Template-independent synthesis and 3'-end labelling of 2'-modified oligonucleotides with terminal deoxynucleotidyl transferases.

Xenobiotic nucleic acids (XNAs) are artificial genetic polymers with altered structural moieties and useful features, such as enhanced biological and chemical stability. Enzymatic synthesis and efficient labelling of XNAs are crucial for their broader application. Terminal deoxynucleotidyl transferases (TdTs) have been exploited for the de novo synthesis and labelling of DNA and demonstrated the capability of recognizing various substrates. However, the activities of TdTs for the synthesis and labelling of commonly used XNAs with 2' modifications have not been systematically explored. In this work, we explored and demonstrated the varied activities of three TdTs (bovine TdT, MTdT-evo and murine TdT) for the template-independent incorporation of 2'-methoxy NTPs, 2'-fluoro NTPs and 2'-fluoroarabino NTPs into the 3' ends of single- and double-stranded DNAs and the extension of 2'-modified XNAs with (d)NTPs containing a natural or unnatural nucleobase. Taking advantages of these activities, we established a strategy for protecting single-stranded DNAs from exonuclease I degradation by TdT-synthesized 2'-modified XNA tails and methods for 3'-end labelling of 2'-modified XNAs by TdT-mediated synthesis of G-quadruplex-containing tails or incorporation of nucleotides with a functionalized nucleobase. A DNA-2'-fluoroarabino nucleic acid (FANA) chimeric hydrogel was also successfully constructed based on the extraordinary activity of MTdT-evo for template-independent FANA synthesis.

Local-structure-preservation and redundancy-removal-based feature selection method and its application to the identification of biomarkers for schizophrenia.

Accurate diagnosis of mental disorders is expected to be achieved through the identification of reliable neuroimaging biomarkers with the help of cutting-edge feature selection techniques. However, existing feature selection methods often fall short in capturing the local structural characteristics among samples and effectively eliminating redundant features, resulting in inadequate performance in disorder prediction. To address this gap, we propose a novel supervised method named local-structure-preservation and redundancy-removal-based feature selection (LRFS), and then apply it to the identification of meaningful biomarkers for schizophrenia (SZ). LRFS method leverages graph-based regularization to preserve original sample similarity relationships during data transformation, thus retaining crucial local structure information. Additionally, it introduces redundancy-removal regularization based on interrelationships among features to exclude similar and redundant features from high-dimensional data. Moreover, LRFS method incorporates l2,1 sparse regularization that enables selecting a sparse and noise-robust feature subset. Experimental evaluations on eight public datasets with diverse properties demonstrate the superior performance of our method over nine popular feature selection methods in identifying discriminative features, with average classification accuracy gains ranging from 1.30 % to 9.11 %. Furthermore, the LRFS method demonstrates superior discriminability in four functional magnetic resonance imaging (fMRI) datasets from 708 healthy controls (HCs) and 537 SZ patients, with an average increase in classification accuracy ranging from 1.89 % to 9.24 % compared to other nine methods. Notably, our method reveals reproducible and significant changes in SZ patients relative to HCs across the four datasets, predominantly in the thalamus-related functional network connectivity, which exhibit a significant correlation with clinical symptoms. Convergence analysis, parameter sensitivity analysis, and ablation studies further demonstrate the effectiveness and robustness of our method. In short, our proposed feature selection method effectively identifies discriminative and reliable features that hold the potential to be biomarkers, paving the way for the elucidation of brain abnormalities and the advancement of precise diagnosis of mental disorders.

Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities.

A primary challenge to the data-driven analysis is the balance between poor generalizability of population-based research and characterizing more subject-, study- and population-specific variability. We previously introduced a fully automated spatially constrained independent component analysis (ICA) framework called NeuroMark and its functional MRI (fMRI) template. NeuroMark has been successfully applied in numerous studies, identifying brain markers reproducible across datasets and disorders. The first NeuroMark template was constructed based on young adult cohorts. We recently expanded on this initiative by creating a standardized normative multi-spatial-scale functional template using over 100,000 subjects, aiming to improve generalizability and comparability across studies involving diverse cohorts. While a unified template across the lifespan is desirable, a comprehensive investigation of the similarities and differences between components from different age populations might help systematically transform our understanding of the human brain by revealing the most well-replicated and variable network features throughout the lifespan. In this work, we introduced two significant expansions of NeuroMark templates first by generating replicable fMRI templates for infants, adolescents, and aging cohorts, and second by incorporating structural MRI (sMRI) and diffusion MRI (dMRI) modalities. Specifically, we built spatiotemporal fMRI templates based on 6,000 resting-state scans from four datasets. This is the first attempt to create robust ICA templates covering dynamic brain development across the lifespan. For the sMRI and dMRI data, we used two large publicly available datasets including more than 30,000 scans to build reliable templates. We employed a spatial similarity analysis to identify replicable templates and investigate the degree to which unique and similar patterns are reflective in different age populations. Our results suggest remarkably high similarity of the resulting adapted components, even across extreme age differences. With the new templates, the NeuroMark framework allows us to perform age-specific adaptations and to capture features adaptable to each modality, therefore facilitating biomarker identification across brain disorders. In sum, the present work demonstrates the generalizability of NeuroMark templates and suggests the potential of new templates to boost accuracy in mental health research and advance our understanding of lifespan and cross-modal alterations.

Common and unique brain aging patterns between females and males quantified by large-scale deep learning.

There has been extensive evidence that aging affects human brain function. However, there is no complete picture of what brain functional changes are mostly related to normal aging and how aging affects brain function similarly and differently between males and females. Based on resting-state brain functional connectivity (FC) of 25,582 healthy participants (13,373 females) aged 49-76 years from the UK Biobank project, we employ deep learning with explainable AI to discover primary FCs related to progressive aging and reveal similarity and difference between females and males in brain aging. Using a nested cross-validation scheme, we conduct 4200 deep learning models to classify all paired age groups on the main data for females and males separately and then extract gender-common and gender-specific aging-related FCs. Next, we validate those FCs using additional 21,000 classifiers on the independent data. Our results support that aging results in reduced brain functional interactions for both females and males, primarily relating to the positive connectivity within the same functional domain and the negative connectivity between different functional domains. Regions linked to cognitive control show the most significant age-related changes in both genders. Unique aging effects in males and females mainly involve the interaction between cognitive control and the default mode, vision, auditory, and frontoparietal domains. Results also indicate females exhibit faster brain functional changes than males. Overall, our study provides new evidence about common and unique patterns of brain aging in females and males.

GLUT1 promotes cell proliferation via binds and stabilizes phosphorylated EGFR in lung adenocarcinoma.

BACKGROUND: While previous studies have primarily focused on Glucose transporter type 1 (GLUT1) related glucose metabolism signaling, we aim to discover if GLUT1 promotes tumor progression through a non-metabolic pathway. METHODS: The RNA-seq and microarray data were comprehensively analyzed to evaluate the significance of GLUT1 expression in lung adenocarcinoma (LUAD). The cell proliferation, colony formation, invasion, and migration were used to test GLUT1 's oncogenic function. Co-immunoprecipitation and mass spectrum (MS) were used to uncover potential GLUT1 interacting proteins. RNA-seq, DIA-MS, western blot, and qRT-PCR to probe the change of gene and cell signaling pathways. RESULTS: We found that GLUT1 is highly expressed in LUAD, and higher expression is related to poor patient survival. GLUT1 knockdown caused a decrease in cell proliferation, colony formation, migration, invasion, and induced apoptosis in LUAD cells. Mechanistically, GLUT1 directly interacted with phosphor-epidermal growth factor receptor (p-EGFR) and prevented EGFR protein degradation via ubiquitin-mediated proteolysis. The GLUT1 inhibitor WZB117 can increase the sensitivity of LUAD cells to EGFR-tyrosine kinase inhibitors (TKIs) Gefitinib. CONCLUSIONS: GLUT1 expression is higher in LUAD and plays an oncogenic role in lung cancer progression. Combining GLUT1 inhibitors and EGFR-TKIs could be a potential therapeutic option for LUAD treatment.

Mediation of mitochondrial DNA copy number and oxidative stress in fluoride-related bone mineral density alteration in Chinese farmers.

Excessive fluoride can adversely affect bone mineral density (BMD). Oxidative stress and mitochondrial dysfunction are crucial mechanisms of health damage induced by fluoride. Here, a cross-sectional survey involving 907 Chinese farmers (aged 18-60) was carried out in Tongxu County in 2017, aiming to investigate the significance of mitochondrial DNA copy number (mtDNAcn) and oxidative stress in fluoride-related BMD change. Concentrations of urinary fluoride (UF), serum oxidative stress biomarkers, including total antioxidant capacity (T-AOC), total superoxide dismutase (T-SOD), glutathione peroxidase (GSH-Px), and malondialdehyde (MDA), as well as relative mtDNAcn in peripheral blood were determined. The multivariable linear model and mediation analysis were performed to assess associations between UF, oxidative stress, and relative mtDNAcn with BMD. Results showed that GSH-Px levels increased by 6.98 U/mL [95% confidence interval (CI) 3.41-10.56)] with each 1.0 mg/L increment of UF. After stratification, the T-AOC, relative mtDNAcn, and BMD decreased by 0.04 mmol/L (-0.08 ~ -0.01), 0.29-unit (-0.55 ~ -0.04), and 0.18-unit (-0.33 ~ -0.03) with every 1.0 mg/L elevation of UF in the excessive fluoride group (EFG, adults with UF > 1.6 mg/L), respectively. Furthermore, T-AOC and relative mtDNAcn were favorably related to the BMD in the EFG (ß = 0.82, 95%CI 0.16-1.48 for T-AOC; ß = 0.11, 95%CI 0.02-0.19 for relative mtDNAcn). Mediation analysis showed that relative mtDNAcn and T-AOC mediated 15.4% and 17.1% of the connection between excessive fluoride and reduced BMD, respectively. Findings suggested that excessive fluoride was related to lower BMD in adults, and the decrement of T-AOC and relative mtDNAcn partially mediate this relationship.

Pan-cancer analysis of G6PD carcinogenesis in human tumors.

Glucose-6-phosphate dehydrogenase (G6PD) is involved in the catalytic pentose phosphate pathway (PPP), which is closely related to energy metabolism. G6PD plays a crucial role in many types of cancer, but the specific molecular mechanisms of G6PD in cancer remain unclear. Therefore, we investigated the potential oncogenic role of G6PD in various tumors based on The Cancer Genome Atlas (TCGA), the cBioPortal datasets, the University of California Santa Cruz (UCSC) Xena browser, and the UALCAN-based online tool. G6PD was highly expressed in several cancer tissues (hepatocellular carcinoma, glioma, and breast cancer) compared with normal tissues and was significantly associated with poor prognosis of hepatocellular carcinoma, clear cell renal cell carcinoma, and breast cancer. Promoter methylation levels of G6PD were lower in Bladder Urothelial Carcinoma (BLCA) (P = 2.77e-02), breast invasive carcinoma (BRCA) (P = 1.62e-12), kidney renal clear cell carcinoma (KIRC) (P = 4.23e-02), kidney renal papillary cell carcinoma (KIRP) (P = 2.64e-03), liver hepatocellular carcinoma (LIHC) (P = 1.76e-02), stomach adenocarcinoma (STAD) (P = 3.50e-02), testicular germ cell tumors (TGCT) (P = 1.62e-12), higher in prostate adenocarcinoma (PRAD) (P = 1.81e-09), and uterine corpus endometrial carcinoma (UCEC) (P = 2.96e-04) compared with corresponding normal tissue samples. G6PD expression was positively correlated with the infiltration level of immune cells in most tumors, suggesting that G6PD may be involved in tumor immune infiltration. In addition, the functional mechanism of G6PD also involves 'Carbon metabolism', 'Glycolysis/Gluconeogenesis', 'Pentose phosphate pathway', and 'Central carbon pathway metabolism in cancer signaling pathway'. This pan-cancer study provides a relatively broad understanding of the oncogenic role of G6PD in various tumors and presents a theoretical basis for the development of G6PD inhibitors as therapeutic drugs for multiple cancers.

Developmental and aging resting functional magnetic resonance imaging brain state adaptations in adolescents and adults: A large N (>47K) study.

The brain's functional architecture and organization undergo continual development and modification throughout adolescence. While it is well known that multiple factors govern brain maturation, the constantly evolving patterns of time-resolved functional connectivity are still unclear and understudied. We systematically evaluated over 47,000 youth and adult brains to bridge this gap, highlighting replicable time-resolved developmental and aging functional brain patterns. The largest difference between the two life stages was captured in a brain state that indicated coherent strengthening and modularization of functional coupling within the auditory, visual, and motor subdomains, supplemented by anticorrelation with other subdomains in adults. This distinctive pattern, which we replicated in independent data, was consistently less modular or absent in children and presented a negative association with age in adults, thus indicating an overall inverted U-shaped trajectory. This indicates greater synchrony, strengthening, modularization, and integration of the brain's functional connections beyond adolescence, and gradual decline of this pattern during the healthy aging process. We also found evidence that the developmental changes may also bring along a departure from the canonical static functional connectivity pattern in favor of more efficient and modularized utilization of the vast brain interconnections. State-based statistical summary measures presented robust and significant group differences that also showed significant age-related associations. The findings reported in this article support the idea of gradual developmental and aging brain state adaptation processes in different phases of life and warrant future research via lifespan studies to further authenticate the projected time-resolved brain state trajectories.

Iron and copper: critical executioners of ferroptosis, cuproptosis and other forms of cell death.

Regulated cell death (RCD) is a regulable cell death that involves well-organized signaling cascades and molecular mechanisms. RCD is implicated in fundamental processes such as organ production and tissue remodeling, removing superfluous structures or cells, and regulating cell numbers. Previous studies have not been able to reveal the complete mechanisms, and novel methods of RCD are constantly being proposed. Two metal ions, iron (Fe) and copper (Cu) are essential factors leading to RCDs that not only induce ferroptosis and cuproptosis, respectively but also lead to cell impairment and eventually diverse cell death. This review summarizes the direct and indirect mechanisms by which Fe and Cu impede cell growth and the various forms of RCD mediated by these two metals. Moreover, we aimed to delineate the interrelationships between these RCDs with the distinct pathways of ferroptosis and cuproptosis, shedding light on the complex and intricate mechanisms that govern cellular survival and death. Finally, the prospects outlined in this review suggest a novel approach for investigating cell death, which may involve integrating current therapeutic strategies and offer a promising solution to overcome drug resistance in certain diseases. Video Abstract.

In Silico Analysis of Ferroptosis-Related Genes and Its Implication in Drug Prediction against Fluorosis.

Fluorosis is a serious global public health problem. Interestingly, so far, there is no specific drug treatment for the treatment of fluorosis. In this paper, the potential mechanisms of 35 ferroptosis-related genes in U87 glial cells exposed to fluoride were explored by bioinformatics methods. Significantly, these genes are involved in oxidative stress, ferroptosis, and decanoate CoA ligase activity. Ten pivotal genes were found by the Maximal Clique Centrality (MCC) algorithm. Furthermore, according to the Connectivity Map (CMap) and the Comparative Toxicogenomics Database (CTD), 10 possible drugs for fluorosis were predicted and screened, and a drug target ferroptosis-related gene network was constructed. Molecular docking was used to study the interaction between small molecule compounds and target proteins. Molecular dynamics (MD) simulation results show that the structure of the Celestrol-HMOX1 composite is stable and the docking effect is the best. In general, Celastrol and LDN-193189 may target ferroptosis-related genes to alleviate the symptoms of fluorosis, which may be effective candidate drugs for the treatment of fluorosis.

A new multimodality fusion classification approach to explore the uniqueness of schizophrenia and autism spectrum disorder.

Schizophrenia (SZ) and autism spectrum disorder (ASD) sharing overlapping symptoms have a long history of diagnostic confusion. It is unclear what their differences at a brain level are. Here, we propose a multimodality fusion classification approach to investigate their divergence in brain function and structure. Using brain functional network connectivity (FNC) calculated from resting-state fMRI data and gray matter volume (GMV) estimated from sMRI data, we classify the two disorders using the main data (335 SZ and 380 ASD patients) via an unbiased 10-fold cross-validation pipeline, and also validate the classification generalization ability on an independent cohort (120 SZ and 349 ASD patients). The classification accuracy reached up to 83.08% for the testing data and 72.10% for the independent data, significantly better than the results from using the single-modality features. The discriminative FNCs that were automatically selected primarily involved the sub-cortical, default mode, and visual domains. Interestingly, all discriminative FNCs relating to the default mode network showed an intermediate strength in healthy controls (HCs) between SZ and ASD patients. Their GMV differences were mainly driven by the frontal gyrus, temporal gyrus, and insula. Regarding these regions, the mean GMV of HC fell intermediate between that of SZ and ASD, and ASD showed the highest GMV. The middle frontal gyrus was associated with both functional and structural differences. In summary, our work reveals the unique neuroimaging characteristics of SZ and ASD that can achieve high and generalizable classification accuracy, supporting their potential as disorder-specific neural substrates of the two entwined disorders.

Privacy-preserving quality control of neuroimaging datasets in federated environments.

Privacy concerns for rare disease data, institutional or IRB policies, access to local computational or storage resources or download capabilities are among the reasons that may preclude analyses that pool data to a single site. A growing number of multisite projects and consortia were formed to function in the federated environment to conduct productive research under constraints of this kind. In this scenario, a quality control tool that visualizes decentralized data in its entirety via global aggregation of local computations is especially important, as it would allow the screening of samples that cannot be jointly evaluated otherwise. To solve this issue, we present two algorithms: decentralized data stochastic neighbor embedding, dSNE, and its differentially private counterpart, DP-dSNE. We leverage publicly available datasets to simultaneously map data samples located at different sites according to their similarities. Even though the data never leaves the individual sites, dSNE does not provide any formal privacy guarantees. To overcome that, we rely on differential privacy: a formal mathematical guarantee that protects individuals from being identified as contributors to a dataset. We implement DP-dSNE with AdaCliP, a method recently proposed to add less noise to the gradients per iteration. We introduce metrics for measuring the embedding quality and validate our algorithms on these metrics against their centralized counterpart on two toy datasets. Our validation on six multisite neuroimaging datasets shows promising results for the quality control tasks of visualization and outlier detection, highlighting the potential of our private, decentralized visualization approach.

Incorporation of Non-Canonical Amino Acids into Antimicrobial Peptides: Advances, Challenges, and Perspectives.

The emergence of antimicrobial resistance is a global health concern and calls for the development of novel antibiotic agents. Antimicrobial peptides seem to be promising candidates due to their diverse sources, mechanisms of action, and physicochemical characteristics, as well as the relatively low emergence of resistance. The incorporation of noncanonical amino acids into antimicrobial peptides could effectively improve their physicochemical and pharmacological diversity. Recently, various antimicrobial peptides variants with improved or novel properties have been produced by the incorporation of single and multiple distinct noncanonical amino acids. In this review, we summarize strategies for the incorporation of noncanonical amino acids into antimicrobial peptides, as well as their features and suitabilities. Recent applications of noncanonical amino acid incorporation into antimicrobial peptides are also presented. Finally, we discuss the related challenges and prospects.

Comparative Genomic Analysis of Vibrio cincinnatiensis Provides Insights into Genetic Diversity, Evolutionary Dynamics, and Pathogenic Traits of the Species.

Vibrio cincinnatiensis is a poorly understood pathogenic Vibrio species, and the underlying mechanisms of its genetic diversity, genomic plasticity, evolutionary dynamics, and pathogenicity have not yet been comprehensively investigated. Here, a comparative genomic analysis of V. cincinnatiensis was constructed. The open pan-genome with a flexible gene repertoire exhibited genetic diversity. The genomic plasticity and stability were characterized by the determinations of diverse mobile genetic elements (MGEs) and barriers to horizontal gene transfer (HGT), respectively. Evolutionary divergences were exhibited by the difference in functional enrichment and selective pressure between the different components of the pan-genome. The evolution on the Chr I and Chr II core genomes was mainly driven by purifying selection. Predicted essential genes in V. cincinnatiensis were mainly found in the core gene families on Chr I and were subject to stronger evolutionary constraints. We identified diverse virulence-related elements, including the gene clusters involved in encoding flagella, secretion systems, several pili, and scattered virulence genes. Our results indicated the pathogenic potential of V. cincinnatiensis and highlighted that HGT events from other Vibrio species promoted pathogenicity. This pan-genome study provides comprehensive insights into this poorly understood species from the genomic perspective.

Thermophilic Nucleic Acid Polymerases and Their Application in Xenobiology.

Thermophilic nucleic acid polymerases, isolated from organisms that thrive in extremely hot environments, possess great DNA/RNA synthesis activities under high temperatures. These enzymes play indispensable roles in central life activities involved in DNA replication and repair, as well as RNA transcription, and have already been widely used in bioengineering, biotechnology, and biomedicine. Xeno nucleic acids (XNAs), which are analogs of DNA/RNA with unnatural moieties, have been developed as new carriers of genetic information in the past decades, which contributed to the fast development of a field called xenobiology. The broad application of these XNA molecules in the production of novel drugs, materials, and catalysts greatly relies on the capability of enzymatic synthesis, reverse transcription, and amplification of them, which have been partially achieved with natural or artificially tailored thermophilic nucleic acid polymerases. In this review, we first systematically summarize representative thermophilic and hyperthermophilic polymerases that have been extensively studied and utilized, followed by the introduction of methods and approaches in the engineering of these polymerases for the efficient synthesis, reverse transcription, and amplification of XNAs. The application of XNAs facilitated by these polymerases and their mutants is then discussed. In the end, a perspective for the future direction of further development and application of unnatural nucleic acid polymerases is provided.

Role of Glycolysis/Gluconeogenesis and HIF-1 Signaling Pathways in Rats with Dental Fluorosis Integrated Proteomics and Metabolomics Analysis.

Fluoride is widely distributed, and excessive intake will lead to dental fluorosis. In this study, six offspring rats administrated 100 mg/L sodium fluoride were defined as the dental fluorosis group, and eight offspring rats who received pure water were defined as the control group. Differentially expressed proteins and metabolites extracted from peripheral blood were identified using the liquid chromatography tandem mass spectrometry and gas chromatography mass spectrometry, with the judgment criteria of fold change >1.2 or <0.83 and p < 0.05. A coexpression enrichment analysis using OmicsBean was conducted on the identified proteins and metabolites, and a false discovery rate (FDR) < 0.05 was considered significant. Human Protein Atlas was used to determine the subcellular distribution of hub proteins. The Gene Cards was used to verify results. A total of 123 up-regulated and 46 down-regulated proteins, and 12 up-regulated and 2 down-regulated metabolites were identified. The significant coexpression pathways were the HIF-1 (FDR = 1.86 × 10−3) and glycolysis/gluconeogenesis (FDR = 1.14 × 10−10). The results of validation analysis showed the proteins related to fluorine were mainly enriched in the cytoplasm and extrinsic component of the cytoplasmic side of the plasma membrane. The HIF-1 pathway (FDR = 1.01 × 10−7) was also identified. Therefore, the HIF-1 and glycolysis/gluconeogenesis pathways were significantly correlated with dental fluorosis.

[Clinical and genetic analysis of two rare male patients with Rett syndrome].

OBJECTIVE: To conduct clinical and genetic analysis of two male patients with atypical Rett syndrome. METHODS: Collection of clinical data in the two patients and these parents; whole exome sequencing (WES) was used to detect the potential variants, which were verified by Sanger sequencing. X chromosome inactivation (XCI) detection is performed in the Patient 1's mother to detect the allelic expression difference of the MECP2 gene. RESULTS: Patient 1, a 5-year and 10-month-old boy, had mental disorders and mild intellectual disability (ID) (IQ: 54), whose mother had ID. Patient 2 was a 9-month and 18-day-old male presented with recurrent infections, respiratory insufficiency, hypotonia and global developmental delay. WES indentified a hemizygous mutation, c.499C>T (p.R167W), in the MECP2 gene in patient 1, which was inherited from his mother. The inactivation of X chromosome is skewed, and the expression ratio of wild-type and mutant MECP2 is 100%:0. Patient 2 was found a de novo splicing mutation, c.62+2_62+3del in the MECP2 gene. They were both reported pathogenic variant related to Rett syndrome. c.499C>T (p.R167W) was defined as likely pathogenic (PS1+PM2+PP3) and c.62+2_62+3del was pathogenic (PVS1+PM2+PM6) based on American College of Medical Genetics and Genomics standards and guidelines. CONCLUSION: Both the two patients were diagnosed with rare male Rett syndrome, which had atypical clinical manifestations and large difference. Above foundings have revealed novel phenotypes in Chinese male patients with Rett syndrome.

Dynamic functional network reconfiguration underlying the pathophysiology of schizophrenia and autism spectrum disorder.

The dynamics of the human brain span multiple spatial scales, from connectivity associated with a specific region/network to the global organization, each representing different brain mechanisms. Yet brain reconfigurations at different spatial scales are seldom explored and whether they are associated with the neural aspects of brain disorders is far from understood. In this study, we introduced a dynamic measure called step-wise functional network reconfiguration (sFNR) to characterize how brain configuration rewires at different spatial scales. We applied sFNR to two independent datasets, one includes 160 healthy controls (HCs) and 151 patients with schizophrenia (SZ) and the other one includes 314 HCs and 255 individuals with autism spectrum disorder (ASD). We found that both SZ and ASD have increased whole-brain sFNR and sFNR between cerebellar and subcortical/sensorimotor domains. At the ICN level, the abnormalities in SZ are mainly located in ICNs within subcortical, sensory, and cerebellar domains, while the abnormalities in ASD are more widespread across domains. Interestingly, the overlap SZ-ASD abnormality in sFNR between cerebellar and sensorimotor domains was correlated with the reasoning-problem-solving performance in SZ (r = -.1652, p = .0058) as well as the Autism Diagnostic Observation Schedule in ASD (r = .1853, p = .0077). Our findings suggest that dynamic reconfiguration deficits may represent a key intersecting point for SZ and ASD. The investigation of brain dynamics at different spatial scales can provide comprehensive insights into the functional reconfiguration, which might advance our knowledge of cognitive decline and other pathophysiology in brain disorders.

Quantitative and objective diagnosis of color vision deficiencies based on steady-state visual evoked potentials.

PURPOSE: Traditional color vision tests depend on subjective judgments and are not suitable for infant children and subjects with cognitive dysfunction. We aimed to explore an objective and quantitative color vision testing method based on sweep steady-state visual evoked potentials (sweep SSVEPs) and compare the results with subjective Farnsworth-Munsell (FM) 100-hue test results. METHODS: A red-green SSVEP pattern reversal checkboard paradigm at different luminance ratios was used to induce visual evoked potentials (VEPs) from 15 color vision deficiencies (CVDs) and 11 normal color vision subjects. After electroencephalography signals were processed by canonical correlation analysis, an equiluminance turning curve corresponding to the activation of the L-cones and M-cones at different levels of color vision was established. Then, we obtained different equiluminance T and proposed the SSVEP color vision severity index (ICVD) to quantify color vision function and the severity of CVDs. In addition, the FM 100-hue test was used to obtain subjective data for the diagnosis of color vision. RESULTS: The value of ICVD can be an indicator of the level of color vision. Both the total error scores (TES) and confusion index (C-index) of the FM 100-hue test were significantly correlated with ICVD values (P < 0.001, respectively). ICVD also had a good classification effect in detecting normals, anomalous trichromats and dichromats. Moreover, equiluminance T had a good effect on classifying protans and deutans in subjects with CVDs. CONCLUSION: Color vision evaluation with sweep SSVEPs showed a good correlation with subjective psychophysical methods. SSVEPs can be an objective and quantitative method to test color vision and diagnose CVDs.

Age-related structural and functional variations in 5,967 individuals across the adult lifespan.

Exploring brain changes across the human lifespan is becoming an important topic in neuroscience. Though there are multiple studies which investigated the relationship between age and brain imaging, the results are heterogeneous due to small sample sizes and relatively narrow age ranges. Here, based on year-wise estimation of 5,967 subjects from 13 to 72 years old, we aimed to provide a more precise description of adult lifespan variation trajectories of gray matter volume (GMV), structural network correlation (SNC), and functional network connectivity (FNC) using independent component analysis and multivariate linear regression model. Our results revealed the following relationships: (a) GMV linearly declined with age in most regions, while parahippocampus showed an inverted U-shape quadratic relationship with age; SNC presented a U-shape quadratic relationship with age within cerebellum, and inverted U-shape relationship primarily in the default mode network (DMN) and frontoparietal (FP) related correlation. (b) FNC tended to linearly decrease within resting-state networks (RSNs), especially in the visual network and DMN. Early increase was revealed between RSNs, primarily in FP and DMN, which experienced a decrease at older ages. U-shape relationship was also revealed to compensate for the cognition deficit in attention and subcortical related connectivity at late years. (c) The link between middle occipital gyrus and insula, as well as precuneus and cerebellum, exhibited similar changing trends between SNC and FNC across the adult lifespan. Collectively, these results highlight the benefit of lifespan study and provide a precise description of age-related regional variation and SNC/FNC changes based on a large dataset.