Serum and synovial fluid lipidomic profiles predict obesity-associated osteoarthritis, synovitis, and wound repair

High-fat diet-induced obesity is a major risk factor for osteoarthritis (OA) and diminished wound healing. The objective of this study was to determine the associations among serum and synovial fluid lipid levels with OA, synovitis, adipokine levels, and wound healing in a pre-clinical obese mouse model of OA. Male C57BL/6 J mice were fed either a low-fat (10% kcal) or one of three high-fat (HF, 60% kcal) diets rich in saturated fatty acids (SFAs), ω-6 or ω-3 polyunsaturated FAs (PUFAs). OA was induced by destabilization of the medial meniscus. Mice also received an ear punch for evaluating wound healing. Serum and synovial fluid were collected for lipidomic and adipokine analyses. We demonstrated that the serum levels of ω-3 PUFAs were negatively correlated with OA and wound size, but positively correlated with adiponectin levels. In contrast, most ω-6 PUFAs exhibited positive correlations with OA, impaired healing, and inflammatory adipokines. Interestingly, levels of pentadecylic acid (C15:0, an odd-chain SFA) and palmitoleic acid were inversely correlated with joint degradation. This study extends our understanding of the links of FAs with OA, synovitis and wound healing, and reports newly identified serum and synovial fluid FAs as predictive biomarkers of OA in obesity

Loss of vesicular dopamine release precedes tauopathy in degenerative dopaminergic neurons in a Drosophila model expressing human tau.

While a number of genome-wide association studies have identified microtubule-associated protein tau as a strong risk factor for Parkinson's disease (PD), little is known about the mechanism through which human tau can predispose an individual to this disease. Here, we demonstrate that expression of human wild-type tau is sufficient to disrupt the survival of dopaminergic neurons in a Drosophila model. Tau triggers a synaptic pathology visualized by vesicular monoamine transporter-pHGFP that precedes both the age-dependent formation of tau-containing neurofibrillary tangle-like pathology and the progressive loss of DA neurons, thereby recapitulating the pathological hallmarks of PD. Flies overexpressing tau also exhibit progressive impairments of both motor and learning behaviors. Surprisingly, contrary to common belief that hyperphosphorylated tau could aggravate toxicity, DA neuron degeneration is alleviated by expressing the modified, hyperphosphorylated tau(E14). Together, these results show that impairment of VMAT-containing synaptic vesicle, released to synapses before overt tauopathy may be the underlying mechanism of tau-associated PD and suggest that correction or prevention of this deficit may be appropriate targets for early therapeutic intervention

A Two-Phase Maximum-Likelihood Sequence Estimation for Receivers with Partial CSI

The optimality of the conventional maximum likelihood sequence estimation (MLSE), also known as the Viterbi Algorithm (VA), relies on the assumption that the receiver has perfect knowledge of the channel coefficients or channel state information (CSI). However, in practical situations that fail the assumption, the MLSE method becomes suboptimal and then exhaustive checking is the only way to obtain the ML sequence. At this background, considering directly the ML criterion for partial CSI, we propose a two-phase low-complexity MLSE algorithm, in which the first phase performs the conventional MLSE algorithm in order to retain necessary information for the backward VA performed in the second phase. Simulations show that when the training sequence is moderately long in comparison with the entire data block such as 1/3 of the block, the proposed two-phase MLSE can approach the performance of the optimal exhaustive checking. In a normal case, where the training sequence consumes only 0.14 of the bandwidth, our proposed method still outperforms evidently the conventional MLSE.Comment: 5 pages and 4 figure

Gratitude and athletes’ life satisfaction: a intra-individual analysis on the moderation of ambivalence over emotional expression

Research on gratitude usually focus on how trait gratitude can contribute to higher subjective well-being, but rarely focus on the role of state gratitude in shaping one’s subjective well-being at a given moment. Focusing on intra-individual differences, the first aim of this study is to examine whether state gratitude will contribute to higher state life satisfaction. Nevertheless, state gratitude may not always contribute to higher state life satisfaction. The second aim of this study is to determinate that when ambivalence over emotional expression in a given moment becomes higher, the association between state gratitude and state life satisfaction will become weaker. Twenty-nine elite student athletes were recruited and completed weekly questionnaires measuring gratitude, life satisfaction, and ambivalence over emotional expression across 10 weeks. Results of hierarchical linear modeling support hypotheses, showing that weekly gratitude positively predicted weekly life satisfaction, but this association was weaker when weekly ambivalence over emotional expression was higher than lower. Contributions to gratitude studies are discussed

Unpacking the role of self-esteem in career uncertainty: a self-determination perspective

The aim of this study is to explain why students with high self-esteem have lower career uncertainty than students with low self-esteem. Based on self-determination theory, students with high self-esteem would have higher efficacy in making decisions, which would encourage them to choose a major for self-concordance, such as interest and ability, and increase their course involvement. Both factors are assumed to be related to lower career uncertainty. Data from a national survey of the Taiwan Higher Education Database within the Survey Research Data Archive from juniors at 92 colleges and universities in Taiwan (N = 7418) were analyzed to examine the model. Results supported the proposed model by showing that students with high self-esteem had lower career uncertainty because they chose a major for self-concordant reasons and had a strong motivation to learn, both of which contribute to lower career uncertainty

Gratitude and Athletes’ Life Satisfaction: The Moderating Role of Mindfulness

Life satisfaction is a critical index of well-being and is well documented in the literature as a means of protecting athletes from stress. However, minimal research has focused on the factors that contribute to life satisfaction in sports. Accordingly, we adopted the positive psychology perspective and proposed that gratitude would relate to athletes’ life satisfaction. Additionally, we further suggested that mindfulness would strengthen the relationship between gratitude and athletes’ life satisfaction. Athletes completed measurements, and the results, which indicated that athletes with higher levels of gratitude exhibited increased life satisfaction when they had higher levels of mindfulness, supported our expectations. The implications and applications are discussed in terms of mindfulness

Extraction of single-trial cortical beta oscillatory activities in EEG signals using empirical mode decomposition

<p>Abstract</p> <p>Background</p> <p>Brain oscillatory activities are stochastic and non-linearly dynamic, due to their non-phase-locked nature and inter-trial variability. Non-phase-locked rhythmic signals can vary from trial-to-trial dependent upon variations in a subject's performance and state, which may be linked to fluctuations in expectation, attention, arousal, and task strategy. Therefore, a method that permits the extraction of the oscillatory signal on a single-trial basis is important for the study of subtle brain dynamics, which can be used as probes to study neurophysiology in normal brain and pathophysiology in the diseased.</p> <p>Methods</p> <p>This paper presents an empirical mode decomposition (EMD)-based spatiotemporal approach to extract neural oscillatory activities from multi-channel electroencephalograph (EEG) data. The efficacy of this approach manifests in extracting single-trial post-movement beta activities when performing a right index-finger lifting task. In each single trial, an EEG epoch recorded at the channel of interest (CI) was first separated into a number of intrinsic mode functions (IMFs). Sensorimotor-related oscillatory activities were reconstructed from sensorimotor-related IMFs chosen by a spatial map matching process. Post-movement beta activities were acquired by band-pass filtering the sensorimotor-related oscillatory activities within a trial-specific beta band. Signal envelopes of post-movement beta activities were detected using amplitude modulation (AM) method to obtain post-movement beta event-related synchronization (PM-bERS). The maximum amplitude in the PM-bERS within the post-movement period was subtracted by the mean amplitude of the reference period to find the single-trial beta rebound (BR).</p> <p>Results</p> <p>The results showed single-trial BRs computed by the current method were significantly higher than those obtained from conventional average method (<it>P </it>< 0.01; matched-pair Wilcoxon test). The proposed method provides high signal-to-noise ratio (SNR) through an EMD-based decomposition and reconstruction process, which enables event-related oscillatory activities to be examined on a single-trial basis.</p> <p>Conclusions</p> <p>The EMD-based method is effective for artefact removal and extracting reliable neural features of non-phase-locked oscillatory activities in multi-channel EEG data. The high extraction rate of the proposed method enables the trial-by-trial variability of oscillatory activities can be examined, which provide a possibility for future profound study of subtle brain dynamics.</p