Search Results (463)

Food allergy diagnosis remains challenging due to the difficulty of distinguishing true clinical allergy from asymptomatic sensitization. Inaccurate diagnosis may result in unnecessary dietary restrictions, reduced quality of life, or, conversely, failure to identify individuals at risk of severe allergic reactions. This review critically analyzes the efficacy, limitations, and clinical utility of currently available diagnostic tests for food allergy, with particular emphasis on their ability to predict true clinical reactivity. A comprehensive literature review was conducted to evaluate the sensitivity, specificity, and predictive values of both traditional and emerging diagnostic modalities. English-language guidelines, systematic reviews, and key clinical studies published primarily within the past 15 years (up to 2025) were identified through PubMed and Google Scholar. Classic diagnostic tools, including skin prick testing (SPT) and serum-specific IgE (sIgE), were assessed alongside novel approaches such as component-resolved diagnostics (CRD), basophil activation test (BAT), mast cell activation test (MAT), atopy patch testing (APT), cytokine profiling, and omics-based diagnostics. Particular attention was given to how these tests compare with the oral food challenge (OFC), which remains the diagnostic gold standard. The findings demonstrate that while conventional tests offer high sensitivity and are valuable for initial risk assessment, their limited specificity often leads to overdiagnosis. Emerging molecular and cellular assays show improved specificity and functional relevance, especially in complex cases involving polysensitization or unclear clinical histories and may reduce reliance on OFCs in the future. However, accessibility, cost, and lack of standardization currently limit their widespread clinical application. Advances in artificial intelligence and data integration hold promise for improving diagnostic accuracy through enhanced interpretation of complex immunological data. Based on the synthesized evidence, this review proposes an evidence-based, stepwise, and individualized diagnostic algorithm for food allergy. Integrating clinical history, targeted testing, and selective use of OFCs can improve diagnostic certainty, enhance food safety, minimize unnecessary dietary avoidance, and optimize patient outcomes. The review underscores the need for continued research, standardization, and validation of novel diagnostic tools to support personalized and precise food allergy management. Full article

Drug resistance is an important challenge in medical research and clinical practice, posing a serious threat to the effectiveness of current therapeutic strategies. Transcriptomics has played a crucial role in analyzing resistance-related genes and pathways, while the application of machine learning in high-throughput data analysis and prediction has also opened up new avenues in this field. However, existing studies mostly focus on a single drug or specific categories, and their conclusions are limited in applicability across drug categories, while studies on drugs beyond antibacterial and antitumor categories remain limited. In this study, we systematically analyzed the transcriptomic data of resistant cell lines treated with 1738 drugs spanning 82 categories and identified core genes through an integrated analysis of three classical machine learning methods. Using the antibacterial drug salinomycin as an example, we established a resistance prediction model that demonstrated high predictive accuracy, indicating the significant value of the selected core genes in prediction. Meanwhile, some of the core genes identified through the protein–protein interaction (PPI) network overlapped with those derived from machine learning analysis, further supporting the reliability of these core genes. Pathway enrichment analysis of differential genes revealed potential resistance mechanisms. This study provides a new perspective for exploring resistance mechanisms across drug categories and highlights potential directions for resistance intervention strategies and novel drug development. Full article

Background and Objective: Colorectal cancer (CRC) liver metastasis (CRLM) represents a major clinical challenge, and acquired resistance to radiotherapy (RT) significantly limits therapeutic efficacy. A deep and comprehensive understanding of the cellular and molecular mechanisms driving RT resistance is urgently required to develop effective combination strategies. Here, we aimed to dissect the dynamic cellular landscape of the tumor microenvironment (TME) and identify key epigenetic regulators mediating radioresistance in CRLM by integrating cutting-edge single-cell and spatial omics technologies. Methods and Results: We performed integrated single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) on matched pre- and post-radiotherapy tumor tissues collected from three distinct CRLM patients. Employing a robust machine-learning framework on the multi-omics data, we successfully identified MORF4L1 (Mortality Factor 4 Like 1), an epigenetic reader, as a critical epigenetic mediator of acquired radioresistance. High-resolution scRNA-seq analysis of the tumor cell compartment revealed that the MORF4L1-high subpopulation exhibited significant enrichment in DNA damage repair (DDR) pathways, heightened activity of multiple pro-survival metabolic pathways, and robust signatures of immune evasion. Pseudotime trajectory analysis further confirmed that RT exposure drives tumor cells toward a highly resistant state, marked by a distinct increase in MORF4L1 expression. Furthermore, cell–cell communication inference demonstrated a pronounced, systemic upregulation of various immunosuppressive signaling axes within the TME following RT. Crucially, high-resolution ST confirmed these molecular and cellular interactions in their native context, revealing a significant spatial co-localization of MORF4L1-expressing tumor foci with multiple immunosuppressive immune cell types, including regulatory T cells (Tregs) and tumor-associated macrophages (TAMs), thereby underscoring its role in TME-mediated resistance. Conclusions: Our comprehensive spatial and single-cell profiling establishes MORF4L1 as a pivotal epigenetic regulator underlying acquired radioresistance in CRLM. These findings provide a compelling mechanistic rationale for combining radiotherapy with the targeted inhibition of MORF4L1, presenting a promising new therapeutic avenue to overcome treatment failure and improve patient outcomes in CRLM. Full article

The concept of individual cellular intelligence reframes cells as dynamic entities endowed with sensory, reactive, adaptive, and memory-like capabilities, enabling them to navigate lifelong metabolic and extrinsic stressors. A likely vital component of this intelligence system is stress-responsive G protein-coupled receptor (GPCR) networks, interconnected by common signaling adaptors. These stress-regulating networks orchestrate the detection, processing, and experience retention of environmental cues, events, and stressors. These networks, along with other sensory mechanisms such as receptor-mediated signaling and DNA damage detection, allow cells to acknowledge and interpret stressors such as oxidative stress or nutrient scarcity. Reactive responses, including autophagy and apoptosis, mitigate immediate damage, while adaptive strategies, such as metabolic rewiring, receptor expression alteration and epigenetic modifications, enhance long-term survival. Cellular experiences that are effectively translated into ‘memories’, both transient and heritable, likely rely on GPCR-induced epigenetic and mitochondrial adaptations, enabling anticipation of future insults. Dysregulation of these processes and networks can drive pathological states, shaping resilience or susceptibility to chronic diseases like cancer, neurodegeneration, and metabolic disorders. Employing molecular evidence, here, we underscore the presence of an effective cellular intelligence, supported by multi-level sensory GPCR networks. The quality of this intelligence acts as a critical determinant of somatic health and a promising frontier for therapeutic innovation. Future research leveraging single-cell omics and systems biology may unravel the molecular underpinnings of these capabilities, offering new strategies to prevent or reverse stress-induced pathologies. Full article

With intensifying global climate change and human activities, and with regional topography interactions, soil and water salinization has intensified, posing major ecological and environmental challenges worldwide. Here, we integrated histology, transmission electron microscopy, RNA sequencing (RNA-seq) and data-independent acquisition (DIA)-based proteomics to profile hepatopancreas responses of Exopalaemon carinicauda during acute sulfate stress (≤48 h). Sulfate exposure disrupted tubular architecture and organelle integrity, consistent with early cellular injury. Multi-omics analyses revealed metabolic reprogramming marked by suppressed glycolysis (e.g., HK2, ENO) and enhanced oxidative phosphorylation (e.g., ATP5F1B), together with activation of calcium signaling (e.g., SLC8A1, ADCY9) and reinforcement of antioxidant/one-carbon and glucose-branch pathways (e.g., SHMT2, PGAM2). These coordinated transcript–protein changes indicate a shift from rapid cytosolic ATP supply to mitochondrial ATP production while buffering Ca²⁺ overload and reactive oxygen species. Collectively, our results delineate the physiological and molecular adjustments that enable E. carinicauda to cope with sulfate conditions and provide mechanistic targets for selective breeding and water-quality management in saline–alkaline aquaculture. Full article

The biomarker landscape in rheumatoid arthritis (RA) is evolving from reliance on traditional markers toward integrated, multimodal strategies enabling precision medicine approaches. To critically evaluate emerging biomarkers across serological, cellular, genetic, imaging, and multi-omic domains, distinguishing those approaching clinical readiness from those requiring further development. In this study, a narrative review of the literature published between 2000 and 2024 relevant to clinical decision-making in RA was conducted. Among novel serological markers, 14-3-3η protein and anti-carbamylated protein antibodies show the strongest validation for seronegative disease and prognostic stratification. Calprotectin demonstrates utility for disease activity monitoring and de-escalation decisions. Multi-biomarker disease activity scores provide an objective assessment but lack outcome trial validation. Musculoskeletal ultrasound offers accessible imaging biomarker capability, while MRI bone marrow edema remains the strongest structural progression predictor. Synovial tissue pathotyping has demonstrated proof-of-concept for treatment stratification. Genetic, epigenetic, and metabolomic approaches remain investigational. Key clinical implications include using 14-3-3η and calprotectin to inform seronegative diagnosis and de-escalation decisions, integrating ultrasound for remission verification, and recognizing that emerging biomarkers for extra-articular complications, including cardiovascular risk and venous thromboembolism, represent important unmet needs. Full article

Background: Depression and Metabolic Dysfunction-Associated Steatotic Fatty Liver Disease (MASLD) are common chronic diseases, respectively. However, the causal and molecular links between them remain unclear. In order to explore whether depression contributes to an increased risk of MASLD and whether inflammation mediates this effect, we integrated multi-level evidence from the epidemiology of the National Health and Nutrition Examination Survey (NHANES), the genetics of GWAS, the transcriptomes of GEO, and single-cell RNA sequencing datasets. Methods: A multi-level integrative analysis strategy was used to validate this pathway. First, a cross-sectional epidemiological analysis based on NHANES data was used to reveal the association between depression and MASLD, and to explore the mediating role of inflammation and liver injury markers. Secondly, a two-sample Mendelian randomization analysis was used to infer the causal direction of depression and MASLD, and to verify the mediating effect of systemic inflammation and liver injury indicators at the genetic level. Then, the transcriptome co-expression network analysis and machine learning were used to screen the common hub genes connecting the two diseases. Finally, single-cell transcriptome data were used to characterize the dynamic expression of potential key genes during disease progression at cellular resolution. Results: Depression significantly increased the risk of MASLD, especially in women (OR = 1.39, 95%CI [1.17–1.65]). Parallel mediation analysis showed that high-sensitivity C-reactive protein (hs-CRP) (p < 0.001), γ-glutamyltransferase (GGT) (p < 0.001), and alkaline phosphatase (ALP) (p < 0.001) mediated this relationship. Mendelian randomization analysis confirmed the unidirectional causal effect of depression on MASLD, and there was no reverse association (β = 0.483, SE = 0.146, p = 0.001). Weighted gene co-expression network analysis and machine learning identified CD40LG as a potential molecular bridge between depression-associated immune modules and MASLD. In addition, single-cell data analysis revealed a stage-specific trend of CD40LG expression in CD4⁺ T cells during MASLD progression, while its receptor CD40 was also activated in B cells. In the female sample, CD40LG maintained an upward trend. However, the stability of this result is limited by the limited sample size. Conclusions: This study provides converging multi-omics evidence that depression plays a causal role in MASLD through inflammation-mediated immune signaling. The CD40LG-CD40 axis has emerged as an immune mechanism that transposes depression into the pathogenesis of MASLD, providing a potential target for the intervention of gender-specific metabolic liver disease. Full article

Human adult cardiomyocytes (CMs) have limited regenerative capacity, posing a significant challenge in restoring cardiac function following substantial CM loss due to an acute ischemic event or chronic hemodynamic overload. Nearly half of patients show no improvement in left ventricular ejection fraction during recovery from acute myocardial infarction. At baseline, both humans and mice exhibit low but continuous cell turnover originating from the existing CMs. Moreover, myocardial infarction can induce endogenous CM cell cycling. Consequently, research has focused on identifying drivers of CM rejuvenation and proliferation from pre-existing CMs. High-throughput screening has facilitated the discovery of novel pro-proliferative targets through small molecules, microRNAs, and pathway-specific interventions. More recently, omics-based approaches such as single-nucleus RNA sequencing and spatial transcriptomics have expanded our understanding of cardiac cellular heterogeneity. The big-data strategies provide critical insights into why only a subset of CMs re-enter the cell cycle while most remain quiescent. In this review, we compare several high-throughput screening strategies used to identify novel targets for CM proliferation. We also summarize the benefits and limitations of various screening models—including zebrafish embryos, rodent CMs, human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), and cardiac organoids—underscoring the importance of integrating multiple systems to uncover new regenerative mechanisms. Further work is needed to identify translatable and safe targets capable of inducing functional CM expansion in clinical settings. By integrating high-throughput screening findings with insights into CM heterogeneity, this review provides a comprehensive framework for advancing cardiac regeneration research and guiding future therapeutic development. Full article

The context of food science and biotechnology is undergoing a profound transformation, characterized by an evolutionary shift from conventional large-scale fermentation to precision biomanufacturing, positioning Lactic Acid Bacteria (LAB) as versatile cellular biofactories for next-generation functional foods. This review analyzes the evolutionary role of LAB, their utilization as probiotics, and the technological advances driving this shift. This work also recognizes the fundamental contributions of pioneering women in the field of biotechnology. The primary methodology relies on the seamless integration of synthetic biology (CRISPR-Cas editing), Multi-Omics analysis, and advanced Artificial Intelligence/Machine Learning, enabling the precise, rational design of LAB strains. This approach has yielded significant findings, including successful metabolic flux engineering to optimize the biosynthesis of high-value nutraceuticals such as Nicotinamide Mononucleotide and N-acetylglucosamine, and the development of Live Biotherapeutic Products using native CRISPR systems for the expression of human therapeutic peptides (e.g., Glucagon-like Peptide-1 for diabetes). From an industrial perspective, this convergence enhances strain robustness and supports the digitalized circular bioeconomy through the valorization of agri-food by-products. In conclusion, LAB continue to consolidate their position as central agents for the development of next-generation functional foods. Full article

Fibrosis is a pathological condition resulting from an excessive tissue response during the repair process, often affecting various tissues such as the skin, organs, and joints, posing a significant threat to global health. Researchers have made substantial efforts to explore the endogenous mechanisms underlying fibrosis in recent years and have developed several therapeutic strategies to block this process. Historically, research on fibrotic diseases has focused on identifying highly relevant therapeutic targets and developing effective antifibrotic drugs. However, due to the complexity of the mechanisms of fibrosis and its effector cells, the effectiveness of antifibrotic therapies remains limited. With the advancement of high-throughput omics technologies and machine learning tools, we now have a clearer understanding of cellular heterogeneity, intercellular interactions, and the specific roles of cells in various biological processes. This enables tracking the trajectory of different cell types during the fibrotic process, facilitating early identification and discovery of new targets for fibrosis treatment, and conducting more precise targeted research. Supported by these novel technologies, numerous studies have revealed that, in addition to normal fibroblasts, a group of bone marrow–derived fibrocytes also contributes to the fibrosis of both parenchymal and non-parenchymal organs and tissues. Circulating fibrocytes are hematopoietic-derived cells that are recruited to injury sites during injury, disease, and aging, acting as participants in inflammation and tissue repair, and directly or indirectly promoting fibrosis in various tissues throughout the body. This review summarizes the general characteristics of circulating fibrocytes, the molecular mechanisms involved in their recruitment to different tissues, the process of their differentiation into fibroblasts, their potential roles in various diseases, and the latest research developments in this field. Given the key role of circulating fibrocytes in fibrosis across multiple tissues, they may serve as promising targets for the development of novel antifibrotic therapies. Full article

Creutzfeldt–Jakob disease (CJD) is a rare but devastating neurodegenerative disorder characterized by the pathological misfolding of the cellular prion protein (PrP^C) into the pathogenic isoform-scrapie prion protein (PrP^Sc), ultimately leading to fatal outcomes. Cerebrospinal fluid (CSF) biomarkers play a pivotal role in early diagnosis, longitudinal monitoring, and prognostic assessment, thereby enhancing the clinical management of this challenging disease. This review summarizes the established CSF biomarkers, 14-3-3 protein, tau protein (total tau), phosphorylated tau isoforms, α-synuclein, neurofilament light chain (Nfl), S100B, neuron-specific enolase (NSE), and phosphorylated neurofilament heavy chain (pNFH), highlighting typical sensitivity ranges (14-3-3 ~70–85%; RT-QuIC > 90%) and subtype-dependent performance variation. We further dissect limitations related to assay variability, inter-laboratory cut-off inconsistencies, and reduced specificity in non-prion dementias. Looking ahead, we discuss emerging multi-omics discovery, integration of CSF with blood-based biomarkers and imaging signatures, and AI-enabled diagnostic modeling. We propose a three-tier biomarker framework combining Real-Time Quaking-Induced Conversion (RT-QuIC) as a confirmatory assay, tau/NfL/pNFH as injury-severity indicators, and multi-omics-derived signatures for early detection and prognosis stratification. Full article

Although there have been advancements in stroke treatment (reperfusion) therapy, and it has been shown that many individuals continue to suffer from partial recoveries and continuing decline in their neurological status as a result of suffering a stroke, a primary barrier to providing precise care to patients with stroke continues to be the inability to capture changes in molecular and cellular programs over time and in biological compartments. This review synthesizes evidence that represents the entire continuum of ischemia, beginning with acute metabolic failure and excitotoxicity, and ending with immune response in the nervous system, reprogramming of glial cells, remodeling of vessels, and plasticity at the level of networks, and organizes this evidence in a temporal framework that includes three biological compartments:central nervous system tissue, cerebrospinal fluid, and peripheral blood. Additionally, this review discusses new technologies which enable researchers to discover biomarkers at an extremely high resolution, including single-cell and spatial multi-omics, profiling of extracellular vesicles, proteoform-resolved proteomics, and glymphatic imaging, as well as new computational methods and machine-learning algorithms to integrate data from multiple modalities and predict trajectories of disease progression. The final section of this review will provide an overview of translationally relevant and ethically relevant issues regarding the deployment of predictive biomarkers, such as privacy, access, equity, and fairness, and emphasize the importance of global coordination of research efforts in order to ensure the clinical applicability and global equity of biomarker-based diagnostics and treatments. Full article

Wound healing is a complex, multi-phase process requiring coordinated interactions among diverse cell types and molecular pathways to restore tissue integrity. Dysregulation can lead to chronic non-healing wounds or excessive scarring, posing major clinical and economic burdens. Single-omics interrogate individual molecular layers, such as the genome, transcriptome, proteome, metabolome, or epigenome, and have revealed key cellular players, but provide a limited view of dynamic wound repair. Single-cell technologies provide higher resolution to single-omic data by resolving cell-type and state-specific heterogeneity, enabling precise characterization of cellular populations. Multi-omics integrates multiple molecular layers at single-cell resolution, reconstructing regulatory networks, epigenetic landscapes, and cell–cell interactions underlying healing outcomes. Recent advances in single-cell and spatial multi-omics have revealed fibroblast subpopulations with distinct fibrotic or regenerative roles and immune–epithelial interactions critical for re-epithelialization. Integration with computational tools and artificial intelligence (AI) continues to reveal cellular interactions, predict healing outcomes, and guide development of personalized therapies. Despite technical and translational challenges, including data integration and cost, multi-omics are increasingly shaping the future of precision wound care. This review highlights how multi-omics is redefining understanding of wound biology and fibrosis and explores emerging applications such as smart biosensors and predictive models with potential to transform wound care. Full article

Melanin pigments are ubiquitous biopolymers across diverse life forms and play multifaceted roles in cellular defense and environmental adaptation. The specialized neuromelanin in human brains accumulates mainly within catecholaminergic neurons of the substantia nigra and locus coeruleus, serving as a crucial modulator of brain homeostasis, metal detoxification, and oxidative stress responses. The intricate processes of human melanogenesis, encompassing both cutaneous and neuronal forms, are governed by complex genetic networks. Concurrently, melanin in fungi (synthesized through distinct genetic pathways) confers remarkable resistance to environmental stressors, including ionizing radiation. Recent advancements in omics technologies—including transcriptomics, proteomics, metabolomics, and epigenomics—have profoundly enhanced our understanding of neuromelanin’s molecular environment in health, aging, and neurodegenerative conditions such as Parkinson’s disease (PD), Alzheimer’s disease (AD), and other neurological disorders. This article reviews the genetic underpinnings of human melanogenesis and fungal melanogenesis, explores the convergent and divergent evolutionary pressures driving their functions, and synthesizes the rapidly accumulating omics data to elucidate neuromelanin’s critical, and often dual, role in human brain pathology. Moreover, we discuss the intriguing parallels between neuromelanin and fungal melanin, highlighting radioprotection and its potential implications for neuroprotection and astrobiology, with a special emphasis on the need to investigate neuromelanin’s potential for radioprotection in light of fungal melanin’s remarkable protective properties. Full article

Chronic diseases, characterized by their high prevalence and protracted course, represent a paramount challenge to global public health, necessitating effective, evidence-based preventive strategies. While functional foods are widely recognized for their potential, a comprehensive synthesis elucidating their multitargeted mechanisms within a “food-medicine homology” framework and a clear trajectory from broad-spectrum health promotion to targeted intervention remains lacking. This review bridges this critical gap by systematically evaluating the scientific evidence and application potential of functional foods, with a specific focus on key bioactive compounds—β-glucan, omega-3 polyunsaturated fatty acids (PUFAs), dietary fiber, and catechins. We provide a critical analysis of how these components orchestrate synergistic effects at molecular, cellular, and systemic levels to counteract core pathological processes, including oxidative stress, chronic inflammation, metabolic dysregulation, and gut microbiota imbalance. Our unique contribution lies in integrating the ancient wisdom of food-medicine homology with modern multi-omics and evidence-based research, thereby proposing a refined nutritional intervention paradigm. The review offers critical insights into the convergent actions of these bioactives, their dose-response relationships substantiated by clinical meta-analyses, and the emerging role of gut microbiota-derived metabolites. Furthermore, this review also explores the emerging evidence for synergistic interactions among these key bioactives, proposing that their combined use may yield amplified and more network-based protective effects against chronic diseases through complementary mechanisms, aims to develop integrated prevention strategies targeting both cardiometabolic and neurodegenerative diseases. The integrated prevention strategies systematically connect mechanistic insights into bioactive compounds, evaluates the strength of clinical evidence, and examines the implications for regulatory standards and societal acceptance, thereby bridging the gap between basic science, clinical application, and public health policy. The “mechanism-to-evidence-to-regulation” framework in this review links molecular insights with clinical validation and regulatory implications, offering a holistic perspective rarely addressed in existing literature. Full article