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.

Aim To evaluate the hypolipidemic effect of the total phenylpropanoid glycosides extracted from Ligustrum robustum (Roxb.) Blume (LRTPG) on hyperlipidemic golden hamsters and explore its regulatory effect on intestinal flora. Methods Sixty hamsters were randomly divided into a control group, a model group, a positive drug group, LRTPG-L group, LRTPG-M group, and LRTPG-H group. After the successful induction of the model by high-fat diet, the animals were continuously administered for four weeks, and their blood lipids and liver lipids were detected. The formed feces from the colorectal region of the hamsters in the control group, model group and LRTPG-H group were collected for 16S rDNA sequencing. Results LRTPG reduced serum TG, TC, LDL-C and liver TG, TC concentrations significantly in hyperlipidemic hamsters. The results of the intestinal microbiota sequencing showed that compared to the control group, LRTPG significantly decreased the relative abundance of the phylum Firmicutes and increased the relative abundance of the phylum Bacteroidetes and Verrucomicrobia (P < 0.01) at the phylum level. At the family level, LRTPG significantly increased the relative abundance of Christensenellaceae, Peptococcaceae, and Verrucomicrobiaceae (P < 0.05 or P < 0.01). At the genus level, LRTPG significantly increased the relative abundance of Oscillospira, Oscillibacter, Flavonifractor and Akkermansiaceae (P < 0.05 or P < 0.01). These changes in the flora were beneficial to the hypolipidemic effect of LRTPG. Conclusion LRTPG may exert its hypolipidemic effect by improving the intestinal flora disorder caused by a high-fat diet in golden hamsters.

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.

italic>Schisandra chinensis is a traditional Chinese medicine with the functions of reinforcing deficiency, strengthening, and inducing astringency, appliable to treat the chronic cough and deficiency in breath, palpitation, and insomnia, etc. A hybrid mass spectrometry scanning strategy (high-definition data-independent/data-dependent acquisition, HDDIDDA), enabling the ion mobility separation and alternating data-independent acquisition/data-dependent acquisition, was established, which, in combination with in-house library-driven automatic peak annotation workflows facilitated by the UNIFI software, was utilized to systematically characterize the multi-classes of chemical components from S. chinensis. The use of an HSS T3 column (100 mm × 2.1 mm, 1.8 μm), 0.1% formic acid in H₂O-acetonitrile as the mobile phase running at the flow rate of 0.3 mL·min^-1, and column temperature at 35 ℃, could enable good separation of the S. chinensis components within 42 min. HDDIDDA scan in both the positive and negative ion modes was employed for data acquisition. Based on the automatic peak annotation, reference standards comparison, MS² data interpretation, and literature analysis, we were able to identify or tentatively characterize 105 compounds in the S. chinensis decoction, involving 56 terpenoids, 42 lignans, five glycosides, one organic acid, and one flavonoid. HDDIDDA scanning can improve the coverage of data acquisition and improve the accuracy of identification, while CCS prediction analysis provides the possibility to distinguish isomers by the ion mobility technology. The results provide reference for the intelligent material basis research of TCM.

Six compounds were isolated from the roots of Ephedra sinica Stapf using various chromatographic techniques such as silica gel column chromatography, thin layer chromatography and semi-preparative HPLC. Their chemical structures were identified by analysis of physicochemical properties and spectral data, and determined as (Z)-docosanylferulate (1), (E)-docosanylferulate (2), bis (2-ethylheptyl) phythalate (3), 2,2′-oxybis (1,4-di-tert-butylbenzene) (4), diisobutyl phthalate (5), bis (2-ethylhexyl) phthalate (6). Among them, compound 1 is a new compound, compounds 2-4 were first isolated from Ephedra. A corticosterone-induced PC-12 cell injury model was used for compound activity screening. The results showed that compounds 1 and 5 significantly improved corticosterone-induced PC-12 cell injury and significantly increased 5-HT₇ receptor protein expression in the cells, indicating potential antidepressant activity.

Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6％),Mycobacterium tuberculosis 249(20.0％),other bacteria 150(12.0％),fungi 68(5.5％),parasites 18(1.4％),Treponema pallidum 18(1.4％)and rickettsia 1(0.1％).The number of cases increased by 177 cases(33.1％)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ￥29,500(￥16,000,￥59,200).The mortality rate from CNS infectious diseases is 1.6％.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.

ObjectiveThe purpose of this study was to investigate the effects of transcutaneous electrical acupoint stimulation (TEAS) on cognitive function of vascular dementia (VD) rats and its mechanism. MethodsVD rat model was established by modified two-vessel occlusion (2-VO). After modeling, TEAS and electroacupuncture (EA) were used to stimulate Baihui and Zusanli points of rats respectively for 14 d. After treatment, novel object recognition test, Morris water maze test, and Y maze test were used to evaluate the spatial memory and learning ability of rats. Hematoxylin and eosin staining was used to observe the morphology of hippocampal neurons. Transmission electron microscopy was used to observe the ultrastructure of hippocampal mitochondria. Enzyme-linked immunosorbent assay kits were used to detected the levels of SOD, CAT, GSH-Px, MDA and ROS in serum of rats. Western blot was used to detect the expression of PGC-1α, TFAM, HO-1, NQO1 proteins in the hippocampus, Keap1 protein in the cytoplasm and Nrf2, NRF1 proteins in the nucleus. ResultsAfter treatment for 14 d, compared to the model group, the escape latency of VD rats decreased, while the discrimination index, the times of rats crossing the original platform area, the residence time in the original platform quadrant, and the percentage of alternation increased. TEAS can improve the structure of hippocampal neurons and mitochondria of VD rats, showing that neurons were arranged more regularly and distributed more evenly, nuclear membrane and nucleoli were clearer, and mitochondrial swelling were reduced, mitochondrial matrix density were increased, and mitochondrial cristae were more obvious. The levels of SOD, GSH-Px and CAT in serum increased significantly, while the concentration of MDA and ROS decreased. TEAS also up-regulated the expression levels of PGC-1α TFAM, NQO1 and HO-1 proteins in the hippocampus and Nrf2, NRF1 proteins in the nucleus, but down-regulated the Keap1 protein in the cytoplasm. ConclusionTEAS can improve cognition, hippocampal neurons and mitochondrial structure of VD rats, and the effect is better than EA. The mechanism may be the activation of PGC-1α mediated mitochondrial biogenesis and antioxidant stress, which also provides a potential therapeutic technology and experimental basis for the treatment of VD.

ObjectiveThe human angiotensin converting enzyme2 （hACE2） transgenic mouse model was used to clarify the antiviral efficacy of BD-77 against a novel coronavirus SARS-CoV-2 and explore the action mechanism of BD-77 against SARS-CoV-2. MethodSARS-CoV-2 Omicron and Delta variant strains-infected VeroE6 cell models were established and administered with BD-77 to observe the antiviral effect of BD-77 in vitro. A kit was used to detect the effect of BD-77 in vitro on the binding of spike S protein of SARS-CoV-2 virus （Delta/Omicron） to angiotensin converting enzyme2 （ACE2）. Chromatography was adopted to detect the binding of BD-77 to the S protein and N protein of the novel coronavirus. hACE2 transgenic C57BL/6 mice were divided into a blank control group， SARS-CoV-2 infection group， BD-77 administration groups of 37.5 mg·kg^-1 and 75 mg·kg^-1， with eight mice in each group. The pneumonia model of SARS-CoV-2-infected hACE2 transgenic mice was built to observe the survival of the mice， detect the virus titer of the lung tissue of the mice， and observe the lesions in the lung tissue. ResultBD-77 had a certain inhibitory effect on Omicron and Delta variant strains in vitro， with median inhibitory concentration （IC₅₀） of 526.3 mg·L^-1 and 653.0 mg·L^-1， respectively. BD-77 had no significant inhibitory effect on the binding of the S protein of WT， Omicron， and Delta variant strains of SARS-CoV-2 to ACE2 and had no binding effect with the S protein and N protein of the novel coronavirus. No mice in the blank group died， while the mortality rate of SARS-CoV-2-infected mice was 75%. There was a large amount of virus replication in the lung tissue of the mice and large areas of inflammatory infiltration in the lung tissue and interstitium. Compared with the model group， BD-77 administration groups of 37.5 mg·kg^-1 and 75 mg·kg^-1 could reduce the mortality of mice， significantly lower the virus titer in the lung tissue of mice （P<0.05）， and improve lung lesions. ConclusionBD-77 demonstrated significant inhibitory effects against SARS-CoV-2 virus in vitro and in vivo. However， its mechanism of action did not involve direct inhibition of the virus itself or intervention in the virus-host binding process. This finding suggests that the mechanism of action of BD-77 needs to be thoroughly investigated and elucidated by further experiments.

Tuberous sclerosis complex(TSC)is a rare genetic disease that can lead to benign dysplasia in multiple organs such as the skin, brain, eyes, oral cavity, heart, lungs, kidneys, liver, and bones. Its main symptoms include epilepsy, intellectual disabilities, skin depigmentation, and facial angiofibromas, whilst incidence is approximately 1 in 10 000 to 1 in 6000 newborns. This case presents a middle-aged woman who initially manifested with epilepsy and nodular depigmentation. Later, she developed a lower abdominal mass, elevated creatinine, and severe anemia. Based on clinical features and whole exome sequencing, the primary diagnosis was confirmed as TSC. Laboratory and imaging examinations revealed that the lower abdominal mass originated from the uterus. CT-guided biopsy pathology and surgical pathology suggested a combination of leiomyoma and abscess. With the involvement of multiple organs and various complications beyond the main diagnosis, the diagnostic and therapeutic process for this patient highlights the importance of rigorous clinical thinking and multidisciplinary collaboration in the diagnosis and treatment of rare and challenging diseases.