Exotoxins produced by Actinobacillus (A.) pleuropneumoniae (Apx) play major roles in the pathogenesis of pleuropneumonia in swine. This study investigated the role of ApxI in hemolysis and cellular damage using a novel apxIA mutant, ApxIA336, which was developed from the parental strain A. pleuropneumoniae serotype 10 that produces only ApxI in vitro. The genotype of ApxIA336 was confirmed by PCR, Southern blotting, and gene sequencing. Exotoxin preparation derived from ApxIA336 was analyzed for its bioactivity towards porcine erythrocytes and alveolar macrophages. Analysis results indicated that ApxIA336 contained a kanamycin-resistant cassette inserted immediately after 1005 bp of the apxIA gene. Phenotype analysis of ApxIA336 revealed no difference in the growth rate as compared to the parental strain. Meanwhile, ApxI production was abolished in the bacterial culture supernatant, i.e. exotoxin preparation. The inability of ApxIA336 to produce ApxI corresponded to the loss of hemolytic and cytotoxic bioactivity in exotoxin preparation, as demonstrated by hemolysis, lactate dehydrogenase release, mitochondrial activity, and apoptosis assays. Additionally, the virulence of ApxIA336 appeared to be attenuated by 15-fold in BALB/c mice. Collectively, ApxI, but not other components in the exotoxin preparation of A. pleuropneumoniae serotype 10, was responsible for the hemolytic and cytotoxic effects on porcine erythrocytes and alveolar macrophages.
Actinobacillus pleuropneumoniae/genetics/*pathogenicity/*physiology ; Animals ; *Apoptosis ; Bacterial Proteins/genetics/metabolism ; Blotting, Southern ; Exotoxins/*genetics ; Hemolysin Proteins/genetics/metabolism ; *Hemolysis ; Macrophages, Alveolar/metabolism/*microbiology ; Polymerase Chain Reaction ; Sequence Analysis, DNA ; Swine ; Virulence

INTRODUCTIONDecreased insulin action (insulin resistance) is crucial in the pathogenesis of type 2 diabetes. Decreased insulin action can even be found in normoglycaemic patients, and they still bear increased risks for cardiovascular disease. In this study, we built models using data from metabolic syndrome (Mets) components and the oral glucose tolerance test (OGTT) to detect insulin resistance in subjects with normal glucose tolerance (NGT).

MATERIALS AND METHODSIn total, 292 participants with NGT were enrolled. Both an insulin suppression test (IST) and a 75-g OGTT were administered. The steady-state plasma glucose (SSPG) level derived from the IST was the measurement of insulin action. Participants in the highest tertile were defined as insulin-resistant. Five models were built: (i) Model 0: body mass index (BMI); (ii) Model 1: BMI, systolic and diastolic blood pressure, triglyceride; (iii) Model 2: Model 1 + fasting plasma insulin (FPI); (iv) Model 3: Model 2 + plasma glucose level at 120 minutes of the OGTT; and (v) Model 4: Model 3 + plasma insulin level at 120 min of the OGTT.

RESULTSThe area under the receiver operating characteristic curve (aROC curve) was observed to determine the predictive power of these models. BMI demonstrated the greatest aROC curve (71.6%) of Mets components. The aROC curves of Models 2, 3, and 4 were all substantially greater than that of BMI (77.1%, 80.1%, and 85.1%, respectively).

CONCLUSIONA prediction equation using Mets components and FPI can be used to predict insulin resistance in a Chinese population with NGT. Further research is required to test the utility of the equation in other populations and its prediction of cardiovascular disease or diabetes mellitus.

Adult ; Blood Glucose ; Cross-Sectional Studies ; Female ; Glucose ; metabolism ; Glucose Tolerance Test ; Humans ; Insulin Resistance ; Male ; Metabolic Syndrome ; metabolism ; Middle Aged ; Models, Statistical

PURPOSE: Cancer cells develop acquired resistance induced by chemotherapeutic drugs. In this study, we investigated the effects of brief treatment with cytotoxic drugs on the phenotype of breast cancer cells. METHODS: Breast cancer cells MCF7 and BT-474 were briefly treated with paclitaxel or doxorubicin. Clonogenic, migration, and invasion assays were performed on the treated cells. Western blot analysis and RhoA activity assay were also performed. RESULTS: Breast cancer cells when briefly treated with paclitaxel or doxorubicin showed reduced clonogenic ability. Doxorubicin, but not paclitaxel, augmented cell migration and invasion. The invasion-promoting effects of doxorubicin were lost when the two drugs were sequentially used in combination. Myosin light chain (MLC) 2 phosphorylation and RhoA activity were upregulated by doxorubicin and downregulated by paclitaxel. Pretreatment with RhoA inhibitors abolished the migration- and invasion-promoting effects of doxorubicin. CONCLUSION: Doxorubicin activates the RhoA/MLC pathway and enhances breast cancer cell migration and invasion. Therefore, this pathway might be explored as a therapeutic target to suppress anthracycline-enhanced tumor progression.
Blotting, Western ; Breast Neoplasms ; Breast ; Cell Movement ; Doxorubicin ; Myosin Light Chains ; Paclitaxel ; Phenotype ; Phosphorylation ; Up-Regulation

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.