ObjectiveThe present study aimed to investigate alterations in white matter microstructure and spontaneous neural activity in male college smokers, and to further explore their associations with nicotine dependence. Given that adolescence and early adulthood represent critical periods for brain maturation, particularly for white matter development, understanding the neural correlates of smoking behavior during this stage is of substantial importance for both neuroscience and public health. MethodsA total of 115 male undergraduate students were initially recruited for this study. After quality control and exclusion procedures, 52 male college smokers and 42 demographically matched healthy non-smokers were included in the final analysis. All participants underwent multimodal magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI) and resting-state functional MRI (rs-fMRI). White matter fiber tracts were reconstructed using the automated fiber quantification (AFQ) method, which enables precise identification and quantification of major fiber bundles. Eighteen major white matter tracts were segmented for each participant. Along the core trajectory of each tract, 100 equidistant nodes were sampled. Fractional anisotropy (FA) was calculated at each node to assess white matter microstructural integrity, while amplitude of low-frequency fluctuation (ALFF) was computed to evaluate spontaneous neural activity within white matter tracts. Between-group differences in FA and ALFF were assessed using two-sample t-tests, with appropriate corrections applied for multiple comparisons. Furthermore, Pearson correlation analyses were conducted to examine the relationships between imaging-derived metrics (FA and ALFF values in regions showing significant group differences) and nicotine dependence severity, as measured by the Fagerström test for nicotine dependence (FTND). ResultsCompared with healthy non-smokers, male college smokers exhibited significantly increased FA values in several white matter tracts, including the left thalamic radiation, right corticospinal tract, forceps major of the corpus callosum, left uncinate fasciculus, and right arcuate fasciculus. These findings suggest altered microstructural organization or increased directional coherence within these pathways. In addition, smokers demonstrated significantly elevated ALFF values in the forceps major, right uncinate fasciculus, and left arcuate fasciculus, indicating enhanced spontaneous neural activity in these white matter regions. Correlation analyses revealed that FA values in the left thalamic radiation and right corticospinal tract were negatively correlated with FTND scores, suggesting that higher levels of nicotine dependence were associated with reduced microstructural integrity or altered fiber organization in these regions. In contrast, ALFF values in the forceps major and right uncinate fasciculus were positively correlated with FTND scores, indicating that greater nicotine dependence was associated with increased spontaneous neural activity in specific white matter pathways. ConclusionThe present study provides evidence that male college smokers exhibit distinct alterations in both white matter microstructure and functional activity. These abnormalities are not uniformly distributed but rather localized to specific fiber tracts implicated in sensorimotor processing, interhemispheric communication, and higher-order cognitive and emotional regulation. Importantly, the observed associations between imaging metrics and nicotine dependence severity suggest that these structural and functional alterations may reflect neurobiological mechanisms underlying addiction. The combination of AFQ-based tract profiling and multimodal MRI offers a sensitive approach for detecting subtle changes along white matter pathways, highlighting its potential utility in identifying neuroimaging biomarkers of nicotine dependence. Overall, these findings indicate that smoking during early adulthood may disrupt ongoing white matter maturation, potentially leading to long-term consequences for brain function. This study provides novel insights into the neural basis of nicotine dependence and underscores the importance of early intervention and prevention strategies targeting young smokers.

Objective This study reports on the obligatory parasitism of water mites Arrenurus sp. on Anopheles messeae at the Manzhouli Port, Inner Mongolia, China. Methods Duing July 2024, a survey on the mosquito diversity was conducted at the Manzhouli Port. Captured mosquitoes and their ectoparasites were identified to species level. Results A total of 1840 adult mosquitoes were collected, representing species from three genera: Culex(Cx. modestus, Cx. pipiens pallens), Aedes(Ae. dorsalis, Ae. flavidorsalis, Ae. flavescens), and Anopheles (An. messeae). Among all the mosqutioes specimens,3 out of 150 captured An. messeae were found to carry ectoparasitic mites, with number of 2,4,27 mites separately. Morphological and molecular identification reached the same result as water mites(Hydrachnidiae, Hydracrina). COI gene sequence showed 94% similarity with the closest species Arrenurus truncatellus. Conlusions Literature review suggests water mites are host-specific parasitism of mosquito species and herein with the first record of Arrenurus sp. parasiting on An. Messeae in the most high-latitude region globally.

Early screening of tumors is crucial for prevention and treatment of cancer,thus identifying effective biomarkers is of great importance for early diagnosis of tumors.In recent years,tumor-secreted exosomes(Exos)have attracted widespread attention as a novel biomarker for tumor liquid biopsy.Especially,some specific proteins contained in Exos play important roles in the occurrence,development,metastasis and microenvironment regulation of tumors,indicating their enormous potential as potential diagnostic biomarkers for tumors.Compared to traditional biopsy sample testing,exosome-based protein detection methods exhibit significant advantages in liquid biopsy,including rapid sampling,easy operation,non-invasiveness,and feasibility for early detection,holding important application value for clinical diagnosis of tumors.This review aimed to comprehensively summarize and discuss various detection strategies for exosomal proteins in liquid biopsy for tumors,while comprehensively evaluating the analytical performance of these methods.Meanwhile,new perspectives and strategies for early diagnosis and treatment of tumors were discussed.Additionally,the unique advantages of exosomal proteins as a new generation of non-invasive diagnostic biomarkers and insights into their promising prospects for future clinical applications were emphasized.

The electrocatalytic nitrate reduction reaction(NO3RR)presents a sustainable pathway for large-scale ammonia production,yet it faces significant challenges due to proton supply limitations caused by the high energy barrier for water dissociation,which slows ammonia(NH3)generation.Herein,a palladium(Pd)-modified copper-cobalt(CuCo)hollow fiber penetration electrode that enabled H2 injection through its hollow structures,thereby enhancing proton availability for NO3RR was developed.The active Pd component efficiently dissociated H2,facilitating active hydrogen(*H)spillover and speeding up the cascade NO3RR process on Cu and Co sites.As a result,a half-cell energy efficiency of 39.53%and an NH3 Faradaic efficiency(FE)of 97.11%±1.17%at-0.1 V(vs RHE)were achieved,comparable to state-of-the-art systems.Importantly,the H2-assisted approach prevented the oxidation of active Cu and Co phases,demonstrating exceptional stability with less than 5.6%decay in current density(267 mA/cm2)and retention of NH3 FE at 94.8%after over 70 h of electrolysis.These findings offered valuable insights into proton supply pathways and design of NO3RR electrodes.

Transfer-RNA derived small RNA(tsRNA),a re-cently discovered class of non-coding RNA,is produced by ma-ture tRNA or tRNA precursor through the mediation of specific endonucleases.By regulating gene expression at the transcrip-tional and post transcriptional levels and acting as an epigenetic regulator,tsRNA plays an important role in the physiological and pathological processes of many organisms.Therefore,it has gradually become a research hotspot in biomedicine and attracted widespread attention.Moreover,there is increasing evidence that tsRNA is involved in the occurrence and development of many neuropsychiatric diseases through participating in stress re-sponse,cell proliferation and apoptosis,neural development,synaptic plasticity,neuroinflammation and immune regulation,epigenetic regulation,RNA processing,and protein translation regulation.This article mainly discusses the generation,classifi-cation and biological functions of tsRNA,and elaborates on the role and possible mechanisms of tsRNA in neurodevelopment and neuropsychiatric disorders,thereby further revealing the poten-tial of tsRNA as a reliable biomarker and therapeutic target for neuropsychiatric disorders.

Objective:Invasive pulmonary mucormycosis(PM)is a rare but highly lethal opportunistic infection.COVID-19 associated mucormycosis(CAM)is difficult to diagnose,often leading to misdiagnosis or missed diagnosis,and has poor treatment outcomes.This study reports a case of successfully treated CAM and explores optimized diagnostic and therapeutic strategies.Methods:A retrospective analysis of the diagnosis and treatment process in a 50-year-old female patient with COVID-19 associated with diabetic ketoacidosis(DKA)and invasive pulmonary mucormycosis was conducted.Combined with a literature review,the therapeutic efficacy of local bronchoscopic instillation in conjunction with systemic treatment using liposomal Amphotericin B(L-AmB)was specifically evaluated.Results:The patient was rapidly diagnosed with Rhizopus microsporus infection through metagenomic next-generation sequencing(mNGS).She subsequently received antifungal treatment with intravenous L-AmB combined with local bronchoscopic instillation.After treatment,the patient was significantly improved,with imaging studies showing gradual absorption of the lesions.Follow-up at six months revealed no recurrence.A literature review suggests that early diagnosis and multimodal therapy are key to improving survival rates in patients with CAM.Conclusion:mNGS can significantly improve the early diagnosis rate of CAM.The combination of local and systemic treatment with L-AmB is valuable in improving prognosis.Early diagnosis,multimodal antifungal therapy,and individualized management are key to increasing the survival rate of patients with CAM.

ObjectiveThe aim of this study was to investigate the prophylactic effects of caloric restriction (CR) on lipopolysaccharide (LPS)-induced septic cardiomyopathy (SCM) and to elucidate the mechanisms underlying the cardioprotective actions of CR. This research aims to provide innovative strategies and theoretical support for the prevention of SCM. MethodsA total of forty-eight 8-week-old male C57BL/6 mice, weighing between 20-25 g, were randomly assigned to 4 distinct groups, each consisting of 12 mice. The groups were designated as follows: CON (control), LPS, CR, and CR+LPS. Prior to the initiation of the CR protocol, the CR and CR+LPS groups underwent a 2-week acclimatization period during which individual food consumption was measured. The initial week of CR intervention was set at 80% of the baseline intake, followed by a reduction to 60% for the subsequent 5 weeks. After 6-week CR intervention, all 4 groups received an intraperitoneal injection of either normal saline or LPS (10 mg/kg). Twelve hours post-injection, heart function was assessed, and subsequently, heart and blood samples were collected. Serum inflammatory markers were quantified using enzyme-linked immunosorbent assay (ELISA). The serum myocardial enzyme spectrum was analyzed using an automated biochemical instrument. Myocardial tissue sections underwent hematoxylin and eosin (HE) staining and immunofluorescence (IF) staining. Western blot analysis was used to detect the expression of protein in myocardial tissue, including inflammatory markers (TNF-α, IL-9, IL-18), oxidative stress markers (iNOS, SOD2), pro-apoptotic markers (Bax/Bcl-2 ratio, CASP3), and SIRT3/SIRT6. ResultsTwelve hours after LPS injection, there was a significant decrease in ejection fraction (EF) and fractional shortening (FS) ratios, along with a notable increase in left ventricular end-systolic diameter (LVESD). Morphological and serum indicators (AST, LDH, CK, and CK-MB) indicated that LPS injection could induce myocardial structural disorders and myocardial injury. Furthermore, 6-week CR effectively prevented the myocardial injury. LPS injection also significantly increased the circulating inflammatory levels (IL-1β, TNF-α) in mice. IF and Western blot analyses revealed that LPS injection significantly up-regulating the expression of inflammatory-related proteins (TNF-α, IL-9, IL-18), oxidative stress-related proteins (iNOS, SOD2) and apoptotic proteins (Bax/Bcl-2 ratio, CASP3) in myocardial tissue. 6-week CR intervention significantly reduced circulating inflammatory levels and downregulated the expression of inflammatory, oxidative stress-related proteins and pro-apoptotic level in myocardial tissue. Additionally, LPS injection significantly downregulated the expression of SIRT3 and SIRT6 proteins in myocardial tissue, and CR intervention could restore the expression of SIRT3 proteins. ConclusionA 6-week CR could prevent LPS-induced septic cardiomyopathy, including cardiac function decline, myocardial structural damage, inflammation, oxidative stress, and apoptosis. The mechanism may be associated with the regulation of SIRT3 expression in myocardial tissue.

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 infer novel therapeutic and phar-macological targets related to lung cancer treatment through multiomics approaches,so as to provide new directions for developing more personalized and effec-tive treatment strategies.Methods Genome-wide as-sociation study(GWAS)data analysis,pan-cancer,single-cell,transcriptomics,and protein-protein interac-tion analysis were employed in this study.Results We analyzed biomarkers and therapeutic targets associ-ated with lung cancer.The study identified key bio-markers closely related to lung cancer progression and explored the interrelationships between these biomark-ers and viral infections.According to KEGG pathway annotation,the number of genes related to metabolic processes increased significantly.In particular,metab-olites such as alanine and isoleucine emerged as pivotal factors in therapeutic interventions.The IgD+CD24+and IgD+CD24-B cell subsets were identified as cen-tral elements in immune evasion and treatment re-sponse.Concurrently,the Lachnospiraceae and Prevo-tella were shown to modulate host immune responses and the tumor microenvironment by regulating short-chain fatty acid levels,thereby opening novel avenues for cancer research.Conclusions Through mul-tiomics analysis combined with transcriptomics and pro-teomics analysis,we identify several potential therapeu-tic targets for lung cancer,providing key insights for developing novel treatment strategies.