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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]

As a kind of biological network, the brain network conduces to understanding the mystery of high-efficiency information processing in the brain, which will provide instructions to develop efficient brain-like neural networks. Large-scale dynamical functional network connectivity (dFNC) provides a more context-sensitive, dynamical, and straightforward sight at a higher network level. Nevertheless, dFNC analysis needs good enough resolution in both temporal and spatial domains, and the construction of dFNC needs to capture the time-varying correlations between two multivariate time series with unmatched spatial dimensions. Effective methods still lack. With well-developed source imaging techniques, electroencephalogram (EEG) has the potential to possess both high temporal and spatial resolutions. Therefore, we proposed to construct the EEG large-scale cortical dFNC based on brain atlas to probe the subtle dynamic activities in the brain and developed a novel method, that is, wavelet coherence–S estimator (WTCS), to assess the dynamic couplings among functional subnetworks with different spatial dimensions. The simulation study demonstrated its robustness and availability of applying to dFNC. The application in real EEG data revealed the appealing “Primary peak” and “P3-like peak” in dFNC network properties and meaningful evolutions in dFNC network topology for P300. Our study brings new insights for probing brain activities at a more dynamical and higher hierarchical level and pushing forward the development of brain-inspired artificial neural networks. The proposed WTCS not only benefits the dFNC studies but also gives a new solution to capture the time-varying couplings between the multivariate time series that is often encountered in signal processing disciplines. [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]

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]

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]

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

The P300 is regarded as a psychosis endophenotype of schizophrenia and a putative biomarker of risk for schizophrenia. However, the brain activity (i.e., P300 amplitude) during tasks cannot always provide satisfying discrimination of patients with schizophrenia (SZs) from healthy controls (HCs). Spontaneous activity at rest indices the potential of the brain, such that if the task information can be efficiently processed, it provides a compensatory understanding of the cognitive deficits in SZs. In this paper, based on the resting and P300 task electroencephalogram (EEG) data sets, we constructed functional EEG networks and then extracted the inherent spatial pattern of network (SPN) features for both brain states. Finally, the combined SPN features of the rest and task networks were used to recognize SZs. The findings of this paper revealed that the combined SPN features could achieve the highest accuracy of 90.48%, with the sensitivity of 89.47%, and specificity of 91.30%. These findings consistently implied that the rest and task P300 EEGs could actually provide comprehensive information to reliably classify SZs from HCs, and the SPN is a promising tool for the clinical diagnosis of SZs. [ABSTRACT FROM AUTHOR]

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]

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]

• 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]

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]

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]

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., (© 2024 Society for Experimental Biology and John Wiley & Sons Ltd.)

Objective . The decision-making behavior of the proposer is a key factor in achieving effective and equitable maintenance of social resources, particularly in economic interactions, and thus understanding the neurocognitive basis of the proposer's decision-making is a crucial issue. Yet the neural substrate of the proposer's decision behavior, especially from the resting-state network perspective, remains unclear. Approach . In this study, we investigated the relationship between the resting-state network and decision proposals and further established a multivariable model to predict the proposers' unfair offer rates in the ultimatum game. Main results. The results indicated the unfair offer rates of proposers are significantly related to the resting-state frontal-occipital and frontal-parietal connectivity in the delta band, as well as the network properties. And compared to the conservative decision group (low unfair offer rate), the risk decision group (high unfair offer rate) exhibited stronger resting-state long-range linkages. Finally, the established multivariable model did accurately predict the unfair offer rates of the proposers, along with a correlation coefficient of 0.466 between the actual and predicted behaviors. Significance . Together, these findings demonstrated that related resting-state frontal-occipital and frontal-parietal connectivity may serve as a dispositional indicator of the risky behaviors for the proposers and subsequently predict a highly complex decision-making behavior, which contributed to the development of artificial intelligence decision-making system with biological characteristics as well., (© 2023 IOP Publishing Ltd.)

Granger causality-based effective brain connectivity provides a powerful tool to probe the neural mechanism for information processing and the potential features for brain computer interfaces. However, in real applications, traditional Granger causality is prone to the influence of outliers, such as inevitable ocular artifacts, resulting in unreasonable brain linkages and the failure to decipher inherent cognition states. In this work, motivated by constructing the sparse causality brain networks under the strong physiological outlier noise conditions, we proposed a dual Laplacian Granger causality analysis (DLap-GCA) by imposing Laplacian distributions on both model parameters and residuals. In essence, the first Laplacian assumption on residuals will resist the influence of outliers in electroencephalogram (EEG) on causality inference, and the second Laplacian assumption on model parameters will sparsely characterize the intrinsic interactions among multiple brain regions. Through simulation study, we quantitatively verified its effectiveness in suppressing the influence of complex outliers, the stable capacity for model estimation, and sparse network inference. The application to motor-imagery (MI) EEG further reveals that our method can effectively capture the inherent hemispheric lateralization of MI tasks with sparse patterns even under strong noise conditions. The MI classification based on the network features derived from the proposed approach shows higher accuracy than other existing traditional approaches, which is attributed to the discriminative network structures being captured in a timely manner by DLap-GCA even under the single-trial online condition. Basically, these results consistently show its robustness to the influence of complex outliers and the capability of characterizing representative brain networks for cognition information processing, which has the potential to offer reliable network structures for both cognitive studies and future brain-computer interface (BCI) realization.

Human cognition is usually underpinned by intrinsic structure and functional neural co-activation in spatially distributed brain regions. Owing to lacking an effective approach to quantifying the covarying of structure and functional responses, how the structural-functional circuits interact and how genes encode the relationships, to deepen our knowledge of human cognition and disease, are still unclear. Here, we propose a multimodal covariance network (MCN) construction approach to capture interregional covarying of the structural skeleton and transient functional activities for a single individual. We further explored the potential association between brain-wide gene expression patterns and structural-functional covarying in individuals involved in a gambling task and individuals with major depression disorder (MDD), adopting multimodal data from a publicly available human brain transcriptomic atlas and 2 independent cohorts. MCN analysis showed a replicable cortical structural-functional fine map in healthy individuals, and the expression of cognition- and disease phenotype-related genes was found to be spatially correlated with the corresponding MCN differences. Further analysis of cell type-specific signature genes suggests that the excitatory and inhibitory neuron transcriptomic changes could account for most of the observed correlation with task-evoked MCN differences. In contrast, changes in MCN of MDD patients were enriched for biological processes related to synapse function and neuroinflammation in astrocytes, microglia, and neurons, suggesting its promising application in developing targeted therapies for MDD patients. Collectively, these findings confirmed the correlations of MCN-related differences with brain-wide gene expression patterns, which captured genetically validated structural-functional differences at the cellular level in specific cognitive processes and psychiatric patients., (Copyright © 2023 Lin Jiang et al.)

Cool executive dysfunction is a crucial feature in people living with schizophrenia which is related to cognition impairment and the severity of the clinical symptoms. Based on electroencephalogram (EEG), our current study explored the change of brain network under the cool executive tasks in individuals living with schizophrenia before and after atypical antipsychotic treatment (before&#95;TR vs. after&#95;TR). 21 patients with schizophrenia and 24 healthy controls completed the cool executive tasks, involving the Tower of Hanoi Task (THT) and Trail-Marking Test A-B (TMT A-B). The results of this study uncovered that the reaction time of the after&#95;TR group was much shorter than that of the before&#95;TR group in the TMT-A and TMT-B. And the after&#95;TR group showed fewer error numbers in the TMT-B than those of the before&#95;TR group. Concerning the functional network, stronger DMN-like linkages were found in the before&#95;TR group compared to the control group. Finally, we adopted a multiple linear regression model based on the change network properties to predict the patient's PANSS change ratio. Together, the findings deepened our understanding of cool executive function in individuals living with schizophrenia and might provide physiological information to reliably predict the clinical efficacy of schizophrenia after atypical antipsychotic treatment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Si, Liu, Kou, Dong, Zhang, Wang, Lu, Luo, Ni, Du and Zhang.)

Multichannel electroencephalogram (EEG) is an array signal that represents brain neural networks and can be applied to characterize information propagation patterns for different emotional states. To reveal these inherent spatial graph features and increase the stability of emotion recognition, we propose an effective emotion recognition model that performs multicategory emotion recognition with multiple emotion-related spatial network topology patterns (MESNPs) by learning discriminative graph topologies in EEG brain networks. To evaluate the performance of our proposed MESNP model, we conducted single-subject and multisubject four-class classification experiments on two public datasets, MAHNOB-HCI and DEAP. Compared with existing feature extraction methods, the MESNP model significantly enhances the multiclass emotional classification performance in the single-subject and multisubject conditions. To evaluate the online version of the proposed MESNP model, we designed an online emotion monitoring system. We recruited 14 participants to conduct the online emotion decoding experiments. The average online experimental accuracy of the 14 participants was 84.56%, indicating that our model can be applied in affective brain-computer interface (aBCI) systems. The offline and online experimental results demonstrate that the proposed MESNP model effectively captures discriminative graph topology patterns and significantly improves emotion classification performance. Moreover, the proposed MESNP model provides a new scheme for extracting features from strongly coupled array signals.

Frontotemporal dementia (FTD) is frequently misdiagnosed as Alzheimer's disease (AD) due to similar clinical symptoms. In this study, we constructed frequency-based multilayer resting-state electroencephalogram (EEG) networks and extracted representative network features to improve the differentiation between AD and FTD. When compared with healthy controls (HC), AD showed primarily stronger delta-alpha cross-couplings and weaker theta-sigma cross-couplings. Notably, when comparing the AD and FTD groups, we found that the AD exhibited stronger delta-alpha and delta-beta connectivity than the FTD. Thereafter, by extracting the representative network features and then applying these features in the classification between AD and FTD, an accuracy of 81.1% was achieved. Finally, a multivariable linear regressive model was built, based on the differential topologies, and then adopted to predict the scores of the Mini-Mental State Examination (MMSE) scale. Accordingly, the predicted and actual measured scores were indeed significantly correlated with each other ( r = 0.274, p = 0.036). These findings consistently suggest that frequency-based multilayer resting-state networks can be utilized for classifying AD and FTD and have potential applications for clinical diagnosis.

Wax coating is an important means to maintain fruit quality and extend fruit shelf life, especially for climacteric fruits, such as apples ( Malus domestica ). Here, we found that wax coating could inhibit ethylene production, chlorophyll degradation, and carotenoid synthesis, but the molecular mechanism remains unclear. The regulatory mechanism of wax coating on apple fruit ripening was determined by subjecting wax-treated apple fruits to transcriptome analysis. RNA-seq revealed that 1,137 and 1,398 genes were upregulated and downregulated, respectively. These differentially expressed genes (DEGs) were shown to be related to plant hormones, such as ethylene, auxin, abscisic acid, and gibberellin, as well as genes involved in chlorophyll degradation and carotenoid biosynthesis. Moreover, we found that some genes related to the wax synthesis process also showed differential expression after the wax coating treatment. Among the DEGs obtained from RNA-seq analysis, 15 were validated by quantitative RT-PCR, confirming the results from RNA-seq analysis. RNA-seq and qRT-PCR of pear ( Pyrus ussuriensis ) showed similar changes after wax treatment. Our data suggest that wax coating treatment inhibits fruit ripening through ethylene synthesis and signal transduction, chlorophyll metabolism, and carotenoid synthesis pathways and that waxing inhibits endogenous wax production. These results provide new insights into the inhibition of fruit ripening by wax coating., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Si, Lv, Li, Liu, Sun, Mu, Qiao, Bu, Yuan and Wang.)