Search Results (4,835)

Chrysanthemum has a long history of medicinal use with rich germplasm resources and extensive cultivation. Traditional chrysanthemum cultivation involves complex patterns and long flowering periods, with the ongoing expansion of planting areas complicating statistical surveys. Currently, reliable, timely, and universally applicable standardized monitoring methods for chrysanthemum cultivation areas remain underdeveloped. This research employed 16 m resolution satellite imagery spanning 2021 to 2023 alongside 2 m resolution data acquired in 2022 to quantify chrysanthemum cultivation extent across Sheyang County, Jiangsu Province, China. After evaluating multiple classifiers, Maximum Likelihood Classification was selected as the optimal method. Subsequently, time-series-based post-classification processing was implemented: initial cultivation information extraction was performed through feature comparison, supervised classification, and temporal analysis. Accuracy validation via Overall Accuracy, Kappa coefficient, Producer’s Accuracy, and User’s Accuracy identified critical issues, followed by targeted refinement of spectrally confused features to obtain precise area estimates. The chrysanthemum cultivation area in 2022 was quantified as 46,950,343 m² for 2 m resolution and 46,332,538 m² for 16 m resolution. Finally, the conversion ratio characteristics between resolutions were analyzed, yielding adjusted results of 38,466,192 m² for 2021 and 47,546,718 m² for 2023, respectively. These outcomes demonstrate strong alignment with local agricultural statistics, confirming method viability for chrysanthemum cultivation area computation. Full article

Tooth development (odontogenesis) is regulated by interactions between epithelial and mesenchymal tissues through signaling pathways such as Bone Morphogenetic Protein (BMP), Wingless-related integration site (Wnt), Sonic Hedgehog (SHH), and Fibroblast Growth Factor (FGF). Mesenchymal stem cells (MSCs) derived from dental tissues—including dental pulp stem cells (DPSCs), periodontal ligament stem cells (PDLSCs), and dental follicle progenitor cells (DFPCs)—show promise for regenerative dentistry due to their multilineage differentiation potential. Epigenetic regulation, particularly DNA methylation, is hypothesized to underpin their distinct regenerative capacities. This study reanalyzed publicly available DNA methylation data generated with Illumina Infinium HumanMethylation450 BeadChip arrays (450K arrays) from DPSCs, PDLSCs, and DFPCs. High-confidence CpG sites were selected based on detection p-values, probe variance, and genomic annotation. Principal Component Analysis (PCA) and hierarchical clustering identified distinct methylation profiles. Functional enrichment analyses highlighted biological processes and pathways associated with specific methylation clusters. Noncoding RNA analysis was integrated to construct regulatory networks linking DNA methylation patterns with key developmental genes. Distinct epigenetic signatures were identified for DPSCs, PDLSCs, and DFPCs, characterized by differential methylation across specific genomic contexts. Functional enrichment revealed pathways involved in odontogenesis, osteogenesis, and neurodevelopment. Network analysis identified central regulatory nodes—including genes, such as PAX6, FOXC2, NR2F2, SALL1, BMP7, and JAG1—highlighting their roles in tooth development. Several noncoding RNAs were also identified, sharing promoter methylation patterns with developmental genes and being implicated in regulatory networks associated with stem cell differentiation and tissue-specific function. Altogether, DNA methylation profiling revealed that distinct epigenetic landscapes underlie the developmental identity and differentiation potential of dental-derived mesenchymal stem cells. This integrative analysis highlights the relevance of noncoding RNAs and regulatory networks, suggesting novel biomarkers and potential therapeutic targets in regenerative dentistry and orthodontics. Full article

Atherosclerosis is a progressive, multifactorial disease driven by the interplay of lipid dysregulation, chronic inflammation, oxidative stress, and maladaptive vascular remodeling. Despite advances in systemic lipid-lowering and anti-inflammatory therapies, residual cardiovascular risk persists, highlighting the need for more precise interventions. Targeted drug delivery represents a transformative strategy, offering the potential to modulate key pathogenic processes within atherosclerotic plaques while minimizing systemic exposure and off-target effects. Recent innovations span a diverse array of platforms, including nanoparticles, liposomes, exosomes, polymeric carriers, and metal–organic frameworks (MOFs), engineered to engage distinct pathological features such as inflamed endothelium, dysfunctional macrophages, oxidative microenvironments, and aberrant lipid metabolism. Ligand-based, biomimetic, and stimuli-responsive delivery systems further enhance spatial and temporal precision. In parallel, advances in in-silico modeling and imaging-guided approaches are accelerating the rational design of multifunctional nanotherapeutics with theranostic capabilities. Beyond targeting lipids and inflammation, emerging strategies seek to modulate immune checkpoints, restore endothelial homeostasis, and reprogram plaque-resident macrophages. This review provides an integrated overview of the mechanistic underpinnings of atherogenesis and highlights state-of-the-art targeted delivery systems under preclinical and clinical investigation. By synthesizing recent advances, we aim to elucidate how precision-guided drug delivery is reshaping the therapeutic landscape of atherosclerosis and to chart future directions toward clinical translation and personalized vascular medicine. Full article

As people with cystic fibrosis (PwCF) live longer, kidney disease is emerging as a significant comorbidity that is increasingly linked to cardiovascular complications and progression to end-stage kidney disease. In our recent review, we proposed the unifying term CF-related kidney disease (CFKD) to encompass the spectrum of kidney dysfunction observed in this population. Early detection of kidney injury is critical for improving long-term outcomes, yet remains challenging due to the limited sensitivity of conventional laboratory tests, particularly in individuals with altered muscle mass and unique CF pathophysiology. Emerging approaches, including novel blood and urinary biomarkers, urinary extracellular vesicles, and genetic risk profiling, offer promising avenues for identifying subclinical kidney damage. When integrated with machine learning algorithms, these tools may enable the development of personalized risk stratification models and targeted therapeutic strategies. This precision medicine approach has the potential to transform kidney disease management in PwCF, shifting care from reactive treatment of late-stage disease to proactive monitoring and early intervention. Full article

RNA-binding proteins (RBPs), particularly IGF2BP3, play critical but underexplored roles in lung adenocarcinoma (LUAD). This study investigated IGF2BP3′s clinical and functional significance using single-cell/RNA sequencing, validated by qPCR, Western blot, and immunohistochemistry. The results show IGF2BP3 was significantly upregulated in LUAD tissues and associated with advanced-stage, larger tumors, lymph node metastasis, and poor prognosis. A prognostic nomogram confirmed its independent predictive value. Functionally, IGF2BP3 knockdown suppressed proliferation, and induced G2/M arrest and apoptosis. GSEA linked high IGF2BP3 to cell cycle activation and low expression to metabolic pathways. Notably, high IGF2BP3 correlated with immune evasion markers (downregulated CD4+ effector T cells, upregulated Th2 cells), while TIDE analysis suggested a better immunotherapy response in low-expressing patients. Drug screening identified BI-2536 as a potential therapy for low-IGF2BP3 cases, supported by strong molecular docking affinity (−7.55 kcal/mol). These findings establish IGF2BP3 as a key driver of LUAD progression and a promising target for immunotherapy and precision medicine. Full article

Intravascular biosensors have become a crucial and novel class of devices in healthcare, enabling the constant real-time monitoring of essential physiological parameters directly within the circulatory system. Recent developments in micro- and nanotechnology have relevantly improved the sensitivity, miniaturization, and biocompatibility of these devices, thereby enabling their application in precision medicine. This review summarizes the latest advances in intravascular biosensor technologies, with a special focus on glucose and oxygen level monitoring, blood pressure and heart rate assessment, and early disease diagnostics, as well as modern approaches to drug therapy monitoring and delivery systems. Key challenges such as long-term biostability, signal accuracy, and regulatory approval processes are critical considerations. Innovative strategies, including biodegradable implants, nanomaterial-functionalized surfaces, and integration with artificial intelligence, are regarded as promising avenues to overcome current limitations. This review provides a comprehensive roadmap for upcoming research and the clinical translation of advanced intravascular biosensors with a strong emphasis on their transformative impact on personalized healthcare. Full article

Inflammatory Bowel Diseases (IBDs) are complex, multifactorial disorders with no known cure, necessitating lifelong care and often leading to surgical interventions. This ongoing healthcare requirement, coupled with the increased use of biological drugs and rising disease prevalence, significantly increases the financial burden on the healthcare systems. Thus, a number of novel technological approaches have emerged in order to face some of the pivotal questions still associated with IBD. In navigating the intricate landscape of IBD, biosensors act as indispensable allies, bridging the gap between traditional diagnostic methods and the evolving demands of precision medicine. Continuous progress in biosensor technology holds the key to transformative breakthroughs in IBD management, offering more effective and patient-centric healthcare solutions considering the One Health Approach. Here, we will delve into the landscape of biomarkers utilized in the diagnosis, monitoring, and management of IBD. From well-established serological and fecal markers to emerging genetic and epigenetic markers, we will explore the role of these biomarkers in aiding clinical decision-making and predicting treatment response. Additionally, we will discuss the potential of novel biomarkers currently under investigation to further refine disease stratification and personalized therapeutic approaches in IBD. By elucidating the utility of biosensors across the spectrum of IBD care, we aim to highlight their importance as valuable tools in optimizing patient outcomes and reducing healthcare costs. Full article

Circadian rhythms are intrinsic 24 h cycles that regulate metabolic processes across multiple tissues, with skeletal muscle emerging as a central node in this temporal network. Muscle clocks govern gene expression, fuel utilisation, mitochondrial function, and insulin sensitivity, thereby maintaining systemic energy homeostasis. However, circadian misalignment, whether due to behavioural disruption, nutrient excess, or metabolic disease, impairs these rhythms and contributes to insulin resistance, and the development of obesity, and type 2 diabetes mellitus. Notably, the muscle clock remains responsive to non-photic cues, particularly exercise, which can reset and amplify circadian rhythms even in metabolically impaired states. This work synthesises multi-level evidence from rodent models, human trials, and in vitro studies to elucidate the role of skeletal muscle clocks in circadian metabolic health. It explores how exercise entrains the muscle clock via molecular pathways involving AMPK, SIRT1, and PGC-1α, and highlights the time-of-day dependency of these effects. Emerging data demonstrate that optimally timed exercise enhances glucose uptake, mitochondrial biogenesis, and circadian gene expression more effectively than time-agnostic training, especially in individuals with metabolic dysfunction. Finally, findings are integrated from multi-omic approaches that have uncovered dynamic, time-dependent molecular signatures that underpin circadian regulation and its disruption in obesity. These technologies are uncovering biomarkers and signalling nodes that may inform personalised, temporally targeted interventions. By combining mechanistic insights with translational implications, this review positions skeletal muscle clocks as both regulators and therapeutic targets in metabolic disease. It offers a conceptual framework for chrono-exercise strategies and highlights the promise of multi-omics in developing precision chrono-medicine approaches aimed at restoring circadian alignment and improving metabolic health outcomes. Full article

Hodgkin’s Lymphoma (HL) affects approximately 8500 individuals annually in the United States. The 5-year relative survival rate has improved to 88.5%, driven by transformative advances in immunotherapy and precision oncology. The integration of Brentuximab vedotin (BV) and immune checkpoint inhibitors (ICIs) has redefined treatment paradigms. The phase III SWOG S1826 trial established nivolumab plus doxorubicin, vinblastine, and dacarbazine (N + AVD) as an emerging new standard for advanced-stage HL, achieving a 2-year progression-free survival (PFS) of 92% compared to 83% for BV plus AVD (HR 0.48, 95% CI: 0.33–0.70), with superior safety, particularly in patients over 60. In relapsed/refractory HL, pembrolizumab outperforms BV, with a median PFS of 13.2 versus 8.3 months (HR 0.65, 95% CI: 0.48–0.88), as demonstrated in the KEYNOTE-204 trial. Emerging strategies, including novel ICI combinations, minimal residual disease (MRD) monitoring via circulating tumor DNA (ctDNA), and artificial intelligence (AI)-driven diagnostics, promise to further personalize therapy. This review synthesizes HL’s epidemiology, pathogenesis, diagnostic innovations, and therapeutic advances, highlighting the role of precision medicine in addressing unmet needs and disparities in HL care. Full article

Pediatric asthma is a multifactorial and heterogeneous disease determined by the dynamic interplay of genetic susceptibility, environmental exposures, and immune dysregulation. Recent advances have highlighted the pivotal role of epigenetic mechanisms, in particular, DNA methylation, histone modifications, and non-coding RNAs, in the regulation of inflammatory pathways contributing to asthma phenotypes and endotypes. This review examines the role of respiratory viruses such as respiratory syncytial virus (RSV), rhinovirus (RV), and other bacterial and fungal infections that are mediators of infection-induced epithelial inflammation that drive epithelial homeostatic imbalance and induce persistent epigenetic alterations. These alterations lead to immune dysregulation, remodeling of the airways, and resistance to corticosteroids. A focused analysis of T2-high and T2-low asthma endotypes highlights unique epigenetic landscapes directing cytokines and cellular recruitment and thereby supports phenotype-specific aspects of disease pathogenesis. Additionally, this review also considers the role of miRNAs in the control of post-transcriptional networks that are pivotal in asthma exacerbation and the severity of the disease. We discuss novel and emerging epigenetic therapies, such as DNA methyltransferase inhibitors, histone deacetylase inhibitors, miRNA-based treatments, and immunomodulatory probiotics, that are in preclinical or early clinical development and may support precision medicine in asthma. Collectively, the current findings highlight the translational relevance of including pathogen-related biomarkers and epigenomic data for stratifying pediatric asthma patients and for the personalization of therapeutic regimens. Epigenetic dysregulation has emerged as a novel and potentially transformative approach for mitigating chronic inflammation and long-term morbidity in children with asthma. Full article

The advancement of artificial intelligence (AI), deep learning, and radiomics has introduced novel methodologies for the detection, classification, prognosis, and treatment evaluation of pancreatic ductal adenocarcinoma (PDAC). As the integration of AI into medical imaging continues to evolve, its potential to enhance early detection, refine diagnostic precision, and optimize treatment strategies becomes increasingly evident. However, despite significant progress, various challenges remain, particularly in terms of clinical applicability, generalizability, interpretability, and integration into routine practice. Understanding the current state of research is crucial for identifying gaps in the literature and exploring opportunities for future advancements. This literature review aims to provide a comprehensive overview of the existing studies on AI applications in PDAC, with a focus on disease detection, classification, survival prediction, treatment response assessment, and radiogenomics. By analyzing the methodologies, findings, and limitations of these studies, we aim to highlight the strengths of AI-driven approaches while addressing critical gaps that hinder their clinical translation. Furthermore, this review aims to discuss future directions in the field, emphasizing the need for multi-institutional collaborations, explainable AI models, and the integration of multi-modal data to advance the role of AI in personalized medicine for PDAC. Full article

Multiple sclerosis (MS) is a chronic, immune-mediated disorder of the central nervous system (CNS) characterized by inflammation, demyelination, axonal degeneration, and gliosis. Its pathophysiology involves a complex interplay of genetic susceptibility, environmental triggers, and immune dysregulation, ultimately leading to progressive neurodegeneration and functional decline. Although significant advances have been made in disease-modifying therapies (DMTs), many patients continue to experience disease progression and unmet therapeutic needs. Drug repurposing—the identification of new indications for existing drugs—has emerged as a promising strategy in MS research, offering a cost-effective and time-efficient alternative to traditional drug development. Several compounds originally developed for other diseases, including immunomodulatory, anti-inflammatory, and neuroprotective agents, are currently under investigation for their efficacy in MS. Repurposed agents, such as selective sphingosine-1-phosphate (S1P) receptor modulators, kinase inhibitors, and metabolic regulators, have demonstrated potential in promoting neuroprotection, modulating immune responses, and supporting remyelination in both preclinical and clinical settings. Simultaneously, artificial intelligence (AI) is transforming drug discovery and precision medicine in MS. Machine learning and deep learning models are being employed to analyze high-dimensional biomedical data, predict drug–target interactions, streamline drug repurposing workflows, and enhance therapeutic candidate selection. By integrating multiomics and neuroimaging data, AI tools facilitate the identification of novel targets and support patient stratification for individualized treatment. This review highlights recent advances in drug repurposing and discovery for MS, with a particular emphasis on the emerging role of AI in accelerating therapeutic innovation and optimizing treatment strategies. Full article

The relationship between metabolic dysfunction and mental health disorders is complex and has received increasing attention. This review integrates current research to explore how stress-related growth differentiation factor 15 (GDF15) signaling, ceramides derived from gut microbiota, and mitochondrial dysfunction in the brain interact to influence both metabolic and psychiatric conditions. Evidence suggests that these pathways converge to regulate brain energy homeostasis through feedback mechanisms involving the autonomic nervous system and the hypothalamic–pituitary–adrenal axis. GDF15 emerges as a key stress-responsive biomarker that links peripheral metabolism with brainstem GDNF family receptor alpha-like (GFRAL)-mediated anxiety circuits. Meanwhile, ceramides impair hippocampal mitochondrial function via membrane incorporation and disruption of the respiratory chain. These disruptions may contribute to sustained pathological states such as depression, anxiety, and cognitive dysfunction. Although direct mechanistic data are limited, integrating these pathways provides a conceptual framework for understanding metabolic–psychiatric comorbidities. Furthermore, differences in age, sex, and genetics may influence these systems, highlighting the need for personalized interventions. Targeting mitochondrial function, GDF15-GFRAL signaling, and gut microbiota composition may offer new therapeutic strategies. This integrative perspective helps conceptualize how metabolic and psychiatric mechanisms interact for understanding the pathophysiology of metabolic and psychiatric comorbidities and highlights therapeutic targets for precision medicine. Full article

Recent studies have demonstrated that the development and progression of hypertensive kidney injury comprise not only elevated systemic blood pressure but also a complex interplay of cellular, molecular, and genetic mechanisms. In this report, we outline the key emerging pathways—ranging from dysregulated renin–angiotensin system signaling, oxidative stress, immune-mediated inflammation, and metabolic abnormalities to epigenetic alterations and genetic susceptibilities—that contribute to kidney damage in hypertensive conditions. In addition, we also discuss precision medicine approaches like biomarker-directed therapies, pharmacologically targeted therapies, and device-based innovations for modulating these pathways. This integrative review emphasizes the application of omics technologies and genetically guided interventions to better stratify patients and offer personalized care for hypertensive kidney disease. Full article

Platelet-rich plasma (PRP) is widely used in regenerative medicine, yet clinical outcomes remain inconsistent. While traditional strategies have focused on platelet concentration and activation methods, emerging evidence suggests that the biological age of platelets, especially platelet senescence, may be a critical but overlooked factor influencing therapeutic efficacy. Senescent platelets display reduced granule content, impaired responsiveness, and heightened pro-inflammatory behavior, all of which can compromise tissue repair and regeneration. This review explores the mechanisms underlying platelet aging, including oxidative stress, mitochondrial dysfunction, and systemic inflammation, and examines how these factors influence PRP performance across diverse clinical contexts. We discuss the functional consequences of platelet senescence, the impact of comorbidities and aging on PRP quality, and current tools to assess platelet functionality, such as HLA-I–based flow cytometry. In addition, we present strategies for pre-procedural optimization, advanced processing techniques, and adjunctive therapies aimed at enhancing platelet quality. Finally, we challenge the prevailing emphasis on high-volume blood collection, highlighting the limitations of quantity-focused protocols and advocating for a shift toward biologically precise, function-driven regenerative interventions. Recognizing and addressing platelet senescence is a key step toward unlocking the full therapeutic potential of PRP-based interventions. Full article