Search Results (1,820)

Silk fibroin (SF) has evolved from a traditional biopolymer to a leading regenerative medicine material. Its combination of mechanical strength, biocompatibility, tunable degradation, and molecular adaptability makes SF a unique matrix that is both bioactive and intelligent. Advances in hydrogel engineering have transformed SF from a passive scaffold into a smart, living hydrogel. These systems can instruct cell fate, sense microenvironmental signals, and deliver therapeutic signals as needed. By incorporating stem cells, progenitors, or engineered immune and microbial populations, SF hydrogels now serve as synthetic niches for organoid maturation and as adaptive implants for tissue regeneration. These platforms replicate extracellular matrix complexity and evolve with tissue, showing self-healing, shape-memory, and stimuli-responsive properties. Such features are redefining biomaterial–cell interactions. SF hydrogels are used for wound healing, musculoskeletal repair, neural and cardiac patches, and developing scalable organoid models for disease and drug research. Challenges remain in maintaining long-term cell viability, achieving clinical scalability, and meeting regulatory standards. This review explores how advances in SF engineering, synthetic biology, and organoid science are enabling SF-based smart living hydrogels in bridging the gap between research and clinical use. Full article

The dental pulp is a dynamic connective tissue essential for tooth vitality, sensory function, immune defense, and reparative dentinogenesis. Conventional endodontic procedures, while effective in eradicating infection, often result in a non-functional, devitalized tooth, highlighting the need for biologically based regenerative approaches. The emergence of three-dimensional (3D) culture systems has transformed pulp biology and endodontic research by providing physiologically relevant microenvironments that better reproduce the dentino-pulp interface, vascular and neural networks, and immune interactions. This review synthesizes current advances in 3D dental pulp modeling, from scaffold-based and hydrogel systems to spheroids, organoids, bioprinted constructs, and microfluidic “tooth-on-a-chip” platforms. Each system’s composition, biological relevance, and translational potential are critically examined with respect to odontogenic differentiation, angiogenesis, neurogenesis, and inflammatory response. Applications in disease modeling, biomaterial screening, and regenerative endodontics are highlighted, showing how these models bridge fundamental biology and therapeutic innovation. Finally, we discuss key challenges including vascularization, innervation, standardization, and clinical translation, and propose integrative strategies combining bioprinting, stem-cell engineering, and organ-on-chip technologies to achieve functional pulp regeneration. Overall, 3D pulp models represent a paradigm shift from reductionist cultures to bioinstructive, patient-relevant platforms that accelerate the development of next-generation endodontic therapies. Full article

Neurological damage, a debilitating condition closely associated with chronic neuroinflammation, currently lacks disease-modifying treatments, with management limited to symptomatic relief. Vitamins B6 (VB6), B12 (VB12), and proteolipid protein 1 (PLP-1) exhibit multimodal neuroprotective and anti-inflammatory effects; however, their therapeutic potential is limited by low bioavailability and inadequate ability to cross the blood–brain barrier (BBB). To address these limitations, we developed an ursolic acid-based nanoparticle system for the intranasal co-delivery of VB6, VB12, and recombinant PLP-1. The PLP-1 model predicted by AlphaFold3 was used for molecular docking. The docking results confirmed high-affinity binding interactions with VB6 and VB12, elucidating the mechanistic basis of their synergy. In vitro studies using a glucose-deprived PC12 cell injury model identified an optimal synergistic molar ratio of 10:1:2 (VB6: VB12: PLP-1). This combination significantly upregulated neuroprotective markers (PLP-1 and PGC-1α) and downregulated the pro-inflammatory cytokine TNF-α. In a mouse model of neural damage, the nano-encapsulated combination therapy demonstrated improved pharmacokinetics and significantly attenuated neuroinflammation and oxidative stress in brain tissue. This was evidenced by lower TNF-α and IL-1β levels and elevated GSH and SOD concentrations compared to free drug controls. The treatment regimen showed no detectable hepatorenal toxicity. Our findings demonstrate that this nanoformulation represents a safe, effective, and promising disease-modifying strategy to treat vestibular dysfunction by synergistically targeting its underlying neuroimmunological mechanisms. Full article

Background. Dystroglycanopathies (DGPs) constitute a set of recessive, neuromuscular congenital dystrophies that result from impaired glycosylation of dystroglycan (DG). These disorders typically course with CNS alterations, which, alongside gradual muscular dystrophy, may include brain malformations, intellectual disability and a panoply of ocular defects. In this process, the protein products of 22 genes, collectively dubbed DGP-associated genes, directly or indirectly participate sequentially along a complex, branched biosynthetic pathway. POMGNT2 and POMGNT1 are two enzymes whose catalytic activity consists of transferring the same substrate, a molecule of N-acetylglucosamine (GlcNAc) to a common substrate, the O-mannosylated α subunit of DG. Despite their presumptive role in retinal homeostasis, there are currently no reports describing their expression pattern or function in this tissue. Purpose. This work focuses on POMGNT2 and POMGNT1 expression in the mammalian retina, and on the characterization of their distribution across retinal layers, and in the 661W photoreceptor cell line. Methods. The expression of POMGNT2 protein in different mammalian species’ retinas, including those of mice, rats, cows and monkeys, was assessed by immunoblotting. Additionally, POMGNT2 and POMGNT1 distribution profiles were analyzed using immunofluorescence confocal microscopy in retinal sections of monkeys and mice, and in 661W cultured cells. Results. Expression of POMGNT2 was detected in the neural retina of all species studied, being present in both cytoplasmic and nuclear fractions of the monkey and mouse, and in 661W cells. In the cytoplasm, POMGNT2 was concentrated in the endoplasmic reticulum (ER) and/or Golgi complex, depending on the species and cell type, whereas POMGNT1 accumulated only in the Golgi complex in both monkey and mouse retinas. Additionally, both proteins were present in the nucleus of the 661W cells, concentrating in the euchromatin and heterochromatin, as well as in nuclear PML and Cajal bodies, and nuclear speckles. Conclusions. Our results are indicative that POMGNT2 and POMGNT1 participate in the synthesis of O-mannosyl glycans added to α-dystroglycan in the ER and/or Golgi complex in the cytoplasm of mammalian retinal cells. Also, they could play a role in the modulation of gene expression at the mRNA level, which remains to be established, in a number of nuclear compartments in transformed retinal neurons. Full article

Background: Minimally invasive hyperthermia and regenerative therapies require materials that deliver precise, localized heat without compromising biocompatibility. Most conventional polymers are thermally insulating and challenging to control in vivo, motivating this review. Objectives: We aimed to (i) examine the use of thermally enhanced biopolymers in hyperthermia-based therapies, (ii) appraise evidence from clinical and preclinical studies, (iii) identify and classify principal applications in regenerative medicine. Methods: A PRISMA-guided systematic review (2020–2025) with predefined inclusion/exclusion criteria was conducted and complemented by a bibliometric analysis using VOSviewer for mapping and visualization. Results: Modifying biopolymers—via functionalization with photothermal or magnetic nanoagents (Au; Fe₂O₃/Fe₃O₄/CoFe₂O₄; CuS; Ag; MXenes, e.g., Nb₂C), crosslinking strategies, and hybrid formulations—significantly increased thermal conductivity, enabling localized hyperthermia and controlled drug release. In vitro and in vivo studies showed that europium-doped iron oxide nanoparticles embedded in chitosan generated heat efficiently while sparing healthy tissues, underscoring the need to balance biocompatibility and thermal performance. Hydrogel systems enriched with carbon nanomaterials (graphene, carbon nanotubes) and matrices such as GelMA, PNIPAM, hyaluronic acid, and PLA/PLGA demonstrated tissue compatibility and effective thermal behavior; graphene was compatible with neural tissue without inducing inflammation. Conclusions: Thermally conductive biopolymers show growing potential for oncology and regenerative medicine. The evidence supports further academic and interdisciplinary research to optimize safety, performance, and translational pathways. Full article

Background/Objectives: Lung cancer (NSCLC), which accounts for approximately 85% of lung cancers, exhibits marked heterogeneity that complicates molecular characterization and treatment selection. Recent advances in deep learning (DL) have enabled the extraction of genomic-related morphological features directly from routine Hematoxylin and Eosin (H&E) histopathology, offering a potential complement to Next-Generation Sequencing (NGS) for precision oncology. This review aimed to evaluate how DL models have been applied to predict molecular alterations in NSCLC using H&E-stained slides. Methods: A systematic search following PRISMA 2020 guidelines was conducted across PubMed, Scopus, and Web of Science to identify studies published up to March 2025 that used DL models for mutation prediction in NSCLC. Eligible studies were screened, and data on model architectures, datasets, and performance metrics were extracted. Results: Sixteen studies met inclusion criteria. Most employed convolutional neural networks trained on publicly available datasets such as The Cancer Genome Atlas (TCGA) to infer key mutations including EGFR, KRAS, and TP53. Reported areas under the curve ranged from 0.65 to 0.95, demonstrating variable but promising predictive capability. Conclusions: DL-based histopathology shows strong potential for linking tissue morphology to molecular signatures in NSCLC. However, methodological heterogeneity, small sample sizes, and limited external validation constrain reproducibility and generalizability. Standardized protocols, larger multicenter cohorts, and transparent validation are needed before these models can be translated into clinical practice. Full article

The process of aging is fundamentally driven by genomic instability and the accumulation of DNA damage, which progressively impair cellular and tissue function. In order to counteract these challenges, cells rely on the DNA damage response (DDR), a multilayered signaling and repair network that preserves genomic integrity and sustains homeostasis. Within this framework, nucleases and helicases have pivotal and complementary roles by remodeling aberrant DNA structures, generating accessible repair intermediates, and determining whether a cell achieves faithful repair, undergoes apoptosis, or enters senescence. Defects in these enzymes are exemplified in human progeroid syndromes, where inherited mutations lead to premature aging phenotypes. This phenomenon is also replicated in genetically engineered mouse models that exhibit tissue degeneration, stem cell exhaustion, and metabolic dysfunction. Beyond their canonical repair functions, helicases and nucleases also interface with the epigenome, as DNA damage-induced chromatin remodeling alters enzyme accessibility, disrupts transcriptional regulation, and drives progressive epigenetic drift and chronic inflammatory signaling. Moreover, their dysfunction accelerates the exhaustion of adult stem cell populations, such as hematopoietic, neural, and mesenchymal stem cells. As a result, tissue regeneration is undermined, establishing a self-perpetuating cycle of senescence, impaired repair, and organismal aging. Current research is focused on developing therapeutic strategies that target the DDR–aging axis on several fronts: by directly modulating repair pathways, by regulating the downstream consequences of senescence, or by preventing DNA damage from accumulating upstream. Taken together, evidence from human disease, animal models, molecular studies, and pharmacological interventions demonstrates that nucleases and helicases are not only essential for genome maintenance but also decisive in shaping aging trajectories. This provides valuable knowledge into how molecular repair pathways influence organismal longevity and age-related diseases. Full article

Microsatellite instability represents a key biomarker in gastrointestinal cancers with significant diagnostic and therapeutic implications. Traditional molecular assays for microsatellite instability detection, while effective, are costly, time-consuming, and require specialized infrastructure. In this paper we propose an explainable deep learning-based method for microsatellite instability detection starting from the analysis of histopathological images. We consider a set of convolutional neural network architectures i.e., MobileNet, Inception, VGG16, VGG19, and a Vision Transformer model, and we propose a way to provide a kind of clinical explainability behind the model prediction through (three) Class Activation Mapping techniques. With the aim to further strengthen trustworthiness in predictions, we introduce a set of robustness metrics aimed to quantify the consistency of highlighted discriminative regions across different Class Activation Mapping methods. Experimental results on a real-world dataset demonstrate that VGG16 and VGG19 models achieve the best performance in terms of accuracy; in particular, the VGG16 model obtains an accuracy of 0.926, while the VGG19 one reaches an accuracy equal to 0.917. Furthermore, Class Activation Mapping techniques confirmed that the developed models consistently focus on similar tissue regions, while robustness analysis highlighted high agreement between different Class Activation Mapping techniques. These results indicate that the proposed method not only achieves interesting predictive accuracy but also provides explainable predictions, with the aim to boost the integration of deep learning into real-world clinical practice. Full article

Prostate cancer is a global health concern, and early diagnosis plays a vital role in improving the survival rate. Accurate segmentation is a key step in the automated diagnosis of prostate cancer; however, manual segmentation remains time-consuming and challenging. Micro-Ultrasound (US) is particularly well-suited for prostate cancer detection, offering real-time imaging with a resolution comparable to that of MRI. This enables improved spatial resolution and detailed visualization of small anatomical structures. With recent advances in deep learning for medical image segmentation, precise prostate segmentation has become critical for biopsy guidance, disease diagnosis, and follow-up. However, segmentation of the prostate in micro-US images remains challenging due to indistinct boundaries between the prostate and surrounding tissue. In this work, we propose a model for precise micro-ultrasound image segmentation. The model employs a dual-encoder architecture that integrates Convolutional Neural Networks (CNN) and Transformer-based encoders in parallel, combined with a fusion module to capture both global dependencies and low-level spatial details. More importantly, we introduce a decoder based on Mamba v2 to enhance segmentation accuracy. A Hypergraph Neural Network (HGNN) is employed as a bridge between the dual encoders and Mamba decoder to model correlations among non-pairwise connections. Experimental results on micro-US datasets demonstrated that our model achieved superior or comparable performance to state-of-the-art methods, with a Dice score of 0.9416 and an HD95 of 1.93. Full article

Background/Objectives: Sclerosing epithelioid fibrosarcoma (SEF) is a rare soft tissue sarcoma with high rates of local recurrence and distant metastasis. Primary spinal involvement is exceedingly uncommon and often misdiagnosed due to radiological and histopathological resemblance to more frequent spinal tumors. The objective of this study is to present a rare case of thoracic spinal SEF and to contextualize it within the available literature. Methods: We describe the case of a 37-year-old woman presenting with progressive back pain and dysesthesia. MRI demonstrated a heterogeneously enhancing mass at the left T10–T11 neural foramen, initially interpreted as a common nerve sheath tumor. Gross total resection (GTR) was achieved, and histopathological analysis revealed a SEF. Clinical course, adjuvant therapies, and outcomes were evaluated, together with a review of previously reported spinal SEF cases. Results: Despite GTR followed by adjuvant chemotherapy, local recurrence occurred 18 months later. The patient underwent subtotal resection (STR) with adjuvant proton therapy. At 18-month follow-up after the second procedure, she remained neurologically stable and disease-free. The literature review confirmed the rarity of spinal SEF, its frequent misdiagnosis, and the absence of standardized therapeutic protocols. Conclusions: Spinal SEF is a rare malignancy that can mimic benign spinal tumors, delaying diagnosis. Its management relies on multidisciplinary assessment, individualized therapy, and long-term follow-up. This report increases awareness of spinal SEF and provides additional evidence to support clinical decision-making in rare spinal tumors. Full article

Improper use of drugs in both animal and human therapy, such as doxycycline (DOX), lead to the accumulation of residues in edible animal tissues as well as in the environment. Plant-derived compounds reduce the adverse effects of drugs. This study aimed to evaluate the effect of cannabidiol (CBD) in two concentrations: lower (1.56 µg/mL) (DOX + C1) and higher (3.125 µg/mL) (DOX + C2) on the cytotoxicity of doxycycline in human cells. The toxicity of DOX and its CBD-containing mixtures was assessed after 72 h of exposure in three human cell lines: neural (SH-SY5Y), hepatic (HepG2), and kidney (HEK-293). The exposure to DOX resulted in inhibition of mitochondrial activity (SH-SY5Y) and inhibition of DNA synthesis (HepG2 and HEK-293). IC₅₀ values for DOX ranged from 9.8 to >200 µg/mL in SH-SY5Y cells, 13.4 to 200 µg/mL in HepG2 cells, and 8.9 to 30.4 µg/mL in HEK-293 cells. The nature of the interaction depended on both the cell lines and the concentration of CBD in the mixture. Both CBD mixtures demonstrated a synergistic interaction in neuronal cells. In HepG2 cells, both mixtures showed additive and antagonistic interactions. In HEK-293 cells, the DOX + C1 mixture exhibited an antagonistic (protective) effect, while the DOX + C2 mixture showed an additive effect. There were no changes in oxidative stress levels; however, alterations in apoptosis levels and cell morphology were observed following exposure to the mixtures. The presence of doxycycline in the diet and the environment poses a health risk to consumers. The increasing consumption of CBD-containing products may reduce the risk associated with the presence of this drug in food. It is worth emphasizing the need for research aimed at minimizing the adverse effects of pharmaceuticals on the health of humans and animals. Full article

Enterovirus D68 (EV-D68) is a significant global pathogen associated with severe respiratory infections and acute flaccid myelitis in children. Currently, there are no vaccines or antiviral drugs available for EV-D68, and a robust model to elucidate the pathogenesis of EV-D68 and evaluate treatment methods is lacking. We developed a mouse-adapted EV-D68 strain that caused progressive limb paralysis after intramuscular inoculation in 7-day-old mice. Viral load analysis showed that the skeletal muscle and spinal cord had the highest titers and most severe injuries. RNA sequencing of the infected muscle, brain, spinal cord, and lung tissues revealed differentially expressed genes (DEGs) associated with viral infection and pathogenesis. DEGs were significantly enriched in various pathways associated with antiviral immunity, interferon responses, and cytokine signaling. In the spinal cord, DEGs highlighted mitochondrial dysfunction and oxidative stress as crucial contributors to neural damage. Flow cytometry analysis of spinal cord cells showed that EV-D68 activates the immune system, leading to systemic inflammation and significant increases in CD8⁺ and CD4⁺ T cells, but limited neutrophil and monocyte infiltration. This mouse model provides a valuable tool for studying EV-D68 pathogenesis and evaluating antiviral and vaccine efficacy, thereby advancing the understanding of its neuropathological mechanisms. Importance: We developed a novel mouse model of EV-D68 that provides a valuable tool for studying its pathogenesis and evaluating antiviral and vaccine efficacy, deepening the understanding of its neuropathological basis. Full article

Drowsy driving is a major cause of traffic accidents worldwide, and its early detection remains essential for road safety. Conventional driver monitoring systems (DMS) primarily rely on behavioral indicators such as eye closure, gaze, or head pose, which typically appear only after a significant decline in alertness. This study explores the potential of facial near-infrared (NIR) imaging as a hypothetical physiological indicator of drowsiness. Because NIR light penetrates more deeply into biological tissue than visible light, it may capture subtle variations in blood flow and oxygenation near superficial vessels. Based on this hypothesis, we conducted a pilot feasibility study involving young adult participants to investigate whether drowsiness levels could be estimated from single-frame NIR facial images acquired at 940 nm—a wavelength already used in commercial DMS and suitable for both physiological sensitivity and practical feasibility. A convolutional neural network (CNN) was trained to classify multiple levels of drowsiness, and Gradient-weighted Class Activation Mapping (Grad-CAM) was applied to interpret the discriminative regions. The results showed that classification based on 940 nm NIR images is feasible, achieving an optimal accuracy of approximately 90% under the binary classification scheme (Pattern A). Grad-CAM revealed that regions around the nasal dorsum contributed to this, consistent with known physiological signs of drowsiness. These findings support the feasibility of NIR-based drowsiness classification in young drivers and provide a foundation for future studies with larger and more diverse populations. Full article

The management of large bulky tumors is very challenging. The current treatment options for effective palliation of symptoms are limited. These tumors often present a large burden at the time of diagnosis, growing along critical bony and neural structures and preventing surgical resection in most of the cases. These tumors are also known to be relatively resistant to chemotherapy, with very low response rates. In addition, conventional photon-based radiotherapy has a limited effect due to their radioresistance, the use of large treatment fields, and the impossibility of delivering high doses because of the higher risk of normal tissue toxicity. Therefore, more effective radiation treatments for palliation are needed to achieve greater local control rates. A recent approach called partial ablative radiotherapy (PART) has been shown to be potentially able to improve the effectiveness of radiotherapy. This technique is based on the ability of recent advanced delivery techniques to deliver a high “ablative” dose to the central part of the tumor, maintaining a very low and safe dose profile at the periphery to spare the surrounding organs at risk. Although this technique has been evaluated only in small studies and case reports, it showed notable treatment responses and safety profiles. The present narrative review describes the rationale for PART, the current and forthcoming state of evidence, the existing studies, and the future directions for the development of this approach, including the associated challenges. Full article

The gut microbiota of Drosophila melanogaster offers a simplified yet powerful system to study conserved mechanisms of host–microbe interactions. Unlike the highly complex mammalian gut microbiota, which includes hundreds of species, the fly gut harbors a small and defined community dominated by Lactobacillus and Acetobacter. Despite its low diversity, this microbiota exerts profound effects on host physiology. Commensal bacteria modulate nutrient acquisition, regulate insulin/TOR signaling, and buffer dietary imbalances to support metabolic homeostasis and growth. They also influence neural and behavioral traits, including feeding preferences, mating, and aggression, through microbial metabolites and interactions with host signaling pathways. At the immune level, microbial molecules such as peptidoglycan, acetate, uracil, and cyclic dinucleotides activate conserved pathways including Imd, Toll, DUOX, and STING, balancing antimicrobial defense with tolerance to commensals. Dysbiosis disrupts this equilibrium, accelerating aging, impairing tissue repair, and contributing to tumorigenesis. Research in Drosophila demonstrates how a low-diversity microbiota can shape systemic host biology, offering mechanistic insights relevant to human health and disease. Full article