MDPI - Publisher of Open Access Journals

Catalysts
Last 20 Years Update of DPEDA-Based Organocatalysts for Asymmetric Reactions
Current Oncology
Malignant Pleural Effusion: Diagnosis and Treatment—Up-to-Date Perspective
Animals
Defining the Role of IgE Against Cross-Reactive Carbohydrates in Dogs

Recent Articles

22 pages, 6166 KiB

Open AccessArticle

Schiff Base-Crosslinked Tetra-PEG-BSA Hydrogel: Design, Properties, and Multifunctional Functions

by Yuanyuan Qu, Jinlong Li, Xin Jia and Lijun Yin

J. Funct. Biomater. 2025, 16(2), 69; https://doi.org/10.3390/jfb16020069 (registering DOI) - 18 Feb 2025

Hydrogel network structures play a crucial role in determining mechanical properties and have broad applications in biomedical and industrial fields. Therefore, their rational design is essential. Herein, we developed a Schiff base-crosslinked hydrogel through the reaction of Tetra-armed polyethylene glycol with aldehyde end groups (Tetra-PEG-CHO) and bovine serum albumin (BSA) under alkaline conditions. In addition, the Tetra-PEG-BSA hydrogel showed a rapid gelation time of around 11 s, much faster than that of the GLU-BSA, HT-BSA, and GDL-BSA hydrogels. It had high optical transmittance (92.92% at 600 nm) and swelling ratios superior to the other gels in different solutions, maintaining structural integrity even in denaturing environments such as guanidine hydrochloride and SDS. Mechanical tests showed superior strain at break (84.12 ± 0.76%), rupture stress (28.64 ± 1.21 kPa), and energy dissipation ability (468.0 ± 34.9 kJ·m⁻³), surpassing all control group hydrogels. MTT cytotoxicity assays indicated that cell viability remained >80% at lower concentrations, confirming excellent biocompatibility. These findings suggest that Tetra-PEG-BSA hydrogels may serve as effective materials for drug delivery, tissue engineering, and 3D printing. Full article

(This article belongs to the Section Synthesis of Biomaterials via Advanced Technologies)

► Show Figures

Figure 1

---

Figure 3

---

Figure 4

---

Figure 5

---

Figure 6

---

Figure 7

---

Figure 8

---

Figure 9

---

Figure 10

26 pages, 492 KiB

Open AccessArticle

Can Digital Human Capital Promote Farmers’ Willingness to Engage in Green Production? Exploring the Role of Online Learning and Social Networks

by Siyu Gong, Ludi Jiang and Zhigang Yu

Behav. Sci. 2025, 15(2), 227; https://doi.org/10.3390/bs15020227 (registering DOI) - 18 Feb 2025

Abstract

The development of rural digitalization has become a key driving force for promoting green agricultural production. However, in practical operations, due to the insufficient digital skills and lack of necessary digital human capital among farmers, they struggle to distinguish between green production methods and traditional practices, which in turn reduces their willingness to adopt green production. This study employed empirical research methods to collect data from 854 farmers in China’s largest grain-producing region and used the Probit model to analyze the impact of digital human capital on farmers’ willingness to engage in green production. The results indicate that an increase in digital human capital can significantly enhance farmers’ willingness to engage in green production. Additionally, it was found that online learning can enhance farmers’ willingness towards green production, with informal online learning proving more effective. Further analysis revealed that social networks play a mediating role between digital human capital and farmers’ willingness to engage in green production. The study also explored the heterogeneous impact of digital human capital on different groups of farmers, highlighting that increases in digital human capital have a more pronounced effect on the willingness of small-scale farmers and middle-aged farmers to engage in green production. Therefore, continuously enhancing digital human capital, emphasizing diverse learning channels, and leveraging ’acquaintance networks’ to encourage farmers to improve their awareness of green production through digital platforms are critical for promoting sustainable green agriculture in developing countries. Full article

(This article belongs to the Section Behavioral Economics)

► Show Figures

Figure 1

12 pages, 6269 KiB

Open AccessArticle

Retrospective Analysis of Dental Implant Stability in Relation to Mandibular Bone Density and Cortical Thickness in Osteopenic and Osteoporotic Patients

by Monika Probst, Florian Probst, Matthias Tröltzsch, Matthias Bruckbauer, Alexander W. Marka, Gustav Andreisek, Thomas Frauenfelder and Egon Burian

J. Clin. Med. 2025, 14(4), 1339; https://doi.org/10.3390/jcm14041339 (registering DOI) - 18 Feb 2025

Abstract

Background/Objectives: The aim of this study is to examine the relationship between cervical spine and jaw bone mineral density (BMD) and assess how cortical thickness and BMD influence primary implant stability (PIS) across different bone health conditions. Methods: The study included 29 patients (mean age: 63.7 ± 13.7 years; 13 women) and 15 healthy controls (mean age: 25.3 ± 3.0 years; seven women). Cervical spine (C2–C4) and mandibular BMD were evaluated using asynchronous calibration and manual segmentation. Cortical thickness was measured, and primary implant stability was assessed via insertion torque in Newton centimeters (Ncm). Results: Cervical spine BMD was significantly lower in the patient group compared to controls (203.0 ± 51.0 vs. 252.0 ± 21.7 mg/dL, p < 0.0001). No significant correlation was found between mandibular BMD and cervical spine BMD in both groups (patients: ρ = 0.1287; p = 0.506, controls r = −0.1214; p = 0.667). Linear regression analysis revealed that cortical thickness alone, not implant site BMD, significantly influenced PIS (F(2.74) = 5.597, p = 0.005). Conclusions: Asynchronous calibration accurately quantifies cervical and mandibular BMD. Cortical thickness rather than overall bone density emerges as a critical factor in determining implant stability. These findings suggest that clinicians should prioritize cortical thickness assessment when planning dental implant procedures, potentially improving outcomes across diverse patient bone health profiles. Full article

(This article belongs to the Special Issue Emerging Technologies for Dental Imaging)

► Show Figures

Figure 1

---

Figure 3

---

Figure 4

---

Figure 5

15 pages, 2044 KiB

Open AccessArticle

Pilot Study on the Efficacy of a Novel Questionnaire for Assessing Psychological Health in Patients with Chronic Rhinosinusitis with Nasal Polyps Treated with Biologics

by Simonetta Masieri, Carlo Cavaliere, Antonella Loperfido, Elona Begvarfaj, Andrea Ciofalo, Francesco Maria Primerano, Gianluca Velletrani, Marcella Bugani, Pamela Cirilli, Francesco Maria Passali, Stefano Millarelli, Gianluca Bellocchi and Stefano Di Girolamo

Healthcare 2025, 13(4), 433; https://doi.org/10.3390/healthcare13040433 (registering DOI) - 18 Feb 2025

Abstract

Background/Objectives: Chronic rhinosinusitis with nasal polyps (CRSwNP) represents a debilitating disease with significant morbidity and decreased quality of life (QoL). The introduction of biologics in its management has allowed new therapeutic options, and Dupilumab represents the first approved biologic. This study aims to evaluate a possible relationship between the clinical response to biological therapy and mental health in patients with severe CRSwNP. Methods: This is a multicenter study conducted at the Otolaryngology departments of three major Italian health institutions. Participants were patients with CRSwNP treated with Dupilumab. Patients were assessed at baseline and during treatment by submitting them to a survey consisting of a dedicated questionnaire focused on psychological health and two patient-reported outcome measures (PROMs): the 22-item Sino-Nasal Outcome Test (SNOT-22) and a Visual Analogue Scale (VAS) for nasal symptoms. Results: 86 patients were included in the study (58 males and 28 females; mean age: 58.2 years). There was a significant improvement in both symptoms and QoL, with an enhanced psychological state observed in patients after the first administration and within the first months of therapy. Conclusions: This study evaluated the possible correlations between Dupilumab treatment and improvements in mental health in patients with CRSwNP, as assessed through a survey, and clinical conditions, assessed through SNOT-22 and VAS. Our findings showed that Dupilumab not only improved clinical symptoms but also had a positive impact on patients’ mental health, with benefits observed already after the first administration and the first months of therapy. This survey highlights the relevance of psychological well-being and its implications for patients with chronic diseases such as CRSwNP. Full article

(This article belongs to the Special Issue Patient-Reported Measures)

► Show Figures

Figure 1

---

Figure 3

---

Figure 4

21 pages, 1850 KiB

Open AccessReview

Deep Learning for Automatic Detection of Volcanic and Earthquake-Related InSAR Deformation

by Xu Liu, Yingfeng Zhang, Xinjian Shan, Zhenjie Wang, Wenyu Gong and Guohong Zhang

Remote Sens. 2025, 17(4), 686; https://doi.org/10.3390/rs17040686 (registering DOI) - 18 Feb 2025

Abstract

Interferometric synthetic aperture radar (InSAR) technology plays a crucial role in monitoring surface deformation and has become widely used in volcanic and earthquake research. With the rapid advancement of satellite technology, InSAR now generates vast volumes of deformation data. Deep learning has revolutionized data analysis, offering exceptional capabilities for processing large datasets. Leveraging these advancements, automatic detection of volcanic and earthquake deformation from extensive InSAR datasets has emerged as a major research focus. In this paper, we first introduce several representative deep learning architectures commonly used in InSAR data analysis, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and Transformer networks. Each architecture offers unique advantages for addressing the challenges of InSAR data. We then systematically review recent progress in the automatic detection and identification of volcanic and earthquake deformation signals from InSAR images using deep learning techniques. This review highlights two key aspects: the design of network architectures and the methodologies for constructing datasets. Finally, we discuss the challenges in automatic detection and propose potential solutions. This study aims to provide a comprehensive overview of the current applications of deep learning for extracting InSAR deformation features, with a particular focus on earthquake and volcanic monitoring. Full article

(This article belongs to the Special Issue Advanced SAR/InSAR Techniques in Understanding and Monitoring Geohazards)

► Show Figures

Figure 1

---

Figure 3

---

Figure 4

21 pages, 1542 KiB

Open AccessReview

Ancestry-Specific DNA Damage Repair Gene Mutations and Prostate Cancer

by Talaibek Borbiev, Kevin Babcock, Kayleigh Sinopole, Gregory T. Chesnut and Gyorgy Petrovics

Cancers 2025, 17(4), 682; https://doi.org/10.3390/cancers17040682 (registering DOI) - 18 Feb 2025

Abstract

This review is intended to reflect the currently available literature on both clinically significant germline mutations in DNA damage repair (DDR) genes as well as the importance of ancestral diversity in the pathogenesis of prostate cancer (PCa). The second most prevalent cancer worldwide in men is PCa, causing significant morbidity and mortality in its advanced stage. Emerging data highlight the substantial role of germline mutations of DDR genes in PCa pathogenesis, especially in progression to aggressive forms of the disease. Germline genetic testing is recognized as a necessary tool for efficient, individualized patient care. NCCR guidelines recommend inquiring about the family history of PCa and known germline variants and, if indicated, proceeding with germline multigene testing followed by post-test genetic counseling. Depending on the germline mutations in HR repair genes or in MMR genes, specific treatment options may provide clinical benefit. We will discuss specific germline mutations that are involved in PCa progression and prognosis in racially diverse populations. Full article

(This article belongs to the Special Issue New Insights into Urologic Oncology)

► Show Figures

Figure 1

---

Figure 3

---

Figure 4

Abstract

It is unknown whether there are differentially expressed proteins (DEPs) in the circulating exosomes of appropriate- vs. small-for-gestational-age (AGA vs. SGA) infants, and if so, whether such DEPs relate to measures of endocrine–metabolic health and body composition in childhood. Proteomic analysis in cord-blood-derived exosomes was performed by label-free quantitative mass spectrometry in AGA (n = 20) and SGA infants (n = 20) and 91 DEPs were identified. Enrichment analysis revealed that they were related to complement and coagulation cascades, lipid metabolism, neural development, PI3K/Akt and RAS/RAF/MAPK signaling pathways, phagocytosis and focal adhesion. Protein–protein interaction (PPI) analysis identified 39 DEPs involved in the pathways enriched by the KEGG and Reactome. Those DEPs were associated with measures of adiposity and insulin resistance and with liver fat at age 7 (all p < 0.01). Multivariate linear regression analysis uncovered that two DEPs (up-regulated in SGA), namely PCYOX1 (related to adipogenesis) and HSP90AA1 (related to lipid metabolism and metabolic-dysfunction-associated steatotic liver disease progression), were independent predictors of the hepatic fat fraction at age 7 (β = 0.634; p = 0.002; R² = 52% and β = 0.436; p = 0.009; R² = 24%, respectively). These data suggest that DEPs at birth may predict insulin resistance, adrenarche and/or ectopic adiposity in SGA children at age 7, when an early insulin-sensitizing intervention could be considered. Full article

27 pages, 5597 KiB

Open AccessArticle

Smart Organization of Imbalanced Traffic Datasets for Long-Term Traffic Forecasting

by Mustafa M. Kara, H. Irem Turkmen and M. Amac Guvensan

Sensors 2025, 25(4), 1225; https://doi.org/10.3390/s25041225 (registering DOI) - 18 Feb 2025

Abstract

Predicting traffic speed is an important issue, especially in urban regions. Precise long-term forecasts would enable individuals to conserve time and financial resources while diminishing air pollution. Despite extensive research on this subject, to our knowledge, no publications investigate or tackle the issue of imbalanced datasets in traffic speed prediction. Traffic speed data are often biased toward high numbers because low traffic speeds are infrequent. The temporal aspect of traffic carries two important factors for low-speed value. The daily population movement, captured by the time of day, and the weather data, recorded by month, are both considered in this study. Hour-wise Pattern Organization and Month-wise Pattern Organization techniques were devised, which organize the speed data using these two factors as a metric with a view to providing a superior representation of data characteristics that are in the minority. In addition to these two methods, a Speed-wise Pattern Organization strategy is proposed, which arranges train and test samples by setting boundaries on speed while taking the volatile nature of traffic into consideration. We evaluated these strategies using four popular model types: long short-term memory (LSTM), gated recurrent unit networks (GRUs), bi-directional LSTM, and convolutional neural networks (CNNs). GRU had the best performance, achieving a MAPE (Mean Absolute Percentage Error) of 13.51%, whereas LSTM demonstrated the lowest performance, with a MAPE of 13.74%. We validated their robustness through our studies and observed improvements in model accuracy across all categories. While the average improvement was approximately 4%, our methodologies demonstrated superior performance in low-traffic speed scenarios, augmenting model prediction accuracy by 11.2%. The presented methodologies in this study are applied in the pre-processing steps, allowing their application with various models and additional pre-processing procedures to attain comparable performance improvements. Full article

(This article belongs to the Section Navigation and Positioning)

► Show Figures