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16 pages, 5605 KB  
Article
Crystal Morphology Prediction of LTNR in Different Solvents by Molecular Dynamics Simulation
by Da Li, Liang Song, Yin Yu, Yan Li and Xue-Hai Ju
Chemistry 2025, 7(5), 161; https://doi.org/10.3390/chemistry7050161 - 1 Oct 2025
Abstract
Molecular dynamics simulations were conducted using the attachment energy (AE) model to investigate the growth morphology of lead 2,4,6-trinitrororesorcinate (LTNR, lead styphnate) under vacuum and different solvents. The adsorption energy of LTNR on (001), (110), (011), (020), (111), (200), and (201) crystal planes [...] Read more.
Molecular dynamics simulations were conducted using the attachment energy (AE) model to investigate the growth morphology of lead 2,4,6-trinitrororesorcinate (LTNR, lead styphnate) under vacuum and different solvents. The adsorption energy of LTNR on (001), (110), (011), (020), (111), (200), and (201) crystal planes were calculated. Meanwhile, the crystal morphology in solvents of ethanol, toluene, dichloromethane, acetone, dimethyl sulfoxide (DMSO), and water at 298 K was predicted by calculating the interaction energies between the solvents and crystal planes. The calculated results show that the morphology of LTNR crystals in different solvents is significantly different. In toluene, LTNR crystal morphologies are flat, while in pure solvents of ethanol, acetone, and DMSO, the number of crystal planes increases, and the crystal thickness is larger. In the water, LTNR tends to form tabular crystals, which is similar to the experimental results. Both radial distribution function (RDF) and mean squared displacement (MSD) analyses reveal that hydrogen bonding dominates the interactions between LTNR and solvent molecules. Solvent molecules with higher diffusion coefficients exhibit increased desorption tendencies from crystal surfaces, which may reduce their inhibitory effects on specific crystallographic planes. However, no direct correlation exists between solvent diffusion coefficients and crystal plane growth rates, suggesting that surface attachment kinetics or interfacial energy barriers play a more critical role in crystal growth. Full article
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18 pages, 301 KB  
Article
An Empirical Comparative Analysis of the Gold Market Dynamics of the Indian and U.S. Commodity Markets
by Swaty Sharma, Munish Gupta, Simon Grima and Kiran Sood
J. Risk Financial Manag. 2025, 18(10), 543; https://doi.org/10.3390/jrfm18100543 - 25 Sep 2025
Abstract
This study examines the dynamic relationship between the gold markets of India and the United States from 2005 to 2025. Recognising gold’s role as a hedge and safe-haven during market uncertainty, we employ the Autoregressive Distributed Lag (ARDL) model to assess long-term co-integration [...] Read more.
This study examines the dynamic relationship between the gold markets of India and the United States from 2005 to 2025. Recognising gold’s role as a hedge and safe-haven during market uncertainty, we employ the Autoregressive Distributed Lag (ARDL) model to assess long-term co-integration and apply the Toda–Yamamoto causality test to evaluate directional influences. Additionally, the Generalised Autoregressive Conditional Heteroskedasticity (GARCH) (1, 1) model is applied to examine volatility spillovers. Results reveal no long-term co-integration between the two markets, suggesting they function independently over time. However, unidirectional causality is observed from the U.S. to the Indian gold market, and the GARCH model confirms bidirectional volatility transmission, indicating interconnected short-run dynamics. These findings imply that gold market shocks in one country may affect short-term pricing in the other, but not long-term trends. From a portfolio diversification and risk management perspective, investors may benefit from allocating assets across both markets. This study contributes a novel empirical framework by integrating ARDL, Toda–Yamamoto Granger causality, and GARCH(1, 1) models over a two-decade period (2005–2025), incorporating post-COVID market dynamics. The combination of these methods, applied to both an emerging (India) and developed (U.S.) economy, provides a comprehensive understanding of gold market interdependence. In doing this, the paper offers valuable insights into causality, volatility transmission, and diversification potential. The econometric rigour of the study is enhanced through residual diagnostic tests, including tests of normality, autocorrelation, and other heteroscedasticity tests, as well as VAR stability tests. These ensure strong inference and model validity; more specifically, they are pertinent to the analysis of financial time series. Full article
(This article belongs to the Section Financial Markets)
15 pages, 1648 KB  
Article
The Concomitant Effect of the Antiepileptic Drug Lacosamide and rTMS on an SH-SY5Y Model of Neuronal Excitability
by Ioannis Dardalas, Efstratios K. Kosmidis, Vasilios K. Kimiskidis, Roza Lagoudaki, Theodoros Samaras, Theodoros Moysiadis, Dimitrios Kouvelas and Chryssa Pourzitaki
Neurol. Int. 2025, 17(10), 152; https://doi.org/10.3390/neurolint17100152 - 24 Sep 2025
Viewed by 67
Abstract
Background/Objectives: Epilepsy is identified by irregular neuronal hyperexcitability, generating recurrent seizures. Despite many available pharmacological treatments, certain patients with drug-resistant epilepsy may require novel therapeutic approaches. In the present study, we aimed to evaluate the effects of lacosamide, low-frequency repetitive transcranial magnetic [...] Read more.
Background/Objectives: Epilepsy is identified by irregular neuronal hyperexcitability, generating recurrent seizures. Despite many available pharmacological treatments, certain patients with drug-resistant epilepsy may require novel therapeutic approaches. In the present study, we aimed to evaluate the effects of lacosamide, low-frequency repetitive transcranial magnetic stimulation, and their combination on intracellular calcium dynamics in an in vitro model of neuronal excitability, hypothesizing that these interventions could mitigate potassium chloride-induced neuronal excitation. Methods: We utilized differentiated SH-SY5Y human neuroblastoma cells as an in vitro model of neuronal excitability. Neuronal excitability was induced with 50 mM KCl, and cells were treated with lacosamide (300 µM), rTMS (1 Hz), or their combination. Intracellular calcium levels were quantified using fluo-4 AM fluorescence calcium imaging, with changes expressed as percentage change in fluorescence intensity (%ΔF/F) relative to baseline. Results: The combination of lacosamide and rTMS was the most effective, significantly reducing KCl-induced calcium elevation (ΔF/F = 9.15) compared to lacosamide alone (ΔF/F = 17.11), rTMS alone (ΔF/F = 23.70), and the untreated cells serving as controls (ΔF/F = 66.70). The combination showed a statistically significant effect, with enhanced suppression of neuronal excitability compared to individual treatments. Conclusions: Lacosamide and low-frequency rTMS (1 Hz) effectively attenuated KCl-induced changes in intracellular calcium levels in vitro, with their combination demonstrating the highest efficacy. These findings suggest a promising foundation in the management of drug-resistant epilepsy. Future studies are necessitated to validate these results and benefit clinical translation. Full article
(This article belongs to the Special Issue Molecular Research of CNS Diseases and Neurological Disorders)
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26 pages, 3010 KB  
Article
Modeling Exchange Rate Volatility in India in Relation to COVID-19 and Lockdown Stringency: A Wavelet Coherence and Quantile Causality Approach
by Aamir Aijaz Syed, Assad Ullah, Simon Grima, Muhammad Abdul Kamal and Kiran Sood
Risks 2025, 13(9), 182; https://doi.org/10.3390/risks13090182 - 22 Sep 2025
Viewed by 202
Abstract
The COVID-19 pandemic and the implementation of strict lockdown measures have significantly impacted various dimensions of the global economy. This study examines the impact of COVID-19 and lockdown stringency on exchange rate volatility in India using three core variables, i.e., COVID-19 cases, the [...] Read more.
The COVID-19 pandemic and the implementation of strict lockdown measures have significantly impacted various dimensions of the global economy. This study examines the impact of COVID-19 and lockdown stringency on exchange rate volatility in India using three core variables, i.e., COVID-19 cases, the lockdown stringency index, and exchange rate volatility. To achieve the above objectives, we have employed advanced econometric techniques, such as wavelet coherence and a hybrid non-parametric quantile causality framework, on the dataset spanning from 30 December 2020 to 24 January 2022. Robustness is assessed using Troster–Granger causality in quantiles and Breitung–Candelon Spectral Causality tests. The wavelet coherence analysis indicates that the initial outbreak of COVID-19 increased the exchange rate volatility, while the enforcement of stringent lockdowns in the later phases helped reduce this volatility. Similarly, the hybrid quantile causality results indicate that both COVID-19 cases and lockdown measures possess predictive power over exchange rate fluctuations. The robustness checks confirm these findings and establish a causal relationship between the pandemic, policy responses, and currency market behaviour. This study helps clarify the complex, nonlinear dynamics between pandemic-related variables and exchange rate volatility in emerging markets. Based on the aforementioned result, it is recommended that policymakers implement targeted lockdown strategies coupled with timely monetary interventions (such as foreign exchange reserve management or interest rate adjustments) to mitigate volatility and maintain currency stability during future pandemic-induced shocks. Full article
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26 pages, 2434 KB  
Article
Assessment of Soil and Water Quality Indices in Agricultural Soils of Manouba Governorate, North-East Tunisia
by Oumayma Hmidi, Feyda Srarfi, Nadhem Brahim, Carmelo Dazzi and Giuseppe Lo Papa
Soil Syst. 2025, 9(3), 105; https://doi.org/10.3390/soilsystems9030105 - 19 Sep 2025
Viewed by 360
Abstract
Assessing soil and water quality in irrigated farming is vital for sustainable agriculture management. Low-quality irrigation water, particularly in semi-arid regions, poses environmental challenges and leads to soil salinization. This study was conducted in the Jedaida district, Manouba province, NE Tunisia. Forty-three soil [...] Read more.
Assessing soil and water quality in irrigated farming is vital for sustainable agriculture management. Low-quality irrigation water, particularly in semi-arid regions, poses environmental challenges and leads to soil salinization. This study was conducted in the Jedaida district, Manouba province, NE Tunisia. Forty-three soil and water samples were collected to develop indices for assessing soil quality. Sixteen indicators were selected using principal component analysis (PCA) for the minimum soil data set (MSD), including electrical conductivity, sand, organic soil carbon, and pH. The linear method shows a correlation with physical and chemical properties, classifying Jedaida soils into three quality metrics: good, moderate, and poor. The non-linear method displays the lowest indicator contribution in Zahira soils, followed by Mansoura soils (high and moderate). MSD combined with linear scoring is the most acceptable method of assessing the soil quality index (SQI). Water quality indices (WQIs) identify the suitability of irrigation. The results show a Kelly’s ratio > 1, a sodium adsorption ratio (SAR) > 10, and a sodium soluble percentage (SSP) varying from 40 to 60%. This highlights the negative effects of long-term irrigation with poor-quality water on soil health. Accordingly, groundwater was found to be unsuitable for irrigating surface soils. This finding emphasizes the importance of selecting suitable irrigation water to ensure soil quality. Full article
(This article belongs to the Special Issue Research on Soil Management and Conservation: 2nd Edition)
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16 pages, 3614 KB  
Article
Molecular Simulation Study on the Competitive Adsorption and Diffusion of CH4 and CO2 in Coal Nanopores with Different Pore Sizes
by Guangli Huang, Qinghua Zhang and Fujin Lin
Processes 2025, 13(9), 2990; https://doi.org/10.3390/pr13092990 - 19 Sep 2025
Viewed by 225
Abstract
Coalbed methane (CBM), mainly composed of methane (CH4) and carbon dioxide (CO2), has attracted increasing attention due to its dual significance as a clean energy resource and its role in greenhouse gas management. This research systematically examines the adsorption, [...] Read more.
Coalbed methane (CBM), mainly composed of methane (CH4) and carbon dioxide (CO2), has attracted increasing attention due to its dual significance as a clean energy resource and its role in greenhouse gas management. This research systematically examines the adsorption, desorption, diffusion, and bubble evolution dynamics of methane (CH4) and carbon dioxide (CO2) in graphene nanopores with diameters of 4 nm, 6 nm, and 8 nm by molecular dynamics simulations. Radial distribution function (RDF) analyses reveal strong solvation of both gases by water, with CO2 exhibiting slightly stronger interactions. Adsorption and desorption dynamics indicate that CO2 molecules display shorter residence times on the graphene surface (0.044–0.057 ns) compared with CH4 (0.055–0.062 ns), reflecting faster surface exchange. Gas-phase molecular number analysis demonstrates that CH4 accumulates more significantly in the vapor phase, while CO2 is more prone to adsorption and re-dissolution. Mean square displacement (MSD) results confirm enhanced molecular mobility in larger pores, with CH4 showing greater overall diffusivity. Structural evolution of the 8 nm system highlights asymmetric bubble dynamics, where large bubbles merge with the upper adsorption layer to form a thicker layer, while smaller bubbles contribute to a thinner layer near the lower surface. CH4 and CO2 follow similar pathways, though CO2 diffuses farther post-desorption due to its weaker surface retention. These results provide fundamental insights into confinement-dependent gas behavior in graphene systems, offering guidance for gas separation and storage applications. Full article
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14 pages, 2835 KB  
Article
Simulating Soil Carbon Under Variable Nitrogen Application, Planting, and Residue Management
by Tajamul Hussain, Charassri Nualsri, Muhammad Fraz Ali and Saowapa Duangpan
Soil Syst. 2025, 9(3), 104; https://doi.org/10.3390/soilsystems9030104 - 19 Sep 2025
Viewed by 217
Abstract
Effective residue management is crucial for maintaining soil organic carbon (SOC) in upland rice systems, particularly under diverse fertilization and planting management practices. This study investigates the impacts of residue management in upland rice fields using the CQESTR model through simulation of SOC [...] Read more.
Effective residue management is crucial for maintaining soil organic carbon (SOC) in upland rice systems, particularly under diverse fertilization and planting management practices. This study investigates the impacts of residue management in upland rice fields using the CQESTR model through simulation of SOC dynamics over a 20-year period. The first 10 years served as a spin-up period for carbon pool stabilization in the model, followed by simulations under varying nitrogen (N) application rates and planting date management strategies. Experiments for various N application rates and planting times were conducted during 2018–2019 and 2019–2020. In 2019, 30% and in 2020, 100% of the residue was returned, and these data were used for evaluating model performance. Subsequently, we modeled predictions for residue retention levels of 100%, 70%, 50%, and 30% to assess their effects on SOC. The results indicated a good agreement between the simulated and observed data for model performance evaluation with an MSD value of 9.13. Lack of correlation (0.44) accounted for 5% of MSD, indicating a good agreement between the simulated and observed SOC values. The highest change in SOC was observed at 100% residue return under moderately delayed planting, potentially due to higher crop productivity and residue retention, and moderate climatic conditions. Reduced residue retention gradually declined the SOC stocks, especially under low N input. Delays in planting exacerbated negative impacts, possibly due to low crop productivity and reduced residue return. Despite the limited number of years of data and inconsistent management practices, the overall trends highlight the importance of residue retention under different N fertilization and planting management strategies. This research serves as a preliminary study for sustainable management practices to enhance long-term soil carbon sequestration in upland rice systems in southern Thailand. Long-term evaluations are necessary using the observed data and the CQESTR model application for applicable recommendations. Full article
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24 pages, 1418 KB  
Article
Integrating Generative Artificial Intelligence in Clinical Dentistry: Enhancing Diagnosis, Treatment Planning, and Procedural Precision Through Advanced Knowledge Representation and Reasoning
by Hossam Dawa, Arthur Rodriguez Gonzalez Cortes, Carlos Ribeiro, José Neves and Henrique Vicente
Digital 2025, 5(3), 44; https://doi.org/10.3390/digital5030044 - 18 Sep 2025
Viewed by 265
Abstract
Generative artificial intelligence (GAI) is poised to transform clinical dentistry by enhancing diagnostic accuracy, personalizing treatment planning, and improving procedural precision. This study integrates logic programming and entropy within knowledge representation and reasoning to generate hypotheses, quantify uncertainty, and support clinical decisions. A [...] Read more.
Generative artificial intelligence (GAI) is poised to transform clinical dentistry by enhancing diagnostic accuracy, personalizing treatment planning, and improving procedural precision. This study integrates logic programming and entropy within knowledge representation and reasoning to generate hypotheses, quantify uncertainty, and support clinical decisions. A six-month longitudinal questionnaire was administered to 127 dentists, of whom 119 provided valid responses across four dimensions: current use and knowledge (CUKD), potential applications (PAD), future perspectives (FPD), and challenges and barriers (CBD). Responses, analyzed with both classical statistics and entropy-based measures, revealed significant differences among dimensions (p < 0.01, η2 = 0.14). CUKD, PAD, and FPD all increased steadily over time (baseline means 2.32, 3.06, and 3.27; rising to 3.75, 4.51, and 4.71, respectively), while CBD remained more variable (1.87–3.87). The overall entropic state declined from 0.43 to 0.31 (p = 0.018), reflecting reduced uncertainty. Statistical and entropy-derived trends converged, suggesting growing professional clarity and cautious acceptance of GAI. These findings indicate that, despite persistent concerns, GAI holds promise for advancing adaptive and evidence-driven dental practice. Full article
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26 pages, 644 KB  
Review
Therapeutic Targeting of Protein Lysine and Arginine Methyltransferases: Principles and Strategies for Inhibitor Design
by Isaac Micallef and Byron Baron
Int. J. Mol. Sci. 2025, 26(18), 9038; https://doi.org/10.3390/ijms26189038 - 17 Sep 2025
Cited by 1 | Viewed by 432
Abstract
Standard cancer chemotherapy is increasingly being supplemented with novel therapeutics to overcome known chemoresistance pathways. Resistance to treatment is common across various tumour types, driven by multiple mechanisms. One emerging contributor is protein methylation, a post-translational modification mediated by protein methyltransferases (PMTs), which [...] Read more.
Standard cancer chemotherapy is increasingly being supplemented with novel therapeutics to overcome known chemoresistance pathways. Resistance to treatment is common across various tumour types, driven by multiple mechanisms. One emerging contributor is protein methylation, a post-translational modification mediated by protein methyltransferases (PMTs), which regulate protein function by adding methyl groups, mainly on lysine and arginine residues. Dysregulation of protein lysine methyltransferases (PKMTs) and protein arginine methyltransferases (PRMTs) has been linked to cancer progression and drug resistance, making them attractive therapeutic targets. Consequently, several small-molecule PMT inhibitors have been developed, with some progressing to clinical trials. However, many candidates showing promise in preclinical studies fail to demonstrate efficacy or safety in later stages, limiting clinical success. This gap highlights the need to rethink current approaches to PMT inhibitor design. A deeper understanding of PMT mechanisms, catalytic domains, and their roles in chemoresistance is essential for creating more selective, potent, and clinically viable inhibitors. This review will summarise major chemoresistance pathways and PMTs implicated in cancer, then explore current and prospective PMT inhibitor classes. Building on mechanistic insights, we propose strategies to develop next-generation inhibitors with improved therapeutic potential against chemoresistant cancers. Full article
(This article belongs to the Special Issue Protein Methyltransferases in Human Health and Diseases)
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25 pages, 1345 KB  
Article
Analysis of the MSD, ICF Function, G’ and G” Modulus and Raman and FTIR Spectroscopy Spectra to Explain Changes in the Microstructure of Vegetable Lubricants
by Rafal Kozdrach and Pawel Radulski
Lubricants 2025, 13(9), 416; https://doi.org/10.3390/lubricants13090416 - 16 Sep 2025
Viewed by 239
Abstract
This paper presents the results of a rheological and spectral study characterising the change in the microstructure of lubricants depending on the type of vegetable oil base. The three lubricating compositions were prepared based on vegetable oils (rapeseed, sunflower and abyssinian), where amorphous [...] Read more.
This paper presents the results of a rheological and spectral study characterising the change in the microstructure of lubricants depending on the type of vegetable oil base. The three lubricating compositions were prepared based on vegetable oils (rapeseed, sunflower and abyssinian), where amorphous silica of a specific particle size was used as a thickener. These three lubricating compositions were then modified by introducing the AW/EP additive (BCH 351) into their structure. Rheological tests were performed for the prepared lubricating compositions on a DWS diffusion spectrometer. Based on the tests, the dependence of ICF function values on time, MSD function values on time and G’ and G” modulus values on frequency were determined. From the collected data, rheological parameters such as the elasticity coefficient, MSD curve slope factor, diffusion coefficients and the value at which the G’ and G” curves intersect were determined, which characterise the microstructure of the tested lubricants. Raman and FTIR spectra were also performed to characterise the chemical structure of the compositions studied, and the intensity of integration of characteristic bands of vegetable greases was calculated. For vegetable greases made from different vegetable oils, a change in the value of the MSD function was observed, and the calculated value of the elasticity index indicates better viscoelastic properties for the grease made from rapeseed oil. Modification of vegetable greases with a multifunctional additive leads to a change in rheological parameters, indicating a change in the structure of the greases studied. The results of tests of diffusion coefficients for vegetable greases show a change in microstructure for greases made with different vegetable oils. Such results testify to moderately strong viscoelastic properties, leading to the conclusion that the produced greases are substances stable to changes in chemical structure depending on the base oil and modifying additive used. Raman and FTIR spectroscopy is a technique that enables changes in the chemical composition of vegetable oils to be assessed by analysing the degree of unsaturation of fatty acids in vegetable oils, making it a very good diagnostic method for quality control of lubricants based on vegetable oils. The results obtained make it possible to differentiate lubricants prepared with different vegetable oils and allow the chemical structure of the vegetable lubricants studied to be assessed on the basis of the intensity of integration of characteristic bands. Full article
(This article belongs to the Special Issue Condition Monitoring of Lubricating Oils)
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12 pages, 2233 KB  
Article
First Record of Sepioteuthis lessoniana from the Maltese Archipelago, with Further Notes on Its Occurrence in the Central Mediterranean Sea
by Alessio Marrone, Alan Deidun, Maria Corsini-Foka, Bruno Zava, Eleonora Tinto, Carmen Rizzo and Pietro Battaglia
J. Mar. Sci. Eng. 2025, 13(9), 1783; https://doi.org/10.3390/jmse13091783 - 16 Sep 2025
Viewed by 518
Abstract
The occurrence of the bigfin reef squid Sepioteuthis lessoniana, a Lessepsian migrant, is documented for the first time from the coastal waters off Malta, based on the collection of a single specimen reported through citizen science. The presence of this species in [...] Read more.
The occurrence of the bigfin reef squid Sepioteuthis lessoniana, a Lessepsian migrant, is documented for the first time from the coastal waters off Malta, based on the collection of a single specimen reported through citizen science. The presence of this species in the broader Strait of Sicily region is further confirmed by a morphometric assessment and genetic analysis of another individual captured off the Pelagian island of Lampedusa. Molecular identification using mitochondrial COI and 16S rRNA markers corroborates the taxonomic identification exercise as it aligns both specimens with Indo-Pacific clades of S. lessoniana. These records represent the first genetically verified occurrences of the species in both Maltese and Italian waters. The findings extend the known Mediterranean distribution of S. lessoniana, emphasizing the Strait of Sicily as an important monitoring region for Lessepsian migrants and highlighting the combined role of integrative taxonomy and citizen science in tracking non-indigenous species introductions. Full article
(This article belongs to the Special Issue Marine Alien Species)
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27 pages, 965 KB  
Review
Unveiling the Impacts of Glyphosate, Deltamethrin, Propamocarb and Tebuconazole on Gut Health
by Kimberly Fenech and Byron Baron
J 2025, 8(3), 36; https://doi.org/10.3390/j8030036 - 15 Sep 2025
Viewed by 355
Abstract
Pesticides are used in agriculture to protect crops from disease. Among these, the herbicide glyphosate, the insecticide deltamethrin, and the fungicides propamocarb and tebuconazole are approved for use in Europe. These pesticides, along with their metabolites, have been detected in the environment including [...] Read more.
Pesticides are used in agriculture to protect crops from disease. Among these, the herbicide glyphosate, the insecticide deltamethrin, and the fungicides propamocarb and tebuconazole are approved for use in Europe. These pesticides, along with their metabolites, have been detected in the environment including in food and water sources. Human biomonitoring studies have confirmed the presence of these compounds in biological samples, indicating persistent exposure even among the general population, unrelated to agricultural occupations. Consequently, numerous studies have investigated the health effects of these four pesticides and their metabolites. This review focuses on their impacts on gut health primarily the gut microbiota, inflammation, metabolism, cancer and gut–brain axis. Epidemiological studies were included to assess health risks among various groups including adults, children and pregnant women. Animal and in vitro models have been employed to explore in a more controlled and targeted way the physiological and biochemical effects observed in epidemiological studies. Despite some controversy, pesticides and their metabolites have been linked to gut dysbiosis, inflammatory bowel disease (IBD), metabolic disorders, cancer and neurodevelopmental disorders. Mechanistically, these pesticides influence gut microbiome composition, sugar and lipid metabolism, oxidative stress, inflammatory pathways, cell death, oncogenic signalling pathways, endocrine disruption, and epigenetics. However, further studies are needed to confirm these risks and health impacts, particularly concerning low-dose, long-term exposure as experienced by the general population. A comprehensive investigation of these effects is essential, incorporating dietary factors, age, sex, health status, and the cumulative impact of multiple pesticides, to develop a thorough risk assessment. Full article
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11 pages, 615 KB  
Article
Immunogenicity and Safety of a Live Attenuated Varicella Vaccine in Healthy Children Aged 12 to 15 Months: A Phase III, Randomized, Double-Blind, Active-Controlled Clinical Trial
by Nancy Nazaire-Bermal, Ningning Jia, Maria Angela C. Maronilla, Josemaria F. Lopez, Gang Zeng, Wenbin Wu, Adrielle Bernice C. Nimo, Chunfang Luan and Qianqian Xin
Vaccines 2025, 13(9), 973; https://doi.org/10.3390/vaccines13090973 - 13 Sep 2025
Viewed by 598
Abstract
Objectives: The varicella vaccine (VarV) produced by Sinovac (Dalian) obtained World Health Organization (WHO) prequalification in November 2022. However, no direct comparative studies have been conducted between VarV and other WHO-prequalified varicella vaccines. The study aimed to assess the immunogenicity and safety [...] Read more.
Objectives: The varicella vaccine (VarV) produced by Sinovac (Dalian) obtained World Health Organization (WHO) prequalification in November 2022. However, no direct comparative studies have been conducted between VarV and other WHO-prequalified varicella vaccines. The study aimed to assess the immunogenicity and safety of Sinovac’s VarV compared with Merck Sharp & Dohme’s (MSD) VARIVAX® (Moorgate, London, UK) following a single dose administration. Methods: This Phase III, randomized, double-blind, active-controlled, non-inferiority trial was conducted in the Philippines. Healthy children aged 12 to 15 months were enrolled. Eligible participants were randomly assigned (1:1) to receive a single dose of varicella vaccine either manufactured by Sinovac (Test group) or MSD (Active control group). Immunogenicity was evaluated 6 weeks after vaccination by enzyme-linked immunosorbent assay (ELISA). The primary immunogenicity endpoint was seroresponse rate 6 weeks after vaccination. Seroresponse rate was defined as varicella-zoster virus (VZV) antibody concentration ≥ 10 mIU/mL in participants who were seronegative (antibody concentration < 10 mIU/mL) at baseline. The secondary endpoint was the corresponding geometric mean concentration (GMC). Adverse events (AEs) and serious adverse events (SAEs) were monitored for 6 weeks after vaccination. Results: Among the 484 participants analyzed, the seroresponse rates 6 weeks after vaccination were 98.85% and 98.88% in the Test group and Active control group, respectively, with a difference of −0.03% (95% CI: −3.10%, 2.99%), which exceeded the predefined non-inferiority margin of −10%. The corresponding GMCs were 35.73 mIU/mL and 37.34 mIU/mL, respectively, with the ratio of 0.96 (95% CI: 0.86, 1.06), also exceeding the predefined non-inferiority margin of 0.67. Furthermore, the incidence of adverse reactions (ARs) in the Test group was lower than that in the Active control group (38.08% vs. 55.51%). Conclusions: Sinovac’s VarV demonstrated non-inferior immunogenicity to WHO-prequalified comparator vaccine (VARIVAX®) and favorable safety profile. These findings indicated that VarV (Sinovac, Beijing, China) met WHO standards for varicella vaccine evaluation, supporting its global use consideration. Full article
(This article belongs to the Section Vaccine Advancement, Efficacy and Safety)
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31 pages, 1160 KB  
Review
Modern Honey-Based Delivery Systems for Wound Healing: A Review of Current Trends and Future Perspectives
by Anna Gościniak, Everaldo Attard, Ida Judyta Malesza, Adam Kamiński and Judyta Cielecka-Piontek
Appl. Sci. 2025, 15(18), 9997; https://doi.org/10.3390/app15189997 - 12 Sep 2025
Viewed by 677
Abstract
Honey is a multifunctional therapeutic agent in wound management with antimicrobial, anti-inflammatory, antioxidant and tissue-regenerative properties. Direct application is limited by high viscosity, variability in composition and instability of bioactive compounds. Advances in biomaterials engineering have enabled the development of honey-based delivery platforms [...] Read more.
Honey is a multifunctional therapeutic agent in wound management with antimicrobial, anti-inflammatory, antioxidant and tissue-regenerative properties. Direct application is limited by high viscosity, variability in composition and instability of bioactive compounds. Advances in biomaterials engineering have enabled the development of honey-based delivery platforms such as nanoparticles, electrospun nanofibers and hydrogels, which improve stability, retention at the wound site and provide controlled release. The review offers a comprehensive overview of honey’s wound-healing mechanisms, evaluates diverse delivery strategies and compares their structural and functional characteristics. Nanoparticles enable targeted delivery and synergistic antimicrobial effects, electrospun mats mimic the extracellular matrix with tunable porosity and hydrogels maintain a moist healing environment with high adaptability. Key challenges include achieving standardization, enhancing mechanical properties and optimizing sterilization methods. Future perspectives emphasize integrating honey-based systems with smart sensors, advanced bioprinting and multifunctional composites to achieve personalized and responsive wound care. Full article
(This article belongs to the Special Issue New Advances in Antioxidant Properties of Bee Products)
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23 pages, 4476 KB  
Article
High-Precision, Automatic, and Fast Segmentation Method of Hepatic Vessels and Liver Tumors from CT Images Using a Fusion Decision-Based Stacking Deep Learning Model
by Mamoun Qjidaa, Anass Benfares, Mohammed Amine El Azami El Hassani, Amine Benkabbou, Amine Souadka, Anass Majbar, Zakaria El Moatassim, Maroua Oumlaz, Oumayma Lahnaoui, Raouf Mouhcine, Ahmed Lakhssassi and Abdeljabbar Cherkaoui
BioMedInformatics 2025, 5(3), 53; https://doi.org/10.3390/biomedinformatics5030053 - 9 Sep 2025
Viewed by 768
Abstract
Background: To propose an automatic liver and hepatic vessel segmentation solution based on a stacking model and decision fusion. This model combines the decisions of multiple models to achieve increased accuracy. It exhibits improved robustness due to the reduction of individual errors. Flexibility [...] Read more.
Background: To propose an automatic liver and hepatic vessel segmentation solution based on a stacking model and decision fusion. This model combines the decisions of multiple models to achieve increased accuracy. It exhibits improved robustness due to the reduction of individual errors. Flexibility is also a key asset, with combination methods such as majority voting or weighted averaging. The model enables managing the uncertainty associated with individual decisions to obtain a more reliable final decision. The combination of decisions improves the overall accuracy of the system. Methods: This research introduces a new deep learning-based architecture for automatically segmenting hepatic vessels and tumors from CT scans, utilizing stacking, decision fusion, and deep transfer learning to achieve high-accuracy and rapid segmentation. This study employed two distinct datasets: the external “Medical Segmentation Decathlon (MSD) task 08” dataset and an internal dataset procured from Ibn Sina University Hospital encompassing a cohort of 112 patients with chronic liver disease who underwent contrast-enhanced abdominal CT scans. Results: The proposed segmentation model reached a DSC of 83.21 and an IoU of 72.76 for hepatic vasculature and tumor segmentation, thereby exceeding the performance benchmarks established by the majority of antecedent studies. Conclusions: This study introduces an automated method for liver vessels and liver tumor segmentation, combining precision and stability to bridge the clinical gap. Furthermore, decision fusion-based stacking models have a significant impact on clinical applications by enhancing diagnostic accuracy, enabling personalized care through the integration of genetic, environmental, and clinical data, optimizing clinical trials, and facilitating the development of personalized medicines and therapies. Full article
(This article belongs to the Section Methods in Biomedical Informatics)
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