High-fat diet (HFD) usually induces oxidative stress and astaxanthin is regarded as an excellent anti-oxidant. An 8-week feeding trial was conducted to investigate the effects of dietary astaxanthin ...supplementation on growth performance, lipid metabolism, antioxidant ability, and immune response of juvenile largemouth bass (
) fed HFD. Four diets were formulated: the control diet (10.87% lipid, C), high-fat diet (18.08% lipid, HF), and HF diet supplemented with 75 and 150 mg kg
astaxanthin (HFA1 and HFA2, respectively). Dietary supplementation of astaxanthin improved the growth of fish fed HFD, also decreased hepatosomatic index and intraperitoneal fat ratio of fish fed HFD, while having no effect on body fat. Malondialdehyde content and superoxide dismutase activity were increased in fish fed HFD, astaxanthin supplementation in HFD decreased the oxidative stress of fish. The supplementation of astaxanthin in HFD also reduced the mRNA levels of
,
,
, and
. These results suggested that dietary astaxanthin supplementation in HFD improved the growth performance, antioxidant ability and immune response of largemouth bass.
It has been suggested that resting-state functional magnetic resonance imaging (RS-fMRI) is a promising tool to study the relation between spontaneous brain activity and behavioral performance. ...However, little is known about whether the local synchronization of spontaneous brain activity could predict response inhibition. In the current study, we used regional homogeneity (ReHo) to measure the local synchronization of RS-fMRI signals, and then investigated the relationship between ReHo and individual differences in response inhibition, as evaluated by the stop signal reaction time (SSRT) in a Stop signal task. The results showed that ReHo of RS-fMRI signals could successfully predict SSRT. Specifically, positive ReHo-SSRT correlations were observed in the bilateral inferior frontal cortex (IFC) and three critical components of the default mode network (DMN), and negative ReHo-SSRT correlations were observed in the rolandic area/posterior insula and the bilateral middle occipital cortex. The present results indicate the possible influence of the IFC and rolandic area/posterior insula on the efficiency of response inhibition, and demonstrate the importance of the DMN for the efficiency of cognitive task performance.
► Individual variation in inhibition was analyzed based on resting fMRI (RS-fMRI). ► Inhibition abilities were evaluated by the stop signal reaction time (SSRT). ► The spontaneous activity was evaluated by regional homogeneity (ReHo) of RS-fMRI. ► Significant ReHo-SSRT relationships were found in the IFC and default mode network. ► The IFC and default mode network may influence the efficiency of inhibition.
is the essential source of bisbenzylisoquinoline alkaloids (BIAs), making it a highly valued raw material in traditional Chinese medicine. The plant's root secondary metabolism is intricately linked ...to the microbial communities that surround it. However, the root-associated microbiomes of
, as well as the potential correlation between its bioactive compounds and these microbiomes, remain poorly understood. Here, the metabolic profiles of root, rhizosphere, and bulk soils of
revealed the dramatic differences in the relative content of plant-specialized metabolites. A total of 31, 21, and 0 specialized metabolites in
were identified in the root, rhizosphere soil, and bulk soil, respectively, with higher content of the seven major BIAs observed in the rhizosphere compared with that in the bulk soils. The composition of the bulk and rhizosphere microbiomes was noticeably distinct from that of the endospheric microbiome. The phylum Cyanobacteria accounted for over 60% of the root endosphere communities, and the α-diversity in root was the lowest. Targeted seven BIAs, namely, berberine, palmatine, magnocurarine, phellodendrine, jatrorrhizine, tetrahydropalmatine, and magnoflorine, were significantly positively correlated with Nectriaceae and Sphingobacteriaceae. This study has illuminated the intricate interaction networks between
root-associated microorganisms and their key chemical compounds, providing the theoretical foundation for discovering biological fertilizers and laying the groundwork for cultivating high-quality medicinal plants.
Despite numerous studies on the microstructural changes of the human brain throughout life, we have indeed little direct knowledge about the changes from early to mid-adulthood. The aim of this study ...was to investigate the microstructural changes of the human brain from early to mid-adulthood. We performed two sets of analyses based on the diffusion tensor imaging (DTI) data of 111 adults aged 18-55 years. Specifically, we first correlated age with skeletonized fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) at global and regional level, and then estimated individuals' ages based on each DTI metric using elastic net, a kind of multivariate pattern analysis (MVPA) method that aims at selecting the model that achieves the best trade-off between goodness of fit and model complexity. We observed statistically significant negative age-vs-FA correlations and relatively less changes of MD. The negative age-vs-FA correlations were associated with negative age-vs-AD and positive age-vs-RD correlations. Regional negative age-vs-FA correlations were observed in the bilateral genu of the corpus callosum (CCg), the corticospinal tract (CST), the fornix and several other tracts, and these negative correlations may indicate the earlier changes of the fibers with aging. In brain age estimation, the chronological-vs-estimated-age correlations based on FA, MD, AD and RD were
= 0.62, 0.44, 0.63 and 0.69 (
= 0.002, 0.008, 0.002 and 0.002 based on 500 permutations), respectively, and these results indicate that even the microstructural changes from early to mid-adulthood
are sufficiently specific to decode individuals' ages. Overall, the current results not only demonstrated statistically significant FA decreases from early to mid-adulthood and clarified the driving factors of the FA decreases (RD increases and AD decreases, in contrast to increases of both measures in late-adulthood), but highlighted the necessity of considering age effects in related studies.
Recent functional imaging studies have indicated that the pathophysiology of Alzheimer’s disease (AD) can be associated with the changes in spontaneous low-frequency (<0.08 Hz) blood oxygenation ...level-dependent fluctuations (LFBF) measured during a resting state. The purpose of this study was to examine regional LFBF coherence patterns in early AD and the impact of regional brain atrophy on the functional results. Both structural MRI and resting-state functional MRI scans were collected from 14 AD subjects and 14 age-matched normal controls. We found significant regional coherence decreases in the posterior cingulate cortex/precuneus (PCC/PCu) in the AD patients when compared with the normal controls. Moreover, the decrease in the PCC/PCu coherence was correlated with the disease progression measured by the Mini-Mental State Exam scores. The changes in LFBF in the PCC/PCu may be related to the resting hypometabolism in this region commonly detected in previous positron emission tomography studies of early AD. When the regional PCC/PCu atrophy was controlled, these results still remained significant but with a decrease in the statistical power, suggesting that the LFBF results are at least partly explained by the regional atrophy. In addition, we also found increased LFBF coherence in the bilateral cuneus, right lingual gyrus and left fusiform gyrus in the AD patients. These regions are consistent with previous findings of AD-related increased activation during cognitive tasks explained in terms of a compensatory-recruitment hypothesis. Finally, our study indicated that regional brain atrophy could be an important consideration in functional imaging studies of neurodegenerative diseases.
It has been a popular trend to decode individuals’ demographic and cognitive variables based on MRI. Features extracted from MRI data are usually of high dimensionality, and dimensionality reduction ...(DR) is an effective way to deal with these high-dimensional features. Despite many supervised DR techniques for
classification
purposes, there is still a lack of supervised DR techniques for
regression
purposes. In this study, we advanced a novel supervised DR technique for regression purposes, namely, supervised multidimensional scaling (SMDS). The implementation of SMDS includes two steps: (1) evaluating pairwise distances among entities based on their labels and constructing a new space through a distance-preserving projection; (2) establishing an explicit linear relationship between the feature space and the new space. Based on this linear relationship, DR for test entities can be performed. We evaluated the performance of SMDS first on a synthetic dataset, and the results indicate that (1) SMDS is relatively robust to Gaussian noise existing in the features and labels; (2) the dimensionality of the new space exerts negligible influences upon SMDS; and (3) when the sample size is small, the performance of SMDS deteriorates with the increase of feature dimension. When applied to features extracted from resting state fMRI data for individual age predictions, SMDS was observed to outperform classic DR techniques, including principal component analysis, locally linear embedding and multidimensional scaling (MDS). Hopefully, SMDS can be widely used in studies on MRI-based predictions. Furthermore, novel supervised DR techniques for regression purposes can easily be developed by replacing MDS with other nonlinear DR techniques.
Movie fMRI has emerged as a powerful tool for investigating human brain function, and functional connectivity (FC) plays a predominant role in fMRI-based studies. Accordingly, movie-watching FC may ...have great potential for future studies on human brain function. Before wide application of movie-watching FC, however, it is essential to evaluate how much it is influenced by differences in movies. The main aim of this study was to investigate the consistency of movie-watching FC across different movies. For this purpose, we performed three sets of analyses on the four movie fMRI runs (with different movie stimuli) included in the HCP dataset. The first set was performed to evaluate the agreement of movie-watching FC in exact values using intra-class correlation (ICC), and the ICC of movie-watching FC across different movies (0.37 on average) was found to be comparable to that of resting-state FC across repeated scans. The second set was performed to evaluate the agreement of movie-watching FC in connectivity patterns, and the results indicate that individuals could be identified with relatively high accuracies (94%-99%) across different movies based on their FC matrices. The final set was performed to test the generalizability of predictive models based on movie-watching FC, as this generalizability is highly dependent on the consistency of the FC. The results indicate that predictive models trained based on FC extracted from one movie fMRI run can make good predictions on FC extracted from runs with different movie stimuli. Taken together, our findings indicate that movie-watching FC is highly consistent across different movies, and conclusions drawn based on movie-watching FC are generalizable.
An 8-week feeding trial was conducted to investigate the effects of dietary mannan oligosaccharide (MOS) on growth performance, gut morphology, and NH3 stress tolerance of Pacific white shrimp ...Litopenaeus vannamei. Juvenile Pacific white shrimp (1080 individuals with initial weight of 2.52 ± 0.01 g) were fed either control diet without MOS or one of five dietary MOS (1.0, 2.0, 4.0, 6.0 and 8.0 g kg−1) diets. After the 8-week feeding trial, growth parameters, immune parameters, intestinal microvilli length and resistance against NH3 stress were assessed. Weight gain (WG) and specific growth rate (SGR) were significantly higher (P < 0.05) in shrimp fed 2.0, 4.0, 6.0 and 8.0 g kg−1 MOS-supplemented diets than shrimp fed control diet. WG and SGR of shrimp fed 2.0 g kg−1 MOS-supplemented diet was the highest (P < 0.05) in all experimental groups. Survival rate (SR) of shrimp was generally similar (P > 0.05) in all experimental groups. Compared with control group, TEM analysis revealed that 2.0, 4.0, 6.0 and 8.0 g kg−1 MOS supplementation could significantly increase (P < 0.05) the intestinal microvilli length of shrimp at the ultrastructural level. After NH3 stress for 24 h, SR of shrimp fed 2.0, 4.0, 6.0 and 8.0 g kg−1 MOS-supplemented diets was significantly higher (P < 0.05) than that of shrimp fed control diet. Phenoloxidase (PO) activity of 4.0 g kg−1 MOS-supplemented group was significantly higher (P < 0.05) than that of control group under normal conditions and NH3 stress. PO activity significantly decreased (P < 0.05) under NH3 stress than under normal conditions. Superoxide dismutase (SOD) activity of 4.0, 6.0 and 8.0 g kg−1 MOS-supplemented groups was significantly higher (P < 0.05) than that of control group under normal conditions. After NH3 stress for 24 h, SOD activity of all experimental groups also significantly decreased (P < 0.05) compared to normal conditions. These results clearly indicated that dietary MOS could improve growth performance and increase the resistance against NH3 stress in L. vannamei, and the 2.0–4.0 g kg−1 MOS supplementation was suitable for L. vannamei.
► MOS supplementation significantly enhanced the weight gain and specific growth rate of Litopenaeus vannamei. ► Dietary MOS significantly increased the intestinal microvilli length of L. vannamei. ► Dietary MOS significantly increased the activities of phenoloxidase and superoxide dismutase in haemolymph L. vannamei. ► Dietary MOS significantly enhanced the resistance against NH3 stress in L. vannamei.
Estimation of individuals' cognitive, behavioral and demographic (CBD) variables based on MRI has attracted much research interest in the past decade, and effective machine learning techniques are of ...great importance for these estimations. Partial least squares regression (PLSR) is an attractive machine learning technique that can accommodate both single- and multi-label learning in a simple framework, while its potential for MRI-based estimations of CBD variables remains to be explored. In this study, we systemically investigated the performance of PLSR in MRI-based estimations of individuals' CBD variables, especially its performance in simultaneous estimation of multiple CBD variables (multi-label learning). We performed the study on the dataset included in the HCP S1200 release. Resting state functional connections (RSFCs) were used as features, and a total of 10 CBD variables (e.g., age, gender, grip strength, and picture vocabulary) were estimated. The results showed that PLSR performed well in both single- and multi-label learning. In fact, the present estimations were better than those reported in literatures, as indicated by stronger correlations between the estimated and actual CBD variables, as well as high gender classification accuracy (97.8% in this study). Moreover, the RSFCs that contributed to the estimations exhibited strong correlations with the CBD variable estimated, that is, PLSR algorithm automatically selected the RSFCs closely related to one CBD variable to establish predictive models for the variable. Besides, the estimation accuracies based on RSFCs among 100, 200, and 300 regions of interest (ROIs) were higher than those based on RSFCs among 15, 25, and 50 ROIs; the estimation accuracies based on RSFCs evaluated using partial correlation were higher than those based on RSFCs evaluated using full correlation. In addition to the aforementioned virtues, PLSR is efficient in model training and testing, and it is simple and easy to use. Therefore, PLSR can be a favorable choice for future MRI-based estimations of CBD variables.
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