The Type III Secretion System (T3SS) serves as a pivotal virulence apparatus for numerous Gram-negative bacterial pathogens, enabling them to infect both animal and plant hosts. Functioning as a molecular syringe, the T3SS directly translocates bacterial effector proteins from the bacterial cytoplasm into the interior of eukaryotic host cells. These effectors are central weapons that precisely manipulate a wide spectrum of host cellular physiological processes, ranging from cytoskeletal dynamics to immune signaling, to establish a favorable niche for bacterial survival and proliferation. Among the diverse arsenal of T3SS effectors, the YopJ family constitutes a critical group of virulence factors. Members of this family are characterized by a conserved catalytic triad structure—a hallmark of the CE clan of cysteine proteases that has been evolutionarily repurposed to confer acetyltransferase activity. A defining and intriguing feature of these enzymes is their stringent dependence on a host-derived eukaryotic cofactor, inositol hexakisphosphate (IP₆), for allosteric activation. This requirement acts as a sophisticated molecular safeguard, ensuring enzymatic activity only within the appropriate host environment, thereby preventing detrimental effects on the bacterium itself. While seminal studies on individual members such as Yersinia’s YopJ and Salmonella’s AvrA have provided deep mechanistic insights, a systematic and integrative understanding of the structure-function relationships across the entire family remains fragmented. Key questions persist regarding how a conserved catalytic core has diverged to recognize distinct host substrates in different kingdoms of life. To address this gap, this article provides a systematic review of the YopJ family, focusing on three interconnected aspects: their structural features, their catalytic mechanism, and their divergent immunosuppressive strategies in animal versus plant hosts. By conducting a comparative analysis of the sequences and resolved three-dimensional structures of three representative members (e.g., HopZ1a, PopP2, AvrA), we elucidate regions of significant variation embedded within the conserved core catalytic architecture. These variable regions, often involving surface loops and substrate-binding interfaces, are crucial determinants of target specificity and functional specialization. The functional divergence of this effector family is most apparent when comparing their modes of action in different hosts. In animal hosts, YopJ-family effectors primarily sabotage innate immune signaling pathways. They achieve this by acetylating key serine and threonine residues within the activation loops of critical kinases in the MAPK and NF‑κB pathways. This post-translational modification blocks the phosphorylation and subsequent activation of these kinases, leading to potent suppression of inflammatory cytokine production. Conversely, in plant hosts, the strategy broadens to dismantle the two-tiered plant immune system. YopJ homologs target a more diverse set of substrates, including immune-associated receptor-like cytoplasmic kinases (RLCKs), microtubule networks via tubulin acetylation (which disrupts cellular trafficking and signaling), and transcription factors central to defense gene regulation. This multi-target approach effectively suppresses both Pattern-Triggered Immunity (PTI) and Effector-Triggered Immunity (ETI). In conclusion, this synthesis aims to deepen the mechanistic understanding of YopJ family-mediated pathogenesis by integrating structural biology with cellular function across host kingdoms. Elucidating the precise molecular basis for substrate selection—how conserved platforms achieve target diversity—is a major frontier. Furthermore, this knowledge provides a vital theoretical foundation for developing novel anti-virulence strategies. Targeting the conserved IP₆-binding pocket or the catalytic acetyltransferase activity itself represents a promising avenue for designing broad-spectrum inhibitors that could disarm this critical family of bacterial effectors, potentially offering new therapeutic approaches against a range of pathogenic bacteria.

This study aims to investigate the effects and mechanisms of the effective-compounds of Jinshui Huanxian formula (ECC-JHF) in improving pulmonary fibrosis. Animal experiments were approved by the Ethics Committee of the Animal Experiment Center of Henan University of Chinese Medicine (approval number: IACUC-202306012). The mouse model of pulmonary fibrosis was induced using bleomycin (BLM). Hematoxylin-eosin (H&E) staining was used to detect the histopathological changes of lung tissues. Masson staining was used to assess the degree of fibrosis in lung tissues. Immunofluorescence (IF) and real-time quantitative PCR (qPCR) were performed to measure the expression of collagen type I (COL I), α-smooth muscle actin (α-SMA), fibronectin (FN), interleukin (IL)-1β, IL-6, and tumor necrosis factor α (TNF-α) in lung tissues. Flow cytometry (FCM) was employed to detect the proportion of M1 and M2 macrophages in the bronchoalveolar lavage fluid (BALF) of mice. IF and qPCR were also used to detect the expression of lipase family member N (LIPN) in lung tissues. Free fatty acid assay kit was used to detect the level of free fatty acids in lung tissue. Bone marrow-derived macrophages (BMDMs) were treated with interleukin-4 (IL-4) to induce M2 polarization. FCM was used to measure the proportion of CD206⁺ M2 macrophages. IF was utilized to detect LIPN expression and lipid droplet decomposition. The results showed that in BLM-induced pulmonary fibrosis mice, ECC-JHF significantly attenuated BLM-induced alveolar inflammation and collagen deposition, inhibited fibroblast activation in lung tissues, and decreased the proportion of M2 macrophages in BALF. It also significantly suppressed LIPN expression and free fatty acid level in lung tissues. In the IL-4 induced BMDMs M2 polarization model, ECC-JHF significantly inhibited the proportion of CD206⁺ M2 macrophages, down-regulated the expression of LIPN, and blocked lipid droplet catabolism. These results suggest that ECC-JHF may alleviate bleomycin-induced pulmonary fibrosis by inhibiting lipid droplet decomposition and M2 macrophage polarization.

Numerous studies on the formation and consolidation of memory have shown that memory processes are characterized by phase-dependent and dynamic regulation. Memory retrieval, as the only representation of memory content and an active form of memory processing that induces memory reconsolidation, has attracted increasing attention in recent years. Although the molecular mechanisms specific to memory retrieval-induced reconsolidation have been gradually revealed, an understanding of the time-dependent regulatory mechanisms of this process is still lacking. In this study, we applied a transcriptome analysis of memory retrieval at different time points in the recent memory stage. Differential expression analysis and Short Time-series Expression Miner (STEM) depicting temporal gene expression patterns indicated that most differential gene expression occurred at 48 h, and the STEM cluster showing the greatest transcriptional upregulation at 48 h demonstrated the most significant difference. We then screened the differentially-expressed genes associated with that met the expression patterns of those cluster-identified genes that have been reported to be involved in learning and memory processes in addition to dipeptidyl peptidase 9 (DPP9). Further quantitative polymerase chain reaction verification and pharmacological intervention suggested that DPP9 is involved in 48-h fear memory retrieval and viral vector-mediated overexpression of DPP9 countered the 48-h retrieval-induced attenuation of fear memory. Taken together, our findings suggest that temporal gene expression patterns are induced by recent memory retrieval and provide hitherto undocumented evidence of the role of DPP9 in the retrieval-induced reconsolidation of fear memory.
Animals ; Fear/physiology* ; Male ; Dipeptidyl-Peptidases and Tripeptidyl-Peptidases/genetics* ; Memory Consolidation/physiology* ; Time Factors ; Mental Recall/drug effects* ; Mice ; Gene Expression Profiling

Due to its high sensitivity and non-destructive nature, Raman spectroscopy has become an essential analytical tool in biopharmaceutical analysis and drug development. Despite of the computational demands, data requirements, or ethical considerations, artificial intelligence (AI) and particularly deep learning algorithms has further advanced Raman spectroscopy by enhancing data processing, feature extraction, and model optimization, which not only improves the accuracy and efficiency of Raman spectroscopy detection, but also greatly expands its range of application. AI-guided Raman spectroscopy has numerous applications in biomedicine, including characterizing drug structures, analyzing drug forms, controlling drug quality, identifying components, and studying drug-biomolecule interactions. AI-guided Raman spectroscopy has also revolutionized biomedical research and clinical diagnostics, particularly in disease early diagnosis and treatment optimization. Therefore, AI methods are crucial to advancing Raman spectroscopy in biopharmaceutical research and clinical diagnostics, offering new perspectives and tools for disease treatment and pharmaceutical process control. In summary, integrating AI and Raman spectroscopy in biomedicine has significantly improved analytical capabilities, offering innovative approaches for research and clinical applications.

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Degenerative cervical myelopathy(DCM)is a group of diseases caused by cervical spine degeneration that compresses the spinal cord.It is a major cause of spinal cord dysfunction in adults,and its incidence is increasing globally.In the late stage,DCM could lead to paralysis due to spinal cord injury,which makes rapid,effective,and accurate medical diagnosis clinically significant.Deep learning(DL)technology can assist physicians in the rapid and accurate diagnosis of DCM by analyzing and processing a large amount of imaging data to extract features of the affected regions.In recent years,DL algorithm models have been leveraged for DCM-related research,which has become a focal point of intelligent medical development.In this review,domestic and international literature is surveyed,and the research progress and application of DL technology in the auxiliary diagnosis and prognosis evaluation of DCM are systematically summarized,aiming to provide a reference for intelligent diagnosis in clinical practice.

Objective:To explore the short-term clinical effects of deep cervical lymph node-venous anastomosis in the treatment of Alzheimer’s disease (AD).Methods:A prospective exploratory study was conducted on the treatment of AD patients using the cervical deep lymph node-venous anastomosis technique in Scar and Wound Treatment Department, Plastic Surgery Hospital, Chinese Academy of Medical Sciences, from September to October 2024. The patients underwent high-frequency ultrasound to locate deep cervical lymph nodes and the external jugular vein. Under general anesthesia, bilateral deep cervical lymph node-venous anastomoses were performed. Indocyanine green (ICG) lymphography was conducted via subcutaneous injection behind the ear to visualize lymph nodes in levels Ⅱ and Ⅲ. After making a skin incision along the posterior margin of the sternocleidomastoid muscle, the external jugular vein, internal jugular veins, and associated lymph nodes were exposed. Adjacent veins were selected for anastomosis of lymph node. Using microsurgical techniques, end-to-side or end-to-end anastomosis was completed for lymph nodes in levels Ⅱ and Ⅲ. Preoperative assessments included the mini-mental state examination (MMSE, a higher score indicates better cognitive function), Alzheimer’s disease assessment scale-cognitive subscale (ADAS-Cog, a higher score indicates greater impairment of cognitive function), Alzheimer’s disease cooperative study scale for activities of daily living (ADCS-ADL, a higher score indicates better ability to perform daily activity), and neuropsychiatric inventory (NPI, a higher score indicates more severe behavioral and emotional symptom). Postoperative follow-up included the same scales to observe changes in cognitive function, activities of daily living, and emotional communication.Results:Four patients (1 male, 3 females, aged 58-79 years) with AD were included. All were diagnosed based on cerebrospinal fluid biomarkers. All patients successfully underwent bilateral deep cervical lymph node-venous anastomoses. On average, 4.3 (2-7 per person) anastomoses were performed per patient. Surgical procedures lasted an average of 6.5 h (5.5-8.5 h) with minimal blood loss (less than 50 ml). Patients resumed normal activity within 6 hours postoperatively and were discharged after an average of 4.1 d (3.5-5.0 d). Postoperative complications included one case each of aspiration pneumonia, lower limb venous thrombosis, and transient delirium, all of whom resolved without long-term effects. Clinical symptoms, including memory decline, mood swings, and anxiety, showed varying degrees of improvement. Patients reported enhanced quality of life, emotional stability, and social engagement, confirming the procedure’s safety and potential cognitive benefits. At one month postoperatively, the MMSE scores of the four patients increased by an average of 0.8 points compared to preoperative levels. Additionally, the two patients who completed the ADAS-Cog assessments showed a decrease in their scores (reduced by 1.0 points and 11.3 points, respectively, compared to preoperative scores), indicating a certain degree of improvement in cognitive function during this period. The ADCS-ADL and NPI scores of four patients varied significantly, without showing any clear pattern.Conclusion:Lymphovenous anastomosis of the deep cervical lymph node-venous anastomosis may provide a new surgical intervention approach for AD, but further large-scale studies and long-term follow-up are needed to validate its safety and effectiveness.

Metal-organic frameworks(MOFs)are porous materials composed of metal ions or metal clusters and organic ligands by coordination,which have the advantages of large specific surface area,good thermal stability and adjustable pore size,and have a promising application in gas chromatographic separation.In recent years,MOFs materials have been used as stationary phases for gas chromatography mainly including ZIF,MIL,UiO-66,HKUST-1,IRMOFs,etc.Based on the molecular sieve effect,van der Waals forces,hydrogen bonding and π-π interactions,the pore size,pore microenvironment,unsaturated metal site and special functional group of the MOFs stationary phase materials can be specifically designed and regulated.MOFs materials as stationary phases have unique separation performance for n-alkanes and their isomers,aromatic compounds and their isomers,alcohols/ketones/aldehydes and their isomers,and chiral compounds.The combination of organic polymers and novel nanomaterials with MOFs materials can improve the separation performance and stability of MOFs.Therefore,MOFs materials are expected to be the promising stationary phase that can be applied to gas separation in complex environments.In this article,the research advances of various stationary phases based on MOFs for gas chromatography in recent years were reviewed.The separation performance and separation mechanism of MOFs stationary phases for mixed gas samples were discussed,and the development trends in the future were prospected.

In this study,an ON/OFF type micro-valve with a sandwich(glass-silicon-glass)structure was designed and fabricated based on the micro-electro-mechanical system(MEMS)technique.The deformable membrane of this micro-valve was prepared on the silicon on insulator(SOI)substrate and sealed using Si-Si bonding and anodic bonding methods.The micro-valve had high-temperature stability and was suitable for integration with other gas chromatography components.The deformable membrane with a thickness of 10 μm was processed on the top silicon of the SOI substrate.The flow control of the micro-valve could be achieved by changing the driving pressure applied to the deformable membrane to deform it.Compared with polymer membranes,the deformable membrane prepared on the top layer silicon of SOI had better temperature stability and could be released using the deep reactive ion etching technique after silicon-silicon bonding,avoiding deformation during the preparation process.In addition,due to the small gap between the membrane and the inlet/outlet holes,the dead volume of the microvalve was very small.The test results indicated that the micro-valve achieved flow control and ON/OFF functions with good repeatability.