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Background: Long non-coding RNA (lncRNA) prostate cancer gene expression marker 1 (PCGEM1) has been revealed to participate in the pathogenesis of osteoarthritis (OA). However, the molecular mechanism of PCGEM1 regulating OA progression has not been fully elucidated.Methods: Fibroblast-like synoviocytes (FLSs) were isolated from synovium tissues of OA patients (OA-FLSs) and trauma donors (Normal-FLSs). The size and morphology of the isolated exosomes were analyzed by transmission electron microscopy and nanoparticle tracking analysis. Protein levels were analyzed by western blotting. Expression levels of PCGEM1, microRNA-142-5p (miR-142-5p), runt-related transcription factor 2 (RUNX2) mRNA, and OA related genes were assessed by qRT-PCR. Cell proliferation, viability, and apoptosis were evaluated by 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide or flow cytometry assays. The relationship between miR-142-5p and PCGEM1 or RUNX2 was verified by dual-luciferase reporter and/or RNA pull down assays.Results: PCGEM1 was overexpressed in OA cartilages and exosomes from OA-FLSs. Exosomal PCGEM1 from OA-FLSs facilitated IL-1β-induced apoptosis and cartilage matrix degradation in chondrocytes. MiR-142-5p was downregulated while RUNX2 was upregulated in OA cartilages. Exosomal PCGEM1 from OA-FLSs regulated RUNX2 expression by sponging miR-142-5p in IL-1β-induced chondrocytes. MiR-142-5p inhibitor offset exosomal PCGEM1 knockdown-mediated effects on the apoptosis and cartilage matrix degradation of IL-1β-induced chondrocytes. RUNX2 overexpression counteracted the suppressive effect of miR-142-5p mimic on apoptosis and cartilage matrix degradation of IL-1β-induced chondrocytes.Conclusion: Exosomal PCGEM1 from OA-FLSs facilitated IL-1β-induced apoptosis and cartilage matrix degradation in chondrocytes by sequestering miR-142-5p and upregulating RUNX2, which offered new insights into the pathogenesis of OA.

In this letter, the 1-bit compressive sensing (CS) technology is utilized to recover joint sparse signal. In the context of multi-bits quantization, compared to the single measurement vector (SMV) case, the successful recovery rate can be significantly improved using multiple measurement vectors (MMV) model. Therefore, we introduce the MMV model for signal recovery from 1-bit sampling. Due to the amplitude information loss using 1-bit quantizing, a new sampling framework is proposed to estimate the l 2 -norm of each measurement vector for continuous-time signal, followed by the corresponding estimation algorithm 1-bit iterative hard thresholding (1-bit IHT). Then we develop the algorithm of binary IHT for MMV (M-BIHT) to recover joint sparse signal under uncertain noise. Compared to the 1-bit SMV model and multi-bits quantization MMV mode, the experimental results illustrate the recovery performance is improved greatly by the 1-bit MMV model.

In this paper, we investigate the problem of bandwidth allocation in wireless sensor network (WSN) under signal to noise plus interference ratio interference model, which aims at finding a tradeoff between fairness and network throughput. Specifically, we propose an approximate algorithm to solve this problem since it has been proved to be NP-hard. Different from similar algorithms proposed in previous issues, we maximize two utility functions, which are the newly defined bandwidth utility function for fairness and network throughput, by jointly considering sensor nodes association and resource allocation in WSN. In addition, we formulate a new utility function with respect to bandwidth allocation, with the method of weighted sum of two objectives as one objective function, which will find a tradeoff between fairness and throughput. Consequently, the problem is decomposed into two sub-problems and solved in two stages, which are cluster formation stage and scheduling stage. In the first stage, we let sensor nodes join to cluster head nodes, which can determine the association of sensor nodes; in the second stage, the total utility function is maximized by allocating time slots for tradeoff between fairness and throughput. Finally, simulation results demonstrate that our algorithm can achieve better performance than compared algorithms.

Two main factors that impact the performance of data aggregation in wireless sensor networks (WSNs) are data quality and energy efficiency. This paper exploits the tradeoff between data quality and energy consumption to maximize the data aggregation precision under heterogeneous per-node energy constraints. Unlike previous work, we explicitly account for link loss in the optimization framework. To tackle link unreliability, we need to appropriately allocate the limited energy across the incoming and outgoing links of each individual node. We present a centralized algorithm based on the Immune-Genetic heuristic to find near-optimal energy allocation strategy such that the precision of the aggregated data received by the sink is maximized. The algorithmic complexity and implementation issues are also discussed. Furthermore, we develop a localized alternative algorithm based on the Gibbs sampler, which is more scalable and can adapt to large-scale distributed WSNs. Finally, we conduct numerical simulations to demonstrate the convergence as well as the data aggregation precision performance of the proposed algorithms.

The acoustic recognition technology of unattended ground sensor systems applied in wild environments is faced with the challenge of complicated and strong acoustic noise, especially wind noise. Moreover, the commonly used Mel-frequency cepstral coefficients (MFCCs) are sensitive to noise interference. To resolve the problem, a robust feature extraction method, called harmonic Mel-frequency cepstral coefficients (HMFCCs), is proposed for acoustic target classification. By combining an acoustic signal's harmonic model with the MFCC method, the HMFCC has the ability to emphasize the signals emitted by the principal acoustic components of the target. In the experiment conducted for this study, three data sets are sampled under the same conditions, except for wind power levels. Then the classifier, which is trained by one of the three data sets, is used to recognize the others data sets. According to the experimental results, the HMFCC-based classification accuracies of the three data sets are higher than those of other state-of-the-art methods, indicating that HMFCC is a kind of noise-insensitive feature.

We study the minimum latency data broadcast problem under the signal-to-interference-plus-noise-ratio (SINR) model, which is known to capture wireless interference more accurately and realistically than the widely used graph-based models. Previous work mainly involves building a broadcast tree first and then computing interference-aware TDMA schedules for the links on the tree. Observing that the separation of routing and scheduling may lead to unsaturated transmissions in each time slot, we develop a polynomial-time heuristic algorithm, namely PRS, by advocating a parallel way of constructing routing and transmission schedules. Theoretical analysis indicates that PRS generates correct schedules under the SINR constraints. Simulation results demonstrate that PRS outperforms state-of-the-art algorithms in terms of broadcast latency under various network conditions.

We study the problem of minimizing data aggregation time in wireless sensor networks (WSNs) under the practical duty-cycle scenario where nodes switch between active states and dormant states periodically for energy efficiency. Under the protocol interference model, we show that the problem is NP-hard and present a lower bound of delay for any data aggregation scheme. To solve the problem efficiently, we then construct a routing tree based on connected dominator set and propose two aggregation scheduling algorithms, which are the centralized Greedy Aggregation Scheduling (GAS) and the distributed Partitioned Aggregation Scheduling (PAS), so as to generate collision-free transmission schedules for data aggregation in duty-cycled WSNs. To minimize the total delay, GAS tries to achieve maximal concurrent transmissions in each time-slot during each frame by using global information, while PAS leverages a network partition based strategy and local information to ensure the largest degree of channel reuse across space and time domains. Theoretical analysis indicates that each algorithm consumes at most $$O(R+\varDelta)$$ O ( R + Δ ) frames and achieves nearly constant factor approximation on the optimal delay. Here R and $$\varDelta$$ Δ are the network radius and the maximum node degree, respectively. We also evaluate the practicability of our algorithms by extensive simulations under various network conditions and the results corroborate our theoretical analysis.

Data aggregation is an essential operation in many applications of Wireless Sensor Networks (WSNs). For energy constrained and delay sensitive WSNs, how to prolong the lifetime and reduce the latency of the network are two critical problems. We deal with these two problems together in data aggregation by proposing a Load Balanced and Delay Efficient Algorithm (LBDEA), which consists of two phases. First, construct a load-balanced data aggregation tree based on Semi-Matching algorithm in the graph theory. Second, seek a collision-free scheduling based on greedy strategy for the transmission links in the aggregation tree. Through balancing the load of the sensor nodes, the lifetime of the network is optimized. By avoiding collisions and retransmissions of data delivery, the total latency is decreased. Simulations show that LBDEA not only improves the lifetime but also cuts down the delay for data aggregation in WSNs, compared with other related algorithms.

The feasibility of bone marrow stromal cells autologous transplantation for rabbit model of dilated cardiomyopathy induced by adriamycin was studied. Twenty rabbits received 2 mg/kg of adriamycin intravenously once a week for 8 weeks (total dose, 16 mg/kg) to induce the cardiomyopathy model with the monitoring of cardiac function by transthoracic echocardiography. Marrow stromal cells were isolated from cell-transplanted group rabbits and were culture-expanded on the 8th week. On the 10th week, cells were labeled with 4,6-diamidino-2-phenylindole (DAPI), and then injected into the myocardium of the same rabbits. The results showed that viable cells labeled with DAPI could be identified in myocardium at 2nd week after transplantation. Histological findings showed the injury of the myocardium around the injection site was relieved with less apoptosis and more expression of bcl-2. The echocardiography found the improvement of local tissue movement from (2.12+/-0.51) cm/s to (3.81+/-0.47) cm/s (P0.05) around the inject site, but no improvement of heart function as whole. It was concluded bone marrow stromal cells transplantation for dilated cardiomyopathy was feasibe. The management of cells in vitro, the quantity and the pattern of the cells transplantation and the action mechanism still need further research.

This paper focuses on wide-sense stationary signal processing within a compressive sensing framework, proposing a new method of compressive sampling fast Fourier transform (FFT) accumulation method (CS-FAM). Depending on how it is applied, CS-FAM has one or two steps, allowing for versatility in multiband signal detection and parameter extraction. In the first step, the active sub-bands are detected using multiple measurement vectors (MMVs) and multiuser detection is achieved using a bandwidth constraint. In applications where it is required, such as in estimations of carrier frequency, symbol rate, or modulation format identification, the second step can be used to reconstruct the cyclic spectrums of each user individually. Based on the results of first step, parameter extraction is performed by searching for peaks in the cyclic spectrum rather than by the usual method of setting a threshold. Compared to other cyclic feature detection methods based on sub-Nyquist sampling, CS-FAM is low in complexity, allowing for practical implementation. Based on the results of the first step, parameter extraction from the cyclic spectrum is performed by searching for peaks rather than by setting a threshold. Although CS-FAM can only be employed for multiband signal detection, compared to other cyclic feature detection methods based on sub-Nyquist sampling, it is low in complexity, which makes practical implementation possible. Numerical simulations are presented to demonstrate the robustness of CS-FAM's multiband signal detection and the effectiveness of its cyclic spectrum estimation against both sampling rate reduction and noise uncertainty.

Background Inadequate right atrial myocardial preservation during cardioplegic arrest may promote postoperative supraventricular arrhythmias (SVA). We determined (1) if oxygenated St. Thomas Hospital Cardioplegia #2 (STH2) alone causes slow reaction pacemaker cell (SR) quiescence; and (2) if hypothermia, higher [K + ], lower [Ca 2+ ], and verapamil in STH2 suppresses SR electrical activity. Materials and methods A glass microelectrode recorded SA node SR membrane action potentials (AP) in rabbits ( n = 23, 1.93 ± 0.45 kg) randomized to normothermic STH2 (33°C, n = 6), hypothermia (20°C, n = 4), hypothermic STH2 (22°C, n = 3), lower calcium STH2 ( n = 3), higher potassium STH2 ( n = 4), and STH2 plus Verapamil ( n = 3). Results Normothermic STH2 depressed SR action potential amplitude and action potential duration (APD), but did not completely suppress action potential generation. Hypothermia alone prolonged APD and sinus cycle length and suppressed SR AP. STH2 with hypothermia (to 20°C) completely suppressed propagating AP and STH2 plus 0.04 Ca 2+ mEq/L inhibited SR AP generation. STH2 plus 30 mEq K + and STH2 plus 2.5 mmol/L verapamil failed to generate SR AP. Conclusion STH2 cannot prevent SA node SR myocardial cells from low-amplitude AP autogeneration above 21°C. STH2 with 30 mEq/L K + , STH2 with 0.02mEq/L Ca 2+ , and STH2 plus 2.5 mmol/L verapamil can arrest AP generation in SR and potentially prevent postoperative SVA.

Data broadcast is a fundamental operation in wireless sensor networks (WSNs). The existence of wireless interference makes it nontrivial to design a minimum-latency broadcast scheme, which is known to be NP-hard. Existing works all assume strict time synchronization and provide centralized TDMA scheduling algorithms. However, WSNs in practice are more likely to be distributed asynchronous systems. In this paper, we investigate the problem of data broadcast with minimum latency for distributed asynchronous WSNs. To this end, we propose a Distributed Asynchronous Broadcast (DAB) algorithm which crucially leverages an elaborately optimized carrier-sensing range together with collision-backoff schemes to coordinate the transmissions among the nodes on a predetermined broadcast backbone. Theoretical analysis shows that DAB is order-optimal and achieves constant factor approximation to the optimal delay. We then conduct extensive simulations to evaluate the practical capability of DAB in asynchronous WSNs and the results corroborate our theoretical analysis.

Inadequate right atrial myocardial preservation during cardioplegic arrest may promote postoperative supraventricular arrhythmias (SVA). We determined (1). if oxygenated St. Thomas Hospital Cardioplegia #2 (STH2) alone causes slow reaction pacemaker cell (SR) quiescence; and (2). if hypothermia, higher [K(+)], lower [Ca(2+)], and verapamil in STH2 suppresses SR electrical activity.A glass microelectrode recorded SA node SR membrane action potentials (AP) in rabbits (n = 23, 1.93 +/- 0.45 kg) randomized to normothermic STH2 (33 degrees C, n = 6), hypothermia (20 degrees C, n = 4), hypothermic STH2 (22 degrees C, n = 3), lower calcium STH2 (n = 3), higher potassium STH2 (n = 4), and STH2 plus Verapamil (n = 3).Normothermic STH2 depressed SR action potential amplitude and action potential duration (APD), but did not completely suppress action potential generation. Hypothermia alone prolonged APD and sinus cycle length and suppressed SR AP. STH2 with hypothermia (to 20 degrees C) completely suppressed propagating AP and STH2 plus 0.04 Ca(2+) mEq/L inhibited SR AP generation. STH2 plus 30 mEq K(+) and STH2 plus 2.5 mmol/L verapamil failed to generate SR AP.STH2 cannot prevent SA node SR myocardial cells from low-amplitude AP autogeneration above 21 degrees C. STH2 with 30 mEq/L K(+), STH2 with 0.02 mEq/L Ca(2+), and STH2 plus 2.5 mmol/L verapamil can arrest AP generation in SR and potentially prevent postoperative SVA.

To investigate the role of anti- interleukin-2 receptor (CD25) monoclonal antibody in the regulation of cytokine mRNA expression of IL-1beta, IL-2, CD25, IL-4, IL-5, IL-6, IL-10, tumour necrosis factor-alpha (TNFalpha), and interferon-gamma (IFNgamma) in cardiac allografts to elucidate its immunological mechanism and role in rats that have undergone cardiac transplantation.These in vivo studies were conducted using a rat MHC mismatch SD to Wistar heterotopic cardiac transplant model. Simulect, an anti-CD25 antibody, was used to prevent allograft rejection. An increase in the rate of allograft survival was observed. Rats were sacrificed on day 1, 3, 5, 7, 9, 11, 14 post-transplantation and hearts were harvested for further study. Cytokine mRNA expression was determined by semiquantitative RT-PCR.In the control group, cardiac allografts were rejected at 8.3 +/- 1.7 days after transplantation (x +/- s). The rats who received CsA rejected the cardiac allograft at 26.4 +/- 5.7 days post-transplant. Allograft survival of Simulect-treated rats was 29.2 +/- 7.1 days (P0.05 vs controls). Rats treated with simulect and CsA had the longest survival of 55.0 +/- 11.6 days (P0.001 vs controls). CD25 mRNA expression in the heart tissue samples of treated rats was undetectable or very weak. However, the untreated group, CD25 expression increased, although anti-CD25 decreased this CD25 expression in the heart graft. Furthermore, in untreated allografts, IL-2, TNFalpha and IFN-gamma were strongly expressed, an effect that markedly decreased after simulect treatment. Finally, IL-4, IL-5, IL-6 and IL-10 expression was strong in anti-CD25-treated allografts.These results suggest that anti-CD25 antibody treatment may not only neutralize CD25 activity but also play a role in altering cytokine mRNA expression and prolong the survival of allografts.