Assessing Consciousness in Patients With Disorders of Consciousness Using a Musical Stimulation Paradigm and Verifiable Criteria.

Numerous studies have shown that musical stimulation can activate corresponding functional brain areas. Electroencephalogram (EEG) activity during musical stimulation can be used to assess the consciousness states of patients with disorders of consciousness (DOC). In this study, a musical stimulation paradigm and verifiable criteria were used for consciousness assessment. Twenty-nine participants (13 healthy subjects, 6 patients in a minimally conscious state (MCS) and 10 patients in a vegetative state (VS)) were recruited, and EEG signals were collected while participants listened to preferred and relaxing music. Fusion features based on differential entropy (DE), common spatial pattern (CSP), and EEG-based network pattern (ENP) features were extracted from EEG signals, and a convolutional neural network-long short-term memory (CNN-LSTM) model was employed to classify preferred and relaxing music.The results showed that the average classification accuracy for healthy subjects reached 85.58%. For two of the patients in the MCS group, the classification accuracies reached 78.18% and 66.14%, and they were diagnosed with emergence from MCS (EMCS) two months later. The accuracies of three patients in the VS group were 58.18%, 64.32% and 62.05%, with two patients showing slight increases in scale scores. Our study suggests that musical stimulation could be an effective method for consciousness detection, with significant diagnostic implications for patients with DOC.

SFT-SGAT: A semi-supervised fine-tuning self-supervised graph attention network for emotion recognition and consciousness detection.

Emotional recognition is highly important in the field of brain-computer interfaces (BCIs). However, due to the individual variability in electroencephalogram (EEG) signals and the challenges in obtaining accurate emotional labels, traditional methods have shown poor performance in cross-subject emotion recognition. In this study, we propose a cross-subject EEG emotion recognition method based on a semi-supervised fine-tuning self-supervised graph attention network (SFT-SGAT). First, we model multi-channel EEG signals by constructing a graph structure that dynamically captures the spatiotemporal topological features of EEG signals. Second, we employ a self-supervised graph attention neural network to facilitate model training, mitigating the impact of signal noise on the model. Finally, a semi-supervised approach is used to fine-tune the model, enhancing its generalization ability in cross-subject classification. By combining supervised and unsupervised learning techniques, the SFT-SGAT maximizes the utility of limited labeled data in EEG emotion recognition tasks, thereby enhancing the model's performance. Experiments based on leave-one-subject-out cross-validation demonstrate that SFT-SGAT achieves state-of-the-art cross-subject emotion recognition performance on the SEED and SEED-IV datasets, with accuracies of 92.04% and 82.76%, respectively. Furthermore, experiments conducted on a self-collected dataset comprising ten healthy subjects and eight patients with disorders of consciousness (DOCs) revealed that the SFT-SGAT attains high classification performance in healthy subjects (maximum accuracy of 95.84%) and was successfully applied to DOC patients, with four patients achieving emotion recognition accuracies exceeding 60%. The experiments demonstrate the effectiveness of the proposed SFT-SGAT model in cross-subject EEG emotion recognition and its potential for assessing levels of consciousness in patients with DOC.

Fine-mapping of LrN3B on wheat chromosome arm 3BS, one of the two complementary genes for adult-plant leaf rust resistance.

The common wheat line 4N0461 showed adult-plant resistance to leaf rust. 4N0461 was crossed with susceptible cultivars Nongda4503 and Shi4185 to map the causal resistance gene(s). Segregation of leaf rust response in F2 populations from both crosses was 9 resistant:7 susceptible, indicative of two complementary dominant resistance genes. The genes were located on chromosome arms 3BS and 4BL and temporarily named LrN3B and LrN4B, respectively. Subpopulations from 4N0461 × Nongda4503 with LrN3B segregating as a single allele were used to fine-map LrN3B locus. LrN3B was delineated in a genetic interval of 0.07 cM, corresponding to 106 kb based on the Chinese Spring reference genome (IWGSC RefSeq v1.1). Four genes were annotated in this region, among which TraesCS3B02G014800 and TraesCS3B02G014900 differed between resistant and susceptible genotypes, and both were required for LrN3B resistance in virus-induced gene silencing experiments. Diagnostic markers developed for checking the polymorphism of each candidate gene, can be used for marker-assisted selection in wheat breeding programs.

Research Progress on the Pathogenesis, Diagnosis, and Drug Therapy of Alzheimer's Disease.

As the population ages worldwide, Alzheimer's disease (AD), the most prevalent kind of neurodegenerative disorder among older people, has become a significant factor affecting quality of life, public health, and economies. However, the exact pathogenesis of Alzheimer's remains elusive, and existing highly recognized pathogenesis includes the amyloid cascade hypothesis, Tau neurofibrillary tangles hypothesis, and neuroinflammation hypothesis. The major diagnoses of Alzheimer's disease include neuroimaging positron emission computed tomography, magnetic resonance imaging, and cerebrospinal fluid molecular diagnosis. The therapy of Alzheimer's disease primarily relies on drugs, and the approved drugs on the market include acetylcholinesterase drugs, glutamate receptor antagonists, and amyloid-ß monoclonal antibodies. Still, the existing drugs can only alleviate the symptoms of the disease and cannot completely reverse it. This review aims to summarize existing research results on Alzheimer's disease pathogenesis, diagnosis, and drug therapy, with the objective of facilitating future research in this area.

Assessment of rare earth elements variations in five water systems in Beijing: Distribution, geochemical features, and fractionation patterns.

This study investigates the distribution of rare earth elements (REEs) within the Beijing water system, specifically examining the Yongding, Chaobai, Beiyun, Jiyun, and Daqing rivers. Results indicate that the Beiyun River exhibits the highest REE concentrations, ranging from 35.95 to 59.78 µg/mL, while the Daqing River shows the lowest concentrations, ranging from 15.79 to 17.48 µg/mL. LREEs (La to Nd) predominate with a total concentration of 23.501 µg/mL, leading to a notable LREE/HREE ratio of 7.901. Positive Ce anomalies (0.70-1.11) and strong positive Eu anomalies (1.38-2.49) were observed. The study suggests that the Beijing water system's REEs may originate from geological and anthropogenic sources, such as mining and industrial activities in neighboring regions, including Inner Mongolia. These findings underscore the importance of ongoing monitoring and effective water management strategies to address REE-related environmental concerns.

Alleviating Recombinant Tissue Plasminogen Activator-induced Hemorrhagic Transformation in Ischemic Stroke via Targeted Delivery of a Ferroptosis Inhibitor.

Intravenous thrombolysis with recombinant tissue plasminogen activator (rtPA) is the primary treatment for ischemic stroke. However, rtPA treatment can substantially increase blood-brain barrier (BBB) permeability and susceptibility to hemorrhagic transformation. Herein, the mechanism underlying the side effects of rtPA treatment is investigated and demonstrated that ferroptosis plays an important role. The ferroptosis inhibitor, liproxstatin-1 (Lip) is proposed to alleviate the side effects. A well-designed macrocyclic carrier, glucose-modified azocalix[4]arene (GluAC4A), is prepared to deliver Lip to the ischemic site. GluAC4A bound tightly to Lip and markedly improved its solubility. Glucose, modified at the upper rim of GluAC4A, imparts BBB targeting to the drug delivery system owing to the presence of glucose transporter 1 on the BBB surface. The responsiveness of GluAC4A to hypoxia due to the presence of azo groups enabled the targeted release of Lip at the ischemic site. GluAC4A successfully improved drug accumulation in the brain, and Lip@GluAC4A significantly reduced ferroptosis, BBB leakage, and neurological deficits induced by rtPA in vivo. These findings deepen the understanding of the side effects of rtPA treatment and provide a novel strategy for their effective mitigation, which is of great significance for the treatment and prognosis of patients with ischemic stroke.

MdbHLH160 is stabilized via reduced MdBT2-mediated degradation to promote MdSOD1 and MdDREB2A-like expression for apple drought tolerance.

Drought stress is a key environmental factor limiting the productivity, quality, and geographic distribution of crops worldwide. Abscisic acid (ABA) plays an important role in plant drought stress responses, but the molecular mechanisms remain unclear. Here, we report an ABA-responsive bHLH transcription factor, MdbHLH160, which promotes drought tolerance in Arabidopsis (Arabidopsis thaliana) and apple (Malus domestica). Under drought conditions, MdbHLH160 is directly bound to the MdSOD1 (superoxide dismutase 1) promoter and activated its transcription, thereby triggering reactive oxygen species (ROS) scavenging and enhancing apple drought tolerance. MdbHLH160 also promoted MdSOD1 enzyme activity and accumulation in the nucleus through direct protein interactions, thus inhibiting excessive nuclear ROS levels. Moreover, MdbHLH160 directly upregulated the expression of MdDREB2A-like, a DREB (dehydration-responsive element binding factor) family gene that promotes apple drought tolerance. Protein degradation and ubiquitination assays showed that drought and ABA treatment stabilized MdbHLH160. The BTB protein MdBT2 was identified as an MdbHLH160-interacting protein that promoted MdbHLH160 ubiquitination and degradation, and ABA treatment substantially inhibited this process. Overall, our findings provide insights into the molecular mechanisms of ABA-modulated drought tolerance at both the transcriptional and post-translational levels via the ABA-MdBT2-MdbHLH160-MdSOD1/MdDREB2A-like cascade.

The apple transcription factor MdbHLH4 regulates plant morphology and fruit development by promoting cell enlargement.

The bHLH family, the second largest transcription factor (TF) family in plants, plays a crucial role in regulating plant growth and development processes. However, the biological functions and mechanisms of most bHLH proteins remain unknown, particularly in apples. In this study, we found that MdbHLH4 positively modulates plant growth and development by enhancing cell expansion. Overexpression (OE) of MdbHLH4 resulted in increased biomass, stem and root length, leaf area, and larger areas of pith, xylem, and cortex with greater cell size compared with wild-type apple plants. Conversely, RNA interference (RNAi)-mediated silencing of MdbHLH4 led to reduced xylem and phloem as well as smaller cell size compared to wild-type apple plants. Ectopic expression of MdbHLH4 in tomatoes resulted in enlarged fruits with impaired color appearance, decreased accumulation of soluble solids, and decreased flesh firmness along with larger seeds. Subsequent investigations have shown that MdbHLH4 directly binds to the promoters of MdARF6b and MdPIF4b, enhancing their expression levels. These findings suggest that MdbHLH4 potentially regulates plant cell expansion through auxin and light signaling pathways. These study results not only provide new insights into the roles of bHLH transcription factors in regulating plant growth and development but also contribute to a deeper understanding of their underlying mechanisms.

Non-invasive estimation of in vivo optical properties and hemodynamic parameters of domestic animals: a preliminary study on horses, dogs, and sheep.

Biosensors applied in veterinary medicine serve as a noninvasive method to determine the health status of animals and, indirectly, their level of welfare. Near infrared spectroscopy (NIRS) has been suggested as a technology with this application. This study presents preliminary in vivo time domain NIRS measurements of optical properties (absorption coefficient, reduced scattering coefficient, and differential pathlength factor) and hemodynamic parameters (concentration of oxygenated hemoglobin, deoxygenated hemoglobin, total hemoglobin, and tissue oxygen saturation) of tissue domestic animals, specifically of skeletal muscle (4 dogs and 6 horses) and head (4 dogs and 19 sheep). The results suggest that TD NIRS in vivo measurements on domestic animals are feasible, and reveal significant variations in the optical and hemodynamic properties among tissue types and species. In horses the different optical and hemodynamic properties of the measured muscles can be attributed to the presence of a thicker adipose layer over the muscle in the Longissimus Dorsi and in the Gluteus Superficialis as compared to the Triceps Brachii. In dogs the absorption coefficient is higher in the head (temporalis musculature) than in skeletal muscles. The smaller absorption coefficient for the head of the sheep as compared to the head of dogs may suggest that in sheep we are indeed reaching the brain cortex while in dog light penetration can be hindered by the strongly absorbing muscle covering the cranium.

MdHB7-like positively modulates apple salt tolerance by promoting autophagic activity and Na+ efflux.

Salt stress adversely affects the yield and quality of crops and limits their geographical distribution. Studying the functions and regulatory mechanisms of key genes in the salt stress response is important for breeding crops with enhanced stress resistance. Autophagy plays an important role in modulating the tolerance of plants to various types of abiotic stressors. However, the mechanisms underlying salt-induced autophagy are largely unknown. Cation/Ca2+ exchanger proteins enhance apple salt tolerance by inhibiting Na+ accumulation but the mechanism underlying the response to salt stress remains unclear. Here, we show that the autophagy-related gene MdATG18a modulated apple salt tolerance. Under salt stress, the autophagic activity, proline content, and antioxidant enzyme activities were higher and Na+ accumulation was lower in MdATG18a-overexpressing transgenic plants than in control plants. The use of an autophagy inhibitor during the salt treatment demonstrated that the regulatory function of MdATG18a depended on autophagy. The yeast-one-hybrid assay revealed that the homeodomain-leucine zipper (HD-Zip) transcription factor MdHB7-like directly bound to the MdATG18a promoter. Transcriptional regulation and genetic analyses showed that MdHB7-like enhanced salt-induced autophagic activity by promoting MdATG18a expression. The analysis of Na+ efflux rate in transgenic yeast indicated that MdCCX1 expression significantly promoted Na+ efflux. Promoter binding, transcriptional regulation, and genetic analyses showed that MdHB7-like promoted Na+ efflux and apple salt tolerance by directly promoting MdCCX1 expression, which was independent of the autophagy pathway. Overall, our findings provide insight into the mechanism underlying MdHB7-like-mediated salt tolerance in apple through the MdHB7-like-MdATG18a and MdHB7-like-MdCCX1 modules. These results will aid future studies on the mechanisms underlying stress-induced autophagy and the regulation of stress tolerance in plants.

Correction of Rotational Eccentricity Based on Model and Microvision in the Wire-Traction Micromanipulation System.

In the realm of automatic wire-traction micromanipulation systems, the alignment of the central axis of the coil with the rotation axis of the rotary stage can be a challenge, which leads to the occurrence of eccentricity during rotation. The wire-traction is conducted at a micron-level of manipulation precision on micron electrode wires; eccentricity has a significant impact on the control accuracy of the system. To resolve the problem, a method for measuring and correcting the coil eccentricity is proposed in this paper. First, models of radial and tilt eccentricity are established respectively based on the eccentricity sources. Then, measuring eccentricity is proposed by an eccentricity model and microscopic vision; the model is used to predict eccentricity, and visual image processing algorithms are used to calibrate model parameters. In addition, a correction based on the compensation model and hardware is designed to compensate for the eccentricity. The experimental results demonstrate the accuracy of the models in predicting eccentricity and the effectiveness of correction. The results show that the models have an accurate prediction for eccentricity that relies on the evaluation of the root mean square error (RMSE); the maximal residual error after correction was within 6 µm, and the compensation was approximately 99.6%. The proposed method, which combines the eccentricity model and microvision for measuring and correcting eccentricity, offers improved wire-traction micromanipulation accuracy, enhanced efficiency, and an integrated system. It has more suitable and wider applications in the field of micromanipulation and microassembly.

Engineered Cytokine-Primed Extracellular Vesicles with High PD-L1 Expression Ameliorate Type 1 Diabetes.

Type 1 diabetes (T1D), which is a chronic autoimmune disease, results from the destruction of insulin-producing ß cells targeted by autoreactive T cells. The recent discovery that mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) function as therapeutic tools for autoimmune conditions has attracted substantial attention. However, the in vivo distribution and therapeutic effects of MSC-EVs potentiated by pro-inflammatory cytokines in the context of T1D have yet to be established. Here, it is reported that hexyl 5-aminolevulinate hydrochloride (HAL)-loaded engineered cytokine-primed MSC-EVs (H@TI-EVs) with high expression of immune checkpoint molecule programmed death-legend 1 (PD-L1) exert excellent inflammatory targeting and immunosuppressive effects for T1D imaging and therapy. The accumulated H@TI-EVs in injured pancreas not only enabled the fluorescence imaging and tracking of TI-EVs through the intermediate product protoporphyrin (PpIX) generated by HAL, but also promoted the proliferative and anti-apoptotic effects of islet ß cells. Further analysis revealed that H@TI-EVs exhibited an impressive ability to reduce CD4+ T cell density and activation through the PD-L1/PD-1 axis, and induced M1-to-M2 macrophage transition to reshape the immune microenvironment, exhibiting high therapeutic efficiency in mice with T1D. This work identifies a novel strategy for the imaging and treatment of T1D with great potential for clinical application.

Research progress on the content and distribution of rare earth elements in rivers and lakes in China.

This study reviewed the content and distribution of rare earth elements (REE) in rivers and lakes in China based on the online literature. The sequence distribution of REE presented the decreasing trends in the order: of Ce > La > Nd > Pr > Sm > Gb > Dy>Er > Yb > Eu > Lu > Ho > Tb > Tm in rivers water. Pearl River and the Jiulong River constitute a significant sediments REE reservoir with an average value mean of 229.6 mg/kg and 266.86 mg/kg, respectively; both have higher concentrations than the global river average (174.8 mg/kg) and higher than the local soil background (Chinese soil background). The Liaohe River is one of China's most polluted rivers, with REE distribution ranging from 106.61 to 174.71 g/L (average 144.59 g/L in water). The total concentrations of dissolved REE in rivers near REE mining areas in China are higher than in other rivers. Increasing anthropogenic inputs to natural systems may permanently alter the natural signatures of REE. The distribution characteristics of REE in Chinese lakes (sediments) varied greatly, and the mean enrichment factor (EF) was sorted as follows: Ce > La > Nd > Pr > Sm > Gd > Dy>Er > Yb > Eu > Ho > Tb > Tm > Lu, where Ce was the most abundant followed by La, Nd, and Pr, and these four elements account for 85.39 % of the total concentration of REE. The REE in the sediments obtained from Poyang Lake and Dongting Lake had an average concentration respectively of 254.0 µg/g and 197.95 µg/g; both are considerably higher than the average upper continental crust (146.4 µg/g) and higher than in other lakes in China and around the world. The distribution and accumulation of LREE in most lake sediments result from the joint action of human activities and natural processes. It concluded that mining tailings were the primary cause of REE pollution in sediments, and industrial and agricultural activities are mainly responsible for water contamination.

Inhibition Effect of Pseudomonas stutzeri on the Corrosion of X70 Pipeline Steel Caused by Sulfate-Reducing Bacteria.

Microbiologically influenced corrosion (MIC) is a common phenomenon in water treatment, shipping, construction, marine and other industries. Sulfate-reducing bacteria (SRB) often lead to MIC. In this paper, a strain of Pseudomonas stutzeri (P. stutzeri) with the ability to inhibit SRB corrosion is isolated from the soil through enrichment culture. P. stutzeri is a short, rod-shaped, white and transparent colony with denitrification ability. Our 16SrDNA sequencing results verify the properties of P. stutzeri strains. The growth conditions of P. stutzeri bacteria and SRB are similar, and the optimal culture conditions are about 30 °C, pH 7, and the stable stage is reached in about seven days. The bacteria can coexist in the same growth environment. Using the weight loss method, electrochemical experiments and composition analysis techniques we found that P. stutzeri can inhibit the corrosion of X70 steel by SRB at 20~40 °C, pH 6~8. Furthermore, long-term tests at 3, 6 and 9 months reveal that P. stutzeri can effectively inhibit the corrosion of X70 steel caused by SRB.

MdbHLH4 negatively regulates apple cold tolerance by inhibiting MdCBF1/3 expression and promoting MdCAX3L-2 expression.

Low temperature affects the yield and quality of crops. Inducer of CBF expression 1 (ICE1) plays a positive role in plant cold tolerance by promoting the expression of CRT binding factor (CBF) and cold-responsive (COR) genes. Several ICE1-interacting transcription factors (TFs) that regulate plant cold tolerance have been identified. However, how these TFs affect the function of ICE1 and CBF expression under cold conditions remains unclear. Here, we identified the MYC-type TF MdbHLH4, a negative regulator of cold tolerance in Arabidopsis (Arabidopsis thaliana) and apple (Malus domestica) plants. Under cold conditions, MdbHLH4 inhibits the expression of MdCBF1 and MdCBF3 by directly binding to their promoters. It also interacts with MdICE1L, a homolog of AtICE1 in apple, and inhibits the binding of MdICE1L to the promoters of MdCBF1/3 and thus their expression. We showed that MdCAX3L-2, a Ca2+/H+ exchanger (CAX) family gene that negatively regulates plant cold tolerance, is also a direct target of MdbHLH4. MdbHLH4 reduced apple cold tolerance by promoting MdCAX3L-2 expression. Moreover, overexpression of either MdCAX3L-2 or MdbHLH4 promoted the cold-induced ubiquitination and degradation of MdICE1L. Overall, our results reveal that MdbHLH4 negatively regulates plant cold tolerance by inhibiting MdCBF1/3 expression and MdICE1L promoter-binding activity, as well as by promoting MdCAX3L-2 expression and cold-induced MdICE1L degradation. These findings provide insights into the mechanisms by which ICE1-interacting TFs regulate CBF expression and ICE1 function and thus plant cold tolerance.

Mesenchymal stem cell-derived extracellular vesicles attenuate tPA-induced blood-brain barrier disruption in murine ischemic stroke models.

Intracerebral hemorrhage following blood-brain barrier (BBB) disruption resulting from thrombolysis of ischemic stroke with tissue plasminogen activator (tPA) remains a critical clinical problem. Mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) are promising nanotherapeutic agents that have the potential to repair the BBB after ischemic stroke; however, whether they can attenuate BBB disruption and hemorrhagic transformation after tPA thrombolysis is largely unknown. Here, we observed that MSC-EVs efficiently passed through the BBB and selectively accumulated in injured brain regions in ischemic stroke model mice in real time using aggregation-induced emission luminogens (AIEgens), which exhibit better tracking ability than the commercially available tracer DiR. Moreover, tPA administration promoted the homing of MSC-EVs to the ischemic brain and increased the uptake of MSC-EVs by astrocytes. Furthermore, the accumulated MSC-EVs attenuated the tPA-induced disruption of BBB integrity and alleviated hemorrhage by inhibiting astrocyte activation and inflammation. Mechanistically, miR-125b-5p delivered by MSC-EVs played an indispensable role in maintaining BBB integrity by targeting Toll-like receptor 4 (TLR4) and inhibiting nuclear transcription factor-kappaB (NF-κB) signaling in astrocytes. This study provides a noninvasive method for real-time tracking of MSC-EVs in the ischemic brain after tPA treatment and highlights the potential of MSC-EVs as thrombolytic adjuvants for ischemic stroke. STATEMENT OF SIGNIFICANCE: Although tPA thrombolysis is the most effective pharmaceutical strategy for acute ischemic stroke, its clinical application and therapeutic efficacy are challenged by tPA-induced BBB disruption and hemorrhagic transformation. Our study demonstrated that MSC-EVs can act as an attractive thrombolytic adjuvant to repair the BBB and improve thrombolysis in a mouse ischemic stroke model. Notably, by labeling MSC-EVs with AIEgens, we achieved accurate real-time imaging of MSC-EVs in the ischemic brain and therapeutic visualization. MSC-EVs inhibit astrocyte activation and associated inflammation through miR-125b-5p/TLR4/NF-κB pathway. Consequently, we revealed that MSC-EVs combined with tPA thrombolysis may be a promising approach for the treatment of ischemic stroke in clinical setting.

Preparation of pyrrolidinyl diglycolamide bonded silica particles and its rare earth separation properties.

The separation of rare earth elements by solid phase containing diglycolamide-type ligands is a hot topic. In this study, 2-[2-oxo-2-(1-pyrrolidinyl)ethoxy]acetic acid (PYRDGA) was synthesized and attached to the silica. The binding strength of SiO2@PYRDGA for rare earths showed a single increasing trend with the radius of rare earth atoms. IR and XPS spectra demonstrated that carbonyl oxygen and ether bond oxygen are binding sites for rare earth ions. SiO2@PYRDGA was used for the chromatographic separation of REEs, and the primary separation of 16 REEs was achieved at pH = 2.0 using HNO3 solution as the eluent, and La, Ce, Pr, Nd, Sm, and Eu reached the baseline separation level.

Parkinson's disease detection based on multi-pattern analysis and multi-scale convolutional neural networks.

Parkinson's disease (PD) is a complex neurodegenerative disease. At present, the early diagnosis of PD is still extremely challenging, and there is still a lack of consensus on the brain characterization of PD, and a more efficient and robust PD detection method is urgently needed. In order to further explore the features of PD based on brain activity and achieve effective detection of PD patients (including OFF and ON medications), in this study, a multi-pattern analysis based on brain activation and brain functional connectivity was performed on the brain functional activity of PD patients, and a novel PD detection model based on multi-scale convolutional neural network (MCNN) was proposed. Based on the analysis of power spectral density (PSD) and phase-locked value (PLV) features of multiple frequency bands of two independent resting-state electroencephalography (EEG) datasets, we found that there were significant differences in PSD and PLV between HCs and PD patients (including OFF and ON medications), especially in the ß and γ bands, which were very effective for PD detection. Moreover, the combined use of brain activation represented by PSD and functional connectivity patterns represented by PLV can effectively improve the performance of PD detection. Furthermore, our proposed MCNN model shows great potential for automatic PD detection, with cross-validation accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve all above 99%. Our study may help to further understand the characteristics of PD and provide new ideas for future PD diagnosis based on spontaneous EEG activity.

Improved classification performance of EEG-fNIRS multimodal brain-computer interface based on multi-domain features and multi-level progressive learning.

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have potentially complementary characteristics that reflect the electrical and hemodynamic characteristics of neural responses, so EEG-fNIRS-based hybrid brain-computer interface (BCI) is the research hotspots in recent years. However, current studies lack a comprehensive systematic approach to properly fuse EEG and fNIRS data and exploit their complementary potential, which is critical for improving BCI performance. To address this issue, this study proposes a novel multimodal fusion framework based on multi-level progressive learning with multi-domain features. The framework consists of a multi-domain feature extraction process for EEG and fNIRS, a feature selection process based on atomic search optimization, and a multi-domain feature fusion process based on multi-level progressive machine learning. The proposed method was validated on EEG-fNIRS-based motor imagery (MI) and mental arithmetic (MA) tasks involving 29 subjects, and the experimental results show that multi-domain features provide better classification performance than single-domain features, and multi-modality provides better classification performance than single-modality. Furthermore, the experimental results and comparison with other methods demonstrated the effectiveness and superiority of the proposed method in EEG and fNIRS information fusion, it can achieve an average classification accuracy of 96.74% in the MI task and 98.42% in the MA task. Our proposed method may provide a general framework for future fusion processing of multimodal brain signals based on EEG-fNIRS.

[Pollution Characteristics and Risk Assessment of Heavy Metals in the Bioretention Systems of Sponge Cities].

As an important water purification and seepage measure for sponge cities, biofiltration systems have been widely used in their construction in China. In order to identify the heavy metal accumulation, pollution, and its potential environmental risk in the biofiltration systems, this study examined the heavy metal contents and spatial distribution characteristics by taking the biofiltration systems of Yuelai new town, Chongqing, the first demonstration area of sponge city construction in China, as the research object, and conducted a risk evaluation of the pollution level and ecological environment in this new town using the contamination factor (CF), geo-accumulation Index (Igeo), and potential ecological risk coefficient (PERC). The results showed that, except for Mn, the average contents of Cu, Zn, Pb, Ni, and Cd in the biofiltration systems of Yuelai new town were 4.14, 1.77, 4.98, 1.23, and 6.51 times higher than the soil background values of Chongqing. In terms of spatial distribution, the contents of heavy metals in biofiltration systems along the roads in different functional areas showed great differences. The contents of Cu, Zn, Mn, Pb, Ni, and Cd in the industrial area were significantly higher than those of the same types of heavy metals in the biofiltration systems in other areas (P<0.05). The CF and Igeo showed that the pollution level of heavy metals was ranked as follows:Mn