Enzymatic Reaction Enhanced Diffusion Accelerates Cargo Transport through Micro/Nano-Channels.

Energy conversion and transfer of enzyme-catalyzed reactions at molecular level are an interesting and challenging scientific topic that helps understanding biological processes in nature. In this study, it is demonstrated that enzyme-catalyzed reactions can enhance diffusion of surrounding molecules and thus accelerate cargo transport within 1D micro/nanochannels. Specifically, urease is immobilized on the inner walls of silica micro/nano-tubes to construct bio-catalytically active micro/nanochannels. The catalytic reaction inside the channels drives a variety of cargoes, including small dye molecules, polymers, and rigid nanoparticles (e.g., quantum dots, QDs), to pass through these micro/nanochannels much faster than they will by free diffusion. The enhanced diffusion of molecular species inside the channels is validated by direct observation of the Brownian motion of tracer particles, and further confirmed by significantly enhanced Raman intensity of reporter molecules. Finite element and Brownian dynamics simulations provide a theoretical understanding of these experimental observations. Furthermore, the effect of the channels' size on the diffusion enhancement is examined. The acceleration effect of the cargo transport through these enzymatically active micro/nanochannels can be turned on or off via chemical activators or inhibitors. This study provides valuable insights on the design of biomimetic channels capable of controlled and efficient transmembrane transport.

The application of impulse oscillometry system based on machine learning algorithm in the diagnosis of chronic obstructive pulmonary disease.

Objective. Diagnosing chronic obstructive pulmonary disease (COPD) using impulse oscillometry (IOS) is challenging due to the high level of clinical expertise it demands from doctors, which limits the clinical application of IOS in screening. The primary aim of this study is to develop a COPD diagnostic model based on machine learning algorithms using IOS test results.Approach. Feature selection was conducted to identify the optimal subset of features from the original feature set, which significantly enhanced the classifier's performance. Additionally, secondary features area of reactance (AX) were derived from the original features based on clinical theory, further enhancing the performance of the classifier. The performance of the model was analyzed and validated using various classifiers and hyperparameter settings to identify the optimal classifier. We collected 528 clinical data examples from the China-Japan Friendship Hospital for training and validating the model.Main results. The proposed model achieved reasonably accurate diagnostic results in the clinical data (accuracy = 0.920, specificity = 0.941, precision = 0.875, recall = 0.875).Significance. The results of this study demonstrate that the proposed classifier model, feature selection method, and derived secondary feature AX provide significant auxiliary support in reducing the requirement for clinical experience in COPD diagnosis using IOS.

Differences in attentional function between experienced mindfulness meditators and non-meditators.

Introduction: Attentional enhancement has often been identified as the central cognitive mechanism underlying the benefits of mindfulness meditation. However, the extent to which this enhancement is observable in the neural processes underlying long-term meditation is unclear. This current study aimed to examine differences in attentional performance between meditators and controls (non-meditators) using a visual oddball task with concurrent electroencephalography (EEG) recordings. Methods: Thirty-four participants were recruited, including 16 meditators and 18 healthy controls, who were non-meditators. The participants completed a visual oddball task, using visual stimuli, and EEG recording. Results: Self-reports revealed that meditators had higher mindful attention scores than did the control group. The behavioral results showed that the meditators demonstrated faster reaction times than the non-meditators did. Neural findings indicated a higher P2 amplitude in the meditators than in the controls. The meditators demonstrated a significantly higher P3 in the target trials than in the distractor trials, which was not observed in the controls. Additionally, the time-frequency analysis demonstrated that the delta and theta powers in the meditators were significantly higher than those in the controls. Conclusions: The study suggests the meditators exhibited greater attentional performance than the controls did, as revealed by EEG and behavioral measures. This study extends previous research on the effects of mindfulness meditation on attention and adds to our understanding of the effects of long-term mindfulness meditation.

Effectiveness of Maze IV procedure versus thoracoscopic ablation for atrial fibrillation: a propensity score-matched analysis.

Background: Thoracoscopic ablation (TA) has emerged as a promising treatment for atrial fibrillation (AF), with the Cox-Maze IV Procedure (CMP-IV) as the current gold-standard intervention. This study aims to evaluate and compare the outcomes of TA and CMP-IV in treating AF. Methods: Patients with AF underwent either CMP-IV or TA through a left-side chest approach. The CMP-IV entailed bi-atrium ablation, whereas the TA involved creating three circular plus three linear ablations in the left atrium. We analyzed baseline characteristics, perioperative outcomes and recurrence rates using propensity score matching (PSM) at a 1:1 ratio, to ensure comparability between the two treatment groups. Results: A total of 459 patients underwent either CMP-IV (n=93) or TA via left chest (n=366) and 174 patients were deemed eligible for 1:1 PSM. The TA group experienced significantly shorter intensive care unit (ICU) and hospital stays. The mean follow-up period was 31.5±22.1 months. Pre- and post-matching analysis showed that CMP-IV had a higher rate of freedom from recurrence compared to TA, particularly in non-paroxysmal AF patients. Multivariable Cox regression analysis revealed that CMP-IV was associated with a reduced risk of recurrence, while an increased left atrial size emerged as an independent predictor of postoperative recurrence, regardless of the use of CMP-IV or TA. Conclusions: Our study suggests that while the therapeutic efficacy of TA for "lone" AF may fall short of the classic CMP-IV, its less invasive nature results in significantly shorter ICU and hospital stays. To enhance patient outcomes following TA, it is essential to improve the quality of ablation, refine the ablation route, and focus on careful patient selection.

An Adaptive Multi-Population Approach for Sphericity Error Evaluation in the Manufacture of Hemispherical Shell Resonators.

The performance of a hemispherical resonant gyroscope (HRG) is directly affected by the sphericity error of the thin-walled spherical shell of the hemispherical shell resonator (HSR). In the production process of the HSRs, high-speed, high-accuracy, and high-robustness requirements are necessary for evaluating sphericity errors. We designed a sphericity error evaluation method based on the minimum zone criterion with an adaptive number of subpopulations. The method utilizes the global optimal solution and the subpopulations' optimal solution to guide the search, initializes the subpopulations through clustering, and dynamically eliminates inferior subpopulations. Simulation experiments demonstrate that the algorithm exhibits excellent evaluation accuracy when processing simulation datasets with different sphericity errors, radii, and numbers of sampling points. The uncertainty of the results reached the order of 10-9 mm. When processing up to 6000 simulation datasets, the algorithm's solution deviation from the ideal sphericity error remained around -3 × 10-9 mm. And the sphericity error evaluation was completed within 1 s on average. Additionally, comparison experiments further confirmed the evaluation accuracy of the algorithm. In the HSR sample measurement experiments, our algorithm improved the sphericity error assessment accuracy of the HSR's inner and outer contour sampling datasets by 17% and 4%, compared with the results given by the coordinate measuring machine. The experiment results demonstrated that the algorithm meets the requirements of sphericity error assessment in the manufacturing process of the HSRs and has the potential to be widely used in the future.

SIRT6-mediated vascular smooth muscle cells senescence participates in the pathogenesis of abdominal aortic aneurysm.

BACKGROUND AND AIMS: In this study, we carried out a clinical sample study, and in vivo and in vitro studies to evaluate the effect of SIRT6 and SIRT6-mediated vascular smooth muscle senescence on the development of abdominal aortic aneurysm (AAA). METHOD AND RESULTS: AAA specimen showed an increased P16, P21 level and a decreased SIRT6 level compared with control aorta. Time curve study of Ang II infusion AAA model showed similar P16, P21 and SIRT6 changes at the early phase of AAA induction. The in vivo overexpression of SIRT6 significantly prevented AAA formation in Ang II infusion model. The expression of P16 and P21 was significantly reduced after SIRT6 overexpression. SIRT6 overexpression also attenuated chronic inflammation and neo-angiogenesis in Ang II infusion model. The overexpression of SIRT6 could attenuate premature senescence, inflammatory response and neo-angiogenesis in human aortic smooth muscle cells (HASMC) under Ang II stimulation. CONCLUSIONS: SIRT6 overexpression could limit AAA formation via attenuation of vascular smooth muscle senescence, chronic inflammation and neovascularity.

A systematic evaluation of computation methods for cell segmentation.

Cell segmentation is a fundamental task in analyzing biomedical images. Many computational methods have been developed for cell segmentation, but their performances are not well understood in various scenarios. We systematically evaluated the performance of 18 segmentation methods to perform cell nuclei and whole cell segmentation using light microscopy and fluorescence staining images. We found that general-purpose methods incorporating the attention mechanism exhibit the best overall performance. We identified various factors influencing segmentation performances, including training data and cell morphology, and evaluated the generalizability of methods across image modalities. We also provide guidelines for choosing the optimal segmentation methods in various real application scenarios. We developed Seggal, an online resource for downloading segmentation models already pre-trained with various tissue and cell types, which substantially reduces the time and effort for training cell segmentation models.

The Impact of Spatial Frequency on the Perception of Crowd Emotion: An fMRI Study.

Recognizing the emotions of faces in a crowd is crucial for understanding overall behavior and intention as well as for smooth and friendly social interactions. However, it is unclear whether the spatial frequency of faces affects the discrimination of crowd emotion. Although high- and low-spatial-frequency information for individual faces is processed by distinct neural channels, there is a lack of evidence on how this applies to crowd faces. Here, we used functional magnetic resonance imaging (fMRI) to investigate neural representations of crowd faces at different spatial frequencies. Thirty-three participants were asked to compare whether a test face was happy or more fearful than a crowd face that varied in high, low, and broad spatial frequencies. Our findings revealed that fearful faces with low spatial frequencies were easier to recognize in terms of accuracy (78.9%) and response time (927 ms). Brain regions, such as the fusiform gyrus, located in the ventral visual stream, were preferentially activated in high spatial frequency crowds, which, however, were the most difficult to recognize behaviorally (68.9%). Finally, the right inferior frontal gyrus was found to be better activated in the broad spatial frequency crowds. Our study suggests that people are more sensitive to fearful crowd faces with low spatial frequency and that high spatial frequency does not promote crowd face recognition.

Intelligent sensing based on active micro/nanomotors.

In the microscopic world, synthetic micro/nanomotors (MNMs) can convert a variety of energy sources into driving forces to help humans perform a number of complex tasks with greater ease and efficiency. These tiny machines have attracted tremendous attention in the field of drug delivery, minimally invasive surgery, in vivo sampling, and environmental management. By modifying their surface materials and functionalizing them with bioactive agents, these MNMs can also be transformed into dynamic micro/nano-biosensors that can detect biomolecules in real-time with high sensitivity. The extensive range of operations and uses combined with their minuscule size have opened up new avenues for tackling intricate analytical difficulties. Here, in this review, various driving methods are briefly introduced, followed by a focus on intelligent detection techniques based on MNMs. And we discuss the distinctive advantages, current issues, and challenges associated with MNM-based intelligent detection. It is believed that the future advancements of MNMs will greatly impact the diagnosis, treatment, and prevention of diseases.

Estimation of Wideband Multi-Component Phasors Considering Signal Damping.

Harmonic and interharmonic content in power system signals is increasing with the development of renewable energy generation and power electronic devices. These multiple signal components can seriously degrade power quality, trip thermal generators, cause oscillations, and threaten system stability, especially the interharmonic tones with positive damping factors. The first step to mitigate these adverse effects is to accurately and quickly monitor signal features, including frequency, damping factor, amplitude, and phase. This paper proposes a concise and robust index to identify the number of modes present in the signal using the singular values of the Hankel matrix and discusses the scope of its application by testing the influence of various factors. Next, the simplified matrix pencil theory is employed to estimate the signal component frequency and damping factor. Then their estimates are considered in the modified least-squares algorithm to extract the wideband multi-component phasors accurately. Finally, this paper designs a series of scenarios considering varying signal frequency, damping factor, amplitude, and phase to test the proposed algorithm thoroughly. The results verify that the proposed method can achieve a maximum total vector error of less than 1.5%, which is more accurate than existing phasor estimators in various signal environments. The high accuracy of the proposed method is because it considers both the estimation of the frequency number and the effect of signal damping.

Integrated Analysis of lncRNA-mRNA Regulatory Networks Related to Lipid Metabolism in High-Oleic-Acid Rapeseed.

A high oleic acid content is considered an essential characteristic in the breeding of high-quality rapeseed in China. Long-chain non-coding RNA (lncRNA) molecules play an important role in the plant's growth and its response to stress. To better understand the role of lncRNAs in regulating plant reproductive development, we analyzed whole-transcriptome and physiological data to characterize the dynamic changes in lncRNA expression during the four representative times of seed development of high- and low-oleic-acid rapeseed in three regions. We identified 21 and 14 lncRNA and mRNA modules, respectively. These modules were divided into three types related to region, development stages, and material. Next, we analyzed the key modules related to the oil content and the oleic acid, linoleic acid, and linolenic acid contents with physiological data and constructed the key functional network analysis on this basis. Genes related to lipid metabolism, such as 3-ketoacyl-CoA synthase 16 (KCS16) and acyl-CoA:diacylglycerol acyltransferase 1 (DGAT1), were present in the co-expression network, suggesting that the effect of these genes on lipid metabolism might be embodied by the expression of these lncRNAs. Our results provide a fresh insight into region-, development-stage-, and material-biased changes in lncRNA expression in the seeds of Brassica napus. Some of these lncRNAs may participate in the regulatory network of lipid accumulation and metabolism, together with regulated genes. These results may help elucidate the regulatory system of lncRNAs in the lipid metabolism of high-oleic-acid rapeseed seeds.

Ring-opening Polymerization of Enantiopure Bicyclic Ether-ester Monomers toward Closed-loop Recyclable and Crystalline Stereoregular Polyesters via Chemical Upcycling of Bioplastic.

Although great successes have been achieved, the preparation of closed-loop recyclable polyesters with high working temperatures still remains as a big challenge. Herein, we present the syntheses of a series of enantiopure bicyclic ether-ester monomers by upcycling of poly(3-hydroxybutyrate) bioplastic. The "living"/controlled ring-opening polymerizations of these enantiopure monomers to produce stereoregular polyesters with controlled molecular weights and well-defined chain ends were achieved. The effects of stereoconfiguration and substituent on polymerization kinetics and thermodynamics as well as the thermal properties of resultant polyesters were investigated. Of note, the stereoregular polyesters are semi-crystalline materials with melting temperatures up to 176 °C, even higher than the commodity polyolefin plastics. These polyesters can be depolymerized back to recover pristine monomers, thus successfully establishing a closed-loop life cycle.

Impact of the degree of worsening renal function and B-type natriuretic peptide on the prognosis of patients with acute heart failure.

Background: The impact of the degree of worsening renal function (WRF) and B-type natriuretic peptide (BNP) on the prognosis of patients with acute heart failure (AHF) is still debatable. The present study investigated the influence of different degrees of WRF and BNP levels at discharge on 1-year all-cause mortality in AHF. Methods: Hospitalized AHF patients diagnosed with acute new-onset/worsening of chronic heart failure (HF) between January 2015 and December 2019 were included in this study. Patients were assigned into high and low BNP groups based on the median BNP level at discharge (464 pg/ml). According to serum creatinine (Scr) levels, WRF was divided into non-severe WRF (nsWRF) (Scr increased ≥0.3 mg/dl and <0.5 mg/dl) and severe WRF (sWRF) (Scr increased ≥0.5 mg/dl); non-WRF (nWRF) was defined as Scr increased of <0.3 mg/dl). Multivariable cox regression was used to evaluate the association of low BNP value and different degrees of WRF with a all-cause death, as well as testing for an interaction between the two. Results: Among 440 patients in the high BNP group, there was a significant difference in WRF on mortality (nWRF vs. nsWRF vs. sWRF: 22% vs. 23.8% vs. 58.8%, P < 0.001). Yet, mortality did not significantly differ across the WRF subgroups in the low BNP group (nWRF vs. nsWRF vs. sWRF: 9.1% vs. 6.1% vs. 15.2%, P = 0.489). In multivariate Cox regression analysis, low BNP group at discharge (HR, 0.265; 95%CI, 0.162-0.434; P < 0.001) and sWRF (HR, 2.838; 95%CI, 1.756-4.589; P < 0.001) were independent predictors of 1-year mortality in AHF.There was a significant interaction between low BNP group and sWRF(HR, 0.225; 95%CI, 0.055-0.918; P < 0.05). Conclusions: nsWRF does not increase the 1-year mortality in AHF patients, whereas sWRF does. A low BNP value at discharge is associated with better long-term outcomes and mitigates the adverse effects of sWRF on prognosis.

HMGB1/TLR4 signaling pathway enhances abdominal aortic aneurysm progression in mice by upregulating necroptosis.

OBJECTIVE AND DESIGN: The age-associated increases in aseptic inflammation and necroptosis are closely related to the emergence of various age-associated diseases. METHODS: In this study, the role of HMGB1/TLR4-induced necroptosis in abdominal aortic aneurysm (AAA) formation was investigated. First, the levels of sterile inflammatory mediators (HMGB1, TLR4) and necroptosis markers were measured in the abdominal aortas of young and old C57BL/6JNifdc mice. We observed that sterile inflammatory mediators and necroptosis markers were greatly increased in the abdominal aortas of old mice. Then, angiotensin II (Ang II)-induced AAA model in APOE-/- mice was used in this study. Mice AAA models were treated with the RIP1 inhibitor necrostatin-1 (Nec-1) or the TLR4 inhibitor TAK-242, respectively. RESULTS: We found that HMGB1, TLR4, and necroptosis markers were elevated in old mice compared with those in young mice. Same elevation was also found in the development of AAA in APOE-/- mice. In addition, the necroptosis inhibitor Nec-1 alleviated Ang II-induced AAA development while downregulating the expression of HMGB1/TLR4. After blocking TLR4 with TAK-242, the expression of necroptosis markers decreased significantly, and the progression of AAA was also alleviated in APOE-/- mice. CONCLUSIONS: Our results indicated that HMGB1/TLR4-mediated necroptosis enhances AAA development in the Ang II-induced AAA model in APOE-/- mice and that TLR4 might be a potential therapeutic target for AAA management.

MilliLoc: Human computer interaction oriented acoustic millimeter-level real-time locating system.

In recent years, people have become more interested in using acoustics to locate equipment in intelligent human-computer interfaces (HCI). However, existing acoustic locating systems have poor compatibility with smart devices. To achieve millimeter-level accuracy, most systems require large microphone spacing, complex algorithms, and a high cost. In this paper, we propose a new HCI system, MilliLoc, to achieve millimeter-level real-time acoustic locating. Our first contribution is to design a high-performance and convenient microphone array. It has a high sampling rate of 96 kHz, real-time complete dataflow, and is compatible with any smart device. The second contribution is to propose an improved generalized cross-correlation phase transform method with simplicity and real-time capability. Even if the signal-to-noise ratio is not high enough, it can still estimate the time delay accurately. We combine the microphone array with the algorithm to illustrate the implementation of MilliLoc. Experiments show that MilliLoc has a median 2D accuracy of 7.2 mm in a 60 cm sector area and achieves millimeter-level locating.

Mindfulness Training Improves Attention: Evidence from Behavioral and Event-related Potential Analyses.

Mindfulness meditation helps to improve attentional capacity. However, the neural correlates that indicate the mechanism through which mindfulness improves attention are unclear. To address this gap, we aimed to assess the effects of mindfulness training on sustained attentional capacity. Event-related potentials (ERPs) associated with the modified sustained attention response task (mSART) were used in this study. A total of 45 college students were randomly assigned to either the mindfulness group (n = 21) or the control group (n = 24). Participants in the mindfulness group received a three-week mindfulness training. The self-report results showed that the mindfulness group reported higher mindfulness scores (observing and non-judgment of inner experiences) after the training. The mindfulness group also scored lower on the state anxiety than the control group. Behavioral results also showed that self-caught mind wandering in the mindfulness group significantly decreased after the training, and the mindfulness group showed a faster response after the training. The ERP results showed that N2 amplitudes in the post-test were significantly greater than those in the pre-test in the mindfulness group. We did not find any interactions between group and time for P3. The findings suggest that mindfulness training can effectively improve sustained attentional capacity, as indicated by reduced mind wandering and increased N2 responses.

Importance of timing and training to implement awake prone positioning in patients with COVID-19: a single-center prospective observational study.

Background: Awake prone positioning (APP) is broadly implemented in patients with severe acute respiratory syndrome coronavirus 2 related disease [coronavirus disease 2019 (COVID-19)] admitted to hospital with severe respiratory distress syndrome. This prospective observational study aimed to explore the factors influencing the implementation of APP in patients with acute respiratory failure due to COVID-19. Methods: Patients with COVID-19, all hospitalized with positive X-ray findings and oxygen supplementation requirement, in the Respiratory Step-Down Unit of the Peking University Third Hospital between January 6th, 2023, and January 20th, 2023, were included in this study. Data regarding basic information, activities of daily living (ADLs) scores, oxygen therapy, vital signs, and duration of APP were collected to investigate the factors influencing prone positioning. Results: Among the 134 patients included, 55.2% showed an improvement in oxygen saturation 1 hour after APP. Logistic regression revealed that the pre-APP heart rate (HR) [odds ratio (OR) =1.032; P=0.046] and peripheral oxygen saturation (SpO2) (OR =0.720; P<0.001) were the associated factors of the improvement in SpO2 after treatment. Multiple linear regression revealed that the ADL scores and pre-APP respiratory rate (RR) were the associated factors of the duration of prone positioning (P<0.01). The APP technical steering group effectively improved duration of APP. Conclusions: Patients with low SpO2 and increased HR before treatment showed greater improvement in oxygen saturation. Patients with lower tolerance to ADL but lower RRs were those to demonstrate a longer duration of prone positioning. This is pointing towards establishing the most favorable time window for APP during the course of COVID-19: after the ADLs have already decreased, but before significant tachypnea has appeared.

Dynamics of rice microbiomes reveal core vertically transmitted seed endophytes.

BACKGROUND: Plants and their associated microbiota constitute an assemblage of species known as holobionts. The plant seed microbiome plays an important role in nutrient uptake and stress attenuation. However, the core vertically transmitted endophytes remain largely unexplored. RESULTS: To gain valuable insights into the vertical transmission of rice seed core endophytes, we conducted a large-scale analysis of the microbiomes of two generations of six different rice varieties from five microhabitats (bulk soil, rhizosphere, root, stem, and seed) from four geographic locations. We showed that the microhabitat rather than the geographic location and rice variety was the primary driver of the rice microbiome assemblage. The diversity and network complexity of the rice-associated microbiome decreased steadily from far to near the roots, rice exterior to interior, and from belowground to aboveground niches. Remarkably, the microbiomes of the roots, stems, and seeds of the rice interior compartments were not greatly influenced by the external environment. The core bacterial endophytes of rice were primarily comprised of 14 amplicon sequence variants (ASVs), 10 of which, especially ASV_2 (Pantoea) and ASV_48 (Xanthomonas), were identified as potentially vertically transmitted taxa because they existed across generations, were rarely present in exterior rice microhabitats, and were frequently isolated from rice seeds. The genome sequences of Pantoea and Xanthomonas isolated from the parental and offspring seeds showed a high degree of average nucleotide and core protein identity, indicating vertical transmission of seed endophytes across generations. In silico prediction indicated that the seed endophytes Pantoea and Xanthomonas possessed streamlined genomes with short lengths, low-complexity metabolism, and various plant growth-promoting traits. We also found that all strains of Pantoea and Xanthomonas exhibited cellulase activity and produced indole-3-acetic acid. However, most strains exhibited insignificant antagonism to the major pathogens of rice, such as Magnaporthe oryzae and X. oryzae pv. oryzae. CONCLUSION: Overall, our study revealed that microhabitats, rather than site-specific environmental factors or host varieties, shape the rice microbiome. We discovered the vertically transmitted profiles and keystone taxa of the rice microbiome, which led to the isolation of culturable seed endophytes and investigation of their potential roles in plant-microbiome interactions. Our results provide insights on vertically transmitted microbiota and suggest new avenues for improving plant fitness via the manipulation of seed-associated microbiomes.  Video Abstract.

Comprehensive evaluation of high-oleic rapeseed (Brassica napus) based on quality, resistance, and yield traits: A new method for rapid identification of high-oleic acid rapeseed germplasm.

To scientifically evaluate and utilize high-oleic acid rape germplasm resources and cultivate new varieties suitable for planting in the Hunan Province, 30 local high-oleic acid rape germplasms from Hunan were used as materials. The 12 personality indices of quality, yield, and resistance were comprehensively evaluated by variability, correlation, principal component, and cluster analyses. The results of variability showed that except for oleic acid, the lowest coefficient of variation was oil content, which was 0.06. Correlation analysis showed that oil content was positively correlated with main traits such as yield per plant and oleic acid, which could be used in the early screening of high-oleic rape germplasm. The results of principal component analysis showed that the 12 personality indicators were integrated into four principal components, and the cumulative contribution rate was 62.487%. The value of comprehensive coefficient 'F' was positively correlated with the first, second, and fourth principal components and negatively correlated with the third principal component. Cluster analysis showed that 30 high-oleic rape germplasms could be divided into four categories consisting of 9 (30%), 6 (20%), 7 (23%), and 8 (27%) high-oleic rape germplasms, each with the characteristics of "high disease resistance", "high yield", "high protein", and "more stability". This study not only provides a reference basis for high-oleic rape breeding but also provides a theoretical basis for their early screening.

Processing of emotions expressed through eye regions attenuates attentional blink.

Despite of the crucial role of eye region in nonverbal communication, how and when the brain responds to affective signals projected from this region remains unclear. This study explored the temporal dynamics in the processing of emotionally valenced eye regions (happy, neutral, and fearful) and the influence of attentional resources using a dual-target rapid serial visual presentation task and event-related potential (ERP) technique. Behaviorally, the recognition accuracy of happy and fearful eye regions was higher than that for neutral eye regions in the deficient attentional resources condition (lag2), indicating reduced attentional blink for emotional eye regions. The ERP findings denote that fearful and happy eye regions modulated the N170. The early posterior negativity (EPN) was influenced by the interaction between lag and emotional valence, which was reflected by larger amplitudes for fearful rather than neutral eye regions in the lag2 condition. The amplitude of the late positive potential (LPP) also increased for the happy and fearful eye regions. These outcomes suggest that the human brain is highly sensitive to isolated eye regions. Moreover, fearful signals emitted from the eye region are processed automatically and are unaffected by attentional resource availability.