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Working memory load (WML) is one of the widely applied signals in the areas of human-machine interaction. The precise evaluation of the WML is crucial for this kind of application. This study aims to propose a deep learning (DL) time series classification (TSC) model for inter-subject WML decoding. We used fNIRS to record the hemodynamic signals of 27 participants during visual working memory tasks. Traditional machine learning and deep time series classification algorithms were respectively used for intra-subject and inter-subject WML decoding from the collected blood oxygen signals. The intra-subject classification accuracy of LDA and SVM were 94.6% and 79.1%. Our proposed TAResnet-BiLSTM model had the highest inter-subject WML decoding accuracy, reaching 92.4%. This study provides a new idea and method for the brain-computer interface application of fNIRS in real-time WML detection.
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Virtual reality (VR) technology has been demonstrated to be effective in rehabilitation training with the assistance of VR games, but its impact on brain functional networks remains unclear. In this study, we used functional near-infrared spectroscopy imaging to examine the brain hemodynamic signals from 18 healthy participants during rest and grasping tasks with and without VR game intervention. We calculated and compared the graph theory-based topological properties of the brain networks using phase locking values (PLV). The results revealed significant differences in the brain network properties when VR games were introduced compared to the resting state. Specifically, for the VR-guided grasping task, the modularity of the brain network was significantly higher than the resting state, and the average clustering coefficient of the motor cortex was significantly lower compared to that of the resting state and the simple grasping task. Correlation analyses showed that a higher clustering coefficient, local efficiency, and modularity were associated with better game performance during VR game participation. This study demonstrates that a VR game task intervention can better modulate the brain functional network compared to simple grasping movements and may be more beneficial for the recovery of grasping abilities in post-stroke patients with hand paralysis.
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INTRODUCTION: Depression is a common mental disorder that endangers physical and mental health. In our study, we aimed to explore whether B vitamins are associated with depression and cognitive dysfunction. METHODS: We enrolled a total of 220 patients with depression and selected 100 controls at the same time. We determined depression and cognitive impairment by assessments. We recorded the basic parameters of the participants and collected blood samples. In addition, we measured serum levels of B vitamins and brain-derived neurotrophic factor (BDNF). RESULTS: We found significant differences in the duration of depression, education, and Hamilton Depression Rating Scale scores between the D-NCI and D-CI groups. We also identified the independent risk factors for patients with depression and cognitive dysfunction. Compared with the healthy controls, serum folate, vitamin B6, and vitamin B12 positively correlated with cognitive dysfunction. The patients with depression and cognitive dysfunction had the lowest levels of B vitamins compared with the other two groups. Our results also showed that the levels of serum folate, vitamin B6, and vitamin B12 in the patients with depression had a positive correlation with each other. CONCLUSION: Our results indicate that vitamin B is associated with depression and cognitive dysfunction and is positively associated with cognitive dysfunction.
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Disfunção Cognitiva , Complexo Vitamínico B , Humanos , Ácido Fólico , Vitamina B 12 , Vitamina B 6 , Depressão , HomocisteínaRESUMO
The manual design of esophageal cancer radiotherapy plan is time-consuming and labor-intensive. Automatic planning (AP) is prevalent nowadays to increase physicists' work efficiency. Because of the intuitiveness of dose distribution in AP evaluation, obtaining reasonable dose prediction provides effective guarantees to generate a satisfactory AP. Existing fully convolutional network-based methods for predicting dose distribution in esophageal cancer radiotherapy plans often capture features in a limited receptive field. Additionally, the correlations between voxel pairs are often ignored. This work modifies the U-net architecture and exploits graph convolution to capture long-range information for dose prediction in esophageal cancer plans. Meanwhile, attention mechanism gets correlations between planning target volume (PTV) and organs at risk, and adaptively learns their feature weights. Finally, a novel loss function that considers features between voxel pairs is used to highlight the predictions. 152 subjects with prescription doses of 50 Gy or 60 Gy are collected in this study. The mean absolute error and standard deviation of conformity index, homogeneity index, and max dose for PTV achieved by the proposed method are 0.036 ± 0.030, 0.036 ± 0.027, and 0.930 ± 1.162, respectively, which outperform other state-of-the-art models. The superior performance demonstrates that our proposed method has great potential for AP generation.
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Neoplasias Esofágicas , Radioterapia de Intensidade Modulada , Humanos , Dosagem Radioterapêutica , Radioterapia de Intensidade Modulada/métodos , Planejamento da Radioterapia Assistida por Computador/métodos , Órgãos em Risco , Neoplasias Esofágicas/diagnóstico por imagem , Neoplasias Esofágicas/radioterapiaRESUMO
The Qaidam Basin is a prominent oil and gas exploration and production base of NW China's Jurassic coal-bearing strata. Coal-bearing mudstones are important source rocks for unconventional reservoirs and can record valuable paleoenvironment and paleoclimate information. Here, geochemical analysis including total organic carbon (TOC), total sulfur, organic carbon isotopic composition, rock pyrolysis, X-ray diffraction, and major and trace elements were carried out on mudstone samples from the Middle Jurassic coal-bearing strata of the Dameigou section in the Qaidam Basin to reveal the paleoclimatic and paleoenvironmental conditions during the deposition of the strata and their controls on organic matter accumulation. Results show that the Middle Jurassic Dameigou and Shimengou formations include three significant stages based on their average TOC values of (3.32%, Stage I; 0.87%, Stage II; and 4.42%, Stage III) from the bottom to the top. The organic matter in mudstones in Stages I and II are mainly derived from terrestrial higher plants, while the organic matter has mixed sources of higher plant debris and lower aquatic organisms in Stage III. Paleoclimate parameters indicate that the mudstones in Stage I were deposited under humid and warm conditions, while the climate in Stage II changed to semiarid and warm conditions before turning dry and hot in Stage III. The varying paleoenvironmental characteristics under different paleoclimatic conditions have also been reconstructed. Our results suggest that the accumulation of organic matter in Stages I and II was primarily controlled by redox conditions, while paleoproductivity is the major controlling factor for organic matter accumulation in Stage III.
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Depression is a common mental disorder that seriously affects patients' social function and daily life. Its accurate diagnosis remains a big challenge in depression treatment. In this study, we used electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) and measured the whole brain EEG signals and forehead hemodynamic signals from 25 depression patients and 30 healthy subjects during the resting state. On one hand, we explored the EEG brain functional network properties, and found that the clustering coefficient and local efficiency of the delta and theta bands in patients were significantly higher than those in normal subjects. On the other hand, we extracted brain network properties, asymmetry, and brain oxygen entropy as alternative features, used a data-driven automated method to select features, and established a support vector machine model for automatic depression classification. The results showed the classification accuracy was 81.8% when using EEG features alone and increased to 92.7% when using hybrid EEG and fNIRS features. The brain network local efficiency in the delta band, hemispheric asymmetry in the theta band and brain oxygen sample entropy features differed significantly between the two groups (p < 0.05) and showed high depression distinguishing ability indicating that they may be effective biological markers for identifying depression. EEG, fNIRS and machine learning constitute an effective method for classifying depression at the individual level.
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This study aims to develop an automatic assessment of after-stroke dyskinesias degree by combining machine learning and near-infrared spectroscopy (NIRS). Thirty-five subjects were divided into five stages (healthy, patient: Brunnstrom stages 3, 4, 5, 6). NIRS was used to record the muscular hemodynamic responses from bilateral femoris (biceps brachii) muscles during passive and active upper (lower) limbs circular exercise. We used the D-S evidence theory to conduct feature information fusion and established a Gradient Boosting DD-MLP Net model, combining the dendrite network and multilayer perceptron, to realize automatic dyskinesias degree evaluation. Our model classified the upper limb dyskinesias with high accuracy: 98.91% under the passive mode and 98.69% under the active mode, and classified the lower limb dyskinesias with high accuracy: 99.45% and 99.63% under the passive and active modes, respectively. Our model combined with NIRS has great potential in monitoring the after-stroke dyskinesias degree and guiding rehabilitation training.
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Discinesias , Acidente Vascular Cerebral , Humanos , Espectroscopia de Luz Próxima ao Infravermelho/métodos , Acidente Vascular Cerebral/complicações , Acidente Vascular Cerebral/diagnóstico por imagem , Músculo Esquelético , Aprendizado de Máquina , Discinesias/etiologiaRESUMO
Significance: Motor function evaluation is essential for poststroke dyskinesia rehabilitation. Neuroimaging techniques combined with machine learning help decode a patient's functional status. However, more research is needed to investigate how individual brain function information predicts the dyskinesia degree of stroke patients. Aim: We investigated stroke patients' motor network reorganization and proposed a machine learning-based method to predict the patients' motor dysfunction. Approach: Near-infrared spectroscopy (NIRS) was used to measure hemodynamic signals of the motor cortex in the resting state (RS) from 11 healthy subjects and 31 stroke patients, 15 with mild dyskinesia (Mild), and 16 with moderate-to-severe dyskinesia (MtS). The graph theory was used to analyze the motor network characteristics. Results: The small-world properties of the motor network were significantly different between groups: (1) clustering coefficient, local efficiency, and transitivity: MtS > Mild > Healthy and (2) global efficiency: MtS < Mild < Healthy. These four properties linearly correlated with patients' Fugl-Meyer Assessment scores. Using the small-world properties as features, we constructed support vector machine (SVM) models that classified the three groups of subjects with an accuracy of 85.7%. Conclusions: Our results show that NIRS, RS functional connectivity, and SVM together constitute an effective method for assessing the poststroke dyskinesia degree at the individual level.
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The presence of human cytomegalovirus (HCMV) in glioblastoma (GBM) and improved outcomes of GBM patients receiving therapies targeting the virus have implicated HCMV in GBM progression. However, a unifying mechanism that accounts for the contribution of HCMV to the malignant phenotype of GBM remains incompletely defined. Here we have identified SOX2, a marker of glioma stem cells (GSCs), as a key determinant of HCMV gene expression in gliomas. Our studies demonstrated that SOX2 downregulated promyelocytic leukemia (PML) and Sp100 and consequently facilitated viral gene expression by decreasing the amount of PML nuclear bodies in HCMV-infected glioma cells. Conversely, the expression of PML antagonized the effects of SOX2 on HCMV gene expression. Furthermore, this regulation of SOX2 on HCMV infection was demonstrated in a neurosphere assay of GSCs and in a murine xenograft model utilizing xenografts from patient-derived glioma tissue. In both cases, SOX2 overexpression facilitated the growth of neurospheres and xenografts implanted in immunodeficient mice. Lastly, the expression of SOX2 and HCMV immediate early 1 (IE1) protein could be correlated in tissues from glioma patients, and interestingly, elevated levels of SOX2 and IE1 were predictive of a worse clinical outcome. These studies argue that HCMV gene expression in gliomas is regulated by SOX2 through its regulation of PML expression and that targeting molecules in this SOX2-PML pathway could identify therapies for glioma treatment.
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Glioma , Proteínas Imediatamente Precoces , Animais , Humanos , Camundongos , Citomegalovirus/fisiologia , Regulação para Baixo , Expressão Gênica , Glioma/genética , Glioma/patologia , Proteínas Imediatamente Precoces/metabolismo , Fatores de Transcrição SOXB1/genética , Fatores de Transcrição SOXB1/metabolismo , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismoRESUMO
Human cytomegalovirus (HCMV) is a leading cause of congenital birth defects. Though the underlying mechanisms remain poorly characterized, mouse models of congenital CMV infection have demonstrated that the neuronal migration process is damaged. In this study, we evaluated the effects of HCMV infection on connexin 43 (Cx43), a crucial adhesion molecule mediating neuronal migration. We show in multiple cellular models that HCMV infection downregulated Cx43 posttranslationally. Further analysis identified the immediate early protein IE1 as the viral protein responsible for the reduction of Cx43. IE1 was found to bind the Cx43 C terminus and promote Cx43 degradation through the ubiquitin-proteasome pathway. Deletion of the Cx43-binding site in IE1 rendered it incapable of inducing Cx43 degradation. We validated the IE1-induced loss of Cx43 in vivo by introducing IE1 into the fetal mouse brain. Noteworthily, ectopic IE1 expression induced cortical atrophy and neuronal migration defects. Several lines of evidence suggest that these damages result from decreased Cx43, and restoration of Cx43 levels partially rescued IE1-induced interruption of neuronal migration. Taken together, the results of our investigation reveal a novel mechanism of HCMV-induced neural maldevelopment and identify a potential intervention target. IMPORTANCE Congenital CMV (cCMV) infection causes neurological sequelae in newborns. Recent studies of cCMV pathogenesis in animal models reveal ventriculomegaly and cortical atrophy associated with impaired neural progenitor cell (NPC) proliferation and migration. In this study, we investigated the mechanisms underlying these NPC abnormalities. We show that Cx43, a critical adhesion molecule mediating NPC migration, is downregulated by HCMV infection in vitro and HCMV-IE1 in vivo. We provide evidence that IE1 interacts with the C terminus of Cx43 to promote its ubiquitination and consequent degradation through the proteasome. Moreover, we demonstrate that introducing IE1 into mouse fetal brains led to neuronal migration defects, which was associated with Cx43 reduction. Deletion of the Cx43-binding region in IE1 or ectopic expression of Cx43 rescued the IE1-induced migration defects in vivo. Our study provides insight into how cCMV infection impairs neuronal migration and reveals a target for therapeutic interventions.
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Conexina 43 , Infecções por Citomegalovirus , Citomegalovirus , Proteínas Imediatamente Precoces , Animais , Humanos , Recém-Nascido , Camundongos , Conexina 43/genética , Conexina 43/metabolismo , Citomegalovirus/fisiologia , Infecções por Citomegalovirus/metabolismo , Proteínas Imediatamente Precoces/genética , Proteínas Imediatamente Precoces/metabolismo , Complexo de Endopeptidases do Proteassoma/metabolismoRESUMO
Congenital human cytomegalovirus (HCMV) infection causes severe damage to the fetal brain, and the underlying mechanisms remain elusive. Cytokine signaling is delicately controlled in the fetal central nervous system to ensure proper development. Here we show that suppressor of cytokine signaling 3 (SOCS3), a negative feedback regulator of the IL-6 cytokine family signaling, was upregulated during HCMV infection in primary neural progenitor cells (NPCs) with a biphasic expression pattern. From viral protein screening, pUL97 emerged as the viral factor responsible for prolonged SOCS3 upregulation. Further, by proteomic analysis of the pUL97-interacting host proteins, regulatory factor X 7 (RFX7) was identified as the transcription factor responsible for the regulation. Depletion of either pUL97 or RFX7 prevented the HCMV-induced SOCS3 upregulation in NPCs. With a promoter-luciferase activity assay, we demonstrated that the pUL97 kinase activity and RFX7 were required for SOCS3 upregulation. Moreover, the RFX7 phosphorylation level was increased by either UL97-expressing or HCMV-infection in NPCs, suggesting that pUL97 induces RFX7 phosphorylation to drive SOCS3 transcription. We further revealed that elevated SOCS3 expression impaired NPC proliferation and migration in vitro and caused NPCs migration defects in vivo. Taken together, these findings uncover a novel regulatory mechanism of sustained SOCS3 expression in HCMV-infected NPCs, which perturbs IL-6 cytokine family signaling, leads to NPCs proliferation and migration defects, and consequently affects fetal brain development.
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Infecções por Citomegalovirus , Citomegalovirus , Humanos , Citomegalovirus/fisiologia , Interleucina-6/metabolismo , Proteômica , Fatores de Transcrição/metabolismo , Células-Tronco , Proteína 3 Supressora da Sinalização de Citocinas/metabolismoRESUMO
BACKGROUND: With the ageing of the world population, the incidence of stroke has been increasing annually, becoming a public health problem affecting adult health. Limb motor dysfunction is one of the common complications of stroke and an important factor in disability. Therefore, restoring limb function is an important task in current rehabilitation. Accurate assessment of motor function in stroke patients is the basis for formulating effective rehabilitation strategies. With the development of neuroimaging technology, scholars have begun to study objective evaluation methods for limb motor dysfunction in stroke to determine reliable neural biomarkers to accurately identify brain functional activity and its relationship with limb motor function. The prefrontal cortex (PFC) plays an important role in motor control and in response to motor state changes. Our previous study found that the PFC network characteristics of stroke patients are related to their motor function status and the topological properties of the PFC network under resting state can predict the motor function of stroke patients to some extent. Therefore, this study used functional near-infrared spectroscopy (fNIRS) to evaluate prefrontal neuroplasticity markers and the relationships between such neural markers and limb motor function in stroke patients with limb motor dysfunction, which could be helpful to further clarify the relationship between brain neuroplasticity and cerebral haemodynamics. At the same time, through accurate and objective means of evaluation, it could be helpful for clinicians to formulate and optimize individualized rehabilitation treatment plans and accurately determine the rehabilitation efficacy and prognosis. METHODS: This study recruited 17 S patients with limb motor dysfunction and 9 healthy subjects. fNIRS was used to collect 22 channels of cerebral blood oxygen signals in the PFC in the resting state. The differences in prefrontal oxygenated haemoglobin (HbO) and deoxygenated haemoglobin (HbR) concentrations were analysed between stroke patients and healthy subjects, and the lateralization index (LI) of HbO in stroke patients was also calculated. Pearson's correlation analysis was performed between the LI and the scores of the Fugl-Meyer Assessment Scale (FMA) of motor function in stroke patients. RESULTS: The results found that the prefrontal HbO concentration was significantly decreased in stroke patients with limb motor dysfunction compared with healthy subjects, and there was a significant, positive correlation between the LI of the PFC and FMA scores in stroke patients. CONCLUSION: These study results showed that stroke can cause cerebral haemodynamic changes in the PFC, and the functional imbalance of the left and right PFC in the resting state is correlated with the severity of limb motor dysfunction. Furthermore, we emphasize that the cerebral haemodynamic activity reflected by fNIRS could be used as a reliable neural biomarker for assessing limb motor dysfunction in stroke.
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Espectroscopia de Luz Próxima ao Infravermelho , Acidente Vascular Cerebral , Adulto , Humanos , Espectroscopia de Luz Próxima ao Infravermelho/métodos , Córtex Pré-Frontal , Extremidades , OxiemoglobinasRESUMO
The broodiness traits of domestic geese are a bottleneck that prevents the rapid development of the goose industry. To reduce the broodiness of the Zhedong goose and thus improve it, this study hybridized it with the Zi goose, which has almost no broody behavior. Genome resequencing was performed for the purebred Zhedong goose, as well as the F2 and F3 hybrids. The results showed that the F1 hybrids displayed significant heterosis in growth traits, and their body weight was significantly greater than those of the other groups. The F2 hybrids showed significant heterosis in egg-laying traits, and the number of eggs laid was significantly greater than those of the other groups. A total of 7,979,421 single-nucleotide polymorphisms (SNPs) were obtained, and three SNPs were screened. Molecular docking results showed that SNP11 located in the gene NUDT9 altered the structure and affinity of the binding pocket. The results suggested that SNP11 is an SNP related to goose broodiness. In the future, we will use the cage breeding method to sample the same half-sib families to accurately identify SNP markers of growth and reproductive traits.
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Gansos , Polimorfismo de Nucleotídeo Único , Animais , Gansos/genética , Simulação de Acoplamento Molecular , Reprodução , OviposiçãoRESUMO
Understanding the mechanisms of grassland productivity variation is critical for global carbon cycling and climate change mitigation. Heretofore, it is unknown how different environmental factors drive small-scale spatial variation in productivity, and whether land use intensification, one of the most important global changes, can regulate the processes that drive productivity change. Here we performed an 18-year exclosure experiment across six sites with high-intensity mowing/grazing history in northern China to examine the effects of land use intensification on plant functional diversity, soil properties, and their relative contributions to above-ground net primary productivity (ANPP). We found that plant functional diversity and soil properties contributed to the variation in ANPP both independently and equally in enclosed grasslands (plant diversity: 20.6%; soil properties: 19.5%). Intensive land use significantly decreased the Rao's quadratic entropy (RaoQ) and community-weighted mean value (CWM) of plant height, and further suppressed the contributions of plant functional diversity to ANPP. In contrast, intensive land use increased soil available N, P, pH, electrical conductivity, and homogeneity of soil available P, and strengthened their contributions to ANPP (31.5%). Our results indicate that high-intensity land use practices in grasslands decrease the role of plant functional diversity, but strengthen the effects of soil properties on productivity. We, therefore, suggest that plant functional diversity can be used effectively to boost productivity in undisturbed grasslands, while soil properties might be a more critical consideration for grassland management in an areas with increased land use.
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Pradaria , Solo , Solo/química , Plantas , China , Mudança ClimáticaRESUMO
Aging is usually accompanied by decrease in limb motor function and change in muscle metabolism patterns. However, few studies have investigated the aging effect on muscle hemodynamics of the upper extremity. This study aims to explore the aging effect on muscle metabolism patterns during upper limb's exercise. Twelve middle-aged and elderly subjects and 12 young subjects were recruited, and muscle oxygenation signals from these subjects' biceps brachii muscles were collected during active and passive upper limb's encircling exercise with near-infrared spectroscopy (NIRS). The old group showed stronger muscle hemodynamic metabolism than the young group. The multiscale fuzzy approximate entropy and multiscale transfer entropy analyses indicated higher complexity and stronger interlimb coupling of the muscle oxygenation signals for the old group. Based on the selected muscle metabolism features, the constructed support vector machine model showed a high accuracy rate for classifying the two groups of subjects: 91.6% for the passive mode and 87.5% for the active mode. Our results proved the specific muscle metabolism patterns in the upper limb's exercise for old subjects, promoting the understanding of the aging effect on muscle hemodynamics.
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During the long coevolution of human cytomegalovirus (HCMV) and humans, the host has formed a defense system of multiple layers to eradicate the invader, and the virus has developed various strategies to evade host surveillance programs. The intrinsic immunity primarily orchestrated by promyelocytic leukemia (PML) nuclear bodies (PML-NBs) represents the first line of defense against HCMV infection. Here, we demonstrate that microrchidia family CW-type zinc finger 3 (MORC3), a PML-NBs component, is a restriction factor targeting HCMV infection. We show that depletion of MORC3 through knockdown by RNA interference or knockout by CRISPR-Cas9 augmented immediate-early protein 1 (IE1) gene expression and subsequent viral replication, and overexpressing MORC3 inhibited HCMV replication by suppressing IE1 gene expression. To relief the restriction, HCMV induces transient reduction of MORC3 protein level via the ubiquitin-proteasome pathway during the immediate-early to early stage. However, MORC3 transcription is upregulated, and the protein level recovers in the late stages. Further analyses with temporal-controlled MORC3 expression and the major immediate-early promoter (MIEP)-based reporters show that MORC3 suppresses MIEP activity and consequent IE1 expression with the assistance of PML. Taken together, our data reveal that HCMV enforces temporary loss of MORC3 to evade its repression against the initiation of immediate-early gene expression.
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Infecções por Citomegalovirus , Proteínas Imediatamente Precoces , Adenosina Trifosfatases/metabolismo , Citomegalovirus/genética , Proteínas de Ligação a DNA/metabolismo , Humanos , Proteínas Imediatamente Precoces/genética , Proteínas Imediatamente Precoces/metabolismo , Proteína da Leucemia Promielocítica/genética , Proteína da Leucemia Promielocítica/metabolismo , Replicação ViralRESUMO
In this study, an intelligent drug delivery system (DDS) based on implanted triboelectric nanogenerator (iTENG) and red blood cell (RBC) is established for in situ hepatocellular carcinoma (HCC) therapy. Apatinib (APA), as an oral antitumor drug, which can inhibit the expression of vascular endothelial growth factor receptor-2 (VEGFR2) is loaded inside RBC, realizing the transform from oral formulation to injection preparation. Multishape designed iTENG adapted for different implant sites and environments can harvest biomechanical energy efficiently. The electric field (EF) generated by the iTENG can increase the release of APA, and the release will decrease quickly when the EF disappears, which shows that the DDS is highly controllable. The controllable DDS demonstrates an exciting killing ability of HCC cells both in vitro and in vivo with strikingly reduced APA dosage. After implantation, the self-powered DDS has a prominent therapeutic effect of HCC-bearing rabbits, which is expected to be applied in clinical medicine.
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Antineoplásicos , Carcinoma Hepatocelular , Neoplasias Hepáticas , Animais , Coelhos , Carcinoma Hepatocelular/patologia , Neoplasias Hepáticas/patologia , Fator A de Crescimento do Endotélio Vascular , Sistemas de Liberação de Medicamentos , Antineoplásicos/farmacologia , Antineoplásicos/uso terapêuticoRESUMO
Oral squamous cell carcinoma (OSCC) is a common oral cancer of the head and neck, which causes tremendous physical and mental pain to people. Traditional chemotherapy usually results in drug resistance and side effects, affecting the therapy process. In this study, a self-powered electrical impulse chemotherapy (EIC) method based on a portable triboelectric nanogenerator (TENG) was established for OSCC therapy. A common chemotherapeutic drug, doxorubicin (DOX), was used in the experiment. The TENG designed with zigzag structure had a small size of 6 cm × 6 cm, which could controllably generate the fixed output of 200 V, 400 V and 600 V. The electrical impulses generated by the TENG increased the cell endocytosis of DOX remarkably. Besides, a simply and ingeniously designed microneedle electrode increased the intensity of electric field (EF) between two adjacent microneedle tips compared with the most used planar interdigital electrode at the same height, which was more suitable for three-dimensional (3D) cells or tissues. Based on the TENG, microneedle electrode and DOX, the self-powered EIC system demonstrated a maximal apoptotic cell ratio of 22.47% and a minimum relative 3D multicellular tumor sphere (MCTS) volume of 160% with the drug dosage of 1 µg mL-1.
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Stroke usually causes multiple functional disability. To develop novel rehabilitation strategies, it is quite necessary to improve the understanding of post-stroke brain plasticity. Here, we use functional near-infrared spectroscopy to investigate the prefrontal cortex (PFC) network reorganization in stroke patients with dyskinesias. The PFC hemodynamic signals in the resting state from 16 stroke patients and 10 healthy subjects are collected and analyzed with the graph theory. The PFC networks for both groups show small-world attributes. The stroke patients have larger clustering coefficient and transitivity and smaller global efficiency and small-worldness than healthy subjects. Based on the selected network features, the established support vector machine model classifies the two groups of subjects with an accuracy rate of 88.5%. Besides, the clustering coefficient and local efficiency negatively correlate with patients' motor function. This study suggests that the PFC of stroke patients with dyskinesias undergoes specific network reorganization.