Search Results (20,954)

It is well known that environmental factors influence the risk of type 2 diabetes mellitus (T2DM). Several studies have linked the xenobiotics present in tobacco or air pollutants to T2DM development, although the underlying mechanisms remain unclear. Surfactant protein D (SP-D), an immune component released into the bloodstream after lung injury, has been associated with metabolic diseases. The aim of this study was to investigate whether SP-D mediates the effects of smoking or air pollution exposure on T2DM risk in the Spanish adult population. Socio-demographic, lifestyle (including smoking status) and clinical data from 2155 participants from the Di@bet.es cohort were analyzed. Annual concentrations of PM₁₀, PM_2.5, SO₂, CO and NO₂ according to participants’ residential address codes were used to study air pollution exposure. T2DM was diagnosed at baseline and after 7.5 years of follow-up. SP-D serum levels were measured by ELISA and categorized as above or below the 25th percentile. Our results revealed a higher percentage of smokers in the high SP-D category; however, no associations were observed between air pollutants (PM₁₀, PM_2.5, SO₂, CO) and SP-D categories. Both smoking and elevated SP-D levels were found to increase the risk of T2DM independently. Mediation analysis indicated that SP-D mediates 14% of the effect of smoking on T2DM incidence in the Spanish adult population. Full article

The central purpose of this study is to develop and validate an advanced numerical model capable of simulating the vibrational behavior of the operator’s seat in a tractor-type agricultural vehicle designed for operation in protected horticultural environments, such as vegetable greenhouses. The three-dimensional (3D) model of the seat was created using SolidWorks 2023, while its dynamic response was investigated through Finite Element Analysis (FEA) in Altair SimSolid, enabling a detailed evaluation of the natural vibration modes within the 0–80 Hz frequency range. Within this interval, eight significant natural frequencies were identified and correlated with the real structural behavior of the seat assembly. For experimental validation, direct time-domain measurements were performed at a constant speed of 5 km/h on an uneven, grass-covered dirt track within the research infrastructure of INMA Bucharest, using the TE-0 self-propelled electric tractor prototype. At the operator’s seat level, vibration data were collected considering the average anthropometric characteristics of a homogeneous group of subjects representative of typical tractor operators. The sample of participating operators, consisting exclusively of males aged between 27 and 50 years, was selected to ensure representative anthropometric characteristics and ergonomic consistency for typical agricultural tractor operators. Triaxial accelerometer sensors (NexGen Ergonomics, Pointe-Claire, Canada, and Biometrics Ltd., Gwent, UK) were strategically positioned on the seat cushion and backrest to record accelerations along the X, Y, and Z spatial axes. The recorded acceleration data were processed and converted into the frequency domain using Fast Fourier Transform (FFT), allowing the assessment of vibration transmissibility and resonance amplification between the floor and seat. The combined numerical–experimental approach provided high-fidelity validation of the seat’s dynamic model, confirming the structural modes most responsible for vibration transmission in the 4–8 Hz range—a critical sensitivity band for human comfort and health as established in previous studies on whole-body vibration exposure. Beyond validating the model, this integrated methodology offers a predictive framework for assessing different seat suspension configurations under controlled conditions, reducing experimental costs and enabling optimization of ergonomic design before physical prototyping. The correlation between FEA-based modal results and field measurements allows a deeper understanding of vibration propagation mechanisms within the operator–seat system, supporting efforts to mitigate whole-body vibration exposure and improve long-term operator safety in horticultural mechanization. Full article

This work investigates the effect of a bio-based plasticizer derived from used sunflower oil on the crystallization behavior of poly (lactic acid) (PLA), comparing it with that of the conventional plasticizer tributyrin. This study aims to explore biodegradable alternatives to petroleum-based materials and to evaluate their potential in modulating PLA crystallization kinetics without altering the crystalline structure of the resulting sustainable material solutions with tailored performance. PLA-based films containing 5%, 10%, and 15% plasticizer were prepared and characterized by differential scanning calorimetry (DSC), polarized optical microscopy (POM), and X-Ray diffraction (XRD). DSC analysis showed a decrease in the glass transition temperatures upon plasticization, with tributyrin producing a more pronounced effect than the recycled sunflower oil plasticizer. XRD patterns confirmed that the crystalline form of PLA remained unchanged regardless of plasticizer type or content. POM revealed that both plasticizers influenced crystallization kinetics, with the bio-plasticizer promoting larger and more sparsely distributed spherulites than tributyrin, indicating differences in nucleation efficiency and crystal growth. Crystallization kinetics were further analyzed using the Avrami model, the Lauritzen-Hoffman theory, and the isoconversional method. Avrami analysis indicated that nucleation mechanisms were largely unaffected, although the overall crystallization rate increased upon plasticization. Lauritzen-Hoffman analysis confirmed crystallization in Regime III, controlled by nucleation, while isoconversional analysis showed reduced activation energy in plasticized PLA. These findings highlight the ability of bio-derived plasticizers to modulate PLA crystallization, promoting the valorization of a food industry residue as a sustainable plasticizer. This study hopes to contribute relevant knowledge to emerging areas of polymer processing, such as 3D printing, to develop sustainable and high-performance PLA-based materials. Full article

Background: Diabetes often causes microvascular complications such as neuropathy. Autonomic neuropathy remains under-recognized, and its impact on quality of life (QoL) is unclear. This study investigated associations between symptoms of autonomic dysfunction, including organ-specific subdomains, and QoL in individuals with type 1 (T1D) and type 2 diabetes (T2D). Methods: A cross-sectional population-based survey was conducted in the North Denmark Region among individuals with T1D and T2D, assessing autonomic symptom burden with the Composite Autonomic Symptom Score-31 (COMPASS-31), general well-being with the Short Form Health Survey (SF-36), and psychological well-being with the Hospital Anxiety and Depression Scale. Multivariate linear regression assessed associations between autonomic symptom scores and QoL outcomes. Results: The COMPASS-31 scores were 8.9 (2.9; 22.8) in T1D and 12.4 (5.3; 26.1) in T2D. SF-36 physical composite scores were 52.1 (43.2; 56.4) in T1D and 49.3 (40.3; 54.8) in T2D, with similar mental composite scores (50.7 (40.3; 56.9) vs. 51.4 (41.2; 57.2)). Signs of moderate to severe anxiety were observed in 9.9% (95% confidence interval (CI): 8.1–11.9) of T1D and 8.9% (95% CI: 8.1–9.6) of T2D, while depression was present in 5.9% (95% CI: 4.5–7.6) and 5.1% (95% CI: 4.5–5.7). Higher autonomic symptom burden, especially pupillary, vasomotor, and bladder domains, was associated with lower SF-36 score and higher anxiety and depression scores. Conclusions: the Autonomic symptom burden is associated with reduced QoL and increased psychological distress in individuals with diabetes. These findings emphasize the importance of assessing and managing autonomic symptoms in diabetes care to support overall well-being. Full article

Although covalently crosslinked gelatin hydrogels have been investigated for use in 3D cell culture due to inherent bioactivity and proliferation within the denatured collagen precursor, the stability of the matrix, and relatively inexpensive synthesis, current systems lack precise control over mechanical properties, including homogeneity, stiffness, and efficient diffusion of nutrients to embedded cells. Difficulties in modifying gel matrix composition and functionalization have limited the use of covalently crosslinked gelatin hydrogels as a three-dimensional (3D) cell culture medium, lacking the ability to tailor the microenvironment for specific cell types. In addition, the currently utilized chain-growth photopolymerization mechanism for crosslinking hydrogels has a potential for side reactions between the matrix backbone and components of the cell surface, requires a high concentration of radicals for initiation, and only cures with long irradiation times, which could lead to cytotoxicity. To overcome these limitations, a superfast curing reaction mechanism, in which a thiol monomer reacts efficiently with non-homopolymerizable alkenes, is suggested. This mechanism reliably produces a well-defined matrix that does not require a high radical concentration for photoinitiation. Mechanical customization of the hydrogel is largely achievable through variation in degree of functionalization of the gelatin backbone, dependent on reaction conditions such as pH, allyl concentration, and time. This work provides a mechanistic framework for GelAGE hydrogel fabrication by elucidating the molecular mechanism of gelatin functionalization with AGE and the thiol-ene crosslinking reactions controlling network stiffness. These insights provide the foundation for engineering hydrogels that mimic the viscoelastic and structural characteristics of cartilage, enabling advanced in vitro models for osteoarthritis research. Full article

The TIP60/NuA4 complex is a large, multifunctional histone acetyltransferase assembly of ~1.7 megadaltons, composed of 17–20 subunits, which plays a central role in epigenetic regulation. Through recognition of H3K4me3 by the ING3 reader, TIP60/NuA4 is recruited to sites of active transcription, where it remodels chromatin to regulate gene expression. Its activities include histone acetylation, histone variant exchange, transcriptional co-activation, and regulation of the cell cycle and apoptosis. In this review, we examine how altered subunit levels or mutations impact the chromatin structure and transcriptional activity, and how these changes influence differentiation across diverse cell types. We emphasize the molecular mechanisms by which TIP60/NuA4 shapes lineage specification, including histone H2A and H4 acetylation by the KAT5 catalytic subunit, H2A.Z incorporation by EP400, and interactions with transcription factors such as MyoD, PPARγ, and Myc. By integrating mechanistic and functional insights, we highlight how TIP60/NuA4 acts as a central epigenetic hub in differentiation and contributes to proper developmental transitions. Full article

Single-molecule nanopore sensors have enabled real-time detection of enzymatic cleavage events, yet achieving sensitive and specific analysis of protease activity remains an important challenge for diagnostic applications. We engineered OmpG nanopore constructs incorporating thrombin recognition peptides into loop 6 with varied flexible and negatively charged linkers to optimize accessibility and cleavage. SDS-PAGE gel analysis showed that constructs with the recognition peptide placed after residue D225 and incorporating dual linkers achieved cleavage efficiencies up to 95%, whereas constructs without linkers showed limited cleavage. Single-channel recordings revealed that linker integration modulates pore conductance, with extended loops exhibiting intermediate open-state currents near 18 pA compared to 25 pA in wild-type OmpG. Upon thrombin addition, rapid and irreversible current drops confirmed real-time protease activity detection. These results demonstrate the critical role of linker design, particularly flexibility and charge, in optimizing nanopore protease sensors, providing a versatile platform for biomedical applications. Full article

Gradient stiffness structures are increasingly recognized for their excellent energy absorption capabilities, particularly under challenging loading conditions. Most studies focus on varying the thickness of the structure in order to produce gradient stiffness. This work introduces an innovative approach to design honeycomb architectures with controlled gradient stiffness along the out-of-plane direction achieved by materials’ microstructure variations. The gradient is achieved by combining three types of thermoplastic polyurethane (TPU) materials: porous TPU, plain TPU, and carbon fiber (CF)-reinforced TPU. By varying the material distribution across the honeycomb layers, a smooth transition in stiffness is formed, improving both mechanical resilience and energy dissipation. To fabricate these structures, a dual-head 3D printer was employed with one head printed processed TPU with a chemical blowing agent to produce porous and plain sections, while the other printed a CF-reinforced TPU. By alternating between the two print heads and modifying the processing temperatures, honeycombs with up to three distinct stiffness zones were produced. Compression testing under out-of-plane loading revealed clear plateau and densification regions in the stress–strain curves. Pure CF-reinforced honeycombs absorbed the most energy at stress levels above ~4.5 MPa, while porous TPU honeycombs were more effective under stress levels below ~1 MPa. Importantly, the gradient stiffness honeycombs achieved a balanced energy absorption profile across a broader range of stress levels, offering enhanced performance and adaptability for applications like protective equipment, packaging, and automotive structures. Full article

Background: Three-dimensional (3D) printed scaffolds have emerged as promising tools for bone regeneration, but the optimal structural design and pore size remain unclear. Polylactic acid (PLA) reinforced with graphene oxide (GO) offers enhanced mechanical and biological performance, yet systematic evaluation of architecture and pore size is limited. Methods: Two scaffold architectures (lattice-type and dode-type) with multiple pore sizes were fabricated using UV-curable PLA/GO resin. Physical accuracy, porosity, and mechanical properties were assessed through compression and fatigue testing. Based on in vitro screening, four pore sizes (930 μm, 690 μm, 558 μm, 562 μm) within the dode-type structure were analyzed. The 558 μm and 562 μm scaffolds, showing distinct fracture thresholds, were further evaluated in rat and rabbit calvarial defect models for inflammation and bone regeneration. Results: In vitro testing revealed that while 930 μm and 690 μm scaffolds exhibited superior compressive strength, the 562 μm scaffold showed a unique critical fracture behavior, and the 558 μm scaffold offered comparable stability with higher resistance to premature failure. In vivo studies confirmed excellent biocompatibility in both groups, with early bone formation favored in the 558 μm scaffold and more continuous and mature bone observed in the 562 μm scaffold at later stages. Conclusions: This stepwise strategy—from structural design to pore size screening and preclinical validation—demonstrates that threshold-level mechanical properties can influence osteogenesis. PLA/GO scaffolds optimized at 558 μm and 562 μm provide a translationally relevant balance between mechanical stability and biological performance for bone tissue engineering. Full article

In regenerative medicine, an engineered tissue is а composition of a sample of cells cultured on a spatially controlled medical device, called a biological scaffold (or just a bioscaffold). These devices are made of tissue-equivalent materials and represent the biological, mechanical, and spatial conditions in a specific type of human or animal tissue, becoming a possible way to replace damaged structures and develop artificial tissues or organs. Scaffolds with narrowly controlled characteristics—biological, mechanical and spatial properties—are vital for experiments mimicking in vivo conditions and in tissue regeneration scenarios. The aim of this narrative review is to identify and discuss the most important properties of these artificial constructs and the ways to achieve them via 3D printing-based technologies. Properties that can direct the development and differentiation of the cultured cells in a specific direction and ensure their biocompatibility and bioresorption, mechanical properties, spatial architecture, and porosity are discussed. The most common considerations in terms of the role of material selection, additives, and signal molecules and the appropriate spatially controlled manufacturing technologies for their assembly are covered, as are the radiological, biomechanical, and histological methods for their analysis. Finally, this paper highlights the challenges to the achievement of optimal scaffolds through additive manufacturing and gives suggestions for further research and development in this field. Full article

Background/Objectives: Odontoid fractures—prevalently Anderson–D’Alonzo type II—are clinically relevant for their biomechanical instability and risk of non-union. Posterior C1–C2 fusion yields the highest fusion rates but sacrifices atlantoaxial rotation. Anterior odontoid screw fixation (AOSF) enables direct osteosynthesis while preserving motion. This study aimed to evaluate the radiographic outcomes, fusion rate, and technical considerations of AOSF in a consecutive single-center series, highlighting anatomical and procedural factors influencing bone healing. Methods: Retrospective, single-center case series of patients who underwent AOSF for acute type II odontoid fractures (2018–2024). Inclusion criteria included CT-confirmed fractures with reducible alignment. Radiographic parameters (fracture gap and angulation) were measured on standardized sagittal CT reconstructions. Outcomes were evaluated at 6 weeks, 3 months, and 6 months. Mean follow-up was 24 months. Results: The mean fracture gap decreased from 5.3 mm preoperatively to 0.8 mm postoperatively, and angulation from 27.8° to 3.5° (p < 0.0001). Nine of ten patients (90%) achieved solid fusion; one required secondary posterior fixation. No intra- or postoperative infections, neurovascular injuries, or neurological deficits were observed. Conclusions: AOSF is a safe and effective motion-preserving technique in appropriately selected Grauer IIA/IIB fractures. Precise anatomical reduction (<2 mm gap, <5–10° angulation) is a key predictor of successful fusion, even in elderly patients. Future multicenter studies with larger cohorts and standardized clinical outcome measures are needed to validate radiographic thresholds and optimize patient selection. Full article

Haemophilus influenzae type b (Hib) is a Gram-negative bacterium that causes severe infections in children under five, especially in developing countries. Although vaccination using capsular polysaccharide by Hib (linear polymer 5-D-ribitol-(1→1)-β-D-ribose-3-phosphate) conjugated to tetanus toxoid is effective, its production is complex and costly. This study aimed to develop a continuous production process for PRP to increase productivity, reduce batch numbers, and simplify manufacturing. Using a 1 L bioreactor, five dilution rates (0.13 to 0.32 h⁻¹) were tested, with the best performance observed at 0.23 h⁻¹, reaching a productivity of 167 mgL⁻¹·h⁻¹. Under optimized conditions, parameters such as free and immobilized PRP, glucose consumption, acetate formation, and biomass were monitored. The process yielded 874 mgL⁻¹ of PRP after 74.4 h, with 78% in the free form and a final productivity of 165 mgL⁻¹·h⁻¹, approximately six times higher than batch processes and twice as high as fed-batch processes. The continuous process proved more efficient and required less infrastructure to meet production demands. However, further optimization is needed to enhance product quality and assess overall feasibility. Full article

Background/Objectives: Conventional two-dimensional (2D) cell cultures offer valuable insights into cancer cell biology; however, they lack in replicating the complex interactions present in solid tumors. Therefore, research has shifted towards the development of three-dimensional (3D) cell models that recapitulate the dynamic cell–cell and cell–matrix interactions within the complex tumor microenvironment (TME), better resembling tumor growth and initial stages of dissemination. Extracellular matrix, a key component within the TME, regulates cell morphology and signaling, influencing key functional properties. Breast cancer remains the most frequently diagnosed cancer type in women and a leading cause of cancer-related mortality. Methods: The aim of the present study was the development of breast cancer cell-derived spheroids, utilizing two breast cancer cell lines with differential estrogen receptor (ER) expression profile, and their characterization in terms of morphology, functional properties, and expression of epithelial-to-mesenchymal transition (EMT) markers and matrix signatures implicated in breast cancer progression. To this end, the ERα-positive MCF-7, and ERβ-positive MDA-MB-231 breast cancer cell lines were utilized. Results: Our findings revealed notable phenotypic transitions between 2D and 3D cultures, which were further supported by differential EMT markers expression. Moreover, spheroids exhibited distinct expression profiles of key receptors [ERs, epidermal growth factor receptor (EGFR) and insulin-like growth factor receptor (IGF1R)] and matrix molecules (syndecans, and matrix metalloproteinases), accompanied by altered functional cell properties. Bioinformatic tools further emphasized the interplay between the studied matrix regulators and their prognostic relevance in breast cancer. Conclusions: Overall, this study introduces a simple yet informative 3D breast cancer model that captures key TME features to better predict cell behavior in vitro. Full article

Background/Objective: Biochemical recurrence (BCR) after radical prostatectomy (RP) for prostate cancer indicates disease progression. Although type 2 diabetes mellitus (T2D) shows a paradoxical association with prostate cancer risk, the prognostic role of T2D-related genetic variants remains unclear. Methods: We analyzed 113 common T2D susceptibility-related single-nucleotide polymorphisms (SNPs) in 644 Taiwanese men with localized prostate cancer (D’Amico risk classification: 12% low, 34% intermediate, and 54% high) treated with RP. Associations between SNPs and BCR were assessed using Cox regression, adjusting for key clinicopathological factors. Functional annotation was performed using HaploReg and FIVEx, while The Cancer Genome Atlas transcriptomic data were analyzed for C2 calcium-dependent domain-containing 4A (C2CD4A) expression. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were applied to explore related biological pathways. Results: C2CD4A SNP rs4502156 was independently associated with a reduced risk of BCR (hazard ratio = 0.80, p = 0.035). The protective C allele correlated with higher C2CD4A expression. Low C2CD4A expression is associated with advanced pathological stages, higher Gleason scores, and disease progression. GSEA revealed negative enrichment of mitotic and chromatid segregation pathways in high-C2CD4A-expressing tumors, with E2F targets being the most suppressed. GSVA confirmed an inverse correlation between C2CD4A expression and E2F pathway activity, with CDKN2C as a co-expressed functional gene. Conclusions: The T2D-related variant rs4502156 in C2CD4A independently predicts a lower risk of BCR, potentially via suppression of the E2F pathway, and may serve as a germline biomarker for postoperative risk stratification. Full article

Machine learning-based digital soil mapping often struggles with spatial heterogeneity and long-range dependencies. To address these limitations, this study proposes Multi-Attention Convolutional Neural Networks (MACNN). This deep learning algorithm integrates multiple attention mechanisms to improve mapping accuracy. First, environmental covariates are determined from the soil-landscape model. These are then fed as structured input to the Convolutional Neural Network. Next, by incorporating Transformer self-attention and multi-head attention mechanisms, this study effectively models the long-range dependencies between soil types and features. Concurrently, the Convolutional Block Attention Module (CBAM) is introduced. CBAM features both channel and spatial dual attention, enabling adaptive weighting of crucial feature channels and spatial locations. This significantly enhances the algorithm’s sensitivity to discriminative information. To validate its effectiveness, the proposed MACNN algorithm was used for soil type mapping in Heilongjiang Province. Compared to Random Forest, Decision Tree, and One-Dimensional Convolutional Neural Network algorithms, MACNN demonstrated superior classification performance. It achieved an overall classification accuracy of 81.27%. An ablation study was conducted to investigate the importance of individual modules within the proposed algorithm. The findings indicate that progressively integrating Transformer and CBAM modules into the 1D-CNN baseline significantly enhances algorithm performance through synergistic gains. Therefore, this integrated algorithm offers a feasible solution to improve digital soil mapping accuracy, providing significant reference value for future research and applications. Full article