ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

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.

Objective To study the bioequivalence and safety of two olmesartan medoxomil and hydrochlorothiazide tablets in Chinese healthy subjects.Methods A total of 24 healthy subjects underwent fasting and postprandial tests in a single-center,randomized,open-label,single-dose,two-formulation,two-sequence,two-period,self-cross-over controlled design.The subjects were administered a single oral dose of the test formulation and reference formulation(each containingolmesartan medoxomil 20 mg and hydrochlorothiazide 12.5 mg)in a random cross-over fashion.The plasma concentrations of olmesartan and hydrochlorothiazide were determined by LC-MS/MS.The non-compartmental model analysis of olmesartan and hydrochlorothiazide was conducted using WinNonlin 7.0 software to calculate pharmacokinetic parameters and assess bioequivalence.Results In the fasting test,the pharmacokinetic parameters of olmesartan of test and reference were as follows:Cmax were(798.35±206.78)and(664.52±168.25)ng·mL-1,AUC0-t were(4 430.71±1 294.87)and(3 976.67±1 083.54)h·ng·mL-1,AUC0-∞ were(4 551.67±1 303.06)and(4 090.37±1 103.97)h·ng·mL-1.The pharmacokinetic parameters of hydrochlorothiazide of test and reference were as follows:Cmax were(92.39±35.96)and(96.15±38.76)ng·mL-1,AUC0_t were(548.69±217.11)and(564.41±208.68)h·ng·mL-1,AUC0-∞ were(603.04±228.59)and(619.26±223.27)h·ng·mL-1.In the fed test,the pharmacokinetic parameters of olmesartan of T and R were as follows:Cmax were(583.15±149.48)and(550.57±104.76)ng·mL-1,AUC0-t were(3 585.18±952.72)and(3 292.19±904.58)h·ng·mL-1,AUC0-∞ were(3 696.05±996.55)and(3 396.30±923.41)h·ng·mL-1.The pharmacokinetic parameters of hydrochlorothiazide of test and reference were as follows:Cmax were(70.30±17.88)and(74.70±21.65)ng·mL-1,AUC0-t were(476.60±119.39)and(492.91±144.81)h·ng·mL-1,AUC0-∞ were(523.37±132.67)and(535.81±151.92)h·ng·mL-1.In fasting and fed condition,the 90％confidence interval(90％CI)of Cmax,AUC0-t and AUC0-∞ of olmesartan and hydrochlorothiazide were in 80.00％-125.00％.Conclusion The two olmesartan medoxomil and hydrochlorothiazide tablets were bioequivalent under fasting and fed conditions,and good security.

Objective To explore the role of 4-hydroxynonenal(HNE)in alleviating acute lung injury(ALI)induced by neonatal sepsis by inhibiting the focal death of endothelial cells(ECs).Methods Newborn mice were randomly divided into five groups:(1)Sham operation group(Sham group),(2)sham operation mice receiving HNE treatment group(Sham + HNE group),(3)cecal serosity(CS group),and(4)CS-treated GS-DMD-/-mice group(CS + GSDMD-/-group).The degree of lung injury was evaluated by lung histopathology and lung wet/dry weight ratio.The ECs of mice were isolated and divided into the Ctrl group,LPS + ATP group,LPS + ATP + HNE-L group and LPS + ATP + HNE-H group.Western blot was used to evaluate the expression of HNE and caspase-1 pathway.Results Compared with CS group,the lung tissue scores of CS + HNE group and CS + GSDMD-/-group were significantly decreased(P<0.05),and the ratio of wet to dry weight of lung tissues was significantly decreased(P<0.05).Compared with the CS group,the 72-hour survival rates of mice in the CS + HNE group and CS + GSDMD-/-group were significantly improved(P<0.05).The expressions of GSDMD-N,C-caspase-1,NLRP3,IL-18 and IL-1β in lung ECs of the CS + HNE group and CS + GSDMD-/-group were signifi-cantly lower than those of the CS group(P<005).Compared with the Ctrl cells,LPS + ATP significantly decreased the cell viability(P<0.05)and increased the protein expressions of GSDMD,C-caspase-1,NLRP3,IL-18 and IL-1β(P<0.05),and these effects were also inhibited by HNE.Conclusion HNE can inhibit the focal death of lung ECs cells by inhibiting NLRP3/caspase-1 signal transduction,and improve ALI in septic mice.

A precursor ion selection (PIS) based ultra high performance liquid chromatography-quadrupole time of flight mass spectrometry (UHPLC-Q-TOF-MS) analytical method was used to screen the chemical components in Jiawei Dingzhi pills (JWDZP) comprehensively and rapidly. To compile the components of the compound medicine, a total of 1 921 components were found utilizing online databases and literature. After verifying the sources, unifying the component names, merging the multi-flavor attributed components, and removing the weak polar molecules, 450 components were successfully retained. The Acquity UPLC HSS T3 column (100 mm × 2.1 mm, 1.8 μm) was used, with a 0.1% formic acid water (A)-acetonitrile (B) as the mobile phase. The flow rate was 0.35 mL·min^-1, the column temperature was 35 ℃, and an electrospray ion source was used. Data was collected with the PIS strategy in both positive and negative ion modes. Compounds were screened through matching accurate molecular weight of the database, and identified according to MS/MS data (characteristic fragment ions and neutral loss), with comparison of reference. Some compounds were confirmed using standard products. A total of 176 compounds were screened out in the extract of JWDZP, among which 26 compounds were confirmed by standard products. These compounds include 96 components from the sovereign drug, and 34 coefflux components with low ion intensity. The PIS-UHPLC-Q-TOF-MS/MS method established in this study can quickly and comprehensively screen the chemical components of JWDZP, which enhanced the screening rate of components with co-elution compounds of low ion intensities and provided a basis for the study of the material foundation of JWDZP.

"MS/MS spectrum to structure"plays a critical role in the confirmative identification of complicated matrices and is currently regarded as an extremely challenging endeavor.MS/MS information provides vital clues to structural identification.In this study,a strategy was proposed to facilitate unambiguous identification through matching MS3 with MS2 spectra.Initially,MS3 spectra of the featured ions(c-and y-type ions)generated by the decomposition of ester functional group in esters and the MS2 spectrum of the structural unit([M-H]-)were all captured on the Qtrap-MS platform equipped with two tandem-in-space collision cells,including the second quadrupole cell(q2)and linear ion trap(LIT)chambers(actually the third quadrupole unit).Subsequently,the MS/MS spectrum matching between MS3 spectra of the ester compound and MS2 spectra of the structural unit(s)were achieved.As a result,the findings corresponding to MS3 and MS2 spectra matching were summarized.Finally,based on HR-MS/MS information of total salvianolic acid derivatives(TSA),36 kinds of compounds were preliminarily identified through matching with literature information and database retrieval.The applicability of MS3 and MS2 spectra matching strategy was further justified by the confirmative identification of phenolic acid compounds(Rosmarinic acid and salvianolic acid B)in TSA.Above all,MS3 and MS2 spectra matching strategy was quite meaningful towards advancing"MS/MS spectrum to structure"analysis through recognizing and identifying featured fragment ions,and also provided inspiration and new insights for the structural characterization.

Objective To investigate the efficacy of Fuzheng Hejie Prescription(composed of Scutellariae Radix,Lonicerae Japonicae Flos,Agastachis Herba,Bupleuri Radix,Atractylodis Rhizoma,Glycyrrhizae Radix et Rhizoma,etc.)in the treatment of respiratory viral infections in children and to observe its effect on inflammatory factors and immune function.Methods A total of 203 children with respiratory viral infection of H1N1 virus were randomly divided into 101 cases in the observation group and 102 cases in the control group.Both groups were given the routine treatment for subsiding fever,maintaining water-electrolyte balance,and ensuring enough sleep.And additionally,the control group was given Ribavirin Granules and Ibuprofen Granules,and the observation group was given Fuzheng Hejie Prescription based on the treatment for the control group.The course of treatment covered 7 days.The changes of traditional Chinese medicine(TCM)syndrome scores and the levels of immunological indicators and inflammatory factors in the two groups were observed before and after the treatment.Moreover,the clinical efficacy,symptom resolution time and the incidence of adverse reactions were compared between the two groups of children.Results(1)In the course of the trial,one case fell off in the observation group and 2 cases fell off in the control group,and eventually 100 children in each group were included in the trial.(2)After 7 days of treatment,the total effective rate of the observation group was 93.00%(93/100),and that of the control group was 88.00%(88/100),and the intergroup comparison showed that the therapeutic effect of the observation group was superior to that of the control group,but the difference was not statistically significant(χ2= 1.454,P = 0.228).(3)After treatment,the scores of primary symptoms and secondary symptoms as well as the total TCM syndrome scores in the two groups were decreased compared with those before treatment(P＜0.05),and the decrease in the observation group was significantly superior to that in the control group(P＜0.01).(4)After treatment,the time for the resolution of clinical symptoms such as fever,cough,expectoration and sore throat in the observation group was significantly shorter than that in the control group(P＜0.01).(5)After treatment,the levels of immunological indicators of T lymphocyte subset CD3+ and CD4+ in the two groups were increased compared with those before treatment(P＜0.05),and the levels of CD8+ and B cells were decreased compared with those before treatment(P＜0.05).The intergroup comparison showed that the increase in the levels of CD3+ and CD4+ as well as the decrease in the levels of CD8+ and B cells of the observation group was significantly superior to that of the control group(P＜0.01).(6)After treatment,the levels of inflammatory factors of serum amyloid A(SAA),C-reactive protein(CRP),serum tumor necrosis factor alpha(TNF-α),soluble interleukin 2 receptor(SIL-2R),and interleukin 6(IL-6)in the two groups were significantly decreased compared with those before treatment(P＜0.05),and the levels of interleukin 2(IL-2)and interferon γ(IFN-γ)ls were all significantly increased compared with those before treatment(P＜0.05).The intergroup comparison showed that the decrease of serum SAA,CRP,TNF-α,SIL-2R,and IL-6 levels and the increase of serum IL-2 and IFN-γ levels in the observation group were significantly superior to those in the control group(P＜0.01).(7)The incidence of adverse reactions in the observation group was 2.00%(2/100),which was significantly lower than that of 8.00%(8/100)in the control group,but the difference was not statistically significant(χ2 = 3.789,P = 0.052).Conclusion Fuzheng Hejie Prescription exerts certain effect in treating children with respiratory viral infection of H1N1 virus,which can effectively decrease children's TCM syndrome scores,regulate the inflammatory response,improve the immune function,accelerate the relief of clinical symptoms and shorten the course of the disease.

Objective To explore the severity of loneliness among the elderly in communities in Shanghai,and to identify factors associated with social and emotional loneliness respectively.Methods A cross-sectional study was conducted in older adults aged 65 years or above in Pudong New Area,Jing'an District and Huangpu District in Shanghai from Mar to Jun 2021.In Pudong New Area,multi-stage stratified random sampling was conducted based on the age and gender distribution of Shanghai,while in Huangpu District and Jing'an District convenience sampling was conducted.A total of 635 samples were included in the study.Loneliness was assessed using the De Jong Gierveld Loneliness Scale with social and emotional loneliness subscales.Logistic regression analyses were conducted to identify factors associated with social and emotional loneliness.Results Among the 635 participants,only 53 older adults(8.4%)were not lonely.Female(OR=0.46,95%CI:0.31-0.70),higher self-efficacy(OR=0.97,95%CI:0.94-1.00),more objective social support(OR=0.96,95%CI:0.93-0.99)were associated with less severe social loneliness.Meanwhile,higher level of education(secondary education,OR=0.56,95%CI:0.34-0.95;college or above,OR=0.30,95%CI:0.11-0.83)and higher self-efficacy(OR=0.96,95%CI:0.93-0.99)were associated with less severe emotional loneliness,while depression(OR=3.41,95%CI:1.76-6.60)and worse social capital(OR=2.02,95%CI:1.29-3.16)were associated with more severe emotional loneliness.Conclusion Up to 91.6%of the elderly in our study sample were moderately lonely or above.The factors associated with social loneliness include self-efficacy,gender and social support.The factors associated with emotional loneliness are self-efficacy,education level,depression,and social capital.