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This study proposes a method for estimating the kinetic coefficient of friction (COF) for asphalt pavements by improving and applying Persson’s friction theory. The method utilizes the power spectral density (PSD) of the top surface topography instead of the full PSD to better reflect the actual contact conditions. This approach avoids including deeper roughness components that do not contribute to real rubber–pavement contact due to surface skewness. The key aspect of the method is determining an appropriate cutting plane to isolate the top surface. Four cutting strategies were evaluated. Results show that the cutting plane defined at 0.5 times the root mean square (RMS) height exhibits the highest robustness across all pavement types, with the estimated COF closely matching the measured values for all four tested surfaces. This study presents an improved method for estimating the kinetic coefficient of friction (COF) of asphalt pavements by employing the power spectral density (PSD) of the top surface roughness, rather than the total surface profile. This refinement is based on Persson’s friction theory and aims to exclude the influence of deep surface irregularities that do not make actual contact with the rubber interface. The core of the method lies in defining an appropriate cutting plane to isolate the topographical features that contribute most to frictional interactions. Four cutting strategies were investigated. Among them, the cutting plane positioned at 0.5 times the root mean square (RMS) height demonstrated the best overall applicability. COF estimates derived from this method showed strong consistency with experimentally measured values across all four tested asphalt pavement surfaces, indicating its robustness and practical potential. Full article

(This article belongs to the Section Construction and Building Materials)

19 pages, 443 KiB

Open AccessArticle

Effects of a Flipped Classroom College Business Course on Students’ Pre-Class Preparation, In-Class Participation, Learning, and Skills Development

by Gordon Wang

Adm. Sci. 2025, 15(8), 301; https://doi.org/10.3390/admsci15080301 (registering DOI) - 2 Aug 2025

Abstract

As an example of pedagogical approaches that blend online and face-to-face instruction, the flipped classroom model has seen exponential growth in business schools. To explore its effectiveness, expectancy-value theory and cognitive load theory were employed to develop a framework linking students’ perceived usefulness of the online and in-person content to their pre-class preparation, class participation, perceived learning, and skills development. A preliminary test of this framework was conducted using a flipped Organizational Behavior course within a business diploma program at a publicly funded Canadian college. The perceived usefulness of the online component was positively associated with students’ pre-class preparation, which, in turn, was positively related to both their perceived learning and skills development. Implications for practice and directions for future research are discussed. Full article

(This article belongs to the Section Organizational Behavior)

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16 pages, 2901 KiB

Open AccessArticle

Unveiling the Genetic Landscape of Canine Papillomavirus in the Brazilian Amazon

by Jeneffer Caroline de Macêdo Sousa, André de Medeiros Costa Lins, Fernanda dos Anjos Souza, Higor Ortiz Manoel, Cleyton Silva de Araújo, Lorena Yanet Cáceres Tomaya, Paulo Henrique Gilio Gasparotto, Vyctoria Malayhka de Abreu Góes Pereira, Acácio Duarte Pacheco, Fernando Rosado Spilki, Mariana Soares da Silva, Felipe Masiero Salvarani, Cláudio Wageck Canal, Flavio Roberto Chaves da Silva and Cíntia Daudt

Microorganisms 2025, 13(8), 1811; https://doi.org/10.3390/microorganisms13081811 (registering DOI) - 2 Aug 2025

Abstract

Papillomaviruses (PVs) are double-stranded DNA viruses known to induce a variety of epithelial lesions in dogs, ranging from benign hyperplasia to malignancies. In regions of rich biodiversity such as the Western Amazon, data on the circulation and genetic composition of canine papillomaviruses (CPVs) remain scarce. This study investigated CPV types present in oral and cutaneous papillomatous lesions in domiciled dogs from Acre and Rondônia States, Brazil. Sixty-one dogs with macroscopically consistent lesions were clinically evaluated, and tissue samples were collected for histopathological examination and PCR targeting the L1 gene. Among these, 37% were histologically diagnosed as squamous papillomas or fibropapillomas, and 49.2% (30/61) tested positive for papillomavirus DNA. Sequencing of the L1 gene revealed that most positive samples belonged to CPV1 (Lambdapapillomavirus 2), while one case was identified as CPV8 (Chipapillomavirus 3). Complete genomes of three CPV1 strains were obtained via high-throughput sequencing and showed high identity with CPV1 strains from other Brazilian regions. Phylogenetic analysis confirmed close genetic relationships among isolates across distinct geographic areas. These findings demonstrate the circulation of genetically conserved CPVs in the Amazon and reinforce the value of molecular and histopathological approaches for the accurate diagnosis and surveillance of viral diseases in domestic dogs, especially in ecologically complex regions. Full article

(This article belongs to the Topic Advances in Infectious and Parasitic Diseases of Animals)

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26 pages, 1613 KiB

Open AccessArticle

Olive Oil-Based Lipid Coating as a Precursor Organogel for Postharvest Preservation of Lychee: Efficacy Combined with Polyamide/Polyethylene Packaging Under Passive Atmosphere

by Alessandra Culmone, Roberta Passafiume, Pasquale Roppolo, Ilenia Tinebra, Vincenzo Naselli, Alfonso Collura, Antonino Pirrone, Luigi Botta, Alessandra Carrubba, Nicola Francesca, Raimondo Gaglio and Vittorio Farina

Gels 2025, 11(8), 608; https://doi.org/10.3390/gels11080608 (registering DOI) - 2 Aug 2025

Abstract

Lychee (Lychee chinensis Sonn.) is a tropical fruit highly appreciated for its vivid red color, sweet flavor, and nutritional properties. However, it is highly perishable, with postharvest losses often due to oxidative browning and dehydration. This study evaluated the organic olive oil coating (OC), a natural lipidic system with the potential to act as a precursor for organogel development, combined with polyamide/polyethylene (PA/PE) packaging under passive modified atmosphere. Fruits were harvested at commercial maturity and divided into two groups: OC-treated and untreated control (CTR). Both groups were stored at 5 ± 1 °C and 90 ± 5% relative humidity and analyzed on days 0, 3, 6, and 9. The OC-treated fruits showed significantly better retention of physical, chemical, microbiological, and sensory qualities. The coating reduced oxidative stress and enzymatic browning, preserving color and firmness. The PA/PE packaging regulated gas exchange, lowering oxygen levels and delaying respiration and ripening. As a result, OC fruits had lower weight loss, a slower increase in browning index and maturity index, and better visual and sensory scores than the CTR group. This dual strategy proved effective in extending shelf life while maintaining the fruit’s appearance, flavor, and nutritional value. It represents a sustainable and natural approach to enhancing the postharvest stability of lychee. Full article

(This article belongs to the Special Issue Edible Coatings and Film: Gel-Based Innovations)

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23 pages, 2091 KiB

Open AccessArticle

Exploring the Impact of Bioactive Compounds Found in Extra Virgin Olive Oil on NRF2 Modulation in Alzheimer’s Disease

by Marilena M. Bourdakou, Eleni M. Loizidou and George M. Spyrou

Antioxidants 2025, 14(8), 952; https://doi.org/10.3390/antiox14080952 (registering DOI) - 2 Aug 2025

Abstract

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder marked by amyloid-β (Aβ) plaques, neurofibrillary tangles, blood–brain barrier dysfunction, oxidative stress (OS), and neuroinflammation. Current treatments provide symptomatic relief, but do not halt the disease’s progression. OS plays a crucial role in AD pathogenesis by promoting Aβ accumulation. Nuclear factor erythroid 2-related factor 2 (NRF2) is a key regulator of the antioxidant response, influencing genes involved in OS mitigation, mitochondrial function, and inflammation. Dysregulation of NRF2 is implicated in AD, making it a promising therapeutic target. Emerging evidence suggests that adherence to a Mediterranean diet (MD), which is particularly rich in polyphenols from extra virgin olive oil (EVOO), is associated with improved cognitive function and a reduced risk of mild cognitive impairment. Polyphenols can activate NRF2, enhancing endogenous antioxidant defenses. This study employs a computational approach to explore the potential of bioactive compounds in EVOO to modulate NRF2-related pathways in AD. We analyzed transcriptomic data from AD and EVOO-treated samples to identify NRF2-associated genes, and used chemical structure-based analysis to compare EVOO’s bioactive compounds with known NRF2 activators. Enrichment analysis was performed to identify common biological functions between NRF2-, EVOO-, and AD-related pathways. Our findings highlight important factors and biological functions that provide new insight into the molecular mechanisms through which EVOO consumption might influence cellular pathways associated with AD via modulation of the NRF2 pathway. The presented approach provides a different perspective in the discovery of compounds that may contribute to neuroprotective mechanisms in the context of AD. Full article

(This article belongs to the Special Issue Inhibition of Oxidative Stress and Related Signaling Pathways in Neuroprotection—2nd Edition)

11 pages, 715 KiB

Open AccessArticle

One Health Approach to Trypanosoma cruzi: Serological and Molecular Detection in Owners and Dogs Living on Oceanic Islands and Seashore Mainland of Southern Brazil

by Júlia Iracema Moura Pacheco, Louise Bach Kmetiuk, Melissa Farias, Gustavo Gonçalves, Aaronson Ramathan Freitas, Leandro Meneguelli Biondo, Cristielin Alves de Paula, Ruana Renostro Delai, Cláudia Turra Pimpão, João Henrique Perotta, Rogério Giuffrida, Vamilton Alvares Santarém, Helio Langoni, Fabiano Borges Figueiredo, Alexander Welker Biondo and Ivan Roque de Barros Filho

Trop. Med. Infect. Dis. 2025, 10(8), 220; https://doi.org/10.3390/tropicalmed10080220 (registering DOI) - 2 Aug 2025

Abstract

Via a One Health approach, this study concomitantly assessed the susceptibility of humans and dogs to Trypanosoma cruzi infections on three islands and in two mainland seashore areas of southern Brazil. Human serum samples were tested using an enzyme-linked immunosorbent assay (ELISA) to detect anti-T. cruzi antibodies, while dog serum samples were tested using indirect fluorescent antibodies in an immunofluorescence assay (IFA). Seropositive human and dog individuals were also tested using quantitative polymerase chain reaction (qPCR) in corresponding blood samples. Overall, 2/304 (0.6%) human and 1/292 dog samples tested seropositive for T. cruzi by ELISA and IFA, respectively, and these cases were also molecularly positive for T. cruzi by qPCR. Although a relatively low positivity rate was observed herein, these cases were likely autochthonous, and the individuals may have been infected as a consequence of isolated events of disturbance in the natural peridomicile areas nearby. Such a disturbance could come in the form of a fire or deforestation event, which can cause stress and parasitemia in wild reservoirs and, consequently, lead to positive triatomines. In conclusion, T. cruzi monitoring should always be conducted in suspicious areas to ensure a Chagas disease-free status over time. Further studies should also consider entomological and wildlife surveillance to fully capture the transmission and spread of T. cruzi on islands and in seashore mainland areas of Brazil and other endemic countries. Full article

(This article belongs to the Section One Health)

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16 pages, 1196 KiB

Open AccessArticle

Integrated Additive Manufacturing of TGV Interconnects and High-Frequency Circuits via Bipolar-Controlled EHD Jetting

by Dongqiao Bai, Jin Huang, Hongxiao Gong, Jianjun Wang, Yunna Pu, Jiaying Zhang, Peng Sun, Zihan Zhu, Pan Li, Huagui Wang, Pengbing Zhao and Chaoyu Liang

Micromachines 2025, 16(8), 907; https://doi.org/10.3390/mi16080907 (registering DOI) - 2 Aug 2025

Abstract

Electrohydrodynamic (EHD) printing offers mask-free, high-resolution deposition across a broad range of ink viscosities, yet combining void-free filling of high-aspect-ratio through-glass vias (TGVs) with ultrafine drop-on-demand (DOD) line printing on the same platform requires balancing conflicting requirements: for example, high field strengths to drive ink into deep and narrow vias; sufficiently high ink viscosity to prevent gravity-induced leakage; and stable meniscus dynamics to avoid satellite droplets and charge accumulation on the glass surface. By coupling electrostatic field analysis with transient level-set simulations, we establish a dimensionless regime map that delineates stable cone-jetting regime; these predictions are validated by high-speed imaging and surface profilometry. Operating within this window, the platform achieves complete, void-free filling of 200 µm × 1.52 mm TGVs and continuous 10 µm-wide traces in a single print pass. Demonstrating its capabilities, we fabricate transparent Ku-band substrate-integrated waveguide antennas on borosilicate glass: the printed vias and arc feed elements exhibit a reflection coefficient minimum of –18 dB at 14.2 GHz, a –10 dB bandwidth of 12.8–16.2 GHz, and an 8 dBi peak gain with 37° beam tilt, closely matching full-wave predictions. This physics-driven, all-in-one EHD approach provides a scalable route to high-performance, glass-integrated RF devices and transparent electronics. Full article

17 pages, 2547 KiB

Open AccessArticle

A Host Cell Vector Model for Analyzing Viral Protective Antigens and Host Immunity

by Sun-Min Ahn, Jin-Ha Song, Seung-Eun Son, Ho-Won Kim, Gun Kim, Seung-Min Hong, Kang-Seuk Choi and Hyuk-Joon Kwon

Int. J. Mol. Sci. 2025, 26(15), 7492; https://doi.org/10.3390/ijms26157492 (registering DOI) - 2 Aug 2025

Abstract

Avian influenza A viruses (IAVs) pose a persistent threat to the poultry industry, causing substantial economic losses. Although traditional vaccines have helped reduce the disease burden, they typically rely on multivalent antigens, emphasize humoral immunity, and require intensive production. This study aimed to establish a genetically matched host–cell system to evaluate antigen-specific immune responses and identify conserved CD8+ T cell epitopes in avian influenza viruses. To this end, we developed an MHC class I genotype (B21)-matched host (Lohmann VALO SPF chicken) and cell vector (DF-1 cell line) model. DF-1 cells were engineered to express the hemagglutinin (HA) gene of clade 2.3.4.4b H5N1 either transiently or stably, and to stably express the matrix 1 (M1) and nucleoprotein (NP) genes of A/chicken/South Korea/SL20/2020 (H9N2, Y280-lineage). Following prime-boost immunization with HA-expressing DF-1 cells, only live cells induced strong hemagglutination inhibition (HI) and virus-neutralizing (VN) antibody titers in haplotype-matched chickens. Importantly, immunization with DF-1 cells transiently expressing NP induced stronger IFN-γ production than those expressing M1, demonstrating the platform’s potential for differentiating antigen-specific cellular responses. CD8+ T cell epitope mapping by mass spectrometry identified one distinct MHC class I-bound peptide from each of the HA-, M1-, and NP-expressing DF-1 cell lines. Notably, the identified HA epitope was conserved in 97.6% of H5-subtype IAVs, and the NP epitope in 98.5% of pan-subtype IAVs. These findings highlight the platform’s utility for antigen dissection and rational vaccine design. While limited by MHC compatibility, this approach enables identification of naturally presented epitopes and provides insight into conserved, functionally constrained viral targets. Full article

(This article belongs to the Special Issue Molecular Research on Immune Response to Virus Infection and Vaccines)

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23 pages, 3916 KiB

Open AccessArticle

Leveraging Wearable Sensors for the Identification and Prediction of Defensive Pessimism Personality Traits

by You Zhou, Dongfen Li, Bowen Deng and Weiqian Liang

Micromachines 2025, 16(8), 906; https://doi.org/10.3390/mi16080906 (registering DOI) - 2 Aug 2025

Abstract

Defensive pessimism, an important emotion regulation and motivation strategy, has increasingly attracted scholarly attention in psychology. Recently, sensor-based methods have begun to supplement or replace traditional questionnaire surveys in personality research. However, current approaches for collecting vital signs data face several challenges, including limited monitoring durations, significant data deviations, and susceptibility to external interference. This paper proposes a novel approach using a NiCr/NiSi alloy film temperature sensor, which has a K-type structure and flexible piezoelectric pressure sensor to identify and predict defensive pessimism personality traits. Experimental results indicate that the Seebeck coefficients for K-, T-, and E-type thermocouples are approximately 41 μV/°C, 39 μV/°C, and 57 μV/°C, respectively, which align closely with national standards and exhibit good consistency across multiple experimental groups. Moreover, radial artery frequency experiments demonstrate a strong linear relationship between pulse rate and the intensity of external stimuli, where stronger stimuli correspond to faster pulse rates. Simulation experiments further reveal a high correlation between radial artery pulse frequency and skin temperature, and a regression model based on the physiological sensor data shows a good fit (p < 0.05). These findings verify the feasibility of using temperature and flexible piezoelectric pressure sensors to identify and predict defensive pessimism personality characteristics. Full article

(This article belongs to the Special Issue Structural Analyses and Designs for Flexible/Stretchable Electronics, 3rd Edition)

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16 pages, 2036 KiB

Open AccessArticle

Scalable Chemical Vapor Deposition of Silicon Carbide Thin Films for Photonic Integrated Circuit Applications

by Souryaya Dutta, Alex Kaloyeros, Animesh Nanaware and Spyros Gallis

Appl. Sci. 2025, 15(15), 8603; https://doi.org/10.3390/app15158603 (registering DOI) - 2 Aug 2025

Abstract

Highly integrable silicon carbide (SiC) has emerged as a promising platform for photonic integrated circuits (PICs), offering a comprehensive set of material and optical properties that are ideal for the integration of nonlinear devices and solid-state quantum defects. However, despite significant progress in nanofabrication technology, the development of SiC on an insulator (SiCOI)-based photonics faces challenges due to fabrication-induced material optical losses and complex processing steps. An alternative approach to mitigate these fabrication challenges is the direct deposition of amorphous SiC on an insulator (a-SiCOI). However, there is a lack of systematic studies aimed at producing high optical quality a-SiC thin films, and correspondingly, on evaluating and determining their optical properties in the telecom range. To this end, we have studied a single-source precursor, 1,3,5-trisilacyclohexane (TSCH, C₃H₁₂Si₃), and chemical vapor deposition (CVD) processes for the deposition of SiC thin films in a low-temperature range (650–800 °C) on a multitude of different substrates. We have successfully demonstrated the fabrication of smooth, uniform, and stoichiometric a-SiCOI thin films of 20 nm to 600 nm with a highly controlled growth rate of ~0.5 Å/s and minimal surface roughness of ~5 Å. Spectroscopic ellipsometry and resonant micro-photoluminescence excitation spectroscopy and mapping reveal a high index of refraction (~2.7) and a minimal absorption coefficient (<200 cm⁻¹) in the telecom C-band, demonstrating the high optical quality of the films. These findings establish a strong foundation for scalable production of high-quality a-SiCOI thin films, enabling their application in advanced chip-scale telecom PIC technologies. Full article

(This article belongs to the Section Materials Science and Engineering)

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36 pages, 8123 KiB

Open AccessArticle

Enhanced Methodology for Peptide Tertiary Structure Prediction Using GRSA and Bio-Inspired Algorithm

by Diego A. Soto-Monterrubio, Hernán Peraza-Vázquez, Adrián F. Peña-Delgado and José G. González-Hernández

Int. J. Mol. Sci. 2025, 26(15), 7484; https://doi.org/10.3390/ijms26157484 (registering DOI) - 2 Aug 2025

Abstract

Recent advancements have been made in the precise prediction of protein structures within the Protein Folding Problem (PFP), particularly in relation to minimizing the energy function to achieve stable and biologically relevant protein structures. This problem is classified as NP-hard within computational theory, necessitating the development of various techniques and algorithms. Bio-inspired algorithms have proven effective in addressing NP-hard challenges in practical applications. This study introduces a novel hybrid algorithm, termed GRSABio, which integrates the strategies of Jumping Spider Algorithm (JSOA) with the Golden Ratio Simulated Annealing (GRSA) for peptide prediction. Furthermore, the GRSABio algorithm incorporates a Convolutional Neural Network for fragment prediction (FCNN), forms an enhanced methodology called GRSABio-FCNN. This integrated framework achieves improved structure refinement based on energy for protein prediction. The proposed enhanced GRSABio-FCNN approach was applied to a dataset of 60 peptides. The Wilcoxon and Friedman statistics test were employed to compare the GRSABio-FCNN results against recent state-of-the-art-approaches. The results of these tests indicate that the GRSABio-FCNN approach is competitive with state-of-the-art methods for peptides up to 50 amino acids in length and surpasses leading PFP algorithms for peptides with up to 30 amino acids. Full article

(This article belongs to the Special Issue Advances in Biomathematics, Computational Biology, and Bioengineering)

18 pages, 3020 KiB

Open AccessArticle

JAK2/STAT3 Signaling in Myeloid Cells Contributes to Obesity-Induced Inflammation and Insulin Resistance

by Chunyan Zhang, Jieun Song, Wang Zhang, Rui Huang, Yi-Jia Li, Zhifang Zhang, Hong Xin, Qianqian Zhao, Wenzhao Li, Saul J. Priceman, Jiehui Deng, Yong Liu, David Ann, Victoria Seewaldt and Hua Yu

Cells 2025, 14(15), 1194; https://doi.org/10.3390/cells14151194 (registering DOI) - 2 Aug 2025

Abstract

Adipose tissue inflammation contributes to obesity-induced insulin resistance. However, increasing evidence shows that high BMI (obesity) is not an accurate predictor of poor metabolic health in individuals. The molecular mechanisms regulating the metabolically activated M1 macrophage phenotype in the adipose tissues leading to insulin resistance remain largely unknown. Although the Janus Kinase (Jak)/signal transducer and activator of transcription 3 (Stat3) signaling in myeloid cells are known to promote the M2 phenotype in tumors, we demonstrate here that the Jak2/Stat3 pathway amplifies M1-mediated adipose tissue inflammation and insulin resistance under metabolic challenges. Ablating Jak2 in the myeloid compartment reduces insulin resistance in obese mice, which is associated with a decrease in infiltration of adipose tissue macrophages (ATMs). We show that the adoptive transfer of Jak2-deficient myeloid cells improves insulin sensitivity in obese mice. Furthermore, the protection of obese mice with myeloid-specific Stat3 deficiency against insulin resistance is also associated with reduced tissue infiltration by macrophages. Jak2/Stat3 in the macrophage is required for the production of pro-inflammatory cytokines that promote M1 macrophage polarization in the adipose tissues of obese mice. Moreover, free fatty acids (FFAs) activate Stat3 in macrophages, leading to the induction of M1 cytokines. Silencing the myeloid cell Stat3 with an in vivo siRNA targeted delivery approach reduces metabolically activated pro-inflammatory ATMs, thereby alleviating obesity-induced insulin resistance. These results demonstrate Jak2/Stat3 in myeloid cells is required for obesity-induced insulin resistance and inflammation. Moreover, targeting Stat3 in myeloid cells may be a novel approach to ameliorate obesity-induced insulin resistance. Full article

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18 pages, 5178 KiB

Open AccessArticle

Quantification of Suspended Sediment Concentration Using Laboratory Experimental Data and Machine Learning Model

by Sathvik Reddy Nookala, Jennifer G. Duan, Kun Qi, Jason Pacheco and Sen He

Water 2025, 17(15), 2301; https://doi.org/10.3390/w17152301 (registering DOI) - 2 Aug 2025

Abstract

Monitoring sediment concentration in water bodies is crucial for assessing water quality, ecosystems, and environmental health. However, physical sampling and sensor-based approaches are labor-intensive and unsuitable for large-scale, continuous monitoring. This study employs machine learning models to estimate suspended sediment concentration using images captured in natural light, named RGB, and near-infrared (NIR) conditions. A controlled dataset of approximately 1300 images with SSC values ranging from 1000 mg/L to 150,000 mg/L was developed, incorporating temperature, time of image capture, and solar irradiance as additional features. Random forest regression and gradient boosting regression were trained on mean RGB values, red reflectance, time of captured, and temperature for natural light images, achieving up to 72.96% accuracy within a 30% relative error. In contrast, NIR images leveraged gray-level co-occurrence matrix texture features and temperature, reaching 83.08% accuracy. Comparative analysis showed that ensemble models outperformed deep learning models like Convolutional Neural Networks and Multi-Layer Perceptrons, which struggled with high-dimensional feature extraction. These findings suggest that using machine learning models and RGB and NIR imagery offers a scalable, non-invasive, and cost-effective way of sediment monitoring in support of water quality assessment and environmental management. Full article

(This article belongs to the Special Issue Water Modeling Using Combined Machine Learning and Fieldwork Investigation)

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22 pages, 1496 KiB

Open AccessReview

Drosophila melanogaster: How and Why It Became a Model Organism

by Maria Grazia Giansanti, Anna Frappaolo and Roberto Piergentili

Int. J. Mol. Sci. 2025, 26(15), 7485; https://doi.org/10.3390/ijms26157485 (registering DOI) - 2 Aug 2025

Abstract

Drosophila melanogaster is one of the most known and used organisms worldwide, not just to study general biology problems but above all for modeling complex human diseases. During the decades, it has become a central tool to understand the genetics of human disease, how mutations alter the behavior and health of cells, tissues, and organs, and more recently to test new compounds with a potential therapeutic use. But how did this small insect become so crucial in genetics? And how is it currently used in the study of human conditions affecting millions of people? In this review, we retrace the historical origins of its adoption in genetics laboratories and list all the advantages it provides to scientific research, both for its daily usage and for the fine tuning of gene regulation through genetic engineering approaches. We also provide some examples of how it is used to study human diseases such as cancer, neurological and infectious diseases, and its importance in drug discovery and testing. Full article

(This article belongs to the Special Issue Drosophila: A Versatile Model in Biology and Medicine—2nd Edition)

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10 pages, 1425 KiB

Open AccessArticle

Reconstructing the Gait Pattern of a Korean Cadaver with Bilateral Lower Limb Asymmetry Using a Virtual Humanoid Modeling Program

by Min Woo Seo, Changmin Lee and Hyun Jin Park

Diagnostics 2025, 15(15), 1943; https://doi.org/10.3390/diagnostics15151943 (registering DOI) - 2 Aug 2025

Abstract

Background and Objective: This study presents a combined osteometric and biomechanical analysis of a Korean female cadaver exhibiting bilateral lower limb bone asymmetry with abnormal curvature and callus formation on the left femoral midshaft. Methods: To investigate bilateral bone length differences, osteometric measurements were conducted at standardized landmarks. Additionally, we developed three gait models using Meta Motivo, an open-source reinforcement learning platform, to analyze how skeletal asymmetry influences stride dynamics and directional control. Results: Detailed measurements revealed that the left lower limb bones were consistently shorter and narrower than their right counterparts. The calculated lower limb lengths showed a bilateral discrepancy ranging from 39 mm to 42 mm—specifically a 6 mm difference in the femur, 33 mm in the tibia, and 36 mm in the fibula. In the gait pattern analysis, the normal model exhibited a straight-line gait without lateral deviation. In contrast, the unbalanced, non-learned model demonstrated compensatory overuse and increased stride length of the left lower limb and a tendency to veer leftward. The unbalanced, learned model showed partial gait normalization, characterized by reduced limb dominance and improved right stride, although directional control remained compromised. Conclusions: This integrative approach highlights the biomechanical consequences of lower limb bone discrepancy and demonstrates the utility of virtual agent-based modeling in elucidating compensatory gait adaptations. Full article

(This article belongs to the Special Issue Clinical Anatomy and Diagnosis in 2025)

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