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16 pages, 2642 KiB

Open AccessArticle

Innovative Lightweight and Sustainable Composite Material for Building Applications

by Corradino Sposato, Tiziana Cardinale, Maria Bruna Alba, Andrea Feo, Luca Pala and Piero De Fazio

Sustainability 2025, 17(16), 7319; https://doi.org/10.3390/su17167319 (registering DOI) - 13 Aug 2025

Abstract

In recent years, the application of sustainable cementitious materials has become of great importance to improve buildings efficiency and to achieve carbon neutrality. Main goal of this work to study and develop BIOAERMAC, an innovative construction material with low density, composed of synthetic [...] Read more.

In recent years, the application of sustainable cementitious materials has become of great importance to improve buildings efficiency and to achieve carbon neutrality. Main goal of this work to study and develop BIOAERMAC, an innovative construction material with low density, composed of synthetic anhydrous calcium sulfate obtained as by-product in the industrial production of hydrofluoric acid and an aerating agent composed of microorganisms and peroxides, with the addition of rubber from end-of-life tires (ELTs). A density from 600 to 950 kg/m³ with a compressive strength up to 6.0 MPa and a thermal conductivity from 0.15 to 0.3 W/mK are the key performance metrics of BIOAERMAC composites. Experimental results showed an improvement in technical and energy performance, combined with a reduction in natural resource consumption and the wide quantity of by-product reintroduced into the production process. Full article

(This article belongs to the Special Issue Innovations in Cementitious Materials Towards Carbon Emissions Reduction)

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22 pages, 3744 KiB

Open AccessArticle

Improved DeepLabV3+ for UAV-Based Highway Lane Line Segmentation

by Yueze Wang, Dudu Guo, Yang Wang, Hongbo Shuai, Zhuzhou Li and Jin Ran

Sustainability 2025, 17(16), 7317; https://doi.org/10.3390/su17167317 (registering DOI) - 13 Aug 2025

Abstract

Sustainable highway infrastructure maintenance critically depends on precise lane line detection, yet conventional inspection approaches remain resource-depleting, carbon-intensive, and hazardous to personnel. To mitigate these constraints and address the low accuracy and high parameterization of existing models, this study utilizes unmanned aerial vehicle [...] Read more.

Sustainable highway infrastructure maintenance critically depends on precise lane line detection, yet conventional inspection approaches remain resource-depleting, carbon-intensive, and hazardous to personnel. To mitigate these constraints and address the low accuracy and high parameterization of existing models, this study utilizes unmanned aerial vehicle (UAV) imagery and proposes a UAV-based highway lane line segmentation method using an improved DeepLabV3+ model that resolves multi-scale lane line segmentation challenges in UAV imagery. MobileNetV2 is used as the backbone network to significantly reduce the number of model parameters. The Squeeze-and-Excitation (SE) attention mechanism is integrated to enhance feature extraction capabilities, particularly at lane line edges. A Feature Pyramid Network (FPN) is incorporated to improve multi-scale lane line feature extraction. We introduce a novel Waterfall Atrous Spatial Pyramid Pooling (WASPP) module, utilizing cascaded atrous convolutions with strategic dilation rate adjustments to progressively expand the receptive field and aggregate contextual information across scales. The improved model outperforms the original DeepLabV3+ by 5.04% mIoU (85.30% vs. 80.26%) and 3.35% F1-Score (91.74% vs. 88.39%) while cutting parameters by 85% (8.03 M vs. 54.8 M) and reducing training time by 2 h 50 min, thereby enhancing the model’s accuracy in lane line segmentation, reducing the number of parameters, and lowering the carbon footprint. Full article

(This article belongs to the Section Sustainable Transportation)

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26 pages, 1202 KiB

Open AccessArticle

Changes in Soil Microbial Diversity Across Different Forest Successional Stages: A Meta-Analysis of Chinese Forest Ecosystems

by Meiyan Pan, Rui Xiao and Hongwei Ni

Forests 2025, 16(8), 1319; https://doi.org/10.3390/f16081319 (registering DOI) - 13 Aug 2025

Abstract

Using meta-analysis of 479 sites across Chinese forests from 136 publications, we quantified changes in soil microbial diversity across forest successional stages and compared patterns between plantation and natural secondary forests. Our systematic review included 136 publications (92 in Chinese, 44 in English), [...] Read more.

Using meta-analysis of 479 sites across Chinese forests from 136 publications, we quantified changes in soil microbial diversity across forest successional stages and compared patterns between plantation and natural secondary forests. Our systematic review included 136 publications (92 in Chinese, 44 in English), spanning tropical to cold temperate climate zones from 1995–2025. Microbial

α

-diversity exhibited a significant U-shaped pattern across successional stages: early succession (0–15 years) and mature forests (>50 years) had higher Shannon diversity (4.56 ± 0.34 and 4.72 ± 0.41, respectively) than middle-aged forests (16–50 years, 4.18 ± 0.27; standardized mean difference = 0.54, 95% CI: 0.39–0.69, p < 0.01). Response patterns differed significantly among microbial groups (Q = 8.74, p = 0.013), with fungi showing the strongest successional responses (SMD = 0.61, 95% CI: 0.43–0.79), followed by bacteria (SMD = 0.49, 95% CI: 0.32–0.66) and actinomycetes (SMD = 0.42, 95% CI: 0.24–0.60). Natural secondary forests consistently supported higher microbial diversity than plantations (SMD = 0.42, 95% CI: 0.28–0.56), particularly for fungal communities (SMD = 0.47, 95% CI: 0.31–0.63). The climate zone significantly moderated diversity–succession relationships, with subtropical regions showing the largest changes (

Δ

Shannon = 0.68 ± 0.07) compared to temperate (

Δ

Shannon = 0.42 ± 0.05) and tropical regions (

Δ

Shannon = 0.54 ± 0.06). Meta-analytic structural equation modeling revealed that soil organic carbon (path coefficient

β

= 0.68, p < 0.001), total nitrogen (

β

= 0.43, p < 0.001), and pH (

β

= −0.35, p < 0.01) were key mediators connecting succession stage with microbial diversity. Despite substantial between-study heterogeneity (I² = 83.6%), a publication bias was not detected (Egger’s test, p = 0.347). These findings provide the first comprehensive quantification of microbial diversity patterns during forest succession in China, with important implications for forest management and ecological restoration strategies targeting microbial conservation. Full article

(This article belongs to the Section Forest Soil)

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14 pages, 3262 KiB

Open AccessArticle

Integrated LCOS-SLM-Based Laser Slicing System for Aberration Correction in Silicon Carbide Substrate Manufacturing

by Heng Wang, Qiang Cao, Yuting Hou, Lulu Yu, Tianhao Wu, Zhenzhong Wang and Du Wang

Micromachines 2025, 16(8), 930; https://doi.org/10.3390/mi16080930 (registering DOI) - 13 Aug 2025

Abstract

Silicon carbide (SiC), a wide-bandgap semiconductor, is renowned for its exceptional performance in power electronics and extreme-temperature environments. However, precision low-loss laser slicing of SiC is impeded by energy divergence and crack delamination induced by refractive-index-mismatch interfacial aberrations. This study presents an integrated [...] Read more.

Silicon carbide (SiC), a wide-bandgap semiconductor, is renowned for its exceptional performance in power electronics and extreme-temperature environments. However, precision low-loss laser slicing of SiC is impeded by energy divergence and crack delamination induced by refractive-index-mismatch interfacial aberrations. This study presents an integrated laser slicing system based on a liquid crystal on silicon spatial light modulator (LCOS-SLM) to address aberration-induced focal elongation and energy inhomogeneity. Through dynamic modulation of the laser wavefront via an inverse ray-tracing algorithm, the system corrects spherical aberrations from refractive index mismatch, thus achieving precise energy concentration at wanted depths. A laser power attenuation model based on interface reflection and the Lambert–Beer law is established to calculate the required laser power at varying processing depths. Experimental results demonstrate that aberration correction reduces focal depth to approximately one-third (from 45 μm to 15 μm) and enhances energy concentration, eliminating multi-layer damage and increasing crack propagation length. Post-correction critical power measurements across depths are consistent with model predictions, with maximum error decreasing from >50% to 8.4%. Verification on a 6-inch N-type SiC ingot shows 90 μm damage thickness, confirming system feasibility for SiC laser slicing. The integrated aberration-correction approach provides a novel solution for high-precision SiC substrate processing. Full article

(This article belongs to the Section D：Materials and Processing)

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9 pages, 1071 KiB

Open AccessCommunication

On the Appropriateness of Fixed Correlation Assumptions in Repeated-Measures Meta-Analysis: A Monte Carlo Assessment

by Vasileios Papadopoulos

Stats 2025, 8(3), 72; https://doi.org/10.3390/stats8030072 (registering DOI) - 13 Aug 2025

Abstract

In repeated-measures meta-analyses, raw data are often unavailable, preventing the calculation of the correlation coefficient r between pre- and post-intervention values. As a workaround, many researchers adopt a heuristic approximation of r = 0.7. However, this value lacks rigorous mathematical justification and may [...] Read more.

In repeated-measures meta-analyses, raw data are often unavailable, preventing the calculation of the correlation coefficient r between pre- and post-intervention values. As a workaround, many researchers adopt a heuristic approximation of r = 0.7. However, this value lacks rigorous mathematical justification and may introduce bias into variance estimates of pre/post-differences. We employed Monte Carlo simulations (n = 500,000 per scenario) in Fisher z-space to examine the distribution of the standard deviation of pre-/post-differences (σ_D) under varying assumptions of r and its uncertainty (σ_r). Scenarios included r = 0.5, 0.6, 0.707, 0.75, and 0.8, each tested across three levels of variance (σ_r = 0.05, 0.1, and 0.15). The approximation of r = 0.75 resulted in a balanced estimate of σ_D, corresponding to a “midway” variance attenuation due to paired data. This value more accurately offsets the deficit caused by assuming a correlation, compared to the traditional value of 0.7. While the r = 0.7 heuristic remains widely used, our results support the use of r = 0.75 as a more mathematically neutral and empirically defensible alternative in repeated-measures meta-analyses lacking raw data. Full article

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15 pages, 3838 KiB

Open AccessArticle

Cavitation–Velocity Correlation in Cavitating Flows Around a Clark-Y Hydrofoil Using a Data-Driven U-Net

by Yadong Han, Bingfu Han, Ming Liu and Lei Tan

Fluids 2025, 10(8), 213; https://doi.org/10.3390/fluids10080213 (registering DOI) - 13 Aug 2025

Abstract

Cavitating flows are of great interest in the fields of hydraulic machineries, which can significantly affect mechanical performance and safety. Despite various efforts being dedicated to figuring out the interaction between flow and cavitation fields, their correlation has not been clearly addressed. To [...] Read more.

Cavitating flows are of great interest in the fields of hydraulic machineries, which can significantly affect mechanical performance and safety. Despite various efforts being dedicated to figuring out the interaction between flow and cavitation fields, their correlation has not been clearly addressed. To this end, in this study, a convolutional neural network, U-Net, was adopted to build a model that can predict the vapor volume fraction from velocity fields. Large eddy simulations of cavitating flows around a Clark-Y hydrofoil were conducted, and the simulated snapshots with velocity and vapor volume fraction were adopted as a dataset for training the network. The predicted vapor volume fraction shows good agreement with the referred simulation results, with a L₁ deviation lower than 2 × 10⁻⁴, considering all the snapshots. The comparable L₁ deviation between the training and validation datasets suggests the existence of a strong correlation between velocity and cavitation fields. The cavitation–velocity interaction derived from using U-Net suggests that the location with zero velocity indicates the interior part of attached and cloud cavitations, and the local vortical velocity fields usually suggest the existence of cavitation shedding. Full article

(This article belongs to the Special Issue Multiphase Flow and Fluid Machinery)

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18 pages, 4654 KiB

Open AccessArticle

Principal Component Analysis of Transient Potential Signals from Ion-Selective Electrodes for the Identification and Quantification of Different Ions

by José Antonio González-Franco, José Manuel Olmos, Alberto Ruiz and Joaquín Ángel Ortuño

Chemosensors 2025, 13(8), 305; https://doi.org/10.3390/chemosensors13080305 (registering DOI) - 13 Aug 2025

Abstract

This study investigates the potential of transient potentiometric signals generated by an array of ion-selective electrodes (ISEs) as the basis for a potentiometric electronic tongue capable of identifying and quantifying a range of inorganic and organic cations. Six distinct polymeric membrane ISEs were [...] Read more.

This study investigates the potential of transient potentiometric signals generated by an array of ion-selective electrodes (ISEs) as the basis for a potentiometric electronic tongue capable of identifying and quantifying a range of inorganic and organic cations. Six distinct polymeric membrane ISEs were fabricated, differing in plasticizer type (either NPOE or DEHS), and in the presence or absence of a lipophilic ion exchanger (KTClPB) and/or an ionophore (DB18C6). Transient potential responses were recorded following the exposure of the electrode array to various cations at different concentrations. A total of 810 transient signals were analyzed through visual inspection and principal component analysis (PCA), revealing characteristic dynamic patterns influenced by membrane composition, ion type, and ion concentration. PCA was conducted both on the transient signals from each individual electrode and on the aggregated dataset comprising signals from the full six-electrode array (electronic tongue). The electronic tongue exhibited a markedly enhanced capacity for discriminating and quantifying ion concentrations in comparison to any single electrode. Full article

(This article belongs to the Special Issue Chemometrics in Electroanalysis and Electrochemical Sensing)

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23 pages, 8681 KiB

Open AccessArticle

Transformer-Based Traffic Flow Prediction Considering Spatio-Temporal Correlations of Bridge Networks

by Yadi Tian, Wanheng Li, Xiaojing Wang, Xin Yan and Yang Xu

Appl. Sci. 2025, 15(16), 8930; https://doi.org/10.3390/app15168930 (registering DOI) - 13 Aug 2025

Abstract

With the widespread implementation of bridge structural health monitoring (SHM) systems, monitored bridge networks have gradually formed. Understanding vehicle loads and considering spatio-temporal correlations within bridge networks is critical for structural condition assessment and maintenance decision making. This study aims to predict traffic [...] Read more.

With the widespread implementation of bridge structural health monitoring (SHM) systems, monitored bridge networks have gradually formed. Understanding vehicle loads and considering spatio-temporal correlations within bridge networks is critical for structural condition assessment and maintenance decision making. This study aims to predict traffic flows by investigating traffic flow correlations within a bridge network using multi-bridge data, thereby supporting bridge network-level SHM. A transformer-based traffic flow prediction model considering spatio-temporal correlations of bridge networks (ST-TransNet) is proposed. It integrates external factors (processed via fully connected networks) and multi-period traffic flows of input bridges (captured by self-attention encoders) to generate traffic flow predictions through a self-attention decoder. Validated using weigh-in-motion data from an 8-bridge network, the proposed ST-TransNet reduces prediction root mean square error (RMSE) to 12.76 vehicles/10 min, outperforming a series of baselines—SVR, CNN, BiLSTM, CNN&BiLSTM, ST-ResNet, transformer, and STGCN—with significant relative reductions of 40.5%, 36.9%, 36.6%, 37.3%, 35.6%, 31.1%, and 22.8%, respectively. Ablation studies confirm the contribution of each component of the external factors and multi-period traffic flows, particularly the recent traffic flow data. The proposed ST-TransNet effectively captures underlying the spatio-temporal correlations of traffic flow within bridge networks, offering valuable insights for enhancing bridge assessment and maintenance. Full article

(This article belongs to the Special Issue Artificial Intelligence for Structural Health Monitoring, Inspection, Maintenance, and Rehabilitation of Civil Infrastructure)

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20 pages, 4584 KiB

Open AccessArticle

Systemic Lonp1 Haploinsufficiency Mitigates Cardiac Mitochondrial Dysfunction Induced by Cardiomyocyte-Specific Lonp1 Haploinsufficiency via Potential Inter-Organ Cross-Talk

by Sakthijothi Muthu, Zinnia Tran, Ramasamy Saminathan, Pratikshya Shrestha and Sundararajan Venkatesh

Biomolecules 2025, 15(8), 1159; https://doi.org/10.3390/biom15081159 (registering DOI) - 13 Aug 2025

Abstract

Efficient mitochondrial matrix protein quality control (mPQC), regulated by the mitochondrial matrix protease LONP1, is essential for preserving cardiac bioenergetics, particularly in post-mitotic cardiomyocytes, which are highly susceptible to mitochondrial dysfunction. While cardiac mPQC defects could impair heart function, it remains unclear whether [...] Read more.

Efficient mitochondrial matrix protein quality control (mPQC), regulated by the mitochondrial matrix protease LONP1, is essential for preserving cardiac bioenergetics, particularly in post-mitotic cardiomyocytes, which are highly susceptible to mitochondrial dysfunction. While cardiac mPQC defects could impair heart function, it remains unclear whether such defects can be mitigated through inter-organ crosstalk by modulating mPQC in extra-cardiac tissues, a potentially valuable strategy given the challenges of directly targeting the heart. To investigate this, we examined two mouse models of Lonp1 haploinsufficiency at young adulthood: a cardiomyocyte-specific heterozygous knockout (Lonp1^CKO-HET) and a whole-body heterozygous knockout (Lonp1^GKO-HET). Despite similar reductions in Lonp1 mRNA expression in the hearts, Lonp1^GKO-HET mice exhibited no cardiac dysfunction, whereas Lonp1^CKO-HET mice showed mild cardiac dysfunction accompanied by activation of the mitochondrial stress response, including induction of genes such as Clpx, Spg7, Hspa9, and Hspd1, increased mitochondrial dynamics (Pink1, Dnm1l), reduced mitochondrial biogenesis, and compensatory upregulation of the mtDNA transcriptional regulator Tfam, all occurring without overt structural remodeling. These alterations were absent in Lonp1^GKO-HET hearts. Our findings reveal a novel adaptive mechanism in which systemic mPQC deficiency can buffer mitochondrial dysfunction in the heart through inter-organ communication that is lost with cardiomyocyte-specific mPQC disruption. This study identifies systemic modulation of Lonp1-mediated mitochondrial stress pathways as a promising strategy to promote cardiac resilience through protective inter-organ signaling. Full article

(This article belongs to the Special Issue Mitochondrial Proteins: From Import and Biogenesis to Complex Functional Network)

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16 pages, 918 KiB

Open AccessStudy Protocol

Investigating the Impact of Fusobacterium nucleatum on Oxidative Stress, Chemoresistance, and Inflammation in Inflammatory Bowel Disease and Colorectal Cancer: Rationale and Design of a Clinical Trial

by Pierluigi Consolo, Carlotta Giorgi, Concetta Crisafulli, Francesco Fiorica, Paolo Pinton, Nicola Maurea, Sonia Missiroli, Vincenzo Quagliariello, Beatrice Mantoan, Alessandro Ottaiano, Giovanni Francesco Pellicanò, Germano Orrù, Alessandra Scano, Irene Cacciola, Teresa Pollicino, Giordana Di Mauro, Salvatore Berretta, Alessia Bignucolo, Enrica Toscano, Giuliana Ciappina and Massimiliano Berretta Show full author list Hide full author list

Int. J. Mol. Sci. 2025, 26(16), 7823; https://doi.org/10.3390/ijms26167823 (registering DOI) - 13 Aug 2025

Abstract

Fusobacterium nucleatum (F. nucleatum), a Gram-negative anaerobe, is increasingly implicated in the pathogenesis of colorectal cancer (CRC) and inflammatory bowel disease (IBD). Its adhesin FadA enables epithelial adherence and invasion, promoting inflammation and tumorigenesis. F. nucleatum has been shown to activate [...] Read more.

Fusobacterium nucleatum (F. nucleatum), a Gram-negative anaerobe, is increasingly implicated in the pathogenesis of colorectal cancer (CRC) and inflammatory bowel disease (IBD). Its adhesin FadA enables epithelial adherence and invasion, promoting inflammation and tumorigenesis. F. nucleatum has been shown to activate the NLRP3 inflammasome, leading to IL-1β release, and is associated with chemoresistance and poor prognosis in CRC. Additionally, lipid peroxidation markers such as malondialdehyde (MDA) and 4-hydroxy-nonenal (4-HNA) may contribute to inflammation-driven carcinogenesis. This study protocol aims to investigate the role of F. nucleatum in the development and progression of IBD and CRC through integrated clinical, molecular, and imaging approaches. The protocol involves quantifying F. nucleatum in tissue biopsies across disease stages and assessing correlations with inflammatory and oxidative markers. It will explore the bacterium’s involvement in NLRP3 inflammasome activation, IL-1β production, and autophagy, and its potential contribution to chemoresistance. Furthermore, radiomic analysis of computed tomography (CT) images will be performed to identify imaging phenotypes associated with microbial load and inflammatory activity. Although primarily a protocol, the study includes preliminary in vitro data showing that exposure to FadA significantly increases inflammatory markers in Caco-2 cells, supporting the hypothesis that F. nucleatum contributes to a pro-inflammatory, pro-tumorigenic microenvironment relevant to CRC progression. Full article

(This article belongs to the Special Issue Immune-Inflammatory and Oxidative Stress Signaling Pathways Involved in Human Disorders)

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23 pages, 14454 KiB

Open AccessArticle

Transcriptomic Analysis Corroborates the New Radial Model of the Mouse Pallial Amygdala

by Gloria Fernández, Lara López-González, Eduardo Pons-Fuster, Luis Puelles and Elena Garcia-Calero

Biomolecules 2025, 15(8), 1160; https://doi.org/10.3390/biom15081160 (registering DOI) - 13 Aug 2025

Abstract

The mammalian amygdala is located in the temporal lobe of the telencephalon and plays a key role in limbic processing. Recently, our group proposed a radial morphological model to understand the glutamatergic (pallial) part of this nuclear complex in terms of separate progenitor [...] Read more.

The mammalian amygdala is located in the temporal lobe of the telencephalon and plays a key role in limbic processing. Recently, our group proposed a radial morphological model to understand the glutamatergic (pallial) part of this nuclear complex in terms of separate progenitor domains. This model explains the amygdala region as consisting of several adjacent developmental radial progenitor units, disposing their distinct periventricular, intermediate, and superficial strata from the ventricle to the pial surface. It was expected that cell populations belonging to specific progenitor domains would present greater molecular similarity to each other than to neighboring developmental units. In this work, we aim to corroborate the existence of several radial domains in the pallial amygdala at the transcriptomic level. snRNAseq experiments in the amygdala of adult mice of both sexes indicated that at low resolution, the whole pallial amygdala was found to divide into two super-radial domains distinguished by differential expression of Slc17a6 and Slc17a7; the former partly imitates molecularly the subpallial (output) amygdalar regions, whereas the rest of the pallial amygdala is molecularly more akin to the surrounding cortical areas. In addition, our snRNAseq transcriptomic analysis fully supports the postulated amygdalar radial model of four main radial domains. Full article

(This article belongs to the Section Bioinformatics and Systems Biology)

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17 pages, 3842 KiB

Open AccessArticle

A Novel Kinematic Calibration Method for Industrial Robots Based on the Improved Grey Wolf Optimization Algorithm

by Bingzhang Cao, Jiuwei Yu, Yi Zhang, Peijun Liu, Yifan Zhang, Hongwei Sun, Peng Jin, Jie Lin and Lei Wang

Actuators 2025, 14(8), 403; https://doi.org/10.3390/act14080403 (registering DOI) - 13 Aug 2025

Abstract

Due to insufficient absolute positioning accuracy, industrial robots frequently face challenges in efficiently performing drilling and riveting operations during the assembly of aircraft and other large-scale workpieces. To enhance the absolute positioning accuracy of industrial robots, this paper proposes a novel kinematic calibration [...] Read more.

Due to insufficient absolute positioning accuracy, industrial robots frequently face challenges in efficiently performing drilling and riveting operations during the assembly of aircraft and other large-scale workpieces. To enhance the absolute positioning accuracy of industrial robots, this paper proposes a novel kinematic calibration method for industrial robots based on the Improved Grey Wolf Optimization (IGWO) algorithm. Specifically, the method employs an enhanced selection and update strategy to avoid convergence stagnation and local optimum traps. The proposed method features a novel boundary search strategy, which leverages the Dimension-oriented Learning (DL) search strategy to enhance search speed and stability. Through parameter identification and calibration experiments, the effectiveness of the method was validated using an ABB IRB4600 industrial robot and a Leica laser tracker. Additionally, compared with the Levenberg–Marquardt (LM) algorithm, Particle Swarm Optimization (PSO), and Genetic Algorithm (GA), the IGWO algorithm demonstrates faster convergence and superior optimization performance. According to the calibration experimental results, by applying the IGWO algorithm, the absolute positioning accuracy of the industrial robot is ultimately improved from 1.918 mm to 0.475 mm and the absolute positioning accuracy is improved by 75.2%. Full article

(This article belongs to the Special Issue Intelligent Sensing, Control and Actuation in Networked Systems)

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20 pages, 1350 KiB

Open AccessArticle

Target-Oriented Opinion Words Extraction Based on Dependency Tree

by Yan Wen, Enhai Yu, Jiawei Qu, Lele Cheng, Yuao Chen and Siyu Lu

Big Data Cogn. Comput. 2025, 9(8), 207; https://doi.org/10.3390/bdcc9080207 (registering DOI) - 13 Aug 2025

Abstract

Target-oriented opinion words extraction (TOWE) is a novel subtask of aspect-based sentiment analysis (ABSA), which aims to extract opinion words corresponding to a given opinion target within a sentence. In recent years, neural networks have been widely used to solve this problem and [...] Read more.

Target-oriented opinion words extraction (TOWE) is a novel subtask of aspect-based sentiment analysis (ABSA), which aims to extract opinion words corresponding to a given opinion target within a sentence. In recent years, neural networks have been widely used to solve this problem and have achieved competitive results. However, when faced with complex and long sentences, the existing methods struggle to accurately identify the semantic relationships between distant opinion targets and opinion words. This is primarily because they rely on literal distance, rather than semantic distance, to model the local context or opinion span of the opinion target. To address this issue, we propose a neural network model called DTOWE, which comprises (1) a global module using Inward-LSTM and Outward-LSTM to capture general sentence-level context, and (2) a local module that employs BiLSTM combined with DT-LCF to focus on target-specific opinion spans. DT-LCF is implemented in two ways: DT-LCF-Mask, which uses a binary mask to zero out non-local context beyond a dependency tree distance threshold, α, and DT-LCF-weight, which applies a dynamic weighted decay to downweigh distant context based on semantic distance. These mechanisms leverage dependency tree structures to measure semantic proximity, reducing the impact of irrelevant words and enhancing the accuracy of opinion span detection. Extensive experiments on four benchmark datasets demonstrate that DTOWE outperforms state-of-the-art models. Specifically, DT-LCF-Weight achieves F1-scores of 73.62% (14lap), 82.24% (14res), 75.35% (15res), and 83.83% (16res), with improvements of 2.63% to 3.44% over the previous state-of-the-art (SOTA) model, IOG. Ablation studies confirm that the dependency tree-based distance measurement and DT-LCF mechanism are critical to the model’s effectiveness, validating their ability to handle complex sentences and capture semantic dependencies between targets and opinion words. Full article

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20 pages, 5202 KiB

Open AccessArticle

On the Localization Accuracy of Deformation Zones Retrieved from SAR-Based Sea Ice Drift Vector Fields

by Anja Frost, Christoph Schnupfhagn, Christoph Pegel and Sindhu Ramanath

Remote Sens. 2025, 17(16), 2801; https://doi.org/10.3390/rs17162801 (registering DOI) - 13 Aug 2025

Abstract

Sea ice is highly dynamic. Differences in the sea ice drift velocity and direction can cause deformations such as ridges and rubble fields or open up leads. These and other deformations have a major impact on the interaction between the atmosphere, sea ice [...] Read more.

Sea ice is highly dynamic. Differences in the sea ice drift velocity and direction can cause deformations such as ridges and rubble fields or open up leads. These and other deformations have a major impact on the interaction between the atmosphere, sea ice and the ocean, and strongly influence ship navigability in polar waters. Spaceborne Synthetic Aperture Radar (SAR) data is well suited to observing the sea ice and retrieving sea ice drift vector fields at a small scale (<1 km), revealing deformation zones. This paper introduces a software processor designed to retrieve high-resolution sea ice drift vector fields from pairs of subsequent SAR acquisitions using phase correlation embedded in a multiscale Gaussian image pyramid. We assess the accuracy of the algorithm by using drift buoys and landfast ice boundaries manually outlined from large series of TerraSAR-X acquisitions taken during winter and spring sea ice break up. In particular, we provide a first analysis of the localization accuracy in deformation zones. Overall, our experiments show that deformation zones are well detected, but can be misplaced by up to 1.1 km. An additional interferometric analysis narrows down the location of the landfast ice boundary. Full article

(This article belongs to the Special Issue Applications of Remote Sensing in Oceanography: Prospects and Challenges (3rd Edition))

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16 pages, 1896 KiB

Open AccessArticle

Modeling Approach to Calculate the Orientation of Liquid Crystal Polymers in a Flow Channel Under Varying Boundary Conditions

by Gernot Zitzenbacher

Polymers 2025, 17(16), 2209; https://doi.org/10.3390/polym17162209 (registering DOI) - 13 Aug 2025

Abstract

Thermotropic liquid crystal polymers comprise rigid chain segments called mesogens. This study presents a modeling approach to simulate the orientation of these mesogens in a flow channel with a rectangular cross section under no slip and wall slip boundary conditions. Rigid rods with [...] Read more.

Thermotropic liquid crystal polymers comprise rigid chain segments called mesogens. This study presents a modeling approach to simulate the orientation of these mesogens in a flow channel with a rectangular cross section under no slip and wall slip boundary conditions. Rigid rods with finite length and an initial orientation are proposed. The interactions between the velocity field in the flow channel and these rods are modeled to simulate orientation. Moreover, a highly oriented boundary layer can be simulated. Orientation occurs in the flow direction close to the die wall under the no slip condition due to the high shear rate. As the distance from the die wall increases, the orientation decreases. Wall slip effectuates a more uniform orientation and causes a delay in the development of the highly oriented boundary layer. The thickness profile of this layer exhibits a shape that is analogous to that of a root function. To ensure products with high mechanical properties, it is essential to orient the mesogens at a high level in the die during manufacturing. The presented model enables the prediction of orientation in the flow channel. Therefore, this model is a useful tool to design the process in the right way to reach this goal. Full article

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21 pages, 4815 KiB

Open AccessArticle

Native putA Overexpression in Synechocystis sp. PCC 6803 Significantly Enhances Polyhydroxybutyrate Production, Further Augmented by the adc1 Knockout Under Prolonged Nitrogen Deprivation

by Suthira Utharn, Peter Lindblad and Saowarath Jantaro

Int. J. Mol. Sci. 2025, 26(16), 7815; https://doi.org/10.3390/ijms26167815 (registering DOI) - 13 Aug 2025

Abstract

This study highlights a new avenue to improve polyhydroxybutyrate (PHB) productivity by optimizing genes related to arginine catabolism, which influences nitrogen metabolism in cyanobacteria based on the carbon/nitrogen metabolism balance. In the Synechocystis sp. PCC 6803 wild type (WT) and its adc1 mutant [...] Read more.

This study highlights a new avenue to improve polyhydroxybutyrate (PHB) productivity by optimizing genes related to arginine catabolism, which influences nitrogen metabolism in cyanobacteria based on the carbon/nitrogen metabolism balance. In the Synechocystis sp. PCC 6803 wild type (WT) and its adc1 mutant (Δadc1), the native putA gene, responsible for the oxidation of proline to glutamate, was overexpressed to create the OXPutA and OXPutA/Δadc1 strains, respectively. PHB accumulation was considerably higher in OXPutA and OXPutA/Δadc1 under the nitrogen-deprived condition than in strains that overexpressed the proC gene, involved in proline synthesis. The increased transcript level of glgX, associated with glycogen degradation, confirmed that glycogen served as the primary carbon source for PHB synthesis under nitrogen stress without any carbon source addition. Furthermore, proline and glutamate level changes helped cells deal with nitrogen stress and considerably improve intracellular carbon/nitrogen metabolism. As indicated by elevated levels of proA and argD transcripts as well as chlorophyll a accumulation, this impact was most noticeable in strains that overexpressed putA, which was crucial for the synthesis of glutamate, a precursor for important metabolic pathways that respond to nitrogen stress. Therefore, our metabolic model presents PHB-producing strains as promising candidates for biomaterial biotechnology applications in medical and agricultural fields. Full article

(This article belongs to the Section Molecular Genetics and Genomics)

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13 pages, 1914 KiB

Open AccessArticle

Therapeutic pCRISPRi Delivery to Lung Squamous Cell Carcinoma by Combining Nanobubbles and Ultrasound

by Taiki Yamaguchi, Yoko Endo-Takahashi, Takumi Amano, Arina Ihara, Tetsushi Sakuma, Takashi Yamamoto, Takuya Fukazawa and Yoichi Negishi

Pharmaceutics 2025, 17(8), 1053; https://doi.org/10.3390/pharmaceutics17081053 (registering DOI) - 13 Aug 2025

Abstract

Background/Objectives: Lung squamous cell carcinoma (SCC), a major subtype of non-small cell lung cancer, remains a significant clinical challenge due to a scarcity of actionable molecular targets and the limited effectiveness of current targeted therapies. Emerging treatment strategies inhibit the gene expression [...] Read more.

Background/Objectives: Lung squamous cell carcinoma (SCC), a major subtype of non-small cell lung cancer, remains a significant clinical challenge due to a scarcity of actionable molecular targets and the limited effectiveness of current targeted therapies. Emerging treatment strategies inhibit the gene expression of lineage survival oncogenes such as ΔNp63 and SOX2. CRISPR interference (CRISPRi) is a promising method to downregulate these genes; however, the efficacy depends on effective delivery. Here, we focused on the delivery system using nanobubbles (NBs) and ultrasound (US) for site-specific CRISPRi delivery to SCC. We evaluated the therapeutic efficacy of plasmid-based CRISPRi (pCRISPRi) targeting SOX2 or ΔNp63 using intratumoral pCRISPRi/NBs injections followed by US. Methods: A mixture of NBs and pCRISPRi was injected directly into the tumors and exposed to US-induced cavitation to facilitate pCRISPRi uptake. Tumor volume was measured every other day, and apoptosis was assessed by TUNEL assay. Results: In a lung SCC xenograft model, NBs/US-mediated pCRISPRi delivery induced apoptosis and significantly suppressed tumor growth. Conclusions: These findings suggest that US-guided, NB-facilitated delivery of pCRISPRi can locally suppress lineage survival oncogenes and trigger tumor cell death, representing a promising targeted therapy for lung SCC. Additionally, this platform could be adapted to other cancers by targeting alternative factors. Full article

(This article belongs to the Special Issue Recent Advances in the Use of Ultrasound to Enhance Drug Delivery and Efficacy for the Treatment of Cancer)

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19 pages, 4907 KiB

Open AccessArticle

Comparative Molecular Dynamics Study of 19 Bovine Antibodies with Ultralong CDR H3

by Olena Denysenko, Anselm H. C. Horn and Heinrich Sticht

Antibodies 2025, 14(3), 70; https://doi.org/10.3390/antib14030070 (registering DOI) - 13 Aug 2025

Abstract

Background/Objectives: Cows produce antibodies with ultralong CDRH3 segments (ulCABs) that contain a disulfide-stabilized knob domain. This domain is connected to the globular core of the antibody by a β-strand stalk. In the crystal structures, the stalk protrudes from the core in an [...] Read more.

Background/Objectives: Cows produce antibodies with ultralong CDRH3 segments (ulCABs) that contain a disulfide-stabilized knob domain. This domain is connected to the globular core of the antibody by a β-strand stalk. In the crystal structures, the stalk protrudes from the core in an extended conformation and presents the knob at its distal end. However, the rigidity of this topology has been questioned due to the extensive crystal packing present in most ulCAB crystal structures. To gain more insight into the dynamics of ultralong CDRH3s, we performed a comparative molecular dynamics (MD) study of 19 unique ulCABs. Methods: For all 19 systems, one-microsecond MD simulations were performed in explicit solvent. The analyses included an investigation of the systems’ conformational stability and the dynamics of the knob domain as well as an energetic analysis of the intramolecular knob interactions. Results: The simulations show that the extended stalk–knob conformation observed in the crystal structures is not preserved in solution. There are significant differences in the degree of knob dynamics, the orientations of the knobs, the number of flexible stalk residues, and the frequency of the motions. Furthermore, interactions between the knob and the light chain (LC) of the ulCABs were observed in about half of the systems. Conclusions: The study reveals that pronounced knob dynamics is a general feature of ulCABs rather than an exception. The magnitude of knob motions depends on the system, thus reflecting the high sequence diversity of the CDRH3s in ulCABs. The observed knob–LC interactions might play a role in stabilizing distinct knob orientations. The MD simulations of ulCABs could also help to identify suitable knob fragments as mini-antibodies by suggesting appropriate truncation points based on flexible sites in the stalks. Full article

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Graphical abstract

29 pages, 12262 KiB

Open AccessArticle

3D Heritage Reconstruction Through HBIM and Multi-Source Data Fusion: Geometric Change Analysis Across Decades

by Przemysław Klapa, Andrzej Żygadło and Massimiliano Pepe

Appl. Sci. 2025, 15(16), 8929; https://doi.org/10.3390/app15168929 (registering DOI) - 13 Aug 2025

Abstract

The reconstruction of historic buildings requires the integration of diverse data sources, both geometric and non-geometric. This study presents a multi-source data analysis methodology for heritage reconstruction using 3D modeling and Historic Building Information Modeling (HBIM). The proposed approach combines geometric data, including [...] Read more.

The reconstruction of historic buildings requires the integration of diverse data sources, both geometric and non-geometric. This study presents a multi-source data analysis methodology for heritage reconstruction using 3D modeling and Historic Building Information Modeling (HBIM). The proposed approach combines geometric data, including point clouds acquired via Terrestrial Laser Scanning (TLS), with architectural documentation and non-geometric information such as photographs, historical records, and technical descriptions. The case study focuses on a wooden Orthodox church in Żmijowiska, Poland, analyzing geometric changes in the structure over multiple decades. The reconstruction process integrates modern surveys with archival sources and, in the absence of complete geometric data, utilizes semantic, topological, and structural information. Geometric datasets from the 1990s, 1930s, and the turn of the 20th century were analyzed, supplemented by intermediate archival photographs and technical documentation. This integrated method enabled the identification of transformation phases and verification of discrepancies between historical records and the building’s actual condition. The findings confirm that the use of HBIM and multi-source data fusion facilitates accurate reconstruction of historical geometry and supports visualization of spatial changes across decades. Full article

(This article belongs to the Special Issue Intelligent Techniques and 3D Virtual Reconstruction for Architectural Heritage)

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27 pages, 1069 KiB

Open AccessReview

Recent Advances and Future Directions in Alzheimer’s Disease Genetic Research

by Mikaela Stancheva, Draga Toncheva and Sena Karachanak-Yankova

Int. J. Mol. Sci. 2025, 26(16), 7819; https://doi.org/10.3390/ijms26167819 (registering DOI) - 13 Aug 2025

Abstract

Alzheimer’s disease (AD) is a complex neurodegenerative condition which, despite its high prevalence and socioeconomic impact on the world, has an etiology that remains poorly understood. The genetic causes of AD are complex and have been continuously studied for decades. They range from [...] Read more.

Alzheimer’s disease (AD) is a complex neurodegenerative condition which, despite its high prevalence and socioeconomic impact on the world, has an etiology that remains poorly understood. The genetic causes of AD are complex and have been continuously studied for decades. They range from rare pathogenic, highly penetrant mutations in early-onset (EOAD) forms, which account for 5% of the cases to multiple-risk alleles across different genes in late-onset (LOAD) forms. Monogenic causes of EOAD allocate within APP, PSEN1, and PSEN2 genes in 10–15% of cases. The most significant risk factor in LOAD heritability is the APOE ε4 allele, as well as numerous loci within genes involved in immunity, endocytosis, lipid metabolism, and amyloid and tau processing. LOAD can also be attributed to the accumulation of somatic mutations, which may be detected by analysis of brain-derived cell-free DNA (cfDNA) in plasma. This review offers a comprehensive overview of the genetic architecture of Alzheimer’s disease, with particular focus on the molecular mechanisms underlying both early- and late-onset forms of the condition. An improved understanding of the genetic etiology of AD can aid better prevention, earlier diagnosis, and novel therapeutic approaches. This can be achieved by analyzing understudied populations, performing case-control studies with appropriately matched controls, and surveying brain-derived cell-free DNA in plasma, with the latter having the potential to contribute to the implementation of liquid biopsy in dementology. Full article

(This article belongs to the Special Issue Molecular Progression of Genome-Related Diseases)

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14 pages, 1054 KiB

Open AccessArticle

Comparison of Amyloid-PET Analysis Software Using ¹⁸F-Florbetaben PET in Patients with Cognitive Impairment

by Miju Cheon, Hyunkyung Yi, Sang-Won Ha, Min Ju Kang, Da-Eun Jeong, Yasser G. Abdelhafez and Lorenzo Nardo

Diagnostics 2025, 15(16), 2028; https://doi.org/10.3390/diagnostics15162028 (registering DOI) - 13 Aug 2025

Abstract

Background/Objectives: Quantitative analysis of amyloid PET imaging plays a crucial role in diagnosing Alzheimer’s disease (AD), particularly in cases where visual interpretation is equivocal. Multiple commercial software tools are available for this purpose, yet differences in their quantification and diagnostic performance remain [...] Read more.

Background/Objectives: Quantitative analysis of amyloid PET imaging plays a crucial role in diagnosing Alzheimer’s disease (AD), particularly in cases where visual interpretation is equivocal. Multiple commercial software tools are available for this purpose, yet differences in their quantification and diagnostic performance remain understudied, especially for Neurophet SCALE PET. Methods: We retrospectively analyzed ¹⁸F-florbetaben PET/CT scans from 129 patients with cognitive impairment, comprising 39 patients with AD and 90 with non-AD diagnoses, using three software tools: MIMneuro, CortexID Suite, and Neurophet SCALE PET. Standardized uptake value ratios (SUVRs) were obtained for six brain regions known for amyloid accumulation. Diagnostic accuracy was evaluated using ROC curve analysis, while inter-software correlations and reliability were assessed via Pearson correlation coefficients and intraclass correlation coefficients (ICC). Results: All three software programs significantly distinguished AD from non-AD patients in most brain regions. MIMneuro and Neurophet SCALE PET demonstrated the highest diagnostic performance, with MIMneuro achieving an AUC of 1.000 in the anterior cingulate gyrus. While MIMneuro and Neurophet SCALE PET showed moderate-to-strong SUVR correlations (r = 0.715–0.865), CortexID Suite showed limited correlation with the other tools. Inter-software reliability was moderate only in selected regions (ICC ≈ 0.5), indicating potential variability in SUVR measurements across platforms. Conclusions: MIMneuro, CortexID Suite, and Neurophet SCALE PET are effective for the semi-quantitative analysis of amyloid PET and can aid in the diagnosis of AD. However, clinicians should be cautious when interpreting SUVRs across different software tools due to limited inter-software consistency. Standardization efforts or consistent use of a single platform are recommended to avoid diagnostic discrepancies. Full article

(This article belongs to the Section Medical Imaging and Theranostics)

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52 pages, 959 KiB

Open AccessReview

Soy and Isoflavones: Revisiting Their Potential Links to Breast Cancer Risk

by Catherine Bennetau-Pelissero

Nutrients 2025, 17(16), 2621; https://doi.org/10.3390/nu17162621 (registering DOI) - 13 Aug 2025

Abstract

Soy has a long history of consumption in Asia and was traditionally prepared by rinsing, cooking, and simmering, methods which remove estrogenic isoflavones (Isofls). Population studies have indicated that soy and/or Isofls may be associated with a decreased risk of breast cancer (BC), [...] Read more.

Soy has a long history of consumption in Asia and was traditionally prepared by rinsing, cooking, and simmering, methods which remove estrogenic isoflavones (Isofls). Population studies have indicated that soy and/or Isofls may be associated with a decreased risk of breast cancer (BC), while in vitro and experimental data indicate dose-related proliferative effects of Isofls on breast cells. This review attempts to decipher the role of soy and Isofls in the risk of BC in women, since previous studies have suggested a lack of association with BC. Several dozen population studies conducted in Asian and Western countries were analyzed, as were data collected during in vitro animal and clinical trials of relevant doses of soy and Isofls. Although soy intake has been estimated well in Asian countries and could be related to preventive effects on BC risk, this has not been the case in the West, where the consumption of hidden soy is often omitted. However, in both cultures, the Isofl intake is misestimated, and the groups are misclassified. Indeed, in Asia, the origin of soy foods, i.e., homemade or industrial, has never been reported, and in the West, the amount of Isofls consumed in hidden soy has not been determined. Moreover, in most cohort studies, only a few subjects were exposed to active doses of Isofls on breast cells. Similarly, clinical interventions showed estrogenic effects of Isofls at relevant doses. Finally, population studies have not shown any convincing link between soy or Isofl intake and BC risk, likely because they have opposite effects on this pathology. Thus, based on in vitro, experimental, and clinical data, a deleterious effect of Isofls cannot be excluded when active doses are ingested, even if the soy food matrix can be protective. Full article

(This article belongs to the Special Issue The Potential Health Effects of Dietary Phytoestrogens)

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17 pages, 17147 KiB

Open AccessArticle

Flexural Performance of Basalt-Fiber-Grid-Reinforced Concrete Two-Way Slabs: Experimental Study and Numerical Simulation

by Chaobin Hu, Shun Jin, Liping Li, Xinrong Liu, Mingjian He, Changrong Fu, Ninghui Liang and Weiping Zhou

Buildings 2025, 15(16), 2862; https://doi.org/10.3390/buildings15162862 (registering DOI) - 13 Aug 2025

Abstract

To evaluate the feasibility of substituting mechanical testing with finite element simulation for basalt-fiber-grid-reinforced concrete, this study fabricated two-way slab specimens with varying basalt fiber grid layers. Flexural tests revealed load–deflection response characteristics of both fiber-reinforced and plain concrete. An ANSYS-based refined finite [...] Read more.

To evaluate the feasibility of substituting mechanical testing with finite element simulation for basalt-fiber-grid-reinforced concrete, this study fabricated two-way slab specimens with varying basalt fiber grid layers. Flexural tests revealed load–deflection response characteristics of both fiber-reinforced and plain concrete. An ANSYS-based refined finite element model successfully replicated bending deformation patterns and grid failure modes under identical conditions, with experimental-simulation comparisons validating model accuracy (error < 8%). Through parametric secondary development, the model was extended to analyze 9 single-layer and 72 double-layer grid configurations. A high-precision response surface model (R² ≥ 0.99) was established via nonlinear regression, enabling rapid performance prediction for arbitrary grid arrangements. This computational framework provides a reliable simulation tool for digital design of fiber-reinforced concrete components. Full article

(This article belongs to the Section Building Materials, and Repair & Renovation)

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22 pages, 294 KiB

Open AccessArticle

Association Between Missed Nursing Care and Nurse Fatigue: A Cross-Sectional Correlational Study

by Bushra Alshammari, Ghady Saud Alsaleh, Awatif Alrasheeday, Nadiah Baghdadi, Nabat Almalki, Farhan Alshammari, Amira Assiry and Mawahib Almalki

Nurs. Rep. 2025, 15(8), 298; https://doi.org/10.3390/nursrep15080298 (registering DOI) - 13 Aug 2025

Abstract

Background/Objectives: Missed nursing care—defined as any aspect of required patient care that is omitted or delayed—has emerged as a significant indicator of healthcare quality. Fatigue among nurses, particularly in high-demand environments, may contribute to care omissions. This study aimed to [...] Read more.

Background/Objectives: Missed nursing care—defined as any aspect of required patient care that is omitted or delayed—has emerged as a significant indicator of healthcare quality. Fatigue among nurses, particularly in high-demand environments, may contribute to care omissions. This study aimed to assess the prevalence and patterns of missed nursing care and its association with occupational fatigue among nurses working in Saudi hospitals. Methods: A cross-sectional correlational study was conducted among 183 registered nurses from multiple hospitals in the Hail and Madinah regions, Saudi Arabia. Data were collected using the Missed Nursing Care Scale (MISSCARE) and the Occupational Fatigue Exhaustion/Recovery Scale (OFER-15). Statistical analysis was performed to assess the relationships between missed care, fatigue, and demographic/work-related variables. Results: Nurses reported moderate levels of missed care, especially in basic care tasks such as oral hygiene, assistance with meals, and timely ambulation. The most frequently cited causes of missed care included insufficient staffing, high patient load, and a lack of support personnel. Occupational fatigue scores were also moderate, with notably low inter-shift recovery. A significant negative correlation was found between inter-shift recovery and missed care (r = −0.120, 95% CI: −0.23 to −0.005, p = 0.040), indicating that poorer recovery between shifts was associated with more frequent omissions. Other fatigue dimensions showed weak, non-significant associations with missed care. Conclusions: Missed nursing care is a prevalent issue in Saudi hospitals and is significantly influenced by organizational factors and nurses’ recovery between shifts. Interventions to improve staffing adequacy and promote rest and recovery may reduce care omissions and enhance patient outcomes. Full article

24 pages, 2010 KiB

Open AccessReview

Gentianaceae Family—Derived Bioactive Compounds—Therapeutic Values and Supporting Role in Inflammation and Detoxification

by Wiktoria Andryszkiewicz, Milena Chmielewska, Julia Ciecierska, Paulina Lenkiewicz, Wiktoria Marciniak, Wiktoria Raczycka, Agata Wojno, Julita Kulbacka, Przemysław Niewiński and Katarzyna Bieżuńska-Kusiak

Nutrients 2025, 17(16), 2619; https://doi.org/10.3390/nu17162619 (registering DOI) - 13 Aug 2025

Abstract

Herbs from the Gentianaceae family are widely known for their medicinal and pharmacological properties. They were used centuries ago as a part of traditional medicine in China and Tibet. This review aims to draw attention to the potential uses of gentian herbs in [...] Read more.

Herbs from the Gentianaceae family are widely known for their medicinal and pharmacological properties. They were used centuries ago as a part of traditional medicine in China and Tibet. This review aims to draw attention to the potential uses of gentian herbs in treating various diseases, including skin conditions, gastrointestinal and liver disorders, wound healing, rheumatoid arthritis, and diabetes. The aim of our study was to systematically summarize current knowledge about key bioactive compounds present in both roots and aerial parts—such as xanthones, iridoids, and flavonoids—and highlight their pharmacological significance. We also focused on the Gentianaceae family’s usage in complementary and alternative medicine, as well as their anti-inflammatory, anti-melanogenic, anti-ischemic, anti-fibrotic, and antioxidant properties, which can be utilized in the treatment and prevention of dermatological diseases, such as skin cancers. Here, we involve ethnomedicinal knowledge with modern pharmacological data; we also highlight the scientific relevance of gentian-derived compounds in drug development. This review concludes that these species represent a promising source of natural agents, while also underlining the need for further research and conservation strategies to preserve threatened species. Full article

(This article belongs to the Special Issue Fruits and Vegetable Bioactive Substances and Nutritional Value)

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27 pages, 1090 KiB

Open AccessArticle

Post-Pandemic Ecotourism Intentions and Climate Change Perceptions: The Role of Personality Domains

by Muhammed Kavak and Ipek Itir Can

Sustainability 2025, 17(16), 7320; https://doi.org/10.3390/su17167320 (registering DOI) - 13 Aug 2025

Abstract

This study aims to reveal how ecotourists’ general perceptions, concerns, and intentions to act regarding climate change have been shaped in the context of their personality domains following the COVID-19 pandemic. Data were collected from 409 participants who took part in nature walking [...] Read more.

This study aims to reveal how ecotourists’ general perceptions, concerns, and intentions to act regarding climate change have been shaped in the context of their personality domains following the COVID-19 pandemic. Data were collected from 409 participants who took part in nature walking activities in Turkey in 2024 using a survey method. The data were analyzed using quantitative methods such as structural equation modeling (SEM) and multiple regression analyses. The findings reveal statistically significant relationships between Big-Five personality domains of ecotourists’ and their perceptions of climate change, concerns, intentions to act, and ecotourism intentions. The results reveal that attitudes toward climate change have become more pronounced, especially in the post-pandemic period, and that personality domains are a strong determinant in shaping these attitudes. This study is important for the development of sustainable tourism policies and for providing strategic recommendations to managers in the field of ecotourism. Full article

(This article belongs to the Section Tourism, Culture, and Heritage)

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