Search Results (1,431)

Bone-related defects present a key challenge in orthopaedics. The current gold standard, autografts, poses significant limitations, such as donor site morbidity, limited supply, and poor morphological adaptability. This study investigates the potential of scaffold geometry to induce osteogenic differentiation of human adipose-derived stem cells (hADSCs) through mechanotransduction, without the use of chemical inducers. Four distinct poly-(L)-lactic acid (PLA) scaffold architectures—Traditional Cross (Tc), Triangle (T), Diamond (D), and Gyroid (G)—were fabricated using fused filament fabrication (FFF) 3D printing. hADSCs were cultured on these scaffolds, and their response was evaluated utilising an alkaline phosphatase (ALP) assay, immunofluorescence, and extensive proteomic analyses. The results showed the D scaffold to have the highest ALP activity, followed by Tc. Proteomics results showed that more than 1200 proteins were identified in each scaffold with unique proteins expressed in each scaffold, respectively Tc—204, T—194, D—244, and G—216. Bioinformatics analysis revealed structures with complex curvature to have an increased expression of proteins involved in mid- to late-stage osteogenesis signalling and differentiation pathways, while the Tc scaffold induced an increased expression of signalling and differentiation pathways pertaining to angiogenesis and early osteogenesis. Full article

Wearable pressure sensors have emerged as vital tools in personalized monitoring, promising transformative advances in patient care and diagnostics. Nevertheless, conventional devices frequently suffer from limited sensitivity, inadequate flexibility, and concerns regarding biocompatibility. Herein, we introduce silk fibroin, a naturally occurring protein extracted from silkworm cocoons, as a promising material platform for next-generation wearable sensors. Owing to its remarkable biocompatibility, mechanical robustness, and structural tunability, silk fibroin serves as an ideal substrate for constructing capacitive pressure sensors tailored to medical applications. We engineered silk-derived capacitive architecture and evaluated its performance in real-time human motion and physiological signal detection. The resulting sensor exhibits a high sensitivity of 18.68 kPa⁻¹ over a broad operational range of 0 to 2.4 kPa, enabling accurate tracking of subtle pressures associated with pulse, respiration, and joint articulation. Under extreme loading conditions, our silk fibroin sensor demonstrated superior stability and accuracy compared to a commercial resistive counterpart (FlexiForce™ A401). These findings establish silk fibroin as a versatile, practical candidate for wearable pressure sensing and pave the way for advanced biocompatible devices in healthcare monitoring. Full article

This Review examines up-to-date advancements in the integration of biomolecules and solar energy technologies, with a particular focus on biohybrid photovoltaic systems. Biomolecules have recently garnered increasing interest as functional components in a wide range of solar cell architectures, since they offer a huge variety of structural, optical, and electronic properties, useful to fulfill multiple roles within photovoltaic devices. These roles span from acting as light-harvesting sensitizers and charge transport mediators to serving as micro- and nanoscale structural scaffolds, rheological modifiers, and interfacial stabilizers. In this Review, a comprehensive overview of the state of the art about the integration of biomolecules across the various generations of photovoltaics is provided. The functional roles of pigments, DNA, proteins, and polysaccharides are critically reported improvements and limits associated with the use of biological molecules in optoelectronics. The molecular mechanisms underlying the interaction between biomolecules and semiconductors are also discussed as essential for a functional integration of biomolecules in solar cells. Finally, this Review shows the current state of the art, and the most significant results achieved in the use of biomolecules in solar cells, with the main scope of outlining some guidelines for future further developments in the field of biohybrid photovoltaics. Full article

Fungal lytic polysaccharide monooxygenases (LPMOs) have revolutionized the field of biomass degradation by introducing an oxidative mechanism that complements traditional hydrolytic enzymes. These copper-dependent enzymes catalyze the cleavage of glycosidic bonds in recalcitrant polysaccharides such as cellulose, hemicellulose, and chitin, through the activation of molecular oxygen (O₂) or hydrogen peroxide (H₂O₂). Their catalytic versatility is intricately modulated by structural features, including the histidine brace active site, surface-binding loops, and, in some cases, appended carbohydrate-binding modules (CBMs). The oxidation pattern, whether at the C1, C4, or both positions, is dictated by subtle variations in loop architecture, amino acid microenvironments, and substrate interactions. LPMOs are embedded in a highly synergistic fungal enzymatic system, working alongside cellulases, hemicellulases, lignin-modifying enzymes, and oxidoreductases to enable efficient lignocellulose decomposition. Industrial applications of fungal LPMOs are rapidly expanding, with key roles in second-generation biofuels, biorefineries, textile processing, food and feed industries, and the development of sustainable biomaterials. Recent advances in genome mining, protein engineering, and heterologous expression are accelerating the discovery of novel LPMOs with improved functionalities. Understanding the balance between O₂- and H₂O₂-driven mechanisms remains critical for optimizing their catalytic efficiency while mitigating oxidative inactivation. As the demand for sustainable biotechnological solutions grows, this narrative review highlights how fungal LPMOs function as indispensable biocatalysts for the future of the Circular Bioeconomy and green industrial processes. Full article

Obstructive sleep apnea (OSA) is a prevalent disorder linked to metabolic complications such as diabetes and cardiovascular disease. By fragmenting normal sleep architecture, OSA perturbs the growth hormone/insulin-like growth factor (GH/IGF) axis and alters circulating levels of IGF-binding proteins (IGFBPs). A prior clinical observation of elevated IGFBP4 in OSA patients motivated the present investigation in a controlled animal model. Building on the previously reported protocol, OSA was induced in male C57BL/6 mice (9–12 weeks old) through intralingual injection of polytetrafluoroethylene (PTFE), producing tongue hypertrophy, intermittent airway obstruction, and hypoxemia. After 8–10 weeks, the study assessed (1) hypoxia biomarkers—including HIF-1α and VEGF expression—and (2) neurobehavioral outcomes in anxiety and cognition using the open-field and novel object recognition tests. PTFE-treated mice exhibited a significant increase in circulating IGFBP4 versus both baseline and control groups. Hepatic Igfbp4 mRNA was also upregulated. Behaviorally, PTFE mice displayed heightened anxiety-like behavior and impaired novel object recognition, paralleling cognitive deficits reported in human OSA. These findings validate the PTFE-induced model as a tool for studying OSA-related hypoxia and neurocognitive dysfunction, and they underscore IGFBP4 as a promising biomarker and potential mediator of OSA’s systemic effects. Full article

Disruption of the intestinal epithelial barrier is a key driver of gut-derived inflammation in various disorders, yet strategies to preserve or restore barrier integrity remain limited. To address this, we evaluated a four-strain Bifidobacterium mixture—selected for complementary anti-inflammatory potency and industrial scalability—in lipopolysaccharide (LPS)-challenged RAW 264.7 macrophages and a Caco-2/THP-1 transwell co-culture model. Pretreatment with the probiotic blend reduced nitric oxide (NO) release in a dose-dependent manner by 25.9–48.3% and significantly down-regulated the pro-inflammatory markers in macrophages. In the co-culture system, the formulation decreased these markers, increased transepithelial electrical resistance (TEER) by up to 31% at 10⁵ colony-forming unit (CFU)/mL after 48 h, and preserved the membrane localization of tight junction (TJ) proteins. Adhesion to Caco-2 cells (≈ 6%) matched that of the benchmark probiotic Lacticaseibacillus rhamnosus GG, suggesting direct epithelial engagement. These in vitro findings demonstrate that this probiotic mixture can attenuate LPS-driven inflammation and reinforce epithelial architecture, providing a mechanistic basis for its further evaluation in animal models and clinical studies of intestinal inflammatory disorders. Full article

Artificial intelligence (AI) techniques—ranging from hybrid mechanistic–machine learning (ML) ensembles to gradient-boosted decision trees, support-vector machines, and deep neural networks—are transforming the management of seasonal influenza, respiratory syncytial virus (RSV), human immunodeficiency virus (HIV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Symptom-based triage models using eXtreme Gradient Boosting (XGBoost) and Random Forests, as well as imaging classifiers built on convolutional neural networks (CNNs), have improved diagnostic accuracy across respiratory infections. Transformer-based architectures and social media surveillance pipelines have enabled real-time monitoring of COVID-19. In HIV research, support-vector machines (SVMs), logistic regression, and deep neural network (DNN) frameworks advance viral-protein classification and drug-resistance mapping, accelerating antiviral and vaccine discovery. Despite these successes, persistent challenges remain—data heterogeneity, limited model interpretability, hallucinations in large language models (LLMs), and infrastructure gaps in low-resource settings. We recommend standardized open-access data pipelines and integration of explainable-AI methodologies to ensure safe, equitable deployment of AI-driven interventions in future viral-outbreak responses. Full article

Prognostic markers such as overall survival (OS) and tertiary lymphoid structure (TLS) ratios, alongside diagnostic signatures like primary cancer-type classification, provide critical information for treatment selection, risk stratification, and longitudinal care planning across the oncology continuum. However, extracting these signals solely from sparse, high-dimensional multi-omics data remains a major challenge due to heterogeneity and frequent missingness in patient profiles. To address this challenge, we present SeNMo, a self-normalizing deep neural network trained on five heterogeneous omics layers—gene expression, DNA methylation, miRNA abundance, somatic mutations, and protein expression—along with the clinical variables, that learns a unified representation robust to missing modalities. Trained on more than 10,000 patient profiles across 32 tumor types from The Cancer Genome Atlas (TCGA), SeNMo provides a baseline that can be readily fine-tuned for diverse downstream tasks. On a held-out TCGA test set, the model achieved a concordance index of 0.758 for OS prediction, while external evaluation yielded 0.73 on the CPTAC lung squamous cell carcinoma cohort and 0.66 on an independent 108-patient Moffitt Cancer Center cohort. Furthermore, on Moffitt’s cohort, baseline SeNMo fine-tuned for TLS ratio prediction aligned with expert annotations (p < 0.05) and sharply separated high- versus low-TLS groups, reflecting distinct survival outcomes. Without altering the backbone, a single linear head classified primary cancer type with 99.8% accuracy across the 33 classes. By unifying diagnostic and prognostic predictions in a modality-robust architecture, SeNMo demonstrated strong performance across multiple clinically relevant tasks, including survival estimation, cancer classification, and TLS ratio prediction, highlighting its translational potential for multi-omics oncology applications. Full article

Alzheimer’s disease (AD) and ischemic stroke (IS) are prevalent neurological disorders that frequently co-occur in the same individuals. Recent studies have demonstrated that AD and IS share several common risk factors and pathogenic elements, including an overlapping genomic architecture. However, the relationship between IS risk gene polymorphisms and AD has been less extensively studied. We aimed at determining whether IS risk gene polymorphisms were associated with the risk of AD and the severity of AD in AD patients. We utilized data of AD patients and normal controls (NCs) sourced from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort. IS risk single nucleotide polymorphisms (SNPs) were identified through the most recent and largest IS genome-wide association study (GWAS) meta-analysis. Subsequently, we conducted SNP-based association analysis of IS-risk SNPs with the risk of AD, along with amyloid, tau, and neuroimaging for AD. The generalized multifactor dimensionality reduction (GMDR) model was used to assess the interactions among IS-risk SNPs and apolipoprotein E (ApoE) ε4. Protein–protein interactions (PPIs) of the IS-risk genes product and APOE were explored using the STRING database. Seven IS-risk SNPs were involved in the study. Five SNPs were found to be associated with at least one measurement of cerebrospinal fluid (CSF) levels of amyloid-beta 1–42 (Aβ₄₂), total tau (t-tau), and phosphorylated tau 181 (p-tau₁₈₁), as well as the volumes of the hippocampus, whole brain, entorhinal cortex, and mid-temporal regions. After multiple testing corrections, we found that T allele of rs1487504 contributed to an increased risk of AD in non-ApoE ε4 carriers. The combination of rs1487504 and ApoE ε4 emerged as the optimal two-factor model, and its interaction was significantly related to the risk of AD. Additionally, C allele of rs880315 was significantly associated with elevated levels of CSF Aβ₄₂ in AD patients, and A allele of rs10774625 was significantly related to a reduction in the volume of the entorhinal cortex in AD patients. This study found that IS risk SNPs were associated with both the risk of AD and AD major indicators in the ADNI cohort. These findings elucidated the role of IS in AD from a genetic perspective and provided an innovative approach to predict AD through IS-risk SNPs. Full article

Background/Objectives: Scutiger ningshanensis (Fang, 1985) is an endemic Chinese amphibian species within the genus Scutiger (Megophryidae). Despite its ecological significance, its mitochondrial genome architecture and evolutionary relationships remain poorly understood. Given the high structural variability in Megophryidae mitogenomes and unresolved phylogenetic patterns in Scutiger, this study aims to (1) characterize the complete mitogenome of S. ningshanensis, (2) analyze its molecular evolution, and (3) clarify its phylogenetic position and divergence history within Megophryidae. Methods: The complete mitochondrial genome was sequenced and annotated, followed by analyses of nucleotide composition, codon usage bias, and selection pressures (Ka/Ks ratios). Secondary structures of rRNAs and tRNAs were predicted, and phylogenetic relationships were reconstructed using maximum likelihood and Bayesian methods. Divergence times were estimated using molecular clock analysis. Results: The mitogenome of S. ningshanensis is 17,282 bp long, encoding 13 protein-coding genes (PCGs), 22 tRNAs, 2 rRNAs, and a control region, with a notable AT bias (61.05%) with nucleotide compositions of T (32.51%), C (24.64%), G (14.3%), and A (28.54%). All tRNAs exhibited cloverleaf structures except trnS1, which lacked a DHU stem. Phylogenetic analysis confirmed the monophyly of Scutiger, forming a sister clade to Oreolalax and Leptobrachium, and that S. ningshanensis and S. liubanensis are sister species with a close evolutionary relationship. Positive selection was detected in Atp8 (Ka/Ks > 1), suggesting adaptation to plateau environments, while other PCGs underwent purifying selection (Ka/Ks < 1). Divergence time estimation placed the origin of Megophryidae at~47.97 MYA (Eocene), with S. ningshanensis diverging~32.67 MYA (Oligocene). Conclusions: This study provides the first comprehensive mitogenomic characterization of S. ningshanensis, revealing its evolutionary adaptations and phylogenetic placement. The findings enhance our understanding of Megophryidae’s diversification and offer a genomic foundation for future taxonomic and conservation studies. Full article

The rapid evolution of SARS-CoV-2 has underscored the need for a detailed understanding of antibody binding mechanisms to combat immune evasion by emerging variants. In this study, we investigated the interactions between Class I neutralizing antibodies—BD55-1205, BD-604, OMI-42, P5S-1H1, and P5S-2B10—and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein using multiscale modeling, which combined molecular simulations with the ensemble-based mutational scanning of the binding interfaces and binding free energy computations. A central theme emerging from this work is that the unique binding strength and resilience to immune escape of the BD55-1205 antibody are determined by leveraging a broad epitope footprint and distributed hotspot architecture, additionally supported by backbone-mediated specific interactions, which are less sensitive to amino acid substitutions and together enable exceptional tolerance to mutational escape. In contrast, BD-604 and OMI-42 exhibit localized binding modes with strong dependence on side-chain interactions, rendering them particularly vulnerable to escape mutations at K417N, L455M, F456L and A475V. Similarly, P5S-1H1 and P5S-2B10 display intermediate behavior—effective in some contexts but increasingly susceptible to antigenic drift due to narrower epitope coverage and concentrated hotspots. Our computational predictions show strong agreement with experimental deep mutational scanning data, validating the accuracy of the models and reinforcing the value of binding hotspot mapping in predicting antibody vulnerability. This work highlights that neutralization breadth and durability are not solely dictated by epitope location, but also by how binding energy is distributed across the interface. The results provide atomistic insight into mechanisms driving resilience to immune escape for broadly neutralizing antibodies targeting the ACE2 binding interface—which stems from cumulative effects of structural diversity in binding contacts, redundancy in interaction patterns and reduced vulnerability to mutation-prone positions. Full article

The germin-like protein (GLP) family plays vital roles for plant growth, stress adaptation, and defense; however, its evolutionary dynamics and functional diversity in halophytes remain poorly characterized. Here, we present the genome-wide analysis of the GLP family in the halophytic forage alkaligrass (Puccinellia tenuiflora), which identified 54 PutGLPs with a significant expansion compared to other plant species. Phylogenetic analysis revealed monocot-specific clustering, with 41.5% of PutGLPs densely localized to chromosome 7, suggesting tandem duplication as a key driver of family expansion. Collinearity analysis confirmed evolutionary conservation with monocot GLPs. Integrated gene structure and motif analysis revealed conserved cupin domains (BoxB and BoxC). Promoter cis-acting elements analysis revealed stress-responsive architectures dominated by ABRE, STRE, and G-box motifs. Tissue-/organ-specific expression profiling identified root- and flower-enriched PutGLPs, implying specialized roles in stress adaptation. Dynamic expression patterns under salt-dominated stresses revealed distinct regulatory pathways governing ionic and alkaline stress responses. Functional characterization of PutGLP37 demonstrated its cell wall localization, dual superoxide dismutase (SOD) and oxalate oxidase (OXO) enzymatic activities, and salt stress tolerance in Escherichia coli, yeast (Saccharomyces cerevisiae INVSc1), and transgenic Arabidopsis. This study provides critical insights into the evolutionary innovation and stress adaptive roles of GLPs in halophytes. Full article

Background/Objectives: Medulloblastoma (MB) is the second leading cause of cancer-related death in children. Its tumor microenvironment (TME) includes endothelial, glial, and immune cells that influence tumor architecture and progression. Neuropilin-1 (NRP1), a co-receptor for semaphorins and vascular endothelial growth factor (VEGF), is expressed in various cell types during oncogenesis, yet its role in MB progression remains unclear. This study aimed to evaluate the expression and localization of NRP1 and glial fibrillary acidic protein (GFAP) in MB tissue. Methods: We analyzed MB tissue samples using immunohistochemistry, immunofluorescence, and quantitative PCR. Samples were stratified by molecular subgroup (WNT, SHH, non-WNT/non-SHH). We assessed NRP1 expression in tumor-associated microglia/macrophages (TAMs) and endothelial cells, as well as GFAP expression in astrocytes and tumor cells. Histopathological correlations and survival analyses were also conducted. Results: NRP1 was consistently expressed by TAMs across all MB molecular subgroups. Tumor vasculature showed strong endothelial NRP1 expression, while perivascular astrocytic coverage was frequently absent. Astrocytic processes exhibited spatial differences according to tumor histology. In SHH-MBs, a subset of tumor cells showed aberrant GFAP expression, which correlated with tumor recurrence or progression. Conclusions: NRP1 and GFAP display distinct expression patterns within the MB microenvironment, reflecting subgroup-specific biological behavior. Endothelial NRP1 positivity combined with limited vascular-astrocytic interaction and aberrant GFAP expression in SHH-MB may contribute to dysregulated angiogenesis and tumor progression. These findings warrant further investigation to explore their prognostic and therapeutic implications. Full article

Inflammatory bowel disease (IBD) is a chronic gastrointestinal disorder associated with gut microbiota dysbiosis and impaired intestinal barrier function. Probiotic interventions have shown potential in alleviating intestinal inflammation and restoring microbial balance. This study explores the protective effects of Lacticaseibacillus paracasei (L. paracasei) E10 in mice. L. paracasei E10 demonstrated strong gastrointestinal transit tolerance, high mucosal adhesion, and probiotic properties such as hydrophobicity and aggregation ability (p < 0.05). The oral administration of L. paracasei E10 significantly alleviated colitis symptoms by reducing the disease activity index, preserving colonic architecture, increasing goblet cell density, and upregulating tight junction proteins, thereby enhancing intestinal barrier integrity. 16S rRNA sequencing revealed that L. paracasei E10 supplementation enriched microbial diversity, increased the abundance of Muribaculaceae, and modulated the Firmicutes/Bacteroidetes ratio, contributing to gut homeostasis. These findings indicate that L. paracasei E10 is a potential candidate for IBD management. Full article

The cryopreservation of three-dimensional (3D) biofabricated constructs is a key enabler for their clinical application in regenerative medicine. Unlike two-dimensional (2D) cultures, 3D systems such as encapsulated cell spheroids, molded hydrogels, and bioprinted tissues present specific challenges related to cryoprotectant (CPA) diffusion, thermal gradients, and ice formation during freezing and thawing. This review examines the current strategies for preserving 3D constructs, focusing on the role of biomaterials as cryoprotective matrices. Natural polymers (e.g., hyaluronic acid, alginate, chitosan), protein-based scaffolds (e.g., silk fibroin, sericin), and synthetic polymers (e.g., polyethylene glycol (PEG), polyvinyl alcohol (PVA)) are evaluated for their ability to support cell viability, structural integrity, and CPA transport. Special attention is given to cryoprotectant systems that are free of dimethyl sulfoxide (DMSO), and to the influence of hydrogel architecture on freezing outcomes. We have compared the efficacy and limitations of slow freezing and vitrification protocols and review innovative approaches such as temperature-controlled cryoprinting, nano-warming, and hybrid scaffolds with improved cryocompatibility. Additionally, we address the regulatory and manufacturing challenges associated with developing Good Manufacturing Practice (GMP)-compliant cryopreservation workflows. Overall, this review provides an integrated perspective on material-based strategies for 3D cryopreservation and identifies future directions to enable the long-term storage and clinical translation of engineered tissues. Full article