Human embryonic stem cell-derived mesenchymal stromal cells suppress inflammation in mouse models of rheumatoid arthritis and lung fibrosis by regulating T-cell function.

BACKGROUND AIMS: Rheumatoid arthritis (RA) is characterized by an overactive immune system, with limited treatment options beyond immunosuppressive drugs or biological response modifiers. Human embryonic stem cell-derived mesenchymal stromal cells (hESC-MSCs) represent a novel alternative, possessing diverse immunomodulatory effects. In this study, we aimed to elucidate the therapeutic effects and underlying mechanisms of hESC-MSCs in treating RA. METHODS: MSC-like cells were differentiated from hESC (hESC-MSCs) and cultured in vitro. Cell proliferation was assessed using Cell Counting Kit-8 assay and Ki-67 staining. Flow cytometry was used to analyze cell surface markers, T-cell proliferation and immune cell infiltration. The collagen-induced arthritis (CIA) mouse model and bleomycin-induced model of lung fibrosis (BLE) were established and treated with hESC-MSCs intravenously for in vivo assessment. Pathological analyses, reverse transcription-quantitative polymerase chain reaction and Western blotting were conducted to evaluate the efficacy of hESC-MSCs treatment. RESULTS: Intravenous transplantation of hESC-MSCs effectively reduced inflammation in CIA mice in this study. Furthermore, hESC-MSC administration enhanced regulatory T cell infiltration and activation. Additional findings suggest that hESC-MSCs may reduce lung fibrosis in BLE mouse models, indicating their potential to mitigate complications associated with RA progression. In vitro experiments revealed a significant inhibition of T-cell activation and proliferation during co-culture with hESC-MSCs. In addition, hESC-MSCs demonstrated enhanced proliferative capacity compared with traditional primary MSCs. CONCLUSIONS: Transplantation of hESC-MSCs represents a promising therapeutic strategy for RA, potentially regulating T-cell proliferation and differentiation.

Phosphene object perception employs holistic processing during early visual processing stage.

Psychophysical studies have verified the possibility of recovering the visual ability by the form of low-resolution format of images, that is, phosphene-based representations. Our previous study has found that early visual processing for phosphene patterns is configuration based. This study further investigated the configural processing mechanisms of prosthetic vision by analyzing the event-related potential components (P1 and N170) in response to phosphene face and non-face stimuli. The results reveal that the coarse processing of phosphenes involves phosphene-specific holistic processing that recovers separated phosphenes into a gestalt; low-level feature processing of phosphenes is also enhanced compared with that of normal stimuli due to increased contrast borders introduced by phosphenes; while fine processing of phosphene stimuli is impaired reflected by reduced N170 amplitude because of the degraded detailed features in the low-resolution format representations. Therefore, we suggest that strategies that can facilitate the specific holistic processing stages of prosthetic vision should be considered in order to improve the performance when designing the visual prosthesis system.

Multilevel Spatial-Temporal Excited Graph Network for Skeleton-based Action Recognition.

The ability to capture joint connections in complicated motion is essential for skeleton-based action recognition. However, earlier approaches may not be able to fully explore this connection in either the spatial or temporal dimension due to fixed or single-level topological structures and insufficient temporal modeling. In this paper, we propose a novel multilevel spatial-temporal excited graph network (ML-STGNet) to address the above problems. In the spatial configuration, we decouple the learning of the human skeleton into general and individual graphs by designing a multilevel graph convolution (ML-GCN) network and a spatial data-driven excitation (SDE) module, respectively. ML-GCN leverages joint-level, part-level, and body-level graphs to comprehensively model the hierarchical relations of a human body. Based on this, SDE is further introduced to handle the diverse joint relations of different samples in a data-dependent way. This decoupling approach not only increases the flexibility of the model for graph construction but also enables the generality to adapt to various data samples. In the temporal configuration, we apply the concept of temporal difference to the human skeleton and design an efficient temporal motion excitation (TME) module to highlight the motion-sensitive features. Furthermore, a simplified multiscale temporal convolution (MS-TCN) network is introduced to enrich the expression ability of temporal features. Extensive experiments on the four popular datasets NTU-RGB+D, NTU-RGB+D 120, Kinetics Skeleton 400, and Toyota Smarthome demonstrate that ML-STGNet gains considerable improvements over the existing state of the art.

Configuration-based processing of phosphene pattern recognition for simulated prosthetic vision.

Visual prosthesis can elicit phosphenes by stimulating the retina, optic nerve, or visual cortex along the visual pathway. Psychophysical studies have demonstrated that visual function can be partly recovered with phosphene-based prosthetic vision. This study investigated the cognitive process of prosthetic vision through a face recognition task. Both behavioral response and the face-specific N170 component of event-related potential were analyzed in the presence of face and non-face stimuli with natural and simulated prosthetic vision. Our results showed that: (i) the accuracy of phosphene face recognition was comparable with that of the normal one when phosphene grid increased to 25 x 21 or more; (ii) shorter response time was needed for phosphene face recognition; and (iii) the N170 component was delayed and enhanced under phosphene stimuli. It was suggested that recognition of phosphene patterns employ a configuration-based holistic processing mechanism with a distinct substage unspecific to faces.

Object recognition under distorted prosthetic vision.

Psychophysical studies have reported the efficacy of phosphene-based prosthetic vision in partly recovering the visual function of blind individuals. However, results by far have been based on evenly aligned phosphene arrays, which neglected the complicated visuotopy in the visual prosthesis system. In this study, we investigated how the objects were recognized under the stimuli with distorted phosphene arrays simulated by transformations of barrel distortion, rotation, or translation. The results revealed that distortions significantly decreased the accuracy of categorization (CA) and showed distinct interactive effects with the factors of object category and phosphene array density. Moreover, the CA changed differently with the increase of distortion levels. Regression analysis suggested a phosphene array of at least 10 × 10 be the essential for achieving a CA over the threshold value (CA(t)=62.5%) under distorted prosthetic vision. It is recommended that discriminative features be extracted to improve the performance of prosthetic vision.

[Auditory guidance systems for the visually impaired people].

Visually impaired people face many inconveniences because of the loss of vision. Therefore, scientists are trying to design various guidance systems for improving the lives of the blind. Based on sensory substitution, auditory guidance has become an interesting topic in the field of biomedical engineering. In this paper, we made a state-of-technique review of the auditory guidance system. Although there have been many technical challenges, the auditory guidance system would be a useful alternative for the visually impaired people.

A splicing model-based DNA-computing approach on microfluidic chip.

DNA computing is a new computation form based on DNA biochemical reactions, which is mainly composed of sticker and splicing computation models. In this work, a microfluidic chip-based approach was established for splicing model-based DNA computing. A finite automaton with two input symbols (a, b) and three states (S0, S1, and S2) was applied in the pattern recognition for isosceles triangles. The DNA computation processes of automaton were realized through DNA digestion, ligation, DNA separation, and detection on the microfluidic chip. The established approach is efficient, controllable, and easy to integrate, which paves the way for the building of complete biomolecular computers in the future.

[Entropy analysis of the EEG alpha activity in depression patients].

The alpha rhythm in electroencephalograph has been associated with the mental state of the brain. The aim of the present study was to analyze the complexity of the alpha activity in depression patients by Renyi entropy (RE) under two conditions, i.e., resting with eyes closed followed by a simple mental arithmetic. The EEGs were recorded in 20 depression patients and 20 age-matched control subjects. Results showed that the alpha activity of depression patients is more complex during resting and is more regular during the mental arithmetic than that of the controls. RE analysis can well characterize the alpha activity in depression patients and could be a valuable tool to study cognitive process and also a potential effective approach for the diagnosis of depression.

[Spatio-temporal distribution of chromatic VEPs].

The VEPs evoked by different colors are differently distributed on human cerebral cortex. This study sought to shed light on the spatio-temporal distribution of chromatic VEPs and compare the distribution characteristics of chromatic VEPs evoked by different colors in different cerebral cortex regions. The subjects were asked to stare at the red, green, black gradient bars against a white background. The results show that the latency periods and the amplitudes of P1 and N1 peaks from different chromatic VEPs exhibit significant differences (P<0.001). The speed and intensity of cognitive task of red are higher than those of green. The latency periods and the amplitudes of P1 and N1 peaks from different cerebral cortex regions also display remarkable differences (P<0.001). The intensity of reaction in the temporal and occipital regions is stronger than that in other regions, and the latency periods in frontal area and central area are shorter than those in temporal and occipital regions.

[Gender difference in face recognition].

The method of event-related potentials (ERP) was used to study the gender difference in face recognition. The stimuli in the experiment were 10 upright and 10 inverted face photos. The subjects, half female and half male, were asked to judge whether the face was upright or inverted. The results showed that the N170 wave forms were observed in the occipito-temporal regions and they were found exhibiting brain's right hemispheric dominance. The stimuli of different gender photos were noticed to have no significant impact on the N170 wave forms, but there were significant differentce in the amplitude and latency period of N170 between different gender participants. Moreover, there was marked difference in the latency period of the male participants watching the same gender face and different gender face. Similar results were not found in the ERP's latency period of female participants.

Microfluidic device for integrated restriction digestion reaction and resulting DNA fragment analysis.

A microfluidic system combining temperature-controlled reactor, analyte delivery, chip electrophoresis (CE) separation, and fluorescence detection was developed, in which the heaters, resistance temperature detectors, enzymatic reactors, CE channels, and pneumatic valves/pumps were integrated onto a single glass-PDMS chip. The microdevice was used to perform the digestion reaction, followed by on-line electrophoresis separation and detection of the resulting fragments with endonuclease BamHI and FokI as models. Pneumatic valves/pumps served not only for isolating the reaction region from the separation medium to prevent contamination, but also for delivering and quantitatively diluting the fluid from the reaction chamber to the CE section. Thus enzymatic reaction and electrophoresis separation could be insulated and connected as needed. A dynamic coating procedure with the use of PVP and mannitol was firstly adopted for glass-PDMS hybrid chip-based DNA separations, leading to an improved separation efficiency with reproducible migration time and theoretical plates. The expected 263- and 287-bp digestion products of BamHI and FokI were definitely verified by the size-based electrophoretic separation and detection. The whole integrated reaction-CE system can be manipulated in a simple manner with good reproducibility, which is expected to be applied in other on-line analysis of various biochemical reactions.

Abnormal EEG complexity in patients with schizophrenia and depression.

OBJECTIVE: Schizophrenics are usually unable to perform well on cognitive tasks due to disturbances in cortical information processing that are observable as abnormalities in electroencephalogram (EEG) signals. However, whether such cortical disturbances can be assessed by quantitative EEG analysis remains unclear. The purpose of this study was to characterize EEG disturbances, using the Lempel-Ziv complexity (LZC), in the subjects with schizophrenia at rest or while performing mental arithmetic tasks. The results were compared to those from the subjects with depression and with healthy controls. METHODS: The subjects included 62 schizophrenia patients, 48 depression patients and 26 age-matched healthy controls. EEG was recorded under two conditions: (i) resting with eyes closed, and (ii) a mentally active condition wherein the subjects were asked to subtract 7 from 100 iteratively with their eyes closed. EEG signals were analyzed by LZC and conventional spectral methods. RESULTS: In all the groups, LZC of EEG decreased during the mental arithmetic compared with those under the resting conditions. Both the schizophrenia and the depression groups had a higher LZC (p<0.05) than the controls. Also, the schizophrenia group had a lower LZC (p<0.05) than the depression group during the mental arithmetic task as well as during the resting state. Significant differences in LZC, at some symmetrically located loci (FP1/FP2, F7/F8), between the two hemispheres were found in all the patient groups only during the arithmetic task. CONCLUSIONS: Compared with conventional spectral analysis, LZC was more sensitive to both the power spectrum and the temporal amplitude distribution. LZC was associated with the ability to attend to the task and adapt the information processing system to the cognitive challenge. Thus, it would be useful in studying the disturbances in the cortical information processing patients with depression or schizophrenia. SIGNIFICANCE: LZC of EEG is associated with mental activity. Thus, LZC analysis can be an important tool in understanding the pathophysiology of schizophrenia and depression in future studies.

Attention rivalry under irrelevant audiovisual stimulation.

Audiovisual integration has been known to enhance perception; nevertheless, another fundamental audiovisual interaction, i.e. attention rivalry, has not been well investigated. This paper studied the attention rivalry under irrelevant audiovisual stimulation using event-related potential (ERP) and behavioral analysis, and tested the existence of a vision dominated rivalry model. Participants need respond to the target in a bi- or unimodal audiovisual stimulation paradigm. The enhanced amplitude of central P300 under visual target bimodal stimulus indicated that vision demanded more cognitive resources, and the significant amplitude of frontal P200 under bimodal stimulus with non-target auditory stimulus implied that the brain mostly restrained the process of the non-target auditory information. ERP results, together with the analysis of the behavioral data and the subtraction waves, indicated a vision dominated attention rivalry model involved in audiovisual interaction. Furthermore, the latencies of P200 and P300 components implied that audiovisual attention rivalry occurred within the first 300ms after stimulus onset, i.e. significant differences were found in P200 latencies among three target bimodal stimuli, while no difference existed in P300 latencies. Attention shifting and re-directing might be the cause of such early audiovisual rivalry.

[Recurrence plot analysis of HRV for brain ischemia and asphyxia].

Heart rate variability (HRV) is the tiny variability existing in the cycles of the heart beats, which reflects the corresponding balance between sympathetic and vagus nerves. Since the nonlinear characteristic of HRV is confirmed, the Recurrence Plot method, a nonlinear dynamic analysis method based on the complexity, could be used to analyze HRV. The results showed the recurrence plot structures and some quantitative indices (L-Mean, L-Entr) during asphyxia insult vary significantly as compared to those in normal conditions, which offer a new method to monitor brain asphyxia injury.

[Review of visual prosthesis (I)--retinal prosthesis].

Research on how to totally or partially restore the vision has attracted more attention in the fields of neural engineering and tissue engineering. Neural interface and visual prosthesis offer alternative ways for partially repairing the visual impairment. The most widely used visual prosthetics are based on retinal stimulation. This article is a state-of-art review of the principles, technical details and the limitations of retinal prosthesis.

[Review of visual prosthesis (II)--cortical visual prosthesis, optic nerve prosthesis and vision substitution devices].

Cortical visual prosthesis, optic nerve visual prosthesis and vision substitution devices are alternative ways for repairing the visual impairment in case of optic nerve injury, retina lose or blindness without fully developed central visual system. This article is a state-of-art review of the principles, technical details and the limitations of different types of prostheses beyond the retinal prosthesis.

[Review of researches on retinal model].

Retinal model is an essential part in the retinal prosthesis. Based on the retinal physiology and the experimental data, the model is able to simulate the information processing in the retina, and can be used to investigate the relation between the input image and the neuron firing. We can categorize the models into circuit realization and algorithm realization. This article is a state-of-art review of different types of retinal models.

[Removal of artifacts from EEG signal].

As a kind of physiological signals, the electroencephalogram (EEG) represents the electrical activity of the brain. Because of its higher time-varying sensitivity, EEG is susceptible to many artifacts, such as eye-movements, blinks, cardiac signals, muscle noise. These noises in recording EEG pose a major embarrassment for EEG interpretation and disposal. A number of methods have been proposed to overcome this problem, ranging from the rejection of various artifacts to the effect estimate of removing artifacts. This paper reviews many kinds of methods for artifact rejection in the EEC recently, including regression-based methods, artifact subtraction, principal component analysis (PCA), independent component analysis (ICA) and wavelet transform. The specific assumptions of each method and its advantage/disadvantage are also summarized.

Describing the nonstationarity level of neurological signals based on quantifications of time-frequency representation.

Most neurological signals including electroencephalogram (EEG), evoked potential (EP) and local field potential (LFP) have been known to be time varying and nonstationary, especially in some pathological conditions. Currently, the most widely used quantitative tool for such nonstationary signals is time-frequency representation (TFR) which demonstrates the temporal evolution of different frequency components. However, TFR does not directly provide a quantitative measure of nonstationarity level, e.g., how far the process deviates from stationarity. In this study, we introduced three different quantifications of TFR (qTFR) to characterize the nonstationarity level of the involving signals: (1) degree of stationarity (DS); (2) Shannon entropy (SE) of the marginal spectrum; and (3) Kullback-Leibler distance (KLD) between a TFR and a uniform distribution. These descriptors provide quantitative analysis of stationarity of a signal such that the stationarity of different signals could be compared. In this study, we obtained the TFRs of the EEG signals before and after the hypoxic-ischemic (HI) brain injury and examined the stationarity of the EEG. DS, SE, and KLD can indicate the nonstationarity change of EEG at each frequency following the HI injury, especially in the upper delta-and lower theta-band (e.g., [2 Hz, 8 Hz]) as well as in the beta2 band (e.g., [22 Hz-26 Hz]). Moreover, it is shown that the stationarity of the EEG changes differently in different frequencies following the HI injury.

Molecular dynamics simulations of dipolar fluids in orientationally ordered phases.

It has been established that the strongly interacting dipoles form orientationally ordered liquid phases. However, most of the computer simulations adapt the point dipole model. In this paper, we report molecular dynamics simulations of orientationally order phases formed by extended dipoles, where the potential energy consists of the site-site Lennard-Jones potential and electrostatic contribution of partial charges. The calculations were performed for a range of densities along an isotherm and for different temperatures at the same reduced densities. It is found that orientationally ordered phases are present in the wide density regime, the extended dipole tends to form chains at low density, and the isotropic liquid phase is not seen in the density regime studied for a specific temperature.