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Yue, G. H.

Publications and source records attributed to Yue, G. H..

4 recordsLinked to original sources

Chromosome-level Reference Genome Provides Insights into Divergence and Stress Adaptation of the African Oil Palm

The palm family (Arecaceae), consisting of [~] 2600 species, is the third most economically important family of plants. The African oil palm (Elaeis guineensis) is one of the most important palms. However, the genome sequences of palms available are still limited and fragmented. Here, we report a high-quality chromosome-level reference genome of an oil palm Dura. The genome of 1.7 Gb was assembled by integrating long reads with [~] 150 x genome coverage. The assembled genome covered 94.5% of the estimated genome size, within which 91.6% were assigned into 16 pseudochromosomes and 73.7% were repetitive sequences. Relying on the conserved synteny with oil palm, the existing draft genome sequences of both date palm and coconut were further assembled into chromosomal level. Transposon burst, particularly long terminal repeat retrotransposons (LTRs) retrotransposons, following the last whole-genome duplication (WGD), likely explains genome size variation across palms. Convergent evolution of fruit colors tends to eliminate the roles of the virescens gene in controlling accumulation of anthocyanins in exocarp of ripe fruit of palms. Recent duplications of high tandemly repeated pathogenesis-related proteins (PRs) from the same tandem arrays played an important role in defense responses to Ganoderma. Whole genome re-sequencing of both ancestral African and introduced oil palms in Southeast Asia revealed that genes under putative selection were notably associated with stress responses, suggesting adaptation to stresses in the new habitat. The genomic resources and insights gained in this study could be exploited for accelerating genetic improvement and understanding the evolution of palms.

genomics↗

Identifying the Neural Correlates of Balance Deficits in Traumatic Brain Injury using the Partial Least Squares Correlation (PLSC) analysis

BackgroundBalance impairment is one of the most debilitating consequences of Traumatic Brain Injury (TBI). To study the neurophysiological underpinnings of balance impairment, the brain functional connectivity during perturbation tasks can provide new insights. To better characterize the association between the task-relevant functional connectivity and the degree of balance deficits in TBI, the analysis needs to be performed on the data stratified based on the balance impairment. However, such stratification is not straightforward, and it warrants a data-driven approach. ApproachWe conducted a study to assess the balance control using a computerized posturography platform in 17 individuals with TBI and 15 age-matched healthy controls. We stratified the TBI participants into balance-impaired and non-impaired TBI using k -means clustering of either center of pressure (COP) displacement during a balance perturbation task or Berg Balance Scale (BBS) score as a functional outcome measure. We analyzed brain functional connectivity using the imaginary part of coherence across different cortical regions in various frequency bands. These connectivity features are then studied using the mean-centered partial least squares correlation (MC-PLSC) analysis, which is a multivariate statistical framework with the advantage of handling more features than the number of samples, thus making it suitable for a small-sample study. Main ResultsBased on the nonparametric significance testing using permutation and bootstrap procedure, we noticed that the theta-band connectivity strength in the following regions of interest significantly contributed to distinguishing balance impaired from non-impaired population, regardless of the type of strat-ification: left middle frontal gyrus, right paracentral lobule, precuneus, and bilateral middle occipital gyri. SignificanceIdentifying neural regions linked to balance impairment enhances our understanding of TBI-related balance dysfunction and could inform new treatment strategies. Future work will explore the impact of balance platform training on sensorimotor and visuomotor connectivity.

neuroscience↗

EEG-Based Spectral Analysis ShowingBrainwave Changes Related to ModulatingProgressive Fatigue During a ProlongedIntermittent Motor Task

Repeatedly performing a submaximal motor task for a prolonged period of time leads to muscle fatigue comprising a central and peripheral component, which demands a gradually increasing effort. However, the brain contribution to the enhancement of effort to cope with progressing fatigue lacks a complete understanding. The intermittent motor tasks (IMTs) closely resemble many activities of daily living (ADL), thus remaining physiologically relevant to study fatigue. The scope of this study is therefore to investigate the EEG-based brain activation patterns in healthy subjects performing IMT until self-perceived exhaustion. Fourteen participants (median age 51.5 years; age range 26-72 years; 5 males) repeated elbow flexion contractions at 40% maximum voluntary contraction by following visual cues displayed on an oscilloscope screen until subjective exhaustion. Each contraction lasted for approximately 5 s with a 2-s rest between trials. The force, EEG, and surface EMG (from elbow joint muscles) data were simultaneously collected. After preprocessing, we selected a subset of trials at the beginning, middle, and end of the study session representing brain activities germane to mild, moderate, and severe fatigue conditions, respectively, to compare and contrast the changes in the EEG time-frequency (TF) characteristics across the conditions. The outcome of channel- and source-level TF analyses reveals that the theta, alpha, and beta power spectral densities vary in proportion to fatigue levels in cortical motor areas. We observed a statistically significant change in the band-specific spectral power in relation to the graded fatigue from both the steady- and post-contraction EEG data. The findings would enhance our understanding on the etiology and physiology of voluntary motor-action-related fatigue and provide pointers to counteract the perception of muscle weakness and lack of motor endurance associated with ADL. The study outcome would help rationalize why certain patients experience exacerbated fatigue while carrying out mundane tasks, evaluate how clinical conditions such as neurological disorders and cancer treatment alter neural mechanisms underlying fatigue in future studies, and develop therapeutic strategies for restoring the patients ability to participate in ADL by mitigating the central and muscle fatigue.

neuroscience↗

Graph-theoretical Analysis of EEG Functional Connectivity during Balance Perturbation in Traumatic Brain Injury.

Traumatic Brain Injury (TBI) often results in balance impairment, increasing the risk of falls, and the chances of further injuries. However, the underlying neurophysiological mechanisms of postural control after TBI are not well understood. To this end, we conducted a pilot study with a multimodal approach of EEG, MRI, and Diffusion Tensor Imaging (DTI) to explore the neural mechanisms of unpredictable balance perturbations in 17 chronic TBI participants and 15 matched Healthy Controls (HC). As quantitative measures of the functional integration and segregation of the brain networks during the postural task, we computed the global graph-theoretic network measures (global efficiency and modularity) of brain functional connectivity derived from source-space EEG in different frequency bands. We observed that the TBI group showed a lower balance performance as measured by the Center of Pressure (COP) displacement during the task, and the Berg Balance Scale. They also showed altered brain activation and connectivity during the balance task. In particular, the task modulation of brain network segregation in alpha-band was reduced in TBI. Moreover, the DTI findings revealed that the structural damage is associated with reduced network connectivity and integration. In terms of the neural correlates, we observed a distinct role played by different frequency bands; greater theta-band modularity during the task was strongly correlated with the BBS in TBI group; alpha-band and beta-band graph-theoretic measures were associated with the measures of white matter structural integrity. Our future studies will focus on how postural training will modulate the functional brain networks in TBI.

neuroscience↗