Pengzhenrongella phosphoraccumulans sp. nov., isolated from high Arctic glacial till, and emended description of the genus Pengzhenrongella.

A yellow pigmented, Gram-stain-positive, motile, facultatively anaerobic and irregular rod-shaped bacteria (strain M0-14T) was isolated from a till sample collected from the foreland of a high Arctic glacier near the settlement of Ny-Ålesund in the Svalbard Archipelago, Norway. Phylogenetic analysis based on 16S rRNA gene sequence comparisons revealed that M0-14T formed a lineage within the family Cellulomonadaceae, suborder Micrococcineae. M0-14T represented a novel member of the genus Pengzhenrongella and had highest 16S rRNA gene sequence similarity to Pengzhenrongella sicca LRZ-2T (97.3 %). Growth occurred at 4-25 °C (optimum 4-18 °C), at pH 6.0-9.0 (optimum pH 7.0), and in the presence of 0-5 % (w/v) NaCl. The predominant menaquinone was MK-9(H4) and the major fatty acids were anteiso-C15 : 0, C16 : 0 and summed feature 3 (comprising C16 : 1ω7c and/or C16 : 1ω6c). The major polar lipids were phosphatidylglycerol, phosphatidylinositol mannosides, phosphatidylinositol, one undefined phospholipid and five undefined phosphoglycolipids. The cell-wall diamino acid was l-ornithine whereas rhamnose and mannose were the cell-wall sugars. Polyphosphate particles were found inside the cells of M0-14T. Polyphosphate kinase and polyphosphate-dependent glucokinase genes were detected during genomic sequencing of M0-14. In addition, the complete pstSCAB gene cluster and phnCDE synthesis genes, which are important for the uptake and transport of phosphorus in cells, were annotated in the genomic data. According to the genomic data, M0-14T has a metabolic pathway related to phosphorus accumulation. The DNA G+C content of the genomic DNA was 70.8 %. On the basis of its phylogenetic relationship, phenotypic properties and chemotaxonomic distinctiveness, strain M0-14T represents a novel species of the genus Pengzhenrongella, for which the name Pengzhenrongella phosphoraccumulans sp. nov. is proposed. The type strain is M0-14T (= CCTCC AB 2012967T = NRRL B-59105T).

A new species, Aster yaoshanensis (Asteracae, Astereae), from Guangxi (China), based on morphology and molecular phylogenetic data.

Aster yaoshanensis sp. nov., a new species of the family Asteraceae is here described and illustrated. The species is presently known only from rock crevices of mountain valleys in Dayaoshan National Nature Reserve, Guangxi autonomous region, China. Phylogenetic analyses based on ITS sequences and complete plastome data have shown that this new species is a member of genus Aster with high support. Morphologically, it mostly resembles A. jishouensis, but it can be easily distinguished from the latter by bract indumentum (glabrous except margin ciliate vs. villous especially on veins abaxially, glabrous adaxially) and color (green vs. purple), shorter corolla (3.2-3.5 mm vs. 4.5-5.3 mm), bract stalk (obvious, ca.1.2 mm vs. sessile), and different distribution (Guangxi vs. Hunan). The detailed description, distribution map, and photos are provided. This study further elucidates the species identification, phylogeny and characteristic evolution of Aster.

Impaired topology and connectivity of grey matter structural networks in major depressive disorder: evidence from a multi-site neuroimaging data-set.

BACKGROUND: Major depressive disorder (MDD) has been increasingly understood as a disruption of brain connectome. Investigating grey matter structural networks with a large sample size can provide valuable insights into the structural basis of network-level neuropathological underpinnings of MDD. AIMS: Using a multisite MRI data-set including nearly 2000 individuals, this study aimed to identify robust topology and connectivity abnormalities of grey matter structural network linked to MDD and relevant clinical phenotypes. METHOD: A total of 955 MDD patients and 1009 healthy controls were included from 23 sites. Individualised structural covariance networks (SCN) were established based on grey matter volume maps. Following data harmonisation, network topological metrics and focal connectivity were examined for group-level comparisons, individual-level classification performance and association with clinical ratings. Various validation strategies were applied to confirm the reliability of findings. RESULTS: Compared with healthy controls, MDD individuals exhibited increased global efficiency, abnormal regional centralities (i.e. thalamus, precentral gyrus, middle cingulate cortex and default mode network) and altered circuit connectivity (i.e. ventral attention network and frontoparietal network). First-episode drug-naive and recurrent patients exhibited different patterns of deficits in network topology and connectivity. In addition, the individual-level classification of topological metrics outperforms that of structural connectivity. The thalamus-insula connectivity was positively associated with the severity of depressive symptoms. CONCLUSIONS: Based on this high-powered data-set, we identified reliable patterns of impaired topology and connectivity of individualised SCN in MDD and relevant subtypes, which adds to the current understanding of neuropathology of MDD and might guide future development of diagnostic and therapeutic markers.

Effects of Supplementing Selenium-Enriched Cardamine violifolia to Laying Hens on Egg Quality and Yolk Antioxidant Capacity during Storage at 4 °C and 25 °C.

Oxidative stress occurs in the process of egg storage. Antioxidants as feed additives can enhance egg quality and extend the shelf life of eggs. Selenium-enriched Cardamine violifolia (SEC) has strongly antioxidant properties. The objective of this study was to assess the effects of dietary supplementation with SEC on egg quality and the yolk antioxidant capacity of eggs stored at 4 °C and 25 °C. Four hundred fifty 65-week-old, Roman hens that were similar in laying rate (90.79 ± 1.69%) and body weight (2.19 ± 0.23 kg) were divided into 5 groups. The birds were fed diets supplemented with 0 mg/kg selenium (Se) (CON), 0.3 mg/kg Se from sodium selenite (SS), 0.3 mg/kg Se from Se-enriched yeast (SEY), 0.3 mg/kg Se for selenium-enriched Cardamine violifolia (SEC) or 0.3 mg/kg Se from Se-enriched Cardamine violifolia and 0.3 mg/kg Se from Se-enriched yeast (SEC + SEY) for 8 weeks. The eggs were collected on the 8th week and were analyzed for egg quality and oxidative stability of yolk during storage at 4 °C or 25 °C for 0, 2, 4, or 6 weeks. Dietary SEC and SEC + SEY supplementation increased the Haugh unit (HU) and albumen foam stability in eggs stored at 4 °C and 25 °C (p < 0.05). SS and SEC supplementation increased the yolk index in eggs stored at 25 °C (p < 0.05). SEC or SEC + SEY slowed down an increase in albumen pH and gel firmness in eggs stored at 4 °C and 25 °C (p < 0.05). Moreover, SEC or SEC + SEY alleviated the increase in malonaldehyde (MDA), and the decrease in total antioxidant capacity (T-AOC) level and total superoxide dismutase (T-SOD) activity in yolks stored at 4 °C and 25 °C (p < 0.05). These results indicate that SEC mitigated egg quality loss and improved the antioxidant capacity of yolks during storage. SEC supplementation would be advantageous to extend the shelf life of eggs.

Transcriptional Patterns of Brain Structural Covariance Network Abnormalities Associated With Suicidal Thoughts and Behaviors in Major Depressive Disorder.

BACKGROUND: Although brain structural covariance network (SCN) abnormalities have been associated with suicidal thoughts and behaviors (STBs) in individuals with major depressive disorder (MDD), previous studies have reported inconsistent findings based on small sample sizes, and underlying transcriptional patterns remain poorly understood. METHODS: Using a multicenter magnetic resonance imaging dataset including 218 MDD patients with STBs, 230 MDD patients without STBs, and 263 healthy control participants, we established individualized SCNs based on regional morphometric measures and assessed network topological metrics using graph theoretical analysis. Machine learning methods were applied to explore and compare the diagnostic value of morphometric and topological features in identifying MDD and STBs at the individual level. Brainwide relationships between STBs-related connectomic alterations and gene expression were examined using partial least squares regression. RESULTS: Group comparisons revealed that SCN topological deficits associated with STBs were identified in the prefrontal, anterior cingulate, and lateral temporal cortices. Combining morphometric and topological features allowed for individual-level characterization of MDD and STBs. Topological features made a greater contribution to distinguishing between patients with and without STBs. STBs-related connectomic alterations were spatially correlated with the expression of genes enriched for cellular metabolism and synaptic signaling. CONCLUSIONS: These findings revealed robust brain structural deficits at the network level, highlighting the importance of SCN topological measures in characterizing individual suicidality and demonstrating its linkage to molecular function and cell types, providing novel insights into the neurobiological underpinnings and potential markers for prediction and prevention of suicide.

Disrupted small-world white matter networks in patients with major depression and recent suicide plans or attempts.

Suicide is a major concern for health, and depression is an established proximal risk factor for suicide. This study aimed to investigate white matter features associated with suicide. We constructed white matter structural networks by deterministic tractography via diffusion tensor imaging in 51 healthy controls, 47 depressed patients without suicide plans or attempts and 56 depressed patients with suicide plans or attempts. Then, graph theory analysis was used to measure global and nodal network properties. We found that local efficiency was decreased and path length was increased in suicidal depressed patients compared to healthy controls and non-suicidal depressed patients; moreover, the clustering coefficient was decreased in depressed patients compared to healthy controls; and the global efficiency and normalized characteristic path length was increased in suicidal depressed patients compared to healthy controls. Similarly, compared with those in non-suicidal depressed patients, nodal efficiency in the thalamus, caudate, medial orbitofrontal cortex, hippocampus, olfactory cortex, supplementary motor area and Rolandic operculum was decreased. In summary, compared with those of non-suicidal depressed patients, the structural connectome of suicidal depressed patients exhibited weakened integration and segregation and decreased nodal efficiency in the fronto-limbic-basal ganglia-thalamic circuitry. These alterations in the structural networks of depressed suicidal brains provide insights into the underlying neurobiology of brain features associated with suicide.

A new species of Odorrana Fei, Ye & Huang, 1990 (Amphibia, Anura, Ranidae) from central Guangxi, China with a discussion of the taxonomy of Odorrana (Bamburana).

A new species of odorous frog, Odorranadamingshanensissp. nov., was found at the Damingshan National Nature Reserve in Guangxi, China. This species can be distinguished from its congeners by a combination of the following characters: medium body size (SVL 52.3-54.8 mm in males and 74.8-81.2 mm in females), sawtooth spinules on the upper lip, obtusely rounded snout that extends beyond the lower margin, distinct dorsolateral folds, horny tubercles on the rear of the back, presence of outer metatarsal tubercles, dilated nuptial pad with velvety spinules, distinct maxillary gland with tiny spines, and external lateral vocal sac. Through analysis of the 16S mitochondria gene, the new species is closely related to O.nasica and O.yentuensis, but the genetic divergence between the new species and the latter exceeds 7% (uncorrected p-distance). Currently, the new species is only known from its original discovery site. Furthermore, a discussion on the taxonomy of Odorrana (Bamburana) was conducted, identifying seven species within the subgenus Odorrana (Bamburana).

Aberrant brain network topology in youth with a familial risk for bipolar disorder: a task-based fMRI connectome study.

BACKGROUND: Youth with a family history of bipolar disorder (BD) may be at increased risk for mood disorders and for developing side effects after antidepressant exposure. The neurobiological basis of these risks remains poorly understood. We aimed to identify biomarkers underlying risk by characterizing abnormalities in the brain connectome of symptomatic youth at familial risk for BD. METHODS: Depressed and/or anxious youth (n = 119, age = 14.9 ± 1.6 years) with a family history of BD but no prior antidepressant exposure and typically developing controls (n = 57, age = 14.8 ± 1.7 years) received functional magnetic resonance imaging (fMRI) during an emotional continuous performance task. A generalized psychophysiological interaction (gPPI) analysis was performed to compare their brain connectome patterns, followed by machine learning of topological metrics. RESULTS: High-risk youth showed weaker connectivity patterns that were mainly located in the default mode network (DMN) (network weight = 50.1%) relative to controls, and connectivity patterns derived from the visual network (VN) constituted the largest proportion of aberrant stronger pairs (network weight = 54.9%). Global local efficiency (Elocal , p = .022) and clustering coefficient (Cp , p = .029) and nodal metrics of the right superior frontal gyrus (SFG) (Elocal : p < .001; Cp : p = .001) in the high-risk group were significantly higher than those in healthy subjects, and similar patterns were also found in the left insula (degree: p = .004; betweenness: p = .005; age-by-group interaction, p = .038) and right hippocampus (degree: p = .003; betweenness: p = .003). The case-control classifier achieved a cross-validation accuracy of 78.4%. CONCLUSIONS: Our findings of abnormal connectome organization in the DMN and VN may advance mechanistic understanding of risk for BD. Neuroimaging biomarkers of increased network segregation in the SFG and altered topological centrality in the insula and hippocampus in broader limbic systems may be used to target interventions tailored to mitigate the underlying risk of brain abnormalities in these at-risk youth.

Multivariate patterns of brain functional connectome associated with COVID-19-related negative affect symptoms.

Severe mental health problems with the representation of negative affect symptoms (NAS) have been increasingly reported during the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to explore the multivariate patterns of brain functional connectome predicting COVID-19-related NAS. This cohort study encompassed a group of university students to undergo neuroimaging scans before the pandemic, and we re-contacted participants for 1-year follow-up COVID-related NAS evaluations during the pandemic. Regularized canonical correlation analysis was used to identify connectome-based dimensions of NAS to compute pairs of canonical variates. The predictive ability of identified functional connectome to NAS dimensional scores was examined with a nested cross-validation. Two dimensions (i.e. mode stress and mode anxiety) were related to distinct patterns of brain functional connectome (r2 = 0.911, PFDR = 0.048; r2 = 0.901, PFDR = 0.037, respectively). Mode anxiety was characterized by high loadings in connectivity between affective network (AFN) and visual network (VN), while connectivity of the default mode network with dorsal attention network (DAN) were remarkably prominent in mode stress. Connectivity patterns within the DAN and between DAN and VN, ventral attention network, and AFN was common for both dimensions. The identified functional connectome can reliably predict mode stress (r = 0.37, MAE = 5.1, p < 0.001) and mode anxiety (r = 0.28, MAE = 5.4, p = 0.005) in the cross-validation. Our findings provide new insight into multivariate dimensions of COVID-related NAS, which may have implications for developing network-based biomarkers in psychological interventions for vulnerable individuals in the pandemic.

Differential cortical gray matter changes in early- and late-onset patients with amyotrophic lateral sclerosis.

Age at onset may be an important feature associated with distinct subtypes of amyotrophic lateral sclerosis (ALS). Little is known about the neuropathological mechanism of early-onset ALS (EO-ALS) and late-onset ALS (LO-ALS). Ninety ALS patients were divided into EO-ALS and LO-ALS group, and 128 healthy controls were matched into young controls(YCs) and old controls (OCs). A voxel-based morphometry approach was employed to investigate differences in gray matter volume (GMV). Significant age at onset-by-diagnosis interactions were found in the left parietal operculum, left precentral gyrus, bilateral postcentral gyrus, right occipital gyrus, and right orbitofrontal cortex. Post hoc analysis revealed a significant decrease in GMV in all affected regions of EO-ALS patients compared with YCs, with increased GMV in 5 of the 6 brain regions, except for the right orbitofrontal cortex, in LO-ALS patients compared with OCs. LO-ALS patients had a significantly increased GMV than EO-ALS patients after removing the aging effect. Correspondingly, GMV of the left postcentral gyrus correlated with disease severity in the 2 ALS groups. Our findings suggested that the pathological mechanisms in ALS patients with different ages at onset might differ. These findings provide unique insight into the clinical and biological heterogeneity of the 2 ALS subtypes.

Multilayer analysis of dynamic network reconfiguration in pediatric posttraumatic stress disorder.

Neuroimage studies have reported functional connectome abnormalities in posttraumatic stress disorder (PTSD), especially in adults. However, these studies often treated the brain as a static network, and time-variance of connectome topology in pediatric posttraumatic stress disorder remain unclear. To explore case-control differences in dynamic connectome topology, resting-state functional magnetic resonance imaging data were acquired from 24 treatment-naïve non-comorbid pediatric posttraumatic stress disorder patients and 24 demographically matched trauma-exposed non-posttraumatic stress disorder controls. A graph-theoretic analysis was applied to construct time-varying modular structure of whole-brain networks by maximizing the multilayer modularity. Network switching rate at the global, subnetwork, and nodal levels were calculated and compared between posttraumatic stress disorder and trauma-exposed non-posttraumatic stress disorder groups, and their associations with posttraumatic stress disorder symptom severity and sex interactions were explored. At the global level, individuals with posttraumatic stress disorder exhibited significantly lower network switching rates compared to trauma-exposed non-posttraumatic stress disorder controls. This difference was mainly involved in default-mode and dorsal attention subnetworks, as well as in inferior temporal and parietal brain nodes. Posttraumatic stress disorder symptom severity was negatively correlated with switching rate in the global network and default mode network. No significant differences were observed in the interaction between diagnosis and sex/age. Pediatric posttraumatic stress disorder is associated with dynamic reconfiguration of brain networks, which may provide insights into the biological basis of this disorder.

Effects of PRRT2 mutation on brain gray matter networks in paroxysmal kinesigenic dyskinesia.

Although proline-rich transmembrane protein 2 is the primary causative gene of paroxysmal kinesigenic dyskinesia, its effects on the brain structure of paroxysmal kinesigenic dyskinesia patients are not yet clear. Here, we explored the influence of proline-rich transmembrane protein 2 mutations on similarity-based gray matter morphological networks in individuals with paroxysmal kinesigenic dyskinesia. A total of 51 paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 mutations, 55 paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 non-mutation, and 80 healthy controls participated in the study. We analyzed the structural connectome characteristics across groups by graph theory approaches. Relative to paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 non-mutation and healthy controls, paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 mutations exhibited a notable increase in characteristic path length and a reduction in both global and local efficiency. Relative to healthy controls, both patient groups showed reduced nodal metrics in right postcentral gyrus, right angular, and bilateral thalamus; Relative to healthy controls and paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 non-mutation, paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 mutations showed almost all reduced nodal centralities and structural connections in cortico-basal ganglia-thalamo-cortical circuit including bilateral supplementary motor area, bilateral pallidum, and right caudate nucleus. Finally, we used support vector machine by gray matter network matrices to classify paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 mutations and paroxysmal kinesigenic dyskinesia patients possessing proline-rich transmembrane protein 2 non-mutation, achieving an accuracy of 73%. These results show that proline-rich transmembrane protein 2 related gray matter network deficits may contribute to paroxysmal kinesigenic dyskinesia, offering new insights into its pathophysiological mechanisms.

Common and distinct neural correlates of emotional processing in individuals at familial risk for major depressive disorder and bipolar disorder: A comparative meta-analysis.

Individuals at familial risk for mood disorders exhibit deficits in emotional processing and associated brain dysfunction prior to illness onset. However, such brain-behavior abnormalities related to familial predisposition remain poorly understood. To investigate robust abnormal functional activation patterns during emotional processing in unaffected at-risk relatives of patients with major depressive disorder (UAR-MDD) and bipolar disorder (UAR-BD), we performed a meta-analysis of task-based functional magnetic resonance imaging studies using Seed-based d Mapping (SDM) toolbox. Common and distinct patterns of abnormal functional activation between UAR-MDD and UAR-BD were detected via conjunction and differential analyses. A total of 17 studies comparing 481 UAR and 670 healthy controls (HC) were included. Compared with HC, UAR-MDD exhibited hyperactivation in the parahippocampal gyrus, amygdala and cerebellum, while UAR-BD exhibited parahippocampal hyperactivation and hypoactivation in the striatum and middle occipital gyrus (MOG). Conjunction analysis revealed shared hyperactivated PHG in both groups. Differential analysis indicated that the activation patterns of amygdala and MOG significantly differed between UAR-MDD and UAR-BD. These findings provide novel insights into common and distinct neural phenotypes for familial risk and associated risk mechanisms in MDD and BD, which may have implications in guiding precise prevention strategies tailored to the family context.

Shared and Distinct Neurobiological Bases of Bipolar Disorder and Attention-Deficit/Hyperactivity Disorder in Children and Adolescents: A Comparative Meta-analysis of Structural Abnormalities.

OBJECTIVE: Pediatric bipolar disorder (PBD) and attention-deficit/hyperactivity disorder (ADHD) frequently co-occur and share dysfunctions in affective and cognitive domains. As the neural substrates underlying their overlapping and dissociable symptomatology have not been well delineated, a meta-analysis of whole-brain voxel-based morphometry studies in PBD and ADHD was conducted. METHOD: A systematic literature search was performed in PubMed, Web of Science, and Embase. The seed-based d mapping toolbox was used to identify altered clusters of PBD or ADHD and obtain their conjunctive and comparative abnormalities. Suprathreshold patterns were subjected to large-scale network analysis to identify affected brain networks. RESULTS: The search revealed 10 PBD studies (268 patients) and 32 ADHD studies (1,333 patients). Decreased gray matter volumes in the right insula and anterior cingulate cortex relative to typically developing individuals were conjunctive in PBD and ADHD. Reduced volumes in the right inferior frontal gyrus, left orbitofrontal cortex, and hippocampus were more substantial in PBD, while decreased volumes in the left precentral gyrus, left inferior frontal gyrus, and right superior frontal gyrus were more pronounced in ADHD. Neurodevelopmental effects modulated patterns of the left hippocampus in PBD and those of the left inferior frontal gyrus in ADHD. CONCLUSION: These findings suggest that PBD and ADHD are characterized by both common and distinct patterns of gray matter volume alterations. Their overlapping abnormalities may represent a transdiagnostic problem of attention and emotion regulation shared by PBD and ADHD, whereas the disorder-differentiating substrates may contribute to the relative differences in cognitive and affective features that define the 2 disorders. STUDY PREREGISTRATION INFORMATION: Structural Brain Abnormalities of Attention-Deficit/Hyperactivity Disorder and Bipolar Disorder in Children/Adolescents: An Overlapping Meta-analysis; https://osf.io/trg4m.

Prediction of the mean transit time using machine learning models based on radiomics features from digital subtraction angiography in moyamoya disease or moyamoya syndrome-a development and validation model study.

Background: Digital subtraction angiography (DSA) is an important technique for diagnosis of moyamoya disease (MMD) or moyamoya syndrome (MMS), and computed tomography perfusion (CTP) is essential for assessing intracranial blood supply. The aim of this study was to assess whether radiomics features based on images of DSA could predict the mean transit time (MTT; outcome of CTP) using machine learning models. Methods: The DSA images and MTT values of adult patients with MMD or MMS, according to the diagnostic guidelines for MMD, as well as control cases, were retrospectively collected in the Guangdong Provincial People's Hospital between January 2018 and December 2020. A total of 93 features were extracted from the images of each case through 3-dimensional (3D) slicer. After features preprocessing and filtering, 3-4 features were selected by the least absolute shrinkage and selection operator (LASSO) regression algorithm. Prediction models were established using random forest (RF) and support vector machine (SVM) for MTT values. Single-factor receiver operating characteristic (ROC) curve analysis and partial-dependence (PD) profiles were conducted to investigate selected features and prediction models. Results: Our results showed that prediction models based on RF models had the best performance in frontal lobe {area under the curve (AUC) [95% confidence interval (CI)] =1.000 (1.000-1.000)], parietal lobe [AUC (95% CI) =1.000 (1.000-1.000)], and basal ganglia/thalamus [AUC (95% CI) =0.922 (0.797-1.000)] in the test set, whereas the SVM model performed the best in the temporal lobe [AUC (95% CI) =0.962 (0.876-1.000)] in the test set. The AUC values in the test set were greater than 0.9. The PD profiles showed good robustness and consistency. Conclusions: Prediction models based on radiomics features extracted from DSA images demonstrate excellent performance in predicting MTT in patients with MMD or MMS, which may provide guidance for future clinical practice.

Cortical and subcortical structural differences in psychostimulant-free ADHD youth with and without a family history of bipolar I disorder: a cross-sectional morphometric comparison.

Although attention-deficit/hyperactivity disorder (ADHD) and a family history of bipolar I disorder (BD) are associated with increased risk for developing BD, their neuroanatomical substrates remain poorly understood. This study compared cortical and subcortical gray matter morphology in psychostimulant-free ADHD youth with and without a first-degree relative with BD and typically developing healthy controls. ADHD youth (ages 10-18 years) with ('high-risk', HR) or without ('low-risk', LR) a first-degree relative with BD and healthy comparison youth (HC) were enrolled. High-resolution 3D T1-weighted images were acquired using a Philips 3.0 T MR scanner. The FreeSurfer image analysis suite was used to measure cortical thickness, surface area, and subcortical volumes. A general linear model evaluated group differences in MRI features with age and sex as covariates, and exploratory correlational analyses evaluated associations with symptom ratings. A total of n = 142 youth (mean age: 14.16 ± 2.54 years, 35.9% female) were included in the analysis (HC, n = 48; LR, n = 49; HR, n = 45). The HR group exhibited a more severe symptom profile, including higher mania and dysregulation scores, compared to the LR group. For subcortical volumes, the HR group exhibited smaller bilateral thalamic, hippocampal, and left caudate nucleus volumes compared to both LR and HC, and smaller right caudate nucleus compared with LR. No differences were found between LR and HC groups. For cortical surface area, the HR group exhibited lower parietal and temporal surface area compared with HC and LR, and lower orbitofrontal and superior frontal surface area compared to LR. The HR group exhibited lower left anterior cingulate surface area compared with HC. LR participants exhibited greater right pars opercularis surface area compared with the HC. Some cortical alterations correlated with symptom severity ratings. These findings suggest that ADHD in youth with a BD family history is associated with a more a severe symptom profile and a neuroanatomical phenotype that distinguishes it from ADHD without a BD family history.

Brain network structural connectome abnormalities among youth with attention-deficit/hyperactivity disorder at varying risk for bipolar I disorder: a cross-sectional graph-based magnetic resonance imaging study.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) is highly prevalent among youth with or at familial risk for bipolar-I disorder (BD-I), and ADHD symptoms commonly precede and may increase the risk for BD-I; however, associated neuropathophysiological mechanisms are not known. In this cross-sectional study, we sought to investigate brain structural network topology among youth with ADHD, with and without familial risk of BD-I. METHODS: We recruited 3 groups of psychostimulant-free youth (aged 10-18 yr), namely youth with ADHD and at least 1 biological parent or sibling with BD-I (high-risk group), youth with ADHD who did not have a first- or second-degree relative with a mood or psychotic disorder (low-risk group) and healthy controls. We used graph-based network analysis of structural magnetic resonance imaging data to investigate topological properties of brain networks. We also evaluated relationships between topological metrics and mood and ADHD symptom ratings. RESULTS: A total of 149 youth were included in the analysis (49 healthy controls, 50 low-risk youth, 50 high-risk youth). Low-risk and high-risk ADHD groups exhibited similar differences from healthy controls, mainly in the default mode network and central executive network. We found topological alterations in the salience network of the high-risk group, relative to both low-risk and control groups. We found significant abnormalities in global network properties in the high-risk group only, compared with healthy controls. Among both low-risk and high-risk ADHD groups, nodal metrics in the right triangular inferior frontal gyrus correlated positively with ADHD total and hyperactivity/impulsivity subscale scores. LIMITATIONS: The cross-sectional design of this study could not determine the relevance of these findings to BD-I risk progression. CONCLUSION: Youth with ADHD, with and without familial risk for BD-I, exhibit common regional abnormalities in the brain connectome compared with healthy youth, whereas alterations in the salience network distinguish these groups and may represent a prodromal feature relevant to BD-I risk.

Time-feature attention-based convolutional auto-encoder for flight feature extraction.

Quick Access Recorders (QARs) provide an important data source for Flight Operation Quality Assurance (FOQA) and flight safety. It is generally characterized by large volume, high-dimensionality and high frequency, and these features result in extreme complexities and uncertainties in its usage and comprehension. In this study, we proposed a Time-Feature Attention (TFA)-based Convolutional Auto-Encoder (TFA-CAE) network model to extract essential flight features from QAR data. As a case study, we used the QAR data landing at the Kunming Changshui International Airport and Lhasa Gonggar International Airport as the experimental data. The results show that (1) the TFA-CAE model performs the best in extracting representative flight features in comparison to some traditional or similar approaches, such as Principal Component Analysis (PCA), Convolutional Auto-Encoder (CAE), Self-Attention-based CAE (SA-CAE), Gate Recurrent Unit based Auto-Encoder (GRU-AE) and TFA-GRU-AE models; (2) flight patterns corresponding to different runways can be recognized; and (3) anomalous flights can effectively deviate from many observations. Overall, the TFA-CAE model provides a well-established technique for further usage of QAR data, such as flight risk detection or FOQA.

Effects of different types of xanthophyll extracted from marigold on pigmentation of yellow-feathered chickens.

OBJECTIVE: This study aimed to explore the effects of different types of xanthophyll extracted from marigold on the growth performance, skin color, and carcass pigmentation. METHODS: A total of 192 healthy 60-day-old yellow-feathered broilers weighing an average of 1,279±81 g were randomly allocated to 4 groups, each with 6 replicates and 8 broilers. The 4 treatments were as follows: i) CON group, fed with basal diet; ii) LTN group, supplemented with lutein; iii) MDP group, supplemented with monohydroxyl pigment including dehydrated lutein, ß-cryptoxanthin, and α-cryptoxanthin; iv) LTN+MDP group, supplemented with lutein and monohydroxyl pigment in proportion to 1:1. The supplementary content of LTN, MDP, and LTN+MDP was 2 g/kg. Skin color was measured after 7, 14, 21, and 28 days of feeding the dietary treatments. The breast, thigh, and abdominal fat of slaughtered chickens were stored in cold storage at 4°C for 24 hours and then the meat color of lightness (L*), redness (a*), and yellowness (b*) values was determined. RESULTS: The results showed that all treatments enhanced the yellow scores of subwing skin on day 14, 21, and 28 (p<0.05), and the mixture of lutein and monohydroxyl pigment promoted the yellow scores of shanks on day 14, 21, and 28 (p<0.05). The mixture of lutein and monohydroxyl pigment increased the yellow scores of beaks and all treatments enhanced the yellow of shanks on day 28 (p<0.05). In addition, all treatments improved the yellow (b*) values of breast and thigh muscle, moreover, the monohydroxyl pigment and the mixture of lutein and monohydroxyl pigment enhanced the values of redness (a*) and yellow (b*) of abdominal fat (p<0.05). CONCLUSION: In summary, different types of xanthophyll extracted from marigold significantly increased the yellow scores of skin color and the yellow (b*) values of carcass pigmentation. Especially, the mixture of lutein and monohydroxyl pigment was more efficient on skin color.