BACKGROUND:Myocardial infarction can cause a massive loss of functional cardiomyocytes, yet effective strategies to stimulate cardiac regeneration remain lacking. A key barrier to adult cardiomyocyte proliferation appears to be cytokinesis inhibition. This study aimed to determine whether combining proliferation stimulators with the removal of cytokinesis-inhibitory constraints could unlock regenerative potential after myocardial infarction. METHODS:Transcriptomic profile from 5 regeneration models, including Aurkb-tdTomato cytokinesis reporter mice and Myh6-MerCreMer;mosaic analysis with double markers (MADM), and cross-species comparative analysis were used to explore the regulatory networks for cardiomyocyte proliferation. MADM mice were used to evaluate cardiac regeneration by quantifying after cytokinesis new cardiomyocytes and clonal clusters. RESULTS:Integrative multimodel analysis revealed a dual regulatory control system for cardiomyocyte proliferation, along with key associated genes and transcriptional regulators. Nfyb was identified as an activator and Nr3c1 as a repressor of cardiomyocyte proliferation. Nfyb overexpression enhanced cardiomyocyte proliferation and post-myocardial infarction cardiac repair through propelling cell-cycle gene transcription. Nr3c1 inhibition promoted cardiomyocyte proliferation, improved cardiac function, and reduced infarct size. A spatiotemporally controlled adeno-associated virus 9 system combining drug-inducible Nfyb overexpression and CRISPR/enOsCas12f1-mediated Nr3c1 deletion efficiently induces cardiomyocyte proliferation. Clonal analysis using MADM mice showed that the dual intervention synergistically increased new cardiomyocyte formation (28% clustered, >28-fold versus control). The enhanced regenerative effect of the dual intervention was demonstrated in post-myocardial infarction mice and human engineered heart tissues. CONCLUSIONS:This work documents a dual-control paradigm of cardiomyocyte proliferation and establishes Nfyb/Nr3c1 cointervention as a putative new therapy to induce and control cardiac regeneration after injury.

Objective This study aimed to develop and validate a machine learning model integrating multi-omics and radiomics data to improve diagnostic accuracy and identify potential biomarkers for Rheumatoid Arthritis-Associated Interstitial Lung Disease (RA-ILD). Methods A total of 278 patients with RA were enrolled across two cohorts. Cohort 1 (63 RA-nonILD, 46 RA-ILD) provided clinical data, chest CT images, plasma, and PBMC samples for non-targeted metabolomics, transcriptomics, and 4D DIA proteomics. Cohort 1 was split in a 6:4 ratio into training and validation sets. Machine-learning algorithms (RF, LASSO, SVM) and a Transformer model were used to screen biomarkers. Diagnostic models were constructed using LASSO, RF, LightGBM, and CatBoost. A combined imaging-clinical logistic regression model was developed and externally validated in cohort 2 (102 RA-nonILD, 67 RA-ILD). Associations between key biomarkers, inflammation, lung function, and CT severity were examined, and pathways related to the radiomic feature Kurtosis were explored. Results Nine radiomic features, five metabolites, two proteins, and eight genes were identified as key biomarkers. The metabolomics-based CatBoost model showed the best single-omics performance (AUC = 0.982). The multi-omics integration model outperformed all single-omics models. The imaging-clinical model demonstrated strong diagnostic accuracy in both internal (AUC = 0.963) and external validation (AUC = 0.913), and a nomogram was constructed for clinical risk assessment. Key biomarkers correlated with inflammatory indicators and lung-function decline, and high-Kurtosis-associated genes were enriched in pro-fibrotic pathways. Conclusion Integrating multi-omics and radiomics with machine learning yields a robust diagnostic strategy for RA-ILD. The imaging-clinical nomogram provides a practical tool for risk assessment, and identified biomarkers reflect disease severity and progression.

Lactate, a key byproduct of glycolysis in tumor cells, has emerged as more than just a metabolic waste product. Increasing evidence reveals that lactate and its associated post-translational modification (PTM), lactylation, play multifaceted roles in regulating various forms of regulated cell death (RCD), thereby contributing to cancer proliferation, therapy resistance, and immune exclusion. Notably, evasion of RCD is a hallmark of cancer and targeting RCD may represent a promising therapeutic strategy for cancer treatment. In this review, we focus on summarizing the dual and context-dependent roles of both lactate and lactylation in modulating distinct types of RCD, including apoptosis, autophagy, ferroptosis, pyroptosis, and cuproptosis. Moreover, we further discuss how RCD processes impact lactate metabolism and highlight the therapeutic potential and current challenges of targeting the lactate-lactylation-RCD axis in cancer treatment.

Cerebral ischemia-reperfusion (I/R) injury remains a major therapeutic challenge, primarily due to complex mechanisms involving oxidative stress and apoptosis. Growth arrest and DNA damage-inducible protein α (Gadd45α), a stress sensor linked to cellular stress responses, has been implicated in I/R injury, yet its precise role in ischemic stroke is incompletely understood. This study aimed to elucidate the function and underlying mechanisms of Gadd45α in cerebral I/R injury using both in vivo and in vitro models. In rats subjected to middle cerebral artery occlusion (MCAO) and in neurons exposed to oxygen-glucose deprivation/reperfusion (OGD/R), Gadd45α expression was significantly upregulated. Lentivirus-mediated knockdown of Gadd45α (sh-Gadd45α) reduced infarct volumes, improved neurological function and increased miniature excitatory postsynaptic current (mEPSC) amplitude. In primary cortical neurons exposed to OGD/R, Gadd45α knockdown decreased reactive oxygen species (ROS) production, DNA damage, and apoptosis, while Gadd45α overexpression exacerbated these effects. Mechanistically, Gadd45α directly interacts with forkhead box O1 (FOXO1) and positively regulates its transcriptional activity. Gadd45α knockdown attenuated the ischemia-induced upregulation of both total FOXO1 and its phosphorylated form (p-FOXO1), thereby suppressing FOXO1 signaling and mitigating cerebral I/R injury. Furthermore, FOXO1 overexpression reversed the neuroprotective effects of Gadd45α silencing, confirming that FOXO1 acts as a critical downstream mediator. These findings demonstrate that Gadd45α silencing alleviates cerebral I/R injury by suppressing FOXO1 signaling, suggesting the Gadd45α/FOXO1 axis as a promising therapeutic target for ischemic stroke.

Adaptive clinical trial designs increasingly aim to improve efficiency while accommodating subgroup heterogeneity, yet most existing methods fix assumptions about drug efficacy and subgroup effects. We propose a Bayesian adaptive design that explicitly models and learns from uncertainty in both components. A hierarchical mixture prior represents uncertainty about overall treatment efficacy and the magnitude of a biomarker-defined subgroup effect. Interim data are used to update these hyperparameters into posterior distributions, enabling a decision-theoretic framework that adaptively selects the optimal testing strategy among three options: continuing with the overall population, focusing on the subgroup, or conducting a joint test of both. When joint testing is chosen, the posterior information further determines the optimal allocation of Type I error between populations by selecting an evidence-based α-splitting parameter that maximizes expected power under error-rate constraints. The resulting optimization is solved efficiently using GPU-accelerated quasi-Monte Carlo integration and smooth search procedures. Simulation studies across a range of subgroup prevalences and effect sizes demonstrate that the proposed design maintains nominal error control, achieves superior power and decision accuracy, and adapts appropriately to prior misspecification. By unifying posterior learning and adaptive α-allocation within a principled Bayesian framework, this design provides a transparent and computationally practical tool for confirmatory clinical trials with uncertain subgroup effects, supporting precision-medicine decision-making and regulatory reproducibility.

Gut dysbiosis is tightly linked to type 2 diabetes (T2D) arterial calcification (AC), but the mechanism of gut dysbiosis remains poorly defined. Here, we found that a T2D AC associated-gut Bacteroides fragilis (BF) was activated by M1 macrophage-derived extracellular vesicles (EVs). BF internalized macrophage EVs via membrane protein OprM-Jup interaction. Upon uptake, Mef2d, which was rich in EVs, translocated to the BF nucleoid and suppressed ArsR family transcriptional regulator (ArsR) transcription and enhanced BF proliferation and trimethylamine N-oxide production in diabetic mice. Mechanistically, Mef2d suppressed the transcriptional activity of ArsR, an arsenic resistance regulator in BF. Overexpression of ArsR inhibited BF growth and trimethylamine synthesis, whereas ArsR knockdown exacerbated these phenotypes. Critically, ArsR overexpression abolished macrophage EV-driven BF activation. Our findings reveal a macrophage EV-BF signaling axis in which Mef2d-mediated ArsR suppression drives bacterial pathogenicity, offering a pharmacologically targetable axis for precision inhibitation of BF pathobiont virulence in diabetic complications.

Dose optimization is a hallmark of Project Optimus for oncology drug development. The number of doses to include in a dose optimization study depends on the totality of evidence, which is often unclear in early-phase development. With equal sample sizes per dose, carrying three doses is clearly more advantageous than two for optimization. In this paper, we show that, even when the total sample size is fixed, it is still preferable to carry three unless there is very strong evidence that one can be dropped. A mathematical approximation is applied to guide the investigation, followed by a simulation study to complement the theoretical findings. Semi-quantitative guidance is provided for practitioners, addressing both randomized and non-randomized dose optimization while considering population homogeneity.

Ufmylation is a newly identified ubiquitin-like modification of histones and plays important roles in DNA-related processes. Dissecting histone ufmylation pathways necessitates the use of chemically defined proteins to assign their structural and functional consequences; however, the preparation of ufmylated histones has not yet been reported. Here, we report the chemical synthesis of ufmylated histones and their analogs through semisynthetic strategies integrating chemoenzymatic C-terminal hydrazinolysis of ubiquitin-fold modifier 1 (UFM1) and auxiliary-mediated formation of an isopeptide bond. The results indicated that the E1-mediated activation of UFM1 can be hijacked by nucleophilic reagents, forming the full-length UFM1 hydrazide that can be readily installed onto histones via auxiliary-mediated ligations. The synthetic histones enabled us to reveal that the two known UFM1-specific proteases 1 and 2 (UfSP1 and UfSP2) cannot efficiently cleave H4 ufmylation at Lys31 (H4K31UFM1) in the nucleosome context. Furthermore, cryo-electron microscopy (cryo-EM) analysis of the H4K31UFM1-nucleosome suggested that the steric hindrance of the nucleosome around the isopeptide bond might be one of the potential reasons for the weak activities of UfSPs. Collectively, we developed practical strategies for the efficient generation of ufmylated histones and exemplified their use in biochemical and structural studies related to histone ufmylation.

Human umbilical cord mesenchymal stem cell extracellular vesicles (hucMSC-EVs) exhibit remarkable potential for alleviating type 2 diabetes mellitus (T2DM). However, the role of hucMSC-EVs in T2DM, particularly concerning oxidative damage to pancreatic β cells, remains underexplored. This study utilized a high-fat diet and streptozotocin (STZ)-induced T2DM mouse model and an STZ-induced INS-1 cell damage model to investigate the effects and mechanisms of hucMSC-EVs. In the T2DM mouse model, hucMSC-EVs effectively lowered blood glucose levels, improved lipid metabolism disorders, and preserved liver function. Moreover, hucMSC-EVs enhanced insulin sensitivity and mitigated oxidative damage. Histological analysis confirmed that hucMSC-EVs marked alleviated liver, kidney, and pancreatic tissue damage. In vitro studies demonstrate that hucMSC-EVs enhance glucose absorption and glycogen synthesis in an insulin-resistant HepG2 model and stimulated insulin secretion in INS-1 cells under high-glucose conditions. In the STZ-induced INS-1 oxidative damage model, hucMSC-EVs protect against oxidative damage by increasing antioxidant enzyme activities, reducing reactive oxygen species production, and decreasing cell apoptosis. The effects were partially mediated by the activation of the phosphatidylinositol 3-kinase (PI3K)/AKT and signal transducer and activator of transcription (STAT) signaling pathways, as well as the up-regulation of key antioxidant proteins such as Nrf2, SOD1, and Bcl2. Further research revealed that miR-191-5p, which is enriched in hucMSC-EVs, targets DAPK1 to activate the PI3K/AKT pathway, thereby contributing to the protective effects against oxidative damage. These findings highlight the critical role and underlying mechanisms of hucMSC-EVs in ameliorating metabolic dysfunction in T2DM, particularly the protective effects against oxidative damage, thus providing a novel strategy for the treatment of T2DM.

Response Evaluation Criteria in Solid Tumors (RECIST) is the primary tool for assessing tumor response in solid tumors. Immunotherapy elicits unique response patterns, and assessment of their contribution to overall survival (OS) is of interest. We evaluated tumor size changes (TSC) for association with OS, evaluated whether deeper response had greater association with OS than the 30

Waterfall plots are a key tool in early phase oncology clinical studies for visualizing individual patients' tumor size changes and provide efficacy assessment. However, comparing waterfall plots from ongoing studies with limited follow-up to those from completed studies with long follow-up is challenging due to underestimation of tumor response in ongoing patients. To address this, we propose a novel adjustment method that projects the waterfall plot of an ongoing study to approximate its appearance with sufficient follow-up. Recognizing that waterfall plots are simply rotated survival functions of best tumor size reduction from the baseline (in percentage), we frame the problem in a survival analysis context and adjust weight of each ongoing patients in an interim look Kaplan-Meier curve by leveraging the probability of potential tumor response improvement (i.e., "censoring"). The probability of improvement is quantified through an incomplete multinomial model to estimate the best tumor size change occurrence at each scan time. The adjusted waterfall plots of experimental treatments from ongoing studies are suitable for comparison with historical controls from completed studies, without requiring individual-level data of those controls. A real-data example demonstrates the utility of this method for robust efficacy evaluations.

FK506 binding proteins (FKBPs) are highly conserved members of the immunophilin family, playing crucial roles in inflammation, immune responses, tumor biology, and developmental signaling pathway. Among these, FK506-binding protein 12 (FKBP12) is the smallest and is renowned for its direct binding to tacrolimus (FK506) and sirolimus (rapamycin). FKBP12 is well-established in mediating drug-protein interactions, neurodegenerative diseases, immune-related processes, and inflammatory signaling pathways. Although accumulating evidence suggests that FKBP12 is associated with numerous tumor-related signaling pathways, its precise role in cancer remains unclear. In this review, we provide a comprehensive overview of the biology and functions of FKBP12, with a particular focus on its mechanisms in malignancies, emphasizing its dual role in oncogenesis. A thorough understanding of this paradox is essential for the development of targeted therapies. We also highlight the clinical applications of FKBP12 in oncology, including its therapeutic potential, diagnostic, and prognostic significance, particularly in relation to its dual role. Finally, we address the contradictory functions of FKBP12 in various cancers and attempt to elucidate the underlying reasons. We also explore the relationship between FKBP12 and tumor microenvironment, aiming to shed new light on the potential role of FKBP12 as a novel immunotherapy target in cancer. We believe this review will be helpful to create second-generation drugs targeting FKBP12 with higher selectivity and fewer complications in the future.

FDA's Project Optimus initiative for oncology drug development emphasizes selecting a dose that optimizes both efficacy and safety. When an inferentially adaptive Phase 2/3 design with dose selection is implemented to comply with the initiative, the conventional inverse normal combination test is commonly used for Type I error control. However, indiscriminate application of this overly conservative test can lead to substantial increase in sample size and timeline delays, which undermines the appeal of the adaptive approach. This, in turn, frustrates drug developers regarding Project Optimus. The inflation of Type I error depends on the probability of selecting a dose with better long-term efficacy outcome at end of the study based on limited follow-up data at dose selection. In this paper, we discuss the estimation of this probability and its impact on Type I error control in realistic settings. Incorporating it explicitly into the two methods we have proposed result in improved designs, potentially motivating drug developers to adhere more closely to an initiative that has the potential to revolutionize oncology drug development.

The MTD has historically been the recommended phase II dose, and this dosage has typically been evaluated in registrational clinical trials for oncology drugs. With the emergence of targeted therapies, this approach may lead to the investigation of unnecessarily high dosages that elicit additional toxicity without added benefit. The utilization of innovative trial designs and model-informed approaches during clinical development can potentially lead to more informed dosage selection. Exposure-response analyses, clinical utility index, and other model-informed approaches have been successfully applied to understand preliminary activity and safety data for various classes of modern oncology drugs, providing insights to support the proposed dosage(s) for the registrational trial. Seamless trial designs have also played an important role in dosage selection by leveraging preplanned flexibilities and statistical procedures to increase efficiency during the conduct of trials. Critically, both approaches can be fit for purpose, allowing for adaptation and the usage of the totality of relevant clinical and nonclinical data. Despite this, the evaluation of MTD remains prevalent in registrational trials. This article, the third in a series of three describing best-practice approaches to dosage optimization in oncology drug development, highlights successful applications of and relevant considerations for innovative trial designs and model-based approaches to aid the selection of better optimized dosages for evaluation in registrational clinical trials.

Aims: To explore the potential functions and impacts of anoikis-related genes (ARGs) in breast cancer chemotherapy and to construct a prognosis model for HER2-negative breast cancer (HNBC) based on drug resistance-related ARGs. Background: Breast cancer remains a leading cause of cancer-related mortality, with HER2-negative subtypes exhibiting high rates of metastasis and recurrence. Standard treatments for HNBC include taxane- and anthracycline-based chemotherapies, which aim to mitigate recurrence and metastasis. Anoikis, a specialized form of programmed cell death, plays a pivotal role in maintaining tissue homeostasis by eliminating detached cells. Cancer cells often develop resistance to anoikis, enabling survival in adverse conditions and promoting tumor progression. Objective: To investigate the intersection of breast cancer drug resistance-related genes and anoikis-related genes (ARGs) and to assess their potential as biomarkers for HNBC. The study also aims to analyze differences in immune microenvironment and drug sensitivity among different prognosis score groups. Method: A bioinformatics approach was employed to identify the intersection of breast cancer drug resistance-related genes and ARGs. A prognosis model for HNBC was developed based on these identified drug resistance-related ARGs. The study further examined differences in the immune microenvironment and drug sensitivity among different prognosis score groups. Result: A prognosis model for HNBC was successfully constructed based on drug resistance-related ARGs. The study identified significant differences in immune microenvironment and drug sensitivity across different prognosis score groups. Conclusion: The findings suggest that ARGs could be key in tailoring more effective therapeutic approaches for patients with HER2-negative breast cancer.

Elevated levels of asparagine, catalyzed by asparagine synthetase (ASNS), have been identified as a prerequisite for lung metastasis in breast cancer. However, the roles and regulatory mechanisms of ASNS in breast cancer brain metastasis (BCBM) are not well understood. Our study revealed that the family with sequence similarity 50 member A (FAM50A) gene substantially modulates the brain metastatic potential of breast cancer by up-regulating ASNS and promoting asparagine biosynthesis. We demonstrated that FAM50A forms a complex with chromosome 9 open reading frame 78 (C9ORF78), specifically at the S121 residue, to enhance ASNS transcription. This interaction accelerates the rate of ASNS-mediated asparagine synthesis, which is essential in facilitating metastatic cascades to the brain. From a therapeutic perspective, both the genetic suppression of FAM50A and pharmacological inhibition of asparagine synthesis effectively counteract BCBM. Our results highlight the importance of the FAM50A-ASNS signaling pathway in BCBM therapy.

Glioblastoma (GBM), the most aggressive primary brain tumor, is shaped by its integration into neural networks. While glutamatergic input is linked to tumor progression, the broader architecture and function of neuron-glioma connectomes remain unclear. Using monosynaptic rabies tracing, we map brain-wide neural input to patient-derived xenografts and reveal a consistent organizational logic: local inputs are primarily glutamatergic, while long-range connections exhibit diverse neurotransmitter profiles, with basal forebrain cholinergic projections emerging as a conserved input across sites. Functionally, presynaptic acetylcholine release promotes GBM progression through muscarinic receptor CHRM3 in a circuit-specific manner. Mechanistically, glutamatergic and cholinergic signals converge to enhance glioma calcium transients but diverge in temporal transcriptional control, with their dual blockade producing additive anti-tumor effects. Therapeutically, the anticholinergic drug scopolamine attenuates glioma growth, whereas the acetylcholinesterase inhibitor donepezil exacerbates disease. These findings reveal the complexity of neuron-glioma connectivity, highlighting long-range neuromodulatory pathways as promising therapeutic targets in GBM.

In recent years, lactylation, a novel post-translational modification, has demonstrated a unique role in bridging cellular metabolism and epigenetic regulation. This modification exerts a dual-edged effect in both cancer and non-cancer diseases by dynamically integrating the supply of metabolic substrates and the activity of modifying enzymes: on one hand, it promotes tissue homeostasis and repair through the activation of repair genes; on the other, it exacerbates pathological progression by driving malignant phenotypes. In the field of oncology, lactylation regulates key processes such as metabolic reprogramming, immune evasion, and therapeutic resistance, thereby shaping the heterogeneity of the tumor microenvironment. In non-cancerous diseases, including neurodegeneration and cardiovascular disorders, its aberrant activation can lead to mitochondrial dysfunction, fibrosis, and chronic inflammation. Existing studies have revealed a dynamic regulatory network formed by the cooperation of modifying and demodifying enzymes, and have identified mechanisms such as subcellular localization and RNA metabolism intervention that influence disease progression. Nevertheless, several challenges remain in the field. This article comprehensively summarizes the disease-specific regulatory mechanisms of lactylation, with the aim of providing a theoretical foundation for its targeted therapeutic application.

Ubiquitin (Ub), a central regulator of protein turnover, can be phosphorylated by PINK1 (PTEN-induced putative kinase 1) to generate S65-phosphorylated ubiquitin (pUb). Elevated pUb levels have been observed in aged human brains and in Parkinson’s disease, but the mechanistic link between pUb elevation and neurodegeneration remains unclear. Here, we demonstrate that pUb elevation is a common feature under neurodegenerative conditions, including Alzheimer’s disease, aging, and ischemic injury. We show that impaired proteasomal activity leads to the accumulation of sPINK1, the cytosolic form of PINK1 that is normally proteasome-degraded rapidly. This accumulation increases ubiquitin phosphorylation, which then inhibits ubiquitin-dependent proteasomal activity by interfering with both ubiquitin chain elongation and proteasome-substrate interactions. Specific expression of sPINK1 in mouse hippocampal neurons induced progressive pUb accumulation, accompanied by protein aggregation, proteostasis disruption, neuronal injury, neuroinflammation, and cognitive decline. Conversely, Pink1 knockout mitigated protein aggregation in both mouse brains and HEK293 cells. Furthermore, the detrimental effects of sPINK1 could be counteracted by co-expressing Ub/S65A phospho-null mutant but exacerbated by over-expressing Ub/S65E phospho-mimic mutant. Together, these findings reveal that pUb elevation, triggered by reduced proteasomal activity, inhibits proteasomal activity and forms a feedforward loop that drives progressive neurodegeneration.

BACKGROUND:Migraine is a prevalent neurological disorder accompanied by a considerable economic burden. Xiongshao Zhitong granules (XSZT) have anti-inflammatory and analgesic functions in the clinic and are used for migraine therapy. However, the mechanisms by which XSZT treats migraine remain unclear. PURPOSE:To discover the underlying mechanism and active ingredients of XSZT in the treatment of migraine. METHODS:The nitroglycerin (NTG)-induced chronic migraine (CM) model was established and used to detect the therapeutic effect of XSZT on migraine. To elucidate the mechanism, we detected transient receptor potential vanilloid 1 (TRPV1) -mediated NOD-like receptor protein 3 (NLRP3) inflammasome activation in the CM rat model and the LPS-induced inflammatory BV-2 cell model using Western blotting, immunofluorescence and ELISA techniques. The potentially active ingredients of XSZT were determined by UHPLC-LTQ-Orbitrap MS, molecular docking, and surface plasmon resonance. RESULTS:Our findings revealed that XSZT reduced the number of head scratching, increased the periorbital pain threshold and shortened the time spent in the dark box, decreased c-Fos expression in the CM rat model, suggesting an analgesic effect of XSZT on migraine. XSZT inhibited neurogenic inflammation, including downregulating CGRP, TNF-α, IL-1β and IL-18 levels and decreasing the degranulation rate of mast cells. Additionally, XSZT suppressed the expression and activation of TRPV1 and the NLRP3 inflammasome in the trigeminal nucleus caudalis. In vitro experiments confirmed that activated TRPV1 increased the level of the NLRP3 inflammasome by increasing intracellular calcium levels. Galloylpaeoniflorin, isogastrin, ellagic acid and salvianolic acid A interacted with TRPV1 and inhibited IL-1β secretion. CONCLUSION:XSZT plays a therapeutic role in migraine through regulating TRPV1-mediated NLRP3 inflammatory activation and galloylpaeoniflorin, isogastrin, ellagic acid and salvianolic acid A might be the active ingredients of XSZT, which provides an experimental basis for the clinical treatment of migraine.