Prediction of Coronary Artery Disease Risk Based on Multiple Longitudinal Biomarkers

In the last decade, few topics in the area of cardiovascular disease (CVD) research have received as much attention as risk prediction. One of the well-documented risk factors for CVD is high blood pressure (BP). Traditional CVD risk prediction models consider BP levels measured at a single time and such models form the basis for current clinical guidelines for CVD prevention. However, in clinical practice, BP levels are often observed and recorded in a longitudinal fashion. Information on BP trajectories can be powerful predictors for CVD events. We consider joint modeling of time to coronary artery disease and individual longitudinal measures of systolic and diastolic BPs in a primary care cohort with up to 20 years of follow-up. We applied novel prediction metrics to assess the predictive performance of joint models. Predictive performances of proposed joint models and other models were assessed via simulations and illustrated using the primary care cohort

Joint Models for Multiple Longitudinal Processes and Time-to-event Outcome

Joint models are statistical tools for estimating the association between time-to-event and longitudinal outcomes. One challenge to the application of joint models is its computational complexity. Common estimation methods for joint models include a two-stage method, Bayesian and maximum-likelihood methods. In this work, we consider joint models of a time-to-event outcome and multiple longitudinal processes and develop a maximum-likelihood estimation method using the expectation–maximization algorithm. We assess the performance of the proposed method via simulations and apply the methodology to a data set to determine the association between longitudinal systolic and diastolic blood pressure measures and time to coronary artery disease

Quality assessment of randomized controlled trial abstracts on drug therapy of periodontal disease from the abstracts published in dental Science Citation Indexed journals in the last ten years

Randomized controlled trials (RCTs) provide the highest level of evidence and are likely to influence clinical decision-making. This study evaluated the reporting quality of RCT abstracts on drug therapy of periodontal disease and assessed the associated factors. The Pubmed database was searched for periodontal RCTs published in Science Citation Indexed (SCI) dental journals from 2010/01/01 to 2019/07/17. Information was extracted from the abstracts according to a modified Consolidated Standards of Reporting Trials (CONSORT) guideline checklist. The data was analyzed using descriptive statistical analysis and the statistical associations were examined using the linear regression analysis (P <0.05). This study retrieved 1715 articles and 249 of them were finally included. The average overall CONSORT score was 15.6 ± 3.4, which represented 40.9% (±0.6) of CONSORT criteria filling. The reporting rate of some items (trial design, numbers analyzed, confidence intervals, intention-to-treat analysis or per-protocol analysis, harms, registration) was less than 30%. The adequate reporting rate of some items (participants, randomization, numbers analyzed, confidence intervals, intention-to-treat analysis or per protocol analysis) was no more than 4%. None of the abstracts reported funding. According to the multivariable linear regression results, number of authors (P=0.030), word count (P <0.001), continent (P=0.003), structured format (P <0.001), type of periodontal disease (P <0.001) and international collaboration (P=0.023) have a significant association with reporting quality. The quality of RCT abstracts on drug therapy of periodontal disease in SCI dental journals remained suboptimal. More efforts should be made to improve RCT abstracts reporting quality

Approximate Analytical Solutions of Fractional Perturbed Diffusion Equation by Reduced Differential Transform Method and the Homotopy Perturbation Method

The approximate analytical solutions of differential equations with fractional time derivative are obtained with the help of a general framework of the reduced differential transform method (RDTM) and the homotopy perturbation method (HPM). RDTM technique does not require any discretization, linearization, or small perturbations and therefore it reduces significantly the numerical computation. Comparing the methodology (RDTM) with some known technique (HPM) shows that the present approach is effective and powerful. The numerical calculations are carried out when the initial conditions in the form of periodic functions and the results are depicted through graphs. The two different cases have studied and proved that the method is extremely effective due to its simplistic approach and performance

Quantum Algorithm for Unsupervised Anomaly Detection

Anomaly detection, an important branch of machine learning, plays a critical role in fraud detection, health care, intrusion detection, military surveillance, etc. As one of the most commonly used unsupervised anomaly detection algorithms, the Local Outlier Factor algorithm (LOF algorithm) has been extensively studied. This algorithm contains three steps, i.e., determining the k-distance neighborhood for each data point x, computing the local reachability density of x, and calculating the local outlier factor of x to judge whether x is abnormal. The LOF algorithm is computationally expensive when processing big data sets. Here we present a quantum LOF algorithm consisting of three parts corresponding to the classical algorithm. Specifically, the k-distance neighborhood of x is determined by amplitude estimation and minimum search; the local reachability density of each data point is calculated in parallel based on the quantum multiply-adder; the local outlier factor of each data point is obtained in parallel using amplitude estimation. It is shown that our quantum algorithm achieves exponential speedup on the dimension of the data points and polynomial speedup on the number of data points compared to its classical counterpart. This work demonstrates the advantage of quantum computing in unsupervised anomaly detection

Total flavonoids extracted from Penthorum chinense Pursh mitigates CCl4-induced hepatic fibrosis in rats via inactivation of TLR4-MyD88-mediated NF-κB pathways and regulation of liver metabolism

Background:Penthorum chinense Pursh (PCP) is widely utilized in China to treat a variety of liver diseases. It has been shown that flavonoids inhibit inflammation and have the potential to attenuate tissue damage and fibrosis. However, the mechanisms underlying how total flavonoids isolated from PCP (TFPCP) exert their anti-fibrotic effects remain unclear.Methods: The chemical composition of TFPCP was determined using UHPLC–Q-Orbitrap HRMS. Subsequently, rats were randomly assigned to a control group (Control), a carbon tetrachloride (CCl4)-induced hepatic fibrosis model group (Model), a positive control group [0.2 mg/(kg∙day)] of Colchicine), and three TFPCP treatment groups [50, 100, and 150 mg/(kg∙day)]. All substances were administered by gavage and treatments lasted for 9 weeks. Simultaneously, rats were intraperitoneally injected with 10%–20% CCl4 for 9 weeks to induce liver fibrosis. At the end of the experiment, the liver ultrasound, liver histomorphological, biochemical indicators, and inflammatory cytokine levels were tested respectively. The underlying mechanisms were assessed using Western blot, immunohistochemistry, immunofluorescence, RT-qPCR, and metabolomics.Results: Fourteen flavonoids were identified in TFPCP. Compared with control animals, CCl4-treated rats demonstrated obvious liver injury and fibrosis, manifested as increases in gray values, distal diameter of portal vein (DDPV) and a decrease in blood flow velocity (VPV) in the ultrasound analysis; increased biochemical index values (serum levels of ALT, AST, TBIL, and ALP); marked increases in the contents of fibrotic markers (PC III, COL4, LN, HA) and inflammatory factors (serum TNF-α, IL-6, and IL-1β); and significant pathological changes. However, compared with the Model group, the ultrasound parameters were significantly improved and the serum levels of inflammatory cytokines were reduced in the TFPCP group. In contrast, the expression of TGF-β1, TLR4, and MyD88, as well as the p-P65/P65 and p-IκBα/IκBα ratios, were considerably reduced following TFPCP treatment. In addition, we identified 32 metabolites exhibiting differential abundance in the Model group. Interestingly, TFPCP treatment resulted in the restoration of the levels of 20 of these metabolites.Conclusion: Our findings indicated that TFPCP can ameliorate hepatic fibrosis by improving liver function and morphology via the inactivation of the TLR4/MyD88-mediated NF-κB pathway and the regulation of liver metabolism

Tau-related white-matter alterations along spatially selective pathways

Progressive accumulation of tau neurofibrillary tangles in the brain is a defining pathologic feature of Alzheimer's disease (AD). Tau pathology exhibits a predictable spatiotemporal spreading pattern, but the underlying mechanisms of this spread are poorly understood. Although AD is conventionally considered a disease of the gray matter, it is also associated with pronounced and progressive deterioration of the white matter (WM). A link between abnormal tau and WM degeneration is suggested by findings from both animal and postmortem studies, but few studies demonstrated their interplay in vivo. Recent advances in diffusion magnetic resonance imaging and the availability of tau positron emission tomography (PET) have made it possible to evaluate the association of tau and WM degeneration (tau-WM) in vivo. In this study, we explored the spatial pattern of tau-WM associations across the whole brain to evaluate the hypothesis that tau deposition is associated with WM microstructural alterations not only in isolated tracts, but in continuous structural connections in a stereotypic pattern. Sixty-two participants, including 22 cognitively normal subjects, 22 individuals with subjective cognitive decline, and 18 with mild cognitive impairment were included in the study. WM characteristics were inferred by classic diffusion tensor imaging (DTI) and a complementary diffusion compartment model - neurite orientation dispersion and density imaging (NODDI) that provides a proxy for axonal density. A data-driven iterative searching (DDIS) approach, coupled with whole-brain graph theory analyses, was developed to continuously track tau-WM association patterns. Without applying prior knowledge of the tau spread, we observed a distinct spatial pattern that resembled the typical propagation of tau pathology in AD. Such association pattern was not observed between diffusion and amyloid-β PET signal. Tau-related WM degeneration is characterized by an increase in the mean diffusivity (with a dominant change in the radial direction) and a decrease in the intra-axonal volume fraction. These findings suggest that cortical tau deposition (as measured in tau PET) is associated with a lower axonal packing density and greater diffusion freedom. In conclusion, our in vivo findings using a data-driven method on cross-sectional data underline the important role of WM alterations in the AD pathological cascade with an association pattern similar to the postmortem Braak staging of AD. Future studies will focus on longitudinal analyses to provide in vivo evidence of tau pathology spreads along neuroanatomically connected brain areas

Identification of different oxygen species in oxide nanostructures with O-17 solid-state NMR spectroscopy

Nanostructured oxides find multiple uses in a diverse range of applications including catalysis, energy storage, and environmental management, their higher surface areas, and, in some cases, electronic properties resulting in different physical properties from their bulk counterparts. Developing structure-property relations for these materials requires a determination of surface and subsurface structure. Although microscopy plays a critical role owing to the fact that the volumes sampled by such techniques may not be representative of the whole sample, complementary characterization methods are urgently required. We develop a simple nuclear magnetic resonance (NMR) strategy to detect the first few layers of a nanomaterial, demonstrating the approach with technologically relevant ceria nanoparticles. We show that the (17)O resonances arising from the first to third surface layer oxygen ions, hydroxyl sites, and oxygen species near vacancies can be distinguished from the oxygen ions in the bulk, with higher-frequency (17)O chemical shifts being observed for the lower coordinated surface sites. H(2)(17)O can be used to selectively enrich surface sites, allowing only these particular active sites to be monitored in a chemical process. (17)O NMR spectra of thermally treated nanosized ceria clearly show how different oxygen species interconvert at elevated temperature. Density functional theory calculations confirm the assignments and reveal a strong dependence of chemical shift on the nature of the surface. These results open up new strategies for characterizing nanostructured oxides and their applications

Head injury is associated with tau deposition on PET in MCI and AD patients

Introduction: Head injuries (HI) are a risk factor for dementia, but the underlying etiology is not fully known. Understanding whether tau might mediate this relationship is important. Methods: Cognition and tau deposition were compared between 752 individuals with (impaired, n = 302) or without cognitive impairment (CN, n = 450) with amyloid and [18F]flortaucipir positron emission tomography, HI history information, and cognitive testing from the Alzheimer's Disease Neuroimaging Initiative and the Indiana Memory and Aging Study. Results: Sixty-three (38 CN, 25 impaired) reported a history of HI. Higher neuropsychiatric scores and poorer memory were observed in those with a history of HI. Tau was higher in individuals with a history of HI, especially those who experienced a loss of consciousness (LOC). Results were driven by impaired individuals, especially amyloid beta-positive individuals with history of HI with LOC. Discussion: These findings suggest biological changes, such as greater tau, are associated with HI in individuals with cognitive impairment. Small effect sizes were observed; thus, further studies should replicate and extend these results