RNA modifications constitute a crucial class of post-transcriptional chemical alterations that profoundly influence RNA stability and translational efficiency, thereby shaping cellular protein expression profiles. These diverse chemical marks are ubiquitously involved in key biological processes, including cell proliferation, differentiation, apoptosis, and metastatic potential, and they exert precise regulatory control over these functions. A major advance in the field is the recognition that RNA modifications do not act in isolation. Instead, they participate in complex, dynamic interactions—through synergistic enhancement, antagonism, competitive binding, and functional crosstalk—forming what is now termed the “RNA modification interactome” or “RNA modification interaction network.” The formation and functional operation of this interactome rely on a multilayered regulatory framework orchestrated by RNA-modifying enzymes—commonly referred to as “writers,” “erasers,” and “readers.” These enzymes exhibit hierarchical organization within signaling cascades, often functioning in upstream-downstream sequences and converging at critical regulatory nodes. Their integration is further mediated through shared regulatory elements or the assembly into multi-enzyme complexes. This intricate enzymatic network directly governs and shapes the interdependent relationships among various RNA modifications. This review systematically elucidates the molecular mechanisms underlying both direct and indirect interactions between RNA modifications. Building upon this foundation, we introduce novel quantitative assessment frameworks and predictive disease models designed to leverage these interaction patterns. Importantly, studies across multiple disease contexts have identified core downstream signaling axes driven by specific constellations of interacting RNA modifications. These findings not only deepen our understanding of how RNA modification crosstalk contributes to disease initiation and progression, but also highlight its translational potential. This potential is exemplified by the discovery of diagnostic biomarkers based on interaction signatures and the development of therapeutic strategies targeting pathogenic modification networks. Together, these insights provide a conceptual framework for understanding the dynamic and multidimensional regulatory roles of RNA modifications in cellular systems. In conclusion, the emerging concept of RNA modification crosstalk reveals the extraordinary complexity of post-transcriptional regulation and opens new research avenues. It offers critical insights into the central question of how RNA-modifying enzymes achieve substrate specificity—determining which nucleotides within specific RNA transcripts are selectively modified during defined developmental or pathological stages. Decoding these specificity determinants, shaped in large part by the modification interactome, is essential for fully understanding the biological and pathological significance of the epitranscriptome.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Tranexamic acid is widely used in joint orthopedic surgery.At the same time,it has high safety and few adverse drug reactions.It can effectively improve intraoperative bleeding and promote early functional recovery of patients.This article reviews the mode of administration,safe dose,administration time and adverse drug reactions of tranexamic acid in the perioperative period of joint replacement and arthroscopic surgery,in order to provide reference for the clinical application of tranexamic acid.

The aim of this study was to investigate and evaluate the antitumor effects of a novel poly(ADP-ribose) polymerase (PARP) 1/2 inhibitor, YHP-836, in combination with temozolomide (TMZ) for the treatment of glioblastoma (GBM). The cytotoxicity of YHP-836 was tested alone or in combination with TMZ using MTT assay. Immunoblotting and flow cytometry were also employed to assess the combination activity of YHP-836 and TMZ in multiply GBM cell lines. Further, the antitumor activity of YHP-836 and TMZ was evaluated using subcutaneous and orthotopic mice xenograft tumor models. All procedures were approved by the Ethics Committee for Animal Experiments of the Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College and conducted under the Guidelines for Animal Experiments of Peking Union Medical College. The approval number is 00009138. It was demonstrated that the combination of YHP-836 and TMZ increased the cytotoxicity against GBM cells and upregulated histone H2AX phosphorylation (γH2AX) expression levels compared to TMZ treatment alone. The combination also led to the S-phase cell cycle arrest. Moreover, YHP-836 significantly enhanced TMZ antitumor effects without significantly increasing chemotherapy drug toxicity in vivo, whereas YHP-836 alone showed limited therapeutic efficacy against GBM. In conclusion, the novel PARP1/2 inhibitor, YHP-836, sensitizes TMZ and provides a basis for further investigation into its mechanism of action. These findings suggest that YHP-836 may be a potential candidate for combination therapy with TMZ in patients with TMZ resistance.

italic>Lamiophlomis rotata is an important medicinal plant species endemic to the Tibetan Plateau, which is prone to strong climate change impacts on its habitable range due to the high sensitivity of the Tibetan Plateau to climate change. Accurate quantification of species vulnerability to climate change is essential for assessing species extinction risk and developing effective conservation strategies. Therefore, we carried out the α-shape analysis to determine the habitat of L. rotata. We then carried out the climate-niche factor analysis (CNFA) to assess the vulnerability of L. rotata to climate change based on five climate variables (i.e., mean diurnal range, temperature seasonality, mean temperature of warmest quarter, precipitation of driest month and precipitation of warmest quarter) in the context of two shared socioeconomic pathways (i.e., SSP126 and SSP585) and three global climate models (CMCC-ESM2: Centro Euro-Mediterraneo sui Cambiamenti Climatici-Earth System Model version 2; HadGEM3-GC31-LL: Hadley Global Environment Model version 3-Global Coupled configuration 3.1; IPSL-CM6A-LR: Institut Pierre Simon Laplace-Climate Model version 6) during two different periods (2041-2060 and 2081-2100). The vulnerability of L. rotata to climate change was calculated by integrating the sensitivity and exposure indices of L. rotata to five climate variables. The results showed that L. rotata had the highest vulnerability to the precipitation of warmest quarter. Its vulnerability within its habitat range generally showed a spatial pattern of high value in the southern region and low in the northern region, high in the western region and low in the eastern region. In general, the vulnerability of L. rotata under the SSP585 scenario was higher than that under the SSP126 scenario. The climate data of different global climate models have some influence on the results, while the resulted uncertainty can be reduced by data integration methods. As a result of climate change, the pressure on the survival of L. rotata in the future will be intensified in the low-altitude areas such as the Yarlung Zangbo River, Yigongzangbu River, Zayu River, and Jiaomuzu River, etc., while the highly weathered scree flats or stony alpine meadows in the high-altitude zones, such as the eastern Tanggula Mountain Range, the northern part of Hengduan Mountain Range, and the western part of the Qinling Mountains, may become its refuge. It is necessary to focus on and strengthen the protection and management of L. rotata resources in these vulnerble and critical areas.

AIM To simultaneously determine the contents of neochlorogenic acid,caffeic acid,chlorogenic acid,cryptochlorogenic acid,hydroxysafflor yellow A,ferulic acid,senkyunolide I,senkyunolide H and senkyunolide A in Fuyang Granules,and to make chemical pattern recognition.METHODS The UHPLC was performed on a 35℃thermostatic Waters Acquity UPLC?BEH C18 column(150 mm×2.1 mm,1.7 μm),with the mobile phase comprising of acetonitrile-0.01%phosphoric acid flowing at 0.4 mL/min in a gradient elution manner,and the detection wavelengths were set at 278,322,325,390 nm.Then heatmap clustering analysis and principal component analysis were adopted.RESULTS Nine constituents showed good linear relationships within their own ranges(r>0.999 0),whose average recoveries were 93.89%-102.25%with the RSDs of 0.85%-2.88%.Different batches of samples from the same enterprises demonstrated consistent overall qualities,while the overall qualities of samples from different enterprises exhibited obvious differences.CONCLUSION This simple and accurate method can be used for the quality control of Fuyang Granules.

AIM To investigate the variation rules of main secondary metabolites in Hedysari Radix before and after rubbing strip.METHODS UPLC-MS/MS was adopted in the content determination of formononetin,ononin,calycosin,calycosin-7-glucoside,medicarpin,genistein,luteolin,liquiritigenin,isoliquiritigenin,vanillic acid,ferulic acid,γ-aminobutyric acid,adenosine and betaine,after which cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were used for chemical pattern recognition to explore differential components.RESULTS After rubbing strip,formononetin,calycosin,liquiritigenin and γ-aminobutynic acid demonstrated increased contents,along with decreased contents of ononin,calycosin-7-glucoside and vanillic acid.The samples with and without rubbing strip were clustered into two types,calycosin-7-glucoside,formononetin,γ-aminobutynic acid,vanillic acid,calycosin-7-glucoside and formononetin were differential components.CONCLUSION This experiment clarifies the differences of chemical constituents in Hedysari Radix before and after rubbing strip,which can provide a reference for the research on rubbing strip mechanism of other medicinal materials.

Objective The volume and cortical thickness of gray matter in patients with multiple sclerosis (MS) and neuromyelitis optica (NMO) were compared and analyzed by voxel⁃based morphometry (VBM) and surface⁃based morphometry (SBM), and the differences in the structural changes of gray matter in the two diseases were discussed. Methods A total of 21 MS patients, 16 NMO patients and 19 healthy controls were scanned by routine MRI sequence. The data were processed and analyzed by VBM and SBM method based on the statistical parameter tool SPM12 of Matlab2014a platform and the small tool CAT12 under SPM12. Results Compared with the normal control group (NC), after Gaussian random field (GRF) correction, the gray matter volume in MS group was significantly reduced in left superior occipital, left cuneus, left calcarine, left precuneus, left postcentral, left central paracentral lobule, right cuneus, left middle frontal, left superior frontal and left superior medial frontal (P<0. 05). After family wise error (FWE) correction, the thickness of left paracentral, left superiorfrontal and left precuneus cortex in MS group was significantly reduced (P<0. 05). Compared with the NC group, after GRF correction, the gray matter volume in the left postcentral, left precentral, left inferior parietal, right precentral and right middle frontal in NMO group was significantly increased (P<0. 05). In NMO group, the volume of gray matter in left middle occipital, left superior occipital, left inferior temporal, right middle occipital, left superior frontal orbital, right middle cingulum, left anterior cingulum, right angular and left precuneus were significantly decreased (P<0. 05). Brain regions showed no significant differences in cortical thickness between NMO groups after FWE correction. Compared with the NMO group, after GRF correction, the gray matter volume in the right fusiform and right middle frontal in MS group was increased significantly(P<0. 05). In MS group, the gray matter volume of left thalamus, left pallidum, left precentral, left middle frontal, left middle temporal, right pallidum, left inferior parietal and right superior parietal were significantly decreased (P<0. 05). After FWE correction, the thickness of left inferiorparietal, left superiorparietal, left supramarginal, left paracentral, left superiorfrontal and left precuneus cortex in MS group decreased significantly (P<0. 05). Conclusion The atrophy of brain gray matter structure in MS patients mainly involves the left parietal region, while NMO patients are not sensitive to the change of brain gray matter structure. The significant difference in brain gray matter volume between MS patients and NMO patients is mainly located in the deep cerebral nucleus mass.

Objective To investigate the mechanism underlying the neuroprotective effect of linarin(LIN)against microglia activation-mediated inflammation and neuronal apoptosis following spinal cord injury(SCI).Methods Fifty C57BL/6J mice(8-10 weeks old)were randomized to receive sham operation,SCI and linarin treatment at 12.5,25,and 50 mg/kg following SCI(n=10).Locomotor function recovery of the SCI mice was assessed using the Basso Mouse Scale,inclined plane test,and footprint analysis,and spinal cord tissue damage and myelination were evaluated using HE and LFB staining.Nissl staining,immunofluorescence assay and Western blotting were used to observe surviving anterior horn motor neurons in injured spinal cord tissue.In cultured BV2 cells,the effects of linarin against lipopolysaccharide(LPS)-induced microglia activation,inflammatory factor release and signaling pathway changes were assessed with immunofluorescence staining,Western blotting,RT-qPCR,and ELISA.In a BV2 and HT22 cell co-culture system,Western blotting was performed to examine the effect of linarin against HT22 cell apoptosis mediated by LPS-induced microglia activation.Results Linarin treatment significantly improved locomotor function(P<0.05),reduced spinal cord damage area,increased spinal cord myelination,and increased the number of motor neurons in the anterior horn of the SCI mice(P<0.05).In both SCI mice and cultured BV2 cells,linarin effectively inhibited glial cell activation and suppressed the release of iNOS,COX-2,TNF-α,IL-6,and IL-1β,resulting also in reduced neuronal apoptosis in SCI mice(P<0.05).Western blotting suggested that linarin-induced microglial activation inhibition was mediated by inhibition of the TLR4/NF-κB signaling pathway.In the cell co-culture experiments,linarin treatment significantly decreased inflammation-mediated apoptosis of HT22 cells(P<0.05).Conclusion The neuroprotective effect of linarin is medicated by inhibition of microglia activation via suppressing the TLR4/NF-κB signaling pathway,which mitigates neural inflammation and reduce neuronal apoptosis to enhance motor function of the SCI mice.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.