Investigating properties of the cardiovascular system using innovative analysis algorithms based on ensemble empirical mode decomposition

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited - Copyright @ 2012 Jia-Rong Yeh et al.Cardiovascular system is known to be nonlinear and nonstationary. Traditional linear assessments algorithms of arterial stiffness and systemic resistance of cardiac system accompany the problem of nonstationary or inconvenience in practical applications. In this pilot study, two new assessment methods were developed: the first is ensemble empirical mode decomposition based reflection index (EEMD-RI) while the second is based on the phase shift between ECG and BP on cardiac oscillation. Both methods utilise the EEMD algorithm which is suitable for nonlinear and nonstationary systems. These methods were used to investigate the properties of arterial stiffness and systemic resistance for a pig's cardiovascular system via ECG and blood pressure (BP). This experiment simulated a sequence of continuous changes of blood pressure arising from steady condition to high blood pressure by clamping the artery and an inverse by relaxing the artery. As a hypothesis, the arterial stiffness and systemic resistance should vary with the blood pressure due to clamping and relaxing the artery. The results show statistically significant correlations between BP, EEMD-based RI, and the phase shift between ECG and BP on cardiac oscillation. The two assessments results demonstrate the merits of the EEMD for signal analysis.This work is supported by the National Science Council (NSC) of Taiwan (Grant number NSC 99-2221-E-155-046-MY3), Centre for Dynamical Biomarkers and Translational Medicine, National Central University, Taiwan which is sponsored by National Science Council (Grant number: NSC 100–2911-I-008-001) and the Chung-Shan Institute of Science & Technology in Taiwan (Grant numbers: CSIST-095-V101 and CSIST-095-V102)

Microsatellite analysis of populations of the endangered tree Gomortega keule suggests pre-Columbian differentiation

Temperate forests have been affected extensively by human activities, resulting in land cover changes and population fragmentation. However, these anthropogenic effects can be superimposed onto the natural history of species, making it difficult to determine which effect is more important for a particular species. Gomortega keule is an endangered tree that is found in one of the world’s biodiversity hotspots in central–south Chile. Human activities have significantly impacted on the original habitat in this region in recent years and are commonly considered to be the main cause of the scarcity of this species. However, aspects of the natural history of this evergreen tree may also help to explain its present-day genetic structure. In this study, we undertook microsatellite genotyping of the two southernmost populations of G. keule, which are 7.5 km apart and well isolated from other populations. We found that there was genetic differentiation between these populations, suggesting that they exhibited at least some differentiation before becoming isolated, most likely before human activities first impacted the region some two centuries ago. Molecular estimates of their divergence time supported a more ancient differentiation of the populations than would be explained by human activities alone. It is possible that their isolation may have followed the extinction of megafaunal seed dispersers around 12,000 years before present in this region, as indicated by fruit characteristics, the absence of recruitment by seedlings and the existence of clonal trees

A targeting microbubble for ultrasound molecular imaging

Microbubbles conjugated with targeting ligands are used as contrast agents for ultrasound molecular imaging. However, they often contain immunogenic (strept)avidin, which impedes application in humans. Although targeting bubbles not employing the biotin-(strept)avidin conjugation chemistry have been explored, only a few reached the stage of ultrasound imaging in vivo, none were reported/evaluated to show all three of the following properties desired for clinical applications: (i) low degree of non-specific bubble retention in more than one non-reticuloendothelial tissue; (ii) effective for real-time imaging; and (iii) effective for acoustic quantification of molecular targets to a high degree of quantification. Furthermore, disclosures of the compositions and methodologies enabling reproduction of the bubbles are often withheld.To develop and evaluate a targeting microbubble based on maleimide-thiol conjugation chemistry for ultrasound molecular imaging.Microbubbles with a previously unreported generic (non-targeting components) composition were grafted with anti-E-selectin F(ab')2 using maleimide-thiol conjugation, to produce E-selectin targeting microbubbles. The resulting targeting bubbles showed high specificity to E-selectin in vitro and in vivo. Non-specific bubble retention was minimal in at least three non-reticuloendothelial tissues with inflammation (mouse heart, kidneys, cremaster). The bubbles were effective for real-time ultrasound imaging of E-selectin expression in the inflamed mouse heart and kidneys, using a clinical ultrasound scanner. The acoustic signal intensity of the targeted bubbles retained in the heart correlated strongly with the level of E-selectin expression (|r|≥0.8), demonstrating a high degree of non-invasive molecular quantification.Targeting microbubbles for ultrasound molecular imaging, based on maleimide-thiol conjugation chemistry and the generic composition described, may possess properties (i)-(iii) desired for clinical applications

Extremely long quasiparticle spin lifetimes in superconducting aluminium using MgO tunnel spin injectors

There has been an intense search in recent years for long-lived spin-polarized carriers for spintronic and quantum-computing devices. Here we report that spin polarized quasi-particles in superconducting aluminum layers have surprisingly long spin-lifetimes, nearly a million times longer than in their normal state. The lifetime is determined from the suppression of the aluminum's superconductivity resulting from the accumulation of spin polarized carriers in the aluminum layer using tunnel spin injectors. A Hanle effect, observed in the presence of small in-plane orthogonal fields, is shown to be quantitatively consistent with the presence of long-lived spin polarized quasi-particles. Our experiments show that the superconducting state can be significantly modified by small electric currents, much smaller than the critical current, which is potentially useful for devices involving superconducting qubits

Phase II study of weekly oxaliplatin and 24-h infusion of high-dose 5-fluorouracil and folinic acid in the treatment of advanced gastric cancer

[[abstract]]To investigate the efficacy and safety of combining weekly oxaliplatin with weekly 24-h infusion of high-dose 5-fluorouracil (5-FU) and folinic acid ( FA) in treatment of patients with advanced gastric cancer. Patients with histologically confirmed, locally advanced or recurrent/metastatic gastric cancer were studied. Oxaliplatin 65 mg m(-2) 2-h intravenous infusion, and 5-FU 2600 mg m(-2) plus FA 300 mg m(-2) 24-h intravenous infusion, were given on days 1 and 8, repeated every 3 weeks. Between January 2001 through January 2002, 55 patients were enrolled. The median age was 64 years (range: 22-75). In all, 52 patients (94.5%) had recurrent or metastatic disease and three patients had locally advanced disease. Among 50 patients evaluable for tumour response, 28 patients achieved partial response, with an overall response rate of 56% (95% confidence interval (CI): 41.8-70.3%). All 55 patients were evaluated for survival and toxicities. Median time to progression and overall survival were 5.2 and 10.0 months, respectively, during median follow-up time of 24.0 months. Major grades 3-4 toxicities were neutropenia in 23 cycles (7.1%) and thrombocytopenia in 16 cycles (5.0%). Treatment was discontinued for treatment-related toxicities in nine patients (16.4%), of whom eight were due to oxaliplatin-related neurotoxicity. One patient (1.8%) died of neutropenic sepsis. This oxaliplatin-containing regimen is effective in the treatment of advanced gastric cancer. Except for neurotoxicity that often develops after prolonged use of oxaliplatin, the regimen is well tolerated

Artificial intelligence extension of the OSCAR-IB criteria

Artificial intelligence (AI)-based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human-led validated consensus quality control criteria (OSCAR-IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI-based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five-point expansion of the OSCAR-IB criteria to embrace AI (OSCAR-AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines

Predicting Hospital-Acquired Infections by Scoring System with Simple Parameters

BACKGROUND: Hospital-acquired infections (HAI) are associated with increased attributable morbidity, mortality, prolonged hospitalization, and economic costs. A simple, reliable prediction model for HAI has great clinical relevance. The objective of this study is to develop a scoring system to predict HAI that was derived from Logistic Regression (LR) and validated by Artificial Neural Networks (ANN) simultaneously. METHODOLOGY/PRINCIPAL FINDINGS: A total of 476 patients from all the 806 HAI inpatients were included for the study between 2004 and 2005. A sample of 1,376 non-HAI inpatients was randomly drawn from all the admitted patients in the same period of time as the control group. External validation of 2,500 patients was abstracted from another academic teaching center. Sixteen variables were extracted from the Electronic Health Records (EHR) and fed into ANN and LR models. With stepwise selection, the following seven variables were identified by LR models as statistically significant: Foley catheterization, central venous catheterization, arterial line, nasogastric tube, hemodialysis, stress ulcer prophylaxes and systemic glucocorticosteroids. Both ANN and LR models displayed excellent discrimination (area under the receiver operating characteristic curve [AUC]: 0.964 versus 0.969, p = 0.507) to identify infection in internal validation. During external validation, high AUC was obtained from both models (AUC: 0.850 versus 0.870, p = 0.447). The scoring system also performed extremely well in the internal (AUC: 0.965) and external (AUC: 0.871) validations. CONCLUSIONS: We developed a scoring system to predict HAI with simple parameters validated with ANN and LR models. Armed with this scoring system, infectious disease specialists can more efficiently identify patients at high risk for HAI during hospitalization. Further, using parameters either by observation of medical devices used or data obtained from EHR also provided good prediction outcome that can be utilized in different clinical settings

Development of FRET Assay into Quantitative and High-throughput Screening Technology Platforms for Protein–Protein Interactions

Förster resonance energy transfer (FRET) technology has been widely used in biological and biomedical research and is a very powerful tool in elucidating protein interactions in many cellular processes. Ubiquitination and SUMOylation are multi-step cascade reactions, involving multiple enzymes and protein–protein interactions. Here we report the development of dissociation constant (Kd) determination for protein–protein interaction and cell-based high-throughput screening (HTS) assay in SUMOylation cascade using FRET technology. These developments are based on steady state and high efficiency of fluorescent energy transfer between CyPet and YPet fused with SUMO1 and Ubc9, respectively. The developments in theoretical and experimental procedures for protein interaction Kd determination and cell-based HTS provide novel tools in affinity measurement and protein interaction inhibitor screening. The Kd determined by FRET between SUMO1 and Ubc9 is compatible with those determined with other traditional approaches, such as isothermal titration calorimetry (ITC) and surface plasmon resonance (SPR). The FRET-based HTS is pioneer in cell-based HTS. Both Kd determination and cell-based HTS, carried out in 384-well plate format, provide powerful tools for large-scale and high-throughput applications