Biomimetic and bioactive nanofibrous scaffolds from electrospun composite nanofibers

Electrospinning is an enabling technology that can architecturally (in terms of geometry, morphology or topography) and biochemically fabricate engineered cellular scaffolds that mimic the native extracellular matrix (ECM). This is especially important and forms one of the essential paradigms in the area of tissue engineering. While biomimesis of the physical dimensions of native ECM’s major constituents (eg, collagen) is no longer a fabrication-related challenge in tissue engineering research, conveying bioactivity to electrospun nanofibrous structures will determine the efficiency of utilizing electrospun nanofibers for regenerating biologically functional tissues. This can certainly be achieved through developing composite nanofibers. This article gives a brief overview on the current development and application status of employing electrospun composite nanofibers for constructing biomimetic and bioactive tissue scaffolds. Considering that composites consist of at least two material components and phases, this review details three different configurations of nanofibrous composite structures by using hybridizing basic binary material systems as example. These are components blended composite nanofiber, core-shell structured composite nanofiber, and nanofibrous mingled structure

Knowledge-based identification of sleep stages based on two forehead electroencephalogram channels

© 2014 Huang, Lin, Ko, Liu, Su and Lin. Sleep quality is important, especially given the considerable number of sleep-related pathologies. The distribution of sleep stages is a highly effective and objective way of quantifying sleep quality. As a standard multi-channel recording used in the study of sleep, polysomnography (PSG) is a widely used diagnostic scheme in sleep medicine. However, the standard process of sleep clinical test, including PSG recording and manual scoring, is complex, uncomfortable, and time-consuming. This process is difficult to implement when taking the whole PSG measurements at home for general healthcare purposes. This work presents a novel sleep stage classification system, based on features from the two forehead EEG channels FP1 and FP2. By recording EEG from forehead, where there is no hair, the proposed system can monitor physiological changes during sleep in a more practical way than previous systems. Through a headband or self-adhesive technology, the necessary sensors can be applied easily by users at home. Analysis results demonstrate that classification performance of the proposed system overcomes the individual differences between different participants in terms of automatically classifying sleep stages. Additionally, the proposed sleep stage classification system can identify kernel sleep features extracted from forehead EEG, which are closely related with sleep clinician's expert knowledge. Moreover, forehead EEG features are classified into five sleep stages by using the relevance vector machine. In a leave-one-subject-out cross validation analysis, we found our system to correctly classify five sleep stages at an average accuracy of 76.7 ± 4.0 (SD) % [average kappa 0.68 ± 0.06 (SD)]. Importantly, the proposed sleep stage classification system using forehead EEG features is a viable alternative for measuring EEG signals at home easily and conveniently to evaluate sleep quality reliably, ultimately improving public healthcare

The Clinical Application of Anti-CCP in Rheumatoid Arthritis and Other Rheumatic Diseases

Rheumatoid arthritis (RA) is a common rheumatic disease in Caucasians and in other ethnic groups. Diagnosis is mainly based on clinical features. Before 1998, the only serological laboratory test that could contribute to the diagnosis was that for rheumatoid factor (RF). The disease activity markers for the evaluation of clinical symptoms or treatment outcome were the erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP). As a matter of fact, the diagnosis of early RA is quite impossible, as the clinical criteria are insufficient at the beginning stage of the disease. In 1998, Schelleken reported that a high percentage of RA patients had a specific antibody that could interact with a synthetic peptide which contained the amino acid citrulline. The high specificity (98%) for RA of this new serological marker, anti-cyclic citrullinated antibody (anti-CCP antibody), can be detected early in RA, before the typical clinical features appear. The presence or absence of this antibody can easily distinguish other rheumatic diseases from RA. Additionally, the titer of anti-CCP can be used to predict the prognosis and treatment outcome after DMARDs or biological therapy. Therefore, with improvement of sensitivity, the anti-CCP antibody will be widely used as a routine laboratory test in the clinical practice for RA

Robust Facial Alignment for Face Recognition

© 2017, Springer International Publishing AG. This paper proposes a robust real-time face recognition system that utilizes regression tree based method to locate the facial feature points. The proposed system finds the face region which is suitable to perform the recognition task by geometrically analyses of the facial expression of the target face image. In real-world facial recognition systems, the face is often cropped based on the face detection techniques. The misalignment is inevitably occurred due to facial pose, noise, occlusion, and so on. However misalignment affects the recognition rate due to sensitive nature of the face classifier. The performance of the proposed approach is evaluated with four benchmark databases. The experiment results show the robustness of the proposed approach with significant improvement in the facial recognition system on the various size and resolution of given face images

Early detection of neurodegeneration in brain ischemia by manganese-enhanced MRI

This study aims to employ in vivo manganese-enhanced MRI (MEMRI) to detect neurodegenerative changes in two models of brain ischemia, photothrombotic cortical injury (PCI) and transient middle cerebral artery occlusion (MCAO) in rodents. After systemic Mn 2+ injection to both ischemic models, a close pattern of Tl-weighted hyperintensity was observed throughout different brain regions in comparison to the distribution of GFAP, MnSOD and GS immunoreactivities, whereby conventional MRI could hardly detect such. In addition, the infarct volumes in the posterior parts of the brain had significantly reduced after Mn 2+ injection to the MCAO model. It is suggested that exogenous Mn 2+ injection may provide enhanced MEMRI detection of oxidative stress and gliosis early after brain ischemia. Manganese may also mediate infarctions at remote brain regions in transient focal cerebral ischemia before delayed secondary damage takes place. © 2008 IEEE.published_or_final_versionThe 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS) 2008, Vancouver, BC., 20-25 August 2008. in Proceedings of the 30th EMBS, 2008, p. 3884-388

Forehead EEG in Support of Future Feasible Personal Healthcare Solutions: Sleep Management, Headache Prevention, and Depression Treatment

© 2013 IEEE. There are current limitations in the recording technologies for measuring EEG activity in clinical and experimental applications. Acquisition systems involving wet electrodes are time-consuming and uncomfortable for the user. Furthermore, dehydration of the gel affects the quality of the acquired data and reliability of long-term monitoring. As a result, dry electrodes may be used to facilitate the transition from neuroscience research or clinical practice to real-life applications. EEG signals can be easily obtained using dry electrodes on the forehead, which provides extensive information concerning various cognitive dysfunctions and disorders. This paper presents the usefulness of the forehead EEG with advanced sensing technology and signal processing algorithms to support people with healthcare needs, such as monitoring sleep, predicting headaches, and treating depression. The proposed system for evaluating sleep quality is capable of identifying five sleep stages to track nightly sleep patterns. Additionally, people with episodic migraines can be notified of an imminent migraine headache hours in advance through monitoring forehead EEG dynamics. The depression treatment screening system can predict the efficacy of rapid antidepressant agents. It is evident that frontal EEG activity is critically involved in sleep management, headache prevention, and depression treatment. The use of dry electrodes on the forehead allows for easy and rapid monitoring on an everyday basis. The advances in EEG recording and analysis ensure a promising future in support of personal healthcare solutions

A robust real-time facial alignment system with facial landmarks detection and rectification for multimedia applications

© 2020, Springer Science+Business Media, LLC, part of Springer Nature. Face detection often plays the first step in various visual applications. Large variants of facial deformations due to head movements and facial expression make it difficult to identify appropriate face region. In this paper, a robust real-time face alignment system, including facial landmarks detection and face rectification, is proposed. A facial landmarks detection model based on regression tree is utilized in the proposed system. In face rectification framework, 2-D geometrical analysis based on pitch, yaw and roll movements is designed to solve the misalignment problem in face detection. The experiments on the two datasets verify the performance significantly improved by the proposed method in the facial recognition task and outperform than those obtained by other alignment methods. Furthermore, the proposed method can achieve robust recognition results even if the amount of training images is not large

Transmutations and spectral parameter power series in eigenvalue problems

We give an overview of recent developments in Sturm-Liouville theory concerning operators of transmutation (transformation) and spectral parameter power series (SPPS). The possibility to write down the dispersion (characteristic) equations corresponding to a variety of spectral problems related to Sturm-Liouville equations in an analytic form is an attractive feature of the SPPS method. It is based on a computation of certain systems of recursive integrals. Considered as families of functions these systems are complete in the $L_{2}$-space and result to be the images of the nonnegative integer powers of the independent variable under the action of a corresponding transmutation operator. This recently revealed property of the Delsarte transmutations opens the way to apply the transmutation operator even when its integral kernel is unknown and gives the possibility to obtain further interesting properties concerning the Darboux transformed Schr\"{o}dinger operators. We introduce the systems of recursive integrals and the SPPS approach, explain some of its applications to spectral problems with numerical illustrations, give the definition and basic properties of transmutation operators, introduce a parametrized family of transmutation operators, study their mapping properties and construct the transmutation operators for Darboux transformed Schr\"{o}dinger operators.Comment: 30 pages, 4 figures. arXiv admin note: text overlap with arXiv:1111.444

Red wine polyphenols prevent metabolic and cardiovascular alterations associated with obesity in Zucker fatty rats (Fa/Fa)

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