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20 pages, 2017 KB  
Article
Interpretable Machine Learning for Risk Stratification of Hippocampal Atrophy in Alzheimer’s Disease Using CSF Erythrocyte Load and Clinical Data
by Rafail C. Christodoulou, Georgios Vamvouras, Platon S. Papageorgiou, Maria Daniela Sarquis, Vasileia Petrou, Ludwing Rivera, Celimar Morales, Gipsany Rivera, Sokratis G. Papageorgiou and Evros Vassiliou
Biomedicines 2025, 13(11), 2689; https://doi.org/10.3390/biomedicines13112689 (registering DOI) - 31 Oct 2025
Abstract
Background/Objectives: Hippocampal atrophy indicates Alzheimer’s disease (AD) progression and guides follow-up and trial enrichment. Identifying high-risk patients is crucial for optimizing care, but accessible, interpretable machine-learning models (ML) are limited. We developed an explainable ML model using clinical data and CSF erythrocyte load [...] Read more.
Background/Objectives: Hippocampal atrophy indicates Alzheimer’s disease (AD) progression and guides follow-up and trial enrichment. Identifying high-risk patients is crucial for optimizing care, but accessible, interpretable machine-learning models (ML) are limited. We developed an explainable ML model using clinical data and CSF erythrocyte load (CTRED) to classify adults with AD as high- or low-risk based on hippocampal volume decline. Methods: Included ADNI participants with ≥2 MRIs, baseline lumbar puncture, and vital signs within 6 months of MRI (n = 26). The outcome was the Annual Percentage Change (APC) in hippocampal volume, classified as low or high risk. Predictors were standardized; models included SVM, logistic regression, and Ridge Classifier, tuned and tested on a set (n = 6). Thresholds were based on out-of-fold predictions under a 10–90% positive rate. Explainability used PFI and SHAP for per-patient contributions. Results: All models gave identical classifications, but discrimination varied: Ridge AUC = 1.00, logistic = 0.889, and SVM = 0.667. PFI highlighted MAPres and sex as main signals; CTRED contributed, and age had a minor impact. Conclusions: The explainable ML model with clinical data and CTRED can stratify AD patients by hippocampal atrophy risk, aiding follow-up and vascular assessment planning rather than treatment decisions. Validation in larger cohorts is needed. This is the first ML study to use CSF erythrocyte load to predict hippocampal atrophy risk in AD. Full article
19 pages, 1121 KB  
Article
Deficiency in the msbB Gene Reduced the Salmonella Typhimurium Virulence Through Mechanisms Beyond LPS Modification
by Ling Yang, Zhuodong Chai, Jiaqian Qi, Yan Zhang, Yuqi Zhou, Zhenyu Li and Yinan Wei
Microorganisms 2025, 13(11), 2510; https://doi.org/10.3390/microorganisms13112510 (registering DOI) - 31 Oct 2025
Abstract
The Salmonella enterica serovar Typhimurium (ST) mutant lacking the msbB gene (ΔmsbB) has been widely studied as a candidate for attenuated bacterial vectors in therapeutic applications. Deletion of msbB results in LPS with under-acylated lipid A, which lowers endotoxicity while maintaining [...] Read more.
The Salmonella enterica serovar Typhimurium (ST) mutant lacking the msbB gene (ΔmsbB) has been widely studied as a candidate for attenuated bacterial vectors in therapeutic applications. Deletion of msbB results in LPS with under-acylated lipid A, which lowers endotoxicity while maintaining structural integrity. This attenuation has traditionally been attributed to reduced TLR4 activation due to weaker interaction between the modified lipid A and TLR4. In our study, we confirmed that ΔmsbB ST was less lethal than wild-type (WT) ST in a mouse sepsis model. However, this difference persisted even in TLR4- and caspase-11-deficient mice, suggesting that LPS signaling is not the primary determinant of virulence. In vitro, bone marrow–derived macrophages (BMDMs) from TLR4- or caspase-11-deficient mice showed only modest reductions in ST-induced cell death and cytokine production. Importantly, ΔmsbB ST behaved similarly to WT ST in these assays, further indicating that LPS-mediated signaling is not central to the observed attenuation. Our previous studies showed that ST-induced mortality in mice is primarily mediated through NLRC4 activation. Using qPCR and immunoblotting, we found that expression of NLRC4 activators was diminished in the ΔmsbB strain. Additionally, the mutant exhibited increased outer membrane permeability—likely contributing to its heightened antibiotic sensitivity—and reduced motility due to lower flagellin protein levels. In summary, the attenuation of virulence observed in the ΔmsbB strain is not directly due to altered LPS–TLR4 interactions, but rather an indirect effect of diminished expression of virulence factors that activate the NLRC4 inflammasome. Full article
(This article belongs to the Section Molecular Microbiology and Immunology)
19 pages, 378 KB  
Article
Patterns of Social Network Site Use Among University Students: A Latent Profile Analysis of Academic and Psychosocial Outcomes
by Nafsika Antoniadou
Adolescents 2025, 5(4), 64; https://doi.org/10.3390/adolescents5040064 (registering DOI) - 31 Oct 2025
Abstract
Social Networking Sites (SNSs) play a central role in university students’ social and academic lives by facilitating relationship maintenance, emotional support, and the exchange of information, especially for those studying away from home. However, it remains unclear how different patterns of SNS use [...] Read more.
Social Networking Sites (SNSs) play a central role in university students’ social and academic lives by facilitating relationship maintenance, emotional support, and the exchange of information, especially for those studying away from home. However, it remains unclear how different patterns of SNS use influence academic outcomes and psychosocial well-being. Grounded in social capital and self-determination theory, the present study adopted a person-centered approach using Latent Profile Analysis (LPA) to identify distinct profiles of SNS engagement, academic outcomes and well-being. A sample of 275 Greek undergraduate students completed anonymous self-report questionnaires [SNSs use intensity, bonding and bridging social capital, perceived social support via SNSs, fear of missing out (FoMO), phubbing, nomophobia (NoMo), academic outcomes and well-being]. LPA revealed four user profiles: (1) Low Use-Low Support (poorest well-being, moderate academic outcomes); (2) Active and Supported (high well-being and academic outcomes); (3) At-Risk Heavy Users (intermediate academic outcomes and moderate well-being, comparable to Profile 2) and (4) Low Use-High Support (highest well-being, poorest academic outcomes). These findings indicate that SNS engagement may be associated with both benefits and risks for students, depending on how and why they are used. Adopting a person-centered perspective allowed the identification of meaningful usage patterns, providing critical insights for developing targeted interventions to support student adjustment. Full article
20 pages, 2788 KB  
Article
Design of a Pill-Sorting and Pill-Grasping Robot System Based on Machine Vision
by Xuejun Tian, Jiadu Ke, Weiguo Wu and Jian Teng
Future Internet 2025, 17(11), 501; https://doi.org/10.3390/fi17110501 (registering DOI) - 31 Oct 2025
Abstract
We developed a machine vision-based robotic system to address automation challenges in pharmaceutical pill sorting and packaging. The hardware platform integrates a high-resolution industrial camera with an HSR-CR605 robotic arm. Image processing leverages the VisionMaster 4.3.0 platform for color classification and positioning. Coordinate [...] Read more.
We developed a machine vision-based robotic system to address automation challenges in pharmaceutical pill sorting and packaging. The hardware platform integrates a high-resolution industrial camera with an HSR-CR605 robotic arm. Image processing leverages the VisionMaster 4.3.0 platform for color classification and positioning. Coordinate mapping between camera and robot is established through a three-point calibration method, with real-time communication realized via the Modbus/TCP protocol. Experimental validation demonstrates that the system achieves 95% recognition accuracy under conditions of pill overlap ≤ 30% and dynamic illumination of 50–1000 lux, ±0.5 mm picking precision, and a sorting efficiency of108 pills per minute. These results confirm the feasibility of integrating domestic hardware and algorithms, providing an efficient automated solution for the pharmaceutical industry. This work makes three key contributions: (1) demonstrating a cost-effective domestic hardware-software integration achieving 42% cost reduction while maintaining comparable performance to imported alternatives, (2) establishing a systematic validation methodology under industrially-relevant conditions that provides quantitative robustness metrics for pharmaceutical automation, and (3) offering a practical implementation framework validated through multi-scenario experiments that bridges the gap between laboratory research and production-line deployment. Full article
(This article belongs to the Special Issue Advances and Perspectives in Human-Computer Interaction—2nd Edition)
22 pages, 6087 KB  
Article
The Effect of Fe2O3 Modification on the CeO2-MnO2/TiO2 Catalyst for Selective Catalytic Reduction of NO with NH3
by Yuming Yang, Xue Bian, Jiaqi Li, Zhongshuai Jia and Yuting Bai
Molecules 2025, 30(21), 4260; https://doi.org/10.3390/molecules30214260 (registering DOI) - 31 Oct 2025
Abstract
High denitration efficiency and strong adaptability to flue gas temperature fluctuations are the core properties of the NH3-SCR catalyst. In this study, Fe2O3 modification is used as a means to explore the mechanism of adding Fe2O [...] Read more.
High denitration efficiency and strong adaptability to flue gas temperature fluctuations are the core properties of the NH3-SCR catalyst. In this study, Fe2O3 modification is used as a means to explore the mechanism of adding Fe2O3 to broaden the temperature range of the 6CeO2-40MnO2/TiO2 catalyst during the preparation process. The results show that the 6Fe2O3-6CeO2-40MnO2/TiO2 catalyst exhibits excellent denitration performance, with a denitration efficiency higher than 90%. The temperature range is from 129 to 390 °C. N2 selectivity and resistance to SO2 and H2O are good, and the denitration performance is significantly improved. When the Fe2O3 content is 6%, it promotes lattice shrinkage of TiO2, improves its dispersion, refines the grain size, and increases the specific surface area of the catalyst. At the same time, Fe2O3 enhances the chemical adsorption of oxygen on the catalyst surface and increases the proportion of low-cost metal ions, thereby promoting electron transfer between active elements, generating more surface reactive oxygen species, increasing the oxygen vacancy content and adsorption sites for NOx and NH3, and significantly improving the redox performance of the catalyst. This effect is particularly conducive to the formation of strong acid sites on the catalyst surface. The NH3-SCR reaction on the surface of the 6Fe2O3-6CeO2-40MnO2/TiO2 catalyst follows both the L-H and E-R mechanisms, with the L-H mechanism being dominant. Full article
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20 pages, 596 KB  
Article
The Effects of Physical Exercise on the Social Adaptation of Older Adults—With Reference to the Mediating Effect of Aging Identity
by Zhiming Zhang, Jiaxiang Zhang, Cheng Fu and Chengwen Fan
Behav. Sci. 2025, 15(11), 1491; https://doi.org/10.3390/bs15111491 (registering DOI) - 31 Oct 2025
Abstract
Maintaining social adaptation in later life has become a key challenge amid China’s rapidly aging population. Using nationally representative data from the China Longitudinal Aging Social Survey (CLASS 2023), this study examined the relationship between physical exercise and social adaptation among 8913 older [...] Read more.
Maintaining social adaptation in later life has become a key challenge amid China’s rapidly aging population. Using nationally representative data from the China Longitudinal Aging Social Survey (CLASS 2023), this study examined the relationship between physical exercise and social adaptation among 8913 older adults. Ordinary least squares regression and the Karlson–Holm–Breen decomposition method were applied to test both direct and mediating effects. The results showed that physical exercise significantly improved social adaptation (β = 0.452, p < 0.001), while aging identity played a partial mediating role, accounting for approximately 11.0% of the total effect. The association was stronger among those aged 80 and above, with lower education and income, without chronic diseases, and covered by social security. These findings suggest that physical exercise enhances social adaptation not only through physical benefits but also by strengthening psychological resilience and fostering a positive sense of aging, providing valuable evidence for developing inclusive aging policies and targeted exercise interventions. Full article
25 pages, 2380 KB  
Article
RBF Neural Network-Enhanced Adaptive Sliding Mode Control for VSG Systems with Multi-Parameter Optimization
by Jian Sun, Chuangxin Chen and Huakun Wei
Electronics 2025, 14(21), 4309; https://doi.org/10.3390/electronics14214309 (registering DOI) - 31 Oct 2025
Abstract
Virtual synchronous generator (VSG) simulates the dynamic characteristics of synchronous generator, offering significant advantages in flexibly adjusting virtual inertia and damping parameters. However, their dynamic stability is susceptible to constraints such as control parameter design, grid disturbances, and the intermittent nature of distributed [...] Read more.
Virtual synchronous generator (VSG) simulates the dynamic characteristics of synchronous generator, offering significant advantages in flexibly adjusting virtual inertia and damping parameters. However, their dynamic stability is susceptible to constraints such as control parameter design, grid disturbances, and the intermittent nature of distributed power sources. This study addresses the degradation of transient performance in traditional sliding mode control for VSG, caused by insufficient multi-parameter cooperative adaptation. It proposes an adaptive sliding mode control strategy based on radial basis function (RBF) neural networks. Through theoretical analysis of the influence mechanism of virtual inertia and damping coefficient perturbations on system stability, the RBF neural network achieves dynamic parameter decoupling and nonlinear mapping. Combined with an integral-type sliding surface to design a weight-adaptive convergence law, it effectively avoids local optima and ensures global stability. This strategy not only enables multi-parameter cooperative adaptive regulation of frequency fluctuations but also significantly enhances the system’s robustness under parameter perturbations. Simulation results demonstrate that compared to traditional control methods, the proposed strategy exhibits significant advantages in dynamic response speed and overshoot suppression. Full article
17 pages, 2149 KB  
Article
Substituting Chemical by Organic Fertilizer Improves Soil Quality, Regulates the Soil Microbiota and Increases Yields in Camellia oleifera
by Li Wen, Hanfang Luo, Chao Li, Kaikai Cheng, Lihong Shi, Lingling Liu, Ke Wang and Haiming Tang
Microorganisms 2025, 13(11), 2509; https://doi.org/10.3390/microorganisms13112509 (registering DOI) - 31 Oct 2025
Abstract
The partial substitution of chemical fertilizer with organic fertilizer has been regarded as an effective strategy for enhancing crop yield and soil quality. Nevertheless, its effects on soil properties and microbes remain contentious. In this study, we examined the effects of four different [...] Read more.
The partial substitution of chemical fertilizer with organic fertilizer has been regarded as an effective strategy for enhancing crop yield and soil quality. Nevertheless, its effects on soil properties and microbes remain contentious. In this study, we examined the effects of four different fertilization strategies (including without fertilizer (CK), 100% chemical fertilizer (NPK), 30% organic fertilizer + 70% chemical fertilizer (LOM) and 60% organic fertilizer + 40% chemical fertilizer (HOM)) on soil nutrients and microbial communities through metagenomic sequencing in a Camellia oleifera field experiment. Compared to CK and NPK, HOM significantly increased SOC, TN, TP, AK and AN contents. The substitution of organic fertilizer notably increased Camellia oleifera yield, with the highest increase of 93.35% observed in HOM relative to NPK. Soil bacterial and fungal communities responded inconsistently to fertilization patterns. Bacteria predominated as the main soil microorganisms, and higher rates of organic fertilizer substitution facilitated a shift from bacterial to fungal communities. Organic fertilizer substitution significantly increased soil bacteria diversity and fungal richness, particularly in the HOM. Soil bacterial community structure was more sensitive to fertilization regimes than soil fungi. High rates of organic fertilizer substitution substantially suppressed oligotrophic and increased copiotrophic bacterial communities. Mucoromycota emerged as the dominant fungal group, with a considerable increment in HOM soils. SOC and TN were the main factors affecting Camellia oleifera yield and shaping soil bacteria and fungal diversity and composition. This study provided crucial insights into the ecological implications of organic fertilizer application and the potential of managing soil microorganisms for sustainable Camellia oleifera productivity. Full article
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19 pages, 2178 KB  
Article
Biological Characteristics of Dasineura jujubifolia and Its Parasitoid Natural Enemies in Hami Region of Xinjiang (China)
by Kailiang Li, Zhiqiang Ge, Zhenyu Zhang, Yuhao Nie and Hongying Hu
Insects 2025, 16(11), 1118; https://doi.org/10.3390/insects16111118 (registering DOI) - 31 Oct 2025
Abstract
Severe leaf galling by the jujube gall midge Dasineura jujubifolia (Diptera: Cecidomyiidae) compromises photosynthesis and yield in arid-zone jujube orchards, yet Xinjiang-specific evidence to guide biological control has been scarce. Here we provide the first systematic characterization in Xinjiang (Hami, China) of D. [...] Read more.
Severe leaf galling by the jujube gall midge Dasineura jujubifolia (Diptera: Cecidomyiidae) compromises photosynthesis and yield in arid-zone jujube orchards, yet Xinjiang-specific evidence to guide biological control has been scarce. Here we provide the first systematic characterization in Xinjiang (Hami, China) of D. jujubifolia and its parasitoid complex, integrating region-specific field surveys with gall dissection and laboratory assays. We documented five parasitoid wasps, including two species newly recorded in China—Pseudotorymus samsatensis (Hymenoptera: Torymidae) and Baryscapus adalia (Hymenoptera: Eulophidae). In Hami, the host completed 4–5 generations per year with a 19–24-day generation time. Functional roles were partitioned: P. samsatensis (dominant), Systasis parvula (Hymenoptera: Pteromalidae), and B. adalia were larval ectoparasitoids, whereas Aprostocetus sp. (Hymenoptera: Eulophidae) and Synopeas sp. (Hymenoptera: Platygastridae) were endoparasitoids. Time-series data revealed tight temporal synchrony between P. samsatensis and host peaks. Controlled experiments quantified daily emergence rhythms, diet-dependent adult longevity, and sex ratios, providing parameters to inform release timing and conservation in biological control programs. Collectively, these findings establish management-ready baselines for D. jujubifolia and its parasitoids in arid jujube systems and support conservation-oriented, reduced-pesticide integrated pest management (IPM). Full article
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28 pages, 2145 KB  
Article
Port Microgrid Capacity Planning Under Tightening Carbon Constraints: A Bi-Level Cost Optimization Framework
by Junyang Ma and Yin Zhang
Electronics 2025, 14(21), 4307; https://doi.org/10.3390/electronics14214307 (registering DOI) - 31 Oct 2025
Abstract
Under the tightening carbon reduction policies, port microgrids face the challenge of optimizing the installed capacity of multiple power generation types to reduce operating costs and increase renewable energy penetration. We develop a bi-level cost-optimization framework in which the upper level decides long-term [...] Read more.
Under the tightening carbon reduction policies, port microgrids face the challenge of optimizing the installed capacity of multiple power generation types to reduce operating costs and increase renewable energy penetration. We develop a bi-level cost-optimization framework in which the upper level decides long-term capacities (PV, wind, gas turbine, bio-fuel unit, and battery energy storage), and the lower level dispatches a multi-energy port microgrid (electricity–heat–cold) on an hourly basis with frequency regulation services. To ensure rigor and reproducibility, we (i) move the methodology upfront and formalize all constraints, (ii) provide a dedicated data–preprocessing pipeline for multi-region 50/60 Hz frequency time series, and (iii) map a policy intensity index to a carbon price and/or an annual cap used in the objective/constraints. The bi-level MILP is solved by a column-and-constraint generation algorithm with optimality gap control. We report quantitative metrics—annualized total cost, CO2 emissions (t), renewable shares (%), and regulation cycles—across scenarios. Results show consistent cost–carbon trade-offs and robust capacity shifts toward storage and biofuel as policy tightens. All inputs and scripts are organized for exact replication. Full article
12 pages, 860 KB  
Case Report
AI-Driven Risk Prediction Tool (TSP-9) Informs Risk-Aligned Care for Patients with Barrett’s Esophagus
by Jay N Yepuri
Diagnostics 2025, 15(21), 2776; https://doi.org/10.3390/diagnostics15212776 (registering DOI) - 31 Oct 2025
Abstract
Background and Clinical Significance: Barrett’s esophagus (BE) is the precursor to esophageal adenocarcinoma (EAC). Accurately predicting which patients with BE are at the highest risk of progressing to EAC is a significant clinical challenge. This article discusses how the tissue systems pathology test [...] Read more.
Background and Clinical Significance: Barrett’s esophagus (BE) is the precursor to esophageal adenocarcinoma (EAC). Accurately predicting which patients with BE are at the highest risk of progressing to EAC is a significant clinical challenge. This article discusses how the tissue systems pathology test (TSP-9, TissueCypher) can help guide risk-aligned care for patients with BE. TSP-9 is an AI-driven prognostic test that stratifies patients with BE for risk of progression to high-grade dysplasia (HGD)/EAC. Case Report Presentation: Three clinically low-risk patients had esophageal biopsies tested by TSP-9. The real-world utility of TSP-9 is demonstrated through a brief discussion of how the test was utilized to assess each patient’s personalized risk of BE progression to HGD/EAC and inform risk-aligned care. Conclusions: The use of validated AI-powered tools such as TSP-9 is poised to become standard practice in gastroenterology clinical settings and will help improve health outcomes for patients with BE to prevent EAC-related mortality. Full article
(This article belongs to the Special Issue Application of Artificial Intelligence in Gastrointestinal Disease)
18 pages, 1513 KB  
Article
Predicting Current and Future Potential Distributions of Ectropis grisescens (Lepidoptera: Geometridae) in China Based on the MaxEnt Model
by Cheng-Fei Song, Qing-Zhao Liu, Xin-Yao Ma, Jiao Liu and Fa-Lin He
Agronomy 2025, 15(11), 2546; https://doi.org/10.3390/agronomy15112546 (registering DOI) - 31 Oct 2025
Abstract
Ectropis grisescens Warren (Lepidoptera: Geometridae) is a destructive pest that has severely impacted major tea-growing regions in recent years; as such, it is vital to determine how climate change influences its areas of distribution. In this study, we employed a parameter-optimized maximum entropy [...] Read more.
Ectropis grisescens Warren (Lepidoptera: Geometridae) is a destructive pest that has severely impacted major tea-growing regions in recent years; as such, it is vital to determine how climate change influences its areas of distribution. In this study, we employed a parameter-optimized maximum entropy (MaxEnt) model, integrating 170 E. grisescens occurrence records and seven selected environmental variables, to predict the pest’s current and future potential distribution in China. Parameter optimization was conducted with the ENMeval package in R, identifying the optimal feature combination as “linear—L, quadratic—Q” and the regularization multiplier as 0.5. These results indicated that the mean diurnal range (bio2), precipitation of driest month (bio14), and elevation were the key variables contributing to the suitable area for E. grisescens. Currently, the total potential suitable area for E. grisescens in China spans approximately 1.969 × 106 km², covering 20.51% of the country's land area, of which 5.121 × 105 km², 7.385 × 105 km², and 7.185 × 105 km² possess low, medium, and high suitability, respectively. Notably, the high-suitability regions are predominantly concentrated in southeastern China, encompassing the provinces and municipalities of Zhejiang, Anhui, Hunan, Jiangsu, Chongqing, Jiangxi, Guangxi, Hubei, and Sichuan. Under future climate scenarios, it is projected that the suitable habitats for this pest will undergo varying degrees of change. Specifically, under the SSP1-2.6 scenario, the suitable habitat area is estimated to increase by up to 12.21% by the 2070s. Under the SSP2-4.5 scenario, the centroid of the suitable habitat will be displaced northwest by up to 238.4 km by the 2030s. Our findings provide valuable insights into the future management of E. grisescens and will aid in mitigating its ecological and economic impacts. Full article
(This article belongs to the Special Issue Sustainable Pest Management under Climate Change)
23 pages, 5086 KB  
Article
PPARα-Mediated Fatty Acid Catabolism in Astrocytes Was Involved in Improvement of Cognitive Dysfunction by Phlorizin in APP/PS1 Mice
by Yan Fu, Xuya Zhang, Lingling Li, Hong Jiang, Qiaozhi Ren, Tianxing Yi, Yali Zhang and Yi Lu
Antioxidants 2025, 14(11), 1321; https://doi.org/10.3390/antiox14111321 (registering DOI) - 31 Oct 2025
Abstract
Central lipid metabolism disorders are crucial for the development of Alzheimer’s disease (AD). Phlorizin (PHZ) improved lipid metabolism abnormalities in AD nematodes, but its mechanism of action in improving AD-related symptoms and whether it can alleviate AD cognitive impairment remain unclear. To elucidate [...] Read more.
Central lipid metabolism disorders are crucial for the development of Alzheimer’s disease (AD). Phlorizin (PHZ) improved lipid metabolism abnormalities in AD nematodes, but its mechanism of action in improving AD-related symptoms and whether it can alleviate AD cognitive impairment remain unclear. To elucidate the effects and mechanisms of PHZ on lipid metabolism disorders in an AD model, gavage administration of PHZ for 8 weeks improved cognitive dysfunction and lipid disorders in APPswe/PSEN1dE9 (APP/PS1) mice. Concurrently, in astrocytes induced by palmitic acid (PA)- mediated lipid metabolic disorder, PHZ treatment improved astrocytic lipid accumulation by upregulating the target peroxisome proliferator-activated receptor α (PPARα) and its downstream pathways, thereby promoting astrocytic fatty acid oxidation. We validated PHZ’s strong in vitro binding affinity with PPARα. Co-culture systems of lipid-metabolically disordered astrocytes and neurons further demonstrated that PHZ significantly improved neuronal cell viability and reduced intracellular lipid accumulation, thereby decreasing the expression of enzymes associated with β-amyloid protein (Aβ) production. This study demonstrates that gavage administration of PHZ for 2 months improves cognitive deficits and pathological markers in AD mice. Furthermore, at the cellular level, PHZ may exert its effects by enhancing astrocytic lipid metabolism, thereby preventing neuronal lipotoxicity and mitigating AD progression. Full article
(This article belongs to the Section Health Outcomes of Antioxidants and Oxidative Stress)
8 pages, 3753 KB  
Interesting Images
Two Cases of Singular Sacral S1 Butterfly Vertebra
by Arturs Balodis, Roberts Tumelkans and Cenk Eraslan
Diagnostics 2025, 15(21), 2775; https://doi.org/10.3390/diagnostics15212775 (registering DOI) - 31 Oct 2025
Abstract
A butterfly vertebra is an uncommon but clinically and radiologically significant pathology. The etiological factor of this pathology is a congenital defect in the formation of the vertebral body during embryogenesis, resulting in a cleft within the vertebral body that, in an X-ray, [...] Read more.
A butterfly vertebra is an uncommon but clinically and radiologically significant pathology. The etiological factor of this pathology is a congenital defect in the formation of the vertebral body during embryogenesis, resulting in a cleft within the vertebral body that, in an X-ray, resembles the shape of a butterfly. Butterfly vertebrae are most often found in the thoracic and lumbar spine and more rarely in the sacral region. The clinical manifestations of this condition do not differ from the symptoms of other diseases, and it may also be asymptomatic. Only the recognition of its characteristic radiologic signs allows for accurate and timely diagnosis, as well as differentiation from other pathological processes such as fractures, metastases, and inflammation. In these cases, magnetic resonance imaging is the first-choice method. An important aspect in recognizing this pathology is its correlation with other congenital syndromes, even in cases of a single vertebral defect. We present 2 cases with an isolated S1 butterfly vertebra. The first is a 47-year-old male who presented to the hospital with complaints of chronic pain in the lower back and sacral region, more pronounced on the right side. The second is of a 39-year-old male who also presented to the hospital with chronic pain. All diagnostic modalities for this pathology have been used to demonstrate high-quality pictures, including X-ray, computed tomography (CT), and magnetic resonance imaging (MRI). Full article
(This article belongs to the Section Medical Imaging and Theranostics)
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22 pages, 541 KB  
Article
Data-Driven Modeling of Web Traffic Flow Using Functional Modal Regression
by Zoulikha Kaid and Mohammed B. Alamari
Axioms 2025, 14(11), 815; https://doi.org/10.3390/axioms14110815 (registering DOI) - 31 Oct 2025
Abstract
Real-time control of web traffic is a critical issue for network operators and service providers. It helps ensure robust service and avoid service interruptions, which has an important financial impact. However, due to the high speed and volume of actual internet traffic, standard [...] Read more.
Real-time control of web traffic is a critical issue for network operators and service providers. It helps ensure robust service and avoid service interruptions, which has an important financial impact. However, due to the high speed and volume of actual internet traffic, standard multivariate time series models are inadequate for ensuring efficient real-time traffic management. In this paper we introduce a new model for functional time series analysis, developed by combining a local linear smoothing approach with an L1-robust estimator of the quantile’s derivative. It constitutes an alternative, robust estimator for functional modal regression that is adequate to handle the stochastic volatility of high-frequency of web traffic data. The mathematical support of the new model is established under functional dependent case. The asymptotic analysis emphasizes the functional structure of the data, the functional feature of the model, and the stochastic characteristics of the underlying time-varying process. We evaluate the effectiveness of our proposed model using comprehensive simulations and real-data application. The computational results illustrate the superiority of the nonparametric functional model over the existing conventional methods in web traffic modeling. Full article
(This article belongs to the Special Issue Functional Data Analysis and Its Application)
55 pages, 11554 KB  
Article
Spatial Flows of Information Entropy as Indicators of Climate Variability and Extremes
by Bernard Twaróg
Entropy 2025, 27(11), 1132; https://doi.org/10.3390/e27111132 (registering DOI) - 31 Oct 2025
Abstract
The objective of this study is to analyze spatial entropy flows that reveal the directional dynamics of climate change—patterns that remain obscured in traditional statistical analyses. This approach enables the identification of pathways for “climate information transport”, highlights associations with atmospheric circulation types, [...] Read more.
The objective of this study is to analyze spatial entropy flows that reveal the directional dynamics of climate change—patterns that remain obscured in traditional statistical analyses. This approach enables the identification of pathways for “climate information transport”, highlights associations with atmospheric circulation types, and allows for the localization of both sources and “informational voids”—regions where entropy is dissipated. The analytical framework is grounded in a quantitative assessment of long-term climate variability across Europe over the period 1901–2010, utilizing Shannon entropy as a measure of atmospheric system uncertainty and variability. The underlying assumption is that the variability of temperature and precipitation reflects the inherently dynamic character of climate as a nonlinear system prone to fluctuations. The study focuses on calculating entropy estimated within a 70-year moving window for each calendar month, using bivariate distributions of temperature and precipitation modeled with copula functions. Marginal distributions were selected based on the Akaike Information Criterion (AIC). To improve the accuracy of the estimation, a block bootstrap resampling technique was applied, along with numerical integration to compute the Shannon entropy values at each of the 4165 grid points with a spatial resolution of 0.5° × 0.5°. The results indicate that entropy and its derivative are complementary indicators of atmospheric system instability—entropy proving effective in long-term diagnostics, while its derivative provides insight into the short-term forecasting of abrupt changes. A lag analysis and Spearman rank correlation between entropy values and their potential supported the investigation of how circulation variability influences the occurrence of extreme precipitation events. Particularly noteworthy is the temporal derivative of entropy, which revealed strong nonlinear relationships between local dynamic conditions and climatic extremes. A spatial analysis of the information entropy field was also conducted, revealing distinct structures with varying degrees of climatic complexity on a continental scale. This field appears to be clearly structured, reflecting not only the directional patterns of change but also the potential sources of meteorological fluctuations. A field-theory-based spatial classification allows for the identification of transitional regions—areas with heightened susceptibility to shifts in local dynamics—as well as entropy source and sink regions. The study is embedded within the Fokker–Planck formalism, wherein the change in the stochastic distribution characterizes the rate of entropy production. In this context, regions of positive divergence are interpreted as active generators of variability, while sink regions function as stabilizing zones that dampen fluctuations. Full article
(This article belongs to the Special Issue 25 Years of Sample Entropy)
21 pages, 596 KB  
Review
Hashing in the Fight Against CSAM: Technology at the Crossroads of Law and Ethics
by Evangelia Daskalaki, Emmanouela Kokolaki and Paraskevi Fragopoulou
J. Cybersecur. Priv. 2025, 5(4), 92; https://doi.org/10.3390/jcp5040092 (registering DOI) - 31 Oct 2025
Abstract
Hashes are vital in limiting the spread of child sexual abuse material online, yet their use introduces unresolved technical, legal, and ethical challenges. This paper bridges a critical gap by analyzing both cryptographic and perceptual hashing, not only in terms of detection capabilities, [...] Read more.
Hashes are vital in limiting the spread of child sexual abuse material online, yet their use introduces unresolved technical, legal, and ethical challenges. This paper bridges a critical gap by analyzing both cryptographic and perceptual hashing, not only in terms of detection capabilities, but also their vulnerabilities and implications for privacy governance. Unlike prior work, it reframes CSAM detection as a multidimensional issue, at the intersection of cybersecurity, data protection law, and digital ethics. Three key contributions are made: first, a comparative evaluation of hashing techniques, revealing weaknesses, such as susceptibility to media edits, collision attacks, hash inversion, and data leakage; second, a call for standardized benchmarks and interoperable evaluation protocols to assess system robustness; and third, a legal argument that perceptual hashes qualify as personal data under EU law, with implications for transparency and accountability. Ethically, the paper underscores the tension faced by service providers in balancing user privacy with the duty to detect CSAM. It advocates for detection systems that are not only technically sound, but also legally defensible and ethically governed. By integrating technical analysis with legal insight, this paper offers a comprehensive framework for evaluating CSAM detection, within the broader context of digital safety and privacy. Full article
(This article belongs to the Section Cryptography and Cryptology)
33 pages, 3576 KB  
Article
Small-Signal Modeling, Comparative Analysis, and Gain-Scheduled Control of DC–DC Converters in Photovoltaic Applications
by Vipinkumar Shriram Meshram, Fabio Corti, Gabriele Maria Lozito, Luigi Costanzo, Alberto Reatti and Massimo Vitelli
Electronics 2025, 14(21), 4308; https://doi.org/10.3390/electronics14214308 (registering DOI) - 31 Oct 2025
Abstract
This paper presents an innovative approach to the modeling and dynamic analysis of DC–DC converters in photovoltaic applications. Departing from traditional studies that focus on the transfer function from duty cycle to output voltage, this work investigates the duty cycle to input voltage [...] Read more.
This paper presents an innovative approach to the modeling and dynamic analysis of DC–DC converters in photovoltaic applications. Departing from traditional studies that focus on the transfer function from duty cycle to output voltage, this work investigates the duty cycle to input voltage transfer function, which is critical for accurate dynamic representation of photovoltaic systems. A notable contribution of this study is the integration of the PV panel behavior in the small-signal representation, considering a model-derived differential resistance for various operating points. This technique enhances the model’s accuracy across different operating regions. The paper also validates the effectiveness of this linearization method through small-signal analysis. A comprehensive comparison is conducted among several non-isolated converter topologies such as Boost, Buck–Boost, Ćuk, and SEPIC under both open-loop and closed-loop conditions. To ensure fairness, all converters are designed using a consistent set of constraints, and controllers are tuned to maintain similar phase margins and crossover frequencies across topologies. In addition, a gain-scheduling control strategy is implemented for the Boost converter, where the PI gains are dynamically adapted as a function of the PV operating point. This approach demonstrates superior closed-loop performance compared to a fixed controller tuned only at the maximum power point, further highlighting the benefits of the proposed modeling and control framework. This systematic study therefore provides an objective evaluation of dynamic performance and offers valuable insights into optimal converter architectures and advanced control strategies for photovoltaic systems. Full article
(This article belongs to the Special Issue New Horizons and Recent Advances of Power Electronics)
15 pages, 1587 KB  
Article
Cytotoxicity of Typical Diiodoalkanes from Shale Gas Wastewater in HepG2 Cells
by Maoyuan Xu, Yusheng Wu, Yunmei Cai, Ruijie Wang and Guofa Ren
Toxics 2025, 13(11), 943; https://doi.org/10.3390/toxics13110943 (registering DOI) - 31 Oct 2025
Abstract
Shale gas extraction releases significant quantities of organic iodides of “unknown origin”, which generally pose high ecological and health risks, yet their toxic mechanisms remain unclear. In this study, the human hepatocellular carcinoma (HepG2) cell line was employed as an in vitro cell [...] Read more.
Shale gas extraction releases significant quantities of organic iodides of “unknown origin”, which generally pose high ecological and health risks, yet their toxic mechanisms remain unclear. In this study, the human hepatocellular carcinoma (HepG2) cell line was employed as an in vitro cell model to assess the cytotoxic effects of three typical organic iodides (1,2-diiodoethane, 1,3-diiodopropane, and 1,4-diiodobutane) identified in shale gas extraction wastewater from Chongqing, China. The results demonstrated that all three diiodoalkanes exhibited significant toxic effects on HepG2 cells at a concentration of 25 µM, and this effect demonstrated a dose-dependent pattern. As the concentration of diiodoalkanes increased, the viability of HepG2 cells decreased significantly, while cell mortality increased markedly. The transcriptomic analysis indicated that exposure to these three diiodoalkanes induced abnormal expression of genes associated with the extracellular space, extracellular matrix (ECM), and endoplasmic reticulum (ER) in HepG2 cells, which was presumed to be linked to the disruption of the intracellular redox-antioxidant system homeostasis by the diiodoalkanes. Furthermore, assays of intracellular reactive oxygen species (ROS) and antioxidant enzyme/molecule levels suggested that diiodoalkane exposure triggered excessive intracellular ROS production, induced oxidative stress, and ultimately resulted in cell death. Full article
(This article belongs to the Special Issue Environmental Transport and Transformation of Pollutants)
14 pages, 1575 KB  
Article
Deep Sequencing Analysis of Hepatitis C Virus Subtypes and Resistance-Associated Substitutions in Genotype 4 Patients Resistant to Direct-Acting Antiviral (DAA) Treatment in Egypt
by Damir Garcia-Cehic, Asmaa Mosbeh, Heba A. Gad, Asmaa Ibrahim Gomaa, Marta Ibañez Lligoña, Josep Gregori, Sergi Colomer-Castell, Carolina Campos, Francisco Rodriguez-Frias, Juan Ignacio Esteban, Mohamed S. Kohla, Mohamed Helmy Abdel-Rahman and Josep Quer
Int. J. Mol. Sci. 2025, 26(21), 10649; https://doi.org/10.3390/ijms262110649 (registering DOI) - 31 Oct 2025
Abstract
Egypt has the highest global prevalence of hepatitis C virus (HCV), with genotype 4 (G4) in over 94% of cases. Direct-acting antivirals (DAAs) yield sustained virologic response (SVR) rates above 95%. Second-generation DAAs are recommended for patients with virological failure, achieving over 90% [...] Read more.
Egypt has the highest global prevalence of hepatitis C virus (HCV), with genotype 4 (G4) in over 94% of cases. Direct-acting antivirals (DAAs) yield sustained virologic response (SVR) rates above 95%. Second-generation DAAs are recommended for patients with virological failure, achieving over 90% eradication. This study aimed to classify and evaluate the pattern of HCV resistance-associated substitutions (RASs) in patients who failed DAA treatment in Egypt. A total of 1778 chronically infected HCV patients from Egypt’s Nile Delta were enrolled (2016–2018). Among them, 37 relapsed, and high-quality serum samples from 22 patients were available, including 6 cases with pre- and post-treatment samples. Next-generation sequencing (NGS) was performed for HCV subtyping and RAS identification. Among the 22 analyzed cases, 21 (95.4%) were G4: 11 were classified as subtype G4a, seven G4o, and three G4m. One patient (4.5%) was identified as G1g. One case shifted from G4a pre- to G4o post-treatment, suggesting reinfection. The RAS pattern in rare G4 subtypes (G4m/G4o) differs from the G4a subtype. The combination of L28M/L30S mutations was detected in 8/11 G4a samples; in contrast, RASs in G4o were characterized by T30S or Y93C/H/N/S substitutions. Notably, some substitutions identified as RASs may represent fixed polymorphisms in regional viral populations, such as those in Egypt’s Nile Delta. HCV subtypes significantly influence the RAS pattern, particularly within the NS5A region, after DAA-treatment failure. The RAS pattern differs among G4 subtypes, particularly in rare ones, predisposing patients to resistance and underscoring the importance of NGS in regional populations to optimize treatment strategies. Full article
42 pages, 17784 KB  
Article
Research on a Short-Term Electric Load Forecasting Model Based on Improved BWO-Optimized Dilated BiGRU
by Ziang Peng, Haotong Han and Jun Ma
Sustainability 2025, 17(21), 9746; https://doi.org/10.3390/su17219746 (registering DOI) - 31 Oct 2025
Abstract
In the context of global efforts toward energy conservation and emission reduction, accurate short-term electric load forecasting plays a crucial role in improving energy efficiency, enabling low-carbon dispatching, and supporting sustainable power system operations. To address the growing demand for accuracy and stability [...] Read more.
In the context of global efforts toward energy conservation and emission reduction, accurate short-term electric load forecasting plays a crucial role in improving energy efficiency, enabling low-carbon dispatching, and supporting sustainable power system operations. To address the growing demand for accuracy and stability in this domain, this paper proposes a novel prediction model tailored for power systems. The proposed method combines Spearman correlation analysis with modal decomposition techniques to compress redundant features while preserving key information, resulting in more informative and cleaner input representations. In terms of model architecture, this study integrates Bidirectional Gated Recurrent Units (BiGRUs) with dilated convolution. This design improves the model’s capacity to capture long-range dependencies and complex relationships. For parameter optimization, an Improved Beluga Whale Optimization (IBWO) algorithm is introduced, incorporating dynamic population initialization, adaptive Lévy flight mechanisms, and refined convergence procedures to enhance search efficiency and robustness. Experiments on real-world datasets demonstrate that the proposed model achieves excellent forecasting performance (RMSE = 26.1706, MAE = 18.5462, R2 = 0.9812), combining high predictive accuracy with strong generalization. These advancements contribute to more efficient energy scheduling and reduced environmental impact, making the model well-suited for intelligent and sustainable load forecasting applications in environmentally conscious power systems. Full article
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19 pages, 1639 KB  
Article
Spatiotemporal Dynamics of Rocky Desertification in the Danjiangkou Reservoir, China
by Shiwen Wu, Chenglong Li, Hongliang Wang, Zhiqi Wang, Haodong Ji, Zhanping Zhang, Yechen Zhang, Wenhui Hao and Yu Song
Sustainability 2025, 17(21), 9748; https://doi.org/10.3390/su17219748 (registering DOI) - 31 Oct 2025
Abstract
Rocky desertification in the Danjiangkou Reservoir area, the core water source of the South-to-North Water Diversion Project, constitutes a significant ecological threat, primarily driven by historical deforestation and agricultural expansion. To addressing the previous lack of comprehensive evaluation and spatiotemporal analysis of rocky [...] Read more.
Rocky desertification in the Danjiangkou Reservoir area, the core water source of the South-to-North Water Diversion Project, constitutes a significant ecological threat, primarily driven by historical deforestation and agricultural expansion. To addressing the previous lack of comprehensive evaluation and spatiotemporal analysis of rocky desertification in the Danjiangkou Reservoir area, this study utilized Google Earth Engine (GEE) and GeoDetector to analyze its evolution and driving factors from 1995 to 2022. The results indicated an overall improvement, with a 1002.02 km2 decrease in the desertification-prone area and an expansion of 26,077.31 km2 in the non-desertified area. However, desertification remains severe in the western and southeastern regions, while the northeastern and central areas showed relative stability. Notably, desertified areas decreased substantially between 1995 and 2022, reflecting the effectiveness of ecological restoration efforts. Key driving factors include potential evapotranspiration (PET), landform, elevation, and temperature, with interactions between PET and environmental variables exhibiting strong explanatory power. These findings highlight the complex interplay between natural and anthropogenic factors in desertification dynamics. Continuing human intervention is essential to restore vegetation, mitigate soil erosion risks, and ensure the long-term stability of the reservoir’s water resources. Full article
22 pages, 17272 KB  
Article
Climate Change Projected Effects on Hamatocaulis vernicosus Occurrence in Romania
by Sorin Ștefănuț, Claudia Biță-Nicolae, Tiberiu Sahlean, Constantin-Ciprian Bîrsan, Ioana Cătălina Paica, Georgiana-Roxana Nicoară, Florența-Elena Helepciuc, Miruna-Maria Ștefănuț and Ana-Maria Moroșanu
Plants 2025, 14(21), 3354; https://doi.org/10.3390/plants14213354 (registering DOI) - 31 Oct 2025
Abstract
Hamatocaulis vernicosus is a pleurocarpous moss of conservation concern, listed in Annex II of the EU Habitats Directive due to its significant and ongoing decline across Europe. H. vernicosus is also listed as ‘Vulnerable’ on the Red List of Romanian Bryophytes. Despite its [...] Read more.
Hamatocaulis vernicosus is a pleurocarpous moss of conservation concern, listed in Annex II of the EU Habitats Directive due to its significant and ongoing decline across Europe. H. vernicosus is also listed as ‘Vulnerable’ on the Red List of Romanian Bryophytes. Despite its protected status, the species remains under-recorded in Romania, where many potentially suitable habitats have yet to be surveyed. The ecosystems, classified as Transition mire and quaking bog (NATURA 2000 code: 7140), are wet peatlands with oligo- to mesotrophic conditions and a pH of 5.0–7.5. H. vernicosus is recorded in 58 Romanian locations (10 confirmed by us, 5 new), spanning the Continental and Alpine bioregions. Models showed good performance (AUC 0.79–0.83; TSS 0.54–0.59), with distribution mainly shaped by mean annual temperature and temperature range, and secondarily by precipitation. The species favors cold, stable climates with high seasonal rainfall. Even though the number of localities reported for this species has increased in recent years, this does not indicate an improvement in its conservation status, but rather is an effect of recent recording efforts. To support targeted conservation planning, an ensemble species distribution model was developed in order to predict the suitable habitats of H. vernicosus across Romania. Both climate models project major range losses for the varnished hook-moss: ~30% by 2050 and ~40–60% by 2100, depending on the scenario. Losses are gradual under SSP245 but more abrupt under SSP585, with increased fragmentation, especially between the Eastern and Southern Carpathians. By integrating field observations with predictive climate change modeling, our study brings critical insights applicable to the conservation of H. vernicosus and the unique peatland ecosystems it relies on. Full article
(This article belongs to the Special Issue Responses and Adaptations of Bryophytes to a Changing World)
14 pages, 416 KB  
Article
A QMIX-Based Multi-Agent Reinforcement Learning Approach for Crowdsourced Order Assignment in Fresh Food Retailing
by Jingming Hu and Chong Wang
Electronics 2025, 14(21), 4306; https://doi.org/10.3390/electronics14214306 (registering DOI) - 31 Oct 2025
Abstract
Crowdsourced delivery plays a key role in fresh food retailing, where tight time limits and perishability require fast, reliable fulfillment. However, real-time order–courier assignment is challenging because orders arrive in bursts, couriers’ locations and availability change, capacities are limited, and many decisions must [...] Read more.
Crowdsourced delivery plays a key role in fresh food retailing, where tight time limits and perishability require fast, reliable fulfillment. However, real-time order–courier assignment is challenging because orders arrive in bursts, couriers’ locations and availability change, capacities are limited, and many decisions must be made simultaneously. We propose Attn-QMIX, a novel attention-augmented multi-agent reinforcement learning framework that models each order as an agent and learns coordinated matching strategies through centralized training with decentralized execution. The framework develops a new capacity-aware multi-head attention mechanism that captures complex order–courier interactions and dynamically prevents courier overload and integrates it with a QMIX-based mixing network equipped with hypernetworks to enable effective credit assignment and global coordination. Extensive experiments on a real-world road network show that Attn-QMIX outperforms five representative methods. Compared with a novel cooperative ant colony optimization method, it reduces total cost by up to 2.30% while being up to 3403 times faster in computation. Full article
(This article belongs to the Special Issue Advances in Data-Driven Artificial Intelligence)
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24 pages, 684 KB  
Article
FLACON: An Information-Theoretic Approach to Flag-Aware Contextual Clustering for Large-Scale Document Organization
by Sungwook Yoon
Entropy 2025, 27(11), 1133; https://doi.org/10.3390/e27111133 (registering DOI) - 31 Oct 2025
Abstract
Enterprise document management faces a significant challenge: traditional clustering methods focus solely on content similarity while ignoring organizational context, such as priority, workflow status, and temporal relevance. This paper introduces FLACON (Flag-Aware Context-sensitive Clustering), an information-theoretic approach that captures multi-dimensional document context through [...] Read more.
Enterprise document management faces a significant challenge: traditional clustering methods focus solely on content similarity while ignoring organizational context, such as priority, workflow status, and temporal relevance. This paper introduces FLACON (Flag-Aware Context-sensitive Clustering), an information-theoretic approach that captures multi-dimensional document context through a six-dimensional flag system encompassing Type, Domain, Priority, Status, Relationship, and Temporal dimensions. FLACON formalizes document clustering as an entropy minimization problem, where the objective is to group documents with similar contextual characteristics. The approach combines a composite distance function—integrating semantic content, contextual flags, and temporal factors—with adaptive hierarchical clustering and efficient incremental updates. This design addresses key limitations of existing solutions, including context-aware systems that lack domain-specific intelligence and LLM-based methods that require prohibitive computational resources. Evaluation across nine dataset variations demonstrates notable improvements over traditional methods, including a 7.8-fold improvement in clustering quality (Silhouette Score: 0.311 vs. 0.040) and performance comparable to GPT-4 (89% of quality) while being ~7× faster (60 s vs. 420 s for 10 K documents). FLACON achieves O(m log n) complexity for incremental updates affecting m documents and provides deterministic behavior, which is suitable for compliance requirements. Consistent performance across business emails, technical discussions, and financial news confirms the practical viability of this approach for large-scale enterprise document organization. Full article
31 pages, 875 KB  
Article
Advanced Spectroscopic Studies of the AIE-Enhanced ESIPT Effect in a Selected 1,3,4-Thiadiazole Derivative in Liposomal Systems with DPPC
by Alicja Skrzypek, Iwona Budziak-Wieczorek, Lidia Ślusarczyk, Andrzej Górecki, Daniel Kamiński, Anita Kwaśniewska, Sylwia Okoń, Igor Różyło and Arkadiusz Matwijczuk
Int. J. Mol. Sci. 2025, 26(21), 10643; https://doi.org/10.3390/ijms262110643 (registering DOI) - 31 Oct 2025
Abstract
Liposomal systems are advanced carriers of active substances which, thanks to their ability to encapsulate these substances, significantly improve their pharmacokinetics, bioavailability, and selectivity. This article presents the results of spectroscopic studies for a selected compound from the 1,3,4-thiadiazole group, namely 4-[5-(naphthalen-1-ylmethyl)-1,3,4-thiadiazol-2-yl]benzene-1,3-diol (NTBD, [...] Read more.
Liposomal systems are advanced carriers of active substances which, thanks to their ability to encapsulate these substances, significantly improve their pharmacokinetics, bioavailability, and selectivity. This article presents the results of spectroscopic studies for a selected compound from the 1,3,4-thiadiazole group, namely 4-[5-(naphthalen-1-ylmethyl)-1,3,4-thiadiazol-2-yl]benzene-1,3-diol (NTBD, see below in the text), in selected liposomal systems formed from the phospholipid 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC). Detailed spectroscopic analyses were carried out using electronic absorption and fluorescence spectroscopy; resonance light scattering (RLS) spectra measurements; dynamic light scattering (DLS); as well as time-resolved methods—fluorescence lifetime measurements using the TCSPC technique. Subsequently, based on the interpretation of spectra obtained by FTIR infrared spectroscopy, the preliminary molecular organization of the above-mentioned compounds within lipid multilayers was determined. It was found that NTBD preferentially occupies the region of polar lipid headgroups in the lipid multilayer, although it also noticeably interacts with the hydrocarbon chains of the lipids. Furthermore, X-ray diffraction (XRD) techniques were used to study the effect of NTBD on the molecular organization of DPPC lipid multilayers. Monomeric structures and aggregated forms of the above-mentioned 1,3,4-thiadiazole analogue were characterized using X-ray crystallography. Interesting dual fluorescence effects observed in steady-state fluorescence measurements were linked to the excited-state intramolecular proton transfer (ESIPT) effect (based on our earlier studies), which, in the obtained biophysical systems—liposomal systems with strong hydrophobicity—is greatly enhanced by aggregation-induced emission (AIE) effects. In summary, the research presented in this study, concerning the novel 1,3,4-thiadiazole derivative NTBD, is highly relevant to drug delivery systems, such as various model liposomal systems, as it demonstrates that depending on the concentration of the selected fluorophore, different forms may be present, allowing for appropriate modulation of its biological activity. Full article
(This article belongs to the Special Issue AIEgens in Action: Design, Mechanisms, and Emerging Applications)
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45 pages, 3725 KB  
Review
Combating White Spot Syndrome Virus (WSSV) in Global Shrimp Farming: Unraveling Its Biology, Pathology, and Control Strategies
by Md. Iftehimul, Neaz A. Hasan, David Bass, Abul Bashar, Mohammad Mahfujul Haque and Morena Santi
Viruses 2025, 17(11), 1463; https://doi.org/10.3390/v17111463 (registering DOI) - 31 Oct 2025
Abstract
White Spot Syndrome Virus (WSSV) is one of the most devastating viral pathogens affecting shrimp, causing severe economic losses to the global farmed shrimp trade. The globalization of live shrimp trade and waterborne transmission have facilitated the rapid spread of WSSV across major [...] Read more.
White Spot Syndrome Virus (WSSV) is one of the most devastating viral pathogens affecting shrimp, causing severe economic losses to the global farmed shrimp trade. The globalization of live shrimp trade and waterborne transmission have facilitated the rapid spread of WSSV across major shrimp-producing countries since its initial emergence. The present review gives an updated account of WSSV biology, pathology, transmission dynamics, and recent developments in control measures. The virus, a double-stranded DNA virus of the Nimaviridae family, utilizes advanced immune evasion strategies, resulting in severe mortality. Shrimp lack adaptive immunity and hence rely predominantly on innate immunity, which is insufficient to mount an effective response against severe infections. Traditional disease control measures such as augmented biosecurity, selective breeding, and immunostimulants have, despite extensive research, achieved only limited success. New biotechnological tools such as RNA interference, CRISPR-Cas gene editing, and nanotechnology offer tremendous potential for disease mitigation. In parallel, the development of DNA and RNA vaccines targeting WSSV structural proteins, such as VP28, holds significant promise for stimulating the shrimp immune system. This review highlights the urgent need for a convergent approach to sustainable disease management in global shrimp aquaculture, with interdisciplinarity playing a pivotal role in shaping the future of WSSV control. Full article
(This article belongs to the Section Viral Immunology, Vaccines, and Antivirals)
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