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SUMMARY: Watercore is a common physiological disease of Rosaceae plants, such as apples (Malus domestica), usually occurring during fruit ripening. Apple fruit with watercore symptoms is prone to browning and rotting, thus losing commercial viability. Sorbitol and calcium ions are considered key factors affecting watercore occurrence in apples. However, the mechanism by which they affect the occurrence of watercore remains unclear. Here, we identified that the transcription factor MdWRKY9 directly binds to the promoter of MdSOT2, positively regulates the transcription of MdSOT2, increases sorbitol content in fruit, and promotes watercore occurrence. Additionally, MdCRF4 can directly bind to MdWRKY9 and MdSOT2 promoters, positively regulating their expression. Since calcium ions can induce the ubiquitination and degradation of the transcription factor MdCRF4, they can inhibit the transcription of MdWRKY9 and MdSOT2 by degrading MdCRF4, thereby reducing the sorbitol content in fruit and inhibiting the occurrence of fruit watercore disease. Our data sheds light on how calcium ions mitigate watercore in fruit, providing molecular‐level insights to enhance fruit quality artificially. [ABSTRACT FROM AUTHOR]

The attention to cueing among nurses with anxiety affects their nursing quality seriously. Nevertheless, the neural mechanism of attention under anxiety among nurses has not been revealed. In this study, we utilized the event-related potential (ERP) and functional brain networks to investigate the neural mechanism of the cueing attention differences between anxiety and non-anxiety nurse groups (AG-20 nurses; NAG-20 nurses) in the spatial cueing task. The results revealed that in the invalid cues (144 trials), longer reaction times, larger P2 amplitudes, and more linkages between the right frontal and parietal areas were found in AG compared to NAG. In the valid cues (288 trials), there were no significant behavioral and neural differences between the two groups. The AG in the invalid cues showed slower response times, larger P2 and N5 amplitudes, and denser linkages originating from the occipital cortex than those in the valid cues. The convolutional neural network was trained for discriminating between the anxiety nurses and the normal ones, with the average accuracy being 0.76. The findings provided a potential physiological biomarker to predict the anxiety group who need to give more psychological attention. Nurse leaders maybe get more information for offering solutions to retain mental health among nurses. [ABSTRACT FROM AUTHOR]

Decision response and feedback in gambling are interrelated. Different decisions lead to different ranges of feedback, which in turn influences subsequent decisions. However, the mechanism underlying the continuous decision-feedback process is still left unveiled. To fulfill this gap, we applied the hidden Markov model (HMM) to the gambling electroencephalogram (EEG) data to characterize the dynamics of this process. Furthermore, we explored the differences between distinct decision responses (i.e. choose large or small bets) or distinct feedback (i.e. win or loss outcomes) in corresponding phases. We demonstrated that the processing stages in decision-feedback process including strategy adjustment and visual information processing can be characterized by distinct brain networks. Moreover, time-varying networks showed, after decision response, large bet recruited more resources from right frontal and right center cortices while small bet was more related to the activation of the left frontal lobe. Concerning feedback, networks of win feedback showed a strong right frontal and right center pattern, while an information flow originating from the left frontal lobe to the middle frontal lobe was observed in loss feedback. Taken together, these findings shed light on general principles of natural decision-feedback and may contribute to the design of biologically inspired, participant-independent decision-feedback systems. [ABSTRACT FROM AUTHOR]

Decision-making plays an essential role in the interpersonal interactions and cognitive processing of individuals. There has been increasing interest in being able to predict an individual's decision-making response (i.e., acceptance or rejection). We proposed an electroencephalogram (EEG)-based computational intelligence framework to predict individual responses. Specifically, the discriminative spatial network pattern (DSNP), a supervised learning approach, was applied to single-trial EEG data to extract the DSNP feature from the single-trial brain network. A linear discriminate analysis (LDA) trained on the DSNP features was then used to predict the individual response trial-by-trial. To verify the performance of the proposed DSNP, we recruited two independent subject groups, and recorded the EEGs using two types of EEG systems. The performances of the trial-by-trial predictors achieved an accuracy of 0.88 ± 0.09 for the first dataset, and 0.90 ± 0.10 for the second dataset. These trial-by-trial prediction performances suggested that individual responses could be predicted trial-by-trial by using the specific pattern of single-trial EEG networks, and our proposed method has the potential to establish the biologically inspired artificial intelligence decision system. • A single-trial EEG based approach is developed to predict individual decision-making response. • A supervised learning approach is developed to extract the discriminative spatial network pattern. • The proposed approach achieves the high prediction performances (over 0.88) for two independent EEG datasets. [ABSTRACT FROM AUTHOR]

• The hypoactivation within the caudate nucleus in patients with depression was largely located in the body and head of the bilateral caudate nuclei. • The hyperactivation within the caudate nucleus was concentrated in the left body of the caudate nucleus. • There is a positive relationship between decreased activation of the caudate body and head and depressed emotional behaviors in patients with depressive disorder. • In the cognition domain, abnormal activation was centered in the right body of the caudate nucleus. During task-based functional magnetic resonance imaging (t-fMRI) patients with depressive disorder (DD) have shown abnormal caudate nucleus activation. There have been no meta-analyses that are conducted on the caudate nucleus using Activation Likelihood Estimation (ALE) in patients with DD, and the relationships between abnormal caudate activity and different behavior domains in patients with DD remain unclear. There were 24 previously published t-fMRI studies included in the study with the caudate nucleus as the region of interest. Meta-analyses were performed using the method of ALE. Included five ALE meta-analyses: (1) the hypoactivated caudate nucleus relative to healthy controls (HCs); (2) the hyper-activated caudate nucleus; (3) the abnormal activation in the caudate nucleus in the emotion domain; (4) the abnormal activation in cognition domain; (5) the abnormal activation in the affective cognition domain. Results revealed that the hypo-/hyper-activity in the caudate subregions is mainly located in the caudate body and head, while the relationships between abnormal caudate subregions and different behavior domains are complex. The hypoactivation of the caudate body and head plays a key role in the emotions which indicates there is a positive relationship between the decreased caudate activity and depressed emotional behaviors in patients with DD. [ABSTRACT FROM AUTHOR]

A large-scale network provides a high hierarchical level for understanding the adaptive adjustment of the human brain during cognition processes. Since high spatial resolution is required, most of the related works are based on functional magnetic resonance imaging (fMRI); however, fMRI lacks the temporal information that is important in investigating the high cognition processes. Although combining electroencephalography (EEG) inverse solution and independent component analysis (ICA), researchers detected large-scale functional subnetworks recently, few researchers focus on the unreasonable negative activation, which is biased from the nonnegative electrical source activations in the brain. In this study, considering the favorable nonnegative property of Bayesian nonnegative matrix factorization (Bayesian NMF) and combining EEG source imaging, we developed a robust approach for EEG large-scale network construction and applied it to two independent real EEG datasets (i.e., decision-making and P300). Eight and nine best-fit networks, including such important subnetworks as the somatosensory-motor network (SMN), the default mode network (DMN), etc., were successfully identified for decision-making and P300, respectively. Compared to the networks acquired with ICA, these networks not only lacked confusing negative activations but also showed clear spatial distributions that are compatible with specific brain function. Based on the constructed large-scale network, we further probed that the self-referential network (SRN), the primary visual network (PVN), and the visual network (VN) demonstrated different interaction patterns with other networks between different responses in decision-making. Our results confirm the possibility of probing the neural mechanisms of high cognition processes at a very high temporal and spatial resolution level. • A robust EEG large-scale network construction approach is proposed by Bayesian NMF. • The networks with positive activations and clear spatial distributions are detected. • The different network patterns between the two decision-making responses are revealed. [ABSTRACT FROM AUTHOR]

Objective: Spectral power analysis plays a predominant role in electroencephalogram-based emotional recognition. It can reflect activity differences among multiple brain regions. In addition to activation difference, different emotions also involve different large-scale network during related information processing. In this paper, both information propagation patterns and activation difference in the brain were fused to improve the performance of emotional recognition. Methods: We constructed emotion-related brain networks with phase locking value and adopted a multiple feature fusion approach to combine the compensative activation and connection information for emotion recognition. Results: Recognition results on three public emotional databases demonstrated that the combined features are superior to either single feature based on power distribution or network character. Furthermore, the conducted feature fusion analysis revealed the common characters between activation and connection patterns involved in the positive, neutral, and negative emotions for information processing. Significance: The proposed feasible combination of both information propagation patterns and activation difference in the brain is meaningful for developing the effective human–computer interaction systems by adapting to human emotions in the real world applications. [ABSTRACT FROM AUTHOR]

• A new character-speech materials is proposed to study the audio-visual competition. • Validating Mandarin has a modality advantages in processing audio-visual information. • Clarifying the dominance of auditory processing in Chinese audio-visual competition. Language is a remarkable cognitive ability that can be expressed through visual (written language) or auditory (spoken language) modalities. When visual characters and auditory speech convey conflicting information, individuals may selectively attend to either one of them. However, the dominant modality in such a competing situation and the neural mechanism underlying it are still unclear. Here, we presented participants with Chinese sentences in which the visual characters and auditory speech convey conflicting information, while behavioral and electroencephalographic (EEG) responses were recorded. Results showed a prominent auditory dominance when audio-visual competition occurred. Specifically, higher accuracy (ACC), larger N400 amplitudes and more linkages in the posterior occipital-parietal areas were demonstrated in the auditory mismatch condition compared to that in the visual mismatch condition. Our research illustrates the superiority of the auditory speech over the visual characters, extending our understanding of the neural mechanisms of audio-visual competition in Chinese. [ABSTRACT FROM AUTHOR]

Background: Patients with major depressive disorders (MDD) have abnormalities in the frontal-limbic structures of the brain. Childhood trauma is a risk factor for both structural brain alterations and MDD. However, the relationships among the three have not been confirmed.Methods: Sixty-four patients with MDD and sixty-one healthy controls (HC) were checked by using MRI, the Hamilton Depression Scale (HAMD) and Childhood Trauma Questionnaire (CTQ). Voxel-based morphometry (VBM) was used to compare gray matter volume (GMV) differences between the two groups. Moreover, partial correlation and mediation analyses were conducted to test for potential associations between CTQ scores, different GMV, and clinical variables.Results: Compared to the HC group, the MDD patients showed decreased GMV in the right middle frontal gyrus (rMFG) and right precentral gyrus (rPreCG). In the patient group, reduced GMV in rMFG was associated with CTQ scores (r = -0.30, P = 0.019) and HAMD scores (r = -0.53, P < 0.001). Finally, in the patient group, mediation analysis revealed that the indirect effect of rMFG GMV in CTQ scores and HAMD scores was 0.115 and the proportion of indirect effect to total effect was 23.86%.Limitations: This study used a cross-sectional collection, and it is unclear whether at the longitudinal level the brain GMV mediates the relationship between childhood trauma and depression.Conclusions: Abnormalities in the frontal GMV were presented in the MDD patients. It is possible that childhood traumatic experiences cause inefficient GMV and ultimately lead to an increased susceptibility to depression. [ABSTRACT FROM AUTHOR]

Summary: Nitric oxide (NO) is known to modulate the action of several phytohormones. This includes the gaseous hormone ethylene, but the molecular mechanisms underlying the effect of NO on ethylene biosynthesis are unclear.Here, we observed a decrease in endogenous NO abundance during apple (Malus domestica) fruit development and exogenous treatment of apple fruit with a NO donor suppressed ethylene production, suggesting that NO is a ripening suppressor.Expression of the transcription factor MdERF5 was activated by NO donor treatment. NO induced the nucleocytoplasmic shuttling of MdERF5 by modulating its interaction with the protein phosphatase, MdPP2C57. MdPP2C57‐induced dephosphorylation of MdERF5 at Ser260 is sufficient to promote nuclear export of MdERF5. As a consequence of this export, MdERF5 proteins in the cytoplasm interacted with and suppressed the activity of MdACO1, an enzyme that converts 1‐aminocyclopropane‐1‐carboxylic acid (ACC) to ethylene. The NO‐activated MdERF5 was observed to increase in abundance in the nucleus and bind to the promoter of the ACC synthase gene MdACS1 and directly suppress its transcription.Together, these results suggest that NO‐activated nucleocytoplasmic MdERF5 suppresses the action of ethylene biosynthetic genes, thereby suppressing ethylene biosynthesis and limiting fruit ripening. [ABSTRACT FROM AUTHOR]

Acoustic stimulation is one of the most influential techniques for distressing tinnitus, while how it functions to reverse neural changes associated with tinnitus remains undisclosed. In this study, our objective is to investigate alterations in brain networks to shed light on the enigma of acoustic intervention for tinnitus. We designed a 75-day long-term acoustic intervention experiment, during which chronic tinnitus patients received daily modulated acoustic stimulation with each session lasting 15 days. Every 15 days, professional tinnitus assessments were conducted, collecting both electroencephalogram (EEG) and tinnitus handicap inventory (THI) data from the patients. Thereafter, we investigated the changes in EEG network organizations during continuous acoustic stimulation and their progressive evolution throughout long-term therapy, alongside exploring the associations between the evolving changes of the network alterations and THI. Our current study findings reveal reorganization in alpha/beta long-range frontal-parietal-occipital connections as well as local frontal and parietal-occipital regions induced by acoustic stimulation. Furthermore, we observed a decrease in modulation effects as therapy sessions progressed. These alterations in brain networks reflect the reversal of tinnitus-related neural activities, particularly distress and perception; thus contributing to tinnitus rehabilitation through long-term modulation effects. This study provides unique insights into how long-term acoustic intervention affects the network organizations of tinnitus patients and deepens our understanding of the pathophysiological mechanisms underlying tinnitus rehabilitation. We investigated the alteration in brain networks during long-term acoustic stimulation of tinnitus patients. The alpha and beta reorganization are found to be closely related to the reverse of tinnitus-relevant neural activities. Long-term acoustic intervention effect on network organization helps to deepen insight into tinnitus rehabilitation. [ABSTRACT FROM AUTHOR]

Ethylene is one of the most important plant hormones involved in the climacteric fruit ripening process. Apple is a climacteric fruit, and its ripening process is regulated by ethylene. The effect of light-emitting diode (LED) light on plant growth and development has been extensively investigated; however, it remains unclear how LED light affects apple fruit ripening. Herein, we observed that the ripening of apple fruit treated with eight kinds of LED light was significantly inhibited compared with that of the dark control, with inhibition by white light being the most significant. Furthermore, the optimal light intensity for the inhibition of ethylene production was 20 μmol·m−2s−1, with an optimal light duration of 12 h per day. LED white light treatment enhanced the expression of two ELONGATED HYPOCOTYL 5 (HY5) genes, MdHY5L and MdHY5S , which encode transcription factors involved in the light signaling pathway. These two HY5s inhibited the transcription of MdACS1 , a crucial rate-limiting enzyme in the ethylene synthesis pathway, by directly binding to its promoter. Collectively, these findings imply that LED white light induces the expression of MdHY5L and MdHY5S and delays the expression of the ethylene synthesis-related gene MdACS1 to prevent fruit ripening. This study preliminarily elucidates the molecular mechanism underlying LED white light-induced inhibition of ethylene synthesis in apple fruit, providing an important theoretical basis for studying how to improve the storage ability and prolong the shelf life of apple fruit. • LED white light inhibits ethylene biosynthesis during apple fruit ripening. • LED white light induced the expression of MdHY5L / S. • MdHY5 binds to the promoter of MdACS1 and downregulates its expression. [ABSTRACT FROM AUTHOR]

Objective: The electroencephalographic (EEG) inverse problem is ill-posed owing to the electromagnetism Helmholtz theorem and since there are fewer observations than the unknown variables. Apart from the strong background activities (ongoing EEG), evoked EEG is also inevitably contaminated by strong outliers caused by head movements or ocular movements during recordings. Methods: Considering the sparse activations during high cognitive processing, we propose a novel robust EEG source imaging algorithm, least absolute $l$ -P (0

Motor imagery (MI) requires subjects to visualize the requested motor behaviors, which involves a large-scale network that spans multiple brain areas. The corresponding cortical activity reflected on the scalp is characterized by event-related desynchronization (ERD) and then by event-related synchronization (ERS). However, the network mechanisms that account for the dynamic information processing of MI during the ERD and ERS periods remain unknown. Here, we combined ERD/ERS analysis with the dynamic networks in different MI stages (i.e. motor preparation, ERD and ERS) to probe the dynamic processing of MI information. Our results show that specific dynamic network structures correspond to the ERD/ERS evolution patterns. Specifically, ERD mainly shows the contralateral networks, while ERS has the symmetric networks. Moreover, different dynamic network patterns are also revealed between the two types of MIs, in which the left-hand MIs exhibit a relatively less sustained contralateral network, which may be the network mechanism that accounts for the bilateral ERD/ERS observed for the left-hand MIs. Similar to the network topologies, the three MI stages also appear to be characterized by different network properties. The above findings all demonstrate that different MI stages that involve specific brain networks for dynamically processing the MI information. [ABSTRACT FROM AUTHOR]

Highlights • The expression of SIRT6 in hDPCs was down-regulated by LPS. • Overexpression of SIRT6 in hDPCs attenuated cell death induced by LPS. • SIRT6 was able to protect hDPCs from apoptosis. • SIRT6 physically binds to Ku70. • SIRT6 promotes interaction of Ku70 with the proapoptotic protein Bax. Abstract Progression of pulpitis is facilitated by the immune system’s response to bacteria, enhancing the production of inflammatory regulators. Bacterial lipopolysaccharide (LPS) is the major structural component of the outer wall of all Gram-negative bacteria and a potent activator of the immune system. Apoptosis is believed to play an important role in the inflammatory process of pulpitis. SIRT6 is a member of class III of histone deacetylases (HDACs), also called sirtuins (SIRTs). The role of SIRT6 in apoptosis in pulpitis is unknown. In this study, we found that the expression of SIRT6 in human dental pulp cells (hDPCs) was down-regulated by treatment with LPS. MTT and LDH assays revealed that overexpression of SIRT6 in hDPCs attenuated cell death induced by LPS. Consistently, our results demonstrated that SIRT6 was able to protect hDPCs from apoptosis. We found that SIRT6 could interact with Ku70, an important apoptosis regulator, by the immunoprecipitation (IP) experiment. SIRT6 physically binds to Ku70. Overexpression of SIRT6 reduced acetylation of Ku70 and promoted interaction of Ku70 with the proapoptotic protein Bax. These studies underscore an essential role of SIRT6 in the survival of hDPCs in stress situations. [ABSTRACT FROM AUTHOR]

• Approach to evaluate information transmission velocity via fusion of EEG and DTI. • A transmission velocity network consists of four hierarchical modules was proposed. • Dynamic bottom-up/top-down information interactions revealed by hierarchical ITVN. • Prediction of P300 amplitude was achieved using ITVN properties. • P300 variability may attribute to the distinct information transmission efficiency. The brain functions as an accurate circuit that regulates information to be sequentially propagated and processed in a hierarchical manner. However, it is still unknown how the brain is hierarchically organized and how information is dynamically propagated during high-level cognition. In this study, we developed a new scheme for quantifying the information transmission velocity (ITV) by combining electroencephalogram (EEG) and diffusion tensor imaging (DTI), and then mapped the cortical ITV network (ITVN) to explore the information transmission mechanism of the human brain. The application in MRI-EEG data of P300 revealed bottom-up and top-down ITVN interactions subserving P300 generation, which was comprised of four hierarchical modules. Among these four modules, information exchange between visual- and attention-activated regions occurred at a high velocity, related cognitive processes could thus be efficiently accomplished due to the heavy myelination of these regions. Moreover, inter-individual variability in P300 was probed to be attributed to the difference in information transmission efficiency of the brain, which may provide new insight into the cognitive degenerations in clinical neurodegenerative disorders, such as Alzheimer's disease, from the transmission velocity perspective. Together, these findings confirm the capacity of ITV to effectively determine the efficiency of information propagation in the brain. [Display omitted] [ABSTRACT FROM AUTHOR]

The P300 event-related potential (ERP) varies across individuals, and exploring this variability deepens our knowledge of the event, and scope for its potential applications. Previous studies exploring the P300 have relied on either electroencephalography (EEG) or functional magnetic resonance imaging (fMRI). We applied simultaneous event-related EEG-fMRI to investigate how the network structure is updated from rest to the P300 task so as to guarantee information processing in the oddball task. We first identified 14 widely distributed regions of interest (ROIs) that were task-associated, including the inferior frontal gyrus and the middle frontal gyrus, etc. The task-activated network was found to closely relate to the concurrent P300 amplitude, and moreover, the individuals with optimized resting-state brain architectures experienced the pruning of network architecture, i.e. decreasing connectivity, when the brain switched from rest to P300 task. Our present simultaneous EEG-fMRI study explored the brain reconfigurations governing the variability in P300 across individuals, which provided the possibility to uncover new biomarkers to predict the potential for personalized control of brain-computer interfaces. • Simultaneous EEG-fMRI is used to study P300 variability during the oddball task. • Network reconfiguration helps to uncover the P300 variability. • Low P300 group shows enhanced connectivity deviating from resting state. • The smaller the network updates, the larger the P300 amplitude. [ABSTRACT FROM AUTHOR]

Background: In schizophrenia, executive dysfunction is the most critical cognitive impairment, and is associated with abnormal neural activities, especially in the frontal lobes. Complexity estimation using electroencephalogram (EEG) recording based on nonlinear dynamics and task performance tests have been widely used to estimate executive dysfunction in schizophrenia.Methods: The present study estimated the cool executive function based on fractal dimension (FD) values of EEG data recorded from first-episode schizophrenia patients and healthy controls during the performance of three cool executive function tasks, namely, the Trail Making Test-A (TMT-A), Trail Making Test-B (TMT-B), and Tower of Hanoi tasks.Results: The results show that the complexity of the frontal EEG signals that were measured using FD was different in first-episode schizophrenia patients during the manipulation of executive function. However, no differences between patients and controls were found in the FD values of the EEG data that was recorded during the performance of the Tower of Hanoi task.Conclusions: These results suggest that cool executive function exhibits little impairment in first-episode schizophrenia patients. [ABSTRACT FROM AUTHOR]