Objective: To explore the relationship between non suicidal self injury (NSSI) behavior and serum lipid levels as well as thyroid function among college students with depression. Methods: A total of 169 college students with depression in the psychiatry departments of tertiary hospitals (grade 3A and 3B) in Ningbo from December 2023 to April 2025 were selected. The Adolescent Self injury Scale (ASIS) was used to assess the presence of NSSI, and participants were accordingly divided into a NSSI group ( n =51) and a non NSSI group ( n =118). General demographic data (including gender, age, and family situation) were collected from both groups. Blood tests were performed to measure lipid profiles [triglyceride (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C)] and thyroid hormones [triiodothyronine (T3), thyroxine (T4), free triiodothyronine (FT3), free thyroxine (FT4), thyroid stimulating hormone (TSH)]. Multivariate Logistic regression was employed to analyze risk factors for NSSI, and receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive value of serum lipid and thyroid hormone levels for NSSI occurrence in college students with depression. Results: The levels of TC, LDL-C, and TSH in the NSSI group were (4.02±0.73) mmol/L, (2.32±0.36) mmol/L, and (6.57±1.95) mU/L , which were significantly higher than those in the non NSSI group [(3.41±0.56) mmol/L, (2.00±0.27) mmol/L, and ( 4.48± 1.09) mU/L, respectively] ( t =5.32, 5.60, 7.20, all P <0.05). Logistic regression analysis revealed that college students from single parent/reconstituted families, those who had experienced school bullying, and those with higher levels of TC, LDL-C, and TSH had a significantly increased risk of engaging in NSSI ( OR =5.22, 6.12, 5.90, 83.64, 3.64, all P <0.05). ROC curve analysis demonstrated that the combined detection of TC, LDL-C, and TSH had high diagnostic efficacy for predicting NSSI in college students with depression, with a sensitivity of 86.3% and a specificity of 94.9%. Conclusions NSSI behavior in college students with depression is associated with serum lipid levels and thyroid function. These biomarkers may serve as useful reference indicators for assessing the conditions of these patients.

Background Regulatory interactions between microRNAs (miRNAs) and messenger RNAs (mRNAs) are involved in the progression of pulmonary fibrosis, which can either promote or inhibit the development of this disease. Objective To explore the miRNA-mRNA regulatory network during the progression of silica (SiO₂)-induced pulmonary fibrosis in mice using integrated mRNA-seq and miRNA-seq analysis. Methods A mouse model of pulmonary fibrosis was established by dynamic SiO₂ dust exposure. The experimental design included a blank control group and four SiO₂-exposed groups (7, 14, 28, and 56 d, n=10 per group). Successful model induction was confirmed by histopathological analysis (HE and Masson staining), hydroxyproline (HYP) quantification, and expression of key fibrosis-related cytokines [fibroblast growth factor (FGF), interleukin-6 (IL-6), transforming growth factor-β (TGF-β), and tumor necrosis factor-α (TNF-α)]. Lung tissues from mice in each group were subjected to sequencing, and Mfuzz was used for time-series gene clustering to identify dynamic progression patterns. DESeq2 was utilized to identify differentially expressed genes (DEGs) and differentially expressed miRNAs. Enrichment analysis of DEGs was performed to identify critical signaling pathways and biological processes underlying pulmonary fibrosis progression. Expression of four selected miRNAs was subsequently validated by real-time quantitative polymerase chain reaction (RT-qPCR). The target mRNAs of key miRNAs were comprehensively predicted by integrating miRBase, starBase, and miRTarBase to construct the regulatory networks and investigate potential functions. Results SiO₂ exposure led to time-dependent aggravation of pulmonary fibrosis in mice, evidenced by increased fibrous deposition, elevated HYP levels (P < 0.01), and up-regulation of four kinds of pro-fibrotic cytokines (P < 0.01) compared with the NT group. Mfuzz clustering revealed the stage-specific characteristics. Compared to controls, 231, 662, 448, and 1020 DEGs were identified after SiO₂ exposure at 7, 14, 28, and 56 d, respectively, primarily enriched in immune responses and chemokine signaling. During critical fibrotic phases—7 d (acute inflammation and initiation) and 28 d (chronic inflammation and establishment)—18 differentially expressed miRNAs were identified; notably mmu-miR-135b-5p was significantly dysregulated at both time points. The expression trends of the four key miRNAs (mmu-miR-135b-5p, mmu-miR-708-5p, mmu-miR-21a-3p, and mmu-miR-205-5p) were consistent with the sequencing results. Furthermore, bioinformatics databases were used to predict the target mRNAs of key miRNAs. The constructed network highlighted critical miRNA-mRNA pairs—including mmu-miR-135b-5p and Meis1, mmu-miR-708-5p and Mmp25, mmu-miR-21a-3p and Cacna1d, mmu-miR-205-5p and Ereg which were closely associated with inflammatory response, extracellular matrix deposition, and fibroblast activation. Conclusion The progression of pulmonary fibrosis is accompanied by dynamic changes in miRNA-mRNA regulatory networks. The identified miRNA-target axes (e.g., miR-135b-5p and Meis1, mmu-miR-708-5p and Mmp25, mmu-miR-21a-3p and Cacna1d, and mmu-miR-205-5p and Ereg—) may play important roles in fibrogenesis and provide potential therapeutic targets for pulmonary fibrosis.

Background Regulatory interactions between microRNAs (miRNAs) and messenger RNAs (mRNAs) are involved in the progression of pulmonary fibrosis, which can either promote or inhibit the development of this disease. Objective To explore the miRNA-mRNA regulatory network during the progression of silica (SiO₂)-induced pulmonary fibrosis in mice using integrated mRNA-seq and miRNA-seq analysis. Methods A mouse model of pulmonary fibrosis was established by dynamic SiO₂ dust exposure. The experimental design included a blank control group and four SiO₂-exposed groups (7, 14, 28, and 56 d, n=10 per group). Successful model induction was confirmed by histopathological analysis (HE and Masson staining), hydroxyproline (HYP) quantification, and expression of key fibrosis-related cytokines [fibroblast growth factor (FGF), interleukin-6 (IL-6), transforming growth factor-β (TGF-β), and tumor necrosis factor-α (TNF-α)]. Lung tissues from mice in each group were subjected to sequencing, and Mfuzz was used for time-series gene clustering to identify dynamic progression patterns. DESeq2 was utilized to identify differentially expressed genes (DEGs) and differentially expressed miRNAs. Enrichment analysis of DEGs was performed to identify critical signaling pathways and biological processes underlying pulmonary fibrosis progression. Expression of four selected miRNAs was subsequently validated by real-time quantitative polymerase chain reaction (RT-qPCR). The target mRNAs of key miRNAs were comprehensively predicted by integrating miRBase, starBase, and miRTarBase to construct the regulatory networks and investigate potential functions. Results SiO₂ exposure led to time-dependent aggravation of pulmonary fibrosis in mice, evidenced by increased fibrous deposition, elevated HYP levels (P < 0.01), and up-regulation of four kinds of pro-fibrotic cytokines (P < 0.01) compared with the NT group. Mfuzz clustering revealed the stage-specific characteristics. Compared to controls, 231, 662, 448, and 1020 DEGs were identified after SiO₂ exposure at 7, 14, 28, and 56 d, respectively, primarily enriched in immune responses and chemokine signaling. During critical fibrotic phases—7 d (acute inflammation and initiation) and 28 d (chronic inflammation and establishment)—18 differentially expressed miRNAs were identified; notably mmu-miR-135b-5p was significantly dysregulated at both time points. The expression trends of the four key miRNAs (mmu-miR-135b-5p, mmu-miR-708-5p, mmu-miR-21a-3p, and mmu-miR-205-5p) were consistent with the sequencing results. Furthermore, bioinformatics databases were used to predict the target mRNAs of key miRNAs. The constructed network highlighted critical miRNA-mRNA pairs—including mmu-miR-135b-5p and Meis1, mmu-miR-708-5p and Mmp25, mmu-miR-21a-3p and Cacna1d, mmu-miR-205-5p and Ereg which were closely associated with inflammatory response, extracellular matrix deposition, and fibroblast activation. Conclusion The progression of pulmonary fibrosis is accompanied by dynamic changes in miRNA-mRNA regulatory networks. The identified miRNA-target axes (e.g., miR-135b-5p and Meis1, mmu-miR-708-5p and Mmp25, mmu-miR-21a-3p and Cacna1d, and mmu-miR-205-5p and Ereg—) may play important roles in fibrogenesis and provide potential therapeutic targets for pulmonary fibrosis.

Radiotherapy is a cornerstone in the treatment of malignant tumors. It induces DNA damage through high-energy radiation, preferentially eliminating rapidly proliferating tumor cells. However, its clinical efficacy is often limited by tumor radioresistance and collateral damage to normal tissues. Consequently, elucidating the cellular response mechanisms to radiation stress and identifying key targets that can both sensitize tumor cells and protect normal tissues have become critical strategies for improving radiotherapy outcomes. Radiation stress triggers structural remodeling of the nucleolus, leading to the dissociation of certain ribosomal proteins from the ribosome and enabling them to acquire extra-ribosomal functions. Among these, RPL11 can be released and specifically binds to MDM2, thus inhibiting its E3 ubiquitin ligase activity, stabilizing p53, and mediating cell cycle arrest and apoptosis. The RPL11-MDM2-p53 pathway, acting as a signaling hub that links nucleolar dysfunction to cell fate determination, plays a pivotal role in maintaining genomic stability and regulating cellular responses to radiation. This review first introduces the basic characteristics of RPL11 and elucidates the molecular basis of radiation-induced ribosomal stress. It then outlines the core regulatory mechanisms of the cell cycle. On this basis, it focuses on the mechanisms by which radiation-induced RPL11 regulates the cell cycle and analyzes the specific effects of RPL11 on cell cycle. Furthermore, it discusses the role of the RPL11-MDM2-p53 pathway in cell cycle regulation. Finally, it explores the role of this pathway in maintaining genomic stability and determining cell fate, and highlights its potential value as a target for radiosensitization, aiming to provide new perspectives for enhancing tumor radiosensitivity and reducing damage to normal tissues.

Radiotherapy is a cornerstone in the treatment of malignant tumors. It induces DNA damage through high-energy radiation, preferentially eliminating rapidly proliferating tumor cells. However, its clinical efficacy is often limited by tumor radioresistance and collateral damage to normal tissues. Consequently, elucidating the cellular response mechanisms to radiation stress and identifying key targets that can both sensitize tumor cells and protect normal tissues have become critical strategies for improving radiotherapy outcomes. Radiation stress triggers structural remodeling of the nucleolus, leading to the dissociation of certain ribosomal proteins from the ribosome and enabling them to acquire extra-ribosomal functions. Among these, RPL11 can be released and specifically binds to MDM2, thus inhibiting its E3 ubiquitin ligase activity, stabilizing p53, and mediating cell cycle arrest and apoptosis. The RPL11-MDM2-p53 pathway, acting as a signaling hub that links nucleolar dysfunction to cell fate determination, plays a pivotal role in maintaining genomic stability and regulating cellular responses to radiation. This review first introduces the basic characteristics of RPL11 and elucidates the molecular basis of radiation-induced ribosomal stress. It then outlines the core regulatory mechanisms of the cell cycle. On this basis, it focuses on the mechanisms by which radiation-induced RPL11 regulates the cell cycle and analyzes the specific effects of RPL11 on cell cycle. Furthermore, it discusses the role of the RPL11-MDM2-p53 pathway in cell cycle regulation. Finally, it explores the role of this pathway in maintaining genomic stability and determining cell fate, and highlights its potential value as a target for radiosensitization, aiming to provide new perspectives for enhancing tumor radiosensitivity and reducing damage to normal tissues.

Radiotherapy is a cornerstone in the treatment of malignant tumors. It induces DNA damage through high-energy radiation, preferentially eliminating rapidly proliferating tumor cells. However, its clinical efficacy is often limited by tumor radioresistance and collateral damage to normal tissues. Consequently, elucidating the cellular response mechanisms to radiation stress and identifying key targets that can both sensitize tumor cells and protect normal tissues have become critical strategies for improving radiotherapy outcomes. Radiation stress triggers structural remodeling of the nucleolus, leading to the dissociation of certain ribosomal proteins from the ribosome and enabling them to acquire extra-ribosomal functions. Among these, RPL11 can be released and specifically binds to MDM2, thus inhibiting its E3 ubiquitin ligase activity, stabilizing p53, and mediating cell cycle arrest and apoptosis. The RPL11-MDM2-p53 pathway, acting as a signaling hub that links nucleolar dysfunction to cell fate determination, plays a pivotal role in maintaining genomic stability and regulating cellular responses to radiation. This review first introduces the basic characteristics of RPL11 and elucidates the molecular basis of radiation-induced ribosomal stress. It then outlines the core regulatory mechanisms of the cell cycle. On this basis, it focuses on the mechanisms by which radiation-induced RPL11 regulates the cell cycle and analyzes the specific effects of RPL11 on cell cycle. Furthermore, it discusses the role of the RPL11-MDM2-p53 pathway in cell cycle regulation. Finally, it explores the role of this pathway in maintaining genomic stability and determining cell fate, and highlights its potential value as a target for radiosensitization, aiming to provide new perspectives for enhancing tumor radiosensitivity and reducing damage to normal tissues.

Silent mutations within the RAS  gene have garnered increasing attention for their potential roles in tumorigenesis and therapeutic strategies. Kirsten-RAS ( KRAS ) mutations, predominantly oncogenic, are pivotal drivers in various cancers. While extensive research has elucidated the molecular mechanisms and biological consequences of active KRAS  mutations, the functional significance of silent mutations remains relatively understudied. This review synthesizes current knowledge on KRAS  silent mutations, highlighting their impact on cancer development. Silent mutations, which do not alter protein sequences but can affect RNA stability and translational efficiency, pose intriguing questions regarding their contribution to tumor biology. Understanding these mutations is crucial for comprehensively unraveling KRAS -driven oncogenesis and exploring novel therapeutic avenues. Moreover, investigations into the clinical implications of silent mutations in KRAS -mutant tumors suggest potential diagnostic and therapeutic strategies. Despite being in early stages, research on KRAS  silent mutations holds promise for uncovering novel insights that could inform personalized cancer treatments. In conclusion, this review underscores the evolving landscape of KRAS  silent mutations, advocating for further exploration to bridge fundamental biology with clinical applications in oncology.
Humans ; Mutation/genetics* ; Neoplasms/genetics* ; Proto-Oncogene Proteins p21(ras)/genetics* ; Animals

Traditional Chinese medicine formula (TCMF) represents a fundamental component of Chinese medical practice, incorporating medical knowledge and practices from both Han Chinese and various ethnic minorities, while providing comprehensive insights into health and disease. The foundation of TCMF lies in its holistic approach, manifested through herbal compatibility theory, which has emerged from extensive clinical experience and evolved into a highly refined knowledge system. Within this framework, Chinese herbal medicines exhibit intricated characteristics, including multi-component interactions, diverse target sites, and varied biological pathways. These complexities pose significant challenges for understanding their molecular mechanisms. Contemporary advances in artificial intelligence (AI) are reshaping research in traditional Chinese medicine (TCM), offering immense potential to transform our understanding of the molecular mechanisms underlying TCMFs. This review explores the application of AI in uncovering these mechanisms, highlighting its role in compound absorption, distribution, metabolism, and excretion (ADME) prediction, molecular target identification, compound and target synergy recognition, pharmacological mechanisms exploration, and herbal formula optimization. Furthermore, the review discusses the challenges and opportunities in AI-assisted research on TCMF molecular mechanisms, promoting the modernization and globalization of TCM.
Artificial Intelligence ; Drugs, Chinese Herbal/pharmacokinetics* ; Humans ; Medicine, Chinese Traditional ; Animals

OBJECTIVES: To investigate the therapeutic mechanism of Sangma Zhike Formula (SMZKF) for relieving cough sensitivity and airway inflammation in rats with postinfectious cough (PIC). METHODS: Male SD rat models were established by cigarette smoke exposure with intranasal LPS instillation and capsaicin aerosol inhalation. From day 19 following the start of PIC modeling, the rats received daily treatment with saline (model group), low-, medium-, and high-dose SMZKF, and compound methoxyphenamine (ASM) via gavage for 10 consecutive days (n=8). The assessments included behavioral changes, cough sensitivity (latency and frequency), lung histopathology, inflammatory cell counts and cytokine/mediator levels in the bronchoalveolar lavage fluid (BALF), oxidative stress markers in the lung tissue, and expressions of proteins related with cough hypersensitivity and pyroptosis. RESULTS: The rat models of PIC exhibited reduced mental alertness, accelerated respiration, and pronounced symptoms such as coughing, sneezing, and facial scratching with significantly shortened cough latency and increased 5-min cough frequency. Histopathological analysis revealed collapsed alveolar structures, thickened alveolar septa, and extensive inflammatory cell infiltration in the bronchi and peribronchial regions, accompanied by elevated bronchial and alveolar inflammation scores of the rat models. In the BALF, inflammatory cell counts and the levels of IL-1β, TNF-α, IL-6, COX-2, PGE-2, and TXA-2 were all markedly elevated, and the pulmonary oxidative stress markers (ROS and MDA) and myeloperoxidase (MPO) activity were also significantly increased. The pulmonary expressions of cough hypersensitivity-related proteins (TRPV1, SP, CGRP, and NK1R) and pyroptosis-associated markers (P-NF-κB, NLRP3, ACS, cleaved caspase-1, cleaved IL-1β, and GSDMD-N) were significantly upregulated in the model group. SMZKF interventions significantly ameliorated these pathological changes in the rat models, and high-dose SMZKF produced a similar therapeutic efficacy to that of ASM. CONCLUSIONS SMZKF alleviates cough sensitivity and airway inflammation in PIC rats possibly by inhibiting TRPV1-mediated SP/NK1R signaling and the NLRP3/caspase-1/GSDMD pyroptosis pathway.
Animals ; Cough/metabolism* ; Rats, Sprague-Dawley ; Pyroptosis/drug effects* ; Male ; TRPV Cation Channels/metabolism* ; Rats ; Drugs, Chinese Herbal/pharmacology* ; Inflammation ; Signal Transduction