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Recent Articles  

41 pages, 22538 KB  
Article
IALA: An Improved Artificial Lemming Algorithm for Unmanned Aerial Vehicle Path Planning
by Xiaojun Zheng, Rundong Liu, Shiming Huang and Zhicong Duan
Technologies 2026, 14(2), 91; https://doi.org/10.3390/technologies14020091 (registering DOI) - 1 Feb 2026
Abstract
With the increasing application of unmanned aerial vehicle (UAV) in multiple fields, the path planning problem has become a key challenge in the optimization domain. This paper proposes an Improved Artificial Lemming Algorithm (IALA), which incorporates three strategies: the optimal information retention strategy [...] Read more.
With the increasing application of unmanned aerial vehicle (UAV) in multiple fields, the path planning problem has become a key challenge in the optimization domain. This paper proposes an Improved Artificial Lemming Algorithm (IALA), which incorporates three strategies: the optimal information retention strategy based on individual historical memory, the hybrid search strategy based on differential evolution operators, and the local refined search strategy based on directed neighborhood perturbation. These strategies are designed to enhance the algorithm’s global exploration and local exploitation capabilities in tackling complex optimization problems. Subsequently, comparative experiments are conducted on the CEC2017 benchmark suite across three dimensions (30D, 50D, and 100D) against eight state-of-the-art algorithms proposed in recent years, including SBOA and DBO. The results demonstrate that IALA achieves superior performance across multiple metrics, ranking first in both the Wilcoxon rank-sum test and the Friedman ranking test. Analyses of convergence curves and data distributions further verify its excellent optimization performance and robustness. Finally, IALA and the comparative algorithms are applied to eight 3D UAV path planning scenarios and two amphibious UAV path planning models. In the independent repeated experiments across the eight scenarios, IALA attains the optimal performance 13 times in terms of the two metrics, Mean and Std. It also ranks first in the Monte Carlo experiments for the two amphibious UAV path planning models. Full article
(This article belongs to the Section Information and Communication Technologies)
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17 pages, 5292 KB  
Article
Nanozyme-Based Colorimetric Assay on a Magnetic Microfluidic Platform for Integrated Detection of TTX
by Chenqi Zhang, Shuo Wu, Fangzhou Zhang, Chang Chen, Jianlong Zhao, Shilun Feng and Bo Liu
Biosensors 2026, 16(2), 89; https://doi.org/10.3390/bios16020089 (registering DOI) - 1 Feb 2026
Abstract
Tetrodotoxin (TTX) is a potent marine neurotoxin, necessitating sensitive and user-friendly on-site assays. To address long workflows of traditional immunoassays and limited signal amplification in colorimetric microfluidics, we developed a nanozyme-catalyzed colorimetric magnetic microfluidic immunosensor (Nano-CMI). This platform combines an aptamer–antibody sandwich capture [...] Read more.
Tetrodotoxin (TTX) is a potent marine neurotoxin, necessitating sensitive and user-friendly on-site assays. To address long workflows of traditional immunoassays and limited signal amplification in colorimetric microfluidics, we developed a nanozyme-catalyzed colorimetric magnetic microfluidic immunosensor (Nano-CMI). This platform combines an aptamer–antibody sandwich capture format with catalytic amplification via AuNR@Pt@m-SiO2 (APMS) nanozymes on a magnetically actuated microfluidic chip. Magnetic actuation simplifies sample handling and washing, while APMS catalysis enhances sensitivity and visual readout. The Nano-CMI has been used for the detection of TTX samples ranging from 0.2 to 20 ng/mL with a detection limit of 0.2 ng/mL in 10 min, following the linear equation: y = −31.14ln x + 110.15, and the entire “capture-reaction-detection” workflow can be completed within 1 h. With rapid response, minimal hands-on time, and robust performance, this platform offers a practical, high-sensitivity solution for on-site TTX screening in food safety and customs inspection. Full article
(This article belongs to the Special Issue Design and Application of Microfluidic Biosensors in Biomedicine)
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28 pages, 32119 KB  
Article
NOAH: A Multi-Modal and Sensor Fusion Dataset for Generative Modeling in Remote Sensing
by Abdul Mutakabbir, Chung-Horng Lung, Marzia Zaman, Darshana Upadhyay, Kshirasagar Naik, Koreen Millard, Thambirajah Ravichandran and Richard Purcell
Remote Sens. 2026, 18(3), 466; https://doi.org/10.3390/rs18030466 (registering DOI) - 1 Feb 2026
Abstract
Earth Observation (EO) and Remote Sensing (RS) data are widely used in various fields, including weather, environment, and natural disaster modeling and prediction. EO and RS done through geostationary satellite constellations in fields such as these are limited to a smaller region, while [...] Read more.
Earth Observation (EO) and Remote Sensing (RS) data are widely used in various fields, including weather, environment, and natural disaster modeling and prediction. EO and RS done through geostationary satellite constellations in fields such as these are limited to a smaller region, while sun synchronous satellite constellations have discontinuous spatial and temporal coverage. This limits the ability of EO and RS data for near-real-time weather, environment, and natural disaster applications. To address these limitations, we introduce Now Observation Assemble Horizon (NOAH), a multi-modal, sensor fusion dataset that combines Ground-Based Sensors (GBS) of weather stations with topography, vegetation (land cover, biomass, and crown cover), and fuel types data from RS data sources. NOAH is collated using publicly available data from Environment and Climate Change Canada (ECCC), Spatialized CAnadian National Forest Inventory (SCANFI) and United States Geological Survey (USGS), which are well-maintained, documented, and reliable. Applications of the NOAH dataset include, but are not limited to, expanding RS data tiles, filling in missing data, and super-resolution of existing data sources. Additionally, Generative Artificial Intelligence (GenAI) or Generative Modeling (GM) can be applied for near-real-time model-generated or synthetic estimate data for disaster modeling in remote locations. This can complement the use of existing observations by field instruments, rather than replacing them. UNet backbone with Feature-wise Linear Modulation (FiLM) injection of GBS data was used to demonstrate the initial proof-of-concept modeling in this research. This research also lists ideal characteristics for GM or GenAI datasets for RS. The code and a subset of the NOAH dataset (NOAH mini) are made open-sourced. Full article
(This article belongs to the Special Issue Artificial Intelligence and Remote Sensing Applications in Natural Ecology Monitoring)
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15 pages, 1018 KB  
Article
Evolutionary Optimization for Job Shop Scheduling with Blocking: A Genetic Algorithm Approach
by John Valencia and Elkin Rodríguez-Velásquez
Algorithms 2026, 19(2), 115; https://doi.org/10.3390/a19020115 (registering DOI) - 1 Feb 2026
Abstract
The Blocking Job Shop Scheduling Problem (BJSSP) is a variant of the classical Job Shop Scheduling Problem in which a job completed on one machine cannot be transferred to the next machine until the latter becomes available, causing the current machine to remain [...] Read more.
The Blocking Job Shop Scheduling Problem (BJSSP) is a variant of the classical Job Shop Scheduling Problem in which a job completed on one machine cannot be transferred to the next machine until the latter becomes available, causing the current machine to remain blocked. Numerous real-world applications have been modeled as the BJSSP, which is classified as a strongly NP-hard problem. Previous studies indicate that several proposed approaches fail to guarantee the generation of feasible solutions during the search process, thereby requiring a solution reconstruction. In this study, we propose a Genetic Algorithm (GA) designed to operate strictly within the feasible solution space of the BJSSP, where the objective function is the minimization of the makespan. Experimental results show that no specific factor levels significantly influenced the solution quality obtained by the GA across all problem sets. On the other hand, incorporating an assignment operator into the solution representation enhanced the diversity of the population. The proposed GA yields solutions that outperform some of the best-known makespan values for the Lawrence benchmark problems. The runtime of the GA ranged from 20 s for instances with 10 jobs and five machines to 600 s for instances with 30 jobs and 10 machines. Full article
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21 pages, 10040 KB  
Article
Design of Monitoring System for River Crab Feeding Platform Based on Machine Vision
by Yueping Sun, Ziqiang Li, Zewei Yang, Bikang Yuan, De’an Zhao, Ni Ren and Yawen Cheng
Fishes 2026, 11(2), 88; https://doi.org/10.3390/fishes11020088 (registering DOI) - 1 Feb 2026
Abstract
Bait costs constitute 40–50% of the total expenditure in river crab aquaculture, highlighting the critical need for accurately assessing crab growth and scientifically determining optimal feeding regimes across different farming stages. Current traditional methods rely on periodic manual sampling to monitor growth status [...] Read more.
Bait costs constitute 40–50% of the total expenditure in river crab aquaculture, highlighting the critical need for accurately assessing crab growth and scientifically determining optimal feeding regimes across different farming stages. Current traditional methods rely on periodic manual sampling to monitor growth status and artificial feeding platforms to observe consumption and adjust bait input. These approaches are inefficient, disruptive to crab growth, and fail to provide comprehensive growth data. Therefore, this study proposes a machine vision-based monitoring system for river crab feeding platforms. Firstly, the Contrast Limited Adaptive Histogram Equalization (CLAHE) algorithm is applied to enhance underwater images of river crabs. Subsequently, an improved YOLOv11 (You Only Look Once) model is introduced and applied for multi-target detection and counting in crab ponds, enabling the extraction of information related to both river crabs and bait. Concurrently, underwater environmental parameters are monitored in real-time via an integrated environmental information sensing system. Finally, an information processing platform is established to facilitate data sharing under a “detection–processing–distribution” workflow. The real crab farm experimental results show that the river crab quality error rate was below 9.57%, while the detection rates for both corn and pellet baits consistently exceeded 90% across varying conditions. These results indicate that the proposed system significantly enhances farming efficiency, elevates the level of automation, and provides technological support for the river crab aquaculture industry. Full article
(This article belongs to the Section Fishery Facilities, Equipment, and Information Technology)
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23 pages, 2170 KB  
Article
Particle Swarm Optimization and Fuzzy Logic Co-Optimization for Energy Efficiency Cooperative Energy Management Strategy of Hybrid Energy Storage Electric Vehicles
by Ning Li, Zhongyuan Huang, Chaopeng Wang and Xiaobin Ning
World Electr. Veh. J. 2026, 17(2), 73; https://doi.org/10.3390/wevj17020073 (registering DOI) - 1 Feb 2026
Abstract
For hybrid energy storage systems requiring efficient energy management to achieve optimal power allocation between the power battery and supercapacitor, this study proposes an optimal energy management method integrating whole-process particle swarm optimization with fuzzy logic control, which simultaneously considers braking safety and [...] Read more.
For hybrid energy storage systems requiring efficient energy management to achieve optimal power allocation between the power battery and supercapacitor, this study proposes an optimal energy management method integrating whole-process particle swarm optimization with fuzzy logic control, which simultaneously considers braking safety and energy efficiency optimization. First, a zonal braking force distribution strategy based on the I-curve, ECE regulations curve, and front wheel lockup curve is designed to maximize energy recovery while ensuring braking safety. On this basis, a whole-process “driving–braking” fuzzy logic control strategy for power distribution is constructed, aiming at maximizing braking energy recovery efficiency and minimizing energy consumption per 100 km. The parameters of the membership functions in the fuzzy controller are optimized using the particle swarm optimization algorithm to achieve global optimization of the control process. Finally, simulation validation of the optimization results demonstrates that, compared with traditional logic threshold control under NEDC conditions, the proposed strategy improves braking energy recovery efficiency by 10.32%, reduces energy consumption per 100 km by 0.96 kWh, and decreases the peak current of the power battery by 6.4%, thereby effectively enhancing vehicle economy and extending battery lifespan. Full article
(This article belongs to the Section Energy Supply and Sustainability)
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Graphical abstract

20 pages, 3214 KB  
Article
Kinetics of Isothermal and Non-Isothermal Pre-Reduction of Chromite with Hydrogen
by Mopeli Ishmael Khama, Beberto Myth Vunene Baloyi, Quinn Gareth Reynolds, Buhle Sinaye Xakalashe and Deshenthree Chetty
Hydrogen 2026, 7(1), 21; https://doi.org/10.3390/hydrogen7010021 (registering DOI) - 1 Feb 2026
Abstract
Production of ferrochrome alloy is carried out using carbon as a reductant in a Submerged Arc Furnace (SAF). Carbothermic reduction of chromite ore results in high CO2 emissions, and alternative reductants such as H2, wherein H2O is the [...] Read more.
Production of ferrochrome alloy is carried out using carbon as a reductant in a Submerged Arc Furnace (SAF). Carbothermic reduction of chromite ore results in high CO2 emissions, and alternative reductants such as H2, wherein H2O is the only by-product, have become attractive potential alternatives. Before utilizing H2 as a reductant, it is crucial to carry out a comprehensive study on the reaction kinetics with the view to aid the design and operation of reactors that facilitate the reduction process. The current study determined the kinetic parameters for isothermal and non-isothermal pre-reduction of chromite with H2 in a thermogravimetric furnace. Results from powder X-ray diffraction and scanning electron microscopy determined the mineralogical variations between the feed and the pre-reduced samples, as well as the variation between isothermally and non-isothermally treated samples. The mass loss data indicates that longer reduction times are required to reach complete reduction. The apparent activation energy for the isothermal and non-isothermal pre-reduction tests was found to be 105 and 124 kJ/mol, respectively. The mineralogical observations for pre-reduced samples at 1300 °C and 1500 °C showed that samples treated at lower temperatures (1300 °C) displayed consistent textures and Fe-Cr droplets along rims of partially altered chromite (PAC), which suggested higher metallization at this temperature. Higher temperatures (1500 °C), on the other hand, resulted in poor metallization, possibly because higher temperatures are often associated with a collapsed pore network, which results in poor diffusion rates, thus hindering complete reduction. Full article
(This article belongs to the Special Issue Reactions of Hydrogen with Inorganic and Organic Molecules in Aqueous Media)
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21 pages, 1805 KB  
Systematic Review
Mapping the Relationship Between Core Executive Functions and Mind Wandering in Children and Adolescents: A Systematic Review
by Ioannis G. Katsantonis and Argyrios Katsantonis
J. Intell. 2026, 14(2), 20; https://doi.org/10.3390/jintelligence14020020 (registering DOI) - 1 Feb 2026
Abstract
Internationally, there are several studies that examined the relationship between core executive functions (working memory, inhibitory control, and cognitive flexibility) and mind wandering. These studies focused mostly on adult samples and there are fewer studies that examined this relationship with children and adolescent [...] Read more.
Internationally, there are several studies that examined the relationship between core executive functions (working memory, inhibitory control, and cognitive flexibility) and mind wandering. These studies focused mostly on adult samples and there are fewer studies that examined this relationship with children and adolescent samples. Therefore, the current systematic review aims to identify and critically examine the existing peer-reviewed literature on the relationship between the core executive functions and mind wandering. Journal articles reporting quantitative results were identified through keyword searches in PsycINFO, Scopus, and PubMed. In total, 750 references were identified using the specified keywords. Among those, only ten studies were deemed to fit the inclusion criteria. The majority of the studies employed behavioural measures. The evidence on the relationship between the core executive functions and mind wandering was rather scarce and mixed. Most of the studies suggest that working memory capacity is critical for reduced mind wandering. The evidence regarding inhibitory control is rather mixed. Cognitive flexibility may underpin adaptive reallocation of attention between internal and external states, producing performance declines. The directional nature of the relationship between the three core executive functions and mind wandering is largely an unresolved matter, which requires further research. Full article
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30 pages, 8655 KB  
Article
GAN-MIGA-Driven Building Energy Prediction and Block Layout Optimization: A Case Study in Lanzhou, China
by Xinwei Guo, Shida Wang and Jingyi Li
Urban Sci. 2026, 10(2), 77; https://doi.org/10.3390/urbansci10020077 (registering DOI) - 1 Feb 2026
Abstract
With the rapid urbanization in China, building energy consumption has become a critical challenge for sustainable urban development. Conventional simulation methods are computationally intensive and inefficient for large-scale urban layout optimization, highlighting the need for fast and reliable predictive approaches. Existing machine learning [...] Read more.
With the rapid urbanization in China, building energy consumption has become a critical challenge for sustainable urban development. Conventional simulation methods are computationally intensive and inefficient for large-scale urban layout optimization, highlighting the need for fast and reliable predictive approaches. Existing machine learning models often overlook spatial relationships among buildings and rely heavily on manual feature engineering, which limits their applicability at the urban block scale. To address these limitations, the study proposes a building energy consumption prediction model for urban blocks based on Generative Adversarial Networks (GANs), which preserves spatial information while significantly advancing computational speed. The optimal GAN model is further integrated with a Multi-Island Genetic Algorithm (MIGA) to form a GAN-MIGA optimization framework, which is applied to the layout optimization of a target urban block in Lanzhou. Key findings include: (1) the GAN model achieves an average prediction error of 6.8% compared with conventional energy simulations; (2) the GAN-MIGA framework reduces energy consumption by 48.78% relative to the worst-performing solution and by 22.53% compared with the original block layout; (3) the spatial distribution patterns of energy consumption predicted by the GAN are consistent with those obtained from traditional simulation methods; (4) the regression model derived from GAN-MIGA optimization results achieves an R2 value exceeding 0.84; and (5) building layout design strategies are formulated based on key morphological indicators in the regression model. Overall, this study demonstrates the effectiveness of the GAN-based method for urban scale building energy prediction and layout optimization. The proposed GAN-MIGA framework provides practical tools and theoretical support for energy-efficient design, policy formulation, and smart city development, contributing to more sustainable urban energy planning. Full article
(This article belongs to the Special Issue Optimizing Urban Building Energy Analysis and Prediction: Evidence from AI, Big Data, and Machine Learning)
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18 pages, 1081 KB  
Data Descriptor
Controlled Generation of Synthetic Spanish Texts: A Dataset Using LLMs with and Without Contextual Retrieval
by José M. García-Campos, Agustín W. Lara-Romero, Vicente Mayor and Jorge Calvillo-Arbizu
Data 2026, 11(2), 29; https://doi.org/10.3390/data11020029 (registering DOI) - 1 Feb 2026
Abstract
The increasing ability of Large Language Models (LLMs) to generate fluent and coherent text has heightened the need for resources to analyze and detect synthetic content, particularly in Spanish, where the scarcity of datasets hinders the development of reliable detection systems. This work [...] Read more.
The increasing ability of Large Language Models (LLMs) to generate fluent and coherent text has heightened the need for resources to analyze and detect synthetic content, particularly in Spanish, where the scarcity of datasets hinders the development of reliable detection systems. This work presents a Spanish-language dataset of 18,236 synthetic news descriptions generated from real journalistic headlines using a fully reproducible, open-source pipeline. The methodology used to produce the dataset includes both a Retrieval Augmented Generation (RAG) approach, which incorporates contextual information from recent news descriptions, and a NO-RAG approach, which relies solely on the headline. Texts were generated with the instruction-tuned Mistral 7B Instruct model, systematically varying temperature to explore the effect of generation parameters. The dataset includes detailed metadata linking each synthetic description to its source headline, generation settings, and, when applicable, retrieved contextual content. By combining contextual grounding, controlled parameter variation, and source-level traceability, this dataset provides a reproducible and richly annotated resource that supports research in Spanish synthetic text and evaluation of LLM-based generation. Full article
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25 pages, 12028 KB  
Article
Neurotoxic Effects of Acute Tributyltin Exposure in Adult Zebrafish: Behavioral Impairments and Mechanistic Insights
by Qi Zheng, Nan Hong, Lin Liu, Cong Wang, Ruixi Gan, Di Xu and Junsong Wang
Metabolites 2026, 16(2), 105; https://doi.org/10.3390/metabo16020105 (registering DOI) - 1 Feb 2026
Abstract
Background/Objectives: Tributyltin (TBT) remains a persistent aquatic contaminant with documented neurotoxic effects, yet the underlying mechanisms of its neurotoxicity remain poorly understood. Methods: We investigated the comprehensive molecular mechanisms of TBT-induced neurotoxicity in zebrafish (Danio rerio) through an integrated approach combining [...] Read more.
Background/Objectives: Tributyltin (TBT) remains a persistent aquatic contaminant with documented neurotoxic effects, yet the underlying mechanisms of its neurotoxicity remain poorly understood. Methods: We investigated the comprehensive molecular mechanisms of TBT-induced neurotoxicity in zebrafish (Danio rerio) through an integrated approach combining histopathological examination, metabolomics analysis, transcriptional profiling, and behavioral assays. Results: Histopathological analysis revealed significant TBT-induced damage to brain tissue architecture. Metabolomic profiling demonstrated that TBT exposure (500 ng/L) severely disrupted cellular energy metabolism, particularly the TCA cycle and purine/pyrimidine metabolism, while exhibiting hormetic responses at lower concentrations. Transcriptional analysis identified widespread downregulation of SNARE complex proteins and neurotransmitter transporters, indicating comprehensive deterioration of synaptic machinery. Conclusions: These molecular perturbations corresponded with systematic disruption of antioxidant defense mechanisms and neurotransmitter signaling pathways, establishing a direct mechanistic link to observed behavioral deficits. Our findings reveal a hierarchical cascade of molecular disruptions triggered by TBT exposure, bridging the critical gap between metabolic dysregulation and synaptic dysfunction. This mechanistic framework provides fundamental insights into the neurotoxicological impact of this widespread environmental contaminant, highlighting potential therapeutic targets for intervention. Full article
(This article belongs to the Section Environmental Metabolomics)
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11 pages, 859 KB  
Article
Diagnostic Utility of Synovial Cell Count Prior to Revision Compared to Re-Revision Arthroplasty
by Jennifer Straub, Paul M. Schwarz, Laurenz Willmann, Joachim Ortmayr, Kevin Staats, Irene K. Sigmund, Reinhard Windhager and Christoph Böhler
Antibiotics 2026, 15(2), 143; https://doi.org/10.3390/antibiotics15020143 (registering DOI) - 1 Feb 2026
Abstract
Background/Objectives: The aim of this study is to investigate how the joint, the number and the type of prior revision surgeries influence the diagnostic thresholds for synovial cell count for patients who undergo their first total hip or knee arthroplasty revision compared [...] Read more.
Background/Objectives: The aim of this study is to investigate how the joint, the number and the type of prior revision surgeries influence the diagnostic thresholds for synovial cell count for patients who undergo their first total hip or knee arthroplasty revision compared to re-revisions, as different cutoffs might substantially influence treatment courses. Methods: In this retrospective single-center register analysis, data from 214 revised THAs (total hip arthroplasties) and TKAs (total knee arthroplasties) were collected, of which 103 (48.1%) have so far undergone at least one revision surgery. Diagnosis was based on the EBJIS criteria, and we identified 163 (76.2%) septic and 51 (23.8%) aseptic cases. Data on synovial cell count were collected and analyzed for their diagnostic accuracy and optimal cutoffs. For re-revisions, a covariate-adjusted ROC (receiver operating characteristic) for the joint, type of previous surgery and number of surgeries was created. Results: We found no significant differences in cell counts between patients before first revision compared to those undergoing re-revision for septic (p = 0.40) and aseptic indications (p = 0.84). The overall diagnostic accuracy was high for all re-revision cases, with a sensitivity of 0.86, specificity of 0.91, AUC (area under the curve) of 0.92, at an optimal cutoff value of 2439.50 G/L. As for re-revised hip joints, the optimal cutoffs were higher compared to knee joints (2439.5 G/L vs. 2626.5 G/L, hip AUC = 0.90, knee AUC = 0.93, p = 0.14). Furthermore, the AUCs for cell count differed significantly depending on the type of previous surgery in re-revision (p = 0.03). The covariate-adjusted analysis showed no significant differences compared to the unadjusted analysis. Conclusions: Cell count remains reliable for diagnosing periprosthetic joint infection in patients with prior revisions, with minor threshold variations from the EBJIS (European Bone and Joint Infection Society) criteria. While the type of preceding revision affects accuracy, the diagnostic value remains consistently high overall. Full article
(This article belongs to the Special Issue Diagnostics and Antibiotic Therapy in Bone and Joint Infections)
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21 pages, 1532 KB  
Review
Thiamine Deficiency in Diabetes: Implications for Diabetic Ketoacidosis
by Mahesh Ramanan and Aashish Kumar
Diabetology 2026, 7(2), 28; https://doi.org/10.3390/diabetology7020028 (registering DOI) - 1 Feb 2026
Abstract
Diabetic ketoacidosis (DKA) remains a life-threatening complication of diabetes mellitus with suboptimal outcomes despite standard management. Emerging evidence suggests that thiamine (vitamin B1) deficiency may play an under-recognized role in DKA pathophysiology and clinical course. This narrative review synthesizes current evidence regarding thiamine [...] Read more.
Diabetic ketoacidosis (DKA) remains a life-threatening complication of diabetes mellitus with suboptimal outcomes despite standard management. Emerging evidence suggests that thiamine (vitamin B1) deficiency may play an under-recognized role in DKA pathophysiology and clinical course. This narrative review synthesizes current evidence regarding thiamine deficiency in diabetes and DKA, examining molecular mechanisms, clinical implications, and the rationale for thiamine supplementation as adjunctive therapy. Thiamine deficiency is highly prevalent in diabetes, with plasma concentrations reduced by approximately 75% compared to healthy controls. In DKA specifically, 25–35% of patients present with thiamine deficiency, which often worsens during insulin therapy. The primary mechanism involves hyperglycemia-induced downregulation of renal thiamine transporters (THTR-1 and THTR-2), resulting in 16–24-fold increased renal clearance and massive urinary losses. Thiamine pyrophosphate serves as an essential cofactor for three critical enzymes in glucose metabolism: pyruvate dehydrogenase, α-ketoglutarate dehydrogenase, and transketolase. Deficiency impairs these pathways, causing pyruvate accumulation with conversion to lactate (resulting in lactic acidosis), compromised TCA cycle function (reducing ATP production by 40–48%), and decreased NADPH generation (increasing oxidative stress). Clinical manifestations include persistent metabolic acidosis despite standard therapy, myocardial dysfunction with elevated cardiac biomarkers, neurological impairment, and prolonged recovery times. Cellular studies demonstrate that thiamine supplementation significantly improves mitochondrial oxygen consumption in DKA patients. The high prevalence of thiamine deficiency in DKA, compelling biochemical rationale, excellent safety profile, and preliminary mechanistic evidence support the urgent need for large-scale randomized controlled trials examining thiamine supplementation to definitively establish efficacy, optimal dosing, and patient selection criteria. Full article
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11 pages, 1038 KB  
Data Descriptor
Refined IDRiD: An Enhanced Dataset for Diabetic Retinopathy Segmentation with Expert-Validated Annotations and Comprehensive Anatomical Context
by Sakon Chankhachon, Supaporn Kansomkeat, Patama Bhurayanontachai and Sathit Intajag
Data 2026, 11(2), 30; https://doi.org/10.3390/data11020030 (registering DOI) - 1 Feb 2026
Abstract
The Indian Diabetic Retinopathy Image Dataset (IDRiD) has been widely adopted for DR lesion segmentation research. However, it contains annotation gaps for proliferative DR lesions and labeling errors that limit its utility for comprehensive automated screening systems. We present Refined IDRiD, an enhanced [...] Read more.
The Indian Diabetic Retinopathy Image Dataset (IDRiD) has been widely adopted for DR lesion segmentation research. However, it contains annotation gaps for proliferative DR lesions and labeling errors that limit its utility for comprehensive automated screening systems. We present Refined IDRiD, an enhanced version that addresses these limitations through (1) expert ophthalmologist validation and correction of labeling errors in original annotations for four non-proliferative lesions (microaneurysms, hemorrhages, hard exudates, cotton-wool spots), (2) the addition of three critical proliferative DR lesion annotations (neovascularization, vitreous hemorrhage, intraretinal microvascular abnormalities), and (3) the integration of comprehensive anatomical context (optic disc, fovea, blood vessels, retinal region). A team of three ophthalmologists (one senior specialist with >10 years’ experience, two expert fundus image annotators) conducted systematic annotation refinement, achieving an inter-rater agreement F1-score of 0.9012. The enhanced dataset comprises 81 high-resolution fundus images with pixel-level annotations for seven DR lesion types and four anatomical structures. All images were cropped to the retinal region of interest and resized to 1024 × 1024 pixels, with annotations stored as unified grayscale masks containing 12 classes enabling efficient multi-task learning. Refined IDRiD enables training of comprehensive DR screening systems capable of detecting both non-proliferative and proliferative stages while reducing false positives through anatomical context awareness. Full article
(This article belongs to the Section Computational Biology, Bioinformatics, and Biomedical Data Science)
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10 pages, 257 KB  
Article
Joint Selection for Growth and Leaf Color in Superior Trees of Sapium discolor in Fujian Province, China
by Yanghui Fang, Xuemei Wang, Liang Fang, Jie Guo, Wenping Chen, Wei Wu, Tong Wang, Zhixian Luo, Xun Lin, Daiquan Ye, Xiaochou Chen and Shunde Su
Plants 2026, 15(3), 452; https://doi.org/10.3390/plants15030452 (registering DOI) - 1 Feb 2026
Abstract
Sapium discolor is a valuable native species in southern China, valued for its rapid growth and vibrant foliage, and widely used in ecological restoration and landscaping. To identify superior propagation materials with fast growth and red leaves, regional open-pollinated progeny trials of 10 [...] Read more.
Sapium discolor is a valuable native species in southern China, valued for its rapid growth and vibrant foliage, and widely used in ecological restoration and landscaping. To identify superior propagation materials with fast growth and red leaves, regional open-pollinated progeny trials of 10 elite trees were established in Nanping, Sanming, and Zhangzhou (Fujian Province) in 2015. Growth (tree height and diameter) was monitored from 2015 to 2023, and leaf color (the proportion of red in leaf color) was assessed in 2024. The species showed early fast growth, with mean tree height and diameter at breast height (DBH) reaching 7.98 m and 9.99 cm at six years, then slowing. Family-level phenotypic variation was limited. ANOVA revealed highly significant differences among families for growth traits from 2016 onward and for leaf color in 2024. Broad-sense heritability was moderate for 2023 tree height (0.3839), DBH (0.1879), and 2024 leaf color (0.2102), with low narrow-sense heritability, indicating non-additive genetic effects. Clonal selection based on genotypic values achieved notable genetic gains, especially for growth. One superior clone combined improvements in height (13.1%), diameter (10.1%), and red coloration (8.3%). These results highlight the value of clonal selection and the need to consider genotype × environment interactions in breeding programs. Full article
(This article belongs to the Special Issue Advances in Dendrological Research: Celebrating the 40th Anniversary of the Dendrology Branch of the Chinese Society of Forestry)
10 pages, 822 KB  
Article
Echocardiographic Red Flags in Wild-Type Transthyretin Amyloidosis: Sex-Specific Gaps for Wall Thickness and Left Ventricular Mass
by Emilio Nardi, Carola Maria Gagliardo, Davide Noto, Carlo Maria Barbagallo, Antonina Giammanco, Gianluca Di Rosa, Federica Bellini, Maurizio Averna and Angelo Baldassare Cefalù
Life 2026, 16(2), 237; https://doi.org/10.3390/life16020237 (registering DOI) - 1 Feb 2026
Abstract
Background: Wild-type transthyretin amyloidosis (ATTRwt) diagnosis remains challenging. Echocardiographic “red flags” play a significant role in raising diagnostic suspicion. Methods: Retrospective study including 33 patients diagnosed with ATTRwt. All patients underwent comprehensive echocardiographic evaluation focusing on the red flags for ATTRwt. Left ventricular [...] Read more.
Background: Wild-type transthyretin amyloidosis (ATTRwt) diagnosis remains challenging. Echocardiographic “red flags” play a significant role in raising diagnostic suspicion. Methods: Retrospective study including 33 patients diagnosed with ATTRwt. All patients underwent comprehensive echocardiographic evaluation focusing on the red flags for ATTRwt. Left ventricular hypertrophy (LVH) was defined as interventricular septal wall thickness (IVST) ≥ 12 mm and/or LV mass indexed for body surface area (LVMI) ≥ 115 g/m2 in men and ≥ 95 g/m2 in women. Results: Relative wall thickness > 0.42 and early diastolic myocardial velocity < 7 cm/s were detected in 100% of patients. Severe diastolic dysfunction (grade ≥ 3) (72.7%), apical sparing (36.4%), granular sparkling pattern (30.3%), and pericardial effusion (39.4%) were also observed. Females were younger than males (median age 68 vs. 74.5 years), and IVST ≥ 12 mm was lower in females than in males (64.4% vs. 100%, respectively, p < 0.05). The combined criterion of IVST ≥ 12 mm in men and LVMI ≥ 95 g/m2 in women was encountered in 100% of the global cohort. Conclusions: IVST is a good predictor of LVH in males but shows limited sensitivity for ATTRwt in females; a gender-differenced approach (IVST for men and LVMI for women) might better stratify for ATTRwt suspicion. Full article
(This article belongs to the Section Medical Research)
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28 pages, 456 KB  
Article
Student-Faculty Partnerships in Mathematics Undergraduate Coursework
by Alyssa G. Cavazos, Luis Miguel Fernández, Isabel del Rosario Amaro, Elianna Olivo and Cristina Villalobos
Educ. Sci. 2026, 16(2), 215; https://doi.org/10.3390/educsci16020215 (registering DOI) - 1 Feb 2026
Abstract
This study examines how student–faculty partnerships are experienced within undergraduate mathematics coursework at a majority Hispanic Serving Institution (HSI). Drawing on the Student as Partners (SaP) theoretical framework and using an interpretive phenomenological research design, we examined the lived experiences of student and [...] Read more.
This study examines how student–faculty partnerships are experienced within undergraduate mathematics coursework at a majority Hispanic Serving Institution (HSI). Drawing on the Student as Partners (SaP) theoretical framework and using an interpretive phenomenological research design, we examined the lived experiences of student and faculty partners who participated in a series of professional development sessions on student-faculty partnerships and equitable teaching and learning practices in mathematics courses. Findings indicate that student partners’ lived experiences in the partnership program contributed to the development of sense of belonging, self-efficacy, and awareness of the need to link real-world and culturally responsive applications to mathematics learning. On the part of the faculty partners, findings indicate that their lived experiences in the student-faculty partnership program contributed to enhanced self-efficacy through professional growth, development of new perspectives on teaching, and awareness of fostering culturally responsive teaching and learning experiences. The study highlights the transformative potential of student-faculty partnerships in bridging traditional mathematics instruction with students’ lived learning experiences and perspectives on fostering real-world, reflective, and student-centered learning environments for all students. Specifically, the study showcases the promise of partnership models in mathematics settings and points to the need for future research on scalable approaches that support the success of culturally and linguistically diverse students in STEM. Full article
(This article belongs to the Special Issue Cross-Cultural Education: Building Bridges and Breaking Barriers)
26 pages, 1080 KB  
Review
Peripartum Depression as a Heart–Brain–Endocrine–Immune Syndrome: Neuroendocrine, Cardiovascular, and Inflammatory Pathways Underlying Maternal Vulnerability
by Giuseppe Marano and Marianna Mazza
Life 2026, 16(2), 236; https://doi.org/10.3390/life16020236 (registering DOI) - 1 Feb 2026
Abstract
Peripartum depression (PPD) represents one of the most prevalent and disabling psychiatric conditions among women, yet its underlying biology remains poorly integrated across medical disciplines. Emerging evidence highlights PPD as a prototypical disorder of the heart–brain axis, where neuroendocrine changes, immune activation, and [...] Read more.
Peripartum depression (PPD) represents one of the most prevalent and disabling psychiatric conditions among women, yet its underlying biology remains poorly integrated across medical disciplines. Emerging evidence highlights PPD as a prototypical disorder of the heart–brain axis, where neuroendocrine changes, immune activation, and cardiovascular dysregulation converge to shape maternal vulnerability. During pregnancy and the postpartum period, abrupt fluctuations in estrogen, progesterone (P4), and placental corticotropin-releasing hormone (CRH) interact with a sensitized hypothalamic–pituitary–adrenal (HPA) axis, altering neural circuits involved in mood regulation, stress reactivity, and maternal behavior. Parallel cardiovascular adaptations, including endothelial dysfunction, altered blood pressure variability, and reduced heart rate variability (HRV), suggest a profound perturbation of autonomic balance with potential long-term implications for maternal cardiovascular health. Neuroinflammation, microglial activation, and systemic cytokine release further mediate the bidirectional communication between the heart and the brain, linking emotional dysregulation with vascular and autonomic instability. Evidence also indicates that conditions such as preeclampsia and peripartum cardiomyopathy share biological pathways with PPD, reinforcing the concept of a unified pathophysiological axis. This review synthesizes current knowledge on the neurobiological, cardiovascular, endocrine, and inflammatory mechanisms connecting PPD to maternal heart–brain health, while discussing emerging biomarkers and therapeutic strategies aimed at restoring integrative physiology. Understanding PPD as a multisystem heart–brain disorder offers a transformative perspective for early detection, risk stratification, and personalized intervention during one of the most biologically vulnerable periods of a woman’s life. Full article
(This article belongs to the Section Reproductive and Developmental Biology)
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17 pages, 427 KB  
Article
From Dropout to Classroom: The Role of Mexico’s PROGRESA Education Grants in Reenrollment
by Nieves Valdés
Educ. Sci. 2026, 16(2), 216; https://doi.org/10.3390/educsci16020216 (registering DOI) - 1 Feb 2026
Abstract
School dropout remains a persistent challenge in developing countries, undermining human capital accumulation and long-term economic development. This paper examines the extent to which Mexico’s PROGRESA conditional cash transfer program influenced school enrollment and reenrollment decisions by analyzing post-program panel data with a [...] Read more.
School dropout remains a persistent challenge in developing countries, undermining human capital accumulation and long-term economic development. This paper examines the extent to which Mexico’s PROGRESA conditional cash transfer program influenced school enrollment and reenrollment decisions by analyzing post-program panel data with a Correlated Random Effects probit model. Results indicate that PROGRESA grants significantly increased school enrollment among girls, with the strongest gains observed at the secondary level. Reenrollment effects for girls were positive only when household childcare responsibilities were limited or when secondary schools were located nearby, highlighting the influence of family and community constraints. In contrast, boys exhibited no consistent response in either enrollment or reenrollment outcomes. These findings indicate that although conditional cash transfers can reduce educational inequality, their lasting developmental impact relies on complementary measures—such as childcare provision and improved school access—that mitigate structural barriers to reenrollment and reinforce the connection between education and inclusive growth. Full article
(This article belongs to the Special Issue Economics of Education and Prospective Developments in Higher Education)
10 pages, 486 KB  
Article
Impact of Preexisting Diabetes on Activities of Daily Living Independence at Hospital Discharge in Critically Ill Patients: A Prospective Cohort Study
by Shinichi Watanabe, Kota Yamauchi, Yuji Naito, Ayato Shinohara, Yasunari Morita, Yuki Iida and from the RELIFE Network
Diabetology 2026, 7(2), 27; https://doi.org/10.3390/diabetology7020027 (registering DOI) - 1 Feb 2026
Abstract
Background: Diabetes mellitus is known to affect the prognosis of critically ill patients; however, its impact on independence in activities of daily living (ADL) at hospital dis-charge remains unclear. This study aimed to investigate whether preexisting diabetes is associated with reduced ADL [...] Read more.
Background: Diabetes mellitus is known to affect the prognosis of critically ill patients; however, its impact on independence in activities of daily living (ADL) at hospital dis-charge remains unclear. This study aimed to investigate whether preexisting diabetes is associated with reduced ADL independence at hospital discharge among critically ill patients. Methods: In this prospective cohort study, 423 adult intensive care unit (ICU) patients who were admit-ted for ≥48 h were enrolled and categorized by the presence or absence of diabetes. Primary outcomes included time to achieve walking independence (unassisted walking over 50 m) and the Barthel Index at discharge. Secondary outcomes were handgrip strength, ICU length of stay, and highest ICU Mobility Scale (IMS) scores. Multivariable analyses adjusted for age, illness severity, and other confounders. Results: Among the 101 patients with diabetes, time to achieve walking independence at discharge was significantly longer compared to those without diabetes (p = 0.013). The diabetes group also had a lower Barthel Index (p = 0.020), longer ICU stays (p = 0.003), weaker handgrip strength (p = 0.041), and lower maximum IMS scores (p = 0.002). Multivariable analysis confirmed that diabetes was independently associated with reduced ADL independence and poorer physical function at discharge. Conclusions: Preexisting diabetes is an independent predictor of impaired ADL independence in critically ill patients. These findings highlight the importance of early and individualized rehabilitation strategies for patients with diabetes in the ICU. Full article
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14 pages, 802 KB  
Article
Preoperative Soluble AXL in Plasma Predicts Futility of Resecting Pancreatic Ductal Adenocarcinoma
by Thomas Samson, Maral Aali, Darien McBride, Thomas Arnason, Sharon E. Clarke, Ravi Ramjeesingh, Lisette Gonzalez-Chavez, Yara Azizieh, Mark J. Walsh, Scott M. Livingstone, Stephanie E. Hiebert, Jeanette E. Boudreau and Boris L. Gala-Lopez
Curr. Oncol. 2026, 33(2), 88; https://doi.org/10.3390/curroncol33020088 (registering DOI) - 1 Feb 2026
Abstract
Surgical resection combined with chemotherapy offers the best chance of survival in pancreatic ductal adenocarcinoma (PDAC), but many will experience recurrence and early mortality. We examined soluble AXL (sAXL), a blood protein, for its ability to predict 6-month mortality after resection and compared [...] Read more.
Surgical resection combined with chemotherapy offers the best chance of survival in pancreatic ductal adenocarcinoma (PDAC), but many will experience recurrence and early mortality. We examined soluble AXL (sAXL), a blood protein, for its ability to predict 6-month mortality after resection and compared it to CA19-9. Fifty-four patients with PDAC who underwent tumour resection were analyzed to assess biomarker performance and identify optimal cut-off levels. The cut-off for sAXL was 40.26 ng/mL (sensitivity 0.729; specificity 0.643), while it 253.3 U/mL for CA19-9 (sensitivity 0.591; specificity 0.621). Patients with sAXL > 40.26 ng/mL had a non-significant trend toward worse survival (log-rank p = 0.088). Univariate Cox regression revealed that high tumour grade (3 + 4) and positive resection margin significantly predicted early mortality. Multivariate Cox regression showed that sAXL > 40.26 ng/mL remained associated with 6-month mortality (hazard ratio 2.42, bootstrap 95% CI 1.15–5.65, p = 0.020), independent of high tumour grade (hazard ratio 4.02, bootstrap 95% CI 1.68–13.2, p = 0.002). These findings suggest that a preoperative blood test (sAXL) has utility for predicting futile surgery beyond the current standard, CA19-9, and can be incorporated into larger models to assist in risk stratification and follow-up planning. Full article
(This article belongs to the Special Issue Surgical Advances in the Management of Gastrointestinal Cancers)
23 pages, 5361 KB  
Article
Rheology and Stability of Tunicate Cellulose Nanocrystal-Based Pickering Emulsions: Role of pH, Concentration, and Emulsification Method
by Sumana Majumder, Matthew J. Dunlop, Bishnu Acharya and Supratim Ghosh
Foods 2026, 15(3), 509; https://doi.org/10.3390/foods15030509 (registering DOI) - 1 Feb 2026
Abstract
Tunicate (marine invertebrates)-derived cellulose nanocrystals (T-CNC) possess unique structural and physicochemical properties compared to other wood-based CNCs. This study aimed to characterize and utilize T-CNC as a stabilizer in Pickering emulsion (PE), highlighting a sustainable alternative to conventional surfactant-based emulsifiers. Characterization of T-CNC [...] Read more.
Tunicate (marine invertebrates)-derived cellulose nanocrystals (T-CNC) possess unique structural and physicochemical properties compared to other wood-based CNCs. This study aimed to characterize and utilize T-CNC as a stabilizer in Pickering emulsion (PE), highlighting a sustainable alternative to conventional surfactant-based emulsifiers. Characterization of T-CNC revealed a rod-shaped morphology with dimensions of 1694 ± 925 nm in length and 13 ± 3 nm in width, resulting in an aspect ratio of 122 ± 45, and high crystallinity (87.6%). Its zeta potential ranged from −4.4 to −45.5 mV across pH 2–10 and contact angles <50° indicate strong water wettability. T-CNC at 0.2%, 0.3%, and 0.4% (w/w) at pH 3 and 5 was used to prepare 20 wt% oil-in-water PE using a high-shear homogenizer followed by ultrasonication. Ultrasonication significantly improved the emulsion stability compared to only high-shear homogenization, decreasing droplet size by 31.4–50.8% and 55.7–89.3% for pH 3 and pH 5, respectively. PEs developed at pH 3 demonstrated smaller droplet sizes, better stability with minimal coalescence after 7 days, and enhanced gel-like rheological behaviour compared to PEs at pH 5, which displayed flocculation and coalescence. The gel strength of the pH 3 PEs increased with T-CNC concentration, as evidenced by progressively denser droplet packing, consistent with stronger interfacial anchoring (higher detachment energy) and reduced coalescence. This study underscores T-CNC’s superior efficiency in stabilizing PEs at low concentrations, offering a green, high-performance solution for food, cosmetic, and pharmaceutical applications. Full article
(This article belongs to the Special Issue Novel Pickering Emulsions in Foods: Potential Applications and Recent Advances)
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26 pages, 13963 KB  
Article
Deciphering Drought Response Mechanisms in Oat Through Comprehensive Transcriptomic and Physiological Analysis
by Baiji Wang, Hang Yin, Xinyi Zhang, Xiangpeng Kong, Wenjie Zhao, Rui Qiu, Muzhapaer Tuluhong, Guowen Cui and Bing Li
Plants 2026, 15(3), 453; https://doi.org/10.3390/plants15030453 (registering DOI) - 1 Feb 2026
Abstract
Oat, an important cereal and forage crop, is significantly affected by drought stress during production. However, the molecular mechanisms underlying oat’s response to drought stress remain largely unknown. In this study, K-means clustering classified 28 oat varieties into drought-tolerant (Muda, Mengshi No. 1) [...] Read more.
Oat, an important cereal and forage crop, is significantly affected by drought stress during production. However, the molecular mechanisms underlying oat’s response to drought stress remain largely unknown. In this study, K-means clustering classified 28 oat varieties into drought-tolerant (Muda, Mengshi No. 1) and drought-sensitive (Heike, Haywire) groups, with grey relational analysis further verifying MS as the most drought-tolerant and HK as the most drought-sensitive variety. Under drought stress, drought-tolerant and drought-sensitive varieties showed notable differences in leaf chlorophyll content, osmoregulation substances, and the activities of antioxidant enzymes. Transcriptomic analysis showed that 1915 differentially expressed genes (DEGs) were shared among all comparisons between treatment groups and the control group. KEGG pathway analysis revealed enrichment in pathways such as plant–pathogen interactions, plant hormone signal transduction, and starch and sucrose metabolism. In the signal transduction of plant hormones, eight PP2C genes associated with ABA signaling were increased, indicating that oats might respond to drought by enhancing metabolic activities via the ABA signaling pathway. WGCNA identified gene modules significantly associated with physiological traits. Notably, Mantel tests revealed that six core genes exhibited a positive correlation with CAT activity in the drought-tolerant variety, while showing an opposite trend in the sensitive variety. This study provides insights into the mechanisms of drought tolerance in oats and aids in the molecular breeding of drought-tolerant varieties. Full article
(This article belongs to the Section Crop Physiology and Crop Production)
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15 pages, 450 KB  
Review
Mechanisms Linking Oxidative Stress and Sarcopenia in Cardiovascular Diseases: A Scoping Review
by Sabina Krupa-Nurcek, Tomasz Semań, Mateusz Szczupak, Jacek Kobak, Wioletta Mędrzycka-Dąbrowska and Kazimierz Widenka
Antioxidants 2026, 15(2), 184; https://doi.org/10.3390/antiox15020184 (registering DOI) - 1 Feb 2026
Abstract
Oxidative stress and sarcopenia are increasingly perceived as interdependent processes that significantly affect the course of cardiovascular diseases. Excessive production of reactive oxygen species leads to muscle cell damage, mitochondrial disorders, and chronic inflammation, which promote progressive loss of muscle mass and function. [...] Read more.
Oxidative stress and sarcopenia are increasingly perceived as interdependent processes that significantly affect the course of cardiovascular diseases. Excessive production of reactive oxygen species leads to muscle cell damage, mitochondrial disorders, and chronic inflammation, which promote progressive loss of muscle mass and function. Methods: The aim of the study was to analyze the mechanisms linking oxidative stress and sarcopenia in the course of cardiovascular diseases. Our scoping review initially identified 854 articles, of which 3 were ultimately included in the review (after removing duplicates (n = 118), 736 articles remained; after re-screening the articles according to the inclusion and exclusion criteria (n = 302), 434 articles remained; 196 publications lacked full text and were excluded, leaving 238 articles). Results: An examination of the available literature indicates a potential association between increased oxidative stress and the possible development of sarcopenia in individuals with cardiovascular diseases. The studies identified in this review suggest that elevated levels of reactive oxygen species, together with reduced antioxidant capacity, may contribute to muscle fiber damage, mitochondrial disturbances, and the activation of chronic inflammatory processes, which could in turn be involved in the accelerated decline of muscle mass and strength. Conclusions: These results confirm that oxidative stress is a key pathophysiological element linking both disease entities and may be an important target of therapeutic interventions. Full article
(This article belongs to the Section Health Outcomes of Antioxidants and Oxidative Stress)
14 pages, 310 KB  
Article
Cytokine Dynamics in Severe COVID-19 vs. Influenza A Elderly Patients: A Prospective Comparative Study
by Mihai Aronel Rus, Adina Huțanu, Daniel Corneliu Leucuța, Violeta Tincuța Briciu, Monica Iuliana Muntean, Angela Ionică and Mihaela Sorina Lupșe
Int. J. Mol. Sci. 2026, 27(3), 1463; https://doi.org/10.3390/ijms27031463 (registering DOI) - 1 Feb 2026
Abstract
COVID-19 and influenza A (FluA) cause severe respiratory infections in elderly patients, with cytokine dysregulation playing a central role. Direct comparative data in older adults remains limited. We aimed to characterize cytokine dynamics and their prognostic value in hospitalized elderly patients with COVID-19 [...] Read more.
COVID-19 and influenza A (FluA) cause severe respiratory infections in elderly patients, with cytokine dysregulation playing a central role. Direct comparative data in older adults remains limited. We aimed to characterize cytokine dynamics and their prognostic value in hospitalized elderly patients with COVID-19 vs. FluA. We performed a prospective cohort study including adults ≥ 60 years hospitalized with respiratory failure due to COVID-19 or FluA between March 2023 and March 2024. Serum IL-1β, IL-6, IL-10, IL-17A, IL-34, MCP-1, and CXCL10 were measured on Day 1 and Day 5 of hospitalization using Luminex®. Cytokines and associations with non-invasive ventilation (NIV) were assessed by ROC analysis and multivariate logistic regression. 83 patients were included (39 COVID-19, median age 79 years; 44 FluA, median 77 years). At Day 1, COVID-19 exhibited significantly higher IL-6, IL-10, and CXCL10; FluA showed an attenuated cytokine response. At Day 5, cytokines declined in both groups. Baseline IL-6 independently predicted NIV (adjusted OR 3.02), whereas higher MCP-1 was associated with reduced NIV requirement. Early cytokine differences between COVID-19 and FluA are evident in elderly patients, but values converged by Day 5. IL-6 remains an informative early predictor of respiratory deterioration; MCP-1 may reflect a regulated innate response. Full article
(This article belongs to the Special Issue Molecular Research and Insights into COVID-19: Third Edition)
24 pages, 3201 KB  
Article
Decoding the Molecular Drivers of Epithelial to Mesenchymal Transition in Breast Cancer: Insights into Epithelial Plasticity and Microenvironment Crosstalk
by Emanuela Peri, Miriam Buttacavoli, Elena Roz, Ida Pucci-Minafra, Salvatore Feo and Patrizia Cancemi
Biology 2026, 15(3), 265; https://doi.org/10.3390/biology15030265 (registering DOI) - 1 Feb 2026
Abstract
‡ Current address: Department of Biomedicine, Neuroscience and Advanced Diagnostics (BIND), University of Palermo, 90127 Palermo, Italy [...] Full article
(This article belongs to the Special Issue Advances in Biological Breast Cancer Research (2nd Edition))
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