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.

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.

SMART (Splitting-Merging Assisted Reliable) Independent Component Analysis for Extracting Accurate Brain Functional Networks.

Functional networks (FNs) hold significant promise in understanding brain function. Independent component analysis (ICA) has been applied in estimating FNs from functional magnetic resonance imaging (fMRI). However, determining an optimal model order for ICA remains challenging, leading to criticism about the reliability of FN estimation. Here, we propose a SMART (splitting-merging assisted reliable) ICA method that automatically extracts reliable FNs by clustering independent components (ICs) obtained from multi-model-order ICA using a simplified graph while providing linkages among FNs deduced from different-model orders. We extend SMART ICA to multi-subject fMRI analysis, validating its effectiveness using simulated and real fMRI data. Based on simulated data, the method accurately estimates both group-common and group-unique components and demonstrates robustness to parameters. Using two age-matched cohorts of resting fMRI data comprising 1,950 healthy subjects, the resulting reliable group-level FNs are greatly similar between the two cohorts, and interestingly the subject-specific FNs show progressive changes while age increases. Furthermore, both small-scale and large-scale brain FN templates are provided as benchmarks for future studies. Taken together, SMART ICA can automatically obtain reliable FNs in analyzing multi-subject fMRI data, while also providing linkages between different FNs.

Enzymatic Preparation of DNA with an Expanded Genetic Alphabet Using Terminal Deoxynucleotidyl Transferase and Its Applications.

Efficient preparation of DNA oligonucleotides containing unnatural nucleobases (UBs) that can pair with their cognates to form unnatural base pairs (UBPs) is an essential prerequisite for the application of UBPs in vitro and in vivo. Traditional preparation of oligonucleotides containing unnatural nucleobases largely relies on solid-phase synthesis, which needs to use unstable nucleoside phosphoramidites and a DNA synthesizer, and is environmentally unfriendly and limited in product length. To overcome these limitations of solid-phase synthesis, we developed enzymatic methods for daily laboratory preparation of DNA oligonucleotides containing unnatural nucleobase dNaM, dTPT3, or one of the functionalized dTPT3 derivatives, which can be used for orthogonal DNA labeling or the preparation of DNAs containing UBP dNaM-dTPT3, one of the most successful UBPs to date, based on the template-independent polymerase terminal deoxynucleotidyl transferase (TdT). Here, we first provide a detailed procedure for the TdT-based preparation of DNA oligonucleotides containing 3'-nucleotides of dNaM, dTPT3, or one of dTPT3 derivatives. We then present the procedures for enzyme-linked oligonucleotide assay (ELONA) and imaging of bacterial cells using DNA oligonucleotides containing 3'-nucleotides of dTPT3 derivatives with different functional groups. The procedure for enzymatic synthesis of DNAs containing an internal UBP dNaM-dTPT3 is also described. Hopefully, these methods will greatly facilitate the application of UBPs and the construction of semi-synthetic organisms with an expanded genetic alphabet.

Correlations between bone metabolism biomarkers and fluoride exposure in adults and children.

Increased exposure to fluoride, which notably affects bone metabolism, is a global concern. However, the correlations and sensitivity of bone metabolism to fluoride remain controversial. In this cross-sectional study, 549 children (aged 7-12 years) and 504 adults (≥ 18 years old) were recruited in the high-fluoride areas of the Henan Province. Urinary fluoride (UF) level was determined using a fluoride electrode. Fasting venous blood serum was collected to measure bone metabolism biomarkers. The selected bone metabolism biomarkers for children included bone alkaline phosphatase (BALP), serum alkaline phosphatase (ALP), osteocalcin (OCN), calcitonin (CT), parathyroid hormone (PTH), phosphorus (P5+), and calcium (Ca2+). For adults, the biomarkers included ALP, CT, PTH, ß-CrossLaps (ß-CTX), P5+, and Ca2+. The correlations between UF and bone metabolism biomarkers were analyzed using binary logistic regression, a trend test, a generalized additive model, and threshold effect analysis. Regression analysis indicated a significant correlation between serum OCN, PTH, and UF levels in children aged 7-9 years. Serum OCN, PTH, and BALP contents were significantly correlated with UF in boys (P < 0.05). Furthermore, the interaction between age and UF affected serum P5+ and PTH (P < 0.05). The generalized additive model revealed nonlinear dose-response relationships between P5+, BALP, and UF contents in children (P < 0.05). Serum OCN level was linearly correlated with the UF concentration (P < 0.05). Similarly, a significant correlation was observed between ß-CTX and UF levels in adults. In addition, significant correlations were observed between UF-age and serum Ca2+, ß-CTX, and PTH contents. There was a non-linear correlation between serum Ca2+, P5+, and ß- CTX and UF levels (P < 0.05). Overall, serum OCN, BALP, and P5+ levels can serve as sensitive bone metabolism biomarkers in children, while ß-CTX, P5+, and Ca2+ can be considered fluoride-sensitive bone metabolism biomarkers in adults.

More reliable biomarkers and more accurate prediction for mental disorders using a label-noise filtering-based dimensional prediction method.

The integration of neuroimaging with artificial intelligence is crucial for advancing the diagnosis of mental disorders. However, challenges arise from incomplete matching between diagnostic labels and neuroimaging. Here, we propose a label-noise filtering-based dimensional prediction (LAMP) method to identify reliable biomarkers and achieve accurate prediction for mental disorders. Our method proposes to utilize a label-noise filtering model to automatically filter out unclear cases from a neuroimaging perspective, and then the typical subjects whose diagnostic labels align with neuroimaging measures are used to construct a dimensional prediction model to score independent subjects. Using fMRI data of schizophrenia patients and healthy controls (n = 1,245), our method yields consistent scores to independent subjects, leading to more distinguishable relabeled groups with an enhanced classification accuracy of 31.89%. Additionally, it enables the exploration of stable abnormalities in schizophrenia. In summary, our LAMP method facilitates the identification of reliable biomarkers and accurate diagnosis of mental disorders using neuroimages.

Effect of zinc intake on association between fluoride exposure and abnormal sex steroid hormones among US pubertal males: NHANES, 2013-2016.

Excessive fluoride exposure can disturb the balance of sex hormones. Zinc is essential for sex hormone synthesis and spermatogenesis. But it is not clear how zinc affects the relationship of fluoride exposure with abnormal sex steroid hormones. Here, a total of 1008 pubertal males from the National Health and Nutrition Examination Survey (NHANES) in two cycles (2013-2014, 2015-2016) were enrolled. The concentrations of water fluoride and plasma fluoride and the levels of serum testosterone, estradiol, and sex hormone binding globulin (SHBG) were measured. Two 24-h dietary recall interviews were conducted to assess the dietary zinc intake. The relationships of fluoride exposure and zinc intake with sex hormones were examined using linear regression and logistic regression models, while the generalized additive model was used to evaluate their non-linear relationship. Our findings revealed that for every two-fold increase in plasma fluoride concentration, testosterone levels decreased by 7.27% (95% CI - 11.49%, - 2.86%) and estradiol levels decreased by 8.73% (95% CI - 13.61%, - 3.57%). There was also significant non-linear association observed between zinc intake and SHBG levels. Being in the first tertile of plasma fluoride had a 60% lower risk of high SHBG (OR = 0.40, 95% CI 0.18, 0.89) compared with being in the second tertile. When compared to the first tertile, being in the second tertile of zinc intake was associated with a 63% (OR = 0.37, 95% CI 0.14, 0.98) lower risk of high SHBG. Furthermore, we observed an interactive effect between the plasma fluoride and zinc intake on estradiol and SHBG, as well as the risk of high SHBG (P-interaction < 0.10). These findings suggest that fluoride exposure and zinc intake can affect sex steroid hormone levels and the risk of high SHBG. Notably, zinc intake may alleviate the increased risk of high SHBG and the abnormal changes of estradiol and SHBG caused by higher fluoride exposure.

How and when awe improves meaning in life: The role of authentic-self pursuit and trait authenticity.

Awe is theoretically proposed as a meaning-making emotion. However, empirical evidence has shown that awe has mixed effects on meaning in life. The explanations for such complicated results have been limited. To fill this gap, in this research, we aimed to clarify how and when awe contributes to meaning in life. In six studies (N = 1,115), we examined the indirect effect of awe on meaning in life through authentic-self pursuit as well as trait authenticity's moderating effect on this indirect effect. We consistently found a positive indirect effect of awe on meaning in life via authentic-self pursuit (Studies 1-3 and Study 5), which arised beyond happiness and self-smallness (Studies 2a, 2b, and 3) and also held for awe brought on by a threatening experience (Study 3). Moreover, we found that manipulating authentic-self pursuit improved meaning in life (Study 4). Importantly, the main effect of awe on meaning in life and indirect effect of awe on meaning in life through authentic-self pursuit were significant for those with low to average rather than high trait authenticity (Study 5). These findings facilitate the understanding of awe as a meaning-making emotion. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Proteomics Sequencing Reveals the Role of TGF-ß Signaling Pathway in the Peripheral Blood of Offspring Rats Exposed to Fluoride.

The underlying mechanism of fluorosis has not been fully elucidated. The purpose of this study was to explore the mechanism of fluorosis induced by sodium fluoride (NaF) using proteomics. Six offspring rats exposed to fluoride without dental fluorosis were defined as group A, 8 offspring rats without fluoride exposure were defined as control group B, and 6 offspring rats exposed to fluoride with dental fluorosis were defined as group C. Total proteins from the peripheral blood were extracted and then separated using liquid chromatography-tandem mass spectrometry. The identified criteria for differentially expressed proteins were fold change > 1.2 or < 0.83 and P < 0.05. Gene Ontology function annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the oeCloud tool. The 177 upregulated and 22 downregulated proteins were identified in the A + C vs. B group. KEGG pathway enrichment analysis revealed that transforming growth factor-ß (TGF-ß) signaling pathway significantly enriched. PPI network constructed using Cytoscape confirmed RhoA may play a crucial role. The KEGG results of genes associated with fluoride and genes associated with both fluoride and inflammation in the GeneCards database also showed that TGF-ß signaling pathway was significantly enriched. The immunofluorescence in HPA database showed that the main expression sites of RhoA are plasma membrane and cytosol, while the main expression site of Fbn1 is the Golgi apparatus. In conclusion, long-term NaF intake may cause inflammatory response in the peripheral blood of rats by upregulating TGF-ß signaling pathway, in which RhoA may play a key role.

A Novel Method for Multi-subject fMRI Data Analysis: Independent Component Analysis with Clustering Embedded (ICA-CE).

The analysis of multi-subject functional magnetic resonance imaging (fMRI) data and the extraction of accurate brain functional networks (FNs) are of great importance. However, traditional independent component analysis (ICA) methods perform analysis on multi-subject fMRI data under the condition of known or assumed classes of subjects, which may decrease its ability to extract accurate individual brain FNs. Although a previous method named clusterwise ICA (C-ICA) clusters subjects and obtains shared FNs in group-level for each class, its clustering performance on complex data is not ideal. To address the issues, we propose a novel method called independent component analysis with clustering embedded (ICA-CE) that can achieve both the estimation of individual FNs and the clustering of subjects in an unsupervised or semi-supervised manner. Using the simulated data with different properties, ICA-CE achieved better clustering performance than group ICA followed by K-means and C-ICA, and the mean accuracy of extracted individual FNs obtained by ICA-CE was greater than 90%. Using the task-related fMRI data from Human Connectome Project (HCP), our method also achieved higher clustering accuracy, while extracting task-related class-specific FNs. In summary, ICA-CE is effective in estimating accurate brain FNs while achieving the clustering of multiple subjects.Clinical Relevance- Our method is promising in estimating accurate brain functional networks for patients with brain disorders and outputting related class label for each subject.

How Does Aging Affect Whole-brain Functional Network Connectivity? Evidence from An ICA Method.

Many studies have shown that changes in the functional connectivity are diverse along with aging. However, few studies have addressed how aging affects connectivity among large-scale brain networks, and it is challenging to examine gradual aging trajectories from middle adulthood to old age. In this work, based on large-sample fMRI data from 6300 subjects aged between 49 to 73 years, we apply an independent component analysis-based method called NeuroMark to extract brain functional networks and their connectivity (i.e., functional network connectivity (FNC)), and then propose a two-level statistical analysis method to explore robust aging-related changes in functional network connectivity. We found that the enhanced FNCs mainly occur between different functional domains, involving the default mode and cognitive control networks, while the reduced FNCs come from not only between different domains but also within the same domain, primarily relating to the visual network, cognitive control network and cerebellum. Our results emphasize the diversity of brain aging and provide new evidence for non-pathological aging of the whole brain.Clinical Relevance-This provides new evidence for non-pathological aging of functional network connectivity in the whole brain.

Corrigendum: Application of single-cell sequencing to the research of tumor microenvironment.

[This corrects the article DOI: 10.3389/fimmu.2023.1285540.].

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.

Application of single-cell sequencing to the research of tumor microenvironment.

Single-cell sequencing is a technique for detecting and analyzing genomes, transcriptomes, and epigenomes at the single-cell level, which can detect cellular heterogeneity lost in conventional sequencing hybrid samples, and it has revolutionized our understanding of the genetic heterogeneity and complexity of tumor progression. Moreover, the tumor microenvironment (TME) plays a crucial role in the formation, development and response to treatment of tumors. The application of single-cell sequencing has ushered in a new age for the TME analysis, revealing not only the blueprint of the pan-cancer immune microenvironment, but also the heterogeneity and differentiation routes of immune cells, as well as predicting tumor prognosis. Thus, the combination of single-cell sequencing and the TME analysis provides a unique opportunity to unravel the molecular mechanisms underlying tumor development and progression. In this review, we summarize the recent advances in single-cell sequencing and the TME analysis, highlighting their potential applications in cancer research and clinical translation.

One-Pot Enzymatic Preparation of Oligonucleotides with an Expanded Genetic Alphabet via Controlled Pause and Restart of Primer Extension: Making Unnatural Out of Natural.

The genetic alphabet of life has been dramatically expanded via the development of unnatural base pairs (UBPs) that work as efficiently as natural base pairs in the storage and retrieval of genetic information. Among the most predominant UBPs, dNaM-dTPT3 and its analogues have been successfully employed to build semisynthetic cells with a functional six-letter genome. With the rapidly growing applications of UBPs in vitro and in vivo, there is an ever-increasing demand for DNA oligonucleotides containing unnatural bases (UBs) at desired positions. Conventional solid-phase synthesis of oligonucleotides has intrinsic limitations and needs to use unstable unnatural phosphoramidites and a DNA synthesizer, so it does not meet the daily urgent requirement for a few UB-containing DNA oligonucleotides in the laboratory. In this work, we develop a one-pot enzymatic method for preparing dNaM- or dTPT3-containing DNA oligonucleotides via controlled pause and restart of primer extension mediated by Klenow fragment (exo-). By systematic optimization of the reaction conditions, high efficiencies and product purities have been achieved. The universality of this method for preparing DNA oligonucleotides containing dNaM or dTPT3 in different sequence contexts is also demonstrated. This method allows convenient production of an arbitrary UB-containing DNA oligonucleotide in a single test tube with only two natural DNA oligonucleotides, stable nucleoside triphosphates, Klenow fragment (exo-), and other common reagents in the laboratory, providing the lowest cost and the highest simplicity for the enzymatic preparation of UB-containing oligonucleotides. Clearly, this method has great potential to facilitate the in vitro and in vivo applications of the UBPs.

Recognition of an Unnatural Base Pair by Tool Enzymes from Bacteriophages and Its Application in the Enzymatic Preparation of DNA with an Expanded Genetic Alphabet.

Unnatural base pairs (UBPs) have been developed to expand the genetic alphabet in vitro and in vivo. UBP dNaM-dTPT3 and its analogues have been successfully used to construct the first set of semi-synthetic organisms, which suggested the great potential of UBPs to be used for producing novel synthetic biological parts. Two prerequisites for doing so are the facile manipulation of DNA containing UBPs with common tool enzymes, including DNA polymerases and ligases, and the easy availability of UBP-containing DNA strands. Besides, for the application of UBPs in phage synthetic biology, the recognition of UBPs by phage enzymes is essential. Here, we first explore the recognition of dNaM-dTPT3 by a family B DNA polymerase from bacteriophage, T4 DNA polymerase D219A. Results from primer extension, steady-state kinetics, and gap-filling experiments suggest that T4 DNA polymerase D219A can efficiently and faithfully replicate dNaM-dTPT3, and efficiently fill a gap by inserting dTPT3TP or its analogues opposite dNaM. We then systematically explore the recognition of dNaM-dTPT3 and its analogues by different DNA ligases from bacteriophages and find that these DNA ligases are generally able to efficiently ligate the DNA nick next to dNaM-dTPT3 or its analogues, albeit with slightly different efficiencies. These results suggest more enzymatic tools for the manipulation of dNaM-dTPT3 and indicate the potential use of dNaM-dTPT3 for expanding the genetic alphabet in bacteriophages. Based on these results, we next develop and comprehensively optimize an upgraded method for enzymatic preparation of unnatural nucleobase (UB)-containing DNA oligonucleotides with good simplicity and universality.

Synthesis, Reverse Transcription, Replication, and Inter-Transcription of 2'-Modified Nucleic Acids with Evolved Thermophilic Polymerases: Efforts toward Multidimensional Expansion of the Central Dogma.

In the past decades, various xenobiotic nucleic acids (XNAs), including 2'-modified nucleic acids, have been developed as novel genetic materials and demonstrated great potential in synthetic biology and biotechnology. Enzymatic polymerization and replication of these artificial polymers are obviously the prerequisite to make full use of them, and DNA and RNA polymerases from different families have thus been extensively engineered for these purposes. However, the performance of engineered XNA polymerases is still far from satisfactory, especially in terms of the efficiency of synthesizing XNA with bigger lengths and the capability of directly replicating XNAs or transcribing one XNA to another. In this work, we tailored a mutant of Stoffel fragment of Taq DNA polymerase, SFM4-3, by engineering a key residue pair on the surfaces of fingers and thumb domains, and successfully obtained mutants with significantly enhanced efficiency for the synthesis of fully 2'-OMe-modified DNA with bigger lengths. Remarkably, we also found that these polymerase mutants are capable of synthesizing, reverse transcribing, and even replicating RNA and different fully 2'-modified XNAs, as well as transcribing one of these nucleic acids to another, with varied efficiencies. The application of these activities for producing DNA strands end-protected by XNA duplexes was then demonstrated. These results clearly suggest that the genetic information can be stored in and transmitted among DNA, RNA, and different 2'-modified XNAs with the assistance of polymerase mutants, and the central dogma of life can be expanded to higher dimensions via the development of XNAs together with engineering their polymerases.

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.

Aging brain shows joint declines in brain within-network connectivity and between-network connectivity: a large-sample study (N > 6,000).

Introduction: Numerous studies have shown that aging has important effects on specific functional networks of the brain and leads to brain functional connectivity decline. However, no studies have addressed the effect of aging at the whole-brain level by studying both brain functional networks (i.e., within-network connectivity) and their interaction (i.e., between-network connectivity) as well as their joint changes. Methods: In this work, based on a large sample size of neuroimaging data including 6300 healthy adults aged between 49 and 73 years from the UK Biobank project, we first use our previously proposed priori-driven independent component analysis (ICA) method, called NeuroMark, to extract the whole-brain functional networks (FNs) and the functional network connectivity (FNC) matrix. Next, we perform a two-level statistical analysis method to identify robust aging-related changes in FNs and FNCs, respectively. Finally, we propose a combined approach to explore the synergistic and paradoxical changes between FNs and FNCs. Results: Results showed that the enhanced FNCs mainly occur between different functional domains, involving the default mode and cognitive control networks, while the reduced FNCs come from not only between different domains but also within the same domain, primarily relating to the visual network, cognitive control network, and cerebellum. Aging also greatly affects the connectivity within FNs, and the increased within-network connectivity along with aging are mainly within the sensorimotor network, while the decreased within-network connectivity significantly involves the default mode network. More importantly, many significant joint changes between FNs and FNCs involve default mode and sub-cortical networks. Furthermore, most synergistic changes are present between the FNCs with reduced amplitude and their linked FNs, and most paradoxical changes are present in the FNCs with enhanced amplitude and their linked FNs. Discussion: In summary, our study emphasizes the diversity of brain aging and provides new evidence via novel exploratory perspectives for non-pathological aging of the whole brain.

A Precise Frequency Recognition Method of Short-Time SSVEP Signals Based on Signal Extension.

OBJECTIVE: Improving the Information Transfer Rate (ITR) is a popular research topic in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs). The higher recognition accuracy of short-time SSVEP signal is critical to improving ITR and achieving high-speed SSVEP-BCIs. However, the existing algorithms have unsatisfactory performance on recognizing short-time SSVEP signals, especially for calibration-free methods. METHOD: This study for the first time proposed improving the recognition accuracy of short-time SSVEP signals based on the calibration-free method by extending the SSVEP signal length. A signal extension model based on Multi-channel adaptive Fourier decomposition with different Phase (DP-MAFD) is proposed to achieve signal extension. Then the Canonical Correlation Analysis based on signal extension (SE-CCA) is proposed to complete the recognition and classification of SSVEP signals after extension. RESULT: The similarity study and SNR comparison analysis on public SSVEP datasets demonstrate that the proposed signal extension model has the ability to extend SSVEP signals. The classification results show that the proposed method outperforms Canonical Correlation Analysis (CCA) and Filter Bank Canonical Correlation Analysis (FBCCA) significantly in the measure of classification accuracy and information transmission rate (ITR), especially for short-time signals. The highest ITR of SE-CCA is improved to 175.61 bits/min at around 1s, while CCA is 100.55 bits/min at 1.75s and FBCCA is 141.76 bits/min at 1.25s. CONCLUSION: The signal extension method can improve the recognition accuracy of short-time SSVEP signals and further improve the ITR of SSVEP-BCIs.