ObjectiveTo explore the mechanism by which Sini San （SNS） inhibits ferroptosis， alleviates inflammation and myocardial injury， and improves myocardial infarction （MI）. MethodsThe active ingredients of SNS were obtained by searching the Traditional Chinese Medicine System Pharmacology Platform （TCMSP） database， its target sites were predicted using the SwissTargetPrediction Database， and the core components were screened out using the CytoNCA plug-in. The targets of MI and ferroptosis were obtained by using GeneCards， Online Mendelian Inheritance in Man （OMIM） database， DrugBank， Therapeutic Target Database （TTD）， FerrDb database and literature review， respectively. The intersection of these targets of SNS-MI-ferroptosis was plotted as a Venn diagram. The protein-protein interaction （PPI） network was constructed using the STRING database， and the visualization graph was prepared using Cytoscape. The core targets were screened out using the CytoNCA plug-in， and the biological functions were clustered by the MCODE plug-in. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed using the David database. Molecular docking was performed using AutoDock and visualized with PyMOL2.5.2. The Kunming mice were randomly divided into the control group， the model group， the SNS group， and the trimetazidine （TMZ） group. The mice were subcutaneously injected with isoprenaline （ISO， 5 mg·kg^-1·d^-1） to establish an MI model. The drug was continuously intervened for 7 days. The ST-segment changes were recorded by electrocardiogram （ECG）， and the tissue morphology changes were observed by hematoxylin-eosin （HE） staining. Cardiomyocyte ferroptosis was investigated by transmission electron microscopy. Serum creatine kinase （CK）， creatine kinase isoenzyme （CK-MB）， lactate dehydrogenase （LDH）， reduced glutathione （GSH）， and malondialdehyde （MDA） levels were detected by biochemical assay. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum levels of interleukin （IL）-6 and 4-hydroxynonenal （4-HNE）. Immunohistochemical staining was employed to detect IL-6 and phosphorylated signal transducer and transcription activator 3 （p-STAT3） in cardiac tissues. Western blot was used to detect STAT3 and p-STAT3 in cardiac tissues. Real-time PCR was used to detect the levels of IL-6， IL-18， solute carrier family 7 member 11 （SLC7A11）， arachidonic acid 15-lipoxygenase （ALOX15）， and glutathione peroxidase 4 （GPx4） in cardiac tissues. ResultsA total of 121 active ingredients of SNS were obtained， and 58 potential targets of SNS in the treatment of MI by regulating ferroptosis were screened. The three protein modules with a score5 were mainly related to the inflammatory response. The GO function was mainly related to inflammation， and KEGG enrichment analysis showed that SNS mainly regulated ferroptosis- and inflammation- related signaling pathways. Molecular docking indicated that the core component had a higher binding force to the target site. Animal experiments confirmed that SNS reduced the level of p-STAT3 （P0.01）， down-regulated the expression of ALOX15 mRNA （P0.01）， up-regulated the level of serum GSH， and the expressions of SLC7A11 and GPx4 mRNA， reduced MDA and 4-HNE levels （P0.05， P0.01）. Additionally， SNS improved the mitochondrial injury induced by cardiomyocyte ferroptosis， reduced the area of MI， alleviated inflammation and myocardial injury， lowered the levels of serum CK， CK-MB， LDH， IL-6， and the mRNA expression levels of IL-16 and IL-18 （P0.05）， and improved ST segment elevation. ConclusionSNS can reduce ISO-induced STAT3 phosphorylation levels， inhibit ferroptosis in cardiomyocytes， alleviate inflammation and myocardial injury， thereby improving MI.

ObjectiveTo explore the mechanism by which Sini San （SNS） inhibits ferroptosis， alleviates inflammation and myocardial injury， and improves myocardial infarction （MI）. MethodsThe active ingredients of SNS were obtained by searching the Traditional Chinese Medicine System Pharmacology Platform （TCMSP） database， its target sites were predicted using the SwissTargetPrediction Database， and the core components were screened out using the CytoNCA plug-in. The targets of MI and ferroptosis were obtained by using GeneCards， Online Mendelian Inheritance in Man （OMIM） database， DrugBank， Therapeutic Target Database （TTD）， FerrDb database and literature review， respectively. The intersection of these targets of SNS-MI-ferroptosis was plotted as a Venn diagram. The protein-protein interaction （PPI） network was constructed using the STRING database， and the visualization graph was prepared using Cytoscape. The core targets were screened out using the CytoNCA plug-in， and the biological functions were clustered by the MCODE plug-in. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed using the David database. Molecular docking was performed using AutoDock and visualized with PyMOL2.5.2. The Kunming mice were randomly divided into the control group， the model group， the SNS group， and the trimetazidine （TMZ） group. The mice were subcutaneously injected with isoprenaline （ISO， 5 mg·kg^-1·d^-1） to establish an MI model. The drug was continuously intervened for 7 days. The ST-segment changes were recorded by electrocardiogram （ECG）， and the tissue morphology changes were observed by hematoxylin-eosin （HE） staining. Cardiomyocyte ferroptosis was investigated by transmission electron microscopy. Serum creatine kinase （CK）， creatine kinase isoenzyme （CK-MB）， lactate dehydrogenase （LDH）， reduced glutathione （GSH）， and malondialdehyde （MDA） levels were detected by biochemical assay. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum levels of interleukin （IL）-6 and 4-hydroxynonenal （4-HNE）. Immunohistochemical staining was employed to detect IL-6 and phosphorylated signal transducer and transcription activator 3 （p-STAT3） in cardiac tissues. Western blot was used to detect STAT3 and p-STAT3 in cardiac tissues. Real-time PCR was used to detect the levels of IL-6， IL-18， solute carrier family 7 member 11 （SLC7A11）， arachidonic acid 15-lipoxygenase （ALOX15）， and glutathione peroxidase 4 （GPx4） in cardiac tissues. ResultsA total of 121 active ingredients of SNS were obtained， and 58 potential targets of SNS in the treatment of MI by regulating ferroptosis were screened. The three protein modules with a score5 were mainly related to the inflammatory response. The GO function was mainly related to inflammation， and KEGG enrichment analysis showed that SNS mainly regulated ferroptosis- and inflammation- related signaling pathways. Molecular docking indicated that the core component had a higher binding force to the target site. Animal experiments confirmed that SNS reduced the level of p-STAT3 （P0.01）， down-regulated the expression of ALOX15 mRNA （P0.01）， up-regulated the level of serum GSH， and the expressions of SLC7A11 and GPx4 mRNA， reduced MDA and 4-HNE levels （P0.05， P0.01）. Additionally， SNS improved the mitochondrial injury induced by cardiomyocyte ferroptosis， reduced the area of MI， alleviated inflammation and myocardial injury， lowered the levels of serum CK， CK-MB， LDH， IL-6， and the mRNA expression levels of IL-16 and IL-18 （P0.05）， and improved ST segment elevation. ConclusionSNS can reduce ISO-induced STAT3 phosphorylation levels， inhibit ferroptosis in cardiomyocytes， alleviate inflammation and myocardial injury， thereby improving MI.

OBJECTIVE To construct an intelligent pharmaceutical Q&A platform for precision medication with low “artificial intelligence （AI） hallucination”， aiming to enhance the accuracy， consistency， and traceability of medication consultations. METHODS Medication package inserts were batch-processed and converted into structured data through Python programming to build a local pharmaceutical knowledge base. The retrieval and question-answering processes were designed based on large language models， and system integration and localized deployment were completed on Dify platform. By designing typical clinical medication questions and comparing the output of the intelligent pharmaceutical Q&A platform with the online version of DeepSeek across dimensions such as peak time retrieval， half-life， and dosage adjustment reasoning for patients with renal impairment， the accuracy and reliability of its retrieval and reasoning results were evaluated. RESULTS The intelligent pharmaceutical Q&A platform， constructed based on local drug package inserts， achieved 100% accuracy in retrieval and reasoning for peak time， half-life， and dosage adjustment schemes. In comparison， the online version of DeepSeek demonstrated accuracies of 30%（6/20）， 50%（10/20）， and 38%（23/60） across these three dimensions， respectively. CONCLUSIONS The constructed intelligent pharmaceutical Q&A platform is capable of accurately retrieving and extracting information from the local knowledge base based on clinical inquiries， thereby avoiding the occurrence of AI hallucinations and providing reliable medication decision support for healthcare professionals.

BACKGROUND: The transcription factor POU2F1 regulates the expression levels of microRNAs in neoplasia. However, the miR-29b1/a cluster modulated by POU2F1 in gastric cancer (GC) remains unknown. METHODS: Gene expression in GC cells was evaluated using reverse-transcription polymerase chain reaction (PCR), western blotting, immunohistochemistry, and RNA in situ hybridization. Co-immunoprecipitation was performed to evaluate protein interactions. Transwell migration and invasion assays were performed to investigate the biological behavior of GC cells. MiR-29b1/a cluster promoter analysis and luciferase activity assay for the 3'-UTR study were performed in GC cells. In vivo tumor metastasis was evaluated in nude mice. RESULTS: POU2F1 is overexpressed in GC cell lines and binds to the miR-29b1/a cluster promoter. POU2F1 is upregulated, whereas mature miR-29b-3p and miR-29a-3p are downregulated in GC tissues. POU2F1 promotes GC metastasis by inhibiting miR-29b-3p or miR-29a-3p expression in vitro and in vivo . Furthermore, PIK3R1 and/or PIK3R3 are direct targets of miR-29b-3p and/or miR-29a-3p , and the ectopic expression of PIK3R1 or PIK3R3 reverses the suppressive effect of mature miR-29b-3p and/or miR-29a-3p on GC cell metastasis and invasion. Additionally, the interaction of PIK3R1 with PIK3R3 promotes migration and invasion, and miR-29b-3p , miR-29a-3p , PIK3R1 , and PIK3R3 regulate migration and invasion via the phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/Akt/mTOR) pathway in GC cells. In addition, POU2F1 , PIK3R1 , and PIK3R3 expression levels negatively correlated with miR-29b-3p and miR-29a-3p expression levels in GC tissue samples. CONCLUSIONS The POU2F1 - miR-29b-3p / miR-29a-3p-PIK3R1 / PIK3R1 signaling axis regulates tumor progression and may be a promising therapeutic target for GC.
MicroRNAs/metabolism* ; Humans ; Stomach Neoplasms/pathology* ; Cell Line, Tumor ; Cell Movement/physiology* ; Phosphatidylinositol 3-Kinases/metabolism* ; Animals ; Mice ; Octamer Transcription Factor-1/metabolism* ; Mice, Nude ; Class Ia Phosphatidylinositol 3-Kinase/metabolism* ; Neoplasm Invasiveness ; Gene Expression Regulation, Neoplastic/genetics* ; Male ; Immunohistochemistry ; Female

Brain-computer interface (BCI) technology is an innovative and cutting-edge medical advancement that enables direct interaction between the brain and external devices, facilitating the reconstruction of daily functions for patients or serving as a method for neuro-regulation therapy. Although this technology offers a broad range of clinical applications, there are problems as potential risks, individual variations, and the need for long-term monitoring of its effects during utilization. Consequently, the comprehensive evaluation of its safety and effectiveness poses a considerable challenge for regulatory agencies. This study provides a concise introduction to the development history and various types of BCI technology, followed by a summary of the regulatory situation for different types of BCI medical devices in the United States. Furthermore, the regulatory requirements imposed by the US FDA on this product category are analyzed. Finally, the article concludes by presenting a summary and future perspective on the current development of BCI technology, with the aim of offering beneficial insights and guidance for the regulation of BCI medical devices.
Brain-Computer Interfaces ; United States ; United States Food and Drug Administration ; Humans ; Electroencephalography

Dendritic cells (DCs) serve as the primary antigen-presenting cells in autoimmune diseases, like rheumatoid arthritis (RA), and exhibit distinct signaling profiles due to antigenic diversity. Type II collagen (CII) has been recognized as an RA-specific antigen; however, little is known about CII-stimulated DCs, limiting the development of RA-specific therapeutic interventions. In this study, we show that CII-stimulated DCs display a preferential gene expression profile associated with migration, offering a new perspective for targeting DC migration in RA treatment. Then, saikosaponin D (SSD) was identified as a compound capable of blocking CII-induced DC migration and effectively ameliorating arthritis. Optineurin (OPTN) is further revealed as a potential SSD target, with Optn deletion impairing CII-pulsed DC migration without affecting maturation. Function analyses uncover that OPTN prevents the proteasomal transport and ubiquitin-dependent degradation of C-C chemokine receptor 7 (CCR7), a pivotal chemokine receptor in DC migration. Optn-deficient DCs exhibit reduced CCR7 expression, leading to slower migration in CII-surrounded environment, thus alleviating arthritis progression. Our findings underscore the significance of antigen-specific DC activation in RA and suggest OPTN is a crucial regulator of CII-specific DC migration. OPTN emerges as a promising drug target for RA, potentially offering significant value for the therapeutic management of RA.

Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.

Objective By using intravoxel incoherent motion(IVIM)double exponential model liver multi-b value diffusion-weighted imaging(DWI)scanning technique to analyze the lesion's IVIM parameters before and after interventional treatment of hepatocellular carcinoma(HCC)with conventional transcatheter arterial chemoembolization(TACE)combined with CalliSpheres drug-loaded microspheres(DEB-TACE),based on which to quantitatively evaluate the efficacy of interventional therapy for HCC.Methods A total of 40 HCC patients,who were admitted to the Department of Interventional Therapy of Anqing Municipal Hospital of China from June 2022 to November 2023 to receive DEB-T ACE,were enrolled in this study.Routine MR examination,DWI and IVIM-DWI scan were performed before and at 1,3 and 6 months after treatment,and a total of 40 interest lesions were selected.The ADC value,perfusion fraction(f),pure diffusion coefficient(D),and perfusion-related diffusion coefficient(D*)of each lesion were analyzed.The receiver operating characteristic(ROC)curve was drawn to analyze the prognosis assessment value of IVIM-DWI parameters.Results After DEB-TACE treatment,the ADC value and D value were increased,and the f value was decreased when compared with their preoperative values,the differences were statistically significant(all P＜0.01).The ADC value and D value in the patients of effective group were remarkably higher than those in the patients of ineffective group,the differences were statistically significant(both P＜0.01);the f value in the patients of effective group was slightly lower than that in the patients of ineffective group,and the difference was statistically significant(P＜0.05).The areas under ROC curve of ADC value,D value and f value for evaluating efficacy were 0.762,0.877,and 0.708 respectively.The area under the curve for the joint assessment of the three parameters was 0.928,with the highest efficacy.Conclusion IVIM-DWI can quantitatively determine the microperfusion and activity of HCC lesions before and after interventional DEB-TACE treatment,and it can also evaluate the curative efficacy of interventional therapy for HCC as well as the outcome of HCC lesions.

Objective:To develop a nomogram model for predicting the risk of ventilator-associated pneumonia (VAP) in patients with mechanical ventilation (MV) and to validate the stability of the prediction performance of the model.Methods:The patients with MV admitted to the Department of Critical Care Medicine of General Hospital of Ningxia Medical University from January 2019 to December 2022 were retrospectively selected according to the order of admission. The patients with MV were divided into the non-VAP group and the VAP group according to whether VAP occurred. The clinical data of the two groups, including general information, disease, medication, condition, and operation-related indicators were collected as candidate predictors of the model for comparison. Multivariate logistic stepwise forward regression analysis was used to screen the predictors that finally entered the model, and a nomogram model was constructed. The model discrimination was evaluated by the area under the receiver operating characteristic curve (AUC), the diagnostic test results of the model at the predicted threshold were calculated, the Hosmer-Lemeshow test was used to evaluate the model fit, and the Bootstrap resampling was used 1 000 times for internal validation, and model calibration and clinical applicability were evaluated by calibration curve and decision analysis curve, respectively.Results:A total of 1 250 patients with MV were included, including 1 102 patients in the non-VAP group and 148 patients in the VAP group, and the prevalence of VAP was 11.8%. The detection of multidrug-resistant organisms, chronic kidney disease, brain injury, oxygenation index, the place of tracheal intubation, reintubation, use of bronchoscopy, use of antibiotics, and MV duration were model predictors of VAP. The AUC of the nomogram model was 0.917 (95% CI: 0.895-0.939), the maximum Youden index of 0.697 corresponded to a prediction threshold of 0.096. The model accuracy, sensitivity and specificity were 0.836, 0.865, and 0.832, respectively. The positive predictive value and the negative predictive value were 0.409 and 0.979, respectively. The Hosmer- Lemeshow test indicated that the model fit well ( P=0.938). The results of the internal validation of the model showed that the predicted risk of the calibration curve was generally consistent with the actual risk, and the decision threshold probability of the decision analysis curve ranged from 2% to 90%. Conclusions:The nomogram model developed in this study is simple, convenient and has relatively stable prediction performance, which can be externally validated to evaluate the extrapolation of the model, and provide a basis for individualized clinical prediction of the risk of VAP in patients with MV.

ObjectiveTo investigate the menstrual conditions of women infected with COVID-19 in Shanghai and analyze the influencing factors. MethodsFrom December 2022 to March 2023， menstrual data from 281 women infected with COVID-19 in Shanghai were collected with a questionnaire survey， including usual menstrual characteristics， the most recent menstrual period post-infection， symptoms of infection， and medication usage. According to the crossover period between the menstrual period and the infection period of the respondents， the samples were divided into two groups for comparative analysis： those whose menstrual and infection periods overlapped （positive group） and those whose menstruation started after conversion to virus-negative （negative conversion group）. ResultsAmong the 281 respondents， 196 （65.8%） experienced menstrual changes. Among them， 145 （51.6%） had changes in menstrual volume， color and texture， and 109 （38.8%） had changes in menstrual duration or cycle. Decreased menstrual volume （22.1%）， darker color （23.49%）， thicker texture （21.0%）， increased blood clots （16.7%）， and prolonged duration （21.8%） were observed in both groups. The rate of changes in menstrual volume， color， and texture was higher in the positive group （56.8%， 69/110） than that in negative group （37.3%， 76/171） （P<0.05）. Regarding the menstrual cycle changes， the rate of early onset was higher in the positive group （14.5%） compared to the negative conversion group （3.5%）（P<0.05）， while the rate of delayed menstruation was higher in the negative conversion group （25.1%） than that in the positive group （5.5%） （P<0.05）. Correlation analysis showed a weak association between sore throat and menstrual changes （r=0.154， P<0.05）. ConclusionSome women infected with COVID-19 experience short-term changes in their menstrual conditions， characterized by reduced volume， darker color， thick texture， increased clots， and prolonged menstrual duration， reflecting a pathogenesis of blood stasis. Menstruation during the infection period tends to occur earlier， while delayed menstruation is more prevalent at post-conversion.