Search Results (2,208)

Objectives: Alzheimer’s disease (AD) remains one of the most prevalent neurodegenerative conditions among older adults, underscoring the urgent need for accurate and ethically grounded early detection methods. Artificial intelligence (AI) techniques, particularly machine learning and deep learning models, show promise in leveraging neuroimaging biomarkers to support early diagnosis. However, significant challenges persist regarding model explainability, accountability, and responsible implementation in real-world healthcare settings. This study presents a generalized Responsible AI (RAI) framework composed of four core components—explainability, fairness, predictive performance, and uncertainty quantification—to address these challenges. Method: Using the TADPOLE neuroimaging dataset, we implemented a Feedforward Neural Network (FNN) within a unified Responsible AI (RAI) framework integrating explainability, fairness, predictive performance, and uncertainty quantification. Although Random Forest achieved slightly higher predictive accuracy (95%), the FNN was selected as the primary model because it better supports end-to-end uncertainty estimation through Monte Carlo Dropout, enabling more reliable clinical decision support. Results: The proposed framework demonstrated strong predictive performance (92% accuracy), improved fairness reflected by an equalized odds difference of 0.124, and progressively lower predictive entropy across training iterations, indicating enhanced confidence in predictions. The framework further enabled model transparency through explainability analyses and supported the identification of low-confidence predictions for potential clinical review. Conclusions: Our findings highlight not only the feasibility of integrating RAI principles into AD prediction pipelines but also the persistent challenges of applying such frameworks to real-world clinical data. This work contributes practical insights toward operationalizing Responsible AI in healthcare contexts. Full article

Acute ischemic stroke is one of the leading causes of mortality and disability globally, characterized by a complex and temporally structured cascade of cellular and molecular events. Although reperfusion therapies have improved outcomes, their narrow therapeutic window and limited availability leave many patients without effective treatment, highlighting the need for effective neuroprotective strategies capable of targeting multiple interconnected pathways. Melatonin has been proposed as a potential adjunctive neuroprotective agent based on its pleiotropic properties, modulating cellular signaling networks including antioxidant, anti-inflammatory, mitochondrial stabilizing, and BBB-preserving effects. Melatonin regulates key signaling pathways, thereby coordinating cellular responses to injury in multiple stages of ischemic pathophysiology, positioning it as a potential adjunctive therapy. Preclinical studies consistently demonstrate reductions in infarct volume, preservation of neuronal architecture, and improvements in neurological outcomes. However, clinical evidence remains limited to a small number of clinical trials, which suggest safety and possible early neurological benefit but are underpowered to determine long-term efficacy. Importantly, translational gaps persist regarding optimal dosing, duration of administration, and alignment with the temporal dynamics of post-ischemic injury. This review integrates current knowledge on the cellular and molecular mechanisms underlying the potential neuroprotective actions and its role as a pleiotropic modulator of ischemic injury. Full article

Metastasis remains a major cause of cancer mortality, making reliable primary–metastatic state prediction from somatic genomic alterations clinically important yet technically difficult. We present TF-GateNet, a biologically constrained neural network that combines TF-aware feature integration based on TRRUST and DoRothEA TF–gene regulatory priors with sample-specific dynamic gating on a Reactome-defined hierarchical sparse backbone. The model was evaluated on multi-center prostate and breast-cancer cohorts using mutation and copy-number features across 10 repeated runs on a fixed 80/10/10 split, together with independent prostate external validation, and was compared with biologically informed neural-network baselines (P-NET, BKGNet-Pathway, and BKGNet-Protein), a dense feed-forward neural network (FNN), and conventional machine-learning baselines (LR, SVM, RF, DT, and XGBoost). On prostate, TF-GateNet achieved the best internal performance (AUROC 0.954 ± 0.005; AUPRC 0.925 ± 0.007) and the best combined external performance (AUROC 0.952 ± 0.009; AUPRC 0.898 ± 0.018). On breast, TF-GateNet achieved the strongest internal ranking performance, reaching AUROC 0.893 ± 0.004 and AUPRC 0.835 ± 0.006. Ablation analysis indicated that TF-aware integration accounted for the larger prostate gain, whereas within the TF-GateNet family on breast, both TF-aware integration and dynamic gating contributed positively. Interpretability analysis further supported a cross-level route from TF-related genomic perturbation cues to genes, pathways, and phenotype-associated predictions. These results position TF-GateNet as a biologically grounded and interpretable framework for primary–metastatic state prediction, with the strongest overall evidence in prostate cancer and favorable internal evidence in breast cancer. Full article

Background/Objective: The increasing global population of older adults presents significant challenges for oral healthcare, particularly regarding the management of chronic conditions and prosthetic rehabilitation. Teledentistry, combined with intraoral scanning, offers a promising solution to enhance access, interdisciplinary collaboration, and clinical outcomes in geriatric populations. This study aimed to evaluate the utilisation of intraoral digital scanning within teledentistry for interdisciplinary oral assessment of older patients. Specifically, it investigated current clinical practices, collaboration among healthcare professionals, and perceptions regarding the effectiveness, challenges, and future potential of teledentistry in prosthodontic care. Methods: An analytical cross-sectional survey was conducted among 84 healthcare professionals, including dentists, prosthodontists, and postgraduate students, recruited via an international network. Participants completed a 40-item electronic questionnaire covering demographics, clinical practice, digital technology use, interdisciplinary collaboration, and attitudes toward research and innovation. Descriptive statistics summarised responses, and inferential analyses, including chi-square tests and Spearman correlations, examined associations between career stage, technology adoption, and interdisciplinary practices. Results: Early-career professionals demonstrated the highest adoption of intraoral scanning (76.3%), while mid-career adoption was lowest (28.6%). Sustained usage significantly increased after one year of adoption (93.8%). While 91.7% of respondents valued interdisciplinary care, active collaboration remained limited. Cost, technical barriers, and training gaps were identified as primary obstacles. Professionals perceived intraoral scanning as beneficial for prosthodontic outcomes and chronic inflammation management, though adoption was influenced by experience, systemic factors, and financial support. Conclusions: Teledentistry integrated with intraoral scanning has substantial potential to improve geriatric oral healthcare. Successful implementation depends on structured training, financial investment, and promotion of interdisciplinary collaboration. Future longitudinal and multicenter studies are warranted to evaluate clinical, economic, and patient-centred outcomes, supporting sustainable digital transformation in geriatric dental care. Full article

Medical image registration integrates information from different types of medical images to support and improve clinical diagnosis. Existing image registration approaches are mainly classified into two categories: model-driven methods and data driven methods. Model-driven methods can achieve high registration accuracy but suffer from low computational efficiency and long processing time. In contrast, data-driven methods stand out for their high efficiency, which gives them great practical value. Taking this advantage as the core basis, this paper proposes a simple unsupervised deep learning framework embedded with a multi-scale strategy. The overall network consists of two core modules: an Affine Transformation Network (AT-Net) and a multi-scale Deformable Transformation Network (DT-Net). The multi-scale design adopted in the DT-Net enables image registration at different feature scales, which effectively improves the overall registration accuracy. In addition, a dual consistency constraint is introduced into the framework to further enhance the model robustness. The entire network realizes end-to-end medical image registration. We verified the performance of the proposed method on a public dataset, with mutual information (MI) adopted as the evaluation metric. The experimental results show that our registration algorithm outperforms several mainstream methods, including Symmetric Image Normalization (SyN), VoxelMorph (VM), the coarse-to-fine deformable transformation framework for unsupervised multi-contrast MR image registration with dual consistency constraint (C-F-I-R), TransMorph and DiffuseMorph. The comparative experiments fully demonstrate that combining the multi-scale strategy with deep learning techniques is an effective solution for medical image registration tasks. Full article

Immune checkpoint inhibitors targeting the PD-1 (Programmed Cell Death Protein 1)/PD-L1 (Programmed Death-Ligand 1) axis have transformed cancer therapeutics, yet their efficacy in gynecologic malignancies particularly high-grade serous ovarian carcinoma remains disappointingly limited. This therapeutic resistance stems from a highly orchestrated, multidimensional immunosuppressive tumor microenvironment (TME) characterized by the convergent actions of regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and an inhibitory cytokine network (IL-10, TGF-β, VEGF). Emerging evidence positions TIGIT (T-cell immunoreceptor with immunoglobulin and ITIM domain) as a master checkpoint integrator that coordinately regulates CD8+ T-cell exhaustion, NK-cell dysfunction, and Treg-mediated suppression. Dual blockade of PD-1 and TIGIT represents a mechanistically rational strategy to dismantle this immunosuppressive fortress. This review synthesizes current understanding of the gynecologic TME architecture, delineates the molecular and cellular basis for TIGIT/PD-1 synergy, critically evaluates ongoing clinical translation efforts, and proposes an integrative framework leveraging spatial transcriptomics, single-cell resolution immunoprofiling, and patient-derived experimental models to accelerate biomarker-driven therapeutic development. Full article

Cancer progression is closely associated with dysregulation of apoptosis, enabling malignant cells to evade programmed cell death and develop resistance to therapy. Among the key regulators of this process, the tumor suppressor protein p53 and the Bcl-2 family of proteins play central and interconnected roles in controlling cell survival and mitochondrial integrity. In recent years, naturally occurring flavonoids have attracted considerable attention as potential modulators of these pathways due to their diverse biological activities and relatively low toxicity. This review provides a focused and integrative overview of how different subclasses of flavonoids modulate the p53–Bcl-2 signaling axis to regulate apoptosis in cancer cells. Particular emphasis is placed on the mechanistic interplay between p53 stabilization, transcriptional regulation of apoptotic targets, mitochondrial outer membrane permeabilization, and caspase activation. In contrast to previous general reviews on flavonoids and cancer, this work provides an integrated overview of evidence across multiple flavonoid subclasses and experimental cancer models, highlighting both shared and pathway-specific apoptotic responses. Experimental findings from in vitro and in vivo studies are discussed, including the effects of quercetin, kaempferol, myricetin, epigallocatechin gallate, and related compounds on cell-cycle arrest, oxidative stress, mitochondrial dysfunction, and intrinsic apoptotic signaling. Furthermore, the review examines the relationship between flavonoid chemical structure and biological activity, with particular attention to bioavailability, metabolic transformation, and strategies aimed at improving therapeutic efficacy, including structural modification and nanocarrier-based delivery systems. Despite promising preclinical findings, significant translational challenges remain, including poor pharmacokinetic properties, variability among experimental models, and limited clinical validation. Overall, flavonoids represent a promising class of bioactive compounds capable of targeting apoptosis through modulation of the p53–Bcl-2 network, and a deeper mechanistic understanding of their activity may support the development of novel targeted and combination anticancer therapies. Full article

Basonuclin 2 (BNC2) is a highly conserved cysteine–histidine (C2H2)-type zinc-finger nuclear regulatory protein characterized by three pairs of zinc-finger domains, a putative nuclear localization signal, a serine-rich region, broad tissue distribution, and remarkable transcript diversity generated through alternative promoter usage, alternative splicing, and polyadenylation. Increasing evidence from human genetics, animal models, functional genomics, and transcriptomic studies indicates that BNC2 links nuclear regulatory mechanisms to tissue-specific developmental and disease phenotypes. In the nervous system, BNC2-positive neuronal populations and BNC2-derived circular RNAs have been implicated in energy-balance circuits and neuroinflammatory regulation. In the skeletal system, BNC2 contributes to osteochondral development, periosteal stem-cell activation, chromatin remodeling, fracture repair, and genetic susceptibility to adolescent idiopathic scoliosis. BNC2 variants have also been associated with congenital lower urinary tract obstruction, whereas its expression and regulatory landscape are closely related to germ-cell development, epithelial ovarian cancer susceptibility, pigmentation traits, fibrosis, and several tumor contexts. Mechanistically, BNC2-associated phenotypes appear to involve cysteine–histidine zinc-finger-mediated transcriptional regulation, non-coding enhancer activity, epigenetic alterations, RNA-processing-associated nuclear functions, and chromatin-remodeling-dependent control of cell proliferation, differentiation, and stromal activation. This review integrates current evidence on the molecular architecture and regulatory functions of BNC2, critically discusses its context-dependent roles across development and disease, and highlights unresolved questions regarding isoform-specific activity, cell-type-specific regulation, downstream target networks, and clinical translation. A clearer understanding of these mechanisms may support the future evaluation of BNC2 as a biomarker, genetic susceptibility locus, molecular stratification factor, and potential therapeutic regulatory node. Full article

Cancer is still one of the world’s major causes of morbidity and mortality; thus, safer and more efficient treatment approaches are required. The structural variety, multitargeted mechanisms, and generally good safety profiles of plant-derived polyphenols have made them attractive anticancer medicines. Flavonoids (like quercetin), stilbenes (like resveratrol), phenolic acids and curcuminoids (like curcumin) are major classes that have shown strong anticancer action against a variety of cancers, including prostate, colorectal and breast cancers. Through targets including PI3K/Akt, MAPK, NF-κB, and p53 signaling networks, these substances influence important molecular pathways involved in tumor initiation and development, including oxidative stress, inflammation, apoptosis, cell cycle control, angiogenesis and metastasis. The clinical translation of polyphenols is still constrained by poor bioavailability, fast metabolism, low aqueous solubility and inefficient pharmacokinetic characteristics, which lead to insufficient systemic exposure and therapeutic efficacy despite strong preclinical data. Their therapeutic applicability is further complicated by variations in absorption and possible dose-related restrictions. To overcome these limitations, the anticancer efficacy of polyphenols has been enhanced via delivery technologies like polymeric nanoparticles, lipid-based carriers, nanoemulsions and phytosome complexes, which have shown improved stability, increased bioavailability and targeted delivery to tumor tissues. This review provides a comprehensive and integrative analysis of plant-derived polyphenols by linking molecular mechanisms, pharmacokinetic limitations and emerging delivery strategies within a translational framework. By bridging these interconnected domains, this review highlights the potential of polyphenols as viable candidates in next-generation cancer therapeutics and underscores the need for well-designed clinical studies to facilitate their successful integration into oncology practice. Full article

Background/Objectives: Insomnia is one of the most prevalent and persistent symptoms among patients with breast cancer, yet it remains under-recognized and undertreated in routine clinical practice. Beyond its impact on sleep quality, insomnia is increasingly understood as a multidimensional condition involving neurobiological, psychological, and behavioral mechanisms, closely intertwined with cancer-related stress and psychiatric comorbidities. This narrative review aims to provide a comprehensive and integrative overview of insomnia in breast cancer, focusing on its epidemiology, pathophysiological underpinnings, neuropsychiatric correlates, and clinical implications, while highlighting gaps in current research and management. Methods: A narrative review of the literature was conducted, including studies published in major medical databases (PubMed, Scopus, and Web of Science) up to 2025. Relevant articles addressing insomnia, sleep disturbances, psychiatric symptoms, and neurobiological mechanisms in breast cancer populations were selected and synthesized. Results: Insomnia affects a substantial proportion of breast cancer patients across the disease trajectory, from diagnosis to survivorship. Its etiology is multifactorial, involving dysregulation of the hypothalamic–pituitary–adrenal axis, inflammatory processes, and circadian rhythm, as well as treatment-related factors such as chemotherapy, endocrine therapy, and menopausal symptoms. Insomnia frequently co-occurs with depression, anxiety, fatigue, and pain, forming symptom clusters that significantly impair quality of life and may influence clinical outcomes. Emerging evidence supports a bidirectional relationship between insomnia and psychiatric vulnerability, suggesting a shared neurobiological substrate within the brain–body stress axis. Conclusions: Insomnia in breast cancer should be conceptualized as a neuropsychiatric condition embedded within a broader stress-related symptom network rather than as an isolated sleep disturbance. Improved screening, interdisciplinary management, and the integration of evidence-based interventions such as cognitive behavioral therapy for insomnia are essential. Research should focus on personalized and mechanistically informed approaches to better address this highly prevalent yet insufficiently managed condition. Full article

Cutaneous tissue engineering has advanced from simple coverage substitutes to increasingly complex living constructs, yet the field remains constrained by a decisive problem: timely and durable perfusion. Many engineered skin substitutes can appear vascular in static culture or in small-animal models. However, they still fail when blood flow must be established quickly enough to rescue cells across clinically relevant tissue thickness. Rather than re-catalog platforms already summarized in recent reviews, this critical narrative review reframes the field around perfusion as the master functional endpoint rather than vessel density alone. We analyze the vascularization bottleneck as a sequence, internal network formation, host inosculation, flow initiation, and perfusion stability—and use that sequence to reassess biomaterial design, cell-based strategies, immunomodulation, decellularized matrices, bioprinting, microfluidics, and prevascularization. We intentionally distinguish implantable skin substitutes from perfused in vitro platforms such as skin-on-chip systems, arguing that these are linked but non-interchangeable application spaces with different success criteria. Building on this distinction, we propose a research agenda centered on functional benchmarking of perfusion, spatiotemporal coordination of scaffold dynamics, immune–mural–lymphatic–vascular crosstalk, scalable hierarchical vascular fabrication, and predictive human test platforms. The central argument is that translation will depend not on ever more isolated pro-angiogenic interventions but on integrated systems that survive the ischemic interval, connect rapidly, tolerate blood entry, maintain a workable inflow–outflow balance, and remodel into a stable, skin-specific microvasculature. Full article

Colorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality, with substantial heterogeneity that is not fully explained by genetic alterations alone. Emerging evidence positions metabolic reprogramming as a central driver of tumor behavior, integrating glycolysis, mitochondrial function, lipid and amino acid metabolism, and autophagy into coordinated networks that extend beyond cancer cells to the tumor microenvironment. Tumor–immune metabolic competition and metabolite-mediated signaling shape immune responses, often promoting immunosuppression and resistance to immunotherapy, particularly in microsatellite-stable (MSS) CRC. Systemic factors, including obesity, insulin resistance, and the diet–microbiota axis, further modulate tumor metabolism and immune function, reinforcing disease progression. Metabolic biomarkers reflecting these multi-level interactions, spanning tumor-intrinsic pathways, immune contexture, and host metabolism, offer promising opportunities for improved patient stratification and therapeutic targeting, although clinical validation remains limited. Current treatments, including chemotherapy, targeted agents, and immune checkpoint inhibitors, are effective in selected subgroups but are constrained by resistance mechanisms. In this review, we propose an integrative immunometabolic framework in which tumor, immune, and systemic metabolic processes co-evolve, defining CRC progression and treatment response. Targeting this interconnected network through combinatorial and metabolism-oriented strategies may enable precision therapies, particularly for immunotherapy-resistant MSS CRC. Full article

Macrophages are highly plastic innate immune cells that adopt context-dependent phenotypes along a continuum, integrating developmental origin with local microenvironmental cues rather than conforming to discrete M1/M2 states. This review delineates the molecular circuits shaping macrophage identity—TLR/cytokine signaling, microRNA networks, metabolic rewiring, and epigenetic mechanisms including histone lactylation—and traces how circulating monocyte subsets contribute to tissue macrophage diversity. We examine macrophage plasticity across a broad disease spectrum—oncology, autoimmune and rheumatic diseases, inflammatory bowel disease, infectious diseases, metabolic disorders, and neurological conditions—showing that the pathogenic phenotype is strikingly context-dependent: for instance, M2-like tumor-associated macrophages promote immune evasion in solid tumors, whereas M1-skewed programs drive tissue damage in autoimmunity. Soluble markers (sCD163, sCD14, soluble mannose receptor) are emerging biomarkers of disease activity and prognosis. High-dimensional flow cytometry and mass cytometry (CyTOF) bridge molecular biology and clinical phenotyping, enabling integrated readouts of surface phenotype, intracellular signaling, and metabolic state. Therapeutic strategies discussed include selective tumor-associated macrophage (TAM) reprogramming, chimeric antigen receptor (CAR)-M cell therapies, and biomaterial-based platforms. Future priorities encompass spatially resolved multi-omics, epigenetic and metabolic targeting, and macrophage-centered vaccine approaches. Standardized cytometry panels will be essential for biomarker-guided stratification and context-specific interventions. Full article

Obesity is a major risk factor for colorectal cancer (CRC) and is increasingly recognized as a contributor to cancer-related cognitive impairment; however, the mechanistic pathways linking metabolic dysfunction, tumor progression, and brain dysfunction remain incompletely defined. Emerging evidence indicates that obesity-induced gut microbial dysbiosis and intestinal barrier disruption may serve as a biologically plausible mechanism connecting these processes via the gut–brain axis although direct clinical causality remains to be firmly established. In obesity, alterations in gut microbiota composition characterized by depletion of barrier-protective taxa and enrichment of pro-inflammatory and genotoxic pathobionts compromise epithelial tight-junction integrity and promote metabolic endotoxemia. The translocation of microbial products, including lipopolysaccharide, sustains chronic systemic inflammation, accelerates CRC progression, and remodels the tumor microenvironment. Notably, these peripheral inflammatory signals extend beyond the intestine and tumor, disrupting blood–brain barrier integrity, activating microglia and astrocytes, and impairing synaptic plasticity within hippocampal and frontal networks. Clinically, these processes manifest as cancer-related cognitive impairment (CRCI), with predominant deficits in attention, processing speed, and working memory, which are often detectable around the time of diagnosis and independent of chemotherapy exposure. This review synthesizes in vivo, in vitro, and human evidence into a proposed theoretical “two-barrier failure” model of obesity-associated CRC and cognitive dysfunction. In addition to mechanistic synthesis, we discuss barrier-centered therapeutic strategies, including targeted probiotics, postbiotics, SCFA supplementation, obesity management through dietary and weight-loss interventions, and potential pharmacological approaches to epithelial and neurovascular barrier protection. We also outline testable clinical trial designs for evaluating these interventions in obesity-associated CRC. Full article

Chronic kidney disease (CKD) affects approximately 700 million people worldwide and is a major contributor to end-stage renal disease (ESRD), cardiovascular morbidity, and premature mortality. Although oxidative stress has long been considered central to CKD progression, conventional antioxidant strategies have not consistently improved clinical outcomes, suggesting that excess reactive oxygen species (ROS) alone cannot fully account for the underlying disease pathophysiology. Emerging evidence supports a broader paradigm of redox network failure, characterized by the disruption of coordinated signaling among ROS, nitric oxide (NO), and reactive sulfur species (RSS). Within this framework, hydrogen sulfide (H₂S), a major endogenous RSS, functions as a key regulator of renal redox homeostasis. CKD is consistently associated with systemic and renal H₂S deficiency, accompanied by downregulation of cystathionine β-synthase (CBS), cystathionine γ-lyase (CSE), and 3-mercaptopyruvate sulfurtransferase (3-MST), as well as impaired transsulfuration and disrupted mitochondrial sulfide oxidation. Importantly, this deficiency cannot be explained solely by reduced renal function but instead reflects active suppression of H₂S biosynthesis. Uremic toxins, particularly indoxyl sulfate (IS), contribute to this process through activation of the aryl hydrocarbon receptor (AhR), which inhibits specificity protein 1 (Sp1)-dependent transcription of H₂S-producing enzymes. This IS–AhR–Sp1 axis provides a mechanistic link between toxin accumulation and disruption of the sulfur arm of the redox network, amplifying oxidative stress, endothelial dysfunction, mitochondrial impairment, ferroptotic vulnerability, and fibrotic remodeling. Beyond H₂S itself, downstream RSS, including persulfides, polysulfides, and thiosulfate, may represent the principal bioactive mediators of sulfur-dependent redox signaling, and their coordinated depletion in CKD may impair redox buffering capacity beyond what H₂S measurement alone reflects. This review integrates current evidence to propose a conceptual model in which CKD progression involves failure of coordinated redox signaling—characterized by feed-forward network collapse and threshold-dependent transition to a self-sustaining high-ROS state—with H₂S deficiency representing one mechanistically supported component of this broader network disruption. This framework highlights the therapeutic potential of targeting redox network restoration rather than isolated oxidative pathways in CKD. Full article