Search

Objectives: To examine the associaiton between environmental measures and brain volumes and its potential mediators., Study Design: This was a prospective study., Methods: Our analysis included 34,454 participants (53.4% females) aged 40-73 years at baseline (between 2006 and 2010) from the UK Biobank. Brain volumes were measured using magnetic resonance imaging between 2014 and 2019., Results: Greater proximity to greenspace buffered at 1000 m at baseline was associated with larger volumes of total brain measured 8.8 years after baseline assessment (standardized β (95% CI) for each 10% increment in coverage: 0.013(0.005,0.020)), grey matter (0.013(0.006,0.020)), and white matter (0.011(0.004,0.017)) after adjustment for covariates and air pollution. The corresponding numbers for natural environment buffered at 1000 m were 0.010 (0.004,0.017), 0.009 (0.004,0.015), and 0.010 (0.004,0.016), respectively. Similar results were observed for greenspace and natural environment buffered at 300 m. The strongest mediator for the association between greenspace buffered at 1000 m and total brain volume was smoking (percentage (95% CI) of total variance explained: 7.9% (5.5-11.4%)) followed by mean sphered cell volume (3.3% (1.8-5.8%)), vitamin D (2.9% (1.6-5.1%)), and creatinine in blood (2.7% (1.6-4.7%)). Significant mediators combined explained 18.5% (13.2-25.3%) of the association with total brain volume and 32.9% (95% CI: 22.3-45.7%) of the association with grey matter volume. The percentage (95% CI) of the association between natural environment and total brain volume explained by significant mediators combined was 20.6% (14.7-28.1%))., Conclusions: Higher coverage percentage of greenspace and environment may benefit brain health by promoting healthy lifestyle and improving biomarkers including vitamin D and red blood cell indices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Aims/introduction: High plasma 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid (CMPF) levels are significantly associated with type 2 diabetes mellitus, which is usually accompanied by metabolic syndrome and non-alcoholic fatty liver disease (NAFLD) with increased triglyceride levels. Thus, we hypothesized that elevated CMPF levels might be related to lipid metabolism and NAFLD risk., Materials and Methods: Serum CMPF levels were determined using an enzyme-linked immunosorbent assay in a total of 466 individuals, including 116 controls with no NAFLD or type 2 diabetes mellitus, 53 individuals with NAFLD but no type 2 diabetes mellitus, 151 individuals with type 2 diabetes mellitus but no NAFLD, and 146 individuals with both NAFLD and type 2 diabetes mellitus. The associations with age, blood pressure, lipid profiles, body mass index and liver injury marker levels were examined, and a meta-analysis of non-diabetic and diabetic groups was carried out to detect the combined effects., Results: The CMPF concentration in NAFLD patients was significantly lower than individuals without NAFLD in both the non-diabetic group (P < 0.05) and diabetic group (P < 0.01), and correlated negatively with several parameters of liver function and the adiposity index. Meta-analysis showed that serum CMPF levels was associated with decreased risk of NAFLD after combining the results (odds ratio 0.677, 95% confidence interval 0.552-0.831, P < 0.001). Additionally, the CMPF concentration was independently negatively associated with triglycerides and high-density lipoprotein cholesterol in the meta-analysis. Multiple stepwise regression analysis showed that body mass index, high-density lipoprotein cholesterol, triglyceride level, age, sex and fasting plasma glucose were independently associated with CMPF (all P < 0.05)., Conclusions: The results suggest that serum CMPF levels are negatively related to lipid metabolism and could be used to predict NAFLD development., (© 2018 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.)

Background: Mass cytometry has recently emerged as a promising tool for clinical research. However, few studies have demonstrated its benefit for patient stratification and biomarker identification. Primary Sjögren's syndrome (pSS) is a prototype of chronic autoimmune disease, the pathogenesis of which remains unclear and for which treatment does not exist., Objective: This observational case-control study was designed to discover new cellular biomarkers and therapeutic targets in patients with pSS., Methods: Forty-nine patients with pSS and 45 control subjects were enrolled for clinical evaluation and mass cytometry quantification of 34 protein markers in blood. For a third of these subjects, matched labial salivary gland biopsy specimens were also analyzed by mass cytometry and immunohistochemistry., Results: In salivary gland biopsy specimens from patients with pSS, we identified a high number of activated CD8(+) T cells, terminally differentiated plasma cells, and activated epithelial cells, pointing to new pathogenic mechanisms for future clinical intervention. In blood, we identified a 6-cell disease signature defined by decreased numbers of CD4 and memory B lymphocytes, decreased plasmacytoid dendritic cell numbers, and increased representation of activated CD4 and CD8 T cells and plasmablasts. These blood cellular components correlated with clinical parameters and, when taken together, clustered patients into subsets with distinct disease activity and glandular inflammation., Conclusion: This first application of mass cytometry to a well-stratified clinical cohort and small biopsy tissues establishes the benefits of such an approach for the discovery of new biomarkers and therapeutic targets. Similar high-dimensional immunophenotyping strategies could be implemented in longitudinal and interventional clinical settings in this and other disease areas., (Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

The rapidly evolving landscape of biomarkers for colorectal cancer (CRC) necessitates an integrative, updated repository. In response, we constructed the Colorectal Cancer Biomarker Database (CBD), which collected and displayed the curated biomedicine information for 870 CRC biomarkers in the previous study. Building on CBD, we have now developed CBD2, which includes information on 1569 newly reported biomarkers derived from different biological sources (DNA, RNA, protein, and others) and clinical applications (diagnosis, treatment, and prognosis). CBD2 also incorporates information on nonbiomarkers that have been identified as unsuitable for use as biomarkers in CRC. A key new feature of CBD2 is its network analysis function, by which users can investigate the visible and topological network between biomarkers and identify their relevant pathways. CBD2 also allows users to query a series of chemicals, drug combinations, or multiple targets, to enable multidrug, multitarget, multipathway analyses, toward facilitating the design of polypharmacological treatments for CRC. CBD2 is freely available at http://www.eyeseeworld.com/cbd. Highlights: CBD2 integrates biomarkers derived from diverse biological sources and clinical applications, employing a standardized approach for annotation and classification.CBD2 facilitates precision medicine in colorectal cancer by providing abundant data, including drug–target information and visualized network analysis functions.With its user‐friendly interface, CBD2 aids in the identification and development of biomarkers for colorectal cancer. [ABSTRACT FROM AUTHOR]

Motivation Many ophthalmic disease biomarkers have been identified through comprehensive multiomics profiling, and hold significant potential in advancing the diagnosis, prognosis, and management of diseases. Meanwhile, the eye itself serves as a natural biomarker for several systemic diseases including neurological, renal, and cardiovascular systems. We aimed to collect and standardize this eye biomarkers information and construct the eye biomarker database (EBD) to provide ophthalmologists with a platform to search, analyze, and download these eye biomarker data. Results In this study, we present the EBD < http://www.eyeseeworld.com/ebd/index.html >, a world-first online compilation comprising 889 biomarkers for 26 ocular diseases and 939 eye biomarkers for 181 systemic diseases. The EBD also includes the information of 78 "nonbiomarkers"—the objects that have been proven cannot be biomarkers. Biological function and network analysis were conducted for these ocular disease biomarkers, and several hub pathways and common network topology characteristics were newly identified, which may promote future ocular disease biomarker discovery and characterizes the landscape of biomarkers for eye diseases at the pathway and network level. The EBD is expected to yield broader utility among developmental biologists and clinical scientists in and outside of the eye field by assisting in the identification of biomarkers linked to eye disorders and related systemic diseases. Availability and implementation EBD is available at http://www.eyeseeworld.com/ebd/index.html. [ABSTRACT FROM AUTHOR]

Herein, we constructed the first sepsis biomarker knowledge database, MetaSepsisBase (http://sysbio.org.cn/sbd/), which contains biomedical information on 320 biomarkers collected from PubMed. Despite numerous studies published and many biomarkers identified, there exists an urgent need for a comprehensive database to collect, annotate, and display the information on human sepsis biomarkers [[3]]. Our goal is to collect and integrate all the reported sepsis biomarkers to provide users with comprehensive biomarker information, and assist critical care physicians in finding specific biomarkers or combined biomarkers to improve the rapid diagnosis and treatment effectiveness of human sepsis. [Extracted from the article]

Background and purpose: Neonatal hyperbilirubinemia, also known as neonatal jaundice, is a common and frequent clinical condition with a complex etiology that can lead to brain damage in severe cases. Early recognition of hyperbilirubinemia and timely intervention and treatment can help reduce the occurrence of sequelae. This study was conducted to identify whether the gut microbiota composition can distinguish neonates with hyperbilirubinemia. Methods: Meconium samples were collected from 69 neonates with neonatal jaundice (NJ) and 69 age- and sex-matched neonates without clinically significant jaundice (healthy controls; HCs) for 16S rRNA gene sequencing and microbiome analysis. Results: Compared with HCs, the Chao 1 richness index of the gut microbiota was significantly decreased in the NJ group. The relative abundance of the probiotic gut bacterium, Lactobacillus, was significantly lower in the NJ group than in the HC group, whereas the abundances of potentially harmful gut bacteria, such as Escherichia coli and Staphylococcus, were significantly higher in the NJ group than in HCs. Correlation of the gut microbiota and clinical indicators revealed a positive correlation between Escherichia coli/Staphylococcus and serum total bilirubin levels. Finally, the results of a random forest machine-learning method to evaluate the possibility of using NJ-associated gut microbiota compositions as potential NJ biomarkers revealed an area under the curve of 96.88%. Conclusions: The abundances of Escherichia coli and Staphylococcus were positively correlated with serum total bilirubin levels. Hence, the gut microbiota composition is a potential biomarker of NJ. [ABSTRACT FROM AUTHOR]

Introduction retinal age derived from fundus images using deep learning has been verified as a novel biomarker of ageing. We aim to investigate the association between retinal age gap (retinal age–chronological age) and incident Parkinson's disease (PD). Methods a deep learning (DL) model trained on 19,200 fundus images of 11,052 chronic disease-free participants was used to predict retinal age. Retinal age gap was generated by the trained DL model for the remaining 35,834 participants free of PD at the baseline assessment. Cox proportional hazards regression models were utilised to investigate the association between retinal age gap and incident PD. Multivariable logistic model was applied for prediction of 5-year PD risk and area under the receiver operator characteristic curves (AUC) was used to estimate the predictive value. Results a total of 35,834 participants (56.7 ± 8.04 years, 55.7% female) free of PD at baseline were included in the present analysis. After adjustment of confounding factors, 1-year increase in retinal age gap was associated with a 10% increase in risk of PD (hazard ratio [HR] = 1.10, 95% confidence interval [CI]: 1.01–1.20, P  = 0.023). Compared with the lowest quartile of the retinal age gap, the risk of PD was significantly increased in the third and fourth quartiles (HR = 2.66, 95% CI: 1.13–6.22, P  = 0.024; HR = 4.86, 95% CI: 1.59–14.8, P  = 0.005, respectively). The predictive value of retinal age and established risk factors for 5-year PD risk were comparable (AUC = 0.708 and 0.717, P  = 0.821). Conclusion retinal age gap demonstrated a potential for identifying individuals at a high risk of developing future PD. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) biomarker database (CBD) was established based on 870 identified CRC biomarkers and their relevant information from 1115 original articles in PubMed published from 1986 to 2017. In this version of the CBD, CRC biomarker data were collected, sorted, displayed and analysed. The CBD with the credible contents as a powerful and time-saving tool provide more comprehensive and accurate information for further CRC biomarker research. The CBD was constructed under MySQL server. HTML, PHP and JavaScript languages have been used to implement the web interface. The Apache was selected as HTTP server. All of these web operations were implemented under the Windows system. The CBD could provide to users the multiple individual biomarker information and categorized into the biological category, source and application of biomarkers; the experiment methods, results, authors and publication resources; the research region, the average age of cohort, gender, race, the number of tumours, tumour location and stage. We only collect data from the articles with clear and credible results to prove the biomarkers are useful in the diagnosis, treatment or prognosis of CRC. The CBD can also provide a professional platform to researchers who are interested in CRC research to communicate, exchange their research ideas and further design high-quality research in CRC. They can submit their new findings to our database via the submission page and communicate with us in the CBD. Database URL: http://sysbio.suda.edu.cn/CBD/ [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the necrosis-avid agent hypericin as a potential indicator for determination of myocardial infarction ( MI). Male Sprague-Dawley rats ( n = 30) weighing 350 ± 20 g were subjected to acute reperfused MI. Animals were divided into four groups ( n = 6), in which hypericin was intravenously injected at 0, 1, 2 and 5 mg kg−1 respectively. One day after injection, rats were euthanized with their hearts excised for qualitative and quantitative studies by means of microscopic fluorescence examination to decide the dosage of hypericin. Another group was injected with hypericin at the decided dose and evaluated by fluorescence macroscopy in colocalization with triphenyltetrazoliumchloride ( TTC) and histomorphology. Infarct-to-normal contrast ratio and relative infarct size were quantified. Hypericin-induced red fluorescence was significantly brighter in necrotic than in viable myocardium as proven by a six times higher mean fluorescence density. Mean MI area was 35.66 ± 22.88% by hypericin fluorescence and 32.73 ± 21.98% by TTC staining ( R2 = 0.9803). Global MI-volume was 34.56 ± 21.07% by hypericin and 35.11 ± 20.47% by TTC staining ( R2 = 0.9933). The results confirm that hypericin specifically labeled necrosis, and enhanced the imaging contrast between the infarcted and normal myocardium, suggesting its potential applications for the assessment of myocardial viability. [ABSTRACT FROM AUTHOR]

Objective: Brown adipose tissue (BAT), a specialized tissue for thermogenesis, plays important roles for metabolism and energy expenditure. Recent studies validated BAT’s presence in human adults, making it an important re-emerging target for various pathologies. During this validation, PET images with 18F-FDG showed significant uptake of 18F-FDG by BAT under certain conditions. Here, we demonstrated that Cerenkov luminescence imaging (CLI) using 18F-FDG could be utilized for in vivo optical imaging of BAT in mice. Methods: Mice were injected with 18F-FDG and imaged 60 minutes later with open filter and 2 minute acquisition. In vivo activation of BAT was performed by norepinephrine and cold treatment under isoflurane or ketamine anesthesia. Spectral unmixing and 3D imaging reconstruction were conducted with multiple-filter CLI images. Results: 1) It was feasible to use CLI with 18F-FDG to image interscapular BAT in mice, with the majority of the signal (>85%) at the interscapular site originating from BAT; 2) The method was reliable because excellent correlations between in vivo CLI, ex vivo CLI, and ex vivo radioactivity were observed; 3) CLI could be used for monitoring BAT activation under different conditions; 4) CLI signals from the group under short-term isoflurane anesthesia were significantly higher than that from the group under long-term anesthesia; 5) The CLI spectrum of 18F-FDG with a peak at 640 nm in BAT after spectral unmixing reflected the actual context of BAT; 6) Finally 3D reconstruction images showed excellent correlation between the source of the light signal and the location and physical shape of BAT. Conclusion: CLI with 18F-FDG is a feasible and reliable method for imaging BAT in mice. Compared to PET imaging, CLI is significantly cheaper, faster for 2D planar imaging and easier to use. We believe that this method could be used as an important tool for researchers investigating BAT. [ABSTRACT FROM AUTHOR]

Objective: Brown adipose tissue (BAT), a specialized tissue for thermogenesis, plays important roles for metabolism and energy expenditure. Recent studies validated BAT’s presence in human adults, making it an important re-emerging target for various pathologies. During this validation, PET images with 18F-FDG showed significant uptake of 18F-FDG by BAT under certain conditions. Here, we demonstrated that Cerenkov luminescence imaging (CLI) using 18F-FDG could be utilized for in vivo optical imaging of BAT in mice. Methods: Mice were injected with 18F-FDG and imaged 60 minutes later with open filter and 2 minute acquisition. In vivo activation of BAT was performed by norepinephrine and cold treatment under isoflurane or ketamine anesthesia. Spectral unmixing and 3D imaging reconstruction were conducted with multiple-filter CLI images. Results: 1) It was feasible to use CLI with 18F-FDG to image interscapular BAT in mice, with the majority of the signal (>85%) at the interscapular site originating from BAT; 2) The method was reliable because excellent correlations between in vivo CLI, ex vivo CLI, and ex vivo radioactivity were observed; 3) CLI could be used for monitoring BAT activation under different conditions; 4) CLI signals from the group under short-term isoflurane anesthesia were significantly higher than that from the group under long-term anesthesia; 5) The CLI spectrum of 18F-FDG with a peak at 640 nm in BAT after spectral unmixing reflected the actual context of BAT; 6) Finally 3D reconstruction images showed excellent correlation between the source of the light signal and the location and physical shape of BAT. Conclusion: CLI with 18F-FDG is a feasible and reliable method for imaging BAT in mice. Compared to PET imaging, CLI is significantly cheaper, faster for 2D planar imaging and easier to use. We believe that this method could be used as an important tool for researchers investigating BAT.

Colorectal cancer (CRC) is one of the major causes of cancer death worldwide. In general, early diagnosis for CRC and individual therapy have led to better survival for the cancer patients. Accumulating studies concerning biomarkers have provided positive evidence to improve cancer early diagnosis and better therapy. It is, however, still necessary to further investigate the precise biomarkers for cancer early diagnosis and precision therapy and predicting prognosis. In this study, AI-assisted systems with bioinformatics algorithm integrated with microarray and RNA sequencing (RNA-seq) gene expression (GE) data has been approached to predict microRNA (miRNA) biomarkers for early diagnosis of CRC based on the miRNA-messenger RNA (mRNA) interaction network. The relationships between the predicted miRNA biomarkers and other biological components were further analyzed on biological networks. Bayesian meta-analysis of diagnostic test was utilized to verify the diagnostic value of the miRNA candidate biomarkers and the combined multiple biomarkers. Biological function analysis was performed to detect the relationship of candidate miRNA biomarkers and identified biomarkers in pathways. Text mining was used to analyze the relationships of predicted miRNAs and their target genes with 5-fluorouracil (5-FU). Survival analyses were conducted to evaluate the prognostic values of these miRNAs in CRC. According to the number of miRNAs single regulated mRNAs (NSR) and the number of their regulated transcription factor gene percentage (TFP) on the miRNA-mRNA network, there were 12 promising miRNA biomarkers were selected. There were five potential candidate miRNAs (miRNA-186-5p, miRNA-10b-5, miRNA-30e-5p, miRNA-21 and miRNA-30e) were confirmed as CRC diagnostic biomarkers, and two of them (miRNA-21 and miRNA-30e) were previously reported. Furthermore, the combinations of the five candidate miRNAs biomarkers showed better prediction accuracy for CRC early diagnosis than the single miRNA biomarkers. miRNA-10b-5p and miRNA-30e-5p were associated with the 5-FU therapy resistance by targeting the related genes. These miRNAs biomarkers were not statistically associated with CRC prognosis. [ABSTRACT FROM AUTHOR]

In order to find out the most valuable biomarkers and pathways for diagnosis, therapy and prognosis in colorectal cancer (CRC) we have collected the published CRC biomarkers and established a CRC biomarker database (CBD: http://sysbio.suda.edu.cn/CBD/index.html). In this study, we analysed the single and multiple DNA, RNA and protein biomarkers as well as their positions in cancer related pathways and protein-protein interaction (PPI) networks to describe their potential applications in diagnosis, therapy and prognosis. CRC biomarkers were collected from the CBD. The RNA and protein biomarkers were matched to their corresponding DNAs by the miRDB database and the PubMed Gene database, respectively. The PPI networks were used to investigate the relationships between protein biomarkers and further detect the multiple biomarkers. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis and Gene Ontology (GO) annotation were used to analyse biological functions of the biomarkers. AI classification techniques were utilized to further verify the significances of the multiple biomarkers in diagnosis and prognosis for CRC. We showed that a large number of the DNA, RNA and protein biomarkers were associated with the diagnosis, therapy and prognosis in various degrees in the CRC biomarker networks. The CRC biomarkers were closely related to the CRC initiation and progression. Moreover, the biomarkers played critical roles in cellular proliferation, apoptosis and angiogenesis and they were involved in Ras, p53 and PI3K pathways. There were overlaps among the DNA, RNA and protein biomarkers. AI classification verifications showed that the combined multiple protein biomarkers played important roles to accurate early diagnosis and predict outcome for CRC. There were several single and multiple CRC protein biomarkers which were associated with diagnosis, therapy and prognosis in CRC. Further, AI-assisted analysis revealed that multiple biomarkers had potential applications for diagnosis and prognosis in CRC. [ABSTRACT FROM AUTHOR]