Background Prenatal exposure to fine particulate matter (PM_2.5) is closely associated with cortical damage and neuroinflammation in offspring. The cyclic guanosine monophosphate–adenosine monophosphate synthase (cGAS)–stimulator of interferon genes (STING) signaling pathway is a key regulator of inflammation and may be subject to epigenetic regulation. Objective To investigate the role of cGAS-STING pathway activation in PM_2.5-induced cortical damage in offspring mice during pregnancy and the underlying epigenetic regulatory mechanisms. Methods Open field tests were used to assess depressive-like behavior in offspring mice. Morphological analysis was conducted to evaluate cortical damage and microglial activation in offspring brains. Real-time fluorescent quantitative PCR (RT-qPCR) and Western blot (WB) were performed to detect changes in the expression of key molecules in the cGAS-STING pathway in cortical tissue. A PM_2.5-induced microglial cell injury model was established in BV2 cells. Microglial activation was observed, cell viability was measured using the Cell Counting Kit-8 (CCK-8), and the expression levels of inducible nitric oxide synthase (iNOS) and key molecules in the cGAS-STING pathway were detected by RT-qPCR and WB. Bioinformatics analysis was performed to explore the epigenetic regulatory association between the STING signaling pathway and lysine-specific demethylase 5A (KDM5A). Changes in KDM5A mRNA and protein expression, as well as the protein level of histone H3 lysine 4 trimethylation (H3K4me3), were detected in an in vitro PM_2.5 injury model. Using small interfering RNA (siRNA) technology, the KDM5A gene was silenced in BV2 cells exposed to PM_2.5. The protein expression of H3K4me3 was detected to evaluate improvements in microglial activation, changes in inflammatory markers such as iNOS and mannose receptor (CD206), and alterations in the cGAS-STING pathway. Results Compared with the control group, the total distance of offspring mice in the PM_2.5 group was significantly reduced, and both the distance traveled and the time spent in the central area of the open field were significantly decreased (P<0.01, P<0.001), indicating depressive-like behavior in the offspring mice. Compared with the control group, the offspring mice in the PM_2.5 group exhibited disorganized cortical structure and significantly activated microglia (P<0.01), with significantly increased mRNA and protein levels of cGAS and STING (P<0.05, P<0.01, or P<0.001). The in vitro experiments demonstrated that the PM_2.5 treatment induced BV2 cells to polarize toward the M1 phenotype, exhibiting a distinct amoeboid morphology, with upregulated expression of the pro-inflammatory factor iNOS (P<0.05, P<0.01, or P<0.001) and activation of the cGAS-STING pathway (P<0.05, P<0.01). The analysis of RNA-seq data from KDM5A knockout cells revealed significantly downregulated STING expression, suggesting that KDM5A may activate the STING signaling pathway. The in vitro experiments further confirmed that the PM_2.5-treated BV2 cells exhibited significantly elevated mRNA and protein levels of KDM5A (P<0.01), while the H3K4me3 protein levels were markedly reduced (P<0.05). After silencing KDM5A in BV2 cells exposed to PM_2.5, compared with the PM_2.5+siNC group, the PM_2.5+siKDM5A group showed no obvious microglial activation and polarized toward the M2 phenotype, with significantly decreased expression levels of iNOS, cluster of differentiation 16 (CD16), and interleukin-1β (P<0.05, P<0.01), and significantly increased expression levels of anti-inflammatory factors CD206, YM1, and interleukin-10 (P<0.01, P<0.001). Meanwhile, the expression levels of cGAS and STING were also reduced (P<0.05, P<0.01). Conclusion KDM5A activates microglia through the cGAS-STING pathway, thereby contributing to PM_2.5-induced cortical damage in offspring mice during pregnancy.

ObjectiveBased on literature data mining， this study explores the modeling elements of diarrhea-predominant irritable bowel syndrome （IBS-D） animal models in China and abroad， providing references and suggestions for improving modeling methods and evaluation indicators. MethodsRelevant literature on IBS-D animal experiments from 2014 to 2024 was retrieved through computer searches in databases such as China National Knowledge Infrastructure （CNKI）， Wanfang Data， VIP， Chinese Medical Journals Full-text Database， and PubMed. Information on experimental animal species， gender， body weight， modeling methods， modeling periods， intervention controls， modeling standards， and detection indicators was organized. Microsoft Excel 2021 software was used to establish a database and perform statistical analysis to examine the characteristics of IBS-D animal models. ResultsA total of 398 articles that met the inclusion criteria were reviewed. The IBS-D animal models were predominantly established using SD rats， Wistar rats， and C57BL/6 mice. Male animals were more commonly used， with rats typically aged 6-8 weeks and mice aged 4-6 weeks. In terms of interventions， piverium bromide was the main Western medicine， Tongxieyaofang was the primary Chinese medicine， and electroacupuncture was the primary acupuncture method. Among the modeling methods， the multi-factor combined composite modeling approach was the most common. Modeling periods were mainly concentrated between 1-14 days and 15-30 days. The success criteria for modeling were mainly evaluated based on the animal's general condition， fecal appearance， visceral sensitivity， gastrointestinal motility， behavior， and pathology. Detection indicators included apparent indexes， pathological markers， biochemical indicators， oxidative stress， brain-gut peptides， neurotransmitters， inflammatory factors， immune function， intestinal permeability， autophagy， apoptosis， proteins related to relevant signaling pathways， intestinal microbiota and its metabolites， etc. ConclusionThere are various methods for establishing IBS-D animal models， but no unified and universally accepted method has been established. The operation of the same modeling methods and the evaluation standards of the models vary across studies. Based on the results of data mining， the authors suggest that the multi-factor combined composite modeling approach most closely reflects the pathophysiological processes of IBS-D， better simulating the complex clinical symptoms of IBS-D patients， such as abdominal pain and diarrhea， and has a high degree of clinical relevance. This method is relatively recommended. While animal models in general align with Western medicine standards， models incorporating traditional Chinese medicine （TCM） syndromes are relatively few. Therefore， one of the future directions for research is to establish IBS-D animal models that meet the combined clinical disease and syndrome requirements of both Western and Chinese medicine.

[Objective] To investigate the factors influencing the detection of HLA-C expression by flow cytometry. [Methods] A total of 12 hematopoietic stem cell suspension samples from peripheral hematopoietic stem cell volunteer donors were randomly collected after CD34⁺ cell counting detection. The influence of detecting different number of nucleated cell (500 000, 50 000 and 5 000), sequential order of red blood cell lysis and antibody incubation, and the HLA-C antibody with varied remaining time from the expiration date on the detection results of HLA-C expression by flow cytometry were investigated, respectively. The significance of differences between different groups was analyzed through Student t test. [Results] There was no significant difference in the proportion of HLA-C positive cells and mean fluorescence intensity (MFI) among the three groups with different nucleated cell numbers detected (500 000, 50 000 and 5 000) (P>0.05). The sequential order of red blood cell lysis and antibody incubation had no influence on the proportion of HLA-C positive cells (P>0.05), but HLA-C MFI value was significantly lower when antibody incubation was performed after red blood cell lysis than that when antibody incubation was performed before red blood cell lysis (P<0.05). The proportion of HLA-C positive cells and MFI value detected by HLA-C antibody remaining 24 months from the expiration date were significantly higher than those detected by HLA-C antibody remaining only 5 months from the expiration date (P<0.05). [Conclusion] The present study has investigated the factors of influencing HLA-C expression level by flow cytometry, the results have important reference and application value for standardizing the experimental operation of HLA-C expression and improving the accuracy and comparability of detection results.

OBJECTIVE To provide reference for rational clinical use of immune checkpoint inhibitor （ICI）. METHODS Electronic medical record information of patients who received ICI treatment from January 1st 2020 to December 31st 2023 at a certain hospital was collected. Patients were divided into thyroid immune-related adverse event （irAE） group （subdivided into clinical hypothyroidism， clinical hyperthyroidism， subclinical hypothyroidism， and subclinical hyperthyroidism subgroups） and non- thyroid irAE group based on whether they experienced immune-induced thyroid irAE. Univariate and multivariate Logistic regression analyses were employed to analyze the influencing factors of ICI-related thyroid adverse events. RESULTS A total of 382 patients who received ICI treatment were included， with 137 cases in the thyroid irAE group （accounting for 35.9%） and 245 cases in the non-thyroid irAE group （accounting for 64.1%）. Multivariate Logistic regression analysis， following univariate screening， revealed that ICI combined with radiotherapy was positively associated with the occurrence of thyroid irAE [odds ratio （OR）＝2.157， 95% confidence interval （CI） （1.144， 4.066）， P＜0.05]， while lung squamous cell carcinoma was negatively associated with the occurrence of thyroid irAE [OR＝0.600， 95%CI （0.369， 0.975）， P＜0.05]. Among various thyroid irAE， nasopharyngeal malignancy was positively associated with the occurrence of immune-related clinical hyperthyroidism [OR＝4.678， 95%CI （1.149， 19.042）， P＜0.05]； ICI combined with radiotherapy [OR＝2.622， 95%CI （1.227， 5.603）， P＜0.05] and lung adenocarcinoma [OR＝2.013， 95%CI （1.078， 3.759）， P＜0.05] were positively associated with the occurrence of immune-related subclinical hyperthyroidism. Age was negatively associated with the occurrence of immune-related clinical hypothyroidism [OR＝0.944， 95%CI （0.896， 0.995）， P＜0.05]； age [OR＝0.963， 95%CI （0.932， 0.994）， P＜0.05] and ICI combined with chemotherapy [OR＝0.332， 95%CI （0.137， 0.802）， P＜0.05] were negatively associated with the occurrence of immune-related subclinical hypothyroidism. CONCLUSIONS Among patients receiving ICI treatment， younger patients are more prone to thyroid irAE. Patients receiving ICI combined with chemotherapy are less likely to experience subclinical hypothyroidism， while ICI combined with radiotherapy significantly increases the risk of thyroid adverse events.

ObjectiveThis study aims to develop a prediction model for the compatibility of Chinese medicinal pairs based on Graph Convolutional Networks （GCN）， named HC-GCN. The model integrates the properties of herbs with modern pharmacological mechanisms to predict pairs with specific therapeutic effects. It serves as a demonstration by applying the model to predict and validate the efficacy of blood-activating herb pairs. MethodsThe training dataset for herb pair prediction was constructed by systematically collecting commonly used herb pairs along with their characteristic data， including Qi， flavor， meridian tropism， and target genes. Integrating traditional characteristics of herb with modern bioinformatics， we developed an efficacy-oriented herb pair compatibility prediction model （HC-GCN） using graph convolutional networks （GCN）. This model leverages machine learning to capture the complex relationships in herb pair compatibility， weighted by efficacy features. The performance of the HC-GCN model was evaluated using accuracy （ACC）， recall， precision， F1 score （F1）， and area under the ROC curve （AUC）. Its predictive effectiveness was then compared to five other machine learning models： eXtreme Gradient Boosting （XGBoost）， logistic regression （LR）， Naive Bayes， K-nearest neighbor （KNN）， and support vector machine （SVM）. ResultsUsing herb pairs with blood-activating effects as a demonstration， a prediction model was constructed based on a foundational dataset of 46 blood-activating herb pairs， incorporating their Qi， flavor， meridian tropism， and target gene characteristics. The HC-GCN model outperforms other commonly used machine learning models in key performance metrics， including ACC， recall， precision， F1 score， and AUC. Through the predictive analysis of the HC-GCN model， 60 herb pairs with blood-activating effects were successfully identified. Among of these potential herb pairs， 44 include at least one herb with blood-activating effects. ConclusionIn this study， we established an efficacy-oriented compatibility prediction model for herb pairs based on GCN by integrating the unique characteristics of traditional herbs with modern pharmacological mechanisms. This model demonstrated high predictive performance， offering a novel approach for the intelligent screening and optimization of traditional Chinese medicine prescriptions， as well as their clinical applications.

Background Arsenic is an environmentally harmful substance that causes hepatic insulin resistance and liver damage, increasing the risk of type 2 diabetes mellitus. Objective To explore whether the insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2) is involved in insulin resistance in HepG2 cells after arsenic exposure through the peroxisome-proliferator-activated receptor γ (PPAR-γ) / glucose transporter 4 (GLUT4) pathway. Methods Cell viability was determined using cell counting kit 8 (CCK8) and an appropriate NaAsO₂ infection dose was determined. A cellular arsenic exposure model of HepG2 cells was established by four concentrations of NaAsO₂ solution for 24 h (the experiment was divided into four groups: 0, 2, 4, and 8 μmol·L⁻¹); HepG2 cells were firstly treated with pcDNA3.1-IGF2BP2 and pcDNA3.1-NC respectively for 6 h, then with 8 μmol·L⁻¹ NaAsO₂ for 24 h to establish a IGF2BP2 overexpression cell model (the experiment was divided into 4 groups: control, NaAsO₂, NaAsO₂+pcDNA3.1-IGF2BP2, and NaAsO₂+pcDNA3.1-NC); finally the cells were subject to 100 nmol·L⁻¹ insulin stimulation for 30 min. Glycogen and glucose in HepG2 cells were determined by glycogen and glucose assay kits; mRNA expression levels of IGF2BP2 were measured by quantitative real-time PCR; protein expression levels of IGF2BP2, PPAR-γ, and GLUT4 in HepG2 were detected by Western blot (WB); and the binding of IGF2BP2 to PPAR-γ and PPAR-γ to GLUT4 was verified by co-immunoprecipitation (CO-IP) experiment. Results The results of CCK8 experiment showed a dose-effect relationship between NaAsO₂ concentration and cell viability. When the concentration of NaAsO₂ was ≥4 μmol·L⁻¹ , the cell viabilities were lower than that of the control group (P <0.05). With the increasing dose of NaAsO₂ infection, reduced glucose consumption and glycogen levels in HepG2 cells were found in the 2, 4, and 8 μmol·L⁻¹ NaAsO₂ treatment groups compared to the control group (P <0.05). The difference between the mRNA expression level of IGF2BP2 in the HepG2 cells treated with 4 or 8 μmol L⁻¹ NaAsO₂ and the control group was significant (P <0.05). In the IGF2BP2 overexpression cell model, compared with the control group, glucose consumption and glycogen levels were lowered in the NaAsO₂ group (P <0.05), the mRNA expression level of IGF2BP2 and the protein expression levels of IGF2BP2, PPAR-γ, and GLUT4 in the cell membrane were all decreased (P <0.05). Compared with the NaAsO₂ group, the glucose consumption and glycogen levels were increased in the NaAsO₂+pcDNA3.1-IGF2BP2 group (P <0.05), and the mRNA expression level of IGF2BP2 and the protein expression levels of IGF2BP2, PPAR-γ, and GLUT4 in the cell membrane were all increased (P <0.05). The results of CO-IP experiments showed that IGF2BP2 interacted with PPAR-γ as well as PPAR-γ with GLUT4 protein. Conclusion IGF2BP2 is involved in arsenic exposure-induced insulin resistance in HepG2 cells by acting on the PPAR-γ/GLUT4 pathway.

Background Existing studies have confirmed that fine particulate matter (PM_2.5)is one of the important factors inducing pulmonary fibrosis. Pulmonary fibrosis is the terminal stage of a major category of lung diseases characterized by the destruction of tissue structure, and eventually leading lung ventilation and ventilation dysfunction. No effective pulmonary fibrosis treatment is available yet. Objective To investigate the protective effect of salidroside on pulmonary fibrosis induced by the exposure of PM_2.5 and its molecular mechanism. Methods Seventy 7-week-old male C57BL/6 mice were randomly divided into four groups: control group (intratracheal instillation of normal saline + saline by gavage, n=25), Sal group (intratracheal instillation of normal saline + Sal 60 mg·kg⁻¹ by gavage, n=10), PM_2.5 group (intratracheal instillation of PM_2.5 5 mg·kg⁻¹ + saline by gavage, n=10), and Sal + PM_2.5 group (intratracheal instillation of PM_2.5 5 mg·kg⁻¹ +Sal 60 mg·kg⁻¹ by gavage, n=10). The mice were administered by gavage once daily, intratracheal instillation once every 3 d, and every 3 d constituted an experimental cycle. At the end of the 26-30th cycles, 3 mice in the control group and 3 mice in the PM_2.5 group were randomly sacrificed, and the lung tissues were collected for Masson staining to verify whether the pulmonary fibrosis model was successfully established. After 30 cycles, the model was successfully constructed. After 1 week of continuous observation, the mice were sacrificed, and the blood and lung tissues of the mice were collected to make lung tissue sections. Assay kits were correspondingly employed to detect oxidative stress indicators such as serum malondialdehyde (MDA) and superoxide dismutase (SOD). Western blotting was used to detect the expression of fibrosis-related proteins (Collagen-III, α-SMA), mitochondrial dynamics-related proteins (MFN1, Drp1), and mitophagy-related proteins (PINK1, Parkin, and LC3). Results Compared with the control group, the weight gain rate of the PM_2.5 group was slowed down (P<0.05), which was alleviated by the Sal intervention (P<0.05). The lung coefficient increased after the PM_2.5 exposure (P<0.05), which was alleviated by Sal intervention. Compared with the control group, the PM_2.5 group showed severe alveolar structure damage, inflammatory cell infiltration, and blue collagen deposition, and significantly increased the lung injury score, collagen volume fraction (CVF), Szapiel score, and Ashcroft score (P<0.05), as well as serum oxidative stress levels (P<0.05). The protein expression levels of Collagen-III, α-SMA, Drp1, PINK1, Parkin, and LC3 II/I were increased (P<0.05), and the expression of MFN1 was decreased (P<0.05). Compared with the PM_2.5 group, the Sal intervention alleviated lung injury, reduced inflammatory cell infiltration and collagen deposition, showing decreased lung injury score, CVF, Szapiel score, and Ashcroft score (P<0.05), and decreased serum oxidative stress levels (P<0.05); the protein expression levels of Collagen-III, α-SMA, PINK1, Parkin, and LC3 II/I were decreased (P<0.05), the expression level of Drp1 was decreased, and the expression level of MFN1 was increased. Conclusion In the process of pulmonary fibrosis induced by PM_2.5 exposure in mice, Sal may affect mitochondrial autophagy through PINK1/Parkin pathway and play a protective role. The specific mechanism needs to be further verified.

Chemical communication in plant-microbiome and intra-microbiome interactions weaves a complex network, critically shaping ecosystem stability and agricultural productivity. This non-contact interaction is driven by small-molecule signals that orchestrate crosstalk dynamics and beneficial association. Plants leverage these signals to distinguish between pathogens and beneficial microbes, dynamically modulate immune responses, and secrete exudates to recruit a beneficial microbiome, while microbes in turn influence plant nutrient acquisition and stress resilience. Such bidirectional chemical dialogues underpin nutrient cycling, co-evolution, microbiome assembly, and plant resistance. However, knowledge gaps persist regarding validating the key molecules involved in plant-microbe interactions. Interpreting chemical communication requires multi-omics integration to predict key information, genome editing and click chemistry to verify the function of biomolecules, and artificial intelligence (AI) models to improve resolution and accuracy. This review helps advance the understanding of chemical communication and provides theoretical support for agriculture to cope with food insecurity and climate challenges.
Microbiota/physiology* ; Plants/microbiology* ; Artificial Intelligence ; Ecosystem

Metastasis is the leading cause of death from cutaneous melanoma. Identifying metastasis-related targets and developing corresponding therapeutic strategies are major areas of focus. While functional genomics strategies provide powerful tools for target discovery, investigations at the protein level can directly decode the bioactive epitopes on functional proteins. Aptamers present a promising avenue as they can explore membrane proteomes and have the potential to interfere with cell function. Herein, we developed a target and epitope discovery platform, termed functional aptamer evolution-enabled target identification (FAETI), by integrating affinity aptamer acquisition with phenotype screening and target protein identification. Utilizing the aptamer XH3C, which was screened for its migration-inhibitory function, we identified the Chondroitin Sulfate Proteoglycan 4 (CSPG4), as a potential target involved in melanoma migration. Further evidence demonstrated that XH3C induces cytoskeletal rearrangement by blocking the interaction between the bioactive epitope of CSPG4 and integrin α4. Taken together, our study demonstrates the robustness of aptamer-based molecular tools for target and epitope discovery. Additionally, XH3C is an affinity and functional molecule that selectively binds to a unique epitope on CSPG4, enabling the development of innovative therapeutic strategies.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by persistent inflammation and joint damage, accompanied by the accumulation of plasma cells, which contributes to its pathogenesis. Understanding the genetic alterations occurring during plasma cell differentiation in RA can deepen our comprehension of its pathogenesis and guide the development of targeted therapeutic interventions. Here, our study elucidates the intricate molecular mechanisms underlying plasma cell differentiation by demonstrating that PRDX1 interacts with DOK3 and modulates its degradation by the autophagy-lysosome pathway. This interaction results in the inhibition of plasma cell differentiation, thereby alleviating the progression of collagen-induced arthritis. Additionally, our investigation identifies Salvianolic acid B (SAB) as a potent small molecular glue-like compound that enhances the interaction between PRDX1 and DOK3, consequently impeding the progression of collagen-induced arthritis by inhibiting plasma cell differentiation. Collectively, these findings underscore the therapeutic potential of developing chemical stabilizers for the PRDX1-DOK3 complex in suppressing plasma cell differentiation for RA treatment and establish a theoretical basis for targeting PRDX1-protein interactions as specific therapeutic targets in various diseases.