Objective: To explore the interaction between school bullying and insomnia in relation to depression-anxiety-stress emotions among primary and secondary school students,so as to provide a basis for preventing negative emotional states in adolescents. Methods: In October 2024, a stratified cluster sampling method was used to select 3 058 students in grade 5-6 of primary, junior and senior high school in Sheyang County of Jiangsu Province. The Delaware Bullying Victimization Scale, Insomnia Severity Index, Depression-Anxiety-Stress Scale-21, and Study Condition Questionnaire were employed to investigate school bullying, insomnia, depression-anxiety-stress emotions, and academic performance. The χ 2 test and Logistic regression were used to analyze the association between school bullying and insomnia interactions and depression-anxiety-stress emotions among primary and secondary school students, multiplicative interaction analysis was conducted, and additive interaction analysis was performed using R software. Results: The detection rates of depression-anxiety-stress emotions among primary and secondary school students were 21.6%, 28.4% and 10.8%, respectively. The detection rates of physical bullying, relationship bullying, verbal bullying and cyberbullying in school bullying were 10.6%, 14.0%, 22.3%, and 6.2%, respectively. The detection rate for insomnia was 23.1%. Results from Logistic regression analysis showed that, after adjusting for relevant factors, physical, relational, verbal, and cyberbullying and insomnia were positively correlated with the detection rates of depression ( OR = 5.72- 10.93), anxiety ( OR =6.35-12.17), and stress emotions ( OR =5.97-14.52) among primary and secondary school students (all P <0.01). The multiplicative interaction between physical, relational, verbal, and cyberbullying and insomnia was positively correlated with the detection rates of depression ( OR =8.00-18.01), anxiety ( OR =11.35-17.76), and stress emotions ( OR =7.64-9.12) in primary and secondary school students (all P <0.01). Additive interactions were observed between physical, relational, verbal, and cyberbullying and insomnia in relation to the detection rates of depression, anxiety, and stress emotions among primary and secondary school students (both RERI and AP >0 and the credible interval excluded 0, SI >1 and the credible interval excluded 1). Conclusion School bullying and insomnia are associated with depression, anxiety, and stress emotions among primary and secondary school students, and they exhibit both multiplicative and additive interactions.

Histone lactylation is a recently identified post-translational modification, wherein lactate mediates the enzymatic addition of lactyl groups to lysine residues on histones. Since its discovery, extensive research has demonstrated that histone lactylation is widely present in human tissues and plays a pivotal role in regulating the transcription of specific genes. Subsequent studies have further established this modification as a widespread epigenetic mark with significant physiological implications. With advancing research, accumulating evidence confirms that lactylation at distinct histone sites elicits diverse biological effects—such as promoting cell proliferation, driving inflammatory responses, and enhancing fibrosis—all of which profoundly influence disease progression and serve as key drivers of disease onset and development. Conversely, inhibiting histone lactylation can alter disease outcomes, positioning histone lactylation as a promising therapeutic target. Moreover, studies have revealed crosstalk between histone lactylation and other post-translational modifications, such as acetylation and methylation, which collectively regulate disease progression. Notably, lactylation occurs not only on histones but also on non-histone proteins. Histone lactylation activates specific gene transcription and reshapes metabolic epigenetics, while non-histone lactylation directly modulates enzyme activity, signal transduction, and protein stability. These two facets form a synergistic network through shared lactate pools, common modifying enzyme systems, and pathway crosstalk, thereby constructing a multi-dimensional regulatory framework—namely, the “histone lactylation-metabolism hub-non-histone lactylation” axis. This architecture bridges metabolism and epigenetics, and deciphering its topological structure may provide novel targets for precise intervention in diseases driven by lactate-mediated signaling hijacking. Traditional Chinese medicine (TCM), grounded in clinical practice, has been shown to regulate histone lactylation by modulating lactate metabolism and lactylation-related enzymes, thereby influencing disease progression. Moreover, certain TCM formulations exhibit potential as alternative therapies for drug-resistant diseases, underscoring the significance of further exploring TCM-mediated regulation of histone lactylation in future therapeutic strategies. This review aims to elucidate the mechanisms underlying histone lactylation, systematically delineate the associations between site-specific histone lactylation and various diseases, present a comprehensive landscape of the “lactate-histone lactylation and functional protein lactylation” axis, and summarize the mechanistic basis and research advances in TCM-mediated regulation of histone lactylation for disease treatment. Additionally, we discuss current challenges in histone lactylation research and propose future directions, ultimately aiming to deepen understanding and broaden perspectives on the roles and therapeutic potential of histone lactylation in disease.

Objective: To explore the developmental trajectories of depression in children and adolescents and their association with family types, and to analyze the role of being an only child in the context, so as to provide a basis for early identification of mental health issues in children and adolescents. Methods: The study was a secondary analysis based on the existing database of the Jiangsu Provincial Student Common Diseases and Health Influencing Factors Monitoring and Intervention Project. A total of 11 502 students who had completed at least two measurements using the Chinese version of the Center for Epidemiologic Studies Depression Scale (CES-D) between 2022 and 2024, and had complete information on family type, gender, and age, were selected as the study subjects. Latent class trajectory modeling was used to identify depression developmental trajectories. Multinomial Logistic regression was applied to analyze the association between family type and depression developmental trajectories, and the interaction effect of family type and being an only child was tested. Results: Three types of depression developmental trajectories were identified among children and adolescents: low stable type (91.3%, 10 504 students), moderate rising type (4.3%, 500 students), and high declining type (4.3%, 498 students). Significant differences were observed among the different trajectory groups in terms of gender, age, parental education level, family type, baseline CES-D score, and baseline school type ( χ 2/H=17.48, 139.97, 19.72 , 30.77, 1 081.35, 220.81, all P <0.05). Multinomial Logistic regression analysis showed that, using the low stable type as the reference trajectory group and the nuclear family as the reference family type, after adjusting for confounding factors such as gender, age, and parental education level, single parent families ( OR=1.87, 95%CI= 1.16-3.03) and grandparent headed families ( OR=1.83, 95%CI =1.04-3.21) were significantly associated with the high declining type trajectory (both P <0.05). No significant association was found between family type and the moderate rising type trajectory (all P >0.05). The interaction effect between family type and being an only child was not statistically significant ( LRT=7.71, df=8, P =0.46). Conclusions Depressive symptoms in children and adolescents show heterogeneous developmental patterns during school age. Children and adolescents from single parent and intergenerational families are more likely to follow the high decreasing trajectory.

Background/Aims: Acetyl coenzyme A (acetyl-CoA) is one of the most essential metabolites in cell metabolism but its function and concentration in hepatocellular carcinoma (HCC) remain elusive and controversial. Methods: A comprehensive analysis of acetyl-CoA levels and acetyl-CoA synthetase 2 (ACSS2) expression across a range of samples, including patient specimens from both hepatitis B virus (HBV) positive and HBV negative HCC individuals, HBV-transgenic mouse HCC models, and multiple cell lines. Furthermore, to evaluate the functional significance of ACSS2 in HBV-related HCC, we implemented both genetic and pharmacological inhibition strategies targeting ACSS2. Molecular mechanism and mitophagy assessment were revealed by cleavage under target and tagmentation sequencing, RNA sequencing, bioinformatic analyses, transmission electron microscopy and JC-1 staining. Results: Our study revealed a distinct metabolic signature of HBV-related HCC, marked by elevated acetyl-CoA, which was driven by ACSS2. ACSS2 was upregulated by the carbohydrate response element-binding protein in HBV-related HCC. Furthermore, ACSS2 improved tumor cell proliferation, an effect that was dependent on its enzymatic activity. Mechanistically, ACSS2-induced acetyl-CoA accumulation activated voltage-dependent anion channels 1 transcription through increased H3K27ac occupancy, which subsequently promoted mitophagy and HBV-related HCC tumorigenesis. Notably, targeting ACSS2 by depletion or inhibition with a catalytic inhibitor significantly suppressed tumor growth. Conclusions These findings not only illustrate the interplay between metabolic reprogramming, epigenetic modification, and tumorigenesis in the context of HBV infection, but also highlight ACSS2 as a novel metabolic vulnerability in HBV-related HCC. Therefore, targeting ACSS2 could be a novel strategy against HBV-related HCC.

Acute kidney injury (AKI) is a prevalent and life-threatening clinical syndrome characterised by a rapid decline in renal function and diverse pathological etiologies. The condition has been demonstrated to be associated with elevated mortality rates and an increased risk of progression to chronic kidney disease. At present, clinicians depend heavily on conventional functional markers, such as serum creatinine and urine output, for the diagnosis and staging of the disease. It is evident that these conventional indicators characteristically manifest a considerable temporal delay and only undergo modification subsequent to considerable tissue damage. This severely restricts the timeframe for early detection and timely therapeutic intervention. Furthermore, standard markers fail to provide specific biological information regarding the underlying cellular injury mechanisms. The utilisation of advanced probe technologies in molecular imaging offers a robust alternative to overcome these inherent diagnostic limitations.This comprehensive review systematically evaluates recent progress in the design and application of two primary categories of molecular imaging tools for acute kidney disease, specifically reactive probes and enzyme-activated probes. Reactive probes are engineered to specifically interact with redox-active chemical species, including hydrogen peroxide, peroxynitrite, hypochlorous acid, and sulfur dioxide. Because oxidative stress constitutes a primary early event in acute renal tubular damage, these probes enable researchers and clinicians to visualize early cellular injury and radical accumulation well before global renal functional decline becomes evident. We discuss the application of these reactive probes across multiple imaging modalities including fluorescence imaging, magnetic resonance imaging (MRI), positron emission tomography (PET), and photoacoustic techniques. Photoacoustic imaging combines high spatial resolution with deep tissue penetration and has successfully demonstrated the ability to provide diagnostic alerts up to 12 h before any detectable rise in serum creatinine levels. Additionally, specific reactive probes have shown promising translational potential when tested by high-throughput screening in clinical human urine samples. Enzyme-activated probes target the specific catalytic activity of disease-relevant enzymes. These include well-documented renal tubular structural biomarkers such as NAG, GGT, and ALP, along with apoptosis-related caspases and specific nitroreductases. By responding only to enzymatic cleavage, these tools provide highly specific and pathology-directed imaging readouts. Recent structural design strategies in this field have advanced significantly beyond single-enzyme detection. Researchers are now focusing on sophisticated dual-target recognition to minimize background noise, multimodal integration to cross-validate imaging signals, and theranostic applications where probes simultaneously deliver diagnostic feedback and therapeutic agents to injured tissues. Nanotechnology serves as a fundamental enabler for realizing these advanced probe functions. By precisely optimizing nanoparticle parameters such as hydrodynamic size, surface charge, and targeting ligands, researchers can achieve amplified signal output, highly precise kidney delivery, and protection against premature degradation in the systemic circulation. For example, modifying surface charges can significantly enhance the active uptake of nanoprobes by damaged renal tubular epithelial cells.While preclinical probe development has progressed rapidly, moving these technologies into routine clinical practice remains a major challenge. We analyze the translational feasibility and current obstacles from biological, technological, and regulatory perspectives. Although biological targets such as KIM-1, FAP, and ALP have been validated in extensive patient cohorts, practical barriers severely limit their immediate clinical application. These obstacles involve complex changes in in vivo pharmacokinetics. During an acute injury episode, the extreme drop in the glomerular filtration rate alters probe clearance and can cause unwanted systemic accumulation or confusing background imaging signals. Other major hurdles include a lack of comprehensive long-term toxicity data and the absence of standardized manufacturing protocols to ensure batch-to-batch consistency. Future successful translation will require rigorous multi-center clinical studies to confirm the true diagnostic value of these probes over traditional markers. Researchers must also establish strict standardization of imaging procedures and comprehensive safety evaluations. Ultimately, this review provides a thorough reference framework for designing clinically translatable molecular probes and building a precision diagnostic imaging system for acute kidney injury.

Colorectal cancer (CRC) is characterized by persistently high incidence and mortality. Current therapies are limited by drug resistance and modest patient benefit, underscoring the urgent need for new perspectives rooted in tumor biology. The unique metabolic landscape of CRC makes it an ideal model in which to dissect the pathological roles of lactylation regulatory networks: microsatellite-stable (MSS) CRC, which accounts for approximately 85% of cases, concurrently upregulates glycolysis and oxidative phosphorylation, engaging in intense metabolic competition with immune cells; the intratumoral lactate pool exhibits a distinctive “dual-source supply” feature—in addition to tumor-intrinsic glycolysis, substantial exogenous lactate is provided by gut microbiota dysbiosis and by colonizing bacteria within liver metastases; high-frequency oncogenic mutations and lactylation modifications establish a feed-forward circuit of “oncogene-driven lactate accumulation-lactylation-facilitated tumor progression”. Moreover, MSS CRC displays near-complete unresponsiveness to immune checkpoint inhibitors, a phenomenon underpinned by multiple immune evasion mechanisms mediated by lactate and lactylation. Lactate metabolism is a hallmark of metabolic reprogramming in cancer. Lactate homeostasis provides tumor cells with metabolic substrates, modulates redox status, and regulates fatty acid metabolism to promote malignant progression. Notably, lactate can drive lactylation—an emerging post-translational modification (PTM) in which lactyl groups are attached to lysine residues, dynamically governing gene transcription and protein function and thereby establishing a bridge between metabolism and epigenetics. Lactate and lactylation form a multidimensional, coordinated network: lactylation of key metabolic enzymes such as LDHA reinforces a positive feedback loop that sustains lactate production; lactylation of upstream transcription factors such as HIF-1α drives metabolic reprogramming; furthermore, lactylation engages in crosstalk with m6A and m5C RNA modifications as well as with other PTMs such as acetylation, profoundly reshaping cellular behavior. In CRC, histone lactylation drives malignant phenotypes by activating immunosuppressive programs, inhibiting ferroptosis, and promoting invasion and migration; non-histone lactylation accelerates translation elongation, stabilizes β‑catenin, maintains redox homeostasis, and prevents PD-L1 degradation, thereby facilitating tumor progression. Lactylation-related gene signatures have demonstrated potential for prognostic stratification. Therapeutic strategies targeting the lactylation network range from upstream metabolic intervention to modulation of the modifying enzymes and direct blockade of lactylation modifications, forming a hierarchical interventional framework. However, current evidence derives predominantly from cell lines and xenograft models, and a causal relationship between lactylation and malignant progression in CRC has yet to be rigorously established. Whether inhibition of lactylation can alter CRC phenotypes independently of metabolic alterations and acetylation fluctuations remains a central unanswered question in the field. This review systematically examines the research progress and translational challenges surrounding lactylation regulatory networks, aiming to provide a circumspect assessment to inform the development of novel therapeutic strategies for CRC.

ObjectiveColorectal cancer (CRC) is a highly heterogeneous malignancy, and traditional Chinese medicine (TCM) syndrome differentiation is widely used in its clinical management. However, the biological basis underlying different TCM syndromes remains insufficiently understood. This study aimed to investigate the proteomic differences between qi-blood deficiency syndrome (QBDS) and damp-heat syndrome (DHS) in CRC patients and to establish a “syndrome-differential protein-herbal component” network for exploring potential molecular mechanisms and therapeutic targets associated with syndrome-specific treatment strategies. MethodsTumor tissue samples were collected from 10 patients with pathologically confirmed CRC, including 5 patients diagnosed with QBDS and 5 with DHS according to standardized TCM syndrome differentiation criteria. Tandem mass tag (TMT)-based quantitative proteomics was employed to identify differentially expressed proteins (DEPs) between the two syndrome groups. Functional enrichment analyses, including Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, were performed to characterize the biological functions and signaling pathways associated with the identified DEPs. Least absolute shrinkage and selection operator (LASSO) regression analysis was further applied to screen key syndrome-related proteins and construct a core protein prediction model. Subsequently, molecular docking was conducted to evaluate the binding affinities between representative herbal compounds, astragaloside IV and berberine, and the identified core proteins. Finally, cell counting kit-8 (CCK-8) assays were performed in HCT 116 and HT-29 colorectal cancer cell lines to validate the anti-proliferative activities of these compounds in vitro. ResultsA total of 44 DEPs were identified between QBDS and DHS tissues, including 21 upregulated and 23 downregulated proteins in the QBDS group relative to the DHS group. Functional enrichment analyses revealed that these proteins were primarily associated with antiviral immune responses, regulation of inflammatory signaling, NF‑κB signaling pathways, cholesterol metabolism, and other biological processes relevant to tumor progression and host immune regulation. LASSO regression analysis identified eight core proteins with potential syndrome-specific significance. Among them, ST7, GPCPD1, and PODXL were closely associated with QBDS, whereas FAT1, GRB7, KRT7, MAFF, and MMP8 were associated with DHS. Molecular docking demonstrated favorable interactions between astragaloside IV and QBDS-related proteins, with binding energies lower than -5 kcal/mol, indicating stable binding activity. Berberine exhibited even lower binding energies and stronger binding specificity toward DHS-related core proteins. In vitro experiments further confirmed that both compounds inhibited CRC cell proliferation, while berberine displayed significantly greater anti-proliferative efficacy. The lowest 48 h IC₅₀ value of berberine reached 15.21 mg/L in CRC cells, indicating a stronger growth-inhibitory effect than astragaloside IV. ConclusionCRC patients with QBDS and DHS exhibit distinct proteomic characteristics, suggesting that different TCM syndromes possess unique molecular signatures. The identified core proteins may serve as potential biomarkers for syndrome differentiation, while astragaloside IV and berberine may exert therapeutic effects through targeting syndrome-specific molecular networks. These findings provide preliminary proteomic evidence supporting syndrome-guided precision integrative medicine in CRC and offer new insights into the biological basis of TCM syndrome differentiation and individualized therapeutic strategies.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.