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Frontiers in Oncology 2024Multiple myeloma (MM), a malignant disease of plasma cells originating in the bone marrow, is influenced significantly by genetic factors. Although plasma liposomes have...
BACKGROUND
Multiple myeloma (MM), a malignant disease of plasma cells originating in the bone marrow, is influenced significantly by genetic factors. Although plasma liposomes have been linked to MM, the nature of their potential causal relationship remains to be elucidated. This study aims to explore this relationship using Mendelian randomization (MR) analysis.
METHODS
Liposome-associated genetic instrumental variables (IVs) were identified from plasma lipidomics data of 7,174 Finnish individuals within a Genome-Wide Association Study (GWAS) pooled database. A MM pooled dataset was sourced from a GWAS meta-analysis encompassing 150,797 individuals, including 598 MM patients and 218,194 controls. These IVs underwent MR analysis, adhering to strict criteria for correlation, independence, and the exclusion of confounders. The inverse variance weighted (IVW) method, MR-Egger method, weighted median (WM) method, and simple median were utilized for MR analysis assessment, alongside Cochran's Q test, MR-Egger intercept, MR-Pleiotropy Residual Sum and Outlier (MR-RESSO) method, and leave-one-out analysis for evaluating heterogeneity, multiplicity, and instrumental bias.
RESULTS
The study identified 88 significant, independent single nucleotide polymorphisms (SNPs) as IVs for MR analysis, each with an F-statistic value above 10, indicating robustness against weak instrument bias. IVW analysis revealed associations between six plasma liposome components and MM risk (p < 0.05). Phosphatidylinositol (16:0_18:1) serum levels (odds ratio [OR] = 1.769, 95% confidence interval [CI]: 1.132-2.763, p = 0.012) and triacylglycerol (56:4) levels (p = 0.026, OR = 1.417, 95% CI: 1.042-1.926) were positively correlated with the risk of multiple myeloma development. Phosphatidylethanolamine (18:0_20:4) (p = 0.004, 95% CI: 0.621-0.916, OR = 0.754), phosphatidylcholine (18:2_20:4) (p = 0.004, OR = 0.680, 95% CI: 0.519-0.889), sterol ester (27:1/18:3) levels (p = 0.013, OR = 0.677, 95% CI: 0.498-0.922), and phosphatidylcholine (O-18:2_20:4) levels (OR = 0.710, 95% CI: 0.517-0.913, p = 0.033) were negatively associated with the risk of developing multiple myeloma. The Cochran's Q test did not detect statistical method heterogeneity, nor did the MR-RESSO test or the MR-Egger intercept detect horizontal pleiotropy; leave-one-out analyses confirmed the absence of bias from individual SNPs.
CONCLUSIONS
Our findings suggest a complex relationship between plasma liposome components and MM risk. Elevated serum levels of triacylglycerol and phosphatidylinositol are positively associated with MM risk, while certain phospholipids and sterol esters offer a protective effect. This study provides valuable insights into the clinical relevance of liposomes in the pathology of multiple myeloma.
PubMed: 38933448
DOI: 10.3389/fonc.2024.1404744 -
Frontiers in Microbiology 2024Some recent observational studies have shown that gut microbiota composition is associated with puerperal sepsis (PS) and no causal effect have been attributed to this....
BACKGROUND
Some recent observational studies have shown that gut microbiota composition is associated with puerperal sepsis (PS) and no causal effect have been attributed to this. The aim of this study was to determine a causal association between gut microbiota and PS by using a two-sample Mendelian randomization (MR) analysis.
METHODS
This study performed MR analysis on the publicly accessible genome-wide association study (GWAS) summary level data in order to explore the causal effects between gut microbiota and PS. Gut microbiota GWAS ( = 18,340) were obtained from the MiBioGen study and GWAS-summary-level data for PS were obtained from the UK Biobank (PS, 3,940 cases; controls, 202,267 cases). Identification of single nucleotide polymorphisms associated with each feature were identified based on a significance threshold of < 1.0 × 10. The inverse variance weighted (IVW) parameter was used as the primary method for MR and it was supplemented by other methods. Additionally, a set of sensitivity analytical methods, including the MR-Egger intercept, Mendelian randomized polymorphism residual and outlier, Cochran's Q and the leave-one-out tests were carried out to assess the robustness of our findings.
RESULTS
Our study found 3 species of gut microbiota, , , and to be associated with PS. The IVW method indicated an approximately 19% decreased risk of PS per standard deviation increase with (OR = 0.81; 95% CI 0.66-1.00, = 0.047). A similar trend was also found with (OR = 0.80; 95% CI 0.66-0.97, = 0.024). However, was positively associated with the risk of PS (OR = 1.33, 95% CI: 1.07-1.67, = 0.011).
CONCLUSION
This two-sample MR study firstly found suggestive evidence of beneficial and detrimental causal associations of gut microbiota on the risk of PS. This may provide valuable insights into the pathogenesis of microbiota-mediated PS and potential strategies for its prevention and treatment.
PubMed: 38933024
DOI: 10.3389/fmicb.2024.1407324 -
Sensors (Basel, Switzerland) Jun 2024A complete framework of predicting the attributes of sea clutter under different operational conditions, specified by wind speed, wind direction, grazing angle, and...
A complete framework of predicting the attributes of sea clutter under different operational conditions, specified by wind speed, wind direction, grazing angle, and polarization, is proposed for the first time. This framework is composed of empirical spectra to characterize sea-surface profiles under different wind speeds, the Monte Carlo method to generate realizations of sea-surface profiles, the physical-optics method to compute the normalized radar cross-sections (NRCSs) from individual sea-surface realizations, and regression of NRCS data (sea clutter) with an empirical probability density function (PDF) characterized by a few statistical parameters. JONSWAP and Hwang ocean-wave spectra are adopted to generate realizations of sea-surface profiles at low and high wind speeds, respectively. The probability density functions of NRCSs are regressed with K and Weibull distributions, each characterized by two parameters. The probability density functions in the outlier regions of weak and strong signals are regressed with a power-law distribution, each characterized by an index. The statistical parameters and power-law indices of the K and Weibull distributions are derived for the first time under different operational conditions. The study reveals succinct information of sea clutter that can be used to improve the radar performance in a wide variety of complicated ocean environments. The proposed framework can be used as a reference or guidelines for designing future measurement tasks to enhance the existing empirical models on ocean-wave spectra, normalized radar cross-sections, and so on.
PubMed: 38931504
DOI: 10.3390/s24123720 -
Micromachines Jun 2024The electromagnetic eddy current non-destructive testing system enables the non-destructive analysis of surface defect information on tested materials. Based on the...
The electromagnetic eddy current non-destructive testing system enables the non-destructive analysis of surface defect information on tested materials. Based on the principles of eddy current detection, this paper presents a digital eddy current detection method using high-speed sampling based on STM32. A differential eddy current coil is used as the detection probe, and the combination of a differential bridge and a differential amplifier circuit helps to reduce common-mode noise interference. The detection signal is collected via an STM32-based acquisition circuit and transmitted to the host computer through Ethernet for digital demodulation processing. The host computer performs operations such as smoothing averaging, sinusoidal fitting, and outlier removal to extract the amplitude and phase of the detection signal. The system also visually displays the condition of the tested object's surface in real time through graphical visualization. Testing showed that this system can operate at frequencies up to 8.84 MHz and clearly identify defects as narrow as 1 mm on the surface of the tested steel plate.
PubMed: 38930745
DOI: 10.3390/mi15060775 -
Medicina (Kaunas, Lithuania) Jun 2024: To assess femoral shaft bowing (FSB) in coronal and sagittal planes and introduce the clinical implications of total knee arthroplasty (TKA) by analyzing a...
: To assess femoral shaft bowing (FSB) in coronal and sagittal planes and introduce the clinical implications of total knee arthroplasty (TKA) by analyzing a three-dimensional (3D) model with virtual implantation of the femoral component. : Sixty-eight patients (average age: 69.1 years) underwent 3D model reconstruction of medullary canals using computed tomography (CT) data imported into Mimics software (version 21.0). A mechanical axis (MA) line was drawn from the midportion of the femoral head to the center of the intercondylar notch. Proximal/distal straight centerlines (length, 60 mm; diameter, 1 mm) were placed in the medullary canal's center. Acute angles between these centerlines were measured to assess lateral and anterior bowing. The acute angle between the distal centerline and MA line was measured for distal coronal and sagittal alignment in both anteroposterior (AP) and lateral views. The diameter of curve (DOC) along the posterior border of the medulla was measured. : The mean lateral bowing in the AP view was 3.71°, and the mean anterior bowing in the lateral view was 11.82°. The average DOC of the medullary canal was 1501.68 mm. The average distal coronal alignment of all femurs was 6.40°, while the distal sagittal alignment was 2.66°. Overall, 22 femurs had coronal bowing, 42 had sagittal bowing, and 15 had both. : In Asian populations, FSB can occur in coronal, sagittal, or both planes. Increased anterolateral FSB may lead to cortical abutment in the sagittal plane, despite limited space in the coronal plane. During TKA, distal coronal alignment guides the distal femoral valgus cut angle, whereas distal sagittal alignment aids in predicting femoral component positioning to avoid anterior notching. However, osteotomies along the anterior cortical bone intended to prevent notching may result in outliers due to differences between the distal sagittal alignment and the distal anterior cortical axis.
Topics: Humans; Arthroplasty, Replacement, Knee; Aged; Female; Male; Femur; Imaging, Three-Dimensional; Middle Aged; Tomography, X-Ray Computed; Aged, 80 and over
PubMed: 38929603
DOI: 10.3390/medicina60060986 -
Bioengineering (Basel, Switzerland) Jun 2024Motion capture (MoCap) technology, essential for biomechanics and motion analysis, faces challenges from data loss due to occlusions and technical issues. Traditional...
Motion capture (MoCap) technology, essential for biomechanics and motion analysis, faces challenges from data loss due to occlusions and technical issues. Traditional recovery methods, based on inter-marker relationships or independent marker treatment, have limitations. This study introduces a novel U-net-inspired bi-directional long short-term memory (U-Bi-LSTM) autoencoder-based technique for recovering missing MoCap data across multi-camera setups. Leveraging multi-camera and triangulated 3D data, this method employs a sophisticated U-shaped deep learning structure with an adaptive Huber regression layer, enhancing outlier robustness and minimizing reconstruction errors, proving particularly beneficial for long-term data loss scenarios. Our approach surpasses traditional piecewise cubic spline and state-of-the-art sparse low rank methods, demonstrating statistically significant improvements in reconstruction error across various gap lengths and numbers. This research not only advances the technical capabilities of MoCap systems but also enriches the analytical tools available for biomechanical research, offering new possibilities for enhancing athletic performance, optimizing rehabilitation protocols, and developing personalized treatment plans based on precise biomechanical data.
PubMed: 38927796
DOI: 10.3390/bioengineering11060560 -
Genes Jun 2024Recent research has highlighted associations between sleep and microbial taxa and pathways. However, the causal effect of these associations remains unknown. To...
Recent research has highlighted associations between sleep and microbial taxa and pathways. However, the causal effect of these associations remains unknown. To investigate this, we performed a bidirectional two-sample Mendelian randomization (MR) analysis using summary statistics of genome-wide association studies (GWAS) from 412 gut microbiome traits (N = 7738) and GWAS studies from seven sleep-associated traits (N = 345,552 to 386,577). We employed multiple MR methods to assess causality, with Inverse Variance Weighted (IVW) as the primary method, alongside a Bonferroni correction (( < 2.4 × 10) to determine significant causal associations. We further applied Cochran's Q statistical analysis, MR-Egger intercept, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) for heterogeneity and pleiotropy assessment. IVW estimates revealed 79 potential causal effects of microbial taxa and pathways on sleep-related traits and 45 inverse causal relationships, with over half related to pathways, emphasizing their significance. The results revealed two significant causal associations: genetically determined relative abundance of pentose phosphate decreased sleep duration ( = 9.00 × 10), and genetically determined increase in fatty acid level increased the ease of getting up in the morning ( = 8.06 × 10). Sensitivity analyses, including heterogeneity and pleiotropy tests, as well as a leave-one-out analysis of single nucleotide polymorphisms, confirmed the robustness of these relationships. This study explores the potential causal relationships between sleep and microbial taxa and pathways, offering novel insights into their complex interplay.
Topics: Humans; Mendelian Randomization Analysis; Gastrointestinal Microbiome; Genome-Wide Association Study; Sleep; Polymorphism, Single Nucleotide; Causality
PubMed: 38927705
DOI: 10.3390/genes15060769 -
Genes Jun 2024Uterine pathologies pose a challenge to women's health on a global scale. Despite extensive research, the causes and origin of some of these common disorders are not... (Comparative Study)
Comparative Study
Uterine pathologies pose a challenge to women's health on a global scale. Despite extensive research, the causes and origin of some of these common disorders are not well defined yet. This study presents a comprehensive analysis of transcriptome data from diverse datasets encompassing relevant uterine pathologies such as endometriosis, endometrial cancer and uterine leiomyomas. Leveraging the Comparative Analysis of Shapley values (CASh) technique, we demonstrate its efficacy in improving the outcomes of the classical differential expression analysis on transcriptomic data derived from microarray experiments. CASh integrates the microarray game algorithm with Bootstrap resampling, offering a robust statistical framework to mitigate the impact of potential outliers in the expression data. Our findings unveil novel insights into the molecular signatures underlying these gynecological disorders, highlighting CASh as a valuable tool for enhancing the precision of transcriptomics analyses in complex biological contexts. This research contributes to a deeper understanding of gene expression patterns and potential biomarkers associated with these pathologies, offering implications for future diagnostic and therapeutic strategies.
Topics: Female; Humans; Transcriptome; Endometriosis; Leiomyoma; Gene Expression Profiling; Endometrial Neoplasms; Uterine Neoplasms; Uterine Diseases; Algorithms
PubMed: 38927658
DOI: 10.3390/genes15060723 -
Aging Jun 2024Iridocyclitis and the use of glucocorticoid medication have been widely studied as susceptibility factors for cataracts. However, the causal relationship between them...
Iridocyclitis and the use of glucocorticoid medication have been widely studied as susceptibility factors for cataracts. However, the causal relationship between them remains unclear. This study aimed to investigate the causal relationship between the development of iridocyclitis and the genetic liability of glucocorticoid medication use on the risk of senile cataracts occurrence by performing Two-sample Mendelian randomization (MR) analyses. Instrumental variables (IVs) significantly associated with exposure factors (P < 5 × 10) were identified using published genome-wide association data from the FinnGen database and UK Biobank. Reliability analyses were conducted using five approaches, including inverse-variance weighted (IVW), MR-Egger regression, simple median, weighted median, and weighted mode. A sensitivity analysis using the leave-one-out method was also performed. Genetic susceptibility to glucocorticoid use was associated with an increased risk of developing senile cataracts (OR, 1.10; 95% CI, 1.02-1.17; P < 0.05). Moreover, iridocyclitis was significantly associated with a higher risk of developing senile cataracts (OR, 1.03; 95% CI, 1.01-1.05; P < 0.05). Nonetheless, some heterogeneity in the IVs was observed, but the MR results remained consistent after penalizing for outliers. The estimates were consistent in multivariate analyses by adjusting for body mass index (BMI) and diabetes mellitus type 2 (T2DM). This study provides new insights into the prevention and management of senile cataracts by highlighting the increased risk associated with iridocyclitis and the use of glucocorticoids.
PubMed: 38925660
DOI: 10.18632/aging.205963 -
Journal of Imaging May 2024Hyperspectral images include information from a wide range of spectral bands deemed valuable for computer vision applications in various domains such as agriculture,...
Hyperspectral images include information from a wide range of spectral bands deemed valuable for computer vision applications in various domains such as agriculture, surveillance, and reconnaissance. Anomaly detection in hyperspectral images has proven to be a crucial component of change and abnormality identification, enabling improved decision-making across various applications. These abnormalities/anomalies can be detected using background estimation techniques that do not require the prior knowledge of outliers. However, each hyperspectral anomaly detection (HS-AD) algorithm models the background differently. These different assumptions may fail to consider all the background constraints in various scenarios. We have developed a new approach called Greedy Ensemble Anomaly Detection (GE-AD) to address this shortcoming. It includes a greedy search algorithm to systematically determine the suitable base models from HS-AD algorithms and hyperspectral unmixing for the first stage of a stacking ensemble and employs a supervised classifier in the second stage of a stacking ensemble. It helps researchers with limited knowledge of the suitability of the HS-AD algorithms for the application scenarios to select the best methods automatically. Our evaluation shows that the proposed method achieves a higher average F1-macro score with statistical significance compared to the other individual methods used in the ensemble. This is validated on multiple datasets, including the Airport-Beach-Urban (ABU) dataset, the San Diego dataset, the Salinas dataset, the Hydice Urban dataset, and the Arizona dataset. The evaluation using the airport scenes from the ABU dataset shows that GE-AD achieves a 14.97% higher average F1-macro score than our previous method (HUE-AD), at least 17.19% higher than the individual methods used in the ensemble, and at least 28.53% higher than the other state-of-the-art ensemble anomaly detection algorithms. As using the combination of greedy algorithm and stacking ensemble to automatically select suitable base models and associated weights have not been widely explored in hyperspectral anomaly detection, we believe that our work will expand the knowledge in this research area and contribute to the wider application of this approach.
PubMed: 38921608
DOI: 10.3390/jimaging10060131