Objective:To summarize the medication law and academic experience of Professor Yuan Jinsheng in the treatment of angina pectoris (AP) of coronary heart disease (CHD) through R language data mining technique.Methods:The effective outpatient medical records of Professor Yuan Jinsheng in the treatment of AP of CHD from January 1, 2016 to September 30, 2023 were selected, and the R 4.2.3 was used for frequency statistics, association rule analysis, systematic clustering analysis and correlation analysis of prescription drugs.Results:A total of 292 prescriptions were included, including 268 patients, involving 204 kinds of Chinese materia medica, and the total frequency of Chinese materia medica was 4 253 times. The main properties were warm and neutral, the main tastes were bitter, pungent and sweet, and the main meridians were spleen, lung and liver meridians. The analysis of association rules obtained 125 core TCM combinations, and the commonly used drug pair was Trichosanthis Fructus-Aurantii Fructus Immaturus. The core prescription composed of Aurantii Fructus Immaturus, Chuanxiong Rhizoma, Trichosanthis Fructus, Citri Reticulatae Pericarpium and Salviea Miltiorrhizae Radix et Rhizoma. Seven TCM groups of were obtained by systematic clustering analysis. Correlation analysis showed that the drug pairs with phi coefficient greater than 0.6 were in 8 groups.Conclusions:Studies suggest that AP of CHD is located in the heart, which is related to lung, spleen, liver and kidney, deficiency in root and excess in superficiality, phlegm, blood stasis and qi stagnation are important pathological factors. The treatment is based on the basic principles of tonifying qi, promoting yang, relieving rheumatism, resolving phlegm, activating blood circulation, and promoting qi circulation. It embodies Professor Yuan's academic thoughts and principles of differentiation and treatments of "taking fluency as the main point, regulating the five internal organs and weighing the root and superficiality".

OBJECTIVE: To develop a method for identifying high-risk patients among septic populations requiring mechanical ventilation, and to conduct phenotypic analysis based on this method. METHODS: Data from four sources were utilized: the Medical Information Mart for Intensive Care (MIMIC-IV 2.0, MIMIC-III 1.4), the Philips eICU-Collaborative Research Database 2.0 (eICU-CRD 2.0), and the Anhui Medical University Second Affiliated Hospital dataset. The adult patients in intensive care unit (ICU) who met Sepsis-3 and received invasive mechanical ventilation (IMV) on the first day of first admission were enrolled. The MIMIC-IV dataset with the highest data integrity was divided into a training set and a test set at a 6:1 ratio, while the remaining datasets were served as validation sets. The demographic information, comorbidities, laboratory indicators, commonly used ICU scores, and treatment measures of patients were extracted. Clinical data collected within first day of ICU admission were used to calculate the sequential organ failure assessment (SOFA) score. K-means clustering was applied to cluster SOFA score components, and the sum of squared errors (SSE) and Davies-Bouldin index (DBI) were used to determine the optimal number of disease subtypes. For clustering results, normalized methods were employed to compare baseline characteristics by visualization, and Kaplan-Meier curves were used to analyze clinical outcomes across phenotypes. RESULTS: This study enrolled patients from MIMIC-IV dataset (n = 11 166), MIMIC-III dataset (n = 4 821), eICU-CRD dataset (n = 6 624), and a local dataset (n = 110), with the four datasets showing similar median ages and male proportions exceeding 50%; using 85% of the MIMIC-IV dataset as the training set, 15% as the test set, and the rest dataset as the validation set. K-means clustering based on the six-item SOFA score was performed to determine the optimal number of clusters as 3, and patients were finally classified into three phenotypes. In the training set, compared with the patients with phenotype II and phenotype III, those with phenotype I had the more severe circulatory and respiratory dysfunction, a higher proportion of vasoactive drug usage, more obvious metabolic acidosis and hypoxia, and a higher incidence of congestive heart failure. The patients with phenotype II was dominated by respiratory dysfunction with higher visceral injury. The patients with phenotype III had relatively stable organ function. The above characteristics were consistent in both the test and validation sets. Analysis of infection-related indicators showed that the patients with phenotype I had the highest SOFA score within 7 days after ICU admission, initial decreases and later increases in platelet count (PLT), and higher counts of neutrophils, lymphocytes, and monocytes as compared with those with phenotype II and phenotype III, their blood cultures had a higher positivity rates for Gram-positive bacteria, Gram-negative bacteria and fungi as compared with those with phenotype II and phenotype III. The Kaplan-Meier curve indicated that in the training, test, and validation sets, the 28-day cumulative mortality of patients with phenotype I was significantly higher than that of patients with phenotypes II and phenotype III. CONCLUSIONS Three distinct phenotypes in septic patients receiving IMV based on unsupervised machine learning is derived, among which phenotype I, characterized by cardiorespiratory failure, can be used for the early identification of high-risk patients in this population. Moreover, this population is more prone to bloodstream infections, posing a high risk and having a poor prognosis.
Humans ; Machine Learning ; Sepsis/therapy* ; Respiration, Artificial ; Intensive Care Units ; Organ Dysfunction Scores ; Male ; Female ; Middle Aged ; Adult

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged

OBJECTIVE: To investigate the anti-inflammatory effect of rutaecarpine (RUT) on monosodium urate crystal (MSU)-induced murine peritonitis in mice and further explored the underlying mechanism of RUT in lipopolysaccharide (LPS)/MSU-induced gout model in vitro. METHODS: In MSU-induced mice, 36 male C57BL/6 mice were randomly divided into 6 groups of 8 mice each group, including the control group, model group, RUT low-, medium-, and high-doses groups, and prednisone acetate group. The mice in each group were orally administered the corresponding drugs or vehicle once a day for 7 consecutive days. The gout inflammation model was established by intraperitoneal injection of MSU to evaluate the anti-gout inflammatory effects of RUT. Then the proinflammatory cytokines were measured by enzyme-linked immunosorbent assay (ELISA) and the proportions of infiltrating neutrophils cytokines were detected by flow cytometry. In LPS/MSU-treated or untreated THP-1 macrophages, cell viability was observed by cell counting kit 8 and proinflammatory cytokines were measured by ELISA. The percentage of pyroptotic cells were detected by flow cytometry. Respectively, the mRNA and protein levels were measured by real-time quantitative polymerase chain reaction (qRT-PCR) and Western blot, the nuclear translocation of nuclear factor κB (NF-κB) p65 was observed by laser confocal imaging. Additionally, surface plasmon resonance (SPR) and molecular docking were applied to validate the binding ability of RUT components to tumor necrosis factor α (TNF-α) targets. RESULTS: RUT reduced the levels of infiltrating neutrophils and monocytes and decreased the levels of the proinflammatory cytokines interleukin 1β (IL-1β) and interleukin 6 (IL-6, all P<0.01). In vitro, RUT reduced the production of IL-1β, IL-6 and TNF-α. In addition, RT-PCR revealed the inhibitory effects of RUT on the mRNA levels of IL-1β, IL-6, cyclooxygenase-2 and TNF-α (P<0.05 or P<0.01). Mechanistically, RUT markedly reduced protein expressions of tumor necrosis factor receptor (TNFR), phospho-mitogen-activated protein kinase (p-MAPK), phospho-extracellular signal-regulated kinase, phospho-c-Jun N-terminal kinase, phospho-NF-κB, phospho-kinase α/β, NOD-like receptor thermal protein domain associated protein 3 (NLRPS), cleaved-cysteinyl aspartate specific proteinase-1 and cleaved-gasdermin D in macrophages (P<0.05 or P<0.01). Molecularly, SPR revealed that RUT bound to TNF-α with a calculated equilibrium dissociation constant of 31.7 µmol/L. Molecular docking further confirmed that RUT could interact directly with the TNF-α protein via hydrogen bonding, van der Waals interactions, and carbon-hydrogen bonding. CONCLUSION RUT alleviated MSU-induced peritonitis and inhibited the TNFR1-MAPK/NF-κB and NLRP3 inflammasome signaling pathway to attenuate gouty inflammation induced by LPS/MSU in THP-1 macrophages, suggesting that RUT could be a potential therapeutic candidate for gout.
Animals ; NF-kappa B/metabolism* ; Male ; Indole Alkaloids/therapeutic use* ; Signal Transduction/drug effects* ; Mice, Inbred C57BL ; Inflammation/complications* ; Uric Acid ; Quinazolines/therapeutic use* ; NLR Family, Pyrin Domain-Containing 3 Protein/metabolism* ; Humans ; Gout/chemically induced* ; Inflammasomes/metabolism* ; Cytokines/metabolism* ; THP-1 Cells ; Mitogen-Activated Protein Kinases/metabolism* ; Mice ; Molecular Docking Simulation ; Lipopolysaccharides ; Quinazolinones

Aim To investigate the effect of ACSL4 on the malignant biological behavior of esophageal cancer cells and gefitinib resistance by regulating FASN,and to explore the related mechanism.Methods Thirty-five fresh esophageal cancer tissues and adjacent nor-mal tissues,and 30 esophageal cancer tissues with ge-fitinib resistance were collected.The expressions of ACSL4 and FASN were detected by qRT-PCR and im-munohistochemistry.The expression levels of ACSL4 and FASN in human normal esophageal cells HET-1 A,esophageal cancer cell lines ECA109,EC9706,TE-1 and TE-1/GR were detected by qRT-PCR.Cells in each group were constructed by liposome transfection technique,and the drug resistance and proliferation a-bility of cells were detected by cloning and CCK-8 as-say,cell apoptosis was detected by flow cytometry,cell invasion ability was detected by Transwell,and EMT pathway protein expression was detected by Western blot.Results Compared with adjacent normal tis-sues,the expression of ACSL4 and FASN genes in cancer tissues increased,and there was a positive corre-lation.The expression of ACSL4 significantly increased in ECA109,EC9706 and TE-1 cells compared with HET-1 A cells.With the increase of gefitinib concen-tration,the expression of ACSL4 in TE-1 cells gradually increased,and the expression of ACSL4 in TE-1/GR cells was higher than that of TE-1.Compared with the control group and the si-NC group,the cell proliferation and invasion ability of si-ACSL4 group decreased,the number of apoptosis increased,the expression of E-Cadherin increased,and the expression of N-Cadherin,Vimentin and β-catenin decreased.The response ex-periment showed that compared with the si-ACSL4 group and the si-ACSL4+oe-NC group,the cells in the si-ACSL4+oe-FASN group increased drug resistance,increased proliferation and invasion ability,decreased apoptosis number and decreased expression of E-Cad-herin.The expressions of N-Cadherin,Vimentin and β-catenin increased.Conclusions By down-regulating the expression of FASN,ACSL4 reverses the resistance of esophageal cancer TE-1/GR cells to gefitinib and in-hibits the proliferation,invasion and accelerates apopto-sis of TE-1/GR cells,which may be related to the regu-lation of EMT signaling pathway.

Objectives:Comparative analysis of the beagles acute-phase electrocardiographic,hemodynamic,left ventricular flow field status,and energy consumption characteristics of pacing at different sites of conduction system may help to elucidate the scientific mechanism of left bundle branch pacing(LBBP)as a option of physiological pacing therapy.Methods:Eight healthy adult beagles were used in this study.Initially,an active fixation lead was implanted in the right atrial appendage,followed by implantation of another active fixation lead at the right ventricular apex,distal His bundle,and left bundle septal branch,respectively.After connecting a dual-chamber pacemaker,electrocardiographic and acute phase hemodynamic parameters under sinus rhythm,right ventricular apex pacing(RVAP),distal His bundle pacing(DHBP),and LBBP states were collected and analyzed.Three complete cardiac cycles of standard apical three-chamber color Doppler dynamic images were acquired under vector flow mapping(VFM)mode.Offline analysis was performed on obtained parameters including isovolumic contraction period,rapid ejection period,isovolumic relaxation period,rapid filling period,atrial contraction period,and left ventricular intracavitary energy consumption.These parameters were compared under pacing at different sites and the linear correlations of major parameters were analyzed.Results:The QRS duration of baseline intrinsic sinus rhythm,RVAP,DHBP and LBBP were(45.0±4.0)ms,(98.4±6.2)ms,(50.0±4.5)ms and(62.0±4.7)ms,respectively.The LBBP-QRS duration was significantly wider than intrinsic sinus rhythm and DHBP,but significantly narrower than RVAP(all P<0.01).Compared with baseline AOO mode(the pacing rate was performed at 10 beats/min above the intrinsic heart rate),the change of acute phase maximum left ventricular pressure rise rate(LVdP/dtmax)in RVAP,DHBP and LBBP was([-7.89±5.67]% ),([0.74±2.05]% )and([-0.14±3.59]% ),respectively.There was no significant difference in LVdP/dtmax changes between DHBP and LBBP(P=0.667),but both pacing modalities were significantly better than RVAP(all P<0.01).The average energy consumption of the left ventricle under RVAP was significantly higher than that of intrinsic sinus rhythm,DHBP,and LBBP in isovolumic contraction period,rapid ejection period,isovolumic relaxation period,rapid filling period,and atrial contraction period(all P<0.01).However,there was no statistically significant difference in energy consumption among intrinsic sinus rhythm,DHBP,and LBBP during the above five phases(all P>0.05).DHBP and LBBP did not show a significant increase in the number of left ventricular vortices,vortex area,and circulation intensity compared to intrinsic sinus rhythm,and LBBP did not show a significant increase in vortex area and circulation intensity compared to DHBP.Conclusions:Although LBBP canines significantly prolonged the paced QRS duration,it showed no significant differences in acute phase left ventricular hemodynamics,left ventricular flow field status,and energy consumption compared to intrinsic sinus rhythm and DHBP.Performance of LBBP was superior to RVAP.This study may contribute to revealing the theoretical basis of LBBP as a feasible physiological pacing therapy.

Objective To evaluate the prognosis and safety of patients with advanced pancreatic ductal adenocarcinoma(PDAC)who received I-125 seed implantation in treatment with anti-PD-1 monoclonal antibody+chemotherapy.Methods A retrospective analysis was conducted on patients with stage Ⅳ metastatic PDAC who received anti-PD-1 combined chemotherapy treatment at Yixing Hospital,Jiangsu University from Jan 2021 to Jun 2023.Patients were divided into two groups based on whether they received I-125 seed implantation:the I-125 seed implantation+anti-PD-1 monoclonal antibody+Chemotherapy group(IPC group)and the anti-PD-1 monoclonal antibody+chemotherapy group(PC group).The follow-up period ranged from 2 to 24 months,with a median follow-up time of 9 months.The prognosis of patients was analysed in combination with peripheral blood biomarkers.The peripheral lymphocyte subsets of patients in different treatment groups were preliminarily analysed by flow cytometry.Results A total of 13 patients were included,with 5 in the IPC group and 8 in the PC group.Progression-free survival(PFS)and overall survival(OS)in the IPC group were significantly longer than those in the PC group.The treatment in the IPC group was relatively safe,adverse reactions were controllable.The neutrophil-lymphocyte ratio(NLR)and CD4/CD8 ratio indicated that the prognosis of the IPC patients was better.The levels of regulatory T cells(Treg)and active regulatory T cells(aTreg)cells in the IPC patients were reduced after treatment compared with those of the PC patients.Conclusion The addition of I-125 seed implantation can improve the prognosis of patients with advanced PDAC who receive anti-PD-1 monoclonal antibody+chemotherapy,the post-treatment levels of patients'circulating aTreg cells are reduced,and the combination therapy has good safety.

High mobility group box protein 1(HMGB1)is one of the most widely expressed protein member in the HMGs family,which is well known for its involvement in the body inflammatory response.Previous researches have found that it plays a significant role in cell migration,immune identification and neuroprotection.Spinal cord injury is a disease that causes severe damage to the nervous system,and neural circuits are disrupted after a spinal cord injury,which leads to many conditions including ischemia and hypoxia,inflammatory responses,demyelinating lesions,and glial scar formation that are detrimental to nerve regeneration and repair,making it one of the most difficult diseases to treat in the modern spinal surgery field.HMGB1 is upregulated after spinal cord injury,thereby regulating neuroinflam-matory responses,and participating in the neuronal apoptosis,promoting neuronal regeneration,and inducing neural stem cell differentiation and migration,which plays an important role in the process of neural function recovery.This paper summarizes the structure and function of HMGB1,as well as its role in spinal cord injury,in order to provide direction for founding therapeutic target for neurological function recovery after spinal cord injury.

Objective To use AI-assisted motor dysfunction assessment for quantitative evaluation of motor function in Parkinson's disease(PD)and multiple system atrophy-Parkinsonian type(MSA-P)in order to achieve accurate differential diagnosis.Methods A total of 105 participants aged ≥60 years were consecutively enrolled from the First and Third Medical Centers of Chinese PLA General Hospital between January and September 2024.Based on diagnostic criteria,they were divided into a PD group(48 cases),a MSA-P group(31 cases),and a control group(26 cases).The general information was collected,and the motor function was evaluated with Move-ment Dysfunction Assessment Software in order to assess the diagnostic value of the AI-assisted assessment in differentiating between PD and MSA-P.Results Significantly differences were observed among the three groups in terms of facial expression indicators,bilateral finger tapping frequency,bilateral hand movement frequency,right hand movement amplitude change rate,bilat-eral palm flipping frequency,bilateral toe tapping frequency,freezing load of bilateral toe tapping,bilateral leg flexibility frequency,right leg flexibility amplitude change rate,freezing load of bilat-eral leg flexibility,upright extension angular velocity,turnaround time,forward step frequency,backward step frequency,forward average stride length,backward average stride length,forward average walking speed,backward average walking speed,forward average step width,backward average step width,bilateral postural tremor frequency,bilateral postural tremor maximum am-plitude,bilateral action tremor frequency,bilateral action tremor maximum amplitude,and com-parison of bilateral resting tremor frequency(P＜0.05,P＜0.01).The MSA-P group exhibited significantly lower blink frequency,maximum amplitude and frequency of facial tremors,upright extension angular velocity,and step frequency,while higher ratio of mouth opening duration and longer turnaround time when compared with the PD group(P＜0.05,P＜0.01).The AUC value of the combined nine motor function indicators and the five facial expression indicators in differ-entiating PD from MSA-P was 0.943(95％CI:0.895-0.991,P=0.000)and 0.925(95％CI:0.870-0.981,P=0.000),respectively,both better than that of individual indicators.Conclusion Combi-nation assessment of facial expression,posture,gait with AI assistance can contribute to the dif-ferential diagnosis of PD and MSA-P.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.