Abstract:Normal synovium is mainly composed of fibroblasts and macrophages. In the pathological process of rheumatoid arthritis (RA), the “tumor like” transformation of fibroblasts is considered to be related to inducers secreted by M1 macrophages. They are manifested as excessive proliferation, decreased apoptosis and abnormal secretion of pro-inflammatory factors, which in turn stimulate the macrophages for M1 polarization. However, the effect of M1 macrophages on fibroblasts and vascular endothelial cells has not been reported. In this study, we aim to reveal the interactions between different types of cells in the RA synovium. mRNA expression of IL-8 and eNOS in M0 and M1 macrophages derived from human myeloid leukemia monocytes (THP-1) were detected by real-time fluorescence quantitative method. Moreover, the concentration of inflammatory factors in the supernatant of THP-1 derived M1 macrophages was determined by enzymelinked immunosorbent assay. In addition, the proliferation of fibroblasts and vascular endothelial cells was investigated by CCK8. The results showed that interlekin-1β and interlekin-8 proteins were mainly secreted by THP-1 derived M1 macrophages. We found that the rheumatoid arthritis synovial fibroblasts (MH7A) treated with mixture of M1 macrophage supernatant and serum-containing roswell park memorial institute (RPMI) with the ratio of 7∶3 for 48 h, and the cells proliferation was improved. Meanwhile, the proliferation of human umbilical vein cells was remarkable enhanced after treated with the mixture ratio at 6∶4 or 7∶3 for 72 h. Based on this study, we will further establish the in vitro RA pannus model in future, which will facilitate the generation of high-throughput screening techniques for anti-RA drugs development.

Abstract:Selection and decision-making involve a series of complex cognitive processes, and time-frequency analysis of electroencephalogram (EEG) signals can help understand brain activity in different cognitive tasks. In this study, a decision-making cognitive task related to the rock-paper-scissors game was designed. By setting the selection probability of the computer (rock 66%, scissors 33%, paper 1%), the subjects are able to make safe or risky decisions. The complete and complex decision task was divided into three stages (planning stage, confirmation stage and feedback stage). During the entire experiment, the NeuroscanQuikCap EEG measurement system recorded data with 64 EEG signal channels in real time. By extracting the characteristics of the change of the average spectral power and the phase synchronization value of each EEG frequency band (δ, θ, α, and β), a comparative analysis of the EEG waves at different task stages was realized. The results show that in the planning stage, the subject’s decision-making activities that want to win or do not want to lose are related to the enhanced activity effects of the parietal lobe α wave and the forehead θ wave. The order in which the brain waves appear may indicate that the subjects will make different types of decision plans. In the confirmation stage, the α wave spectrum power suppression effect and the δ wave phase synchronization enhancement activity show that the subject will increase attention after confirming the choice. In the feedback stage, the θ and β wave power spectrum increase effect and the α wave power spectrum decrease effect are related to different feed back results. And the effects are most obvious in the feedback that the subject finds the game lost. This preliminary study shows that, combined with a complete cognitive task, time-frequency analysis of EEG signals may be an important tool for visualizing brain activity in response to different cognitive functions. It also contributes to the further development for objective cognitive assessment solutions.

Abstract:With the improvement of people’s material lives and changes in lifestyles, the prevalence of chronic diseases such as hypertension has shown a rapidly growing trend. Numerous animal and human fasting trials have reported that fasting has been emerging as an effective tool to control weight and lower blood pressure, having a profound health benefit. In a fasting trial involving 149 participants in China, the subjects’ body weight, BMI (body mass index) and waist circumference all significantly decreased from baseline after 5 consecutive days of fasting intervention (P＜0.001). The magnitude of systolic and diastolic blood pressure (BP) reduction in subjects with hypertension was －11.2 mmHg (－14.9 to －7.5 mmHg, 95% CI (confidence intervals), P＜0.001) and －7.2 mmHg (－9.7 to －4.7, 95% CI, P＜0.001) after 5-day fasting intervention, respectively. No significant reduction occurred in systolic and diastolic BP of participants with normal BP. Then we implemented a further assessment of antihypertensive effects during the period of fasting trial by developing an easy-to-use nomogram based on proportional hazards regression, and the nomogram in our study achieved a bootstrap-corrected concordance index (C-index) of 0.891.

Abstract:The ability of animals to respond to different life-threatening stimuli and take the most adaptive defensive behavior is essential for survival and breeding. Studies have found that a gradually expanding black disk in the upper field which simulates the looming of natural predators approaching from above can induce different instinct defensive behaviors of mice, including freezing or flight. In conventional animal behavior studies, time and labor-consuming manual operations are used to generate the stimuli, limiting the efficiency of animal behavior studies. In this paper, we have developed a closed-loop animal behavior regulation and analysis system. Based on this system, we have studied the defensive behavior of mice facing different stimuli. Looming with low gray value or low-frequency light stimulation would induce the freezing behavior of mice, which tend to escape to a safe area under looming with high gray value or high-frequency light stimulation. This study has demonstrated an automatic behavior regulation system capable of delivering random stimuli, which can further improve the efficiency and accuracy of the experiment.

Abstract:The high thermal conductivity of graphene makes it an important filler material for thermally conductive composite materials. However, the interfacial thermal resistance between the fillers greatly hinders the heat transfer between the fillers. The functionalization of the edges of graphene can introduce covalent or hydrogen bonding between the graphene edge interfaces to replace Van Der Waals (VDWs) interaction connections, which is expected to enhance the interfacial thermal conductance. In this paper, the interfacial heat transfer properties of the graphene chemically functionalized with —COOH groups are systematically studied, and the effects of the distance between graphene sheets and the functionalized density on the interface thermal resistance are discussed. The results show that, as the distance between the edges of the two graphene sheets decreases, the interfacial thermal conduction between the interfaces of the functionalized graphene gradually converges to around 5×108 W/ (m2 ·K), which is an order of magnitude higher than that between the H-terminated graphene. The interfacial thermal conduction shows a non-linear monotonous increase with increasing the functionalization density. Further results show that there is a synergistic effect between the functionalized density and the graphene edge interface spacing. Increasing the functionalized density improves the interaction between the interfaces and reduces the interface spacing between the graphene edges, thereby enhancing the interfacial thermal conduction. The results of this paper provide an important reference for the study of effects of hydrogen bonding on the interfacial heat transfer between graphene fillers.

Abstract:There is a risk of geological disaster in the large-scale exploitation of submarine hydrate, so it is necessary to monitor the exploitation process. Time-lapse seismic can be used to retrieve the seismic reflection characteristics of reservoir sediments caused by hydrate decomposition. Based on the high-resolution multichannel seismic technology, a two-dimensional time-lapse seismic system is proposed in this paper. The structure design, flow design and key parameters design of the system and its main components are given, and the design process and relevant basis are discussed in detail. The system is mainly composed of deep water sparker, deep water multi-element receiving cable, multi-channel data acquisition system, battery pack and its management system. At the same time, it also includes deep water motor, deep water slip ring and automatic cable arranging device. The maximum excitation energy of the sparker is 1 000 J, and the receiving cable is composed of 16 deep-water hydrophones with pressure resistance of 20 MPa. The gap distance between the hydrophones is 1 m. The received seismic wavelet is processed by the 16 channel acquisition system and stored in situ. The system is powered by lithium battery and adopts the periodic wake-up mode. It is designed to work underwater for 2 months and conduct data acquisition once an hour. The maximum working depth of the system is 1 500 m, the maximum stratum penetration depth is 250 m and the maximum resolution is 0.5 m. The insitu excitation and acquisition of seabed can perfectly achieve the spatial consistency of acquisition data, and ensure that the time-lapse seismic data can reflect the seismic reflection characteristics of reservoir sediments in the process of hydrate mining.

Abstract:Person re-identification suffers from some problems such as confusion with excessive background, incomplete targets, and different viewing point etc. There are two basic observations for most person re-identification applications, i.e., strong correlation exists between the discriminative features, and weak correlation exist between feature points of the pedestrian areas and the background areas. Based on such observations, a person re-identification method based on features correlation is proposed in this paper. The CIP (contextual information processing) module based on viewpoint invariance and soft-detection is applied to realize the proposed method. Since strong correlative features distribute at different granularities, the multi-granularity based person re-identification methods can describe relationship between granularities by embedding the CIP module. The experiments are implemented on four large-scale person re-identification data sets. Both single-domain and cross-domain tests are used in the experiments. The Rank-1 and mean average error criterion are used as the evaluation indicators. As the experiment shows, the proposed method enhances the identification performance of several mainstream multi-granularity methods by CIP module.