ObjectiveTo explore the relationship between plasma angiopoietin-like(ANGPTL) 3, ANGPTL8, coronary artery lesions, and major adverse cardiovascular events(MACE) after percutaneous coronary intervention(PCI) in patients with acute coronary syndrome(ACS) complicated by type 2 diabetes mellitus(T2DM).MethodsA total of 200 patients with ACS complicated by T2DM(comorbidity group) and 100 patients with pure ACS(pure ACS group) were selected from the Emergency Department of Beijing Tongren Hospital, Capital Medical University, from January 2021 to June 2023. Additionally, 100 healthy volunteers were selected as the healthy control group. According to the severity of coronary artery lesions, the ACS complicated by T2DM patients were divided into mild(62 cases), moderate(80 cases), and severe(58 cases) subgroups. Based on whether MACE occurred one year after PCI, the patients were divided into the MACE subgroup(71 cases) and the non-MACE subgroup(129 cases). The levels of plasma ANGPTL3 and ANGPTL8 were detected by enzyme-linked immunosorbent assay. Multivariate Logistic regression analysis was used to analyze the influencing factors of MACE in ACS complicated by T2DM after PCI. The receiver operating characteristic( ROC) curve was used to analyze the predictive value of plasma ANGPTL3 and ANGPTL8 levels for MACE after PCI.ResultsPlasma levels of ANGPTL3 and ANGPTL8 in the comorbidity group were higher than those in the pure ACS group, which were higher than those in the healthy control group(F/P=225.251/<0.001, 166.309/<0.001). Plasma levels of ANGPTL3 and ANGPTL8 increased sequentially from mild to moderate to severe subgroups(F/P=410.079/<0.001, 390.246/<0.001). Plasma ANGPTL3 and ANGPTL8 levels in ACS complicated by T2DM were positively correlated with the Gensini score(rs/P=0.803/<0.001,0.814/<0.001). Compared with non-MACE subgroup, cTnI,CK-MB,HbA1c,ANGPTL3, ANGPTL8 and Gensini score were increased in MACE subgroup(t/P=2.720/0.007,3.005/0.003,3.790/<0.001,7.914/<0.001,8.249/<0.001,7.048/<0.001).Multivariable Logistic regression analysis showed that increased Gensini score, elevated ANGPTL3, and elevated ANGPTL8 were independent risk factors for MACE after PCI in ACS complicated by T2DM[OR(95%CI)=1.053(1.030-1.077), 1.244(1.120-1.381), 1.017(1.010-1.024)]. The area under the curve(AUC) for predicting MACE after PCI in ACS complicated by T2DM using plasma ANGPTL3, ANGPTL8, and their combination were 0.780, 0.790, and 0.886, respectively. The combined use of ANGPTL3 and ANGPTL8 was superior to each individual prediction(Z/P=3.638/<0.001, 3.756/<0.001).ConclusionElevated plasma ANGPTL3 and ANGPTL8 levels in ACS complicated by T2DM are associated with increased coronary artery lesions and the occurrence of MACE after PCI. The combination of ANGPTL3 and ANGPTL8 has a high predictive value for MACE after PCI.

ObjectiveTo investigate the changes of serum low density lipoprotein cholesterol(LDL-C)/high density lipoprotein cholesterol(HDL-C) ratio, lipoprotein(a) [Lp(a)] in patients with type 2 diabetes mellitus(T2DM) and coronary heart disease(CHD) and their correlation with major adverse cardiovascular events(MACE) in the near future after percutaneous coronary intervention(PCI).MethodsA total of 120 T2DM patients with CHD admitted to the Second Affiliated Hospital of Xi 'an Jiaotong University from September 2022 to June 2023 were selected as the observation group, and 65 patients with CHD alone were selected as the control group. According to whether MACE occurred recently after PCI, T2DM patients with CHD were divided into poor prognosis subgroup(29 cases) and good prognosis subgroup(91 cases). Serum LDL-C and HDL-C levels were determined by enzymatic method, and serum Lp(a) levels were determined by immunoturbidimetry. The correlation between serum LDL-C/HDL-C ratio, Lp(a) level and Gensini score was analyzed by Pearson method. Multivariate Logistic regression analysis was performed to analyze the influencing factors of MACE in T2DM patients with CHD after PCI. The predictive value of serum LDL-C/HDL-C ratio and Lp(a) level for short-term MACE in T2DM patients with CHD after PCI was analyzed by receiver operating characteristic(ROC) curve.ResultsThe LDL-C/HDL-C ratio and Lp(a) level in the observation group were higher than those in the control group(t/P=6.594/<0.001, 11.369/<0.001). The results of Pearson analysis showed that the serum LDL-C/HDL-C ratio and Lp(a) level in T2DM patients with CHD were positively correlated with Gensini score(r/P=0.751/<0.001, 0.744/<0.001). At 12 months follow-up after PCI, the incidence of MACE in 120 T2DM patients with CHD was 24.17%(29/120). Gensini score, serum LDL-C/HDL-C ratio and Lp(a) level in poor prognosis subgroup were higher than those in good prognosis subgroup(t/P=3.939/<0.001,4.413/<0.001,4.333/<0.001). Multivariate Logistic regression analysis showed that high Gensini score, high LDL-C/HDL-C ratio, and high serum Lp(a) level were independent risk factors for MACE in patients with T2DM combined with CHD after PCI [OR(95%CI)=5.298(3.259-8.614). 4.817(2.914-7.963), 4.855(2.852-8.264)]; The area under the curve(AUC) of serum LDL-C/HDL-C ratio, Lp(a) level and their combined prediction of near-term MACE after PCI in T2DM patients with CHD were 0.765, 0.737 and 0.930, respectively. The combined AUC was greater than that predicted by serum LDL-C/HDL-C ratio and Lp(a) level alone(Z/P=20.093/0.000,18.651/0.000).ConclusionLDL-C/HDL-C ratio and serum Lp(a) level are abnormally high in T2DM patients with CHD, and are positively correlated with Gensini score, respectively. The combination of the two can effectively predict the near-term risk of MACE in T2DM patients with CHD after PCI.

ObjectiveTo investigate the correlation between the expression of miR-222-3p and SLFN11 in cervical cancer tumor tissue and clinical pathological characteristics and prognosis.MethodsA total of 103 patients with cervical cancer treated in the General Hospital of the Central Theater Command of the Chinese People's Liberation Army from January 2019 to June 2021 were divided into the cervical cancer group and 57 patients with benign cervical diseases as the control group. Real-time fluorescence quantitative polymerase chain reaction was used to detect the expression of miR-222-3p and SLFN11 in the two groups of patients; the differences in the expression of miR-222-3p and SLFN11 in tumor tissues of patients with different clinical pathological characteristics of cervical cancer were analyzed; Correlation analysis was performed using Spearman rank correlation, poor prognostic efficacy of cervical cancer was analyzed using ROC curve analysis and compared using DeLong method, risk factors were analyzed using multivariate Cox regression analysis, and survival analysis was performed using K-M method and Log Rank comparison.ResultsThe expression of miR-222-3p in tumor tissue of cervical cancer group was higher than that in adjacent tissues and control group, while the expression of SLFN11 in adjacent tissues and control group was lower(F/P=945.371/<0.001, 226.816/<0.001). The expression of miR-222-3p in patients with positive CTC, Ki-67 ≥ 70%, T stage T3-4, N stage N1, distant metastasis M1 and TNM stage Ⅲ-Ⅳ was higher than that in patients with negative CTC, Ki-67 < 70%, T stage T1-2, N stage Nx-N0, no distant metastasis and TNM stage Ⅰ-Ⅱ(t/P=3.263/0.002, 4.208/<0.001, 4.182/<0.001, 3.342/0.001, 5.391/<0.001, 3.298/<0.001), SLFN11 expression was lower than that in patients with negative CTC, Ki-67 < 70%, T stage T1-2, N stage Nx-N0, no distant metastasis and TNM stage Ⅰ-Ⅱ(t/P=5.140/<0.001, 5.706/<0.001, 5.984/<0.001, 7.701/<0.001, 6.704/<0.001, 7.859/<0.001) In the cervical cancer group, the expression of miR-222-3p in tumor tissue was positively correlated with CTC, Ki-67, T stage, N stage, distant metastasis, and TNM stage(rs/P=0.683/0.035, 0.704/0.009, 0.626/0.021, 0.651/0.029, 0.627/0.023, and 0.649/0.015), and the expression of SLFN11 was negatively correlated with CTC, Ki-67, T stage, N stage, distant metastasis, and TNM stage(rs/P=-0.624/0.037,-0.651/0.025,-0.677/0.032,-0.632/0.019,-0.648/0.007, and-0.675/0.023). The AUCs of miR-222-3p, SLFN11 and their combination for predicting poor prognosis in cervical cancer patients were 0.674, 0.652 and 0.883, respectively. The combination of miR-222-3p and SLFN11 was superior to their individual predictive efficacy(Z/P=8.143/<0.001,10.561/<0.001). CTC positivity, Ki-67≥70%, T stage T3-4, N stage N1, distant metastasis, TNM stage Ⅲ-Ⅳ, miR-222-3p≥ 1.18 and SLFN11 ≤ 0.65 were independent risk factors for poor prognosis of cervical cancer[HR(95%CI) = 2.776(1.128-4.424), 1.865(1.044-2.685), 2.056(1.095-3.018), 2.192(1.127-3.257), 3.473(1.133-5.813), 2.656(1.026-4.286), 5.371(1.644-9.098), 4.367(1.512-7.221)]; the median survival of cervical cancer patients with miR-222-3p≥1.18 and SLFN11≤0.65 was(25.19±4.36) months, which was lower than that of patients with miR-222-3P<1.18 or="" slfn11="">0.65(30.68±5.21) months(Log Rankχ2=9.046,P<0.001).ConclusionThe expression of miR-222-3p and SLFN11 in cervical cancer tumor tissue is closely related to clinical pathological characteristics, prognosis and survival. The combined detection of the two can significantly improve the value of poor prognosis assessment in cervical cancer.

ObjectiveTo investigate the influencing factors of axillary lymph node metastasis(ALNM) in Luminal type A breast cancer patients and to establish a nomogram prediction model.MethodsOne hundred and thirty-five patients with Luminal A breast cancer admitted to the Department of Breast Oncology Surgery of the People's Hospital of Inner Mongolia Autonomous Region from January 2019 to January 2024 were selected for the study, and they were divided into 94 cases of the modelling group and 41 cases of the validation group according to the ratio of 7∶3. According to the occurrence or non-occurrence of ALNM after surgery, patients in the modelling group were divided into 43 cases of the ALNM subgroup and no ALNM subgroup of 51 cases. Multifactorial logistic regression was used to analyse the influencing factors of ALNM in patients with Luminal A breast cancer; R software was used to construct the column chart model; ROC curves were used to assess the discriminatory degree of the column chart model in predicting ALNM in patients with Luminal A breast cancer; and clinical decision curves were used to assess the clinical application value of the column chart model.ResultsThe incidence of ALNM was 45.19%(61/135) in 135 patients with Luminal A breast cancer and 45.74%(43/94) in 94 patients in the modelling group. The ALNM subgroup had a higher proportion of age<50 maximum="" tumour="" diameter="">2 cm, histological grade Ⅱ-Ⅲ, vascular invasion, multifocal tumour, and p53 gene mutation than the no ALNM subgroup,(χ2/P=15.474, 12.163, 14.026, 12.983, 21.803, 15.159, allP< 0.001); multifactorial logistic regression analysis showed that age < 50 years, maximum tumour diameter > 2 cm, histological grading Ⅱ-Ⅲ, vascular invasion, multifocal tumour, and p53 gene mutation were the independent risk factors for ALNM in patients with Luminal A breast cancer[OR(95%CI) = 2.531(1.336-4.975), 3.120(1.095-8.886), 3.657(1.602-8.346), 5.208(1.854-14.633), 14.718(2.073-104.485), 6.807(1.934-19.157)], and constructed a column-line graph prediction model; the validation results showed that the area under the curve(AUC) was 0.960(95%CI=0.916-0.999) for the modelling group, and the AUC was 0.967(95%CI=0.918-0.999) for the validation group. The slopes of the calibration curves of the modelling and validation groups were close to 1. The H-L test wasχ2=7.067(P=0.701) in the modelling group andχ2=6.923(P=0.706) in the validation group; from the DCA curves, it was clear that when the probability of the high-risk threshold was between 0.08 and 0.96, the column-line diagram model for assessing ALNM in patients with Luminal A breast cancer had a clinical use value is high.ConclusionAge >50, maximum tumour diameter >2 cm, histological grading Ⅱ-Ⅲ, vascular invasion, multifocal tumour, and p53 gene mutation are the risk factors of ALNM in patients with Luminal A breast cancer, and the column-line graph model constructed in this way has some clinical value in predicting ALNM in patients with Luminal A breast cancer.