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Superparamagnetic clustering (SPC) is an unsupervised classification technique in which clusters are self-organised based on data density and mutual interaction energy. Traditional SPC algorithm uses the Swendsen–Wang Monte Carlo approximation technique to significantly reduce the search space for reasonable clustering. However, Swendsen–Wang approximation is a Markov process which limits the conventional superparamagnetic technique to process data clustering in a sequential manner. Here the authors propose a parallel approach to replace the conventional appropriation to allow the algorithm to perform clustering in parallel. One synthetic and one open-source dataset were used to validate the accuracy of this parallel approach in which comparable clustering results were obtained as compared to the conventional implementation. The parallel method has an increase of clustering speed at least 8.7 times over the conventional approach, and the larger the sample size, the more increase in speed was observed. This can be explained by the higher degree of parallelism utilised for the increased data points. In addition, a hardware architecture was proposed to implement the parallel superparamagnetic algorithm using digital electronic technologies suitable for rapid or real-time neural spike sorting.

BackgroundSupport vector machines (SVMs) based on brain-wise functional connectivity (FC) have been widely adopted for single-subject prediction of patients with schizophrenia, but most of them had small sample size. This study aimed to evaluate the performance of SVMs based on a large single-site dataset and investigate the effects of demographic homogeneity and training sample size on classification accuracy.MethodsThe resting functional Magnetic Resonance Imaging (fMRI) dataset comprised 220 patients with schizophrenia and 220 healthy controls. Brain-wise FCs was calculated for each participant and linear SVMs were developed for automatic classification of patients and controls. First, we evaluated the SVMs based on all participants and homogeneous subsamples of men, women, younger (18–30 years), and older (31–50 years) participants by 10-fold nested cross-validation. Then, we hold out a fixed test set of 40 participants (20 patients and 20 controls) and evaluated the SVMs based on incremental training sample sizes (N = 40, 80, …, 400).ResultsWe found that the SVMs based on all participants had accuracy of 85.05%. The SVMs based on male, female, young, and older participants yielded accuracy of 84.66, 81.56, 80.50, and 86.13%, respectively. Although the SVMs based on older subsamples had better performance than those based on all participants, they generalized poorly to younger participants (77.24%). For incremental training sizes, the classification accuracy increased stepwise from 72.6 to 83.3%, with >80% accuracy achieved with sample size >240.ConclusionsThe findings indicate that SVMs based on a large dataset yield high classification accuracy and establish models using a large sample size with heterogeneous properties are recommended for single subject prediction of schizophrenia.

Integrated optrodes for optogenetics have been becoming a significant tool in neuroscience through the combination of offering accurate stimulation to target cells and recording biological signals simultaneously. This makes it not just be widely used in neuroscience researches, but also have a great potential to be employed in future treatments in clinical neurological diseases. To optimize the integrated optrodes, this paper aimed to investigate the influence of surface material and illumination upon the performance of the microelectrode/electrolyte interface and build a corresponding evaluation system. In this work, an integrated planar optrode with a blue LED and microelectrodes was designed and fabricated. The charge transfer mechanism on the interface was theoretically modeled and experimentally verified. An evaluation system for assessing microelectrodes was also built up. Using this system, the proposed model of various biocompatible surface materials on microelectrodes was further investigated under different illumination conditions. The influence of illumination on the microelectrode/electrolyte interface was the cause of optical artifacts, which interfere the biological signal recording. It was found that surface materials had a great effect on the charge transfer capacity, electrical stability and recoverability, photostability, and especially optical artifacts. The metal with better charge transfer capacity and electrical stability is highly possible to have a better performance on the optical artifacts, regardless of its electrical recoverability and photostability under the illumination conditions of optogenetics. Among the five metals used in our investigation, iridium served as the best surface material for the proposed integrated optrodes. Thus, optimizing the surface material for optrodes could reduce optical interference, enhance the quality of the neural signal recording for optogenetics, and thus help to advance the research in neuroscience.

Recent technical advancements in neural engineering allow for precise recording and control of neural circuits simultaneously, opening up new opportunities for closed-loop neural control. In this work, a rapid spike sorting system was developed based on template matching to rapidly calculate instantaneous firing rates for each neuron in a multi-unit extracellular recording setting. Cluster templates were first generated by a desktop computer using a non-parameter spike sorting algorithm (Super-paramagnetic clustering) and then transferred to a field-programmable gate array digital circuit for rapid sorting through template matching. Two different matching techniques-Euclidean distance (ED) and correlational matching (CM)-were compared for the accuracy of sorting and the performance of calculating firing rates. The performance of the system was first verified using publicly available artificial data and was further confirmed with pre-recorded neural spikes from an anesthetized Mongolian gerbil. Real-time recording and sorting from an awake mouse were also conducted to confirm the system performance in a typical behavioral neuroscience experimental setting. Experimental results indicated that high sorting accuracies were achieved for both template-matching methods, but CM can better handle spikes with non-Gaussian spike distributions, making it more robust for in vivo recording. The technique was also compared to several other off-line spike sorting algorithms and the results indicated that the sorting accuracy is comparable but sorting time is significantly shorter than these other techniques. A low sorting latency of under 2 ms and a maximum spike sorting rate of 941 spikes/second have been achieved with our hybrid hardware/software system. The low sorting latency and fast sorting rate allow future system developments of neural circuit modulation through analyzing neural activities in real-time.

Objectives Environmental exposure at home, such as dampness, has been shown to have adverse effects on respiratory health. However, few studies explored the association between home dampness and genetic polymorphisms on childhood asthma. The aim of the study is to evaluate the effects of home dampness and tumour necrosis factor-α gene ( TNF-α ) on asthma in Taiwanese children. Methods The authors investigated 3810 schoolchildren in Taiwan Children Health Study from 14 communities. Children9s exposure and disease status were measured from a parental questionnaire. Multiple logistic regression models were fitted to estimate the effects of home dampness exposure and TNF-α genotypes on the prevalence of asthma and wheeze. Results Mildewy odour at home was significantly associated with increased prevalence of lifetime wheeze (OR=1.36, 95% CI 1.05 to 1.77, p for trend=0.04). The effects of water stamp on the wall at home were associated with lifetime asthma and lifetime wheeze. Children with water stamp on the wall at home and TNF-308 A allele had increased risks on lifetime asthma, active asthma and lifetime wheeze. TNF-α showed significant interactive effects with mildewy odour on lifetime asthma (p for interaction=0.01), and with water stamp on the wall at home on lifetime wheeze (p for interaction=0.04). Under stratification by TNF-308 genotypes, we found that the frequency of water stamp on the wall was associated with increased risks of all asthma subcategories and lifetime wheeze among TNF-308 GA or AA genotypes (p for trend Conclusions Home dampness is a risk factor for asthma and wheeze among children, especially for those with the TNF-308 A allele.

A wearable wireless general purpose bio-signal acquisition prototype system is presented in this paper. Three types of bio-signals could be acquired by the system then wirelessly transmitted to the computer for real-time processing. The prototype experimental results show that the system could acquire electrocardiogram (ECG), surface-electromyography (s-EMG) and electroencephalogram (EEG) for home healthcare and telemedicine.

This paper describes a high-dynamic-range 2.4 Hz-to-10 kHz wide-range tunable 5th-order Butterworth lowpass filter for biomedical applications. A differential g m -C topology in conjunction with a subthreshold-biased wide-g m -range OTA realizes efficiently a wide frequency tuning capability. For capacitance savings with consequent silicon area reduction, a merged use of floating real capacitor and grounded multiplier-based capacitor is proposed. Optimized in a 0.35-µm CMOS process, the filter achieves over 68-dB dynamic range, 64 dB stopband attenuation and 28 µW power consumption at a single 3-V supply.

Emotional changes, impairment of object recognition, and neuroinflammation are seen in Parkinson's disease with dementia (PDD). Here, we show that bilateral infusion of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) into the rat substantia nigra pars compacta (SNc) of Wistar rats caused degeneration of nigrostriatal dopaminergic neurons, microglial activation in the SNc and hippocampus, and cell loss in the hippocampal CA1 area. With regard to behavior, an increase in anxiety-like behavior and impairment of object recognition were observed during the fourth week after MPTP lesioning. The behavioral changes were not caused by motor impairment, since the rats had already recovered from MPTP-induced catalepsy before the tests were performed. These findings show that MPTP-induced neuroinflammation and its consequences, for example, microglial activation and cell loss in the hippocampus, may be involved in dopaminergic degeneration-related behavioral deficits and suggest that, in addition to the dopaminergic system, the limbic system may also participate in the pathophysiology of PDD. MPTP-lesioned rats are therefore proposed as a useful tool for assessing the ability of pharmacological agents to prevent recognition deficits in PDD.

This paper introduces a general purpose intelligent adaptive biosignal acquisition system both using Field Programmable Gate Array (FPGA) and Field Programmable Analog Array (FPAA). The design system inherits the powerful properties from the above devices to provide a stable and adaptive platform for processing various biosignals like ECG, EMG and EEG, etc. This system implementation solves the complexity in biosignal samples acquisition in home healthcare and stability in long term monitoring. It can be dynamically reconfigured and adapt to acquire different biosignals without changing any hardware. This system provides a simplified testing platform allowing different algorithms for processing real time biosignals embedded into it. In additions, the RS232 serial data port (or USB) can implement a connection with personal computer to ease and speed up the acquiring of biosignal samples or test results for further analysis. Alternatively, the system is also designed for outputting acquired and/or processed biosignals to PDA/PC at real time for visual inspection of results.

This paper introduces a portable, battery operable bioelectric signals acquisition system with an adaptive, online reconfigurable frontend implemented on programmable hardware like Field Programmable Gate Array (FPGA) and Field Programmable Analog Array (FPAA). This system inherits the properties and functionalities in [1] with advancements in system modularity, independency and mobility. The system can acquire electrocardiogram (ECG), surface electromyography (EMG) and electroencephalogram (EEG) with the same hardware system and solves the complexity for acquiring different bioelectric signals in non-medical devices for home-healthcare and telemedicine. The modular design also supports addition of extra functions without much impact on other existing modules. VGA interface and battery operation are introduced to increase the system independency, usability and possibility for integrating into mobile devices.

Human telomeric repeat binding factor 1(TRF1) contains one Myb-type DNA-binding repeat and an amino-terminal acidic domain. It can bind to the duplex array of TTAGGG repeats at chromosome ends and is shown to be important in preserving genomic stability, maintaining cell proliferative capacity, and blocking the activation of DNA-damage cell cycle checkpoints. Interestingly, the double strand DNA breaks sensor ATM interacts with and phosphorylates Pin2/TRF1 and inhibits its function after DNA damage. Are there some proteins else that can interact with TRF1 and influence its function? In order to analysis the interaction between TRF1 and other proteins, we must prepare the antiserum that can recognize the endogenous TRF1 of cell lysates. TRF1 cDNA was amplified using cDNA Library of HeLa cell by PCR and cloned into pUCm-T vector. Sequence analysis reveals identity to the GenBank report. The TRF1 cDNA was subcloned into expression vector pET-28c(+) and expressed in E. coli as a fusion protein of 65 kD. The recombinant TRF1 can express in the supernatant (about 12.3% in total protein) on the induction of 0.5 mmol/L IPTG at 37 degrees C for 3 hours. Western-blot analysis showed the recombinant protein can react with TRF1 polyclonal antibody sc-6165 (from Santa Cruz Company). His6-TRF1 was purified by Ni(2+) -NTA resin affinity chromatography made by ourselves and showed to be homogeneity in SDS-PAGE. Rabbits were immunized for four times to prepare polyclonal antibody. The unpurified antiserum can recognize the overexpressed TRF1 with myc-tag and the endogenous Pin2/TRF1 of cell lysate by Western-blot at 1:1000 dilution. At 1:400 dilution, the antiserum can interact with endogenous TRF1 by Immunofluorescence cell staining analysis. The endogenous TRF1 in different cell lines, such as HepG2, 803, MCF7 and HeLa, locates in the nucleus. The soluble expression TRF1 and preparation of its antibody lay the foundation to study it further.