnexal sampling; their utility assumes stable tumor-intrinsic properties relative to the primary. Metastases may diverge due to microenvironmental pressure as well as the site-specific subtype dynamics. Methods: Treatment-naïve HGSOC specimens from 138 patients were profiled using the 55-gene nanostring PrOTYPE assay at adnexal, contralateral adnexal, and/or metastatic sites. Results: Adnexal PrOTYPE yielded expected distributions (21% C1.MES, 31% C2.IMM, 23% C4.DIF, 25% C5.PRO) with moderate reproducibility (κ = 0.49). Same-site replicate analysis showed substantial reproducibility (κ = 0.7). Non-adnexal sites were enriched for immune/mesenchymal subtypes (C1.MES/C2.IMM, 36/63 cases), most prominently at the omentum (24/32 C1.MES). C5.PRO was distinctly underrepresented at non-adnexal sites. Subtype shifts from adnexal to extra-adnexal sites were enriched for the second-place adnexal type prediction (p < 0.001). Detailed 55-gene analysis showed POSTN/CTSK were most commonly upregulated across metastatic sites. EMT pathway enrichment increased with metastatic distance (from adnexa to omentum, adj p < 0.05), paralleling—but independent of—C1.MES predominance. Conclusions: Adnexal PrOTYPE showed good stability. However, non-random subtype shifts and EMT enrichment at metastatic sites suggest dissemination selects pre-existing transcriptional plasticity rather than acquiring states de novo as HGSOC adapts to new microenvironments. Microenvironment changes may help predict metastatic potential and should be considered for precision medicine targeting. Full article

(This article belongs to the Section Cancer Pathophysiology)

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12 pages, 773 KB

Open AccessArticle

Early Versus Delayed Introduction of Faricimab for Initially Treatment-Naïve Diabetic Macular Edema: A Real-World Pilot Study

by Tanya Gupta, Benjamin Setters, Lama Hanbali, Shruti Wadhwa, Michael W. Daniels, Wei Wang, Charles Barr, Melis Kabaalioglu Guner, SriniVas R. Sadda and Aditya Verma

J. Clin. Transl. Ophthalmol. 2026, 4(3), 17; https://doi.org/10.3390/jcto4030017 (registering DOI) - 30 Jun 2026

Abstract

Background: Faricimab is one of the most potent anti-vascular endothelial growth factors used in the management of diabetic macular edema (DME). However, real-world benefits regarding its timing and efficacy are still being explored. Methods: This retrospective non-randomized pilot study aimed to evaluate the efficacy of intravitreal faricimab in the treatment of DME. Eyes initially treatment-naïve for DME with a follow-up of 1 year were grouped as: group 1, where faricimab was introduced within the first six months after the start of treatment; group 2, where it was initiated six or more months after treatment with other drugs. Study parameters included changes in best corrected visual acuity (BCVA) and optical coherence tomography based structural parameters within the 6 × 6 mm optical coherence tomography (OCT) scan regions. Results: Forty-two eyes from 26 patients were analyzed. No statistically significant differences were observed between the groups in cluster-weighted proportions of intra- or sub-retinal fluid, retinal thickness or volume parameters, although group 1 showed modest numerical benefits. SRF showed a trend towards qualitative reduction in group 1, although IRF showed persistence in both groups. Adjusted linear mixed-effects modeling demonstrated no significant impact of early faricimab initiation on functional and anatomical outcomes, which appeared to be influenced by the baseline BCVA, glycemic control, and the number of injections, nullifying the benefits. Conclusions: Faricimab demonstrated modest anatomical improvements with earlier treatment in eyes initially treatment-naïve for DME. Further prospective studies are indicated to assess the treatment strategy and the timing of introduction with faricimab in such eyes. Full article

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18 pages, 1065 KB

Open AccessArticle

Microbially Matured Phytomedicines from Sesame Hull (Sesamum indicum L.) Cell-Wall Oligosaccharides: Lactobacillus-Generated Pre-Postbiotics with Antioxidant, Enzyme-Inhibitory and Anti-Helicobacter pylori Activity in a Functional Beverage

by Fatemeh Naderi, Maryam Salami, Seyed Hadi Razavi, Mona Miran, Michael J. Serpe, Marleny D. A. Saldaña, Raimar Loebenberg, Marlon C. Mallillin, Shengnan Zhao and Neal M. Davies

J. Phytomed. 2026, 1(2), 7; https://doi.org/10.3390/jphytomed1020007 (registering DOI) - 30 Jun 2026

Abstract

Many bioactive constituents of medicinal plants depend on microbial biotransformation for their pharmacological activity, positioning postbiotics from plant substrates as microbially matured phytomedicines. An emerging framework integrates prebiotic phytochemicals with probiotic strains to modulate gut microbiota and host health. In this study, we explored the functional properties of heat-inactivated Lactobacillus strains following the fermentation of oligosaccharides obtained from sesame hulls (Sesamum indicum L.), underutilised agro-industrial residues. Cell-wall oligosaccharides were obtained by alkaline or enzymatic (Celluclast^® 1.5 L (Novonesis, Copenhagen, Denmark)) extraction with Ultraflo^® L (Novonesis, Copenhagen, Denmark) hydrolysis and fermented with Lactobacillus acidophilus, L. casei, or L. paracasei. Heat-inactivated pre-postbiotic preparations were profiled for antioxidant capacity, inhibition of metabolic enzymes implicated in obesity and type 2 diabetes, and anti-Helicobacter pylori urease activity. Moreover, these preparations were incorporated into a barley malt (Hordeum vulgare L.) beverage. Bioactivity was strain- and substrate-dependent: L. casei-derived postbiotics most strongly inhibited pancreatic lipase (47.82%) and α-glucosidase (52.14%); L. acidophilus most strongly inhibited α-amylase (43.67%); and L. paracasei exhibited the strongest urease inhibition (20.66%). All strains displayed enhanced antioxidant activity, with ABTS scavenging reaching 87.02%. The supplemented beverages improved antioxidant activity by ~20%. The fermentation of these oligosaccharides thus yields a microbially matured phytomedicine with multi-target activity, supporting postbiotics as active mediators of plant-based therapeutics. Full article

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22 pages, 26427 KB

Open AccessArticle

Estimating Crop Nitrogen Uptake from UAV-Based Imagery Using Machine Learning Techniques

by Amir M. Chegoonian, Keshav D. Singh, Charles M. Geddes, Christian Hansen, Louis J. Molnar and Manoj Natarajan

Remote Sens. 2026, 18(13), 2106; https://doi.org/10.3390/rs18132106 (registering DOI) - 30 Jun 2026

Abstract

Unmanned Aerial Vehicle (UAV)-based remote sensing using high-throughput spectral imaging has emerged as an effective non-destructive alternative for large-scale agricultural monitoring. This study evaluates the performance of UAV-based multispectral (MSI) and hyperspectral (HSI) imaging combined with machine learning for estimating in-season nitrogen uptake in spring wheat and canola. Field trials were conducted at irrigated and non-irrigated sites in southern and central Alberta, Canada, respectively, over three growing seasons (2023–2025). Coincident with ground-truth tissue sampling, aerial imagery was collected and processed to train and validate six machine learning models, using ~520 matchups per crop. All models successfully estimated nitrogen uptake across years and locations, although performance varied by sensor and data types. For canola, ANN produced the highest MSI-based accuracy (R² = 0.83, RMSE = 0.5%), whereas HSI data improved prediction performance, with SVR achieving the best results (R² = 0.90, RMSE = 0.40%). In wheat, ANN yielded the highest accuracy for both MSI and HSI data (R² = 0.77, RMSE = 0.54% for MSI; R² = 0.8, RMSE = 0.48% for HSI). These findings demonstrate that UAV-based spectral imaging combined with machine learning provides a reliable and scalable approach for non-destructive nitrogen uptake estimation. Although MSI sensors produced strong predictive performance, the enhanced spectral resolution of HSI data consistently improved estimation accuracy for both crops across varied growing conditions. Full article

(This article belongs to the Special Issue Machine Learning Approaches for Semantic and Instance Segmentation in Remote Sensing)

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24 pages, 828 KB

Open AccessReview

Modern Approaches to Diagnosis and Evaluation of Survival Prognosis in Patients with Pancreatic Cancer

by Maria Getsina, Nikolay Tsyba and Ekaterina Chernevskaya

Int. J. Mol. Sci. 2026, 27(13), 5867; https://doi.org/10.3390/ijms27135867 (registering DOI) - 29 Jun 2026

Abstract

Pancreatic cancer is among the most aggressive malignancies, and late diagnosis remains a key challenge. For a systematic review of pancreatic cancer diagnosis and prognosis, Scopus and Web of Science databases were used for the period from 2016 to 2026. The search query included the following keywords and their combinations: pancreatic cancer, diagnosis, early detection, prognosis, biomarkers, metabolomic profiling, CA19-9, microbiome, metagenomic changes, circulating tumor DNA, genomic analysis. Inclusion criteria included only articles published in English. Exclusion criteria included case reports and studies that did not examine pancreatic cancer. Our analysis demonstrates that integrating multi-omics data, particularly combining traditional CA19-9 with circulating tumor DNA (ctDNA) and metabolomic profiles (lipids, amino acids, carbohydrates), significantly improves diagnostic accuracy. Microbiome composition and genomic alterations further refine risk stratification and prognostic assessment. The synergistic use of these biomarkers may facilitate the development of screening, early diagnosis, risk stratification, and treatment optimization. However, the introduction of new diagnostic approaches into clinical practice requires additional verification, standardization and prospective clinical studies. Full article

(This article belongs to the Special Issue Molecular Advances in Cancer and Cell Metabolism—3rd Edition)

29 pages, 2659 KB

Open AccessArticle

Output-Bias Reference Correction Using Long Short-Term Memory Networks for Model Predictive Control of Industrial Processes with Delays and Variable Parameters: Application to a Mining Thickener

by Mouna El Hamrani, Khalid Benjelloun, Jean-Pierre Kenné, Saad Maarouf and Mohamed El Khouakhi

Appl. Sci. 2026, 16(13), 6487; https://doi.org/10.3390/app16136487 (registering DOI) - 29 Jun 2026

Abstract

Many continuous industrial processes are non-linear, multi-variable, subject to transport or reaction delays, and described by operating-point-dependent parameters. These characteristics reduce the reliability of fixed models used in model predictive control (MPC), particularly when slow disturbances, regime changes and operational constraints are dominant. This paper proposes an output-bias reference-correction framework based on Long Short-Term Memory (LSTM) networks for predictive control of industrial processes with delays and variable parameters. The dominant dynamics are represented by a fixed compact linear nominal model in deviation coordinates; this model drives a standard constrained MPC that remains structurally unchanged throughout operation. The persistent output bias between the actual process and the nominal model is learned from closed-loop data by an LSTM network. At each sampling step, the predicted bias is used to correct the future reference trajectory fed to the nominal MPC, so that the controller compensates for model–process mismatch without modifying its internal model, constraint set or solver. The final implementation uses a one-step bias predictor, selected by ablation, and it extends this one-step estimate across the MPC horizon by exponentially decayed persistence. A closed-loop bias-error bound links the LSTM identification error, the adaptive correction gain and the resulting tracking deviation. The framework is illustrated using a mining thickener, a representative process characterised by slow dynamics, delays, variable parameters and stringent safety constraints. A three-controller Monte Carlo study compares the nominal MPC, a classical offset-free MPC and the proposed LSTM-MPC, and it highlights the resulting tracking–actuation–constraint trade-off. Applied to a mining thickener, the LSTM corrector reduces the first-step output-prediction RMSE by 96.6 % (FIT from

- 14.8 %

96.1 %

). In a 50-scenario Monte Carlo closed-loop evaluation, the LSTM-MPC outperforms the nominal MPC in 92 % of scenarios on RMSE while using substantially less actuator activity than the offset-free baseline (mean input total variation: 67.0 vs. 119.4). Full article

(This article belongs to the Special Issue Artificial Intelligence in Mining, Mineral and Material Processing)

26 pages, 3010 KB

Open AccessArticle

Attention Under Fire: The Effect of Wartime Public Focus on Israel’s Stock and Exchange Rate

by Nikolaos Papanikolaou, Evangelos Vasileiou and Themistoclis Pantos

Risks 2026, 14(7), 148; https://doi.org/10.3390/risks14070148 (registering DOI) - 29 Jun 2026

Abstract

This study examines the impact of public attention on financial markets during the Israel–Hamas conflict, focusing on the TA35 stock index and the Israeli Shekel (ILS) exchange rate over the period October 2023 to April 2025. By distinguishing between global and domestic Google search activity, the analysis investigates whether the origin of attention differentially affects market performance and currency dynamics. Public attention is treated as a real-time proxy for investor sentiment and perceived risk. Methodologically, the study combines Google Trends data with EGARCH(1,1) models to capture both return effects and asymmetric volatility responses. To enhance robustness, Principal Component Analysis (PCA) is applied separately to global and domestic search datasets, generating latent indices that reflect conflict-related and humanitarian narratives. These indices are subsequently incorporated into the empirical models. The findings reveal that global search intensity related to conflict topics exerts a significant negative effect on stock returns and contributes to currency depreciation, reflecting heightened uncertainty and risk aversion. In contrast, domestic search activity is associated with stabilizing or positive effects, suggesting local resilience and confidence. PCA-based models improve explanatory power and confirm that the geographical origin of attention plays a crucial role in shaping financial outcomes. Additionally, the results indicate that attention-driven shocks influence volatility asymmetrically, amplifying downside risk during periods of intensified global concern. Overall, the study contributes to the literature by integrating behavioral indicators into financial risk modeling and providing a novel, real-time framework for assessing how digital attention transmits geopolitical risk into asset prices. Full article

(This article belongs to the Special Issue Risk-Based and Behavioral Approaches to Stock Market Investment)

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17 pages, 4138 KB

Open AccessArticle

Calcined Crab Shell as a Sustainable Supplementary Cementitious Material in Cement Pastes: Chemical Interaction, Microstructural Evolution, and Mechanical Performance

by Khouloud Ben Chaabene, Rose-Marie Dheilly, Geoffrey Promis and Marzouk Lajili

Constr. Mater. 2026, 6(4), 41; https://doi.org/10.3390/constrmater6040041 (registering DOI) - 29 Jun 2026

Abstract

The growing demand for sustainable construction materials has stimulated interest in alternative binders derived from waste resources. This study investigates the use of calcined crab shell (CCS), a calcium-rich marine biowaste, as a partial replacement for Portland limestone cement. Cement pastes containing 0%, 5%, 10%, and 15% CCS were prepared and evaluated through compressive strength, water absorption, open porosity, bulk density, SEM, XRD, FTIR, and TGA analyses. The results showed that incorporating 10% CCS produced the most favorable performance, increasing compressive strength from 17.6 MPa to 33.6 MPa after 28 days of curing. This improvement was accompanied by reduced porosity, increased bulk density, and the development of a denser and more homogeneous microstructure. Physicochemical analyses suggest that CCS acts both as a filler and as a source of reactive calcium species. The CaO generated during calcination may participate in hydration processes and influence the formation of hydration products, contributing to matrix densification. In contrast, the incorporation of 15% CCS resulted in increased porosity, a less homogeneous microstructure, and lower mechanical performance. These findings indicate that replacing Portland limestone cement with up to 10% CCS can improve the properties of cement pastes while promoting the valorization of marine shell waste and reducing cement consumption, thereby supporting the development of more sustainable construction materials. Full article

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19 pages, 3434 KB

Open AccessArticle

A Probabilistic Model of Fatigue Life at the Interface of CRTS II Slab Ballastless Track

by Anxiang Song, Yuanchen Guo, Guowen Yao and Xuanrui Yu

Materials 2026, 19(13), 2762; https://doi.org/10.3390/ma19132762 (registering DOI) - 29 Jun 2026

Abstract

The gradual deterioration of interfacial performance in CRTS II (China Railway Track System II) slab ballastless tracks during long-term service can significantly affect structural stability and durability. Existing studies have mainly focused on the fatigue performance of the overall track system and individual structural layers, whereas probabilistic fatigue-life modeling of the interlayer interface remains relatively limited. This study investigates the fatigue life behavior of the track slab-CA (cement-asphalt) mortar interface under cyclic loading. An exponential stress life relationship was combined with a two-parameter Weibull distribution of fatigue life at a specified stress ratio to establish a multi-parameter Weibull-based probabilistic framework that links fatigue life, stress ratio, and failure probability. Push-out and positive tensile fatigue tests were conducted on composite specimens to obtain interface fatigue lives under different stress ratios. Leveraging the multi-parameter Weibull model and experimental data, the L-BFGS-B (Limited-memory Broyden-Fletcher-Goldfarb-Shanno with Box constraints) algorithm was employed to optimize the model parameters and construct a probabilistic fatigue life model. The calibrated model was then used to analyze the fatigue behavior of the slab-CA mortar interface under tangential and vertical loading. The results show that the proposed probabilistic framework provides good agreement with the interface fatigue test data and enables the fatigue-life distribution and failure probability of the interlayer interface to be evaluated under different stress ratios. The findings provide a probabilistic basis for fatigue assessment and durability analysis of CRTS II slab ballastless track interfaces. Full article

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30 pages, 2266 KB

Open AccessArticle

Nanoencapsulation of Artemisia annua Essential Oil in Chitosan-Lipid Carriers Enhances Stability, Larvicidal, Antifungal, and Anticancer Efficacy

by Ghassab M. Al-Mazaideh, Mohammed Alshammari, Bader Alsuwayt, Abdulkareem A. Alanezi, Nimer Fehaid Alsabeelah, Afaf F. Almuqati, Meshal Alotaibi, Shatha Alzahrani, Turki Hamdan Alsayyali, Haya Ayyal Salman, Abdulrahman Fahad Nagi Almutairi and Mohammed Helmy Faris Shalayel

Pharmaceutics 2026, 18(7), 804; https://doi.org/10.3390/pharmaceutics18070804 (registering DOI) - 29 Jun 2026

Abstract

Background/Objectives:Artemisia annua essential oil (EO) possesses diverse biological activities; however, its practical application is limited by volatility, instability, and poor bioavailability. This study aimed to develop chitosan-coated nanostructured lipid carriers (CH-NLCs) for efficient encapsulation and delivery of A. annua EO and to evaluate their physicochemical characteristics and biological performance. Methods: The nanoformulation exhibited favorable physicochemical properties, including a high encapsulation efficiency (85.97 ± 1.30%) and a strongly positive surface charge (approximately +45 mV), indicating good colloidal stability. Structural analyses by SEM, FTIR, and XRD confirmed successful encapsulation of the EO within the nanocarrier matrix. Results: The CH-NLC formulation significantly enhanced larvicidal activity against Aedes aegypti larvae, reducing the LC₅₀ value from 213 ppm for the free EO to 142 ppm. Enhanced antifungal activity was also observed, with 47–56% greater inhibition against Malassezia furfur, Trichophyton mentagrophytes, and Candida albicans compared with the free EO. Furthermore, CH-NLC demonstrated improved cytotoxic activity against skin cancer cell lines, achieving IC₅₀ values of 21.4 ± 1.7 µg/mL and 30.1 ± 1.6 µg/mL against A431 and A375 cells, respectively, while maintaining lower toxicity toward normal HaCaT keratinocytes. Mechanistic investigations revealed enhanced apoptosis and an approximately 3-fold increase in intracellular reactive oxygen species (ROS) levels in treated cancer cells. Conclusions: Collectively, these findings indicate that chitosan-coated nanostructured lipid carriers effectively improve the stability and biological efficacy of A. annua essential oil and represent a promising platform for future biomedical and biocidal applications. Full article

(This article belongs to the Special Issue Anti-Inflammatory Effects from Natural Bioactive Compounds—from Bench to Bedside, 3rd Edition)

14 pages, 1209 KB

Open AccessArticle

Influence of Supersaturation Level on the Efficacy of Crystallization Inhibitors

by Jaume Dietrich, Bernat Isern, Felix Grases and Antonia Costa-Bauza

Crystals 2026, 16(7), 423; https://doi.org/10.3390/cryst16070423 (registering DOI) - 29 Jun 2026

Abstract

This in vitro study examined the influence of supersaturation level on the efficacy of different inhibitors in preventing the crystallization of calcium oxalate, uric acid, and cystine. Kinetic–turbidimetric assays were used to determine the induction time of crystallization (t_i) in the absence and presence of different inhibitors. For calcium oxalate, the inhibitory effects of citrate, hydroxycitrate, tartronate, and phytate decreased significantly as the Ca²⁺ concentration increased from 220 mg/L to 240 mg/L. The polyhydroxycarboxylic compounds (citrate, hydroxycitrate, tartronate) can form complexes with calcium ions, decreasing overall supersaturation. Even though phytate also forms complexes with calcium, its urinary concentration is much lower than that of calcium, so the decrease in supersaturation can be considered negligible. For uric acid, theobromine and two of its metabolites (3-methylxanthine and 7-methylxanthine) inhibited the formation of these crystals. For each compound, the efficacy of inhibition decreased as the supersaturation of uric acid increased. For cystine, the inhibitory effect of N-acetylcysteine was lower at pH 4.5 and 5.0 than at pH 6.0. These studies of the crystallization of calcium oxalate, uric acid, and cystine showed that the efficacy of crystallization inhibitors decreased as the level of supersaturation increased. The results demonstrate that, in patients prone to kidney stone formation, the effectiveness of crystallization inhibitors can be improved by reducing the supersaturation of the specific stone-forming compound. Full article

(This article belongs to the Special Issue Bridging the Embryonic Period for Disruptive Innovation in Crystal Growth)

22 pages, 2620 KB

Open AccessArticle

Mechanical Properties, Hydration Mechanisms, and Microwave-Absorbing Properties of Alkali-Activated Blast-Furnace Slag Containing Steel Slag

by Qian Wang, Xiaotong Peng, Yuxin He, Zhenhua Yang, Ziqi Li, Yulin Wang, Taibing Wei, Rong Wang and Huawei Li

Materials 2026, 19(13), 2761; https://doi.org/10.3390/ma19132761 (registering DOI) - 29 Jun 2026

Abstract

As a novel low-carbon material, alkali-activated materials (AAMs) can effectively mitigate the environmental burden caused by the cement industry, and their functional development can further enhance their additional commercial benefits. This study employed alkali-activated blast-furnace slag (AAS) as a matrix and incorporated steel slag (SS) as a functional component, and the compressive strength, workability, shrinkage characteristics, microstructure, and microwave-absorbing properties of SS-containing AAS were systematically investigated. The results show that although the low reactivity of SS impairs the compressive strength of AAS, it effectively reduces the setting rate of AAS. At an SS dosage of 50% (sample B-S50), the 28-day drying shrinkage of AAS reached a minimum value of 778 με. The dissolution and hydration of SS provide additional Ca²⁺ and OH⁻ for AAS, thereby effectively promoting the hydration of blast-furnace slag and facilitating the formation of C–(A)–S–H and N–A–S–H gels. Moreover, SS acts as a conductive functional component, enhancing the conductivity of AAS and enabling a minimum reflection loss of −29.47 dB with 0.53 GHz effective bandwidth at 20 mm thickness. After further modification with steel fibers, the thickness-dependence of the microwave-absorbing properties of AAS was reduced, allowing effective absorption across multiple thicknesses (5 mm, 15 mm, and 25 mm). This study offers new insights into the high-value utilization of low-reactivity industrial solid waste and offers design methods for its functional development. Full article

(This article belongs to the Section Construction and Building Materials)

14 pages, 2181 KB

Open AccessCase Report

Multimodal Analysis of Aggressive Multifocal Cutaneous Squamous Cell Carcinoma Associated with a Germline COL6A3 Truncating Variant: A Case Report

by Mircea Negrutiu, Stefan Cristian Vesa, Bogdan Florea, Diana Miclea, Razvan Bucur, Adrian Baican, Monica Focșan and Sorina Danescu

Diagnostics 2026, 16(13), 2032; https://doi.org/10.3390/diagnostics16132032 (registering DOI) - 29 Jun 2026

Abstract

Background: Cutaneous squamous cell carcinoma (cSCC) is commonly regarded as a sporadic malignancy primarily driven by ultraviolet exposure. However, the occurrence of multiple, aggressive tumors at a relatively young age suggests the presence of underlying genetic susceptibility. The role of germline variants affecting extracellular matrix organization, pigmentation pathways, and tumor metabolism in aggressive cSCC remains incompletely understood. Case Presentation: We describe a 53-year-old patient with a long-standing history of multiple aggressive cutaneous squamous cell carcinomas involving the scalp and facial regions, characterized by recurrent and multifocal disease. A comprehensive diagnostic approach was undertaken, including histopathological examination, fluorescence confocal microscopy, high-frequency cutaneous ultrasound, and genetic analysis using whole-exome sequencing (WES). Results: Histopathology confirmed high-risk features consistent with aggressive cSCC. Cutaneous ultrasound and fluorescence confocal microscopy provided complementary, non-invasive insights into tumor depth, architecture, and invasive patterns. Whole-exome sequencing identified a heterozygous truncating variant in COL6A3 (NM_004369.4:c.5645C>A, p.Ser1882Ter), classified as likely pathogenic according to ACMG criteria. Additionally, two heterozygous variants of uncertain significance were detected in TYR (NM_000372.5:c.1569C>A, p.Ser523Arg) and FH (NM_000143.4:c.1237-5_1237-4insTCTCCCTCCCTC). Although individually inconclusive, the combined germline genetic background may have contributed to the patient’s aggressive and multifocal cutaneous phenotype. Discussion: This case report supports a potential role of extracellular matrix remodeling, pigmentation-related susceptibility, and metabolic dysregulation in cutaneous carcinogenesis and tumor aggressiveness. This case illustrates how integrating WES with advanced non-invasive imaging techniques can enhance the understanding of biologically aggressive cSCC. Conclusions: This report highlights a unique case of multifocal aggressive cSCC characterized by a distinct germline genetic profile identified by WES and multimodal imaging assessment. Comprehensive molecular and imaging evaluation may be beneficial in selected patients with atypical or aggressive cutaneous squamous cell carcinoma, with implications for personalized surveillance and management. Full article

(This article belongs to the Special Issue Ultrasound and Multimodal Diagnostics in Personalized Medicine)

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22 pages, 12952 KB

Open AccessArticle

Fluid Flow Analysis in Fractured Rock Mass by Data Integration of Digital Outcrop Model and Discrete Fracture Network (DFN)

by Matteo Giovanni Foletti, Niccolò Menegoni, Yuri Panara, Daniele Giordan, Claudia Meisina, Giorgio Pilla, Davide Elmo and Cesare Perotti

Geosciences 2026, 16(7), 257; https://doi.org/10.3390/geosciences16070257 (registering DOI) - 29 Jun 2026

Abstract

Fracture characterization is crucial to constrain a realistic subsurface reservoir model. They are key elements, affecting fluid flow, permeability and consequently recovery factor and productivity. Considering a proper assessment of fracture network from subsurface investigation is often difficult; in recent years, the application of Digital Photogrammetry (DP) has become popular for fracture network characterization. In this paper, we combined DP and Discrete Fracture Network modeling (DFN) to assess the fluid circulation analysis of the Monte Antola Formation (Northern Apennines, Italy). Thanks to the application of DP, it is possible to reconstruct Digital Outcrop Models (DOMs) and acquire high-precision fracture measurements such as size, location, and orientation. Utilizing quantitative measurements, we performed DFNs to simulate rock mass permeability. The primary findings from the DFNs indicate that fluid circulation is primarily influenced by (1) regions with a high density of fractures, which are associated with the primary structural features observed throughout the study area, and (2) locally, by the orientation of the dominant and persistent fracture set. The proposed approach highlights the importance of the use of DOMs for better reconstruction of the fracture network and defining an important number of relevant parameters; such quantitative information remarkably improves the reliability of DFNs. Full article

(This article belongs to the Special Issue New Trends in Numerical Methods in Rock Mechanics and Rock Engineering)

29 pages, 3264 KB

Open AccessArticle

Temporal Variability and Evolution of PM_2.5 Sources in an Urban Environment: A PIXE–PMF Study in Vilnius, Lithuania

by Viachaslau Alifirenka, Daria Pashneva, Vitalij Kovalevskij, Mindaugas Gaspariūnas, Kristina Plauškaitė and Steigvilė Byčenkienė

Atmosphere 2026, 17(7), 645; https://doi.org/10.3390/atmos17070645 (registering DOI) - 29 Jun 2026

Abstract

This study investigates the long-term variability and evolution of particulate matter with an aerodynamic diameter of <2.5 µm (PM_2.5) sources in Vilnius, Lithuania, during the period 2013–2021. Source apportionment was performed using Positive Matrix Factorization (PMF) based on elemental composition data obtained through particle-induced X-ray emission (PIXE) analysis. The results revealed substantial year-to-year variability in the chemical profiles of the identified sources. Crustal/mineral dust was characterized by high contributions of lithogenic elements, including Si, Ca, Ti, and Fe, while soil dust exhibited elevated proportions of Al, Ca, and Fe. Traffic non-exhaust emissions were marked by elevated Cu, Zn, and Pb in 2013–2015, whereas exhaust emissions in 2019–2021 were characterized by sulfur-rich aerosols. Industrial and oil combustion sources showed enhanced contributions of Ni, V, and Cr, particularly in 2016, 2018, and 2020. Biomass/wood burning represented a major seasonal source, reaching peak intensity in 2018–2019 and characterized by elevated K and Zn contributions. A notable long-term trend was the increasing importance of soil-derived particles, as reflected by Al contributions rising to 91.2% by 2021. Overall, the major PM₂.₅ source categories remained relatively stable, while their chemical fingerprints and relative importance exhibited substantial temporal variability. Full article

(This article belongs to the Special Issue Urban Air Quality, Green Spaces, and Microclimate Analysis)

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