To explore the clinical characteristics， imaging features， diagnostic approaches， effective treatment methods， and prognosis of labyrinthine infarction caused by anterior inferior cerebellar artery （AICA） occlusion.A retrospective analysis was conducted on the detailed clinical data of a patient with labyrinthine infarction caused by AICA occlusion， including medical history， symptoms and signs， auxiliary examination results， therapeutic interventions， and follow-up process. The characteristics of this condition were summarized through a review of the relevant literature.Following a comprehensive treatment regimen， including anti-platelet aggregation， lipid regulation， circulation improvement， nerve nutrition， anti-inflammation， and blood pressure and blood sugar regulation， the symptoms of the nervous system were relieved to a certain extent.Labyrinthine infarction caused by AICA occlusion is rare in clinical practice and its diagnosis is difficult. Early and accurate diagnosis and timely and standardized treatment are of great significance for improving the prognosis of patients. Attention should be paid to the management of high-risk factors.
Vertigo ; Deafness

Clinical research on rare diseases has always faced multiple challenges in clinical research design and implementation due to small sample sizes of patients,high heterogeneity,and limited research resources.The rapid development of digital intelligence technology has provided innovative solutions for rare disease research.This article systematically explores the current status and response strategies of clinical research on rare diseases in the digital intelligence age.On the one hand,the efficiency of rare disease research has been optimized through adaptive design,mixed trial mode,and precision medicine stratification methods.On the other hand,solutions based on digital technology have been proposed to address the practical challenges of recruitment difficulties and underrepresentation of rare disease clinical research patients,data management and technical barriers,and insufficient coverage of natural medical history and baseline databases through digital intelligence technology.By combining international collaboration,intelligent screening,and remote experiments,a multidisciplinary collaboration and international cooperation,adaptive design,digital data platform,and patient-centered remote research model have been constructed as the core implementation strategies.Typical cases demonstrate that digital intelligence technology not only effectively shortens the drug development cycle,but also significantly enhances patient benefits,providing a replicable practical paradigm for global rare disease research.The practice of digital platforms represented by the International Rare Disease Research Alliance and the China Rare Disease Diagnosis and Treatment Collaboration Network has further verified the feasibility and promotional value of the digitalization path.In summary,digital intelligence technology has shown considerable promise in overcoming the clinical research challenges of rare diseases and accelerating the development of treatment plans,providing systematic references for researchers,regulatory agencies,and patient organizations.It is expected to drive the clinical research of rare diseases towards a more efficient and accurate future.

Objective:To explore the relationship between general demographic characteristics,inflammatory indicators,nutritional indicators,pathological data and lymph node metastasis in endometrial cancer(EC)pa-tients,and to construct and validate a model for preoperative prediction of lymph node status in endometrial canc-er patients.Methods:The preoperative clinical data of 473 patients with EC who underwent surgical treatment in the Zhu Jiang Hospital of Southern Medical University from January 2010 to April 2024 were retrospectively ana-lyzed.The independent risk factors of lymph node metastasis of endometrial cancer were screened by univariate and multivariate Logistic regression analyses,and the nomogram prediction model was constructed by R soft-ware.The performance of the model was evaluated by the receiver operating characteristic(ROC)curve,calibra-tion curve and clinical decision curve.Results:Menopausal status,high grade biopsy pathology,CA125 ≥24.47U/ml,systemic immune inflammatory index(SII)≥710.91,and prognostic nutritional index(PNI)＜52.90 were in-dependent risk factors for lymph node metastasis in endometrial cancer(OR＞1,P＜0.05).The nomogram model constructed based on these five factors had an AUC of 0.853 in the training set and 0.871 in the test set.The cali-bration curve fitted well,and the clinical decision curve shows a positive benefit.Conclusions:The endometrial cancer lymph node metastasis prediction model constructed based on menopausal status,biopsy pathology,CA125,SII,and PNI has good accuracy and fit,with certain clinical application value.

Objective To conduct a retrospective analysis of the correlation among bedaquiline(BDQ)plasma concentrations,relevant clinical factors,and disease prognosis.Methods In this retrospective study,22 patients diagnosed with rifampicin-resistant tuberculosis(RR-TB),multidrug-resistant tuberculosis(MDR-TB),or pre-extensively drug-resistant tuberculosis(pre-XDR-TB)were enrolled.These patients were admitted to the tuberculosis ward of our hospital between February 2022 and October 2024.All patients were administered a treatment regimen containing BDQ.The cohort comprised 6 RR-TB patients(27.27%),12 MDR-TB patients(54.55%),and 4 pre-XDR-TB patients(18.18%).Peripheral blood samples were collected 2 hours after the oral administration of Bedaquiline.The plasma concentration of Bedaquiline was measured using liquid chromatography-tandem mass spectrometry(LC-MS/MS).Spearman correlation analysis was performed using R studio software with the ggplot2 and corrplot packages.The factors included the blood concentration of bedaquiline,electrocardiogram QTcF(QT interval corrected by the Fridericia method),liver and kidney function parameters,weight,age,body mass index,sex,blood uric acid level,serum creatinine level,and other relevant indicators.Results In 22 patients treated with BDQ,the plasma concentration reached a peak after 1.5 weeks of administration,and gradually stabilized after 2 weeks.The plasma concentration was approximately 1-3 μg/mL.After 24 weeks of withdrawal of bedaquiline,patients were continued to monitor their bedaquiline concentration and found that BDQ blood concentration in peripheral blood was approximate 1 μg/mL up to 36 weeks.The serum concentration of BDQ was not correlated with age,body weight,BMI,ALT,AST,GGT,TDiL,urea,uric acid and QT interval,but correlated with sputum negative transformation and serum creatinine.The correlation analysis between serum concentration of BDQ and acid-fast staining of sputum smear showed,the difference was significant(r=0.35,P<0.05).In addition,the correlation analysis between serum BDQ concentration and serum creatinine showed,the difference was significant(r=0.34,P<0.05).The results of multiple linear regression analysis showed that BDQ blood concentration was positively correlated with Scr level,and Scr was an independent factor affecting BDQ blood concentration.20 cases(90.9%,20/22)were cured,1 case died of Covid-19 virus infection,1 case was recurrence.Conclusions Regimens containing bedaquiline seem to exhibit relatively high safety profiles and good tolerability among patients with rifampicin-resistant,multidrug-resistant,or pre-extensively drug-resistant tuberculosis,typically yielding favorable treatment outcomes.The BDQ shows a positive correlation with serum creatinine(SCr).Consequently,close surveillance of BDQ levels and renal function remains of utmost importance throughout the treatment course.

Objective To investigate necroptosis-related diagnostic biomarkers of bronchopulmo-nary dysplasia(BPD)and their relationships with the immune microenvironment through the analysis of necroptosis-related genes(NRGs)in BPD.Methods The dataset GSE32472 was downloaded from the Gene Expression Omnibus(GEO)database,and NRGs were obtained from the Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway and Gene Cards databases.Differentially expressed necroptosis-related genes(DE-NRGs)were screened,and their biological functions and pathways were explored through functional enrichment analysis.Machine learning algorithms,inclu-ding least absolute shrinkage and selection operator(LASSO)and support vector machine-recursive feature elimination(SVM-RFE),were applied to screen feature genes.The Cell-type Ⅰdentification By Estimating Relative Subsets of RNA Transcripts(CIBERSORT)algorithm and the Estimation of Stromal and Immune Cells in Malignant Tumor Tissues using Expression Data(ESTIMATE)algo-rithm were used to explore the immune infiltration characteristics of BPD.Spearman correlation anal-ysis between feature genes and immune cells was performed using the"corrplot"package in R lan-guage.Results A total of 19 DE-NRGs were identified.The main biological functions and path-ways of DE-NRGs included the regulation of necroptosis and inflammatory responses.Three feature genes,namely flotillin-2(FLOT2),CASP8 and FADD-like apoptosis regulators(CFLAR),and charged multivesicular body protein 7(CHMP7),were further screened to construct a nomogram.In the validation sets GSE8586 and GSE188944,the area under the curve(AUC)values were all greater than 0.7.CIBERSORT analysis revealed that BPD group presented a higher proportion of naive B cells,neutrophils,eosinophils and resting mast cells compared to control group(P＜0.05).Meanwhile,the proportion of CD8+T cells,CD4+naive T cells,CD4+resting memory T cells,regulatory T cells,resting natural killer(NK)cells,M0 macrophages,M2 macrophages and activated dendritic cells was lower than that in the control group(P＜0.05).ESTIMATE analysis showed that the stromal score in the BPD group was higher than that in the control group,while the immune score was lower,with statistically significant differences(P＜0.05).Correlation analysis between the three feature genes and ESTIMATE scores indicated that FLOT2 and CFLAR were posi-tively correlated with the stromal score and negatively correlated with the immune score,whereas CHMP7 was positively correlated with the immune score and negatively correlated with the stromal score.Conclusion The three necroptosis-related feature genes can serve as diagnostic biomarkers for BPD-related necroptosis,with high diagnostic efficacy.They may play an important roles through immune mechanisms,providing new insights and theoretical references for the early diagnosis and immune intervention of BPD.

Objective To investigate the effect of programmed cell death-ligand 1(PD-L1)monoclonal antibody and paclitaxel(PTX)combined with lentinan(LNT)on human breast cancer MDA-MB-231 cells in vitro.Methods MDA-MB-231 cells,human peripheral blood mononuclear cells(PBMCs),and MDA-MB-231+PBMCs co-culture were randomly divided into control group,PTX group,LNT group,MPDL3280A(PD-L1 monoclonal antibody)group,PTX+LNT group,and PTX+LNT+MPDL3280A group.The cell activity was detected by CCK8.The expressions of MHC-I and PD-L1 were detected by flow cytometry.The levels of IFN-γ and TNF-α were detected by ELISA kits.Results Compared with control group,the activity of MDA-MB-231 cells was significant inhibited in PTX group,MPDL3280A group,PTX+LNT group,and PTX+LNT+MPDL3280A group(P＜0.01).LNT group and PTX+LNT+MPDL3280A group significantly promoted the immune effect of PBMCs(P＜0.05,P＜0.01).PTX+LNT+MPDL3280A group significantly inhibited the activity of MDA-MB-231cells co-cultured with PBMCs(0.56±0.16 vs.0.39±0.13,P＜0.05).Compared with the negative control,LNT significantly promoted the expression of PD-L1 in MDA-MB-231 and the secretion of IFN-γ by PBMCs(P＜0.05).Conclusion By blocking the effect between PD-L1 and PD-1,PD-L1 monoclonal antibody can improve immunity and promote the antitumor effect of PTX combined with LNT in vitro.

Objective:To explore the relationship between general demographic characteristics,inflammatory indicators,nutritional indicators,pathological data and lymph node metastasis in endometrial cancer(EC)pa-tients,and to construct and validate a model for preoperative prediction of lymph node status in endometrial canc-er patients.Methods:The preoperative clinical data of 473 patients with EC who underwent surgical treatment in the Zhu Jiang Hospital of Southern Medical University from January 2010 to April 2024 were retrospectively ana-lyzed.The independent risk factors of lymph node metastasis of endometrial cancer were screened by univariate and multivariate Logistic regression analyses,and the nomogram prediction model was constructed by R soft-ware.The performance of the model was evaluated by the receiver operating characteristic(ROC)curve,calibra-tion curve and clinical decision curve.Results:Menopausal status,high grade biopsy pathology,CA125 ≥24.47U/ml,systemic immune inflammatory index(SII)≥710.91,and prognostic nutritional index(PNI)＜52.90 were in-dependent risk factors for lymph node metastasis in endometrial cancer(OR＞1,P＜0.05).The nomogram model constructed based on these five factors had an AUC of 0.853 in the training set and 0.871 in the test set.The cali-bration curve fitted well,and the clinical decision curve shows a positive benefit.Conclusions:The endometrial cancer lymph node metastasis prediction model constructed based on menopausal status,biopsy pathology,CA125,SII,and PNI has good accuracy and fit,with certain clinical application value.