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16 pages, 476 KB

Open AccessArticle

Growing Nutrition on Waste: Exploring Pleurotus columbinus as a Sustainable Functional Food

by Marianna Dedousi, Chrysavgi Gardeli, Milena Pantić, Gordana Krstić, Vladimir Dobričić, Seraphim Papanikolaou and Panagiota Diamantopoulou

Appl. Sci. 2026, 16(3), 1548; https://doi.org/10.3390/app16031548 (registering DOI) - 3 Feb 2026

Abstract

The present study investigated the cultivation of Pleurotus columbinus on alternative substrates derived from spent mushroom substrate combined with spent coffee grounds or wheat straw, with or without supplementation with wheat bran and soybean flour, in comparison to conventional wheat straw. All substrates [...] Read more.

The present study investigated the cultivation of Pleurotus columbinus on alternative substrates derived from spent mushroom substrate combined with spent coffee grounds or wheat straw, with or without supplementation with wheat bran and soybean flour, in comparison to conventional wheat straw. All substrates were evaluated for their effects on the nutritional composition, amino acid profile, lipid, carbohydrate contents and bioactive compounds of the harvested carposomes. Protein content ranged from 15.6 to 21.4% w/w. Methionine was identified as the first limiting amino acid and the essential amino acid index was up to 60.9%. Carbohydrate content exceeded 63.3% w/w in all samples, with glucose identified as the major monosaccharide. Lipid content was low (1.7–3.4% w/w), with polyunsaturated fatty acids predominating. Ash content ranged from 5.7 to 6.3% w/w and the energy value varied between 36.2 and 37.1 kcal/100 g f.w. Bioactive compounds, including β-glucans (35.9–44.4% w/w) and ergosterol (3.3–4.7 mg/g d.w.), along with their metabolites, were successfully quantified. Non-supplemented substrates enhanced β-glucan levels; most of them were further isolated, whereas lovastatin was not detected in any sample. Overall, P. columbinus cultivated on alternative substrates exhibited improved nutritional quality and higher bioactive compound content compared to conventional cultivation, demonstrating the potential of agro-industrial by-products as sustainable substrates for high-value mushroom production. Full article

(This article belongs to the Special Issue Sustainable Recovery of Bioactive Compounds from Food Industry By-Products)

21 pages, 3922 KB

Open AccessArticle

From Acute Stress to Long-Term Dysregulation: Changes in Hematological and Hormonal Parameters in the Long-Term Post-Stress Period in a Modified SPS&S Model

by Darya I. Gonchar, Tatiana A. Shmigol, Dmitri N. Lyakhmun, Aleksandra E. Soloveva, Svetlana K. Yankovskaya, Olga V. Krendeleva, Veriko D. Vizgalina, Ekaterina V. Efimova, Aiarpi A. Ezdoglian, Nina M. Kiseleva and Vadim V. Negrebetsky

Biomedicines 2026, 14(2), 356; https://doi.org/10.3390/biomedicines14020356 (registering DOI) - 3 Feb 2026

Abstract

Objectives: Existing animal models of post-traumatic stress disorder (PTSD) are often methodologically complex and produce variable outcomes. The aim of this study was to develop a modified PTSD model that accurately recapitulates the clinical progression of the disorder, incorporating both behavioral features [...] Read more.

Objectives: Existing animal models of post-traumatic stress disorder (PTSD) are often methodologically complex and produce variable outcomes. The aim of this study was to develop a modified PTSD model that accurately recapitulates the clinical progression of the disorder, incorporating both behavioral features and objective physiological parameters. Methods: We utilized a modified Single Prolonged Stress with Subsequent Stress (SPS&S) protocol, supplemented by a stress reminder phase (without re-exposure to primary stressors) and an evaluation of stress response extinction. Eighty male Wistar rats were subjected to the stress protocol, followed by comprehensive behavioral, hematological (leukocytes, hemoglobin, and hematocrit), and hormonal (corticosterone; adrenocorticotropic hormone (ACTH)) assessments 4–5 weeks post-stress. Results: The model produced a PTSD-like phenotype in 25% of animals, characterized by persistent alterations in the investigated biomarkers. The PTSD group exhibited sustained behavioral impairments (increased anxiety), hematological changes (neutrophilic leukocytosis), and endocrine dysregulation (decreased corticosterone, ACTH, and epinephrine). Conclusions: This modified SPS&S model demonstrates validity for studying the long-term consequences of stress, with PTSD markers remaining stable throughout the 28-day observation period. Full article

(This article belongs to the Special Issue Neurodevelopmental and Neuropsychiatric Disorders in Animal Models)

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27 pages, 1144 KB

Open AccessArticle

Preference-Aligned Ride-Sharing Repositioning via a Two-Stage Bilevel RLHF Framework

by Ruihan Li and Vaneet Aggarwal

Electronics 2026, 15(3), 669; https://doi.org/10.3390/electronics15030669 (registering DOI) - 3 Feb 2026

Abstract

Vehicle repositioning is essential for improving efficiency and service quality in ride-sharing platforms, yet existing approaches typically optimize proxy rewards that fail to reflect human-centered preferences such as wait time, service coverage, and unnecessary empty travel. We propose the first two-stage Bilevel Reinforcement [...] Read more.

Vehicle repositioning is essential for improving efficiency and service quality in ride-sharing platforms, yet existing approaches typically optimize proxy rewards that fail to reflect human-centered preferences such as wait time, service coverage, and unnecessary empty travel. We propose the first two-stage Bilevel Reinforcement Learning (RL) from Human Feedback (RLHF) framework for preference-aligned vehicle repositioning. In Stage 1, a value-based Deep Q-Network (DQN)-RLHF warm start learns an initial preference-aligned reward model and stable reference policy, mitigating the reward-model drift and cold-start instability that arise when applying on-policy RLHF directly. In Stage 2, a Kullback–Leibler (KL)-regularized Proximal Policy Optimization (PPO)-RLHF algorithm, equipped with action masking, behavioral-cloning anchoring, and alternating forward–reverse KL, fine-tunes the repositioning policy using either Large Language Model (LLM)-generated or rubric-based preference labels. We develop and compare two coordination schemes, pure alternating (PPO-Alternating) and k-step alternating (PPO-k-step), demonstrating that both yield consistent improvements across all tested arrival scales. Empirically, our framework reduces wait time and empty-mile ratio while improving served rate, without inducing trade-offs or reducing platform profit. These results show that human preference alignment can be stably and effectively incorporated into large-scale ride-sharing repositioning. Full article

(This article belongs to the Special Issue Advanced Applications of Multi-Agent Systems and Intelligent Control Technologies)

11 pages, 1145 KB

Open AccessArticle

Enhancing Vaccine Immunogenicity of H9N2 Influenza HA by Locking Its Pre-Fusion Conformation via Cleavage Site Engineering

by Xiaoyu Xu, Weihuan Shao, Kehui Zhang, Meimei Wang, Mingqing Wu, Yixiang Wang, Guanlong Xu, Zhaofei Wang, Yuqiang Cheng, Heng’an Wang, Yaxian Yan, Jingjiao Ma and Jianhe Sun

Vet. Sci. 2026, 13(2), 147; https://doi.org/10.3390/vetsci13020147 (registering DOI) - 3 Feb 2026

Abstract

Avian influenza (AI) significantly threatens poultry health and causes major economic losses in the poultry industry. Vaccination remains crucial for AI prevention and control. The major protective epitopes of influenza viruses are located on hemagglutinin (HA), a surface glycoprotein essential for viral infection. [...] Read more.

Avian influenza (AI) significantly threatens poultry health and causes major economic losses in the poultry industry. Vaccination remains crucial for AI prevention and control. The major protective epitopes of influenza viruses are located on hemagglutinin (HA), a surface glycoprotein essential for viral infection. Most influenza vaccines induce neutralizing antibodies against HA to block viral entry. HA maturation requires the HA0 precursor to be proteolytically cleaved at a conserved site by host proteases to yield HA1 and HA2 subunits. A subsequent acidic condition triggers HA conformational changes, enabling viral–host membrane fusion. However, whether HA conformational variations affect immunogenicity remains unclear. In this study, the cleavage site of the HA gene from an H9N2 avian influenza virus was modified to block the proteolytic cleavage of the HA protein. Our results revealed distinct proteolytic patterns of certain mutants, which exhibited either increased or decreased cleavage efficiencies compared to the wild-type (WT) HA. However, none of the mutants exhibited completely abolished HA0 cleavage. To assess the immunogenicity of these variants, BALB/c mice were immunized with DNA vaccines expressing either WT or mutant HA proteins. Strikingly, the mutant HA protein with a 19-amino-acid deletion Dlt5 (P6~P1, P1’~P′13) at the cleavage site exhibited reduced cleavage efficiency and induced significantly higher HI antibody titers compared to the WT. These results offer valuable perspectives for enhancing avian influenza vaccine efficacy through strategic modification of HA cleavage properties. Full article

(This article belongs to the Special Issue Veterinary Microbial Infectious Diseases in the One Health Era: Pathogenesis, Antimicrobial Resistance, and Innovative Control Strategies in Zoonoses)

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18 pages, 1490 KB

Open AccessArticle

Closing the Nutrient Loop Through Multi-Cycle Phototrophic Reuse of Landfill Leachate in Cyanobacterial PHB Bioproduction

by Antonio Zuorro, Jessica Ximena Pedreros-Sánchez, Roberto Lavecchia, Maria D. Ortiz-Alvarez, Janet B. García-Martínez and Andrés F. Barajas-Solano

Water 2026, 18(3), 394; https://doi.org/10.3390/w18030394 (registering DOI) - 3 Feb 2026

Abstract

This study investigated a phototrophic approach to close nutrient loops by using landfill leachate as a culture medium to produce biomass and polyhydroxybutyrate (PHB) from a thermotolerant strain of Potamosiphon sp. A multi-cycle reuse scheme in which post-culture leachate was partially replenished with [...] Read more.

This study investigated a phototrophic approach to close nutrient loops by using landfill leachate as a culture medium to produce biomass and polyhydroxybutyrate (PHB) from a thermotolerant strain of Potamosiphon sp. A multi-cycle reuse scheme in which post-culture leachate was partially replenished with fresh leachate and reused in successive cultivation rounds to increase the biomass concentration (g/L) and the intracellular PHB content (% w/w) was tested. Three operational variables were optimized (leachate replenishment percentage, number of reuse cycles, and sanitation method (autoclaving, UV irradiation, or no treatment)) via the Box–Behnken response surface method. Both response variables were modeled with high predictive accuracy (R² = 0.98 for biomass and R² = 1.00 for PHB content). According to the experimental data, leachate replenishment emerged as the key factor influencing nutrient availability—particularly nitrogen and phosphorus—and thus PHB accumulation. The optimized conditions (2.17% v/v fresh leachate, three reuse cycles, and UV sanitation) yielded predicted values of 0.29 g/L biomass and 3.48% w/w PHB. These results demonstrate the feasibility of a controlled multicycle reuse process that integrates effluent treatment and biopolymer synthesis, offering a low-input, circular biotechnological approach for sustainable leachate valorization. Full article

(This article belongs to the Section Wastewater Treatment and Reuse)

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12 pages, 1195 KB

Open AccessSystematic Review

Nonlinear Microscopy of ECM Remodeling in Renal and Vascular Tissues: A Systematic Review Integrating Human AVF Imaging

by Viltė Gabrielė Samsonė, Danielius Samsonas, Laurynas Rimševičius, Mykolas Mačiulis, Elena Osteikaitė, Birutė Vaišnytė, Edvardas Žurauskas, Virginijus Barzda and Marius Miglinas

Medicina 2026, 62(2), 317; https://doi.org/10.3390/medicina62020317 (registering DOI) - 3 Feb 2026

Abstract

Background and Objectives: Extracellular matrix (ECM) and collagen remodeling contribute to chronic kidney disease (CKD) progression and vascular access dysfunction. Conventional histological techniques rely on staining and provide limited sensitivity for detecting early or subtle ECM alterations. Nonlinear optical imaging modalities, including second-harmonic [...] Read more.

Background and Objectives: Extracellular matrix (ECM) and collagen remodeling contribute to chronic kidney disease (CKD) progression and vascular access dysfunction. Conventional histological techniques rely on staining and provide limited sensitivity for detecting early or subtle ECM alterations. Nonlinear optical imaging modalities, including second-harmonic generation (SHG), third-harmonic generation (THG), and multiphoton fluorescence (MPF) microscopy, enable label-free, high-resolution visualization of fibrillar collagen and may offer additional structural information. This study aimed to evaluate the added value of nonlinear imaging beyond conventional histology for assessing ECM remodeling in renal and vascular tissues. Materials and Methods: A systematic literature review was conducted in accordance with the PRISMA 2020 guidelines. PubMed and Web of Science were searched for studies published between 1 January 2015, and 4 April 2025, investigating ECM or collagen remodeling in renal or vascular tissues using SHG, THG, or MPF microscopy. After screening 115 records, 10 studies were included in the qualitative synthesis. In addition, representative SHG, THG, and MPF images of excised human arteriovenous fistula (AVF) tissue were acquired as illustrative feasibility examples to demonstrate the application of these imaging modalities. The use of human tissue was approved by the Vilnius Regional Biomedical Research Ethics Committee (approval No. 2022/6-1443-917). Results: The included studies demonstrated that nonlinear microscopy enables label-free assessment of collagen density, organization, and fiber orientation. SHG imaging differentiated healthy from diseased tissues and has been reported to support fibrosis assessment and staging in preclinical and selected clinical studies and revealed microstructural remodeling patterns not readily detected by conventional histology. The illustrative AVF images demonstrated collagen disorganization consistent with patterns reported in the reviewed literature and are presented solely to demonstrate imaging feasibility, without implying disease phenotype or clinical outcome associations. Conclusions: Nonlinear optical microscopy provides complementary structural information on ECM organization that is not accessible with standard histological techniques. Further validation and methodological standardization are required to support its broader application in clinical nephrology and vascular medicine. Full article

(This article belongs to the Special Issue End-Stage Kidney Disease (ESKD))

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33 pages, 916 KB

Open AccessArticle

Integrating Technology Acceptance, Sustainability Orientation, and Entrepreneurial Orientation: Evidence from Saudi Smallholder Farmers’ Social Media Marketing

by Badrea Al Oraini

Sustainability 2026, 18(3), 1556; https://doi.org/10.3390/su18031556 (registering DOI) - 3 Feb 2026

Abstract

Social media has emerged as a powerful marketing channel for smallholder farmers, reshaping how they engage with consumers through direct online interactions and content sharing, while also facilitating the communication of sustainable agricultural practices. This study investigates social media marketing usage among smallholder [...] Read more.

Social media has emerged as a powerful marketing channel for smallholder farmers, reshaping how they engage with consumers through direct online interactions and content sharing, while also facilitating the communication of sustainable agricultural practices. This study investigates social media marketing usage among smallholder farmers in Saudi Arabia and examines its impact on marketing capabilities through the Technology Acceptance Model (TAM), sustainability orientation (SO), and entrepreneurial orientation (EO). Survey data collected from 300 farmers were analyzed using partial least squares structural equation modeling (PLS-SEM). The results indicate that perceived usefulness (β = 0.195, p < 0.001) and perceived ease of use (β = 0.511, p < 0.001) significantly influence social media marketing usage, with perceived ease of use exerting the strongest influence, while perceived usefulness remains a significant enabler. Social media marketing usage also positively affects sustainability orientation (β = 0.525, p < 0.001) and enhances marketing capabilities both directly and indirectly through sustainability orientation, which acts as a significant mediator. Entrepreneurial orientation further exerts a positive influence on social media usage, marketing capabilities, and financial performance. The model explains 53.6% of the variance in social media marketing usage, 40.3% in marketing capabilities, and 73.5% in financial performance. The study extends TAM by conceptualizing sustainability orientation as a value-creation mechanism through which social media marketing use is transformed into enhanced marketing capabilities, rather than as a mere outcome of digital adoption. The findings offer practical and policy-relevant insights for strengthening digital literacy, sustainability-driven marketing strategies, and agricultural digital infrastructure. Full article

24 pages, 1338 KB

Open AccessReview

Evaluating the Measurement of Heat Stress in a Tropical City: Kolkata, India

by Charles A. Weitz and Barun Mukhopadhyay

Climate 2026, 14(2), 47; https://doi.org/10.3390/cli14020047 (registering DOI) - 3 Feb 2026

Abstract

People living in India are experiencing some of the hottest summers on the planet. Conditions are particularly harsh in Indian cities, like Kolkata, where high temperatures are combined with high humidity. Understanding how conditions in Kolkata have evolved could provide an important addition [...] Read more.

People living in India are experiencing some of the hottest summers on the planet. Conditions are particularly harsh in Indian cities, like Kolkata, where high temperatures are combined with high humidity. Understanding how conditions in Kolkata have evolved could provide an important addition to the growing study of the problems facing megacities in the hot, humid tropics. Yet in Kolkata, this understanding is obscured by different, often incompatible, methods of assessing the intensity of heat stress. This narrative review considers the problems encountered when attempting to develop a clear understanding of past increases or even to quantify current conditions using conventional meteorological or remote sensing data. Rather than trying to arrive at a precise quantification of how much hotter it is now in Kolkata than in the past, we argue for more fine-grained, individual-level understanding of how heat is experienced. An example of this approach is provided by a study that used telemetric devices to continuously monitor the temperature and humidity to which elderly residents of slum areas in Kolkata were exposed during 24h periods as they went about their daily lives. This study indicates that individuals experience a diversity of heat conditions that are inadequately represented by outdoor temperatures. Living in dwellings where indoor temperatures are often hotter than outdoor temperatures, the daily heat stress experienced by this vulnerable group varies between conditions that are stressful but endurable to those that approach the limits of human heat tolerance. Given the likelihood of even hotter environments in the future, urban planners will need access to more comprehensive heat studies, focusing on continual monitoring of heat stress and physiological responses of individuals from different walks of life. Full article

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24 pages, 4871 KB

Open AccessArticle

Excavating Precursors from the Traditional Chinese Pair Herbs Polygala tenuifolia and Gastrodia elata: Synthesis, Anticonvulsant Activity Evaluation of 3,4,5-Trimethoxycinnamic Acid (TMCA) Peptide Analogs

by Zefeng Zhao, Mengchen Lei, Yujun Bai and Haifa Qiao

Pharmaceuticals 2026, 19(2), 265; https://doi.org/10.3390/ph19020265 (registering DOI) - 3 Feb 2026

Abstract

Background: Epilepsy comprises a range of disorders affecting the central nervous system (CNS) characterized by recurrent seizures, impacting approximately 60 million individuals globally. In this study, we designed and derived a series of peptide analogs 1–30 of 3,4,5-trimethoxycinnamic acid (TMCA) [...] Read more.

Background: Epilepsy comprises a range of disorders affecting the central nervous system (CNS) characterized by recurrent seizures, impacting approximately 60 million individuals globally. In this study, we designed and derived a series of peptide analogs 1–30 of 3,4,5-trimethoxycinnamic acid (TMCA) from the herbal combinations of Polygala tenuifolia and Gastrodia elata, recognized in Traditional Chinese Medicine (TCM). Methods: All the analogs were synthesized, and their anticonvulsant efficacy was subsequently assessed. The anticonvulsant activity of all TMCA analogs was evaluated using two acute seizure models in mice: the maximal electroshock (MES) and the sc-pentylenetetrazole (PTZ) models. Furthermore, we explored the electroencephalogram (EEG) and double-labeling immunofluorescence experiments were carried out as well. Results: Our findings indicated that compounds 11, 19, 22, and 23 demonstrated favorable anticonvulsant activities during the initial assessment. Compounds 19 and 23 also played roles in controlling the onset of epilepsy in EEG, modulating levels of GABA aminotransferase (GABA-AT)/gamma-aminobutyric acid type A receptor (GABA_AR), interacting with active sites of GABA-AT and GABA_AR obtained from docking simulation methods. Conclusions: Novel derivatives in this study provide new cores for further design and optimization inspired by TCM herb pair drugs P. tenuifolia and G. elata, with the aim of exploring new anticonvulsant agents. Full article

(This article belongs to the Section Medicinal Chemistry)

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14 pages, 615 KB

Open AccessReview

Neurocognition, Metacognition, and Outcome in Schizophrenia Spectrum Disorders: A Scoping Review

by Courtney N. Wiesepape, Samantha Roop, Maham Ahmed, Makenzie Dubas and Marlee Gieselman

Int. J. Cogn. Sci. 2026, 2(1), 5; https://doi.org/10.3390/ijcs2010005 (registering DOI) - 3 Feb 2026

Abstract

Neurocognitive and metacognitive impairments are well-documented in schizophrenia spectrum disorders (SSDs). However, the relationship between these two domains remains underexplored, despite increasing interest in their combined impact on recovery and functional outcomes. Neurocognition refers to processes such as attention, memory, and executive functioning, [...] Read more.

Neurocognitive and metacognitive impairments are well-documented in schizophrenia spectrum disorders (SSDs). However, the relationship between these two domains remains underexplored, despite increasing interest in their combined impact on recovery and functional outcomes. Neurocognition refers to processes such as attention, memory, and executive functioning, and the neural systems that support these processes, both of which are frequently abnormal in SSDs and contribute to significant functional difficulties. Metacognition, in contrast, refers to the capacity to reflect on and integrate thoughts, emotions, and experiences into a coherent understanding of oneself and others. Although both domains are often studied in isolation, emerging evidence suggests a potential interdependence between neurocognition and metacognition, particularly regarding their influence on outcome. This scoping review explores empirical studies examining associations between neurocognition and metacognition in individuals with SSDs, specifically in the context of functional outcomes. We aim to clarify how these domains interact and explore their combined implications for recovery-oriented interventions and clinical practice. Findings may inform more integrated models of cognition and guide the development of dual-targeted treatment approaches to improve functional recovery in SSDs. Full article

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12 pages, 1563 KB

Open AccessSystematic Review

Clinical and Imaging Features of Aortic Penetrating Atherosclerotic Ulcers: A Systematic Review and Meta-Analysis

by Fatemeh Esfahanian and Mohammad Hossein Madani

J. Clin. Med. 2026, 15(3), 1200; https://doi.org/10.3390/jcm15031200 (registering DOI) - 3 Feb 2026

Abstract

Background/Objectives: Penetrating atherosclerotic ulcer (PAU) is a type of acute aortic syndrome (AAS) characterized by an ulcer that penetrates from the inner lining into the middle layer of the aorta, often leading to serious complications such as intramural hematoma (IMH), aortic dissection, [...] Read more.

Background/Objectives: Penetrating atherosclerotic ulcer (PAU) is a type of acute aortic syndrome (AAS) characterized by an ulcer that penetrates from the inner lining into the middle layer of the aorta, often leading to serious complications such as intramural hematoma (IMH), aortic dissection, aneurysm, and rupture. PAU incidence has risen significantly in recent years. Advancements in imaging technologies like CT and MRI have improved early detection, yet the true prevalence remains unclear due to the asymptomatic nature of many cases. Thoracic endovascular aortic repair (TEVAR) is becoming the preferred treatment, but questions remain regarding its effectiveness in different clinical settings. This systematic review and meta-analysis aim to consolidate findings on PAU’s clinical presentation, imaging characteristics, and outcomes to improve diagnosis, risk assessment, and treatment strategies. Methods: PubMed, Scopus, Embase, and Web of Science (WOS) were systematically searched from 1994 until November 2023. Related data were collected and evaluated. We used a random-effect model to calculate a forest plot, a funnel plot, pooled prevalence, and publication bias by STATA 18. Results: Of 1179 studies, 56 met the inclusion criteria, and we analyzed 3023 PAU patients. The 30-day mortality rate was 4.4%, with a late mortality rate of 15.6%. According to our study, open surgery, pre-operation (pre-op) aortic rupture, post-operation (post-op) endoleak, distant year of publication, symptomatic patients, lesions in the ascending aorta, and greater diameter of the lesion were associated with mortality. TEVAR was the most common treatment (67.3%), the endoleak rate was 3.7%, and re-intervention occurred in 4.4% of cases. Significant heterogeneity and publication bias were noted across several outcomes. Conclusions: PAU primarily affects elderly males with cardiovascular comorbidities; interventions like TEVAR reduce short-term mortality; however, long-term outcomes remain challenging, which indicates further investigation is needed into early detection and treatment. Full article

(This article belongs to the Section Nuclear Medicine & Radiology)

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14 pages, 569 KB

Open AccessArticle

Multi-Objective Preparation Process Optimization of Ultra-Small Manganese Ferrite Nanoparticles Using Probability-Based Method

by Danghua Zhao, Pengcheng He, Xiaoyan Cheng and Haipeng Teng

Processes 2026, 14(3), 535; https://doi.org/10.3390/pr14030535 (registering DOI) - 3 Feb 2026

Abstract

With increasing demands for controllable synthesis of nanomaterials, it has become particularly important to develop efficient and accurate methods for optimizing preparation processes. This study focuses on the nucleation and growth stages in the synthesis of ultra-small manganese ferrite nanoparticles, aiming to clarify [...] Read more.

With increasing demands for controllable synthesis of nanomaterials, it has become particularly important to develop efficient and accurate methods for optimizing preparation processes. This study focuses on the nucleation and growth stages in the synthesis of ultra-small manganese ferrite nanoparticles, aiming to clarify the influence mechanisms of key parameters such as oleic acid dosage, precursor concentration, and aging temperature on the product size and properties and to optimize the preparation process accordingly. The probability-based multi-objective optimization method was adopted, using the above parameters as optimization variables to systematically design and screen the experimental conditions. The results show that this method can effectively achieve the optimization of multiple objectives in the preparation process, providing a reliable methodological framework for the controlled synthesis of ultra-small manganese ferrite nanoparticles. Full article

(This article belongs to the Special Issue Multi-Criteria Decision Making in Chemical and Process Engineering)

22 pages, 33722 KB

Open AccessArticle

Integrated Transcriptomic and Histological Analysis of TP53/CTNNB1 Mutations and Microvascular Invasion in Hepatocellular Carcinoma

by Ignacio Garach, Nerea Hernandez, Luis J. Herrera, Francisco M. Ortuño and Ignacio Rojas

Genes 2026, 17(2), 190; https://doi.org/10.3390/genes17020190 (registering DOI) - 3 Feb 2026

Abstract

Background/Objectives: Hepatocellular carcinoma (HCC) shows marked molecular and histopathological heterogeneity. Among the alterations most strongly associated with clinical outcome are mutations in TP53 and CTNNB1, as well as the presence of microvascular invasion (MVI). Although these factors are well established as [...] Read more.

Background/Objectives: Hepatocellular carcinoma (HCC) shows marked molecular and histopathological heterogeneity. Among the alterations most strongly associated with clinical outcome are mutations in TP53 and CTNNB1, as well as the presence of microvascular invasion (MVI). Although these factors are well established as prognostic indicators, how their molecular effects relate to tumor morphology remains unclear. In this work, we studied transcriptomic changes linked to TP53 and CTNNB1 mutational status and to MVI, and examined whether these changes are reflected in routine histology. Methods: RNA sequencing data from HCC samples annotated for mutations and vascular invasion were analyzed using differential expression analysis combined with machine learning-based feature selection to characterize the underlying transcriptional programs. In parallel, we trained a weakly supervised multitask deep learning model on hematoxylin and eosin-stained whole-slide images using slide-level labels only, without spatial annotations, to assess whether these features could be inferred from global histological patterns. Results: Distinct gene expression profiles were observed for TP53-mutated, CTNNB1-mutated, and MVI-positive tumors, involving pathways related to proliferation, metabolism, and invasion. Image-based models were able to capture morphological patterns associated with these states, achieving above-random discrimination with variable performance across tasks. Conclusions: Taken together, these results support the existence of coherent biological programs underlying key risk determinants in HCC and indicate that their phenotypic effects are, at least in part, detectable in routine histopathology. This provides a rationale for integrative morpho-molecular approaches to risk assessment in HCC. Full article

(This article belongs to the Special Issue AI and Machine Learning in Cancer Genomics)

12 pages, 851 KB

Open AccessArticle

Circulating CCDC3 as an Indicator of Visceral Fat Accumulation in Patients with Type 2 Diabetes Mellitus

by Lin Zhu, Xiaodie Fan, Jiangang Lu, Yutao He, Youyuan Gao, Sirong He, Longbin Lai, Ruobei Zhao, Rui Cheng, Xi Li, Fengning Chuan and Bin Wang

Metabolites 2026, 16(2), 111; https://doi.org/10.3390/metabo16020111 (registering DOI) - 3 Feb 2026

Abstract

Background: Visceral fat plays a central role in cardiometabolic risk among people with type 2 diabetes mellitus (T2DM), yet its assessment in routine clinical practice remains largely dependent on imaging techniques or indirect anthropometric measures. Identifying accessible blood-based markers that reflect visceral [...] Read more.

Background: Visceral fat plays a central role in cardiometabolic risk among people with type 2 diabetes mellitus (T2DM), yet its assessment in routine clinical practice remains largely dependent on imaging techniques or indirect anthropometric measures. Identifying accessible blood-based markers that reflect visceral adiposity may facilitate improved phenotyping in this population. This study aimed to investigate whether circulating coiled-coil domain–containing protein 3 (CCDC3) reflects visceral fat accumulation in adults with T2DM. Methods: Public RNA-sequencing datasets and human adipose tissue samples were analyzed to identify CCDC3 as a visceral fat–enriched secretory gene. In this cross-sectional study of 160 adults with T2DM undergoing dual-energy X-ray absorptiometry, plasma CCDC3 was measured by ELISA. Associations between plasma CCDC3 and visceral fat area (VFA) were examined using multivariable regression. Logistic regression models for abdominal obesity (VFA ≥ 100 cm²), with and without CCDC3, were evaluated using receiver operating characteristic (ROC) analysis, calibration curves, decision curve analysis (DCA), and Shapley additive explanations (SHAP). Results: Circulating CCDC3 levels were positively associated with VFA (β = 3.11, p < 0.001), independent of demographic and metabolic factors. Incorporating CCDC3 into the baseline model significantly improved discrimination of abdominal obesity (AUC 0.820 vs. 0.663; p = 0.009). Calibration curves and DCA supported better model fit and higher net clinical benefit with CCDC3. SHAP analysis showed that CCDC3 contributed the greatest incremental importance beyond waist circumference, sex, and age. Conclusions: Circulating CCDC3 may serve as a blood-based biomarker reflecting visceral adiposity in adults with T2DM and provides complementary information beyond traditional anthropometric measures. Full article

(This article belongs to the Section Endocrinology and Clinical Metabolic Research)

24 pages, 2992 KB

Open AccessArticle

Tributary-to-Mainstream Aquatic Macroinvertebrate Discontinuities in the Colorado River, Southwestern USA

by Lawrence E. Stevens, Joseph H. Holway and Craig Ellsworth

Water 2026, 18(3), 395; https://doi.org/10.3390/w18030395 (registering DOI) - 3 Feb 2026

Abstract

Tributary-to-mainstem discontinuities (TMDs) are understudied, but are likely common in river networks, arising from abrupt transitions in stream order and dominant ecological factors. We present a conceptual model of aquatic macroinvertebrate (AMI) TMD directionality and relative magnitude by contrasting the impacts of hydrography, [...] Read more.

Tributary-to-mainstem discontinuities (TMDs) are understudied, but are likely common in river networks, arising from abrupt transitions in stream order and dominant ecological factors. We present a conceptual model of aquatic macroinvertebrate (AMI) TMD directionality and relative magnitude by contrasting the impacts of hydrography, geochemistry, and sediment transport on tributary-related channel-floor precipitate cementation and the mainstream embeddedness (burial) of channel-floor substrata in fine sediment. We test that model using AMI assemblage density/m², species richness/sample, and diversity data from 24 tributaries confluent with the regulated Colorado River in Grand Canyon through pairwise and multivariate analyses of long-term discharge records and substrate and water-quality data in three habitats: tributaries, their confluences, and adjacent mainstream habitats. Mean AMI density decreased 2.7-fold from low to high cementation, 6.1-fold from low-to-high embeddedness, and 136.0-fold across combined gradients. We also analyzed pre-dam aquatic insect literature, finding that TMDs were naturally common in Glen Canyon upstream but were more strongly tributary-positive (discontinuity magnitude, D_mag = 0.62 in pre-dam Glen Canyon) compared to tributaries in the post-dam Grand Canyon (D_mag = 0.31). We conclude that, depending on D_mag directionality, tributary confluences can function as hotspots or barriers to AMI assemblage development. Our results demonstrate that TMDs are and were common in the contemporary regulated and natural unregulated Colorado River corridor, and we expand the concept of biotic discontinuity to improve understanding of fluvial ecosystem ecology and constraints on river and dam management. Full article

(This article belongs to the Special Issue Freshwater Ecosystems—Biodiversity and Protection: 2nd Edition)

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26 pages, 4986 KB

Open AccessArticle

Electromechanical Coupling Modeling and Control Characteristics of Permanent Magnet Semi-Direct Drive Scraper Conveyors

by Wenjia Lu, Guangda Liang, Zunling Du, Weibo Huang, Lisha Zhu, Yimin Zhang and Xiaoyu Zhao

Actuators 2026, 15(2), 97; https://doi.org/10.3390/act15020097 (registering DOI) - 3 Feb 2026

Abstract

To address the challenges of strong electromechanical coupling, nonlinear friction, and poor disturbance rejection in semi-direct-drive scraper conveyor systems under complex coal mining conditions, this paper aims to propose a high-performance drive control strategy that balances dynamic response speed with steady-state operational smoothness. [...] Read more.

To address the challenges of strong electromechanical coupling, nonlinear friction, and poor disturbance rejection in semi-direct-drive scraper conveyor systems under complex coal mining conditions, this paper aims to propose a high-performance drive control strategy that balances dynamic response speed with steady-state operational smoothness. First, an integrated electromechanical coupling dynamic model incorporating Permanent Magnet Synchronous Motor (PMSM) vector control and the time-varying meshing stiffness of a two-stage planetary gear train is established. Subsequently, a Sliding Mode Control (SMC) strategy optimized with a saturation boundary layer is designed and compared with traditional Proportional-Integral (PI) control under multiple operating conditions. Time-frequency domain analysis indicates that SMC significantly enhances the dynamic stiffness of the drive system. Under sudden load change conditions, the speed recovery time is shortened by approximately 76%, and the steady-state error is reduced by 37% compared to PI control. Microscopic characteristic evaluation based on FFT and Total Variation (TV) metrics reveals that SMC achieves active disturbance rejection through spectral broadening of the electromagnetic torque. Crucially, the steady-state cumulative control effort of SMC is equivalent to that of PI, implying no additional mechanical stress burden, while the equivalent dynamic transmission force fluctuation in the mechanical chain is reduced by about 3%. The study confirms that the proposed strategy successfully achieves a synergistic optimization of “macroscopic rapid response” and “microscopic smooth operation,” providing a theoretical basis for the high-precision control of heavy-duty underground transmission equipment. Full article

(This article belongs to the Section Control Systems)

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23 pages, 643 KB

Open AccessArticle

Care-MOVE: A Smartphone-Based Application for Continuous Monitoring of Mobility, Environmental Exposure and Cognitive Status in Older Patients

by Fabrizia Devito, Vincenzo Gattulli and Donato Impedovo

Appl. Sci. 2026, 16(3), 1549; https://doi.org/10.3390/app16031549 (registering DOI) - 3 Feb 2026

Abstract

This study presents Care-MOVE, a smartphone-based application designed for continuous, passive, and unobtrusive monitoring of mobility, environmental exposure, and cognitive status in older adults within a telemedicine framework. The system integrates movement-related data collected through smartphone sensors (GPS, activity recognition, and caloric [...] Read more.

This study presents Care-MOVE, a smartphone-based application designed for continuous, passive, and unobtrusive monitoring of mobility, environmental exposure, and cognitive status in older adults within a telemedicine framework. The system integrates movement-related data collected through smartphone sensors (GPS, activity recognition, and caloric expenditure estimation) with contextual air quality information and standardized neuropsychological assessments, resulting in a comprehensive multimodal dataset (Care-MOVE Dataset). An exploratory proof-of-concept study was conducted on a subsample of 53 participants aged over 65, each monitored continuously for five days, contributing on average more than 30,000 longitudinal records. To investigate whether daily motor behavior can serve as a digital biomarker of cognitive functioning, several Machine Learning and Deep Learning models were evaluated using a Leave-One-User-Out (LOUO) cross-validation strategy. The comparative analysis included traditional classifiers (Logistic Regression, Random Forest, Gradient Boosting, K-Nearest Neighbors, and Support Vector Machines) as well as temporal deep learning architectures (1D CNN, LSTM, GRU, and Transformer). Among all of the evaluated approaches, the Support Vector Machine with RBF kernel achieved the best performance, reaching an accuracy of 98.1%, a balanced accuracy of 0.988, and an F1-score of 0.981, demonstrating robust generalization across unseen subjects. For this reason, the study was designed and presented as an exploratory proof-of-concept rather than a definitive clinical validation. This integrated approach not only enables the collection of detailed and contextualized data but also opens new perspectives for proactive digital healthcare, focused on risk prevention, improving quality of life, and promoting autonomy in elderly patients. Full article

(This article belongs to the Special Issue Robotics, IoT and AI Technologies in Bioengineering, 2nd Edition)

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25 pages, 1801 KB

Open AccessArticle

by Marek Kulka, Iwona Monika Szopa, Karolina Mizera-Szpilka and Maciej Klockiewicz

Int. J. Mol. Sci. 2026, 27(3), 1506; https://doi.org/10.3390/ijms27031506 (registering DOI) - 3 Feb 2026

Abstract

The immune status of dogs is shaped by continuous exposure to antigenic and various environmental stimuli, which together influence the development, regulation, and effectiveness of immune responses. Stress-related immune alterations may not be evident at the systemic level but can emerge at cellular [...] Read more.

The immune status of dogs is shaped by continuous exposure to antigenic and various environmental stimuli, which together influence the development, regulation, and effectiveness of immune responses. Stress-related immune alterations may not be evident at the systemic level but can emerge at cellular and molecular scales. Therefore, this study aimed to comprehensively characterize the hematological and immunological profiles of dogs in different environments. We evaluated lymphocyte responses under basal conditions and following CD3/CD28-mediated in vitro activation, with subsequent long-term culture. Gene expression analyses targeted markers of early T cell activation, cytotoxic effector function, cytokine signaling, and inhibitory immune regulation. The memory phenotype of T lymphocytes was evaluated after blood collection and prolonged in vitro culture. In addition, hematological and biochemical profiles were assessed, including basic parameters, cortisol, and C-reactive protein. Our results revealed that client-owned dogs exhibited lower baseline expression of activation markers, especially in comparison with the short-term stay group, indicating an early immune activation state upon entry to the shelter environment. Furthermore, T lymphocytes from short- and long-term shelter dogs exhibited marked differences in the distribution of naïve and effector-memory subsets as well as different expansion capacity. These alterations persisted during prolonged in vitro culture, indicating that stress duration and environmental antigen exposure differentially shape immune responsiveness. In summary, chronic stress modulates canine immune status in a time-dependent manner, highlighting the importance of integrated cellular and molecular approaches in assessing the impact of environmental stressors on dogs’ health and welfare. Full article

(This article belongs to the Special Issue Molecular Mechanism of Immune Response)

27 pages, 1194 KB

Open AccessArticle

How Does Climate Policy Uncertainty Affect Corporate Sustainability? Evidence from a Quasi-Natural Experiment in China

by Xiao Qin, Zifeng Wang, Yanju Liang and Yuan Virtanen

Sustainability 2026, 18(3), 1554; https://doi.org/10.3390/su18031554 (registering DOI) - 3 Feb 2026

Abstract

As global climate change intensifies and the Paris Agreement advances low-carbon transformation, frequent local policy adjustments under China’s dual carbon goals have made climate-policy uncertainty a core challenge for corporate sustainability. Environmental, social, and governance (ESG) performance has grown exponentially in international capital [...] Read more.

As global climate change intensifies and the Paris Agreement advances low-carbon transformation, frequent local policy adjustments under China’s dual carbon goals have made climate-policy uncertainty a core challenge for corporate sustainability. Environmental, social, and governance (ESG) performance has grown exponentially in international capital markets, evolving from a peripheral concept to a key investment decision-making dimension. This study uses China’s carbon peaking and neutrality policies as a quasinatural experiment, applying the difference-in-differences (DID) method to the panel data of Chinese A-share listed companies (2014–2023). Taking high-energy-consuming enterprises as the treatment group, this study identifies net policy effects via the interaction of policy and time dummy variables. The results show that carbon peaking and neutrality policies significantly suppress the ESG performance of energy-intensive firms; mediating effect tests confirm that the policy harms ESG performance by increasing uncertainty. Implications include enhancing policy transparency and predictability and optimizing resource allocation to strengthen ESG resilience. Future research should focus on micro-level policy indicators and long-term effect tracking to provide theoretical and practical support for synergizing dual carbon goals with high-quality economic development. Full article

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14 pages, 324 KB

Open AccessArticle

Improved Nonparallel Support Vector Machine for Pattern Classification

by Shujun Lian and Jingjing Yang

Algorithms 2026, 19(2), 124; https://doi.org/10.3390/a19020124 (registering DOI) - 3 Feb 2026

Abstract

In this paper, we propose a new nonparallel support vector machine for binary classification problems and name it the improved nonparallel support vector machine (IMNSVM). The IMNSVM uses a one-sided

ε

-band and minimizes

ε

to achieve a better fitting effect for the [...] Read more.

In this paper, we propose a new nonparallel support vector machine for binary classification problems and name it the improved nonparallel support vector machine (IMNSVM). The IMNSVM uses a one-sided

ε

-band and minimizes

ε

to achieve a better fitting effect for the same class of training points. By introducing a new variable,

ρ

, the IMNSVM keeps one class of training points at a certain distance from the hyperplane corresponding to another class of training points, keeping them as far away as possible so as to better adapt to the training points and better describe the difference in data distribution between different categories. The IMNSVM can degenerate into the standard support vector machine (SVM) under certain conditions and is applicable to a wider range of data types. Finally, numerical experiments also explain the effectiveness of the method. Full article

(This article belongs to the Special Issue Algorithms in Data Classification (3rd Edition))

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10 pages, 256 KB

Open AccessEditorial

Synthesis, Properties, and Applications of Novel Polymer-Based Gels

by Zhen Gao, Peng Zhang and Yuanxun Zheng

Gels 2026, 12(2), 143; https://doi.org/10.3390/gels12020143 (registering DOI) - 3 Feb 2026

Abstract

Polymer gels, as a class of soft materials with three-dimensional cross-linked networks, have garnered escalating attention in recent decades due to their exceptional capacity to absorb and retain solvents, coupled with tunable mechanical, chemical, and responsive properties [...] Full article

(This article belongs to the Special Issue Synthesis, Properties, and Applications of Novel Polymer-Based Gels)

24 pages, 3109 KB

Open AccessFeature PaperArticle

Once Upon a Time Without DMF: Greener Paths in Peptide and Organic Synthesis

by Antonia Scognamiglio, Elisa Magli, Giuseppe Caliendo, Elisa Perissutti, Vincenzo Santagada and Beatrice Severino

Molecules 2026, 31(3), 536; https://doi.org/10.3390/molecules31030536 (registering DOI) - 3 Feb 2026

Abstract

N,N-Dimethylformamide (DMF) has been a cornerstone solvent in both peptide and organic synthesis due to its excellent solubilizing properties and chemical stability. However, its use has raised significant health and environmental concerns. DMF is classified as a substance of very high concern (SVHC) [...] Read more.

N,N-Dimethylformamide (DMF) has been a cornerstone solvent in both peptide and organic synthesis due to its excellent solubilizing properties and chemical stability. However, its use has raised significant health and environmental concerns. DMF is classified as a substance of very high concern (SVHC) by the European Chemicals Agency (ECHA) due to its reproductive toxicity and potential for skin absorption, leading to liver damage upon prolonged exposure. Consequently, restrictions on its use have been introduced, encouraging the scientific community to seek safer, more sustainable alternatives. This review provides a comprehensive analysis of the existing literature on alternative solvents to DMF, identifying current gaps or problems, and offering recommendations for future research. Full article

(This article belongs to the Special Issue Molecular Strategies for the Synthesis of Drug-Like Bioactives)

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4 pages, 168 KB

Open AccessEditorial

Exploring Bioactive Polyphenolic Compounds in Food and Natural Real-World Samples II: Molecular Diversity, Functionality, and Future Directions

by Francesco Cacciola and Katia Arena

Molecules 2026, 31(3), 537; https://doi.org/10.3390/molecules31030537 (registering DOI) - 3 Feb 2026

Abstract

Polyphenolic compounds have long been recognized as one of the most structurally diverse and biologically relevant classes of secondary metabolites in plant-derived foods and natural products [...] Full article

(This article belongs to the Special Issue Exploring Bioactive Polyphenolic Compounds in Food and Natural Real-World Samples II)

21 pages, 1315 KB

Open AccessArticle

Ensemble Deep Learning Models for Multi-Class DNA Sequence Classification: A Comparative Study of CNN, BiLSTM, and GRU Architectures

by Elias Tabane, Ernest Mnkandla and Zenghui Wang

Appl. Sci. 2026, 16(3), 1545; https://doi.org/10.3390/app16031545 (registering DOI) - 3 Feb 2026

Abstract

DNA sequence classification is a fundamental problem in bioinformatics, playing an indispensable role in gene annotation and disease prediction. Whereas most deep learning models, such as CNNs, BiLSTM networks, and GRUs, have been found individually optimal, each of these methods excels in modeling [...] Read more.

DNA sequence classification is a fundamental problem in bioinformatics, playing an indispensable role in gene annotation and disease prediction. Whereas most deep learning models, such as CNNs, BiLSTM networks, and GRUs, have been found individually optimal, each of these methods excels in modeling a specific aspect of sequence data: local motifs, long-range dependencies, and efficient temporal modeling of the sequences. Here, we present and evaluate an ensemble model that integrates CNN, BiLSTM, and GRU architectures via a majority voting combination scheme so that their complementary strengths can be harnessed. We trained and evaluated each standalone and the integrated model on a DNA dataset comprising 4380 sequences falling under five functional categories. The ensemble model achieved a classification accuracy of 90.6% with precision, recall, and F1 score equal to 0.91, thereby outperforming the state-of-the-art techniques by large margins. Although previous studies have tried analyzing each Deep Learning method individually for DNA classification tasks, none have attempted a systematic combination of CNN, BiLSTM, and GRU based on their ability to extract features simultaneously. The current research aims at presenting a novel method that combines these architectures based on a Majority Voting strategy and proves how their combination is better at extracting local patterns and long dependency information when compared individually. In particular, the proposed ensemble model smoothed the high recall of BiLSTM with the high precision of CNN, leading to more robust and reliable classification. The experiments involved a publicly available DNA sequence data set of 4380 sequences distributed over 5 classes. Our results emphasized the prospect of hybrid ensemble deep learning as a strong approach for complex genomic data analysis, opening ways toward more accurate and interpretable bioinformatics research. Full article

(This article belongs to the Special Issue Advances in Deep Learning and Intelligent Computing)

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41 pages, 10153 KB

Open AccessReview

A Comprehensive Review on Sustainable Triboelectric Energy Harvesting Using Biowaste-Derived Materials

by Wajid Ali, Tabinda Shabir, Shahzad Iqbal, Syed Adil Sardar, Farhan Akhtar and Woo Young Kim

Materials 2026, 19(3), 592; https://doi.org/10.3390/ma19030592 (registering DOI) - 3 Feb 2026

Abstract

The growing demand for sustainable and distributed energy solutions has driven increasing interest in triboelectric nanogenerators (TENGs) as platforms for energy harvesting and self-powered sensing. Biowaste-based triboelectric nanogenerators (BW-TENGs) represent an attractive strategy by coupling renewable energy generation with waste valorization under the [...] Read more.

The growing demand for sustainable and distributed energy solutions has driven increasing interest in triboelectric nanogenerators (TENGs) as platforms for energy harvesting and self-powered sensing. Biowaste-based triboelectric nanogenerators (BW-TENGs) represent an attractive strategy by coupling renewable energy generation with waste valorization under the principles of the circular bioeconomy. This review provides a comprehensive overview of BW-TENGs, encompassing fundamental triboelectric mechanisms, material categories, processing and surface-engineering strategies, device architectures, and performance evaluation metrics. A broad spectrum of biowaste resources—including agricultural residues, food and marine waste, medical plastics, pharmaceutical waste, and plant biomass—is critically assessed in terms of physicochemical properties, triboelectric behavior, biodegradability, biocompatibility, and scalability. Recent advances demonstrate that BW-TENGs can achieve electrical outputs comparable to conventional synthetic polymer TENGs while offering additional advantages such as environmental sustainability, mechanical compliance, and multifunctionality. Key application areas, including environmental monitoring, smart agriculture, wearable and implantable bioelectronics, IoT networks, and waste management systems, are highlighted. The review also discusses major challenges limiting large-scale deployment, such as material heterogeneity, environmental stability, durability, and lack of standardization, and outlines emerging solutions involving material engineering, hybrid energy-harvesting architectures, artificial intelligence-assisted optimization, and life cycle assessment frameworks. Full article

(This article belongs to the Special Issue Materials, Design, and Performance of Nanogenerators)

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17 pages, 1345 KB

Open AccessArticle

Design and Numerical Analysis of an Ultra-Sensitive π-Configuration Fibre Optic-Based SPR Sensor: Dual Plasmonic Enhancement for Low-Refractive-Index Biomolecular Detection

by John Ehiabhili, Radhakrishna Prabhu and Somasundar Kannan

Photonics 2026, 13(2), 147; https://doi.org/10.3390/photonics13020147 (registering DOI) - 3 Feb 2026

Abstract

Surface plasmon resonance (SPR)-based optical fibre sensors have transformed label-free biosensing; however, single-interface evanescent field interactions continue to limit their sensitivity. This study presents a novel π-configuration optical fibre-based surface plasmon resonance sensor that greatly increases sensitivity by enabling dual plasmonic excitation on [...] Read more.

Surface plasmon resonance (SPR)-based optical fibre sensors have transformed label-free biosensing; however, single-interface evanescent field interactions continue to limit their sensitivity. This study presents a novel π-configuration optical fibre-based surface plasmon resonance sensor that greatly increases sensitivity by enabling dual plasmonic excitation on two symmetrically polished surfaces coated with optimized metallic thin films (Ag, Au, or Cu). We show, using finite element method simulations in COMSOL Multiphysics v6.3, that the π-configuration increases the interaction volume between the analyte and guided light, resulting in an enhanced sensitivity of 3300 nm/RIU for silver at refractive index (RI) 1.37–1.38, which is a 120% improvement over traditional D-shaped sensors (1500 nm/RIU). The maximum field norm for the π-configuration sensor is approximately 1.4 times greater than the maximum observed for the D-shaped SPR sensor at an analyte RI of 1.38. The sensor’s performance is evaluated using full-width half-maximum, wavelength sensitivity, and wavelength interrogation metrics. For the π-configuration sensor at an analyte RI of 1.38, the values of the FWHM, figure of merit, detection accuracy, and confinement loss were 36 nm, 94.29 RIU⁻¹, 0.94, and 38.5 dB/cm, respectively. The results obtained are purely simulated using COMSOL. With the support of electric field confinement analysis, a thorough theoretical framework describes the crucial coupling regime that causes ultra-high sensitivity at low RI. This design provides new opportunities for environmental monitoring, low-abundance biomarker screening, and early-stage virus detection, where it is necessary to resolve minute RI changes with high precision. Full article

(This article belongs to the Special Issue Science and Applications of Optical Fiber Sensors: Recent Advances and Future Trends)

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