Biomedicines最新文献

Acute myeloid leukemia (AML) is a highly aggressive malignancy defined by significant biological diversity and variable patient outcomes. A key subset of AML is driven by abnormalities that lead to the overexpression of the oncogenic transcription factors HOXA9 and MEIS1. These abnormalities include KMT2A (formerly MLL) rearrangements and NPM1 mutations, as well as other rare lesions such as NUP98 rearrangements. This review focuses on the biology of the KMT2A, NPM1, and HOX/MEIS1 pathways, dissecting their molecular mechanisms of leukemogenesis. A central theme is the role of the scaffolding protein menin in the epigenetic regulation of this pathway, which ultimately drives malignant transformation. Currently, the clinical landscape is being transformed by the emergence of menin inhibitors as promising therapeutic agents for AML harboring these specific genetic anomalies. We evaluate the latest data on various menin inhibitors-both as monotherapy and in combinations-emphasizing their efficacy and safety profiles. As new evidence continues to accumulate with recent drug approvals and ongoing randomized, phase 3 studies, menin inhibitors are rapidly becoming a component of the AML treatment paradigm for relapsed/refractory and likely newly diagnosed disease.

Background: Cardiovascular polypharmacy inherently amplifies the risk of drug-drug interactions (DDIs), yet most studies remain limited to isolated drug pairs or predefined high-risk classes, without mapping the systemic architecture through which interactions accumulate. Objectives: To characterize the burden, severity, and network structure of potential DDIs in a real-world cohort of hospitalized cardiovascular patients using interaction profiling combined with graph-theoretic network analysis. Methods: This retrospective observational study included 250 hospitalized cardiovascular patients. All home medications at admission were analyzed using the Drugs.com interaction database, and a drug interaction network was constructed to compute topological metrics (i.e., degree, betweenness, and eigenvector centrality). Results: Polypharmacy was highly prevalent, with a mean of 7.7 drugs per patient, and 98.4% of patients exhibited at least one potential DDI. A total of 4353 interactions were identified, of which 12.1% were classified as major, and 35.2% of patients presented high-risk profiles with ≥3 major interactions. Interaction burden showed a strong correlation with medication count (r = 0.929). Network analysis revealed a limited cluster of hub medications, particularly pantoprazole, furosemide, spironolactone, amiodarone, and perindopril, that disproportionately governed both interaction density and high-severity risk. Conclusions: These findings move beyond conventional pairwise screening by demonstrating how interaction risk propagates through interconnected therapeutic networks. The study supports the integration of hub-focused deprescribing, targeted monitoring strategies, and network-informed clinical decision support to mitigate DDI risk in cardiovascular polypharmacy. Future studies should link potential DDIs to clinical outcomes and validate network-based prediction models in prospective settings.

Objective: This study aimed to explore how maternal gestational diabetes mellitus (GDM) affects adipose tissue remodeling and the expression of C1q/TNF-related protein 6 (CTRP6) in offspring, with a focus on sex- and depot-specific differences. Methods: A GDM mouse model was established by feeding female C57BL/6J mice a high-fat diet (HFD) before and during pregnancy. Offspring were weaned onto standard chow or an HFD until 9 weeks of age. Metabolic phenotypes, adipose tissue morphology, and CTRP6 expression were assessed at weaning and adulthood. Results: GDM offspring exhibited increased adiposity and impaired glucose tolerance at weaning, with these effects persisting into adulthood in males. Maternal GDM reduced plasma CTRP6 levels in both sexes at weaning, but in adulthood, male GDM offspring maintained lower circulating CTRP6, while females on the chow diet showed elevated levels. Tissue-specific analysis revealed decreased CTRP6 expression in male interscapular brown adipose tissue (iBAT) and female visceral white adipose tissue (vWAT), accompanied by depot- and sex-specific changes in adiponectin signaling. Conclusions: Maternal GDM programs offspring's metabolic phenotype and adipose tissue CTRP6 expression in a sex- and depot-specific manner, suggesting CTRP6 may serve as an early, sex-biased indicator of the intergenerational transmission of metabolic disease risk.

Background: Cytokine oncostatin M (OSM) is implicated in inflammatory conditions. The plant sterol stigmasterol (ST) is found in diverse plant foods and exerts various benefits, such as antitumor, antioxidant, and anti-inflammatory effects. However, the inhibitory mechanism of ST on OSM production in neutrophils needs to be elucidated. Methods: To evaluate the modulatory effects of ST, this investigation employed neutrophil-like differentiated (d)HL-60 cells. ELISA, real-time PCR, Western blotting, and immunofluorescence staining were conducted. dHL-60 cells were pretreated with ST (0.02 to 2 µg/mL) for 1 h, and then stimulated with GM-CSF (5 ng/mL). Results: Our results showed that addition of granulocyte-macrophage colony-stimulating factor (GM-CSF) leads to up-regulation of OSM mRNA and protein in dHL-60 cells, while pretreatment with ST reduces OSM mRNA and protein levels. Mechanistically, the highest dose (2 µg/mL) of ST significantly decreased phosphorylation of phosphatidylinositol 3-kinase, protein kinase B (Akt), and nuclear factor-κB. Conclusions: Our findings suggest that the plant sterol ST shows potential and warrants in vivo validation on OSM regulation via suppressing PI3K/Akt/NF-κB Signaling Processes.

Background/Objectives: The triglyceride-to-High-density lipoprotein cholesterol (TG/HDL) ratio is an established marker of atherogenic dyslipidaemia and insulin resistance. Although its association with subclinical atherosclerosis has been reported, the relative contributions of long-term TG/HDL burden and visit-to-visit variability to carotid intima media thickness (CIMT) remain unclear. This study aimed to evaluate the differential associations of the longitudinal mean and temporal variability of the TG/HDL ratio with CIMT. Methods: This retrospective single-center observational cohort study included 260 adult patients with at least three years of longitudinal lipid measurements and a standardized carotid ultrasonography assessment. The longitudinal mean TG/HDL ratio and variability indices, including standard deviation, coefficient of variation, average real variability and variability independent of the mean, were calculated. CIMT was measured using B-mode ultrasonography. Associations were assessed using correlation analyses, multivariable linear regression, joint category analyses and stratified analyses according to statin therapy. Results: The longitudinal mean TG/HDL ratio was independently associated with increased CIMT after adjustment for traditional cardiovascular risk factors. In contrast, TG/HDL variability indices showed no independent association with CIMT and did not improve model performance beyond the mean TG/HDL ratio. Restricted cubic spline analysis demonstrated a significant non-linear association between TG/HDL mean and CIMT, suggesting a threshold-dependent relationship. Joint category analyses demonstrated higher CIMT values in groups with elevated TG/HDL mean regardless of variability status. A significant interaction was observed between TG/HDL variability and statin therapy (p for interaction = 0.011). Conclusions: These findings indicate that cumulative exposure to atherogenic dyslipidaemia, reflected by the long-term mean TG/HDL ratio, is more strongly associated with subclinical carotid atherosclerosis than short-term lipid fluctuations.

Background/Objectives: We have previously demonstrated that fatty acid oxidation (FAO) enzymes physically and functionally interact with electron transfer chain supercomplexes (ETC-SC) at two contact points. The FAO trifunctional protein (TFP) and electron transfer flavoprotein dehydrogenase (ETFDH) interact with the NADH⁺-binding domain of ETC complex I (com I) and the core 2 subunit of complex III (com III), respectively. In addition, the FAO enzyme very-long-chain acyl-CoA dehydrogenase (VLCAD) interacts with TFP. These interactions define a functional FAO-ETC macromolecular complex (FAO-ETC MEC) in which FAO-generated NADH⁺ and FADH₂ can safely transfer electron equivalents to ETC in order to generate ATP. Methods: In this study, we use multiple mitochondrial functional studies to demonstrate the effect of added VLCAD protein on mutant mitochondria. Results: We demonstrate that heart mitochondria from a VLCAD knockout (KO) mouse exhibit disrupted supercomplexes, with significantly reduced levels of TFPα and TFPβ subunits, electron transfer flavoprotein a-subunit (ETFα), and NDUFV2 subunit of com I in the FAO-ETC MEC. In addition, the activities of individual oxidative phosphorylation (OXPHOS) enzymes are decreased, as is the transfer of reducing equivalents from palmitoyl-CoA to ETC (FAO-ETC flux). However, the total amount of these proteins did not decrease in VLCAD KO animals. These results suggest that loss of VLCAD affects the interactions of FAO and ETC proteins in the FAO-ETC MEC. Reconstitution of VLCAD-deficient heart mitochondria with recombinant VLCAD improved the levels of FAO-ETC MEC proteins and enzyme activities, as well as restoring FAO-ETC flux. It also reduced mitochondrial ROS levels, previously demonstrated to be elevated in VLCAD-deficient mitochondria. In contrast, incubation of VLCAD KO mitochondria with two VLCADs with mutations in the C-terminal domain of the enzyme (A450P and L462P) did not restore FAO-ETC MECs. Conclusions: These results suggest that VLCAD is a necessary component of the FAO-ETC MEC and plays a major role in assembly of the macro-supercomplex. These studies provide evidence that both the level of enzyme and its structural confirmation are necessary to stabilize the FAO-ETC MEC.

Non-communicable diseases (NCDs) impose an overwhelming burden on global health systems. Prevailing healthcare for NCDs remains largely hospital-centered, episodic, and reactive, rendering them poorly suited to address the long-term, heterogeneous, and multifactorial nature of NCDs. Rapid advances in digital technologies, artificial intelligence (AI), and precision medicine have catalyzed the development of an integrative framework for digital-intelligent precision health management, characterized by the functional integration of data, models, and decision support. It is best understood as an integrated health management framework operating across three interdependent dimensions. First, it is grounded in multidimensional health-related phenotyping, enabled by continuous digital sensing, wearable and ambient devices, and multi-omics profiling, which together allow for comprehensive, longitudinal characterization of individual health states in real-world settings. Second, it leverages intelligent risk warning and early diagnosis, whereby multimodal data are fused using advanced machine learning algorithms to generate dynamic risk prediction, detect early pathological deviations, and refine disease stratification beyond conventional static models. Third, it culminates in health management under intelligent decision-making, integrating digital twins and AI health agents to support personalized intervention planning, virtual simulation, adaptive optimization, and closed-loop management across the disease continuum. Framed in this way, digital-intelligent precision health management enables a fundamental shift from passive care towards proactive, anticipatory, and individual-centered health management. This Perspectives article synthesizes recent literature from the past three years, critically examines translational and ethical challenges, and outlines future directions for embedding this framework within population health and healthcare systems.

Perioperative pain remains a major clinical challenge, with many surgical patients experiencing inadequate analgesia and progression to chronic postsurgical pain. Conventional opioid-centered strategies are limited by narrow therapeutic windows, systemic toxicity, tolerance, opioid-induced hyperalgesia, and poor efficacy in neuroimmune-driven pain states. Advances in molecular neuroscience and biomedical engineering have catalyzed the development of nonpharmacologic analgesic technologies that modulate pain pathways through biophysical rather than receptor-ligand mechanisms. This narrative review synthesizes emerging nonpharmacologic analgesic platforms relevant to anesthesiology, integrating molecular, cellular, and systems-level mechanisms with clinical evidence. It examines how peripheral sensitization, spinal dorsal horn plasticity, glial and neuroimmune activation, and supraspinal network dysfunction create ideal targets for device-based interventions. Electrical neuromodulation strategies, including peripheral and central techniques, are discussed alongside temperature-based, photonic, and focused-energy modalities. These include cryoneurolysis, radiofrequency techniques, photobiomodulation, and low-intensity focused ultrasound. Clinical integration within enhanced recovery pathways, patient selection, workflow considerations, and limitations of the current human evidence base are reviewed. While many of these technologies are established in chronic pain management, this review emphasizes available human perioperative data and discusses how chronic pain evidence informs perioperative translation within opioid-sparing multimodal anesthesia care. Collectively, these technologies support a mechanism-based, systems-level approach to pain modulation, with perioperative relevance varying by modality and strength of available human evidence.

Organoid culture represents a sophisticated biological model that surpasses traditional two-dimensional (2D) methods and animal models in physiological relevance and cost-effectiveness. Current organoid systems derive from adult, fetal, and induced pluripotent stem cells, providing innovative platforms for studying organ development, disease pathogenesis, and drug discovery. Recent technological advances now enable respiratory organoids to significantly contribute to respiratory disease research. This review comprehensively synthesizes the development of respiratory organoid models and their applications in studying major respiratory diseases, including pulmonary fibrosis, chronic obstructive pulmonary disease (COPD), and lung cancer. It further evaluates the transformative potential of these models in advancing respiratory disease research. Respiratory organoids uniquely model disease mechanisms and drug responses in human-specific microenvironments, enabling pathogenesis studies of respiratory diseases. They serve as functional platforms for drug screening and personalized therapy development. Future integration of multi-organoid systems with precision medicine promises to redefine respiratory disease research paradigms.

Alzheimer's disease (AD) involves a constellation of molecular processes that extend well beyond amyloid-β (Aβ) accumulation. Recent anti-amyloid antibodies provide limited clinical benefits, highlighting the need for additional strategies due to their modest efficacy and safety concerns. Increasing proteomic evidence reveals that proteins such as midkine (MDK), pleiotrophin (PTN) and clusterin (CLU) accumulate within amyloid plaques and may shape disease progression, although their precise contributions-protective, pathogenic, or both-remain unknown. In this Perspective, we examine how emerging targeted protein degradation (TPD) technologies, including Proteolysis-Targeting Chimeras (PROTACs), Lysosome-Targeting Chimeras (LYTACs) and molecular glues (MGs), could provide a means to selectively eliminate these co-aggregating proteins. We also discuss advances in degrader design, artificial intelligence (AI)-assisted screening, and strategies aimed at enhancing Central Nervous System (CNS) delivery. We finally outline how integrating TPD modalities with antibody-based and multi-target therapeutic approaches may promote more effective, systems-level interventions for AD.