BnaABF3 and BnaMYB44 regulate the transcription of zeaxanthin epoxidase genes in carotenoid and abscisic acid biosynthesis.

Zeaxanthin epoxidase (ZEP) is a key enzyme that catalyzes the conversion of zeaxanthin to violaxanthin in the carotenoid and abscisic acid (ABA) biosynthesis pathways. The rapeseed (Brassica napus) genome has 4 ZEP (BnaZEP) copies that are suspected to have undergone subfunctionalization, yet the 4 genes' underlying regulatory mechanisms remain unknown. Here, we genetically confirmed the functional divergence of the gene pairs BnaA09.ZEP/BnaC09.ZEP and BnaA07.ZEP/BnaC07.ZEP, which encode enzymes with tissue-specific roles in carotenoid and ABA biosynthesis in flowers and leaves, respectively. Molecular and transgenic experiments demonstrated that each BnaZEP pair is transcriptionally regulated via ABA-responsive element-binding factor 3 s (BnaABF3s) and BnaMYB44s as common and specific regulators, respectively. BnaABF3s directly bound to the promoters of all 4 BnaZEPs and activated their transcription, with overexpression of individual BnaABF3s inducing BnaZEP expression and ABA accumulation under drought stress. Conversely, loss of BnaABF3s function resulted in lower expression of several genes functioning in carotenoid and ABA metabolism and compromised drought tolerance. BnaMYB44s specifically targeted and repressed the expression of BnaA09.ZEP/BnaC09.ZEP but not BnaA07.ZEP/BnaC07.ZEP. Overexpression of BnaA07.MYB44 resulted in increased carotenoid content and an altered carotenoid profile in petals. Additionally, RNA-seq analysis indicated that BnaMYB44s functions as a repressor in phenylpropanoid and flavonoid biosynthesis. These findings provide clear evidence for the subfunctionalization of duplicated genes and contribute to our understanding of the complex regulatory network involved in carotenoid and ABA biosynthesis in B. napus.

Resting-state EEG dynamic functional connectivity distinguishes non-psychotic major depression, psychotic major depression and schizophrenia.

This study aims to identify dynamic patterns within the spatiotemporal feature space that are specific to nonpsychotic major depression (NPMD), psychotic major depression (PMD), and schizophrenia (SCZ). The study also evaluates the effectiveness of machine learning algorithms based on these network manifestations in differentiating individuals with NPMD, PMD, and SCZ. A total of 579 participants were recruited, including 152 patients with NPMD, 45 patients with PMD, 185 patients with SCZ, and 197 healthy controls (HCs). A dynamic functional connectivity (DFC) approach was employed to estimate the principal FC states within each diagnostic group. Incremental proportions of data (ranging from 10% to 100%) within each diagnostic group were used for variability testing. DFC metrics, such as proportion, mean duration, and transition number, were examined among the four diagnostic groups to identify disease-related neural activity patterns. These patterns were then used to train a two-layer classifier for the four groups (HC, NPMD, PMD, and SCZ). The four principal brain states (i.e., states 1,2,3, and 4) identified by the DFC approach were highly representative within and across diagnostic groups. Between-group comparisons revealed significant differences in network metrics of state 2 and state 3, within delta, theta, and gamma frequency bands, between healthy individuals and patients in each diagnostic group (p < 0.01, FDR corrected). Moreover, the identified key dynamic network metrics achieved an accuracy of 73.1 ± 2.8% in the four-way classification of HC, NPMD, PMD, and SCZ, outperforming the static functional connectivity (SFC) approach (p < 0.001). These findings suggest that the proposed DFC approach can identify dynamic network biomarkers at the single-subject level. These biomarkers have the potential to accurately differentiate individual subjects among various diagnostic groups of psychiatric disorders or healthy controls. This work may contribute to the development of a valuable EEG-based diagnostic tool with enhanced accuracy and assistive capabilities.

The control patterns of affective processing and cognitive reappraisal: insights from brain controllability analysis.

Perceiving and modulating emotions is vital for cognitive function and is often impaired in neuropsychiatric conditions. Current tools for evaluating emotional dysregulation suffer from subjectivity and lack of precision, especially when it comes to understanding emotion from a regulatory or control-based perspective. To address these limitations, this study leverages an advanced methodology known as functional brain controllability analysis. We simultaneously recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data from 17 healthy subjects engaged in emotion processing and regulation tasks. We then employed a novel EEG/fMRI integration technique to reconstruct cortical activity in a high spatiotemporal resolution manner. Subsequently, we conducted functional brain controllability analysis to explore the neural network control patterns underlying different emotion conditions. Our findings demonstrated that the dorsolateral and ventrolateral prefrontal cortex exhibited increased controllability during the processing and regulation of negative emotions compared to processing of neutral emotion. Besides, the anterior cingulate cortex was notably more active in managing negative emotion than in either controlling neutral emotion or regulating negative emotion. Finally, the posterior parietal cortex emerged as a central network controller for the regulation of negative emotion. This study offers valuable insights into the cortical control mechanisms that support emotion perception and regulation.

Divergent electroencephalogram resting-state functional network alterations in subgroups of autism spectrum disorder: a symptom-based clustering analysis.

Autism spectrum disorder (ASD) is characterized by etiological and phenotypic heterogeneity. Despite efforts to categorize ASD into subtypes, research on specific functional connectivity changes within ASD subgroups based on clinical presentations is limited. This study proposed a symptom-based clustering approach to identify subgroups of ASD based on multiple clinical rating scales and investigate their distinct Electroencephalogram (EEG) functional connectivity patterns. Eyes-opened resting-state EEG data were collected from 72 children with ASD and 63 typically developing (TD) children. A data-driven clustering approach based on Social Responsiveness Scales-Second Edition and Vinland-3 scores was used to identify subgroups. EEG functional connectivity and topological characteristics in four frequency bands were assessed. Two subgroups were identified: mild ASD (mASD, n = 37) and severe ASD (sASD, n = 35). Compared to TD, mASD showed increased functional connectivity in the beta band, while sASD exhibited decreased connectivity in the alpha band. Significant between-group differences in global and regional topological abnormalities were found in both alpha and beta bands. The proposed symptom-based clustering approach revealed the divergent functional connectivity patterns in the ASD subgroups that was not observed in typical ASD studies. Our study thus provides a new perspective to address the heterogeneity in ASD research.

Virtual (Zoom) Interactions Alter Conversational Behavior and Interbrain Coherence.

A growing number of social interactions are taking place virtually on videoconferencing platforms. Here, we explore potential effects of virtual interactions on observed behavior, subjective experience, and neural "single-brain" and "interbrain" activity via functional near-infrared spectroscopy neuroimaging. We scanned a total of 36 human dyads (72 participants, 36 males, 36 females) who engaged in three naturalistic tasks (i.e., problem-solving, creative-innovation, socio-emotional task) in either an in-person or virtual (Zoom) condition. We also coded cooperative behavior from audio recordings. We observed reduced conversational turn-taking behavior during the virtual condition. Given that conversational turn-taking was associated with other metrics of positive social interaction (e.g., subjective cooperation and task performance), this measure may be an indicator of prosocial interaction. In addition, we observed altered patterns of averaged and dynamic interbrain coherence in virtual interactions. Interbrain coherence patterns that were characteristic of the virtual condition were associated with reduced conversational turn-taking. These insights can inform the design and engineering of the next generation of videoconferencing technology.SIGNIFICANCE STATEMENT Videoconferencing has become an integral part of our lives. Whether this technology impacts behavior and neurobiology is not well understood. We explored potential effects of virtual interaction on social behavior, brain activity, and interbrain coupling. We found that virtual interactions were characterized by patterns of interbrain coupling that were negatively implicated in cooperation. Our findings are consistent with the perspective that videoconferencing technology adversely affects individuals and dyads during social interaction. As virtual interactions become even more necessary, improving the design of videoconferencing technology will be crucial for supporting effective communication.

Multimodal investigation of dynamic brain network alterations in autism spectrum disorder: Linking connectivity dynamics to symptoms and developmental trajectories.

BACKGROUND: Autism spectrum disorder (ASD) has been associated with disrupted brain connectivity, yet a comprehensive understanding of the dynamic neural underpinnings remains lacking. This study employed concurrent electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) techniques to investigate dynamic functional connectivity (dFC) patterns and neurovascular characteristics in children with ASD. We also explored associations between neurovascular characteristics and the developmental trajectory of adaptive behavior in individuals with ASD. METHODS: Resting-state EEG and fNIRS data were simultaneously recorded from 58 ASD and 63 TD children. We implemented a k-means clustering approach to extract the dFC states for each modality. In addition, a multimodal covariance network (MCN) was constructed from the EEG and fNIRS dFC features to capture the neurovascular characteristics linked to ASD. RESULTS: EEG analyses revealed atypical properties of dFC states in the beta and gamma bands in children with ASD compared to TD children. For fNIRS, the ASD group exhibited atypical properties of dFC states such as duration and transitions relative to the TD group. The MCN analysis revealed significantly suppressed functional covariance between right superior temporal and left Broca's areas, alongside enhanced right dorsolateral prefrontal-left Broca covariance in ASD. Notably, we found that early neurovascular characteristics can predict the developmental progress of adaptive functioning in ASD. CONCLUSION: The multimodal investigation revealed distinct dFC patterns and neurovascular characteristics associated with ASD, elucidating potential neural mechanisms underlying core symptoms and their developmental trajectories. Our study highlights that integrating complementary neuroimaging modalities may aid in unraveling the complex neurobiology of ASD.

Kinase CIPK9 integrates glucose and abscisic acid signaling to regulate seed oil metabolism in rapeseed.

Rapeseed (Brassica napus), an important oil crop worldwide, provides large amounts of lipids for human requirements. Calcineurin B-like (CBL)-interacting protein kinase 9 (CIPK9) was reported to regulate seed oil content in the plant. Here, we generated gene-silenced lines through RNA interference biotechnology and loss-of-function mutant bnacipk9 using CRISPR/Cas9 to further study BnaCIPK9 functions in the seed oil metabolism of rapeseeds. We discovered that compared with wild-type (WT) lines, gene-silenced and bnacipk9 lines had substantially different oil contents and fatty acid compositions: seed oil content was improved by 3%-5% and 1%-6% in bnacipk9 lines and gene-silenced lines, respectively; both lines were with increased levels of monounsaturated fatty acids and decreased levels of polyunsaturated fatty acids. Additionally, hormone and glucose content analyses revealed that compared with WT lines the bnacipk9 lines showed significant differences: in bnacipk9 seeds, indoleacetic acid and abscisic acid (ABA) levels were higher; glucose and sucrose contents were higher with a higher hexose-to-sucrose ratio in bnacipk9 mid-to-late maturation development seeds. Furthermore, the bnacipk9 was less sensitive to glucose and ABA than the WT according to stomatal aperture regulation assays and the expression levels of genes involved in glucose and ABA regulating pathways in rapeseeds. Notably, in Arabidopsis (Arabidopsis thaliana), exogenous ABA and glucose imposed on developing seeds revealed the effects of ABA and glucose signaling on seed oil accumulation. Altogether, our results strongly suggest a role of CIPK9 in mediating the interaction between glucose flux and ABA hormone signaling to regulate seed oil metabolism in rapeseed.

Effects of radial extracorporeal shock wave therapy on flexor spasticity of the upper limb in post-stroke patients: A randomized controlled trial.

OBJECTIVE: This study aimed to assess the efficacy of radial extracorporeal shock wave therapy in treating upper limb spasticity after a stroke. DESIGN: Randomized controlled trial. SETTING: Zhujiang Hospital of Southern Medical University. SUBJECTS: This study included 95 people with stroke. INTERVENTION: The active (n = 47) and sham-placebo (n = 48) radial extracorporeal shockwave therapy groups received three treatment sessions (every third day). MAIN MEASURES: The Modified Ashworth Scale, Hmax/Mmax ratio, root mean square, co-contraction ratio, mechanical parameters of the muscle and temperature were measured at baseline and days 2, 5 and 8. RESULTS: Among the 135 potential participants screened, 100 were enrolled and allocated randomly, with 95 participants ultimately being included in the intent-to-treat analysis dataset. The active group showed significantly better improvements in upper limb spasticity and muscle function than did the sham-placebo group. Greater improvements in the Modified Ashworth Scale were observed in the active group than in the sham-placebo group (difference, -0.45; 95% CI, -0.69 to -0.22; P < 0.001). Moreover, significant differences in root mean square, co-contraction ratio and Hmax/Mmax ratio were observed between the two groups (all P < 0.001). The mechanical parameters of the biceps muscle were significantly better in the active group than in the sham-placebo group (P < 0.001). The active group had a higher temperature than the sham-placebo group, although the difference was not significant (P = 0.070). CONCLUSIONS: This study revealed that the treatment with extracorporeal shockwave therapy can relieve upper limb spasticity in people with stroke.

Associations between brain network, puberty, and behaviors in boys with Klinefelter syndrome.

BACKGROUND: Klinefelter syndrome (KS), also referred to as XXY syndrome, is a significant but inadequately studied risk factor for neuropsychiatric disability. Whether alterations in functional brain connectivity or pubertal delays are associated with aberrant cognitive-behavioral outcomes in individuals with KS is largely unknown. In this observational study, we investigated KS-related alterations in the resting-state brain network, testosterone level, and cognitive-behavioral impairment in adolescents with Klinefelter syndrome. METHODS: We recruited 46 boys with KS, ages 8 to 17 years, and 51 age-matched typically developing (TD) boys. All participants underwent resting-state functional magnetic resonance imaging scans, pubertal, and cognitive-behavioral assessments. Resting-state functional connectivity and regional brain activity of the participants were assessed. RESULTS: We found widespread alterations in global functional connectivity among the inferior frontal gyrus, temporal-parietal area, and hippocampus in boys with KS. Aberrant regional activities, including enhanced fALFF in the motor area and reduced ReHo in the caudate, were also found in the KS group compared to the TD children. Further, using machine learning methods, brain network alterations in these regions accurately differentiated boys with KS from TD controls. Finally, we showed that the alterations of brain network properties not only effectively predict cognitive-behavioral impairment in boys with KS, but also appear to mediate the association between total testosterone level and language ability, a cognitive domain at particular risk for dysfunction in this condition. CONCLUSION: Our results offer an informatic neurobiological foundation for understanding cognitive-behavioral impairments in individuals with KS and contribute to our understanding of the interplay between pubertal status, brain function, and cognitive-behavioral outcome in this population.

Xanthophyll esterases in association with fibrillins control the stable storage of carotenoids in yellow flowers of rapeseed (Brassica juncea).

Biosynthesis, stabilization, and storage of carotenoids are vital processes in plants that collectively contribute to the vibrant colors observed in flowers and fruits. Despite its importance, the carotenoid storage pathway remains poorly understood and lacks thorough characterization. We identified two homologous genes, BjA02.PC1 and BjB04.PC2, belonging to the esterase/lipase/thioesterase (ELT) family of acyltransferases. We showed that BjPCs in association with fibrillin gene BjFBN1b control the stable storage of carotenoids in yellow flowers of Brassica juncea. Through genetic, high-resolution mass spectrometry and transmission electron microscopy analyses, we demonstrated that both BjA02.PC1 and BjB04.PC2 can promote the accumulation of esterified xanthophylls, facilitating the formation of carotenoid-enriched plastoglobules (PGs) and ultimately producing yellow pigments in flowers. The elimination of BjPCs led to the redirection of metabolic flux from xanthophyll ester biosynthesis to lipid biosynthesis, resulting in white flowers for B. juncea. Moreover, we genetically verified the function of two fibrillin genes, BjA01.FBN1b and BjB05.FBN1b, in mediating PG formation and demonstrated that xanthophyll esters must be deposited in PGs for stable storage. These findings identified a previously unknown carotenoid storage pathway that is regulated by BjPCs and BjFBN1b, while offering unique opportunities for improving the stability, deposition, and bioavailability of carotenoids.

Aberrant brain network and eye gaze patterns during natural social interaction predict multi-domain social-cognitive behaviors in girls with fragile X syndrome.

Girls with fragile X syndrome (FXS) often manifest significant symptoms of avoidance, anxiety, and arousal, particularly in the context of social interaction. However, little is currently known about the associations among neurobiological, biobehavioral such as eye gaze pattern, and social-cognitive dysfunction in real-world settings. In this study, we sought to characterize brain network properties and eye gaze patterns in girls with FXS during natural social interaction. Participants included 42 girls with FXS and 31 age- and verbal IQ-matched girls (control). Portable functional near-infrared spectroscopy (fNIRS) and an eye gaze tracker were used to investigate brain network alterations and eye gaze patterns associated with social-cognitive dysfunction in girls with FXS during a structured face-to-face conversation. Compared to controls, girls with FXS showed significantly increased inter-regional functional connectivity and greater excitability within the prefrontal cortex (PFC), frontal eye field (FEF) and superior temporal gyrus (STG) during the conversation. Girls with FXS showed significantly less eye contact with their conversational partner and more unregulated eye gaze behavior compared to the control group. We also demonstrated that a machine learning approach based on multimodal data, including brain network properties and eye gaze patterns, was predictive of multiple domains of social-cognitive behaviors in girls with FXS. Our findings expand current knowledge of neural mechanisms and eye gaze behaviors underlying naturalistic social interaction in girls with FXS. These results could be further evaluated and developed as intermediate phenotypic endpoints for treatment trial evaluation in girls with FXS.

Social gaze behavior and hyperarousal in young females with fragile X syndrome: A within-person approach.

Children with fragile X syndrome (FXS) often avoid eye contact, a behavior that is potentially related to hyperarousal. Prior studies, however, have focused on between-person associations rather than coupling of within-person changes in gaze behaviors and arousal. In addition, there is debate about whether prompts to maintain eye contact are beneficial for individuals with FXS. In a study of young females (ages 6-16), we used eye tracking to assess gaze behavior and pupil dilation during social interactions in a group with FXS (n = 32) and a developmentally similar comparison group (n = 23). Participants engaged in semi-structured conversations with a female examiner during blocks with and without verbal prompts to maintain eye contact. We identified a social-behavioral and psychophysiological profile that is specific to females with FXS; this group exhibited lower mean levels of eye contact, significantly increased mean pupil dilation during conversations that included prompts to maintain eye contact, and showed stronger positive coupling between eye contact and pupil dilation. Our findings strengthen support for the perspective that gaze aversion in FXS reflects negative reinforcement of social avoidance behavior. We also found that behavioral skills training may improve eye contact, but maintaining eye contact appears to be physiologically taxing for females with FXS.

Concurrent fNIRS and EEG for Brain Function Investigation: A Systematic, Methodology-Focused Review.

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis, EEG has poor spatial resolution while presenting high temporal resolution. In contrast, fNIRS offers better spatial resolution, though it is constrained by its poor temporal resolution. One important merit shared by the EEG and fNIRS is that both modalities have favorable portability and could be integrated into a compatible experimental setup, providing a compelling ground for the development of a multimodal fNIRS-EEG integration analysis approach. Despite a growing number of studies using concurrent fNIRS-EEG designs reported in recent years, the methodological reference of past studies remains unclear. To fill this knowledge gap, this review critically summarizes the status of analysis methods currently used in concurrent fNIRS-EEG studies, providing an up-to-date overview and guideline for future projects to conduct concurrent fNIRS-EEG studies. A literature search was conducted using PubMed and Web of Science through 31 August 2021. After screening and qualification assessment, 92 studies involving concurrent fNIRS-EEG data recordings and analyses were included in the final methodological review. Specifically, three methodological categories of concurrent fNIRS-EEG data analyses, including EEG-informed fNIRS analyses, fNIRS-informed EEG analyses, and parallel fNIRS-EEG analyses, were identified and explained with detailed description. Finally, we highlighted current challenges and potential directions in concurrent fNIRS-EEG data analyses in future research.

Combined Transcriptomics and Metabolomics Analysis Reveals the Molecular Mechanism of Salt Tolerance of Huayouza 62, an Elite Cultivar in Rapeseed (Brassica napus L.).

Soil salinity is one of the most significant abiotic stresses affecting crop yield around the world. To explore the molecular mechanism of salt tolerance in rapeseed (Brassica napus L.), the transcriptome analysis and metabolomics analysis were used to dissect the differentially expressed genes and metabolites in two rapeseed varieties with significant differences in salt tolerance; one is an elite rapeseed cultivar, Huayouza 62. A total of 103 key differentially expressed metabolites (DEMs) and 53 key differentials expressed genes (DEGs) that might be related to salt stress were identified through metabolomics and transcriptomics analysis. GO and KEGG analysis revealed that the DEGs were mainly involved in ion transport, reactive oxygen scavenging, osmotic regulation substance synthesis, and macromolecular protein synthesis. The DEMs were involved in TCA cycle, proline metabolism, inositol metabolism, carbohydrate metabolic processes, and oxidation-reduction processes. In addition, overexpression of BnLTP3, which was one of the key DEGs, could increase tolerance to salt stress in Arabidopsis plants. This study reveals that the regulation mechanism of salt tolerance in rapeseed at the transcriptome and metabolism level and provides abundant data for further in-depth identification of essential salt tolerance genes.

Dynamic inter-brain synchrony in real-life inter-personal cooperation: A functional near-infrared spectroscopy hyperscanning study.

How two brains communicate with each other during social interaction is highly dynamic and complex. Multi-person (i.e., hyperscanning) studies to date have focused on analyzing the entire time series of brain signals to reveal an overall pattern of inter-brain synchrony (IBS). However, this approach does not account for the dynamic nature of social interaction. In the present study, we propose a data-driven approach based on sliding windows and k-mean clustering to capture the dynamic modulation of IBS patterns during interactive cooperation tasks. We used a portable functional near-infrared spectroscopy (fNIRS) system to measure brain hemodynamic response between interacting partners (20 dyads) engaged in a creative design task and a 3D model building task. Results indicated that inter-personal communication during naturalistic cooperation generally presented with a series of dynamic IBS states along the tasks. Compared to the model building task, the creative design task appeared to involve more complex and active IBS between multiple regions in specific dynamic IBS states. In summary, the proposed approach stands as a promising tool to distill complex inter-brain dynamics associated with social interaction into a set of representative brain states with more fine-grained temporal resolution. This approach holds promise for advancing our current understanding of the dynamic nature of neurocognitive processes underlying social interaction.

Analysis of measurement electrode location in bladder urine monitoring using electrical impedance.

PURPOSE: The aim of this study was to document more appropriate electrode location of a four-electrode-based electrical impedance technology in the monitoring of bladder filling, and to characterize the relationship between bladder filling duration and the measured electrical impedances. METHODS: A simulation study, based on a 2-dimension computational model, was conducted to determine the preferable locations of excitation and measurement electrodes in a conventional four-electrode setup. A human observation study was subsequently performed on eight healthy volunteers during natural bladder urine accumulation to validate the result of the simulation study. The correlation between the bladder filling time and the measured electrical impedance values was evaluated. RESULTS: The preferable location of measurement electrodes was successively validated by the model simulation study and human observation study. Result obtained via the selected electrodes location revealed a significant negative correlation (R = 0.916 ± 0.059, P < 0.001) between the measured electrical impedance and the urine accumulation time, which was consistent with the result of simulation study. CONCLUSIONS: The findings in this study not only documented the desirable electrodes location to monitor the process of bladder urine accumulation using four-electrode measurement, but also validated the feasibility of utilizing electrical impedance technique to monitor and estimate the bladder urine volume for those with urological disorders.

Fine-mapping and candidate gene analysis of the Brassica juncea white-flowered mutant Bjpc2 using the whole-genome resequencing.

Flower color in Brassica spp. is an important trait and considered a major visual signal for insect-pollinated plants. In previous study, we isolated and identified two genes (BjPC1 and BjPC2) that control the flower color in B. juncea, and mapped BjPC1 to a 0.13-cM region. In this study, we report the fine-mapping and candidate analysis of BjPC2. We conducted whole-genome resequencing, using bulked segregant analysis (BSA) to determine the BjPC2 candidate intervals. Crossing, allelism testing, and repeated full-sib mating were used to generate XG3, a near isogenic line (NIL) population that segregated on the BjPC2 locus. Through a genome-wide comparison of single nucleotide polymorphism (SNP) profiles between the yellow- and white-flowered bulks, a candidate interval for BjPC2 was identified on chromosome B04 (2.45 Mb). The BjPC2 linkage map was constructed with the newly developed simple sequence repeat (SSR) markers in the candidate interval to narrow the candidate BjPC2 region to 31-kb. Expression profiling and RNA-seq analysis partially confirmed that the AtPES2 homolog, BjuB027334 is the most promising candidate gene for BjPC2. Furthermore, analyses with high pressure liquid chromatography and transmission electron microscopy demonstrated that BjPC2 might be important in xanthophyll esterification, a process that limits xanthophyll degradation and increases sequestration. Overall, we mapped the BjPC2 to a 31-kb region on the B04 in B. juncea and identified BjuB027334 as a valuable candidate gene. Our results provide a basis for understanding the molecular mechanisms underlying the white-flowered trait and for molecular marker-assisted selection of flower color in B. juncea breeding.

Neurovascular Coupling Analysis Based on Multivariate Variational Gaussian Process Convergent Cross-Mapping.

Neurovascular coupling (NVC) provides important insights into the intricate activity of brain functioning and may aid in the early diagnosis of brain diseases. Emerging evidences have shown that NVC could be assessed by the coupling between electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). However, this endeavor presents significant challenges due to the absence of standardized methodologies and reliable techniques for coupling analysis of these two modalities. In this study, we introduced a novel method, i.e., the collaborative multi-output variational Gaussian process convergent cross-mapping (CMVGP-CCM) approach to advance coupling analysis of EEG and fNIRS. To validate the robustness and reliability of the CMVGP-CCM method, we conducted extensive experiments using chaotic time series models with varying noise levels, sequence lengths, and causal driving strengths. In addition, we employed the CMVGP-CCM method to explore the NVC between EEG and fNIRS signals collected from 26 healthy participants using a working memory (WM) task. Results revealed a significant causal effect of EEG signals, particularly the delta, theta, and alpha frequency bands, on the fNIRS signals during WM. This influence was notably observed in the frontal lobe, and its strength exhibited a decline as cognitive demands increased. This study illuminates the complex connections between brain electrical activity and cerebral blood flow, offering new insights into the underlying NVC mechanisms of WM.

Longitudinal Changes in Functional Neural Activation and Sensitization During Face Processing in Fragile X Syndrome.

BACKGROUND: Fragile X syndrome (FXS) is a genetic condition associated with increased risk for social anxiety and avoidance. Using functional near-infrared spectroscopy (fNIRS), we previously demonstrated aberrant neural activity responding to faces in young girls with FXS cross-sectionally. Here, we tested the hypothesis that abnormalities in neural activation and sensitization would increase with age in 65 girls with FXS (ages 6-16 years) relative to an age-matched control group of 52 girls who had comparable cognitive function and clinical symptoms. METHODS: fNIRS data were collected at 2 time points (mean [SD] = 2.8 [0.6] years apart) during a face processing task. Linear mixed-effect models examined longitudinal neural profiles in girls with FXS and control participants. Correlational analysis was performed to examine associations between neural sensitization (increasing neural response to repeated stimuli) and clinical ratings. RESULTS: In the FXS group, 24 participants had 1 fNIRS scan, and 32 had 2 scans. In the control group, 28 participants had 1 fNIRS scan, and 22 had 2 scans. Brain activations in the superior frontal gyrus were higher in girls with FXS than control participants at both time points. Neural sensitization also increased in girls with FXS at a higher rate than control participants in the superior frontal gyrus when responding to upright faces. For the FXS group, sensitization in the superior frontal gyrus positively correlated with longitudinal increases in anxiety and social avoidance scores. CONCLUSIONS: Girls with FXS show increasingly abnormal neural activation and sensitization responding to faces over time. Aberrant neural sensitization in girls with FXS is associated with longitudinal changes in anxiety and social skills.

Disentangling the impact of motion artifact correction algorithms on functional near-infrared spectroscopy-based brain network analysis.

Significance: Functional near-infrared spectroscopy (fNIRS) has been widely used to assess brain functional networks due to its superior ecological validity. Generally, fNIRS signals are sensitive to motion artifacts (MA), which can be removed by various MA correction algorithms. Yet, fNIRS signals may also undergo varying degrees of distortion due to MA correction, leading to notable alternation in functional connectivity (FC) analysis results. Aim: We aimed to investigate the effect of different MA correction algorithms on the performance of brain FC and topology analyses. Approach: We evaluated various MA correction algorithms on simulated and experimental datasets, including principal component analysis, spline interpolation, correlation-based signal improvement, Kalman filtering, wavelet filtering, and temporal derivative distribution repair (TDDR). The mean FC of each pre-defined network, receiver operating characteristic (ROC), and graph theory metrics were investigated to assess the performance of different algorithms. Results: Although most algorithms did not differ significantly from each other, the TDDR and wavelet filtering turned out to be the most effective methods for FC and topological analysis, as evidenced by their superior denoising ability, the best ROC, and an enhanced ability to recover the original FC pattern. Conclusions: The findings of our study elucidate the varying impact of MA correction algorithms on brain FC analysis, which could serve as a reference for choosing the most appropriate method for future FC research. As guidance, we recommend using TDDR or wavelet filtering to minimize the impact of MA correction in brain network analysis.