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18 pages, 4873 KB

Open AccessArticle

Effect of N-Acetyl-L-Cysteine (NAC) on Inflammation After Intraperitoneal Mesh Placement in an Escherichia coli Septic Rat Model: A Randomized Experimental Study

by Styliani Parpoudi, Ioannis Mantzoros, Orestis Ioannidis, Konstantinos Zapsalis, Thomai Gamali, Dimitrios Kyziridis, Christos Gekas, Elissavet Anestiadou, Savvas Symeonidis, Stefanos Bitsianis, Efstathios Kotidis, Manousos-Georgios Pramateftakis, Dimosthenis Miliaras, Anastasia Bikouli, Georgios Iosifidis and Stamatios Angelopoulos

Med. Sci. 2025, 13(4), 318; https://doi.org/10.3390/medsci13040318 (registering DOI) - 14 Dec 2025

Abstract

Background/Objectives: The safety of intraperitoneal mesh placement in contaminated fields remains controversial because of the increased risk of inflammation and adhesion formation. N-acetyl-L-cysteine (NAC) has antioxidant, pro-fibrinolytic and antibiofilm actions that could attenuate this response. The aim of this study is to [...] Read more.

Background/Objectives: The safety of intraperitoneal mesh placement in contaminated fields remains controversial because of the increased risk of inflammation and adhesion formation. N-acetyl-L-cysteine (NAC) has antioxidant, pro-fibrinolytic and antibiofilm actions that could attenuate this response. The aim of this study is to determine whether NAC reduces mesh-related inflammation in a septic model created by intraperitoneal Escherichia coli (E.coli) inoculation. The primary comparison was prospectively defined between E. coli–inoculated animals treated with NAC (D) and those without NAC (B). Groups without E. coli (A,C,E) are presented for context and were compared previously. Methods: In this randomized, double-blind experimental model (five groups, n = 20 per group), all rats underwent midline laparotomy with intraperitoneal placement of a composite mesh, followed by standardized ciprofloxacin administration. The septic groups received intraperitoneal E. coli, while the NAC-treated groups additionally received intraperitoneal NAC (150 mg/kg). Serum levels of IL-1α, IL-6, and TNF-α were measured on postoperative days 7, 14, and 21. On day 21, adhesions were graded using the Modified Diamond system, histology (inflammatory infiltration, fibrosis, neovascularization) was scored, and mesh cultures were obtained. Cytokine data were analyzed with repeated-measures ANOVA, while categorical or ordinal outcomes were assessed using χ² or Fisher’s exact tests with Bonferroni-adjusted pairwise comparisons. Results: E. coli inoculation significantly increased adhesion burden and worsened histologic scores compared with controls (both p < 0.001). NAC administration in the septic model significantly reduced adhesions and improved all histologic domains relative to E. coli alone (all p ≤ 0.003), with values comparable to controls (non-significant across domains). For cytokines, there was a significant overall group effect for IL-1α, IL-6, and TNF-α (all p < 0.001), without a main effect of time or time × group interaction. Pairwise contrasts showed lower IL-1α (p = 0.024), IL-6 (p < 0.001), and TNF-α (p < 0.001) levels in group D versus B, and lower IL-6 and TNF-α in group D versus A (both p < 0.001). Mesh culture positivity rate was higher in group B than A (p < 0.001) and showed a non-significant reduction in group D versus B (p = 0.10). No perioperative deaths occurred. Conclusions: NAC attenuated septic, mesh-associated inflammation—normalizing adhesions and histology and reducing IL-6 and TNF-α— supporting its role as a host-directed adjunct alongside antibiotics. Further translational studies are warranted to define the optimal dose, timing, and clinical indications. Full article

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14 pages, 606 KB

Open AccessArticle

Efficacy of Combined Hyperbaric Oxygen, per Os Steroid, and Prostaglandin E1 Therapy for Idiopathic Sudden Sensorineural Hearing Loss and Prognostic Factors for Recovery

by Takumi Nakayama, Satoshi Hara, Takeshi Kusunoki, Yusuke Takata, Hirotomo Honma, Takashi Anzai, Yoshinobu Kidokoro, Akihisa Yoshikawa and Fumihiko Matsumoto

J. Otorhinolaryngol. Hear. Balance Med. 2025, 6(2), 25; https://doi.org/10.3390/ohbm6020025 (registering DOI) - 14 Dec 2025

Abstract

Background: Idiopathic sudden sensorineural hearing loss (ISSNHL) is an abrupt unilateral hearing loss of unknown origin. Combination therapy with hyperbaric oxygen (HBO), systemic steroids (SS), and prostaglandin E1 (PGE1) has been used in Japan; however, its prognostic factors remain unclear. Objective: To evaluate [...] Read more.

Background: Idiopathic sudden sensorineural hearing loss (ISSNHL) is an abrupt unilateral hearing loss of unknown origin. Combination therapy with hyperbaric oxygen (HBO), systemic steroids (SS), and prostaglandin E1 (PGE1) has been used in Japan; however, its prognostic factors remain unclear. Objective: To evaluate the efficacy of HBO combined with SS and PGE1 and to identify prognostic factors for hearing recovery in patients with ISSNHL. Methods: This retrospective study included 116 patients treated within 14 days of ISSNHL onset. Sixty patients received HBO, SS, and PGE1 (HBO group), and 56 received SS and PGE1 alone (No-HBO group). Hearing outcomes were assessed using PTA (arithmetic mean hearing at 250–4000 Hz) and graded by Siegel’s criteria. Prognostic factors were analyzed by multivariate logistic regression. Results: The HBO group showed significantly better hearing grade outcomes (p = 0.007) and greater PTA improvement (p = 0.003) than the No-HBO group. Vertigo and higher initial PTA were identified as independent predictors of poor hearing outcomes. Patients without vertigo showed significantly greater improvement at 2000 Hz (p = 0.009). Receiver operating characteristic analysis revealed an optimal initial PTA cutoff of ≥90.5 dB for predicting poor hearing outcome. Conclusions: HBO combined with SS and PGE1 significantly improves hearing outcomes in ISSNHL. However, the presence of vertigo and severe initial hearing loss remain poor prognostic indicators. These findings suggest that while the addition of HBO may enhance hearing outcomes, prognosis remains limited in severe cases. Further prospective studies are needed to confirm these results. Full article

(This article belongs to the Section Otology and Neurotology)

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19 pages, 3929 KB

Open AccessArticle

Application of Integrated Multi-Operation Paddy Field Leveling Machine in Rice Production

by Yangjie Shi, Jiawang Hong, Xingye Shen, Peng Xu, Jintao Xu, Xiaobo Xi, Qun Hu and Hui Shen

Agronomy 2025, 15(12), 2877; https://doi.org/10.3390/agronomy15122877 (registering DOI) - 14 Dec 2025

Abstract

Paddy field leveling is the foundation of high-yield rice cultivation. In response to the current issues of low leveling accuracy and the lack of efficient multi-operation machinery, an Integrated Multi-operation Paddy Field Leveling Machine was designed in this study. This machine can complete [...] Read more.

Paddy field leveling is the foundation of high-yield rice cultivation. In response to the current issues of low leveling accuracy and the lack of efficient multi-operation machinery, an Integrated Multi-operation Paddy Field Leveling Machine was designed in this study. This machine can complete soil crushing, stubble burying, mud stirring, and leveling in a single pass. Combined with an adaptive control system based on Global Navigation Satellite System—Real-Time Kinematic (GNSS-RTK) technology, it enables adaptive and precise paddy field leveling operations. To verify the operational performance of the equipment, field tests were conducted. The results showed that the machine achieved an average puddling depth of 14.21 cm, a surface levelness of 2.16 cm, an average stubble burial depth of 8.15 cm, and a vegetation coverage rate of 89.33%, demonstrating satisfactory leveling performance. Furthermore, to clarify the feasibility and superiority of applying this equipment in actual rice production, experiments were conducted to investigate the effects of different field leveling methods on early rice growth, yield, and its components. One-way analysis of variance was employed to examine the differences in agronomic indicators between the different field leveling treatments. The results indicated that using this equipment for paddy field leveling, compared to traditional methods and dry land preparation, can improve the seedling emergence rate, thereby laying a solid population foundation for the formation of effective panicles. It also promoted root growth and development and increased the total dry matter accumulation at maturity, thereby contributing to high yield formation. Over the two-year experimental period, the rice yield remained above 9.8 t·hm⁻². This research provides theoretical support and practical guidance for the further optimization and development of subsequent paddy field preparation equipment, thereby promoting the widespread application of this technology in rice production. Full article

(This article belongs to the Special Issue Ecophysiological Principles for Sustainable Rice and Wheat Cultivation)

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22 pages, 4124 KB

Open AccessArticle

Design and Optimization of an Inductive-Stub-Coupled CSRR for Non-Invasive Glucose Sensing

by Zaid A. Abdul Hassain, Malik J. Farhan, Taha A. Elwi and Iulia Andreea Mocanu

Sensors 2025, 25(24), 7592; https://doi.org/10.3390/s25247592 (registering DOI) - 14 Dec 2025

Abstract

This paper presents a high-sensitivity microwave sensor based on a modified Complementary Split Ring Resonator (CSRR) architecture, integrated with inductive stubs, for non-invasive blood glucose monitoring. The proposed sensor is designed to enhance the electric field localization and coupling efficiency by introducing inductive [...] Read more.

This paper presents a high-sensitivity microwave sensor based on a modified Complementary Split Ring Resonator (CSRR) architecture, integrated with inductive stubs, for non-invasive blood glucose monitoring. The proposed sensor is designed to enhance the electric field localization and coupling efficiency by introducing inductive elements that strengthen the perturbation effect caused by glucose concentration changes in the blood. Numerical simulations were conducted using a multilayer finger model to evaluate the sensor’s performance under various glucose levels ranging from 0 to 500 mg/dL. The modified sensor exhibits dual-resonance characteristics and outperforms the conventional CSRR in both frequency and amplitude sensitivity. At an optimized stub gap of 2 mm, which effectively minimizes the capacitive coupling effect of the transmission line and thereby improves the quality factor, the sensor achieves a frequency shift sensitivity of 0.086 MHz/mg/dL and an amplitude sensitivity of 0.02 dB/mg/dL, compared to 0.032 MHz/mg/dL and 0.0116 dB/mg/dL observed in the standard CSRR structure. This confirms a significant enhancement in sensing performance and field confinement due to the optimized inductive loading. These results represent significant enhancements of approximately 168% and 72%, respectively. With its compact design, increased sensitivity, and potential for wearable implementation, the proposed sensor offers a promising platform for continuous, real-time, and non-invasive glucose monitoring in biomedical applications. Full article

(This article belongs to the Section Biosensors)

21 pages, 3100 KB

Open AccessArticle

Toxicological Assessment of Trace Element Exposure in Relation to Sudden Unexplained Death (SUD): Environmental Geochemistry and Dietary Risk in Central-Eastern Yunnan, China

by Yangchun Han, Litao Hao, Shixi Zhang and Kunli Luo

Toxics 2025, 13(12), 1078; https://doi.org/10.3390/toxics13121078 (registering DOI) - 14 Dec 2025

Abstract

Sudden Unexplained Death (SUD) has been reported in specific regions of Yunnan Province, China, yet its environmental causes remain unclear. This study aimed to explore the potential toxicological link between trace element exposure and SUD by investigating the concentrations of multiple elements in [...] Read more.

Sudden Unexplained Death (SUD) has been reported in specific regions of Yunnan Province, China, yet its environmental causes remain unclear. This study aimed to explore the potential toxicological link between trace element exposure and SUD by investigating the concentrations of multiple elements in soil, corn, and drinking water from typical SUD and non-SUD villages in central-eastern Yunnan. Elemental abundances were determined, and dietary exposure and non-carcinogenic health risks for adults and children were assessed. Results showed that soils in SUD villages were markedly deficient in Na but enriched in Se and Cr compared with non-SUD villages. Corn and drinking water were generally low in essential trace elements, with notable Co deficiency in corn and Fe, Li, Mn, and Cu deficiency in water. Cr and Mn in corn were identified as the main contributors to non-carcinogenic risks, especially for children. Comparative analysis with Keshan Disease (KD) villages in Shaanxi Province indicated distinct elemental patterns, suggesting different pathogenic mechanisms. Overall, environmental Na deficiency and exposure to Cr and Mn may be potential toxicological factors associated with SUD, warranting further investigation into their physiological effects and regional disease etiology. Full article

(This article belongs to the Topic Disease Risks and Toxic Pathway from Environmental Chemical Exposure)

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21 pages, 10280 KB

Open AccessArticle

A Clinically Relevant Classification and Staging System for Chronic Rhinosinusitis with Nasal Polyposis: A Cross-Sectional Study

by Goran Latif Omer, Stefano Di Girolamo, Sahand Soran Ali, Riccardo Maurizi, Sveva Viola and Giuseppe De Donato

Diagnostics 2025, 15(24), 3197; https://doi.org/10.3390/diagnostics15243197 (registering DOI) - 14 Dec 2025

Abstract

Background/Objectives: Tissue eosinophilia plays a central role in chronic rhinosinusitis with nasal polyposis (CRSwNP), yet the spectrum of disease, particularly central compartment atopic disease (CCAD), remains underexplored. This study aimed to classify CRSwNP into three distinct phenotypes, eosinophilic CRSwNP (ECRSwNP), non-eosinophilic CRSwNP (NECRSwNP), [...] Read more.

Background/Objectives: Tissue eosinophilia plays a central role in chronic rhinosinusitis with nasal polyposis (CRSwNP), yet the spectrum of disease, particularly central compartment atopic disease (CCAD), remains underexplored. This study aimed to classify CRSwNP into three distinct phenotypes, eosinophilic CRSwNP (ECRSwNP), non-eosinophilic CRSwNP (NECRSwNP), and CCAD, based on radiologic and endoscopic features. It also proposes a novel severity-based staging system to guide clinical decision-making. Methods: A cross-sectional observational study was conducted in a single private clinic between January 2019 and August 2025. Patients were assessed using clinical history, paranasal sinus computed tomography (CT), and intranasal endoscopy. Key variables included symptom clusters, comorbidities, hematologic and atopy profiles, radiologic and endoscopic findings, histopathology, and pre-treatment SNOT-22 scores. Results: A total of 2060 patients (mean age: 29.8 ± 11 years; 51.8% male) were included. Asthma was the most frequent comorbidity (23.5%). Classification into ECRSwNP, NECRSwNP, and CCAD was achieved using integrated clinical, radiologic, and histopathologic criteria. Conclusions: This study presents a phenotype- and severity-based classification system for CRSwNP that incorporates endoscopic and radiologic features. This framework may enhance diagnostic accuracy and enable more tailored therapeutic strategies. Full article

(This article belongs to the Section Clinical Diagnosis and Prognosis)

12 pages, 1115 KB

Open AccessArticle

Click Detect: A Rapid and Sensitive Assay for Shiga Toxin 2 Detection

by Benjamin M. Thomas, Emma L. Webb, Katherine L. Yan, Alexi M. Fernandez and Zhilei Chen

Biosensors 2025, 15(12), 813; https://doi.org/10.3390/bios15120813 (registering DOI) - 14 Dec 2025

Abstract

Shiga toxin-producing Escherichia coli (STEC) is a major foodborne pathogen, responsible for severe gastrointestinal disease and hemolytic uremic syndrome (HUS). Here, we report Click Detect, a novel diagnostic platform that leverages click display to efficiently produce sensing probes for sandwich-style antigen detection. Click [...] Read more.

Shiga toxin-producing Escherichia coli (STEC) is a major foodborne pathogen, responsible for severe gastrointestinal disease and hemolytic uremic syndrome (HUS). Here, we report Click Detect, a novel diagnostic platform that leverages click display to efficiently produce sensing probes for sandwich-style antigen detection. Click display is an in vitro protein display technology that generates uniform and covalently linked protein–cDNA conjugates in a simple one-pot reaction format within 2 h. The captured sensing probe can be quantified by standard nucleic acid amplification assays. Using click displayed DARPin (D_#20) as the sensing probe and a high-affinity nanobody (N_G1) as the capture reagent, Click Detect reliably detected Shiga toxin 2 (Stx2) at 600 fM by quantitative PCR (qPCR) and 6 pM by loop-mediated isothermal amplification (LAMP). The assay maintained comparable sensitivity in matrices containing up to 40% public swimming pool water or lettuce extract, highlighting robustness for real-world surveillance applications. Key advantages of Click Detect include simple, rapid, and cost-effective (~USD 0.04 per assay) sensing probe preparation, as well as a versatile plug-and-play probe format for detecting other targets. We believe that Click Detect has great potential as a novel sensing platform for food/environmental monitoring and point-of-care diagnostics, with potentially broad applicability to other toxins and protein targets. Full article

(This article belongs to the Special Issue Sensors for Detection of Bacteria and Their Toxins)

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13 pages, 826 KB

Open AccessArticle

Gene-Level Analyses of Novel Olfactory-Related Signal from Severe SARS-CoV-2 GWAS Reveal Association with Disease Mortality

by Yu Chen Zhao, Xinan Wang, Yujia Lu, Rounak Dey, Yuchen Liu, Francesca Giacona, Elizabeth A. Abe, Emma White, Li Su, Qingyi Wei, Xihong Lin, Lorelei A. Mucci, Jehan Alladina and David C. Christiani

COVID 2025, 5(12), 206; https://doi.org/10.3390/covid5120206 (registering DOI) - 14 Dec 2025

Abstract

Importance: The coronavirus disease 2019 (COVID-19) was the third leading cause of mortality in the United States for three years in a row. The genetic contributions to disease severity remain unclear and many previously identified single nucleotide polymorphisms (SNPs) have not been replicated [...] Read more.

Importance: The coronavirus disease 2019 (COVID-19) was the third leading cause of mortality in the United States for three years in a row. The genetic contributions to disease severity remain unclear and many previously identified single nucleotide polymorphisms (SNPs) have not been replicated nor linked with functional significance. Objective: To identify SNPs associated with mortality among hospitalized COVID-19 patients supplemented by expression quantitative trait loci (eQTL) evidence to infer plausible functional mechanisms related to COVID-19 severity. Design: A quality-controlled genome-wide association study (GWAS) supported by robust gene-level omnibus kernel association tests (SKAT-O), functional prediction, and eQTL analyses of the top GWAS signal. Setting: Massachusetts General Hospital (MGH). Participants: 370 adult ICU patients with SARS-CoV-2 infection and acute hypoxemic respiratory failure and floor patients with mild hypoxemia managed with supplemental oxygen consecutively admitted to MGH between March and June 2020 (Surge 1), and January and March 2021 (Surge 2) with baseline clinical characteristics and demographics collected. Exposures: Low-pass genotyped SNPs from whole blood and aggregated SNP-sets of potential disease susceptibility loci with

\pm

500 kb flanking regions. Main Outcomes & Measures: Genome-wide individual SNP associations and SNP-set associations with mortality outcomes from 370 severe COVID-19 cases. Results: After LD pruning (<0.8) and false discovery rate adjustment (<0.05), we identified rs7420371 G>A of the receptor transporter protein 5 (RTP5) gene as the top independent signal significantly associated with 30- and 60-day mortality among severe COVID-19 patients (OR, 2.32; 95% CI, 1.59–3.39; p = 4.92 × 10⁻⁹ and OR, 2.06; 95% CI, 1.43–2.97; p = 5.43 × 10⁻⁸, respectively). SKAT-O analyses on the RTP5 SNP-set showed associations with both mortality outcomes (p = 5.90 × 10⁻⁵ and 6.17 × 10⁻⁵, respectively). eQTL analysis showed rs7420371 A allele significantly upregulated the mRNA expression of RTP5 in 266 cerebellum tissues, in 277 cerebellar hemisphere tissues, and in 270 cerebral cortex samples. Conclusions & Relevance: We discovered a novel, independent, and potentially functional SNP RTP5 rs7420371 G>A to be significantly associated with COVID-19 mortality. The A allele is significantly associated with elevated mRNA expression of RTP5 in the brain, an important protein coding gene that modulates olfactory binding and taste perceptions in response to SARS-CoV-2 infection. Full article

(This article belongs to the Section Long COVID and Post-Acute Sequelae)

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20 pages, 4533 KB

Open AccessArticle

YOLOv11-LADC: A Lightweight Detection Framework for Micro–Nano Damage Precursors in Thermal Barrier Coatings

by Cong Huang, Xing Peng, Feng Shi, Ci Song, Hongbing Cao, Xinjie Zhao and Hengrui Xu

Nanomaterials 2025, 15(24), 1878; https://doi.org/10.3390/nano15241878 (registering DOI) - 14 Dec 2025

Abstract

Performance breakthroughs and safety assurance of aerospace equipment are critical to the advancement of modern aerospace technology. As a key protective system for the hot-end components of aeroengines, thermal barrier coatings (TBCs) play a vital role in ensuring the safe operation of aeroengines [...] Read more.

Performance breakthroughs and safety assurance of aerospace equipment are critical to the advancement of modern aerospace technology. As a key protective system for the hot-end components of aeroengines, thermal barrier coatings (TBCs) play a vital role in ensuring the safe operation of aeroengines and overall flight safety. To address the core detection technology challenge for micro–nano damage precursors in aerospace TBCs, this study proposes an enhanced detection framework, namely YOLOv11-LADC. Specifically, the framework integrates the LSKA attention mechanism to construct the C2PSA-LA module, thereby enhancing the detection capability for micro–nano damage precursors and adaptability to complex small-sample datasets. Additionally, it introduces deformable convolutions (DeformConv) to build the C3k2-DeformCSP module, which dynamically adapts to the irregular deformations of micro–nano damage precursors while reducing computational complexity. A data augmentation strategy incorporating 19 transformations is employed to expand the dataset to 5140 images. A series of experimental results demonstrates that, compared with the YOLOv11 baseline model, the proposed model achieves a 1.6% improvement in precision (P) and a 2.0% increase in recall (R), while maintaining mAP50 and mAP50-95 at near-constant levels. Meanwhile, the computational complexity (GFLOPs) is reduced to 6.2, validating the superiority of the enhanced framework in terms of detection accuracy and training efficiency. This further confirms the feasibility and practicality of the YOLOv11-LADC algorithm for detecting multi-scale micro–nano damage precursors in aerospace TBCs. Overall, this study provides an effective solution for the intelligent, high-precision, and real-time detection of multi-scale micro–nano damage precursors in aerospace TBCs. Full article

(This article belongs to the Section Nanoelectronics, Nanosensors and Devices)

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24 pages, 4862 KB

Open AccessArticle

Computational Modeling of the Temperature Distribution in a Butt Weld of AISI 304L Stainless Steel Using a Volumetric Heat Source

by Thiago da Silva Machado, Thiago da Silveira, Liércio André Isoldi and Luiz Antônio Bragança da Cunda

Metals 2025, 15(12), 1371; https://doi.org/10.3390/met15121371 (registering DOI) - 14 Dec 2025

Abstract

The Finite Element Method is an indispensable tool for analyzing the transient thermal phenomena in welding processes. This study aims to simulate the temperature field during Gas Metal Arc Welding of an AISI 304L V-groove butt joint, employing a volumetric heat source model. [...] Read more.

The Finite Element Method is an indispensable tool for analyzing the transient thermal phenomena in welding processes. This study aims to simulate the temperature field during Gas Metal Arc Welding of an AISI 304L V-groove butt joint, employing a volumetric heat source model. The numerical simulations were conducted using ABAQUS SIMULIA^® (version 6.11-3) on a plate measuring 200 mm × 50 mm × 9.5 mm. For validation, the numerical results were compared against experimental data obtained at the Welding Engineering Research Laboratory of Federal University of Rio Grande. A parametric study was performed by varying the geometric parameter b (controlling the volumetric heat distribution depth) to enhance the model’s accuracy and achieve the closest approximation to experimental observations. The calibrated volumetric source demonstrated high accuracy, yielding low percentage differences between predicted and experimental peak temperatures: 1.02%, 2.50%, and 4.44% at the 4 mm, 8 mm, and 12 mm thermocouple positions, respectively. Full article

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22 pages, 6964 KB

Open AccessArticle

Thermal, Structural, and Phase Evolution of the Y₂(SO₄)₃*8H₂O–Eu₂(SO₄)₃*8H₂O System via Dehydration and Volatilization to Y₂(SO₄)₃–Eu₂(SO₄)₃ and Y₂O₂(SO₄)–Eu₂O₂(SO₄) and Its Thermal Expansion

by Andrey P. Shablinskii, Olga Yu. Shorets, Rimma S. Bubnova, Maria G. Krzhizhanovskaya, Margarita S. Avdontceva and Stanislav K. Filatov

Minerals 2025, 15(12), 1304; https://doi.org/10.3390/min15121304 (registering DOI) - 14 Dec 2025

Abstract

The synthesis, crystal structure, phase transformations, and thermal expansion of (Y_1–xEu_x)₂(SO₄)₃*8H₂O (where x = 0, 0.17, 0.33, 0.50, 0.66, 0.83, and 1) are presented. (Y_1–xEu_x) [...] Read more.

The synthesis, crystal structure, phase transformations, and thermal expansion of (Y_1–xEu_x)₂(SO₄)₃*8H₂O (where x = 0, 0.17, 0.33, 0.50, 0.66, 0.83, and 1) are presented. (Y_1–xEu_x)₂(SO₄)₃*8H₂O solid solutions were synthesized via crystallization from an aqueous solution. (Y_1–xEu_x)₂(SO₄)₃*8H₂O (C2/c) ↔ (Y_1–xEu_x)₂(SO₄)₃ (Pbcn) → (Y_1–xEu_x)₂O₂SO₄ (C2/c) and Eu₂(SO₄)₃*8H₂O (C2/c) ↔ Eu₂(SO₄)₃ (C2/c) → Eu₂O₂SO₄ (C2/c) phase transformations for all samples were investigated by high-temperature powder X-ray diffraction, differential scanning calorimetry and thermogravimetry in the temperature ranges of 25–750 and 25–1350 °C, respectively. The aim of this work is to identify the structural heredity of the phases formed during thermal transformations of (Y_1–xEu_x)₂(SO₄)₃*8H₂O solid solutions, and to study the mechanisms of the thermal deformations of the crystal structure. Structural relations between these phases were found. The crystal structures of YEu(SO₄)₃*8H₂O and (Y_0.83Eu_0.17)₂(SO₄)₃*8H₂O were refined at −173, −123, −73, −23, 27, and 77 °С. Thermal expansion coefficients for (Y_1–xEu_x)₂(SO₄)₃*8H₂O, Eu₂(SO₄)₃, (Y_1–xEu_x)₂O₂SO₄ (where x = 0, 0.17, 0.33, 0.50, 0.66, 0.83, and 1) compounds and solid solutions were calculated for the first time. The thermal expansion of Eu₂(SO₄)₃ was highest in the direction approximately coinciding with the c-axis, because the Eu–O chains extended in this direction. As temperature increased, the crystal structure of (Y_1–xEu_x)₂(SO₄)₃*8H₂O expanded significantly in the ac plane along directions close to the a and c axes, while thermal expansion along the b axis was relatively low. The distance between layers in the (Y_1–xEu_x)₂(SO₄)₃*8H₂O crystal structure increased with increasing temperature, and corrugated layers (parallel to (101) direction) straightened out due to the rotation of the S2O₄ tetrahedra. At high temperature, thermal expansion of Y₂O₂SO₄ was highest along the longer diagonal of the ac parallelogram perpendicular to the plane of the oxo-centered

\frac{2}{\infty}

[YO] layers. Full article

(This article belongs to the Special Issue Crystal Chemistry of Sulfate Minerals and Synthetic Compounds)

18 pages, 1309 KB

Open AccessArticle

Seed Coating Synergies: Harnessing Plant Growth Regulators to Strengthen Soybean Nodulation and Stress Resilience

by Saranyapath Pairintra, Nantakorn Boonkerd, Neung Teaumroong and Kamolchanok Umnajkitikorn

Agronomy 2025, 15(12), 2876; https://doi.org/10.3390/agronomy15122876 (registering DOI) - 14 Dec 2025

Abstract

Soybean (Glycine max) is a globally important crop, but its productivity is often limited by suboptimal nodulation and nitrogen fixation, particularly under stress conditions. Bradyrhizobium diazoefficiens strain USDA110 is widely applied to enhance nodulation, yet its efficiency can be further improved [...] Read more.

Soybean (Glycine max) is a globally important crop, but its productivity is often limited by suboptimal nodulation and nitrogen fixation, particularly under stress conditions. Bradyrhizobium diazoefficiens strain USDA110 is widely applied to enhance nodulation, yet its efficiency can be further improved by phytohormone modulation. This study examined the effects of seed coatings containing plant growth regulators (PGRs)—acetylsalicylic acid (ASA), aminoethoxyvinylglycine (AVG), Indole-3-butyric acid (IBA), and 6-benzylaminopurine (BAP)—at varying concentrations (5, 50, and 500 nM), in combination with USDA110, on nodulation, nitrogenase activity, ethylene emission, physiological traits, and yield of soybean cultivar CM60. Laboratory assays identified 50 nM AVG, 5 nM IBA, and 5 nM ASA as optimal treatments, significantly enhancing nodule number and nitrogenase activity more than 32% and 28%, as, respectively, compared to untreated seeds. Greenhouse trials in pots, both under well-watered and water stress conditions, showed that USDA110 + AVG/IBA significantly improved photosynthetic rate (+21 and +18% compared to USDA110 alone) and increased plant height. Notably, USDA110 + AVG/IBA treatments sustained higher seed weight under drought, increasing it by over 25%, indicating strong synergistic effects in mitigating stress impacts. These findings highlighted that integrating USDA110 with specific PGRs represented a promising strategy to optimize nitrogen fixation and enhanced soybean productivity under both favorable and challenging conditions. Full article

(This article belongs to the Section Agricultural Biosystem and Biological Engineering)

23 pages, 1787 KB

Open AccessArticle

Does Xenophobia Among Local Residents Affect Sustainable Tourism Development in China? A Study Based on Attribution Theory and Social Identity Theory

by Peng Gao and Zong-Yi Zhu

Sustainability 2025, 17(24), 11201; https://doi.org/10.3390/su172411201 (registering DOI) - 14 Dec 2025

Abstract

Research on xenophobia in inbound tourism is relatively scarce, and the literature focusing on the support of local residents’ xenophobia for inbound tourism is even more limited. Using attribution theory as the guiding framework and incorporating social identity theory, this study systematically explored [...] Read more.

Research on xenophobia in inbound tourism is relatively scarce, and the literature focusing on the support of local residents’ xenophobia for inbound tourism is even more limited. Using attribution theory as the guiding framework and incorporating social identity theory, this study systematically explored Chinese residents’ attitudes towards inbound tourism and focused on three types of social identities––cultural, environmental, and place identities, as well as xenophobia of local residents. Residents in Yangzhou, China were surveyed, yielding 401 valid questionnaires for analysis. The results showed that cultural and place identities significantly negatively affected residents’ xenophobia, while environmental identity had no significant effect on residents’ xenophobia. In addition, residents’ xenophobia significantly negatively affected their community participation as well as their endorsement of inbound tourism. Secondly, residents’ cultural and place identities indirectly influence their endorsement of inbound tourism through xenophobia. Finally, social distance played a significant moderating role in certain pathways, specifically in moderating the relationship between cultural identity and xenophobia, and between xenophobia and endorsement of inbound tourism. This study extends the research on the factors affecting inbound tourism, which is significant for promoting the sustainable development of inbound tourism. Full article

(This article belongs to the Special Issue Moving beyond Sustainable Tourism Rediscovery through Regenerative Travel)

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22 pages, 1760 KB

Open AccessArticle

Modeling Energy Storage Systems for Cooperation with PV Installations in BIPV Applications

by Grzegorz Trzmiel, Damian Głuchy, Stanisław Mikulski, Nikodem Sowinski and Leszek Kasprzyk

Energies 2025, 18(24), 6546; https://doi.org/10.3390/en18246546 (registering DOI) - 14 Dec 2025

Abstract

The main objective of this article is to model, simulate, and analyze the interaction of energy storage systems with BIPV installations. Currently, due to the instability of energy generation, the economic challenges of integrating PV installations into the electricity grid, and the desire [...] Read more.

The main objective of this article is to model, simulate, and analyze the interaction of energy storage systems with BIPV installations. Currently, due to the instability of energy generation, the economic challenges of integrating PV installations into the electricity grid, and the desire to increase self-consumption, energy storage facilities are becoming increasingly popular. Subsidy programs most often favor PV installations, including BIPV, that work with energy storage devices. Therefore, there is a justified need to model energy storage devices for use with BIPV. The article describes the rationale for the benefits of using energy storage systems within current billing models, using Poland as an example. The introduction also provides an overview of the most popular energy storage technologies compatible with renewable energy installations. To achieve these objectives, appropriate system solutions were designed in the MATLAB environment and used to perform simulations, taking into account variable energy demand. An economic analysis of the system’s operation was conducted using a prosumer net-billing model, and adjustments were made to the system configuration. It has been shown that the use of appropriate energy storage solutions, cooperating with photovoltaic installations, allows for increased self-consumption and more efficient management of electricity obtained in BIPV, which has a positive impact on the payback time and economic profits. The analysis method used and the results obtained are true for the assumed known load profile; however, the method can be successfully applied to various load profiles. Full article

(This article belongs to the Special Issue Building-Integrated Photovoltaics: Prospects, Theories and Key Technologies)

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3 pages, 196 KB

Open AccessEditorial

Bio-Nanocomposite Coatings: A Potential Strategy to Improve the Overall Performance of Food Packaging Materials

by Daniele Carullo and Stefano Farris

Coatings 2025, 15(12), 1474; https://doi.org/10.3390/coatings15121474 (registering DOI) - 14 Dec 2025

Abstract

Growing concern over the environmental impact of fossil-based plastics used in food packaging has prompted new legislative action (most notably EU Regulation 2025/40, commonly referred to as the “Packaging and Packaging Waste Regulation”) demanding a transition toward more sustainable and highly functional alternatives [...] Read more.

Growing concern over the environmental impact of fossil-based plastics used in food packaging has prompted new legislative action (most notably EU Regulation 2025/40, commonly referred to as the “Packaging and Packaging Waste Regulation”) demanding a transition toward more sustainable and highly functional alternatives [...] Full article

(This article belongs to the Special Issue Bio-Nanocomposite Coatings: A Potential Strategy to Improve the Overall Performance of Food Packaging Materials)

18 pages, 4087 KB

Open AccessArticle

Characterization of VOCs at Shaoxing in the Winter Campaign: Sources and Chemical Reactivity

by Dongfeng Shi, Yan Lyu, Junpeng Song, Qing Ren, Xing Chen, Liyong Hu, Wenting Zhuge, Kewen Hu, Dongmei Cai, Xianda Gong and Jianmin Chen

Atmosphere 2025, 16(12), 1404; https://doi.org/10.3390/atmos16121404 (registering DOI) - 14 Dec 2025

Abstract

Despite recent improvements in particulate matter (PM) pollution, haze events still frequently occur in many regions of China. Volatile organic compounds (VOCs), as key precursors in atmospheric photochemistry, play a crucial role in haze formation. To elucidate their contributions, high-resolution hourly VOC measurements [...] Read more.

Despite recent improvements in particulate matter (PM) pollution, haze events still frequently occur in many regions of China. Volatile organic compounds (VOCs), as key precursors in atmospheric photochemistry, play a crucial role in haze formation. To elucidate their contributions, high-resolution hourly VOC measurements were conducted in Shaoxing, an industrial city in eastern China, during a winter field campaign from 1 December 2023 to 15 January 2024. The VOC groups were dominated by alkanes (31.5–53.8%), followed by alkenes (7.1–15.1%) and aromatics (6.7–14.1%). Positive Matrix Factorization (PMF) analysis resolved six major VOC sources: vehicle emissions (VE, 33.8%), combustion sources (CS, 20.0%), industrial emissions (IE, 13.4%), gasoline evaporation (GE, 14.6%), solvent usage (SU, 6.9%), and biogenic activities (BA, 12.6%). Based on the PMF results, we further evaluated the source-specific contributions of VOCs to OH radical loss rate (L_OH), ozone formation potential (OFP), and secondary organic aerosol potential (SOAP). During the haze episode, GE was the dominant driver of L_OH (33%), while IE (23%), GE (22%), and VE (20%) were major SOAP contributors. In contrast, during the other periods, CS contributed most to both OFP (24%) and SOAP (28%), followed by VE (22–23%). Overall, our study highlights the critical role of anthropogenic activities in driving secondary pollution and suggests that sector-specific mitigation strategies hold significant potential for local haze abatement. Full article

(This article belongs to the Section Air Quality)

16 pages, 954 KB

Open AccessArticle

Study of 3C-SiC Power MOSFETs

by Hamid Fardi

Micromachines 2025, 16(12), 1406; https://doi.org/10.3390/mi16121406 (registering DOI) - 14 Dec 2025

Abstract

This work presents the simulation and design of 3C-SiC power MOSFETs, focusing on critical parameters including avalanche impact ionization, breakdown voltage, bulk and channel mobilities, and the trade-off between on-resistance and breakdown voltage. The device design is carried out by evaluating the blocking [...] Read more.

This work presents the simulation and design of 3C-SiC power MOSFETs, focusing on critical parameters including avalanche impact ionization, breakdown voltage, bulk and channel mobilities, and the trade-off between on-resistance and breakdown voltage. The device design is carried out by evaluating the blocking voltage of scaled structures as a function of the blocking layer’s doping concentration. To mitigate edge-effect breakdown at the p-well/n-drift interface, a step-profile doping strategy is employed. Multiple transistor layouts with varying pitches are developed using a commercially available device simulator. Results are benchmarked against a one-dimensional analytical model, validating the on-state resistance, current–voltage behavior, and overall accuracy of the simulation approach. For the selected material properties, simulations predict that a 600 V 3C-SiC MOSFET achieves an on-state resistance of 0.8 mΩ·cm², corresponding to a 7 μm drift layer with a doping concentration of 1 × 10¹⁶ cm⁻³. Full article

(This article belongs to the Special Issue Recent Advances in Field-Effect Transistors: Materials, Devices, and Emerging Applications)

24 pages, 2729 KB

Open AccessArticle

Analysis of Ionospheric TEC Anomalies Using BDS High-Orbit Satellite Data: A Regional Statistical Study and a Case Study of the 2023 Jishishan Ms6.2 Earthquake

by Xiao Gao, Hanyi Cao, Ranran Shen, Meiting Xin, Penggang Tian and Lin Pan

Remote Sens. 2025, 17(24), 4032; https://doi.org/10.3390/rs17244032 (registering DOI) - 14 Dec 2025

Abstract

This study presents a comprehensive analysis of pre- and co-seismic ionospheric disturbances associated with the 2023 Ms6.2 Jishishan earthquake by leveraging the unique observational strengths of BDS, particularly its high-orbit satellites. A multi-parameter space weather index was employed to effectively isolate seismogenic signals [...] Read more.

This study presents a comprehensive analysis of pre- and co-seismic ionospheric disturbances associated with the 2023 Ms6.2 Jishishan earthquake by leveraging the unique observational strengths of BDS, particularly its high-orbit satellites. A multi-parameter space weather index was employed to effectively isolate seismogenic signals from geomagnetic disturbances, confirming that the main shock occurred during geomagnetically quiet conditions. Statistical analysis of 41 historical earthquakes (Mw ≥ 5.5) reveals that 47.2% were associated with detectable Total Electron Content (TEC) anomalies. An inverse correlation between earthquake magnitude and anomaly detectability within a 31-day window suggests prolonged precursor durations for larger events may produce longer-duration precursory signals, which challenge conventional detection methods. The synergistic capabilities of BDS Geostationary Earth Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO) satellites were demonstrated: GEO satellites provide unprecedented temporal stability for continuous TEC monitoring, while IGSO satellites enable high-resolution spatial mapping of Co-seismic Ionospheric Disturbances (CIDs). The detected CIDs propagated at velocities below 1.6 km/s, consistent with acoustic gravity wave (AGW) mechanisms. A case study during a geomagnetically active period further reveals modulated CID propagation characteristics, indicating potential coupling between seismic forcing and space weather. Our findings validate BDS as a powerful and precise tool for ionospheric seismology and provide critical insights into Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) dynamics. Full article

(This article belongs to the Section Earth Observation Data)

13 pages, 1220 KB

Open AccessArticle

Reproductive Ecology and Early-Life Morphological Development of Krabi Mouth-Brooding Fighting Fish Betta simplex Kottelat, 1994 (Actinopterygii: Osphronemidae)

by Santi Poungcharean, Idsariya Wudtisin, Soranath Sirisuay, Phongchate Pichitkul and Sommai Janekitkarn

Diversity 2025, 17(12), 856; https://doi.org/10.3390/d17120856 (registering DOI) - 14 Dec 2025

Abstract

The Krabi mouth-brooding fighting fish, Betta simplex Kottelat, 1994, is a critically endangered and endemic fish species in Krabi province, Southern Thailand. Little information is available on its reproductive ecology and early developmental morphology, which are essential for studying its conservation. Generally, B. [...] Read more.

The Krabi mouth-brooding fighting fish, Betta simplex Kottelat, 1994, is a critically endangered and endemic fish species in Krabi province, Southern Thailand. Little information is available on its reproductive ecology and early developmental morphology, which are essential for studying its conservation. Generally, B. simplex is considered an adaptable animal that can tolerate lower alkalinity and higher hardness compared to its natural environment conditions. In this study, wild broodstocks of B. simplex were collected from the reported type localities and bred in captivity under laboratory conditions for size-series collection. Some biological aspects of B. simplex in its natural environmental conditions were determined. We found that its flaring and mating behavior was similar to those of bubble-nesting fighting fish but did not involve bubble-nest building. The fertilized eggs and pre-flexion larvae were nurtured in the mouth cavity of parental males within 11–12 (mode = 11) days after fertilization (DAF). The first-release offspring developed to the post-flexion stage with a body size of 4.39 ± 0.01 mm of standard length (SL; n = 6) and then to the juvenile stage within 30 days after release with 11.72 ± 0.62 mm SL (n = 4). Thus, we propose the following linear regression equation for growth prediction by age (DAF) and body size (SL; mm): age = 0.2425 SL + 1.7036 (r² = 0.9549). The findings of this study will deepen our knowledge of the reproduction and ontogeny of B. simplex and contribute to its future conservation and management. Full article

(This article belongs to the Special Issue Ecology and Conservation of Endangered Wildlife)

28 pages, 4180 KB

Open AccessArticle

Ecofriendly Application of Synthetic Zinc Oxide Nanoparticles as Stress Regulator Bio-Fertilizer for Zea mays

by Mostafa Ahmed, Zoltán Tóth, Roquia Rizk, Muhammad Waqar Nasir and Kincső Decsi

Agronomy 2025, 15(12), 2875; https://doi.org/10.3390/agronomy15122875 (registering DOI) - 14 Dec 2025

Abstract

Agricultural production is consistently threatened by stressors such as salinity. Few studies have reported on the released antioxidative enzymes and the salinity-responsive genes identified using RNA sequencing and de novo assembly in maize. To further understand the harmony between stressing the maize with [...] Read more.

Agricultural production is consistently threatened by stressors such as salinity. Few studies have reported on the released antioxidative enzymes and the salinity-responsive genes identified using RNA sequencing and de novo assembly in maize. To further understand the harmony between stressing the maize with a NaCl solution as a compensatory water-irrigation method and spraying regulatory zinc oxide nanoparticles (ZnO/NPs), the salinity-responsive genes were analyzed using RNA sequencing and bioinformatics tools, and the antioxidant enzymatic activities were determined. Differential expression analysis was used to uncover genes that were up-/down-regulated during the experiment. The regulatory pathways and functions of differentially expressed genes (DEGs) were estimated. Glutathione reductase/-s-transferase (GR/GST), peroxidase (POX), superoxide dismutase (SOD), and catalase (CAT) enzymes were determined spectrophotometrically. Mitigating salinity stress with 150 mM NaCl led to significant oxidative stress, markedly elevating enzyme activities: POX and GST by 275% and 254%, GR by 166%, CAT by 91%, and SOD by 56%. Treatment with ZnO/NPs alleviated this stress, decreasing enzyme activity by 61% for GST, 55% for POX, 38% for CAT, 28% for SOD, and 25% for GR. The results of RNA-seq revealed candidate genes related to changes in stressed/non-stressed maize plants, regardless of whether they were sprayed with the nanoparticles or not. This study’s results offer novel insights into the genetic traits of maize subjected to salinity stress and ZnO/nanoparticle application, thereby advancing the comprehension of how ZnO/nanoparticles might alleviate the detrimental impacts of salinity on plants whose properties were enhanced to be used in the eco-friendly synthesis of nanoparticles that were used as a bio-fertilizer in priming plants. Full article

(This article belongs to the Special Issue Bio-Based Fertilizers and Soil Health: Innovations for Nutrient Recycling and Environmental Protection)

10 pages, 856 KB

Open AccessViewpoint

Immunosuppressive Therapy in Pediatric Kidney Transplantation: Evolution, Current Practices, and Future Directions

by Mohamed S. Al Riyami, Badria Al Gaithi, Naifain Al Kalbani and Suleiman Al Saidi

Biomedicines 2025, 13(12), 3084; https://doi.org/10.3390/biomedicines13123084 (registering DOI) - 14 Dec 2025

Abstract

Pediatric kidney transplantation (KTx) offers the best outcomes for children with end-stage renal disease (ESRD), offering dramatic improvements in survival, quality of life, growth, and developmental outcomes compared to dialysis. Modern regimens centered on tacrolimus, mycophenolate mofetil, and risk-adapted induction have substantially reduced [...] Read more.

Pediatric kidney transplantation (KTx) offers the best outcomes for children with end-stage renal disease (ESRD), offering dramatic improvements in survival, quality of life, growth, and developmental outcomes compared to dialysis. Modern regimens centered on tacrolimus, mycophenolate mofetil, and risk-adapted induction have substantially reduced acute rejection and improved graft survival. This viewpoint summarizes the evolution of pediatric immunosuppression, current practice trends, and emerging strategies aimed at minimizing toxicity while preserving long-term graft function. Recent data show increasing use of T-cell-depleting induction, selective application of IL-2 receptor antagonists, and gradual adoption of steroid-sparing and mTOR-based protocols. Nevertheless, progress is limited by a scarcity of pediatric randomized trials, continued reliance on extrapolated adult evidence, infection risk, long-term metabolic complications, and adherence challenges during adolescence. Insights from recent trials including steroid minimization, everolimus-based regimens, and selective Belatacept use highlight opportunities for more individualized, risk-adapted therapy. Future efforts must prioritize precision approaches supported by biomarkers, multicenter collaboration, and long-term follow-up. Overall, contemporary trends support a shift toward tailored immunosuppression that balances efficacy with safety to optimize outcomes in pediatric KTx recipients. Full article

(This article belongs to the Special Issue Innovations and Perspectives in Kidney Transplantation)

24 pages, 1600 KB

Open AccessReview

AI-Enabled Reduction of Animal Use in Cardiovascular Translational Medicine: Regulatory and Technological Perspectives

by Rasit Dinc and Nurittin Ardic

Life 2025, 15(12), 1916; https://doi.org/10.3390/life15121916 (registering DOI) - 14 Dec 2025

Abstract

Background: Animal studies remain fundamental to cardiovascular drug and device development, yet their ability to predict human responses is increasingly being questioned. The US Food and Drug Administration (FDA)’s April 2025 roadmap supports alternative testing approaches that strategically reduce animal use while increasing [...] Read more.

Background: Animal studies remain fundamental to cardiovascular drug and device development, yet their ability to predict human responses is increasingly being questioned. The US Food and Drug Administration (FDA)’s April 2025 roadmap supports alternative testing approaches that strategically reduce animal use while increasing human relevance by combining laboratory methods, computer simulations, and artificial intelligence. This review examines AI-enabled alternative methodologies for cardiovascular safety assessment within established validation frameworks and regulatory acceptance programs. We describe machine learning approaches for predicting cardiac safety risks, automated analysis of human heart cells, and patient-specific computer simulations for evaluating medical devices. These tools can improve our understanding of biological mechanisms, focus limited animal studies on critical questions, and accelerate decision-making. Regulatory acceptance requires rigorous validation appropriate to each specific use and decision context. Conclusion: We outline practical steps for establishing credibility, including transparent data documentation, independent testing, and identifying where models can be reliably applied, and identify remaining challenges in data standardization and regulatory readiness. With ongoing alignment between regulators, standards bodies, and product developers, these alternative approaches could significantly reduce reliance on animal testing in cardiovascular research while maintaining or improving the quality of evidence. Full article

(This article belongs to the Topic Animal Models of Human Disease 3.0)

21 pages, 6537 KB

Open AccessArticle

In Silico Lead Identification of Staphylococcus aureus LtaS Inhibitors: A High-Throughput Computational Pipeline Towards Prototype Development

by Abdulaziz H. Al Khzem, Tagyedeen H. Shoaib, Rua M. Mukhtar, Mansour S. Alturki, Mohamed S. Gomaa, Dania Hussein, Ahmed Mostafa, Layla A. Alrumaihi, Fatimah A. Alansari and Maisem Laabei

Int. J. Mol. Sci. 2025, 26(24), 12038; https://doi.org/10.3390/ijms262412038 (registering DOI) - 14 Dec 2025

Abstract

The emergence of multidrug-resistant Staphylococcus aureus underscores the urgent need for novel therapeutic agents targeting essential bacterial pathways. The lipoteichoic acid synthase (LtaS) is crucial for the synthesis of lipoteichoic acid in the cell wall of Gram-positive bacteria and represents a promising and [...] Read more.

The emergence of multidrug-resistant Staphylococcus aureus underscores the urgent need for novel therapeutic agents targeting essential bacterial pathways. The lipoteichoic acid synthase (LtaS) is crucial for the synthesis of lipoteichoic acid in the cell wall of Gram-positive bacteria and represents a promising and vulnerable target for antimicrobial drug development. This study employed a comprehensive computational pipeline to identify potent inhibitors of the LtaS enzyme. A library of natural compounds was retrieved from the COCONUT database and screened against the crystal structure of the extracellular domain of LtaS (eLtaS) (PDB ID: 2W5R, obtained from the Protein Data Bank) through a multi-stage molecular docking strategy. This process started with High-Throughput Virtual Screening (HTVS), followed by Standard Precision (SP) docking, and culminated in Extra Precision (XP) docking to refine the selection of hits. The top-ranking compounds from XP docking were subsequently subjected to MM-GBSA binding free energy calculations for further filtration. The stability and dynamic behavior of the resulting candidate complexes were then evaluated using 100 ns molecular dynamics (MD) simulations, which confirmed the structural integrity and binding stability of the ligands. Density Functional Theory calculations revealed that screened ligands exhibit improved electronic stabilization and charge-transfer characteristics compared to a reference compound, suggesting enhanced reactivity and stability relevant for hit identification. Finally, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiling was conducted to assess the drug-likeness and pharmacokinetic safety of the lead compounds. These findings support them as promising orally active leads for further optimization. Our integrated approach shortlisted eight initial hits (A–H) that showed interesting scaffold diversity and finally identified two compounds, herein referred to as Compound A and Compound B, which demonstrated stable binding, favorable free energy, and an acceptable Absorption, Distribution, Metabolism, and Excretion, and Toxicity (ADMET) profile. These candidates emerge as promising starting points for developing novel anti-staphylococcal agents targeting the LtaS enzyme that cand be further proved by experimental validation. Full article

(This article belongs to the Special Issue Artificial Intelligence and Computer-Aided Design: Molecular Simulation Technology in Exploring Bioactive Compounds for Health Promotion)

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48 pages, 1173 KB

Open AccessReview

Harnessing Machine Learning Approaches for the Identification, Characterization, and Optimization of Novel Antimicrobial Peptides

by Naveed Saleem, Naresh Kumar, Emad El-Omar, Mark Willcox and Xiao-Tao Jiang

Antibiotics 2025, 14(12), 1263; https://doi.org/10.3390/antibiotics14121263 (registering DOI) - 14 Dec 2025

Abstract

Antimicrobial resistance (AMR) has become a major health crisis worldwide, and it is expected to surpass cancer as one of the leading causes of death by 2050. Conventional antibiotics are struggling to keep pace with the rapidly evolving resistance trends, underscoring the urgent [...] Read more.

Antimicrobial resistance (AMR) has become a major health crisis worldwide, and it is expected to surpass cancer as one of the leading causes of death by 2050. Conventional antibiotics are struggling to keep pace with the rapidly evolving resistance trends, underscoring the urgent need for novel antimicrobial therapeutic strategies. Antimicrobial peptides (AMPs) function through diverse, often membrane-disrupting mechanisms that can address the latest challenges to resistance. However, the identification, prediction, and optimization of novel AMPs can be impeded by several issues, including extensive sequence spaces, context-dependent activity, and the higher costs associated with wet laboratory screenings. Recent developments in artificial intelligence (AI) have enabled large-scale mining of genomes, metagenomes, and quantitative species-resolved activity prediction, i.e., MIC, and de novo AMPs designed with integrated stability and toxicity filters. The current review has synthesized and highlighted progress across different discriminative models, such as classical machine learning and deep learning models and transformer embeddings, alongside graphs and geometric encoders, structure-guided and multi-modal hybrid learning approaches, closed-loop generative methods, and large language models (LLMs) predicted frameworks. This review compares models’ benchmark performances, highlighting AI-predicted novel hybrid approaches for designing AMPs, validated by in vitro and in vivo methods against clinical and resistant pathogens to increase overall experimental hit rates. Based on observations, multimodal paradigm strategies are proposed, focusing on identification, prediction, and characterization, followed by design frameworks, linking active-learning lab cycles, mechanistic interpretability, curated data resources, and uncertainty estimation. Therefore, for reproducible benchmarks and interoperable data, collaborative computational and wet lab experimental validations must be required to accelerate AI-driven novel AMP discovery to combat multidrug-resistant Gram-negative pathogens. Full article

(This article belongs to the Special Issue Novel Approaches to Prevent and Combat Antimicrobial Resistance)

23 pages, 6247 KB

Open AccessArticle

Biochar Particle Size Modulates the Microbial Degradation of Petroleum Hydrocarbons in Contaminated Soil

by Yanjie Wang, Qiong Wang, Meijuan Wang, Haiqing Lei and Jiabo Chen

Agronomy 2025, 15(12), 2874; https://doi.org/10.3390/agronomy15122874 (registering DOI) - 14 Dec 2025

Abstract

Petroleum hydrocarbons are pervasive soil pollutants that detrimentally affect the soil structure, nutrients, and microbial ecosystems. However, the effect of biochar particle size on the remediation effectiveness remains a critical, unresolved parameter. Here, a soil remediation experiment was conducted to evaluate the synergy [...] Read more.

Petroleum hydrocarbons are pervasive soil pollutants that detrimentally affect the soil structure, nutrients, and microbial ecosystems. However, the effect of biochar particle size on the remediation effectiveness remains a critical, unresolved parameter. Here, a soil remediation experiment was conducted to evaluate the synergy between biochars of different particle sizes and nutrient addition. Total petroleum hydrocarbons (TPHs) were quantified gravimetrically, and specific hydrocarbon fractions were analysed via gas chromatography mass spectroscopy (GC‒MS) while the microbial community composition was analysed via high-throughput sequencing. The results revealed that granular bulrush straw biochar (0.85 mm) with nutrients achieved the greatest TPH degradation (73.35%), significantly outperforming both powder biochar and soybean straw biochar. This enhanced remediation was associated with a significant shift in the microbial community (p < 0.05), characterized by substantial increases in hydrocarbon-degrading bacteria, particularly Actinobacteria and the genus Mycobacterium. This study revealed that the synergistic application of granular biochar and nutrients is a highly effective, nature-based strategy for petroleum-contaminated soil, which functions by resolving a critical biochar parameter to enhance key microbial degraders. Full article

(This article belongs to the Special Issue Soil Degradation and Restoration: Challenges and Prospects for Agroecological Development)

26 pages, 10331 KB

Open AccessArticle

STM-Net: A Multiscale Spectral–Spatial Representation Hybrid CNN–Transformer Model for Hyperspectral Image Classification

by Yicheng Hu, Jia Ge and Shufang Tian

Remote Sens. 2025, 17(24), 4031; https://doi.org/10.3390/rs17244031 (registering DOI) - 14 Dec 2025

Abstract

Hyperspectral images (HSIs) have been broadly applied in remote sensing, environmental monitoring, agriculture, and other fields due to their rich spectral information and complex spatial properties. However, the inherent redundancy, spectral aliasing, and spatial heterogeneity of high-dimensional data pose significant challenges to classification [...] Read more.

Hyperspectral images (HSIs) have been broadly applied in remote sensing, environmental monitoring, agriculture, and other fields due to their rich spectral information and complex spatial properties. However, the inherent redundancy, spectral aliasing, and spatial heterogeneity of high-dimensional data pose significant challenges to classification accuracy. Therefore, this study proposes STM-Net, a hybrid deep learning model that integrates SSRE (Spectral–Spatial Residual Extraction Module), Transformer, and MDRM (Multi-scale Differential Residual Module) architectures to comprehensively exploit spectral–spatial features and enhance classification performance. First, the SSRE module employs 3D convolutional layers combined with residual connections to extract multi-scale spectral–spatial features, thereby improving the representation of both local and deep-level characteristics. Second, the MDRM incorporates multi-scale differential convolution and the Convolutional Block Attention Module mechanism to refine local feature extraction and enhance inter-class discriminability at category boundaries. Finally, the Transformer branch equipped with a Dual-Branch Global-Local (DBGL) mechanism integrates local convolutional attention and global self-attention, enabling synergistic optimization of long-range dependency modeling and local feature enhancement. In this study, STM-Net is extensively evaluated on three benchmark HSI datasets: Indian Pines, Pavia University, and Salinas. Additionally, experimental results demonstrate that the proposed model consistently outperforms existing methods regarding OA, AA, and the Kappa coefficient, exhibiting superior generalization capability and stability. Furthermore, ablation studies validate that the SSRE, MDRM, and Transformer components each contribute significantly to improving classification performance. This study presents an effective spectral–spatial feature fusion framework for hyperspectral image classification, offering a novel technical solution for remote sensing data analysis. Full article

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