OBJECTIVE To investigate the mechanism by which esketamine improves postoperative cognitive impairment in rats with hip fracture based on the AMP-activated protein kinase （AMPK）/silencing information regulatory factor 1 （SIRT1）/ peroxisome proliferator activated-receptor-γ coactivator-1α （PGC-1α） signaling pathway. METHODS Rats with hip fracture surgery were assigned into model group， esketamine group （10 mg/kg）， inhibitor group （250 μg/mL AMPK inhibitor Compound C）， and esketamine+inhibitor group （10 mg/kg esketamine + 250 μg/mL Compound C）， and rats undergoing sham surgery were used as the control group， with 12 rats in each group. New object recognition and Barnes maze experiments were used to E-mail：448231@163.com evaluate cognitive function in rats. The levels of serum tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β），superoxide dismutase （SOD）， malondialdehyde （MDA）， gamma-aminobutyric acid （GABA）， dopamine （DA） and glutamate （Glu）， and the apoptosis of hippocampal neurons were detected. The pathological morphology of the hippocampal tissue and the ultrastructure of mitochondria were observed. The mRNA expression of B-cell lymphoma-2 （Bcl-2） and Bcl-2-associated X protein （Bax），the mRNA and protein expression of AMPK， SIRT1 and PGC-1α， as well as the expression of phosphorylated （p）-AMPK in hippocampal tissue， were detected. RESULTS Compared with the control group， the hippocampal neurons in the model group of rats were disordered， with more neurons necrotic and swollen mitochondria；the new object recognition index， the SOD， GABA， DA levels， Bcl-2， AMPK， SIRT1 and PGC-1α mRNA expression levels， and p-AMPK， SIRT1， PGC-1α protein expression levels were significantly reduced， while the latency and number of errors for locating unknown holes， the TNF-α， IL-1β， MDA and Glu levels， neuronal cell apoptosis rate， and Bax mRNA expression levels were significantly increased/prolonged （P＜0.05）. Compared with the model group， the esketamine group showed reduced pathological damage to the hippocampal tissue of rats， and the new object recognition index， the SOD， GABA and DA levels， the Bcl-2， AMPK， SIRT1 and PGC-1α mRNA expression levels， and p-AMPK， SIRT1， PGC-1α protein expression levels were significantly increased，while the latency and error frequency for locating unknown holes， TNF-α， IL-1β， MDA and Glu levels， neuronal cell apoptosis rate， and Bax mRNA expression levels were significantly decreased （P＜0.05）；the inhibitor group showed the opposite trend of changes in these indicators compared to the esketamine group （P＜0.05）.AMPK inhibitor could reverse the improvement effect of esketamine on the above indicators after hip fracture surgery in rats （P＜0.05）. CONCLUSIONS Esketamine may improve postoperative inflammatory response and oxidative stress levels in rats with hip fracture by activating the AMPK/SIRT1/PGC-1α signaling pathway， inhibiting neuronal cell apoptosis， improving mitochondrial structure， and promoting postoperative cognitive function recovery.

The study investigated the intrinsic changes in material basis of Angelicae Sinensis Radix during wine processing by headspace-gas chromatography-ion mobility spectrometry(HS-GC-IMS), headspace-solid phase microextraction-gas chromatography-mass spectrometry(HS-SPME-GC-MS), and ultra-high performance liquid chromatography-quadrupole-orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS) combined with chemometrics. HS-GC-IMS fingerprints of Angelicae Sinensis Radix before and after wine processing were established to analyze the variation trends of volatile components and characterize volatile small-molecule substances before and after processing. Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed for differentiation and difference analysis. A total of 89 volatile components in Angelicae Sinensis Radix were identified by HS-GC-IMS, including 14 unsaturated hydrocarbons, 16 aldehydes, 13 ketones, 9 alcohols, 16 esters, 6 organic acids, and 15 other compounds. HS-SPME-GC-MS detected 118 volatile components, comprising 42 unsaturated hydrocarbons, 11 aromatic compounds, 30 alcohols, 8 alkanes, 6 organic acids, 4 ketones, 7 aldehydes, 5 esters, and 5 other volatile compounds. UPLC-Q-Orbitrap-MS identified 76 non-volatile compounds. PCA revealed distinct clusters of raw and wine-processed Angelicae Sinensis Radix samples across the three detection methods. Both PCA and OPLS-DA effectively discriminated between the two groups, and 145 compounds(VIP>1) were identified as critical markers for evaluating processing quality, including 4-methyl-3-penten-2-one, ethyl 2-methylpentanoate, and 2,4-dimethyl-1,3-dioxolane detected by HS-GC-IMS, angelic acid, β-pinene, and germacrene B detected by HS-SPME-GC-MS, and L-tryptophan, licoricone, and angenomalin detected by UPLC-Q-Orbitrap-MS. In conclusion, the integration of the three detection methods with chemometrics elucidates the differences in the chemical material basis between raw and wine-processed Angelicae Sinensis Radix, providing a scientific foundation for understanding the processing mechanisms and clinical applications of wine-processed Angelicae Sinensis Radix.
Wine/analysis* ; Gas Chromatography-Mass Spectrometry/methods* ; Chromatography, High Pressure Liquid/methods* ; Angelica sinensis/chemistry* ; Solid Phase Microextraction/methods* ; Drugs, Chinese Herbal/isolation & purification* ; Chemometrics ; Volatile Organic Compounds/chemistry* ; Principal Component Analysis ; Ion Mobility Spectrometry/methods*

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.

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

OBJECTIVE: To investigate chronic hepatitis C virus (HCV) infection's effect on gestational liver function, pregnancy and delivery complications, and neonatal development. METHODS: A total of 157 HCV antibody-positive (anti-HCV[+]) and HCV RNA(+) patients (Group C) and 121 anti-HCV(+) and HCV RNA(-) patients (Group B) were included as study participants, while 142 anti-HCV(-) and HCV RNA(-) patients (Group A) were the control group. Data on biochemical indices during pregnancy, pregnancy complications, delivery-related information, and neonatal complications were also collected. RESULTS: Elevated alanine aminotransferase (ALT) rates in Group C during early, middle, and late pregnancy were 59.87%, 43.95%, and 42.04%, respectively-significantly higher than Groups B (26.45%, 15.70%, 10.74%) and A (23.94%, 19.01%, 6.34%) ( P < 0.05). Median ALT levels in Group C were significantly higher than in Groups A and B at all pregnancy stages ( P < 0.05). No significant differences were found in neonatal malformation rates across groups ( P > 0.05). However, neonatal jaundice incidence was significantly greater in Group C (75.16%) compared to Groups A (42.25%) and B (57.02%) ( χ ² = 33.552, P < 0.001). HCV RNA positivity during pregnancy was an independent risk factor for neonatal jaundice ( OR = 2.111, 95% CI 1.242-3.588, P = 0.006). CONCLUSIONS Chronic HCV infection can affect the liver function of pregnant women, but does not increase the pregnancy or delivery complication risks. HCV RNA(+) is an independent risk factor for neonatal jaundice.
Humans ; Female ; Pregnancy ; Adult ; Pregnancy Complications, Infectious/epidemiology* ; Retrospective Studies ; Pregnancy Outcome ; Infant, Newborn ; Viremia/virology* ; Hepatitis C ; Hepacivirus/physiology* ; Hepatitis C, Chronic/virology* ; Young Adult ; Alanine Transaminase/blood*

OBJECTIVE: To investigate the association between long-term glycemic control and cerebral infarction risk in patients with diabetes through a large-scale cohort study. METHODS: This prospective, community-based cohort study included 12,054 patients with diabetes. From 2006 to 2012, 38,272 fasting blood glucose (FBG) measurements were obtained from these participants. FBG trajectory patterns were generated using latent mixture modelling. Cox proportional hazards models were applied to assess the subsequent risk of cerebral infarction associated with different FBG trajectory patterns. RESULTS: At baseline, the mean age of the participants was 55.2 years. Four distinct FBG trajectories were identified based on FBG concentrations and their changes over the 6-year follow-up period. After a median follow-up of 6.9 years, 786 cerebral infarction events were recorded. Different trajectory patterns were associated with significantly varied outcome risks (Log-Rank P < 0.001). Compared with the low-stability group, Hazard Ratio ( HR) adjusted for potential confounders were 1.37 for the moderate-increasing group, 1.23 for the elevated-decreasing group, and 2.08 for the elevated-stable group. CONCLUSION Sustained high FBG levels were found to play a critical role in the development of ischemic stroke among patients with diabetes. Controlling FBG levels may reduce the risk of cerebral infarction.
Humans ; Cerebral Infarction/blood* ; Middle Aged ; Male ; Female ; Blood Glucose/analysis* ; Fasting/blood* ; Aged ; Prospective Studies ; Risk Factors ; Diabetes Mellitus/blood* ; Adult ; Proportional Hazards Models

Objective:To explore the genetic basis for a Chinese pedigree affected with co-morbid Ornithine carbamoyl transferase deficiency (OTCD) and MECP2 duplication syndrome.Methods:A proband who was admitted to the Neonatal Intensive Care Unit of Gansu Provincial Maternal and Child Health Care Hospital on December 19, 2017 was selected as the study subject. High-throughput sequencing and multiplex ligation-dependent probe amplification (MLPA) were carried out for her pedigree, and short tandem repeat-based linkage analysis and chromosome copy number variation sequencing (CNV-seq) were used for the prenatal diagnosis.Results:The proband, a 3-day-old female, was found to harbor heterozygous deletion of exons 7-9 of the OTC gene. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variant was classified as likely pathogenic (PVS1+ PM2_Supporting+ PP4). The proband was diagnosed with OTCD, which was in keeping with her acute encephalopathy and metabolic abnormalities (manifesting as hyperammonemia, decreased blood citrulline, and increased urine orotic acid). Prenatal diagnosis was carried out for the subsequent pregnancy. The fetus did not harbor the exons 7-9 deletion of the OTC gene, but was found to carry a duplication in Xq28 region (which encompassed the whole region of MECP2 duplication syndrome) and was positive for the SRY sequence. The same duplication was also found in the proband and her mother. Considering the possible existence of X-chromosome inactivation, the proband was diagnosed with two X-linked recessive disorders including OTCD and MECP2 duplication syndrome, and the fetus was determined as a male affected with the MECP2 duplication syndrome. Conclusion:Discoveries of the pathogenic variants underlying the OTCD and MECP2 duplication syndrome have enabled clinical intervention, treatment, genetic counseling and prenatal diagnosis for this pedigree.

Objective To screen the key characteristic genes of metastatic nasopharyngeal carcinoma(mNPC)and analyze the immune cell infiltration in tumor microenvironment using machine learning algorithm.Methods Firstly,the training set GSE103611 was downloaded from the GEO database,and the data were subjected to differential expression gene(DEGs)screening,Gene Ontology(GO),Kyoto Encyclopedia of Genes and Genome(KEGG)and immune cell infiltration analysis.Second,the predicted genes in DEGs were screened by least absolute shrinkage and selector operation(LASSO)regression,and the characteristic genes were screened by using the expression level of the predicted genes and receiver operating characteristic(ROC).Third,the correlation between characteristic genes and immune cells was further analyzed to determine the key characteristic genes.Finally,the expression levels of key characteristic genes and ROC were verified using the reverse validation set GSE1245 data.Results A total of 136 DEGs were obtained,and their KEGG were mainly enriched in cytochrome P450,tumor necrosis factor(TNF)signaling pathway,prion disease,EB virus infection,and other pathways.GO was mainly enriched in the negative regulatory processes of peptide-based tyrosine phosphorylation modification,viral gene expression,and B cell and leukocyte activation.The difference in the degree of infiltration of the 22 immune cells in nasopharyngeal carcinoma(NPC)and mNPC was not significant.Two key characteristic genes(DAZ1 and SCCPDH)of mNPC were finally obtained by LASSO regression,and they were significantly correlated with immune cells in the mNPC microenvironment(P＜0.05).In the reverse validation data set,the differential expressions of DAZ1 and SCCPDH between non-NPC(nNPC)and NPC groups were not significant(P＞0.05),and the AUC values of ROC of both were less than 0.6.Conclusion DAZ1 and SCCPDH are the key characteristic genes of mNPC and can be used as important markers for mNPC and immunotherapy.

Drug resistance presents a significant challenge to achieving positive clinical outcomes in anti-tumor therapy.Prior research has illuminated reasons behind drug resistance,including increased drug efflux,alterations in drug targets,and abnormal activation of oncogenic pathways.However,there's a need for deeper investigation into the impact of drug-resistant cells on parental tumor cells and intricate crosstalk between tumor cells and the malignant tumor microenvironment(TME).Recent studies on extracellular vesicles(EVs)have provided valuable insights.EVs are membrane-bound particles secreted by all cells,mediating cell-to-cell communication.They contain functional cargoes like DNA,RNA,lipids,proteins,and metabolites from mother cells,delivered to other cells.Notably,EVs are increasingly recognized as regulators in the resistance to anti-cancer drugs.This review aims to summarize the mechanisms of EV-mediated anti-tumor drug resistance,covering therapeutic approaches like chemo-therapy,targeted therapy,immunotherapy and even radiotherapy.Detecting EV-based biomarkers to predict drug resistance assists in bypassing anti-tumor drug resistance.Additionally,targeted inhibition of EV biogenesis and secretion emerges as a promising approach to counter drug resistance.We highlight the importance of conducting in-depth mechanistic research on EVs,their cargoes,and functional ap-proaches specifically focusing on EV subpopulations.These efforts will significantly advance the devel-opment of strategies to overcome drug resistance in anti-tumor therapy.

Objective To explore the construction and visualization for knowledge graph of Ling Shu(Spiritual Pivot),with a view to providing ideas for the structured storage and display of the theoretical knowledge of the ancient Chinese medical books.Methods Using the professional idea of constructing knowledge graphs for reference,text mining technology was applied to construct the thesaurus,and then word division,entity recognition,and relationship extraction for the original text of Ling Shu were performed to get the elements of knowledge graph construction.The graph database Neo4j was used for the storage and query of the knowledge graph,and then the visual display of the knowledge graph was achieved.Results The 1 216 high-quality words consisting of the thesaurus of Ling Shu were obtained,and the construction of the knowledge graph of the theory of Ling Shu was realized.The constructed knowledge graph basically displayed the traditional Chinese medicine theories such as the correlation of visceral manifestations with essence qi,and the relationship between emotions and the five-zang organs described in Ling Shu,which made the retrieval and utilization of the related entities and relationships possible,and provided ideas for the structured storage and display of the theoretical knowledge of the ancient books of Chinese medicine.Conclusion The knowledge graph construction technology can be used to obtain the Chinese medicine theoretical knowledge graph of Ling Shu,and to display the knowledge connections of yin-yang and the five elements,and the internal organs and meridians expressed in the Ling Shu.The construction of the knowledge graph and its storage in the graph database enable the knowledge graph involved in the text of Ling Shu to be displayed in the form of visualized semantic network graph,and also make the embedding of other search systems such as the semantic search and semantic wiki possible,which will be helpful for the development of Chinese medicine intelligent medical services.