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Open AccessArticle

Changes in Pitching Performance After Ulnar Collateral Ligament Reconstruction Differ Among Major League Baseball Starting and Relief Pitchers

by Thomas Almonroeder, Zachary Knapp, Charles Dunavan, Jay Krebs, Margaret T. Jones, Jennifer B. Fields, Michael H. Bittner, Brandon Merfeld and Andrew R. Jagim

Appl. Sci. 2026, 16(12), 5846; https://doi.org/10.3390/app16125846 (registering DOI) - 10 Jun 2026

Abstract

The primary aim of this study was to examine pitching performance metrics before and after ulnar collateral ligament reconstruction (UCLR) among Major League Baseball (MLB) starting and relief pitchers. The following information was extracted from the “Tommy John Surgery List” database regarding UCLR [...] Read more.

The primary aim of this study was to examine pitching performance metrics before and after ulnar collateral ligament reconstruction (UCLR) among Major League Baseball (MLB) starting and relief pitchers. The following information was extracted from the “Tommy John Surgery List” database regarding UCLR surgeries among MLB pitchers: UCLR date, pitcher type (starting pitcher, relief pitcher), and age at time of UCLR. Pitching performance metrics were extracted from the Baseball Savant online platform for the two seasons immediately prior to UCLR (pre) and the two seasons immediately following returning to pitching after UCLR (post). Fifty-nine pitchers were included in this study (29 starting pitchers, 30 relief pitchers). The outcome measures included the number of pitches thrown, earned run average (ERA), walks plus hits per inning pitched (WHIP), strikeout percentage, whiff percentage, walk percentage, batting average against, ground ball percentage, and fastball velocity. There was a pitcher type-by-time interaction effect for ERA (p = 0.01; η² = 0.12) and WHIP (p = 0.01; η² = 0.12). Starting pitcher ERA increased from 3.68 to 4.40 from pre- to post-surgery, while relief pitcher ERA decreased from 4.47 to 3.90. In addition, starting pitcher WHIP increased from 1.22 to 1.29 from pre- to post-surgery, while relief pitcher WHIP decreased from 1.38 to 1.28. There was a main effect of time for pitches thrown (p = 0.04; η² = 0.07). Significant differences between starting and relief pitchers were observed for changes in ERA and WHIP following UCLR, whereas no pitcher type-by-time interactions were observed for the remaining performance metrics. Both starting and relief pitchers threw fewer pitches following UCLR, while fastball velocity and other key pitching performance metrics remained largely unchanged. Full article

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21 pages, 1073 KB

Open AccessArticle

A Unified AI Framework for Turkish E-Commerce Review Analysis: Sentiment Classification, LLM-Based Summarization, and Fuzzy Evaluation

by Erdal Özbay, Feyza Altunbey Özbay and Ahmet Bedri Özer

Appl. Sci. 2026, 16(12), 5849; https://doi.org/10.3390/app16125849 (registering DOI) - 10 Jun 2026

Abstract

The rapid growth of user-generated reviews on e-commerce platforms has created a significant decision-making challenge for both consumers and sellers, particularly in morphologically rich low-resource languages such as Turkish. This study proposes a unified artificial intelligence framework for Turkish e-commerce review intelligence by [...] Read more.

The rapid growth of user-generated reviews on e-commerce platforms has created a significant decision-making challenge for both consumers and sellers, particularly in morphologically rich low-resource languages such as Turkish. This study proposes a unified artificial intelligence framework for Turkish e-commerce review intelligence by integrating transformer-based sentiment classification, instruction-tuned large language model summarization, and explainable fuzzy logic-based product evaluation within a single end-to-end architecture. A balanced dataset containing 183,333 Turkish reviews was constructed from Trendyol, Amazon Turkey, and Hepsiburada using LLM-assisted annotation and stratified downsampling. Experimental evaluations demonstrated that the fine-tuned BERTurk 128k model achieved a macro F1-score of 0.9243 on the held-out test set. To overcome the limitations of multilingual news-oriented summarization models on informal review text, the framework employed the Turkish instruction-tuned Kumru-2B model together with structured prompt engineering to generate sentiment-aware abstractive summaries. In addition, a Mamdani-type fuzzy inference system was designed to combine sentiment distribution, seller reliability, star ratings, and review volume into an interpretable product-level score. The complete pipeline was integrated into a FastAPI and React-based web platform capable of processing approximately 850 reviews in under 60 s. The findings demonstrate that domain-specific Turkish language models combined with explainable reasoning mechanisms can provide accurate, scalable, and human-interpretable decision support for large-scale e-commerce environments. Full article

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23 pages, 28122 KB

Open AccessArticle

Urban–Rural Spatial Patterns, Landscape Configuration, and Carbon Emission Performance: A County-Level Analysis in Henan Province, China

by Shaowei Zhang, Xiaoyang Guo, Shennian Zhang, Chen Li and Chenming Zhang

Land 2026, 15(6), 1021; https://doi.org/10.3390/land15061021 (registering DOI) - 10 Jun 2026

Abstract

Against the backdrop of global climate change and increasing pressure to mitigate carbon emissions, counties serve as critical units for urban–rural spatial development and carbon governance. However, their carbon emission performance (CEP) and underlying spatial mechanisms remain insufficiently understood. This study focuses on [...] Read more.

Against the backdrop of global climate change and increasing pressure to mitigate carbon emissions, counties serve as critical units for urban–rural spatial development and carbon governance. However, their carbon emission performance (CEP) and underlying spatial mechanisms remain insufficiently understood. This study focuses on 157 counties in Henan Province, selecting three time points: 2013, 2018, and 2023. The study measures the CEP and analyzes its spatiotemporal differentiation characteristics. First, considering that carbon emissions are undesirable outputs generated during the economic production process, this study employs the undesirable output slack-based measure (UN_SBM) model and the super-efficiency slack-based measure model with undesirable outputs (Un_Super_SBM) to evaluate county-level carbon emission performance. Second, landscape pattern indicators, including expansion, complexity, and compactness, are selected, and regression models are constructed to explore the influence of different factors on carbon emission performance. The results show the following: (1) The overall CEP of counties in Henan Province improved from 2013 to 2023, but there were significant spatial differences. (2) Both “Total landscape area” (TA) and “Area-weighted mean shape index” (AWMSI) had significant positive impacts on CEP, whereas the “Splitting index” (SPLIT) inhibited CEP. (3) The effects of vegetation cover and transportation conditions varied, reflecting the heterogeneity of development stages and spatial functional positioning across different counties. This study reveals the relationship between urban–rural spatial form and carbon emission performance at the county level, providing empirical evidence for optimizing construction land spatial structure, enhancing CEP, and promoting regional low-carbon development. Full article

(This article belongs to the Special Issue Land Use Sustainability from the Viewpoint of Carbon Emission: 3rd Edition)

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16 pages, 3225 KB

Open AccessArticle

National Trends and Demographic Disparities in Mortality Involving Co-Recorded Parkinson’s Disease and Dementia in the United States, 1999–2025: A CDC WONDER Analysis

by Hassaan Abid, Sohana Memon, Vishan Das, Kaneez Fatima, Muhammad Mukhlis and Muhammad Vazaym

NeuroSci 2026, 7(3), 66; https://doi.org/10.3390/neurosci7030066 (registering DOI) - 10 Jun 2026

Abstract

Background: Parkinson’s disease and dementia are major neurodegenerative disorders that substantially contribute to disability, dependency, and mortality worldwide. Although prior CDC WONDER studies have separately evaluated Parkinson’s disease and dementia mortality trends, fewer analyses have examined national mortality patterns in which both conditions [...] Read more.

Background: Parkinson’s disease and dementia are major neurodegenerative disorders that substantially contribute to disability, dependency, and mortality worldwide. Although prior CDC WONDER studies have separately evaluated Parkinson’s disease and dementia mortality trends, fewer analyses have examined national mortality patterns in which both conditions are recorded on death certificates simultaneously over extended time periods. Methods: We analyzed U.S. death certificates from 1999 through 2025 using the CDC WONDER Multiple Cause of Death database, identifying deaths among adults aged ≥45 years in which both Parkinson’s disease (ICD-10 G20) and dementia-related codes (F01, F03, G30, G31) were recorded anywhere on the certificate. This operational definition captures co-recorded diagnoses and does not identify clinically confirmed Parkinson’s disease dementia. Age-adjusted mortality rates (AAMRs) per 100,000 were standardized to the 2000 U.S. standard population, a method that controls for shifts in population age structure over time and allows valid temporal comparisons independent of absolute population growth. Joinpoint regression was used to quantify trends. Sensitivity analyses excluded 2025 provisional data and the COVID-19 period (1999–2019). Results: A total of 337,721 deaths were identified. Overall AAMR increased from 5.75 (95% CI: 5.60–5.90) in 1999 to 11.15 (95% CI: 10.98–11.32) in 2025 (AAPC: 2.07; p = 0.002). A sharp transient increase occurred in 2020, attributable to pandemic-related factors including disproportionate COVID-19 mortality among older adults with neurodegenerative conditions, care disruptions, and changes in death-certificate coding practices. Following this pandemic-era peak, AAMRs declined significantly through 2025 and should be interpreted cautiously given provisional data. Males (AAPC: 2.14), non-Hispanic White individuals (AAPC: 2.29), the Midwest region (AAPC: 2.65), and non-metropolitan areas carried the highest mortality burden. Mortality was greatest among adults aged ≥85 years. Conclusion: Population-level death rates involving co-recorded Parkinson’s disease and dementia demonstrated significant temporal changes over the study period, with marked demographic and geographic disparities. These findings reflect death-certificate surveillance data and cannot establish clinical co-occurrence, causal relationships, or individual disease risk. Full article

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21 pages, 1382 KB

Open AccessReview

Precision Cardiogenomics in Athletes

by Pari Goyal, Alwaleed Aljohar, Reid A. Mitchell, Nathaniel Moulson, James McKinney, Saul Isserow and Zachary Laksman

Int. J. Mol. Sci. 2026, 27(12), 5250; https://doi.org/10.3390/ijms27125250 (registering DOI) - 10 Jun 2026

Abstract

Sudden cardiac death (SCD) in athletes often represents the first manifestation of an underlying inherited cardiovascular disorder exposed by adrenergic stress, altered calcium cycling, mechanical loading, and metabolic demand during intense exercise. This review focuses on the molecular architecture that links genotype to [...] Read more.

Sudden cardiac death (SCD) in athletes often represents the first manifestation of an underlying inherited cardiovascular disorder exposed by adrenergic stress, altered calcium cycling, mechanical loading, and metabolic demand during intense exercise. This review focuses on the molecular architecture that links genotype to arrhythmogenic phenotype in athletes, emphasizing sarcomeric force generation and energetic inefficiency in hypertrophic cardiomyopathy, desmosomal failure and Hippo/Wnt/transforming growth factor-beta (TGF-β) signaling in arrhythmogenic cardiomyopathy, and ion-channel and calcium/calmodulin-dependent protein kinase II (CaMKII)calcium handling abnormalities in inherited channelopathies. This review further examines how exercise-induced physiological remodeling intersects with these pathways through insulin-like growth factor-1 (IGF-1)/phosphoinositide 3-kinase (PI3K)/ protein kinase B (AKT) signaling, mitochondrial biogenesis, oxidative stress, inflammatory signaling, and epigenetic regulation. Attention is given to the molecular basis of genotype-positive/phenotype-negative states, variable penetrance, and exercise-mediated disease expression. Finally, the integration of molecular biology with genomic data, polygenic risk, and emerging digital phenotyping is discussed to refine mechanism-based risk stratification and identify future therapeutic targets for prevention of SCD in athletes. Full article

(This article belongs to the Special Issue Exercise in Health and Diseases: From the Molecular Perspectives)

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20 pages, 9634 KB

Open AccessArticle

Heat Transfer Modulation of Micro-Textured Interfaces: A Multi-Scale Topology Optimization and Numerical Simulation

by Qing Rao, Benben Guo, Jiafu Ruan and Xigui Wang

Micromachines 2026, 17(6), 712; https://doi.org/10.3390/mi17060712 (registering DOI) - 10 Jun 2026

Abstract

To address the critical challenge of excessive junction temperature caused by ultra-high heat flux densities (>100 W/cm²) in deep-sea LED Fish-Attracting Lamp (FAL) arrays, this study proposes a hybrid thermal management scheme integrating interfacial micro-texturing, chimney-effect convection, and heat pipe phase-change [...] Read more.

To address the critical challenge of excessive junction temperature caused by ultra-high heat flux densities (>100 W/cm²) in deep-sea LED Fish-Attracting Lamp (FAL) arrays, this study proposes a hybrid thermal management scheme integrating interfacial micro-texturing, chimney-effect convection, and heat pipe phase-change heat transfer, achieving the unification of passive high-efficiency heat dissipation and pressure-resistant sealing. The FAL housing structure is reconfigured using topology optimization to construct chimney-effect enhanced flow channels integrated with heat pipe bundle arrays, thereby establishing efficient heat conduction pathways from the Phenolic Resin Substrate (PRS) to the structural periphery. Micro-Element Texture (MET) arrays are fabricated at the PRS thermal interface to enhance interfacial thermal conductance. Based on multi-physics coupled numerical simulation, a parametric mapping model correlating geometric topology with thermal performance is established through response interface methodology, enabling the parametric optimization of micro-texture configurations. A thermal interface performance testing platform is constructed to validate the accuracy and reliability of the numerical model. Experimental results demonstrate that the integrated heat pipe technology effectively suppresses LED junction temperature rise; moreover, groove-type MET arrays oriented perpendicular to the gravity direction not only significantly increase the effective heat dissipation area but also optimize the dynamic characteristics of natural convection. This proposed solution reduces the maximum operating temperature of deep-sea FALs by 6.70% compared with conventional structures, providing an effective engineering solution for thermal structural design of high-power illumination systems. Full article

(This article belongs to the Section A2: Surfaces and Interfaces)

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37 pages, 2562 KB

Open AccessReview

A Decade of Optical Remote Sensing Applications in Marine Biodiversity and Benthic Habitat Monitoring: A Systematic Review

by Laura Martín-García, Enrique Casas, Pedro A. Hernández-Leal, Andrea Z. Botelho and Manuel Arbelo

Remote Sens. 2026, 18(12), 1917; https://doi.org/10.3390/rs18121917 (registering DOI) - 10 Jun 2026

Abstract

Monitoring biodiversity in coastal and marine ecosystems is essential for supporting conservation strategies, sustaining ecosystem services, and meeting policy commitments at multiple scales, including the European Union’s Habitats Directive, Sustainable Development Goal 14 (SDG 14, Life Below Water), and the Kunming–Montreal Global Biodiversity [...] Read more.

Monitoring biodiversity in coastal and marine ecosystems is essential for supporting conservation strategies, sustaining ecosystem services, and meeting policy commitments at multiple scales, including the European Union’s Habitats Directive, Sustainable Development Goal 14 (SDG 14, Life Below Water), and the Kunming–Montreal Global Biodiversity Framework (GBF). However, many benthic habitats remain insufficiently mapped or monitored due to the spatial, temporal, and logistical limitations of traditional field-based approaches. Optical Remote Sensing (ORS), based on the use of optical sensors to retrieve spectral information from shallow-water environments, has emerged as a powerful tool for mapping and monitoring these ecosystems. This study presents a systematic review aimed at providing a comprehensive synthesis of above-water ORS applications for benthic biodiversity and habitat monitoring over the period 2014–2023. A total of 179 peer-reviewed studies were analyzed to identify temporal trends, geographic patterns, target ecosystems, and methodological workflows. The review considered observation platforms including satellite, airborne, unmanned aerial vehicles (UAVs), and field spectrometry systems, together with key preprocessing procedures required for reliable benthic detection, such as atmospheric correction, water column correction, and sunglint removal, alongside validation using independent measurements. The analysis reveals a rapid expansion of ORS applications, with a strong geographic concentration in tropical and subtropical regions. Studies focusing on specific benthic groups predominantly target coral reefs and seagrass ecosystems, although many adopt integrative benthic habitat classifications that incorporate multiple benthic components at the habitat level. However, significant limitations persist, including inconsistent preprocessing workflows, limited reporting transparency, and the underrepresentation of several ecologically important taxa (e.g., annelids, mollusks, echinoderms). Despite these challenges, ORS has become a cornerstone of large-scale and repeatable coastal monitoring. By analyzing methodological practices, ecological targets, and geographic biases, this review provides a critical foundation for improving the robustness, scalability, and global applicability of ORS in benthic habitat mapping, biodiversity monitoring, and ecosystem-based management. Full article

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40 pages, 3358 KB

Open AccessArticle

Heteroaromatic Pyrazole-Based Carbohydrazones: Structure-Dependent Redox Activity, DNA-Associated Spectroscopic Behavior, and Multifunctional Biological Properties

by Aliye Gediz Erturk and Ertuğrul Yiğit

Molecules 2026, 31(12), 2031; https://doi.org/10.3390/molecules31122031 (registering DOI) - 10 Jun 2026

Abstract

Six novel pyrazole-based carbohydrazone derivatives (3a–3f) bearing structurally diverse heteroaromatic substituents were synthesized and characterized by ATR-FTIR, ¹H NMR, APT-¹³C NMR, and HRMS analyses. Their multifunctional bioactivity was evaluated using antioxidant, photoprotective, CT-DNA-associated spectroscopic response, cytotoxicity, [...] Read more.

Six novel pyrazole-based carbohydrazone derivatives (3a–3f) bearing structurally diverse heteroaromatic substituents were synthesized and characterized by ATR-FTIR, ¹H NMR, APT-¹³C NMR, and HRMS analyses. Their multifunctional bioactivity was evaluated using antioxidant, photoprotective, CT-DNA-associated spectroscopic response, cytotoxicity, and scratch wound closure assays. Antioxidant activity was assessed by DPPH radical scavenging, Fe²⁺ chelation, and ferric thiocyanate (FTC) assays against appropriate reference standards, while photoprotective potential was determined by spectrophotometric SPF analysis using carrot seed oil as a reference. The benzothiazole-containing derivative (3f) showed the strongest DPPH scavenging activity, FTC antioxidant capacity, and photoprotective activity, while also producing one of the most pronounced CT-DNA-associated spectroscopic responses under the experimental conditions employed. In contrast, the benzimidazole derivative (3e) displayed the highest Fe²⁺ chelating activity among the synthesized compounds. In cell-based assays, the imidazole- and thiazole-containing derivatives (3b and 3c) showed the most favorable balance between growth-inhibitory potency and selectivity toward A431 epidermoid carcinoma cells relative to HaCaT keratinocytes. Scratch assay results did not support direct anti-migratory activity under the tested conditions but indicated compound-dependent modulation of wound-closure-associated cellular responses. Overall, these findings demonstrate that heteroaromatic substitution strongly modulates redox behavior, CT-DNA-associated spectroscopic behavior, photophysical properties, and cytotoxic selectivity in pyrazole-based carbohydrazones, identifying this scaffold as a structurally tunable platform for further bioactivity optimization. Full article

(This article belongs to the Section Medicinal Chemistry)

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18 pages, 1282 KB

Open AccessArticle

Scheduling Group Care in Routine Perinatal Care: Identifying Implementation Modifications Across Belgium, Kosovo, and the UK

by Astrid Van Damme, Florence Talrich, Deborah L. Billings, Christine McCourt, Ashley Gresh, Crystal L. Patil, Matty Crone, Marlies Rijnders, Ilir Hoxha, Sharon Schindler Rising and Katrien Beeckman

Healthcare 2026, 14(12), 1642; https://doi.org/10.3390/healthcare14121642 (registering DOI) - 10 Jun 2026

Abstract

Background: Group Care (GC) is an antenatal/postnatal care model comprised of a stable group of pregnant people or parent–child dyads receiving care in two-hour group sessions that combine clinical care with interactive discussion and learning. Integrating GC into healthcare systems organised for [...] Read more.

Background: Group Care (GC) is an antenatal/postnatal care model comprised of a stable group of pregnant people or parent–child dyads receiving care in two-hour group sessions that combine clinical care with interactive discussion and learning. Integrating GC into healthcare systems organised for individual care poses challenges at both site and system levels. This study identified scheduling-related modifications across contexts to understand modification processes. Methods: We used an explanatory sequential design with mixed qualitative methods across seven GC implementation sites in Belgium, Kosovo, and the United Kingdom. A qualitative survey based on the Framework for Reporting Adaptations and Modifications to Evidence-based interventions (FRAME) was completed at each site by multiple stakeholders. Subsequently, in-depth interviews were conducted to further explore modification processes and examine whether changes were sustained or discontinued up to three years post-implementation initiation. Results: Two modifications were identified across countries: (1) combining GC sessions with individual consultations, and (2) integrating GC into digital booking and medical record systems. Guided by FRAME, we identified similarities and differences in the goals, drivers, and impact of these modifications. The dominant one-to-one antenatal care model strongly influenced modifications, making it more difficult to implement GC as a stand-alone model in obstetrician-led systems (Belgium and Kosovo) compared to a midwifery-led system (UK). In both contexts, the dominant model negatively influenced the perceived value of GC, with GC sessions viewed only as education and individual consultations seen as the actual care. Integration in the booking system appeared essential for payment and scheduling arrangements. Conclusions: Integrating GC scheduling into existing care pathways is challenging in systems where one-to-one care is the predominant model. Sustainable integration of GC requires early coordination and shared ownership across areas, including clinical, administrative, and IT. Full article

(This article belongs to the Special Issue Interdisciplinary Perspectives in Maternal Health: Integrating Theoretical Frameworks and Practical Applications)

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18 pages, 5859 KB

Open AccessArticle

Biocomposites of Alginate, Calcium Polyphosphate, and Silver Nanostructures: Antibacterial Systems for Bone Regeneration Applications

by Joalen Pereira do Monte, Rafael B. G. Pessoa, Adriana Fontes, Beate S. Santos, Giovannia A. L. Pereira and Goreti Pereira

Pharmaceuticals 2026, 19(6), 917; https://doi.org/10.3390/ph19060917 (registering DOI) - 10 Jun 2026

Abstract

Background/Objectives: Bone infection remains a severe clinical challenge characterized by recurrence, antimicrobial resistance, and high morbidity, driving the search for new therapeutic strategies. Despite advances in developing biomaterials with suitable biocompatibility, biodegradability, and structural properties, the lack of effective antibacterial activity continues [...] Read more.

Background/Objectives: Bone infection remains a severe clinical challenge characterized by recurrence, antimicrobial resistance, and high morbidity, driving the search for new therapeutic strategies. Despite advances in developing biomaterials with suitable biocompatibility, biodegradability, and structural properties, the lack of effective antibacterial activity continues to significantly limit the treatment of bone defects. To overcome this issue, we investigated the incorporation of silver-based nanostructures into calcium polyphosphate/alginate (CPP/Alg) matrices as an antibacterial reinforcement strategy for bone-related applications. Methods: Silver nanoparticles (AgNPs) were synthesized in aqueous medium via NaBH₄-mediated chemical reduction, using either alginate (Alg) or sodium polyphosphate (PP) as stabilizing agents, enabling a comparative evaluation of biocompatible polymer- and polyphosphate-stabilized systems. Subsequently, AgNPs were incorporated into calcium polyphosphate/alginate (CPP/Alg) matrices to obtain Ag-containing composites. Results: The AgNPs exhibited spherical morphology, Zeta potential values ranging from −38.7 ± 0.2 to −23 ± 0.3 mV, and hydrodynamic diameters between 25.2 ± 0.2 and 143 ± 5 nm. Structural characterization of the biocomposites by X-ray diffraction confirmed hydroxyapatite as the major crystalline phase, while Raman spectroscopy revealed vibrational bands corresponding to both the inorganic and polymeric components. SEM revealed a dense, rough surface, and ICP-OES analysis confirmed the presence of Ag. Antibacterial activity assays demonstrated effective growth inhibition of Staphylococcus aureus and Staphylococcus epidermidis, with inhibition halos growing with increasing composite dosage. Notably, antibacterial activity was achieved at relatively low Ag contents, underscoring the efficiency of these biocomposites. Conclusions: These findings confirm the effective incorporation of AgNPs into the CPP/Alg matrix and support the classification of composites as promising antibacterial biomaterials for bone regeneration applications. Full article

(This article belongs to the Special Issue Therapeutic Potential of Silver Nanoparticles (AgNPs), 2nd Edition)

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19 pages, 1775 KB

Open AccessArticle

A Correlation Analysis-Based Hierarchical Identification Strategy for Hammerstein Models

by Qi Dong, Haolong Jiang, Qinyao Liu and Yuan Gao

Algorithms 2026, 19(6), 472; https://doi.org/10.3390/a19060472 (registering DOI) - 10 Jun 2026

Abstract

Reliable mathematical models are essential for high-performance analysis and optimization of complex power and energy systems. However, inherent nonlinearities pose significant challenges to accurate model identification. The Hammerstein model, a typical block oriented nonlinear system, consists of a static nonlinear block followed by [...] Read more.

Reliable mathematical models are essential for high-performance analysis and optimization of complex power and energy systems. However, inherent nonlinearities pose significant challenges to accurate model identification. The Hammerstein model, a typical block oriented nonlinear system, consists of a static nonlinear block followed by a linear dynamic block. This paper investigates the data-driven modeling method for the Hammerstein model and proposes a hierarchical identification strategy that integrates the correlation analysis with the Levenberg–Marquardt algorithm. Unlike traditional methods, this hierarchical algorithm strategy decouples the linear and nonlinear modules to avoid parameter coupling and reduces computational complexity. Simulations on a solid oxide fuel cell system and a real-world wind power system confirm the effectiveness and feasibility of the proposed method. The results demonstrate that the hierarchical identification strategy achieves accurate parameter estimation with satisfactory convergence performance. Full article

(This article belongs to the Special Issue Computational Modeling and Intelligent Simulation of Next-Generation Energy Systems)

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16 pages, 1071 KB

Open AccessArticle

The Use and Utility of Adjuvant Checkpoint Inhibitors in Elderly Patients with Melanoma: A Single Institution Experience

by Maira A. Bhatty, Natalie N. Chakraborty, Kevin G. Zablonski, Jarred M. Boone, Hailey Seibert, Trisha Lal, Hanna Kakish, Madelyn N. Stevens, Iris Y. Sheng, Andrew N. Hanna, Ankit Mangla, Richard S. Hoehn and Luke D. Rothermel

Cancers 2026, 18(12), 1893; https://doi.org/10.3390/cancers18121893 (registering DOI) - 10 Jun 2026

Abstract

Background: Elderly patients have low utilization of adjuvant ICIs, although they achieve similar RFS benefits as younger patients. It remains unclear why elderly patients use adjuvant ICIs less frequently and whether toxicity impacts treatment utilization. Methods: Adult patients with stage III [...] Read more.

Background: Elderly patients have low utilization of adjuvant ICIs, although they achieve similar RFS benefits as younger patients. It remains unclear why elderly patients use adjuvant ICIs less frequently and whether toxicity impacts treatment utilization. Methods: Adult patients with stage III melanoma treated from 2017 to 2023 at a single academic cancer center were retrospectively identified. Multivariable logistic regressions evaluated the association of age with receipt of adjuvant ICIs and toxicity. RFS was assessed using Kaplan–Meier and multivariable Cox proportional hazards regression. Results: Among 240 patients, those aged ≥ 75 years were less likely to receive adjuvant ICI than those aged 18–74 years (aOR: 0.30; 95% CI: 0.11–0.80). Among 53 (22.1%) patients who did not receive adjuvant ICI, 58% declined treatment, 15% were not offered adjuvant ICI by provider, 9% had a comorbid autoimmunity, and 6% had another comorbidity. A total of 12% of patients aged 75–80 years old declined treatment versus 33% of those aged 80–90 years old. Older age was not associated with toxicity, treatment interruption, or discontinuation from adjuvant ICI. Adjuvant ICI was associated with low recurrence (aHR: 0.76; 95% CI: 0.63–0.92), whereas age ≥ 75 years was associated with higher recurrence risk (aHR: 1.79; 95% CI: 1.04–3.10) and low overall survival (aHR: 3.07; 95% CI: 1.43–6.57) compared to patients aged 18–74 years. Conclusions: Older patients with stage III melanoma were less likely to receive adjuvant ICIs, despite similar toxicity, treatment interruption, and discontinuation rates across age groups. Because adjuvant therapy is associated with lower recurrence risk, efforts to better understand and address age-related differences in treatment use are warranted. Full article

(This article belongs to the Collection Emerging Therapeutics in Advanced Melanoma)

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27 pages, 3791 KB

Open AccessArticle

A Dual-Factor Defrosting Model for Air-Source Heat Pumps Considering Ambient Temperature and Compressor Frequency

by Xuyan Xu, Tao Zhang, Dongming Li, Wanchun Sun, Zhijiang Wu and Yansheng Xu

Energies 2026, 19(12), 2787; https://doi.org/10.3390/en19122787 (registering DOI) - 10 Jun 2026

Abstract

This study presents a novel investigation into the coupled effects of ambient temperature and compressor frequency on frosting behavior and thermal performance of inverter-driven air-source heat pumps (ASHPs) under low-temperature, high-humidity conditions. Unlike previous studies that focused on single environmental parameters, this work [...] Read more.

This study presents a novel investigation into the coupled effects of ambient temperature and compressor frequency on frosting behavior and thermal performance of inverter-driven air-source heat pumps (ASHPs) under low-temperature, high-humidity conditions. Unlike previous studies that focused on single environmental parameters, this work systematically explores temperature–frequency coupling. Experiments were conducted on a 3-HP DC inverter low-ambient-temperature ASHP unit using a multi-climate simulated enthalpy difference test bench. Single-factor analysis shows that frosting is most severe at 0 °C, where the frost growth rate peaks. Regarding compressor frequency, the coefficient of performance (COP) initially increases and then decreases with frequency. The maximum COP occurs near 45 Hz, representing the optimal energy efficiency balance in this experimental system. Sensitivity analysis demonstrates that relative humidity contributes less than 5% to performance degradation at the critical 10% COP reduction point. Thus, ambient temperature and compressor frequency are the core determinants of defrosting timing. A dual-factor prediction model for the critical defrosting air-to-coil temperature difference (∆T) is developed using temperature (t) and frequency (f) as independent variables. Validation confirms that the model maintains prediction error within 10% under both single-factor and multi-factor coupling conditions. Collectively, this research quantifies the coupled effects of ambient temperature and compressor frequency on frosting performance and provides a novel theoretical framework for precise defrosting control in inverter ASHPs based on performance attenuation. Full article

(This article belongs to the Special Issue Heat Transfer Performance and Influencing Factors of Waste Management)

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26 pages, 2151 KB

Open AccessSystematic Review

Microfluidics for Drug Encapsulation and Controlled Release: A Systematic Review of Recent Advances

by Leonardo D. Binda, Mario A. Cachile, María V. D’Angelo and María C. Martínez Ceron

J. Pharm. BioTech Ind. 2026, 3(2), 13; https://doi.org/10.3390/jpbi3020013 (registering DOI) - 10 Jun 2026

Abstract

Background: Conventional drug delivery systems often lead to fluctuating plasma concentrations (“Peak and Trough” phenomenon), causing toxicity or inefficacy. Microfluidics has emerged as a revolutionary tool to overcome, among other applications, the limitations of conventional bulk encapsulation methods, such as polydispersity and poor [...] Read more.

Background: Conventional drug delivery systems often lead to fluctuating plasma concentrations (“Peak and Trough” phenomenon), causing toxicity or inefficacy. Microfluidics has emerged as a revolutionary tool to overcome, among other applications, the limitations of conventional bulk encapsulation methods, such as polydispersity and poor reproducibility. Methods: A systematic review of the literature published between 2020 and 2025 was conducted to evaluate the application of microfluidics in the synthesis of advanced nanomedicines. The review focused on Lipid Nanoparticles (LNPs), Polymeric Nanoparticles (PNPs), and Hydrogel Microspheres. Results: Microfluidics enables the production of monodisperse particles with precise control over geometry and drug loading stoichiometry. Key therapeutic applications include oncology (passive and active targeting), gene therapy (mRNA vaccines), and regenerative medicine (diabetic wound healing). Conclusions: While microfluidics offers superior quality control compared to bulk methods, industrial scalability remains the primary challenge, currently addressed through parallelization and continuous flow strategies. Full article

(This article belongs to the Special Issue In Honor of Prof. Dr. Osvaldo Cascone: From His Biotechnology Lessons to Industrial Application)

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17 pages, 2466 KB

Open AccessArticle

Rapid Culture-Independent Detection of Fish Pathogens Using Oxford Nanopore Technologies: Case-Based Insights Across Multiple Species and Tissues

by Konrad Wojnarowski, Paulina Cholewińska, Dongqing Zhao, Yoshikazu Hasegawa, Daniela Denk and Dušan Palić

Pathogens 2026, 15(6), 622; https://doi.org/10.3390/pathogens15060622 (registering DOI) - 10 Jun 2026

Abstract

Rapid and accurate diagnosis of infectious diseases in aquaculture is essential for preventing major economic and ecological losses. Traditional culture-based methods focus on isolation of individual pathogens, and often are burdened with extended processing times, particularly during investigations of polymicrobial infections. Application of [...] Read more.

Rapid and accurate diagnosis of infectious diseases in aquaculture is essential for preventing major economic and ecological losses. Traditional culture-based methods focus on isolation of individual pathogens, and often are burdened with extended processing times, particularly during investigations of polymicrobial infections. Application of Oxford Nanopore Technologies (ONT) sequencing offers a rapid, culture-independent workflow for the identification of bacterial and fungal pathogens directly from fish tissues. Swab and organ samples from four cases (1: Salmo spp.; 2: Cyprinus carpio; 3: Salvelinus fontinalis; 4: Heniochus acuminatus) were analyzed using ONT long-read sequencing for metagenomic screening and bioinformatic classification. The results revealed case-, species-, and tissue-specific microbial profiles, with external tissues showing higher microbial diversity and internal organs enriched in pathogenic taxa. Dominant pathogens included Streptococcus iniae, Aeromonas hydrophila, Pseudomonas spp., and Saprolegnia parasitica, alongside opportunistic zoonotic bacteria such as Escherichia coli and Acinetobacter baumannii. We demonstrate the potential for diagnostic application of ONT sequencing in investigations and detection of multi-pathogen infections, including assessments of microbial community structure changes during disease outbreaks in aquatic species. The presented workflow enables rapid, cost-effective, and comprehensive pathogen profiling, supporting early disease surveillance and improved management in aquatic veterinary practice. Full article

(This article belongs to the Special Issue Recent Advances in the Diagnosis of Fish Pathogens)

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32 pages, 1944 KB

Open AccessArticle

A Layered Governance Coverage Model for Decentralized Autonomous Organizations: Formalization, Empirical Analysis, and Implications for Blockchain-Based IoT/AI Systems

by Abeer S. Al-Humaimeedy and Rand Alkharashi

Information 2026, 17(6), 577; https://doi.org/10.3390/info17060577 (registering DOI) - 10 Jun 2026

Abstract

Decentralized Autonomous Organizations (DAOs) enable blockchain-based collective governance, yet existing studies often evaluate DAO governance through isolated mechanisms, particularly voting systems. This narrow view does not sufficiently explain recurring problems such as governance capture, weak accountability, inadequate safeguards, and inefficient resource allocation. This [...] Read more.

Decentralized Autonomous Organizations (DAOs) enable blockchain-based collective governance, yet existing studies often evaluate DAO governance through isolated mechanisms, particularly voting systems. This narrow view does not sufficiently explain recurring problems such as governance capture, weak accountability, inadequate safeguards, and inefficient resource allocation. This paper proposes a Layered Governance Coverage Model that conceptualizes DAO governance as a system of seven interdependent institutional functions spanning participation, agenda formation, collective choice, safeguards, execution, incentives, and meta-governance. The model uses a four-level strength scale to assess not only whether governance functions are present, but also how strongly they are institutionalized. It is empirically applied to thirty-seven active DAOs through evidence-based coding of publicly available governance artifacts. The results show that governance breadth does not necessarily imply governance maturity: collective choice and execution mechanisms are more developed than accountability, safeguards, and meta-governance. Beyond DAO-native settings, the paper positions governance maturity as a trust and resilience regime for blockchain-based IoT and AI infrastructures, where governance affects security, reliability, data integrity, and risk oversight. The paper discusses AI-enabled governance analytics as a support mechanism for monitoring governance activity, detecting anomalies, and improving governance observability. The proposed framework contributes a structured approach for evaluating and designing resilient governance architectures in DAOs and blockchain-based IoT/AI systems. Full article

(This article belongs to the Special Issue IoT, AI, and Blockchain: Applications, Security, and Perspectives)

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3 pages, 155 KB

Open AccessEditorial

Influence of Irrigation and Water Use on Agronomic Traits of Crops—2nd Edition

by Ruoshui Wang, Qibiao Han, Yuguo Han and Tibin Zhang

Agronomy 2026, 16(12), 1136; https://doi.org/10.3390/agronomy16121136 (registering DOI) - 10 Jun 2026

Abstract

The escalating challenge of global water scarcity continues to threaten agricultural sustainability, making the optimization of water management practices more critical than ever before [...] Full article

(This article belongs to the Special Issue Influence of Irrigation and Water Use on Agronomic Traits of Crops—2nd Edition)

24 pages, 61837 KB

Open AccessArticle

The Abuduo Fault on the Eastern Margin of the Tibetan Plateau: Geometric Structure Interpretation and Slip Rate Estimation

by Cheng Liao, Mingjian Liang, Weiwei Wu, Cong Chen, Hong Zuo, Fuxiu He, Ailin Chen, Yunxi Dong and Shuhuai Liu

Remote Sens. 2026, 18(12), 1916; https://doi.org/10.3390/rs18121916 (registering DOI) - 10 Jun 2026

Abstract

The Abuduo Fault is a Holocene left-lateral strike-slip fault located on the eastern margin of the Tibetan Plateau, potentially connecting eastward with the Garzê–Yushu Fault. Due to its high-altitude setting, this fault remains poorly studied, and knowledge of its detailed surface geometry and [...] Read more.

The Abuduo Fault is a Holocene left-lateral strike-slip fault located on the eastern margin of the Tibetan Plateau, potentially connecting eastward with the Garzê–Yushu Fault. Due to its high-altitude setting, this fault remains poorly studied, and knowledge of its detailed surface geometry and slip rate is still insufficient. Using GF-7 and other multi-source remote sensing data, field surveys, semi-automatic offset extraction software, and radiocarbon (¹⁴C) dating, we determined the fault’s fine surface geometry, offsets, and slip rate. The results show that the fault can be divided into western, central, and eastern segments based on geometric discontinuities. The central segment consists of four right-stepping en echelon faults. The western and central segments are separated by a left-stepping compressional ridge with a step-over width of ~3.1 km, while the central and eastern segments are separated by a right-stepping pull-apart basin with a step-over width of ~9.4 km. Offsets generally increase from west to east. The western and central segments may exhibit stronger Late Quaternary activity, but this understanding remains to be further validated. Based on offset measurement and the dating of a typical offset gully, the Holocene slip rate of the western segment is estimated at 2.5–2.8 mm/yr. Full article

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15 pages, 4127 KB

Open AccessArticle

Effects of Non-Thermal Electrons and Non-Extensive Positrons on Dust-Ion-Acoustic Solitary Waves in an Unmagnetized Plasma

by Satyendra Nath Barman and Kingkar Talukdar

Plasma 2026, 9(2), 21; https://doi.org/10.3390/plasma9020021 (registering DOI) - 10 Jun 2026

Abstract

In this study, we investigated the existence and properties of solitons in an unmagnetized plasma composed of positive ions, negative ions, negatively charged dust grains, non-thermal electrons and non-extensive positrons. We have conducted our study on this complex plasma model because it moves [...] Read more.

In this study, we investigated the existence and properties of solitons in an unmagnetized plasma composed of positive ions, negative ions, negatively charged dust grains, non-thermal electrons and non-extensive positrons. We have conducted our study on this complex plasma model because it moves away from simplistic and idealized plasma models. Also, a study of solitons has not previously been conducted on this complex plasma model. Through the Sagdeev potential method, we have derived the energy integral and investigated the variation in the Sagdeev potential for different values of the parameters that are involved in our plasma model. We have found that the non-thermal parameter (β) and the non-extensive parameter (q) significantly influence the features of the solitons. The features of the solitons are also found to be influenced by the Mach number (M), the negative-ion-to-positive-ion mass ratio (

Ω

), the positron-to-positive-ion density ratio (δ_p), the electron-to-positron temperature ratio (σ_p), the dust charge density ratio (δ_d) and the negative-ion-to-positive-ion density ratio (δ_). The results from our study can be useful in investigating plasma in astrophysical environments, such as cometary tails and interstellar clouds. Full article

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38 pages, 4424 KB

Open AccessReview

Unique Bioactive Secondary Metabolites of Ferns and Their Enhancement by Abiotic Stress: Medicinal Potential and Future Perspectives

by Kanchan Soneji, Antoni Szumny and Katarzyna Wróblewska

Molecules 2026, 31(12), 2029; https://doi.org/10.3390/molecules31122029 (registering DOI) - 10 Jun 2026

Abstract

Ferns represent an evolutionarily distinct group of vascular plants and constitute an underexplored source of structurally diverse secondary metabolites with potential medicinal value. Several fern-derived compounds, including sesquiterpenes, triterpenes, flavonoids, phloroglucinol derivatives, lactones, and glycosides, have been associated with antibacterial, antidiabetic, analgesic, anticancer, [...] Read more.

Ferns represent an evolutionarily distinct group of vascular plants and constitute an underexplored source of structurally diverse secondary metabolites with potential medicinal value. Several fern-derived compounds, including sesquiterpenes, triterpenes, flavonoids, phloroglucinol derivatives, lactones, and glycosides, have been associated with antibacterial, antidiabetic, analgesic, anticancer, hepatoprotective, neuroprotective, and other biological activities. However, despite their biochemical uniqueness and long-standing use in traditional medicine, ferns remain less extensively investigated than angiosperms as sources of bioactive compounds. In addition to their natural phytochemical diversity, the production of secondary metabolites in ferns may be influenced by abiotic stressors, such as light quality and intensity, temperature, salinity, drought, water availability, and mineral nutrition. Available studies indicate that selected abiotic stress conditions can enhance the accumulation of phenolic acids, flavonoids, polyphenols, carotenoids, and related compounds in several fern families, including Aspleniaceae, Athyriaceae, Dryopteridaceae, Onocleaceae, and Thelypteridaceae. Nevertheless, information on stress-induced modulation of metabolites that are unique or highly characteristic of ferns, particularly terpenes, terpene glycosides, and specific flavonoid derivatives, remains limited. This review summarizes the current knowledge on unique secondary metabolites in ferns, their reported medicinal properties, and the potential use of abiotic stress as an elicitation strategy to enhance their production. Overall, the review highlights ferns as promising but still insufficiently explored reservoirs of bioactive metabolites and identifies key directions for future phytochemical, pharmacological, and cultivation-based research. Full article

(This article belongs to the Special Issue Nutritional and Bioactive Components of Edible Parts of Medicinal Plants)

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16 pages, 9960 KB

Open AccessArticle

Preparation of Unburned Lightweight Aggregates via Synergistic Utilization of Red Mud and Multi-Source Solid Wastes and Its Performance Investigation

by Jixiang Cai, Lianghuan Wei, Xianghao Zha, Rubin Han and Hui Luo

Materials 2026, 19(12), 2490; https://doi.org/10.3390/ma19122490 (registering DOI) - 10 Jun 2026

Abstract

This study aims to explore the preparation process and properties of unburned lightweight aggregate using red mud synergistically with fly ash, granulated blast-furnace slag, and other multi-source solid wastes. Curing regimes and alkali-activated systems were controlled. Their effects on physical properties and environmental [...] Read more.

This study aims to explore the preparation process and properties of unburned lightweight aggregate using red mud synergistically with fly ash, granulated blast-furnace slag, and other multi-source solid wastes. Curing regimes and alkali-activated systems were controlled. Their effects on physical properties and environmental safety of lightweight aggregate were systematically evaluated. Results show that curing temperature and alkali activator exert significant synergistic effects on physical properties of lightweight aggregates. Steam curing performs better than standard curing. Performance improves with increasing steam temperature. Sodium silicate solution with a modulus of 1.0 is determined as the optimal activator. Under 90 °C steam curing, Sample D2 achieves the best overall performance. Its cylinder compressive strength reaches 6.92 MPa. 1 h water absorption is 14.8%. Softening coefficient is 0.93. Porosity is as low as 31.07%. Microscopic analysis reveals that higher curing temperature significantly accelerates the hydration reaction of the RMLWA system. It promotes the formation of abundant cementitious products such as C-S-H gel. These products fully fill internal pores and microcracks of the aggregate. A dense three-dimensional network skeleton structure is finally formed. For environmental safety, heavy metal leaching concentrations of steam-cured samples are generally lower than those of standard-cured samples. This study realizes high-value resource utilization of industrial solid wastes. It also provides a new technical route for the development of green building lightweight aggregate. Full article

(This article belongs to the Special Issue Advanced Polymer Composites for Sustainable Technologies: Synthesis, Characterization, and Performance)

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23 pages, 4009 KB

Open AccessArticle

Multi-Objective Design Optimization of Serpentine Liquid-Cooled Plates Based on CFD and Hybrid Surrogate Modeling

by Shuo Ma, Qingtong Liu, Wenting Liu, Mantuo Li and Xinyu Hong

Processes 2026, 14(12), 1882; https://doi.org/10.3390/pr14121882 (registering DOI) - 10 Jun 2026

Abstract

This study proposes a multi-objective optimization strategy for the structural design of liquid-cooled channels in battery systems, aiming to identify liquid-cooled plate design schemes with better cooling performance and acceptable flow resistance. Optimal Latin hypercube sampling (OLHS) was combined with computational fluid dynamics [...] Read more.

This study proposes a multi-objective optimization strategy for the structural design of liquid-cooled channels in battery systems, aiming to identify liquid-cooled plate design schemes with better cooling performance and acceptable flow resistance. Optimal Latin hypercube sampling (OLHS) was combined with computational fluid dynamics (CFD) simulations to construct a CFD-generated dataset that includes the maximum temperature and system pressure drop. Then, modeFRONTIER was employed to integrate surrogate-model training, rapid prediction, and non-dominated sorting genetic algorithm II (NSGA-II) optimization, thereby obtaining the Pareto optimal set. The technique for order preference by similarity to ideal solution (TOPSIS) decision method was further introduced to determine the final optimal design. Results indicate that the optimized liquid-cooling system exhibits outstanding comprehensive performance in terms of balancing heat dissipation and flow resistance at a 5 C discharge rate. Remarkably, sensitivity analysis shows that inlet velocity is the dominant factor affecting the maximum battery temperature, with a correlation coefficient of −0.789. The maximum temperature of the battery module is effectively limited to 30.07 °C, while the flow pressure drop is only 799.58 Pa, achieving an excellent balance between heat dissipation efficiency and energy consumption. Full article

(This article belongs to the Section Process Control, Modeling and Optimization)

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11 pages, 232 KB

Open AccessArticle

Eltrombopag for Chemotherapy-Induced Thrombocytopenia: A Multicenter Retrospective Real-World Study

by Mehmet Baysal, Fatos Dilan Köseoğlu, Sevil Sadri, Ünal Ataş, Ufuk Demirci, Rafiye Çiftçiler, Seval Akpınar and Elif Gülsüm Ümit

Hematol. Rep. 2026, 18(3), 39; https://doi.org/10.3390/hematolrep18030039 (registering DOI) - 10 Jun 2026

Abstract

Introduction: Chemotherapy-induced thrombocytopenia (CIT) is a common dose-limiting toxicity that disrupts on-time, full-dose chemotherapy, yet no pharmacologic therapy is formally approved. Growing evidence from randomized and late-phase studies with thrombopoietin receptor agonists (TPO-RAs) has renewed interest in targeted supportive care. We evaluated the [...] Read more.

Introduction: Chemotherapy-induced thrombocytopenia (CIT) is a common dose-limiting toxicity that disrupts on-time, full-dose chemotherapy, yet no pharmacologic therapy is formally approved. Growing evidence from randomized and late-phase studies with thrombopoietin receptor agonists (TPO-RAs) has renewed interest in targeted supportive care. We evaluated the effectiveness and safety of eltrombopag for CIT in routine clinical practice. Methods: We conducted a small, retrospective, single-arm multicenter cohort study of 31 adults with solid tumors (74.2% stage IV). Given the descriptive, hypothesis-generating nature of this study, no causal inference regarding efficacy can be drawn. Platelet counts and chemotherapy continuity were tracked from baseline through week 12 after eltrombopag initiation. Bleeding, thrombosis, and laboratory safety signals were recorded. Results: The median platelet count increased from 33 × 10⁹/L at baseline to 71 × 10⁹/L at week 1 and 99.5 × 10⁹/L by week 12. Overall, 18/31 patients (58.1%) resumed chemotherapy within 3 weeks, and 15/31 (48.4%) completed planned regimens by week 6. Adverse events were limited to mild, transient elevations in transaminases (n = 3); no major bleeding or thrombotic events occurred. Conclusions: In this real-world multicenter cohort, eltrombopag was associated with rapid platelet recovery and improved chemotherapy deliverability with an acceptable safety profile. The retrospective, single-arm design and the hypothesis-generating nature of these findings preclude definitive conclusions regarding causal efficacy. These observational data highlight the need for prospective controlled trials to characterize the clinical role, optimal dosing, and long-term safety of oral TPO-RAs in CIT. Full article

15 pages, 1669 KB

Open AccessArticle

Low-Molecular-Weight Versus Protein Inhibitors for the CXCL8/Glycosaminoglycan Interaction: Biophysical Characterization and Cellular Activity

by Tanja Gerlza, Paula Peinsipp, Birgit Müller, Klaus Thirring and Andreas J. Kungl

Chemistry 2026, 8(6), 80; https://doi.org/10.3390/chemistry8060080 (registering DOI) - 10 Jun 2026

Abstract

CXCL8, a pro-inflammatory chemokine, which can be induced by TNF-α or IL-1, is responsible for the recruitment and activation of neutrophils. Chemokines interact with glycosaminoglycans on endothelial cells and are thus protected from degradation and sequestration, holding them in an optimal position for [...] Read more.

CXCL8, a pro-inflammatory chemokine, which can be induced by TNF-α or IL-1, is responsible for the recruitment and activation of neutrophils. Chemokines interact with glycosaminoglycans on endothelial cells and are thus protected from degradation and sequestration, holding them in an optimal position for recruiting immune cells. Inhibiting the interaction of chemokines with their glycosaminoglycan co-receptors represents an attractive approach for the treatment of chemokine-mediated diseases. Two polyketide-pyrone compounds, PA501 and PA502 were synthesized, which bind to CXCL8 with affinities higher than the natural glycosaminoglycan ligand heparan sulfate, and in a similar range as heparin. Significant structural changes were induced in the chemokine by interacting with the two compounds, as expressed in fluorescence and far-UV CD experiments. In filter binding assays, both compounds were found to displace heparan sulfate efficiently from CXCL8, with PA501 displaying the highest competition efficacy. Using a C-terminally truncated form of the chemokine, CXCL81-58, which lacks the main glycosaminoglycan-binding α-helical domain, the two compounds are suggested to use—to a varying degree—different binding sites on the protein, which have also been proposed for the natural heparan sulfate ligand. In a transmigration assay, PA501 and PA502 exhibited dose-dependent modulation of CXCL8-induced neutrophil mobilization and migration. The compounds PA501 and PA502 may thus be regarded as early novel lead compounds in the quest for anti-inflammatory, chemokine-targeting drugs. Full article

(This article belongs to the Section Medicinal Chemistry)

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31 pages, 5817 KB

Open AccessArticle

A Comparative Study of Day-Ahead Wind Power Forecasting Models for a Single Wind Farm Under Strict Chronological Splitting and Unified Hyperparameter Tuning Conditions

by Jiacheng Liu, Yihang Lu and Guoping Zou

Energies 2026, 19(12), 2784; https://doi.org/10.3390/en19122784 (registering DOI) - 10 Jun 2026

Abstract

Short-term wind power forecasting is a key enabling technology for wind farm operation optimization, power grid dispatch, and electricity market decision-making. However, existing studies often lack unified standards in data partitioning, input feature construction, and hyperparameter tuning, making fair and reproducible comparisons across [...] Read more.

Short-term wind power forecasting is a key enabling technology for wind farm operation optimization, power grid dispatch, and electricity market decision-making. However, existing studies often lack unified standards in data partitioning, input feature construction, and hyperparameter tuning, making fair and reproducible comparisons across models difficult to achieve. To address this issue, this study focuses on day-ahead wind power forecasting for a single wind farm and establishes a benchmarking framework with strict chronological splitting, a shared feature information set, and a consistent hyperparameter tuning budget. Within this framework, six representative models, namely Ridge, XGBoost, LightGBM, DLinear, Transformer, and PatchTST, are systematically evaluated. A two-level evaluation protocol combining a fixed hold-out split and expanding-window rolling validation is adopted to compare model performance from multiple perspectives, including overall accuracy, sensitivity to hyperparameter tuning, robustness across rolling windows, and performance under typical operating scenarios. The results show that model rankings are not fully consistent between the hold-out evaluation and the rolling-validation setting. Under the fixed hold-out split, LightGBM achieved the lowest NRMSE of 10.2326%, while Transformer obtained the lowest NMAE of 6.9944%. In contrast, under the 8-fold expanding-window rolling validation, Transformer achieved the lowest average NRMSE of 8.1684%, followed by LightGBM with 8.7344%. These results indicate that the best performance on a single test split does not necessarily imply the strongest robustness across multiple time windows. In addition, strong tree-based models remain highly competitive in this single-wind-farm forecasting task, whereas more complex deep temporal models do not always deliver stable advantages. Meanwhile, the performance gains brought by hyperparameter optimization vary substantially across models, suggesting that conclusions drawn from default-parameter comparisons are of limited reliability. These findings demonstrate that systematic benchmarking under strict temporal constraints and fair tuning conditions is essential for clarifying the comparative performance, robustness, and engineering applicability of different model families. The study can therefore provide practical guidance for model selection and deployment in short-term wind power forecasting for single wind farms. Full article

(This article belongs to the Section F5: Artificial Intelligence and Smart Energy)

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30 pages, 2677 KB

Open AccessReview

Advances and Applications of Agricultural Spray Deposition Detection Technologies

by Rui Ye, Jialin Wang, Zhihao Kong and Mingxiong Ou

Appl. Sci. 2026, 16(12), 5848; https://doi.org/10.3390/app16125848 (registering DOI) - 10 Jun 2026

Abstract

Pesticide application efficiency is fundamentally governed by the spatial distribution of droplet deposition. However, characterizing this dynamic process is challenging due to complex environmental and canopy variables. Consequently, conventional offline sampling methods lack the temporal and spatial resolution required for modern intelligent spraying [...] Read more.

Pesticide application efficiency is fundamentally governed by the spatial distribution of droplet deposition. However, characterizing this dynamic process is challenging due to complex environmental and canopy variables. Consequently, conventional offline sampling methods lack the temporal and spatial resolution required for modern intelligent spraying systems. This review systematically examines recent progress in droplet deposition detection. We first revisit traditional methods like water-sensitive paper, addressing high-coverage quantification biases and fluorescence-based techniques. Next, we analyze real-time sensing technologies, including capacitive and optical sensors, highlighting their responsiveness and inherent physical constraints. Furthermore, deep learning approaches for droplet detection, overlap segmentation, and geometric-to-physical regression are discussed. While these methods substantially enhance feature extraction, they often struggle with cross-scenario generalization. Ultimately, current techniques face inherent trade-offs among real-time capability, quantification accuracy, and environmental adaptability, remaining insufficient for complex field conditions. To enable reliable closed-loop control in precision plant protection, future research must prioritize multi-modal sensor fusion, the integration of data-driven and physics-based models, and real-time deployment via edge computing. Full article

(This article belongs to the Section Agricultural Science and Technology)

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