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Frontiers in Neuroscience 2023Reduced brain volume, impaired cognition, and possibly a range of psychoneurological disorders have been reported in patients with non-alcoholic fatty liver disease...
BACKGROUND
Reduced brain volume, impaired cognition, and possibly a range of psychoneurological disorders have been reported in patients with non-alcoholic fatty liver disease (NAFLD); however, no underlying cause has been specified. Here, Mendelian randomization (MR) was employed to determine the causative NAFLD effects on cortical structure.
METHODS
We used pooled-level data from FinnGen's published genome-wide association study (GWAS) of NAFLD (1908 cases and 340,591 healthy controls), as well as published GWAS with NAFLD activity score (NAS) and fibrosis stage-associated SNPs as genetic tools, in addition to the Enigma Consortium data from 51,665 patients, were used to assess genetic susceptibility in relation to changes with cortical thickness (TH) and surface area (SA). A main estimate was made by means of inverse variance weighted (IVW), while heterogeneity and pleiotropy were detected using MR-Egger, weighted median, and MR Pleiotropy RESidual Sum and Outlier to perform a two-sample MR analysis.
RESULTS
At the global level, NAFLD reduced SA (beta = -586.72 mm, se = 217.73, = 0.007) and several changes in the cortical structure of the cerebral gyrus were found, with no detectable pleiotropy.
CONCLUSION
NAFLD causally affects cortical structures, which supports the presence of an intricate liver-brain axis.
PubMed: 38260009
DOI: 10.3389/fnins.2023.1305624 -
Arthritis Research & Therapy Nov 2023Prior research has revealed a heightened prevalence of neoplasms in individuals diagnosed with rheumatoid arthritis (RA). The primary objective of this study is to delve...
OBJECTIVE
Prior research has revealed a heightened prevalence of neoplasms in individuals diagnosed with rheumatoid arthritis (RA). The primary objective of this study is to delve into the causal association between RA and two distinct types of neoplasms: benign neoplasm of bone and articular cartilage (BNBAC) and malignant neoplasm of bone and articular cartilage (MNBAC).
METHODS
We employed summary data from genome-wide association analyses (GWAS) to investigate the causal relationship between RA and two neoplasms, BNBAC and MNBAC, using a two-sample bidirectional Mendelian randomization (MR) study design. The IEU OpenGWAS database provided the GWAS summary data for RA, while the Finnish consortium supplied the GWAS summary data for BNBAC and MNBAC. Our analysis involved the utilization of eight distinct MR methods, namely random-effects inverse variance weighted (IVW), MR Egger, weighted median, simple mode, weighted mode, maximum likelihood, penalized weighted median, and fixed effects IVW. Subsequently, we conducted assessments to evaluate heterogeneity, horizontal pleiotropy, outliers, the impact of a single-nucleotide polymorphism (SNP), and adherence to the assumption of normal distribution in the MR analysis.
RESULTS
The results from the MR analysis revealed that there was no significant genetic association between RA and BNBAC (P = 0.427, odds ratio [OR] 95% confidence interval [CI] = 0.971 [0.904-1.044]). However, a positive genetic association was observed between RA and MNBAC (P = 0.001, OR 95% CI = 1.413 [1.144-1.745]). Conducting a reverse MR analysis, we found no evidence to support a genetic causality between BNBAC (P = 0.088, OR 95% CI = 1.041 [0.994-1.091]) or MNBAC (P = 0.168, OR 95% CI = 1.013 [0.995-1.031]) and RA. Our MR analysis demonstrated the absence of heterogeneity, horizontal pleiotropy, and outliers and confirmed that the effect was not driven by a single SNP. Additionally, the data exhibited a normal distribution.
CONCLUSION
The findings of this study demonstrate that RA constitutes a significant risk factor for MNBAC. In the context of clinical application, it is advisable to conduct MNBAC screening in RA patients and remain vigilant regarding its potential manifestation. Importantly, the outcomes of this investigation introduce a fresh vantage point into the understanding of the tumorigenesis associated with RA.
Topics: Humans; Cartilage, Articular; Genome-Wide Association Study; Mendelian Randomization Analysis; Neoplasms; Arthritis, Rheumatoid
PubMed: 37957703
DOI: 10.1186/s13075-023-03205-5 -
Journal of Inflammation (London,... Sep 2023An increasing body of evidence now shows that the long-term mortality of patients with sepsis are associated with various sepsis-related immune cell defects. Alternative...
BACKGROUND
An increasing body of evidence now shows that the long-term mortality of patients with sepsis are associated with various sepsis-related immune cell defects. Alternative splicing (AS), as a sepsis-related immune cell defect, is considered as a potential immunomodulatory therapy target to improve patient outcomes. However, our understanding of the role AS plays in sepsis is currently insufficient.
AIM
This study investigated possible associations between AS and the gene regulatory networks affecting immune cells. We also investigated apoptosis and AS functionality in sepsis pathophysiology.
METHODS
In this study, we assessed publicly available mRNA-seq data that was obtained from the NCBI GEO dataset (GSE154918), which included a healthy group (HLTY), a mild infection group (INF1), asepsis group (Seps), and a septic shock group (Shock). A total of 79 samples (excluding significant outliers) were identified by a poly-A capture method to generate RNA-seq data. The variable splicing events and highly correlated RNA binding protein (RBP) genes in each group were then systematically analyzed.
RESULTS
For the first time, we used systematic RNA-seq analysis of sepsis-related AS and identified 1505 variable AS events that differed significantly (p <= 0.01) across the four groups. In the sepsis group, the genes related to significant AS events, such as, SHISA5 and IFI27, were mostly enriched in the cell apoptosis pathway. Furthermore, we identified differential splicing patterns within each of the four groups. Significant differences in the expression of RNA Binding Protein(RBP) genes were observed between the control group and the sepsis group. RBP gene expression was highly correlated with variant splicing events in sepsis, as determined by co-expression analysis; The expression of DDX24, CBFA2T2, NOP, ILF3, DNMT1, FTO, PPRC1, NOLC1 RBPs were significant reduced in sepsis compared to the healthy group. Finally, we constructed an RBP-AS functional network.
CONCLUSION
Analysis indicated that the RBP-AS functional network serves as a critical post-transcriptional mechanism that regulates the development of sepsis. AS dysregulation is associated with alterations in the regulatory gene expression network that is involved in sepsis. Therefore, the RBP-AS expression network could be useful in refining biomarker predictions in the development of new therapeutic targets for the pathogenesis of sepsis.
PubMed: 37749550
DOI: 10.1186/s12950-023-00355-w -
Entropy (Basel, Switzerland) Aug 2023In the field of image processing, noise represents an unwanted component that can occur during signal acquisition, transmission, and storage. In this paper, we introduce...
In the field of image processing, noise represents an unwanted component that can occur during signal acquisition, transmission, and storage. In this paper, we introduce an efficient method that incorporates redescending M-estimators within the framework of Wiener estimation. The proposed approach effectively suppresses impulsive, additive, and multiplicative noise across varied densities. Our proposed filter operates on both grayscale and color images; it uses local information obtained from the Wiener filter and robust outlier rejection based on Insha and Hampel's tripartite redescending influence functions. The effectiveness of the proposed method is verified through qualitative and quantitative results, using metrics such as PSNR, MAE, and SSIM.
PubMed: 37628207
DOI: 10.3390/e25081176 -
SSM - Population Health Mar 2024BACKGROUNDDue to the long time interval between exposure and outcome, it is difficult to infer the causal relationship between educational attainment (EA) and common...
BACKGROUNDDue to the long time interval between exposure and outcome, it is difficult to infer the causal relationship between educational attainment (EA) and common chronic diseases. Therefore, we utilized Mendelian randomization (MR) to predict the causal relationships of EA with hypertension and type-2 diabetes (T2DM). METHODSA two-sample MR analysis was conducted using genome-wide association studies (GWASs) combined with inferential measurements. A GWAS meta-analysis including 1,131,881 European individuals was used to identify instruments for EA. Hypertension and T2DM data were obtained from a Finnish database. MR analyses were performed using inverse-variance weighted meta-analysis (IVW), weighted median regression, MR‒Egger regression, simple mode regression, weighted mode regression and the MR-Pleiotropy RESidual Sum and Outlier test. Sensitivity analyses were further performed using the leave-one-out method to test the robustness of our findings. RESULTSUsing the MR approach, our results showed that EA was significantly associated with a reduced risk of hypertension (OR = 0.63; P = 2.94 × 10; [95% CI: 0.59, 0.67]) and type-2 diabetes (OR = 0.59; P = 1.25 × 10; [95% CI: 0.52, 0.67]). CONCLUSIONSThis study showed that EA is causally linked to the risk of chronic diseases, including high blood pressure and T2DM.
PubMed: 38283548
DOI: 10.1016/j.ssmph.2023.101585 -
Heliyon Jan 2024This review aimed to harmoniously summarize and compare outlier rates for various cardiac troponin (cTn) assays, including high-sensitivity-cTn (hs-cTn) assays and... (Review)
Review
OBJECTIVES
This review aimed to harmoniously summarize and compare outlier rates for various cardiac troponin (cTn) assays, including high-sensitivity-cTn (hs-cTn) assays and contemporary cTn (generation of assays prior to hs-cTn ones) assays, from the published studies.
METHODS
The PRISMA guidelines were utilized to perform this systematic review. Five databases, including PubMed, Scopus, Embase, Cochrane Library, and Web of Science, were searched using specific keywords up to June 30th, 2023. Studies reporting specifically calculated outlier rates for cTn assays when conducting in-vitro diagnosis in human samples were included. Selected studies were then further assessed using the GRADE tool.
RESULTS
Thirteen studies were included. The data from the studies were summarized statistically in this review. The results showed substantial evidence of improved analytical robustness or reduced respective mean rates of outliers, critical outliers, and analytical outliers for hs-cTn assays (0.14 %, 0.18 %, and 0.18 %) compared to contemporary cTn assays (0.63 %, 0.71 %, and 0.50 %).
CONCLUSION
The findings offer promisingly provide a comprehensive reference for laboratory scientists and clinical staff in choosing the most suitable cTn assay for patient care regrading outlier rates. Besides, this review reveals the advancements of hs-cTn assays with lower outlier rates than contemporary cTn assays. The emerging challenges for continuously improving analytical robustness of cTn assays are also elaborated.
PubMed: 38205298
DOI: 10.1016/j.heliyon.2023.e23788 -
PloS One 2023The long-term protection and restoration of aquatic resources depends on robust monitoring data; data that require systematic quality control and analysis tools. The...
The long-term protection and restoration of aquatic resources depends on robust monitoring data; data that require systematic quality control and analysis tools. The MassWateR R package facilitates quality control, analysis, and data sharing for discrete surface water quality data collected by monitoring programs of various size and technical capacity. The tools were developed to address regional needs for programs in Massachusetts, USA, but the principles and outputs can be applicable to monitoring data collected anywhere. Users can create quality control reports, perform outlier analyses, and assess trends by season, date, and site for more than 40 parameters. Users can also prepare data for submission to the United States Environmental Protection Agency Water Quality Exchange, thus sharing data to the largest water quality database in the United States. The automated and reproducible workflow offered by MassWateR is expected to increase the quantity and quality of publicly available data to support the management of aquatic resources.
Topics: United States; Water Quality; Environmental Monitoring; Databases, Factual; Data Accuracy; Quality Control
PubMed: 37910583
DOI: 10.1371/journal.pone.0293737 -
Indian Journal of Anaesthesia Jan 2024This narrative review explores the evolving role of artificial intelligence (AI) in haemodynamic monitoring, emphasising its potential to revolutionise patient care. The...
This narrative review explores the evolving role of artificial intelligence (AI) in haemodynamic monitoring, emphasising its potential to revolutionise patient care. The historical reliance on invasive procedures for haemodynamic assessments is contrasted with the emerging non-invasive AI-driven approaches that address limitations and risks associated with traditional methods. Developing the hypotension prediction index and introducing CircEWS and CircEWS-lite showcase AI's effectiveness in predicting and managing circulatory failure. The crucial aspects include the balance between AI and healthcare professionals, ethical considerations, and the need for regulatory frameworks. The use of AI in haemodynamic monitoring will keep growing with ongoing research, better technology, and teamwork. As we navigate these advancements, it is crucial to balance AI's power and healthcare professionals' essential role. Clinicians must continue to use their clinical acumen to ensure that patient outliers or system problems do not compromise the treatment of the condition and patient safety.
PubMed: 38406336
DOI: 10.4103/ija.ija_1260_23 -
Journal of Orthopaedic Surgery and... Dec 2023Poor rotation of the femoral component in total knee arthroplasty (TKA) can result in various postoperative complications, underscoring the critical importance of...
Accuracy and reproducibility of two-dimensional computed tomography-based positioning of femoral component rotational alignment in preoperative planning for total knee arthroplasty.
BACKGROUND
Poor rotation of the femoral component in total knee arthroplasty (TKA) can result in various postoperative complications, underscoring the critical importance of preoperative planning.
PURPOSE
To improve the accuracy of femoral component positioning during TKA, this study compared the accuracy and repeatability of different two-dimensional (2D) computed tomography (CT) measurement methods for measuring the posterior condylar angle (PCA) in preoperative TKA planning.
METHODS
A retrospective analysis was conducted on 75 patients (150 knees) who underwent bilateral lower extremity computed tomography angiography (CTA) at Fuyang People's Hospital from January 2021 to July 2021. Three different methods were used to measure the PCA based on 2D CT images (axial CT slices) and three-dimensional(3D) models (femoral models reconstructed from CT data) in this study. Method 1: Single-plane 2D CT measurement, measuring PCA in the most obvious single-plane CT slice of the surgical transepicondylar axis (sTEA); Method 2: multi-plane 2D CT measurement, identifying and locating anatomical landmarks in multiple 2D CT slices and measuring PCA; Method 3: 3D model measurement, measuring PCA in the reconstructed femur 3D model. Compare the differences in PCA measurements between the three measurement methods. A positive PCA measurement was recorded when the sTEA was externally rotated relative to the posterior condylar line (PCL). Any difference exceeding 3° between the PCA measurement in the 2D CT and the PCA reference value in the 3D model was classified as an outlier. The intraclass correlation coefficient (ICC) and Bland-Altman method were utilized to assess the intra- and inter-observer reproducibility of the three measurement methods.
RESULTS
The PCA measurement in the single-plane 2D CT was 1.91 ± 1.94°, with a measurement error of - 1.22 ± 1.32° and 12.7% of outlier values. In the multi-plane 2D CT, the PCA measurement was 2.96 ± 1.68°, with a measurement error of -0.15 ± 0.91° and 6.0% of outlier values. The PCA measurement in the 3D model was 3.12 ± 1.69°. The PCA measurement in single-plane 2D CT was notably smaller than that in multi-plane 2D CT and 3D models, with no significant difference between the latter two. The multi-plane 2D CT showed significantly lower measurement error and outlier values than the single-plane 2D CT. All three PCA measurement methods exhibited high reproducibility (ICC: 0.93 ~ 0.97).
CONCLUSIONS
Using of multi-plane 2D CT for measuring PCA in preoperative planning of TKA has high reproducibility and accuracy, with fewer outlier values. We recommend preoperative measurement of PCA using muti-plane 2D CT to improve the accuracy of positioning the femoral component rotational alignment during surgery.
Topics: Humans; Arthroplasty, Replacement, Knee; Reproducibility of Results; Retrospective Studies; Tomography, X-Ray Computed; Femur; Knee Joint; Osteoarthritis, Knee
PubMed: 38098082
DOI: 10.1186/s13018-023-04466-1 -
Scientific Reports Nov 2023Adverse pregnancy outcomes, such as low birth weight (LBW) and preterm birth (PTB), can have serious consequences for both the mother and infant. Early prediction of...
Adverse pregnancy outcomes, such as low birth weight (LBW) and preterm birth (PTB), can have serious consequences for both the mother and infant. Early prediction of such outcomes is important for their prevention. Previous studies using traditional machine learning (ML) models for predicting PTB and LBW have encountered two important limitations: extreme class imbalance in medical datasets and the inability to account for complex relational structures between entities. To address these limitations, we propose a node embedding-based graph outlier detection algorithm to predict adverse pregnancy outcomes. We developed a knowledge graph using a well-curated representative dataset of the Emirati population and two node embedding algorithms. The graph autoencoder (GAE) was trained by applying a combination of original risk factors and node embedding features. Samples that were difficult to reconstruct at the output of GAE were identified as outliers considered representing PTB and LBW samples. Our experiments using LBW, PTB, and very PTB datasets demonstrated that incorporating node embedding considerably improved performance, achieving a 12% higher AUC-ROC compared to traditional GAE. Our study demonstrates the effectiveness of node embedding and graph outlier detection in improving the prediction performance of adverse pregnancy outcomes in well-curated population datasets.
Topics: Pregnancy; Female; Infant, Newborn; Humans; Pregnancy Outcome; Premature Birth; Infant, Low Birth Weight; Mothers; Risk Factors
PubMed: 37963898
DOI: 10.1038/s41598-023-46726-4