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.

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.

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.

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.

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.

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.

Brain-Computer Interfaces for Awareness Detection, Auxiliary Diagnosis, Prognosis, and Rehabilitation in Patients with Disorders of Consciousness.

In recent years, neuroimaging studies have remarkably demonstrated the presence of cognitive motor dissociation in patients with disorders of consciousness (DoC). These findings accelerated the development of brain-computer interfaces (BCIs) as clinical tools for behaviorally unresponsive patients. This article reviews the recent progress of BCIs in patients with DoC and discusses the open challenges. In view of the practical application of BCIs in patients with DoC, four aspects of the relevant literature are introduced: consciousness detection, auxiliary diagnosis, prognosis, and rehabilitation. For each aspect, the paradigm design, brain signal processing methods, and experimental results of representative BCI systems are analyzed. Furthermore, this article provides guidance for BCI design for patients with DoC and discusses practical challenges for future research.

Fine mapping of a powdery mildew resistance gene MlIW39 derived from wild emmer wheat (Triticum turgidum ssp. dicoccoides).

KEY MESSAGE: Powdery mildew resistance gene MlIW39, originated from wild emmer wheat accession IW39, was mapped to a 460.3 kb genomic interval on wheat chromosome arm 2BS. Wheat powdery mildew, caused by Blumeria graminis f. sp. tritici (Bgt), is destructive disease and a significant threat to wheat production globally. The most effective way to control this disease is genetic resistance. However, when resistance genes become widely deployed in agriculture, their effectiveness is compromised by virulent variants that were previously minor components of the pathogen population or that arise from mutation. This necessitates continual search for new sources of resistance in both wheat and its near relatives. In this study, we produced a common wheat line 8D49 (87-1/IW39//2*87-1), which has all-stage immunity to Bgt isolate E09 and many other Chinese Bgt isolates, by transferring powdery mildew resistance from Israeli wild emmer wheat (WEW) accession IW39 to the susceptible common wheat line 87-1. Genetic analysis indicated that the powdery mildew resistance in 8D49 was controlled by a single dominant gene, temporarily designated MlIW39. Genetic linkage analyses with molecular markers showed that MlIW39 was located in a 0.7 cm genetic region between markers QB-3-16 and 7Seq546 on the short arm of chromosome 2B. Fine mapping using three large F2 populations delimited MlIW39 to a physical interval of approximately 460.3 kb region in the WEW reference genome (Zavitan v1.0) that contained six annotated protein-coding genes, four of which had gene structures similar to known disease resistance genes. This provides a foundation for map-based cloning of MlIW39. Markers 7Seq622 and 7Seq727 co-segregating with MlIW39 can be utilized for marker-assisted selection in further genetic studies and wheat breeding.

Extraction and Back-Extraction Behaviors of La(III), Ce(III), Pr(III), and Nd(III) Single Rare Earth and Mixed Rare Earth by TODGA.

N,N,N',N'-Tetraoctyl diglycolamide (TODGA), as a new extraction agent, is effective for its excellent performance and low environmental hazard, and it is very welcome for the rare earth separation process. In this paper, by controlling the extraction time, diluent type, acid type and its concentration, rare earth concentration, etc., the optimum extraction and back-extraction effects of TODGA on La(III), Ce(III), Pr(III), and Nd(III) and mixed rare earths were obtained. The experiment showed that 0.10 mol·L-1 TODGA had the best extraction effect on single rare earth under the conditions of using petroleum ether as diluent, 5 mol·L-1 nitric acid, 20 min extraction time, and 0.01 mol·L-1 rare earth. In the mixed rare earth extraction, the percentage concentrations of La(III), Ce(III), Pr(III), and Nd(III) could be achieved from 21.7%, 19.9%, 30.8%, and 22.2% at the initial stage to 90.5%, 37%, 51%, and 62% after extraction, respectively, by controlling the number of back-extraction cycles and the concentrations of hydrochloric acid and nitric acid in the back-extraction system. The TODGA-rare earth carrier system showed the best back-extraction effect when the hydrochloric acid concentration was 1 mol·L-1 and the back-extraction time was 20 min. At the same time, the mixed rare earth liquid system with low initial concentration was selected for extraction and separation of mixed rare earth. The separation effect was better, and the recovery rate was higher than that of mixed rare earth liquid system with a high initial concentration.

Enhancing BCI-Based Emotion Recognition Using an Improved Particle Swarm Optimization for Feature Selection.

：Electroencephalogram (EEG) signals have been widely used in emotion recognition. However, the current EEG-based emotion recognition has low accuracy of emotion classification, and its real-time application is limited. In order to address these issues, in this paper, we proposed an improved feature selection algorithm to recognize subjects' emotion states based on EEG signal, and combined this feature selection method to design an online emotion recognition brain-computer interface (BCI) system. Specifically, first, different dimensional features from the time-domain, frequency domain, and time-frequency domain were extracted. Then, a modified particle swarm optimization (PSO) method with multi-stage linearly-decreasing inertia weight (MLDW) was purposed for feature selection. The MLDW algorithm can be used to easily refine the process of decreasing the inertia weight. Finally, the emotion types were classified by the support vector machine classifier. We extracted different features from the EEG data in the DEAP data set collected by 32 subjects to perform two offline experiments. Our results showed that the average accuracy of four-class emotion recognition reached 76.67%. Compared with the latest benchmark, our proposed MLDW-PSO feature selection improves the accuracy of EEG-based emotion recognition. To further validate the efficiency of the MLDW-PSO feature selection method, we developed an online two-class emotion recognition system evoked by Chinese videos, which achieved good performance for 10 healthy subjects with an average accuracy of 89.5%. The effectiveness of our method was thus demonstrated.

Glycerol-Induced Powdery Mildew Resistance in Wheat by Regulating Plant Fatty Acid Metabolism, Plant Hormones Cross-Talk, and Pathogenesis-Related Genes.

Our previous study indicated that glycerol application induced resistance to powdery mildew (Bgt) in wheat by regulating two important signal molecules, glycerol-3-phosphate (G3P) and oleic acid (OA18:1). Transcriptome analysis of wheat leaves treated by glycerol and inoculated with Bgt was performed to identify the activated immune response pathways. We identified a set of differentially expressed transcripts (e.g., TaGLI1, TaACT1, and TaSSI2) involved in glycerol and fatty acid metabolism that were upregulated in response to Bgt infection and might contribute to G3P and OA18:1 accumulation. Gene Ontology (GO) enrichment analysis revealed GO terms induced by glycerol, such as response to jasmonic acid (JA), defense response to bacterium, lipid oxidation, and growth. In addition, glycerol application induced genes (e.g., LOX, AOS, and OPRs) involved in the metabolism pathway of linolenic and alpha-linolenic acid, which are precursor molecules of JA biosynthesis. Glycerol induced JA and salicylic acid (SA) levels, while glycerol reduced the auxin (IAA) level in wheat. Glycerol treatment also induced pathogenesis related (PR) genes, including PR-1, PR-3, PR-10, callose synthase, PRMS, RPM1, peroxidase, HSP70, HSP90, etc. These results indicate that glycerol treatment regulates fatty acid metabolism and hormones cross-talk and induces the expression of PR genes that together contribute to Bgt resistance in wheat.

Broadband, polarization insensitive low-scattering metasurface based on lossy Pancharatnam-Berry phase particles.

In this paper, a novel composite metasurface (MS) with diffuse scattering and absorbing characteristics is proposed to reduce the radar cross section (RCS) of a metal target in a broad band. The combination of absorption and diffusion is realized based on lossy Pancharatnam-Berry (PB) phase particles. The units are arranged according to a coding sequence which is obtained by an optimization algorithm based on simulated annealing algorithm. Simulation results show that the MS obtained based on the optimized coding sequence is insensitive to polarization. Due to the combination of absorption and diffusion, the MS has good performance in both monostatic and bistatic scenarios. Finally, the proposed MS is fabricated and measured, and the experimental results are in good agreement with simulation results. A 10 dB backward reflection reduction can be achieved from 21GHz to 38GHz and a 15 dB backward reflection reduction can be achieved from 22GHz to 35GHz under normal incidence. Furthermore, the MS has good performance under large angle (<45°) incidence.

The Predictive Value of Motor-Evoked Potentials and the Silent Period on Patient Outcome after Acute Cerebral Infarction.

BACKGROUND: The predictive value of neurophysiologic assessment on patients' outcome after acute cerebral infarction is poorly understood. The aim of this study was to investigate the prognostic value of motor-evoked potentials (MEPs) and the silent period (SP) on clinical outcome. METHODS: A total of 202 patients with acute cerebral infarction were prospectively recruited. MEP and SP were recorded from the abductor pollicis brevis of the affected side within 10 days after stroke onset. Patient outcome was measured as the dependency rate. RESULTS: Cortical MEP was induced in 78 patients whereas it was absent in 82 patients. The initial NIHSS (National Institutes of Health Stroke Scale) score was significantly lower in patients with MEP than in those without MEP (P < .001). Regression analysis demonstrated that a left-sided lesion (OR = .391, 95% CI .178-.858, P = .019), NIHSS at admission (OR = .826, 95% CI .744-.917, P < .001), and presence of MEP (OR = 3.918, 95% CI 1.770-8.672, P < .001) were independent predictors of outcome 3 months after stroke. Among patients with MEP, only the contralateral cortical SP value was significantly shorter in the good outcome subgroup (t = 2.541, P = .013). Receiver operating characteristic curve analysis demonstrated that SP was able to predict patients at higher risk of unfavorable outcome 3 months after stroke onset (area under the curve .721, 95% CI .58-.86, P = .008). CONCLUSIONS: These data suggested that MEP and SP were useful tools to predict patients' acute outcomes following cerebral infarction.

Predictive value of high residual platelet reactivity by flow cytometry for outcomes of ischemic stroke patients on clopidogrel therapy.

High residual platelet reactivity (HRPR) assessed by multiple tests has been associated with worse clinical outcomes. However, the clinical impact of HRPR assessed by flow cytometry is unknown. The aim of this study was to validate the predictive value of HRPR measured by flow cytometry for clinical outcomes in ischemic stroke patients during clopidogrel therapy. Overall, 198 consecutive patients with ischemic stroke taking clopidogrel underwent platelet function testing on flow cytometer including adenosine diphosphate (ADP)-induced platelet aggregation (PAg) and platelet activation markers (CD62P, CD63, and PAC-1). Poor outcome was defined as poor prognosis and ischemic events during 12-month follow-up. By receiver operating characteristic curve analysis, residual platelet reactivity assessed by flow cytometry was able to distinguish between patients with and without poor outcomes, when platelet inhibition was evaluated with ADP-PAg (area under the curve [AUC], .77; 95% confidence interval [CI], .69-.84; P < .001), CD62P (AUC, .73; 95% CI, .64-.81; P < .001), CD63 (AUC, .72; 95% CI, .64-.80; P < .001), and PAC-1 (AUC, .70; 95% CI, .62-.78; P < .001). The prevalence of HRPR was 25.8% for ADP-PAg, 32.8% for CD62P, 41.4% for CD63, and 56.1% for PAC-1. The multiple logical regression analysis demonstrated that HRPR was an independent predictor of poor outcomes (ADP-PAg: odds ratio [OR] 13.03, 95% CI 5.66-29.98, P < .001; CD62P: OR 8.55, 95% CI 3.94-18.57, P < .001; CD63: OR 8.74, 95% CI 3.89-19.64, P < .001; PAC-1: OR 4.23, 95% CI 1.98-9.08). In conclusion, HRPR, assessed by flow cytometry, is able to detect ischemic stroke patients at increased risk of 12-month poor outcomes on clopidogrel treatment.

Distribution characteristics and indicator significance of Dechloranes in multi-matrices at Ny-Ålesund in the Arctic.

In recent years, Dechloranes have been widely detected in the environment around the world. However, understanding and knowledge of Dechloranes in remote regions, such as the Arctic, remain lacking. Therefore, the concentrations of 5 Dechloranes in surface seawater, sediment, soil, moss, and dung collected from Ny-Ålesund in the Arctic were measured with the concentrations 93 pg/L, 342, 325, 1.4, and 258 pg/g, respectively, which were much lower than those in Asian and European regions. The mean ratios of anti-Dechlorane Plus (DP) to total DP (ƒanti) in seawater, sediment, soil, moss, dung, and atmospheric samples were 0.36, 0.21, 0.18, 0.27, 0.66, and 0.43, respectively. Results suggested that the main source of DP in seawater, sediment, soil, and moss was long-range atmospheric transport. However, the ratio identified in dung was different, for which the migration behavior of the organism is probably the main source of DP.

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.

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.

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.

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.

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.