Abstract
Background
Coronary bifurcation lesion, as a complex coronary lesion, is associated with higher risk of long-term poor prognosis than non-bifurcation lesions. The triglyceride-glucose (TyG) ...index has been shown to predict cardiovascular (CV) events in patients with coronary artery disease (CAD). However, the prognostic value of the TyG index in patients with bifurcation lesions who are at high risk of CV events remains undetermined. Therefore, this study aimed to investigate the association between the TyG index and CV events in patients with bifurcation lesions.
Methods
A total of 4530 consecutive patients with angiography-proven CAD and bifurcation lesions were included in this study from January 2017 to December 2018. The TyG index was calculated as Ln fasting triglyceride (mg/dL) × fasting plasma glucose (mg/dL)/2. Patients were assigned into 3 groups according to TyG tertiles (T) (T1: <8.633; T2: 8.633–9.096 and T3: ≥9.096). The primary endpoint was CV events, including CV death, nonfatal myocardial infarction and nonfatal stroke at 3-year follow-up. Restricted cubic spline (RCS) analysis, Kaplan-Meier curves and Cox proportional hazard models were used to investigate the associations between the TyG index and study endpoints.
Results
During a median follow-up of 3.1 years, 141 (3.1%) CV events occurred. RCS analysis demonstrated a linear relationship between the TyG index and events after adjusting for age and male sex (non-linear
P
= 0.262). After multivariable adjustments, elevated TyG index (both T2 and T3) was significantly associated with the risk of CV events (hazard ratio HR, 1.68; 95% confidence interval CI,1.06–2.65; HR, 2.10; 95%CI, 1.28–3.47, respectively). When study patients were further stratified according to glycemic status, higher TyG index was associated with significantly higher risk of CV events in diabetic patients after adjusting for confounding factors (T3 vs. T1; HR, 2.68; 95%CI, 1.17–6.11). In addition, subgroup analysis revealed consistent associations of the TyG index with 3-year CV events across various subgroups. Furthermore, adding the TyG index to the original model significantly improved the predictive performance.
Conclusions
High TyG index was associated with CV events in patients with bifurcation lesions, suggesting the TyG index could help in risk stratification and prognosis in this population.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The Ki-67 index is an established prognostic factor in gastrointestinal neuroendocrine tumors (GI-NETs) and defines tumor grade. It is currently estimated by microscopically examining tumor tissue ...single-immunostained (SS) for Ki-67 and counting the number of Ki-67-positive and Ki-67-negative tumor cells within a subjectively picked hot-spot. Intraobserver variability in this procedure as well as difficulty in distinguishing tumor from non-tumor cells can lead to inaccurate Ki-67 indices and possibly incorrect tumor grades. We introduce two computational tools that utilize Ki-67 and synaptophysin double-immunostained (DS) slides to improve the accuracy of Ki-67 index quantitation in GI-NETs: (1) Synaptophysin-KI-Estimator (SKIE), a pipeline automating Ki-67 index quantitation via whole-slide image (WSI) analysis and (2) deep-SKIE, a deep learner-based approach where a Ki-67 index heatmap is generated throughout the tumor. Ki-67 indices for 50 GI-NETs were quantitated using SKIE and compared with DS slide assessments by three pathologists using a microscope and a fourth pathologist via manually ticking off each cell, the latter of which was deemed the gold standard (GS). Compared to the GS, SKIE achieved a grading accuracy of 90% and substantial agreement (linear-weighted Cohen's kappa 0.62). Using DS WSIs, deep-SKIE displayed a training, validation, and testing accuracy of 98.4%, 90.9%, and 91.0%, respectively, significantly higher than using SS WSIs. Since DS slides are not standard clinical practice, we also integrated a cycle generative adversarial network into our pipeline to transform SS into DS WSIs. The proposed methods can improve accuracy and potentially save a significant amount of time if implemented into clinical practice.
•The NGS technology has superior sensitivity and shorter turnaround times compared with culture-based methods for identifying causative pathogens, particularly for unculturable or ...difficult-to-culture microorganisms.•The application of NGS technology can identify all types of microorganisms simultaneously.•The NGS technology should be considered an essential supplement to blood culture and valve culture.
Identification of the underlying pathogens of infective endocarditis (IE) is critical for precision therapy.
We evaluated a metagenomic method with next-generation sequencing (NGS) for the direct detection of pathogens from the resected valves of 44 IE patients and seven rejected IE patients according to the modified Duke criteria.
NGS displayed sensitivity, specificity, positive predictive values and negative predictive values of 97.6%, 85.7%, 97.6%, and 85.7% compared with 46.2%, 100%, 100%, and 12.5% for blood culture and 17.1%, 100%, 100%, and 17.1% for valve culture and 51.4%, 100%, 100%, and 26.1% for valve Gram staining, respectively.
NGS technique had superior sensitivity and shorter turnaround time compared with culture-based methods for identifying causative pathogens of IE. The NGS technology should be considered an essential supplement to culture-based methods, particularly for unculturable or difficult-to-culture microorganisms.
Highlights • Nuclear overexpression of YAP1 was linked to poor prognosis with GBC. • This study examined the mechanistic roles of YAP1 in GBC. • YAP1 promotes GBC cell growth via activation of the ...AXL/MAPK pathway. • This work provided a rationale for YAP1 as a therapeutic target for GBC.
Objectives
To improve the prognostic value of the age, creatinine, and ejection fraction (ACEF) score following percutaneous coronary intervention (PCI) by integrating the residual SYNTAX score ...(rSS).
Background
ACEF score was proposed for predicting the operative mortality risk in elective cardiac operations and has been validated in numerous studies. However, it does not incorporate coronary lesion‐based variables for risk assessment of patients who undergo PCI.
Methods
Overall, 10,072 patients who underwent PCI at our hospital in 2013 were enrolled. The endpoint was 2‐year cardiac death after PCI, defined as death that was not attributed to a non‐cardiac cause. ACEF‐rSS was constructed with incremental weights attributed to the ACEF score and rSS according to their estimated coefficients.
Results
2‐year cardiac death occurred in 63 patients (0.63%). In multivariable analyses, the ACEF score and rSS > 8 were independently associated with the risk of cardiac death. ACEF‐rSS was computed as age (years)/ejection fraction (%) + 1 (if creatinine ≥2.0 mg/dl) + 1 (if rSS >8). The discrimination of ACEF‐rSS was significantly better than that of the ACEF score based on receiver operating characteristic (ROC) curve analysis and integrated discrimination improvement (IDI) (C‐statistics = 0.835 vs. 0.776 for ACEF‐rSS and ACEF score, respectively, p = .029; IDI = 0.014, p < .001). Compared with all other SYNTAX‐derived risk scores, ACEF‐rSS had significantly better discrimination ability based on ROC curve analysis, net reclassification improvement, and IDI.
Conclusions
Combining the ACEF score with rSS to produce the ACEF‐rSS enhanced the predictive ability for long‐term cardiac mortality.
In software projects, a large number of bugs are usually reported to bug repositories. Due to the limited budge and work force, the developers often may not have enough time and ability to inspect ...all the reported bugs, and thus they often focus on inspecting and repairing the highly impacting bugs. Among the high-impact bugs, surprise bugs are reported to be a fatal threat to the software systems, though they only account for a small proportion. Therefore, the identification of surprise bugs becomes an important work in practices. In recent years, some methods have been proposed by the researchers to identify surprise bugs. Unfortunately, the performance of these methods in identifying surprise bugs is still not satisfied for the software projects. The main reason is that surprise bugs only occupy a small percentage of all the bugs, and it is difficult to identify these surprise bugs from the imbalanced distribution. In order to overcome the imbalanced category distribution of the bugs, a method based on machine learning to predict surprise bugs is presented in this paper. This method takes into account the textual features of the bug reports and employs an imbalanced learning strategy to balance the datasets of the bug reports. Then these datasets after balancing are used to train three selected classifiers which are built by three different classification algorithms and predict the datasets with unknown type. In particular, an ensemble method named optimization integration is proposed to generate a unique and best result, according to the results produced by the three classifiers. This ensemble method is able to adjust the ability of the classifier to detect different categories based on the characteristics of different projects and integrate the advantages of three classifiers. The experiments performed on the datasets from 4 software projects show that this method performs better than the previous methods in terms of detecting surprise bugs.
Dual antiplatelet therapy (DAPT) score emerged as a tool for quantification of ischemia and bleeding risks. However, there was discrepancy of the prediction ability of DAPT score in previous studies. ...We aimed to assess the utility of DAPT score in a large-scale cohort of consecutive percutaneous coronary intervention (PCI) patients. This study enrolled 9,114 patients who had undergone PCI at Fuwai Hospital in 2013, adhered to DAPT and were event-free within the first 12 months following PCI. The endpoints included primary ischemic endpoints (major adverse cardiovascular and cerebrovascular events, and myocardial infarction and/or stent thrombosis), and bleeding endpoint from 12 through 24 months after PCI. Patients were classified into low (score <2, n = 3,989) and high (score ≥2, n = 5,125) DAPT score groups. The incidence rates of primary ischemic endpoints and bleeding endpoint were similar between the two groups. Multivariable analysis demonstrated DAPT score not to be an independent predictor of primary ischemic endpoints or bleeding endpoint. Based on receiver operating characteristic curves analysis, the C-statistic of DAPT score for primary ischemic endpoints or bleeding endpoint did not achieve a significant extent. In this large-scale cohort of PCI patients, DAPT score did not discriminate the risks of ischemic and bleeding events.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Magnolol, the major active compound found in Magnolia officinalis has a wide range of clinical applications due to its anti‐inflammation and anti‐oxidation effects. This study investigated the ...effects of magnolol on the growth of human gallbladder carcinoma (GBC) cell lines. The results indicated that magnolol could significantly inhibit the growth of GBC cell lines in a dose‐ and time‐dependent manner. Magnolol also blocked cell cycle progression at G0/G1 phase and induced mitochondrial‐related apoptosis by upregulating p53 and p21 protein levels and by downregulating cyclin D1, CDC25A, and Cdk2 protein levels. When cells were pretreated with a p53 inhibitor (pifithrin‐a), followed by magnolol treatment, pifithrin‐a blocked magnolol‐induced apoptosis and G0/G1 arrest. In vivo, magnolol suppressed tumor growth and activated the same mechanisms as were activated in vitro. In conclusion, our study is the first to report that magnolol has an inhibitory effect on the growth of GBC cells and that this compound may have potential as a novel therapeutic agent for the treatment of GBC.
This study investigated the effects of magnolol on the growth of GBC cells. The results indicated that magnolol inhibited GBC cell growth in vitro and in vivo via the p53 pathway. This work provided a rationale for Magnolol as a novel therapeutic agent for GBC.
Timothy syndrome (TS) is a multiorgan dysfunction caused by a Gly to Arg substitution at position 406 (G406R) of the human
CaV1.2 (L-type) channel. The TS phenotype includes severe arrhythmias that ...are thought to be triggered by impaired open-state
voltage-dependent inactivation (OS vd I). The effect of the TS mutation on other L-channel gating mechanisms has yet to be investigated. We compared kinetic properties
of exogenously expressed (HEK293 cells) rabbit cardiac L-channels with (G436R; corresponding to position 406 in human clone)
and without (wild-type) the TS mutation. Our results surprisingly show that the TS mutation did not affect close-state voltage-dependent
inactivation, which suggests different gating mechanisms underlie these two types of voltage-dependent inactivation. The TS
mutation also significantly slowed activation at voltages less than 10 mV, and significantly slowed deactivation across all
test voltages. Deactivation was slowed in the double mutant G436R/S439A, which suggests that phosphorylation of S439 was not
involved. The L-channel agonist Bay K8644 increased the magnitude of both step and tail currents, but surprisingly failed
to slow deactivation of TS channels. Our mathematical model showed that slowed deactivation plus impaired OS vd I combine to synergistically increase cardiac action potential duration that is a likely cause of arrhythmias in TS patients.
Roscovitine, a tri-substituted purine that enhances L-channel OS vd I, restored TS-impaired OS vd I. Thus, inactivation-enhancing drugs are likely to improve cardiac arrhythmias and other pathologies afflicting TS patients.
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